Biology 103 Lab 2002 Forum


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Survey of Unknown Planet
Name: Heather Pr
Date: 2002-09-10 14:59:57
Link to this Comment: 2589

On the planet PSB we found 35 different species of plants. We classified them into the following four catagories: trees; weeds; mosses/lichens/grasses; bushes/shrubs. Our naming system was primarily based on leaf shape, size, color and texture as we related them to species of plants on Earth.

The planet PSB had 20 different types of weed. All were green in color, and few had flowers, so the main criterion for categorization was leaf shape and size. A few species include the jagged-edge clover weed, the fat fuzzy weed, and the Minnesota weed which we felt was reminiscent of the wheat fields of the state.

In the tree category, we only found two species. The star tree was characterized by large, star-like leaves. As opposed to the spikey tree which had longer, spikier leaves.

On the surface of PSB, we found a vast array grasses, lichen and moss. There was soft moss and hairy moss, which generally covered the base of trees. Only one form of lichen was found, but the dead banana lichen proved to be most interesting. However, further study was inhibited by lack of funding. The grasses proved to be most difficult in its classification because of the various types. There were three particular types of grass-voluptuous, tall and shaggy- which were closly related and could belong to the same genius.

Finally the bushes and shrubs included blooming, spikey berry, spoon, and crew. We differentiated between them based on leaf shape. For instance, the blooming shrub has small bright green leaves and the spoon bush has dark, spoon-shaped leaves. We also encountered a dead bush that with further analysis could be identified.

Though this first encounter proved successfull in finding life on another planet, further study is required to fully understand the complexity and the actual relationship between plants on both planet PSB and planet Earth.



Name:
Date: 2002-09-10 15:00:46
Link to this Comment: 2590

above group: Christine Traversi, Katie Campbell, and Heather Price


exploration of new planet
Name:
Date: 2002-09-10 15:04:05
Link to this Comment: 2592

Explorers: Elizabeth Damore, Sarah Tan, Brenda Zera

24 plants were discovered. They were placed into the following categories: bushes, trees, grasses, small plants and ground covers.

Bushes: 3 types. All bushes have the following traits: they stem from one root (branching off close to the ground), have green leaves, and are able to grow in the shade.

Bush #1: Fuzzy leaves growing in clusters of 9+ leaves. Big leaves at the bottom, newer growth towards the center of the cluster.

Bush #2: Waxy, short needles. Small red berries and immature dark green berries.

Bush #3: Small, oval shaped waxy leaves. Many per branch.

Also found: dead shrub, uncertain which variety.


Trees: 2 types. All trees have green leaves and have a trunk growing from a single root. Ground cover #1 (see below) growing near base and on trunk. Root system partially exposed. About 40 feet tall.

Tree #1: smooth bark with disruptions. Multiple leaves per stem growing out of branches. Spikey nuts (seeds) fall from tree. 

Tree #2: Star shaped green leaves. Rough bark.


Grasses: 3 types. Both are green and long. Stay close to the ground.

grass #1: thin individual leaves.

grass #2: thicker reed-like leaves with sharp edges.

grass #3: dark green, thicker than grasses 1 or 2.


Small plants: 13 types. All have green leaves with distinct shapes. Grow no higher than 2 feet.

s.p. #1: green, flat spikey leaves.

s.p. #2: medium sized green leaves, on single stem.

s.p. #3: dark green, two leaves on a single stalk.

s.p. #4: tiny green leaves and small yellow flowers (5 petals). All clustered on a single fuzzy stalk.

s.p. #5: smooth green leaves.

s.p. #6: serated green leaves (5 per stalk).

s.p. #7: small green leaves on single stalk with flower cluster (yellow) at top.

s.p. #8: flat leaves with green seed stalk growing out of center.

s.p. #9: huge, broad leaves. Grows straight from the ground. Diameter of about 3 feet.

s.p. #10: green leaves with white splotches (disease?)

s.p. #11: bright green leafy clusters, short to ground, concentrated in one area.

s.p. #12: tiny dark green plant with small leaves. White spots. 3 leaves per stalk.

s.p. #13: enormous dark green leaves, red stems.


Ground Cover: 2 kinds.

g.c. #1: soft, easily removed, green/brown in color, individual growths in a large group. Grows in shade.

g.c. #2: green leaves on a long, vining red stem.

The plants evolved close to the ground because there is not enough sunlight in the area to let them grow higher. The trees are higher because they're older - they cause the shade that stunts the other plants' growth. Keep the competition down!

Where there's no shade, the plants are smaller because they are new growth - haven't reached their full height yet? Need funding to investigate this further.


Lab #1 Tuesday, 9.10.02
Name: Kyla Ellis
Date: 2002-09-10 15:04:38
Link to this Comment: 2593

Margaret Hoyt, Kyla Ellis, Kate Amlin.

Background:
Due to all prior knowledge, we hold that life exists when any or all of the following occur in an organism:
* dependent on energy
* highly impobable / organized
* bounded

Introduction:
Drs Hoyt, Ellis and Amlin landed on a previously uncharted, undiscovered, and unnamed planet on the 10th of Spetember at 1.30pm Atlantic Earth time. We hereby claim the right to name said planet, (as defined in the Eplorer's Law) which we shall exercise at a later date and time.

Upon arrival, we encountered certain organisms which, in conjuction with our background knowledge, we deem to be, in fact, living. These organisms were dependent on a source of light and heat similar to our Sun. Organisms which were not touched by this source of light and heat lost energy and died. (They became brittle, changed color, fell to our feet and became, in fact, lifeless.) They therefore show evidence of a life-span. Each organism exhibited a complementary structure that extended underground. The larger organisms showed major evidence of waste products. We also found evidence of growth with different sizes of the same-looking organism. For these reasons, we consider that all these organisms are living.

Observations:
We classified the organisms into three classes according to size:

CLASS A) Shorter than two feet tall.
1) All one floppy, pliable piece of organism. Moves with any type of force (wind, etc.)
2) Identifiable stem, but still bendable. Also move with slightest force.
3) Very small. Inter-connected growth-system. Seemingly dependent on class C.

GENERAL OBSERVATIONS FOR CLASS A: The largest class -- covers the most area.
Most variable types of organisms. Basically all the same shade of green. Least permanant -- most easily displaced. Least amount of waste. Each organism has one long stalk. No branches. Stems/stalks are very thin. Color

CLASS B) 2 ft to 8 ft tall.
1) Broad, single leaves. Many veins in leaves. Branches are most spread-out. Tends to be shorter than others in class. Leaves appear in clusters.
2)Sword-type leaf. Small leaves in abundance. Numerous leaves. Spherical red berry-like growth attached to random branches.
3) Circular, shiny, broad leaves. Leaves appear in pairs on stem. Thicker leaves.

GENDERAL OBSERVATIONS FOR CLASS B: Leaves on branches were arranged in some kind of pattern.
More complex branch pattern than Class A.
All branches made up plant -- as opposed to one trunk with many branches.
Lots of evidence of waste.
Branches were brittle, less pliable than in Class A.
Definitive underside of leaf.

CLASS C) Over 8 ft.
Appeared to have distinctions in leaf and stem. But adequate study was not performed due to time and monetary constraits. The most promising of the three classes, we all agree that this Class is worthy of further investigation.

GENERAL OBSERVATIONS FOR CLASS C:
Flat, broad leaves with veins.
Thick, stocky trunk.
Not easily displaced, very attached in its environment.

CONCLUSION:
We conclude that the organisms were living. Yet the only way to unquestionably discover if this is "true" would be to further study the said planet with observations over time.


Astronauts
Name: Yarimee, J
Date: 2002-09-10 15:05:35
Link to this Comment: 2595

Joanna Robertson
Yarimee Gutierrez
Jen Rusk
Lab Report 09/10/02
"Astronauts on the Remote Planet"

Description of life forms in the "remote planet"...
I.Short organisms (.5 inches- 1 ft.)
a. dry/weathered/brown/crispy/yellow/thin/fragile/weak
b. under tall organisms- less sunlight; less energy?

II. Medium organism (4 ft.to 7ft.)
a. "shrub-like" organisms; thicker leaf, but shorter than short organisms...start to develop closer to the ground;
b. Even though they're in the same conditions, one is completely dried out while the others are green and flourishing
c. located under tall organisms which implies they get less sunlight due to shaded areas

III. Tall Organisms (15ft. -25ft.)
a. greener than all other organisms because they have the most direct access to the sunlight?
b. different "leaf" shapes implies different types of trees live on this planet


Questions??

1. What energy sources do these organisms depend on to survive?

2. Why are some short organisms greener than the rest? Is it because of sunlight or location?

3. Does it rain? Snow? Do these organisms depend on anything other than sunlight?

4. Fact: The greener short organisms "soil" is moist, while the drier short organisms are dry. Does this contribute to the outcome?


survey of unknown planet nte
Name:
Date: 2002-09-10 15:07:54
Link to this Comment: 2596

Number of plant species determined:27

Tools we used to differentiate plant species: We used organizational structure to determine different plant species desptite different stages in development. For example leaf patterns, veins, size, etc..in combination these categories allowed us to determine different species. The following plants are what our team discovered on the unkown planet:

Grasses: pre-requisites for classification: Slim leaves, parallel veins, smooth edges.

Grass 1: Bluish-green color, 7-8in tall, smooth, grows abundantly in shaded areas, in the far corner.

Grass 2: Yellow-green color, shoots of leaves come out of the stalk, 12-18 in tall, had a seed puff growing out the top, with long hairs and fuzzy seeds.

Grass 3: Green, short leaves growing out of the stalk, leaves were pointed, 6-7in tall, seed pod at the top.

Grass 4: Green, 3-6 in, no visible seeds, individual leaves growing straight out of the ground, didn't grow well without sunlight.

Weeds: pre-requisites for classification: Found intermittedly among other plans species, leaves seemed to grow from focal point beneath the ground.

Weed 1: Jagged leaves, flower growing in middle. 6in.

Weed 2: 1 ft tall, hairs on the leaves, leaves little and round, seeds in pods on top.

Weed 3: 7in tall, sparse rounded leaves.

Ferns: we only have one

Fern 1: light yellow green, clustered leaves, 8 in, low to the ground.

possible food sources: Plants that bore fruit, possibly edible.

Bush 1: 7ft, branches coming from one root, leaves on tips of every branch, bore small red berries.

Plant 1: Heart shaped leaves, small red berries with seeds on outside, low to the ground.

Clover 1: small to ground yellow flowers, 3 leaves on stem, shaded,

Bushes:
Bush 2: 6ft, waxy rounded leaves.
Bush 3: 6ft, light green clustered leaves.

Trees:
Tree 1: 3 stories tall, rounded leaves bark peeling
tree2: 2.5 stories tall, light green 5 pt leaves, produces a spikey ball shaped nut.

Fungus 1: jagged and porous mint green, grows on bark.
Fungus 2: orabge bumps, looks like melted wax.
Fungus 3: tubular, white yellow color, 3 cm. tall.
Fungus 4: white dispersed throughout the bark, when in crevases displays underside, which has a fan shape.
Fungus 5: white with yellowish top, fan shaped.
Fungus 6: spongy moss at the bass of Tree 1 small green leaves.

unkown1: greenish pink color, in young plants large plants had a solid green color,
Unknown2: tiered, 4 petaled flowers, bursts of 5-6 leaves.
Unknown 3: 1ft tall located near bush 2.
unknown 4: jagged leaves growing out of the grate.

Mom plants are large specimens of weeds:
Mom 1:2 feet across, low to ground, veined leaves,
Mom2: bubbly leaves, shiny looking, leaves heart shaped.
Mande Maclay, Tegan Georges, Diana Fernadez


planet exploration
Name: virginia &
Date: 2002-09-10 15:08:03
Link to this Comment: 2597

virginia culler, mary beth curtiss, laura silvius

our trip to the subject planet was informative, but there remains much research to be done. our general summary of observations is
as follows:
we divided the obvious plant life into three basic categories, based on size, shape/form, and similarity to plnat forms on earth:

1) plants resembling earth trees (tall, rigid, with a hard bark-covered trunk like stem, and branches ending in leaves): 2+ different
species

we considered the two "trees" we found to be different species because, while they were similar in size and general tree-like
attributes, they had different leaf forms, different branch patterns and different trunk characteristics ("bark" texture and color, size,
ratio to rest of tree)

2) bushes/shrubs: 5+ since these plants seemed to be of a size in between that of the "trees" and the ground cover plants, we
decided to call them "bushes" due to their similarities with earth bushes. these plants were all roughly 3-6 feet tall, with branches
that ended in leaves an/or needles. these were of varying shapes and sizes and textures and colors, but they all shared the
characteristic of being smaller than those of the trees. Some bushes were found to bear fruit or seed-like "pods", as was one of hte
trees, whereas nothing of that form was found on ground cover plants upon our brief inspection. However, this could be much
better determined by more extensive research. We came up with three possible hypotheses explaining the size of hte shrubs: a) they
are a different category of plants from the trees and ground cover, b) they are trees whose growth is not yet complete, or c) they are
trees whose growth has been stunted by being shaded from light by the (seemingly) fully developed trees.

3) ground cover plants: 31+ these came in all shapes and sizes, from under two centimeters up to more than 30, and everthing in
between. their stems were more flexible and soft than those of hte trees and shrubs, and they seemed to lack the protective "bark"
layer for the most part. the exception to this were some small plans with similar leaves to one of hte trees, and our hypothesis is that
this could possibly be a "sapling" or some sort of very early "tree" growth. within the category of "ground cover" we discoverd
what we believe to be two sub-categories, one being "moss" and the other "fungi", based on their similarities to the earth organisms
by those names. the "fungi" seemed to only be growing on what we believe to be teh dead remains of a "tree," which lead us to
believe that they may be some sort of parasite, possibly the cause of the "tree"'s death. Another hypothesis is that the seemingly
dead tree died because it was completely shaded by light from both the tree branches above it and a large hunk of what appeared to
be shale rock. another interesting characteristic of the ground cover is taht we were able to determine that, at least amongst the
plants that we sampled, there is an obvious root structure underlying hte soil while the part above is green and of a different texture.
this lead us to believe that these plants possibly recieve some sort of chemical from the sunlight that affects their coloring, similar to
plants on earth. we were unable to verify this finding with the trees and shrubs, as the plants were too big for any excavation under
such a short research period, but with a more extended deadline and budget we would be able to further investigate this topic. what
we were able to verify was that the trees seem to have a broad underground root system as well, which we concluded after
observing roots partially protruding from the ground surrounding the tree which had similar "bark" patterns, leading us to believe
that they were part of the same plant. also, the bushes and trees did display the same generally green coloring as the ground cover.

specific examples:

-there was one seemingly dead bush, which had no leaves and whose branches were dry, brown and brittle both inside and out
upon inspection, whereas the other bushes had branches whose insides were somewhat moist and green.

-there was a big patch of ground cover which appeared different from the rest, and which seemed to be in cooler, moister soil
overall. at hte time of our inspection the area was completely covered by shadow, and with further research we would be able to
determine if this were a different climate which would affect the plant's progress. also, as the patch of this different vegetation was
rather large, wiht all the plants growing densely together, we could assume that they do in fact reproduce and were spreading.
however, few plants and VERY few ground cover plants bore any evidence of fruits, seeds, or any other reproductive method
resembling those of earth plants. however, we have no way to know if this is simply because htese plants reproduce on some sort of
larger cycle, which we would be able to determine wiht more extensive research and more time for the project.

-on the ground on nearly all of hte site, particularly near the "trees", we observed leaves which appeared to be from said trees and
which were both brown and yellow in coloring, and appeared to be either dead or dying. the brown ones were of a brittle, easily
broken texture, whereas the yellow retained some of the rubbery, plastic categories of the green tree leaves.


survey of unknown planet
Name:
Date: 2002-09-10 15:09:12
Link to this Comment: 2599

23 plant species found. We keyed the different species out using the key below.
A23 plant species found. We keyed the different species out using the key below.:

A. One foot and below
I. <3 inches
a. light green
1.1/16 " stalks
a) leaves
1) spade shape
i) jagged contour
ii) smooth contour
2) oval shape
i) jagged contour
ii) smooth contour
3) rectangle shape
b) no leaves
2.1/8" stalks
a) leaves
1)spade shape
i) jagged contour
iii) smooth contour
2)oval shape
i)jagged contour
ii)smooth contour
3) rectangle shape
b) no leaves

b. dark green
1.1/16 " stalks
a)alternating leaves
1)spade shape
i)jagged contour
ii)smooth contour
2)oval shape
i)jagged contour
ii)smooth contour
3) rectangle shape
b) leaves symmetrical from stalk
c) no leaves
2.1/8" stalks
a)leaves
1)spade shape
i) jagged contour
ii)smooth contour
2)oval shape
i)jagged contour
ii)smooth contour
3) rectangle shape
b) no leaves


c. green/brown
II. < 6 inches (See above key)
III. < 9 inches (See above key)
IV. < 12 inches (See above key)

B. Between one and 10 feet
1. less than 1 " oval leaves
2. cylindrical leaves
3. large circular leaves
C. Between Above 10 feet

* ground cover and community of plant species noted for observational purposes. The possible takeover of portion of planet hospitable by humans is a large concern. Further rescources would allow for further research
Sarah Frayne and Kathryn Bailey


plant findings
Name:
Date: 2002-09-11 14:49:07
Link to this Comment: 2613

Lawral "Lo" Wornek, Joanna "Ja Rule" Ferguson, Melissa "Eminem" Brown, Roma "R-Dawg" Hassan

On Planet PSB we discovered many plants. We separated them into the following categories:

tree, small plants, grasses, mosses, shrubs, large plants.

we defined these with our accepted definitons from earth. a small plant was something under a foot or so tall, and a large plant was something larger than that. grass was short but widespread; moss was close to the ground and didn't have easily definable leaves. shrubs were short and fat trees that grew out rather than up; they also didn't have trunks. trees had trunks! they grew up rather than out.

we found 28 different specimens.

some examples of each:

we found 17 different varieties of small plants.
one example is a chive-like plant, which smells and looks exactly like a chive. interesting. what would darwin say about this? it is thin and long, no leaves, and feels like it is hollow. it has a pungent aroma.

another example is a flowering leafy small plant. the leaves are thin and grow directly off the stem. they have a grainy texture. at the top there are buds for flowers. the flowers will be yellow.

we found two different varieties of trees

both were tall; one had wider leaves than the other. the one with wide leaves had forked leaves and spikey balls that were attached to the leaf clusters. the bark was more course than the other tree. the tree with the slender leaves (which were also in clusters) had bark that was smoother and flakey.

we found four different varieties of grass

one example has flat leaves that are very thin and long. it divides at the top into more than one leaf. the leaves have grooves. they are cupped with a definitive point at the bottom of the cup. (like a piece of paper folded).

we found three different varieties of shrub

one example had waxy rounded leaves (they look like fake nails) that grew in clusters. the shrub was about six feet tall and about as wide. the stems were hard to break off. it was similar to a beach umbrella. the leaves were dark in color.

another example had small dark green leaves that grew in circular clusters around the stem. the shrub had small red berries with a large seed. the shrub had the appearance of an evergreen.

we found one variety of a large plant. it looked like a rhubarb plant. we smelled the stem but found no smells similar to the rhubarb; this could be because of its young age, or because it is not a rhubarb. the leaf is fuzzy and has a spade shape. it is deep green. the stem is a reddish color. the veins are very defined. the leaf is about the size of a normal human's face and can be larger.

we found one variety of moss. it grew close to the ground, was fuzzy to the touch, and very very dark green. forest green, actually. in places it was yellow in appearance but we concluded it was the same type of moss due to its appearance apart from color.

we have concluded that the environment on Planet PSB is very similar to that on Earth. the plants seem to resemble almost exactly those found on earth. one could say one was on earth. funny, that.


Plants on New Planet
Name: Chelsea R.
Date: 2002-09-11 14:49:59
Link to this Comment: 2614

In our survey of the new planet (aptly named"COURTYARD") we discovered what we believe to be 43 different types of plants, loosely classified as types of bushes, grasses or trees:
Bushes:
1)bush with small, red berries
2)shiny-leaved bush
3)not-so-shiny-leaved bush
4)bush now appearing dead, but likely formerly alive (difficult to give further identifying features b/c it is no longer alive)
5)red-branched bush (top, along with all leaves, appears to have been cut off)
Grassses/Low-ground plants:
1)thin grass
2)thick grass
3)thicker grass
4)tall skinny grass
5)traditional clover
6)spiky-leaved clover
7)mini-lily-pad-shaped plant
8)fuzzy, big-leaved plant
9)taller moss
10)non-fuzzy, big-leaved plant
11)wheat-like plant
12)plant with heart-shaped leaves
13)super-skinny, limp grass
14)oval-leaved plant
15)poison-ivy-like plant
16)plant with small, yellow flowers
17)plant with small, dot-like, white flowers
18)plant with small, diamond-shaped leaves
19)mini-bamboo-like grass
20)plant with larger-petaled, yellow flowers
21)pointed-leaved plant
22)spiky-leaved plant
22)plant with red flowers
23)plant with mushroom-shaped leaves
24)lighter-colored moss
25)tall, rope-like grass
26)dandelion
27)spotted clover
28)purple-leaved plant
29)plant with small, but not dot-like, white flowers
30)large-leaved plant
31)giant-leaved plant
32)fern-like plant
33)plant with larger, white flowers
34)red-stemmed plant
Trees:
1)star-shaped-leaves tree (maple-like)
2)oval-leaved tree
3)wide-leaved sapling


Plant Lab Report
Name: Emily Sene
Date: 2002-09-11 14:50:50
Link to this Comment: 2615

1. High, large woody plant with thick stem and multiple branches. Soft 5-pointed green leaves and rough bark.
2. High, large woody plant with thick stem and multiple branches. Individual tear-drop green leaves and smooth bark.
3. short, greenish-bown ground-covering carpet.
4. Medium height, thin green pointed stalks that grow in clumps.
5. Small woody stemmed plant with large pale green leaves. The leaves had three prominent points at the top and two smaller ones on the sides.
6. Small woody stemmed plant with serrated oval leaves.
7. Medium height, green stalks with alternating side oval leaves.
8. Leafy green plant with reddish stalk leading into oval green leaves.
9. Short, round woody plant with multiple stems. At the end of the stems are tiny needle-like leaves. Small round hard green berry-like structures. On a different speciman of this plant, the berry-like structures had become covered in a red fruit that emits juice when squeezed.
10. Short, round woody plant with multiple stems and many small oval glossy leaves at the tips.
11. Medium height green plan with alternating branches and smooth, fat oval leaves in pairs along the branches.
12. Medium height green stalks that grow in clums, slightly thicker, darker, and glossier than the stems of similar plants.
13. Small, brown, woody plant with no leaves, possibly dead.
14. Short, wide, woody brown plant with oddly flat top. No leaves, rough bark. Seems to be the host of another white, flat, smooth organism.
15. Small green plant with large oval leaves growing off of a small thin stalk.
16. Small reddish-green plant with three heart-shaped leaves at the top of each stem. On another speciman of this plan there were tiny bell-shaped yellow flowers with five petals.
17. Small vertically growing plant with thin, green oval leaves growing off of one main stalk.
18.Low, green ground-covering plant with three round leaves at the tip of each stem.
19. Small vertically growing plant with few small leaves growing from one rough stalk.
20. Short plant with red stalk and opposite oval green leaves.
21. Medium sized plant with thin stalk and three to six long pointy green leaves growing from stalk.
22. Medium height plant with a green stalk and alternating branches. Littler branches grow off of main branches, each branch ends in a pointy, serrated, oval leaf.
23. Medium sized low growing plant with short, thick stalk and long, thick floppy oval leaves.
24. Low, leafy, green plant, leaves are long and oval with little pointy prickly tips all along the sides.
25.Low plant with multiple, large dark green leaves low to the ground. One stalk rising from the middle with many seed-like structures covering the outside of this stalk.


Plant life on PSB
Name:
Date: 2002-09-11 14:51:04
Link to this Comment: 2616

Diana DiMuro, Erin Myers, Brie Farley

We found 32 species of plant life on the planet. They ranged in size from tiny to huge and spanned ground, mid, and high levels of growth. We distinguished the plant species by color, shape, size, texture, and location. All plants were green unless otherwise noted.

The following are the species we determined
#1 -- mid level bush with shiny, fuzzy, green, almond-shaped leaves, remnants of flowers.
#2 -- high level tree with 5-6 pointed, star-like, green leaves, on outstretched branches.
#3 -- ground level thin bladed grass
#4 -- ground level thick bladed grass
#5 -- ground level heart-shaped grean leaves
#6 -- ground level long, green, pointed leaves
#7 -- mid level tiny, shiny, smooth, green leafed bush
#8 -- mid level red berry producing thin, green, spikey needled bush
#9 -- ground level tall yellow-green medium width blade grass
#10-- ground level spikey moss
#11-- ground level soft fern-like spikey green leaves
#12-- ground level fuzzy spikey- edged prickley weed-like leaves.
#13-- high level flaking bark green, tear-dropped shaped, smooth leaves, branches growing straight up tree. Had spikey pods on ground.
#14-- mid level smooth, velvety green leaves, sappling/shrub.
#15 -- 3-leafed in shade, green ground covering.
#16 -- Discolored green/brown "eaten Looking" plant, sappling or shrub.
#17 -- ground level, small yellow flowers on clover-like tiny round leaves growing in groups of three.
#18 -- tall wide bladed grass with centers of long fuzzy "wheat" like flowers.
#19 --almond shaped weed like leaves ground level.
#20 -- fuzzy leafy geranium shaped leaves ground level.
#21 -- non-fuzzy spikey weed-like leaves layered and grow out of center.
#22 -- scalloped leaves with buds red and brown stem, green leaves.
#23 -- tall stemmed long weed like spikey flowered plant.
#24 -- tiny bunched up layered leaves with fuzzy new leaves at center.
#25 -- light green tiny scalloped layered leaves growing to med ground level with flowered plant and white speckles on leaves.
#26 -- Super shiny giant spikey edged green leaves with red stalks. Ground level.
#27 -- Huge green thick stalked ruffled edged leaves at ground level.
#28 -- Huge red-stalked scalloped and ruffled heart shaped green leaves, floppy, hang over to ground from stems.
#29 -- Parsley looking clustered bunched leaves.
#30 -- Symmetrical light green with a lighter greenish-white pattern on leaves, flat fern-looking ground level.
#31 -- Vine like leaves grow in circular pattern around stalk.
#32 -- Five leaves clustered with scalloped edges red around edges.


Bio 103 Lab #1
Name:
Date: 2002-09-11 14:55:42
Link to this Comment: 2617

Will Carroll, Michele Doughty, Diana La Femina

In order to count the number of plants, we observed and noted specific characteristics that differentiated and distinguished them. The following is our observations:

1. Really thin (gossamer) grass-like plant, yellowish.
2. Thin grass-like plant, green
3. Thicker grass-like plant, green
4. Broad leaf grass-like plant, green, very close to ground in clusters
5. Spiny grass-like plant, green
6. Tall, thin grass with alternate thicker blades at 90 degree angles
7. Small clovers with round leaves, green, very close to ground
8. Large clovers, green
9. Small plant with three spikey, green, tear-drop shaped leaves all at the top of the stem of the same plant
10. Small plant with four spikey, green, tear-drop shaped leaves with red spots, all at the stem of the same plant
11. Small plant with five spikey, green, tear drop shaped leaves all at the stem of the same plant
12. Cluster of broad, spikey leaves with deep cuts into the sides, close to the ground with basically no stem
13. Flowering very thin leaved and stalked with whorled leaves. Flowers were small, whitish and ball-like
14. Small, fern-like, double compounded plant
15.Moss, flat on the ground, with a dark base but small, green-tipped spongey tecture
16. Tree with star-shaped leaves
17. Tree with tear-drop shaped leaves
18. Six inch tall plant with a thick, red-striped stalk, alternate branches and two small leaves at the base of a really big leaf
19. Spade shaped small, single-leaved plant, lighter green in color
20. Five-point leaf with two small points at the base of three more pronounced points
21. Tear drop shaped, lopsided leavesm, three on a cluster on each stalk
22. Seven foot bush with thin needles at the end of branches, very small base but branches spawl
23. Six foot bush with small, round, waxy leaves and red berries
24. Similar to six foot bush in shape but leaves were longer and broader and no berries or wax coating. There were small bunches of leaves.



Name:
Date: 2002-09-11 15:21:46
Link to this Comment: 2625

Mer
Chels
Heidi
Margot

Questionables (molds and fungi that are either animal or plant)

- Moss (2)
soft spikes growing on the bark of trees
fern like, on ground between plants with star blooms

- Fungus (3)
blue fungus growing on trees, sprawling out from a central place
striped mushroom in shades of brown and white
yellow that sprouted like a mushroom on stump

Grasses (10)

Crab Grass
Club-shaped, leaved ivy
Prairie Grass
Wheat Grass
Long, thin grass, dark green, growing parallel to ground
Standard short grass, more yellow (lack of water?), 2-3 inches
Clovers (4)

Three-leaved
Four-leaved
14 round points
Speckeled leaves

Plants (15)

Strawberry-like plants, red berries
Mutant Collard Greens (2)

Green Stems, thin leaves
Purple Stems, wide leaves

Marigold-like, non-blooming plants
Dandilions (4)

Spiked leaves
Low, fuzzy
Rounded
Fern-like, centralized, low to ground

Small plants(7)

Vertical (5)

Spiked, enlongated leaves, with red base
Minature pussywillow, long stem, with white bloom
Lower leaves purple, upper leaves green (of medium size)
Violets
Mushroom-shaped leaves

Horizontal (2)

Red stem, small round green leaves, glossed
Thin, green Ivy with small staggered leaves

Trees and Bushes (5)

Maple tree
Silvery-green leaves, pointy
Pine bush with red berries
Larger leaves, thin, yellowy green
Small, hard, glossy dark-green leaves


categorization of plants
Name: Diana & A
Date: 2002-09-17 14:35:53
Link to this Comment: 2722

1.green stalk
A: Jagged leaf edges
a.stalked plants b.ground plants
B: smooth leaf edges
a. round leaf (s) b.single point c. multi pointed

2. Brown stalk
A: < 10 ft
a. needles b.soft leaves bb1.rounded bb2. pointed
B:>10ft
a:single point b:multi point

3.No stalk
A:green
a. spongy leaf b.no leaves/hard
B:other(color, or "Grobstein" category)
a. flat aa1:bumpy aa2:smooth/close to surface
b. protruding bb1:disc shape bb2:tubular shape

Amanda Maclay Diana Fernandez


Planet Courtyard Key
Name:
Date: 2002-09-17 14:39:59
Link to this Comment: 2723

UNIDENTIFIED PLANTS

A. Tree Like
1A. Tall (8' and taller)
1A'. Jagged leaves (papery bark)
1A". Five lobe leaves (regular bark)

2A. Smaller (8' and smaller)
2A'. needles with berries
2A". leafy
2A"1. Alive
2A"1'. Lt green leaves (not waxy)
2A"1". dk green leaves (waxy)
2A"2. Dead

B. Un-tree Like
1B. Ground Cover
1B'. Leafy
1B'1. Stringy
1B'2. Vuluptuos
1B'3. Shag
1B'4. Crab Grass
1B'5. Tall
1B". "Mossy"
1B"1. Moss
1B"1'. Soft
1B"1". Hairy
1B"2. Lichen

2B. Individual Plants
2B'. Leafy
2B". Flowery
2B"1. Red-vein crawling
2B"2. Tall flowering
2B"3. Yellow flowering
2B"3. Oreo
2B"4. Squash
2b"5. Pumpkin
2B"6. Red Berry
2B'1. More than one stem
2B'2. Single-stemed
2B'1'. Clusters
2B'1'1. Lilly pad
2B'1'2. Jagged-edge clover
2B'1'3. Clover
2B'1". Not clustered
2B'1"1. Smooth leaves
2B'1"2. Jagged leaves
2B'1"3. Spunky fern
2B'1"4. Fat fuzzy
2B'1"5. Long fuzzy

Stephanie Lane, Katie Campbell, Kate Amilin


lab report II
Name: Joanna, Ya
Date: 2002-09-17 14:43:37
Link to this Comment: 2724

Joanna Robertson
Yarimee Gutierrez
Jennifer Rusk
September 17, 2002
CC: PLANET BACKYARD

****************************PLANT LIFE*********************************

I. PLANTS

A. soft texture

1. moss (close to ground)
2. skinny leaf/Linear
3. thick leaf


B. thin/hard texture and leaves

1. leafy branches/ Even Pinnate
2. few leaves/ Biternate
3. single leaves/YEW(needle foliage leaf)

C. single thick/hard trunk and leaves

1. Orbicular
2. Palmately Lobed


II. FUNGI

A. Black

1. round/cap/ Pilius
2. Oyster

B. Tan

1. Fan-shaped Pilius

C. White

1. Fan- shaped Pilius

D. Lite Beige

1. Mushroom


Planet Courtyard - Voyage #2
Name: virginia l
Date: 2002-09-17 14:45:27
Link to this Comment: 2725

Virginia Culler, Laura Silvius, MaryBeth Curtiss Plantlife on Planet Courtyard
I. Hard Brown Stemmed Plants
---A. Single Central Stem
------1. Elongated pointy leaves
---------a. "Pointy Leaf Tree"
------2. Spikey Leaves
---------a. "Star Leaf Tree"
---B. Ground-level Branching Stems
------1. Small Rounded Leaves
---------a. Small Waxy Dark Green Leaves
------------i. "Waxy Bush"
---------b. Small Matte Light Green Leaves
------------i. "Furry Leaf Bush"
------2. Needles
---------a. "Needle Bush"
II. Soft, Green Stem or No Stem
---A. Soft Green Stem
------1. Overall Green
---------a. Elongated Leaves
------------i. Stemmed Grasses
---------------aa. "String Bean Grass
---------------bb. "Fuzzy Top Grass"
---------b. Short Leaves
---------------aa. Under 2 inches
------------------i) "Mini Spikey Maple Leaves"
------------------ii) "Clover-like Leaves"
------------------iii) "Stiffer Crack Plants"
---------------bb. Above 2 Inches
------------------i) "Big Dock"
------------------ii) "Big Thistle"
------2. Other Colors
---------a. "Yellow Flower"
---B. No Stem
------1. Stemless Leaf Plants
---------a. Leafy
------------i. Multi-leaf
---------------aa. "Crack Plant"
---------------bb. "Teardrop Plant"
------------ii. Single Leaf
---------------aa. "Round Dock"
---------------bb. "Spikey"
---------------cc. "Heartshaped"
---------b. Grass -like
------------i. "Skinny Grass"
------------ii. "Fat Grass"
------2. Blanketing Plants
---------a. Defined Parts
------------i. Mold-like
---------------aa. "Tree Mold"
------------ii. Moss-like
---------------aa. Dark Green
------------------i) "Regular Dark Green"
------------------ii) "Spikey Dark Green"
---------------bb. Light Green
------------------i) "Regular Light Green
------------iii. Lichen-like
---------------aa. "Orange Lichen-like"
---------------bb. "Green Lichen-like"
---------b. Undefined Parts
---------------aa. "Rock Stain Growth"
------3. Fungus-like Plants
---------a. "Puffy White Growth"


back to planet PSB
Name:
Date: 2002-09-17 14:46:42
Link to this Comment: 2726

Heather Price, Chistine Traversi, Margot Rhyu

We noticed that the biggest difference between the plants is the support system, which then determines the size, shape, and foliage of the plants. We wanted to find the least complex way of organizing all of the differences. We didn't classify and specifically name all of the plant life here, we are just presenting the basic outline of how the organization.

Support System

I. Brittle

A. Trees
1. horizontal branches
2. vertical branches

B. Bushes
1. Needles
2. Contoured
a.Round tip
b. Pointy tip

II. Non-Brittle

A. Mosses
1. Soft spike
2. Fern like

B. Grasses
1. Bladed
a. Long and skinny
b. Long and flat
c. Short and skinny
2. Non-Bladed
a. Clover
-3 leaves
-4 leaves
-14 leaves

C. Small Plants
1. Leaves from root
2. Leaves from stalk


Planet Courtyard Key
Name:
Date: 2002-09-17 14:46:50
Link to this Comment: 2727

Elizabeth Damore, Sarah Tan, and Brenda Zera


PLANTS

1.0) Single Stalk 2.0) Mult. Stalk 3.0) No Stalk
(single root) (single root) (sngl. or mult.)

1.1 - Branches
1.1.1 - smooth bark (oval leaves - tree#1)
1.1.2 - rough bark (star shaped leaves - tree#2)

1.2 - No Branches (weeds)
1.2.1 - Flowers
1.2.1 A - clover-like flowers (s.p.#12)
1.2.1 B - small plant with yellow flowers (s.p.#7)
1.2.2 - No Flowers
1.2.2 A - big spotted leaves (s.p. #10)
1.2.2 B - dk. green multiple solid leaves (s.p. #3)
1.2.2 C - dk. green single solid leaves (s.p. #2)

2.1 - Branches
2.1.1 - Needles (bush #2)
2.1.2 - Leaves
2.1.2 A - fuzzy leaves (bush #1)
2.1.2 B - waxy leaves (bush #3)
2.2 - No Branches
2.2.1 - weed with small yellow flowers (s.p. #4)

3.1 - Ground Covers
3.1.1 - Vine (g.c. #2)
3.1.2 - Moss (g.c. #1)
3.2 - Leaves straight from Root
3.2.1 - Skinny (grasses)
3.2.1 A - flat leafed grass (grass #2)
3.2.1 B - thin leafed grass (grass #1)
3.2.1 C - Fine grass (grass #4 - new!)
3.2.1 D - Chive (grass #3)
3.2.2 - Wide Leaves
3.2.2 A - Horizontal growth
3.2.2 A' - large leaves with seed stalk (s.p. #8)
3.2.2 A'' - huge plant (s.p. #13)
3.2.2 A''' - big plant leaves (s.p. #9)
3.2.2 A'''' - dandylion (s.p. #11)
3.2.2 B - Vertical Growth
3.2.2 B' - spikey plant (s.p. #1)
3.2.2 B'' - white spot plant (s.p. #5)
3.2.2 B''' - serated leaf plant (s.p. #14 - new!)


plant key
Name: sarah fray
Date: 2002-09-17 14:49:25
Link to this Comment: 2728

I Trunk (s)
---A single trunk from ground
-----1 cordate leaves
-----2 pinnatified leaves
---B multiple trunks from ground
-----1 spear shaped leaves
-----2 oval shaped leaves
-------a leaves whorled at end of stalk
-------b leaves alternate up the stalk

II No Trunks
---A no leaves
-----1 green
-----2 brown
---B leaves
-----1 linear leaves
-------
-----2 non linear leaves
-------a cordate
-------b jagged
-------c straight
-------d pinnatifid


Lab 2
Name: Kyla And M
Date: 2002-09-17 14:49:29
Link to this Comment: 2729

Kyla Ellis
Margaret Hoyt

1. Is it a plant? Yes? Go to 2.
2. Is it dificult to uproot? ...Yes: go to 3
............................No: go to 11
3. Is it majorly difficult to uproot? ...Yes: go to 4
......................................No: go to 7
4. Difficult to uproot......Has deep ridges on trunk?....Yes, go to 5
......Has smooth trunk with easy- peelable bark?...Yes, go to 6
5. Has 5-point leaf? CLASS C SUB 1
6. Has one-point leaf? CLASS C SUB 2
7. Do branches grow straight up?...Yes: go to 8
................................No: go to 10
8. Are leaves blade-like?.......Yes: go to 9
9. Does plant have red berries?.....Yes: CLASS B SUB 1
10. Has glossy leaves?....Yes: CLASS B SUB 2
.....................No: CLASS B SUB 3
11. Does it have blades? Yes: go to 12
.....................No: go to 17
12. Does it have a stalk? Yes: go to 13
..........................No: go to 16
13. Is stalk thick or thin? Thick: go to 14
.............................THin: go to 15
14: Does plant have a bud-like growth? Yes: CLASS A SUB 1
........................................No: CLASS A SUB 2
15. Does it have broad leaves? Yes: CLASS A SUB 3
..................thin leaves? Yes: CLASS A SUB 4
16. Does it have broad leaves? Yes: CLASS A SUB 5
..................Single blades? Yes: CLASS A SUB 6
17. Does it have a Stalk? Yes: go to 18
..........................No: go to 19
18. Does it have a flower? Yes: CLASS A SUB 7
............................No: CLASS A SUB 8
19. Does it have spiky leaves? Yes: CLASS A SUB 9
...............................No: go to 20
20. Are leaves elliptical in shape? Yes: CLASS A SUB 10
....................................No: CLASS A SUB 11


Classifications
Name: Adrienne,
Date: 2002-09-18 14:03:01
Link to this Comment: 2747

Classifications for Plant-Life:
We found 4 main groups; trees, shrubs, plants, and grasses. The characteristics we used to differentiate between individual species were the same for all four categories.
They are...
Leaf shape, size, texture, color, and location
Stem height, thickness, texture, strength, and color
Fruit size, shape, color, taste, and texture
Seed size, shape, color, and texture
Branch location, number, direction, and size
Flower size, shape, color, texture, and scent
Root location, shape, and size

PLANTS
I. Woody
A. Trees
...1. branches
......-location
......-shape
......-size
......-texture
...2. leaves
......-shape
......-color
......-size
......-texture
......-location
...3. Fruit/Flower/Seed
......-color
......-texture
......-taste/smell
......-size
......-shape
...4. Root
......-location
......-shape
......-size
......-depth
...5. Trunk
......-texture
......-thickness
......-strength
......-color
......-height
B. Shrubs

II. Non-Woody
**see Woody Plants**
A. Plants
B. Grasses

Maggie, Emily, Laura B., Adrienne


planet psb revisited
Name:
Date: 2002-09-18 14:04:59
Link to this Comment: 2748

Joanna "Leonardo" Ferguson, Lawral "Donatello" Wornek, Roma "Raphael" Hassan, Melissa "Michaelangelo" Brown: the teenage mutant ninja botanists!!!


on planet PSB the diversity was broken down into woody and non-woody.

1. woody plants : as the definitions below state, trees and shrubs are both woody plants. they are differentiated by height and where the branches start. we have them in the same category due to their woody stems.
...A) tree: a woody plant at least 5 metres high, with a main axis the lower part of which is usually unbranched.
...B) shrub: a woody plant less than 5 metres high, either without a distinct main axis, or with branches persisting on the main axis almost to its base.
(definitions found at http://www.b-and-t-world-seeds.com/k-o.htm#karyoevolution)


2. non-woody plants : these plants did not have a well-defined support system. they did not have woody stems.
...A) stems : these plants did have stems, but they were not woody; they were soft and fleshy. the stems were green or reddish in color.
.......a) large plants : the large plants were over one foot tall.
.......b) small plants : the small plants were under one foot tall.
............1) flowering
............2) non-flowering
...B) no stems : these plants did not have stems that were readily discernable. these plants grew close to the ground and in clusters. the clusters also grew close together, so it was hard to distinguish them from one another.
.......a) mosses : the mosses looked like a plant carpeting the ground. it was a consistent dark green color with yellow discolorations. the leaves are not distinct from each other. mosses grow along the ground, spreading out rather than growing vertically.
.......b) grasses : the grasses, although they do not have stems, were one continuous plant. the leaves had vein and were vertical and thin.
............1) flowering
............2) non-flowering


Classifications
Name: Mer, Chels
Date: 2002-09-18 14:13:23
Link to this Comment: 2749

Chelsea Phillips
Heidi Adler-Michaelson
Mer Stoll


I. Plants

------A. No Bark

--------------1. Flowering plants

------------------a. Leaf distinctions (color, shape, size etc.)

------------------b. Stalks (color, thickness - realizing that age of the plant is an influence)

--------------2. Fronds - Non flowering plants (no visible buds and no evidence of sprouting)

------------------a. Generic Grasses (in referenece to earth's many and diverse grasses)

------------------b. Tall Grasses (over 7 inches tall)

------------------c. Stalked Plants (differentiated by leaf shape, color, patterns, etc)

--------------3. Mosses

------B. Bark

---------------1. Bushes

-------------------a. Texture of bark

-------------------b. Leaf shape, color, size, texture, etc.

-------------------c. Berries

---------------2. Trees

-------------------a. Growth Pattern

-------------------b. Leaves

-------------------c. Bark

II. Fungi


A Return to the Planet of Pretty Plants, Intern in
Name: Carrie, La
Date: 2002-09-18 14:14:05
Link to this Comment: 2750


This is our intern, Tegan.

Thanks to the aide of our trusty intern, we were able to conduct a more in-depth investigation of the plant life we encountered.
We broke down our former categories into sub-categories. As you may recall, we had four main categories of documented plantlife: mosses, grasses, shrubs, and trees. (see here for previous report)
Come, let us proceed from last week's exploration. Our more detailed categories are as follows:
    Mosses
      - Mixed Moss: This moss is mixed colors and is moist to the touch. There are white and green tendrils that reach across the area of the moss.       - Green Moss: This moss is a deep green, and dried-out at the edges.
    Grasses
      - "Common" Grass: This grass is also referred by homemakers as a "lawn" or "front yard." It is about an inch to an inch and a half in length, and the color is a dark green. A single vein runs down the center of the blade. It has a very simple structure, with only one part (the blade.)
      - "Marsh" Grass: This grass is longer and thicker than "Common" Grass. (If you take a blade between your fingers, pull it taut, and blow, it sounds really cool. Like a horn.) We tasted it; it is not recommended for human consumption. Like "Common" Grass, there is a single vein running down the center, and the blade comes to a point at the top (the bottom is thicker than the top).
      - Three-Sectioned Grasses: This can be classified as a grass, but is not built with the same "blade" structure as the two categories above. Instead, the blade ends in a tri-segmented leaf. The height of this kind of grass is comparable to that of "Common" Grass, and sometimes shorter.
    Shrubs
      - Leafy: This type of shrub is identifiable by its small, round leaves which grow densely over the thin branches. The branches on this kind of shrub grow more upward than outward.
      - Evergreen: This kind of shrub has flat needle-like leaves and small red berries (not good to eat!). The branches grow more outward than upward, making this type of shrub not as tall as the Leafy shrub.
    Trees
      - "Basic" Tree: This kind of tree has a trunk that goes all the way up with branches coming off the sides of it at varying angles. The leaves on this tree have three prongs, and a number of "veins" separating the leaf in subsections.
      - "Complex" Tree: The trunk of this kind of tree divides into branches that grow more upward than outward. The leaves have only one section (prong-less), but still have veins running across them. The trunk is thicker than that of the "Basic" Tree.



Name: Anne, Bobb
Date: 2002-09-18 14:18:31
Link to this Comment: 2751

Plants with Height:
A). small plants--Small
A plant growing in a community which covers substantial ground space. Height of each individual plant is greater than its width. Exhibits vertical growth. Roots and weak and unstable (easily torn from ground). A malleable organism that takes the shape of its environment.

B). Trees--Large
A single vertical growing plant that branches out as height increases. It grows independently. Has one main stem which is grounded by stable roots. Height is normally greater than width. Able to sustain secondary growth (leaves). Branches begin growing outward at mid trunk.

C). Bushes--Medium
A plant having a width greater than (or close in length to) height. Branches begin growing outward at base of trunk. Branches contain many smaller leaves.

Plant with minimal height (in comparison with other groups found on planet)
D). Moss:
A ground plant with relatively no height. Grows ouward, over a surface area. Spft texture.

Surface Growing Plants
A) flat (1)
B) bushy (2)

Within the small plants:
A) grasses-a plant that grows in an individual strand
B) weeds--a small plant that has a stem which is the base for other growth such as leaves, buds, or flowers.

Small Plants
A) grasses- 1) thin i) long, thin, green waxy clusters (1)
2) thick i) leaf like one stem branches out (2)

B) weeds- 1) seeds i) loose seeds (12)
ii) grouped soft seeds (13)
2) cloved i) ridged leaves (6)
ii) smooth leaves (7)
3) vine-like i) tall (5)
ii) stuck to ground (11)
4) wide leafed i) tall (9)
ii) close to ground (3)
iii) spiky leafed (15)
iv) lettuce like leaves (17)
v) spotted (14)
5) flowered i) one stem with multiple flowers (8)
ii) with oval leaves (19)
iii) one flower (10)
6) buds i) long and stubbly (4)

Medium Plants
A) Bushes- 1) non leafed (4)
2) leafed i) needle-like (2)
ii) oval shaped a) large (1)
b) small (3)

Big Plants
A) Trees- 1) rough bark (1)
2) smooth bark (2)


Classifying Plants
Name:
Date: 2002-09-18 14:24:51
Link to this Comment: 2752

Will Carroll, Michele Doughty, Diana La Femina

IF:
A. Plant has continuous root system:
---a.If plant has clover-shaped leaves.
----------1.Small clovers with round leaves, green, very close to ground
----------2.Large clovers, green

---b.If plants have individual blades:
----------1.Thick blades
--------------------i. Thicker grass plant, green
--------------------ii. Broad leaf grass plant, green, very close to ground in clusters
--------------------iii. Spiny grass plant, green
---------------------iv..Cluster of broad, spikey leaves with deep cuts into the sides, close to the ground with basically no stem

----------2. Thin blades
--------------------i. Really thin (gossamer) grass plant, yellowish
--------------------ii. Thin grass plant, green
--------------------iii. Tall, thin grass with alternate thicker blades at 90 degree angles

B. If plants have individual roots:
--a. If plant has soft exterior
----1. Spikey leaves
----------i. Small plant with three spikey, green, tear-drop shaped leaves all at the top of the stem of the same plant
----------ii. Small plant with four spikey, green, tear-drop shaped leaves with red spots, all at the stem of the same plant
----------iii. Small plant with five spikey, green, tear drop shaped leaves all at the stem of the same plant

----2. Tear-drop shaped leaves
----------i.Compound leaves
----------------Small, fern-like, double compounded plant
----------ii. non-compound leaves
----------------* non-flowering
----------------------Tear drop shaped, lopsided leavesm, three on a cluster on each stalk
----------------------Six inch tall plant with a thick, red-striped stalk, alternate branches and two small leaves at the base of a really big leaf
---------------* Flowering
----------------------very thin leaved and stalked with whorled leaves. Flowers were small, whitish and ball-like

----3. Spade shaped leaves
---------i. spade shaped small, single-leaved plant, lighter green in color

--b. If plants have hard exterior (bark)
----1. branches originate at base of plant
--------i. needles
-------------Seven foot bush with thin needles at the end of branches, very small base but branches spawl
--------ii. leaves
----------waxy leaves
--------------Six foot bush with small, round, waxy leaves and red berries
----------non-waxy leaves
--------------similar to six foot bush in shape but leaves were longer and broader and no berries or wax coating. There were small bunches of leaves.

----2. branches originate above the base
--------i. star shaped leaves
--------------Tree with star-shaped leaves
--------ii. tear shaped leaves
--------------Tree with tear-drop shaped leaves

C. Un/Classified
----1. Moss, flat on the ground, with a dark base but small, green-tipped spongey tecture
----2. Appears to be a small tree, but did not know how to classify it until it matures to full size- Five-point leaf with two small points at the base of three more pronounced points


Classification
Name:
Date: 2002-09-18 14:34:19
Link to this Comment: 2753

Erin Myers, Diana DiMuro, and Brie Farley

This classification should be used only on Planet Courtyard. It is created from our discoveries.

  • II. Non-Woody
    • A. Brittle Stalk
      • 1. Red Stalk
        • a. Heart shaped leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
        • b. Almond shaped leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
        • c. Feathered leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
        • d. Scalloped leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
      • 2. White Stalk
        • a. Heart shaped leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
        • b. Almond shaped leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
        • c. Feathered leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
        • d. Scalloped leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
      • 3. Green Stalk
        • a. Heart shaped leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
        • b. Almond shaped leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
        • c. Feathered leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
        • d. Scalloped leaves
          • i. smooth
          • ii.spiny
          • iii.fuzzy
    • B. Flexible Stem
      • 1. Parallel Veins
        • a. wide blade
        • b. narrow blade
      • 2. Branching Veins
        • a. Heart
        • b. Almond
        • c. Feather
        • d. Scalloped

  • cells
    Name: TEGAN, AMA
    Date: 2002-09-24 14:47:34
    Link to this Comment: 2873

    Hypothosis: In more complex multi cellular organisms there are wider variances in cell size within the organism.

    Observations:

    Fungi:uniform cells, 10.4 Micrometers in diameter, slightly oblong shape.
    Small leaf: Jigsaw membrane: 39Micrometers, Stomatal: 26 Micrometers.
    Large Leaf:Jigsaw membrane, Stomatal: 23.4 Micrometers
    Earthworm: Non uniform cells: 13-15.6 Micrometers.
    Human cartilage: Non Uniform: 10.4-13.0 Micrometers

    Conclusion: We did not find a sepcific corrolation between size of organism and size of cell. We did however find that there was more variance in cell size the more complex the multi cellular organism.

    Diana Fernandez, Amanda Maclay, Tegan Georges


    Ginny, Maggie, Kyla
    Name:
    Date: 2002-09-24 14:56:42
    Link to this Comment: 2874

    Kyla Ellis, Maggie Hoyt, Ginny Culler
    Question: Is cell-makeup the thing that makes things unique? Do different cells define class? Do all plants have the same kinds of cells? Do all berries? All animals?

    Hypothesis: We think that diferent types of organisms have different types of cells.

    Data:
    Fungi cells: Long and stringy like spagetti, but not arranged in a cohesive pattern
    Berry Cells: slightly elliptical with solid nuclei, kinda like fried eggs
    Leaf Cells: circular, with jagged edges
    Grass Cells: Rectangular/elliptical
    Hair Cells: Long, stringy, ("hair-like" hehe...) cells that fit together in a set pattern
    Eyelash Cells: Had similar structure as the hair, but had a deep, dark core that was continuous except for at the two ends. The edges had ragedy edges and the core was smooth
    Earthworm Cells: Different shaped-sized cells, indicating different pars of the worm's body.
    Human cartilagde: Elliptical roundish shape with possible nucleus inside.

    Conclusion:
    Yes, different organisms have different cells. Not only that, but diffrent parts of the organism are made up of different cells. Identification of a species/plant/organisms can be traced down to the most basic form, i.e., the cell. Because each organism's cells are so destinctive, identification can be based on those cells alone. This is cause for futher study.


    Cell Sizes
    Name:
    Date: 2002-09-24 14:58:30
    Link to this Comment: 2875

    Kate Amlin
    Katie Campbell
    Stephanie Lane

    In beginning to compare the size of cells with the size of their organism and then with each other, we hypothesized that the size of a cell would correspond with the kingdom of its organism. Therefore we predicted animal cells would be the largest whereas plant cells would be smaller. (In this stdy, we did not compare all five kingdoms, but just Animals and Plants.)

    We looked at seven cells from a variety of sources such as a Paramecium, human thyroid, PSB courtyard planet bush, buttercup, and earthworms.

    The following is our recorded observations of their size.

    PSB courtyard planet bush
    Organism sixe: 2.6 m approximately
    Cell size: 26 micrometers

    Paramecium
    Organism size: +/- .5 milimeters
    Cell size: 156 micrometers by 36.4 micrometers

    Human thyroid
    Organism size: 2-2.5 m approximately
    Cell size: 85.8 micrometers

    Blade of Grass
    Organism Size: 114 mm approximately
    Cell Sizes: 18.2 - 57.2 micrometers

    Earthworm
    Organism Size: 74 mm approximately
    Cell Sizes: 10.4 - 182.0 micrometers

    Buttercup Stem
    Organism Size: 115 cm approximately
    Cell Sizes: 15.6-26 micrometers

    Corn Stalk
    Organism Size: 3 m
    Cell Sizes: 208-1040 micrometers

    We were wrong (#5421 this week). Organisms don't just have one cell size but many different cells. The sizes aren't consistant within the organisms themselves, nor the different kingdoms. If we could look into this further, we might discover and define certain types of cells and find their size and how they correlate and compare that way.


    Cell Sizes
    Name:
    Date: 2002-09-24 14:58:47
    Link to this Comment: 2876

    Kate Amlin
    Katie Campbell
    Stephanie Lane

    In beginning to compare the size of cells with the size of their organism and then with each other, we hypothesized that the size of a cell would correspond with the kingdom of its organism. Therefore we predicted animal cells would be the largest whereas plant cells would be smaller. (In this stdy, we did not compare all five kingdoms, but just Animals and Plants.)

    We looked at seven cells from a variety of sources such as a Paramecium, human thyroid, PSB courtyard planet bush, buttercup, and earthworms.

    The following is our recorded observations of their size.

    PSB courtyard planet bush
    Organism sixe: 2.6 m approximately
    Cell size: 26 micrometers

    Paramecium
    Organism size: +/- .5 milimeters
    Cell size: 156 micrometers by 36.4 micrometers

    Human thyroid
    Organism size: 2-2.5 m approximately
    Cell size: 85.8 micrometers

    Blade of Grass
    Organism Size: 114 mm approximately
    Cell Sizes: 18.2 - 57.2 micrometers

    Earthworm
    Organism Size: 74 mm approximately
    Cell Sizes: 10.4 - 182.0 micrometers

    Buttercup Stem
    Organism Size: 115 cm approximately
    Cell Sizes: 15.6-26 micrometers

    Corn Stalk
    Organism Size: 3 m
    Cell Sizes: 208-1040 micrometers

    We were wrong (#5421 this week). Organisms don't just have one cell size but many different cells. The sizes aren't consistant within the organisms themselves, nor the different kingdoms. If we could look into this further, we might discover and define certain types of cells and find their size and how they correlate and compare that way.


    Cell Sizes
    Name: Katie, Kat
    Date: 2002-09-24 14:59:46
    Link to this Comment: 2877

    Kate Amlin
    Katie Campbell
    Stephanie Lane

    In beginning to compare the size of cells with the size of their organism and then with each other, we hypothesized that the size of a cell would correspond with the kingdom of its organism. Therefore we predicted animal cells would be the largest whereas plant cells would be smaller. (In this stdy, we did not compare all five kingdoms, but just Animals and Plants.)

    We looked at seven cells from a variety of sources such as a Paramecium, human thyroid, PSB courtyard planet bush, buttercup, and earthworms.

    The following is our recorded observations of their size.

    PSB courtyard planet bush
    Organism sixe: 2.6 m approximately
    Cell size: 26 micrometers

    Paramecium
    Organism size: +/- .5 milimeters
    Cell size: 156 micrometers by 36.4 micrometers

    Human thyroid
    Organism size: 2-2.5 m approximately
    Cell size: 85.8 micrometers

    Blade of Grass
    Organism Size: 114 mm approximately
    Cell Sizes: 18.2 - 57.2 micrometers

    Earthworm
    Organism Size: 74 mm approximately
    Cell Sizes: 10.4 - 182.0 micrometers

    Buttercup Stem
    Organism Size: 115 cm approximately
    Cell Sizes: 15.6-26 micrometers

    Corn Stalk
    Organism Size: 3 m
    Cell Sizes: 208-1040 micrometers

    We were wrong (#5421 this week). Organisms don't just have one cell size but many different cells. The sizes aren't consistant within the organisms themselves, nor the different kingdoms. If we could look into this further, we might discover and define certain types of cells and find their size and how they correlate and compare that way.


    cell size
    Name:
    Date: 2002-09-24 15:04:58
    Link to this Comment: 2878

    We thought that cell size would be proportionate to the size of the specimen. However, our data revealed a scatteredness. The cell of the leaf was 30 micrometers big, the cell of the earthworm was 50 micrometers, the cell of the moss was 50 micrometers, the cell of the buttercup was 80 micrometers, the cell of the apple 20 micrometers, and the cell of the paramecium was 30 micrometers. This shows either that cells size does not have a definite proportion to the size of an organism or that there is a good reason why we are not science majors...

    We feel that maybe the size of the cell is perhaps determined by the function of the cell- otherwise our data should be more consistent to our first thoughts about cell size. Even within the samples we found, there were different size cells.

    Heather, Christine, Margot


    kathryn bailey, sarah frayne, laura sylvius
    Name:
    Date: 2002-09-24 15:06:10
    Link to this Comment: 2879

    ................size of organism...............cell size

    corn............10 ft...........................0.80 um
    tree leaf.......20 ft...........................1.30 um
    earthworm.......0.25 ft.........................1.04 um
    elodea..........0.50 ft.........................0.68 um
    moss............0.10 ft.........................2.58 um

    hypothesis: There is a direct correlation between the size of the organiism and the size of the organism's cells.

    Conclusion: Our hypothesis was disproven because we did not find a sizable correlation between the size of the five organisms and the size of their cells.


    Cells
    Name:
    Date: 2002-09-24 15:06:18
    Link to this Comment: 2880

    Brenda Zera, Sarah Tan, Elizabeth Damore

    Our original hypothesis was that all cells would be of a comprable size, regardless of the size of the organism. However, our observations proved that our hypothesis was wrong. No only did cell size vary from plant to plant, but there were also cells of differing sizes within the same organism.

    We observed five different samples: grass, a tree leaf, and clover from the courtyard, and an earthworm and moss from the prepared slides. For individual cell size, our measurements were as follows (in micrometers):

    Moss (1 inch): from 10.4-78

    Earthworm (8-10 inches): from 5.2-13

    Clover (3 inches): from 5.2-26

    Grass (6 inches): from 13-104

    Tree leaf: (40ft tree): from 26-130


    cells
    Name: joanna, ya
    Date: 2002-09-24 15:16:20
    Link to this Comment: 2882

    Joanna, Yarimee, and Jen

    hypothesis: Cell size does not depend on organism size

    observations:

    moss- 52.0 mm

    Elodea- 102 mm

    cheeck- 78.0 mm

    corn stalk- 67.6 mm

    earthworm- 52 mm (LONGER cells)
    13 mm ( small cells)

    Conclusion: Size of the organism does not account for cell size, but all cells are not the same size. There are even different cell sizes within one organism.

    Questions....
    1. Does cell function determine cell size?

    2. Was it human error that accounts for the differences we saw?

    3. Is volume a better way to measure cells?

    Joanna Robertson, Yarimee Gutierrez, Jennifer Rusk


    Cell Lab
    Name: Diana, Mic
    Date: 2002-09-25 14:33:13
    Link to this Comment: 2888

    Our group looked at 5 different organisms of differing sizes (from largest to smallest):
    Elodea - approx. 10cm
    Plant from Planet Courtyard - approx. 4cm
    Zea stem - width was .78cm
    Amoeba - 262.6 um
    Paramecium - 65 um

    The original hypothesis was that organism size depends on cell size, that bigger organisms will have bigger cells.

    Results are as follows:
    Elodea cell - 50 um
    Plant from PC cell - varied from 7.8 to 28.6 um
    Zea stem cell - varied from 7.8 to 117 um
    Amoeba cell - 262.6 um
    Paramecium - 65 um

    Our conclusion is that cell size does not determine organism size. However, this hypothesis stands when used for single celled organisms alone. Our observation of plant cells demonstrated the various cell size within one organism. Due to the congregration of similar sized cells within multicellular organisms, we concluded that they have varying sized cells for various functions.


    Cell Size
    Name: Chelsea R.
    Date: 2002-09-25 14:48:42
    Link to this Comment: 2889

    Hypothesis: The size of an organism will not always correlate to the size of its cells.

    Data/Observations: Corn Stem Cell - length: 70um Moss Cell - length: 78 um Elodea Cell - length: 50um Ameoba Cell - length: 36.4um Hair Cell - length: 100um

    Note: Many of these samples showed cells of varying sizes within the organism. We recorded, for our purposes, the length of what appeared to be a relatively represetative cell (except, of course, in the ameoba, which is a one-celled organism).

    Conclusion: Our hypothesis still appears to work. Within each organism, cell size varied, and between organisms cell size also varied, although without any apparent correlation to size of organism. For example, a moss plant is smaller than an elodea plant, but our observations showed moss cells larger than elodea cells.


    Cells Fabulous Cells!
    Name:
    Date: 2002-09-25 14:50:18
    Link to this Comment: 2890

    Lab Group: Erin Myers, Brie Farley, and Diana DiMuro

    Lab Hypothesis: Bigger organisms have bigger cells.

    Collected Data through use of microscope:

    Corn Stem cell size range: 7.8 -143 micrometers

    Clover flower petal cell (from planet courtyard): 13 micrometers

    Earthworm (one of many cells): 18.2 micrometers

    Elodia cell width: 26 micrometers
    Elodia cell length: 61.8 micrometers

    Erin's Cheek cell: 50 micrometers

    Ameba proteus : 200 micrometers

    Conclusion: Bigger organisms do not actually have bigger cells. Cell size varies from organism to organism not depending on the size of the organism.


    bio lab #3
    Name: Annie and
    Date: 2002-09-25 14:53:31
    Link to this Comment: 2891

    Our hypothesis asserts that larger organisms have larger cells. To test this, we looked and measured celss from five organisms: a clover leaf, an earthworm, a mushroom, moss, and cells from a human thyroid. The measurements are as follows (listed from largest organism, to smallest):
    (all initial measurements are multiplied by proper number to standardize data)

    human thyroid
    length: 234 um
    width: 78 um
    area: 18252 um^2

    mushroom
    length: 156 um
    width: 9.1 um
    area: 1419.6 um^2

    earthworm
    length: 169 um
    width: 31 um
    area: 5239 um^2

    clover leaf
    length: 91 um
    width: 31 um
    area: 2821 um^2

    moss
    length: 174 um
    width: 52 um
    area: 9048 um^2

    (obviously, the area calculated is only a rough estimate not account for the irregular shape of the cells)
    areas (ranked by size, largest to smallest):
    human thyroid (18252), moss (9048), worm (5239), clover (2821), mushroom (1419).

    The cells we measured are only single examples of a cell in each organism. The size of cells within a single organism vary greatly.
    According to our data, there is no parallel between the size of the cells and the size of the organism. Our hypothesis is therefore incorrect.


    cell size
    Name: no
    Date: 2002-09-25 14:55:40
    Link to this Comment: 2892

    Lawral "Woo Woo" Wornek and Joanna "Ja Ja" Ferguson

    Our hypothesis was that cell size relates directly to plant or animal size. We found, however, that just because a plant or animal is large is doesn't necessarily mean the cells of that living organism are large as well. Our evidence for this new idea is as follows:

    Corn stem cells, from a corn stem, which as we all know is quite a large plant, were found to have cells about 90 micrometers across.

    The Water Plant cells were between 50 and 100 micrometers. The water plants found in the lab are as big as that particular plant grows.

    Buttercup stem cells were found to be between 50 and 70 micrometers. As we all know, buttercups are plants the size of redwoods, and are found in only select parts of Maine and New Hampshire. NO! This is actually a lie. Buttercups are small flowering plants found throughout the world. SMALL is the point we need to make here.

    Moss (Mature Archegonium) was found to have cells roughly 125 micrometers in size. Think about moss. Think about size. Moss is small.

    We also looked at a sample of cells from Ja Ja's mouth. As we all know, she is a large animal, being human. The cells were found to be from 50 to 120 micrometers in diameter.

    From these samples we have determined that although there are many different sized plants and animals in the world, they do not all have different sized cells. Just because a plant may be larger than another plant does not mean its cells are larger than those in other plants. It would make sense that this is true, because if a plant had very large cells I would think the plant would be brittle, as the cell wall would have to be very large and tough to support a large plant. It makes more sense to build a large building with smaller, stronger bricks than with larger bricks. As Woo Woo just said, it's more the TYPE of cells.

    We hope we have not offended anyone with our findings. Can we go home now?


    ps tobacco looks nasty under a microscope. so does bleached hair. ...excellent...


    Determining Cell size of different specimens
    Name:
    Date: 2002-09-25 14:58:37
    Link to this Comment: 2893

    Melissa Brown and Roma Hassan

    For this lab we looked at different cell specimens and determined the average cell size for each specimen.
    Hypothesis: The larger the organism is in real life the larger its cells.
    Methods: For this experiment we used a simple microscope to determine cell structure and cell size for 5 different specimens, 4 of which had been previously prepared and one specimen for which we prepared the slide.
    The general method we followed was to adjust the slide under the microscope under various lenses (usually using the highest powered lens) and moving the stage till the cell was at its best focus. Then we went on to measure its size using the ruler inside the lens. We looked at three different cell sizes for each specimen and then took the average of all the three measurements that we determined.

    Observations:
    Specimen 1:
    HB 7-12, Hyaline Cartilage
    1) 13x2.6 =33.8micrometer
    2) 15x2.6 =39micrometer
    3) 12x2.6 =31.2 micrometer
    Avg. size =34.67micrometer
    Roundish/Elliptical in shape

    Specimen 2:
    Elodea (plant)
    1) 40x2.6 =104micrometer
    2) 42x2.6 =109.2 micrometer
    3) 39x2.6 =101.4micrometer
    Avg.size =104.87micrometer
    Rectangular in shape with rounded edges, lots of chloroplasts inside.

    Specimen 3:
    Lumbricus X-Section
    1) 4x2.6 =10.4micrometer
    2) 5x2.6 =13micrometer
    3) 3x2.6 =7.8micrometer
    Avg.size =10.4micrometer
    Elliptical purple cells and roundish green cells could be seen.

    Specimen 4:
    Zea Stem C.S.
    1) 43x2.6 =111.8micrometer
    2) 59x2.6 =153.4micrometer
    3) 46x2.6 =119.6micrometer
    Avg.size =128.27micrometer
    Different cells could be seen but the one examined and measured is a transport cell from the vascular tissues.The cell is big and unevenly shaped.

    Specimen 5:
    Cheek cells
    1)77micrometer
    2)76micrometer
    3)78micrometer
    Avg.size = 77micrometer
    roundish in appearance.

    Conclusion: We are happy to say that our hypothesis is wrong (yay!). Larger organisms do not necessarily have larger cells than smaller organisms.


    Cell size
    Name: heidi adle
    Date: 2002-09-25 15:03:20
    Link to this Comment: 2894

    Chelsea
    Heidi
    Mer

    Hypothesis: The size of an individual cell is directly related to the size of the complete organism.

    Earthworm--> 5.2 micrometers (ums)

    Moss--> 130 mircometers (ums) (we also saw smaller cells, but could not measure them)

    Elodea--> 85.8 mircometers (ums)

    Dried Tobacco--> 33.8 micrometers (ums)

    Mare's skin--> 65 micrometers (ums)

    An individual moss is about 5 cm long compared to an elodea branch which is about 10 cm long. The cells of these two organisms are 130 ums and 85.8, respectively. A human epidermis covers a person who is about 5'4", with a cell size of 65 ums, in comparision with tobacco (dried) that has a cell of 33.8 ums. Finally, the earthworm can grow up to 20 cm long, and its cells are only at the size of 5.2 ums.

    In conclusion, the size of an individual cell is not directly related to the size of the complete organism. Also, different parts of the same organism can have different sized cells (as seen in the moss cells)


    Microscope
    Name: The Cool G
    Date: 2002-09-25 15:08:34
    Link to this Comment: 2895

    Lauren Friedman, Carol E. Griffin, Catherine Rhy

    Hypothesis: The bigger organisms/samples will be composed of bigger cells.

    Here are our observations:


    earthworm: 57.2 micrometers


    elodia: 85.8 micrometers


    amoeba: 68 micrometers


    cuboidal epithelium thyroid: 3.9 micrometers


    buttercup stem: 65 micrometers


    moss: 156 micrometers

    We have concluded, cautiously of course: Our hypothesis was wrong wrong wrong. In the organisms where there were smaller cells, they were packed very close together, like sardines.* Because there can be many many small cells or very few larger cells, we can conclude that the size of the organism cannot be determined by the size of the cell. Large organisms be composed of cells that are smaller than the cells of smaller organisms. Of course, in single-cell organisms, the organism is exactly the size of the cell, so in that case the smaller cell would be that of the smaller organism. But that is an exception, not a universal rule.

    *


    Special thanks to Will.


    Bead measurements
    Name: Mande and
    Date: 2002-10-01 15:13:59
    Link to this Comment: 3064

    hypothesis: The larger the bead the less they are moved by water molecules.

    Measurments:

    2micrometer bead-143 micrometers in movement
    4micrometer bead-80.4 micrometers in movement
    6micrometer bead-5micrometers in movement

    Variables: due to the fact that i have a lazy eye and Mande has horrendous vision, keeping track of the bead proved difficult and may have had have effected our outcome.

    Onion cell

    Hypothesis: Adding water will create movement within the cell wall therefore causeing the cell membrane to expand (turgid), the addition of salt however will cause the membrane to retract within the cell wall.

    Observations:
    3% salt solution-all cells are turgid with noticible nucleus.
    Distilled H2O- Cells are clear under scope, with turgid cells, noticable nucleus.
    25% salt solution- Cell membrane appears smaller than cell wall(plasmolized), not all of the cells retain this plasmolized state, some are still turgid.

    Conclusion:
    Water molecule movement seems to be inhibited in some way by the addition of salt, because the cell membrane retracted within the cell wall, when salt was applied therefore implying that the water created movement within the cell hence swollen and retracted states of the membrane.


    Molecule Movements
    Name:
    Date: 2002-10-01 15:20:17
    Link to this Comment: 3066

    Elizabeth Damore, Brenda Zera

    Movement in a thirty second period

    2 microns: First Trial- 35 units (91 microns)
    Second Trial- 22 units (57.2 microns)

    4 microns: First Trial- 11 units (28.6 microns)
    Second Trial- 14 units (36.4 microns)

    8 microns: First Trial- no movement
    Second Trial- 1 unit (2.6 microns)

    This data supports the hypothesis that bigger molecules do not move as quickly as the smaller ones.

    Onion Observations

    3% solution- some plasmolyzed cells

    Distilled Water- mostly turgid cells

    25% solution- mostly plasmolyzed cells

    Water fills up the cells because its molecules are lighter than salt's and move quicker. Distilled water has a lower viscosity than saltwater, so it can flow quicker into the cells.


    plastic beads
    Name:
    Date: 2002-10-01 15:26:58
    Link to this Comment: 3067

    bead size.....movement

    2um............4 segments
    4um............2 segments
    8um............1 segments

    all measurements were taken at the 40x power

    the data suggests that the hypothesis is correct. the larger the bead the less it moves

    onion data

    3% salt.......turgid
    H2O...........turgid
    25% salt.......plasmolyzed

    the data suggests that the presence of salt changes the cells.

    Both observations combine to suggest that the cells are turgent with water because the movement of the molecules pushes the membrane, but when the salt is added the membrane becomes denser/heavier and so the water is unable to move it outwards to the cell wall.

    Sarah Frayne
    Stephanie Lane


    On the Consequenses of Having Blue Eyes
    Name: The blue-e
    Date: 2002-10-01 15:27:07
    Link to this Comment: 3068

    Trial #1: We first observed the 2 Micron beaded water, and after much fiddling around with the microscope and several visits from Will (which we are not entirely sure were merely class-related but rather to admire our lovely blue eyes), we were finally able to locate the position of the beads. These were moving very quickly, but they seemed to be moving in unison, which we later discovered was due to the vibrations from the desk-bench-lab table thing. They moved about 200 micrometers in three minutes

    Trial #2: We looked at what we think was 4 Micron beaded water, but we couldn't see it moving. Then we thought that we saw the molecules, but they were stationary. Then Will and Prof. Grobstein informed us that we did not have enough water on our slide, and so we tried again.

    Trial #3: This time we were sure to put 4 Micron beaded water on the slide, and after again much playing wih the microscope, we were able to find the water molecules, which were moving, but very slowly, especially when compared to the movement of the 2 Micron water. The 4 Micron water moved about 109 micrometers in three minutes.

    Trial #4: With the 8 Micron beaded water, we looked through the 'scope and saw that the molecules were hauling ass (it's an industry term) on the slide. When we expressed our surprise about this, Will informed us that perhaps we should look in again, and when we did, the molecules had slowed down significantly - in fact, they were hardly moving at all. We concluded that we had begun our observation too early and had not given the molecules tme to settle down. In three minutes, the 8 Micron water moved 44 micrometers.

    The Onion Phenomenon

    #1: With the 3% salt solution, several of the cells were plasmolyzed, and some are even empty (AAHH!!!). This is because Will overestimated the isotonic solution, which is the level of salt solution that is in perfect harmony with the cells (bad Will.) This may also be because we chose as our subject the outermost layer of the onion, which Will says may be closer to death. Perhaps our obervations would have been different if we had chosen a layer of onion closer to the core.

    #2: After adding the water, all of the cells appeared to be empty. However, we have learned that this clear and empty appearance is somewhat deceptive. All of the cells were turgid, and Will was wrong when he told us that the cells were really plasmolyzed. After reducing the light source and focusing in a little closer, we could see the green chloroplasm along the cell wall, and a nucleus in almost every cell.

    #3: After adding the 25% salt solution, we found that a large percent of the cell membranes have been plasmolyzed. This would lead us to believe that the more salt which is present, the more plasmolyzed the cells become.

    OConclusions: Because the cells were the most turgid when immersed in the pure water solution, the NaCl is therefore responsible for the collapse of the Cell Membranes. We hypothesize this occurs because the NaCl has an averse reaction to the water: when the onion sample is immersed in the pure water solution, the molecules move faster and therefore become turgid enough to fill the entire space of the cell wall. Because when NaCl is present, the cell membrane shrinks away from the cell wall, we think that the salt causes the molecules to move slower, thereby making it unable to become completely turgid.


    Names
    Name: Laura
    Date: 2002-10-01 15:28:20
    Link to this Comment: 3069

    the above comments were posted by Laura Silvius, Kyla Ellis and Maggie Hoyte.


    microbeads!
    Name: ginnie & m
    Date: 2002-10-01 15:30:06
    Link to this Comment: 3070

    Virginia Culler, Marybeth Curtiss

    ---microbeads---

    8 micron beads:
    1) not much movement noticed - nominal if any. we hypothesize that these beads may be too big to demonstrate significant movement. if these beads are 8 microns in diameter, then the furthest bead movement we recorded was approx 1-3 microns in distance, not much at all.

    2) 4 micron beads: still not much movement, though significantly more than with the 8 micron beads. the movement is still fairly slow but is varying, some will seem to speed up and then slow back down. it's not so much distance which is traveled, but rather random, slow floating movements concentrated in primarily one area. we'd say maximum distance traveled is between 3 and 5 microns, and some of this may be due to jostling of the table, lens, etc.

    3) 2 micron beads: eureka! movement! ok not much, but they sort of vibrate at a faster rate and their vibrations make them travel more distance- like more than 5 microns after only 30 seconds or so. pretty fast in comparison to the other beads.

    ---onions---

    1) with the 3% salt solution we observed that all the cells seem to be perfectly happy, turgent or whatever that word was, and in firm contact with the cellulose walls. however, in some specific places we noted that the cell edge and the cell wall didnt quite line up, which might suggest that the cell edge is already starting to pull away from the cell wall

    2) the water seemed to flush everything pretty well and actually re-inflate the cells that were slightly pulling away from the cell walls

    3) this time the 25% salt solution seemed to really make the cells pull away from their walls, except for a few spiderweb-like tendrils that cling on to the cellulose.

    accounting for these observations:
    we seem to see that water infuses cells and makes them "fuller," whereas salt seems to make things contract. perhaps this is due to the fact that the amount of water on the outside of the cell must equalize with the amount of water in the celll


    Beads!! (and onions)
    Name: The Ks
    Date: 2002-10-01 15:30:29
    Link to this Comment: 3071

    Kate Amlin
    Katie Campbell

    Hypothesis: Our idea was that in water, big beads would move less than smaller beads following the principle that the water molecules are also moving.

    We observed different sized beads in water and measured the largest radius covered by each over a period of four minutes.

    8 micron beads: largest radius covered 18.2 micrometers
    4 micron beads: largest radius covered 24.3 micrometers
    2 micron beads: largest radius covered 33.8 micrometers

    Our observations supported our hypothesis and so we will use these observations to aid explaination of the onion and water/salt solutions.

    The onion cells with 3% salt solution showed primarily turgid cells with a few beginning to plasmolyze with the corners of their cell membranes pulling away from the cell wall.

    The onion cells in water (distilled H20) were completely swollen, all cells are turgid.

    The onion cells in the concentrated 25% salt solution are plasmolyzed. The cell membranes appear squished and shrunken within the cell walls.

    So to explain this phenomena and what it has to do with the beads...
    Both observations prove that water is in constant motion.
    Our observations with the onion showed us the different ways that cells look with different concentrations of water and salt.

    Our idea is that the concentration of salt in the water effects the degree to which water moves in and around the cell. Just like the size of the beads effected how much they moved.

    So our next course of action would be to determine what the degree of water movement has to do with the appearance of the cell. Hopefully this would have something to do with density, but maybe not.

    This exercise has challenged us in many ways and we realize that our final obersations are inconclusive, leading us to be wrong, yet again.


    sarah tan, kathryn bailey
    Name:
    Date: 2002-10-01 15:30:55
    Link to this Comment: 3072

    hypothesis: the larger the bead, the less distance it will move in a three minute time period.

    data:

    bead size............maximum radial distance
    2 um.................156um
    4um..................15.6um
    8um..................7.8um

    conclusion: the data supports the hypothesis, leading us to believe that the larger the bead, the shorter the distance it will move. however, since we only did one trial of each bead size, these data may not reflect an actual trend.
    -------------------
    Procedure:
    Prepared onion slide with one-cell layer.
    When we looked at the onion cells in a 3% salt solution, the cell membranes and cell walls were quite close to each other, and the cells were turgent. When we looked at the cells after changing to a 25% solution, the cell membranes had drastically pulled away from the cell walls, and the cell itself had shrunk.

    Given our new observations that water molecules are always in motion, we hypothesize that the cells shrank in the 25% salt solution because the water molecules had a smaller radial distance than when the cells were in a pure water solution, in which case the radial distance increased. We would like to take this lab to be one of our times to be wrong every day.



    Name:
    Date: 2002-10-01 15:33:45
    Link to this Comment: 3073

    In the first slide activity, we observed that the 2nm microsphere moved a distance of 236 microns in the time of 1 minute, 25 seconds. In the second slide, we observed that the 4nm microsphere moved in that same time, about 5.2 microns. From this we believe that the bigger the bead, the slower it moves.

    In the slide of the onion with 3 percent saltwater, we observed some shriveling of the membranes. When the distilled water was added, there cell membrane swelled to where they were turgid. When the 25 percent solution was added, there was severe shriveling of the membaranes. From this we concluded that the amount of salt in the water determines the amount of contraction of the cell membrane.

    From both activities, we can conclude that water particles are always moving. Water caused the onion cell membranes to move; when the water was replaced by the salt, there was a moving in of the membrane, not a swelling out.

    Christine Traversi
    Margot Rhyu



    Name: Joanna Rob
    Date: 2002-10-01 15:41:47
    Link to this Comment: 3075

    Yarimee Gutierrez
    Joanna Robertson


    Bead Size Distance Traveled
    8 micrometer 10 micrometers

    4 micrometers 104 micrometers

    2 micrometers 13 micrometers

    Onions

    3% salt solution-> most cells are turgid, but some cells are plasmolyzed

    0% salt solution-> more cells are turgid than plasmolyzed

    25% salt solution-> most cells are asignificantly plasmolyzed.

    Observations-
    1. Water molecules are constantly in motion.
    2. The quantiy of salt directly affects the distance traveled by water molecules.
    3. Perhaps salt molecules are bigger.


    Molecular Motion
    Name:
    Date: 2002-10-02 15:11:25
    Link to this Comment: 3085

    Melissa Brown, Roma Hassan and Lawral Wornek

    Hypothesis: The smaller the microsphere; the faster its motion.

    Methods: We took a special slide which had depressions on either side to act as a reservoir for any liquid that we would place there. After putting a specific liquid in the reservoir we covered it up with a cover slip and put the slide on the stage of the microscope to determine our observations. In this case we are supposed to measure the speed of the liquid molecules which can be found by measuring the distance a certain molecule moves in a fixed period of time since speed is distance divided by time. We used 2 minutes as the time for observation.

    Observations 1:
    1) 2 micrometer bead moved 30 micrometers in 2 minutes.
    2) 4 micrometer bead moved 21 micrometers in 2 minutes.
    3) 8 micrometer bead moved 1 micrometer in 2 minutes.

    Conclusion: Sadly, we were right. Thus the smaller the size of the microsphere the faster it seemed to move. We believe that our conclusion is correct because it follows that a smaller molecule when bombarded by other moving molecules will move faster because the energy generated by the impact will cause the molecule to move faster.

    Observations 2:
    An onion membrane was placed on the slide and 3% salt water was dropped on it. The onion cells turned turgid. Next, distilled water was put on the same membrane and it was observed that the cells turned more turgid. 25% salt water was next added to the membrane and plasmolysis of the onion cells were observed.

    Relating observations 1 and 2 we can say that the molecules moved from inside the onion cell to the outside area because the outside area had a higher concentration. We observed that as the added solution became more concentrated the cells became more plasmolyzed. In the higher concentration of solvent the number of molecules increased in each group (as the molecules bombarded each other they clustered together in groups) and therefore the groups moved more slowly.

    These experiments have successfully demonstrated both brownian motion and osmosis.


    Water and Onions
    Name: Maggie and
    Date: 2002-10-02 15:14:14
    Link to this Comment: 3086

    Experiment 1:
    8 micrometer microspheres moved 3.95 micrometers in 5 minutes
    4 micrometer microspheres moved 10.4 micrometers in 5 minutes
    2 micrometer microspheres moved 143 micrometers in 5 minutes

    Our findings support the thesis that says that water molecules are continuously moving, and the smaller the object was the more it moved.

    Experiment 2:

    3% salt solution made almost all of the cells turgid but a few of them were partially plasmolyzed.
    0% salt solution made the cells even more turgid, and filled out the ones that were plasmolyzed earlier.
    25% salt solution made the cells very plasmolyzed.

    When there is salt in the environment outside of the cell, it takes water away from the inside of the cell, making the cell plasmolyzed. This relates to the hypothesis we supported in our last experiment (that water molecules are always moving whether we can see them or not) because the water was moving from the inside of the cell to outside of the cell, or vice versa.

    Maggie Scott-Weathers and Emily Senerth


    Beakman's World
    Name: Will and D
    Date: 2002-10-02 15:22:30
    Link to this Comment: 3087

    2um -> 23.4um/min, 54.6um/2min
    ......39um/min
    ......36.4um/min
    ..avg.-> 32.9um with conversion
    4um -> 1.3 um/2min
    ..........2.6um/2min
    .......1.3 um/2min
    ..avg.-> 1.7 um/2min
    8um -> .85 um/2min
    ..........0um/2min
    ..........0um/2min
    ..avg.-> .28 um/2min

    Onion Cell Observations:

    In 3% solution the onion cells are pretty much turgid, and there is not much change from the cell appearance when the 3% solution is changed to distilled water, which has a 0% salt content. However, when the distilled water is replced by the 25% solution a majority of the cells become plasmolyzed.

    Onion Cell Story:

    When salt is introduced to the surrounding environment, the NaCl molecules are too big to pass through the cell wall. Therefore, to create equilibrium, water leaves the cell into it's surrounding environment. A cell is turgid when it has many water molecules in it because the water molecules move around and stretch the cell membrane to its capacity. This is the case in the distilled water solution. When salt is introduced to the cell's environment and water leaves the cell there are not as many water molecules to move around and thus the cell membrane "shrinks" and is not stretched to its capacity. The more concentrated the salt solution the more water exits the cell and thus the fewer water molecules inside the cell which makes the cell more plasmolyzed.


    Lab 4
    Name: Annie S.,
    Date: 2002-10-02 15:28:27
    Link to this Comment: 3088

    Experiment #1:
    Our hypothesis is that smaller molecules should move slower than larger molecules. To test this we measured the movement of three different sized molecules. The smallest molecule was 2um and during one minute it moved 33um. The middle sized molecule was 4um and during one minute it moved 2.6um. The largest molecule was 8um and during one minute it moved 1.3um. Smaller molecules move faster because in a given area there are more of them which causes the molecules to have more contact with one another which creates more movement. Smaller molecules require less energy to move which enables them to sustain momentum...

    Experiment #2 Plant cells under three different conditions:
    Th onion with the 3% salt solution showed all turgid cells. After replacing the solution with distilled water, not notced no change in the cell walls and membrane. We then replaced this solution with a 25% salt solution. We noticed that this solution caused the cell membranes to shrink, or to pull away from the cell wall.

    Conclusion: In a higher salt concentration solution, we observed that the cells are all plasmalyzed. This is because the salt ions absorb the water molecules, which causes the actual membrane to shrink. Water is necessary to sustain the shape and structure of the cell membrane (in a plant cell, the cell wall will not move).


    learning through osmosis
    Name:
    Date: 2002-10-02 15:28:32
    Link to this Comment: 3089

    Brie Farley, Erin Myers, Diana DiMuro

    Microspheres
    2m beads moved ~30 microns
    4m beads moved ~13-15.6 microns
    8m beads couldn't be seen moving

    Onion Skin
    distilled water saturated had mostly turgid cells
    3% NaCl(q) saturated had some turgid cells and some plasmolyzed cells
    25% NaCl(q) saturated had mostly plasmolyzed cells

    The vacuoles of the cell filled with water when saturated with distilled water. This made the cell bigger and pushed its mebrane up against its cell wall (turgid). When we added 3% NaCl solution, water escaped the vacuoles and cell membrane as salt came into the cell, trying to equalized the salt level inside and outside the cell. This made the cells smaller and the membrane recede from the cell wall. When we added the 25% NaCl solution even more water was required outside the cell to equalize the salt levels in and out of the cell, making the individual cells more plasmolyzed.
    Microbeads and onions are connected...


    Water Movement & Onion Cells
    Name:
    Date: 2002-10-02 15:29:02
    Link to this Comment: 3090

    Chelsea R., Adrienne, & Laura B.

    Part I: Motion of Microspheres in Water

    Prediction: Smaller microspheres will move more than bigger microspheres in water.

    Observations:
         8um microsphere had no visible motion during a three-minute period.
         4um microsphere moved 15.6um in 2 minutes.
         2um microsphere moved 390um

    Conclusion: Because our 2um microsphere measurement was so large compared to the other groups' observations, we think we were looking at the wrong things. However, according to our observations and the other groups' observations, it seems that our prediction (that smaller microspheres would move more than larger microspheres in water) still holds true at this time. This appears to show that water molecules do move. (Though of course nothing can be proven absolutely.)

    Part II: Onion Cells in Salt and Water Solutions

    Observations: Turgid or Plasmolyzed?
         3% salt: the majority of the cells appear mostly turgid
         0% salt: the majority of the cells appear turgid
         25% salt: the majority of the cells appear plasmolyzed

    Part III: Putting It All Together

    Since water molecules move (as observed in Part I) and in order for a cell to be turgid it requires something to fill it, the water molecules probably move into the cell to fill it up, and since the water is moving so much it pushes the cell wall out, causing the cell to be turgid. When more NaCl is added to the water, there are fewer water molecules to fill the cell and make it turgid. So when the solution is 25% NaCl, the cells are plasmolyzed because there is less water to fill the cell and push against the cell wall.


    call me sketchy.
    Name: Jody, Carr
    Date: 2002-10-02 15:37:35
    Link to this Comment: 3093

    We started the class with some poetry, compiled from explanations of molecular activity. An excerpt:

    dye molecules.
    motionless?
    illusion
    water molecules running around all the time
    disappeared
    why?
    constant motion.
    escaping!
    wandering!
    boiling maelstrom
    hot spring
    (i am a hot spring)
    mountain lake in the arctic
    they all seem to be quiet
    peaceful
    boom
    boom
    boom
    spreading occurs more rapidly
    why?
    spreading takes more time
    why?
    absolute zero
    nothing is that cold
    (awesome)
    everything does
    well, that's a good story.






    The lake pictured above may appear to be motionless. It is not.

    Our hypothesis was that the size of the molecule relates to how fast it moves, that smaller molecules will move more quickly.

    We found conclusive evidence to support our initial claim.

    The microspheres of 2 microns moved about 18.2 micrometers. The microspheres of 4 microns moved about 7.8 micrometers. The microspheres of 8 microns... did not move AT ALL. That's right, folks. It was completely motionless. Whew.

    Let's keep in mind that while it APPEARED motionless, it in fact was not, for nothing on this grand old planet is ever truly still.





    We learned from our first set of observations that molecules move faster and collide more in liquid when they are smaller. In our second experiment, viewing onion epidermis under three different conditions, we were able to apply this knowledge. Viewed under distilled water and lower concentrated solutions, the plant cells remain primarily turgid, maintaining their cell walls. Under higher concentrated solutions, such as the 25 percent salt solution used here, the cell walls soften and become plasymelyzed. Why, you may wonder? Higher concentrations of molecules are ultimately more attractive and have a stronger pull, which is why under a twenty five percent solution, the cell wall molecules were distended, resulting in plasymalization.


    the wonderful world of beads
    Name: Chelsea, M
    Date: 2002-10-02 15:38:55
    Link to this Comment: 3094

    Hypothesis: Larger beads move less than smaller beads in water

    Observations: The 2micrometer bead moved a total of 20.8 ums away from its point of origin. The 4 micrometer bead moved a total of only 1.4 ums away from its point of origin. The 8 micrometer bed moved only .75 ums in total.


    In the second half of the lab, we watched the cells of an onion react with different levels of salt within water. When the cells were placed in the 3% salt solution, we noticed that the cells' membranes were mostly turgid, although is some of the coners of the cells, there was slight plasmolyzation. In the distilled water, the cells were completely turgid, and fianlly in the 25% solution, the cells became very plasmolyzed, with the membranes clumpy together, pulling all the internal organelles closer together within the cell wall. (The wall itslef does not move).

    Therefore, given these observations and our previous observations, we have found the meaning of life and the orgin of clumpy diversity.

    The membrane retracting from the wall is a consequence of its interaction with the salt, an interaction due to the fact that water continually moves and passes through the membrane.


    Once upon a time there was not a whole lot of salt in the ocean, right? That is analogous to the distilled water, so the cell (ie the earth's diversity) was turgid (and the reason for that more species and variations can exsist in distilled H2O then in the salt solution). THEN, salt slowly began to be more prevalent in the ocean and along with this, there came a little tiny bit of plasmolyzity (ie, clumpiness, because some of the intermediary species, like perhpas Heterotrophs with cell walls, couldn't manage). Even more salt came, and so the end result, which is the plasma all being CLUMPED together in the middle of the cell, was that all of the intermediary species that didn't work became extinct, and what you have left is clumpiness.


    Oxygen levels
    Name:
    Date: 2002-10-08 15:10:03
    Link to this Comment: 3205

    Brenda Zera, Elizabeth Damore

    All measurements were taken at 15 second intervals.

    First experiment: 0, .2, .4, .4, .6, 1, 1.2, 1.4, 1.6, 1.8, 2, 2, 2.2, 2.2, 2.4, 2.6, 2.6, 2.8, 2.8, 3, 3, 3.

    After change in H2O2 level (Experiment #2): .4, .4, .5, .6, .7, .8, 1, 1.1, 1.3, 1.4, 1.5, 1.6, 1.7, 1.7, 1.8, 1.9, 2, 2, 2, 2.2, 2.2, 2.3, 2.4

    We used less H2O2 in the second experiment which raised the rate of reaction, resulting in a lower production of oxygen within the same time period.

    Reaction Rate (First experiment)= .4
    Reaction rate (second experiment)= .7


    experiment 5
    Name: amanda mac
    Date: 2002-10-08 15:15:48
    Link to this Comment: 3206

    135 seconds- .9
    150 s.- 1.0
    165s. 1.0
    180 s.- 1.1
    195 sec. - 1.1
    210 sec. - 1.1
    225 sec. - 1.1
    240sec. - 1.1
    255 sec. 1.2
    270 sec. - 1.2
    285 sec. - 1.2
    300 sec. - 1.2

    reaction rate = (1.2-.9)/3 = .1/1 minute

    method: our portion of the experiment was to see if changing temperature would affect reaction time of the enzyme. We hypothesized that temperature woudl slow down the reaction time by making the oxygen release per minute lower than the test run that we first ran.
    we found that the reaction time during trial one of the experiment was much higher (.8/1minute) than that of our reaction time for experiment number five.
    mande adn debe


    Catalase Lab
    Name: MaryBeth &
    Date: 2002-10-08 15:23:14
    Link to this Comment: 3207

    Experiment #1 and Experiment #3, MaryBeth Curtiss and Virginia Culler

    Trial #1: Results for 15 second time intervals:
    .2, .3, .4, .6, .6, .8, 1.0, 1.4, 1.8, 2.0, 2.4, 2.4, 2.6, 2.8, 2.9, 3.0, 3.2, 3.4, 3.5, 3.6, 3.5, 3.6, 3.6, 3.7, 3.8, 3.9, 4.0, 4.1, 4.1, 4.1
    Total oxygen: 4.1cc
    Trial#2: Results for 15 second intervals, more catalase:
    .1, .5, .7, 1.0, 1.4, 1.7, 2.0, 2.2, 2.5, 2.6, 2.8, 3.0, 3.1, 3.2, 3.2, 3.3, 3.4, 3.5, 3.6, 3.6, 3.7, 3.8, 3.9, 3.9, 3.9
    Total oxygen: 3.9cc
    Trial #3: Results for 15 second intervals, same catalase as Trial#2:
    .2, .5, .8, 1.3, 1.7, 2.0, 2.2, 2.4, 2.7, 2.8, 3.0, 3.2, 3.3, 3.3, 3.6, 3.6, 3.6
    Total oxygen: 3.6

    Rates of oxygen conversion for each trial:
    Trial #1: .5857 cc of O2/minute*
    Trial #2: .7667 cc of O2/minute
    Trial #3: .7667 cc of O2/minute

    *For the Trial #2 and #3 calcualtions, we used a span of three minutes to determine the rate of oxygen production because the actual total time elapsed was shorter than the first trial. To calculate the Trial #1 rate, we used the total span of seven minutes.

    The results of the experiment were mostly what we expected to observe. The second and third trial were shorter and more productive because more of the catalase was added, and the rate results, though the specific numbers sometimes varied, were the same. The first trial took longer to produce the same amount of oxygen because the first vial had less of the catalase enzymes.



    Name: kyla &laur
    Date: 2002-10-08 15:23:54
    Link to this Comment: 3208

    Kyla Ellis
    Laura Silvius
    10/8/02
    Volume Of Oxygen Produced Over Time By Degradation Of Hydrogen Peroxide By Catalase

    Experiment 1, Trial 1 (Volume of Oxygen in CCs, taken at 15 second intervals):
    0,0,0,.2,.4,.5,.62,1,1.1,1.2,1.4,1.5,1.6,1.8,2,2.2,2.3,2.4,2.6,2.6,2.7,2.8,2.9,3,3.1,3.2,3.3,3.4,3.5,3.6,3.6,3.7,3.7,3.8,3.9,3.9,3.95,3.95,4,4.1,4.2,4.2,4.2,4.2
    Reaction Rate:.533

    Experiment 2, Trial 1:
    .4,.4,.5,.6,.8,1,1.2,1.4,1.8,2,2.2,2.4,2.6,2.9,3,3.2,3.3,3.6,3.7,3.9,4,4.1,4.4,4.5,4.6,4.7,4.8,4.9,4.9,5,5.1,5.18,5.2,5.2,5.3,5.35,5.4,5.5,5.5,5.6,5.7,5.8,5.8,5.8,5.8
    Reaction Rate:.83

    Experiment 2, Trial 2:
    0,.1,.2,.5,.7,1,1.2,1.4,1.6,1.8,2.2,2.2,2.4,2.6,2.7,2.9,3.2,3.2,3.4,3.7,3.9,4.1,4.2,4.3,4.4,4.6,4.6,4.8,4.8,4.9,5,5,5.1,5.2,5.2,5.2,5.3,5.4,5.4,5.4
    Reaction Rate: .76

    When we increased the amount of H2O2, the reaction became quicker and more noticeable to the naked eye.
    We conclude that as the ratio between the two components decreases, the reaction becomes more rapid and stronger.


    Chemical Reactions
    Name: the Ks
    Date: 2002-10-08 15:25:54
    Link to this Comment: 3209

    This experiment was conducted by the Ks-
    Katie Campbell
    Kate Amlin

    (All volume units are in cc.)

    EXPERIMENT #1:Standard Catalase at Room Temp.

    DATA: .1,.2,.3,.4,.6,1.0,1.2,1.5,1.5,1.8,2.0,2.3,2.4,2.5,2.7,2.8,
    2.9,3.0,3.2,3.3,3.5,3.6,3.7,3.7,3.7

    REACTION RATE: Volume at 2 minutes = 1.5cc
    Volume at 4 minutes = 2.8cc
    (2.8cc - 1.5cc)/2 = 0.65cc/min

    EXPERIMENT #4:Change of pH of Buffer
    (Due to time constraints we were only able to conduct one trial.)

    DATA: 0.0,0.0,0.0,0.0,0.1,0.2,0.2,0.2,0.3,0.3,0.4,0.5,0.6,0.6,0.7,0.8,
    0.8,0.9,1.0,1.1,1.2,1.2,1.3,1.4,1.4,1.5,1.6,1.7

    REACTION RATE: Volume at 2 minutes = 0.2cc
    Volume at 4 minutes = 0.8cc
    (0.8cc - 0.2cc)/2 = 0.3cc/min

    CONCLUSION: The pH effects the reaction rate. Lowering the pH
    significantly slowed the rate of the reaction between the
    enzyme and the hydrogen peroxide.

    Obviously the enzyme reacts with the hydrogen peroxide to release the oxygen. The pH only effects the reaction time. It does not effect the amount of oxygen that is produced by the chemical reaction. As you can see from our second experiment in which we changed the pH of the buffer, the reaction would still produce the same amount of oxygen that the first experiment did but at a much slower pace.


    Lab
    Name:
    Date: 2002-10-08 15:28:43
    Link to this Comment: 3211

    In our experiment, 2C, we increased the level of H2O2, or peroxide. The x was up, the rate was up. The length of time it took for the reaction to comlete itself was longer.


    This is our data:
    Experiment 1:
    0, .2, .4, .6, .8, 1.0, 1.2, 1.4, 1.5, 1.6, 1.65, 1.8, 1.9, 2.0, 2.0, 2.05, 2.1, 2.15, 2.2, 2.2, 2.3, 2.35, 2.4, 2.4, 2.4, 2.4
    Total time: 6 minutes 30 seconds
    Rate: .2 ml/min

    Experiment 2C:
    Trial 1:
    .2, .35, .6, .85, 1.2, 1.5, 1.8, 2.0, 2.3, 2.6, 2.8, 3.0, 3.2, 3.4, 3.6, 3.7, 3.8, 4.0, 4.1, 4.2, 4.25, 4.4, 4.5, 4.6, 4.6, 4.6, 4.65, 4.7, 4.8, 4.8, 4.8, 4.8
    Total time: 8 minutes
    Rate: .6 ml/min

    Trail 2:
    .1, .2, .4, .6, .8, 1.1, 1.4, 1.7, 2.0, 2.2, 2.4, 2.7, 3.0, 3.1, 3.3, 3.4, 3.6, 3.8, 4.0, 4.1, 4.3, 4.4, 4.5, 4.6, 4.65, 4.8, 4.8, 5.0, 5.0, 5.1, 5.2, 5.2, 5.4, 5.4, 5.4, 5.4
    Total time: 9 minutes
    Rate: .7 ml/min

    Trial 3:
    .1, .2, .4, .6, .8, 1.1, 1.4, 1.7, 2.0, 2.2, 2.4, 2.6, 2.7, 3.0, 3.1, 3.2, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4.0, 4.0, 4.2, 4.2, 4.3, 4.4, 4.4, 4.4, 4.5, 4.6, 4.6, 4.6, 4.7, 4.8, 4.8, 4.8, 4.8
    Total time: 10 minutes
    Rate: .52 ml/min

    Christine Traversi
    Heather Price


    oxygen levels
    Name: Jen + Step
    Date: 2002-10-08 15:31:56
    Link to this Comment: 3212

    Stephanie and Jen
    Original Results
    .2
    .8
    .9
    1.0
    1.2
    1.4
    1.6
    1.8
    2.0
    2.2
    2.4
    2.6
    2.8
    2.8
    3.0
    3.2
    3.4
    3.4
    3.6
    3.8
    3.8
    3.8
    3.9
    4.0
    Original Reaction rate: .070

    Trial B Results
    .6
    .8
    .8
    1.0
    1.2
    1.3
    1.5
    1.8
    2.0
    2.2
    2.4
    2.6
    2.8
    3.0
    3.2
    3.3
    3.4
    3.5
    3.6
    3.8
    3.9
    4.0
    4.1
    4.2
    Trial B reaction rate: .075
    (Trial A reaction rate: .015)

    Methods: Every fifteen seconds recorded reaction measurement from the injection of the H2O2.

    Observations: We found a variety of observations. In trial A, nothing really moved and when it did, it was slow. In Trial B, the results were similiar to the original.

    Our enzyme did not change because our rate stayed the same as X went up.


    Results
    Name: Kathryn Ba
    Date: 2002-10-08 15:33:20
    Link to this Comment: 3213

    Trial 1
    (Room Temp)

    0,0,0,0,0,.1,.2,.2,.4,.4,.4,1.1,1.3,1.5,1.5,1.8,2.0,2.2,2.2,2.3,2.4,2.6,2.8,2.8,2.8

    Reaction Rate: 0.7 O2/minute

    Trial 2
    (Increased Temp)

    0,.1,.4,.6,1.0,1.3,1.6,1.8,2.2,2.4,2.8,3.0,-,-,-,3.8,3.8,4.0,4.1,4.2,4.2,4.3,4.3,4.3

    Reaction Rate: .8 O2/minute

    Trial 3
    (Increased Temp)

    0,0,.2,.6,.8,1.0,1.4,1.6,1.8,2.2,2.4,2.8,3.2,3.2,3.2,3.2,3.5,3.8,4.0,4.0,4.1,4.1,4.2,4.2,4.3,4.3,4.3

    Reaction Rate: .8 O2/minute


    Our data shows that the reaction rate was slightly faster when the chemicals at higher temperatures. The amount of overall O2 volume was higher at the larger temp, however we only did one trial at room temperature, toconfirm this change we would need to do another trial at room temp. Our story is that the hightened temperature allowed for a faster reaction rate because the molecules were moving around faster. that's our story and we're sticking to it....for a while anyway.....



    Name: Yarimee Gu
    Date: 2002-10-08 15:36:57
    Link to this Comment: 3214

    Yarimee Gutierrez
    Joanna Robertson
    Ex #1 Ex #2
    15-0 15-0
    30-.1 30-0
    45-.2 45-.1
    60-.3 60-.1
    75-.4 75-.1
    90-1.0 90-.1
    105-.1.1 105-.1
    120-1.2 120-.1
    135-1.3 135-.1
    150-1.4 150-.1
    165-2.0 165-.2
    180-2.1 180-.2
    195-2.2 195-.2
    210-2.2 210-.2
    225-2.3 225-.3
    240-2.3 240-.3
    255-2.4 255-.3
    270-2.4 270-.3
    285-3.0 285-.3
    300-3.0 300-.3
    315-3.1 315-.3
    330-3.1 330-.3
    345-3.1 345-.3
    360-3.1 360-.3

    Rate of Oxygen produced:
    Ex 1 (control):0.6 cc/min
    Ex 2 (pH 2.0): 0.067 cc/min

    Observations:
    -Reaction rate significantly decreased.
    -x(plateu value) significantly decreased.
    Story- The pH level affects how the Catalase works.



    Name: Michele an
    Date: 2002-10-09 14:15:27
    Link to this Comment: 3226

    Heidi Adler-Michaelson & Michele Doughty

    Trial 1:
    .2, .4, .8, 1.2, 1.4, 1.6, 1.8, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0, 3.0, 3.2, 3.3, 3.4, 3.4, 3.5, 3.6, 3.6, 3.7, 3.8, 3.8, 4.0, 4.0, 4.0
    The rate of change is fairly constant for 4 minutes at an additional .2 cm for every 15 seconds. After 4 minutes it changes .2 cm for every 30 seconds until it stabilizes after 6 min 40 sec reaching 4.0 cm of oxygen in the tube.


    Breakin' Down H2O2 Baby!!!
    Name:
    Date: 2002-10-09 14:47:25
    Link to this Comment: 3227

    Melissa Brown and Roma Hassan

    Introduction:
    This experiment demonstrates the effects of the enzyme Catalase on hydrogen peroxide.

    Methods:
    We were given a nicely set-up apparatus consisting of a ring stand and a Scholander respirometer. We had two vials one of which was a control vial and the other was the experimental vial. In the control vial we put in 0.5cc of H2O2 and 4.5cc of pH 7.4 buffer and in the experimental vial we first put in 1.5cc of Catalase and 3cc of the buffer. The two vials were attached to the respirometer and then 0.5cc of H2O2 was injected into the experimental vial and the small plug was pushed in and at the same time the oxygen syringe was slowly pulled up and different volumes of oxygen were measured for different time intervals. The methods are the same for both trial 1 and trial 2.

    Observations:
    Trial 1
    Time/sec Volume O2
    15 .2
    30 1
    45 1.6
    60 2.2
    75 2.7
    90 3
    105 3.1
    120 3.2
    135 3.2
    150 3.4
    165 3.4
    180 3.6
    195 3.8
    210 3.8
    225 3.9
    240 3.9
    255 3.9
    270 3.9
    . .
    . .
    . .
    . .

    Trial 2(performed twice)
    Time/sec Volume O2
    15 .2/.4
    30 .9/.8
    45 1.4/1.4
    60 1.8/1.8
    75 2.2/2.0
    90 2.4/2.4
    105 2.7/2.7
    120 2.8/2.8
    135 3.0/3.0
    150 3.2/3.2
    165 3.2/3.3
    180 3.4/3.4
    195 3.6/3.5
    210 3.8/3.6
    225 3.9/3.8
    240 3.9/3.9
    255 3.9/3.9
    270 3.9/3.9
    . .
    . .
    . .
    . .

    Conclusion/ThE StoRY:
    Rate of Concentration= 1.6/2= 0.8cc of O2/min
    Our experiment remained the same, thus observations remained similar and hence we conclude with our rate of concentration and alas, no remarks on enzyme behavior!!!


    Lab 5
    Name: Brie Farle
    Date: 2002-10-09 14:50:31
    Link to this Comment: 3228

    Our results from experiment one were:
    DATA: .5, 1, 1.5, 2, 2.5, 2.9, 3, 3.5, 3.8, 4, 4, 4, 4.1, 4.1, 4.1, 4.1
    Our data was collected over a period of four minutes. This experiment was the first trial of adding .50 H2O2 to the experimental mixture, which contained 1.50 ml of Catalase and 3 ml of 7.4 Buffer for a total volume of 5.00 ml.

    Our results from experiment two were:
    DATA: .1, .5, 1, 1.5, 1.9, 2, 2.2, 2.4, 2.4, 2.6, 2.6, 2.6
    Our data was collected over a period of three minutes. This experiment was the first trial of adding .40 H2O2 to the experimental mixture, which contained 1.50 ml of Catalase and 3.10 ml of 7.4 Buffer for a total volume of 5.00 ml.

    Our results from the second trial of the same experiment were:
    DATA: .1, .5, 1, 1.4, 1.8, 2.1, 2.2, 2.4, 2.6, 2.6, 2.8, 2.8

    In the first experiment the rate we computed over two minutes was 1 O2/minute. In the second experiment the rate we computed over two minutes was .9 O2/min. When we add less H2O2, we ended up with less O2 per minute, but our rate was the same in both experiments. This means that the rate is independent of the amount of H2O2 that is added. Our conclusion is that the rate is determined by the enzyme that is added. Since the amount of enzyme was the same in both experiments, the rate should stay the same. Since it did, our conclusion has been proven.



    Name: Maggie Sco
    Date: 2002-10-09 14:59:56
    Link to this Comment: 3229

    Experiment 1:

    1.8, 2.1, 2.4, 2.7, 2.8, 2.9, 3.0, 3.1, 3.2, 3.25, 3.3, 3.3, 3.35, 3.4, 3.45, 3.5, 3.55, 3.6, 3.6, 3.6

    Experiment 4B:
    (Experiment 4 was using a buffer of 4.01 pH instead of the previously used pH level of 7.4)
    Trial 1: .2 cc after 15 seconds
    Trial 2: .2 cc after 15 seconds.

    In both of our trials for experiment 4, the brody shot up quickly, equalling .2 cc, but then stopped moving completely.

    This made us come to the conclusion that the higher the buffer's pH is, the longer the reaction will run, and the lower the buffer's pH is, the shorter the time of the reaction. This may mean that the lower the buffer's pH, the less effective the catalase (the enzyme) is at breaking apart the peroxide.

    Our rate = .2/15= .01333 cc/sec. However, this rate could be deceiving because while we took the first measurement at fifteen seconds, the oxygen had stopped moving before that.


    October 9th Lab
    Name: Annie S.,
    Date: 2002-10-09 15:05:32
    Link to this Comment: 3230

    Trial 1

    Time (seconds) / Volume of 02
    15 / -
    30 / -
    45 / 2.6
    60 / 3.0
    75 / 3.6
    90 / 3.8
    105 / 4.0
    120 / 4.2
    135 / 4.4
    150 / 4.6
    165 / 4.7
    180 / 4.8
    195 / 4.9
    210 / 4.9
    225 / 5.0
    240 / 5.0
    255 / 5.0
    270 / 5.0
    285 / 5.1
    300 / 5.1
    315 / 5.1
    330 / 5.1
    345 / 5.1
    360 / 5.1

    Trial 2

    Time (seconds) / Volume of 02
    15 / 0.8
    30 / 2.1
    45 / 2.4
    60 / 2.8
    75 / 3.0
    90 / 3.1
    105 / 3.2
    120 / 3.3
    135 / 3.4
    150 / 3.5
    165 / 3.6
    180 / 3.6
    195 / 3.7
    210 / 3.75
    225 / 3.8
    240 / 3.8
    255 / 3.85
    270 / 3.9
    285 / 3.9
    300 / 3.95
    315 / 4
    330 / 4
    345 / 4
    360 / 4

    Trial 3

    Time (seconds) / Volume of 02
    15 / 1.8
    30 / 2.2
    45 / 2.3
    60 / 2.6
    75 / 2.8
    90 / 3.0
    105 / 3.2
    120 / 3.25
    135 / 3.3
    150 / 3.4
    165 / 3.4
    180 / 3.5
    195 / 3.6
    210 / 3.6
    225 / 3.65
    240 / 3.7
    255 / 3.75
    270 / 3.8
    285 / 3.8
    300 / 3.85
    315 / 3.85
    330 / 3.85
    345 / 3.85
    360 / 3.9

    -We decreased the amount of H2O2 in the system, predicting that this decrease would produce less oxygen.
    -Our data proves there is a direct corrollation between the two variables.
    -Decrease in the amount H2O2 lowers the rate of oxygen production in relation to time from about 0.9 to approximately 0.425.



    Name: Heidi & Mi
    Date: 2002-10-09 15:07:01
    Link to this Comment: 3231

    Heidi Adler-Michaelson & Michele Doughty

    Trial A: (at room temperature)
    .2, .4, .8, 1.2, 1.4, 1.6, 1.8, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0, 3.0, 3.2, 3.3, 3.4, 3.4, 3.5, 3.6, 3.6, 3.7, 3.8, 3.8, 4.0, 4.0, 4.0
    The rate of change was fairly constant for 4 minutes at an additional .2 cm for every 15 seconds. After 4 minutes it changed .2 cm for every 30 seconds until it stabilized after 6 min 40 sec reaching 4.0 cm of oxygen in the tube.

    Our rate between 1 and 3 minutes was 0.80 O2 per minute.

    Trial B: (at heated temperature)
    test #1
    .3, .8, 1.3, 2.0, 2.4, 2.7, 3.0, 3.2, 3.4, 3.6, 3.7, 3.8, 4.0, 4.1, 4.2, 4.2, 4.3, 4.4, 4.4, 4.5, 4.6, 4.6, 4.6, 4.7, 4.8, 4.8, 4.8, 4.9.

    Our rate between 1 and 3 minutes was 0.90 O2 per minute.

    test#2
    .2, .8, 1.4, 2.0, 2.5, 2.8, 3.2, 3.4, 3.6, 3.8, 4.0, 4.1, 4.2, 4.4, 4.4 4.6, 4.6, 4.7, 4.8, 4.8, 4.9, 5.0, 5.0, 5.0

    Our rate between 1 and 3 minutes was 1.05 O2 per minute.

    ** Our average rate of O2 per minute for Trial B was 0.98***

    Discussion:
    With higher temperature the rate of the O2 per minute was greater than the rate of the room temperature by a difference in rate of 0.18 O2 per minute.


    We love Hiooouuueeee
    Name: MC the ama
    Date: 2002-10-09 15:07:58
    Link to this Comment: 3232

    Mer, Chels(ea)

    The control trial involved 1.5cc of the Catalase, 0.50cc of the Hydrogen Peroxide, and 3.00cc of the buffer. The readings were taken every 15 seconds.

    Our control set of data was as follows:

    .4, .8, 1.2, 1.6, 2, 2.2, 2.5, 2.6, 2.7, 2.8, 2.9, 3.0, 3.1, ~3.2, 3.2, 3.2,

    3.3, 3.3, 3.4, 3.4, 3.4


    Our next trials involved 0.6cc of Hydrogen Peroxide, 2.9cc of the buffer, and the enzyme remained constant at 1.5cc. The rate from our first trial (for minutes 1-3) was 0.7cc/minute of oxygen; the rate from the data set below with the increased amount of Hydrogen Peroxide is 1cc/ minute. Our data for the second set was as follows:

    .3, 1.0, 1.8, 2.4, 2.8, 3.2, 3.5, 3.7, 3.9, 4.1, 4.2, 4.4, 4.4, 4.5, 4.6,

    4.7, 4.8, 4.8, 4.9, 5.0, 5.0, 5.1, 5.2, 5.2, 5.2

    Based on our scientific observations, we have concluded that increasing the amount of HP added to the enzyme increases the rate at which oxygen converts to a gas. NOTE: Although the time is different on each of these trials, we feel that it is not really legitimate to say that the amount of HP affects time as well because our first trial was shorter than the control.


    Hydrogen Peroxide and Catalase Lab
    Name: Chelsea an
    Date: 2002-10-09 15:09:28
    Link to this Comment: 3233

    Trial 1:
    Time (in seconds) -- Volume of Oxygen (in mL)
    15 -- .2
    30 -- .6
    45 -- 1.2
    60 -- 1.8
    75 -- 2
    90 -- 2.4
    105 -- 2.6
    120 -- 2.8
    135 -- 3.0
    150 -- 3.2
    165 -- 3.2
    180 -- 3.4
    195 -- 3.6
    210 -- 3.6
    225 -- 3.8
    240 -- 3.8
    255 -- 3.9
    270 -- 4.0
    285 -- 4.0
    300 -- 4.0
    Rate of Reaction: .8 mL of Oxygen/minute

    Summary of Data from Trial 2 (with same substances, but chilled):
    Volume of Oxygen: .2, .2, .6, .8, 1, 1.2, 1.6, 1.8, 2, 2, 2.2, 2.4, 2.4, 2.6, 2.6, 2.8, 2.8, 3.0, 3.0, 3.0, 3.2, 3.2, 3.2, 3.3, 3.3, 3.4, 3.4, 3.4, 3.5, 3.6, 3.6, 3.6, 3.7, 3.7, 3.8, 3.8, 3.8, 3.8, 3.8,3.8, 3.8
    Rate of Reaction: .3 mL of Oxygen/minute

    Summary of Data from Trial 3 (with same substances, but chilled):
    Volume of Oxygen:.2, .4,.8, 1. 1.4, 1.7, 2, 2.2, 2.4, 2.6, 2.8, 3.0, 3.0, 3.2, 3.4, 3.6, 3.6, 3.7, 3.8, 3.8, 3.9, 4.0, 4.0, 4.0, 4.1, 4.1, 4.1, 4.1, 4.2, 4.2, 4.2, 4.2
    Rate of Reaction: .3 mL of Oxygen/minute

    Cooler temperatures mean slower molecules. Thus, when all the solutions were chilled, their slower molecular movement accounts for the drop in reaction rate. Rock on.



    Name: Adrienne &
    Date: 2002-10-09 15:10:01
    Link to this Comment: 3234

    Adrienne & Laura B.

    First Data Set:
       Vol. O2 in 15 sec. increments:
          .7, 1.9, 2.3, 2.6, 2.8, 2.9, 2.9, 2.9, 2.9, 2.9, 2.9

    Second Data Set:
       Vol. O2 in 15 sec. increments with pH 2.0:
          Trial #1: .2, .2, .3, .4, .4, .5, .7, .9, .9, .9, .9, 1.0, 1.0, 1.0, 1.1, 1.1, 1.1, 1.1, 1.1
          Trial #2: .7, .7, .8, .9, .9, .9, .9, .9, 1.0, 1.0, 1.0, 1.0, 1.1, 1.1, 1.1, 1.1, 1.1, 1.2, 1.2

          Trial #1 Reaction Rate = .05 O2 per minute
          Trial #2 Reaction Rate = .1 O2 per minute

    The Story:
    According to our observations, a change in the pH of the buffer slows the reaction down. The first experiment that we did as a class with a pH 7.4 buffer had an average reaction rate of about .7 O2 per minute, while our experiment with a pH 2.0 buffer had a reaction rate of about .075 O2 per minute.


    Hydrogen Peroxide
    Name: Lawral and
    Date: 2002-10-09 15:12:11
    Link to this Comment: 3235

    Larwal Kenrow and Annaoj Nosugref


    Experiment #1:
    All measurements were taken at 15 second intervals.
    .8, 1, 1.2, 1.6, 2, 2.4, 2.5, 2.7, 2.8, 2.9, 3, 3, 3.1, 3.2, 3.2, 3.2
    The solution reacted for 4 full minutes (240 seconds).

    Experiment #4c:
    3.00cc of pH 10.4 buffer was added to the original experiment.
    All measurments were taken at 15 second intervals.
    .6/.6, .8/.8, 1/1.2, 1.3/1.4, 1.6/1.7, 2/2, 2.2/2.3, 2.4/2.6, 2.7/2.8, 2.9/3, 3.1/3.2, 3.2/3.4, 3.4/3.5, 3.5/3.6, 3.6/3.8, 3.7/3.9, 3.8/4, 3.8/4.1, 3.9/4.2, 4/4.3, 4/4.4, 4.1/4.4, 4.2/4.4, 4.2, 4.2
    The solution reacted for 375sec/345sec.

    When a higher pH was added to the experiment, the solution reacted for a longer time. The rate of reaction was also higher. In the original solution, the rate of reaction was .4 O2/min. The average rate for the experiment with the added pH was .692 O2/min. The higher pH level is condusive to the reaction; it helps remove more oxygen for a longer amount of time.


    Not just for hair
    Name:
    Date: 2002-10-09 15:16:13
    Link to this Comment: 3236

    Diana DiMuro
    Erin Myers

    Volume Gas reading every 15 seconds (ml)
    Experiment 1: 0.2, 0.4, 0.8, 1.4, 1.6, 2.0, 2.2, 2.5, 2.7, 2.8, 2.9, 3.0, 3.1, 3.2, 3.2, 3.3, 3.4, 3.4, 3.4, 3.5, 3.6, 3.6, 3.6, 3.6
    rate volume O2/min (0-2mins): 1.3
    rate volume O2/min (1-3mins): 0.8
    rate volume O2/min (1-4mins): 0.633


    Experiment 3 increase in amount of calalase
    3a: 0.6,1.4,2.0,2.4,2.8,3.1,3.2,3.4,3.5,3.6,3.7,3.8,3.8,3.8,3.9,4.0,4.0,4.1,4.2,4.2,4.2,4.2

    rate volume O2/min (0-2mins): 1.7

    3b:
    0.4, 0.8, 1.4, 2.0, 2.4, 2.7, 2.8, 3.0, 3.0, 3.1, 3.2, 3.2, 3.4, 3.4, 3.5, 3.6, 3.6, 3.6, 3.6

    rate volume O2/min (0-2mins): 1.5
    rate volume O2/min (1-3mins): 0.7

    3c:
    0.8, 1.6, 2.2, 2.6, 3.0, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.8, 3.9, 4.0, 4.1, 4.1, 4.1, 4.2, 4.2, 4.2

    rate volume O2/min (0-2mins): 1.7

    An increase in the amount of calalase yielded an increase in the rate of production of O2 gas. It did not yield more O2 gas.


    enzyme numbers
    Name: Diana and
    Date: 2002-10-09 15:25:03
    Link to this Comment: 3237

    Trial 1:
    x (not recorded), .7, 1.1, 1.6, 2.1, 2.4, 2.7, 2.9, 3.1, 3.3, 3.4, 3.5, 3.5, 3.6, 3.7, 3.8, 3.8, 3.9, 4.0, 4.0, 4.1, 4.1, 4.2, 4.2, 4.2
    total time: 3 minutes
    Rater from minute 2 to minute 5: .4 O2/minute

    Trial 2 (less enzyme):
    .2, .3, .4, .6, .8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0, 2.2, 2.4, 2.5, 2.6, 2.8, 2.9, 3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.5, 3.6, 3.7, 3.7, 3.8, 3.9, 3.9, 4.0, 4.0, 4.0
    total time: 8 minutes 15 seconds
    Rate from minute 2 to minute 5: .6 O2/minute

    Trial 3 (less enzyme):
    .1, .2, .3, .4, .6, .75, .9, 1.1, 1.3, 1.5, 1.8, 1.9, 2.1, 2.2, 2.4, 2.6, 2.8, 2.9, 3.0, 3.1, 3.2, 3.4, 3.5, 3.6, 3.7, 3.8, 3.8, 3.9, 4.0, 4.1, 4.2, 4.2, 4.3, 4.3, 4.3
    total time: 8 minutes 45 seconds
    Rate from minute 2 to minute 5: .66 O2/minute

    Trial 4 (less enzyme):
    .0, .1, .2, .4, .5, .6, .8, 1.0, 1.1, 1.3, 1.4, 1.6, 1.8, 1.9, 2.0, 2.2, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3.0, 3.05, 3.1, 3.3, 3.4, 3.45, 3.6, 3.6, 3., 3.8, 3.9, 4.0, 4.0, 4.0
    total time: 9 minutes
    Rate from minute 2 to minute 6: .56 O2/minute



    Name: Maggie
    Date: 2002-10-22 14:50:39
    Link to this Comment: 3315

    Katie Campbell, Steph Lane, Kate Amlin, Margaret Hoyt, Kyla Ellis

    Experiment 1

    Initials Base Line Rate Exercise Rate

    KC 54 78
    SL 72 110
    KA 70 128
    MH 74 118
    KE 68 122


    Experiment 2

    Hypothesis:
    We hypothesized that if a person would hold their breath, their resting heart rate would be lower than when breathing normally.

    Data:
    We used MH as our lab rat, particularly because she had a really strong beat. We recorded her resting heart rate while breathing normally 3 times before we recorded the heart rate while she held her breath. We then did another trial where MH breathed normally just to make sure her heart rate hadn't dropped while breathing normally.

    trial 1 (breathing normally)
    94
    86
    84

    trial 2 (holding breath)
    64
    68
    64

    trial 3 (breating normally)
    92
    93
    90

    Conclusions:
    Because MH's heart rate dropped while she held her breath, the obvious conclusion is that breathing makes the heart beat faster. Therefore, the process of respiration requires oxygen and a faster heart beat.


    HR lab
    Name: Amanda, Di
    Date: 2002-10-22 14:58:03
    Link to this Comment: 3316

    We chose to examine emotional state and how it affects heart rate. We thought of something exciting, and something calming, then as a side experiment we smoked a cigarette and observed how that affected our heart rate. Mande: Resting HR: 66bpm Excited thought: 66bpm, 68bpm, 68bpm Calming thought: 64bpm, 62bpm, 66 bpm Cigarette: the reading was too low to distinguish peaks Diana: Resting HR:88bpm Excited thought: 96,84,88 Calming thought: 94, 86,87 Cigarette: The reading was too low to distiguish peaks We found that altering our thoughts had little to no effect on our HR. This may be due to outside distractions making a fully calmed or excited state difficult to attain. The cigarette seemed to greatly lower our the height of the peaks, yet it may be due to ineffective use of the equipment.


    Heart Rates
    Name:
    Date: 2002-10-22 14:58:57
    Link to this Comment: 3317

    Brenda Zera Elizabeth Damore

    We ran a couple of trials to test the effects of different influences on heart rates. First, we experimented with the effect of laughter on heart rate. We found that the heart rate didn't vary overall, but it spiked when the subject laughed. This may be due to the motion caused by laughing. Next, we experimented with the effect of raising an arm over the head on heart rate. The heart rate quickened slightly, along with an increase in pressure. However, the heart rate was not significantly affected by either of these changes.


    Sarah Tan is a rock
    Name:
    Date: 2002-10-22 14:59:01
    Link to this Comment: 3318

    Heart Rate-
    Sarah Tan 82 beats per min.
    Heather Price 76 beats per min.
    Margot Rhyu 84 beats per min.

    After exercise
    Sarah 136 beats per min.
    Heather 152 beats per min.
    Margot 146 beats per min.

    Sarah after being "scared"- There was no effect on her heart rate after Grobstein screamed. Her heart rate stayed the same.

    Heather held her breath for thirty seconds. Her heart rate increased to 96 beats per min. but the pressure decreased.

    Margot thought sad thoughts for thirty seconds. We showed her a sad picture, thus making her heart rate slow down to 80 beats per min.

    Our story about heart rates is that they increase or decrease depending upon both physical and emotional stimuli.


    Heart Rate
    Name: Kathryn, S
    Date: 2002-10-22 15:00:46
    Link to this Comment: 3319

    ..............................Kathryn.....Sarah
    Base Line......................86..........70
    Exercise.......................136.........100
    Emotional Thoughts.............88..........86
    Thinking of lowering hr........92..........74
    Holding Breath.................84..........90

    Any sort of heightened stimulation requires a higher heart (more oxygen) because internal functions are in a more active state- for example, there is more going on in your brain, you blush, you sweat, stomach gets tight, you laugh....etc. By the same logic, a relaxed state , or a conserted effort to lower the heart rate, should have been sucessful in slowing the functions. However, the conditions of the experiment were less than ideal, random, noise, movements and other exterior stimulants and distractions most likely played a role in theresults nd the abiity to concertrae on specific emotional or mental states.


    Heart rate
    Name: Yarimee
    Date: 2002-10-22 15:20:20
    Link to this Comment: 3320

    Virginia Culler
    Joanna Robertson
    Jennifer Rusk
    Yarimee Gutierrez

    Base Rate:
    Virginia-> 94
    Yarimee -> 82
    Jen -> 70
    Joanna -> 80

    After 2 min of rigorous exercise
    V-> 102
    Y-> 150
    Je->96
    Jo->96

    Hypothesis:
    -Increases with exercise because of the need for more oxygen.
    -Increases due to need to rid body of carbon dioxide.

    Holding Breath
    Virginia -> 144
    Jen -> 64

    Emotions
    Joanna-> when told to imagine a happy scenario heart beat increased
    Virginia-> when told to imagine a frightening senario heart rate increased a very small amount.

    Food for thought:
    -Maybe caffein and nicotine affect heart rate?
    -relaive body health affects heart rate? (prior Knowledge)


    Heart rate measurements
    Name:
    Date: 2002-10-23 14:44:46
    Link to this Comment: 3325

    Roma Hassan, Melissa Brown and Adrienne Wardy

    Hypothesis: A person's heart rate varies from its base rate due to activity (eg. exercise), emotion (eg. fear) etc.

    Observations: A converter and a computer program called SuperScopeII was used to measure the heart rates at different stages for 30 seconds of three human subjects and then the different measurements were recorded.

    AVG. RESTING HEART RATES:
    Roma: 92 beats/min
    Melissa: 83 beats/min
    Adrienne: 91 beats/min

    HEART RATES AFTER VIGOROUS EXERCISE:
    Roma: 154 beats/min
    Melissa: 156 beats/min
    Adrienne: 252 beats/min

    HEART RATES AFTER A PARTICULAR EMOTIONAL EXPERIENCE:
    Roma (after Melissa pinched her hand HARD!!): 111 beats/min
    Melissa (after thinking happy thoughts of going home): 96 beats/min
    Adrienne (after trying very hard to think sad thoughts): 111 beats/min
    Adrienne (after practising yoga breathing): 87 beats/min
    Melissa (after holding her breath): 105 beats/min
    Roma (after letting her head hang upside down): 87 beats/min

    Conclusion: A person's heart rate does indeed vary from its resting stage with changes in physical activity or emotional state of mind. As physical activity is increased more oxygen is required, hence the heart rate increases to allow for that. As for emotional state, depending on a particular emotion a person's heart rate may increase or decrease from normal. Yoga breathing and letting one's head hang upside down causing the blood to rush to it decreases heart rate while holding one's breath increases it. For further research one can look into changes in heart rate after consumption on different levels of nicotine, caffeine, alcohol etc. That should provide an interesting perspective on the effects of different chemicals in the blood system on a person's heart rate.


    Heart Rate Lab
    Name: Bobbi, Ros
    Date: 2002-10-23 15:10:29
    Link to this Comment: 3327

    Basically, we took heart rates for each person in the group, under different circumstances. We came up with this data:

    Resting Heart Rate

    Bobbi: 66 / min.
    Rosie: 70 / min.
    Catherine: 88 / min.
    Annie: 88 / min.

    "Vigorous" Exercise Heart Rate

    Rosie: 116 / min. Catherine: 142 / min.

    "Irritation" Heart Rate

    Catherine: 98 / min.

    Relaxation Heart Rate

    Rosie: 65 / min.

    Hypothesis: Anxiety raises heart rate, while relaxation lowers it.
    Our resting heart rates were taken first; the variations in our data show that there are different conditions which affect heart rate, so we decided to test one variation per person in the group.
    Our data shows that heart rate is affected by mental state; it increases with irritation/anxiety, and lowers with more relaxed state. Our systems are obviously all interconnected, and change in one area causes changes in others.
    The hypothesis was correct in this experiment.


    Heart Rate
    Name:
    Date: 2002-10-23 15:11:18
    Link to this Comment: 3328

    The Scientists: Emily S., Maggie S.-W., Chelsea R., and Laura B.

    Observations:

    Heart Rate (in beats per minute)

      Resting Heart Rate After 2 mins. Vigorous Exercise While Holding Breath (Trial 1) While Holding Breath (Trial 2)
    Laura 82 156 88 90
    Emily 78 126 96 84
    Chelsea 98 106 104 90
    Maggie 86 140 74 72

    Hypothesis: We all agreed that we thought our heart rates would increase after exercising. When coming up with a hypothesis for what would happen to our heart rate when we held our breath, however, some of us thought that heart rate would increase and some of us thought that heart rate would decrease.

    Putting it all together: According to the observations made by the class, our hypothesis that heart rate would increase after exercise appears to be true. However, we could not really conclude anything based on our observations of heart rate while holding one's breath. We measured our heart rate while holding our breath for 30 seconds, and some of our heart rates increased and the others decreased, so we cannot really conclude anything. Those of us who thought that heart rate would decrease while holding our breath, thought that because we thought that heart rate was dependent on oxygen intake and when you stop taking in oxygen (i.e.: hold your breath) your heart rate should decrease. Those of us who thought that heart rate would increase thought that because we thought that the heart would pump faster because the heart would try to get all the remaining oxygen in the lungs distributed to the body in an attempt to start the breathing process again.


    Heart Rate Lab
    Name:
    Date: 2002-10-23 15:19:23
    Link to this Comment: 3329

    Mer
    Heidi
    Will
    Diana
    Chelsea


    Our base heart rates are as followes:

    MS- 98 (just came from badminton)
    HAM- 72
    WSSC- 72
    DGL- 84 (fasting for last two days)
    CLP- 78 (drank coke)


    Exercise:

    MS- 146
    HAM- 102
    WSSC- 128
    DGL- 178
    CLP- 152

    Hypothesis: Caffine will increase heart rate, as it is a stimulant.
    Caffine:

    MS- control 101

    HAM- 76 (weaker beats)
    WSSC- 82 (stronger beats)
    DGL- 96
    CLP- 92 (stronger beats)

    Massage:

    MS- 88

    Thinking happy thoughts:

    CLP: 88 (after coffee)

    Laughing:

    CLP: 128 (after coffee)

    In conclusion, we feel that caffine increases heart rates, massage decreases, and so does thinking happy thoughts. Laughing we feel was affected by the movement of the hands as well.

    THE END. yummy cooooooffeeeeeeeeeeeee:)


    Hot damn. Pump it up, yo.
    Name: see below,
    Date: 2002-10-23 15:20:39
    Link to this Comment: 3330

    This lab has been a production of the aortas of:
    Lauren "HTML this, hizzo!" Friedman, Jodie "I'm... healthy?" Ferguson, Carrie "Bring On da Drizzugs" Griffin, Lawral "Don't Mess With Me" Wornek

    Heartbeat.
    booooom.
    Name Resting Vigorous Exercise Cigarette Coffee Cigarette + Coffee Cigarette + Stairs
    Lauren8615092------
    Jodie72160--84----
    Carrie84130----86--
    Lawral90126------108



    (1) Everyone has a different resting heart rate (RHR). There are a number of factors in what determines each person's RHR, so this makes sense. These factors include but are not limited to: fitness level, smoker/non-smoker, and genetic predisposition. (Noting the variation in the chart above, Jodie's low RHR may be attributed to the fact that she plays rugby, and Lawral's ridiculously [and possibly unhealthy] high RHR may be attributed to the fact that she is a smoker.)

    (2) When a person exercises, their heartbeat goes up to provide more oxygen to the body.

    (3) Different factors for our final test altered our heart rates in varying ways. We expected all of our heart rates to go up in varying increments, which they did.


    Caffeine, Massage, Nicotine
    Name:
    Date: 2002-10-23 15:23:46
    Link to this Comment: 3331

    Erin Myers
    Michelle Doughty
    Diana DiMuro
    Brie Farley


    Resting Rates
    Erin: 80bpm
    Michelle: 80bpm
    Diana: 82bpm
    Brie: 82bpm

    Post-Exercise (2 min. vigorous stair-running)
    Erin: 128bpm
    Michelle: 146bpm
    Diana: 132bpm
    Brie: 124bpm


    Relaxation Techniques


    Sleeping

    Michelle: 66bpm
    Diana: 88bpm (recently exercised, medication)

    Massage

    Erin:
    pre-massage: 102bpm (recently exercised)
    Brie:
    pre-massage: 94bpm (recently exercised)

    Erin:
    post-massage: 92bpm
    Brie:
    post-massage: no change (new noise in room)

    Exciting Techniques

    Cigarette

    Michelle:
    pre-cigarette: 80bpm
    post-cigarette: 78bpm

    Coffee

    Erin:
    pre-coffee: 86bpm
    post-coffee: 88bpm (immediately after consumption)


    CONCLUSIONS!

    Context in environment has strongly affected our results. (noise in room, etc.) For the most part, relaxation techniques of sleep and massage lowered bpm, exercise raised bpm, and coffee and nicotine had trivial results.


    reaction lab
    Name: Diana and
    Date: 2002-10-29 15:07:09
    Link to this Comment: 3414

    Diana and I wondered if the timing of reactions to tactile stimuli wa dependent upon whether the signals had to travel far to reach the brain. therefore, we decided to create an experiment in which we poked different parts of the body (both right and left side to eleminate possible tactile dominance one side may have) that represented different legnths form the brain. Our results were as follows:L

    Right side Left side
    Diana : Feet- .291 .141
    Shin - .125 .114
    hands - .055 .016
    chest - .231 .041
    head - .022 .062
    Mande : feet - .244 .231
    shin - .248 .247
    hands - .281 .278
    chest - .197 .091
    head - .092 .073
    Our hypothesis held true for mande ,the closer we moved to the brain, the faster the reaction time. For Diana, either she doesn't have a brain or ah aha, or our hypothesis does not hold true. Notably, the reaction times for Diana's head and hands were similar indicating that perhaps the amount of nerve endings have an effect on the time of a reaction from a tactile stimulus.


    Tactile test
    Name: Brenda and
    Date: 2002-10-29 15:11:14
    Link to this Comment: 3415

    Brenda Zera Elizabeth Damore

    We ran the tactile test multiple times, focusing on the differences a change in the location of the touch would make in reaction time. All tests run on bare skin.

    Muscle reaction time: .076

    First Location (10 trials): HAND- Average reaction time: .0318

    Second Location (5 trials): LOWER ARM- Average reaction time: .0616

    Third Location (5 trials): FOREHEAD- Average reaction time: .0078

    Fourth Location (5 trials): LOWER LEG- Average reaction time: .0128

    We concluded that the reaction time was not much affected by the changing of locations, with the exception of the forehead.


    reaction time
    Name:
    Date: 2002-10-29 15:14:49
    Link to this Comment: 3416

    Our initial results were:
    Auditory
    CT - 0.194
    HP - 0.179
    LS - 0.207

    Visual
    CT - 0.212
    HP - 0.250
    LS - 0.239

    Tactile
    CT - 0.226
    HP - 0.207
    LS - 0.273

    Muscle Contraction Time
    CT - 0.078
    HP - 0.074
    LS - 0.086

    Based on our results, we believe that our anticipation and the expectation of the sound/visual/tap may have accounted for some of our faster reaction times. We hypothesize that if the subject was preoccupied and could not hear the click of the mouse, then the reaction time would be slower and more accurate to what it would be without any anticipation.

    We took our test subject (Heather) and put headphones on her while she tried to memorize a poem in Russian. The stimuli (taps and beeps) were given at random to help create a more realistic reaction. Our results are as follows:

    Audio: 0.331, as opposed to the previous experiment's result of 0.179
    Tactile: 0.286, as opposed to the previous experiment's result of 0.207

    We believe that our results would be more accurate given a more realistic setting. The more the subject is consumed with their present activities the slower their reaction time becomes.

    Christine Traversi
    Heather Price
    Laura Silvius


    Response Times
    Name: The Ks
    Date: 2002-10-29 15:22:20
    Link to this Comment: 3418

    Kyla Ellis, Kate Amlin, Katie Campbell

    Experiment One-
    Reaction Time to Beeps, Pokes, and Flashing things...
    (All numbers in milliseconds)

    Kate
    Aud median-
    186
    Vis median-
    183
    Tac median-
    126
    Median Muscle contraction time-
    49

    Katie
    Aud median-
    202.5
    Vis median-
    213
    Tac median-
    158.5
    Median Muscle contraction time-
    63

    Kyla
    Aud median-
    202.5
    Vis median-
    238.5
    Tac median-
    260.5
    Median Muscle contraction time-
    70

    Experiment 2
    Location of Poke!!! Our next inquiry is what difference in response time does it make if you are poked on different places of your body?
    Our points of inquiry will be
    finger tips
    back of the hand
    palm of the hand
    face (forehead)
    Experiment 3
    Then we will test out random placements on the body and see what kind of variation in response time occurs.

    Each place was tested with ten trials, all on Kate.
    #2
    Collected Data:
    Finger Tips
    302, 123, 108, 7.81x10^-3, 178, 55, 78, 109, 155, 244
    Median-116
    Back of Hand
    119, 119, 97, 184, 59, 130, 161, 270, 192, 122
    Median-126
    Palm of Hand
    127, 139, 122, 127, 172, 142, 114, 152, 130, 170
    Median-134.5
    Face (Forehead)
    25, 178, 166, 142, 144, 164, 284, 134, 127, 112
    Median-143
    #3
    Collected Data:
    Random Placements
    back of hand-195
    right bicep- 180
    right quadracep- 194
    right elbow- 227
    right calf- 203
    right side of head- 164
    right forearm- 205
    forehead- 120
    left calf- 212
    left bicep- 166

    Conclusions:
    #2- The fastest reaction time was for the finger tips. The slowest reaction time was for the face (forehead). We assume from this experiment that reaction time varies for different physical locations, and that areas with faster reaction times have more nerve endings.

    #3- The subject did not know where she would be poked and therefore could not anticipate the sensation. This affected her reaction time -- in general the reaction times are longer than the medians for experiment #2 (the anticipated areas). We realize that we did not perform an adequate amount of tests (due to time constraints) but we believe that the data gives us reason to conclude temporarily as such.



    Name: katheryn b
    Date: 2002-10-29 15:22:28
    Link to this Comment: 3419

    general sense testing:


    ........auditory...........visual..........tactile........muscle contracion
    kb......0.91...............0.110...........0.292..........0.059
    sf......0.225..............0.300...........0.1835.........0.0405

    These are the medians of ten trials. The data shows that there is visaul difference. The visual seems to be slightlyslower than the auditory, however the tactile is not consistantly faster or slower than either of the other two tests. This is not suprising becuase there are only two subjects.... the trends were much more easily seen after looking at the class's data.

    different places on the body

    .......head..........finger tips........shins
    kb.....0.334.........0.300..............0.315
    sf.....0.1735........0.159..............0.1615

    the response times for the finger tips were faster for each of us. this may be because we use this our fingers for touch more regularly and are therefor conditioned to respomd quickly to touch there, or we may have more sensory equipment for touch on our finger tips either on the the fingertips or in the wiring of the sensors to the brain. again it may be helpful to see trends in a larger tested group. our original hypothesis that distance from the brain would have a direct relationship to the response times of the sensory stimulas.


    Reaction Time in Body
    Name: Yarimee, J
    Date: 2002-10-29 15:35:44
    Link to this Comment: 3420

    Yarimee Gutierrez
    Sarah Tan
    Jen Rusk

    Body reaction time to different "triggers"

    SARAH:
    Auditory-.159
    Visual-.137
    Tactile-.175
    Muscle contraction-.044

    Yarimee:
    Auditory-.260
    Visual-.206
    Tactile- .109
    Muscle contraction- .049

    Jen:
    Auditory-.100
    Visual- .131
    tactile- .166
    Muscle contraction- .044

    from these results, it is obvious that there is something else that plays into reaction time because muscle contraction only accounts for a very small number in this.

    We attempted to account for some of the other reasons for the reaction time. Jen experimented with being poked in different areas of the body, with her eyes closed so that she could not expect where we would poke her next. She was testing whether not knowing where she would be poked would affect reaction time because in the original tests, all pokes were limited to the forearm. Yarimee tested reactions time with her glasses off, and Sarah tested with her glasses off and sat about 7 feet away. Both the visual tests were to determine whether reaction time would be affected by how clearly we could see the pop-up box. We hypothesized that reactions times for all the tests we chose would increase.

    Mean results:
    Jen- .316
    Yarimee- .216
    Sarah- .200

    Conclusion: As it turned out, our hypotheses were right, and reaction times increased with the varying tests. The difference between Yarimee and Sarah's original and new reaction times especially proved that not being able to clearly see the visual stimulus affected reaction time because Sarah's reaction time greatly increased when she could barely see the screen, and Yarimee's reaction time slightly increased, and she was much closer to the screen.


    visual stimuli and such
    Name:
    Date: 2002-10-30 15:00:15
    Link to this Comment: 3426

    Roma Hassan, Melissa Brown, Adrienne Wardy and CR

    Introduction: An experiment was carried out to see if the right and left hands respond differently to visual stimuli. Our hypothesis is that the right-hand responses will be faster than the left-hand ones.

    Methods: We used an analogue digital input-output system and a computer program called SuperScope to measure the reaction times of the left and right hands to visual stimuli.
    Observations:

    Avg. right-hand response to visual stimuli :
    RH-.1940ms
    MB-.2356ms
    AW-.3410ms
    CR-.1870ms

    Avg. left-hand response to visual stimuli :
    RH-.2099ms
    MB-.2777ms
    AW-.3228ms
    CR-.2712ms

    Conclusions: Since we are all right -handed, we are more comfortable using our right- hands than our left -hands. Therefore we can't determine whether variation between the right-hand responses and the left -hand responses resulted from being conditioned for right-hand usage or by some other factor such as inheritance. This experiment could have been modified to test visual stimuli responses for the right and left eyes too.


    Tests
    Name: Brie, Erin
    Date: 2002-10-30 15:18:23
    Link to this Comment: 3428

    First we did four tests along with the rest of the class, and these are our results and averages:

    Visual Test
    A) 161, 173, 167, 198, 170, 169, 217, 461, 205, 167, 137
    Average: 222.5
    B) 184, 167, 134, 166, 127, 128, 214, 130, 162, 152
    Average: 156.3
    C) 192, 155, 161, 208, 172, 148, 172, 156, 162, 172
    Average: 170
    D) 181, 164, 114, 137, 152, 231, 209, 209, 117, 145
    Average: 187.4

    Auditory
    A) 122, 173, 108, 78, 144, 86, 91, 147, 52, 122
    B) 117, 214, 155, 102, 162, 137, 131, 116, 92, 102
    C) 139, 117, 120, 142, 109, 112, 117, 112, 153, 142
    D) 122, 139, 203, 134, 95, 106, 197, 91, 97, 117, 97

    Double Time
    A) 37
    B) 38
    C) 39
    D) 34

    Tactile
    A) 155, 127, 123, 144, 119, 156, 127, 155, 155, 123
    B) 207, 136, 145, 150, 152, 159, 156, 139, 128, 114
    C) 155, 158, 145, 170, 173, 156, 197, 152, 167, 145
    D) 297, 141, 250, 147, 212, 220, 109, 194, 294, 286

    Our Own Idea

    Basically, our idea was to pretend we were talking on cell phones while driving our cars... it was an audio interference to visual. Basically, we had slower reaction times.
    A) 317, 286, 470, 295, 247
    Average: 323
    B) 466, 308, 406, 197, 475
    Average: 370.4
    C) 408, 362, 256, 264, 227
    Average: 303.4
    D) 436, 194, 225, 234, 277
    Average: 273.2


    Strangely, the people who seemed to have faster reaction times when there was only one stimulus were slower when there was more than one distraction.



    Name: CLP
    Date: 2002-10-30 15:20:13
    Link to this Comment: 3429

    Michelle, Diana, Heidi, Mer, Chelsea

    The first experiments (aud, vis, tactile, muscule contraction)
    were done with everyone and are as follows:

    Heidi- .0986 .168 .1626 .0674
    Chelsea- .111 .204 .1728 .0396
    Mer- .1312 .1562 .544 .0396
    Diana .148 .1852 .191 .0804
    Michelle- .1686 .3046 .215 .0784

    Heidi and Chelsea did three separate experiments. First, they performed a conrol, second they recorded their response times while having a conversation, and lastly, Mer joined them for a stimulating intellectual conversation.

    CONTROL
    Chelsea- .1982
    Heidi- .0962

    Conversation (Heidi and Chelsea)
    Chelsea- .2557
    Heidi- .2396

    Conversation #2 (Heidi, Mer, Chelsea)
    Chelsea- .2232
    Heidi- .1651

    Any active distraction increases reaction time, and when two distract a third, concentration is still affected, but slightly less than talking to only one other person. We believe this is because it takes less concentration to follow a conversation involving three people than two (you actually have to listen when you are the only one expected to respond to the other person's comments).



    Name:
    Date: 2002-10-30 15:21:53
    Link to this Comment: 3431

    Maggie S-W, Emily Senerth, Laura Bang

    Our initial results were:

      Auditory Visual Tactile Muscle Contraction
    Maggie 0.1372 0.1831 0.1512 0.035
    Emily 0.1669 0.2264 0.1437 0.059
    Laura 0.2279 0.2744 0.3692 0.069

    For the second experiment we each did different things to play around with the visual test. Emily and Maggie did the test with their right hand, and alternated which eye they covered. Laura did the test without her glasses on. Emily has contact lenses, and Maggie should have glasses but doesn't. And Laura's glasses aren't very strong, so she can still see fairly well without them, it's just a bit fuzzy.

    Both of Maggie's second trials were faster, but only by about 0.005 seconds. Since this is such an insignificant difference, covering one eye probably didn't really effect the outcome. Both of Emily's second trials were faster than her original times as well -- her right eye/right hand was 0.02 seconds faster, and her left eye/right hand was 0.007 seconds faster. Laura's results from her second trial averaged about 0.03 seconds slower.

    Laura's slower results without her glasses is what we expected, since it seems reasonable that the sharper your vision is the faster you would be able to react. However, her results are the only ones that really support this hypothesis. Maggie's vision is slightly worse when she closes one eye, so we expected her results to be slower, but her reaction time was about the same. Emily should have 20/20 vision in each eye since she has contacts, so seeing out of one eye shouldn't have effected her reaction time. We believe the decrease in her reaction time is due more to familiarity with the test than improved vision.



    Name: Rosie, Ana
    Date: 2002-10-30 15:26:04
    Link to this Comment: 3432

    Name:Rosie, Anastasia, Annie
    Username:Anonymous
    Subject:
    Date:2002-10-30 15:04:43
    Message Id:3427
    Comments:
    For the first experiment, we tested Audio, Visual, and Tactile reaction times. Our results were:
    Anastasia: Audio - .1488
    Visual - .1549
    Tactile - .1495
    Muscle contraction - .058

    Rosie: Audio - .2211
    Visual - .2293
    Tactile - .1919
    Muscle contraction - .07

    Annie: Audio - .142
    Visual - .2416
    Tactile - .1637
    Muscle contraction - .044

    For the second experiment we first tested Audio when one person was having a conversation with the person who was being tested.
    The average reaction time for this was .2186.

    We then tested the reaction time for Touch when the person's eyes were closed and they were hit randomly anywhere on their body. The average reaction time for this was .1638.

    Finally we tested the reaction time Visually. The person watched the screen with only one eye open. The reaction time for only the right eye was .3008 and the reaction time for the left eye was .2374. The person was using their right hand to click.

    From this experiment we concluded that for Audio it was much faster when the person was not being distracted. Annie originally had .1416 as her reaction time, but when she was being distracted her reaction time was .2186. It almost doubled. For Visual reaction time, we concluded that when the eye on the same side as the hand that clicks the button is open, the reaction time is slower. For the right hand and right eye, the reaction time was .3008. For the right hand left eye, the reaction time was .2186.



    Name: carrie gri
    Date: 2002-10-30 15:29:09
    Link to this Comment: 3433

    Jodie Ferguson, Lawral Wornek, Lauren Friedman, and Carrie Griffin


    Hypothesis: When standing, your tactile reaction time will be slower than when you're sitting. And, furthermore, different parts of the body (i.e. arm v. leg) would yield different reactions times.

    Conclusions: However, we discovered that neither criteria made any difference. Our results remained the same, despite the location of the hit and the difference between sitting and standing.

    Sitting:

    Jodie: arm-.161
    leg- .172

    Carrie: arm-.187
    leg-.227

    Lauren: arm-.146
    leg- .213

    Lawral: arm- .326
    leg- .213

    Standing:

    Jodie: arm-.189
    leg- .172

    Carrie: arm- .187
    leg- .247

    Lauren: arm-.130
    leg- .194

    Lawral: arm-.198
    leg- .223



    Name: carrie gri
    Date: 2002-10-30 15:29:09
    Link to this Comment: 3434

    Jodie Ferguson, Lawral Wornek, Lauren Friedman, and Carrie Griffin


    Hypothesis: When standing, your tactile reaction time will be slower than when you're sitting. And, furthermore, different parts of the body (i.e. arm v. leg) would yield different reactions times.

    Conclusions: However, we discovered that neither criteria made any difference. Our results remained the same, despite the location of the hit and the difference between sitting and standing.

    Sitting:

    Jodie: arm-.161
    leg- .172

    Carrie: arm-.187
    leg-.227

    Lauren: arm-.146
    leg- .213

    Lawral: arm- .326
    leg- .213

    Standing:

    Jodie: arm-.189
    leg- .172

    Carrie: arm- .187
    leg- .247

    Lauren: arm-.130
    leg- .194

    Lawral: arm-.198
    leg- .223


    Read/Think/Negate/Act
    Name: Laura Silv
    Date: 2002-11-05 14:58:49
    Link to this Comment: 3537

    Laura Silvius

    I think that the two factors which could have affected this experiment the most are the internal/external factors and the practice effects which we discussed during lab time. Everything, from emotion to sleep (whether or not you get enough, which is another issue altogether) to room temperature could affect how quickly our minds are able to tell our fingers to push those buttons. For example, a sleepy person would have a longer reaction time than one with, say, 13 cups of coffee flowing through her veins (that's me!). If the temperature had been warmer in the room (it's freezing in here - can we do something about that?), we might have felt more awake and had better reaction times.

    The practice effect was something that I noticed helped out my reaction times a lot. Between cases 2 and 3, my reaction time went up from 0.313 seconds to 0.404 seconds because of the vast differences between the excersizes. However, between cases 3 and 4, my reaction time went down to 0.347 seconds, and I got the feeling that it was because I was now accustomed the the manner of the excersize. I simply had to change my word association (that is, whenever I see the word "Don't", I know to push the button, and when I see the word "Do", I know NOT to push the button). This, by the way, also ties in to the "Strategy Affect" that we discussed in class also.

    These were my own personal average times:
    Case 1: 0.221 seconds, +/- 0.019 sec.
    Case 2: 0.313 seconds, +/- 0.082 sec., average difference 0.092 sec.
    Case 3: 0.404 seconds, +/- 0.059 sec., average difference 0.091 sec.
    Case 4: 0.347 seconds, +/- 0.066 sec., average difference -0.057 sec.


    I'd like to see if men or women have better reaction times. I think that would be pretty interesting to see.


    Trial 3 test
    Name:
    Date: 2002-11-05 15:09:25
    Link to this Comment: 3538

    Elizabeth Damore Brenda Zera

    For our experiment we decided to see if a person's reaction time on the Act/Read/Think trial would be affected by repitition. Our hypothesis was that if you did the same trial over and over, your reaction time would be quicker and you would get a lower score. While the score initially was reduced considerably, in subsequent times the scores increased. Although they increased, they stayed lower than the initial score.
    Our final reasoning why the scores first lowered and then increased is that the subject did initially become more familiar with the experiment ( lowering their score), then subsequently got bored with the experiment, causing sloppier, slower behavior. This caused the scores to rise again.

    Brenda's data for the Act/Read/Think experiment:

    trial #1: 526ms
    trial #2: 416ms
    trial #3: 419ms
    trial #4: 445ms
    trial #5: 445ms


    Trial 3 test
    Name:
    Date: 2002-11-05 15:09:34
    Link to this Comment: 3539

    Elizabeth Damore Brenda Zera

    For our experiment we decided to see if a person's reaction time on the Act/Read/Think trial would be affected by repitition. Our hypothesis was that if you did the same trial over and over, your reaction time would be quicker and you would get a lower score. While the score initially was reduced considerably, in subsequent times the scores increased. Although they increased, they stayed lower than the initial score.
    Our final reasoning why the scores first lowered and then increased is that the subject did initially become more familiar with the experiment ( lowering their score), then subsequently got bored with the experiment, causing sloppier, slower behavior. This caused the scores to rise again.

    Brenda's data for the Act/Read/Think experiment:

    trial #1: 526ms
    trial #2: 416ms
    trial #3: 419ms
    trial #4: 445ms
    trial #5: 445ms


    hey
    Name: debe and m
    Date: 2002-11-05 15:14:05
    Link to this Comment: 3540

    Mande and Diana were wondering if presenting an external noise, such as diana sayign fart over and over under her breath would affect reactin times to the stimulus. We hypothesized that this woudl raise reaction time and thinking time, as mande would have to eliminate an external noise form her thinking process.

    observations:
    mande before fart noise- 244, 746, -484, -58
    during fart noise - 274, 334, 540, 123

    After experimenting with the external noise, diana and i found that at first, my reaction times when acting during the noise was affected slightly but after time there was not much of a differance. We conclude that over time I became acclimated to the noise.



    Name:
    Date: 2002-11-05 15:17:58
    Link to this Comment: 3542

    For our experiment, we had one subject watching the screen and telling the other subject when to click the mouse. The subject with the mouse could not see the screen. We were curious to see if the communication time between the two subjects would affect the total response time. For trial one, CT watched the screen and told ST when to click the mouse. Our data for that trial is as follows (all measurements in milliseconds):

    Case one (act): 576 +/- 72
    Case two (think): 778 +/- 158
    Case three (read): 934 +/- 95
    Case four (negate): 876 +/- 235

    Act time: 576
    Think time: 202
    Read time: 156
    Negate time: -58

    For trial two, the two subjects switched places, so that ST watched the screen and CT clicked the mouse. Results for that trial are:

    Case one (act): 550 +/- 130
    Case two (think): 833 +/- 149
    Case three (read): 928 +/- 130
    Case four (negate): 1023 +/- 344

    Act time: 550
    Think time: 283
    Read time: 95
    Negate time: 95

    Conclusions:
    The communication time from the person watching the screen to the person clicking the mouse definitely increased the total resulting time. The average additional time seemed fairly consistent between the two trials, thus validating our hypothesis.

    Christine Traversi
    Sarah Tan


    Reaction Lab
    Name: MaryBeth C
    Date: 2002-11-05 15:24:52
    Link to this Comment: 3543

    After seeing my results for the reaction lab, I decided to experiment with some of the factors that may have affected my reaction times. In class, I experimented with the reaction program, reacting slowly without trying to beat my own times, as I was doing the first time. I found that the kind competition I was having with myself in the kind of test atmosphere did not radically change my times when I attempted the same test more relaxed. In general, my times were slightly longer by a few milliseconds, but overall I had fewer of the long trials that raised my averages.

    Later on, in my room, I plan to experiment with one of the other factors that I think affected my reation times, the distractions of the classroom. I will experiment with total silence, and lots of noise to see how these factors effect my performance.

    I would also lik to experiment with how the body reacts to auditory stimulation, as opposed to the visual stimulation of this particular test, but I have not figured out how to accomplish this task as yet.


    peripheral vision
    Name: jen
    Date: 2002-11-05 15:25:40
    Link to this Comment: 3544

    Joanna Robertson
    Jennifer Rusk

    Hypothesis: By looking straight ahead, while taking part in this activity,your perepheral vision will not be as accurate as you normal vision.

    Observations: When not looking directly at the computer, reaction time was longer becauseyou could not see exactly what was wrtten on the screen. After two ro three times, once you get the idea of what each prompt is telling you, you become more familiar and reaction time increases similiar to what it was originally, but not completely. our numbers increased by 100 millseconds(at least)

    Conclusion: Our hypothesis was right.By notlooking straight at the scrren, our perepheral vision would delayreaction time.


    Practice Makes Perfect?
    Name: Stephanie
    Date: 2002-11-05 15:25:48
    Link to this Comment: 3545

    Hypothesis: Increased practice decreases reaction times.
    We conducted three trials of Stephanie's reaction times to test this:
    CASE 1:
    trial 1: 272 +or- 238
    trial 2: 268 +or- 121
    trial 3: 217 +or- 45

    CASE 2:
    trial 1: 317 +or- 105
    trial 2: 279 +or- 37
    trial 3: 519 +or- 544

    CASE 3:
    trial 1: 472 +or- 72
    trial 2: 397 +or- 61
    trial 3: 462 +or- 106

    CASE 4:
    trial 1: 451 +or- 114
    trial 2: 384 +or- 78
    trial 3: 436 +or- 105

    Our hypothesis was proven false. In many cases, reaction time increased after practice. This leads us to conclude that many internal factors affect reaction time, including but not limited to: Attention span, level of frustration with the trial, desire to push the button, degree of overall physical exhaustion (esp. in the eyes).

    Stephanie's reaction times for Case 1 got lower with practice, but her reaction times for Cases 2- 4 got higher with practice. This seems to indicate that an action can increase with practice but thinking can't.



    Name: Margaret H
    Date: 2002-11-05 15:27:14
    Link to this Comment: 3546

    Margaret Hoyt
    Kyla Ellis

    We wanted to see if women could really multi-task. If outside influences and activity would affect the response time for the Act, Think, Read, Negate experiment. We took the first test with a silent room. In fact, Laura turned around to Maggie while Kyla was taking her test and remarked on how quiet the room was. For the next trial, we decided to tell each other stories while the other person was taking the experiment. Results are as follows:

    Trial 1:

    Maggie:
    Act 277
    Think 231
    Read 146
    Negate 302

    Kyla:
    Act 279
    Think 138
    Read 217
    Negate 180

    Trial 2 (with distraction)

    Maggie:
    Act 335
    Think 141*
    Read 280
    Negate 192*

    *lower times than Trial 1, all other times were higher

    Kyla:
    Act 330
    Think 120*
    Read 151*
    Negate 194

    Conclusions:
    Our hypothesis was that the distractions would have an increased effect on response times. However, that was not the case for all of the times. Both act times were significantly higher, however Maggie had lower times for Thinking and Negating while Kyla had lower times for Thinking and Reading. We do not have enough evidence to conclude that distractions make a difference in reaction times for Acting, Thinking, Reading, and Negating.



    Name: kathryn ba
    Date: 2002-11-05 15:29:33
    Link to this Comment: 3547

    Hypothesis: Listening to different types of music will affect think time.

    Data:

    HERBIE HANCOCK..............KB................Sf
    Act Time...................239................239
    Time to Think..............115................78

    WHITESNAKE
    Act Time..................242.................257
    Time to Think.............51...................58

    SPOTLIGHT ON GUITAR
    Act Time..................251................257
    Time to Think.............32..................48

    Results:
    The data shows that time to think was greatest for both subjects when listening to Herbie Hancock, and smallest when listening to Spotlight on Guitar. The Act Times were consistent across all trials.

    Discussion:
    This experiment indicates that music can affect one's ability to think quickly. It also is significant that the think times are consistent across two people. This experiment does not answer the question of why different music has particular effects on one's ability to think, suggesting that further study is needed.


    Reaction Times
    Name:
    Date: 2002-11-06 14:54:35
    Link to this Comment: 3562

    CR
    Roma Hassan

    Hypothesis: Distractions will slow down reaction time.

    Methods: We used the reaction time applet in serendip to measure reaction times for case 1:"act" and case 3:"read, think, act" experiments. During these experiments the person reacting was also engaged in a conversation with her partner who attempted to distract her by asking questions.

    Observations:

    Chelsea:
    Case 1 without distraction: 295 +/- 63
    Case 1 with distraction: 734 +/- 369
    Case 3 without distraction: 735 +/- 102
    Case 3 with distraction: 1157 +/- 249

    Roma:
    Case 1 without distraction: 274 +/- 30
    Case 1 with distraction: 422 +/- 69
    Case 3 without distraction: 544 +/- 164
    Case 3 with distraction: 661 +/- 200

    Conclusions:
    There is substantial difference between the data gathered for experiments with and without distraction strongly suggesting that our hypothesis is correct. There also may have been a larger disparity in the data had the initial experiment been carried out in a silent room. Additionally worth noting is that the incidence of error (ie: clicking when told not to which removes the last recorded piece of data) was much higher with distraction. Further experiments might involve other types of multi-tasking.



    Name: Laura B. a
    Date: 2002-11-06 15:01:14
    Link to this Comment: 3563

    For the first experiment our average times were:
    Laura: Act time: 239; Think act time: 303; Read, think, act: 427; Read, think-negate, act: 419

    Adrienne: Act time: 331; Think, act time: 468; Read, think, act: 941; Read, think-negate, act: 1996

    For our second experiment, we decided to try talking while performing case 1 and case 4. Our hypothesis was that our reaction times would be slower because of the distraction of carrying on a conversation. Our results were as follows:

    Laura: Act time: 374; Read, think-negate, act: 622

    Adrienne: Act time: 385; Read, think-negate, act: 1409

    Our results were slower except for Adrienne's negating time, which was probably due to the practice factor. Therefore, with that one exception, our hypothesis proved to be true.


    thinking time
    Name:
    Date: 2002-11-06 15:14:10
    Link to this Comment: 3564

    Michele Doughty, Margot Rhyu, Diana La Femina

    We decided to see if our thinking time was inhibited by over-thinking. When some of us were doing the tests we realized that we had to think the command, "Click!" before we actually did. This was above and beyond thinking aboiut whether we had to click or not. To conduct our experiment, we distracted our minds slightly by either singing to ourselves or reciting poetry. In doing this we hoped to make our overall thinking time faster. Our results are as follows:

    Margot:

    Control: 251+/-14 258+/-14 519+/-29 614+/-65
    Experiment: 322+/-18 406+/-70 955+/-857 582+/-54

    Michele:

    Control: 212+/-28 286+/-46 454+/-15 1421+/-1358
    Experiment: 380+/-42 301+/-20 453+/-38 537+/-72

    Diana:

    Control: 239+/-21 374+/-83 536+/-30 801+/-141
    Experiment: 289+/-53 379+/-131 499+/-41 659+/-127

    Our results show that for cases 1 and 2 our times are slower, which is understandable. In our last lab we found out that reflex times slow when one is distracted and case one is a reflex test. We also found that we made significantly more mistakes on case 2, although Michele made the same amount of mistakes. For cases 3 and 4 however our times were better, especially in case 4. Our overall deviation was higher for most all cases in the experiment.

    We believe that a slight distraction from the test will help most people do better, although this is not true for all people.



    Name: Rosie, Bob
    Date: 2002-11-06 15:22:27
    Link to this Comment: 3567

    After gathering an initial set of data, we decided to test the practice effect. We hypothesized that as we gained practice experience, our times would decrease. To test this, we performed a second trial, this time performing ten trials rather than five. We thought that as a second overall trial (consisting of a greater number of individual trials), that our reaction times would become faster. Following is a summary of our data:

    Case 1: all three of us increased in reaction time.
    Case 2: Rosie increased, Annie and Bobbi decreased.
    Case 3: Annie increased, Bobbi and Rosie decreased.
    Case 4: all three of us decreased in reaction time.

    Our data shows no correlation between reaction time and increased experience or practice. Our hypothesis is therefore incorrect. The results seem random. The practice effect cannot help in this situation because the test is still random and the prompts are unexpected (concentration is still necessary). While we may have gained familiarity with the practice (meaning that our times should have decreased), we were also growing distracted and tired of taking the test--these two factors may have counteracted one another.


    Reaction Time
    Name: Catherine
    Date: 2002-11-06 15:23:13
    Link to this Comment: 3568


    In my own experiment, I decided to use the Act and Read, Think-Negate, Act labs to figure out reaction time differences between just acting, negating "do not", and negating "don't". No error data was taken off for any of the three experiments.

    Act Time Data:
    188, 189, 196, 224, 175, 177, 211, 275, 212, 226
    Average: 207, Standard Deviation: 29

    Negate "Don't" Time Data:
    514, 335, 940, 551, 439, 595, 548, 458, 479, 348

    Negate "Do Not" Time Data:
    336, 826, 437, 416, 464, 342, 555, 436, 234, 575

    Obviously, Act Time took a lot less time than both Negate "Don't" and Negate "Do Not" Times. At no point were the second and third able to be responded to as fast as the first, and the second and third reactions obviously had much higher standard deviations. But "Don't" had less standard deviation than "Do Not", and came up much more frequently in the experiment. I also became trained to look for only the words "Do", "Do Not", and "Don't", and "Don't" was by far the easiest to distinguish of the three. The lab involving negation had much more error (14 times) than the lab involving solely action (1 time). Lastly, although it is difficult to see because outside stimuli frequently had the effect of slowing my reaction rate, some of my numbers down each lab's line show that later on, I was more capable of reacting faster if I was focused, not because of pre-disposition, but because of experience.



    Name: Mer
    Date: 2002-11-06 15:28:55
    Link to this Comment: 3569

    Mer
    Hei
    Chel

    The first time that we all used the Thinking Program, we came up with the following results:

    CHEL:
    233 +- 30 (1)
    308 +- 89 (2)
    582 +-66 (3)
    585 +-66 (4)
    233 +- 30 (acting)
    75 +- 94 (thinking
    274 +- 41 (reading)
    6 +-128 (Negating)

    MER
    269 +-81 (1)
    304 +- 69 (2)
    369 +- 115 (3)
    631 +- 439 (4)
    269 +- 81 (acting)
    35 +- 107 (thinking)
    63 +- 135 (reading)
    262 +-464 (negating)

    HEI:
    224 +-20 (1)
    245 +-19 (2)
    475 +- 141 (3)
    467 +- 144 (4)
    224 +- 20 (acting)
    21 +- 28 (thinking)
    330 +- 143 (reading)
    -8 +- 202 (negating)

    For our second experiment, we decided to test the impact of practice with the system, and using another set of data for comparison, what the impact of distraction was upon Chelsea.

    Our hypothesis is thus, Chelsea will get better with practice and her times will improve. Also, Chelsea will become distracted with the noises, and as a result, her scores will drop.

    Results:
    Quiet Practice:

    Trial 1
    Average: 459.9 SD: 84.5 Errors: 3

    Trial 2
    Average: 412.4 SD: 126.5 Errors: 2

    Trial 3
    Average: 462.1 SD: 291.5 Errors: 1 (two times high because of double clicks)

    Total Average: 444.8 SD: 167.5 Errors: 2

    So far, Chelsea improved greatly from her first trial (with the class), and since the last trial was inaccurate, we cannot decisively say that she continued to get better (but she did improve from trial 2 to 3)

    Experiment 2
    Distracted

    Average: 352.1 SD: 122.5 Errors: 2 (both when clapped)

    Trial 2
    Average: 513.1 SD: 258 Errors: 2

    Trial 3
    Average: 361.6 SD: 120 Errors: 1 (clapping)

    Total Average: 408.93 SD: 166.83 Errors: 2ish

    Conclusions: Overall Chelsea concentrated better with distractions, although practice might play a role (we need to do more experiments to decide though). It is important to note that while times seemed to improve, consistency did not, meaning that Chelsea was faster, but also just as inaccurate. We think that noises that are sharp (clapping) have a great impact on concentration than softer or less aggressive noises.


    if you can't walk the walk, don't fall out of your
    Name: Lauren Fri
    Date: 2002-11-06 15:30:25
    Link to this Comment: 3570

    MULTITASKING:
    A Study in Efficiency



    Introduction: In this experiment, we tested the efficacy of multi-tasking. We wanted to see whether or not the pressure to continue a coherent conversation with a fellow would affect the response time in cases one and two, and if so, to what extent.

    Methods: While one individual took the tests, the other engaged her in conversation. Before each conversation, we chose a subject which had to be elaborated upon by both parties during the experiment. The conversations required active listening and participating from both of us.

    Case 1 Case 1 + Case 2 Case 2 +
    Lauren 215 252 304 330
    Carrie 254 337 375 386
    All number values contained in the above table are in milliseconds.
    The plus sign ("+") indicates the added element of conversation.


    Conclusions: As expected, the time to act and time to think both rose when the subject had to multitask (conversing and test-taking simultaneously). For Carrie, her time to act was 83 milliseconds longer and her time to think was 11 milliseconds longer when involved in conversation. For Lauren, her time to act was 37 milliseconds longer and her time to think was 26 milliseconds longer when involved in conversation. We believe that the practice gained from Case 1 contributed to the significant decrease in differention seen in Case 2 vs Case 2+. We can conclude that multitasking increases the time it takes to both act and think; therefore, multitasking does not save time, but in fact decreases the efficiency of each of the tasks.


    finally. ha ha.
    Name: jodie and
    Date: 2002-11-06 15:39:27
    Link to this Comment: 3572

    we hypothesized that our accuracy would be lower if we concentrated on speed. we tested this by repeating the second, third, and fourth cases twice each,
    once concentrating on accuracy and once concentrating on speed. here are our results:

    Lawral:
    case 2 accuracy - 390 +- 105 100% accuracy
    case 2 speed - 355 +- 70 84% accuracy
    case 3 accuracy - 581 +- 188 100% accuracy
    case 3 speed - 434 +- 81 83% accuracy
    case 4 accuracy - 536 +- 87 93% accuracy
    case 4 speed - 492 +- 83 86% accuracy


    Jodie:
    case 2 accuracy - 312 +- 63 100% accuracy
    case 2 speed - 274 +- 37 90% accuracy
    case 3 accuracy - 366 +- 53 100% accuracy
    case 3 speed - 415 +- 160 71% accuracy
    case 4 accuracy - 414 +- 128 91% accuracy
    case 4 speed - 360 +- 277 72% accuracy


    for the most part, our hypothesis was correct. our accuracy was affected by concentrating on speed. the actual speed, however, was affected by
    concentrating on it in a negative way because we were flustered by the amount of mistakes we were making. we would also like to note that we are sorry for posting this in the regular forum. oops.


    "The Flaming Lips"
    Name: Will, Dian
    Date: 2002-11-06 15:40:16
    Link to this Comment: 3573

    Will:
    Act time: 237 +/- 22, 215 +/- 20
    Think+A time: 313 +/- 55, 291 +/- 39
    Read+T+A time: 435 +/- 82, 412 +/- 47
    R+Think Negate+A time: 503 +/- 67, 419 +/- 56

    Act time: 237 +/- 22, 215 +/- 20
    Think time: 76 +/- 60, 76 +/- 44
    Read time: 122 +/- 99, 121 +/- 62
    Negate time: 68 +/- 166, 7 +/- 74

    Diana:
    Act time: 258 +/- 37, 221 +/- 15
    Think+A time: 298 +/- 26, 302 +/- 52
    Read+T+A time: 464 +/- 65, 493 +/- 70
    R+Think Negate+A time: 620 +/- 109, 905 +/- 293

    Act time: 258 +/- 37, 221 +/- 15
    Think time: 40 +/- 46, 83 +/- 55
    Read time: 166 +/- 71, 189 +/- 88
    Negate time: 156 +/- 127, 412 +/- 302

    Brie:
    Act time: 210 +/- 17, 229 +/- 19
    Think+A time: 264 +/- 30, 234 +/- 11
    Read+T+A time: 450 +/- 25, 391 +/- 27
    R+Think Negate+A time: 408 +/- 40, 312 +/- 46

    Act time: 210 +/- 17, 229 +/- 19
    Think time: 54 +/- 35, 5 +/- 22
    Read time: 186 +/- 40, 157 +/- 30
    Negate time: -42 +/- 48, -79 +/- 54

    Second times in each were while listening to music.


    FLY LAB
    Name: Brenda and
    Date: 2002-11-12 15:24:41
    Link to this Comment: 3695

    Brenda Zera, Elizabeth Damore

    For our experiment, we crossed a long-antennaed (Ar) female with an Eyeless (Ey) male.

    Cross #1: Their Children

    264 Wild-type (+) female, 256 (+) male
    257 (Ar) female, 249 (Ar) male

    The eyeless trait did not appear in the children.

    Now, we'll cross the children with each other.

    Cross #2a: (+) female crossed with (+) male

    Results: 369 (+) female, 382 (+) male
    134 (Ey) female, 140 (Ey) male

    In this cross, the (Ar) trait did not show up

    Cross #2b: (Ar) female crossed with (Ar) male

    Results: 132 (+) female, 147 (+) male
    265 (Ar) female, 248 (Ar) male
    42 (Ey) female, 35 (Ey) male
    103 (Ar/Ey) female, 87 (Ar/Ey) male

    All traits appeared in the children, with a 3:3:1:1 ratio

    Cross #2c: (Ar) female crossed with (+) male

    Results: 171 (+) female, 200 (+) male
    187 (Ar) female, 207 (Ar) male
    63 (Ey) female, 65 (Ey) male
    59 (Ar/Ey) female, 51 (Ar/Ey) male

    Once again, all traits showed with a 3:3:1:1 ratio

    Cross #2d: (+) female crossed with an (Ar) male

    Results: 187 (+) female, 174 (+) male
    175 (Ar) female, 192 (Ar) male
    53 (Ey) female, 77 (Ey) male
    62 (Ar/Ey) female, 80 (Ar/Ey) male

    Again, all traits appear with a 3:3:1:1 ratio


    Fly Lab
    Name: Kate Amlin
    Date: 2002-11-12 15:30:20
    Link to this Comment: 3696

    After exploring ebony and wild type genes,
    we explored the purple eye and the lobed eye genes.

    First we established that the
    purple eye gene is an example of true breeding, and recessive...
    then that the lobed eye gene is also and example of true breeding,
    but it is dominant.

    We hypothesized that breeding a purple, lobed female with a wild type male would produce a
    9 lobed m/f : 3 wild type m/f : 3 purple, lobed m/f : 1 purple m/f.

    We tested the hypothesis by breeding a purple, lobed female with a wild type male.
    They produced=> lobed females + lobed males (1:1) ratio
    the lobed males and females produced=> 1 wild m/f : 2 lobed m/f : 1 purple, lobed m/f

    Our hypothesis was disproven since tour results were in a
    1 wild: 2 lobed: 1 purple, lobed : 0 purple ratio
    INSTEAD OF A 3 wild: 9: lobed: 3 purple, lobed: 1 purple ratio

    So because our hypothesis was disproven, we concluded that there must be some linkage between the genes. Instead of each gene being carried by a different chromosome (which would result in our hypothesized Punett Square with 16 combinations), the genes are linked and share the same chromosome. The lobed and the purple eyes were carried on one chromosome and the wild gene was carried on a chromosome. This would then give us 4 possible results when doing the Squares and explain the 2:1:1 0 ratio that resulted in our experiment.

    Kate Amlin, Katie Campbell, Stephanie Lane


    virtual fruit flies
    Name: Kathryn Ba
    Date: 2002-11-12 15:35:40
    Link to this Comment: 3697

    1) We started by testing purple eye color:

    (e)PR & (e) PR = PR

    * PR is true breeding; Phenotype PR, Genotype PR PR

    2) Next we tested (e)PR and (a) AR

    PR AR & PR AR = (1) PR + : (2) PR AR

    * PR again was homozygous, the AR seemed to be heterozygous

    3) We examined (a) AR further
    AR & AR = (2) AR: (1) +
    * As with (2) the part of the model of genes where the AR AR should have existed was absent. The only way to obtain the ratio is if the phenotype AR is genotypically AR +

    4) In order to test this further, we bred (e)PR (a) AR and an (e)+ (a) +

    PR AR & + + = (1) (e) + (a) AR : (e) + (a) +
    * This shows that the (e) + is dominant over the (e) PR and that the AR AR combination does not exist and is always heterozygous


    Fly lab
    Name: Mande Macl
    Date: 2002-11-12 15:36:59
    Link to this Comment: 3698

    Diana and I first started by breeding Curly winged wilds with wilds. when we tried to decipher if the curly winged were pure breed, we found that wen breeding curly winged, curly winged was a fatal combination, therefore leaving us with a 1:2 ratio. Then we tried to breed, the wilds and the curly and found that the wild dominated in the end, the offspring were wild.
    Next when trying to breed two pairs of genes we bred teh lobed eye yellow bodied with a wild. knowing that the lobed eye yellow body was a pure breed, we went into it expecting a 1:1 ratio. We found that it was true fr the first generation yet in second generation we found that it was a 1:3 ratio. Eventually we found other breeds to be fatal and ended up with thoriginal two breeds.


    genes
    Name: joanna yar
    Date: 2002-11-12 15:37:56
    Link to this Comment: 3699

    first of all, we noted that when the ee (homozygous ebony) was breeded with another homozygous wild type (also true breeding) the result ratio in offspring was 3:1 the second time around



    so then we tried the gene for funky looking antennae (AR) and we performed tests to see if htey were true breeding (i.e., we breeded them with each other for several generations to see if the offspring yielded were all AR phenotypes) and they WEREN'T! therefore we can instantly conclude that AR must not be a homozygous gene, i.e. flies that show the AR phenotype don't have two AR genes, so we assume they probably have an AR + structure, i.e. one AR and one wild type



    Then, we made a punnet square for the AR gene in question, assuming that AR had to be heterozygous with a wild type gene, since that was the other type of offspring yielded in the breedings. therefore we would expect a 3:1 ratio of AR to +. however, we got a 2:1 ratio AR to wildtype when we breeded two AR + flies together (this was the hypothesized makeup, anyway) and, in looking at our punnet square and analyzing our breeding results, it looks liek for some inexplicable reason it is not possible to have an ARAR (homozygous AR) gene in the flies. WHY? we dont know, we're not geneticists but it seems that more is going on here than we know about. question - why can there not be a homozygous gene for funky antennae?



    then, our next gene to be analyzed was the tan body color gene (T). we tested it for true breeding and found that it was indeed true breeding through successive generations. so then we made a punnet square and assumed htat again, like the ebony true breeder in class, we would get a 3:1 ratio if we bred a (TT) with a (++). However we got a 1:1 ratio, a puzzling phenomenon indeed. this means that either (T+) or (+T) yields a Tan phenotype, but as we have NO way of knowing which is which, it makes for totally unpredictable breeding patterns.




    despite this uncertainty factor, we breeded the Tan body wild type antennae with the AR antennae and wild type body color. we were somewhat uncertain of the results due to the above mentioned uncertainty factor; however, we tried to analyze all possible results and we got a one to one ratio in the end. who knew? we don't know how to analyze that until we are more certain about the inner workings of both the AR gene and the T gene, both of which seem to display some sort of irregularity not covered by this program. we need additional time and funding to complete the project $$$$$


    CV and +
    Name: Margot and
    Date: 2002-11-12 15:45:11
    Link to this Comment: 3700

    Margot Rhyu
    Sarah Tan

    We decided to test the wing vein trait of crossveinlessness.

    When both male and female were crossveinless (CV), the kids were both CV and there was an equal number of males and females. When we mated the kids, the grandkids were also both CV, and there was also an equal number of males and females.

    When the female is CV and the male is wild (+), the female kids were all + and the males were all CV, with equal amounts of male and female. When the kids were mated together, there were equal amounts of male and female. Within the females, there were equal amounts of + and CV, and in the male there were also equal amounts of + and CV.

    Now...
    When the female is + and the male is CV, the kids were ALL +, with equal amounts of male and female. In the grandkids, there were equal amounts of male and female, but there were ONLY female +. Within the males, there were equal amounts of + and CV.

    And then...
    When we mated the grandkids of a female + and a male CV, we got equal amounts of male and female and within each gender, equal amounts of + and CV.

    So how do we account for the reappearance of the female CV when it seemed to have disappeared in both the female kids and grandkids generations? Our theory is that CV is a recessive gene that exists on the sex chromosome. This follows the same type of genetic pattern as recessive genes in humans, where recessive genes on the X chromosome do not show up in the female unless it is on both of her X chromosome. However, because males only have one X chromosome, when they have a recessive gene on the X, it will show up no matter what. Therefore, it is more unlikely for a recessive gene to affect the phenotype of the female than in the male.


    CV and +
    Name: Margot and
    Date: 2002-11-12 15:46:43
    Link to this Comment: 3701

    Margot Rhyu
    Sarah Tan

    We decided to test the wing vein trait of crossveinlessness.

    When both male and female were crossveinless (CV), the kids were both CV and there was an equal number of males and females. When we mated the kids, the grandkids were also both CV, and there was also an equal number of males and females.

    When the female is CV and the male is wild (+), the female kids were all + and the males were all CV, with equal amounts of male and female. When the kids were mated together, there were equal amounts of male and female. Within the females, there were equal amounts of + and CV, and in the male there were also equal amounts of + and CV.

    Now...
    When the female is + and the male is CV, the kids were ALL +, with equal amounts of male and female. In the grandkids, there were equal amounts of male and female, but there were ONLY female +. Within the males, there were equal amounts of + and CV.

    And then...
    When we mated the grandkids of a female + and a male CV, we got equal amounts of male and female and within each gender, equal amounts of + and CV.

    So how do we account for the reappearance of the female CV when it seemed to have disappeared in both the female kids and grandkids generations? Our theory is that CV is a recessive gene that exists on the sex chromosome. This follows the same type of genetic pattern as recessive genes in humans, where recessive genes on the X chromosome do not show up in the female unless it is on both of her X chromosome. However, because males only have one X chromosome, when they have a recessive gene on the X, it will show up no matter what. Therefore, it is more unlikely for a recessive gene to affect the phenotype of the female than in the male.


    Flies in my eyes
    Name: Mags and K
    Date: 2002-11-12 15:49:59
    Link to this Comment: 3702

    Margaret Hoyt
    Kyla Ellis

    We crossed a Purple-eyed Female with a Wild-eyed male.
    The offspring had a 3:1 ratio for wild-eye color to purple. And after hand graphing the crossing of a PR PR female and a + + male, it was confirmed that the PR gene is recessive.

    We then crossed a Curley-winged Female to a normal (wild type) male. For that, we had a two to one ratio. When hand-graphing the results of mating a CY CY female and a + + male, we realized we should have had all offspring be the same if that was to work. Therefore, (because we know that the wild type is + + from a previous experiment) the curly eyed gene cannot be CY CY. Upon graphing the results of a CY+ female mating with a ++ male, the correct ratio of two to one appeared. In order for the 2:1 to hold, we must assume that the CY gene is dominant over + gene. Also, the CYCY gene does not exist.

    Finally, we paired a purple eyed, curly winged female with a wild-type male. The first generation offspring have two wild type offspring(both eyes and wings) and two wild type eyes with curly wings. When hand graphing the mating of a CY+, PRPR female with the ++,++ male, we realize there is a 50% chance of finding an offspring with curly wings (CY+) and no chance of the PR gene appearing. This holds, since the CY gene is dominant over the wild type and the wild type is dominant over the Purple eye gene.


    Fly Lab Results
    Name: Emily and
    Date: 2002-11-13 15:04:56
    Link to this Comment: 3718

    FLY LAB RESULTS

    Cross 1:
    Purple-Eyed Female x Purple-Eyed Male
    result - 492f and 499m ALL PURPLE

    1b:
    offspring of cross 1
    result - 505f and 513m ALL PURPLE

    CONCLUSION - purple-eyed trait is true breeding


    Cross 2:
    Eyeless Female x Eyeless Male
    result - 511f and 475m ALL EYELESS

    2b:
    offspring of cross 2
    result - 498f and 506m ALL EYELESS

    CONCLUSION - eyeless trait is true breeding


    Cross 3:
    Purple, Eyeless Female x Purple, Eyeless Male
    result - 528f and 506m ALL EYELESS

    3b:
    offspring of cross 3
    result - 498f and 493m ALL EYELESS

    CONCLUSION - because both parents were homozygous for eyeless, there was no chance for the eye color trait to be displayed phenotypically since they could not have eyes


    Cross 4:
    Purple, Eyeless Female x Wild Eyed Male
    result - 518f and 471m ALL HAD WILD EYES

    4b:
    offspring of cross 4
    result - 297f and 280m WILD EYES
    101f and 84m WILD-SHAPED, PURPLE EYES
    129f and 133m EYELESS


    CONCLUSION - for eye shape, parents in the second generation were heterozygous for wild eye and eyeless. as a result, some of the offspring in the 3rd generation showed the wild-eye trait and others were eyeless.

    for eye color, parents in the second generation were heterozygous for wild eye and purple. as a result, some offspring showed the purple eye trait and others were wild.

    the ratio for this double-trait cross was 3:1:1 instead of the regular 9:3:3:1 ratio. when more eye-color traits would have been displayed, some offspring turned out eyeless. this is because the 3rd gen. the genotypes that would have shown purple eyeless and wild-colored eyeless could not be distinguished as two different phenotypes. we could not see the eye color trait if they did not have eyes.


    Mellow Yellow
    Name:
    Date: 2002-11-13 15:26:15
    Link to this Comment: 3720

    Diana DiMuro and Brie Farley

    We were curious about the inheritance of the yellow gene and whether it was passed on specifically by the male or the female and if it was possibly passed on to a specific sex.

    Our first experiment was conducted with a yellow male and a "true" wild female. The offspring were all phenotype wild.
    Once we continued the experiment and bred both phenotype wild sexes they yielded all phenotype wild flies again.
    Our first hypothesis was that the male fly could not pass on yellow to either sex offspring.

    For our second experiment we mated a yellow female with a "true" wild male fly. The offspring were about half phenotype wild female and half yellow male. We had no idea then how female yellow flies could possibly exist. Next we bred the offspring (wild phenotype females with yellow males) and this produced both wild phenotype males and females, and yellow phenotype males and females.
    After this occured we started pulling our hair out, we knew something was wrong with our original hypothesis but we couldn't figure out how yellow males and females had been produced or if one sex had passed it on to its offspring.

    After strenuous thinking aided by our lab companion Will, we came to the conclusion that the yellow allele is a recessive trait on the X chromosome. Thus, if a male has a yellow allele on his X chromosome he will be phenotype yellow. In order for a female fly to be phenotype yellow, she needs both of her X chromosomes to have yellow alleles. We wondered if this trait was similar to that of color blindness in humans, since colorblindness is more common in males.


    virtual fly lab
    Name: drosophila
    Date: 2002-11-13 15:29:02
    Link to this Comment: 3721

    Roma Hassan, Melissa Brown and CR

    Hypothesis: Both male and female fruit flies have two genes for each characteristic and the characteristics which are exhibited in inheritence will reflect this fact, with the wild type of each trait being dominant.

    Methods and Results: We mated male and female brown-eyed fruit flies and found them to be "true breeding" (ie: their off-spring were all brown-eyed). Then, we mated a brown-eyed female with a wild-type male, producing offspring which all exhibited the wild-type phenotype. These offspring, when mated, produced offspring some of which are wild-type, some brown-eyed in an approximately 3:1 ratio.

    We then examined wing angle, first mating a male and female both with the dichaete wing angle. This trait did not appear to be "true-breeding" as some of the offspring produced had a wildtype wing angle and some had a dichaete in an approximately 1:2 ratio.

    Experimenting with a combination of these traits (eye color and wing angle) produced other interesting results. We mated a brown-eyed female with a dichaete wing angle with a wild type male, resulting in offspring which all had wild-type eyes and some of which had a wild-type wing angle and some a dichaete wing angle. Mating two of these offspring (a female wild-type and a male with wild-type eyes and dichaete wing angle) produced offspring in a 3:3:1:1 ratio (+, dichaete, brown-eyed, brown-eyed dichaete).

    Conclusion:
    The results of breeding brown-eyed fruit flies supports our hypothesis, as the presence of two genes for every trait would lead to the 3:1 ratio which was present in our results. Experimenting with wing angle, however, suggested that our hypothesis (wild type is always dominant) was incorrect, as it suggests that dichaete is a dominant trait and, in fact, lethal in a double dose. Also, the experiment combining brown eyes and dichaete wing angle further supported these findings because the ratio produced was what was expected in accordance with the punnett square examining that combination.


    Weird Genes
    Name: Will Carro
    Date: 2002-11-13 15:33:06
    Link to this Comment: 3722

    Curly Wings:

     

    First generation
    Curly Fem. X Curly Male
    353 Curly Fem.
    168 Wild Fem
    349 Curly Male
    156 Wild Male

    2:1 (ignoring sex)

     

    Second generation
    Wild Fem x Father (Curly Male)
    257 Wild Fem
    241 Curly Fem
    235 Wild Male
    255 Curly Male

    1:1 (ignoring sex)

     

    Hypothesis: Curly wings are a heterozygous genotype. Wild type wings are homozygous dominant. A homozygous recessive genotype is fatal.

     

    First generation
     

    MOTHER

    C c

    F C

    A

    T

    H c

    E

    R

    CC (wild)

    Cc (curly)

    Cc (curly)

    cc (fatal)

    Second generation
     

    MOTHER

    C C

    F C

    A

    T

    H c

    E

    R

    CC (wild)

    CC (wild)

    Cc (curly)

    Cc (curly)

     

    White eyes:

    First generation
    White Fem. X Wild Male
    495 Wild Fem.
    502 White Male

    Ratio 1:1

     

    Second generation
    Wild Fem. X White Male
    266 White Fem.
    259 White Male
    252 Wild Fem.
    247 Wild Male

    Ratio: 1:1:1:1

     

    Third generation
    First generation Wild Female X Wild Male
    487 Wild Fem.
    267WildMale
    250 White Male

    Ratio: 2:1:1

     

    Hypothesis: White eyes are a X-chromosome linked characteristic. A female that carries only one chromosome associated with the white eye gene has wild eyes. A female must have both chromosomes associated with the white eye gene to have white eyes. Because males only have one X chromosome, if they carry the white eyed gene they have white eyes.

     

    First Generation
     

    MOTHER

    X Xw

    F X

    A

    T

    H Y

    E

    R

    XwX

    (wild)

    XwX (wild)

    XwY

    (white)

    XwY (white)

    Second Generation
     

    MOTHER

    Xw X

    F Xw

    A

    T

    H Y

    E

    R

    XwXw

    (white)

    XwX (wild)

    XwY

    (white)

    XY (wild)

    Test Cross
     

    MOTHER

    Xw X

    F X

    A

    T

    H Y

    E

    R

    XwX

    (wild)

    XX (wild)

    XwY

    (white)

    XY (wild)


    gene lab
    Name: Annie S.,
    Date: 2002-11-13 15:36:26
    Link to this Comment: 3723

    Upon testing eyecolor, we found that this trait causes true breeding (we found that the expected ration of 1:3 held by our second cross breeding). We then chose to test wing type. After testing for true breeding, we bred a crossveinless female with a wild type male. Our results: 2 images resulted; 524 wild type females and 505 crossveinless males. In order to account for these results (the fact that ONLY the males recieved the trait) we conclude that this trait is a sex linked characteristic on the female x chromosome. While the trait is, in fact, recessive, when it is passed on to males, it dominates the gene because he has only one x chromosome (the y chromosome is essentially empty and overshadowed by the x chromosome linked CV trait). Therefore, when we switched the roles, and bred a crossveinless male with a wild type female, the following data resulted: two images; 512 wild type females and 501 wild type males. Because the male has only one trait to offer, the one x chromosome linked CV trait, it will always be overpowered by the female's two + traits. In this generation, the crossveinless trait is hidden, only to emerge in the next generation.

    Our next experiment examines double trait flies in comparison to the wild type mate. We first bred a purple-eyed, cossveinless female with a wildtype male. Our results: 2 images; 528 wild type females and 493 CV males. Purple eyes is a recessive trait and CV is carried on the x chromosome of the female. We cross that generation and we got a 3:1:3:1 ratio of wild type to purple eyes to cross veined to purple eyed cross veined.

    The female will always contribute the following traits: ++, +CV, p+, p CV. The male will contribute one of two sets of genes depending on whether the offspring is male or female. Is the offspring is female, he will either contribute +CV, or pCV. If the offspring is male, he will give either +Y, or pY. The Y trait here is essentially "empty" since it cannot carry the CV trait.



    Name: Chelsea
    Date: 2002-11-13 15:39:12
    Link to this Comment: 3724

    Mer
    Heidi
    Chelsea
    Diana
    Katherine

    Scalloped winged: True Breeding
    Wild Winged: True Breeding

    Hypothesis:

    Either wild winged or scalloped winged will be dominant. (regardless of sex).

    One female Scalloped winged and One male Wild winged: all female offspring are wild winged and all males are scalloped. In the second generation males and females both had equal proportions of wild and scalloped winged.

    One male Scalloped and One female wild winged: all offpring are wild winged in the first generation and in the second generation all females are wild winged and all males are equally split between scalloped and wild winged.

    Conclusion:
    Dominance is sex related in this case of scalloped versus wild winged fruit flies. This is due to the fact that some genes are located exclusively on the X chromosome and there is no counterdominant gene on the Y chromosome. Because females have 2 X chromosomes and males one X and one Y, then whatever gene is on the X (scalloped) will be dominant in males because there is no counter gene on the Y chromosome. Also, the female flies with wild prove that scalloped is recessive, since they have both scalloped and wild genes. Finally, a female with two scalloped is not lethal, merely guarentees that her son will be scalloped.


    damn bugs
    Name:
    Date: 2002-11-13 15:58:00
    Link to this Comment: 3725

    jodie, lawral, adrienne, laura


    we tested aristapedia antennae and dichaete wing alignment. we have been testing both of these characteristics together and separately in males and/or females for the last two hours. we have figured out that both traits are lethal homozygos, meaning that they cannot truebreed because there can never be a homozygos aristopedia or a homozygos dichaete. any fruit flie that is aristapedia or dichaete is heterozygos. the problem is that these traits are only lethal homozygos in females. because they are only lethal in females, the genes for the aristapedia and dichaete are in the x chromosome. because the genes are both on the x chromosome, they cannot be separated, except in the case of cross-over when the chromosome splits.

    our results were as follows:

    m(ArD) & f(++):
    1:1
    of Ar:D

    f(ArD) & m(++):
    1:15-20:15-20:1
    of ++:Ar:D:ArD


    oops
    Name: Erin Myers
    Date: 2002-11-14 16:20:44
    Link to this Comment: 3738

    Change in hypothesis of curly wings: curly wings are a lethal dominant allele. It is lethal when homozygous dominant. This is evident because when you cross two curly winged flies CY/+ there are more curly winged flies than wild winged flies in the ratio of 2:1. This suggests that curly is dominant over wild and the ratio suggests a homozygous gene for this trait is lethal.


    fly lab
    Name: Heather an
    Date: 2002-11-18 21:23:00
    Link to this Comment: 3783

    We started by testing each of our two traits individually. First we tested the purple eye gene, and found it to exhibit true breeding characteristics. So purple is a homogeneous recessive gene. Next, we tested the genes for the star shaped eye. We found that to be heterogeneous dominant.

    Then we crossed a wild type male with a purple-star-eyed female. From the first cross we got only wild type and wildtype with star eyes. we then bred the two wild/star-eyed flies together. What we recieved were wild/wild, wild/star, and purple/star in a ratio from 1.5:2.5:1. We were then confused because when we did the cross ourselves, the results were very different. We soon learned that we had a lethal combination in out genetic set. if the fly recieves two star-eyed dominant genes, then that fly cannot exist. Also, purple/wild type flies did not exhist. That's because both the gene for purple and that for star are on the same chomosome. These genes are linked, so there is something that makes this mix impossible, though Will never really explained what...



    Name: kathryn ba
    Date: 2002-11-19 14:24:17
    Link to this Comment: 3789

    We examined the esophagus and the trachea and determined that the esophagus has more dense cells and less lumen than the trachea. The esophagus, which allows for food to be carried into the body, has a thicker inside layer for protection against foregein objects (ie food). The trachea is less dense to allow for oxygen to be carried into the body effectively. Heart cells are elongated and often overlapping and non-linear to allow for the pumping function of the organ.


    Body Cells and their Functions
    Name: Diana Fern
    Date: 2002-11-19 14:30:21
    Link to this Comment: 3790

    Diana and I were assigned to analyze teh esophogagus and trachea cells. Before looking at the cells we did some brainstorming about teh functions of each of these parts of the body and tries to predict, or hypothesize what the differences in the cells may be. The main differance amongst the trachea and esophagus, is that the trachea carries air and the esophogus, water adn mucus. Therefore, we hypothesized that the difference in teh cells would be teh amount of lumen, or air, within the cells; the trachea woudl contain more lumen than the esophogus. In order to further our experiment we decided to also look at lung cells. Perhaps they would most resemble the cells in the trachea.

    Observations:
    Esophogus - thick epithereal layer, inside ring is composed of purple cells, cilia is present

    Trachea -
    thin epithereal layer, large lumen amount in the cell, also a layer of small purple cells.

    Lung - resembles trachea in that it has a lot of lumen, a layer of purple cells, evident oblong cells in the epithereal layer that stretch from one side of the layer to the other.

    In conclusion we found that our hypothesis was right. Since teh trachea and lung both function to get air to teh blood stream, they had very similar structures.


    Cells
    Name: kate katie
    Date: 2002-11-19 14:32:23
    Link to this Comment: 3791

    Katie Campbell, Kate Amlin, Stephanie Lane

    We decided to explore cells of the liver, kidney, and lung. We wanted to observe the similarities and differences in the cells and the higher assemblies of cells and how they relate to the function of the organ.

    Our hypothesis was that the cells and their organization would be similar in each of the organs because we believed that their functions were closely related in responsibility of delivering materials to the blood.

    We looked at the three differnt slides and discovered that at first glance, each of the organs looked pretty similar. Our observations on a more detailed cell level, however, showed us that the liver and kidney cells were of similar size and make-up. The nucleus took up approximately half of the cell size. Whereas the appearance of the lung cells reminded us of the liver and kidney cells they were noticably smaller than the other cells.

    Although the cells seemed to be physically similar, the spatial organization of the liver, kidney, and lungs were quite different. The liver cells were organized in rings/clumps. The kidney cells were arranged in long strings with more lumen than in the liver cells. The lung cells were placed in long, twisty strings and the lung had the most lumen of the three slides.

    From these observations we conclude that the lumen plays a key role in the function of the lung. The empty space provides room for the oxygen that enters the lung each time an individual inhales. However, the lumen found in the kidney and liver would not serve the same purpose. Therefore, the lumen is not a similarity that can connect the functions of these three organs. Perphaps similarities of the individual cells are what link the purposes of the liver, kidney, and lung.


    Intestines
    Name: Midgie
    Date: 2002-11-19 14:34:50
    Link to this Comment: 3792

    Margaret Hoyt, Brenda Zera, Christine Traversi

    Small Intestine:
    Cross section appeared to be tubular in shape - with a band of muscle fibers or tissues around the outside of the tube, and finger-like extensions reaching into the empty space (lumen). The fingers were very long and had high concentration of cells in them.

    Large Intestine:
    Cross section appeared to be only half of what we assume would be another tube. The fingers were shorter in length and close together. The fingers had more cells in them than in the band on the outside.

    Comparasion:
    Band is thicker in the large intestine, with the finger extensions shorter in length and set closer together than the small intestine. The small intestine fingers were longer than the large intestine, but had a larger concentration of cells in the fingers. Because food is processed in the small intestine before it travels to the large intestine, we think that the high concentration of cells in the large fingers of the small intestine serve to absorb the nutrients from the food. The large intestine also absorbs whatever nutrients haven't been absorbed in the small intestine, but basically serves to turn the food into waste, since all the nutrients are gone. Therefore, the large intestine doesn't need the long fingers and high concentration of cells to absorb the nutrients the way the small intestine does.

    Heart cell:
    Unlike the tubular appearance of the intenstines, the heart slide lacks the large pockets of lumen. What lumen we could see was very long and stringy, and blended in with the muscle fibers of the heart. There seemed to be a more even distribution of cells throughout the cell, rather than in concentrated areas.


    Ovaries, TESTES, and spinal cord, oh my!!
    Name: Heather, M
    Date: 2002-11-19 14:41:27
    Link to this Comment: 3793

    Ah, the ovary. We laughed, we cried, and Wil says there were eggs... well, we hope. There were many small, dark cells which surrounded big eggesque cells. So, the smaller cells would eventually become egg cells, but until then their main function is to help the growth of the developing egg mature. Many eggs develop, but only some become full grown eggs. The other eggs which don't develop become little spots for the production of projestrogen.

    So, the testes. Singular, testis. There were many chambers which the cells organized themselves into, which, depending on the section we looked at, looked like rings or tubey things. Naturally, those were all made up of cells. It was interesting that because new sperm is created every 70 days (information courtesy of Wil), unlike the ovaries, where eggs come prepackaged for life, we could see cells dividing in the testes. In some cells in the chamber linings, we could even see the individual chromosomes, which looked like sausages. Within the chambers, there were big masses of "furry things," which, it turned out, was sperm. Sperm tails, to be exact. Really, this is what does it for Grobstein. He said so.

    Okay, so maybe the spinal cord lacks the excitement of the ovaries and the testis, but it is still pretty important. The cells are really tightly packed together- this is why a small impact on the spinal cord greatly affects the rest of the body. Also, since the spinal cord is vertical, a cross section only shows basically tiny circles. The basic function of the spinal cord is to transport information and the organization of the cells reflects this.

    The cells in the spinal cord are really different from those in the reproductive organs. This is because so many different stages of the reproductive process have to be accomadated by those cells for the organs to perform their function. However, all of the cells in the spinal cord have the same basic function, they specialize in transmitting information.

    Sarah Tan- testis
    Heather Price- ovaries
    Margot Rhyu- spinal cord


    Cell shape and function
    Name: Jen Rusk,
    Date: 2002-11-19 14:58:45
    Link to this Comment: 3795

    We first examined the crossection of a Kidney and a pig liver. The kidney cells were set up in long chains of cells end to end, with cells set up in a circle with an opening.

    The kidneys are where blood is filtered for different things, such as salt and water. So the cells are probably set up in this way (tubular fashion) to allow liquid to pass by so it can be filtered.

    The Liver had a similar structure, in that there were tubular openings. From prior knowledge we know that impurities, such as alcohol, are filtered and broken down in the liver. This could account for the similarities in shape and organization, the similar functions.

    We also looked at a crossection of the aorta as comparison. there was a big difference in the way the cells looked and were organized. In the aorta, the clumpy and more scattered, with blood vessels (some of different sizes) spread throughout.


    lab
    Name:
    Date: 2002-11-20 14:07:40
    Link to this Comment: 3805

    Diana La Femina & Michele Doughty

    We studied three organs: Small intestine, large intestine, and skeletal muscle. The questions we were asked are:

    1. # of cell types/tissues?
    2. arragement of tissue within tactic organ?
    3. Can an organ be formed from the cells of another?

    Small intestine
    3 types of cells:
    outer layer- very elongated, thin, smooth muscle to help move food
    middle layer- space between cells, lumen, spongy looking
    inner layer- concentration of nuclei and spaced out

    Large intestine
    3 types of cells: similar to structure of small intestine cells
    Overall make up of them took up a larger area, they're larger, hence large intestine.

    Skeletal muscle
    one type of cell but it did look like there might have been connective tissue. It appeared smooth and thin.

    Discussion:
    Small and large intestines appeared to have the same types of cells. The only major difference was that the large intestine's cells took up greater space. It appears that the cells of the small and large intestines could make up one another. The skeletal muscle cells appeared to be the same type of cell as the outer layer of the large and small intestine. This is probably because the outer layer is smooth muscle that aids in parastolisis.


    cells
    Name: Adrienne a
    Date: 2002-11-20 14:11:33
    Link to this Comment: 3806

    Adrienne and Laura B.

    We looked at the small intestine vs. the large intestine, and then looked at the lung.

    Small intestine: We found about 6 or 7 different cell/tissue types. The cells were more densely packed toward the outside of the cross section, and toward the middle they got less dense, and then in the very middle, there was a bunch of blank space (lumen).

    Large intestine: We found about 6 different cell/tissue types. The cell arrangement was pretty much the same as the small intestine, but the less dense cells toward the middle were more stringy.

    Lung: We found about 8 different cell/tissue types. The cell arrangement is VERY different from that in the intestines. There is no blank space (lumen) in the middle, rather there are smaller blank spaces spread throughout the sample we looked at. The cells look very different from the intestines' cells as well.

    Comparison: The intestines seemed pretty similar, but since they are separate in our bodies they probably can't replace each other. The lung cells looked totally different and therefore could not replace intestine cells.


    organs and cells
    Name:
    Date: 2002-11-20 14:14:50
    Link to this Comment: 3808

    Melissa Brown and Roma Hassan

    We examined different organs taken from various organisms for the classification of different cell types. The experiment was carried out with the help of a simple microscope. Our hypothesis is that all of the organs examined would have same types of cells since all these different organs work together to carry out the many bodily functions.

    At first, we looked at a section of pig liver cells. Clumps of cells which looked like they were the same kind of cell could be seen along with lumens. Perhaps one reason for the existence of many lumen is the function of the liver which is to channel out impurities from the bloodstream.

    Next, kidney cells were observed. Elongated, elliptical and tubular cells were seen along with lumen which had larger surface areas than the lumen in the liver cells. The function of the kidneys is to filter the salt and water from the bloodstream and an arrangement of longish-shaped cells could account for this function.

    Cells from the cardiac muscle in the heart were then examined. The arrangement in this organ is very different from the cell arrangement in the other two organs previously observed. The lumen is arranged in a stringy longitudinal way. The cells are longitudinal as well and are tightly packed. This is probably to enhance the function of the heart, since such narrow passageways would regulate blood flow and balance the pressure of blood flow as well.

    We found out that the cells in the different organs were not the same after all and the reason would be that they have different functions and even if the functions are carried out harmoniously, they are still different functions being carried out by different organs.


    Today's Lab
    Name: Bobbie, An
    Date: 2002-11-20 14:23:00
    Link to this Comment: 3810

    Our group examined the Esophagus, Trachea, and the Heart.
    In the esophagus, we found three different types of tissues as well as three different types of cells.
    The tissues were in cirgular arrangement with consolidated layers. In the trachea, we found four different tissue types. The tissues formed rings around each other.
    In the heart, we found three different types of tissues and three different types of cells. We do not believe that an organ can be formed from cells of another organ.
    The way we could differentiate between the esophagus and the trachea was that the trachea needs to be rigid, solid, and fixed in shape in order to take air in and out. The esophagus, on the other hand, can be soft and bendable. There does not need to be as much open space for it, because it is pushing the food down. The lumen for both need to be fairly large, but larger for the trachea because the amount of air going through needs to have space.


    Almost Thanksgiving
    Name: Brie and D
    Date: 2002-11-20 14:23:11
    Link to this Comment: 3811

    We looked at HJ 1-2 (Lung) and HJ 2-11 (Esophagus and Trachea).

    1. # of Cell Types/Tissues
    Trachea=4-5
    Esophagus=3-4
    Lung=3-4

    2. Arrangement of tissues w/in entire organ
    Trachea=4 layers; cartillage type cells to help keep structure rigid and open for air, more lumen than esophagus.
    Esophagus=muscular layers, darker layers around lumen, outside shredded layer.
    Lung=mostly spongey layer that looks perforated, a lot of air. Oval longer shapes in the spongey layer, thick dark layer around lumen, tiny dark spotty layer around lumen.

    3. Can one organ be formed from the cells of another?
    No! If the esophagus was made from Trachea cells, it would not be able to perform peristalsis which would result in choking and suffocation. The trachea must be rigid to prevent choking and allow air to flow continuously. The lung tissue must be expandable to allow the influx of air.

    3a. Are they made of different types of tissues? Yes! Rigid vs. Muscle vs. Airy !


    Cell Lab
    Name: Chelsea, M
    Date: 2002-11-20 14:37:38
    Link to this Comment: 3812

    Testes
    a. small, narrow cells present in clumps (sperm cells)
    b. rounder, larger cells that make up a lining around the clumps
    c. lumen between the sperm and lining cells
    function: the lining may be present to protect (cushion) and contain the sperm cells

    Ovaries
    a. outer lining cells which resemble the cells in the testes
    b. inner lining cells present directly around the egg cell which are the same kind as the outer liner cells but located in a different place
    c. egg cell with a membrane
    function: outer and inner liner cells protect and contain egg cells. the outer cells form a cushion around the egg to protect it from destruction.

    compare:
    the lining cells of the testes and ovaries seem to be simiar and perform a similar function- protecting the reproductive cells

    Lung
    a. many of the same type of smaller cell with large, round lumen gaps in between groups of cells
    b. pink, spongy-looking groups of blood cells present in clumps throughout the other cells.
    c. there are blood vessels throughout the lung cells
    function: the cells form gaps in between for the purpose of flexibility and being able to hold oxygen. lungs need to expand and contract to take in air.
    the blood vessels and blood cells are present because blood flows through the lungs to become oxygenated.

    Can one organ be formed from the cells of another?
    From looking at the cells, we noticed a lot of similarities, but we think cells are specialized to organize themselves in a certain pattern depending on what organ they make up. As a result, cells from one organ can't rearrange themselves to form another.


    testes! ovaries! heart!
    Name: jodie and
    Date: 2002-11-20 14:43:01
    Link to this Comment: 3813

    Joannannanna Ferguson and Lauren Friedmano
    If the pictures don't work, bite me. No, both of us.

    Testes: There are three different kinds of cells we observed in the testes. The first kind, oblong in appearance, seem to be spread between the main cell groups. These cell groups are themselves made up of two kinds of cells. One of these forms a boundary for the cell group; the other is contained within the group. It's like one of those balloons with confetti inside. (See Figure 1.1.) You know. The balloon and the confetti make up the "cell group," but the balloon is made up of one kind of "cell" and the confetti is made up of another kind of "cell." The second cells, which are the balloon cells, are sort of rectangular, with the nucleiaeouii toward the outside. The confetti cells are actually sperm cells, some of which appear different since they regenerate every 70 days. they are basically little spikes of color with bluriness around them. ha ha! and so, we conclude that the testes have three different types of cells.


    Fig 1.1: A confetti filled balloon. The confetti would be one kind of cell, and the balloon would be another.

    Ovaries: The ovaries are very special to us. We have them, after all. (One of us also has testes, but we're not going to tell you who. Guess.) The structure of the cells within the ovaries is similar to that of the testes. We have determined that there are indeed three different types of cells contained within these wondrous little organs. The first type (which resembles the first type described in the testes) is also oblong in nature, with a stringy-seeming consistency and visible nucleeeeeaauoui. There is another balloon-like structure with cells that form the "balloon" and cells that form a sort of "toy" inside. (See Fig 1.2.) (IT'S A BOY! but it's actually a girl. ovaries. get it?) The cells in the middle have four layers. The outside layer looks like a bunch of nucleaeauai, possible cells that will eventually become fully-formed egg cells. The next layer is like the shell, containing the "egg white" and the "yolk" inside of it. (The nucleus is the "yolk," the "egg white" is the "stuff" surrounding it.)


    Fig 1.2: A balloon with toys inside. Imagine it with only one toy. The toy would be one kind of cell, and the balloon would be another.

    Heart: The outer layer of the culture is made of of small, dark cells. Inside this boundary, there is mostly one kind of cell, which has a rather indefinate form and are all irregularly shaped. They all seem to be "flowing" in one direction. There is a "chamber" in the heart full of blood cells, a third type of cell. These "chambers" are bound by the same type of cell that bounds the whole culture (the small, dark ones). Thus, we conclude that the heart has three clear different types of cells, probably more.


    Fig 1.3: A heart. (Not anatomically correct.)


    examining cells (your mom)
    Name: Mer, Chel,
    Date: 2002-11-20 14:49:27
    Link to this Comment: 3814

    Lab: examining the cells of a pig's liver, kidney and heart

    Pig liver: At least magnification there appear to be two different types of cells. There appear to be purple veins intersecting the pink portion of the cells. The smaller of the two (orange colored cell) seems to be surrounded by the bigger (pink colored cells) appearing as pistol surrounded by petals.
    After increasing the magnification by one level, there appear to be three differnet types of cells: The original pink cells, the orange cells in the middle and other smaller pink colored cells separating the orange and pink cells from each other. They fit in perfectly into the mold. It is possible that this is just a lumen filled up with somthing other than cells. At this magnification the size differences become clearer and the small orange cells in the middle are visibly smaller compared to the others than we first assumed.
    After increasing the magnification by another level, there appear to clearly be no more than two differnet types of cells: The pink cells surrounding the orange centers. The pink mass inbetween the two, that we thought might be another type of cell, has turned out to be white instead and a clear lumen.

    Kidney, non-med: At least magnification there appear to be three differnet types of cells. There are big pink masses that look like cells, orange cells pulled in oval circles and smaller pink cells that have lumen in their centers.
    At greater magnification there seem to still be three different types of cells but the arrangement becomes clearer. It seems that the cells are within each other starting with the small pink ones that at this magnification look like thumb prints with a white hole in the middle, the next circle are the orange cells and these are in turn surrounded by the huge pink mass we discribed earlier.
    At even greater intensity the orange mass we assumed to be another type of cell resembles blood vessles instead. We believe now that there are only two different types of cells in the kidney. There is a light pink mass that is clearly a cell type (with white lumen all throughout the mass) and a deeper pink colored cell type that is stringy.

    Spinal cord: At least magnification there appear to be three different cell types. There is a cell type in the middle that is surrounded by a great space of nothing. Further out, there is a cell type that is shaped like a butterfly. This cell is surrounded by a mass of less intense pink almost orange color. This massive cell type is of oval shape.

    At greater magnification there appear to be three different types of cells. There is the small pink cell in the middle surrounded by lumen, the dark pink cell type and the pink cell typ on the outside. The second cell type from the inside is very dense compared to the outside cell type is spaced out with little "buds" connected by longer cells of the same type.

    We believe that it is possible to form one organ from the cells of another organ. There were some cells in the liver that look like they could be closely related to the cells of the kindey and vise versa. But, in comparing the liver or kidney cells to the spinal cord cells, it is more than apparent that the spinal cord cells are completely different. Whereas the liver and kidney cells were boxish of different shapes and sizes, the spinal cord cells were bunched, almost as if being "baby's breath." We think that the budding is conducive to transfering information, but we would need more testing to be positive.


    Cells, cells, everywhere
    Name: Will and E
    Date: 2002-11-20 14:50:10
    Link to this Comment: 3815

    We first examined ovaries:
    There were three cell types we identified:
    1) small ovarian cells that were everywhere, but were arranged in a different manner around the border of the ovary. These cells appeared streak-like throughout the ovary.
    2) egg cells, which were bigger and located toward the edge of the ovary. They ranged in size from almost fully mature (ginormous) to small pre-mature cells. The almost fully developed cells were located within empty space (Lumen!)
    3) hormone producing cells, which bordered the edge of the lumen. These cells were not streaky like the ovarian cells and were generall smaller.

    Testes:
    The sample provided us with a cross section of the many tubes that make up the testes. There seemed to be two types of tubes, with some cells within a tube and empty tubes.
    There were five types of cells we identified in the testes:
    1) The "divider cells" as we called them, formed a divider between the two type of tubes. These cells were streaky and surrounded the main tubes.
    2) The first type of tubes (the ones which contained another type of cells), irregularly shaped, generally bigger than the other tube cells.
    3) Sperm cells, the cells within one of the types of tubes. We were able to indentify the flagellum of the sperm.
    4) The border of the sperm-filled tubes were of a different type, many of which had chromosomes in the process of replicating.
    5) The final type of cell was another type of tube that was not filled with anything. Rather, these cells were in the midst of mitosis AND meiosis, whoa. These were developing sperm cells, and therefore look like a different type of cell.

    Spinal cord:
    "The spinal cord looked stupid" - Erin Myers
    "I wish we had tails" - Will Carroll
    The cell was ovular with an x-shape of a different cell type and a lumen space in the center, with a border of similar cells to the x-shape.
    Two kinds of cells:
    1) The cells not in the x-shape are spongey and irregularly shaped.
    2) The cells in the x-shape and along the border are "super small" and more densely packed in a longitudinal pattern.
    There are also vein-like things running through the less densely packed cells that oringinate in the center of the cell.


    examining cells (your mom)
    Name: Mer, Chel,
    Date: 2002-11-20 15:08:46
    Link to this Comment: 3816

    Lab: examining the cells of a pig's liver, kidney and heart

    Pig liver: At least magnification there appear to be two different types of cells. There appear to be purple veins intersecting the pink portion of the cells. The smaller of the two (orange colored cell) seems to be surrounded by the bigger (pink colored cells) appearing as pistol surrounded by petals.
    After increasing the magnification by one level, there appear to be three differnet types of cells: The original pink cells, the orange cells in the middle and other smaller pink colored cells separating the orange and pink cells from each other. They fit in perfectly into the mold. It is possible that this is just a lumen filled up with somthing other than cells. At this magnification the size differences become clearer and the small orange cells in the middle are visibly smaller compared to the others than we first assumed.
    After increasing the magnification by another level, there appear to clearly be no more than two differnet types of cells: The pink cells surrounding the orange centers. The pink mass inbetween the two, that we thought might be another type of cell, has turned out to be white instead and a clear lumen.

    Kidney, non-med: At least magnification there appear to be three differnet types of cells. There are big pink masses that look like cells, orange cells pulled in oval circles and smaller pink cells that have lumen in their centers.
    At greater magnification there seem to still be three different types of cells but the arrangement becomes clearer. It seems that the cells are within each other starting with the small pink ones that at this magnification look like thumb prints with a white hole in the middle, the next circle are the orange cells and these are in turn surrounded by the huge pink mass we discribed earlier.
    At even greater intensity the orange mass we assumed to be another type of cell resembles blood vessles instead. We believe now that there are only two different types of cells in the kidney. There is a light pink mass that is clearly a cell type (with white lumen all throughout the mass) and a deeper pink colored cell type that is stringy.

    Spinal cord: At least magnification there appear to be three different cell types. There is a cell type in the middle that is surrounded by a great space of nothing. Further out, there is a cell type that is shaped like a butterfly. This cell is surrounded by a mass of less intense pink almost orange color. This massive cell type is of oval shape.

    At greater magnification there appear to be three different types of cells. There is the small pink cell in the middle surrounded by lumen, the dark pink cell type and the pink cell typ on the outside. The second cell type from the inside is very dense compared to the outside cell type is spaced out with little "buds" connected by longer cells of the same type.

    We believe that it is possible to form one organ from the cells of another organ. There were some cells in the liver that look like they could be closely related to the cells of the kindey and vise versa. But, in comparing the liver or kidney cells to the spinal cord cells, it is more than apparent that the spinal cord cells are completely different. Whereas the liver and kidney cells were boxish of different shapes and sizes, the spinal cord cells were bunched, almost as if being "baby's breath." We think that the budding is conducive to transfering information, but we would need more testing to be positive.



    Name: kathryn ba
    Date: 2002-12-03 14:23:18
    Link to this Comment: 3938

    http://www.cotf.edu/ete/modules/msese/earthsysflr/biomes.html

    http://www.radford.edu/~swoodwar/CLASSES/GEOG235/biomes/intro.html

    http://earthobservatory.nasa.gov/Laboratory/Biome/

    http://curriculum.calstatela.edu/courses/builders/lessons/less/biomes/introbiomes.html

    Biomes vary with location because of a multitude of environmental differences, such as temperature and precipitation. These factors are directly related to longitude and latitudes, as well as topography.

    Different communities are describes most generally in seven different biomes.
    1. coniferous forest: temperature = -40-20 C / precipitation= 300-900 mm/year
    2. temperatue decidous forest: temp= -30 - 30 C / precip = 750-1500 mm/year
    3. Desert: temp= -3.9 -38 c / precip= 250 mm/year
    4. grassland: -20 -30C / precip 500-900 mm/year
    5. rain forest: 20 -25 C / precip= 2,000-10,000 mm/year
    6. shrubland: 20- 10 C / precip= 200-1,000 mm/year
    7. tundra: -40-18C / precip= 150-250 mm/ year

    Biomes are subject to change due to deforestation, global warming, and climate change. A typical progression is from forest to grassland to desert.


    Aquatic Biomes
    Name:
    Date: 2002-12-03 14:37:04
    Link to this Comment: 3939

    Brenda Zera and Elizabeth Damore

    We chose to compare the different aquatic biomes on Earth. There are two main categories: marine and freshwater.

    Marine: Covers 75% of the Earth. Is comprised of oceans, coral reefs and estuaries. Within the ocean there are different zones (each zone supports a different series of flora and fauna).
    The tidal zone has a lower diversity because the wave action disrupts the area from becoming a stable habitat. Shorebirds will come to feed on what is washed up. The shorebirds will vary on what part of the world you are in: in Alaska, you might find bird like puffins which are adapted to the cold water, while in Florida a heron or egret will be easier to find.
    The pelagic zone (farther out into the ocean) is home to whales, dolphins and other large marine species (as well as lots of plankton!)
    The benthic zone hosts primarily bacteria and fungi.
    The deep sea, or abyssal zone, is very cold yet supports a great biodiversity near mid-oceanic ridges (thermal rifts which heat the nearby water, as well as provide nutrients).
    Closer to the surface, coral reefs surround islands in the tropics. They are home to many different plants and animals. A single reef can support a diverse population.
    The final marine category is estuaries, which is where rivers meet the ocean. The mixture of fresh and salt water creates an enviornment for unique species of trees, birds and other wildlife.

    Freshwater: Must have less than 1% salt content, and is divided into ponds and lake, streams and rivers, and wetlands (this last category is controversial).
    Ponds and lakes have a lower biodiversity because they are isolated environments. Within a single pond or lake there will be many species of fish, birds and amphibians. Species will vary from one lake/pond to another. Fish species vary because they cannot transplant themselves between isolated bodies of water (they [or their eggs] must be carried by birds). The birds will vary from lake to lake because of their mating habits and climatic differences. You're not gonna find a flamingo in Minnesota.
    The next sub-division is streams and rivers. These offer more diversity, but it depends on the type of stream (meandering, braided, etc.) and how turbid the water is. If the water is full of sediment, it will block sunlight (therefore block plant growth), but will offer habitats for fish like catfish. The diversity of a stream/river will increase towards the center of the channel. Along the edge, other wildlife will venture into the water to drink or eat.
    The third category is wetlands. Wetlands are home to acquatic plants known as hydrophytes. Wetlands are placed in neither the freshwater nor the marine category, since both saltwater and freshwater wetlands exist. This difference alone will vary the biodiversity between each wetland.

    a few links:
    http://www.ucmp.berkeley.edu/glossary/gloss5/biome/aquatic.html

    http://www.worldbiomes.com/biomes_aquatic.htm


    Communities
    Name: Amanda Mac
    Date: 2002-12-03 14:48:52
    Link to this Comment: 3940

    Amanda and I were interested in studying the desert community system. The harsh conditions of the desert produce a surprising amount of diversity as species have adapted over time. deserts come in different variations, as we found on http://www.ucmp.berkeley.edu/glossary/gloss5/biome/deserts.html, an excellent source on biomes. These variations are hot and dry, semiarid, coastal, and cold. Mande and i chose to compare hot and dry deserts to cold deserts to note the different types of biological systems that occur and contribute to desert landscapes. Interestingly enough we found that there were many similarities among the two types of desert although they have different climates.

    Hot and Dry:
    "Canopy in most deserts is very rare. Plants are mainly ground-hugging shrubs and short woody trees. Leaves are "replete" (fully supported with nutrients) with water-conserving characteristics. They tend to be small, thick and covered with a thick cuticle (outer layer). In the cacti, the leaves are much-reduced (to spines) and photosynthetic activity is restricted to the stems. Some plants open their stomata (microscopic openings in the epidermis of leaves that allow for gas exchange) only at night when evaporation rates are lowest. These plants include: yuccas, ocotillo, turpentine bush, prickly pears, false mesquite, sotol, ephedras, agaves and brittlebush.

    The animals include small nocturnal (active at night) carnivores. The dominant animals are burrowers and kangaroo rats. There are also insects, arachnids, reptiles and birds. The animals stay inactive in protected hideaways during the hot day and come out to forage at dusk, dawn or at night, when the desert is cooler."

    Cold Desert:The winters receive quite a bit of snow. The mean annual precipitation ranges from 15-26 cm. Annual precipitation has reached a maximum of 46 cm and a minimum of 9 cm. The heaviest rainfall of the spring is usually in April or May. In some areas, rainfall can be heavy in autumn. The soil is heavy, silty, and salty. It contains alluvial fans where soil is relatively porous and drainage is good so that most of the salt has been leached out.

    The plants are widely scattered. In areas of shad-scale, about 10 percent of the ground is covered, but in some areas of sagebush it approaches 85 percent. Plant heights vary between 15 cm and 122 cm. The main plants are deciduous, most having spiny leaves. Widely distributed animals are jack rabbits, kangaroo rats, kangaroo mice, pocket mice, grasshopper mice, and antelope ground squirrels. In areas like Utah, population density of these animals can range from 14-41 individuals per hectare. All except the jack rabbits are burrowers. The burrowing habit also applies to carnivores like the badger, kit fox, and coyote. Several lizards do some burrowing and moving of soil. Deer are found only in the winter.

    Comparision:
    We found that there were many similar animals in both hot and cold deserts which led us to conclude that the harsh conditions and ground brush found in both deserts may make the similarties; such as the kangaroo rats and burrowing predaters. Differances amongst the two desert creatures may be attributed to the homogenous climate of the hot and dry desert to the variations in hot and dry to the cold and moist. This is demonstrated by teh deer that exist in the cold desert during the winter times. We found that these deer most likely leap down the surrounding mountains - as cold deserts are nestled betwixt mountain ranges- when the climates of the mountain become too cold on the tipey tops. Thus, the location of the desert affects whether or not the desert is cold or hot, and also affects teh surounding locations such as teh mountains aroudn the cold desert.


    The "bo...real" forest
    Name: KKS
    Date: 2002-12-03 14:52:19
    Link to this Comment: 3941

    Kate Amlin
    Katie Campbell
    Stephanie Lane

    Web Sources

    http://www.ucmp.berkeley.edu/glossary/gloss5/ biome/forests.html#boreal

    http://www.borealnet.org/overview/whatistheboreal.html

    http://www.borealnet.org/overview/whataretheproblems.html

    http://www.borealnet.org/overview/whycare.html

    In the boreal forest temperatures are generally very low and little precipitation in the form of snow. The plant population is composed of "cold-tolerant evergreen conifers with needle-like leaves like pines, firs, and spruces. The lack of floor vegetation, apart from fungi, is because the canpoy of these trees allows low light penetration so it's difficult for floor or "understory" plants to grow.
    The boreal spatial arangement is effected by humans logging the trees for paper and drilling for oil.
    Before people tree arangement looks like:
    aghe;wagn;asn
    a;genaoighwaoi
    nage;owingaeio
    angeo;inae
    After people:
    B B B B
    B B B B
    B B B B
    In this "emerald halo" there are five thousand species of fungi. This is possible because they are able to grow without so much sunlight. The presence of fungi relates to the fauna population that in addition to woodpeckers, hawks, moose, bear, weasel, lynx, fox, wolf, deer, hairs, munks, and bats, includes squirrels that eat the fungi and spread the spores.
    Obviously there is reason behind the spatial array of the boreal forest.


    BIOMES
    Name: marybeth y
    Date: 2002-12-03 14:57:43
    Link to this Comment: 3943

    Yarimee Gutierrez
    Virginia Culler
    MaryBeth Curtiss

    in our search, we found that "biomes" are basically the different types of ecosystems found on the earth. the most inclusive list we found is as follows:

    rainforest, tundra, taiga, desert, temperate, grasslands, rivers & streams, ponds & lakes, wetlands, shorelines, temperate oceans, and tropical oceans.

    examples for each and explanations:

    rainforest - there are actually 2 types of rainforest, temperate and tropical. we will focus on tropical as it is the more well known of the two. some characteristics is that they are warm and moist and very green with a large array of diverse plant and animal life. in fact, half of the earth's plant and animal species are found in the tropical rainforests of the world.

    tundra - characterized by being fairly stark and barren, year-round. short cool summers, long cold winters. plants grow low to the ground. animals breed fast and are well adapted for the extremely cold conditions, and many animals even hibernate during hte winter months

    taiga -this biome stretches across a large portion of the world. in fact, it is the largest biome in the world. winters are cold. summers are warm. lots of conifers grow here. snow, cold, and a scarcity of food make life very difficult, especially in the winter. some taiga animals migrate south, others go into hibernation, while others just cope. the taiga is characterized by having larger numbers of hte same plant and animal species - i.e. much less diveristy than a tropical rainforest

    desert - There are 2 main types of desert, hot and cold. both get very small amounts of precipitation. Only difference is that cold deserts main form of precipitation is snow, and for warm deserts it's rain. deserts have more plants and animals than people think. in fact, deserts are second only to tropical rainforests in the variety of plant and animal species that live ther

    temperate - temperate climates are those in which there are defined seasons with significant rainfall, just slightly less than that of a rainforest. These areas are also characterized by the presence of deciduous forests and significant coverage by wooded areas. Bryn Mawr, and much of the United States are located in temperate biomes.

    grasslands - Grasslands are typified by low, ground-covering plant life, such as grasses and shrubs. Grasslands are generally located in plains, valleys, and other flat landscapes. The Midwestern United States praries are a kind of this grassland environment.

    rivers & streams - Rivers and streams are one of the primary habitats for aquatic life on earth. Rivers and streams are the homes and breeding grounds for many species of fish, plantlife, amphibians, and others. These waterways are also vital to the suvival of many land species for drinking and bathing.

    ponds & lakes - Ponds and lakes are also the homes of countless fish and animals, but are also hugely important for aquatic plantlife. The stillness of the pond and lake setting is ideal for kinds of algae and others to form on the surface of the water. Again, these bodies of water are important for the survival of surrounding land species, as well.

    wetlands - Wetlands are marshy landscapes that can range from swamps to bogs. Wetlands are key in the sustenance and reproduction of many bird species, as well as some tall grasses and plants. Wetlands also play a key role in the maintenance of the ecosystem in that they often act as a kind of filtration system for the waters before they move on to rivers, streams, ponds, lakes, and oceans.

    shorelines - Shorelines are another aquatic habitat for many shellfish, insects, and grasses, among others. The Shoreline is an environment that is always changing, and quickly. Therefore, all species who live in this habitat are mobile, or firmly attached to the earth or rocks, such as deeply rooted grasses, and barnacles.

    temperate oceans - Temperate oceans share seasons like those familiar to us. These marine habitats are home to both the largest and smallest species known to man.

    tropical oceans - Tropical oceans are most frequently characterized as the homes of coral reefs. These bodies are located in the south Pacific and Indian Ocean.
    http://mbgnet.mobot.org/

    Each of these ecosystems has a very distinct array of lifeforms because the climates have affected the evolution of these species. They've adapted to contend with the different challenges posed by each of these habitats.



    Name: Maggie and
    Date: 2002-12-03 15:02:18
    Link to this Comment: 3944

    Margaret Hoyt, Kyla Ellis.


    We were interested in comparing the different types of forest biomes. 3 different forests exist, Tropical, Temperate (Decidious), and Boreal (Tiaga). We concentrated on Temperate and Boreal forests with the hope of understanding more about biomes and biological communities.

    According to http://www.ucmp.berkeley.edu/glossary/gloss5/biome/,
    "the world's major communities, classified according to the predominant vegetation and characterized by adaptations of organisms to that particular environment"

    In other words, different animals (and plants and insects) live in different environments. The type of climate and vegetation highly influence the type of organisms inhabiting a biome.

    http://www.cotf.edu/ete/modules/msese/earthsysflr/biomes.html suggests that different animals live in different areas because of the weather conditions. Animals must adapt to live in their environment - after living in one particular climate for so many years, their systems become accustomed to the fluctuations of one particular biome.

    In fact, all of the changes that differentiate one type of biome from another are directly responsible for the varying organisms living within. For example, Boreal forests do not let a lot of sunlight reach the understory layers of the forest; therefore, only plants thta do not require large amounts of sunlight can live there. It is a codependent environement: the plants live in a particular biome because of the climate, and the animals live in a biome because of the plants. Therefore, the climate is responsible for all living organisms within a biome.

    Below are the key differences between a Temperate forest and a Boreal or Tiaga forest.

    Temperate:
    *well defined seasons with distinct winter
    *soil is very fertile
    *canopy is moderately dense and allows some light to penetrate through to the forest floor
    *flora: about 3-4 species for every square kilometer.
    According to http://www.enchantedlearning.com/biomes/:
    *Fall Colors: In the Fall, the number of hours of daylight decreases. This causes some plants and trees (called deciduous) to stop producing chlorophyll (a green pigment that converts sunlight into chemical energy) and eventually lose their leaves. During this time, these leaves turn brilliant colors, ranging from red to orange to yellow to brown.
    *Soil: The soil in the deciduous forests is quite fertile, since it is often enriched with falling leaves, twigs, logs, and dead organisms.
    Layers of the Temperate Deciduous Forest: There are five layers (also called zones or strata) in the temperate deciduous forest. These include the:
    * Tree stratum, the tallest layer, 60 -100 feet high, with large oak, maple, beech, chestnut, hickory, elm, basswood, linden, walnut, or sweet gum trees.
    * Small tree or sapling layer - short tree species and young trees.
    * Shrub layer - shrubs like rhododendrons, azaleas, mountain laurels, and huckleberries.
    * Herb layer - short plants.
    * Ground layer - lichens, clubmosses, and true mosses.


    Boreal or Tiaga
    *short, moist, warm summers, and long, cold, dry winters.
    *soil is thin and acidic, is rocky and has deep gorges often frozen over with water.
    *canopy is thick and allows almost no light to reach understory
    *flora is comprised of only cold-tolerant evergreens
    *taiga, also called a boreal forest or northern coniferous forest, is a cold woodland or forest. This biome span the northern parts of North America, Europe, and Asia. Taigas are generally located south of tundras and north of temperate deciduous forests and temperate grasslands. The taiga is the largest land biome on Earth, covering about 50 million acres of land (20 million hectares); this is about 17% of the Earth's land area. Taiga is a Russian word for marshy pine forest.
    *The taiga is characterized by a cold, harsh climate, a low rate of precipitation (snow and rain), and short growing season. There are two types of taigas: open woodlands with widely spaced trees, and dense forests whose floor is generally in shade.
    *Taigas are relatively low in animal diversity because of the harsh winters. Some taiga animals are able to cope with the cold winter environment, but many migrate south to warmer climates during the winter and others go into hibernation.

    Because of the temperate climate, fertile soil, moderate canopy, and sunlight, a plethora of animals and other organisms inhabit a Temperate forest. Whereas the Boreal forest has little sunlight and extremely cold temperatures, the organisms and animals living there are less in number.

    Studying forests is very important for the advancement of mankind. Potential medicines and undiscovered plant speicies could exist. The trees seem to exist as a buggering agent for the ozone layer and the effect of global warming. And because all of the organisms within the forests have evolved together, the resulting biome is interdependent.



    Name:
    Date: 2002-12-03 15:07:48
    Link to this Comment: 3945

    Websites:
    1.www.bio.bris.ac.uk/research/community/

    2.www.ucmp.berkeley.edu/glossary/gloss5/biome/

    3.www.emc.maricopa.edu/faculty/farabee/BIOBK/Biobookcommecosys.html

    4.www.pbs.org/wgbh/evolution/library/04/1/1_041_01.html

    5.www.scu.k12.ca.us/pomeroy/1st/Animals.html

    Groups of organisms live together because they are adapted to live with each other. An example of this is the food web, where organisms are interedependent and are adapted to eat what is available to them. It is also important that the food web is not disrupted by one organism not being too overly preyed upon. Groups of organisms occur in different locations because of the limitations of their geography and because of their specific adaptations. Certain organisms depend on others with which they live to create the environment in which they need to survive.

    Christine Traversi
    Margot Rhyu
    Sarah Tan


    dessert biomes
    Name: Joanna Rob
    Date: 2002-12-03 15:17:47
    Link to this Comment: 3947

    Joanna Robertson
    jen Rusk

    Desert Biomes
    Desert Biomes are the final stage of a biome. Due to global warming and climate change. The Biome cycle starts with aquatic to forest, grassland, and finally deserts. Desert biomes differ according to location. There are four different types of deserts that vary in temperature and location.

    Hot and Dry
    temps on average range from 20-24c. They are located inthe lower latitudes of North America.

    Semiarid
    Temps on average range from 20-24c. They are located in the basins of America, for example in Utah. The Semiarid deserts are similiar to hot and dry deserts.

    Coastal
    Temps on average range from 13-20c They are located on the coast of chile.

    Cold
    Temps range from -2-4c. They are located in colder climates, such as Greenland. Cold deserts has precipatation due to snowfalls. As a result there are plant life and animal life as such as deers and rabbits. Opposed to the other 3 which contains lizards.

    In general the mortality rate in desert Biomes are higher than Rain forest. In hot and dry deserts plants absorb and store water becuase there is a lack of rainfall.
    http://www.ucmp.berkeley.edu/glossary/gloss5/biome/deserts.html

    http://www.cotf.edu/ete/modules/msese/earthsysflr/biomes.htmlhttp://www.cotf.edu/ete/modules/msese/earthsysflr/biomes.html


    tropical rainforests
    Name:
    Date: 2002-12-04 14:16:40
    Link to this Comment: 3955

    Roma Hassan and Melissa Brown

    We decided to investigate the climate and environment of rainforests.
    Tropical rainforests are complex ecosystems, which are made up of four distinct environments. These "sub-ecosystems" are referred to as levels. In each level, animals and plants have adapted to the existing environmental conditions. The different levels are: the emergent level, the canopy, the understory, and forest floor.
    Tropical rainforests are spread over the Americas, Africa , Asia and the Caribbean with the largest portion found in Puerto Rico and Trinidad.
    Lush vegetation, rainfall througout the year and a high temperature make the rainforest one of the world's most diverse ecosystems.
    Rainforests are a product of planetary processes and are - in turn - contributors to the water and carbon cycles on which all life depends. Rainforests control climate by influencing wind, rainfall, humidity and temperature. They recycle water, oxygen and carbon which reduces soil erosion, flooding and air pollution.
    More than 65 million years old, rainforests are the oldest major vegetation types on Earth. Fossil records show that the forests of Southeast Asia have existed in more or less their present form for 70 to 100 million years.
    Certain environmental conditions must be present in order for the delicate balance of rainforest to be held intact. There must be substantial rainfall (at least 80 inches) of rain each year, but many rainforests receive in excess of 200-300 inches annually.
    Because rainforests are in tropical areas, they have a very hot, wet climate. Temperatures can be above 24 degrees centigrade all year round and rainfall levels can be up to 2,400mm a year.
    The soil in the rainforest is 4 inches deep with a layer of clay beneath, hence trees have shallow roots.
    A variety of living organisms at all different sub-ecosystems exist in the rainforests. Tropical rainforests contain more than half of the Earth's plant and animal species, yet cover only about 7% of the earth's land surface. A typical forest in the United States contains from 5 to 12 different kinds of trees, while a typical rainforest may have over 300 different kinds. If the rainforests are destroyed, most of these plant and animal species will be lost forever. The different species of plants and animals along with microscopic living organisms co-exist in their own way in the rainforests. In just four square miles of some Rainforests you might find over 750 species of trees, 1500 types of flowering plants, 125 different kinds of mammals, 400 different birds, 100 reptiles, 65 amphibians, and a staggering number of insects. One quarter of today's pharmaceuticals come from Tropical Rainforest plants.
    The Amazon Rainforest is the richest biological incubator on the planet. It supports millions of plant, animal and insect species - a virtual library of chemical invention. In these archives, drugs like quinine, muscle relaxants, steroids and cancer drugs are found. More importantly, are the new drugs still awaiting discovery - drugs for AIDS, cancer, diabetes, arthritis and Alzheimer's. Thus it is very clear that the rainforests are a major part of life on earth and all living organisms are dependent on this biome in some way or another.
    Loss of these incredibly diverse forests would be a serious loss for people everywhere. The loss of thousands of acres of tropical rainforests is already causing serious local problems, including increased soil erosion and water pollution. As more deforestation occurs, the problems will increase.
    People don't have the right to destroy the world's rainforests and other habitats for their own purposes.
    IDEA: Further investigation can be carried out on the differences between tropical and temperate rainforests.

    WEB REFERENCES:
    http://www.animalsoftherainforest.org/map.htm
    http://www.orecity.k12.or.us/ogden/BBBeck/TropicalRainforest.html
    http://www.stemnet.nf.ca/CITE/rainforest_what.htm



    Name: Rosie, Ana
    Date: 2002-12-04 14:19:20
    Link to this Comment: 3956

    We observed organisms that live in both the desert and the arctic. Organisms are grouped together because of adaptations that they have made to specific climates. The climactic characteristics for the desert are harsh environments, very dry, and very little rainfall. There is limited plant and animal life as well. Animals in the desert have adapted to cope with lack of water, extreme temperatures and lack of food. They emerge at night to collect food in order to avoid high heat.

    The climactic charactetic he arctic are cold, windy temperatures, and often snowy biomes. Dry air, wind, and snow are part of the climate. 90% of the land area is covered with hardy, cold-and-dry vegetation. Animals that live in the Arctic are adapted to extreme conditions. Those with coats, have coats that thicken and change color to white in order to be camoflouged with the snow. Many animals also hibernate.

    ArcticAnimals


    desert life
    Name: Brie Miche
    Date: 2002-12-04 14:31:37
    Link to this Comment: 3957

    DESERT LIFE

    There are four different types of deserts. They vary in
    temperature and location.

    Hot and Dry
    20-24c. Lower latitudes of North America.

    Semiarid
    20-24c. Basins of America (Utah). Similiar to hot and dry deserts.

    Coastal
    13-20c. Coast of chile.

    Cold
    -2-4c. Colder climates (Greenland). Cold deserts have precipitation due to snowfalls. Plant life and animal life exists.

    Plants and Animals have adapted to these extreme desert climates. The lack of water creates a survival problem for all desert organisms, so they have evolved behavioral and physiological mechanisms to avoid excess heat, dissipate heat, retain water, and acquire water.

    To avoid heat , many animals (especially mammals and reptiles) are active only at dusk and again at dawn. Likewise, many animals are completely nocturnal, restricting all their activities to the cooler temperatures of the night. Bats, many snakes, most rodents and some larger mammals like foxes and skunks, are nocturnal, sleeping in a cool den, cave or burrow by day.

    To dissipate heat , many desert animals are paler than their relatives elsewhere in more moderate environments. Pale colors may be seen in feathers, fur, scales or skin. Pale colors not only ensure that the animal takes in less heat from the environment, but help to make it less conspicuous to predators in the bright, pallid surroundings.

    Some animals retain water by burrowing into moist soil during the dry daylight hours (all desert toads). Some predatory and scavenging animals can obtain their entire moisture needs from the food they eat (e.g., Turkey Vulture) but still may drink when water is available.

    Acquiring water in the desert is a challenge. Kangaroo Rats, for example, live in underground dens which they seal off to block out midday heat and to recycle the moisture from their own breathing. They also have specialized kidneys with extra microscopic tubules to extract most of the water from their urine and return it to the blood stream. Much of the moisture that would be exhaled in breathing is recaptured in the nasal cavities by specialized organs.

    Thousands of animal species exist in the desert. Obviously, the extreme conditions have created a need to evolve and adapt their needs to the environment. Desert animals are characteristic to this environment because if these animals were relocated, they would have no need for these specializations. Their adaptations would be detrimental in a different environment. If a desert animal was relocated to a tropical environment, retaining water might result in drowning. Pale coloring that helps to dissipate heat in the desert would make the animal a target in a darker, greener biome.

    Plant Life in Deserts
    Most desert plants are succulents, meaning they store water to survive the dry, hot, desert climates. One of the most well known species of desert plants is the cactus. The Saguaro Cactus has grows in a dry hot desert climate. It's waxy skin helps it keep water in. When it rains, the Saguaro Cactus soaks up water and holds it in its ribs. The ribs on the plant expand to absorb a lot of water. The plant itself does not need a lot of water to survive. It depends on heavy winter precipatation. During dry periods, the Saguaro Cactus uses water it has stored. The Saguaro has a very special root system. It has two sets of radial roots, a thick set about one foot long, and a thinner set which is often as the same length as the height of the cactus itself. The Saguaro, like many other species of Cactus, has 3-4 inch spines to protect it from predators. In addition to protection from predators, these spines help cool the outer skin of the plant, as well as redirect the wind and insulate the outer skin of the cactus. The Saguaro typically flowers at night when it is cool. Animal and insect species that live in the same environment are: long-nosed bats, bees, wasps, ants, butterflies, and some small rodents, like pocket mice.

    For More information:

    Mojave Desert
    Desert Plants
    Desert Animal Survival
    Desert Biomes

    Organisms live in characteristic environments. Desert Life is related by certain adaptations to their environment. Therefore, if life from other climates and conditions were relocated to the desert, they would not survive.


    Tundras
    Name:
    Date: 2002-12-04 14:40:19
    Link to this Comment: 3959

    Laura Silvius
    Tegan Georges
    CR

    In investigating websites on the ecosystem known as the tundra, we found observations which show organisms which are interdependent and existing in specific, cooperative communities. This system of organisms, like other systems which we have studied, exhibits a quality of being substantially influenced by the physical conditions in which it exists. The thick protective fur pocessed by the musk ox of the tundra is one instance of the relationship between organisms and the physical conditions under which they live and have evolved. It's fur is composed of two layers: an outer protective layer and an under layer which is nearly waterproof (The Tundra Biome). Examples of the interdependence of organisms includes the presence of lichen in the tundra, which then provides sustinence for caribou and musk ox (Tundra Plants).
    The teperature in the tundra tends to range from -40 to 18 degrees celcius (Earth Observatory Tundra). The ground is permanently frozen -- permafrost (The Tundra Biome), and thus soil in a form useable by plants only exists in small clumps, like in cracks between rocks. The bacteria that can survive in such conditions in turn enables specific low-growing shrub-like plants to grow.
    It can be infered that, as tundra organisms have developed under similar conditions (i.e.: those of extreme cold and little moisture) they have also developed to be dependent upon those things which are available under those conditions, leading them to evolve into interdependent communities.


    biomes: tundra vs. grassland
    Name: Laura B. a
    Date: 2002-12-04 14:42:39
    Link to this Comment: 3960

    Biomes: Arctic Tundra vs. Grasslands
    Brought to you by: Laura Bang and Adrienne Wardy

      Arctic Tundra Grasslands
    Average Temperatures -34 degrees Celsius in winter; 3-12 degrees Celsius in summer as low as -40 degrees Celsius in winter; higher than 38 degrees Celsius in summer
    Yearly Precipitation 15-25 cm 50.8-88.9 cm
    Characteristics
  • Extremely cold climate
  •  
  • Low biotic diversity
  •  
  • Simple vegetation structure
  •  
  • Limitation of drainage
  •  
  • Short season of growth and reproduction
  •  
  • Energy and nutrients are in the form of dead organic material
  •  
  • Large population oscillations
  •  
  • Permanently frozen soil (permafrost)
  •  
  • Plants are short and group together; adapted to harsh conditions
  •  
  • Dominated by grasses rather than large shrubs and trees
  •  
  • Seasonal drought and occasional fires are important to biodiversity
  •  
  • Drought, fires, and grazing by large animals prevent shrubs and trees from becoming established
  •  
    Location The Arctic regions of the Northern Hemisphere Veldts of South Africa; puszta of Hungary; pampas of Argentina and Uruguay; steppes of former Soviet Union; plains and prairies of central North America
    Plant Life About 1700 kinds of plants: low shrubs, sedges, lichen, reindeer mosses, liverworts, grasses; about 400 varieties of flowers Lots of different kinds of grass; very few tall shrubs and/or trees, although there are some trees in river valleys
    Animals lemmings, wolves, caribou, arctic hares, foxes, polar bears, ravens, falcons, terns,... gazelles, zebras, rhinos, wild horses, lions, wolves, prairie dogs, jack rabbits, coyotes, foxes, skunks, badgers, blackbirds, grouses, meadowlarks,...

    For more exciting information about these biomes, go to Biomes.


    Not ALL deserts are created equal!
    Name: Heidi Mer
    Date: 2002-12-04 14:48:20
    Link to this Comment: 3961

    Are all deserts created equal? I think not!

    One of the best known deserts in the world: The Sahara Desert, Africa

    Geographical features: Shallow basins, highest point is 11,204 feet, lowest .....point is 436 feet, 25% sand sheets and dunes, underground waterways.

    Weather: short to medium length dry and humid conditions.

    Two major climates:
    .....dry tropical climate: mild and dry winters, hot and dry season, 1 annual temperature cycle, 5 in annual rainfall.

    .....dry subtropical climate: annual high temp ranges, cold winters, hot summers, two rainy seasons, 3 in annual rainfall at most.

    Vegetation: varied, sparse, include grasses, shrubs, and trees that are .....adapted to unreliable precipitation and excessive heat

    Animal life: varied and numerous, gerbil, jerboa, Cape hare, the desert hedgehog, dorcas gazelle, dama deer, Nubian wild, anubis baboon, spotted hyena, common jackal, sand fox, Libyan striped weasel, and the slender mongoose. Variety of birds also exists.

    The largest block of ice you'll ever see: Antarctica

    Geographical features: 95% ice, 70% of the earth's fresh water is locked .....within this ice

    Weather: coldest temp -129F, high winds

    Climate: less than 2 in annual precipitations, this makes it a desert.

    Vegetation: current tundra cannot have vegetation, fossilized plants have been found from 2 million years ago.

    Animals: exist in water and on coastline, includes macaroni penguins as well as other species, albatross, elephant seals and leopard seals as well as other seals, killer whales and right whales as well as other whales, seabirds.


    Conclusion: Both the Sahara and Antarctica are technically deserts because they each get very little annual precipitation. However, as noted above, the organisims that live within each desert are obviously different. In the Sahara desert, reptiles are the most obvious difference because being cold blooded, they need to remain in an area that remains warm. The other birds and mammals are found in and around oasises for the most part. The Sahara also consists of two subclimates because of the span of latitude in relation to the equator. Antarctica never has a significant difference in distance from the equator to change the climates.

    Antarctica, being almost a complete sheet of ice, is obviously much colder and as a result all of the plants and animals that might live in that climate have a thick layer of fat or other natural protection from the cold. Therefore, the zebra that lives in the Sahara could not live in the arctic and the penguin would probably overheat and die in the Sahara.


    Marine Ecology
    Name:
    Date: 2002-12-04 14:50:21
    Link to this Comment: 3962

    Marine Ecology

    Basically, I looked at "underwater communities" to see why life is "organized", inside them. Obviously, organisms living in water are categorized separately from other organisms for a reason. What I found out from mainly one site is that many different factors create an active aquatic environment. These factors control the distribution of plants and animals in a "liquid column of water". The balance of co-existence and dependency sets the levels of each ecosystem. These elements are viable for life to reach an equilibrium.
    Aquatic ecology is a composed piece of nature developing to a point of harmony within its own set parameters. The sun and gas/liquid forms set the medium for existence and occupation. Boundaries and temperatures distribute plant and organism lives. Consumption and redistribution of energy and nutrients keep the numbers in certain boundaries.



    Name:
    Date: 2002-12-04 14:53:10
    Link to this Comment: 3963

    Websites we forgot to mention:

    Animal Live
    The Living Africa
    Nature: Antarctica-Life In The Icebox


    Forest Biomes
    Name: Maggie Sco
    Date: 2002-12-04 14:59:03
    Link to this Comment: 3964

    The Earth has many different environments, varying in temperature, moisture, light, flora, fauna, and other factors. Each of these habitats has distinct life forms that form complex communities of interdependent organisms. A complex community of plants and animals in a region and a climate is called a biome. I decided to research the differences between forest biomes. There are three types of forest biomes: tropical, temperate and boreal. Tropical forests are what we sometimes call rainforests, and boreal forests are also called tiagas.

    Characteristics

    Tropical
    -greatest diversity of species
    -occur near the equator, within the area bounded by latitudes 23.5 degrees N and 23.5 degrees S.
    -two seasons are present are rainy and dry
    -daylight is 12 hours with little variation.
    -temperature is on average 20-25 C and varies little
    -precipitation is evenly distributed throughout the year, with annual rainfall exceeding 2000 mm.
    -soil is nutrient-poor and acidic
    -canopy in tropical forests is multilayered and continuous, allowing little light penetration.
    -flora (plantlife) is highly diverse, one square kilometer may contain as many as 100 different tree species. Examples include trees (mostly evergreen, with large dark green leaves), plants such as orchids, bromeliads, vines, ferns, mosses, and palms.
    -fauna (animal life) includes numerous birds, bats, small mammals, and insects

    Tropical forests can be further subdivided based on seasonal distribution of rainfall:
    evergreen rainforest has no dry season.
    seasonal rainforest has a short dry period in a very wet tropical region
    semievergreen forest has a longer dry season
    moist/dry deciduous forest has a dry season that increases as rainfall decreases

    Temperate
    -occur in eastern North America, northeastern Asia, and western and central Europe
    -have well-defined seasons with a distinct winter
    -moderate climate and a growing season of 140-200 days during 4-6 frost-free months
    -temperature varies from -30 C to 30 C.
    -precipitation (75-150 cm) is distributed evenly throughout the year.
    -soil is fertile, enriched with decaying litter.
    -canopy is moderately dense and allows light to penetrate, resulting in well-developed and richly diversified understory vegetation and stratification of animals
    -flora is characterized by 3-4 tree species per square kilometer. Trees are distinguished by broad leaves that are lost annually and include such species as oak, hickory, beech, hemlock, maple, basswood, cottonwood, elm, willow, and spring-flowering herbs
    -fauna is represented by squirrels, rabbits, skunks, birds, deer, mountain lion, bobcat, timber wolf, fox, and black bear

    Temperate forests can be further subdivided based on seasonal distribution of rainfall:
    moist conifer and evergreen broad-leaved forests have wet winters and dry summers
    dry conifer forests dominate higher elevation zones, have low precipitation
    mediterranean forests have precipitation that is concentrated in winter, with less than 1000 mm per year
    temperate coniferous have mild winters, high annual precipitation (greater than 2000 mm)
    temperate broad-leaved rainforests have mild, frost-free winters, high precipitation (more than 1500 mm) evenly distributed throughout the year

    Boreal
    -represent the largest terrestial biome
    -occur between 50 and 60 degrees north latitudes
    -found in the broad belt of Eurasia and North America, two-thirds in Siberia with the rest in Scandinavia, Alaska, and Canada
    -seasons are divided into short, moist, and moderately warm summers and long, cold, and dry winters
    -growing season in boreal forests is 130 days
    -temperatures are very low
    -precipitation is primarily in the form of snow, 40-100 cm annually
    -soil is thin, nutrient-poor, and acidic
    -canopy permits low light penetration, and as a result, understory is limited
    -flora consist mostly of cold-tolerant evergreen conifers with needle-like leaves, such as pine, fir, and spruce
    -fauna include woodpeckers, hawks, moose, bear, weasel, lynx, fox, wolf, deer, hares, chipmunks, shrews, and bats

    Conclusion
    Groups of organisms live in the same areas and are associated with each other because they adapted to live in similar environments. Organisms, depending on their specific adaptations, depend on each other and their environment in different ways. The food chain in an example of how animals depend on each other, and plants, in order to live. By looking at the specific information about the three different types of forests, it is apparent that different types of animals and vegetation are found in different environments.


    Sources
    http://www.enchantedlearning.com/biomes/
    http://www.ucmp.berkeley.edu/glossary/gloss5/biome/forests.html


    A Tundra Site we made
    Name: the crew
    Date: 2002-12-04 15:00:27
    Link to this Comment: 3965

    Tundra Website! by Lauren, Carrie, Jodie, and Lawral


    Anonymity
    Name: Catherine
    Date: 2002-12-04 15:27:53
    Link to this Comment: 3968

    The anonymous was me.

    Underwater Life


    Evolution Lab
    Name: Paul Grobstein
    Date: 2002-12-09 21:23:18
    Link to this Comment: 4019

    This lab is intended to give you some experiences with aspects of evolution. It consists of three simulations, all three of which you should explore at least briefly. You should choose one for more extensive exploration and post a lab report on that one.

    The Game of Life, at http://serendip.brynmawr.edu/complexity/life.html

    In this simple "world" random patterns evolve into stable "life forms". Among the questions you might explore are
    • How many different stable life forms can evolve from random patterns?
    • How sensitive is evolution to the particular random starting pattern?
    • By making sufficient observtations, can you work out a set of rules that allow you to predict what life forms will evolve from a given starting pattern?

    The Prisoner's Dilemna, at http://serendip.brynmawr.edu/playground/pd.html

    In this game, the task is to develop a playing strategy which will reliably maximize your income. Are you best off cooperating or competing on every move, or using some combination of the two?

    (Pseudo)-Altruism, at http://www.brynmawr.edu/Acads/Biology/Bio101/prot/pseudoaltruism.html - thanks to Ted Wong - REQUIRES Internet Explorer instead of Netscape

    The issue here is whether individuals who "cooperate" can be evolutionarily successful in the presence of individuals who don't. Under what cirumstances are non-cooperative individuals more successful? cooperative individuals?

    Some additional models to play with (also require Internet Explorer):


    ANTS
    Name: Diana Aman
    Date: 2002-12-10 14:19:53
    Link to this Comment: 4024

    The task of having a proportionate number of red (alturistic) and blue(selfish) is an almost impossible task to achive. The blue ants prey on the red ant's capacity to share. Even when starting with one blue ant, and all of the set levels of trust and alt probability and feidelity set in the preset modes, the blue ants rate of growth is ipressive. It was difficult to keep one population living harmoniously with the other, yet the settings that i found in which both populations remaned stable for an extended period of time was when the initial anti trust was at 47%, and the aulturistic probalibity was set on .1, and the fidelity was at .4, and we started with one blue ant. Over the perdiod the blue ants remained stable, and did not overwhelm the population suddenly, they did so gradually.
    It is important to note that we did have populations where the red ants did dominate, yet only under circumstances in which the blue ants were in a highly adverse situation, (extremly low trust and low aulturistic probability).


    Ants!!!
    Name:
    Date: 2002-12-10 14:31:23
    Link to this Comment: 4025

    Brenda Zera and Elizabeth Damore

    First, we ran a control run from which to base our hypothesis about ant survival.
    Cooperative ants (red): 50
    Selfish ants (blue): 1
    Probability of altruism: 1
    Fidelity: 0

    The two populations crossed at 50 time units. The red ant population crashed, while the blue went up to 967 members and reached an equilibrium.


    From this we hypothesized that if we increased the initial number of red ants that it would take longer for the blue ant population to overtake them.

    Red ants: 100 individuals
    blue ants: 1
    probabilty: 1
    fidelity: 0

    The results were the same as the initial experiment, but this time the maximum ant populations were 1019. (first the red, then the blue) Our hypothesis was proved incorrect!

    We then messed around with the other controls, to see what the effect would be on the population (we wanted to try and keep the red ants alive).
    All experiments were conducted with a 100 red: 1 blue ant ratio


    First, reduced the probability of altruism from 1 to 0.
    The red ants grew to a population of 988. The blue ants had a small population at first, but died out completely by 300 time units.

    Next, we changed the probability to .5 from 1.
    The red increased greatly to 1029, then began to decrease rapidly. The blue ants increased and crossed the red ant population at 100 time units. The red ants flat-lined at 130 time units. The blue stabilized at 1029 individuals.

    Then, we changed the fidelity to 1 from 0, and put the probabilty back to 1 as well.
    The red ants increased to 1018 and stay there. The blue rises slowly, but doesnt get very high. They decrease and eventaully die at 170 time units.

    We then changed the fidelity to .5 and kept the probability at 1.
    The red went up to 955 individuals. They start to decrease (blue rises) at 100 time units. The two cross at 160 time units. Red ants are gone by 254 time units. The blue ants stabilize at 955 individuals.

    Next, we tried the fidelity at 1 and the probabilty at 0.
    The red ants increased to 962. The blue ants stay low and die before 100 time units.

    This time, we put the fidelity at 0 and the probabilty at .1 units
    The red increased to 984; around 250 time units, they dropped. The blue began to rise. Reds decrease some more at 319. Blues rising fast at 400 time units. The blue and red ant populations cross at 502 time units. They stay together (coexisting for a short while) before the red drops and the blue continues to rise (slowly).


    Last test, we put both the probability and fidelity at .5 units
    The red ant population increased to 987 ants. It stays there until 160 time units, when the population starts to go down. The blue ants stay low until 160 when they start to rise. The populations cross at 210 time units. The red ants are all dead by 400 time units and the blue have levelled off around 990.


    When the altruism probabilty was lowered, the red ants were more likely to survive, as well as when the fidelity was increased (this allows altruistic ants to gain energy from each other).

    GO ANTS!


    prisoners' dilemma
    Name: Margot "it
    Date: 2002-12-10 14:48:20
    Link to this Comment: 4028

    We chose to focus on the "prisoner's dilemma" which involved us playing against Serendip. We found that the best strategy for us to get more coins and keep a good average was to cooperate until the end, and at the last minute cheat. this way, serendip could not predict our cheating, which would only give the both of us 1 coin at a time. the only problem that arises is the number of rounds is not constant. this means that you have to take a risk if you really want to profit.

    Sarah Tan
    Yarimee Gutierrez
    Margot Rhyu


    Strategerie
    Name: Midgie
    Date: 2002-12-10 14:57:54
    Link to this Comment: 4031

    We played with the second game, with the gold coins and the pirates.

    We suveyed the different types of strategy involved with the game. Below is an outline:

    A. You can cheat the whole time.
    You will win only by one coin
    B. You can cooperate the whole time.
    You will tie
    C. You can alternate clicking cooperate and cheating
    You will tie
    D. You can alternate cheating and cooperating
    You will tie
    E. You can cooperate the whole time, then anticipate when the "Wizard" will end the game and then jump ahead and cheat just before the game ends. This is risky, and you still only win by five points.
    F. You can choose to cheat first since you will automatically benefit by either one coin or five.

    After the first time cheating, you can either chose to tie (by going back to cooperating) or only increase by one for the rest of the game (by cheating). If you cheat for the rest of the game and only increase by one, the computer dubs you as "Flirting With An Inconcievably Foul Fate" and therefore not be a very nice person. However, you never get ahead by being nice. (You never fall behind either).

    Ultimatley, you can only win by 5 points and the computer will tell you that you can do better. But you really can't.


    the life of a prisoner
    Name: kathryn ba
    Date: 2002-12-10 14:58:05
    Link to this Comment: 4032

    In each trial of the game, the computer starts with cooperation and will mirror your turn every turn thereafter. Consequenly, we, the autonomous party, will always WIN! We did two trials each of all A)of the turns the same B) the turns alternating every other turn and C) alternating every two turns. Each set of two trials started one with cooperation and one with competition. We recorded the averages instead of the ending number of coins because we felt this most accurately represented the ongoing interactions between systems or individual in life ( which is also ongoing). The point, presumably, of this excercise was to find the most lucrative pattern and method of survival for both parties. While the trials show that the strategy of full cooperation was most beneficial for both, we are hesitant to think this finding applies to a larger world context. The game does not account for any randomness on the part of the computer. If this autonomy were added to the simmulation the results would presumably be different.


    the improbability of altruistic action
    Name: KKS
    Date: 2002-12-10 15:05:35
    Link to this Comment: 4033

    Stephanie Lane, Kate Amlin, Katie Campbell

    For this lab we came up with the following hypothesis:
    (As postulated with The Prisoner's Dilemma:) "The best strategy for a given player is often one that increases the payoff to one's partner as well."

    First, we explored The Prisoner's Dilemma by playing the game with four different strategies:

    Strategy #1: We competed each time.
    The outcome: We had 14 coins, serendip had 9.

    Strategy #2: We cooperated each time.
    The outcome: We had 36 coins, serendip had 36.

    Strategy #3: We cheated the first time and then cooperated for the remaining times.
    The outcome: We had the same number of coins that serendip did.

    Strategy #4: We cooperated until the last time when we cheated.
    The outcome: We had 41 coins, serendip had 36.

    This leads us to believe that pure cooperation is not MORE beneficial than our other strategies.

    However, since pure cooperation, in this instance, is defined as your ability to increase your oponents ability and not just your own, we began to question the nature of altruistic action.

    This led us to the exploration of the (Pseudo) - Altruism Game.

    We started out with equal numbers of selfish and altruistic ants, an .5 altuistic probability, and .5 fidelity probability.
    The altruistic ants were extinct around 128 time-intervals.

    When we kept the alruistic and fidelity probabilities at .5, increased the altruistic population to 100, and decreased the selfish population to 10, the altruistic ants became a minority at 90 time-intervals and were extinct at around 319 time-intervals.

    When we increased the fidelity level to 1, kept the probability level at .5, and set selfisth and altruistic ant levels at 50...
    the altruistic ants maintained a population comparable to the selfish ants.

    Therefore, we disproved our hypothesis. We conclude that it is impossible for life to exist, and therefore evolve, with purely altruistic actions.

    The Prisoner's Dilemma showed us that alruistic actions can be beneficial.
    However, our experiences with the (Pseudo) - Altruism experiment prove that pure altruism will inevitably lead to extinction. Since life cannot be substained without some selfish acts, it is doubtful that any action in life is void of selfishness.



    Name: Rosie, Ana
    Date: 2002-12-11 14:26:18
    Link to this Comment: 4048

    The Prisoner's Dilemna

    Alternate cheating/cooperating you can earn a maximum of 5 pts. in two rounds if Serendipity does the opposite of your move.

    Cooperate each time, earn maximum of 6 pts. per 2 rounds and then cheat the last round to earn 5 pts. in the end. If both start to cheat you reduce pts. to only one per round.

    This only works because you are able to predict the computer's move. Also it is necessary to know when the last round is which is a chance because it is whenever the wizard is tired of playing.


    to cheat or not to cheat
    Name: Heidi & co
    Date: 2002-12-11 14:40:46
    Link to this Comment: 4049

    To cheat or not to cheat, that is the question. Whether 'tis nobler to screw the computer over...

    Ok. In the prisioners dilemea we must look at the probability of profit. Serendip will mirror your actions, but always starts off cooperating. If you both cooperate, you will each gain 3 coins. If you both cheat, you will each gain one coin. If one of you cheats and the other does not, the cheater gets 5 coins. Simple, right? Here are the possibilites (excluding random cooperation/competition):

    1. It seems as if cheating is the most profitable way, but if you cheat you will gain 5 coins. Serendip will then mirror your actions. You will then only gain 1 coin each time unless you decide to cooperate while serendip cheats and come off even in the end.

    5 coins
    6 coins
    7 coins

    2. Then maybe cooperation is best. If you do this, you will continue to get 3 coins each and stay tied throughout the entire game. Your overall coinge will be higher than the previous example, but the hightest?

    3 coins
    6 coins
    9 coins

    3. Wouldn't it be better to cooperate up until the last moment, when you cheat serendip? This way you would have gotten many more coins than if you had cheated throughout and an extra 2 coins at the end when you cheat.

    3 coins
    6 coins
    11 coins

    Which is the best strategy? Is there a best strategy? In the game it seems that you should cooperate until just before the end. The problem with this is that we do not know when the end of the game is. We are not told until some limiting number is reached that we have reached the end of the game. Thus, this theory is not as good as it seemed initially. In real life it seems as if it might be the most profitable overall. However, we can not say that this is the best.


    merry christmas.
    Name: see below.
    Date: 2002-12-11 14:50:28
    Link to this Comment: 4050


    We decided to explore The Game of Life.

    :: Observations ::
    No matter how much life you start with, whether a small or large amount, the area will be populated evenly, then eventually kill itself out through overcrowding, and then will finally separate itself into separate, sustainable colonies of either three in a line or four in a square or diamond formation. For example, if every spot is populated, every spot dies out in only one time step. Also, if the player begins with isolated squares of four, no changes occur throughout the timesteps, because the colonies are already stable.


    :: Implications ::
    There needs to be a certain amount of red squares to supply the green squares with what they need to sustain life. When the green squares compete, only the fittest survive. The problem is that there are a limited number of resources (red squares) to go around no matter how many green squares there are. This gives the smaller, more isolated "colonies" a better shot at survival and sustainability.


    :: Conclusions ::
    The best conditions for life exist in the creation of small, isolated colonies in which there is minimal competition for the limited resources. In fact, this formation, which reconciles the competition versus cooperation issue, is the only viable option for continued sustainability.


    This has been a production of Carol Griffin, Joanna Ferguson, Lawral Wornek, Emily Senerth, and Lauren Friedman


    ants are better than cows
    Name: Brie and W
    Date: 2002-12-11 14:56:02
    Link to this Comment: 4051

    When trying to plan your ant farm, and you want nice ants, you should take into consideration the following data: (Remember-red ants are altruistic, blue ants are selfish)

    If you begin with 50/50 selfish/altruistic
    Altruism Probability (AP) = 1
    Fidelity (F) =1
    Results: Red took over after 400 units of time.

    We repeated this test, and the blue held out for 500 units of time until they all died.

    Next...
    Population: 50/50
    AP=1
    F=.5
    Results: Blue took over in 75 units of time

    Population: 50/50
    AP=.5
    F=1
    Results: Equal for a long time, then blue died off slowly but surely.

    Population: 50 selfish/25 altruistic
    AP=.5
    F=1
    Results: Both were steady, with blue higher than red until becoming even, finally red took over and blue died out.

    Population: 50/50
    AP=0
    F=1
    Results: Both red and blue rose quickly, but red died out slowly once carrying capacity was reached.

    Our first test was successful (selfish died) because all of the reds were cooperating with eachother, while blues could not depend on eachother or anyone else. Whereas reds were able to support eachother and thrive!

    In our second test, red ants would get fitness 3/4 of the time, and the blue ants were getting fitness 1/4 of the time, but the blue ants had an advantage because they never had to give up anything, whereas the red ants were supporting both blue and red ants.

    Next, this was the same as the first experiment, but it took longer because altruism did not occur as frequently so the red ants were not cooperating as frequently, so they weren't benefitting as frequently.

    In our fourth test, we started with fewer reds, so the process was much longer. Each state was prolonged because there were fewer ants to begin with.

    Our final test was confusing, because the probabilty of altruism is zero, so noone is giving up anything or sharing, so there should be no advantage and no disadvantage. We expected red and blue to reach steady levels.

    Our conclusion is that the only time red ants will win is if Fidelity is 1. The altruism probability just affects the amount of time it will take. Time is also affected by the population.


    ANTS
    Name:
    Date: 2002-12-11 14:56:17
    Link to this Comment: 4052

    CR
    Catherine Rhy

    Trials and Tribulations of Altruistic Ants

    Trial 1:
    Initial-selfish � 1
    Initial-altruist � 50
    Altruism-probability � 1
    Fidelity � 0
    Outcome: All blue (Time: 126)

    Trial 2:
    Initial-selfish � 1
    Initial-altruist � 50
    Altruism-probability � 1
    Fidelity � 0
    Outcome: All blue (Time: 202)

    Trial 3:
    Initial-selfish � 1
    Initial-altruist � 50
    Altruism-probability � 0
    Fidelity � 0
    Outcome: Some blue, some red

    Trial 4:
    Initial-selfish � 1
    Initial-altruist � 100
    Altruism-probability � 1
    Fidelity � 0
    Outcome: All blue (Time: 100)

    Trial 5:
    Initial-selfish � 1
    Initial-altruist � 50
    Altruism-probability � 1
    Fidelity � 1
    Outcome: All red (Time:158)

    Trial 6:
    Initial-selfish � 1
    Initial-altruist � 50
    Altruism-probability � 1
    Fidelity � .5
    Outcome: All blue (Time: 200)

    Trial 7:
    Initial-selfish � 1
    Initial-altruist � 50
    Altruism-probability � 1
    Fidelity � 0
    SPATIAL STRUCTURE ON
    Outcome: All blue (Time: 100)

    All of this data suggests that pseudo-altruism (that is, "altruism" with 100% fidelity) may be the most conducive to domination by the pseudo-altruistic population.


    Tit for Tat
    Name: Laura and
    Date: 2002-12-11 14:57:22
    Link to this Comment: 4053

    Laura Bang and Adrienne Wardy

    We looked at the prisoners' dilemma game. Serendip uses a very simple (and predictable) strategy called "Tit for Tat". Tit for Tat means that Serendip's default first move is to cooperate, and for every move after that Serendip copies the previous move of its opponent. This strategy is very easy to beat because all you have to do is start out cooperating every time, and then at some point to cheat, and from that point to keep on cheating. This leads to a win of 5 points higher than Serendip. The difficult part is anticipating when the "wizard" will decide the game is over, because you have to make your cheating move before that happens, or you and Serendip will tie. The longer you keep cooperating the more coins you will get overall, but no matter what you can only win by 5.

    The strategy of "Tit for Tat" is encouraging toward cooperation: its first move is to cooperate, then if you cheat it will cheat too, but once you cooperate again "Tit for Tat" forgives you and cooperates again. However, in order to win, you have to cheat.

    This applies to evolution because if we cooperate within and between species, we get more as a whole; but for the most part we act in our own self-interest (trying to win, even though it is only a small win), which leads to survival of the fittest.


    cheeeeeeat!!!!
    Name: Mer and Ch
    Date: 2002-12-11 14:58:45
    Link to this Comment: 4054

    Mer
    Chels

    We decided to play Pirate's Dilemma. First, we tried cooperating each round until the game was over. This resulted in a goodly amount of booty for both players. Then, we decided that cheating is cool, so we cheated until the game was over. Trusting serendip cooperated the first round, giving us 5 more coins-ha! Serendips, unfortunately learns quickly and cheated as well for the rest of the game. We then tried to cheat and then cooperate. Initially the computer cooperated and we cheated, then it cheated and we cooperated and from then on, we both cooperated. We've determined that the computer basis its decisions on what we did in the previous round. Finally, we determined the best way to beat serendip AND have a decent average is to cooperated for approx. 10 rounds, then stab the in the back- bloody landlubbers!!

    We then focused on how many rounds we can play all cheating or all cooperating. We found a negligable difference of 1-2 rounds longer in games where we only cooperated. The average number of rounds when only cheating is 10.5, when only cooperating approx. 13 (one time we had 23, go us!).

    Given these results, we determined that stabbing the computer in the back after the tenth round was most profitable. We also noted that if we were wrong and the game didn't end, we should continue cheating because, once betrayed, serendip doesn't trust us anymore.

    In conclusion, although continually cooperating yields a better average and more coins on average, to beat serendip you must be a blue-blooded, bearded, bastard and cheat at the last minute- harharhar.


    Darwin's Voyage Revisited
    Name: Paul Grobstein
    Date: 2003-09-09 09:53:29
    Link to this Comment: 6386

    Life has recently been discovered on two planets, coded named Nearer and Farther. Survey expeditions are being undertaken to characterize life on each, with the objective of comparing the charcteristics of life on the two planets both with each other and with life on earth. The general effort is to better understand general properties of living systems.

    Expeditionary groups have been formed to undertake an initial survey of "plant" life on Nearer and Farther. Their goal is to try and determine the number of different kinds of plant life on each planet without prior presumptions that categories of plant life on Nearer and Farther are necessarily similar to those on Earth.

    You are a member of one such expeditionary group. Your group must return with a scheme for categorizing plant life on the planet assigned that is clearly described and yields a definite quantitative result for numbers of kinds of plants on that planet. You may also want to consider why the planet contains the particular number of different plants you describe. Your findings will be presented at a conference on "Diversity in BioSystems: New Findings From Additional Cases", focused on the question of whether "diversity" is or is not a fundamental characteristic of living systems.

    Some related readings:


    Lab Report for Elizabeth Bryan, Brianna Twofoot, E
    Name: Elizabeth
    Date: 2003-09-09 14:44:44
    Link to this Comment: 6391

    Common Life Elements:
    -Rooted into ground
    -Soft green leaves
    -Sunnier areas have more abundant plant life
    -Plant life grows upwards
    -They are mobile

    Grass:
    -No stems
    -Comes to a point
    -Thin
    -Grows close to ground

    Trees:
    -Produce leaves
    -Have dark colored bark
    -Have a trunk
    -The largest group found
    -Found five types

    Shrubs:
    -Half a knee to stomach height (5'8 ft. person)
    -Had 3 to 49 leaves
    -Had 2 to 12 parting branches
    -No flowers or buds
    -Scattered location
    -Either oval or pointed extremeties

    Leaves:
    -Some have holes
    -Different shapes and sizes
    -Mostly close to trees


    Planet Nearer Observations
    Name: Talia Libe
    Date: 2003-09-09 14:47:50
    Link to this Comment: 6392

    Upon our landing on the planet Nearer, we were struck by the spledid array of flora. We acknowledge that although we tried our hardest, the list may not be exhaustive.
    We have organized our findings into four categories with their our respective sub-categories. They are as follows:

    I. Ground Coverings (3) - direct ground coverage that varied in terms of color and texture
    II. Low Proximity to Ground (9) - thick, diverse populations of low growing plants
    a) Blade (1)
    b) Leaf
    i) Singular (1)
    ii) Multiple
    1) Smooth edged (5)
    2) Jagged edged (2)
    III. Medium Proximity to Groud (3) - branched entities greater than a foot from the ground
    a) Spiked (1)
    b) Elliptical (1)
    c) Waxed (1)
    IV. High Elevation (2) - vegetation greater than six feet from the ground
    a) Smooth base/vertical branching (1)
    b) Ridged base/horizontal branching (1)
    Total Plant Types Found: 17

    Again, while we recognize that this is not an all-inclusive list, this scheme provides a basis for the categorization of vegetation found in Nearer.

    This system, the Planet Nearer, offered an example of the diversity which can be found in a given area in terms of energy sources and stage of growth. Both aspects are elements which attribute to the diversity and variation among the vegatation of the same type.


    Message 6392 Talia Liben, Abby Fritz, Melissa Hope
    Name: see below/
    Date: 2003-09-09 14:51:56
    Link to this Comment: 6393

    Message 6392 belongs to the individuals listed above.



    Name:
    Date: 2003-09-09 14:58:38
    Link to this Comment: 6394

    Biology 103

    GROUP NEARER: Justine Patrick, Shafiqah Berry, Latoya Lavita, Vanessa Herrera


    Criteria for plant description

    Premise: All specimens observed are living plants.

    Shape, texture, and shape distinguished our observations.

    Specimen # 1: Has attachments that are green star-shaped. There are two cylindrical shaped objects, they appear to be the same shape and size, indicating that they may be of the same species, but texture variations indicate possible reproduction, that is duplication without exact replication.

    Specimen # 2: Amorphous cube, smooth top, rough and jagged sides, pattern of uniform discoloration, appears to be another specimen in and of itself. There is a possibility of it being an older version of specimen # 1, perhaps a fossilization of the cylindrical shapes.

    Specimen # 2a: Green rug-like texture gets less green as the shape declines.

    Specimen # 3: Broad brown surface has two parts interwoven with specimen # 1 into a symbiotic relationship.

    Specimen # 4: Presented in an upright position, it's green, crisp, and easiest to break of all the specimens so far.

    Specimen # 5: Similar to specimen # 1, but shape is not cylindrical. The shorter attachments are closer together and there are more of them. The extensions have pricklier attachments.

    Specimen # 6: Appear to be from the same family, characteristic of having similar organisms growing on them, which may indicate an eco-system within an eco-system within the greater hierarchy of different systems.


    What we have gathered from our overall findings is that plot of"land" we observed is a symbiotic eco- system supporting various life forms while itsef being supported.


    Farther Team 1
    Name:
    Date: 2003-09-09 15:03:16
    Link to this Comment: 6395

    Time: Tuesday, September 9, 2003, 2:37
    Planet: Farther
    Excavation Team: #1
    Members: Michelle Choi, Su-Lyn Poon, Emily Breslin, Brittany Pladek


    Lab expedition to "Farther"

    Observations:

    I. Small (1 ft. and under)
    a. Rooted vs. Unrooted
    b. Clustered vs. Unclustered
    c. Green vs. Brown vs. Yellow vs. Red
    d. Long, pointy, broad, branched
    1. Leaves
    a. tear shaped
    b. jagged tear shaped
    c. heart shaped.
    2. No Leaves
    e. Long, pointy, skinny
    1. Leaves
    a. round
    b. reverse heart
    c. jagged tear shaped
    d. tear shaped
    e. fuzzy
    2. No Leaves

    II. Medium (1-5 ft.)
    a. Pliant vs. Non-pliant
    b. Lowlying vs. Tall
    c. Cluster/unclustered
    d. Rough vs. Smooth bark
    e. Number of branches/types of branches
    f. Leaf Shape
    g. Appendages: berries/none
    h. Thorns/no thorns

    III. Big (over 5 ft)
    a. 1 person to hug vs. 1+ persons to hug
    b. numerous branches vs. minimal branches vs. one big black metal branch
    c. tear shaped vs. rigid tear shaped leaves vs. glove shaped

    Conclusions:

    There are approximately 37 species of plant life in the area we studied. There was a wide range in the size of plants. The reason for this diversity is to allow the different plants to take advantage of limited resources in different ways. The vertical occupation of space, as well as horizontal, allows plants to compete for light, air and space. The sizes cannot be assumed to follow a plant's time line (juvenile, adult, old) as that would be basing our judgments on the case on Earth. Because the period during which we studied these samples is an insufficient timescale to study growth, this remains an unacceptable assumption and thus, we must receive the grant for further observation.


    Planet Nearer Plant Life Analysis
    Name:
    Date: 2003-09-09 15:04:35
    Link to this Comment: 6396

    Our expeditionary force, including researchers Natalya Krimgold, Paula Arboleda, Bessy Guevara, and Laura Wolfe, found many fascinating types of plant life on the planet Nearer and categorized them in this way:
    I. Low-to-the-Ground
    - leafed
    + 1 leafers
    * heart-shaped leaf
    * star-shaped leaf
    * elongated leaf
    + 3 leafers
    + multiple leafers
    - leafless
    + thin
    + thick
    + dry
    + feathery
    + single-stem fluffy
    II. Low-Branch
    - needles
    - leaves
    + shiny
    + matte
    + tiny
    III. Extended Trunk
    - star-shaped leaves
    - tear-shaped leaves
    IV. Fuzzy Stuff
    - dark green
    - light green
    - flaky
    + blue
    + white
    V. Nasty Stuff
    - puffy
    - shelf-like
    - orange

    The "Low-to-the-Ground" categorization describes vegetation that was less than six inches tall and it generally covered a large area of ground space. We broke this category into two sub-categories "leafed" and "leafless" based on the presence or absence of leaves. The leafed sub-category includes further sub-groups based on leaf quantity and shape. The leafless category is further divided into subcategories based on texture and size.

    The "Low Branched" category refers to plant life with stems and branches that expand horizontally starting at ground level. On the stems were either leaves or needles. The leafed sub-group of low branched plant life was divided into Shiny, and Mat refering to the texture of the leaves and Tiny, refering to the relative small size of one variaty of Low branched plant life.

    The "Extended Trunk" category refers to plant life with a thick tall trunk, whose branches expand horizontally. The extended trunk types are further subcategorized by the types of leaves which grow on their branches. They are star shaped leaf and tear drop shaped leaf.

    The "Fuzzy Stuff" category refers to a unique type of plant life that spread out over a diverse array of surfaces includingother plant life and inanimate objects in the environment. The sub-groups were categorized onthe basis of color and texture.

    The "Nasty Stuff" category refers to t he plant life that grows from other oragisms and is also less than 6 inches tall. The Nasty Stuff types are further subcategorized by its physical appearance. These types are "puffy", "shell like", "orange". A unique characteristic of this plant life is that one could see the immature and mature state of this particular organism.

    The expeditionary force discovered five major groups of plant life and twenty-two minor ones in total.



    Name: Sarah, Mar
    Date: 2003-09-09 15:13:09
    Link to this Comment: 6397

    Our observations were made on the planet Farther, and we divided the plant life we saw into 3 preliminary catagories, as we had no tools (sophisticated or otherwise) to measur, we used our bodies for comparison leaving us with the catagories of below ankle (a.k.a. groundcovering), below waist, and above eye-level. There were three main areas on Farther. One area was open and consisted of mostly groundcover with a few organisms that were above eye-level. The second area was densely populated with plant life, primarily above ankle level. The third area was the smallest of the three; the surface of which was significantly different from the others, covered in small pieces of tough, fibrous, dry material, reminiscent of the plants above eye-level. In the open area with relatively few tall (a.k.a. above eye-level) specimens of plant life the groundcover consisted of mainly one species of plant. Overall, we catagorized 5 different kinds of plant life, but we were not able to perform an extensive examination of the 2nd, densely populated area. Also, closer examination may reveal further subcatagories within our current system. Each kind of plant life appeared simliar in structure, but on closer inspection had variation in dimension, coloring, and superficial characteristics. Our findings support the theory of biological diversity is a fundamental part of living systems.

    Groundcover:
    -groundcovering thinned as light diminished
    -common disturbance of ground seems to coincide with a lack of ground covering
    1) Long, thin, fibrous, green leaves:
    -partially subterranean
    -shallow roots
    -pigmentation lessens near the roots
    -variation within stalks (either 1 stalk or multiple)
    -variation of height, but average of Romina's hand length
    2) Single stalk with 3 round/oval leaves:
    -symmetrical discoloration and veins
    -grow in clusters
    -edges are ridged
    Below Waist:
    1) Groups of branches with thicker stems and more leaves:
    -only grew in 3rd (smallest) area
    -leaves are almond shaped
    -leaves have shiny, waxy texture on one side
    -backside of leaves is lighter, duller, and has prominent stem through middle
    -branches were thicker, brown, and sturdy
    Above Eye-Level:
    1) 5-Point Leaf:
    -found on 3 of 4 above eye-level organisms in open area
    -base of plant was brown, thick, with textured, apparently protective covering
    -sturdier build
    -irregular breaks in covering on one of specimens, which seemed suggestive of an unidentifiable, external force
    2) Oval Leaf:
    -only specimen with branches lacking foliage
    -covering of stem was rougher and more textured than 5-point variety
    -many branches were without foliage and were discolored


    Plant Life on Planet Nearer
    Name: Melissa Te
    Date: 2003-09-10 14:35:59
    Link to this Comment: 6406

    Initial assumption: Plants are living organisms that are photosynthetic; therefore, they contain chlorophyl and are green.

    I. Ground Coverage
    a. Plants that grow off of ground
    1. Leaves
    -grows in patches in dark areas
    -grows more plentifully in sunny areas
    2. Branches and Leaves
    -Stem with one leaf
    a. small heartshaped leaves
    b. large elongated leaves
    c. medium oval shaped leaves with stems growing out of middle of
    patches
    d. medium elongated and serrated leaves
    -Stem with multiple leaves
    a. stems with a few larger leaves
    b. stems with many smaller leaves
    c. stems with many smaller speckled leaves
    d. stems with many leaves and fruit
    b. Plants growing on the ground
    1. Hairy looking
    2. Blanket-like
    a. fuzzy and darker colored
    b. granular-looking and lighter colored
    3. Leaf-like with red hairs
    II. Plants taller than 4 feet
    a. Shorter Plants - plants that branch closer to the ground
    1.leaves
    -smaller oval leaves with more leaves on each branch, darker color
    -larger oval leaves with less leaves on each branch, lighter color
    2. needles and fruit
    b. Taller Plants - plants that branch farther away from the ground
    1.star shaped leaves with spiney geometric pods
    2.oval shaped leaves



    Name:
    Date: 2003-09-10 14:41:39
    Link to this Comment: 6407

    The last posting was posted by Melissa Teicher, Anna Marciniak, Lara Kallich, and Alice Goldsberry.



    Name:
    Date: 2003-09-10 14:41:40
    Link to this Comment: 6408

    The last posting was posted by Melissa Teicher, Anna Marciniak, Lara Kallich, and Alice Goldsberry.


    lab report 1
    Name: Mariya Sim
    Date: 2003-09-10 14:50:16
    Link to this Comment: 6409

    So...according to our observations we came to determine that plant life on Planet Farther can be described as semi automonous, with highly improbable assembly, possibly energy dependant and or free floating (with potentiality for random independent movement).
    We developed four broad categories as follows.
    Category 1:\
    Vertical, with trunk and extensions, grounded, with differing leaf-like structures. (30 sub categories)

    Category 2:
    Bladelike structure, no stem or trunk, vertical, grounded (3 sub categories)

    Category 3:;
    Free-floating, elongated round and flat. (5 sub categories)


    September 10th lab-Voyage to Planet Far
    Name: anonymous
    Date: 2003-09-10 14:56:30
    Link to this Comment: 6410

    By
    Kathryn McMahon
    J'London Hawkins
    Flicka Michaels
    Denise Erland

    We arrived at Planet Far and were overwhelmed by the diversity of life. In order to make sense of it all, we developed broad categories into which we grouped the subjects of our observations.

    Realizing the magnitude of our task, we focused on distinguishing the different kinds of life close to the ground. The criteria for classifying our subjects as plant life include the implicated growth found in the various sizes and stages of life that particular subjects exhibited. They also were rooted in the ground signifying permanancy within their life cycle, thus exposing themselves to the elements.

    We noted a variety of texture, shapes, sizes, and colors.

    We divided the subjects into:

    We found three different forms of strands: wide, narrow, and circular. Within these groups there were green and brown specimens, the green more moist and the brown more brittle.

    We had eight different varieties of stems with colorful appendages.

    We had a group of five different longer stemmed, rounded/oval large and flat shaped samples.

    We had six samples with stemmed extensions off of their main shoot.

    Bring it on! :)


    Planet Farther
    Name: Julia Wise
    Date: 2003-09-10 14:57:01
    Link to this Comment: 6411

    Researchers: Julia Wise, Megan Williams, Nomi Kaim, Patty Palermo

    We classifed plant life on Planet Farther based on four categories: number of leaf prongs, length to width ratio,
    Upon discovering a new plant, we first counted the number of leaf prongs, categorizing these in groups of 1, 2-3, and 4 or more. After that, we looked at:
    - # of leaves
    - leaf shape (lobes and notches)
    - leaf size ratios (length to width)
    - leaf vein structure
    - general plant shape and size (length to width/depth ratio)
    - patterns of change in size and shape (tendency to get wider or narrower as height or length increases)
    - # of branches, and branching tendency (# of branching nodes)
    - Texture and changes in texture


    Other criteria that we did not get to measure include:

    -Root structure or what happens where plant connects to ground
    - proximity to other plants like it
    - # of plants per given distance (10 sq. yards)
    - flexibility or rigidity, stability
    - average size
    - leaf thickness
    - presence of seeds/flowers/fruit/spores/etc

    For example, one plant we loooked at had one prong on each leaf, oval-shaped leaves with no notches or lobes, one central vein in each leaf with smaller veins branching from the central one, a total plant height of about 2.5 feet and width of about 3.5 feet, and about 30 main branches coming from the ground.

    Our data:
    Non-leaved plants: 1
    1-prong: 11
    2-3 prong: 3
    4 or more: 5

    Total plant species observed: 20


    Life on Planet Nearer
    Name: group near
    Date: 2003-09-10 14:59:38
    Link to this Comment: 6412

    This report was constructed by Adina Halpern, Maggie Tucker, Lindsay Updegrove, and Stefanie Fedak.

    Discerning life on Planet Nearer was a difficult task indeed. We were able to uncover what we believe to be 22 different species of plant life, with several other objects which classified as inanimate.

    Ground Growth [1-17 types]

    Specimens 1-4: grew closest to the ground, like a blanket over the dirt.

    1.looked and felt like felt and was a deep green color. next was an even 2.darker green with tiny ball shapes composing the covering.
    3.light green and string-like.
    4.light green and found in the far corner of the planet. felt like shag carpet.

    Specimens 5-9: all specimens were less than two inches from the ground, and had visible stems, leaves, and were all green.

    5.ovular leaf shape, and grew in clusters across the planet.
    6.round leaf shape
    7.spade shaped leaves
    8.ridged shaped leaves, with five leaves per sprout, was also a darker hue of green than the other specimens.
    9.ridged and covered with fuzz, three sections per leaf.

    Specimens 10-11: blade like leaves protruding from the ground in clumps. Both types of clumps were green. In the far corner of the planet these clumps grew in a darker green and thicker, perhaps because of the favorable conditions in this portion of the planet.

    10.this type of growth sprouted from the ground, and separated above ground.
    11.this type of growth sprouted and separated below ground.

    Specimens 12-17: ranged in height from 4-6.5 inches off the ground, most were a light green hue.

    12.very thin with no visible leaves but perhaps seedlings sprouting from the weed.
    13.growing close to the ground, with thin leaves.
    14.taller than most weeds, with large leaves.
    15.long, bottom, with leaves on top.
    16.low growing, with many clustered leaves and visible seeds growing on the stalk.
    17.long bottom, with spade shaped leaves on top. the leaves were shades of white, green, and purple.


    Bushes [18-20 types]

    Specimens 18-20:

    18.thin, sharp leaves like pine needles. some berries spotted sprouting from the tips of some of these needles. they appeared to be underdeveloped. branch separated below ground.
    19.shiny, ovular leaves. branches separated below ground, and were a ligher color.
    20.light green matte finish leaves. there was a knotted, twisted trunk, with branches sprouting above ground.

    Very Tall Bushes [2 types]

    Specimens 21-22: About twenty foot tall, cylandrical base, branching out over the entire planet. Extensions of this species were noted to be growing both above and below ground surrounding the tree. Two types of this species were observed.

    21.The base appeared dark brown and chunky, with leaves of a light to dark green hue. These leaves were five pointed. One section of the tree had brown leaves.
    22.The base was smooth and a lighter brown. The leaves were tear drop shaped and of a medium green hue.



    Name: Alison Jos
    Date: 2003-09-10 15:05:11
    Link to this Comment: 6413

    Our group visited planet nearer, found 24 species, and decided to categorize our findings into five groups, as follows:

    "Grass-like" plants:
    -Long-stemmed grass
    -Dry grass
    -Thin/fine grass
    -Regular
    -Thick grass

    "Trees"
    -Maple (?) tree
    "Other" tree

    "Bush-like" plants:
    -Big bush # 1 (smooth surfaced leaves)
    -Big bush # 2 (x-mas, needle leaves), bush appeared 4 times
    -Big bush # 3 (penny-sized, oval leaves), bush appeared 3 times

    "Ground"-coverings, stemmed:
    -Long-stalked w/stacked leaves
    -Uni-leafed "weed" with rigid edges
    -5-leafed with serated edges
    -Uni-leaf, teardrop shape
    -Mini-strawberry plant
    -Three leaved clover
    -Long, seeded, corn-like plant
    -Tiny, muliple-leafed weed
    -Plant with one, fan-shaped leaf
    -Oak-like weed
    -Tri-leafed plant with serated edges

    "Ground"-coverings, non-stemmed:
    -Moss

    Our group was surprised to find the extent to which the plant life on "planet nearer" varied. With ground coverings, in particular, the number of different species of plant life found was extremely surprising.



    Name:
    Date: 2003-09-10 15:21:45
    Link to this Comment: 6415

    Jessica Knapp, Diana Medina, Christina Alfonso, Mariya Simakov


    the last group nearer
    Name:
    Date: 2003-09-10 15:46:14
    Link to this Comment: 6416

    the last group who observed planet nearer (containing 24 species of plants) included : Alice, Ramatu, Rochelle, and Enor


    Further exploration requests approved
    Name: Paul Grobstein
    Date: 2003-09-16 13:04:26
    Link to this Comment: 6493

    The funding agency is impressed by the thought put into the initial explorations and the observations returned, the results of of which have been archived and are accessible as a basis for futher exploration. On this basis, the funding agency agrees to provide, funding for follow-up explorations as suggested by the investigators.


    Follow-up investigations should be undertaken with the same general objectives as the initial exploration but with the following additional recommendations in mind:



    Relevant information about plant life on earth:


    Paula, Bessy, Katie, Melissa, Abby
    Name:
    Date: 2003-09-16 14:33:54
    Link to this Comment: 6494

    Introduction:
    *Upon revisiting Planet Nearer, we reassessed our method of categorization under the following assumptions,
    - that there exists a dominant light source from which certain plants derive energy
    -there exist certain plants that form symbiotic relationships with other vegitation
    -we are making observations based on what we have had the opportunity to see in a given period of time
    -we cannot predict what will come of each plant species that we find, but we can make educated guesses as to how things might progress

    *We have addressed issues that came up in the first presentation of this system of categorization. The first element of the system that we tried to clarify was the size boundaries for each category. We have also considered possible alternative energy sources other than the seemingly dominant one. This is a seemingly simplified system of organization given that we have not been able to examine the internal features of each species.

    Category 1: Immediate proximity to a surface, whether the ground or surface of another organism - a negligable distance from the ground - under 1/2 inch
    A. spongey ground covering that spreads out moreso than growing up
    B. plants that seem to derive energy from plants in Category 4
    Category 2: Low proximity to the ground - from 1 inch to 1 foot.
    A. single blade
    B. leaf-like structure
    1. singular leafed
    2. multi-leafed
    Category 3: Medium proximity to ground - from 1 foot 1 inch, to 6 feet
    A. eliptical shaped needle-like leaf
    B. spiked leaf
    C. oval, smooth, waxy leaf
    Category 4: High proximity - 10 feet and above
    A. rigid base with horizontal branching
    B. smooth, flakey base with vertical branching


    Lab 2
    Name:
    Date: 2003-09-16 14:34:36
    Link to this Comment: 6495

    Natalya, Nancy, Laura, Talia

    Plants:
    I. Green
    A. Leaves
    1. petal-like
    a. single
    ~ star
    ~ heart
    ~ other
    b. multiple
    ~ from-ground
    ~ from-branches
    * diverge at ground level
    + shiny
    + matte
    * diverge from trunk
    + star
    + tear-drop
    2. Needle-like
    B. No Leaves
    1. fuzzy
    a. dark green
    b. light green
    2. blade-like
    II. Not Green
    A. Shelf-like
    1. orange
    2. brown
    B. Flaky
    1. blue
    2. white
    C. Puffy

    This expeditionary team followed-up on the research of the previous expeditionary force on planet Nearer. This group improved on the categorization methods by creating a hierarchy of differences among forms of plant life, whereas the previous group categorized plant life broadly according to similarity of features, without any linkage between categories.
    The categories of the previous group did not relate the different types of plant life to one another. This group's categories, by contrast, are a coherent map of all plants on planet Nearer.


    Report for Brianna Twofoot, Emily Breslin, Shafiqa
    Name: Brianna, E
    Date: 2003-09-16 14:35:40
    Link to this Comment: 6496

    Will's Classification:

    1 Not Green (Brown)
    2 Fleshy mold (1)
    2' Hard mold
    1'Green
    3 Algae: Lichen
    3' Not Algae
    4 No true leaves/small
    4' True leaves/big
    5 ferns
    5' not highly divided
    6 no fruit/prolific wood
    6'flowering plants
    **6.5 Clearly defined trunk (2)
    **6.5' random assembly of branches (7)
    7 parallel veins in leaves
    7' floral veins (1)

    - Found system of organization to be extremely helpful.
    - Last week, without any prior knowledge, each group began by focusing on size of flora and fauna. However, we learned that size was problematic because a younger version of the same species may be mistaken for an entirely separate species due to observation. We felt an additional step was necessary, in order that, by default, size was incorporated into the schema. We eliminated the possibility of error based on age by focusing on the structure of the flora and fauna as opposed to the size alone.
    - This classification is more efficient because it groups flora and fauna together on broader terms.


    Plant lab 2
    Name:
    Date: 2003-09-16 14:56:26
    Link to this Comment: 6497

    Participants: Romina Gomez, La Toya La Vita, Justine Patrick, Manuela Ceballos

    Based on observations made by the eyenad other senses, on Planet Farther, plants can be classified by size:
    Big (taller than 5 ft)
    Medium (above ankle but below waistline)
    Small (below ankle).

    By color: Green or Not Green

    By function (whether they produce flowers, leaves, fruits or not).

    By the shape and texture: description of the leaf-like structure, if it is present, (direction where the veins go (vertical and parallel, or horizontal/diagonal), smooth or rough), or sensory perception of the organism itself.

    By location (where they grow- on the ground, on another organism, in the light, in the shade)

    By characteristics of the stem: for example: brown and hard, none, green and frail.

    What we found:

    A mushroom-like thing: small, fleshy, easy to break, feathery, no fruits, leaves or flowers, brown (not green) , grows in the shade, frail, brown stem.

    Big plant one: no fruits, no flowers, 5 pointed leaf-life structure, with diagonal veins, green that grow in the sunlight, has a stem like structure connected to the ground that is brown, rough, and sturdy). It sheds, and when it does, some of the leaves in the ground become discolored.

    -An independent organism grows from the stem of big plant 1. It is whitish green and rough, very, very small without flowers or fruits. We put it in an independent category, although it is connected to Big plant 1.

    Big plant two: produces fruits - a cluster of samll green, hard berries, no flowers, long, pointy, green leaf with diagonal veins, grows in the sunlight, thick, brown, rough stem (different in texture than Big plant one).

    Grassy-like plant: small, green, does not produce fruits or flowers, grows in sunlight and moderate shade, parallel fibers growing from north to south.

    Medium-flowery-green plant: grows in molch-like shady territory, produces flowers, long, smooth, green leaf that is lighter on the back than on the front, which is waxy and shiny, veins grow diagonally, small sturdy branches that interlock.

    Medium cabbage-like plant: grows in the territory as the previous one, highly textured, dark brown leaf, did not have a visible stem, fragile.

    White flower-like plant: puffy, white, long, thin, green stem with smaller ones that open up to flower, no leaves, looks like earth's cottonballs, grows in the sunlight, no leave-like structures.



    Name:
    Date: 2003-09-16 14:58:52
    Link to this Comment: 6498

    Sarah Kim, Su-Lyn Poon, Maria S-W, Charlotte Haimes, Elisabeth Py, Brittany Pladek

    Critique of Baseline Report:
    -Insufficient number of samples had been taken by the previous group. This resulted in incomplete and therefore highly inaccurate results.
    -The sample size used by the previous group in their classification scheme wasn't diverse or large enough. ( For example, the sample they used did not include a sample of fungus, though it was present in the area.)
    -The previous group's classification scheme underestimated the number of species due to small sample size, as was illustrated by the omission of fungus in the previous report
    -The previous group's use of size as a method of classification proved problematic. A difference in size could simply indicate an organism at a different stage of development as opposed to different species, ex: fully mature maple tree and sapling
    -The previous group's use of size as a method of classification resulted in an overestimation of the number of species.

    Critique of Earth Plant Classification Scheme:
    - The classification scheme did not account for free-standing, un-rooted specimens which on Earth would be assumed dead, but are not necessarily the case on Farther.

    Problems in both schemes:
    -not detailed enough, insufficient categories (didn't differentiate between vein patterns in leaves)
    -location of organisms: it is unclear why organisms grow in certain locations... further investigation could reveal another set of categorizations based on similar observations

    New Categorization Scheme:

    - Made observations on additional and different samples, more diverse selection of specimens in order to obtain more accurate results.
    - Size no longer used as the primary means of differentiating between organisms and therefore not as likely to mistake organisms at different stages of development as different species

    Green vs. not green: Free-standing elements, divided by color, shape, texture.
    Lichens: expand category to include color, texture, location
    Leaves: location (ground/trees), clusters, rooted, shape (jagged/rounded edges), texture (fuzzy, smooth), veins (more categories: not all were strictly parallel or branching)


    Planet Nearer
    Name:
    Date: 2003-09-17 14:31:43
    Link to this Comment: 6511

    Melissa Teicher
    Anna Marciniak
    Julia Wise
    Flicka Michaels

    We classified the plants by Leaves

    I. No Leaves

    -hairy (1)
    -feathery (1)
    -carpet-like (1)
    -flat/thin (looked like cracked paint) (1)

    II. Leaves

    -Needles (1)
    -Parallel Veins (2)
    -Branched Veins
    ---one main wooden trunch (2)
    ---multiple trunks (2)
    ---no trunk
    ------stemmed
    ---------leaves in multiples of 3 (3)
    ---------leaves in multiples of 4 and 5 (1)
    ---------only one leaf (3)
    ---------more than five leaves (2)
    ------non-stemmed (1)

    # of species = 21


    revision of categories of lifeon planet far
    Name: jessica
    Date: 2003-09-17 14:38:05
    Link to this Comment: 6512

    Jessica Knapp, Katy McMahon, Lara Kallich, Nomi Kaim

    Having looked at previous analyses of plant life on planet far, we found the systems of categorization to be insufficient. Specifically, we were troubled by the use of categories that occured along a gradient, and therefore had no distinct divisions amongst them. Our new system utilizes categories that are drawn from far less arbitrary distinctions.

    The past categories were based on qualitative definitions of color, shape, texture, and size. We reformed each as follows:

    - color: green or not green

    - shape: monochot or dichot
    the basis for the categorization is the structure. we noticed that plants which appeared to have parallel veins generally took on one group of leaf shapes (long and thin), whereas plants which had many branching veins had different groups of leaf shapes (not long and thin). plants that had many divided leaves, constituting one big leaf formed another category.

    - texture: hard and woody or soft and fleshy

    - size, or height: plants that cling to surfaces get a different categorization from ones that appear to rise out of the ground


    Life revision
    Name: Explorers
    Date: 2003-09-17 14:39:18
    Link to this Comment: 6513

    By:
    Rochelle Merilien, Diana Medina, Ramatu Kallon, Denisse Erland, Christina Alfonso, J'London Hawins


    In this new exploration of Planet Far we came to realize that the previous report needed major revision as it did not nearly approximate the intricacies and details of the plant life we were observing. The already mentioned report had 3 major classification, one of which was "free-floating." Including Rock type objects as well as wood chips adn dead leaves. We decided that this category did not fit into any of the descriptions given to us by Prof. Franklin, so left in untampered, leaving room for possible, further "discovery?" as it didn't fit with any of the categories in the given scheme.
    For the remaining categories we did the following:

    Tree like structures were reclassified into 2 groups:
    1. green, woody, dichots (2 varieties)
    a. fruit producing (3)
    b. flat leaves (2)

    Small plants like:
    1. green dichot, flowering (13)
    2. GREEN, dichot (12)
    3. Green, monochot, flowering (1)
    4. Grass like: Green, monochot (6)


    With this we concluded that the categories from the previous exploration had to be reorganized into more detailed sub types, as we were blessed with more information.


    Lab 2
    Name: Nearer II
    Date: 2003-09-17 14:41:18
    Link to this Comment: 6514

    The members of this lab group are Lindsay Updegrove, Margaret Tucker, Mariya Simakova, and Alice Goldsberry.

    To further classify the lant and fungus life on planet Nearer, we used the basic classifications of plant life cited in Will Franklin's Plant and Fungi Key for the Biology Courtyard. We were able to categorize 29 species of Plant and Fungi life.

    Basidiomycota: 3
    Ascomycota: 2
    Lichen: 1
    Bryophyta: 4
    Pterophyta: 0
    Coniferophyta: 1
    Anthophyta: 18
    Monocots: 5
    Dicots: 13

    Disclaimers:
    1) It was difficult to differentiate between one sample of tree bark and an organism of the class Ascomycota as covering one of the trees was a brown to black hard globular substance which could have been either.

    2) There was also an unidentified large brownish-gray object with bryophyte growths which could have been stone or a type of Fungi; we could not tell.

    3) Some items were of the same shape but different colors; i.e. we did not include instances of brown leaves where green leaves of the same shape were already present in our classification.

    4) Our reasons for utilizing this system of classification for plants and fungi on planet Nearer were as follows:

    -We found few exceptions to the rules of this classification
    -It provides a useful vocabulary that we might have a starting point for discourse on the life of Planet Nearer.
    -It eliminated the problem of size in classifying different species as experienced by previous teams of explorers.
    -Just as this system is founded on earth to be a useful differentiation between the life cycles of different species, we believe that a similar premise holds true on the planet Nearer.


    Review of Base Report on Planet Near
    Name:
    Date: 2003-09-17 14:42:30
    Link to this Comment: 6515

    This secondary report was prepared by Stefanie Fedak, Adina Halpern, Allison Jost, and Enor Wagner


    All members of the group agreed that the Base Report prepared by Group Near 2, which was done according to specimen size, was an adequate preliminary observation of specimen characteristics. However, holes existed in the report, because the size categorizations were rather vague. Just because something is a particular size, for example, doesn't mean it can't be associated with things of other sizes.

    By referencing the detailed work done in the base report, and utilizing Will's classifications this exploratory group deems it possible to begin getting these categorizations "less wrong". However, limitations will still exist due to the fact that it is not possible at this time for us to discern some of the classifications Will describes. Further funding would allow the purchase of more advance technology, which would in turn allow us to continue the process of getting it "less wrong". Lastly, the following list has been reclassified after reviewing the base report in conjunction with Will's classifications. It should be noted that Will's report prompted this exploratory group to include several species which had not been classified as "living" in the preliminary report.


    Chlorophyllus:

    Specimens 1-4

    We believe at this time that three of the four initial ground growth species are lichen. These growths appeared light green and stringy, which fits with Will's categorization of the lichen family. The last specimen in this group appeard a very deep hue of green and "clingy" which would correlate with the Bryophyta classification.

    Specimens 5-9

    The team has concluded that speicmens 5 and 8 are dicots because of the appearance of five leaf structures on the specimens.

    This group believes that speicmens 6,7, and 9 are monocots because they came in clusters of three and have a branching vein structure.

    Speicmens 10-11

    We conclude that Specimens 10 and 11 are monocots because of the visible parallel vein structure (and the fact that these are grasses, and Will's classification clearly lists "grasses" as monocots.

    Speicmens 12-17

    This category of specimens is still uncertain, but it is believed that all of these specimens can be categorized as dicots.

    Specimens 18-20

    These species are most likely anthopytha because they were flowering bushes, and this was the best classification within our means.

    Specimens 21 and 22

    21 and 22 are coniferophyta because of the appearance of prolific wood.

    Non-Chlorophyllus

    These were not noted in the base report, but it appears that there is the appearance of both ascomycota and basidilmycota, which would bring the specimen total up to 24 from the initial 22.


    lab 3
    Name: Paul Grobstein
    Date: 2003-09-23 12:38:18
    Link to this Comment: 6585

    As you've discovered, scientific research can be done (and often is done) with vague general questions that in turn motivate making observations that in turn lead to more specific understandings and new questions and hypotheses.

    Scientific research can also be done by using general questions and existing observations to shape an hypothesis that itself motivates new observations. Today's lab is aimed at giving you some experience with the latter kind of scientific research.

    We know that multicellular organisms come in a variety of sizes but that they all have in common that they are assemblies of cells. A general question that follows from this is "is there any relation between the size of an organism and the size of the cells that make it up?".

    Your task today (in groups of two) begins with thinking of some possible general answers to this question, and about which ones make good (ie interesting and testable) hypotheses. You should then pick such an hypothesis and (using tools we will make available, including a microscope) collect relevant observations.

    Your report should include a brief description of your hypothesis and of what motivated it, an account of your observations, and a conclusion in which you discuss the significance of your observations for your hypothesis.


    Natalya Krimgold and Nancy Evans
    Name:
    Date: 2003-09-23 14:50:25
    Link to this Comment: 6587

    The researchers hypothesized that larger organisms are not necessarily composed of larger cells than smaller organisms. This hypothesis was based on the premise that many organism are composed of specialized cells that perform different functions and those cells may vary in size. The examination of four cell specimens from organisms of varied sizes supported the researchers' hypothesis. The four cell specimens and their measurements were as follows:
    1. Elodia, 104 X 26 um
    2. Cheek, 52 um in diameter
    3. Larynx, 20.8 X 5.2 um
    4. Corn Root 26 um to 52 um in diameter
    The Elodia cell is much larger than the cheek or larynx cells although the Elodia plant is much smaller than a human being. In addition cell size within an organism can vary substantial as the corn root cells did which also indicates that cell size does not vary directly with organism size. The exact relationship between cell size and organism size remains to be determined.


    does size really matter?
    Name: Maria Scot
    Date: 2003-09-23 15:00:02
    Link to this Comment: 6588

    Maria Scott-Wittenborn, Michelle HoKyung Choi

    Hypothesis:
    If two organisms (regardless of their size) belong to the same species, then their cell sizes will be similar.

    Motivation of Hypothesis:
    Common sense told us that all cells are not the same size. For example, an ostrich egg is one complete cell while an amoeba is also one complete cell but of significantly smaller size. But within the same species if size differs, then the quantity of cells may differ but the size of the cells which actually make up the organism does not differ.

    Observations:
    (Human)
    5'7" --> 10x = 7 um/OR
    5'5" ---> 10x = 7 um/OR

    (Maple leaf)
    4" --> 10x = 2 um/OR
    1.5" --> 10x = 2 um/OR

    (Clover leaf)
    1/2" --> 10x = 1.5 um/OR
    1/4" --> 10x = 1.5 um/OR

    (Mushroom)
    3/4" --> 10x = 3 um/OR
    1/2" --> 10x = 3 um/OR

    Conclusions:
    From the small sample of organisms we investigated we have concluded that our hypothesis is correct; as long as the specimens are within the same species their cell sizes are the same. However, within our sample of organisms cell sizes proved to differ between species relevant to the organisms' size (i.e. Humans over 5' tall, 7 um; clover leaves smaller than 1", 1.5 um).


    Bio Lab
    Name: Brianna Tw
    Date: 2003-09-23 15:02:20
    Link to this Comment: 6589

    Group: Brianna Twofoot, Brittany Pladek


    Problem: Does the size of cells depend, relatively, on the size of the overall organism?

    Hypothesis: Cells occur in a size range which varies according to the size of the multicellular organism. For example, human cells will be bigger than moss cells.

    Observations (in microns)
    Algae: 4060
    Cheek cell: 3050
    Trachea cell: type 1: 12
    Type 2: 37
    Worm epidermis: ~ 350
    Moss globule: 3050
    Moss strand: ~10

    These observations indicate that cells do not occur in a size-relative relationship. For example, while the earthworm as a whole organism is smaller than a human, the human cheek cells are smaller than the earthworm epidermis cells. However, we must keep in mind that we only sampled a specific type of cell for each organism. There are many different types of cells. For example, of the two moss cell-types sampled, one type was 10 microns in length while one was 3050 microns. We must modify our hypothesis to say that not only do cells not vary in size relative to their greater organism, but cells within a certain-sized organism come in many different shapes and sizes, each different, none relative to the overall size of the organism.


    LaToiya, Katie
    Name: see subjec
    Date: 2003-09-23 15:05:09
    Link to this Comment: 6590

    We started out with the hypothesis that cell size does not have direct correlation to the size of the organism. We based this on the knowledge that organisms are composed of different kinds of cells that vary in size, shape and function. What if a human spinal cord cell is larger than an algae cell, but a human cheek cell is smaller?

    Data:
    Algae:
    - cell #1: 26 um (@ 4x)
    - cell#2: 72 um (@4x)

    Human Cheek:
    - cell #1: 5.2 um (@40x)
    - cell #2: 5.85um (@40x)

    Human Spinal Cord:
    - cell #1: 1.82 um (@40x)
    - cell#2: 2.6 um (@40x)

    Earthworm:
    -cell#1: 13 um (@40x)
    - cell#2: 14.3 um (@40x)

    Based on our observations it seems that our hypothesis may not be correct. From the size of the cells measured, it appears that smaller organisms have larger cells, which means that from the size of the cells you can estimate the size of the organism. Perhaps smaller organisms have fewer, larger cells than larger organisms, which have many small cells. In other words, "size does matter".


    Abby, Melissa, Talia
    Name:
    Date: 2003-09-23 15:05:21
    Link to this Comment: 6591

    Hypothesis:
    There is an inverse relationship between the size of the organism and the size of the cell -- as an organism gets larger, the cells become smaller.
    Our reasoning for this hypothesis was that a larger organism requires more complex functions necessary for survival. Therefore, we thought that smaller cells, and therefore more cells, would allow for these more complex systems to survive.
    From our observations of various samples from organisms of various sizes, we found that our hypothesis was not consistent with the numbers that we collected. First we organized the organisms according to size - largest to smallest: human samples (spinal cord and cheek cells, earthworm, buttercup, paramecium). Then, after collecting our data, we converted all the numbers to one common system and ordered the cells from largest to smallest: cheek cell, buttercup, earthworm, spinal cord, paramecium.
    We disproved our hypothesis! yay!
    According to our findings, which may be flawed because of our lack of experience in measuring cells, it would seem that the size of the organism and the size of the cells do not follow a set pattern.
    Question to consider: would it be more helpful if we could measure the surface area of a cell because of the variance in cell shapes?


    Su-Lyn & Sarah
    Name:
    Date: 2003-09-23 15:05:51
    Link to this Comment: 6592


    Hypothesis:
    The size of the cell is not correlated to the size of the organism. In considering what "relevant samples" to look at, we realized that even within the same organism, there would be different types of cells of different shapes and sizes. This led us to consider the difference between multicellular organisms and single-cell organisms. In the latter case, we imagine that the cell would expand in size as the organism grows. However, the growth of multicellular organisms could affect the size of their cells differently. While these cells could expand as well, we think that an organism would grow primarily by multiplying the number of cells in it. Furthermore, with the higher number of cells, there would most likely be specialization, with different types of cells taking on different functions. Because of this specialization, we could expect cells in multicellular organisms to be smaller and more plentiful.

    Our hypothesis, therefore, is that the size of the cell is not correlated to the size of the organism.

    Account of observations
    Organism (size in micrometers)
    Moss (20.8x31.2 and 9.1x23.4)
    Corn root (40x60 and 50x40 and 70x60)
    Artery (36.4x26)
    Blood cells (3x5)
    Muscles (not measurable too big)
    Cerebellum (5.2x7.8, while some not measurable too small)
    Earthworm (65x5.2)

    Conclusion:
    We feel that the observations refute any direct correlation between the size of the organism and the size of the cells that make it up. Cells clearly exist in many different types and sizes even within the same sample. In the cerebellum sample, we were able to obtain measurements on one type of cell, but not on another. The research supports our initial hypothesis but more money will be required to study a wider range of samples in terms of organisms and cell types.


    Manuela Ceballos and Laura Wolfe
    Name: Manuela Ce
    Date: 2003-09-23 15:06:23
    Link to this Comment: 6593

    Our hypothesis states that we would find larger cells when looking at larger organisms under a microscope. Our observations were:

    Larynx cell = 18.2 micro meters

    Spinal cord cell = 13 micro meters

    Moss cell = 150 micro meters (50 micro meters in width)

    Earth worm cell = 39 micro meters

    Buttercup cell = 48.2 micro meters


    Based on these observations, our original hypothesis was proven wrong. For instance, an earth worm is generally smaller than a human, however its cells were found to be larger. In addition, in each sample we found cells multiple sizes, colors and shapes - the measurements were taken from the clearest areas of vision. This leads us to a more important point - different organisms have different kinds of cells, (in humans, for example, the larynx cells differed significantly from the spinal cord cells). We can suggest, from our observations, that the link between size of an organism and the size of its cells is more arbitrary than we orginally hypothesized. Perhaps if we compared corresponding cells in organisms, such as a human spinal cord cell to a dog's spinal cord cell, we might get closer to finding a relationship concerning size. However, these correspondences are not often present, because plants have no spinal cords, for instance, so we would be required to find a different method of comparison.


    Cell size
    Name: Charlotte
    Date: 2003-09-23 15:06:30
    Link to this Comment: 6594

    Elisabeth Py, Charlotte Haimes

    hypothesis: The greater the size of an organism, the greater the size of its cells.

    Observations:
    - Humans:
    cheek cell: average size = 70 microns
    vein cell: average size = 46.8 microns
    spinal cord cell = 57.2 microns

    - Elodea:
    between 19 and 27 hash marks (X40)
    average cell size = 241.8 microns

    - Wild Algae
    between 14 and 19 hash marks (X40)
    average cell size = 174.2 microns

    Conclusion:
    There is no absolute relation between the size of an organism and the size of the cells that constitute it. As we observed earlier, the elodea's average cell size is larger than that of the human's. We also observed that cells within one organism are approximately the same size.


    Lab3
    Name: Paula & Ro
    Date: 2003-09-23 15:07:10
    Link to this Comment: 6595

    Group Members--Paula Arboleda, Romina Gomez


    Hypothesis: The smaller the organism, the smaller the cell. We felt that the most obvious way of trying to make relationships between these different organisms is to begin by making size/cell comparisons.

    Observations:

    Romina's cheek cell:
    4x--104 mm/or
    10x--70 mm/or
    40X--65 mm/or
    Description: Small, oval

    Paula's cheek cell:
    4x--100 mm/or
    10x--60 mm/or
    40x--59.8 mm/or

    Algea 1
    4x--650 mm/or
    10x--600 mm/or
    40x--26 mm/or (26 was the measurable unit because it extended beyond the measurement capacity of the ruler)
    Description: Long, rectangular, green

    Algea 2
    4x--104 mm/or
    10x--150 mm/or
    40x--130 mm/or
    Description: Small, brownish

    Buttercup Mature Root
    4x--52 mm/or
    10x--6 mm/or
    40x--57.2 mm/or
    Description: Small, circular

    Flowering Plant
    4x--104 mm/or
    10x--100 mm/or
    40x--130 mm/or
    Description: Long, thin, rectangular

    Conclusions:

    Well, our observations have led us to believe that the size of the organism and the size of the cells are independent of each other. For example, we noticed that the buttercup mature root had almost the same size as that of a human cheek cell. We, therefore, cannot say with any certainty that this presumed relationship exists.



    Name: justine &
    Date: 2003-09-23 15:07:56
    Link to this Comment: 6596

    Shafiqah Berry and Justine Patrick
    Hypothesis: Does the complexity of an organism dictate the variety and the complexity of a cell?
    Experiment:
    In our experiment we examined several different types of specimens ranging from plant life to human cheek cells and animal cells. We found that for the plant cells the structure seemed to be very rigid and geometrically shaped. For example in the elodea cell there were elongated strips of cells. The rigid block like structure of the cell components in the middle of the cell indicated the fact that this cell structure made up the cell wall. The simplicity of the cell as demonstrated by the cell patterns indicate the incomplexity of the organism which is a plant. When we viewed the spinal cord or the trachea cells we found much more "diversity" in the cellular structure. Litlle clumps and big sections of cells, it was grreat!! There was an absence of a single pattern. The cheek unlike the other human cells was only a single cell that contained a nucleus. This however does not exclude it from the human cell category because its shape was different from the shape of a plant cell. The fact that there was no cell wall lead us to the conclusion that the cheek cell was human. Other non plant cells included the worm cross-section slide. We viewed that there were concentric circles of cells. The center was larger than the outer rings, think Saturn! not el coche, no the planet.
    In conclusion; aka grand finale- we have new questions such as ; what would happen if a dna gene of a human being was spliced with a cellular wall? what was our hypothesis again? it doesn't matter at this stage. we feel that it does have some correlation to biology.


    does size really matter?
    Name: Maria Scot
    Date: 2003-09-24 13:28:53
    Link to this Comment: 6606

    Maria Scott-Wittenborn, Michelle HoKyung Choi

    Hypothesis:
    If two organisms (regardless of their size) belong to the same species, then their cell sizes will be similar.

    Motivation of Hypothesis:
    Common sense told us that all cells are not the same size. For example, an ostrich egg is one complete cell while an amoeba is also one complete cell but of significantly smaller size. But within the same species if size differs, then the quantity of cells may differ but the size of the cells which actually make up the organism does not differ.

    Observations:
    (Human)
    5'7" --> 10x = 7 um/OR
    5'5" ---> 10x = 7 um/OR

    (Maple leaf)
    4" --> 10x = 2 um/OR
    1.5" --> 10x = 2 um/OR

    (Clover leaf)
    1/2" --> 10x = 1.5 um/OR
    1/4" --> 10x = 1.5 um/OR

    (Mushroom)
    3/4" --> 10x = 3 um/OR
    1/2" --> 10x = 3 um/OR

    Conclusions:
    From the small sample of organisms we investigated we have concluded that our hypothesis is correct; as long as the specimens are within the same species their cell sizes are the same. However, within our sample of organisms cell sizes proved to differ between species relevant to the organisms' size (i.e. Humans over 5' tall, 7 um; clover leaves smaller than 1", 1.5 um).


    lab 3
    Name: megan will
    Date: 2003-09-24 14:37:50
    Link to this Comment: 6607

    Hypothesis- Cells that come from similar species will carry similar traits and sizes. Size alone of the matter from which the cell came from will not affect the size of the single cell.

    Our data-
    Buttercup- measured at 40x, 23or= 53.8 um
    Corn- measured at 40x, 22or= 51.2 um
    Moss- measured at 10x, 15or = 150 um (length)
    Larynx- measured at 40x, 50or = 130 um (length)
    Human Cheek- measured at 40x, 30or = 78 um

    Our observations lead us to the conclusion that size of an organism is not the deciding factor in cell size. We noticed also that while some of the plant samples (buttercup and corn) were close in cellular size, the moss was much larger. So we can also derive that similar species do not necessarily have similar cell size. A question we have from our observations is, is the complexity of the cellular make up of an organism a factor in similarity in cell size?


    cells cells cells
    Name:
    Date: 2003-09-24 14:47:17
    Link to this Comment: 6608

    Enor Wagner and Katy McMahon
    Lab #3
    September 24. 2003

    Hypothesis: There is no correlation between the size of the organism and the size of the cell.

    Observations:
    Spinal Cord - 13 um
    Buttercup - 39 um
    Shark Brain - 36.4 um
    Enor's Cheek - 80 um
    Algae - 169 um


    Our observations support our hypothesis in the sense that cell size had no relation to the size of the organism (seeing as how a human is larger than a tiny piece of algae). Our measurements were based on what appeared to be the average cell size - we measured the longest points.


    Lab 3
    Name:
    Date: 2003-09-24 14:48:07
    Link to this Comment: 6609

    Mariya Simakova, Lindsay Updegrove

    Hypothesis:
    Cell size has no direct relation to the size of the organism. The size of the organism is determined by the number of cells that it is composed of.

    Observations:

    Human Cells:

    Vena Cava: Average 85um
    Cheek cells: Average 70um

    Plants:

    Buttercup Root Cells: Average 46um
    Algae cells: Average 50um

    Conclusion:
    Our observations show that our intitial hypothesis is correct. A human organism is composed of cells of different sizes. If
    cell size determined the size of the organism, the sizes of the human cells would have been the same. Moreover, a buttercup is bigger than an algae plant, but its cells are smaller. Therefore, there is no direct relationship between the cell size and the size of the organism. Rather, we can hypothesize that each organism is composed of different cells and that the cell size varies with the particular kind and function of each cell (for instance, see the discrepancy in the size of different human cells).


    Cell/Size correlation
    Name:
    Date: 2003-09-24 14:48:48
    Link to this Comment: 6610

    Diana Medina
    Jessic Knapp

    Hypothesis: Size of cell ought not have a direct correlation with the size of the orgmanism. Rather, the relation ought to lie in the amount of cells an organism has in accord with it's size.

    Butter Cup: 12um at 40x
    Moss: 7um at 40x
    Cheek: 1um at 40x

    Based on the latter observations we conclude that our hypothesis holds true for the experiment. As shown, the size of a cheek cell was many times smaller than that of a butter cup cell. As is clear, a human is many times larger than a butter cup plant which goes to show that size of cell and size of organism are not directly correlated.


    Cells
    Name: Anna & Ali
    Date: 2003-09-24 14:53:49
    Link to this Comment: 6611

    Hypothesis: We propose that there is no direct correlation between the size of an object and the size if its cells; i.e. A tree's cells will not be larger than an acorn's cells simply because of the size difference.

    Cheek Cells
    -cell 1- 5 um
    -cell 2- 4 um

    Note: In the animal/ human cells it was more difficult to measure, because the walls were globulous and not really as thick, or as perceptible as plant cell walls. All data has been converted.

    Tonsil
    -cell 1- 2.6 um
    -cell 2- 4.6 um

    Shark Brains
    -cell 1- 13 um
    -cell 2- 39 um

    Human Skeletal Muscle
    -cell 1- 22 um
    -cell 2- 40 um

    Spinal Cord
    -cell 1- width 15 um, length 40 um
    -cell 2- width 25 um, length 30 um
    -cell 3- width 20 um, length 20 um

    Alison and I agreed that our hypothesis was workable, but it still remains difficult to come upon an answer. The spinal cord is fairly large, and its cells were the largest, however, the shark brain cell was also comparable, as was cell 2 from the Human Skeletal Muscle. We have no conclusion other than that we believe that the size of cells has nothing to do with the size of the thing they make up. Since cells divide to make new cells, we really cannot make any sort of correlation between the sizes.


    Micro
    Name:
    Date: 2003-09-24 14:55:24
    Link to this Comment: 6612

    Stefanie Fedek and Adina Halpern

    Hypothesis:
    there is no correlation between cell size and organism size.

    In order to prove we will look at cells from organisms of varying sizes. we will look at more than one cell from each organism in order to account for possible variation within the organism.

    Observations:

    1. Corn Cell: 70 um

    2. Human Cheek Cell: 50 um

    3. Elodia Cell: 100 um

    We observed that there is no correlation between the size of an organism and the cell size of that organism.


    Cell size vs. organism size
    Name: Julie and
    Date: 2003-09-24 14:58:48
    Link to this Comment: 6613

    Our hypothesis was that cell size would not be related to organism size.

    Sub-hypotheses included: Cell shape will depend on presence/absence of a cell wall; cell size will depend on presence/absence of a cell wall; cell shape and size will depend on the function of the cell in the organism.

    We based our hypotheses on previous observations collected in former biology classes.

    We recorded the size measurements and shapes of cells from the bulbilis moss, earthworm cells and human nasal cells. Our data were:

    Moss cells (In moss stem): long and thin, average 1,800 micrometers. Shape: rectangular.

    Earthworm cells: average 100 micrometers. Shape: roughly oval or round.

    Human nasal cells: average 650 micrometers. Shape: globby; roughly oval or round.

    Our data and observations support our hypotheses, suggesting that larger organisms do not necessarily have larger cells (moss cells > human cells), and that cell size and shape does depend on absence or presence of a cell wall (the plant cells were decidedly larger, on average, and more rectangular or box-shaped than the animal cells).

    We were not able to collect any data with regards to cell function; however , a new hypothesis would be that the cells in moss stems are long and thin because they are vascular cells, and that vascular cells are generally longer and thinner.


    Lab #3
    Name:
    Date: 2003-09-24 15:00:11
    Link to this Comment: 6614

    Rochelle Merilien, Christina Alfonso, Denise Erland

    Hypothesis: We believe that cell size is irrelevant in relation to the size of an organisim.

    Measurements:
    Spinal Cord 14.0 um
    Worm 36.4 um
    Buttercup 44.2 um

    Our findings suggest that the larger the organism, the smaller the cell size; however it is important to note the limited number of specimens that we measured (3). We are not confident in making any conclusion from our measurements. We feel we would need more specimens of different sizes to have a more inclusive summary of possible observations.


    Lab 3
    Name:
    Date: 2003-09-24 15:07:39
    Link to this Comment: 6616

    Flicka Michaels
    Alice Goldsberry

    Hypothesis: Smaller organisms are made up of smaller cells and larger organisms are made of larger cells.

    Observations:
    Moss- 3 OR at 10x = 30 um for round cells
    1 OR at 10x = 10 um for striped cells

    Corn Prop root- 27 OR at 40x= 70.2 um

    Human trachea- 7 OR at 40x= 18.2 um

    Earthworm- 12 OR at 40 x = 31.2

    Our collection of observations disproved our theory because the corn prop roots and the earthworm both had bigger cells than the trachea cells, although humans are larger organisms than earthworms. Also, corn prop roots had a significantly larger measurement of cells than humans even though they are around the same size.
    So we concluded that the because the organism is large, that does not necessarily mean that the cells of that organisms are large and vica versa.


    Lab #3 Romatu Kallon, J'London Hawkins, Patricia P
    Name: Ramatu Kal
    Date: 2003-09-24 15:10:01
    Link to this Comment: 6617

    HYPOTHESIS:

    We assert that the size of a cell is NOT dependent upon the size of the entire organism.

    MOTIVATION:

    Although we HUMANS are large organisms in relationship to that of a plant, we are compoosed of extremely small cells. Each cellular size depends not upon the size of the organism but is POSSIBLY correlated to the function that cell executes in relationship to the larger body.

    OBSERVATIONS:

    WORM CELL 1430.0 um/OR @ LENS 4X
    FLOWER CELL 91.0 um/OR @ LENS 40X
    J'LONDON'S CHEEK CELL 500.0 um/OR @ LENS 100X

    We find that our collected data supports the original hypothesis, in that the cheek cell of a 5'9.5" human being weighing an undisclosed amount proved to be the SMALLEST cell. While the worm, which is often times squished by the feet of human beings proved to have the LARGEST cell.


    Randomness: A first mover?
    Name: Paul Grobstein
    Date: 2003-09-30 11:54:02
    Link to this Comment: 6710

    Our broad objective today is to make sense and explore the implications of a remark by the physicist Erwin Schrodinger in a classic book called What Is Life? published in 1944.

    The activity falls into three parts. The first we will do and discuss together. From it will emerge an hypothesis that groups will attempt to test with relevant observations. A summary of your observations and the conclusions you draw from them should be the first part of your lab report. Your group will then be asked to make an additional set of observations, and try and come up with an hypothesis to account for it that draws from the first two activities in the lab. The second part of your lab report should include a summary of your observations, the resulting hypothesis, and a suggestion of a set of new observations that could be used to test it.


    Microsphere Observations for Liz Bryan and Romina
    Name: Liz Bryan
    Date: 2003-09-30 14:31:45
    Link to this Comment: 6714

    Hypothesis: Smaller sized microspheres should move greater distances

    Observations:

    8 Micron Microsphere (measured at 4):
    -Quick jiggling movements, all in similar directions
    -Beads are small and circular shaped
    -Microns moved in 2-3 degree distances*

    4 Micron Microsphere (measured at 10):
    -Quick jiggling/jutting movements
    -Outside force is causing them to move in similar directions
    -Microns moved in 2 degree distances*

    2 Micron Microsphere (measured at 10):
    -Faster movement than any other group
    -Microns moved in 1 degree distances*

    *measured using micron ruler

    Conclusion:
    We couldn't really draw an absolute conclusion because the microspheres kept vibrating, and we couldn't differentiate between their movement and outside movement.


    Lab Three
    Name: nancy kati
    Date: 2003-09-30 14:31:49
    Link to this Comment: 6715

    Nancy Evans, Natalya Kiromgold, Katie Ottati

    Hypothesis: Larger microbeads will move father distances (randomly) than smaller microbeads during a constant period of time.

    Our period of time was 10 seconds for each size of microbead. After establishing what movement could be attributed to bulk movement, currents, table shaking, and other outside forces, we came up with the following observations:

    2 Micron-sized beads:
    moved 30 ums

    4 Micron-sized beads
    moved 2.6-4.8 ums

    8 Micron-sized beads
    moved 50 ums

    we realize the discrepancies in our accounts of the observations, and these errors could be attributed to any number of sources. the flawed measurements were wrong, but we did resist the urge to change our data and observations to match our expectations. since we learned this valuable lesson, we believe our erroneous data collection should be discarded.


    Melissa, Talia, Abby
    Name: Melissa, T
    Date: 2003-09-30 14:32:14
    Link to this Comment: 6716

    After observing the microspheres for a 10 second period each time at 10 magnification, we gathered the following data:

    8um-- 3 tics, 4, 5

    4um-- 5 tics,7,10

    2um-- 9 tics, n/a, n/a

    Observations and conclusions: Given that the results are inconclusive, from those which we were able to gather, we found that the smaller the sphere size, the greater the movement. There was a visible difference between the 8um ad 2um spheres, in that the latter would migrate further from their origin point, whereas the former would circulate around their origin area ,moreso.


    Sarah Kim, Brianna Twofoot
    Name: Brianna Tw
    Date: 2003-09-30 14:32:21
    Link to this Comment: 6717

    Hypothesis: The bigger the microsphere, the less it will move.

    We recorded movement in a given amount of time in units of micron, under a magnification of 40.


    8 micron spheres: Moved 5 microns in 5 seconds
    4 micron spheres: Moved 9 microns in 5 seconds
    2 micron spheres: Moved 9 microns in 3 seconds


    Conclusion: Observations support our hypothesis.


    Why?
    Name:
    Date: 2003-09-30 14:34:22
    Link to this Comment: 6718

    Justine Patrick and Shafiqah Berry
    (Please note that we have the ability to be serious)

    We looked high and low, nearer and farther for these moving microspheres, and got nothing, what is this? why can't these storming malestroms be seen? What is science? who are we? Oh, where are you beadies...? The conclusion is we were duped, hoodwinked, bamboozled , but Ah we found some with help from Professor Grobstein. Part two better be an improvement or else what is the point of these futile efforts on the part of people who are born to die and get three hours of sleep while living anyway?!!!!!!!!!!

    We discovered four moving "beadies" that moved pretty slowly, but were cool nonetheless. However, many of the surrounding beads were still, which sucked. We were unable to measure the size and speed due to lack of time, but from our very general observations, we saw a bead move 1 milimeter in about 1.5 seconds, this is for the largest bead, but we have yet to measure the others.


    moving balls
    Name: emily and
    Date: 2003-09-30 14:46:19
    Link to this Comment: 6719



    Happy Balls

    Further observations to support or not support the implication:
    The smaller microspheres will move faster and have more movement in comparison to larger microspheres; compared to each other, 2nm will move the most and the fastest, 4 nm will move a little less, and 8 un will move the least and the slowest.

    Observations:
    8 nm:
    30 un --> 35 sec
    30 un --> 31 sec
    30 un --> 19 sec
    avg = 28.33 sec

    4 nm:
    30 un --> 9 sec
    30 un --> 9 sec
    30 un --> 8 sec
    avg = 8.66 sec

    Conclusion:
    As we had predicted, the movement of the 4 un microspheres was more eradic than the 8 un microspheres. This fact made it more difficult to collect the data. However, the information that we did collect supports the implication made previously with the class.



    Microsphere Observations for Liz Bryan and Romina
    Name: Liz Bryan
    Date: 2003-09-30 14:53:59
    Link to this Comment: 6720

    Hypothesis: Smaller sized microspheres should move greater distances

    Observations:

    8 Micron Microsphere (measured at 4):
    -Quick jiggling movements, all in similar directions
    -Beads are small and circular shaped
    -Microns moved in 2-3 degree distances*

    4 Micron Microsphere (measured at 10):
    -Quick jiggling/jutting movements
    -Outside force is causing them to move in similar directions
    -Microns moved in 2 degree distances*

    2 Micron Microsphere (measured at 10):
    -Faster movement than any other group
    -Microns moved in 1 degree distances*

    *measured using micron ruler

    Conclusion:
    We couldn't really draw an absolute conclusion because the microspheres kept vibrating, and we couldn't differentiate between their movement and outside movement.


    Brianna Twofoot, Sarah Kim
    Name: Brianna Tw
    Date: 2003-09-30 15:20:46
    Link to this Comment: 6721

    Hypothesis: The bigger the microsphere, the less it will move.

    We recorded movement in a given amount of time in units of micron, under a magnification of 40.


    8 micron spheres: Moved 50 microns in 5 seconds
    4 micron spheres: Moved 90 microns in 5 seconds
    2 micron spheres: Moved 90 microns in 3 seconds


    Conclusion: Observations support our hypothesis.

    Observation:


    1% Salt Water
    - Long, thin cells
    - Stationary

    25% Salt Water
    - Little bubble like things are forming within the cell walls. The cell membrane is shrinking.
    - Keep getting smaller, i.e. cell membrane keeps shrinking.
    - Not necessarily all pulling away in a circle or uniform shape.

    Distilled Water
    - Begins to return to normal shape, but does not return entirely.


    Story: The cell is made up of water. The presence of salt begins to eliminate the presence of water, or pushes out/extracts water from the cell. The presence of distilled water refloods the cell, causing it to return to its normal shape.


    Lab Three--Part Two
    Name: Natalya, N
    Date: 2003-09-30 15:22:54
    Link to this Comment: 6722

    Is the first hypothesis relevant to other inquiries?

    WATER ONE(1% salt concentration) observations:
    well-defined cells with cell walls; can see organelles inside cells. Nothing appears to be moving at this magnification (4x) or at a higher magnification (10x).

    WATER TWO (25% salt concentration) observations:
    cell walls got darker, smaller. and seem to be more condensed. They appear to have lost water content as a result of adding the salt water.

    WATER THREE (distilled water- 0% salt concentration) observations:
    upon addition of the distilled water, we observed the un-doing of the salt water addition: the cells appeared condensed like before, at first, but were more transparent than with the salt . Over a longer period of time, the cells were even more transparent, but now the "pockets" of space created by salt water filled back up. evantually things looked "back to normal".

    OBSERVATIONS:
    Salt water removed the water from the cell membrane, and left the wall intact. It took a longer period of time for the cell wall to retain its original appearance as distilled water is added.

    HYPOTHESIS:
    during the addition of the different waters, the cell wall remains intact, however the cell membrane contracts (as more salt is added) and water is drawn out and expands (as less salt is present).

    CONCLUSION:
    Salt affects the movement of water across the cell membrane.


    Turgid Glory
    Name: emily & mi
    Date: 2003-09-30 15:30:12
    Link to this Comment: 6723

    Observations:
    1% NaCl: Cell walls of onion skin seem to be turgid and structured.
    25% NaCl: The cell walls are harder to make out and it has become harder to distinguish where one cell starts and another begins.
    Distilled H2O: The cell walls have returned to their original turgid glory.

    Are water molecules in constant random motion? YES.

    Conclusion:
    Obviously, water is crucial in maintaining the structure of cell walls in plants. The movement of water molecules pushes the NaCl or the distilled water through the semi-permeable cell walls, resulting in the destruction and restoration of the cells.

    New Hypothesis:
    Water molecules are in constant motion.


    Su-Lyn, Brittany
    Name:
    Date: 2003-09-30 15:31:22
    Link to this Comment: 6724

    Hypothesis: molecules move around, even if such movement is invisible to the naked eye

    Implications of hypothesis ("test"-able observations): When smaller objects are placed in water, they will "jiggle" around more than larger objects in water. This will happen because the moving molecules will push them around more.

    Group: Su-Lyn, Brittany


    Observations:

    The 8 micrometer beads didn't appear to move at all at a magnification of 10x, but we used a coverslip, so that could have affected the outcome. The second time we tried, however, the 8 micrometer beads rocketed across the screen in circular patterns at very fast speeds; however, some of them were moving faster, others slower, and some didn't move at all. The 4 micrometer beads, however, moved quite a lot a magnification 10x.


    8 m: 0, 30, 40, and 100 microns/second

    2 m: 0, 200, 250, and 300, 2740 microns/second


    Our conclusions support the idea that larger objects, on average, "jiggle" or move less in water than smaller objects, which in turn would support the greater hypothesis that liquids such as water are not static at the molecular level. However, discrepancies in our experiment---for example, the different particles moving at different speeds and the fact that some didn't move at all---indicate that more observations will be necessary to formulate a new less wrong hypothesis. However, we did notice that the particles seemed to be moving in the same direction, so we hypothesize that the movement of the particles is not totally random. New observations will be necessary to determine the order (if, in fact, any) of the particles' movement.

    ********************

    Plant Cell Experiment

    Regular plant cells
    Plant cells w/distilled water
    Plant cells w/salt water
    Plant cells w/distilled water again

    What happens when we put in the 25% salt: the yellow areas swell up.
    What happens when we put in distilled water: the yellow areas shrink.


    Melissa, Abby, Talia
    Name: Talia Libe
    Date: 2003-09-30 15:33:37
    Link to this Comment: 6725

    Observations:

    1% Solution of NaCl-- Distinguishable pattern of the cell walls and membrane with nuclei

    25% Solution of NaCl-- The NaCl absorbed the moisture from the cells, thereby causing the cell membrane to contract

    Distilled H20-- The solution restored moisture to the cell, therefore returning the cell wall and membrane to its original shape

    Story:

    The NaCl properties cause the membrane to contract as it absorbs the moisture. Once the distilled water replaces the salt water, the cells return to their original state.


    Onion Cells and Salt Water
    Name: Liz and Ro
    Date: 2003-09-30 15:33:42
    Link to this Comment: 6726

    Group Superstar :)
    Romina Gomez and Liz Bryan

    Hypothesis: Water molecules are constantly in motion.

    Observations:

    1% NaCl
    -The observations started at lens 4. The different cells are visible. They are long and rectangular. We cn see the outline of the cell walls and when we magnified to 10, there was a clearer picture of the cell walls and we were able to observe the nuclei in some of the cells. We were not able to differentiate the cell wall from the cell membrane.

    25%
    -We were able to see both the cell wall and the cell membrane. The membrane appears to have shrunk with the salt water. We could now see the nucleus in all of the cells.

    Distilled Water
    The cell membranes appear to have gone back to their original position, pressed up against the cell wall. The nuclei was visible.

    Conclusion:

    We know that a cell membrane is permeable. Thus when the salt water enters the cell it shrivels up the cell membrane, pushing the water out and thus making it easier to observe. We can assume that the salt in the water dehydrates the cell membrane. Then when we put distilled water back onto the cell, the membrane becomes hydrated and it is harder to see.



    Name: Shafiqah a
    Date: 2003-09-30 15:33:48
    Link to this Comment: 6727

    When you add a 1% salt water solution to the cell slide it seems to disentergrate the cell wall,and boundaries that separate each little thingy from the next, it's probably corosive because it melts the borders.after the addition of the distilled water, the cell went back to normal. so, maybe the distilled water gave the salt water the people's elbow (wwf style) and finished off its enemy the salt water, and saved day like superman, guess what my name starts with an "s", so technically i saved metropolis, and justine assisted like pinky and the brain, obviously we all know which one i am. In conclusion, whatever the hypothesis was, nobody told us so , we think that sometimes in an area where water molecules are in constant motion, and there is salt involved things get jacked up. that's all folks bedeep bedeep
    So, let's all take chances and make mistakes, or maybe we can refer to Newton when he stated that a thing in motion stays in motion unless acted upon by an outside force, like water and the invasion of it by salt.



    Name: Charlotte
    Date: 2003-09-30 15:36:03
    Link to this Comment: 6728

    Charlotte Haimes, Elisabeth Py

    Hypothesis: The smaller the object, the faster it moves.

    Observations:
    At 8 microspheres, the beads jiggled individually and moved in one direction simultaneously.
    At 4 microspheres, the beads also jiggled individually and moved in more random directions at a faster speed than the 8 microsphere beads.10s.-->2
    At 2 microspheres, the beads jiggled, moved in random directions at a higher speed. 10 s. -->4

    Conclusion: The observations are consistent with the hypothesis.

    Hypothesis:
    Water makes things move.

    Observations:
    1%: we can observe long thin cells, cell walls, membranes and mnucleus are visible.

    Salt Water(25%): salts eats up the cell and diminishes its size.

    Distilled Water: the cell takes its initial form within the cell wall.

    Our Story: When salt water is added, the size of the cells diminish. But when distilled water replaces the salt water, the sizes of the cells take their initial form. It seems that water allows the mobility of cells, whereas salt inhibits them from moving, therefore the cells contract.
    We can come to the conclusion that water is essential for cell function.


    Bessy Guevara, Paula Arboleda
    Name:
    Date: 2003-09-30 15:49:58
    Link to this Comment: 6729

    Part I.
    Upon looking at the 4 & 8 microspheres, we found that the distance moved in a minute for the 4 microsphere was 500 microns (at 10x); while the distance moved in a minute for the 8 microsphere was 650 microns (at 10x). We also acknowledge that we had much difficulty making these observations, and do not find the data we collected to be very reliable. Our observations are not consistent with our hypothesis. We do not have enough reliable data for a conclusion.

    Part II
    Original hypothesis: Water molecules are constantly in motion
    Observations: When using the 1% salt water, the plant cell is considered to be at the natural state, where the cell walls are rectangular shaped and seem uniformly position in the area. When adding the 25% salt water, we observed that the cell membrane shrunk and the cell walls lost it's rectangular shape. The high concentation of salt shriveled the cell walls. When distilled water was added, the cells took their rectangular shape. However, they were wider and seemingly bigger with small circular pockets(cell membrane) within the cell wall. With these observations we can state that the concetration of salt greatly affects the plant cells by either making them bigger or smaller; salt molecules affect the rate of motion of the water molecules.


    Melissa, Talia, Abby
    Name: Melissa, T
    Date: 2003-09-30 15:56:52
    Link to this Comment: 6730

    After observing the microspheres for a 10 second period each time at 10 magnification, we gathered the following data:

    8um-- 3 tics, 4, 5

    4um-- 5 tics,7,10

    2um-- 9 tics, n/a, n/a

    Observations and conclusions: Given that the results are inconclusive, from those which we were able to gather, we found that the smaller the sphere size, the greater the movement. There was a visible difference between the 8um ad 2um spheres, in that the latter would migrate further from their origin point, whereas the former would circulate around their origin area ,moreso.



    Name: Laura Wolf
    Date: 2003-09-30 16:01:20
    Link to this Comment: 6731

    When observing the 8 micron object in water over a time period of one minute, there was a range of motion of 60 micrometers. The object was heading in the same direction most of the time.

    The 4 micron object, over a time period of one minute, traveled within a range of 50 micrometers, but traveled back and forth multiple times so that the total distance it moved was unclear.

    Although it would be helpful to gather more data, the data we have so far is consistent with the original hypothesis.

    Now we are testing a small sample of onion to see what effect water has on the cells.

    When adding salt water: the cells (perhaps the cell membranes) changed from straight and even to shriveled and bubbly-looking. They look destroyed.

    When adding Distilled water: there are water pockets inside the cell walls.

    We have two possible explanations/ new hypotheses:

    1) that the salt molecules might be moving faster than the regular water molecules, causing more damage/ change to the plant cells.

    2) that water molecules might be smaller and move faster than the salt molecules, and so when there is salt in the solution, there is a longer time for change to occur.

    With more time and funding, we could ake more observations and see which of these hypotheses we want to keep.


    movers and shakers
    Name:
    Date: 2003-10-01 14:27:31
    Link to this Comment: 6747

    Maggie Tucker and Adina Halpern

    Obsevations:
    In ten seconds, the spheres moved the following distances:

    2 um spheres -- 10.4 um

    4 um spheres -- 7.8 um

    8 um spheres -- 3.9 um

    We observed that as the size of the particles decreased, the speed of the movement increased.



    Name:
    Date: 2003-10-01 14:27:32
    Link to this Comment: 6748

    Melissa Teicher
    Anna Marciniak

    Our hypothesis was that the smaller particles would move further distances.

    However, in the short time that we had to make observations, our evidence did not support that.

    2-micron particle traveled 15 tics in 30 seconds
    4-micron particle traveled 30 tics in 30 seconds
    8-micron particle traveled 100 tics in 30 seconds

    We suspect that there is a large percentage of error due to movement of the slide, movement of the table, etc.



    Name:
    Date: 2003-10-01 14:31:39
    Link to this Comment: 6749

    Melissa Teicher
    Anna Marciniak

    Ammendment to our posting:

    We measured it under the 40X lense.

    so the 2 micron particle moved 39 um
    the 4 micron particle moved 78 um
    and the 8 micron particle moved 260 um


    Particle motion
    Name: Mariya
    Date: 2003-10-01 14:32:07
    Link to this Comment: 6750

    Julia Wise, Mariya Simakova


    Hypothesis:

    Smaller particles move faster in water than larger particles do.

    Observations:

    All observations were made in 30 seconds span.

    8um -- moved 16.1um , 10.4um
    4um -- moved 44.2um, 39um
    2um -- moved 52um, 49.4um, 52um

    Conclusion:

    Our observations are consistent with our hypothesis. The smaller particles have a larger diameter of motion than the larger particles, therefore the smaller particles move faster than the larger particles. We anticipate some measurement error due to random movement of particles (the precise distance they travel is hard to measure).


    invisible beads
    Name: Alison J.,
    Date: 2003-10-01 14:32:55
    Link to this Comment: 6751

    2 microns, 40x, for thirty seconds: 7 notches


    we were only able to collect data for the smallest size of bead. the beads were obviously moving at what seemed to be a rather fast rate. however, we were unable to find any movement in the other sizes. but may be inclined to say that the large beads would have moved less than the smaller beads.


    Microbeads
    Name:
    Date: 2003-10-01 14:33:56
    Link to this Comment: 6752

    Katy McMahon, Nomi Kaim, Megan Williams

    Hypothesis: Smaller microbeads will move faster than larger microbeads in water.

    We looked at three different sizes of microbeads, but only got measurements for two sizes. What we observed did not support our hypothesis but instead implied that smaller microbeads moved more slowly.

    Size four microbeads moved 50 micrometers in 30 seconds, or 100 a minute.

    Size two microbeads moved 25 micrometers in 30 seconds, or 50 a minute. Most of these actually vibrated in place, even though we examined them at multiple depths.


    Lab 4
    Name:
    Date: 2003-10-01 14:36:02
    Link to this Comment: 6753

    Alice Goldsberry, Patty Palermo, Rochelle Merilien

    Before we began our observations, we predicted that the larger beads would move slower and be less affected by the collisions, because they had a larger body and that the smaller beads would move faster because they had less mass and more affected by the collisions.

    Our results were as follows:

    8 in 5 seconds approx. 52 emds

    4 in 5 seconds approx. 30-40 emds

    2 in 5 seconds approx. 8-12 emds

    We believe that the quicker/ further travel of the smaller beads, and the less distance the beads traveled within 5 seconds as they got larger, supports our hypothesis.


    Excercise #1
    Name: J'London,
    Date: 2003-10-01 14:38:31
    Link to this Comment: 6754

    Enor, J'London, Ramatu

    Hypothesis: We beleive that the smaller particles move at faster rate due to the fact that they possess less mass, in conjuntion with the idea that these particles contain less energy in proportion to the energy emitted by the water.

    Observations:

    8 microspheres- particles moved approximately 6um in 10 seconds

    4 microspheres- particles moved approximately 15 um in 10 seconds

    2 microspheres- partcles moved approximately 23 um in 10 seconds

    These observations were obtained using the 40x lens.

    We proved our hypothesis to be true as the larger microspheres moved at a slower rate than each of the smaller ones.


    Movement of particles
    Name:
    Date: 2003-10-01 14:39:51
    Link to this Comment: 6755

    Flicka Michaels
    Lara Kallich

    Hypothesis: Smaller particles move around more than bigger particles.

    Observations:

    8 microns: beads moved 5.2 ums in a time span of about 30 seconds. The beads were vibrating.

    4 microns: beads moved 26 ums in a time span of 30 seconds. The beads were vibrating quickly, but drifting slowly.


    Our observations supported our hypothesis that smaller particles moved more than larger beads.



    Name:
    Date: 2003-10-01 15:11:32
    Link to this Comment: 6756

    Melissa Teicher
    Anna Marciniak

    We think that the cells will look more shriveled up in the 25% salt solution because the salt removes the water from the cell, but when the cells are in the distilled water, we feel it was return back to its regular shape and plumpness.

    Observations:
    1% salt - cell walls are stable, not deteriorating, thick
    2% salt - the membrane is shrinking, the inside of the cell is shriveling up, the cell wall appears to be thinner
    distilled water (0% salt) - returning to original shape, cell wall thicker, membrane plump

    We felt that this happened because the salt could have broken down the particles of the cells and therefore resulted in a shriveling effect.


    Part 2, onion/salt water
    Name:
    Date: 2003-10-01 15:22:23
    Link to this Comment: 6757

    Nomi, Katy, and Megan

    Observations--

    1% NaCl-- cell walls and membranes appear to be intact and stable, not moving
    25% NaCl-- cells have shrunken, cell membranes have been destroyed, looks collasped. still able to see cell walls intact. little circles that appear to be smaller cells are smaller as well.
    Distilled water-- cells have returned to normal size, initial conditions

    Due to our observations, we would hypothesis that 25% salt solution causes water to move out of a cell membrane which makes the cell shrink. Pure water moves back into the cell membrane and returns the cell to its original size.


    Onions
    Name: Stefanie F
    Date: 2003-10-01 15:22:24
    Link to this Comment: 6758

    After an unsuccessful data recovery in the first set of observations, we were able to clearly see a change in the second set of observations.

    After adding 1% NaCl, we noticed a very small change in the size of the cells.

    After extracting the 1% and adding 25% we saw a very pronounced change in the appearance of the cells. The cells had contracted, and were obviously darker, almost filled with solution.

    In the presence of distilled water, the cells were wide and clear.

    We have hypothesized that, salt decreases the size of the cells.


    salt
    Name:
    Date: 2003-10-01 15:29:11
    Link to this Comment: 6759

    Maggie, Adina

    Observation: The cell nuclii grow with salt.

    Hypothesis as to why this occures: The water particles move the salt inside the cell nucleus, and this pushes the outside of the nuclues in all directions, stretching it.


    Semi-Organic Hypothesis
    Name: J'London H
    Date: 2003-10-01 15:30:47
    Link to this Comment: 6760

    Ramatu, Enor, J'London

    Well, through observing the onion cell and cooperating the knowledge we observed through phase one of our explanation we are able to assert that:

    NaCl @ 1% we observed no movement of the cells, however we were able to note the rectangular shape of the cells, which is very different from the organism we observed prior to this experiment.

    NaCl @ 25% we were able to detect slight movement in the cells, we noted the rectangular shape of the cells observed at 1% we now perceived to be ovular.

    Distilled Water we did not notice much difference from NaCl 1%.


    Onion Cells
    Name: Mariya
    Date: 2003-10-01 15:31:04
    Link to this Comment: 6761

    Mariya Simakova, Julia Wise


    Observations:

    Onion cells in 1% salt solution: clearly visible cell walls and cell membranes, transparent cells


    Onion cells in 25% salt solution: the cell walls stay the same, while the membrane shrinks significantly, cells get more clouded


    Onion cells in 0% salt solution: the membrane expands back to its regular size, cells look the same as the cells in the 1% solution (perhaps a bit more transparent). The cell walls stay the same throughout.

    Hypothesis: The 25% salt solution draws water out of the cell through the cell membrane. Because there is less water left in the cell, the membrane shrinks. When we add pure distilled water, its constantly moving particles enter into the cell through the membrane, filling it again to the size observed in the first instance.


    pt II of water motion lab
    Name:
    Date: 2003-10-01 15:32:15
    Link to this Comment: 6762

    Lara Kallich, Flicka Michaels

    Original hypothesis: water molecules are constantly in motion.

    Observations:

    onion skin + 1% NaCl solution: cells are in "normal" state. long, thin cells with very distinct cell walls. cell membrane not remarkably visible.
    onion skin + 25% NaCl solution: cell walls remain completely intact; however, cell membranes are now distinctly shriveled or shrunken.

    onion skin + DI H20: cells return to "normal" state - looked identical (if not even clearer) to original set of observations.

    Conclusions:
    It seems that salt affects the motion of water molecules by slowing them down: we can infer from our observations that the salt molecules caused water to move more slowly inside the cell membrane, which would have caused it to lose its shape and shrink or shrivel.


    Lab 4 part 2
    Name:
    Date: 2003-10-01 15:36:21
    Link to this Comment: 6763

    Alice Goldsberry, Patty Palermo, Rochelle Merilien

    Hypothesis: The 25% salt would leave a residue on the cells of the onion membrane and that the water would move across the onion faster than salt.

    N.Cl on Onion- You can see cells clearly. Can see small amount of motion. Nothing to compare the motion to yet.

    25% Salt on Onion- Can see what we feel are salt particles moving rapidly and randomly across the onion membrane. The salt seems to spread itself out over the membrane, eventually causing a film over the membrane. The 1% N.Cl and the 25% salt, we assume, have appeared to mix over the membrane. while causing the walls of the individual cells to appear thicker.

    0% distilled water- Seemed to rinse off some of the residue. Allow the walls of each individual cell to appear sharper and thinner. The cells also looked lighter under what remained the same magnification and light the entire observational period.


    Flux and Its Regulation: Chemical Reactions and En
    Name: Paul Grobstein
    Date: 2003-10-07 09:53:37
    Link to this Comment: 6819

    Not only is everything in motion but the "natural" tendency of everything ), as we'll talk more about in class, is to fall apart, become more disordered. That tendency is apparent in diffusion (as we saw in the last lab) and also in chemical reactions. In this lab we will begin looking at how life processes can make use of the natural tendency to fall apart to create order. A key part of this story is that things fall apart at different rates and that "enzymes" influence that rate. We will explore the capability of enzymes to control chemical reaction rate and try and deduce characteristics of enzymes from our observations.

    We will begin with some basic observations implying the existence of enzymes and then explore a particular chemical reaction, the "falling apart" of hydrogen peroxide into water and oxygen gas, as it is affected by the enzyme hydrogen peroxidase:

    2H2O2 ---> 2H2O + 02

    Your report should include a description of your observations relevant to identifying important characteristics of enzymes and some hypotheses about what produces those characteristics.


    Temperature
    Name: emily & mi
    Date: 2003-10-07 14:51:51
    Link to this Comment: 6822

    Does the speed of the reaction depend on the temperature? We expect increased temp increases the rate of the reaction.

    Iced H2O2:
    5.0 sec
    4.0 sec
    5.0 sec

    Room temperature H2O2:
    4.0 sec
    3.5 sec
    3.3 sec
    Warmed H2O2:
    2.5 sec
    2.5 sec
    3.0 sec



    Name: Su-Lyn, Br
    Date: 2003-10-07 14:54:15
    Link to this Comment: 6823

    pH trials: DATA
    Time it took for the little round slip-thing to rise
    pH 2 (acidic): 8.5, 7.5, 9 seconds
    pH 7.4 (neutral): 5,5, 5.5
    pH 10.1 (basic): 7, 7, 6.5

    (each number is a different trial)


    La Toiya, Natalia
    Name: La Toiya L
    Date: 2003-10-07 14:58:29
    Link to this Comment: 6825

    Part I - Substrate Level Effects on Rate & End Product
    {Readings every 30 sec}
    1. 1.3
    2. 1.3
    3. 1.4
    4. 1.5
    5. 1.5
    6. 1.7
    7. 1.8
    8. 2.0
    9. 2.2
    10. 2.3
    11. 2.5
    12. 2.6
    13. 2.8
    14. 2.9
    15. 3.0
    16. 3.1
    17. 3.2
    18. 3.3
    19. 3.4
    20. 3.5
    21. 3.6
    22. 3.7
    23. 3.8
    24. 3.8
    25. 3.9
    26. 4.0
    27. 4.0
    28. 4.0

    Part III - Effects of pH on Enzyme Activity
    {2.0 Buffer w/ 10ml of Hydrogen Peroxide w/ Catalase B}
    It took the filter disc 2 seconds to rise to the top of the solution


    Part I
    Name: emily & mi
    Date: 2003-10-07 15:10:39
    Link to this Comment: 6826

    In 30 second intervals the amt of gas (O2) in the volumetric test tube:

    1.5
    1.7
    1.9
    2.3
    3.0
    3.5
    4.0
    4.5
    5.5
    6.4
    6.5
    6.6
    6.7
    7.0
    7.1
    7.2
    7.3
    7.5
    7.5
    7.6
    7.8
    8.0
    8.0
    8.0
    8.0

    In the same amount of time, 0.5 H2O2 < 1.0 H2O2 gas. Less hydrogen poroxide produces less gas (O2). The enzyme doesn't affect the final state it just affects how fast you get there.


    Brianna Twofoot, Liz Bryan, Justine Patrick
    Name: Brianna Tw
    Date: 2003-10-07 15:14:31
    Link to this Comment: 6827

    First Experiment Observations:

    .8
    1.4
    1.9
    2.4
    2.8
    3.1
    3.5
    3.8
    4.1
    4.4
    4.7
    4.9
    5.1
    5.3
    5.5
    6.0
    6.5
    7.5
    8.5
    9.5


    Experiment 2 Observations
    Catalase B:
    Run 1- 5
    Run 2- 3
    Run 3- 2

    Catalase C:
    Run 1- 6
    Run 2- 4
    Run 3- 5

    Catalase D:
    Run 1- 11
    Run 2- 10
    Run 3- 8

    Yes, rate depends on concentration of the enzyme. The less concentrated the enzymes, the slower the rate of reaction.

    - An enzyme speeds up something that is already occuring more slowly. Only affects speed, not destination.


    An enzyme is a something that can speed or slow a reaction based on ph or temperature, and can increase the rate of a reaction based on concentration. Perhaps an enzyme is some sort of a living thing, because much like a plant or animal or person, if you heat it up too much, it will slow down, and if you freeze it it will slow down. This is different than what we observed about water molecules, where the extreme temperature in fact made the molecules move faster.


    What is an enzyme?
    Name: emily & mi
    Date: 2003-10-07 15:21:56
    Link to this Comment: 6828

    Enzymes do what nature would do, but just faster. That's not to say that nature would be incapable of completing all processes without enzymes, but that enzymes help to increase the rate in which certain processes may take to complete. Take for example decaying food, if food is left out it would naturally break down with time. But if food is digested, it is broken down faster with the use of the many enzymes that participate in the digestion process (mouth, saliva, bile, etc.).


    katie ottati, nancy evans, abby fritz
    Name: see subjec
    Date: 2003-10-07 15:27:23
    Link to this Comment: 6829

    We made observations for part II of the experiment - enzyme concentration:

    Catalase B (full):
    1 - 3 seconds
    2 - 5 seconds
    3 - 5 seconds

    Catalase C (1/5):
    1 - 8 seconds
    2 - 9 seconds
    3 - 8 seconds

    Catalase D (1/10):
    1 - 12 seconds
    2 - 12 seconds
    3 - 11 seconds

    A decrease in the enzyme concentration means a slower reaction rate.

    What is an enzyme?: We do not know. It appears to have characteristics in common with living organisms (it has an optimal temp & pH), but it also has characteristics in common with water (H20 molecules break down the cracker, as do the enzymes in spit). The group was unable to decide whether we thought enzymes were living organisms or perhaps molecules that move faster than most and thus better facilitate the breaking down of things.



    Name: Su-Lyn, Br
    Date: 2003-10-07 15:27:54
    Link to this Comment: 6830



    After looking at all the data, here are the conclusions we have drawn:

    What we know: Enzymes are essential to life in that they accelerate reactions within organisms. This may suggest that living organisms produce enzymes. If so, they would produce them in order to keep their metabolisms working---ie to keep the necessary chemical functions inherent in organisms going.

    Our hypothesis: Firstly, because of the obvious bell-curves in 2/3 of the areas analyzed (temperature and pH) and the eventual leveling out of the third (concentration), we hypothesize that reactions involving enzymes are not the same as simple diffusion. In diffusion, molecules randomly crash into one another so that the higher the temperature, the faster the reaction; here, it seems that there is more of an optimal temperature in which he reactions occur.

    Secondly, in terms of concentration... because the concentration of enzyme plateaus instead of constantly rising, it suggests that there is a "cap" to the amount of enzyme needed to catalyze a certain amount of substrate. This would imply that the type of molecule present affects the rate of the reaction. For example, say that the molecules of enzyme somehow attach/affect the molecules of the substance; this would mean that the number of enzyme molecules that could affect a certain amount of substance (in this case, peroxide) would be fixed.

    With regards to pH, it appearslike temperaturethat there is an "optimum" pH at which enzymatic reactions occur.

    In conclusion, with regard to all of our previous observations, it appears that enzymes are produced for a purpose. They don't occur randomly; they only operate in certain temperature and pH ranges---which coincidentally happen to be the same conditions inside living organisms. Therefore, we hypothesize that enzymes are created by living organisms to speed up the necessary chemical reactions in their bodies.


    Bessy Guevara, Vanessa Herrera
    Name:
    Date: 2003-10-07 15:29:20
    Link to this Comment: 6831

    Temperature Rate in Seconds

    @ Chilled 4.0 4.0 4.0

    @ Room Temp. 4.0 3.0 4.0

    @ Warmed 3.0 2.0 3.0


    These observations reveal that as the temperature rises, the reaction rate of the disc is faster therefore, taking less time to reaching the top of the solution. However, had the warmed temperature been higher, the reaction rate would have been slower and the time in reaching the top would have been greater.

    In our observations, we concluded that the property of an enzyme is a catalyst that promotes the speed in which a chemical reaction takes place . In our second set of observations, we investigated the effect of temperature on the reaction rate of an enzyme.

    There's an optimal temperature where the speed can reach its summit; at chilled and very warm temperatures it decreases the rate of reaction. Since, everything is falling apart, it most hold true that the enzyme will breakdown.


    enzymes
    Name: Laura Wolf
    Date: 2003-10-07 15:29:30
    Link to this Comment: 6832

    When testing the relationship between enzymes and pH, we used solutions with a pH level of 2.0, 7.4, and 10.1, and we then timed how long it would take for the fiberglass disk to rise to the top of the solution.
    My hypothesis is that a higher pH will create a faster reaction, related to the concentration of enzymes.

    Data:

    pH level......... Number of seconds (trial 1, trial 2, trial 3)

    pH 2.0 ............... 6 , 6, 5

    pH 7.4 .............. 6, 4, 5

    pH 10.1 ............ 8, 6, 8

    This data is not convincing that a higher pH either speeds up or slows down the process, because the data is all relatively the same. There is no gap, or significant difference, among the groups of data. From the observations collected, the hypothesis is wrong.

    However, combining my data with the other group's data seems to suggest a curve; that on the pH scale the reaction time goes from slower to faster to slower. My results could have been due to human error or other small problems.

    ********What is an enzyme, then, and how is it related to the speeds of these reactions?

    Why did the enzymes work fastest in a pH of 7.4 which is close to distilled water (7.0)? My guess was that acidic solutions would contain more enzymes to help break things down faster (such as stomach acids that are used to break down food), and also basic solutions (such as bleach) are more hamful to humans than water because they break things down faster too. So maybe enzymes balance pH. Maybe the reason that solution was a steady 7.4 pH was because it had more enzymes in it than the 2.0 or the 10.1 solutions.

    But the data from the "temperature" group supports our hypothesis from last week, which says reactions happen faster in warmer temperatures, and it helped speed up the enzyme's productivity.

    So my new hypothesis is that enzymes speed up reactions and balance pH towards a neutral number.


    enzyme
    Name: Elisabeth
    Date: 2003-10-07 15:30:43
    Link to this Comment: 6833

    Elisabeth Py
    Charlotte Haimes

    Temperature Observations:
    >Chilled hydrogen peroxide: 3.67s, 4.73s, 3.59s
    >Room temperature: 3.20s, 3.51s, 3.24s
    >Warm temperature: 2.50s, 1.87s, 1.80s


    Conclusions: The higher the temperature of the hydrogen peroxide, the greater the speed of the reaction.

    What is an enzyme? : Based on our observations, we know that an enzyme is a mobile molecule that serves as a catalyst. Its function is to speed up a reaction, without changing its final state.


    La Toiya Natalya
    Name:
    Date: 2003-10-07 15:31:02
    Link to this Comment: 6834

    An enzyme increases the rate at which things "naturally" fall apart. For every enzyme there is an optimal temperature and pH level at which the enzyme functions most effectively.
    Why are we so interested in the speed and rate at which things fall apart?
    If we didn't know the rate at which things fell apart and what caused them to fall apart then there would be a great deal of uncertainty in everyday life as well as science, which would lead to an unstable state of disorder.


    temperature
    Name: Jessica an
    Date: 2003-10-08 14:56:30
    Link to this Comment: 6842

    room temp.

    trial 1: 5 sec
    trial 2: 5 sec
    trial 3: 4 sec

    chilled

    trial 1: 7 sec
    trial 2: 8 sec
    trial 3: 8 sec

    warmed

    trial 1: 5 sec
    trial 2: 6 sec
    trial 3: 6 sec



    Name: stefanie f
    Date: 2003-10-08 15:14:50
    Link to this Comment: 6843

    We were testing the way in which the cocnentration of enzymes affects the rate of things falling apart. Our data leads us to believe that the higher concentration of an enzyme, the more quickly an object will "fall apart." Our data is as follows:

    Enzyme B (highest concentration):
    Trial 1: 4 seconds
    Trial 2: 3 seconds
    Trial 3: 4 seconds

    Enzyme C (middle concentration):
    Trial 1: 13 seconds
    Trial 2: 14 seconds
    Trial 3: 13 seconds

    Enzyme D: (lowest concentration):
    Trial 1: 13 seconds
    Trial 2: 15 seconds
    Trial 3: 15 seconds

    An enzyme is a catalyst; it is a substance with a chemical composition that speeds a reaction. In other words, adding an enzyme produces an increased rate of change in a process that would have been slower otherwise.


    Bio Enzyme Lab
    Name: Anna & Mel
    Date: 2003-10-08 15:15:51
    Link to this Comment: 6844

    Anna Marciniak & Melissa Teicher

    Part IV: Temperature

    Chilled:
    8
    7.5
    8

    Room Temp:
    5
    5
    5

    Hot:
    12
    13
    30

    What is an enzyme?
    We think that an enzyme is something that speeds up a process; something that acts as a catalyst to speed up a reaction. We have observed that the enzyme works at a faster rate as the concentration increases, and that there is no linear relationship between the rate the enzyme works to temperature or pH. At this point, all we can say for sure is that it is some kind of substance that speeds up a reaction at different rates depending on the concentration of the enzyme.


    Enzymes
    Name:
    Date: 2003-10-08 15:21:19
    Link to this Comment: 6845

    Flicka Michaels
    Julia Wise

    We measured the time it took for a filter disc soaked in Catalase B to rise to the surface with different ph buffer solutions. We repeated each trial 3 times for each ph solution.

    2.0 ph buffer- 17 sec, 15 sec, 16 sec

    7.4 ph buffer- 12 sec, 13 sec, 13 sec

    10.1 ph buffer- 11 sec, 11 sec. 11 sec

    Our results show that the rate of rising accelerated as the ph level increased. Unfortunately, this was not supposed to happen. However, we learned from the first part of the lab that an enzymes do not affect what happens, only how quickly it happens. Also, they work better at some ph levels and not others. So based on our observations, we can infer that an enzyme is alive, because it needs certain conditions to function effectively. Our results showed that enzymes just like other living organisms need a certain temperature and ph level to function best.


    Part III
    Name:
    Date: 2003-10-08 15:23:24
    Link to this Comment: 6846

    by Lindsay Updegrove and Alice Goldsberry

    Does pH level affect the rate and time of a chemical reaction?

    pH 2.0: 20, 24, 18 seconds

    pH 7.4: 32, 24, 22 seconds

    pH 10.0: 31, 31, 30 seconds

    It appears as though pH level does have some effect on the rate and time of the reaction's "falling apart." Certain pH levels seem to be more effective than others in speeding up the reaction. From the data of other groups, it appears that the temperature of the enzyme affects the reaction in a similar way.

    From what we have seen in the past two hours, an enzyme is a liquid that has some bearing on the rate of a reaction. It is actvated more optimally by certain temperatures and pH levels. When the rate of the reaction is increased, bubbles appear more quickly and move more rapidly, which tells us that things are falling apart faster. Also, the higher the concentration of the enzyme added to the reaction, the faster the reaction will occur.

    Our hypothesis for enzyme reactions is that the more concentrated the enzyme, the faster a reaction will occur, but for pH and temperature, there is no linear relationship between acid/temperature levels and reaction rate. Rather, there are certain optimal temperatures and pH levels which cause the enzyme to work at its highest possible rate.


    conclusion
    Name: Diana and
    Date: 2003-10-08 15:23:41
    Link to this Comment: 6847

    In our previous experimentation with the temperatures of enzymes, we discovered that there is not a consistent increase or decrease in the speed at which the enzymes react with regards to temperature. It appears from our data that chilled or hot reactions will be slightly slower than room temperature reactions, but only by one or two seconds.

    This goes to show that enzymes are important as catalysts to reactions in nature, but we find that their temperature does not necessarily affect the speed of their reaction. If this is the case at all times, we can say that the effect of an enzyme will be the same in all temperature conditions.

    (our data is posted above, but for your convenience, here it is again. )

    room temp: (5, 5, 4)

    chilled: (7, 8, 8)

    warmed: (4, 6, 6)


    lab #4
    Name: J'London,
    Date: 2003-10-08 15:24:59
    Link to this Comment: 6848

    Enor, Rochelle, J'London

    We conducted PART IV of the group experiment entitled EFFECTS OF TEMPERATURE ON ENZYME ACTIVITY.

    Our observations yielded the following data:

    ACTIVITY @ ROOM TEMPERATURE:

    trial one... 2.25 sec
    trial two... 3.5 sec
    trial three... 3.5 sec

    ACTIVITY @ CHILLED TEMPERATURE:

    trial one... 7 sec
    trial two... 5 sec
    trial three... 5 sec

    ACTIVITY @ WARMED TEMPERATURE:

    Our results were deviant from the other experiments conducted. Our "nubbie" failed to rise in the hydrogen peroxide, giving us the time constraint of the infinite. We believe that the Hydrogen Peroxide, during the hot test segment, imposed some ill effect onto our nubbie.

    THE STORY BEGINS:

    It was a hot october afternoon when jlo, enor and rochelle were stirred from the dining hall and drawn mystically to the biology laboratory. We observed soft nubbies of varying thickness as they were expelled from the tweezers into solutions of different temperatures and compositions. The reaction perplexed us, however divine intervention in conjuction with the genius that is these budding scientists we have concluded:

    1) Microscopic Organisms from Planet Farther infaltrated the soft glove like exterior of the nubbies causing them to scurry to the top of the solution of hydrogen peroxide. They are drawn to the nubbies because they are soooooo soft.

    2) We believe that the reactants in causing these reactions are an improbable assembly of elements which when forced into the solution of hydrogen peroxide actively effect the maelstorm of motion.



    Name:
    Date: 2003-10-08 15:26:06
    Link to this Comment: 6849

    Maggie and Adina

    Once apon a time we studied the Enzyme Concentration Effects on Rate. We got the following results:

    Enzyme Concentration B:
    1) 4 seconds
    2) 4 seconds
    3) 5 seconds
    4) 4 seconds

    Enzyme Concentration C:
    1) 17 seconds
    2) 16 seconds
    3) 23 seconds
    4) 16 seconds

    Enzyme Concentration D:
    1) 23 seconds
    2) 20 seconds
    3) 27 seconds
    4) 19 seconds

    Like a living organism, the enzyme appears to have peak performance levels at certain temperatures and pH levels. Also like a living organism, there is a limit to its possibilities (as is shown in our results). Based on this story, we think enzymes are ALIVE!!!

    The end.


    substrate level effects on rate + end product
    Name:
    Date: 2003-10-08 15:28:18
    Link to this Comment: 6850

    Lara Kallich, Christina Alfonso

    Part III: Effects of pH on enzyme activity
    (pH level of buffer/time it took catalase-soaked filter disc to rise to surface of buffer-H202 solution)

    1. pH 2.0
    a) 17 secs
    b) 20 secs
    c) 20 secs
    2. pH 7.4
    a) 8 secs
    b) 8 secs
    c) 7.5 secs
    3. pH 10.1
    a) 8 secs
    b) 8 secs
    c) 7 secs

    What we think an enzyme is:
    It seems that an enzyme is a substance whose constituent molecules move around comparatively much faster, thereby speeding up the breakdown process. In terms of pH, it seems that enzymes (supposedly) function best at a neutral level - at both higher and lower pH levels its functioning slows down. Had we more time and funding, we would elaorate on these findings.


    Effect of Enzyme Concentration on Rate Little Slip
    Name: Nomi alone
    Date: 2003-10-08 15:33:12
    Link to this Comment: 6851

    I analyzed the effects of different concentrations of the enzyme peroxidase on the rate at which little paper slips, saturated with one of said enzyme concentrations, rose to the top of a beaker of Hydrogen Peroxide (H202).

    Hypothesis: Increasing the concentration of the enzyme peroxidase will increase the rate at which a paper slip (of a given size) will rise to the top of a beaker of H202 (of a given volume). Conversely, decreasing the concentration of peroxidase will decrease the rising rate. Concentration and rate should increase proportionally.
    Concentration ~ Rising Rate.

    My data were:

    Concentration B - Most Concentrated
    5 sec, 4 sec, 4 sec ---> avg. about 4 sec.

    Concentration C - Intermediate Concentration
    8 sec, 6 sec, 7 sec ---> avg. 7 sec.

    Concentration D - Least Concentrated
    24 sec, 17 sec, 19 sec ---> avg. 20 sec.

    My data support my hypothsis. In the most concentrated enzyme, the paper rose in as little as 4 seconds -- quite quickly. On the other hand, the third and least concentrated enzyme caused the paper to take as much as 24 seconds to rise -- a very slow rate. Greater concentration induced greater rising speeds.

    The function appears to be linear.

    The paper slips allowed us to trace the rate at which oxygen bubbles rose, which, in turn, indicate the rate at which an enzyme reaction has occurred. [Is this true? What effects might the paper have on the accurracy of the experiment.]

    What is an enzyme? Why does it increase the rate of chemical reactions (of "falling apart")?

    I think an enzyme is a molecule or cluster of molecules that uses and stores energy (taken from the environment). The enzyme can then use or expend this stored energy toward a useful purpose: breaking molecules apart. In the case of 2H202 ----------> 2H20 + 02 , peroxidase speeds the natural process of dissociation (into water and oxygen) by GRABBING molecules of hydrogen peroxide and FORCING them apart, rather than leaving this breakdown to the natural but slow process of randomness.

    How does an enzyme do this? An enzyme must be shaped in such a way that it can grab or latch onto, in this case, a molecule of H202. This means the peroxidase enzyme must be shaped so that it can fit or match hydrogen peroxide. Enzymes must also be capable of stretching themselves out a relatively large amount. Hence, peroxidase, having securely attached itself to the hydrogen peroxide, must STRETCH it out to the extent that the bonds of the molecules break down! The thus broken-off atoms then reform into oxygen and water, probably with the aid of different enzymes (enzymes with remarkable powers of CONTRACTION, rather than stretching, so they can stick different atoms together).

    Alternatively, enzymes may be molecule clusters that possess a "saw-like" molecular compound capable of "sawing" apart other molecules' bonds every time it randomly bumps into them. Enzymes that assemble rather than disassemble molecules would have, in place of the "saw," a kind of molecular or atomic "glue" that sticks to select atoms and causes them to stick together more rapidly when they bump. However, this explanation seems unlikely because analysis of assembled molecules does not indicate the presence of special "glue" particles; so, enzymes, must do their work without using any other intermediary substance.

    Whatever the means, I think enzymes speed up disocciation (and assembly) of atoms by making the atoms more likely to bump into each other and to break apart (or stick together).

    Question: where do enzymes get the energy they use to put things together or break things apart? Maybe as a part of the process of respiration? Maybe that's why only living things have enzymes -- because only living things respire?


    Oneself As A Biological Entity. I. The Pulse and I
    Name: Paul Grobstein
    Date: 2003-10-21 12:30:59
    Link to this Comment: 6930

    This week we're beginning a set of labs on humans as biological entities ... and a set of labs in which you should use the skills and insights you've developed as a researcher in past labs to develop and carry out your own lines of investigation.

    We will introduce you to some techniques for observing the pulse, and make a few observations on it together. It is then your task, in groups of three, to develop an interesting inquiry using those techniques to explore the regulation of the pulse ("who's in control?"), carry it out, and report your study (motivation, observations, interpretations) here in the lab forum area.


    ABBY,NANCY,NATALYA,MELISSA
    Name:
    Date: 2003-10-21 14:36:49
    Link to this Comment: 6932

    QUESTION: How does controlled breathing effect heart rate?
    HYPOTHESIS: As breathing slows, the frequency of the heart rate decreases.

    DATA:
    Over 12 seconds -
    normal: 87.5 bpm
    in 2, out 2: 70 bpm
    in 4, out 4: 80 bpm
    in 6, out 6: 85 bpm

    Over 30 seconds -
    normal: 86 bpm
    in 2, out 2: 84 bpm
    in 4, out 4: 78 bpm
    in 6, out 6: 82 bpm

    Analysis: Our first set of data was inconsistent with our hypothesis. There didn't appear to be a direct correlation between breathing and heart rate. Over a 30 second interval, the first three data points were consistent with our hypothesis, but the fourth was not, so we cannot draw any definite conclusions.

    A possible reason for discrepancies is thats perhaps the body needs a specified amount of time for heart rate to change in accordance with breathing.


    Pulse and smoking
    Name:
    Date: 2003-10-21 14:40:09
    Link to this Comment: 6933

    Sarah Kim, La Toiya La Vita, Manuela Ceballos
    Hypothesis: Smoking will increase a non-smoker's pulse more than a smoker's pulse, and for a longer period of time.

    We took samples from two subjects: a smoker and a non smoker. Our samples consisted in 20 second intervals where we recorded heart rate before smoking one cigarrete, immediately after smoking a cigarrete and 10 minutes after smoking the cigarrete, to see how pulse was affected over time by smoking in both subjects.

    Before:
    Sarah (smoker) 81
    La Toiya (non smoker) 78

    Immediately after:
    Sarah 96
    La Toiya 90

    After 10 minutes:
    Sarah 87
    LaToiya 78

    Sarah's pulse increased by 15 after the cigarrete. After 10 minutes it went by 9 (7 beats away from what it was before smoking).

    LaToiya's pulse increased by 12 after the cigarrete. It decreased by 12 after 10 minutes (back to the initial heart rate).

    Our observations did not confirm our hypothesis in these two subjects, since our non smoker's pulse increased less than our smoker's pulse, and "recovered" faster.


    tick tick tick
    Name: Group Supe
    Date: 2003-10-21 14:45:56
    Link to this Comment: 6934

    Group Members: Paula A., Vanessa H., Shafiqah B., Romina G.

    Hypothesis: Music Affects the Heart rate.

    Methods:
    Everyone in the group had their heart rate taken four times. The first time was a control with no music. The second time was with the subject listening to Cuban rap. The third time was a control. And the fourth time was with the subject listening to funky jazz.

    Findings:
    Control 1
    Shafiqah: 99.01
    Romina: 98.20
    Paula: 81.74
    Vanessa: 77.52

    Cuban Rap
    Shafiqah: 93.31
    Romina: 88.63
    Paula: 81.08
    Vanessa: 69.93

    Control 2
    Shafiqah: 69.93
    Romina: 85.11
    Paula: 81.41
    Vanessa: 62.70

    Funky Jazz
    Shafiqah: 93.17
    Romina: 100.2
    Paula: 80.86
    Vanessa: 81.86

    Conclusion
    Our results were inconclusive. Different people had different results. For example, Shafiqah's highest was the 1st control and the lowest was in the second control. Romina's highest was funky jazz and the lowest was the second control. Paula's highest was the 1st control and the lowest was funky jazz. Vanessa's highest was funky jazz and the lowest was the 2nd control.

    Some of the things that might have affected these results would be preferences in music, previous exposure to the songs. These two things appeared to result in lower heart rates for the people in the group. The second control resulted in lower heart rates which could be due to familiarity to the testing procedure as opposed to the first time when people might have been a little nervous or excited about the test.


    Stay in School, Don't Do Drugs
    Name: Brianna Tw
    Date: 2003-10-21 14:52:32
    Link to this Comment: 6935

    Subject: Brianna
    Resting heart rate: 88.96

    Variables & Observations:
    Coldplay (mellow): 93.19, 94.96, 89.71 --> 92.62
    Techno Music: 91.63, 93.92, 97.27 --> 94.27
    Sad Thoughts: 96.8, 95.57, 92.33 --> 94.9
    Angry Thoughts: 98.06, 93.77, 94.66 --> 95.49
    Smoking: 124.8, 113, 107.5 --> 115.1
    Height: n/a

    Hypothesis:
    Heart rate is sensitive to external variables.

    Discussions:
    External variables affect the heart rate.

    Using our data collected from testing mental variables (ie. Sad Thoughts and Angry Thoughts), perhaps it is partially possible for humans to mentally control their heart rates. However, the heart rate seemed to adjust closer to the resting heart rate as time progressed.

    Smoking is bad.



    Name:
    Date: 2003-10-21 14:54:18
    Link to this Comment: 6936

    Brianna Twofoot, Michelle Choi, Emily Breslin, Charlotte Haimes were in the same group.

    Thanks.


    Katie Ottati, Bessy Guevara, Laura Wolfe
    Name: Bessy Guev
    Date: 2003-10-21 14:54:46
    Link to this Comment: 6937

    We conducted two experiments concerning heart rate - first looking at impact of air intake, secondly looking at activity level.

    Hypothesis for breathing: The less oxygen you take in, the higher the heart rate. e think the heart has to work faster when there is less oxygen coming in, and we've observed that when you hold your breath your heart seems to be pounding.

    Data:

    Control (sitting without moving or talking, breathing normally)

    1) 69 beats/min
    2) 75 beats/min
    3) 93 beats/min

    Holding breath

    1) 64.5 beats/min
    2) 92 beats/min
    3) 132 beats/min

    Deep Breathing

    1) 69 beats/min
    2) 87 beats/min
    3) 87 beats/min

    Conclusion: some data increased with the lack of air, which would support our hypothesis, but not all the data followed the same pattern. Therefore, we are unable to support the hypothesis with this data.

    hypothesis for activity: We think more activity would increase the heart rate. We used only one subject.

    Control = 93 beats/min

    Resting= 75 beats/min

    After jogging in place = 150 beats/min

    Conclusion: Our data supports our hypothesis.


    Lab
    Name: Justine, S
    Date: 2003-10-21 14:58:55
    Link to this Comment: 6938

    Hypothesis:
    Visual stimulus affects heart rate.

    Method:
    We retrieved various pieces of art retrieved from different websites. We had one "dark" piece, one "light" piece, and one "scary/shocking" piece for each. We showed the images to each group member and recorded her reaction.

    Justine
    Light: small decrease in amplitude, no change in frequency
    Shock: large decrease in amplitude, " "
    Dark: medium decrease in amplitude, but an overall wave pattern, " "

    Su-Lyn
    Light: Amplitude falls, no change in frequency
    Dark: increase in amplitude, no change in frequency
    Shocking: decrease in amplitude w/a slight wave pattern, no change in frequency

    Brittany
    Light: smaller decrease in amplitude, no change in frequency
    Dark: huge decrease in amplitude, no change in frequency
    Happy: increase in amplitude, increase in frequency


    Methods: Each member of the group searched the web and found different websites that showed different pictures of art.

    Conclusions

    First off, the main thing we learned in this lab is that visual stimulus *does* affect heart rate. No matter what image we showed a given group member, she had *some* sort of reaction to it.

    The observations support our hypothesis. However, we did not learn exactly how, as there were a number of factors we could not control. For example, the picture was *not* the only thing each group member saw, the art we used varied across different genres/styles/subjects, and we did not have a wide enough sample of different types of images to draw any conclusions about what type of image affects heartrate in what way. We also couldn't be 100% sure what changes were attributed to the visual stimuli themselves and what changes were attributed to the physical act of focusing on the images. Additionally, we had a huge number of technical difficulties, including slow internet, malfunctioning equipment, and difficulty in finding images. To determine with greater accuracy what types of visual stimuli affect heartrate in specific ways, we'd need more time, more subjects, and more images.


    Jump Around
    Name: Stefanie
    Date: 2003-10-22 14:26:27
    Link to this Comment: 6945

    Group: Stefanie Fedak, Alison Jost, Mariya Simakova, Julia Wise

    We hypothesize that physical activity will increase the heart rate of a person. In order to test this hypothesis we had each member of the group take their standing heart rate. Each member was then subject to a "rigorous" physical test (25 jumping jacks), a second reading was taken immediately following the physical activity.

    Data:

    Stefanie:
    Resting: 72 beats/minute
    After exercise: 112 beats/minute
    Increase in beats/minute: 40

    Julia:
    Resting: 76 beats/minute
    After exercise: 116 beats/minute
    Increase in beats/minute: 40

    Alison:
    Resting: 92 beats/minute
    After exercise: 144 beats/minute
    Increase in beats/minute: 52

    Mariya:
    Resting: 90 beats/minute
    After exercise: 120 beats/minute
    Increase in beats/minute: 30

    Our data supports the hypothesis that exercise will increase a person's heart rate.

    Therefore, from our observations, we may further hypothesize that other variables such as physical fitness, or pre-existing health conditions may also affect the number of beats per minute. Stefanie is an athlete who exercises seven days a week, and had both the lowest resting number of beats per minute and the lowest following the physical test. Julia, who lives in Brecon and exercises at the gym about once a week, had the second lowest standing number of beats per minute and the second lowest following the physical test. Mariya, who suffers from asthma which impedes her ability to exercise regularly, had a significantly higher resting heart rate and also a higher rate following the physical test. Alison, who would rather die than exercise, had the highest resting rate and the largest increase in beats per minute following the physical test.

    Other variables might include: anxiety regarding the act of performing jumping jacks in front of laughing peers (Alison), the pace at which each subject performed their jumping jacks (Mariya). We suspect that Mariya, who was not as enthusiastic about the testing (and was wearing heels) performed her jacks less rigrously than the other subjects. This might explain why she had the lowest increase in beats between her standing and post-activity heart rate.



    Name:
    Date: 2003-10-22 14:33:40
    Link to this Comment: 6946

    Patty Palermo
    Jessica Knapp
    Diana Medina
    Megan Williams
    Nomi Kaim


    We decided to investigate the effects of proximity to another classmate, as well as physical contact with another classmate, on a student's heart rate. Specifically, we measured Patty's seated heart rate while looking at the wall (baseline rate), while looking at Megan from a comfortable distance of about 4 feet, while looking at Megan from a culturally uncomfortable distance of about 1 foot, as well as while Megan patted her shoulder gently and, lastly, gave her a forceful shoulder massage.

    Our hypothesis: As compared to the base rate, increasing proximity to another and increasingly forceful touch will correspond with an increase in the seated person's heart rate. That is, a person at a comfortable distance will cause a slight increase in HR from the base rate (of sitting alone), a person at an uncomfortable distance will increase HR even more, a gentle touch will yield an HR that is higher still, and a forceful touch will cause the highest HR of all.



    Name:
    Date: 2003-10-22 14:33:53
    Link to this Comment: 6947

    Anna Marciniak, Melissa Teicher, Adina Halpern, Maggie Tucker

    We hypothesize that all of the following things will increase our heart rates:
    Holding our breath, Exercise, Smoking

    Normal Resting Heart Rate:
    Maggie: 60 bpm
    Anna: 94 bpm
    Adina: 63 bpm
    Melissa: 93 bpm

    Heart rate while holding breath:
    Maggie: 72
    Anna: 105
    Adina: 72
    Melissa: 93

    Heart rate while performing abdominal exercise (which does not include Movement):
    Maggie: 138
    Adina: 108
    Anna: 159
    Melissa: N/A

    Heart rate immediately after smoking one cigarette:
    Anna: 108
    Melissa: 96

    From these observations, it appears that heart rate is affected by outside viariables as we have deduced from the above tests. True to our hypothesis, exercise greatly affected heart rate. Holding breath increased heart rate slightly as did smoking. However, there was not as dramatic a difference in these last two cases.

    Had we more time, and funding for beds, we would have liked to have ruled out excess stimuli that could have had an affect on the resting heartbeats of our subjects. If we were to test them overnight, it would be interesting to see how dreams affect one's heartbeat. And had we male subjects to observe, how their heartbeat differs from females'.


    Heart Rate
    Name: Lindsay, A
    Date: 2003-10-22 14:37:08
    Link to this Comment: 6948

    By Alice Goldsberry, Christina Alfonso. Lindsay Updegrove, Rochelle Merilien

    We hypothesized that standing would increase our control heart rates (sitting down) and that jogging would increase it to an even greater extent.

    1. Sitting Down:
    Lindsay: 87 bpm
    Alice: 99 bpm
    Rochelle: 84 bpm
    Christina: 84 bpm

    2. Standing
    Lindsay: 93 bpm
    Alice: 102 bpm
    Rochelle: 96 bpm
    Christina: 102 bpm

    3. After Jogging
    Lindsay: 105 bpm
    Alice: 180 bpm
    Rochelle: 165 bpm
    Christina: 105

    Everyone's heart rate increased somewhat while standing, and after jogging around the hall for about thirty seconds it increased significantly for some of us and very little for others. This may be due to the fact that some of us get more exercise on a regular basis. Also some people may have taken longer to run although we all ran the same distance.

    We also tested holding our breath while taking our heart rates.

    Lindsay: 93 bpm
    Alice: 87 bpm
    Rochelle: 87 bpm
    Christina: 72 bpm

    We did not notice a significant difference in the frequencies of heart rates while holding our breaths. However, amplitude was lower than for the other tests and seemed to increase while taking the heart rates for Rochelle and Christina. We inferred from this that after holding our breath for a few seconds, our hearts start to work harder to circulate blood.


    From this data we can conclude that some factors that affect heart rate are sitting/standing position, exercise, and respiration.


    The Affected Heart Rate
    Name: enor lara
    Date: 2003-10-22 14:42:57
    Link to this Comment: 6949

    Lara, Ramatu, Enor and J'London

    Hypothesis: External factors will affect the heart rate and amplitude.

    Observations:
    Normal Heart Rates
    Lara: 88 beats per minute
    Ramatu: 88 beats per minute

    For the second part of our experiment we told the subject jokes (why was Helen Keller's ear red? Her iron rang. + What did the redneck boyfriend say to his redneck girlfriend when he wanted to break up? We can still be cousins) and read their affected heart rate after.

    Lara: We may have miscalculated the heart rate since the bar should have probobly been lowered, however it read 72 beats per minute - The more noticable change was the amplitude. At the highest point - the amplitude increased by 10 millivolts.

    Ramatu: again - this calculation may be wrong - 54 beats per minute
    But the more noticable amplitude change 10 millivolts.

    The third part of our experiment focused on what happens to your heart rate when you lie. Two questions were asked wherein the subject told the truth - then a third question was asked and a lie was told. The answered question for the third was an OBVIOUS lie.

    Lara : When she told the truth the amplitude remained steady however, when she lied the amplitude fluctuated. Heart rate 88 beats per minute.

    Ramatu: Same results as Lara

    Our fourth experiment tested heart rate when pain was inflicted. The pain was in the form of flicks and pinches.

    Lara: Amplitude increased by 20 mv when the first pinch occured. The second, more expected time, the amplitude increased by 5. The heart rate remained the same.

    Ramatu: Before flick the amplitude was steady - after the flick the amplitude went crazy and remained this way until the end of the trial even though there were two more flicks coming.


    continued!
    Name: Nomi et. a
    Date: 2003-10-22 14:45:20
    Link to this Comment: 6950

    continued...

    We took measurements at 20 second intervals and multiplied the number of beats (number of graph peaks) by three to get beats/minute. These are the data we collected:

    At Rest (Baseline): 69 beats/min
    Comfortable distance: (about 4-5 feet) 69 beats/min
    Uncomfortable distance: (about 1 foot) 69 beats/min
    Light Touch: 78 beats/min
    Forceful Touch: 81 beats/min

    Our data are partially consistent with our hypothesis but partially inconsistent. The fact that Patty's heart rate remained the same regardless of whether Megan was absent, near her, or very very near her suggests that proximity of another person does NOT affect heart rate (we had hypothesized that it would cause an increase). However, the increase from 69 beats/min to 78 beats/min when Megan touched Patty, and the subsequent increase to 81 beats per minute when Megan gave her a forceful massage, suggests a clear trend: having someone touch you will increase your heart rate, and the harder a person touches you, the more your heart rate will increase. This piece of our data is consistent with our hypothesis. Our data suggest, in sum, that proximity has no effect on heart rate, but that heart rate increases proportionally with the forcefulness of touch.

    Why? We think physical contact stimulates psychological responses associated with anxiety, which causes an increase in heart rate. With further investigation, we might test whether our findings are statistically significant (not due to chance) and, if so, why that might be so.



    Name:
    Date: 2003-10-22 14:50:29
    Link to this Comment: 6952

    Flicka Michaels
    Maria Scott-Wittenborn
    Kathryn McMahon

    Hypotheses: Heart rate is increased by running, lying, and holding your breath.

    Maria: heart rate when...
    resting 114 beats/min
    lying 114 beats/min
    running 162 beats/min
    holding breath 114 beats/min

    Flicka's heart rate when....,
    resting 90 beats/min
    lying 114 beats/min
    running 168 beats/min
    holding breath 111 beats/min

    Katy's heart rate when....
    resting 84 beats/min
    lying 84 beats/min
    running 159 beats/min
    holding breath 75 beats/min

    Our observations showed that running had a big impact on one's heat rate, greatly increasing in each case. However, lying had almost no impact on heart rate, except for Flicka's case. Holding breath was more ambiguous because it increased in some cases and decreased in others.


    Oneself As A Biological Entity. II. Reacting
    Name: Paul Grobstein
    Date: 2003-10-27 18:18:43
    Link to this Comment: 7015


    " if we don't think of a dog's tail wagging as simply that but rather as the visible culmination of bunches and bunches of smaller things doing their jobs ..." Maria

    So, how about when something touches us and we move? What sorts of smaller things are going on? That's what we want to look into today.

    A touch starts signals moving in sensory neurons which eventually cause signals to move in motor neurons which eventually cause muscle contractions and movement. How long does it take to move when one is touched? And how much of that time is the time it takes for signals to move from the endings of sensory neurons to the endings of motor neurons? How much of that time is the time it takes muscles to contract and cause movement? That's what we'll be looking at in the first part of the lab.

    In the second part of the lab, you and your team should develop your own questions and observation protocols to explore some interesting aspect of what is going on in reacting. For example, would you expect the time taken to be different if the stimulus occurred at a more distant location on the body? On the same side as the response as opposed to the opposite side? If the response was with your dominant or your non-dominant hand? Would you expect the time to change if you were tired? preoccupied? had recently had coffee? Is it the time that signals take within the nervous system that changes or the time for muscles to contract and cause movement? Or both?

    Don't try and answer ALL the questions. Pick one (or think up one) that you're interested in and have a guess about. And collect enough data so you have some confidence in your conclusions about that situation. And write up your question/hypothesis, observations, conclusions in the lab forum.


    dominant hand vs latency
    Name: Nancy and
    Date: 2003-10-28 14:34:05
    Link to this Comment: 7025

    We decided to see whether or not using the dominant hand would affect reaction time (and latency).

    HYPOTHESIS: The dominant hand will have a faster reaction time than the subordinate hand.

    Note: we are both right handed.

    Nancy Right Hand:
    trial one
    - TTL latency-- .22
    - Latency one-- .11
    - Latency two-- .11

    trial two
    - TTL-- .14
    - one-- .08
    - two-- .06

    Talia right hand:
    trial one
    - TTL-- .20
    - one-- .04
    - two-- .16

    trial two
    - TTL-- .35
    - one-- .31
    - two-- .04

    Nancy Left hand
    trial one
    TTL-- .29
    -one-- .19
    - two-- .10

    trial two
    TTL-- .57
    -one-- .52
    - two-- .05

    Talia Left hand
    trial one
    TTL: .24
    one-- .21
    two-- .03

    trial two
    TTL-- .26
    -one-- .22
    - two-- .04

    OBSERVATIONS: We observed that there seemed to be faster respnse times in the dominant hand. This was the case in three out of four trials. The fourth trial could have been influenced by a numer of factors, including outside noise, thought patterns, etc.


    Time between stimulus and reaction in dominant and
    Name: Charlotte
    Date: 2003-10-28 14:54:27
    Link to this Comment: 7026

    Charlotte Haimes, Elisabeth Py

    Hypothesis: With the assumption that the dominant hand is more used than the non-dominant hand, the time of reaction for the dominant hand would occur in less time than it would for the non-dominant hand.

    Observations in the thumb of the dominant hand:
    1. muscle activity 5.93
    total time of reaction 5.97
    initial time of stimulus 5.56
    Latency 1 = 0.37
    Latency 2 = 0.04

    2. muscle activity 4.2
    total time of reaction 4.29
    initial time of stimulus 3.98
    Latency 1 = 0.22
    Latency 2 = 0.09

    3. Muscle activity 4.5
    total time of reaction 4.61
    initial time of stimulus 4.35
    Latency 1=0.15
    Latency 2=0.11

    Observations in the thumb of the non-dominant hand:
    1. muscle activity 4.62
    total time of reaction 4.69
    initial time of stimulus 4.48
    Latency 1= 0.14
    Latency 2=0.07

    2. muscle activity 4.23
    total time of reaction 4.27
    initial time of stimulus 4.01
    Latency 1 = 0.26
    Latency 2 = 0.04

    3. muscle activity 4.84
    total time of reaction 4.86
    initial time of stimulus 4.67
    Latency 1=0.17
    Latency 2=0.02

    Conclusion:
    Our initial assumption that the dominant hand would react faster to the stimulus was proved wrong: the time between the stimulus and the movement of the muscle is approximately the same and sometimes faster in the non-dominant hand and the time of the muscle contraction shows a faster movement in the non-dominant hand. Therefore, there is no correlation between a dominant side of the body and its time of reaction and movement.


    Manuela, Katie, Bessy, LaToiya
    Name:
    Date: 2003-10-28 14:55:08
    Link to this Comment: 7027

    Control (eyes closed):

    Katie: Latency 1 (average) 0.2 Latency 2 (average) 0.05

    Manuela: Latency 1 (average) 0.075 Latency 2 (average) 0.041

    Bessy: Latency 1 (average) 0.2 Latency 2 (average) 0.05

    La Toiya: Latency 1 (average) 0.22 Latency 2 (average) 0.06

    Our hypothesis states that when a person can see the stimulus coming, both latency periods will be shorter.

    Eyes open, watching stimulus:

    Katie: Latency 1 (average) 0.07 Latency 2 (average) 0.03

    Manuela: Latency 1 (average) 0.02 Latency 2 (average) 0.062

    Bessy: Latency 1 (average) 0.03 Latency 2 (average) 0.06

    La Toiya: Latency 1 (average) 0.04 Latency 2 (average) 0.07

    Our hypothesis was only partially correct. The response time (Latency 1) is shorter, but muscle movement (Latency 2) still takes about the same amount of time.


    Melissa Hope, Abby Fritz
    Name:
    Date: 2003-10-28 15:01:45
    Link to this Comment: 7028

    HYPOTHESIS:
    The reaction time to a stimulus with a non-dominant hand will be slower than the reaction time with a dominant hand.

    DATA:
    Dominant --
    Melissa: TL - .383, L1 - .370, L2 - .330
    Abby: TL - .177, L1 - .148, L2 - .136

    Non-dominant --
    Melissa: TL - .266, L1 - .246, L2 - .041
    Abby: TL - .291, L1 - .246, L2 - .047

    Summary: After performing three trials on each variable (dominant/non-dominant), we averaged the times and came up with the data presented. Abby's data was consistent with the hypothesis, but Melissa's was not. The data therefore was could not support this hypothesis or the opposite of this hypothesis, because of the inconsistency of our data.
    We found that L1 was consistently slower than L2, but the lag time varied significantly. Why?
    These discrepancies may have been due to the fact that stimulus was applied to the same arm in both experiments.



    Name: Sarah, Nat
    Date: 2003-10-28 15:09:15
    Link to this Comment: 7029

    First, we tested our reaction times to the stimulus of being tapped with a mallet on the leg by pressing a button as soon as we felt the tap. We measured the latency periods of the reaction times: between the stimulus and the muscle contraction and between the muscle contraction and the response. We took 3 trials per test subject to ensure reliability of the results. Here are our results in seconds:

    Test Subject 1 (Natalya):
    Latency 1(between stimulus and muscle contraction): .18, .24, .12
    Latency 2 (between muscle contraction and response): .07, .07, .07
    Test Subject 2 (Sarah):
    Latency 1: .28, .18, .16
    Latency 2: .12, .07, .09
    Test Subject 3 (Brittany):
    Latency 1: .04, .21, .29
    Latency 2: .06, .07, .06

    For the second part of the lab, we attempted to determine whether or not the location of the stimulus on the test subject's body affected their reaction time. We tested 3 stimulus locations: the original data from tapping on the leg, and then 2 new locations (3 trials each) on the head and the foot. Our hypothesis was the the closer the stimulus is to the brain, the faster the reaction time. Therefore, we hypothesized that the head tap would produce the fastest reaction time and the foot tap would produce the slowest. Here is our data in seconds:

    Test Subject 1:
    (Natalya - Head):
    Latency 1: .27, .16, .11 Average: .18
    Latency 2: .05, .51, .06 Average: .20
    (Natalya - Ankle):
    Latency 1: .24, .28, .15 Average: .22
    Latency 2: .05, .05, .12 Average: .07
    Test Subject 2:
    (Sarah - Head):
    Latency 1: .17, .19, .13 Average: .16
    Latency 2: .05, .10, .09 Average: .08
    (Sarah - Ankle):
    Latency 1: .25, .14, .20 Average: .19
    Latency 2: .07, .15, .07 Average: .09
    Test Subject 3:
    (Brittany - Head):
    Latency 1: .22, .22, .19 Average: .21
    Latency 2: .07, .05, .08 Average: .06
    (Brittany - Ankle):
    Latency 1: .26, .36, .27 Average: .29
    Latency 2: .06, .03, .04 Average: .04

    Overall, our results for the latency 1 period (from the stimulus to the muscle action) is faster when the stimulus location was closer to the head. But the latency 2 period (from the muscle action to the response) varied by test subject. So though our results appear to corroborate our hypothesis, the results are not conclusive. Our hypothesis for further research is that the latency 2 period is independent of stimulus location in relation to the head. We do believe that our data supports our claim for at least the latency 1 period.



    Name:
    Date: 2003-10-28 15:12:32
    Link to this Comment: 7030

    Justine Patrick, Vanessa Herrera, Shafiqah Berry

    Hypothesis: Our hypothesis for this experiment was to test the difference in reaction between the dominant hand and the other. Both subjects were hit on their knee in the area above the patella.

    Results:
    Vanessa:
    - standing up during both trails
    Right Hand: (dominant)
    Latency Total: -.240 (Trial 1)
    Latency Total: -1.05 (Trial 2)
    Latency Total: -1.186 (Trial 3)

    Left Hand:
    Latency Total: -.081 (Trial 1)
    Latency Total: -.107 (Trial 2)
    Latency Total: -.167 (Trial 3)

    Justine:
    - sitting down in the chair
    Right Hand: (dominant)
    Latency Total:-.187 (Trial 1)
    Latency Total:-.198 (Trial 2)
    Latency Total: -.184 (Trial 3)

    Left Hand:
    Latency Total:-. 194 (Trial 1)
    Latency Total: -.136 (Trial 2)
    Latency Total: -.152 (Trial 3)

    Conclusion:
    See first conclusion (ie experiment done by the first group)


    Right/Left hand dominance
    Name:
    Date: 2003-10-29 14:38:00
    Link to this Comment: 7037

    By Margaret Tucker, Mariya Simakova, and Lindsay Updegrove

    We tested the muscle reaction times on both our left and right hands. All of us are right-handed. We hypothesized that the muscle contraction times would be faster on our right hands.

    Data (Average of 3 tests):

    Margaret:
    Right Hand: 0.05 milliseconds
    Left Hand: 0.06 milliseconds

    Mariya:
    Right Hand: 0.03 milliseconds
    Left Hand: 0.06 milliseconds

    Lindsay:
    Right Hand: 0.03 milliseconds
    Left Hand: 0.03 milliseconds

    The data seems to have supported our hypothesis. Lindsay's reactions could be explained by the fact that she was ambidextrous as a child but got used to using her right hand to write. The muscles in the right hand are more trained to reacting to stimuli. This is why it takes them less time to shorten and press the button. It was interesting that the times between the initial stimulus and beginning of muscle reaction did not vary significantly between hands. This could lead to a further hypothesis that since the arms are equidistant from the central nervous system, it takes the left and right equal amounts of time to process the reaction signal.



    Name:
    Date: 2003-10-29 14:50:39
    Link to this Comment: 7038

    Anna Marciniak
    J'London Hawkins
    Enor Wagner
    Melissa Teicher

    Hypothesis: We observed the reaction times of the dominant vs. the non-dominant hands. We hypothesized that the dominant hand would have a faster reaction time than the non-dominant hand.

    Note: Each of the women observed was dominant in her right hand.

    Key:
    first figure = time from stimulus to muscle activity
    second figure = time from muscle activity to response

    Dominant:

    Anna
    1.) 90 ms
    43 ms

    2.) 4 ms
    28ms

    3.) 78 ms
    39 ms

    J'London
    1.) 140 ms
    64 ms

    2.) 126 ms
    63 ms

    3.) 120 ms
    31 ms

    Enor
    1.) 185 ms
    29 ms

    2.) 252 ms
    21 ms

    3.) 214 ms
    36 ms

    Non-Dominant:

    Anna
    1.) 153 ms
    40 ms

    2.) 143 ms
    27 ms

    3.) 141 ms
    28 ms

    J'London
    1.) 77 ms
    92 ms

    2.) 154 ms
    50 ms

    3.) 121 ms
    48 ms

    Enor
    1.) 97 ms
    32 ms

    2.) 150 ms
    62 ms

    3.) 236 ms
    69 ms

    Anna's data was consistent with our hypothesis in regards to the time from the stimulus to muscle activity; however, J'London's and Enor's data was inconsistent. In regards to the time from muscle activity to response, we did not see enough of a change in time from dominant to non-dominant hand for it to be significant.

    We cannot say for sure if our hypothesis was correct or not based on our data. Perhaps there is no difference from dominant to non-dominant hand. We attribute our inconsistencies in observations to expectancy, which hand was tested first, desensitization of reactions, etc.



    Name:
    Date: 2003-10-29 14:50:47
    Link to this Comment: 7039

    Alison, Julia, Adina

    We studied the effect of distance of stimulus from the brain on reaction time. The body parts we tested were upper arm, ankle, and head, and we tested each body part of each person three times. We hypothesized that the further from the brain the stimulus, the longer the response time would be.

    Average Results:
    Alison:
    Arm: 0.17 sec
    Head: 0.21 sec
    Ankle: 0.38 sec

    Adina:
    Arm: 0.51 sec
    Head: 0.23 sec
    Ankle: 0.35 sec

    Julia:
    Arm: 0.40 sec
    Head: 0.37 sec
    Ankle: 0.41 sec

    These results do not support our hypothesis. There are other factors that influence reaction time but distance does not appear to be significant.



    Name:
    Date: 2003-10-29 15:06:21
    Link to this Comment: 7040

    Flicka, Diana, Alice

    Hypothesis: Poking people in places farther away from the brain will take them longer to react to the stimulus.

    Alice:

    ankle: 0.24-0.04
    knee: 0.17-0.04
    chest: 0.19-0.04

    foot: 0.34-0.02
    calf: 0.18-0.04
    back: 0.19-0.03

    calf: 0.20-0.02
    wrist: 0.18-0.04
    forehead: 0.19-0.03

    Flicka:

    b. knee: -0.54-0.03
    forearm: 0.34-0.01
    neck: 0.23-0.03

    thigh: 0.43-0.01
    elbow: 0.12-0.01
    b of shoulder: 0.22-0.01

    calf: 0.49-0.01
    l. hand: 0.26-0.03
    forehead: 0.38-0.01

    Conclusion: We decided that there is no correlation between the poking and the distance from the brain because in some cases, the reaction time was greater when stimulated farther away from the brain. Our data was inconsistent, which leads us to conclude that there are other factors that influence the reaction time.


    The Effect of Right vs. Left Hand on Stimulus-Resp
    Name: Denise, Me
    Date: 2003-10-29 15:06:23
    Link to this Comment: 7041

    Megan , Nomi, Denise

    We tested the effect of using the right vs. left hand to push a button on total response time. Does the hand used make a difference in total reaction time?

    Hypothesis: Total reaction time will be higher for the left hand in right-handed people than for the right hand. This will occur because right-handed people have better developed nerve pathways and muscles on the right side of the body than the left.

    We took 5 measurements for each the right and the left hand in three subjects (a total of 30 pieces of data collected). We then averaged the 5 left- and right-hand data points for each person, resulting in one figure for each hand of each person. To keep variables other than the experimental (which hand) constant, subjects positioned their arm on the table and held the button in the same way each time. The administrator-of-touch hit the subject in the same place each trial with as constant a force as possible. The subjects closed their eyes so they would not overly anticipate the time of touch administration.

    Our averages were as followed:

    Total Average Time between stimulus and response

    Subject A
    right hand- .18
    left hand - .20

    Subject B
    right hand- .19
    left hand- .18

    Subject C
    right hand - .20
    left hand - .16

    These data do not support our hypothesis. Although the left hand response time was longer for one subject (A), it was actually shorter for the other two cases -- the reverse of our hypothesis. Moreover, the differences among all of the data points -- no more than .04 in total, and no more than .02 in all but one cases -- do not appear significantly / proportionally large enough to suggest any significant trend. Rather, the differences in response time seem attributable to chance / experimental error.

    The fact that the left hand response time was slightly longer in one case and slightly shorter in two cases suggests that these differences, rather than representing a trend, are randomly distributed around some average. This means that the response times for right vs. left hands are probably NOT significantly different from each other, as a whole. Nor do they seem to be significantly different for any one subject we tested.

    Our results also indicate, by induction, that the neural pathways and muscles involved with the left vs. right hands -- and perhaps the left and right sides of the body? -- do not significantly differ.


    Muscle Reaction Time
    Name: Patty
    Date: 2003-10-29 15:20:29
    Link to this Comment: 7042

    Patty Palermo, Ramatu Kallon, and Rochelle Merilien

    We hypothesized that the closer the probe was located to the brain on the body, the shorter the distance would be for the message to travel from the probed area of the body-to the brain-and back to the subjects hand for a response.

    We took 3 samples of responses from being probed in 4 diffrent parts of the body: 1) The thigh, 2) the toe, 3) the shoulder, and 4) the forehead. We wanted to use body parts that we 1) a moderately far place on the body as a type of control, 2) the farthest place on the body from the brain, 3) a place that is between the brain and the hand that will be responding, and 4) the place closest to the brain. We wanted to observe which place would elicit the quickest response.

    L1 Neural Processing
    L2 Motor Response
    TL L1+ L2

    Thigh Test

    Trial 1 L1= .3147
    L2= .0123
    TL= .327
    Trial 2
    L1= -.066
    L2= .3185
    TL= .3845
    Trial 3
    L1= -.014
    L2= .0405
    L3= .0265

    Toe Test

    Trial 1
    L1= .1841
    L2=.2364
    TL= .4205
    Trial 2
    L1= -.005
    L2= .1076
    TL= .1026
    Trial 3
    L1= .0801
    L2= .2328
    TL= .3129

    Shoulder Test

    Trial 1 L1= .1275
    L2= .1678
    TL= .2953
    Trial 2
    L1= .0524
    L2= -.173
    TL= -.1206
    Trial 3
    L1=.0826
    L2=.0761
    TL= .1587

    Forhead Test

    Trial 1
    L1= .059
    L2= .0761
    TL= .6661
    Trial 2
    L1= .0847
    L2= .1325
    TL= .9795
    Trial 3
    L1= .125
    L2=.0509
    TL= .1759

    We determined that the shortest time between L1 and L2 on average would indicate that the travel time of the neural message to response was fastest. .246 was the average TL for our control (the thigh.) .278 was the average TL for the toe test, which supported our hypothesis. .3337 was the average TL for the shoulder test, which was extremely suprizing to us, as it would have little space between the hand and the brain and this response time took longer than the toe. (we poked on the arm that we were responding with.) And finally, the average TL on the forehead test was .607 which was far greater than we had expected.


    Oneself As A Biological Entity. III. Thinking
    Name: Paul Grobstein
    Date: 2003-11-03 21:10:45
    Link to this Comment: 7097

    Reflecting on our lab [last week] makes me marvel at how mechanical we humans really are. ... I was also amazed when Professor Grobstein told us that thinking burns calories. I wonder if it burns more if you're thinking harder. It's so strange that the mysterious processes of thought and emotion could be quantified in time and space ... Natalya

    So, what about "thinking"? Can that be "quantified in time and space"? Its an interesting question, first asked explicitly in the late 1800's with a very clever set of observations then requiring elaborate equipment. Today we can make the same observations more easily. See Time to Think?.

    The observational set up allows one to measure various kinds of thinking, as well as to test hypotheses about how they are related to one another. Once you get the hang of it, you can/should develop your own hypotheses about what might or might not influence the various kinds of thinking time. And develop your own experiments. Do one as a group in class. And you're free to do additional ones any place you can find a computer.

    Remember that we've reached a phase where we'd like to have our hypotheses and observations sufficiently in hand so that we can generate as conclusions something more than "more data is needed".



    Name:
    Date: 2003-11-04 13:04:52
    Link to this Comment: 7103

    Flicka, Diana, Alice

    Hypothesis: Poking people in places farther away from the brain will take them longer to react to the stimulus.

    Alice:

    ankle: 0.24-0.04
    knee: 0.17-0.04
    chest: 0.19-0.04

    foot: 0.34-0.02
    calf: 0.18-0.04
    back: 0.19-0.03

    calf: 0.20-0.02
    wrist: 0.18-0.04
    forehead: 0.19-0.03

    Flicka:

    b. knee: -0.54-0.03
    forearm: 0.34-0.01
    neck: 0.23-0.03

    thigh: 0.43-0.01
    elbow: 0.12-0.01
    b of shoulder: 0.22-0.01

    calf: 0.49-0.01
    l. hand: 0.26-0.03
    forehead: 0.38-0.01

    Conclusion: We decided that there is no correlation between the poking and the distance from the brain because in some cases, the reaction time was greater when stimulated farther away from the brain. Our data was inconsistent, which leads us to conclude that there are other factors that influence the reaction time.



    Name: Group Supe
    Date: 2003-11-04 14:55:37
    Link to this Comment: 7104

    Group: Paula "Fascist" Arboleda, Romina "ADHD" Gomez, Toiya "I Don't Care" La Vita

    Hypothesis: Foreign language speakers will react slower to English instructions b/c it takes longer to process.

    Observations:
    These are only the averages out of 10 trials.

    Romina (non native speaker)
    Case 1: 250 sd:16
    Case 2: 340 sd 82
    Case 3: 495 sd 49
    Case 4: 968 sd 323

    Toiya (English speaker)
    Case 1: 234 sd 16
    Case 2: 320 sd 65
    Case 3: 514 sd 78
    Case 4: 555 sd 147

    *sd= standard deviation

    Overall, our results supported our hypothesis. It seemed that Romina had a significantly slower reaction time than Toiya, especially when the instructions became more complicated, i.e Case 4. In the case of Case 3, Romina pressed the button at the wrong time several times causing her scores to be randomly deleted. She therefore had to pay closer attention which may have contributed to her faster score.


    Reaxn
    Name: emily & mi
    Date: 2003-11-04 14:56:25
    Link to this Comment: 7105

    Data (Avg., Standard Deviation):
    Emily
    Case 1: 243 ms, 73 ms.
    Case 2: 387 ms, 182 ms.
    Case 3: 644 ms, 199 ms.
    Case 4: 710 ms, 508 ms.

    Michelle
    Case 1: 207 ms, 13 ms.
    Case 2: 308 ms, 97 ms.
    Case 3: 474 ms, 131 ms.
    Case 4: 471 ms, 131 ms.

    Average:
    Case 1: 313.39 ms.
    Case 2: 376.59 ms.
    Case 3: 633.34 ms.
    Case 4: 773.55 ms.

    Conclusions:
    By analyzing the steady increase in reaction time, it is apparent that thinking and reacting are two different processes. They are certainly related, but represent very different demands on the brain. When the exercise demanded a simple reaction, response time was much quicker. As the demands increased, so did the response time.


    Brain Reaction
    Name: Brianna
    Date: 2003-11-04 14:57:32
    Link to this Comment: 7106

    Act: 245 p/m 62
    Think/Act: 330 p/m 69Read/Think/Act: 507 p/m 96
    Read/Think/Negate: 682 p/m 167

    Time to Act: 245 p/m 62
    " Think: 85 p/m 93
    " Read: 177 p/m 119
    " Negate: 175 p/m 193


    I thought that the more trials I did, the faster my time would become, because my brain would adjust/anticipate the next action of the program. However, it happened that the last two trials of each test were the worst times. Additionally, outside distractions increased my response time. So, there was no consistency in the trials of each test, when isolated, probably due to outside distraction. However, as I suspected, the more processes the test had, the longer it took my brain to react. In other words, each test took longer and longer to complete. However, my thinking time was less than half the time it took me for the other processes. I anticipated the act time to be the least, because it was the least complex of the processes, basically muscle reaction. However, it was longest. The think time was the least. This leads me to the conclusion that thinking and reacting are two different processes.


    Time and Thinking
    Name: Sarah and
    Date: 2003-11-04 14:59:34
    Link to this Comment: 7107

    First, we conducted a series of trials for our baseline data. We did 10 trials for each of the 4 tests: act (A); think and act (TA); read, think, and act (RTA); and read, think-negate, and act (RTNA). The results are as follows:

    Test Subject 1 (Sarah):
    A: 282, sd: 47
    TA: 392, sd: 58
    RTA: 490, sd: 71
    RNTA: 585, sd: 164

    Test Subject 2 (Natalya):
    A: 241, sd: 21
    TA: 276, sd: 47
    RTA: 428, sd: 88
    RNTA: 455, sd: 85

    Next, we decided to investigate how chewing gum affected our thinking time. We used the same method as in the first set of trials, but each chewed a piece of Dentyne Ice while conducting the new trials. Sarah hypothesized that she would perform better while chewing gum, while Natalya had the opposite hypothesis for herself. These hypotheses were based on previous experience and personal preferences. Here are the data:

    Sarah (test subject 1):
    A: 249, sd: 80
    TA: 384, sd: 85
    RTA: 622, sd: 141
    RNTA: 569, sd: 177

    Natalya (test subject 2):
    A: 284, sd: 28
    TA: 403, sd: 130
    RTA: 539, sd: 72
    RNTA: 740, sd: 393

    Sarah's hypothesis for herself was supported by the data because overall, her average times for every test were faster when chewing gum. The standard deviations for each of her tests while chewing gum were bigger though, than the original test, showing that while in general, the second trial was faster, it also had a bigger variety. Natalya's hypothesis for herself held true in all cases as well. However, her standard deviations were also larger, except in the RTA case. But the RNTA case shows an especially large standard deviation during her second trial while chewing gum.

    Overall we can't conclusively state that chewing gum either helps or hinders thinking time, but we can state that our individual hypotheses based on personal preference were correct.


    Melissa, nancy, Abby
    Name: nancy abby
    Date: 2003-11-04 15:04:40
    Link to this Comment: 7108

    Hypothesis: As the difficultly the task performed increases, the time needed to perform the task will increase as well.

    Hypothesis 2: Performing the second group in a reversed order, our case 4 (Originially case 1) times would decrease due to prolonged focus on the previous three tests.

    Method: We performed 10 trials twice for each of the four cases. The first group of data was simply following the case as laid out. For the second group of data, the sequence was performed in reverse order- from case 4 to case 1. The data is as follows:

    MELISSA:
    Group 1
    subj_id trial_type avg sd num_trials
    675 A 255 30 10
    675 TA 325 99 10
    675 RTA 559 140 10
    675 RNTA 495 74 10

    Group 2
    subj_id trial_type avg sd num_trials
    686 A 270 65 10
    686 TA 302 57 10
    686 RTA 492 148 10
    686 RNTA 430 105 10

    NANCY:
    Group 1
    subj_id trial_type avg sd num_trials
    689 A 270 58 10
    689 TA 371 96 10
    689 RTA 501 56 10
    689 RNTA 578 119 10

    Group 2
    subj_id trial_type avg sd num_trials
    695 A 271 31 10
    695 TA 362 57 10
    695 RTA 532 90 10
    695 RNTA 449 31 10

    ABBY:
    Group 1
    subj_id trial_type avg sd num_trials
    690 A 334 142 10
    690 TA 303 65 10
    690 RTA 578 126 10
    690 RNTA 597 51 10

    Group 2
    subj_id trial_type avg sd num_trials
    696 A 244 42 10
    696 TA 370 63 10
    696 RTA 522 99 10
    696 RNTA 568 138 10


    Summary: From our results, our results were not consist with our hypothesis- actually becoming the opposite of the expected in two of the three case subjects.

    We observed that when performing task 4 (the most difficult) first a opposed to last, times decreased for all of us.


    Laura Wolfe, Katie Ottati
    Name:
    Date: 2003-11-04 15:07:58
    Link to this Comment: 7109

    Hypothesis: Based on initial observations, we think that thinking, acting and talking will take more time than just acting and thinking - basically that talking requires additional thinking time.

    When acting/talking, subjects carried on a conversation while completing the "Act" excercise.

    Subject 1 -
    Act: 234 +/- 27
    Acting & thinking: 304 +/- 28
    Reading, thinking, acting: 553 +/- 124
    Reading, thinking, negating, acting: 722 +/- 522
    *Acting, talking: 320 +/- 19

    Subject 2 -
    Act; 233 +/- 25
    Thinking, acting: 398 +/- 81
    Reading, thinking, acting: 664+/- 107
    Reading, thinking, negating, acting: 901 +/- 142
    * Acting, talking: 464 +/- 145

    Conclusion: Our data supports our hypothesis. Subject 2, for example, had a diference of 165 milliseconds between "act" and "thinking and acting", and a 66 millisecond difference between "thinking and acting" and "talking and acting". It appears that talking requires thought and thus slows the reation time.


    Time to think
    Name:
    Date: 2003-11-04 15:11:12
    Link to this Comment: 7110

    Maria Winterborn, Manuela C.
    subj_id trial_type avg sd num_trials

    Manuela A 191 10 5 Average reactions: 312.11
    Manuela TA 292 58 5 Average 375.55
    Manuela RTA 387 53 5 Average 630.87
    Manuela RNTA 373 92 5 Average 769.23

    Maria A 193 40 5
    Maria TA 215 41 5
    Maria RTA 408 70 5
    Maria RNTA 345 59 5

    Time to Act: 193 40 milliseconds
    Time to Think: 22 58 milliseconds
    Time to Read: 193 82 milliseconds
    Time to Negate: -63 92 milliseconds

    Our hypothesis predicted that Manuela as a non native English speaker would take significantly longer to follow instructions and react and follow instructions and do the opposite than Maria, native English speaker.

    Observations: Both students have comparable times, though Maria was faster in the last trial (negating instructions). Both students were also significantly faster than the averages in all of the trials, and it is important to keep in mind that our times to act and think and act, are pretty similar, Maria being faster in the second.

    Our hypothesis then can not be confirmed. Also keeping in mind the averages, for which we are assuming most test takers have English as a native language (?), both the native and the non native English speaking students were quicker. Determining level of fluency is also more difficult, which might undermine differences.


    Su-Lyn, Brittany
    Name:
    Date: 2003-11-04 15:15:01
    Link to this Comment: 7111

    Introduction:
    If thinking is a physical process, then it follows that thinking should take time. From Donders's psychometric studies, we know that thinking is indeed a physiological process that takes time.

    In addition to reading and negation, thinking time may be affected by outside stimuli. In this lab, we studied the effects of distraction (in the form of music) on thinking time. We tested the hypothesis that listening to music lengthens thinking time.

    Methodology:
    We first performed two controls using Donders's methodology; we then repeated his experiments while listening to music.

    Results:

    Act Time
    Think, Act Time:
    Read, Think, Act Time:
    Read, Think-Negate, Act Time:


    Time to Act:
    Time to Think:
    Time to Read:
    Time to Negate:
    Su-Lyn control
    250 73 milliseconds
    339 40 milliseconds
    541 151 milliseconds
    504 60 milliseconds

    250 73 milliseconds
    89 84 milliseconds
    202 157 milliseconds
    -37 163 milliseconds
    Su-Lyn with music
    325 134 milliseconds
    355 52 milliseconds
    558 159 milliseconds
    587 164 milliseconds

    325 134 milliseconds
    30 144 milliseconds
    203 168 milliseconds
    29 229 milliseconds

    Act Time
    Think, Act Time:
    Read, Think, Act Time:
    Read, Think-Negate, Act Time:


    Time to Act:
    Time to Think:
    Time to Read:
    Time to Negate:
    Brittany control
    244 41 milliseconds
    281 54 milliseconds
    575 224 milliseconds
    546 119 milliseconds

    244 41 milliseconds
    37 68 milliseconds
    294 231 milliseconds
    -29 254 milliseconds
    Brittany with music
    348 122 milliseconds
    384 47 milliseconds
    483 45 milliseconds
    700 166 milliseconds

    348 122 milliseconds
    36 47 milliseconds
    99 45 milliseconds
    217 166 milliseconds
    Conclusions:

    The results show that when the subject is listening to music, she is distracted and thus thinking takes longer. These observations are consistent with our hypothesis that listening to music lengthens thinking time.


    Vanessa Herrera, Shafiqah Berry
    Name:
    Date: 2003-11-04 15:15:36
    Link to this Comment: 7112

    Vanessa
    Control 1:
    674 A 1 209
    674 A 2 292
    674 A 3 246
    674 A 4 248
    674 A 5 262
    674 A 6 243
    674 A 7 277
    674 A 8 283
    674 A 9 336
    674 A 10 282
    674 RNTA 1 725
    674 RNTA 2 800
    674 RNTA 3 660
    674 RNTA 4 1007
    674 RNTA 5 683
    674 RNTA 6 415
    674 RNTA 7 634
    674 RNTA 8 673
    674 RNTA 9 464
    674 RNTA 10 573

    Variable A:
    A 318
    A 291
    A 242
    A 253
    A 287
    A 306
    A 512
    SA 356
    A 321
    A 304
    RNTA 834
    RNTA 522
    RNTA 888
    RNTA 1076
    RNTA 988
    RNTA 1047
    RNTA 943
    RNTA 908
    RNTA 511
    RNTA 468

    Shafiqah
    Control B:
    A 254
    A 214
    A 234
    A 259
    A 237
    A 424
    A 226
    A 276
    A 231
    A 233
    RNTA 908
    RNTA 834
    RNTA 704
    RNTA 712
    RNTA 896
    RNTA 748
    RNTA 450
    RNTA 758
    RNTA 608
    RNTA 650

    Variable B:
    A 243
    A 493
    A 234
    A 225
    A 208
    A 276
    A 272
    A 288
    A 257
    A 307
    RNTA 638
    RNTA 554
    RNTA 822
    RNTA 832
    RNTA 796
    RNTA 794
    RNTA 674
    RNTA 632
    RNTA 578
    RNTA 530

    Our variable represents the change in action time and thinking speed after prayer. Our observatins concludes that our times are much slower in the variable than in the control. We believe this to be so, for when the mind has been cleared we have to think twice as much.



    Name: Stefanie F
    Date: 2003-11-05 14:18:36
    Link to this Comment: 7124

    We hypothesize that, because Stefanie is an athlete (and Alison is far from one), that Stefanie's reaction time will be faster than Alison's. Because, for instance, Stefanie participates daily in basketball which requires her to think and react quickly. Our dilemma was, how would this affect the reading and reacting portion. However, when a play is called from the sideline or by the point guard Stefanie has to think about that play, recall what it is, and then begin to move. Therefore, the basic ins and outs of athletics will have honed Stefanie's thought and reaction processes.

    Summary of Data:

    Stefanie's Average Times:
    Trial 1: 196 milliseconds
    Trial 2: 251 milliseconds
    Trial 3: 479 milliseconds
    Trial 4: 536 milliseconds

    Alison's Average Times:
    Trial 1: 231 milliseconds
    Trial 2: 320 milliseconds
    Trial 3: 499 milliseconds
    Tiral 4: 721 milliseconds

    From the data, we see that Alison's reaction times are consistently slower than Stefanie's. Our data is consistent with our hypothesis in that Stefanie, the athlete, is faster than Alison.


    reaction time
    Name: Megan, Eno
    Date: 2003-11-05 14:21:50
    Link to this Comment: 7125

    Megan and Enor

    Hypothesis- Reaction time will consistently go down as the subject become habituated to the experimental process. The response time will become increasingly lower because the subject is desensitized to the directions.

    Megan's data (in milliseconds)
    ACT- 196, 213, 198, 185, 265
    THINK, ACT- 288, 470, 274, 236, 251
    READ, THINK, ACT- 426, 356, 365, 336, 298
    READ, THINK/NEGATE, ACT- 784, 409, 319, 352, 367

    Enor's data (in milliseconds)
    ACT- 232, 271, 260, 211, 217
    THINK, ACT- 242, 612, 458, 454, 354
    READ, THINK, ACT- 692, 848, 610, 520, 619
    READ, THINK/NEGATE, ACT- 1104, 941, 744, 826, 419

    Conclusions- Our results did not prove our hypothesis. We noticed that many of our trials had a slight improvement in reaction time as the trials went on, yet the improvement was not consistent in the majority of our trials. The reason for this may be that when the directions are first read, the subject anticipates the response more strongly. The experiment is more exciting because it is new and thus your mind is more focused on the experiment. As the time goes on, and more trials are done, the anticipation lessens.


    Julia and Alice's marvelous data
    Name:
    Date: 2003-11-05 14:44:16
    Link to this Comment: 7127

    We decided to test the effect of distraction on time to react, think, read, and negate. We thought a distracted person would take more time to do these things than a person who was not distracted. We did five tests each with no distractions, and five tests each while talking to someone else.

    Julia
    Undistracted: (701) 289, 780*, 639, 1009
    Distracted: (704) 445, 531, 611, 1071

    Alice
    Undistracted: (708) 210, 321, 585*, 476
    Distracted: (711) 260, 417, 530, 573

    *There were two pieces of data that did not support the hypothesis. The first was when Julia got distracted when she wasn't supposed to, making her reaction time ridiculously long. The second was Alice's undistracted read/think/react time, which for reasons unknown to us was higher than we would have expected.

    Except for these two glitches, though, the data did support the idea that distraction lengthens people's times.


    distractions and time to think/react
    Name: Lara Kalli
    Date: 2003-11-05 14:51:12
    Link to this Comment: 7128

    Hypothesis: That holding and fidgeting with an object is a distraction that will therefore lengthen reaction and thinking time.

    Test time averages without an object:
    A: 232 ms (sd 39)
    TA: 375 ms (sd 100)
    RTA: 511 ms (sd 87)
    RNTA: 637 ms (sd 119)
    Acting time: 232 ms
    Thinking time: 143 ms
    Reading time: 136 ms
    Negating time: 126 ms

    Test time averages with an object (in this case, my car key, which is of the totally awesome switchblade design):
    A: 284 ms (sd 32)
    TA: 406 ms (sd 93)
    RTA: 577 ms (sd 116)
    RNTA: 828 ms (sd 173)
    Acting time: 284
    Thinking time: 122 ms
    Reading time: 171 ms
    Negating time: 251 ms

    Discussion:
    First of all, it is important to note the following external factors which would most definitely have affected my results: a) I am extremely tired and b) the room in which I conducted this experiment was quite noisy. That having been said, these results seem to be in support of the part of my hypothesis that claimed that fidgeting with an object would lengthen my reaction time. In fact, according to the data it would be safe to say that fidgeting slows down all of my actions. In the second trial, my thinking time actually became shorter (by, it should be noted, the smallest increment of change out of all the results above); however, that could just as easily be attributed to my having familiarized myself with the structure and content of the experiment. Thus: will fidgeting help me think about my homework? We're not really sure, but it's possible. Will it help me finish my homework faster? Conclusively: no.

    Of course, these results are only really applicable to myself.


    Distractions
    Name: Lindsay, A
    Date: 2003-11-05 14:56:46
    Link to this Comment: 7129

    We hypothesized that visual distractions would increase acting, thinking, reading, and think-negating times because the distractions would force the test subject to blink or think about the distractions instead of focusing on the task at hand.

    Lindsay Not Distracted:
    Acting: 252 ms
    Thinking:73
    Reading: 157
    Negating: 82

    Lindsay Distracted:
    Acting: 319
    Thinking: 64
    Reading: 222
    Negating: 48

    Lindsay Difference:
    Acting: 67 ms
    Thinking: -9 ms
    Reading: 65 ms
    Negating: -34 ms

    Adina Not Distracted
    Acting: 268 ms
    Thinking:45 ms
    Reading: 224 ms
    Negating: 246 ms

    Adina Distracted
    Acting: 308 ms
    Thinking: 52 ms
    Reading: 271 ms
    Negating: 51 ms

    Adina Difference:
    Acting: 40 ms
    Thinking: 7 ms
    Reading: 47 ms
    Negating: -195

    Our acting and reading times were both lengthened by the distractiions. However, our negating times were both reduced and our thinking times were about the same. From our observations, it appears that the visual distraction hinders our physical responses like acting and reading, but not our mental processes like thinking and negating. To account for the significant in negating time, we believe that we became accustomed to the distractions and were able to focus and overcome them.


    Are Foreigners Dumb?
    Name:
    Date: 2003-11-05 14:58:28
    Link to this Comment: 7130

    Margaret Tucker and Mariya Simakova

    We postulated that it takes more time for a non-native speaker of English to read the commands in English and to negate the commands in English. Mariya also thought that it will be easier for her to think in Russian while she was negating the commands.

    We performed three sets of trials (10 trials each). Maggie performed the trials as a native English speaker and Mariya as a Russian native speaker. Mariya performed two sets of reading and negation trials. During the first one she tried to just read the instructions and react to them without focusing on the language in which she was processing it. During the second one she read the instructions in English, translated them to herself and told herself to negate them in Russian.

    Observations:

    Maggie

    A 260 milliseconds
    TA 331 milliseconds
    RTA 523 ms
    RNTA 437 ms
    With Average Negation Time of -86ms

    Mariya
    1st set of observations (simply thinking and negating)
    A 232 ms
    TA 324ms
    RTA 538ms
    RNTA 873ms
    With Average Negation Time of 335ms

    2nd set of observations (thinking and negating in Russian)
    RTA 526ms
    RNTA 1412ms
    With Average Negation Time of 886ms

    The first part of our hypothesis is supported by data collected. It took Mariya and Maggie about equal time to respond to non-verbal stimulae, however, it took Mariya significantly longer than Maggie both to read the instructions and to negate them. The second part of our hypothesis (that it will take less time for Mariya to negate the instructions if she thinks in Russian) is not refuted by data. Mariya's Average Negation Time when she was thinking about verbal instructions in Russian was significantly longer (886ms) than her Average Negation Time when she wasn't focusing on the language she was using (335ms). She believes that she was thinking in English during her first trials.



    Name:
    Date: 2003-11-05 14:59:40
    Link to this Comment: 7131

    Ramatu Kallon, Denise Erland, Rochelle Merilien

    Hypothisis: Level of sleep will correlate with all categories(time to act, time to think, time to read, and time to negate).

    *All time is in milliseconds

    Test Subject A (Denise):
    Tme to Act: 200 sd. 23
    Time to Think: 57 sd. 65
    Time to Read: 284 sd. 98
    Time to negate: 38 sd. 323

    Test Subject B (Ramatu):
    Time to Act: 260 sd.74
    Time to Think: 133 sd. 119
    Time to Read: 306 sd. 217
    Time ti Negate: 124 sd.371

    Test Subject C (Rochelle):
    Time to Act: 280 sd. 76
    Time to Think: 413 sd. 105
    Time to Read: 1080 sd. 228
    Time to Negate: 942 sd. 228

    We conclude our hypothesis to be inaccurate. As shown in our observation there are clearly other factors beside sleep level that can affect our response times, there were no data to establish any patterns,including one that would support our hypothesis.


    Brain
    Name: Patricia P
    Date: 2003-11-05 15:02:28
    Link to this Comment: 7132

    Jessica Knapp, Patricia Palermo

    We hypothesised that attempting to hold a generic conversation would raised the times in the trials of cases 2, 3, and 4, but would not have any significant effect on trial 1.

    Jessica, the first subject, recored these marks:

    Control (ID 713)

    AVG SD

    A 306 106
    TA 391 107
    RTA 641 66
    RNTA 796 159

    Distracted (1D 710)

    AVG SD

    A 330 82
    TA 400 71
    RTA 728 43
    RTNA 950 164

    We found that, on average, it took more time when the subject was distracted, but the standard deviation was less for the set of distracted trials.

    Patty's marks:

    Control (ID 717)

    AVG SD
    A 193 13
    TA 311 38
    RTA 481 61
    RNTA 671 341

    Distracted (ID 721)

    AVG SD
    A 285 69
    TA 268 52
    RTA 509 94
    RTNA 992 498

    For Patty, it took more time when distracted, but the standard deviation was also larger for the set of distracted trials.

    We found that relatively, all of the trials were affected by conversational distraction, so our hypothesis was partly false. We may have been originally assuming that if thinking or motor skills were needed from the subject, as long as it did not involve the specific re-actionary tasks as provided by the first trial we were messuring, that it would nothave as great of an effect. However, cases 1-4 were all affected by conversational distration.


    Thinking Time
    Name: Katy and F
    Date: 2003-11-05 15:02:51
    Link to this Comment: 7133

    Flicka Michaels, Katy McMahon

    Hypothesis: Distraction increases the time it takes to act, think, read and negate.

    Results:

    Flicka

    Case 1
    No Distraction Av 248 ms SD 15 ms
    Distraction Av 231 ms SD 19 ms

    Case 2
    No Distraction Av 335 ms SD 105 ms
    Distraction Av 331 ms SD 54 ms

    Case 3
    No Distraction Av 584 ms SD 136 ms
    Distraction Av 582 ms SD 134 ms

    Case 4
    No Distraction Av 515 ms SD 84 ms
    Distraction Av 739 ms SD 188 ms

    With distraction time to act DEcreased 17 ms
    time to think DEcreased 4 ms
    time to read DEcreased 2 ms
    time to negate INcreased 224 ms


    Katy

    Case 1
    No Distraction Av 199 ms SD 15 ms
    Distraction Av 216 ms SD 57

    Case 2
    No Distraction Av 330 ms SD 88 ms
    Distraction Av 323 ms SD 44 ms

    Case 3
    No Distraction Av 474 ms SD 131 ms
    Distraction Av 544 ms SD 151 ms

    Case 5
    No Distraction Av 547 ms SD 134 ms
    Distraction Av 748 ms SD 322 ms

    With distraction time to act INcreased 17 ms
    time to think DEcreased 7 ms
    time to read INcreased 70 ms
    time to negate INcreased 201 ms

    *****

    Based on our results we think that distraction affects people differently. Flicka was able to block out the distractions and even think faster than without distractions. In Case 4 this was reversed. We believe that this is due to the difficulty of the case because we both had trouble with it even without the distractions. While Katy's acting time is faster, it took longer for her to respond with distractions in 3 out of 4 cases.


    Wherin Lies the "Disability"?
    Name: Nomi, Chri
    Date: 2003-11-05 15:03:39
    Link to this Comment: 7134

    The Question: Does having a diagnosed reading disability (slow reading speed / a form of dyslexia) influence the rate at which a person reacts, thinks, and / or reads?

    Hypothesis: As compared to a person with no such disability, a person with a diagnosed reading disability will take longer to perform a task involving reading, but will not take significantly longer or shorter to perform tasks involving only reacting and thinking.

    Data Collected:

    Person #1 has no diagnosed reading disability (Control).
    Person #2 HAS a diagnosed reading disability (Experimental).

    Controls: both subjects wear glasses (corrected vision).
    Each avg. number was compiled from 10 pieces of data.

    Person #1: Task -- Act
    Average Time -- 264 milliseconds
    Standard Deviation -- 62 milliseconds

    Task -- Think, Act
    Average Time -- 348 millisec.
    Standard Deviation -- 83 millisec.

    Task -- Read, Think, Act
    Average Time -- 571 millisec.
    Standard Deviation -- 114 millisec.
    -----------------------------------------------------------------------
    Person #2: Task -- Act
    Avg. Time -- 259 millisec
    Stand. Dev. -- 111 millisec.

    Task -- Think, Act
    Avg. Time -- 426 millisec.
    Stand. Dev. -- 92 millisec.
    NOTE: Errors - 2 x click-too-soon, 1 x click incorrectly

    Task -- Read, Think, Act
    Avg. Time -- 678 millisec.
    Stand. Dev. -- 434 millisec.
    NOTE: Errors - 1 x click-too-soon, 1 x click incorrectly

    Our Findings:
    Our findings support our hypothesis. While average reaction times (Act) are very similar for persons #1 and #2 -- 264 vs. 259, not significantly different -- average Read, Think and Act times are significantly different for the two, with Person #2 being significantly slower at 678 millisec. as opposed to 571 millisec, a difference of approximately 15% (which counts for something!). It seems that having a reading disability does, indeed, increase reading time!

    But this is not for certain, because it might just be increasing thinking time. The two averages obtained for the Think, Act experiment were also significantly different: 434 for #2, vs. 348 for #1, about a 20% difference! According to this data, it would appear that having a reading disability increases THINKING time, but not reading time. This suggests that our hypothesis does not "work" in this case, and that a "Reading disability" might actually suggest a disability -- or slowing down -- in THINKING rate.


    Wherin Lies the "Disability"?
    Name: Nomi, Chri
    Date: 2003-11-05 15:03:40
    Link to this Comment: 7135

    The Question: Does having a diagnosed reading disability (slow reading speed / a form of dyslexia) influence the rate at which a person reacts, thinks, and / or reads?

    Hypothesis: As compared to a person with no such disability, a person with a diagnosed reading disability will take longer to perform a task involving reading, but will not take significantly longer or shorter to perform tasks involving only reacting and thinking.

    Data Collected:

    Person #1 has no diagnosed reading disability (Control).
    Person #2 HAS a diagnosed reading disability (Experimental).

    Controls: both subjects wear glasses (corrected vision).
    Each avg. number was compiled from 10 pieces of data.

    Person #1: Task -- Act
    Average Time -- 264 milliseconds
    Standard Deviation -- 62 milliseconds

    Task -- Think, Act
    Average Time -- 348 millisec.
    Standard Deviation -- 83 millisec.

    Task -- Read, Think, Act
    Average Time -- 571 millisec.
    Standard Deviation -- 114 millisec.
    -----------------------------------------------------------------------
    Person #2: Task -- Act
    Avg. Time -- 259 millisec
    Stand. Dev. -- 111 millisec.

    Task -- Think, Act
    Avg. Time -- 426 millisec.
    Stand. Dev. -- 92 millisec.
    NOTE: Errors - 2 x click-too-soon, 1 x click incorrectly

    Task -- Read, Think, Act
    Avg. Time -- 678 millisec.
    Stand. Dev. -- 434 millisec.
    NOTE: Errors - 1 x click-too-soon, 1 x click incorrectly

    Our Findings:
    Our findings support our hypothesis. While average reaction times (Act) are very similar for persons #1 and #2 -- 264 vs. 259, not significantly different -- average Read, Think and Act times are significantly different for the two, with Person #2 being significantly slower at 678 millisec. as opposed to 571 millisec, a difference of approximately 15% (which counts for something!). It seems that having a reading disability does, indeed, increase reading time!

    But this is not for certain, because it might just be increasing thinking time. The two averages obtained for the Think, Act experiment were also significantly different: 434 for #2, vs. 348 for #1, about a 20% difference! According to this data, it would appear that having a reading disability increases THINKING time, but not reading time. This suggests that our hypothesis does not "work" in this case, and that a "Reading disability" might actually suggest a disability -- or slowing down -- in THINKING rate.


    Correction!
    Name: Nomi, Chri
    Date: 2003-11-05 15:11:32
    Link to this Comment: 7136

    We made a mistake in our data analysis! We used incorrect numbers in the Read-Think-Act analysis. We should have used 571 for person #1 and 678 for person #2. The percentages would be different then, but the trend is the same -- higher for person #2, who had the disability.


    Mendel's Garden
    Name: Paul Grobstein
    Date: 2003-11-11 12:38:39
    Link to this Comment: 7197

    One central piece of modern biology derived from Darwin's voyage to the Galapagos in the latter part of the 19th century. A second emerged, more or less independently, during the same period and resulted from the work of Gregor Mendel breeding pea plants and carefully observing the results. This work produced the first clear understanding of "laws of inheritance", and remains fundamental to most modern understanding of genetics.

    In this lab you will be invited to participate yourself in making the kinds of observations and inferences that Mendel made. We will do so together studying not pea plants but fruit flies, and using not live animals (for which the studies would take weeks or months) but a computer simulation which is quite realistic in most important characteristics. The simulation, called FlyLab, is available to registered individuals (students in this class) at http://biologylab.awlonline.com.

    After we've worked through some of the basic observations together, you should work in pairs to make observations yourself on some fly traits other than those we have explored together. Your task is to "make sense" of your observations starting with the basic ideas we develop together and adding whatever additional ideas seem necessary. Try and find some traits that yield unexpected results in a monhybrid cross, as well as some that yield unexected results in a dihybrid cross.


    Fly Lab
    Name: Nancy Evan
    Date: 2003-11-11 15:06:42
    Link to this Comment: 7200

    For my first cross, I used a female with white eyes and a male with wild type (red) eyes.

    First Generation:
    50% white eyes
    50% red eyes
    *two flies appeared on the screen

    Second Generation: (used two flies from first generation)
    50% white eyes
    50% red eyes
    *four flies appeared on the screen

    Third Generation: (used top two flies from second generation, both had red eyes)
    75% red eyes
    25% white eyes
    *the white eyes only appeared in the males in this generation.

    For my second cross, I used a female with spread wings (D) and a black body and a wild type male.

    First Generation:
    50% closed wings
    50% open wings

    Second generation:
    75% wild type bodies
    25% black bodies

    Third Generation:
    75 % wild type bodies
    25% black bodies

    HYPOTHESIS: Some traits do not follow the general ratio of 9:9:3:1. Some traits may not be able to be expressed at the same time (such as open wings and black bodies). Also, some traits may be muted in a sex (as in the case with females and white eyes).

    Because I wrote my hypothesis after I performed the experiment, my hypothesis seems to follow the data. However, I don't know why this is true. Why could first and second generation females have white eyes but not third?


    Fly Lab
    Name: Sarah Kim
    Date: 2003-11-11 15:12:49
    Link to this Comment: 7202

    We discovered through several trials that not all of the traits were true-breeding. At first, we assumed that all traits were true-breeding, but we observed that half of the offspring of a curly-winged fly and a straight-winged fly were curly-winged and the other half were straight-winged. We realized that this outcome would not have been possible unless one of the traits (curly or straight wingedness) was heterozygous. We determined that the curly-winged trait was the heterozygous one because of previous tests with only straight-winged subjects. We tested breeding two curly-winged flies, and the results were 75% curly-winged and 25% straight-winged in the first generation. This leads us to believe that the curly-winged flies have one curly-winged gene and one straight-winged gene. The same was true of the aristapedia antennae trait.


    Katie Ottati, Michelle Choi
    Name: Katie, Mic
    Date: 2003-11-11 15:14:03
    Link to this Comment: 7203

    We looked at dichaete wing angle and eyeless "eye shape" traits in the fruit flies.

    Dicheate:
    - exhibits true breeding
    - is not more dominant than "wild type" wing angle. Starting from the first generation of offspring, there was a 1:1 ratio of each wing angle.
    - is not gendered. Both males and females exhibit the trait at the same frequency

    Eyeless:
    - exhibits true breeding
    - is recessive in relation to the "wild type" eye shape. In the first generation of offspring there were no phenotypically eyeless flies, in the second there was a 2:1 ratio of eyes to eyeless. In subsequent generations, whether or not there were eyeless flies depended on whether or not we selected a phenotypically eyeless parent.
    - is not gendered.

    Dicheate wing angle and eyelessness do not seem to have any impact on one another. When we bread an dicheate mother with wild type eyes and an eyeless father with wild type wings (and vice versa), each trait appeared with the frequency that would be expected based on the earlier experiments.


    Bessy Guevara, Vanessa Herrera, Shafiqah Berry
    Name:
    Date: 2003-11-11 15:18:27
    Link to this Comment: 7204

    Hypothesis: After making the female with white eyes and the male wild typed, we hypothesized the the female would be recessive and the male dominant.

    First Generation: Female (white eyes) Male (wild)

    Second Generation: Female (wild) Male (white eyes)

    Given that the white eyes appeared in the first process of mating, white eyes are clearly not a recessive trait in the male of the second generation, but is in the female of the first generation. We concluded that the white eyed trait is sex-linked since it turns up to be neither a dominant or recessive trait.

    Third Generation: 1 Female (wild) 1 Male (wild)
    2 Female (white) 2 Male (white)

    Throughout the three generations the ration of wild to white is 1:1. In the last observation, only one of the males turned up with white eye. Yet we had to take in account that the female that turned up white in the Second generation still carried the white eyed trait from the first generation. We assumed the same for the males.


    Brianna Twofoot, Emily Breslin
    Name:
    Date: 2003-11-11 15:19:05
    Link to this Comment: 7205

    We cross-bred a female fly with purple eyes and a male fly with minature wings. Here were the offspring they produced:

    + (wild type): 552
    PR (like the mother): 204
    M (like the father): 192
    PR, M (combination of the mother and father traits): 64

    These results yielded an approximate ratio of: 9:3:3:1
    These were the expected results based on two parents with traits that we determined to be true breeding.

    We discovered that the wing trait of Dicheate, where the wings are spread apart, was not true breeding. Any combination of breeding, over numerous generations, yielded a mysterious disappearance of the trait. This confused and baffled us. We determined that perhaps there is something inherent in the definition of "not true breeding" that allows traits to completely disappear or appear completely randomly.

    Does a not true breeding trait mean that it is a mutation of a gene and cannot be inherited in the same statistical way that 'normal' genes are?


    Fly Lab
    Name:
    Date: 2003-11-11 15:20:02
    Link to this Comment: 7206

    Manuela y LaToiya

    We started with a female with "lobe" eyes, and a male with apterous wing size.(both flies were otherwise wildtype).
    We bred them and got :

    1002 flies -all lobe eyed w/ wildtype wings
    we assumed that lobe eyes might be dominant, and that the female parent was homozygous(LL). To prove this, we checked to see if the lobe eyed trait was a true breed. and it was! :)
    The male's apterous wings were also proven to be true breed.

    Next we crossed the offspring of our lobe eyed female and apterous male. (lobe eyed wildtype) w/ the following results out of a total of 998 flies:
    34 wildtype(ratio:1)
    723 lobe eyed wildtype wings(ratio:21.265)
    206 apterous wildtype eyes(ratio:6.059)
    35 lobe eyed apterous(ratio:1.029)

    For a second experiment we crossed a female with apterous wings and a male with lobe eyes.
    For this experiment we got very similar results, which we could infer from that there are no sex linked traits.
    Lobe eyes must have been dominant over wildtype eyes. And the apterous is a recessive gene. Both are homozygous.

    We DO NOT have an explanation for why we hae such peculiar ratios.


    Su-Lyn
    Name: su-lyn
    Date: 2003-11-11 15:20:29
    Link to this Comment: 7207

    I hypothesized that the wild type, being the most common phenotype, was the result of a dominant gene. I began by crossbreeding a female wild type (+) and male with curly wing shape (CY). Based on my hypothesis, I predicted that CY would be a recessive gene and that the crossbreeding would produce offspring (F1) that all had the + phenotype, and that their offspring (F2) would have the 3:1 ratio of + to CY.

    RESULTS 1:
    Parents + and CY --> F1 50+ and 65CY i.e. 1 : 1.3 ratio
    This fairly equal distribution suggests that + is not dominant over the CY. In fact, a greater proportion of offspring are CY phenotypes, but dominance is not total.

    RETEST:
    I crossbred a new pair of flies, CY and CY. Based on the assumption that they were homozygous, I predicted that they would produce offspring that were all CY in phenotype.

    RESULTS 2:
    Parents CY and CY --> F1 32+ and 79CY i.e. 1 : 2.47 ratio
    Subsequent crossbreeds of two CY offspring produced the following +:CY ratios
    1 : 1.81
    1 : 1.842
    1 : 1.941
    1 : 1.872

    CONCLUSION:
    This implies that CY is not a homozygous phenotype. It is possible that one of the two variants that make up CY is recessive to +, and the other variant is dominant over +. This would help explain the first set of results in the crossbreed between + and CY.


    Fly Lab
    Name: Team Bitte
    Date: 2003-11-11 15:26:43
    Link to this Comment: 7208

    Team members: Paula "Calm" Arboleda, Romina "Cranky" Gomez

    First Generation
    Tan Female and Wild Male
    Offspring
    519Tan male
    504 Wild Female

    Second Generation
    WIld Female and Tan male
    262 Tan male
    271 Tan Female
    257 Wild Male
    266 Wild Female

    Third Generation
    Wild Female and Wild Male
    514 Wild Female
    243 Wild Male
    249 Tan Male

    Fourth Generation
    Wild Female and Wild Male
    508 Wild Female
    521 Wild Male

    Observation
    When there is a tan female the tan gene appears in the male in the first offspring. We then crossed a wild female and a tan male and you had a 50% chance of getting a tan offspring in both the male and females. We then crossed a wild female and a wild male and we got the tan gene appeared only in the males but most of the offspring were wild type. When we crossed another wild female and another wild male, the tan gene disappears and you only get wild offspring. In other words, the tan gene disappears in the fourth generation. It is interesting to note that in the 3rd generation there were no tan females.


    fly lab
    Name: Charlotte
    Date: 2003-11-11 15:30:00
    Link to this Comment: 7209

    Charlotte Haimes, Elisabeth Py

    hypothesis:
    It seems that the variations present in the parent or parents increase the chances for the traits to take on the dominant gene in the offsprings.

    Observations:

    Experiment 1:
    Female (tan body) + Male (wild)
    -> Female (228 wild) + Male (228 wild)
    -> Female (255 tan) + Male (264 tan)
    -> Female (473 tan) + Male (512 tan)
    -> Female (477 tan) + Male (508 tan)
    Tan body: dominant trait

    Experiment 2:
    Female (curly wings) + Male (purple eyes)
    -> Female (257 W) + Male (218 W)
    -> Female (271 C) + Male (240 C)
    -> Female (175W) + Male (160 W)
    -> Female (76 P) + Male (92 P)
    -> Female (239 C) + Male (200 C)
    -> Female (25 PC) + Male (32 PC)
    -> Female (158 P) + Male (176 P)
    -> Female (327 PC) + Male (328 PC)

    Conclusion: Our hypothesis was proved right since in each experiment the offspring took on the variant traits. In the first experiment, the offspring showed to have tan bodies just like the female parent at the beginning of the chain. In the second experiment, the traits surface in further generations simultaneously in both sexes. Therefore, not only are the variant traits passed on to future generations, but also become more apparent as the chain progresses.


    sex-linked traits discovered?!
    Name: stefanie a
    Date: 2003-11-12 14:53:44
    Link to this Comment: 7227

    For our experimet, we decided to use bristle type as the observable characteristic. We crossed a wildtype female with a shaven male. In the F1 generation, both offspring had a wildtype phenotype. In the F2 generation, after crossing the offspring of the F1 generation, we found that the one to three ratio that had been visible in earlier experiments was present in this as well. There was roughly 1 shaven bristle type for every 3 wildtype bristle types.

    For our next experiment, we mated a yellow-bodied female with a wildtype-bodied male. In the F1 generation half of the offspring were yellow and half wild-type, unlike the other experiments we performed, where all offspring were wild-type.

    To ensure that it was not another type of variable we tested a yellow-bodied female with a yellow-bodied male, and offspring in three generations to follow were all yellow-bodied, this led us to conclude that yellow-bodiedness is in fact a pure-breeding trait.

    Upon further review of our results, we realized that only the males were yellow-bodied, which would mean that the yellow body color gene is sex-linked.


    fly incest
    Name: Julia and
    Date: 2003-11-12 14:57:29
    Link to this Comment: 7228

    Our hypothesis is that if you breed two flies with different eye colors in a monohybrid cross, eventually you will see that one trait shows up more often than the other.
    We first crossed a red-eyed male (wild type) with a red-eyed female (wild type.) We found that no matter how many filial generations you made, you kept gettng wild type flies. We repeated the experiment with purple-eyed flies, and found that all their kids and grandkids, etc, had purple eyes. Because these flies were true breeders, we know they are homozygous, having either pp (for purple eyes) or ++ (for wild type.)
    Next, we bred a wild type fly with a purple-eyed fly. We expected that one of these traits would override the other in some cases, leading to generations with more of one eye color or the other. In the F1 generation, all the offspring had red eyes. In the F2 generation, though, about a quarter of the offspring had purple eyes.
    F1:
    p p
    + p+ (red) p+ (red)
    + p+ (red) p+ (red)

    F2:
    p +
    p pp(purple) p+ (red)
    + p+ (red) p+ (red)


    This supports the idea that the combination of two genes from two parents leads to four possibilities in each generation. In the F1 generation, because every offspring got one purple gene from the mother and one wild type gene from the father, they all had the same combination of one p and one +. In the next generation, though, offspring could inherit a p or a + gene from either parent. So one possibility was pp, one was ++, and the other two were +p. The phenotype of the +p genotype in the F2 generation would reveal which of these genes overrides the other. We found that 3/4 of the F2 generation had the wildtype phenotype, so we concluded that + was the gene that overrode p.


    Lindsay and Alice
    Name:
    Date: 2003-11-12 15:01:00
    Link to this Comment: 7229

    We crossed a female with purple, regular shaped eyes with a male with purple, star-shaped eyes. We found their first generation of offspring to have half purple, regular shaped and half purple, star shaped. We then crossed the following F1 flies:

    Purple, regular shaped + Purple, star shaped
    Yielded half Purple, regular shaped and half purple, star shaped again.

    Purple, regular shaped + purple, regular shaped
    Yielded all purple, regular shaped

    Purple, star shaped + purple, star shaped
    Yielded 1/3 purple regular shaped and 2/3 purple star shaped.

    When we isolated the eye shape gene and disregarded the eye color gene, the resuts of the cross
    Star shaped + star shaped
    still yielded this 2:1 ratio. So the fact that our results were the same when the two traits were isolated says that eye color and eye shape are not related in their inheritance. However, we do not know how to account for this 2:1 ratio when crossing eye shapes. We found this ratio odd because when we crossed flies with different eye colors, we came up with a 3:1 ratio in phenotype in the first generation, and either a 1:1 or 1:0 ratio in the second generation. We think that in order for this 2:1 ratio to occur there must be some other factor contributing to the flies' inheritance of eye shape.


    fly-love
    Name: lara kalli
    Date: 2003-11-12 15:01:14
    Link to this Comment: 7230

    1st cross: curly-winged female (CY) and wild-type male (+)
    F(1): 50% CY, 50% +
    - I was pretty surprised by these results, so for the next two generations I crossed a CY with a + from the previous generation:
    F(2): 50% CY, 50% +
    F(3): 50% CY, 50% +

    Given that these results were a bit different from the all same/3:1 ratios that we saw in the earlier examples, I decided to test whether or not curly-wingedness was a true-breeding characteristic:

    2nd cross: CY male and female
    F(1): 50% CY, 50% +
    F(2): 50% CY, 50% +
    F(3): 50% CY, 50% +

    Hypothesis: In a monohybrid cross, a trait that is characteristic of one of the parents that does NOT appear in F(1) is a true-breeding characteristic; conversely, a trait characteristic of one of the parents that DOES appear in F(1) is not a true-breeding characteristic.


    Fly Lab
    Name:
    Date: 2003-11-12 15:10:01
    Link to this Comment: 7231

    Flicka Michaels

    First I bred a tan female fly with a wildtype male fly.

    F1- 1 female wildtype, 1 male tan
    F2- 2 wildtypes, 2 tan (1 male and female of each)
    bred male and female tan
    F3- 2 tan (1 female tan, 1 male tan)

    Next, I bred a female wildtype with a shaven male.

    F1- 2 wildtypes
    F2- 2 wild types, 2 shaven
    bred 2 shaven
    F3- 2 shaven

    So, I can conclude from my results that tan coloring and shaven are true breeding traits since when I bred 2 tan flies or 2 shaven flies together the offspring continually showed these traits and no others.


    Flies
    Name:
    Date: 2003-11-12 15:12:05
    Link to this Comment: 7232

    Jessica Knapp and Diana Medina

    Hypothesis: There is equal chance for the offspring to have either father or mother traits.

    Parents:
    Mother: Wild type (+) Father: Curly Wings (cy)

    Offspring:
    females + 271, Male + 247
    females (cy) 271, Males (cy) 243

    Second generation incest:
    Mother (cy) father (+)

    offspring:
    females: (+) 253 Males (+) 241
    females:(cy) 238 Males (cy) 268

    Conclusion:
    Our hypothesis seems to have proven correct as we came to see that in only changing one trait in the original parents, offspring were equally likely to have curly wings or wild type bodies.
    As for the second generation we saw that characteristics equally carried through to the third generation.
    There were variations but they were probably insignificant.


    FlyLab with Respect the the Characterisitcs of Sha
    Name: J'London a
    Date: 2003-11-12 15:12:46
    Link to this Comment: 7233

    We exerimented with the trair of hairtype within the fly community. We asser that The Wild Type hair trait are dominant when combined with the other types. However, when other hairtypes besidesWild Type are mated with the Shaven they tend to be dominant. The only offspring that showed shaven traits in physical form were when it was mated with another shaven type.

    We very much enjoyed taking on the brain and logic of Mendel. We mated every "weird" thing with the wild type and they only produced about five offspring. Why were there no babies?



    Name:
    Date: 2003-11-12 15:12:53
    Link to this Comment: 7234

    Maggie Tucker and Adina Halpern

    We hypothesized that either dichaete-winged or wildtype would be a dominate gene, and whichever was not dominate would be recessive.

    We bred a dichaete-winged fly with a wildtype fly. These flies produced an f1 generation of 50% dichaete-winged and 50% wildtype. This continued for all subsequent breedings involving one dichaete and one wildtype.

    We did two types of breeding variation once this constant was found. For our first variation, we bred two dichaetes. We ended up with a ratio of 1 wildtype: 2 dichaete. This pattern remained constant when we continued to breed two dichaete from each subsequent generation.

    For the second variation, we bred two wildtypes after the initial hybrid breeding. Our f2 generation consisted of all wildtyped. As two wildtypes were continuing to be bred, the dichaetes did not reappear.

    Our results were not true to our hypothesis. Neither gene stood out as either recessive or dominate but we do not know why these results occurred.


    Fly Eye Color Trends
    Name: Patricia P
    Date: 2003-11-12 15:15:55
    Link to this Comment: 7235

    We exained a purple-eye female / wild-eye male cross and analyzed their offspring following three breeding rules;

    Key: W = wild eyed; P = Purple eyed

    Rule #1: Breed W with P whenever possible (whenever both w and p exist among offspring).

    Rule #2: Breed W whenever possible.

    Rule #3: Breed P whenever possible.

    Test #1: Applying Rule #1
    P 1:1
    F1 2:0
    F2 1:1
    F3 2:0
    F4 1:1
    F5 1:1
    and follows with breeding as 1:1

    Test #2: Applying Rule #2

    P 1:1
    F1 2:0
    F2 1:1
    F3 1:1
    F4 2:0
    F5 2:0
    and follows with breeding as 2:0

    Test #3: Applying Rule #3

    P 1:1
    F1 2:0
    F2 1:1
    F3 0:2
    F4 0:2
    F5 0:2
    and follows with breeding as 0:2

    The interesting occurance was that consistancy with seeing just wild type in test two (which was what we were looking for) arrived by trial F4. But the consistancy of seeing just purple in test 3 (which was what we were after in that test) arrived earlier, in the F3 breeding. This lead us to infer that the red contains something thats holds on to a "hiddenpurple " longer. While the purple does not hang on to a red trait for any length of time.



    Name: Maria S-W
    Date: 2003-11-12 15:16:18
    Link to this Comment: 7236

    We found the process of attempting to breed fruit flies virtually more frustrating and irritating than it could be in reality. We attempted two monohybrid crosses, once with antennae and once with body color and both times the result was not the phenotypical ratios that mendel's model has. During our first attempt, in which we bred a wild type male with a AR antennae female, the offspring was half and half. So we tried a different trait: Body color. The first generation did have the same apperance, but subsequent generations always resulted in a 50-50 split between the Wild type body color and the black body color. We are not sure why this happened. We think it might be bad luck. Or perhaps the computer software. We also considered that perhaps the specific traits that we chose resulted in our unusual results.


    fly-love: a revision
    Name:
    Date: 2003-11-12 15:47:16
    Link to this Comment: 7237

    I would like to retract some of the data I posted earlier. It is still the case that curly-wingedness is not a true-breeding trait; however, when a CY male and female are crossbred the ratios in F(1) and following generations of CY to + was NOT in fact 50%:50% or 1:1 - it was in fact closer to 2:1. The error was solely due to carelessness on my part; I apologize for any confusion and hope that this statement clears things up.



    Name:
    Date: 2003-11-12 15:47:51
    Link to this Comment: 7238

    above remarks by Lara Kallich (lkallich@brynmawr.edu)


    Watching Cellular Life in Process
    Name: Paul Grobstein
    Date: 2003-11-18 12:34:18
    Link to this Comment: 7308

    Life depends on breaking things down, and can be observed from its break down products:

    C6H12O6 + 6 O2 -> 6 CO2 + 6 H2O + 32-34 ATP

    This description, however, summarizes a more complex reality, involving many individual chemical reactions and different enzymes in particular spatial arrays. In this lab we will explore the implications of both the overall breakdown process involved in life and its complexity. To do this, we will look at CO2 production by yeast cells under a variety of conditions.

    You will work in pairs to set up a series of experimental conditions. While these are evolving measurable CO2, you should write a set of predictions about which tubes should generate the most carbon dioxide and why. We will then look at the collected data and see to what extent it satisfies the various predictions.


    Predictions
    Name: Sarah, Nat
    Date: 2003-11-18 14:14:19
    Link to this Comment: 7312

    Our predictions, in order of most carbon dioxide to least carbon dioxide, are: 2, 3, 4, 1, 6, 7, 8

    We predict this because we think that glucose will break down faster than sucrose because sucrose is made up of glucose and fructose, therefore, 2 will produce more carbon dioxide than 1. Also, pyruvate breaks down into ethanol and carbon dioxide, therefore 4 will have more carbon dioxide than 1. Will said that fluoride was an inhibitor, so the more fluoride, the less carbon dioxide, so 6 will have more than 7. Without oxygen, the citric acid cycle cannot take place, therefore, the anaerobic yeast will produce the least carbon dioxide.


    Predictions
    Name: Brittany,
    Date: 2003-11-18 14:26:58
    Link to this Comment: 7313

    Our prediction for the order of carbon dioxide evolution (fastest first):

    4. Active Yeast with Pyruvate (closer to end product)
    2. Active Yeast with Glucose
    3. Active Yeast with Sucrose (more complex)
    6. Active Yeast with 0.01 NaF (inhibitor)
    7. Active Yeast with 0.1 NaF (more inhibitor)
    5. Lysed Yeast (uh, Will...?)
    8. Anaerobic Yeast (produces smaller amount than aerobic)
    1. Active Yeast with Water (nothing to break down)

    Su-Lyn & Brittany


    Predictions
    Name: brianna tw
    Date: 2003-11-18 14:29:18
    Link to this Comment: 7314

    Ranked from producing the most yeast to the least:

    Test Tube #: 4, 7, 6, 2, 5, 3, 1.


    We thought that an element is produced closer to the end of the process would yield more carbon dioxide when introduced to the yeast.


    Abby and Melissa
    Name: Abby Fritz
    Date: 2003-11-18 14:35:14
    Link to this Comment: 7315

    Order of CO2 production from fastest to slowest:
    4.)Active Yeast, h20, Pyruvate (closest to Citric Acid Cycle)
    2.) Active Yeast, Glucose, H2O
    6.)Active Yeast, Glucose, 0.01 NaF
    7.) Active Yeast, Glucose, 0.1 NaF
    5.) Lysed Yeast, Glucose, H20
    3.)Active Yeast, Sucrosem H2O
    1.) Active Yeast, 10mL H20



    Name:
    Date: 2003-11-18 14:49:05
    Link to this Comment: 7316

    Vanesssa Herrera, Justine Patrick

    (All in accordance to the Spacial Arrangements and Metabolism)

    We made these predictions based on a scale from 1-10
    Tube 1 ( 9)

    Tube 2 (6)

    Tube 3 (4)

    Tube 4 (8)

    Tube 5 (7)

    Tube 6 (9)

    Tube 7 (10)


    Results
    Name: Sarah, Nat
    Date: 2003-11-18 15:03:19
    Link to this Comment: 7317

    In order of the most net carbon dioxide to the least carbon dioxide: 3, 2, 6, 8, 7, 1/4

    Net gas volume:
    Test Tube 1: 0 cc/hr
    Test Tube 2: 3 cc/hr
    Test Tube 3: 4 cc/hr
    Test Tube 4: 0 cc/hr
    Test Tube 6:2.75 cc/hr
    Test Tube 7: 0.5 cc/hr
    Test Tube 8: 1.25 cc/hr

    In looking at the results, we noticed that there was no sugar in either 1 or 4, therefore, no change in carbon dioxide is to be expected. 7 had the most fluoride, which is an inhibitor, so that makes sense. Since the concentration of fluoride in 6 isn't very large, the lack of oxygen in 8 served as more of an inhibitor. Since sucrose is made of glucose and fructose, and fructose will break down into glucose, the sucrose may be providing more volume of glucose, leading to 3 producing more carbon dioxide than 2. So our predictions were mainly incorrect, but we were correct that 2 and 3 would produce the most carbon dioxide.


    co2 production
    Name: denise,meg
    Date: 2003-11-19 14:24:07
    Link to this Comment: 7327

    Denise, Megan and Maria

    We hypothesis the following order of gas reading, from most gas to least gas: (1=most, 7=least)

    1. Active Yeast/Glucose/H2O (2)
    2. Active Yeast/Sucrose/ H20 (3)
    3. Lysed Yeast/Glucose/H2O (5)
    4. Active Yeast/H2O (1)
    5. Active Yeast/Pryruvate/H20 (4)
    6. Active Yeast/Glucose/0.01 M NaF (6)
    7. Active Yeast/Glucose/0.1 M NaF (7)

    We made the following predictions based on our previous knowledge that flouride is an inhibitor of gas production. We also know that glucose promotes the production of gas. We also think that the active yeast will produce more gas b/c it is "active" versus the lysed yeast.



    Name:
    Date: 2003-11-19 14:25:36
    Link to this Comment: 7328

    Anna Marciniak
    Melissa Teicher

    Our predictions:
    1 is most carbon dioxide and 8 is least carbon dioxide:

    1. tube 3
    2. tube 2
    3. tube 5
    4. tube 7
    5. tube 6
    6. tube 8
    7. tube 4
    8. tube 1

    We chose this order based on how long we thought the breakdown process would take place. If it took longer to break down, then we thought it would produce more carbon dioxide, but if it broke down quickly, then we thought it would produce less carbon dioxide.


    yeast waste
    Name:
    Date: 2003-11-19 14:31:00
    Link to this Comment: 7329

    Lara Kallich, Katy McMahon

    CO2 yield predictions for yeast metabolic activity (least to most)

    - 1. Active yeast + water
    - 8. Anaerobic yeast + glucose + water
    - 7. Active yeast + glucose + 0.1 NaF
    - 6. Active yeast + glucose + 0.01 NaF
    - 5. Lysed yeast + glucose + water
    - 3. Active yeast + sucrose + water
    - 2. Active yeast + glucose + water
    - 4. Active yeast + pyruvate + water



    Name:
    Date: 2003-11-19 14:38:00
    Link to this Comment: 7330

    Maggie Tucker and Adina Halpern

    1. Lysed Yeast/Glucose/H2O
    2. Active Yeast/Sucrose/H2O
    3. Active Yeast/Glucose/H2O
    4. Active Yeast/Pyruvate/H2O
    5. Anaerobic Yeast/Glucose/H2O
    6. Active Yeast/Glucose/0.01M NaF
    7. Active Yeast/Glucose/0.1M NaF
    8. Active Yeast/H2O

    We think that Lysed Yeast will produce the most gas in 45 minutes because the cell membrane is already broken down. We thought the next three would happen in that order because of the sequence of sucrose, glucose, and pyruvate in the breaking down process. If the reaction starts later in the process, less enzymes will be active. Starting from the back, we thought that active yeast and H2O would be last because there would be no enzymes active in the reaction. We thought that the mixtures wih NaF would be next to last because they seem to act as a block in the order of the reaction. Anaerobic Yeast is fifth because the reaction is stopping at the pyrubic acid phase.


    Predictions for CO2
    Name:
    Date: 2003-11-19 14:40:22
    Link to this Comment: 7331

    Alice Goldsberry
    Diana Medina
    Flicka Michaels

    Here are our predictions for the most CO2 to the least CO2.

    Test Tube 1: 7
    Test Tube 2: 2
    Test Tube 3: 6
    Test Tube 4: 1
    Test Tube 5: 5
    Test Tube 6: 4
    Test Tube 7: 3


    my hand smells
    Name: stefanie a
    Date: 2003-11-19 14:44:12
    Link to this Comment: 7332

    After preparing the solutions in the eight test tubes we took the initial gas readings. They were as follows:

    1: 1.75
    2: 3.5
    3: 2
    4: 2
    5: 2.5
    6: 2
    7: 2
    8: .75

    We predict that the tube which would have the greatest net change would be in tube number 4. The tubes that follow, from greatest net evaporation to least, would be:
    3
    2
    1
    5
    8
    6
    7


    Test Tube CO2
    Name: Nomi and J
    Date: 2003-11-19 14:48:57
    Link to this Comment: 7333

    Which test tubes (of the same volumes of yeast) will produce the most CO2? Which will produce the least?

    Hypothesis: Amounts of CO2 will occur, from most to least, in this order:

    #1) Pyruvate. Pyruvate is one of the products of glucose; it occurs later in the cycle. Because glucose breaks down into other substances in addition to pyruvate, 5 ml glucose would yield less than 5 ml pyruvate. So, using 5 ml pyruvate, which is implicated in later CO2 production, should produce more CO2 than any of the tests that use 5 ml of any kind of sugar (and hence less pyruvate) instead.

    #2) Active Yeast and Glucose. Active yeast should be stronger than, and produce more CO2 than, lysed yeast (which is really dead already and so weaker) and anaerobic yeast (which doesn't perform the citric acid cycle and so can't produce CO2). Glucose, as a pure, simple reactant that is used in full and doesn't need converting from a more complex sugar or carb, should allow a lot of CO2 to be produced.

    #3) Active Yeast and Sucrose. Should produce almost as much CO2 as #2 above, but not quite, because sucrose (a double sugar) must be broken down to form glucose (a simple, single sugar). This process of breaking down takes time and energy, so at any given point in time, this reaction will be less far along in its CO2 production than the reaction above, which uses pure glucose.

    #4) Lysed Yeast and Glucose. Lysed yeast, since it is dead, won't be as potent. However, some of the enzymes should still be working, and some CO2 should still be produced.

    #5) Active Yeast, Glucose, .01M NaF. NaF should inhibit the action of the enzyme which converts the glucose into other forms, thereby limiting CO2 production.

    #6) Active Yeast, Glucose, .1M NaF. A higher concentration of NaF will have the same effect on CO2 production as in #5 above, but to a greater extent, because there is more of it to inhibit the enzyme action.

    #7) Active Yeast, Water, No Glucose. Without glucose as the substrate/reactant, a lot less CO2 should be produced. However, Julia has observed that plain yeast mixed with water does produce bubbles of CO2, so we decided not to place this one last on the CO2 hierarchy.

    #8) Anaerobic Yeast, Glucose. Anaerobic yeast cannot, without using oxygen, go through the Krebs / Citric Acid cycle, so it cannot produce CO2. According to this estimate, the anaerobic yeast should do whatever it can do without oxygen without producing ANY CO2. Maybe it will produce something else....



    Name:
    Date: 2003-11-19 15:01:37
    Link to this Comment: 7335

    Ramatu Kallon and Rochelle Merilien

    From our observations we hypothesize that the lysed yeast will produce the most amount of gas, because it expands when it comes in contact with water.

    Ranking of tubes that will produce the most gas (from greatest to least):
    4
    5
    2
    3
    7
    6
    8
    1
    We really do not have an explanation to why we have picked this order.


    Who's In Charge?
    Name: Paul Grobstein
    Date: 2003-12-02 12:21:31
    Link to this Comment: 7425

    In this lab we want to develop some intuitions about a perhaps counter-intuitive idea relevant to thinking both about cells in multicellular organisms and about multicellular organisms interacting in populations: the idea that order can emerge in the absence of an identifiable director or conductor. To do this, we will first play a game together, and then look at some computer implementations of simple sets of rules relevant to biological systems that produce order in the absence of a director or conductor.
    Such models are a recent addition to the observational repertoire of biologists (and other scientists), and increasingly important in developing new understandings of biological (and other) systems. You and your partner should choose on of these models to explore on your own, with the objective of discovering what are the requirements for order of this kind to emerge.


    The models we will use come from Northwestern University's Center for Connected Learning and Computer Based Modelling and run in a program called Netlogo. The program and models are available for downloading, so you can continue to explore them on your own computers if you're so inclined.
    The models from this site that we will be exploring in class are:


    You might also be interested in a model under development on Serendip called Segregation/Integration.

    Whichever model you choose to explore, think of it as a process of making observations in order to try and come up with a "story" of how the system behaves. Report your observations and story in the course forum area.



    Name: Denise and
    Date: 2003-12-02 14:42:01
    Link to this Comment: 7428

    We used the sheep and wolf model. Our goal was to try and create order in a sustainable ecosysem--in other words, where no species died off.

    Our hypothesis was that if we put everything exactly in the middle on the bars---if the sheep and wolves, for example, had the same reproduction rate and nutrition intake--the ecosysem would be balanced.

    We were wrong. Yay for us.

    After scrupulous experimentation with differing levels of variables, we discovered a model in which the ecosystem sustained itself. In this system, while the wolves got more nutrition from their food, the sheep reproduced faster. We kept the grass rate at around 100 (if we took away the primary nutrition source of the sheep, they died off and the wolves followd them), and eventually the screen flashed, alternately, full-sheep and full-wolves. Then the mac crashed, because macs are evil.

    In conclusion, we suggest a new hypothesis. Wheras wolves, as predators, will deplete the sheep population if they are allowed to reproduce equally, if they simply gain more from their food (as actually happens in real life, considering they're eating meat, which has a higher nutritional quotient anyway) and reproduce less than the sheep, the sheep will be able to maintain a stable population. To test this hypothesis, we could run the simulation several more times.


    Abby and Melissa
    Name: melissa ab
    Date: 2003-12-02 15:03:51
    Link to this Comment: 7429

    Using the Wolf/Sheep Model, we attempted to sustain the respective species.

    Initially, we attempted to achieve homeostasis by setting all rates at the same level. In doing so, we found inverse relationships between the sheep/grass levels and the sheep/wolf levels.

    In revision, we increased wolf gains from food. This resulted in the inherent death of sheep.

    Our optimal level, yet not consistently sustained, was when when the sheep population levels were slightly higher than wolf, yet the wolf gain from consumption was considerable higher. While the model began with a direct relationship between the species, it ended in the inverse fluctuations of population levels.

    In conclusion, death is inherent. While we are dealing with only two to three variables, it is possible that other external variables not introduced into the model aid in the consistency of survivorship curves.


    epidemic
    Name: Charlotte,
    Date: 2003-12-02 15:09:31
    Link to this Comment: 7430

    We decided to use Netlog's program that simulated the spread of HIV, because we found it fascinating.

    The factors that can be changed with this program include probability of having a sexual relationship, condom use, length of relationship, and frequency of testing.

    We kept these factors constant:
    -300 people
    -5 average coupling tendency
    -20 week duration of relationship
    -observed over 30 years

    **we altered the condom use and frequency of testing.

    Our hypothesis was that condom use would be the most important factor in preventing the spread of HIV.

    Scenario 1:
    Condom use: 3/10
    Testing: 0 times a year

    Percent infected: 99%

    Scenario 2:
    Condom: 3/10
    Testing: 1 time a year

    Percent infected: 9.33%

    Scenario 3:
    Condom: 3/10
    Testing: 2 times a year

    Percent: 4.33%


    Scenario 4:
    Condom: 7/10
    Testing: 0 times a year

    Percent: 97.67%

    Scenario 5:
    Condom: 7/10
    Testing: 1 time a year

    Percent: 8.67%


    Scenario 6:
    Condom: 7/10
    Testing: 2 times a year

    Percent: 3.33%


    Final Observations: Condom use was important; but test frequency had a greater effect on percent infected. We were shocked at how drastic the difference was, particularly between scenario 4 and 6, because we set them up to simulate what we estimate is closest to real life in our generation.

    Conclusion: get tested. twice a year.


    don't follow the leader
    Name: Natalya an
    Date: 2003-12-02 15:09:36
    Link to this Comment: 7431

    We discovered, by playing with these models, that there is no director in biological systems. A number of factors influence the outcome in a given biological system, but none of them function in a vacuum, the result depends upon all of them. The same way that genes do not predetermine a certain characteristic, one factor, such as chance of recovery, does not determine how deadly a disease will be in a given population. Even a disease with a very high chance of recovery may decimate an entire population if its duration is very long and its infectiousness is very high. Unless you control all the factors in an ecosystem, you cannot control what will happen in that ecosystem under a certain condition.


    Katie Ottati, Manuela, Laura Wolfe
    Name:
    Date: 2003-12-02 15:12:32
    Link to this Comment: 7432

    We were looking at the wolves and sheep model and seeing how to create a stable environment. If the sheep die, the wolves have no food so they die. But if the wolves die first, the sheep keep reproducing and the population gets out of control (unless you turn on the grass setting in which case the sheep will quickly run out of food and die if there are no wolves to control their population).

    We wanted to make the sheep, wolves and grass all survive for a long period of time. We figured out since the sheep are lower on the food chain you need a lot more of them. You also need more grass than sheep fr the same reason. We found that it was easier to have the grass on, so that would be a variable as well, because when there was a never-ending supply of grass the populations never stayed stable. By letting everything depend on the other variables, everything stayed more stable.

    Also, we played with how much energry wolves can derive from eating a sheep compared to how much energy sheep got from grass. We ended up succeeding in making a stable environment.


    stuff
    Name:
    Date: 2003-12-02 15:26:40
    Link to this Comment: 7433

    Bessy Guevara & Shafiqah Berry
    Our hypothesis was that if all variables were the same, we would attain equilibrium.

    We used the sheep and wolf model. We kept all of the variables the same, the results were always random. When we tried changing the number of sheep and wolves, while still keeping the other variables the same, the results were either one or both would die. Our observations were inconsistent with our hyothesis. We then reduced alll variables for the sheep and the esults showed (surprisingly) that the wolves died first and the sheep reproduced continously.
    When examining with grass as a changing factor, we followed the same procedures as the first trial. The results we had were always random with one or both dying.
    Sheep
    165
    5- food gain
    9% reproduction
    wolves
    100
    25-food gain
    10% reproduction
    Grass at 30 reproduction rate

    It was at this point that we found equilibrium.



    Name:
    Date: 2003-12-03 14:55:36
    Link to this Comment: 7440

    Lindsay Updegrove
    Melissa Teicher

    We played around with the termite model. We found that changing the density determined how well the termites clustered the wood chips. When we changed the population, the only thing that changed was how fast or slow the termites clustered the wood chips.

    A bigger density resulted in huge irregular looking clumps, almost like bands. A smaller density caused termites to make a lot of really small piles before eventually building up into few large clusters.

    Since they move randomly, the clusters are always of different shapes and patterns. There is no predictability.


    wolf and sheep
    Name: anonymous
    Date: 2003-12-03 15:03:28
    Link to this Comment: 7441

    Jessica Knapp and Diana Medina

    We tried to create a system which ensured that no species would become extinct by lack of food or by becoming food for predators.

    We assumed that in creating a balance of wolf, sheep, and grass, it was important to begin with the same number of wolves and sheep, including the gain from food and reproduction rate.

    Having attempted to begin with equal numbers, we found that an equilibrium of species could not be maintained. The wolves ate the sheep too quickly, so we decreased their number, assuming that the sheep population would be maintained due to a decreased number of predators. However, we soon came to see that the wolves would eventually become extinct, whereas the sheep would not become extinct and exist with the grass. Something else that we noticed was that the relative gain from food for sheep was quicker than that of the wolves, even with less number of wolves. If we had kept the gain from food equal, the sheep would have had a better advantage. We decided to lower the gain from food for sheep, so that the wolves had a better chance of remaining part of the ecosystem.

    We then came to understand that in order to maintain equilibrium, we had to start out with a smaller number of wolves and sheep in general. We kept the proportion of wolves and sheep the same as the previous experiments, but lowered the number from 100 sheep to 44 and 80 wolves to 32.
    This produced an equilibrium of species, that is, all were able to survive together.


    sheep and wolves
    Name:
    Date: 2003-12-03 15:10:33
    Link to this Comment: 7442

    Adina Halpern and Maggie Tucker

    For this lab we studied the Wolf/Sheet Predation model. We went into experiment expecting to be able to find a harmonious balance between wolves and sheep. We first increased the sheep population to 250 and increased the wolf population to 120. This lead to the extinction of wolves. We changed reprodution rates of both animals, and yet the wolves stiff suffered from extinction. Differnces in the wolf population were also made, but failed to yeild positive results. After these many changes in variables we decided that balance could not be reached with this vast number of sheep.

    We then added grass as another variable, again starting with 250 sheep and 120 wolves. However, the wolves still became extinct.

    At this point, we decided to use the initial populations given by the computer program -- 49 wolves and 82 sheep. We kept the grass as a variable, decreasing the regrowth rate to 25. With these factors in place, we found a stable environment for an infinate number of time. The sheep were dominate at most points in time, however, neither species became extinct.


    and the green grass grows all around
    Name: Stefanie a
    Date: 2003-12-03 15:11:10
    Link to this Comment: 7443

    Initial Numbers:
    Sheep: 80 Wolves: 50
    Gain From Food:
    Sheep: 10 Wolves: 12
    Reproduction Rate:
    Sheep: 4% Wolves: 2%

    At these setting the sheep and wolf populations expanded indefinitely. The rate of expansion of the sheep population was very high, and for the wolves very low. Yet, somehow a balance was achieved because both populations survived until our computer ran out of memory, and terminated netlogo. The sheep population at the time of termination was 28,774 and the wolf population a mere 188.

    We had the grass option turned off in our first couple of trials. We hypothesize that the grass option, while complicating the experiment, will ultimately serve to limit the expansion of the sheep population.

    After setting the grass option to on, and changing the rate of grass regrowth time to 50 (all other values were constant), we found a repeating, self-perpetuating pattern that continued indefinitely. The number of sheep was still greater than the number of wolves, however unlike our previous trials the number of sheep was closer to the number of wolves (about three times the number of wolves).

    The pattern gained stability, with the values fluctuating around a point, with no net gain or loss. Our data supports our original hypothesis, that the use of the grass option will limit the expansion of the sheep population. This limitation is what allowed the values to become stable (because the sheep did not increase indefinitely as before).


    Slime mold
    Name: Mariya and
    Date: 2003-12-03 15:12:47
    Link to this Comment: 7444

    We used the slime-mold scenario. Mmmm, slime.
    Hypothesis: if the population is increased, the slime cells will form more clusters.
    Keeping all other factors the same (at about the middle of the respective scales) we changed the population from 50 to 400 at intervals of 50.
    50 - 0 clumps (no white)
    100 - 0 clumps, but more tendency towards clumping (brief white spots)
    150 - 1 cluster, lots of random cell motion outside the clump
    200 - 3 clusters, formed faster than before. Less random motion.
    250 - 5 clusters, no unattached cells, still faster
    300 - 9 clusters
    350 - 11 clusters
    400 - 12 clusters

    There was not a regular pattern in the increase of the number of clusters, but the number of clusters did increase as the population increased. We think this is because the cells don't have to go as far to form clumps when there are lots of cells present. If there are too few cells, the green chemical evaporates before any other cells happen upon it, so they do not form clumps. (We think they might eventually, given a long time, but we did not observe any clumps below a population of 150.)


    sheep and wolves and grass and DEATH
    Name:
    Date: 2003-12-03 15:14:27
    Link to this Comment: 7445

    Lara Kallich, Alice Goldsberry

    In dealing with the wolf-sheep predation model, we quickly discovered that the key to creating a stable ecosystem was to, without changing any of the other settings, "turn on" the grass. So we decided to change several of the other settings. We found that this ecosystem has a tendency to stabilize at a point where there are approximately twice as many sheep as there are wolves, even if the starting numbers of both are equal or even if the starting number of wolves is greater. We also found that altering the "sheep/wolf reproduce" numbers (the probabilities of each group reproducing at each timestep) did not really destabilize the ecosystem by that much. We found, however, that altering the "sheep/wolf gain from food" numbers had very significant effects on the ecosystem - if we increased the sheep gain-from-food, both the sheep and wolves became extinct very quickly. We then decided to increase proportionally the wolves' gain from food, and found once again that both species quickly became extinct.

    Why did this happen? We're not really sure. However, we can hazard a guess:

    When, for example, the sheep gain from food was increased, the number of sheep that showed up on the field greatly increased. This would suggest that the probability of their reproducing at each timestep had increased, but we knew that we controlled that number, so we had to discard that idea. What we believe was happening can be explained as follows: Sheep can die in two ways, according to this model: starvation and being eaten by a wolf. Having a low gain from food entails a greater likelihood of dying from starvation (if the grass function is turned on, of course). So, when the gain from food was increased, the sheep were much less likely to starve, causing there to be more of them over the course of time....

    as stated above, we're not really sure. at all.


    Who's In Charge?
    Name: Katy and F
    Date: 2003-12-03 15:24:43
    Link to this Comment: 7446

    Wolf and Sheep Predation
    Flicka Michaels
    Katy McMahon

    We attempted to achieve a stable environment in which both sheep and wolf populations coexisted for a long duration.

    We observed the effect of altering one variable at a time while keeping the others constant. This confirmed for us that the relationship between all of the variables is highly important.

    We noticed that different combinations of variables; inital number of sheep/wolves, gain from food, and reproductive rate, not only produced different results, but the time until extinction also changed.

    We hypothesized that the number of sheep had to be greater than the number of wolves, that the wolves had to gain more from their food than the sheep, and that the rate of reproduction for wolves had to be slightly greater than that of sheep.

    The closest we got to achieving a long duration of existence was:

    # of sheep: 102 # of wolves: 60
    gain from food: 11 gain from food: 25
    reproduction: 6% reproduction: 7%


    Wolf and Sheepies
    Name: Fabulous A
    Date: 2003-12-03 15:28:17
    Link to this Comment: 7447

    We tried several settings before finding a combination of circumstances that maintained both populations of wolves and sheep. The major problem we ran into was that the sheep population would take off, spurring the wolf population to follow, then the sheep population would die, and the wolf population would follow suit, then eventually the sheep population would take off again (for reasons we cannot asscertain), and the wold population wouldn't recover.

    Example:

    Init.sheep Init. Wolves SheepgainFood W.G.F S. repro W. repro
    100 40 5% 15% 5% 5%

    Thus, sheep Up, wolves Up--> sheep Down, wolves Down--> sheep Up


    The one we did that worked:

    I. Sheep I. Wolves S.gainFood W.gainFood S. repro W. repro
    100 40 29 60 19 6

    After 53 time units there were

    sheep--- 339351
    Wolves---649
    grass----420

    The sheep were continuing upward, while the wolves increased at a steady, but slower rate. In conclusion, although our model works, we believe that there is no real solution to this problem: the key is moderation and balance, and diversity. Things are dependent upon one another, in order to create something new, something must first be destroyed---if a model could give us a solution to this problem, then life would be very easy.


    HIV spread
    Name: Patricia P
    Date: 2003-12-03 15:28:46
    Link to this Comment: 7448

    Enor Wagner Patricia Palermo

    We thought it would be intersting to test the spread of HIV observing two main variables: Weeks of commitment between partners and condom use. There was a constant 300 person population and 2.67 % was infectd to start.

    An extremely brief conclusion: (we will explain further)
    with 50 weeks commitment, 0 condom use
    65.67% infected by 10 years

    with 10 weeks commitment, 0 condom use
    100% infected in 10 years

    with 50 weeks commitment, 10 condom use (full condom use)
    32.88% infected in ten years

    10 week commitment, 10 condom use
    48.66%


    We determined from this that we need to know several other factors. What changes once the people know they are infected? Based on the experiment, we can still see them coupling rapidly. This would not happen in real life. We also wanted to know if 10 condom use stood for 100% of the population using condoms, because that seemed unlikely and high for the scores we got.

    Basically we can conclude that if no condoms are used, and commitment to one partner is extreamly short, than the entire population of 300 would contract HIV in 10 years. With comparitive observations of our data, we can say that condom use is a more important factor in stopping the spread (or slowing the spread) of HIV than lengthening the weeks commitment.



    Name: Ramatu Kal
    Date: 2003-12-03 15:35:17
    Link to this Comment: 7449

    Ramatu Kallon and Rochelle Merilien


    Hypothesis:
    We hypothesize that when the density of the simulation is higher, there will be none or fewer piles, on the contrary to that when the density of the simulation is lower there will be more piles.

    Observations:
    1st Test
    Number of Termites- 110 (number used in all test)
    Density- 30%
    @ 2 mins. 4 piles
    @5 mins. 4 piles
    @7 mins. 4 piles

    2nd Test
    Density- 70%
    @2 mins..- 0 piles
    @ 5 mins.- 0 piles
    @ 7 mins- 0 piles

    3rd Test
    @2 mins. 2 piles
    @5mins- 2 piles (one extremely large and 1 tiny)
    @ 5mins- 2 piles

    Conclusion:
    We feel that to get a proper set we will need to do more trials.


    wolf/sheep trials
    Name: megan will
    Date: 2003-12-03 23:09:41
    Link to this Comment: 7457

    In my initial test, I began the sheep population at 80 and the wolf population at 40. However, I did not increase the grass levels or the amount of food gained by either population. This resulted in the sheep rapidly increasing in population and the wolves maintaining a low population, however, as the grass decreased, the sheep population was being taxed not only by the predator wolf but also the decline in food source.

    I tried many different combinations to match the level of growth of all 3 species. The final one I came up with kept an environmental balance, each of the 3, grass, sheep, and wolves, would increase and decrease interchangeably. None of the species died out, and they continuously overlapped each other in population. I ran this trial for 350 ticks.

    Starting combo:
    Sheep settings:
    Initial number: 75
    Gain: 5.0
    Reproduction: 6%

    Wolf settings:
    Initial number: 50
    Gain : 25
    Reproduction: 7%

    Grass growth time: 25


    My observations from the graph were that as each species population increased, so did the other, and as each decreased, the same occurred. Since the wolves did have a limited food source, the sheep also had to have a limited food source, or their population would skyrocket within seconds. The 25 extra sheep in the beginning were enough of a buffer to let the wolves catch up, then for the two to grow and decline together.


    Chromosome and DNA
    Name: HT Binh
    Date: 2005-04-09 05:58:02
    Link to this Comment: 14395

    Dear all I'd like to receive a flash file about chromosome and DNA for teaching biology lessons of grade 11. Thanks a lot.





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