Popluation Size Estimation Lab

There are numerous uses for population size estimation, and numerous ways to estimate.

In this lab, the mark and recapture method was used by randomly choosing and marking 10 specimens from a bag of an unknown number. The ten trials of 15 specimens were randomly taken from the bag. This yielded variegated results from the different teams.

Using the random sampling method, a four (4) foot by four (4) foot grid was made on the floor, and the specimens were randomly spread across this. The specimens from four of the four (4) foot squares were added together and multiplied by four (4) to garner the population estimation. This process was repeated a varied number of times, with varied accuracy, among the groups.

Orion K, SIN, The Beginning of Life as described by Math, October

The Beginning of Life as described by Math

A mathematical model has predicted the beginnings of life on earth. Heather Wax reported in Using Math to Explain How Life on Earth Began at sciam.com that Martin A. Nowak produced a computer simulation founded on a mathematical algorithm. Martin A. Nowak is the first person to have a joint professorship in Mathematics and Biology at Harvard University.
This algorithm uses binary to model the fundamental building blocks of life, nucleic acids (adenine, thymine, guanine, cytosine or uracil). Nowak composes these “building blocks” into “random and spontaneous” strings of binary coding that he calls monomers. He then uses his binary strings to make a model of the evolution of the nucleic acids. Nowak claims that the nucleic acids will perform the same way that his model suggests; however, this is not without problems. David W. Deamer, a biomolecular engineer at the University of California, Santa Cruz, explains: “It’s hard to imagine an easy way to make nucleic acids.” This is because the model does not allow for enzymes that would process and build the nucleic acid molecules.
Though it may not seem important, using math in biology is imperative, according to Nowak. This is because math is capable of solving previously unsolvable problems such as decoding gene sequences. These could be used in a wide variety of topics; from curing diseases to building AIs, to improving education. Moreover, the exploration of the beginning of life is one of the fundamentals of biology.

Alex L., S.I.N., October

Jaguar Land Rover’s Virtual Reality Center

Jaguar Land Rover, a division of Tata, an Indian carmaker, has worked with Sony, Sun Microsystems, ICIDO, and HoloVis International to construct what they call a “Virtual Reality Center” (VRC) to aid in the design process. In conjunction with a Computer Aided Virtual Environment (CAVE) that they say will allow the company to reduce design time by an estimated 3 months and reduce design costs. As reported by Stuart Birch, an author for Automotive Engineering Online, and published under the title “Jaguar Land Rover projects new images” (found at http://www.sae.org/mags/aei/simul/4364) this product took 18 months and $4 million to develop and produce, a sum they say they are on track to recovering within the first year of its use.

VRC and CAVE are, as the names suggest, a virtual environment system that is constructed with the use of eight Sony SRX-S105 projectors, which have an image definition of 4096 x 2160. These projectors, each powered by two powerful computers (each with two prime quality graphics cards), display a bifocal view of the vehicle, in full scale, with realistic components all in 3D. Another computer coordinates these; another manages the database, which the work of the employees (such as designed parts) is uploaded to. The system uses complex surround sound to simulate a real driving environment, and hopes to incorporate a haptic glove, which would allow the tester to feel the textures and contours of the model. They would utilize the haptic glove under development at Salford University (England) that will be ready in about six months. This technology would streamline the R&D of Jaguar Land Rover, improving their finances, allowing them to make vehicles more cheaply, thereby stimulating the economy.

Orion K, SIN, Environmental Complexity, September

Environmental Complexity
Davidson, A. W. and Bar-Yam, Y. Environmental Complexity: Information for Human-Environment Well-Being.

This study linked environmental complexity to cognitive function in the elderly. Environmental complexity is calculated based on the number of visually distinct characteristics of objects appearing in photographs of the participants’ houses.

A board of assessors viewed every photograph, and assigned a complexity “score” to each, using a “semi-quantitative measure”. The photograph was also scored on aesthetics. This method was used in correlation with a mathematical model, called Shannon's Information Theory: I = – Σ P(i) log2P(i), where P(i) is the probability of an item’s particular location and the sum is the over all possible locations.

The “Brief Psychiatric Rating Scale” was used to measure the participants’ mental fitness. Cognitive wellness was evaluated using the Mini-Mental Status Exam. The circadian locomotor activity of the participants was measured through a “wrist worn ambulatory activity monitor”.
It was found that the greater the complexity of the environment the greater was the cognitive skills of the participant. Moreover, the circadian activity increased as the environment was more complex. However, mental fitness was not increased.

This research is beneficial to me in that I will someday be considered one of these “elders” and will wish to maintain my mental capabilities.

Alex L., Science In The News(S.I.N.), September

Learning Aptitudes in Mathematics

Hinterthuer, A. (4-25-08). Word Problems Fail Math Students, Scientific American Online. Retrieved 9/10/08 from http://www.sciam.com/podcast/episode.cfm?id=86148EF0-91C8-2DCA-768F20CDA543F8E7

A study, preformed at Ohio State University, shows that when students learned through real-world word problems their overall ability to adequately solve the overall type of problem suffered. In the study two groups of undergraduates were taught mathematical concepts, which they would use later to solve other problems. One of the groups learned in the traditional style; by using abstract equations and formulae. The other group was taught in a style that used “real-world” problems and applied mathematics to them. The results were as follows: the students taught with abstract problems tested, on average, at 80% correctness, the students taught with the “real-world” situation tested at 44%. The lower scoring group did seem to acquire the knowledge faster, although they could not transpose this knowledge.