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Three Harrison High School Students Qualify as Finalists in Regeneron International Science and Engineering Fair 

Harrison High School  Science Research Scholars, Seniors Mai Blaustein, Jack Kelly and Junior Ariella Blackman have qualified to compete in the prestigious Regeneron International Science and Engineering Fair in May.

The Westchester Science & Engineering Fair (WESEF) encourages students to participate in hands on science by providing a forum for showcasing the outstanding research of high school students in Westchester & Putnam counties of New York State and sponsoring the top students from the fair to advance to the REGENERON International Science & Engineering Fair.

Mai and Jack won "Best in Fair" (top 20 projects) at The Westchester Science & Engineering Fair (WESEF) which qualified them for the Regeneron International Science and Engineering Fair (ISEF) competition in Atlanta, May 7-13th.  Approximately 550 students from 39 schools competed at WESEF this year.

They also placed first in their respective competition categories, Mai in Chemistry and Jack in Behavioral Sciences. In addition, Mai won the SM Materials Education Foundation Award for outstanding research in materials engineering.

Mai Blaustein, Ariella Blackman and Zaynab Faisal also qualified for the final round of the New York State Science and Engineering Fair (NYSSEF). Since Mai already qualified for ISEF, only Ariella & Zaynab competed at the state fair. Ariella won first place in her competition category, was named among the top 15 projects out of almost 300, and won the Mu Alpha Theta award for creative use of math.  As a result, Ariella qualified for ISEF. Zaynab earned honorable mention and won the Stockholm Junior Water Prize.

Additional Student Awards: Morgan Remeza: 2nd place in Environmental Science, and Environmental Perspiration Award; Katie Pflieger: 3rd Place in Bioinformatics; Ariella Blackman: 4th Place in Plant Sciences, and American Meteorological Association Award; Nicole Giandomenico: 4th Place in Cellular & Molecular Biology; Keelan Vaswani: Honorable Mention in Behavioral Sciences; Yuiko Suzuki: Honorable Mention in Behavioral Sciences; Macarena Hesse: United States Air Force Award; Zaynab Faisal:  Teatown Young Environmentalist Award.


Jack Kelly

Quantifying Linguistic Polarization for Congressional Representatives Facing Primary Challengers: A Random Effects Logit Regression Approach 

Linguistic polarization is a change in frequency of policy references in a representative’s lexicon. When incumbent representatives face challengers, they may change their speech patterns to distinguish themselves to voters. Since Sulkin (2009) found a strong correlation between how representatives speak and how they vote, linguistic polarization could lead to policy differences. This study used a random effects logit regression to see if progressive primary challengers linguistically polarize Democratic Congressional incumbents. Because Kamarck and Podkul (2018) showed a 151% percentage increase of progressive Democratic House candidates from 2016 to 2018, the 116th Congress was chosen. Twitter was used as the data source because of the brevity and frequency of tweets. A total of 601,304 tweets from 410 representatives were coded for progressive language using a dictionary based approach. The dictionary had 194 terms (identified from 14 websites) and 50,722 total tweets were coded as progressive. 30 progressive challengers were included since they received > 5% of the votes in a primary and a major progressive endorsement. A regression was run for 30 incumbents facing viable challengers that looked at percentage of progressive tweets from incumbents (DV) before and after the challenger was endorsed (IV). Results showed incumbents had a 27% decrease in progressive language after a challenger entered the race (p<.05), a decrease 3x greater than a control group of randomized Democratic incumbents. One implication was that progressive challengers might have a moderating effect on Democratic incumbents as they aim to establish a distinct electoral path to victory.

Mai Blaustein

Identification of Chemical Contaminants in Spiked Beverages with the use of Infrared Spectroscopy through Development of An Inexpensive and Inconspicuous Device to Identify Date Rape Drugs

Gamma Hydroxybutyrate (GHB) and its precursor Gamma Butyrolactone (GBL) are easily accessible, Class C drugs, commonly used in drug-facilitated sexual assault cases. Existing technologies for detecting date-rape drugs in drinks have significant limitations: chemical tests only look at GHB or GBL, not both, pH indicators allow for false readings depending on acidity of the drink, and visible color-based detection methods allow for drink color interference. Infrared (IR) Spectroscopy is a light-based detection method used to identify molecules from larger mixtures. The purpose of this study was to determine if IR Spectroscopy could be used to detect harmful concentrations of illegal substances such as GHB/GBL in alcoholic beverages, and to construct a proof of concept detection instrument. A placeholder chemical, caprolactone was used as it shares a similar IR profile to GBL (the precursor to GHB) since GHB/GBL are illegal substances and could not be obtained. The methodology consisted of three parts: 1. Identifying relevant peaks in the IR window using a commercial IR spectrometer 2. Using identified peaks to determine filter and detector wavelengths necessary for a proof of concept instrument 3. Testing the instrument and constructing a calibration curve to determine ranges of concentrations of contaminants that could be detected. The calibration curve confirmed the proof of concept instrument could distinguish various concentrations of caprolactone in model spiked beverages (r² =0.89). Future research is needed to make the device portable and inconspicuous. 

Ariella Blackman

Developing a Model In-Situ Resource Utilization System for Oxygen Sustaining Life Support and Launch Cost Reduction for Mars

Martian agriculture may be the most cost-effective means to develop sustainable human life support systems on Mars by employing in-situ resource utilization to convert atmospheric CO2 into O2. However, launching necessary Earth soil is prohibitively expensive and Eichler et al. (2021) failed to germinate seeds in MGS-1, the most accurate Martian regolith simulant. This study determined whether Phaseolus acutifolius could grow in ratios of MGS-1 and Earth-based potting soil, and which substrate resulted in maximum O2 while reducing Earth-based mass. Plants were grown in ratios of MGS-1 and potting soil and used to create an original mathematical model that estimated the number of plants required to produce enough O2 to support human life with the smallest total Earth-based soil mass. Plants germinated in 0%, 25%, and 50% MGS-1 ratios. MGS-1 limited plant growth due to its water-retention properties. A significant difference existed between wet biomasses of plants grown in 50% MGS-1 and 0% MGS-1 (p<.05), with no such significant difference for the dry biomasses (p>.05). Plants in 50% MGS-1 allocated more resources towards obtaining water with significantly more below-ground biomass than the control (p<.05). Model calculations demonstrated a trend from 0% to 25% MGS-1: estimated number of required plants increased (867-1003 plants), but amount of Earth-based soil decreased (101kg-87.2kg). This trend potentially holds between 25% and 50% MGS-1, but is unclear because of large amounts of below-ground biomass. Results imply that ideal regolith content is between 50-75% MGS-1, as cost benefits of increasing regolith outweigh any decreased O2-production efficiency.