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Can Green Tea Alleviate the Effects of Stress Related to Learning and Long-Term Memory in the Great Pond Snail (Lymnaea stagnalis)?

Elias et al. | Jan 30, 2021

Can Green Tea Alleviate the Effects of Stress Related to Learning and Long-Term Memory in the Great Pond Snail (<em>Lymnaea stagnalis</em>)?

Stress and anxiety have become more prevalent issues in recent years with teenagers especially at risk. Recent studies show that experiencing stress while learning can impair brain-cell communication thus negatively impacting learning. Green tea is believed to have the opposite effect, aiding in learning and memory retention. In this study, the authors used Lymnaea stagnalis , a pond snail, to explore the relationship between green tea and a stressor that impairs memory formation to determine the effects of both green tea and stress on the snails’ ability to learn, form, and retain memories. Using a conditioned taste aversion (CTA) assay, where snails are exposed to a sweet substance followed by a bitter taste with the number of biting responses being recorded, the authors found that stress was shown to be harmful to snail learning and memory for short-term, intermediate, and long-term memory.

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Predicting college retention rates from Google Street View images of campuses

Dileep et al. | Jan 02, 2024

Predicting college retention rates from Google Street View images of campuses
Image credit: Dileep et al. 2024

Every year, around 40% of undergraduate students in the United States discontinue their studies, resulting in a loss of valuable education for students and a loss of money for colleges. Even so, colleges across the nation struggle to discover the underlying causes of these high dropout rates. In this paper, the authors discuss the use of machine learning to find correlations between the built environment factors and the retention rates of colleges. They hypothesized that one way for colleges to improve their retention rates could be to improve the physical characteristics of their campus to be more pleasing. The authors used image classification techniques to look at images of colleges and correlate certain features like colors, cars, and people to higher or lower retention rates. With three possible options of high, medium, and low retention rates, the probability that their models reached the right conclusion if they simply chose randomly was 33%. After finding that this 33%, or 0.33 mark, always fell outside of the 99% confidence intervals built around their models’ accuracies, the authors concluded that their machine learning techniques can be used to find correlations between certain environmental factors and retention rates.

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Investigating ecosystem resiliency in different flood zones of south Brooklyn, New York

Ng et al. | Mar 23, 2024

Investigating ecosystem resiliency in different flood zones of south Brooklyn, New York
Image credit: Ng and Zheng et al 2024

With climate change and rising sea levels, south Brooklyn is exposed to massive flooding and intense precipitation. Previous research discovered that flooding shifts plant species distribution, decreases soil pH, and increases salt concentration, nitrogen, phosphorus, and potassium levels. The authors predicted a decreasing trend from Zone 1 to 6: high-pH, high-salt, and high-nutrients in more flood-prone areas to low-pH, low-salt, and low-nutrient in less flood-prone regions. They performed DNA barcoding to identify plant species inhabiting flood zones with expectations of decreasing salt tolerance and moisture uptake by plants' soil from Zones 1-6. Furthermore, they predicted an increase in invasive species, ultimately resulting in a decrease in biodiversity. After barcoding, they researched existing information regarding invasiveness, ideal soil, pH tolerance, and salt tolerance. They performed soil analyses to identify pH, nitrogen (N), phosphorus (P), and potassium (K) levels. For N and P levels, we discovered a general decreasing trend from Zone 1 to 6 with low and moderate statistical significance respectively. Previous studies found that soil moisture can increase N and P uptake, helping plants adopt efficient resource-use strategies and reduce water stress from flooding. Although characteristics of plants were distributed throughout all zones, demonstrating overall diversity, the soil analyses hinted at the possibility of a rising trend of plants adapting to the increase in flooding. Future expansive research is needed to comprehensively map these trends. Ultimately, investigating trends between flood zones and the prevalence of different species will assist in guiding solutions to weathering climate change and protecting biodiversity in Brooklyn.

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Using machine learning to develop a global coral bleaching predictor

Madireddy et al. | Feb 21, 2023

Using machine learning to develop a global coral bleaching predictor
Image credit: Madireddy, Bosch, and McCalla

Coral bleaching is a fatal process that reduces coral diversity, leads to habitat loss for marine organisms, and is a symptom of climate change. This process occurs when corals expel their symbiotic dinoflagellates, algae that photosynthesize within coral tissue providing corals with glucose. Restoration efforts have attempted to repair damaged reefs; however, there are over 360,000 square miles of coral reefs worldwide, making it challenging to target conservation efforts. Thus, predicting the likelihood of bleaching in a certain region would make it easier to allocate resources for conservation efforts. We developed a machine learning model to predict global locations at risk for coral bleaching. Data obtained from the Biological and Chemical Oceanography Data Management Office consisted of various coral bleaching events and the parameters under which the bleaching occurred. Sea surface temperature, sea surface temperature anomalies, longitude, latitude, and coral depth below the surface were the features found to be most correlated to coral bleaching. Thirty-nine machine learning models were tested to determine which one most accurately used the parameters of interest to predict the percentage of corals that would be bleached. A random forest regressor model with an R-squared value of 0.25 and a root mean squared error value of 7.91 was determined to be the best model for predicting coral bleaching. In the end, the random model had a 96% accuracy in predicting the percentage of corals that would be bleached. This prediction system can make it easier for researchers and conservationists to identify coral bleaching hotspots and properly allocate resources to prevent or mitigate bleaching events.

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The Effect of Music on Heart Rate

Agrawal et al. | Apr 25, 2013

The Effect of Music on Heart Rate

Different songs can seem to evoke different emotions. Here the authors demonstrate that different songs can have a significant effect on the heart rate of listeners. A slower song slows heart rate, and a faster song increases it.

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More efficient sources of water distribution for agricultural and general usage

Jung et al. | Nov 11, 2022

More efficient sources of water distribution for agricultural and general usage

Here, the authors investigated alternative methods to irrigate plants based on the their identification that current irrigation systems waste a large amount of fresh water. They compared three different delivery methods for water: conventional sprinkler, underground cloth, and a perforated pipe embedded in the soil. They found the cloth method to save the most water, although plant growth was slightly less in comparison to plants watered with the sprinkler method or pipe method.

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The Development and Maximization of a Novel Photosynthetic Microbial Fuel Cell Using Rhodospirillum rubrum

Gomez et al. | Mar 02, 2014

The Development and Maximization of a Novel Photosynthetic Microbial Fuel Cell Using <em>Rhodospirillum rubrum</em>

Microbial fuel cells (MFCs) are bio-electrochemical systems that utilize bacteria and are promising forms of alternative energy. Similar to chemical fuel cells, MFCs employ both an anode (accepts electrons) and a cathode (donates electrons), but in these devices the live bacteria donate the electrons necessary for current. In this study, the authors assess the functionality of a photosynthetic MFC that utilizes a purple non-sulfur bacterium. The MFC prototype they constructed was found to function over a range of environmental conditions, suggesting its potential use in industrial models.

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The Effect of Interactive Electronics Use on Psychological Well Being and Interpersonal Relationship Quality in Adults

Belkin et al. | Apr 19, 2018

The Effect of Interactive Electronics Use on Psychological Well Being and Interpersonal Relationship Quality in Adults

In recent years, usage of interactive electronic devices such as computers, smartphones, and tablets has increased dramatically. Many studies have examined the potential adverse effects of excessive usage of such devices on children and adolescents, but the effects on adults are not well understood. In this study, the authors examined the relationship between adult usage of interactive electronic devices and a variety of clinical measures of psychological well-being. They found that according to some metrics, higher usage of interactive electronic devices is associated with several adverse psychological outcomes, suggesting a need for more careful consideration of such usage patterns in clinical settings.

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