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Each year, large amounts of carcinogenic pollutants are released into the environment, which negatively affects human health. This study ranks the major carcinogenic pollutants that are released into the air, water, and land by both the total released amounts and the potential carcinogenic risks.

Using facial recognition as a use-case scenario, we attempt to identify sources of bias in a model developed using transfer learning. To achieve this task, we developed a model based on a pre-trained facial recognition model, and scrutinized the accuracy of the model’s image classification against factors such as age, gender, and race to observe whether or not the model performed better on some demographic groups than others. By identifying the bias and finding potential sources of bias, his work contributes a unique technical perspective from the view of a small scale developer to emerging discussions of accountability and transparency in AI.

In this study, the authors survey middle and high school students in different states in the U.S. to evaluate stress levels, learning experiences, and activity levels during the COVID-19 pandemic.

In this study, the authors investigate the effects that microplastics (which pollute fresh and saltwater ecosystems) have on plankton species Daphnia Magna by measuring their movement and viability.

In this study, the authors sample water at different points closer and closer to two different airports to determine if these airports may be contributing to water pollution, specifically by measuring metals, nitrates, and pH.

In this study, the authors use high-throughput virtual screening to design and evaluate a set of non-nucleoside reverse transcriptase inhibitors for binding affinity to the protein reverse transcriptase. These studies have important applications toward HIV therapies.

Berberine, a natural product alkaloid, and its analogs have a wide range of medicinal properties, including antibacterial and anticancer effects. Here, the authors explored a library of alkyl or aryl berberine analogs to probe binding to double-stranded and G-quadruplex DNA. They determined that the nature of the substituent, the position of the substituent, and the nucleic acid target affect the free energy of binding of berberine analogs to DNA and G-quadruplex DNA, however berberine analogs did not result in net stabilization of G-quadruplex DNA.

In this study, we developed an algorithm to estimate the contact rate and the average infectious period of influenza using a Susceptible, Infected, and Recovered (SIR) epidemic model. The parameters in this model were estimated using data on infected Greek individuals collected from the National Public Health Organization. Our model labeled influenza as an epidemic with a basic reproduction value greater than one.

Each year, invasive tree roots cause large amounts of damage to underground pipes. While this is usually due to leaks and cracks, tree roots can also invade pipes that are structurally sound. We are interested in investigating whether plant roots have an affinity towards flowing water, measured through mass, even when the running water is not in direct contact with soil. We tested this by creating a choice chamber with water running under one end and no stimulus on the other end. Overall, the masses of the roots growing towards flowing water were greater than the masses of the roots growing towards the end with no stimulus, showing that plant roots did have an affinity towards flowing water.

In this study, the authors tested different approaches for removing arsenic from rice. Due to higher arsenic levels in water, some areas grow rice with higher levels as well. This is a health hazard and so developing methods to remove arsenic from the rice will be helpful to many. Using a rapid arsenic kit, the authors found that activated charcoal was the most effective at removing arsenic from rice.