This study examined the relationship between the slope of a terrain and vegetation, measured by the normalized difference vegetation index (NDVI). It was hypothesized that lower slope ranges would be more supportive of vegetation growth than higher slope ranges. Analysis showed that no slope (even as extreme as 85–90°) prohibits the growth of vegetation completely; even the steepest slopes examined contain plant life. Knowing that steep slopes can still support plant life, agriculturalists can begin to explore and start planting additional crops and plants at these extreme slopes.
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Characterizing the evolution of antibiotic resistance in commercial Lactobacillus strains
In this study, the authors studied the ability for bacteria to develop antibiotic resistance over successive generations and modeled the trajectory to predict how antibiotic resistance is developed.
Read More...Hammett linear free-energy relationships in the biocatalytic hydrolysis of para-substituted nitrophenyl benzoate esters
As the world moves towards more eco-friendly methods for chemical synthesis, there's a strong interest in employing enzymes in chemical synthetic processes. Here, the authors explore how the activity of enzymes such as trypsin, lipase and nattokinase is affected by the electronic effects of the substrate they are acting on.
Read More...Observing effects of resolving leaky gut on sugar, fat, and insulin levels during type 1 diabetes in fruit flies
This study uses a fruit fly model of type 1 diabetes (T1D) to determine whether strengthening intestinal tight junctions to reduce intestinal permeability would improve T1D symptoms.
Read More...Estimating the Carcinogenic Risks of Major Pollutants Released into the Environment
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.
Read More...Propagation of representation bias in machine learning
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.
Read More...Exercise, grades, stress, and learning experiences during remote learning due to the COVID-19 pandemic
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.
Read More...The effect of microplastics on the speed, mortality rate, and swimming patterns of Daphnia Magna
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.
Read More...Effects of airport runoff pollution on water quality in bay area sites near San Francisco and Oakland airports
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.
Read More...Design and in silico screening of analogs of rilpivirine as novel non-nucleoside reverse transcriptase inhibitors (NNRTIs) for antiretroviral therapy
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.
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