![Effects of airport runoff pollution on water quality in bay area sites near San Francisco and Oakland airports](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBdllIIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--249d3fe4410e53f8edee9c1da12337014512fc84/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJYW5CbkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--a3b53ba1a0f83efef18f6e75a8d4ce784384bee2/Figure%201.jpg)
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...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...Modeling and optimization of epidemiological control policies through reinforcement learning
Pandemics involve the high transmission of a disease that impacts global and local health and economic patterns. Epidemiological models help propose pandemic control strategies based on non-pharmaceutical interventions such as social distancing, curfews, and lockdowns, reducing the economic impact of these restrictions. In this research, we utilized an epidemiological Susceptible, Exposed, Infected, Recovered, Deceased (SEIRD) model – a compartmental model for virtually simulating a pandemic day by day.
Read More...A comparative analysis of machine learning approaches for prediction of breast cancer
Machine learning and deep learning techniques can be used to predict the early onset of breast cancer. The main objective of this analysis was to determine whether machine learning algorithms can be used to predict the onset of breast cancer with more than 90% accuracy. Based on research with supervised machine learning algorithms, Gaussian Naïve Bayes, K Nearest Algorithm, Random Forest, and Logistic Regression were considered because they offer a wide variety of classification methods and also provide high accuracy and performance. We hypothesized that all these algorithms would provide accurate results, and Random Forest and Logistic Regression would provide better accuracy and performance than Naïve Bayes and K Nearest Neighbor.
Read More...An Investigative Analysis of Climate Change Using Historical and Modern Weather Data
Climate change is an important and contentious issue that has far-reaching implications for our future. The authors here compare primary temperature and precipitation data from almost 200 years ago against the present day. They find that the average annual temperature in Brooklyn, NY has risen significantly over this time, as has the frequency of precipitation, though not the amount of precipitation. These data stress the need for more ecologically-conscious choices in our daily lives.
Read More...The impact of COVID-19 quarantine on physical activities in Basra, Iraq: A cross-sectional study
As the COVID-19 pandemic continues, the authors noticed a change in the physical activity of many people, as well as a change in the type of physical activity they practice. Here, the authors used a cross-sectional survey of 150 participants from the province of Basra in Iraq. They found an overall decrease in the number of days of physical activity for participants along with an increasing proportion of at-home exercises compared to other activities that are performed inside sports clubs during the pandemic.
Read More...Effects of Photoperiod Alterations on Stress Response in Daphnia magna
Here, seeking to better understand the effects of altered day-night cycles, the authors considered the effects of an altered photoperiod on Daphnia magna. By tracking possible stress responses, including mean heart rate, brood size, and male-to-female ratio they found that a shorter photoperiod resulted in altered mean heart rates and brood size. The authors suggest that based on these observations, it is important to consider the effects of photoperiod alterations and the stress responses of other organisms.
Read More...Heat impact to food’s shelf life - An example of milk
Food spoilage happens when food is not kept in a good storage condition. Qualitatively estimating the shortened shelf life of food could reduce food waste. In this study, we tested the impact of heat on milk shelf life. Our results showed that an exposure at room temperature (25°C) for 3.2 hours will decrease the shelf life of milk by one day.
Read More...Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset
Auto-Regressive Integrated Moving Average (ARIMA) models are known for their influence and application on time series data. This statistical analysis model uses time series data to depict future trends or values: a key contributor to crime mapping algorithms. However, the models may not function to their true potential when analyzing data with many different patterns. In order to determine the potential of ARIMA models, our research will test the model on irregularities in the data. Our team hypothesizes that the ARIMA model will be able to adapt to the different irregularities in the data that do not correspond to a certain trend or pattern. Using crime theft data and an ARIMA model, we determined the results of the ARIMA model’s forecast and how the accuracy differed on different days with irregularities in crime.
Read More...Plasmid Variance and Nutrient Regulation of Bioluminescence Genes
Numerous organisms, including the marine bacterium Aliivibrio fischeri, produce light. This bioluminescence is involved in many important symbioses and may one day be an important source of light for humans. In this study, the authors investigated ways to increase bioluminescence production from the model organism E. coli.
Read More...Inflated scores on the online exams during the COVID-19 pandemic school lockdown
In this study, the authors explored whether students' test scores were significantly higher on online exams during the COVID-19 school lockdown when compared to those of the in-person exams before the lockdown.
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