In this study, the authors test ways to increase knowledge of green consumerism amongst high school students. Their knowledge was measured based on the New Ecological Paradigm Scale.
Read More...Awareness of plastic pollution and adoption of green consumer lifestyles among students from high school
In this study, the authors test ways to increase knowledge of green consumerism amongst high school students. Their knowledge was measured based on the New Ecological Paradigm Scale.
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...Determination of Optimal Relevant Joint Angles for Vertical Jump Height Across Teenagers with Differing Amounts of Jumping Experience
Reaching one’s maximum jump height requires optimizing one’s jump techniques. In order to find this optimal jump technique, three high school participants with varying vertical jump (VJ) abilities recorded videos of themselves with varying degrees of maximum/minimum shoulder, knee, and hip angles—with or without respect to the horizontal—at the isometric phase of a regular countermovement (CM) VJ or countermovement jump (CMJ). Results showed that the shoulder angle without respect to the horizontal (SA), knee angle with respect to the horizontal (KAH), and the hip angle with respect to the horizontal (HAH) possessed a more consistent correlation with VJ height across the subjects compared to the same respective angles with opposite relations to the horizontal.
Read More...The impact of timing and magnitude of the El Niño- Southern Oscillation on local precipitation levels and temperatures in the Bay Area
Understanding the relationships between temperature, MEI, SPI, and CO2 concentration is important as they measure the major influencers of California’s regional climate: temperature, ENSO, precipitation, and atmospheric CO2. In this article, the authors analyzed temperature, Multivariate El Niño-Southern Oscillation Index (MEI), and Standard Precipitation Index (SPI) data from the San Francisco Bay Area from 1971 to 2016. They also analyzed CO2 records from Mauna Loa, HI for the same time period, along with the annual temperature anomalies for the Bay Area.
Read More...Fourier-Transform Infrared (FTIR) spectroscopy analysis of seven wisconsin biosolids
The authors analyzed biosolids from five Wisconsin wastewater treatment plants and suggest using KBr pellet FTIR as a simple and rapid method to start characterizing P species in biosolids.
Read More...Effects of an Informational Waste Management App on a User’s Waste Disposal Habits
While 75% of waste in the United States is stated to be recyclable, only about 34% truly is. This project takes a stance to combat the pillars of mismanaged waste through a modern means of convenience: the TracedWaste app. The purpose of this study was to identify how individuals' waste disposal habits improved and knowledge increased (i.e. correctly disposing of waste, understanding negative incorrect waste disposal) due to their use of an informational waste management app as measured by a survey using a 1-5 Likert Scale. The results showed that the TracedWaste app helped conserve abundant resources such as energy and wood, decrease carbon emissions, and minimize financial toll all through reducing individual impact.
Read More...Culturally Adapted Assessment Tool for Autism Spectrum Disorder and its Clinical Significance
Diagnosing of Autism Spectrum Disorder (ASD) using tools developed in the West is challenging in the Indian setting due to a huge diversity in sociocultural and economic backgrounds. Here, the authors developed a home-based, audiovisual game app (Autest) suitable for ASD risk assessment in Indian children under 10 years of age. Ratings suggested that the tool is effective and can reduce social inhibition and facilitate assessment. Further usage and development of Autest can improve risk assessment and early intervention measures for children with ASD in India.
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...The effect of the consumption of the probiotic B. infantis on ethanol withdrawal symptoms in planaria (Dugesia dorotocephala)
Alcohol use disorder is a chronic, relapsing disease that affects millions of Americans every day. There are limited treatment options for alcohol dependence and alcohol withdrawal symptoms, including depression and anxiety. Previous studies have shown that probiotics can decrease depression in rodents during maternal separation and anxiety in humans. Therefore, we hypothesized that the ethanol-withdrawn planaria who consumed probiotics would have decreased withdrawal symptoms as measured by increased motility compared to the ethanol-withdrawn planaria that were not fed probiotics. The ethanol-withdrawn planaria had a statistically significant decrease in motility compared to the control group, while the planaria that consumed probiotics had no statistically significant change in motility compared to the control group.
Read More...The Effect of Poverty on Mosquito-borne Illness Across the United States
Mosquito-borne diseases are a major issue across the world, and the objective for this project was to determine the characteristics that make some communities more susceptible to these diseases than others. The authors identified and studied characteristics that make communities susceptible to mosquito-borne diseases, including water in square miles, average temperature, population, population density, and poverty rates per county. They found that the population of a county is the best indicator of the prevalence of mosquito-borne diseases.
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