Impact of carbon tax and dividend on financial security
Read More...Analyzing carbon dividends’ impact on financial security via ML & metaheuristic search
Impact of carbon tax and dividend on financial security
Read More...Using NLP to ascertain changes in the fast-fashion industry based on UN sustainable development goals
Here, the authors sought to evaluate the efforts of fast fashion clothing companies towards sustainability, specifically in regards to the United Nations Sustainable Development Goals. The authors used natural language processing to investigate the sustainability reports of fast fashion companies focusing on terms established by the UN. They found that the most consistently addressed areas were related to sustainable consumption/production, with a focus on health and well-being emerging during the recent pandemic.
Read More...The impacts of different Al(NO3)3 concentrations on the mitotic index of Allium sativum
Recognizing the increasing threat of acid deposition inn soil through the reaction of NOx and SO2 pollutants with water in Spain, the authors investigates the effects of Al(NO3)3 concentrations on the health of Allium sativum. By tracking its mitotic index, they found a negative exponential correlation between Al(NO3)3 concentrations and the mitotic index of A. sativum.
Read More...Milkweed sustainability in the Sonoran Desert: A. erosa is more water-efficient compared to two other species
This study assesses the capacity for milkweed species, an important host plant for Monarch butterflies, to grow in desert environments with different water levels.
Read More...Biowaste to Biofuel: Using Methane-Producing Microorganisms Found in Soil Samples from Local Wetlands
Methane is a naturally-occurring gas that could be utilized as a renewable source of energy. In this study, authors isolated microorganisms from the Puget Sound region that could produce methane biofuel from composted waste.
Read More...Exploring Political Discourse Among High School Journalists with Web Scraping and AI Technology
Here the authors provided greater coverage of adolescent stances by investigating the political perspectives and trends of high school journalists, utilizing web scraping methods and artificial intelligence (ChatGPT-4o) to analyze over 153,000 articles. They found that high school publications exhibit lower levels of political polarization compared to mainstream media and that journalists' views, while tending to lean moderately liberal, showed no significant correlation with local voting patterns.
Read More...Changing public opinions on genetically modified organisms through access to educational resources
Genetically modified organisms (GMOs) are crops or animals that have been genetically engineered to express a certain physical or biological characteristic and have various benefits that have made them become increasingly popular. However, the public has had mixed reactions to the use of GMOs, with some skeptical of their safety. The purpose of this study was to evaluate how opinions on genetically modified foods can change from exposure to small amounts of information
Read More...Linearity of piezoelectric response of electrospun polymer-based (PVDF) fibers with barium titanate nanoparticles
Here, seeking to develop an understanding of the properties that determine the viability of piezoelectric flexible materials for applications in electro-mechanical sensors, the authors investigated the effects of the inclusion BaTiO3 nanoparticles in electrospun Polyvinyledene Fluoride. They found the voltage generated had a piecewise linear dependence on the applied force at a few temperatures.
Read More...The Effects of Ocean Acidification on the food location behavior and Locomotion of Pagurus Longicarpus
Increasing levels of atmospheric carbon dioxide is slowly acidifying our oceans. Here the authors test the effects of ocean acidification on the ability of hermit crabs (P. longicarpus) to find food. Though no statistically significant changes in food finding were observed, the data suggest a trend toward different activity.
Read More...Monitoring drought using explainable statistical machine learning models
Droughts have a wide range of effects, from ecosystems failing and crops dying, to increased illness and decreased water quality. Drought prediction is important because it can help communities, businesses, and governments plan and prepare for these detrimental effects. This study predicts drought conditions by using predictable weather patterns in machine learning models.
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