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Autonomous drone imaging combined with machine learning offers a promising approach for early detection of invasive species. In this study, students built an autonomous drone and compared three models: CNN, SGDC, and XGBoost, to identify Brassica nigra from aerial footage. Their results show that CNNs most effectively recognize key visual features, demonstrating strong potential for supporting conservation and invasive plant management.

The authors investigated adoption rates of solar photovoltaic power at K-12 schools in California.

Here the authors used morphological characters and DNA barcoding to identify arthropods found within a residential house. With this method they identified their species and compared them against pests lists provided by the US government. They found that none of their identified species were considered to be pests providing evidence against the misconception that arthropods found at home are harmful to humans. They suggest that these methods could be used at larger scales to better understand and aid in mapping ecosystems.

Autism Spectrum Disorder (ASD) and Alzheimer's Disease (AD) are distinct conditions, but research suggests a link, as individuals with ASD are 2.5 times more likely to develop AD. A study employing genome-wide association studies and Mendelian randomization revealed shared genetic factors, particularly in synaptic regulation pathways, that may increase the risk of AD in those with ASD. These findings provide insights into the genetic underpinnings connecting the two disorders.

Car emissions harm both the environment and human health, and current U.S. EV tax credits mainly benefit high-income households because EVs are expensive. This study evaluates U.S. vehicle emissions policies by analyzing 2022 national vehicle data to compare the fuel economy and greenhouse gas impacts of the current EV tax credit with a proposed policy that incentivizes hybrid vehicle purchases.

This study explored how green spaces, climate, traffic, and air quality (GCTA) collectively influence asthma-related emergency department visits in the U.S using machine learning models and explainable AI.

Here the authors sought to understand the effects of different variables that may be tied to pollution and climate change on genetic variation of Pacific white-sided dolphins, a species that is currently threatened by water pollution. Based on environmental data collected alongside a genetic distance matrix, they found that ocean currents had the most significant impact on the genetic diversity of Pacific white-sided dolphins along the Japanese coast.

Large corporations often are known for their financial power, but what social and environmental power and conscious do they have? The more responsible corporations are in relation to environmental, social, and governance criteria the better they do fiscally.

Here, the authors sought to investigate the efficiency, cost, and environmental impact of several possible propellants that are or could be used for space flight. By deriving three novel equations, they identified harm, energy, and cost scores for each fuel, suggesting that considering each factor will be essential to the ongoing growth of the space industry.

In this study, the authors look into some of the implications of rising carbon dioxide levels by studying the effects of acidic pH on the ability of T. pyriformis to feed by quantifying phagosome formation and motility.