Browse Articles

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.

In this study, the authors investigate the demographic indicators for voter shift between the 2016 and 2020 presidential elections based on demographic data put through a K-nearest neighbors classification algorithm and Principal Component Analysis.

Research relating to freshwater acidification is minimal, so the impact of aquatic plants, Anubias barteri var. congensis and Anubias barteri var. nana, on minimizing changes in pH was explored in an ecosystem in Northern California. Creek water samples, with and without the aquatic plants, were exposed to dry ice to simulate carbon emissions and the pH was monitored over an eight-hour period. There was a 25% difference in the observed pH based on molar hydrogen ion concentration between the water samples with plants and those without plants, suggesting that aquatic plants have the potential to limit acidification to some extent. These findings can guide future research to explore the viable partial solution of aquatic plants in combating freshwater acidification.

The authors access a panel of leaf traits across ten deciduous tree species to explore adaptive strategies between large and small trees.

The authors assessed the degree of women participation in India's economy as a way to estimate woman's participation in India's economic growth.

Observing transients like supernovae, which have short-lived brightness variations, helps astronomers understand cosmic phenomena. This study analyzed transient 2023jri, hypothesizing it was a Type IIb supernova. By collecting and analyzing data over four weeks, including light and color curves, they confirmed its classification and provided additional insights into this less-studied supernova type.

The authors compare the predicted versus actual geyser eruption times for the Old Faithful and Beehive Geysers at Yellowstone National Park.

Here, in an effort to develop a model to predict future groundwater levels, the authors tested a tree-based automated artificial intelligence (AI) model against other methods. Through their analysis they found that groundwater levels in Texas aquifers are down significantly, and found that tree-based AI models most accurately predicted future levels.

With the advance of technology, artificial intelligence (AI) is now applied widely in society. In the study of AI, machine learning (ML) is a subfield in which a machine learns to be better at performing certain tasks through experience. This work focuses on the convolutional neural network (CNN), a framework of ML, applied to an image classification task. Specifically, we analyzed the performance of the CNN as the type of neural activation function changes.

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.