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In this article, the authors looked at developing a strategy that would allow for earlier diagnosis of Diabetes as that improves long-term outcomes. They were able to find that BMI, tricep skin fold thickness, and blood pressure are the risk factors with the highest accuracy in predicting diabetes risk.

Metal-organic frameworks (MOFs) are promising new nanomaterials for use in the fight against climate change that can efficiently capture and convert CO₂ to other useful carbon products. This research used computational models to determine the reaction conditions under which MOFs can more efficiently capture and convert CO₂. In a cost-efficient manner, this analysis tested the hypothesis that pressure and temperature affect the efficacy of carbon capture and conversion, and contribute to understanding the optimal conditions for MOF performance to improve the use of MOFs for controlling greenhouse CO₂ emissions.

The authors set out to develop an electrochemical device that would have efficient and sustained carbon dioxide capture.

Here, beginning from an initial interest in the possibility to use a computer to automatically solve a geometry diagram parser, the authors developed their own Fast Geometry Diagram Parser (FastGDP) that uses clustering and corner information. They compared their own methods to a more widely available, method, GeoSolver, finding their own to be an order of magnitude faster in most cases that they considered.

With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.

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.

Water scarcity affects upwards of a billion people worldwide today. This project leverages the potential of capturing humidity to build a high-efficiency water condensation device that can generate water and be used for personal and commercial purposes. This compact environment-friendly device would have low power requirements, which would potentially allow it to utilize renewable energy sources and collect water at the most needed location.

Vibrio fischeri is an amazing species of bacteria that lives symbiotically in the light organ of luminescent bobtail squid. In this study, authors study the strength and optimal conditions for V. fischeri light production, and assess whether this luminescence could be a natural light source comparable to manmade lighting.

The authors looked at the presence of coliform bacteria present in ground beef after cooking it various CDC standards. They found that no coliform bacteria was present when CDC guidelines for cooking ground beef were properly followed.

In this research, a novel bioplastic inclusive of bamboo tannins and chitosan is selected from more than 60 trial formula variations based on resulting strength, fatigue, and transparency attributes. The biodegradability of the finalized bioplastic is compared to that of conventional polyethylene, in addition to investigating its solubility and water absorbance. This research displays the potential of a legitimate, fully biodegradable plastic alternative to current marketplace bioplastics.