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The authors studied optimized delivery routes to reduce travel times using different traveling salesman algorithms.

α-amylase breaks down starch into glucose, which can cause blood sugar spikes and increase the risk of type II diabetes. This study tested natural extracts from cassia cinnamon and green tea as alternatives to synthetic inhibitors like acarbose, which can be costly and cause side effects.

To address the limitations in predicting the severity of Atrial Septal Defect (ASD), here the authors utilized a fluid-filled chamber model to quantify the relationship between defect size and right atrial fluid output. The findings confirmed that larger ASD diameters result in a linear increase in fluid output, validating a cost-effective model that can improve clinical prognosis and treatment planning for heart failure risks.

The authors looked at the difference in investing in stock vs. mutual funds.

The authors looked at the ability of berberine in combination with melatonin to have anticancer effects when tested in an in vitro cell model.

The authors compare current machine learning algorithms with a new Explainable AI algorithm that produces a human-comprehensible decision tree alongside predictions.

The authors combine fine needle aspiration biopsy and machine learning algorithms to develop a breast cancer detection method suitable for resource-constrained regions that lack access to mammograms.

The authors created a 1D model to diagnose hepatomegaly and cirrhosis via ultrasound of the liver.

The escalating crisis of climate change, driven by the accumulation of greenhouse gases from human activities, demands urgent and innovative solutions to curb rising global temperatures. Plasma-based methane (CH₄) and carbon dioxide (CO₂) reforming offers a promising pathway for carbon capture and the sustainable production of hydrogen fuel and syngas components. To advance this technology, particularly in terms of energy efficiency and selectivity, it is essential to enhance the conversion efficiencies of CO₂ and CH₄.

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.