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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 identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.

Although commonly associated with cryptocurrency, blockchains offer security that other databases could benefit from. These student authors tested a blockchain database framework, and by tracking runtime of four independent variables, they prove this framework is feasible for application.

Wearing face masks has become a common occurrence in everyday life and during athletics due to the spread of diseases. This study tested if masks would affect blood percent saturation of hemoglobin (SpO₂) during treadmill exercise. The data analysis showed that mask type, time, and the interaction of mask type and time were significant results, regardless of physical ability. These results may assist athletes in understanding the differences between training and competing with and without a mask.

In this study, the authors investigate the relationship between iron/hydrogen ratio [Fe/H] of a type of variable stars commonly used as reference points RR Lyrae stars and their light curves to see if one can determine the composition of these stars solely by measuring their light curve characteristics.

Phagocytes feed by forming food vacuoles. In this article the authors investigate the extent that exposure of non-nutritional food, such as India Ink, to Tetrahymena pyriformis affects the number of vacuole formation. These studies provide insight to how organisms budget their energy and metabolic processes during an energy shortage.

In this article, the authors look into what is already known about the factor affecting longevity and determine the importance of behavioral factors including alcohol consumption, smoking, and obesity on longevity. The authors quantify data from over 150 countries and, interestingly, find that the impact each factor has on longevity is at least in part dependent on the country's economic development status. Overall, they conclude that an average person’s life expectancy can increase by more than 3 years if smoking and alcohol consumption is reduced by a half and weight is decreased by 10%.

Many of us take our vision for granted, but rarely do we measure how well we can see. In this study, the authors investigate the ability of people of different ages to read progressively fainter letters in dark light. They find that the ability to see in dim light drops drastically after age 30. The ability to read fainter letters worsens after age 30 as well. These findings should help inform lighting decisions everywhere from restaurants to road signs.

It's time-consuming to complete the calculations that are used to study nuclear reactions and energy. To uncover which computational chemistry tools are useful for this challenge, Pan, Vaiyakarnam, Li, and McMahan investigated whether the Python-based Simulations of Chemistry Framework’s Hartree-Fock (PySCF) method is an efficient and accurate way to assess alkane molecules.

The authors looked at the ability of machine learning algorithms to interpret language given their increasing use in moderating content on social media. Using an explainable model they were able to achieve 81% accuracy in detecting fake vs. real news based on language of posts alone.