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This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.

The authors look at using publicly available data and machine learning to see if they can develop a criminal activity index for counties within the state of California.

The authors use the Lanczos algorithm to computationally solve the Schrodinger equation for 2D potentials with a Python program

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.

We hypothesize that berberine has broad-spectrum antibacterial properties, along with potency that is comparable to current broad-spectrum antibiotics that are commercially available. Here, we screened berberine against four strains of bacteria and evaluated its antimicrobial activity against five broad-spectrum antibiotics from different classes to better quantify berberine’s antibacterial activity and compare its efficacy as an antibacterial agent to the broad-spectrum antibiotics. Our results indicated that berberine had strain-selective cytotoxic effects and was significantly less potent than most of the broad-spectrum antibiotics

Here the authors investigate the effects of plastic pollutants on terrestrial life. Specifically they look at the growth of Brassica rapa and determine that phosphate levels have the most negative impact on growth.

Surface tension and viscosity are both measures of how "sticky" a liquid is, but are they related? The authors here investigate the surface tension and viscosity of mixtures of water with different concentrations of agar agar, flour, or detergent. Surprisingly, they find that the least viscous mixtures had the strongest surface tensions, indicating that the two properties are not linked.

The authors looked at student behaviors around disposal of face masks. The goal of the study was to bring awareness to improper mask disposal and how the resulting litter contributes to overall environmental pollution.

The authors use machine learning and electroencephalogram data to propose a method for improving epilepsy diagnosis.