In this study, the authors conduct a bibliometric analysis to understand the recent growth in and current state of peripheral nerve regeneration research. They also explored potential future studies.

Climate change has contributed to the increasing annual temperatures around the world and poses a grave threat to Maize crops. Two methods proven to help combat plant drought stress effects are presoaking seeds (seeds are soaked in a liquid before planting) and the application of Acetic Acid (vinegar) to soil. The purpose of this experiment was to explore if combining these two methods by presoaking seeds with a vinegar solution can improve the seed development and plant drought tolerance of Maize plants during drought conditions.

Coronary heart disease (CHD) is a global disease that causes fatal buildup of plaque in the arteries. Currently stents are placed in the artery for many patients with CHD to support proper blood flow. Here, the authors build a system to explore how the shape of the stent affects blood flow rate, a finding that can help optimize stents for patients.

The authors looked at using genetic algorithms to look at the Indian labor market and what features might best explain any variation seen. They found that features such as economic growth and household consumption, among others, best explained variation.

This study hypothesized that a machine learning model could accurately predict the severity of California wildfires and determine the most influential meteorological factors. It utilized a custom dataset with information from the World Weather Online API and a Kaggle dataset of wildfires in California from 2013-2020. The developed algorithms classified fires into seven categories with promising accuracy (around 55 percent). They found that higher temperatures, lower humidity, lower dew point, higher wind gusts, and higher wind speeds are the most significant contributors to the spread of a wildfire. This tool could vastly improve the efficiency and preparedness of firefighters as they deal with wildfires.

Based on the success of deep learning, recent works have attempted to develop a waste classification model using deep neural networks. This work presents federated learning (FL) for a solution, as it allows participants to aid in training the model using their own data. Results showed that with less clients, having a higher participation ratio resulted in less accuracy degradation by the data heterogeneity.

This study utilizes machine learning models to predict missing and unclear signs from the Indus script, a writing system from an ancient civilization in the Indian subcontinent.

Berberine is a natural quaternary alkaloid that has anti-microbial and anti-cancer effects. This compound can bind to Guanine Quadruplex (G4) DNA secondary complexes to help inhibit cancer cell proliferation. In this study, the authors investigate whether incorporating large aromatic rings helps to stabilize berberine-G4 interactions.

Powered by the sociological framework that exposure to television bleeds into social biases, limiting media representation of women and minority groups may lead to real-world implications and manifestations of racial and gender disparities. To address this phenomenon, the researchers in this article take a look at primetime fictional representation of minorities and women as lawyers and physicians and compare television representation to census data of the same groups within real-world legal and medical occupations. The authors maintain the hypothesis that representation of female and minority groups as television lawyers and doctors is lower than that of their white male counterparts relative to population demographics - a trend that they expect to also be reflected in actual practice. With fictional racial and gender inequalities and corresponding real-world trends highlighted within this article, the researchers call for address towards representation biases that reinforce each other in both fictional and non-fictional spheres.

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.