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.

Natural selection shapes the evolution of all organisms, and one question of interest is whether natural selection will reach a "stopping point": a stable, ideal, value for any particular trait. Madhan and Kanagavel tackle this question by building a computer simulation of trait evolution in organisms.

In this study, with consideration for the increasing participation of high school students in indoor rowing, the authors analyzed World Indoor Rowing Championship data. Statistical analysis revealed two key features that can determine the performance of a rower as well as increasing competitiveness in nearly all categories considered. They conclude by offering a 2000-meter ergometer time distribution that can help junior rowers assess their current performance relative to the world competition.

Here the authors sought to use three machine learning models to predict poverty levels in Cambodia based on available household data. They found teat multilayer perceptron outperformed the other models, with an accuracy of 87 %. They suggest that data-driven approaches such as these could be used more effectively target and alleviate poverty.

One largely untapped source of clean energy is the use of osmotic gradients where freshwater and saltwater are mixed, for example at estuaries. To harness such energy, charge-selective membranes are needed to separate the anions and cations in saltwater, establishing an electric potential like a battery. The objective of this study was twofold: to investigate the creation of the polymer matrix and test the properties of boron nitride nanotubes, as both are essential in the creation of an ion-selective membrane. Out of three polymer samples tested in this study, the mixture known as Soltech 704 showed the best resistance to etching, as well as the highest UV cure rate.

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.

This article describes the relationship between socioeconomic factors and the extent of how the COVID-19 Pandemic affected communities. Factors such as infection rate, vaccination rate, and economic status were all evaluated within the context of this article.

Rising atmospheric carbon dioxide levels are projected to lead to a 0.3- 0.4 unit decrease in ocean surface pH levels over the next century. In this study, the authors investigate the effect of pH change on the mass of calcified exoskeletons of common aquatic organisms found in South Florida coastal waters.

In this study, the authors investigate the antibacterial efficacy of penicillin G and its analogs amoxicillin, carbenicillin, piperacillin, cloxacillin, and ampicillin, against four species of bacteria. Results showed that all six penicillin-type antibiotics inhibit Staphylococcus epidermidis, Escherichia coli, and Neisseria sicca with varying degrees of efficacy but exhibited no inhibition against Bacillus cereus. Penicillin G had the greatest broad-spectrum antibacterial activity with a high radius of inhibition against S. epidermidis, E. coli, and N. sicca.

Here, the authors sought to develop a new metric to evaluate the efficacy of baseball pitchers using machine learning models. They found that the frequency of balls, was the most predictive feature for their walks/hits allowed per inning (WHIP) metric. While their machine learning models did not identify a defining trait, such as high velocity, spin rate, or types of pitches, they found that consistently pitching within the strike zone resulted in significantly lower WHIPs.