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This study examined the ability of copper and copper alloy surfaces to inhibit bacterial growth, which may be help prevent healthcare-associated infections. The authors exposed two non-pathogenic strains of bacteria to different metal plates for varying degrees of time and measured bacterial growth.

In this study, the authors test whether providing a larger dataset of glass transition temperatures (T_g) to train the machine-learning platform Polymer Genome would improve its accuracy. Polymer Genome is a machine learning based data-driven informatics platform for polymer property prediction and T_g is one property needed to design new polymers in silico. They found that training the model with their larger, curated dataset improved the algorithm's T_g, providing valuable improvements to this useful platform.

Energy efficiency is becoming more important as we struggle to find better, more sustainable energy sources to power our planet; the car industry is no exception. In this article, the authors examine the effect of shape on automobile aerodynamics By finding the shape that makes cars less resistant to wind, and therefore more energy efficient, can help the automobile industry make better, more eco-friendly cars that are also cheaper to operate.

In this work, the authors develop an algorithm that solves the problem of efficient space travel between planets. This is a problem that could soon be of relevance as mankind continues to expand its exploration of outer space, and potentially attempt to inhabit it.

Textile waste from the fashion industry is a major environmental pollutant, but recycling waste into novel building material is a strategy to reduce the negative effects. This manuscript characterized five different binders that can be used to repurpose textile waste into bricks for construction purposes. Water-based glue, cement, white cement, plaster of Paris, and epoxy resin were mixed with shredded textile waste, and the mechanical characteristics and thermal insulation of each brick type were measured. Bricks with increased mechanical strength had the poorest thermal resistance, and the contrasting properties would suit different building purposes. This work provides a first step in generating recycled textile bricks for construction in a circular economy framework.

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.

Here the authors investigated the effects of natural coagulants on reducing the turbidity of water samples from the Tennessee River Watershed. They found that turbidity reduction was higher at lower temperatures for eggshells. They then projected and mapped turbidity reactions under two climate change scenarios and three future time spans for eggshells. They found site-specific and time-vary turbidity reactions using natural coagulants could be useful for optimal water treatment plans.

Droughts have a wide range of effects, from ecosystems failing and crops dying, to increased illness and decreased water quality. Drought prediction is important because it can help communities, businesses, and governments plan and prepare for these detrimental effects. This study predicts drought conditions by using predictable weather patterns in machine learning models.

This assessed the hypothesis that stars in wide binary systems are chemically homogeneous because of their shared origin. Abundances of the HIP 34407/HIP 34426 binary were obtained by analyzing high-resolution spectra of the system. Discrepancies found in the system’s elemental abundances might be an indicator of the presence of rocky planets around this star. Thus, the differences found in chemical composition might demonstrate limitations in the assumptions of chemical tagging.

Rhizopus stolonifer is a mold commonly found growing on bread that can cause many negative health effects when consumed. Preservatives are the well-known answer to this problem; however, many preservatives are not naturally found in food, and some have negative health effects of their own. We focused on honey as a possible solution because of its natural origin and self-preservation ability. We hypothesized that honey would decrease the growth rate of R. stolonifer . We evaluated the honey with a zone of inhibition (ZOI) test on agar plates. Sabouraud dextrose agar was mixed with differing volumes of honey to generate concentrations between 10.0% and 30.0%. These plates were then inoculated with a solution of spores collected from the mold. The ZOI was measured to determine antifungal effectiveness. A statistically significant difference was found between the means of all concentrations except for 20.0% and 22.5%. Our findings support the hypothesis as we showed a positive correlation between the honey concentration and growth rate of mold. By using this data, progress could be made on an all-natural, honey-based preservative.