Counterintuitive in nature, the Mpemba effect asserts that hot liquid freezes faster than cold liquid. While noted throughout history by scientific minds like Aristotle, the phenomenon remains in contention with varying hypotheses for the effect proposed alongside the effect’s rise in popularity. Contributing to the research efforts surrounding the Mpemba effect, the authors in this article explore the effect in different liquids ranging in physical properties and intermolecular forces to determine potential parameters attributable to producing the Mpemba effect.

Recognizing the need for a method to filter microplastics from polluted water the authors sought to use nonpolar solvents, palm oil and palm kernel oil, to filter microplastics out of model seawater. By relying on the separation of polar and nonpolar solvents followed by freezing the nonpolar solvent, they reported that microplastics could be extracted with percentages ranging from 96.2% to 94.2%. They also provided an estimation to use this method as part of container ships to clean the Pacific Ocean of microplastics.

In this study, the authors design a series of new biaryl small molecules to target and block the binding pocket of the enzyme dihydropteroate synthase, which is important for prokaryotic biosynthesis of folic acid and could serve as better antimicrobial compounds.

Here, in an effort to develop a model to predict future groundwater levels, the authors tested a tree-based automated artificial intelligence (AI) model against other methods. Through their analysis they found that groundwater levels in Texas aquifers are down significantly, and found that tree-based AI models most accurately predicted future levels.

Many species of trees are distributed widely around the world, though not always in a way that makes immediate sense. The authors here use genetic information to help explain the geographic distribution of various conifer species throughout the world.

Here, beginning from an interest in fractals, infinitely complex shapes. The authors investigated the fractal object that results from crumpling a sheet of paper. They determined its fractal dimension using continuous Chi-squared analysis, thereby testing and validating their model against the more conventional least squares analysis.

In this study, the authors investigated the antimicrobial properties of the tree species, Populus balsamifera. It was observed that the extract of the buds of P. balsamifera was highly effective against gram-positive bacteria. This helps to indicate the potential use of P. balsamifera in the medical field to eliminate gram-positive bacteria.

Medicinal plants could be a good source of medication to combat antibiotic resistance. Dombeya wallichii, which is commonly called Pink Ball Tree in the family Sterculiaceae, has been documented to have medicinal potential. We observed the highest antibacterial activity in the stem extracts, followed by leaf and bark extracts. The extracts were more effective against tested Gram-positive bacteria when compared with Gram-negative strains.

Over the last few decades, childhood stunting has persisted as a major global challenge. This study hypothesized that TPTO (Tree-based Pipeline Optimization Tool), an AutoML (automated machine learning) tool, would outperform all pre-existing machine learning models and reveal the positive impact of economic prosperity, strong familial traits, and resource attainability on reducing stunting risk. Feature correlation plots revealed that maternal height, wealth indicators, and parental education were universally important features for determining stunting outcomes approximately two years after birth. These results help inform future research by highlighting how demographic, familial, and socio-economic conditions influence stunting and providing medical professionals with a deployable risk assessment tool for predicting childhood stunting.

Access to green space—an area of grass, trees, or other vegetation set apart for recreational or aesthetic purposes in an urban environment—and clean drinking water can be unequally distributed in urban spaces, which are often associated with income inequality. Little is known about public drinking water and green space inequities in the Bay Area. For our study, we sought to understand how public park access, drinking fountain access, and the quality of public drinking water differ across income brackets in the Bay Area. Though we observed smaller-scale instances of inequalities, in the park distribution in the Bay Area as a whole, and in the Southern Bay’s water quality and park distribution, our results indicate that other factors could be influencing water quality, and park and fountain access in the Bay Area.