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The authors examine the relationships between race, racist beliefs, and perceptions of beauty across cultures and generations.

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.

In this study, the authors conduct a series of experiments within an elevator traveling on an angle to determine if Einstein's Equivalency Principle and motion vector decomposition can be used to calculate the angle of inclination.

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.

This study explores how different economic sectors, geographic regions, and greenhouse gas types might affect future global mean surface temperature (GMST) anomalies differently from historical patterns. Using the Finite Amplitude Impulse Response (FaIR) model and four Shared Socioeconomic Pathways (SSPs) — SSP126, SSP245, SSP370, and SSP585 — the research reveals that future contributions to GMST anomalies.