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Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

Sirohi et al. | Sep 25, 2022

Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

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.

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Correlates of Sugar Consumption Among High School Students and Faculty

McBurnett et al. | Mar 07, 2019

Correlates of Sugar Consumption Among High School Students and Faculty

The availability, portion sizes, and consumption of highly palatable food has been linked adverse health outcomes. McBurnett and O’Donnell sought to assess the relationship between reward-based eating drive, consumption, cravings, and knowledge of the effects of sugary foods. In this study population, reward-based eating drive was related to both consumption and cravings. Further, for females, the knowledge of sugar’s effects was significantly and inversely associated with its consumption.

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The Role of Race in the Stereotyping of a Speaker’s Accent as Native or Non-native

Bhuvanagiri et al. | Jan 07, 2019

The Role of Race in the Stereotyping of a Speaker’s Accent as Native or Non-native

In the modern world, communication and mobility are no longer obstacles. A natural consequence is that people from all over the world are mixing like never before and national identity can no longer be determined simply by a person's appearance or manner of speech. In this article, the authors study how a person's accent interferes with the perception of a their national identity and proposes ways to eliminate such biases.

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The Effect of Ultraviolet Radiation and the Antioxidant Curcumin on the Longevity, Fertility, and Physical Structure of Drosophila melanogaster: Can We Defend Our DNA?

Lateef et al. | May 18, 2019

The Effect of Ultraviolet Radiation and the Antioxidant Curcumin on the Longevity, Fertility, and Physical Structure of <em>Drosophila melanogaster</em>: Can We Defend Our DNA?

Ultraviolet (UV) radiation is known to alter DNA structure and impair cellular function in all living organisms. In this study, Lateef et al examine the effects of UV radiation to determine whether antioxidant-enriched nutrition can combat the potential deleterious effects of UV radiation on Drosophila melanogaster. They found that UVB (320nm) radiation caused a 59% decrease in the Drosophila lifespan and mutagenic effects on flies' physical appearance, but did not significantly affect fertility. Curcumin significantly prolonged lifespan and enhanced fertility for both UV- and non-UV-exposed flies. The research demonstrates the positive potential of natural antioxidants as weapons against radiation-induced diseases including cancer.

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Blue light blocking glasses: do they do what they promise?

Lee et al. | Dec 13, 2023

Blue light blocking glasses: do they do what they promise?
Image credit: nacer eddine

With increased screen time and exposure to blue light, an increasing number of people have sleep deprivation. Blue light suppresses the release of melatonin and hinders sleep at night. We hypothesized that people could get a greater amount of sleep by controlling the blue light exposure from screen time before bedtime. BBG’s effect on reducing time to fall asleep was significant within the teenage group, but not significant in the adult group. This indicated that BBG could improve the time taken to sleep for young teenagers post screen time in the evening.

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Firearm-purchase laws that limit the number of guns on the market reduce gun homicides in the South Side of Chicago

Krishnan et al. | Jan 24, 2022

Firearm-purchase laws that limit the number of guns on the market reduce gun homicides in the South Side of Chicago

Gun violence has been a serious issue in the South Side of Chicago for a long time. To intervene, regulators have passed legislation they hoped to curb -if not completely eradicate- the issue. However, there is little analysis done on how effective the various laws have been at reducing gun violence. Here the authors explore the association between firearm purchase laws passed between 1993-2018 and the incidence of gun homicide in Chicago's South Side. Their analysis suggests that some laws have been more effective than others, while some might have exacerbated the issue. However, they do not consider other contributing factors, which makes it difficult to prove causation without further investigation.

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Leveraging E-Waste to Enhance Water Condensation by Effective Use of Solid-state Thermoelectric Cooling

Joshi et al. | Dec 02, 2020

Leveraging E-Waste to Enhance Water Condensation by Effective Use of Solid-state Thermoelectric Cooling

Water scarcity affects upwards of a billion people worldwide today. This project leverages the potential of capturing humidity to build a high-efficiency water condensation device that can generate water and be used for personal and commercial purposes. This compact environment-friendly device would have low power requirements, which would potentially allow it to utilize renewable energy sources and collect water at the most needed location.

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Utilizing meteorological data and machine learning to predict and reduce the spread of California wildfires

Bilwar et al. | Jan 15, 2024

Utilizing meteorological data and machine learning to predict and reduce the spread of California wildfires
Image credit: Pixabay

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.

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