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Machine learning predictions of additively manufactured alloy crack susceptibilities

Gowda et al. | Nov 12, 2024

Machine learning predictions of additively manufactured alloy crack susceptibilities

Additive manufacturing (AM) is transforming the production of complex metal parts, but challenges like internal cracking can arise, particularly in critical sectors such as aerospace and automotive. Traditional methods to assess cracking susceptibility are costly and time-consuming, prompting the use of machine learning (ML) for more efficient predictions. This study developed a multi-model ML pipeline that predicts solidification cracking susceptibility (SCS) more accurately by considering secondary alloy properties alongside composition, with Random Forest models showing the best performance, highlighting a promising direction for future research into SCS quantification.

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The optical possibilities of gelatin

Parikh et al. | Mar 28, 2024

The optical possibilities of gelatin
Image credit: Lensabl

Here the authors investigated the optical possibilities of gelatin and acrylic in regards to potential implementations at soft contact lenses. They fabricated lenses of different shapes and evaluated the refraction of laser light finding that gelatin needed to be thickened or increased in curvature to account for its lower refractive index compared to plastics, or used in a mixture to strengthen the lens.

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An evaluation of the trends in U.S. maternal deaths based on abortion policies from 2018 to 2021

Haq et al. | Feb 18, 2026

An evaluation of the trends in U.S. maternal deaths based on abortion policies from 2018 to 2021

Here the authors evaluate the relationship between state-level abortion policies and maternal mortality across the United States from 2018 to 2021. Their findings reveal that states with restrictive abortion laws consistently experienced higher maternal mortality ratios than those with protective policies, culminating in a 72% increase in deaths within restrictive states by the end of the study period.

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Two Wrongs Could Make a Right: Food Waste Compost Accelerated Polystyrene Consumption of Tenebrio molitor

Fu et al. | Jul 13, 2020

Two Wrongs Could Make a Right: Food Waste Compost Accelerated Polystyrene Consumption of <em>Tenebrio molitor</em>

Expanded polystyrene (EPS) is a plastic used to make food containers and packing materials that poses a threat to the environment. Mealworms can degrade EPS, but at a slow rate. Here, researchers assessed the impact of food waste compost and oats on the speed of EPS consumption by mealworms, superworms, and waxworms. A positive correlation was found between food waste compost supplementation and EPS consumption, especially by mealworms, indicating a potential industrial application.

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Formation and sticking of air bubbles in water in d-block containers

Gupta et al. | Jun 21, 2021

Formation and sticking of air bubbles in water in d-block containers

Bubbles! In this study, the authors investigate the effects that different materials, temperature, and distance have on the formation of water bubbles on the surface of copper and steel. They calculated mathematical relations based on the outcomes to better understand whether interstitial hydrogen present in the d-block metals form hydrogen bonds with the water bubbles to account for the structural and mechanical stability.

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Determining viability of image processing models for forensic analysis of hair for related individuals

Wang et al. | Feb 04, 2025

Determining viability of image processing models for forensic analysis of hair for related individuals
Image credit: Taylor Smith

Here, the authors used machine learning to analyze microscopic images of hair, quantifying various features to distinguish individuals, even within families where traditional DNA analysis is limited. The Discriminant Analysis (DA) model achieved the highest accuracy (88.89%) in identifying individuals, demonstrating its potential to improve the reliability of hair evidence in forensic investigations.

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