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Developing a neural network to model the mechanical properties of 13-8 PH stainless steel alloy

Zeng et al. | Sep 10, 2023

Developing a neural network to model the mechanical properties of 13-8 PH stainless steel alloy
Image credit: Pixabay

We systematically evaluated the effects of raw material composition, heat treatment, and mechanical properties on 13-8PH stainless steel alloy. The results of the neural network models were in agreement with experimental results and aided in the evaluation of the effects of aging temperature on double shear strength. The data suggests that this model can be used to determine the appropriate 13-8PH alloy aging temperature needed to achieve the desired mechanical properties, eliminating the need for many costly trials and errors through re-heat treatments.

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Antibacterial Effects of Copper Surfaces

Mulukutla et al. | May 19, 2020

Antibacterial Effects of Copper Surfaces

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.

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A comparison of use of the mobile electronic health record by medical providers based on clinical setting

Stover et al. | Jul 12, 2023

A comparison of use of the mobile electronic health record by medical providers based on clinical setting
Image credit: Tima Miroshnichenko

The electronic health record (EHR), along with its mobile application, has demonstrated the ability to improve the efficiency and accuracy of health care delivery. This study included data from 874 health care providers over a 12-month period regarding their usage of mobile phone (EPIC® Haiku) and tablet (EPIC® Canto) mEHR. Ambulatory and inpatient care providers had the greatest usage levels over the 12-month period. Awareness of workflow allows for optimization of mEHR design and implementation, which should increase mEHR adoption and usage, leading to better health outcomes for patients.

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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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Using machine learning to develop a global coral bleaching predictor

Madireddy et al. | Feb 21, 2023

Using machine learning to develop a global coral bleaching predictor
Image credit: Madireddy, Bosch, and McCalla

Coral bleaching is a fatal process that reduces coral diversity, leads to habitat loss for marine organisms, and is a symptom of climate change. This process occurs when corals expel their symbiotic dinoflagellates, algae that photosynthesize within coral tissue providing corals with glucose. Restoration efforts have attempted to repair damaged reefs; however, there are over 360,000 square miles of coral reefs worldwide, making it challenging to target conservation efforts. Thus, predicting the likelihood of bleaching in a certain region would make it easier to allocate resources for conservation efforts. We developed a machine learning model to predict global locations at risk for coral bleaching. Data obtained from the Biological and Chemical Oceanography Data Management Office consisted of various coral bleaching events and the parameters under which the bleaching occurred. Sea surface temperature, sea surface temperature anomalies, longitude, latitude, and coral depth below the surface were the features found to be most correlated to coral bleaching. Thirty-nine machine learning models were tested to determine which one most accurately used the parameters of interest to predict the percentage of corals that would be bleached. A random forest regressor model with an R-squared value of 0.25 and a root mean squared error value of 7.91 was determined to be the best model for predicting coral bleaching. In the end, the random model had a 96% accuracy in predicting the percentage of corals that would be bleached. This prediction system can make it easier for researchers and conservationists to identify coral bleaching hotspots and properly allocate resources to prevent or mitigate bleaching events.

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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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Correlation of socioeconomic status and lead concentration in tap water in Missouri

Rabbani et al. | Feb 03, 2022

Correlation of socioeconomic status and lead concentration in tap water in Missouri

Organic and non-organic contaminants in tap water have been linked to adverse health effects. Tap water is a major source of lead, which is neurotoxic and poses a major health risk, particularly to children and pregnant women. Using publicly available annual water quality reports data for the state of Missouri, the authors show that communities with lower median household income and lower per capita incomes had significantly higher lead levels in their tap water.

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Investigating the Role of Biotic Factors in Host Responses to Rhizobia in the System Medicago truncatula

Rathod et al. | Jan 22, 2019

Investigating the Role of Biotic Factors in Host Responses to Rhizobia in the System Medicago truncatula

Nitrogen-fixing bacteria, such as the legume mutualist rhizobia, convert atmospheric nitrogen into a form that is usable by living organisms. Leguminous plants, like the model species Medicago truncatula, directly benefit from this process by forming a symbiotic relationship with rhizobia. Here, Rathod and Rowe investigate how M. truncatula responds to non-rhizobial bacterial partners.

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