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Quantitative analysis and development of alopecia areata classification frameworks

Dubey et al. | Jun 03, 2024

Quantitative analysis and development of alopecia areata classification frameworks

This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.

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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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Impact of gadodiamide (Omniscan) on a beef liver catalase ex vivo model

Hirsch et al. | Mar 10, 2023

Impact of gadodiamide (Omniscan) on a beef liver catalase <em>ex vivo</em> model
Image credit: Marcelo Leal

Here, seeking to better understand the effects of gadolinium-based contrast agents, dyes typically used for MRI scans, the authors evaluated the activity of catalase found in beef liver both with and without gadodiamide when exposed to hydrogen peroxide. They found that gadioamide did not significantly inhibit catalase's activity, attributing this lack of effects to the chelating agent found in gadodiamide.

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The comparative effect of remote instruction on students and teachers

Ng et al. | Jan 16, 2022

The comparative effect of remote instruction on students and teachers

In this study, high school students and teachers responded to a survey consisting of Likert-type scale, multiple-choice, and open-ended questions regarding various aspects of remote instruction. After analyzing the data collected, they found that remote learning impacted high school students academically and socially. Students took longer to complete assignments, and both students and teachers felt that students do not learn as much in remote learning compared to in-person instruction. However, most high school students demonstrated a comprehensive understanding of the topics, and an overall negative impact on students' grades was not detected.

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Towards an Integrated Solution for Renewable Water and Energy

Chen et al. | Jan 09, 2015

Towards an Integrated Solution for Renewable Water and Energy

An integrated plant that would generate energy from solar power and provide clean water would help solve multiple sustainability issues. The feasibility of such a plant was investigated by looking at the efficacy of several different modules of such a plant on a small scale.

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The determinants and incentives of corporate greenhouse gas emission reduction

Liu et al. | Jun 04, 2021

The determinants and incentives of corporate greenhouse gas emission reduction

This study used hand-collected Greenhouse gas (GHG) emissions data from the Environmental Protection Agency (EPA) and aimed to understand the determinants and incentives of GHG emissions reduction. It explored how companies’ financials, Chief Executive Officer (CEO) compensation, and corporate governance affected GHG emissions. Results showed that companies reporting GHG emissions were wide-spread among the 48 industries represented by two-digit Standard Industrial Classification (SIC) codes.

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