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Detection and Control of Spoilage Fungi in Refrigerated Vegetables and Fruits

Chari et al. | May 16, 2021

Detection and Control of Spoilage Fungi in Refrigerated Vegetables and Fruits

Food spoilage leads to a significant loss in agricultural produce each year. Here, the authors investigate whether certain essential oils can protect against fungus-mediated spoilage of fruits and vegetables. Their results suggest that the compounds they tested might indeed inhibit fungal growth, at various temperatures, a promising result that could reduce food wasting.

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Time-Efficient and Low-Cost Neural Network to detect plant disease on leaves and reduce food loss and waste

Singh et al. | Apr 24, 2023

Time-Efficient and Low-Cost Neural Network to detect plant disease on leaves and reduce food loss and waste

About 25% of the food grown never reaches consumers due to spoilage, and 11.5 billion pounds of produce from gardens are wasted every year. Current solutions involve farmers manually looking for and treating diseased crops. These methods of tending crops are neither time-efficient nor feasible. I used a convolutional neural network to identify signs of plant disease on leaves for garden owners and farmers.

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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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A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Dey et al. | Oct 31, 2022

A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Intelligent vehicles utilize a combination of video-enabled object detection and radar data to traverse safely through surrounding environments. However, since the most momentary missteps in these systems can cause devastating collisions, the margin of error in the software for these systems is small. In this paper, we hypothesized that a novel object detection system that improves detection accuracy and speed of detection during adverse weather conditions would outperform industry alternatives in an average comparison.

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The influence of experience on the perception of homelessness in individuals

Dua et al. | Jun 30, 2022

The influence of experience on the perception of homelessness in individuals

Economic disruptions and housing instabilities have for long propelled a homelessness epidemic among adults and youth in the United States. The COVID-19 pandemic has accelerated this phenomenon with a 2.2% increase in the number of homeless individuals and more than 70% of Americans fearing this outcome for themselves. This study aimed to analyze the perception of homelessness in two groups: Those who have previously experienced and overcome homelessness and those who are at-risk for experiencing the same. The study analyzed publicly available Reddit posts by people in both groups and found that at-risk individuals tended to associate primarily fearful emotions with the event, and those who had overcome homelessness tended to view the event in a negative context. These results may encourage the establishment of resources to support the currently homeless and help them transition into society, and services to help them cope with negative emotions, as negative attitudes have been shown to decrease life expectancy.

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Molecular Alterations in a High-Fat Mouse Model Before the Onset of Diet–Induced Nonalcoholic Fatty Liver Disease

Lee et al. | Sep 20, 2016

Molecular Alterations in a High-Fat Mouse Model Before the Onset of Diet–Induced Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) is one of the most prevalent chronic liver diseases worldwide, but there are few studied warning signs for early detection of the disease. Here, researchers study alterations that occur in a mouse model of NAFLD, which indicate the onset of NAFLD sooner. Earlier detection of diseases can lead to better prevention and treatment.

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Interaction of light with water under clear and algal bloom conditions

Ramesh et al. | Feb 01, 2024

Interaction of light with water under clear and algal bloom conditions
Image credit: Liz Harrell

Here, recognizing the potential harmful effects of algal blooms, the authors used satellite images to detect algal blooms in water bodies in Wyoming based on their reflectance of near infrared light. They found that remote monitoring in this way may provide a useful tool in providing early warning and advisories to people who may live in close proximity.

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Artificial intelligence assisted violin performance learning

Zhang et al. | Aug 30, 2023

Artificial intelligence assisted violin performance learning
Image credit: Philip Myrtorp

In this study the authors looked at the ability of artificial intelligence to detect tempo, rhythm, and intonation of a piece played on violin. Technology such as this would allow for students to practice and get feedback without the need of a teacher.

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The Development of a Highly Sensitive Home Diagnosis Kit for Group A Streptococcus Bacteria (GAS)

Mai et al. | Dec 05, 2018

The Development of a Highly Sensitive Home Diagnosis Kit for Group A Streptococcus Bacteria (GAS)

In this article, Mai et al. have developed a do-it-yourself kit for the detection of Strep A bacterial infections. While Strep A infections require antibiotic administration, viral infections, which can present with similar symptoms, often resolve on their own. The problem with delayed antibiotic treatment is an increasing risk of complications. Currently an accurate diagnosis requires that patients make the trip to the hospital where sensitive tests can be performed. The method described here, bundled into a commercially available kit, could help speed up the identification of such bacterial infections. When presented with symptoms of a sore throat and fever, you could just buy the kit at your local pharmacy, perform the simple yet highly accurate and sensitive test, and know whether an urgent trip to the doctor's for an antibiotic prescription is necessary. How convenient!

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QuitPuff: A Simple Method Using Saliva to Assess the Risk of Oral Pre-Cancerous Lesions and Oral Squamous Cell Carcinoma in Chronic Smokers

Shamsher et al. | Mar 27, 2019

QuitPuff: A Simple Method Using Saliva to Assess the Risk of Oral Pre-Cancerous Lesions and Oral Squamous Cell Carcinoma in Chronic Smokers

Smoking generates free radicals and reactive oxygen species which induce cell damage and lipid peroxidation. This is linked to the development of oral cancer in chronic smokers. The authors of this study developed Quitpuff, simple colorimetric test to measure the extent of lipid peroxidation in saliva samples. This test detected salivary lipid peroxidation with 96% accuracy in test subjects and could serve as an inexpensive, non-invasive test for smokers to measure degree of salivary lipid peroxidation and potential risk of oral cancer.

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