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A comparative study on the suitability of virtual labs for school chemistry experiments

Praveen et al. | Aug 22, 2022

A comparative study on the suitability of virtual labs for school chemistry experiments

Virtual labs have been gaining popularity over the last few years, especially during the worldwide lockdown due to the COVID-19 pandemic. In this study, the suitability of virtual labs for school chemistry experiments is addressed and their effectiveness is compared to traditional physical lab experiments by focusing on physical and human resources, convenience, cost, safety, and time involved as well as topic "matter".

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Antibacterial activity by Dombeya wallichii plant extracts obtained by ultrasound-assisted extraction

Herur et al. | Nov 13, 2023

Antibacterial activity by <em>Dombeya wallichii</em> plant extracts obtained by ultrasound-assisted extraction

Medicinal plants could be a good source of medication to combat antibiotic resistance. Dombeya wallichii, which is commonly called Pink Ball Tree in the family Sterculiaceae, has been documented to have medicinal potential. We observed the highest antibacterial activity in the stem extracts, followed by leaf and bark extracts. The extracts were more effective against tested Gram-positive bacteria when compared with Gram-negative strains.

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Predicting the factors involved in orthopedic patient hospital stay

D’Souza et al. | Dec 13, 2023

Predicting the factors involved in orthopedic patient hospital stay
Image credit: Pixabay

Long hospital stays can be stressful for the patient for many reasons. We hypothesized that age would be the greatest predictor of hospital stay among patients who underwent orthopedic surgery. Through our models, we found that severity of illness was indeed the highest factor that contributed to determining patient length of stay. The other two factors that followed were the facility that the patient was staying in and the type of procedure that they underwent.

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The Effect of Bead Shape and Texture on the Energy Loss Characteristics in a Rotating Capsule

Misra et al. | Jan 25, 2019

The Effect of Bead Shape and Texture on the Energy Loss Characteristics in a Rotating Capsule

Industrial process are designed to optimize speed, energy use and quality. Some steps involve the translation of product-filled barrels, how far and fast this happens depends on the properties of the product within. This article investigates such properties on a mini-scale, where the roll of bead size, texture and material on the distance travelled by a cylindrical capsule is investigated.

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Applying centrality analysis on a protein interaction network to predict colorectal cancer driver genes

Saha et al. | Nov 18, 2023

Applying centrality analysis on a protein interaction network to predict colorectal cancer driver genes

In this article the authors created an interaction map of proteins involved in colorectal cancer to look for driver vs. non-driver genes. That is they wanted to see if they could determine what genes are more likely to drive the development and progression in colorectal cancer and which are present in altered states but not necessarily driving disease progression.

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Can the attributes of an app predict its rating?

Feng et al. | Jul 03, 2024

Can the attributes of an app predict its rating?
Image credit: Mika Baumeister

In this article the authors looked at different attributes of apps within the Google Play store to determine how those may impact the overall app rating out of five stars. They found that review count, amount of storage needed and when the app was last updated to be the most influential factors on an app's rating.

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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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