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A Crossover Study Comparing the Effect of a Processed vs. Unprocessed Diet on the Spatial Learning Ability of Zebrafish

Banga et al. | Sep 18, 2022

A Crossover Study Comparing the Effect of a Processed vs. Unprocessed Diet on the Spatial Learning Ability of Zebrafish

The authors compared the short-term effects of processed versus unprocessed food on spatial learning and survival in zebrafish, given the large public concern regarding processed foods. By randomly assigning zebrafish to a diet of brine shrimp flakes (processed) or live brine shrimp (unprocessed), the authors show while there is no immediate effect on a fish's decision process between the two diets, there are significant correlations between improved learning and stress response with the unprocessed diet.

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Redesigning an Experiment to Determine the Coefficient of Friction

Hu et al. | Jun 27, 2016

Redesigning an Experiment to Determine the Coefficient of Friction

In a common high school experiment to measure friction coefficients, a weighted mass attached to a spring scale is dragged across a surface at a constant velocity. While the constant velocity is necessary for an accurate measurement, it can be difficult to maintain and this can lead to large errors. Here, the authors designed a new experiment to measure friction coefficients in the classroom using only static force and show that their method has a lower standard deviation than the traditional experiment.

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Tomato disease identification with shallow convolutional neural networks

Trinh et al. | Mar 03, 2023

Tomato disease identification with shallow convolutional neural networks

Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.

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Cathodal Galvanotaxis: The Effect of Voltage on the distribution of Tetrahymena pyriformis

Zheng et al. | Jun 10, 2019

Cathodal Galvanotaxis: The Effect of Voltage on the distribution of <em>Tetrahymena pyriformis</em>

The surface of the unicellular eukaryote, Tetrahymena pyriformis, is covered with thousands of hair-like cilia. These cilia are very similar to cilia of the human olfactory and respiratory tracts making them model organisms for studying cilia function and pathology. The authors of this study investigated the effect of voltage on T. pyriformis galvanotaxis, the movement towards an electrical stimulus. They observed galvanotaxis towards the cathode at voltages over 4V which plateau, indicating opening of voltage gated-ion channels to trigger movement.

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Analysis of biofertilization impacts on Pisum sativum

Holden et al. | May 18, 2023

Analysis of biofertilization impacts on <i>Pisum sativum</i>
Image credit: David Boozer

This study explored the various effects of three different produce-based biofertilizers on pea plant growth, using red apple, pear, strawberry, and control treatments. It was hypothesized that the application of fruit biomatter would increase the growth of pea plants, with the application of strawberry biomatter having the most significant effect due to strawberries containing a higher nutrient content compared to pears and apples. Analysis confirmed the hypothesis. The application of strawberry biomatter could prove to be an effective way to increase plant growth in commercial agriculture.

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DyGS: A Dynamic Gene Searching Algorithm for Cancer Detection

Wang et al. | Jun 05, 2018

DyGS: A Dynamic Gene Searching Algorithm for Cancer Detection

Wang and Gong developed a novel dynamic gene-searching algorithm called Dynamic Gene Search (DyGS) to create a gene panel for each of the 12 cancers with the highest annual incidence and death rate. The 12 gene panels the DyGS algorithm selected used only 3.5% of the original gene mutation pool, while covering every patient sample. About 40% of each gene panel is druggable, which indicates that the DyGS-generated gene panels can be used for early cancer detection as well as therapeutic targets in treatment methods.

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