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Reducing Crop Damage Caused by Folsomia candida by Providing an Alternate Food Source

Tamura et al. | May 28, 2018

Reducing Crop Damage Caused by Folsomia candida by Providing an Alternate Food Source

Tamura and Moché found that Folsomia candida, a common crop pest, prefers to consume yeast instead of lettuce seedlings. The authors confirmed that even with the availability of both lettuce seedlings and yeast in the same dish, Folsomia candida preferred to eat the yeast, thereby reducing the number of feeding injuries on the lettuce seedlings. The authors propose that using this preference for yeast may be a way to mitigate crop damage by this pest.

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Analysis of Patterns in the Harmonics of a String with Artificially Enforced Nodes

Jain et al. | Jan 28, 2021

Analysis of Patterns in the Harmonics of a String with Artificially Enforced Nodes

This study examines the higher harmonics in an oscillating string by analyzing the sound produced by a guitar with a spectrum analyzer. The authors mathematically hypothesized that the higher harmonics in the series of the directly excited 2nd harmonic contain the alternate frequencies of the fundamental series, the higher harmonics of the directly excited 3rd harmonic series contain every third frequency of fundamental series, and so on. To test the hypotheses, they enforced artificial nodes to excite the 2nd, 3rd, and 4th harmonics directly, and analyzed the resulting spectrum to verify the mathematical hypothesis. The data analysis corroborates both hypotheses.

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An Analysis of the Density and Patterns of the Solutions of Diophantine Equations of the Third Power

Grewal et al. | Oct 05, 2020

An Analysis of the Density and Patterns of the Solutions of Diophantine Equations of the Third Power

In this study, the authors sought to find out how many mathematical solutions there were to the Indian mathematician Ramanujan's formula, which is a3 + b3 + c3 = d3, and also quantify the densities its solutions. They wrote their own computer program to do so and kept values of a, b, and c less than 10,000. While conducting the analysis, they were also looking for perfect power taxicab numbers and their frequency. They were able to find solutions and densities for the equation. Additionally, while they found that most perfect cube taxicab numbers had a frequency of 2 or 3, they also found on number with a frequency of 42!

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How CAFOs affect Escherichia coli contents in surrounding water sources

Lieberman et al. | Feb 24, 2023

How CAFOs affect <i>Escherichia coli</i> contents in surrounding water sources
Image credit: CDC

Commercial Concentrated Animal Feeding Operations (CAFOs) produce large quantities of waste material from the animals being housed in them. These feedlots found across the United States contain livestock that produce waste that results in hazardous runoff. This study examines how CAFOs affect water sources by testing for Escherichia Coli (E. coli) content in bodies of water near CAFOs.

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How Ya Doin'? with COVID-19

Kung et al. | Dec 02, 2021

How Ya Doin'? with COVID-19

In this study, the authors survey students and adults about how the COVID-19 pandemic has impacted their sleep patterns, eating habits, mood, physical activity, and screen time.

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Influence of Infill Parameters on the Tensile Mechanical Properties of 3D Printed Parts

Guan et al. | Jul 17, 2020

Influence of Infill Parameters on the Tensile Mechanical Properties of 3D Printed Parts

Manufacturers that produce products using fused filament fabrication (FFF) 3D printing technologies have control of numerous build parameters. This includes the number of solid layers on the exterior of the product, the percentage of material filling the interior volume, and the many different types of infill patterns used to fill their interior.This study investigates the hypothesis that as the density of the part increases, the mechanical properties will improve at the expense of build time and the amount of material required.

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The Effect of Varying Training on Neural Network Weights and Visualizations

Fountain et al. | Dec 04, 2019

The Effect of Varying Training on Neural Network Weights and Visualizations

Neural networks are used throughout modern society to solve many problems commonly thought of as impossible for computers. Fountain and Rasmus designed a convolutional neural network and ran it with varying levels of training to see if consistent, accurate, and precise changes or patterns could be observed. They found that training introduced and strengthened patterns in the weights and visualizations, the patterns observed may not be consistent between all neural networks.

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