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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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Significance of Tumor Growth Modeling in the Behavior of Homogeneous Cancer Cell Populations: Are Tumor Growth Models Applicable to Both Heterogeneous and Homogeneous Populations?

Reddy et al. | Jun 10, 2021

Significance of Tumor Growth Modeling in the Behavior of Homogeneous Cancer Cell Populations: Are Tumor Growth Models Applicable to Both Heterogeneous and Homogeneous Populations?

This study follows the process of single-cloning and the growth of a homogeneous cell population in a superficial environment over the course of six weeks with the end goal of showing which of five tumor growth models commonly used to predict heterogeneous cancer cell population growth (Exponential, Logistic, Gompertz, Linear, and Bertalanffy) would also best exemplify that of homogeneous cell populations.

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Rhythmic lyrics translation: Customizing a pre-trained language model using stacked fine-tuning

Chong et al. | May 01, 2023

Rhythmic lyrics translation: Customizing a pre-trained language model using stacked fine-tuning
Image credit: Pixabay

Neural machine translation (NMT) is a software that uses neural network techniques to translate text from one language to another. However, one of the most famous NMT models—Google Translate—failed to give an accurate English translation of a famous Korean nursery rhyme, "Airplane" (비행기). The authors fine-tuned a pre-trained model first with a dataset from the lyrics domain, and then with a smaller dataset containing the rhythmical properties, to teach the model to translate rhythmically accurate lyrics. This stacked fine-tuning method resulted in an NMT model that could maintain the rhythmical characteristics of lyrics during translation while single fine-tuned models failed to do so.

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The effects of early probiotic supplementation on the germination of Arabidopsis thaliana

Gambino et al. | Oct 25, 2020

The effects of early probiotic supplementation on the germination of <em>Arabidopsis thaliana</em>

The use of fertilizers is associated with an increase in soil degradation, which is predicted to lead to a decrease in crop production within the next decade. Thus, it is critical to find solutions to support crop production to sustain the robust global population. In this study, the authors investigate how probiotic bacteria, like Rhizobium leguminosarum, Bacillus subtilis and Pseudomonas fluorescens, can impact the growth of Arabidopsis thaliana when applied to the seeds.They hypothesized that solutions with multiple bacterial species compared to those with only a single bacterial species would promote seed germination more effectively.

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Effects of an Informational Waste Management App on a User’s Waste Disposal Habits

Rao et al. | Apr 28, 2021

Effects of an Informational Waste Management App on a User’s Waste Disposal Habits

While 75% of waste in the United States is stated to be recyclable, only about 34% truly is. This project takes a stance to combat the pillars of mismanaged waste through a modern means of convenience: the TracedWaste app. The purpose of this study was to identify how individuals' waste disposal habits improved and knowledge increased (i.e. correctly disposing of waste, understanding negative incorrect waste disposal) due to their use of an informational waste management app as measured by a survey using a 1-5 Likert Scale. The results showed that the TracedWaste app helped conserve abundant resources such as energy and wood, decrease carbon emissions, and minimize financial toll all through reducing individual impact.

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Deciphering correlation and causation in risk factors for heart disease with Mendelian randomization

Singh et al. | Feb 08, 2023

Deciphering correlation and causation in risk factors for heart disease with Mendelian randomization
Image credit: Robina Weermeijer

Here, seeking to identify the risk of coronary artery disease (CAD), a major cause of cardiovascular disease, the authors used Mendelian randomization. With this method they identified several traits such as blood pressure readings, LDL cholesterol and BMI as significant risk factors. While other traits were not found to be significant risk factors.

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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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An Analysis of the Mathematical Accuracy of Perspective in Paintings

Grewal et al. | Dec 13, 2019

An Analysis of the Mathematical Accuracy of Perspective in Paintings

Here the authors investigate whether there are mathematical inaccuracies of perspective in artists' paintings that are undetectable with our naked eyes. Using the cross-ratio method, they find that there are three significant errors in various famous paintings which increase as the structures in the paintings recede from the viewer.

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