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Augmented Reality Chess Analyzer (ARChessAnalyzer): In-Device Inference of Physical Chess Game Positions through Board Segmentation and Piece Recognition using Convolutional Neural Networks

Mehta et al. | Jul 17, 2020

Augmented Reality Chess Analyzer (ARChessAnalyzer): In-Device Inference of Physical Chess Game Positions through Board Segmentation and Piece Recognition using Convolutional Neural Networks

In this study the authors develop an app for faster chess game entry method to help chess learners improve their game. This culminated in the Augmented Reality Chess Analyzer (ARChessAnalyzer) which uses traditional image and vision techniques for chess board recognition and Convolutional Neural Networks (CNN) for chess piece recognition.

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Substance Abuse Transmission-Impact of Parental Exposure to Nicotine/Alcohol on Regenerated Planaria Offspring

Bennet et al. | Jul 02, 2024

Substance Abuse Transmission-Impact of Parental Exposure to Nicotine/Alcohol on Regenerated Planaria Offspring

The global mental health crisis has led to increased substance abuse among youth. Prescription drug abuse causes approximately 115 American deaths daily. Understanding intergenerational transmission of substance abuse is complex due to lengthy human studies and socioeconomic variables. Recent FDA guidelines mandate abuse liability testing for neuro-active drugs but overlook intergenerational transfer. Brown planaria, due to their nervous system development similarities with mammals, offer a novel model.

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Expression of Anti-Neurodegeneration Genes in Mutant Caenorhabditis elegans Using CRISPR-Cas9 Improves Behavior Associated With Alzheimer’s Disease

Mishra et al. | Sep 14, 2019

Expression of Anti-Neurodegeneration Genes in Mutant <em>Caenorhabditis elegans</em> Using CRISPR-Cas9 Improves Behavior Associated With Alzheimer’s Disease

Alzheimer's disease is one of the leading causes of death in the United States and is characterized by neurodegeneration. Mishra et al. wanted to understand the role of two transport proteins, LRP1 and AQP4, in the neurodegeneration of Alzheimer's disease. They used a model organism for Alzheimer's disease, the nematode C. elegans, and genetic engineering to look at whether they would see a decrease in neurodegeneration if they increased the amount of these two transport proteins. They found that the best improvements were caused by increased expression of both transport proteins, with smaller improvements when just one of the proteins is overly expressed. Their work has important implications for how we understand neurodegeneration in Alzheimer's disease and what we can do to slow or prevent the progression of the disease.

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Using Gravitational Waves to Determine if Primordial Black Holes are Sources of Dark Matter

Sivakumar et al. | Jul 15, 2024

Using Gravitational Waves to Determine if Primordial Black Holes are Sources of Dark Matter

In the quest to understand dark matter, scientists face a profound mystery. Two compelling candidates, Massive Compact Halo Objects (MACHOs) and Weakly Interacting Massive Particles (WIMPs), have emerged as potential sources. By analyzing gravitational waves from binary mergers involving these black holes, authors sought to determine if MACHOs could be the elusive dark matter.

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A Novel Approach to Prevent and Restrict Early Stages of Cancer Cell Growth Using a Combination of Moringa and Sesame in a Drosophila Model

Ganesh et al. | Sep 28, 2020

A Novel Approach to Prevent and Restrict Early Stages of Cancer Cell Growth Using a Combination of Moringa and Sesame in a <em>Drosophila</em> Model

Sesame (Sesamum indicum) and moringa (Moringa oleifera) have natural antioxidants that could prevent cancer growth. Previously, this group found that sesame and moringa individually suppress eye tumor grown in the Drosophila melanogaster model. In the present study, combinations of sesame and moringa at different concentrations were included in the D. melanogaster diet. The impact on eye tumor development was assessed at different stages of growth.

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Analyzing breath sounds by using deep learning in diagnosing bronchial blockages with artificial lung

Bae et al. | Jan 22, 2024

Analyzing breath sounds by using deep learning in diagnosing bronchial blockages with artificial lung

Many common respiratory illnesses like bronchitis, asthma, and chronic obstructive pulmonary disease (COPD) lead to bronchial inflammation and, subsequently, a blockage. However, there are many difficulties in measuring the severity of the blockage. A numeric metric to determine the degree of the blockage severity is necessary. To tackle this demand, we aimed to develop a novel human respiratory model and design a deep-learning program that can constantly monitor and report bronchial blockage by recording breath sounds in a non-intrusive way.

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