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Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance

Gupta et al. | Oct 18, 2020

Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance

In this study, the authors seek to improve a machine learning algorithm used for image classification: identifying male and female images. In addition to fine-tuning the classification model, they investigate how accuracy is affected by their changes (an important task when developing and updating algorithms). To determine accuracy, a set of images is used to train the model and then a separate set of images is used for validation. They found that the validation accuracy was close to the training accuracy. This study contributes to the expanding areas of machine learning and its applications to image identification.

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Effects on Learning and Memory of a Mutation in Dα7: A D. melanogaster Homolog of Alzheimer's Related Gene for nAChR α7

Sanyal et al. | Oct 01, 2019

Effects on Learning and Memory of a Mutation in Dα7: A <em>D. melanogaster</em> Homolog of Alzheimer's Related Gene for nAChR α7

Alzheimer's disease (AD) involves the reduction of cholinergic activity due to a decrease in neuronal levels of nAChR α7. In this work, Sanyal and Cuellar-Ortiz explore the role of the nAChR α7 in learning and memory retention, using Drosophila melanogaster as a model organism. The performance of mutant flies (PΔEY6) was analyzed in locomotive and olfactory-memory retention tests in comparison to wild type (WT) flies and an Alzheimer's disease model Arc-42 (Aβ-42). Their results suggest that the lack of the D. melanogaster-nAChR causes learning, memory, and locomotion impairments, similar to those observed in Alzheimer's models Arc-42.

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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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The effect of Omega-3 on bovine blood cells as a potential remedy for Cerebral Cavernous Malformations

Pulluru et al. | Sep 22, 2023

The effect of Omega-3 on bovine blood cells as a potential remedy for Cerebral Cavernous Malformations
Image credit: Carolien van Oijen

Here, the authors investigated if dietary Omega-3 fatty acids could reduce the potential for cerebral cavernous malformations, which are brain lesions that occur due to a genetic mutation where high membrane permeability occurs between endothelial cell junctions. In a bovine-based study where some cows were fed an Omega-3 diet, the authors found the membranes of bovine blood cells increased in thickness with Omega-3 supplementation. As a result, they suggest that dietary Omega-3 could be considered as a possible preventative measure for cerebral cavernous malformations.

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An analysis of junior rower performance and how it is affected by rower's features

Biller et al. | Jan 07, 2022

An analysis of junior rower performance and how it is affected by rower's features

In this study, with consideration for the increasing participation of high school students in indoor rowing, the authors analyzed World Indoor Rowing Championship data. Statistical analysis revealed two key features that can determine the performance of a rower as well as increasing competitiveness in nearly all categories considered. They conclude by offering a 2000-meter ergometer time distribution that can help junior rowers assess their current performance relative to the world competition.

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Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Dao et al. | Jun 27, 2021

Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Engineered bacteria that degrade oil are currently being considered as a safe option for the treatment of oil spills. For this approach to be successful, the bacteria must effectively express oil-degrading genes they uptake as part of an external genoming vehicle called a "plasmid". Using a computational approach, the authors investigate plasmid-bacterium compatibility to find pairs that ensure high levels of gene expression.

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Singlet oxygen production analysis of reduced berberine analogs via NMR spectroscopy

Su et al. | Feb 10, 2023

Singlet oxygen production analysis of reduced berberine analogs via NMR spectroscopy

Berberine is a natural product isoquinoline alkaloid derived from plants of the genus Berberis. When exposed to photoirradiation, it produces singlet oxygen through photosensitization of triplet oxygen. Through qNMR analysis of 1H NMR spectra gathered through kinetic experiments, we were able to track the generation of a product between singlet oxygen and alpha terpinene, allowing us to quantitatively measure the photosensitizing properties of our scaffolds.

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Developing a Method to Remove Inorganic Arsenic from Rice with Natural Substances

Mukai et al. | Oct 27, 2020

Developing a Method to Remove Inorganic Arsenic from Rice with Natural Substances

In this study, the authors tested different approaches for removing arsenic from rice. Due to higher arsenic levels in water, some areas grow rice with higher levels as well. This is a health hazard and so developing methods to remove arsenic from the rice will be helpful to many. Using a rapid arsenic kit, the authors found that activated charcoal was the most effective at removing arsenic from rice.

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