Browse Articles

Solubility of graphite and the efficacy of using its dissolved form as a conductive paste

Kirby et al. | Aug 23, 2024

Solubility of graphite and the efficacy of using its dissolved form as a conductive paste

This study explored the use of graphite's conductivity for circuit boards by creating a conductive paste through exfoliation with organic solvents and sonication. The combination of acetone and sonication was found to be the most effective, producing a high-conductivity paste with desirable properties such as a low boiling point. While not a replacement for wires, this conductive paste has potential applications in electronics and infrastructure, provided that key engineering challenges are addressed.

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Color photometry and light curve modeling of apparent transient 2023jri

Favretto et al. | Aug 13, 2024

Color photometry and light curve modeling of apparent transient 2023jri

Observing transients like supernovae, which have short-lived brightness variations, helps astronomers understand cosmic phenomena. This study analyzed transient 2023jri, hypothesizing it was a Type IIb supernova. By collecting and analyzing data over four weeks, including light and color curves, they confirmed its classification and provided additional insights into this less-studied supernova type.

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A HOG feature extraction and CNN approach to Parkinson’s spiral drawing diagnosis

Tripathi et al. | Aug 09, 2024

A HOG feature extraction and CNN approach to Parkinson’s spiral drawing diagnosis

Parkinson’s disease (PD) is a prevalent neurodegenerative disorder in the U.S., second only to Alzheimer’s disease. Current diagnostic methods are often inefficient and dependent on clinical exams. This study explored using machine and deep learning to enhance PD diagnosis by analyzing spiral drawings affected by hand tremors, a common PD symptom.

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Quantitative analysis and development of alopecia areata classification frameworks

Dubey et al. | Jun 03, 2024

Quantitative analysis and development of alopecia areata classification frameworks

This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.

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Effects of material advantage and space advantage on the Komodo and Stockfish chess engines

Kaushikan et al. | May 14, 2024

Effects of material advantage and space advantage on the Komodo and Stockfish chess engines
Image credit: The authors

Chess engines, or computer programs built to play chess, outperform even the best human players. Kaushikan and Park investigate the inner workings of these chess engines by studying popular chess engines' evaluations of which side of a chess match is most likely to win, and how this is affected by the number of pieces and controlled squares on each side.

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Investigating Lemna minor and microorganisms for the phytoremediation of nanosilver and microplastics

Iyer et al. | Apr 01, 2024

Investigating <i>Lemna minor</i> and microorganisms for the phytoremediation of nanosilver and microplastics

The authors looked at phytoremediation, the process by which plants are used to remove pollutants from our environment, and the ability of Lemna minor to perform phytoremediation in various simulated polluted environments. The authors found that L. minor could remove pollutants from the environment and that the addition of bacteria increased this removal.

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Impact of carbon number and atom number on cc-pVTZ Hartree-Fock Energy and program runtime of alkanes

Pan et al. | Mar 06, 2024

Impact of carbon number and atom number on cc-pVTZ Hartree-Fock Energy and program runtime of alkanes
Image credit: The authors

It's time-consuming to complete the calculations that are used to study nuclear reactions and energy. To uncover which computational chemistry tools are useful for this challenge, Pan, Vaiyakarnam, Li, and McMahan investigated whether the Python-based Simulations of Chemistry Framework’s Hartree-Fock (PySCF) method is an efficient and accurate way to assess alkane molecules.

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