Browse Articles

Assessing machine learning model efficacy for brain tumor MRI classification: a multi-model approach

Dhingra et al. | Mar 14, 2026

Assessing machine learning model efficacy for brain tumor MRI classification: a multi-model approach
Image credit: Dhingra and Dhingra

This manuscript explores the performance of five different machine learning models in classifying brain tumors from a dataset of MRI scans. The authors find that several of the models showed >90% accuracy. Thus, the authors suggest that machine learning models demonstrate potential for effective implementation in clinical settings, including as a diagnostic tool that can be used to complement the expertise of neuroradiologists.

Read More...

The effect of lead oxide concentrations on the bioluminescence intensity of Panellus stipticus

Park et al. | Mar 02, 2026

The effect of lead oxide concentrations on the bioluminescence intensity of <i>Panellus stipticus</i>

Here the authors investigate the potential of the bioluminescent fungus Panellus stipticus to serve as a sustainable bioindicator for environmental lead contamination. Their findings demonstrate that higher lead concentrations cause a measurable decrease in fungal bioluminescence intensity over time suggesting that the fungus could be an effective tool for detecting lead in an environment.

Read More...

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.

Read More...

Antibacterial activity by Dombeya wallichii plant extracts obtained by ultrasound-assisted extraction

Herur et al. | Nov 13, 2023

Antibacterial activity by <em>Dombeya wallichii</em> plant extracts obtained by ultrasound-assisted extraction

Medicinal plants could be a good source of medication to combat antibiotic resistance. Dombeya wallichii, which is commonly called Pink Ball Tree in the family Sterculiaceae, has been documented to have medicinal potential. We observed the highest antibacterial activity in the stem extracts, followed by leaf and bark extracts. The extracts were more effective against tested Gram-positive bacteria when compared with Gram-negative strains.

Read More...

Tomato disease identification with shallow convolutional neural networks

Trinh et al. | Mar 03, 2023

Tomato disease identification with shallow convolutional neural networks

Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.

Read More...