Browse Articles

Impact of light intensity and electrolyte volume on performance of photo-electrochemical (PEC) solar cell

Patel et al. | Mar 14, 2022

Impact of light intensity and electrolyte volume on performance of photo-electrochemical (PEC) solar cell

Here, seeking to develop more efficient solar cells, the authors investigated photo-electrochemical (PEC) solar cells, specifically molybdenum diselenide (MoSe2) based on its high resistance to corrosion. They found that the percentage efficiency of these PEC solar cells was proportional to light intensity–0.9 and that performance was positively influenced by increasing the electrolyte volume. They suggest that studies such as these can lead to new insight into reaction-based solar cells.

Read More...

Nintendo Da Vinci: A Novel Control System to Improve Performance in Robotic-Assisted Surgery

Al-Akash et al. | Oct 26, 2019

Nintendo Da Vinci: A Novel Control System to Improve Performance in Robotic-Assisted Surgery

Complications of robotic-assisted surgery are on the rise, partly due to surgeons not receiving proper training. Al-Akash and Al-Akash hypothesized Nintendo JoyCon controls would improve surgical performance compared to the FDA-approved Da Vinci Surgical System with two user groups (doctor and gamer). Their results show that implementing a Nintendo JoyCon control system is associated with improved surgical performance and learning rate compared to the Da Vinci Surgical System.

Read More...

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.

Read More...

Environmental, Social, and Governance (ESG) Standards and Financial Performance in Vietnam’s Media Sector

Nguyen et al. | Jul 29, 2026

Environmental, Social, and Governance (ESG) Standards and Financial Performance in Vietnam’s Media Sector
Image credit: Nguyen, Tran, Pham, and Nguyen

In this study, the authors examine the relationship between ESG (Environmental, Social, and Governance) factors on financial performance of Vietnamese media companies, as measured by ROA and ROE. They find that ESG is positively correlated with financial performance, as is sales growth. They also find that financial leverage is negatively correlated with ROA. Overall, this is a quality study, although the methods section requires more detail.

Read More...

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...