Browse Articles

The authors studied the ability of freshwater clams to improve water quality.

Here the authors propose integrating magnetic iron (II) oxide nanoparticles into the high-density polyethylene linings of disposable paper cups to create a waterproof, magnetically responsive composite liner. Their findings demonstrate that these nanoparticles successfully bond with the plastic layer without disrupting its structural integrity, offering a viable method to improve plastic recovery through magnetic recycling and mitigate global microplastic pollution.

Tax incentives for sustainable technology are a key part of the push for a greener future. However, these incentives may not reach all income strata equally. Using a machine learning approach, this study analyzed the distributional effects of residential energy tax credits across different income levels in the United States.

Cancer cells rely heavily on glycolysis, but how they respond when glucose is reintroduced after acute starvation is not well understood. Using fluorescence lifetime imaging microscopy, students tracked metabolic changes in HeLa cells and found a rapid shift toward glycolysis within 20 minutes of glucose reintroduction, followed by heterogeneous recovery toward oxidative phosphorylation. These results highlight metabolic flexibility and variability in cancer cells, offering insights relevant to treatment resistance and therapeutic design.

This study investigates skin tone bias in artificial intelligence models used for dermatological disease classification and evaluates a CycleGAN-based data augmentation approach to improve diagnostic performance on darker skin types. We generated synthetic dark-skinned images to enhance dataset diversity and compared model performance before and after augmentation. The results demonstrate that augmentation with synthetic dermatological images can help reduce disparities in diagnostic performance across skin tones, highlighting a practical strategy for improving fairness in dermatology AI systems.

This study developed an effective method for extracting valuable information from social media data and employed computer-assisted human coding alongside the AI-powered tool to analyze social media posts. The findings provide a deep understanding of the major challenges that home health care workers are experiencing and offer important implications regarding how to improve home healthcare workers' well-being, and provide suggestions on optimizing the home health care service experience.

The authors looked at how different blends of synthetic and non-synthetic fabrics protected against UV radiation.

This study investigated perceptions of the emerging workforce toward the use of artificial intelligence in hiring, specifically for assessing subjective "culture fit." Through a mixed-methods survey of 150 high school and early-college students in Nepal, we found a significant disconnect between organizational adoption of AI and the profound skepticism of young job candidates, who express deep concerns about fairness, transparency, and the potential for AI to perpetuate systemic discrimination.

The authors studied optimized delivery routes to reduce travel times using different traveling salesman algorithms.

This study investigates the migration intentions of Syrian high school and university students amid ongoing conflict and economic instability. Drawing on survey data, the research examines how academic stage influences migration motivations, preferred destinations, and return intentions. The findings reveal a widespread desire to emigrate, driven by educational, economic, and security concerns, highlighting significant implications for Syria’s future workforce and post-conflict recovery.