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Integration of iron oxide nanoparticles into high-density polyethylene for sustainable cup coatings

Atmadja et al. | Jul 08, 2026

Integration of iron oxide nanoparticles into high-density polyethylene for sustainable cup coatings

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.

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Investigating the effects of glucose reintroduction on acutely starved HeLa cells

Puduru et al. | Jul 05, 2026

Investigating the effects of glucose reintroduction on acutely starved HeLa cells

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.

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Mitigating skin color bias in dermatology AI using CycleGAN-based data augmentation

Kannan et al. | Jun 24, 2026

Mitigating skin color bias in dermatology AI using CycleGAN-based data augmentation
Image credit: Kannan and Ramasamy

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.

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Mining social media posts: An alternative approach to understanding home health care workers’ experiences

Tang et al. | Jun 15, 2026

Mining social media posts: An alternative approach to understanding home health care workers’ experiences
Image credit: Markus Winkler

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.

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Algorithmic barriers: Investigating student perceptions of AI bias in subjective “culture fit” hiring

Mahatara et al. | May 25, 2026

Algorithmic barriers: Investigating student perceptions of AI bias in subjective “culture fit” hiring
Image credit: JonTyson

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.

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