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Pancreatic Adenocarcinoma: An Analysis of Drug Therapy Options through Interaction Maps and Graph Theory

Gupta et al. | Feb 04, 2014

Pancreatic Adenocarcinoma: An Analysis of Drug Therapy Options through Interaction Maps and Graph Theory

Cancer is often caused by improper function of a few proteins, and sometimes it takes only a few proteins to malfunction to cause drastic changes in cells. Here the authors look at the genes that were mutated in patients with a type of pancreatic cancer to identify proteins that are important in causing cancer. They also determined which proteins currently lack effective treatment, and suggest that certain proteins (named KRAS, CDKN2A, and RBBP8) are the most important candidates for developing drugs to treat pancreatic cancer.

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The Effect of UV Treatment on the Degradation of Compostable Polylactic Acid

Zhang et al. | Nov 28, 2013

The Effect of UV Treatment on the Degradation of Compostable Polylactic Acid

Polylactic acid (PLA) is a bio-based, compostable plastic that is comparable in cost to petroleum-based plastics. This study aims to evaluate the effects of UV treatment and mechanical chopping on the degradation of PLA. Based on their findings, the authors propose an alternative PLA degradation process that may be more time and energy efficient than current processes.

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The Effect of Music on Heart Rate

Agrawal et al. | Apr 25, 2013

The Effect of Music on Heart Rate

Different songs can seem to evoke different emotions. Here the authors demonstrate that different songs can have a significant effect on the heart rate of listeners. A slower song slows heart rate, and a faster song increases it.

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It's better than me: Investigating the psychological risks of AI on self-esteem

Kim et al. | Sep 07, 2026

It's better than me: Investigating the psychological risks of AI on self-esteem

Here the authors investigated whether frequent use of generative AI tools triggers upward social comparison and negatively impacts users' performance self-esteem. Based on a survey of 121 adults, they found no significant relationship between AI usage and self-esteem, concluding that current chatbot interactions do not pose the same psychological threat as peer-based comparisons.

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Understanding the impossibility of machine learning fairness with data examples

Pillutla et al. | Sep 04, 2026

Understanding the impossibility of machine learning fairness with data examples

Machine learning systems are often expected to make fair decisions, yet the most widely used fairness criteria—independence, separation, and sufficiency—cannot generally be satisfied at the same time. In this study, students tested these criteria using a logistic regression model on a real-world student performance dataset and found that each criterion was met only at different prediction thresholds, with no threshold satisfying all three simultaneously. These results illustrate the inherent trade-offs in algorithmic fairness and highlight why achieving perfectly fair machine learning models is often impossible in practice.

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