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The authors looked at abundance of bacteria in stool samples from patients with colorectal cancer compared to controls. They found different bacteria that was more prevalent in patients with colorectal cancer as well as bacteria in control patients that may indicate a beneficial gut microbiome.

Debates around legacy preferences, recruited athletes, and affirmative action in U.S. college admissions often focus on the belief that graduating from a more selective institution leads to higher future earnings. The study hypothesized a positive correlation between college selectivity and future income due to enhanced resources and opportunities.

Obsessive-compulsive disorder (OCD) can cause significant impairment, and studies indicate that delays in diagnosis and treatment lead to worse outcomes. This study aimed to assess whether these delays have improved over the past three decades and to identify their causes.

Machine translation remains a challenging area in artificial intelligence, with neural machine translation (NMT) making significant strides over the past decade but still facing hurdles, particularly in translation quality due to the reliance on expensive bilingual training data. This study explores whether large language models (LLMs), like GPT-4, can be effectively adapted for translation tasks and outperform traditional NMT systems.

The authors test how the size-segregation theory applies to the behavior of hollow and irregular-shaped objects.

The authors use machine learning to develop an evidence-based detection tool for identifying human trafficking.

The authors looked at the ability of eggshells to slow ice melting. They found that eggshells were able to increase ice melting time when crushed showing that they were an effective thermal barrier.

The authors looked at variables associated with identity fraud in the US. They found that national unemployment rate and online banking usage are among significant variables that explain identity fraud.

The authors looked at student behaviors around disposal of face masks. The goal of the study was to bring awareness to improper mask disposal and how the resulting litter contributes to overall environmental pollution.

The authors test various machine learning models to improve the accuracy and efficiency of pneumonia diagnosis from X-ray images.