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In a world where water shortage is becoming an increasing concern, and where population increase seems inevitable, food shortage is an overwhelming concern for many. In this paper, the authors aim to characterize a drought-resistant strain of A. thaliana, investigating the cause for its water resistance. These and similar studies help us learn how plants could be engineered to improve their ability to flourish in a changing climate.

The authors studied bacterial contamination of the New York City transit system, as well as the effectiveness of hand washing and hand sanitizer.

This study used single-cell RNA sequencing to examine whether B cells can predict response to pembrolizumab and radiation therapy in patients with triple-negative breast cancer.

The authors looked at the feasibility to predict wind speeds that will have less reliance on using historical data.

The authors studied the ability of deep learning models to predict droughts in the midwestern United States.

Advertising platforms like Google Ads use AI to drive the algorithms used to maximize advertisers benefits. This study shows that AI does not adjust it strategy based on auction type and highlights the limitations of AI running without explicit guidance.

The author looked at how dance styles can vary by individuals, even between a student and their teacher.

The authors looked at how the length of an audio clip used of a song impacted the ability to properly classify it by musical genre.

Lung cancer is highly fatal, largely due to late diagnoses, but early detection can greatly improve survival. This study developed three models to enhance early diagnosis: an MLP for clinical data, a CNN for imaging data, and a hybrid model combining both.

This article describes the classification of medical text data using vector databases and text embedding. Various large language models were used to generate this medical data for the classification task.