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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.

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

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 the relationship between unemployment and minimum wage in Turkey (Türkiye). They found that there is a positive correlation between minimum wage and unemployment.

The authors looked at the ability of Shewanella oneidensis to generate energy in a microbial fuel cell under varying conditions. They found that the S. Onedensis biofilm was able to produce energy in microgravity and that one of the biggest factors that limited energy production was a decrease in growth medium present.

Medicinal plants could be a good source of medication to combat antibiotic resistance. Dombeya wallichii, which is commonly called Pink Ball Tree in the family Sterculiaceae, has been documented to have medicinal potential. We observed the highest antibacterial activity in the stem extracts, followed by leaf and bark extracts. The extracts were more effective against tested Gram-positive bacteria when compared with Gram-negative strains.

In this article the authors look at the lung microbiome in patients with cystic fibrosis to determine what the major bacterial species present are.

In this study, the authors investigate differences in psychological outcomes from patients who undergo different surgical procedures.

The authors test the antiproliferative and apoptosis-inducing properties of an extract created from a traditional Indian medicinal plant of the Amaranthus genus.

Here, recognizing the recognizing the growing threat of non-biodegradable plastic waste, the authors investigated the ability to use a modified enzyme identified in bacteria to decompose polyethylene terephthalate (PET). They used simulations to screen and identify an optimized enzyme based on machine learning models. Ultimately, they identified a potential mutant PETases capable of decomposing PET with improved thermal stability.