Software bug report classification is one of the most significant processes in software development for determining the nature and severity of faults based on their causes and effects. In many projects, software experts implement this process manually, which requires exorbitant time and effort. Although there are a few studies on automatic bug report classification using machine learning techniques, they mainly focus on structured open-source datasets. This paper presents an ensemble learning...

Vector-borne diseases are increasing in prevalence, posing a risk to 80% of the human population worldwide. In the United States, tick-borne diseases account for 75% of all nationally reported vector-borne disease cases. As the distribution of medically important ticks and tick-borne diseases increases, it is crucial to understand the factors driving their expansion. Changes in land cover are a known driver of vector-borne disease emergence and prevalence. In the U.S. Great Plains, a dominant...

CONCLUSION: Most RCTs showed internal validity but limited real-world relevance. Narrow eligibility, short follow-up, and poor transparency limit clinical impact. These findings should not be interpreted as a dismissal. Rather, they highlight opportunities to strengthen future trials so that they remain a cornerstone of evidence-based orthopaedics.

CONCLUSION: Quantifying ECS by deconvolution supports a transcriptomics-driven approach towards the non-invasive evaluation of endothelial damage in respiratory outcomes. This is a first step towards elucidating mechanistic components linking endothelial damage to ARDS utilizing non-invasive, circulating transcriptomic data by leveraging a novel deconvolution approach.

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