Development and validation of a machine learning-based risk prediction model for stroke-associated pneumonia in older adult hemorrhagic stroke.

Objective: To develop and validate a machine learning (ML)-based model for predicting stroke-associated pneumonia (SAP) risk in older adult hemorrhagic stroke patients.

Methods: A retrospective collection of older adult hemorrhagic stroke patients from three tertiary hospitals in Guiyang, Guizhou Province (January 2019-December 2022) formed the modeling cohort, randomly split into training and internal validation sets (7:3 ratio). External validation utilized retrospective data from January-December 2023.

Alkane degradation coupled to Fe(III) reduction mediated by Gram-positive bacteria.

Petroleum hydrocarbon contamination, such as n-alkanes, poses a significant global threat to ecosystems and human health. Microbial remediation emerges as a promising strategy for addressing this issue through both aerobic and anaerobic processes. Notably, the majority of anaerobic hydrocarbon degraders identified to date are Gram-negative bacteria.

Gamma Radiation Image Noise Prediction Method Based on Statistical Analysis and Random Walk.

The gamma radiation environment is one of the harshest operating environments for image acquisition systems, and the captured images are heavily noisy. In this paper, we improve the multi-frame difference method for the characteristics of noise and add an edge detection algorithm to segment the noise region and extract the noise quantization information. A Gaussian mixture model of the gamma radiation noise is then established by performing a specific statistical analysis of the amplitude and quantity information of the noise.