Infection control / Modes of transmission

Risk prediction models for imported infectious diseases: A systematic review.

OBJECTIVES: Accurate prediction models for imported infectious diseases are essential for early warning, cross-border surveillance, and resource allocation. Despite the growing number of predictive models for imported infectious diseases, substantial heterogeneity in model structure, reporting, and performance across studies has led to confusion for researchers and limited practical uptake, even f...

Prospective genomic and epidemiologic surveillance of Klebsiella pneumoniae in a tertiary NICU.

BACKGROUND: Klebsiella pneumoniae complex (Kp) is a relevant neonatal pathogen colonizing preterm infants. While outbreak investigations often focus on multidrug-resistant strains, the epidemiology and genomic dynamics of wild-type Kp in nonoutbreak neonatal intensive care unit (NICU) settings remain elusive. METHODS: We conducted a 30-month (October 2021 to March 2024) cohort study with weekly ac...

Automated detection of racket-ball impact timing in tennis strokes using deep learning models and a markerless motion capture system.

Event identification, which refers to defining important moments within a movement, is a fundamental process in biomechanical analysis. This study aim...

Robust service migration for autonomous vehicles leveraging deep learning and cooperative V2V protocols.

Autonomous vehicles are essentially data centers on wheels. Between self-driving algorithms and high-definition mapping, the demand for instant proces...

Extruded droplet-on-demand (X-DoD) bioprinting for controlled iPSC-based functional cortical network formation.

Engineered three-dimensional (3D) neural constructs hold significant promise for repairing neural tissue damage and recapitulating the human brain in ...

Automated estimation of drain output in postoperative patients using deep learning on clinical images.

Postoperative drains are essential components of care in general surgery and intensive care units, where accurate monitoring of drain output is critic...

Harnessing machine learning to improve ice sheet bed mapping.

Airborne radio-echo sounding (RES) surveys are currently the primary method of measuring ice sheet thickness to derive subglacial topography, which un...

Advances in Large-Scale Surveying and Monitoring of Large Wild Animals Using Unmanned Aerial Vehicles.

As the number of endangered animal species increases, their conservation requires effective methods for the surveying and monitoring of the spatial an...

Modelling the epidemic dynamics of HPV among women in China and optimization of ongoing cervical cancer elimination strategies.

BACKGROUND: The infection of high-risk human papillomavirus (hr-HPV) and related cervical cancer have greatly threatened women's health. However, the ...

Smart PPE and wearable technology for construction safety management: A scientometric analysis and state-of-the-art review.

This study presents a scientometric and state-of-the-art review of smart personal protective equipment (PPE) and wearable safety technologies (WSTs) i...

From risk to resilience: A narrative review on strengthening veterinary clinical biosecurity to prevent healthcare-associated infections.

Veterinary clinical biosecurity is key to preventing infectious diseases in animal clinics, particularly when there is high patient turnover, a mix of...

Workers/crews' mental workload dynamics in closed cabins: A task-difficulty-adaptive random forest model for instrument monitoring tasks using multimodal biosignals.

BackgroundAccurate assessment of operator mental workload (MWL) is critical for ensuring safety in closed-cabin environments, yet traditional contact-...

METLIN 960 K: An Empirical Tandem Mass Spectrometry Data Resource.

METLIN 960 K represents the largest collection of experimentally acquired small-molecule MS/MS spectra currently available. We introduce a reengineere...

Predicting Somatization Risk Among Infectious Disease Disaster Frontline Nurses Using Machine Learning.

This study aimed to identify key risk factors associated with high-somatization risk among frontline nurses responding to infectious diseases, utilizi...

Environmental drivers and machine learning forecasting of leptospirosis: a multi-province study in Thailand.

Leptospirosis is a major environmental health concern in Thailand, where transmission is strongly influenced by hydrometeorological conditions such as...

MechMemDyn: Coupling Frustration Analysis with Membrane Dynamics to Target the TREM2-DAP12 Complex Interface.

The transmembrane complex formed by TREM2 (Triggering Receptor Expressed on Myeloid cells 2) and DAP12 (DNAX-activating protein of 12 kDa) constitutes...

Moisture-driven, self-powered noncontact sensing interfaces via turbulence-tailored hygroelectronic effect.

Noncontact human-machine interfaces (HMIs) provide a hygienic and intelligent approach for the communication between human and robots. However, they a...

Geometry parameters estimation in Monte Carlo simulation using machine learning.

This study investigates the application of Artificial Neural Networks (ANNs) to estimate geometry parameters in Monte Carlo simulations of High Purity...

Machine-Learning Microfluidic Minute-Scale Microorganism Metrics Monitoring(M6).

On-site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion,...

A natural defense against particulate matter 10 (PM10): Network pharmacology-based insights into the protective effects of Chrysanthemum zawadskii var. latilobum against PM10-induced lung inflammation.

Airborne particulate matter 10 (PM10) induces lung inflammation. However, interventions remain limited. We evaluated the protective effects of Chrysan...