Results 231 to 240 of about 13,021,809 (342)
Association between shift/night work and irregular periods and period pain among two cohorts of Australian women 16 years apart: findings from the Australian longitudinal study on women's health. [PDF]
Alemu BW, Waller M, Tooth LR.
europepmc +1 more source
The ICARUS project developed pilot‐scale processes to recover and refine secondary raw materials from silicon photovoltaic (PV) ingot and wafer manufacturing waste. Silicon kerf, graphite, and silica residues are purified into high‐value inputs for the PV value chain and beyond.
Martin Bellmann +18 more
wiley +1 more source
A circadian-informed lighting intervention accelerates circadian adjustment to a night work schedule in a submarine lighting environment. [PDF]
Guyett A +15 more
europepmc +1 more source
This Perspective examines practical power solutions for wearable healthcare systems, highlighting the limits of standard batteries. It categorizes wearables into four domains—point‐of‐care diagnostics, episodic monitoring, continuous long‐term monitoring, and therapeutic platforms—and analyzes their power needs.
Seokheun Choi
wiley +1 more source
Combined exposure to night work and noise in relation to hyperglycemia among long-term night workers: a nationwide population-based prospective cohort study. [PDF]
Chu PC +5 more
europepmc +1 more source
Abstract This study explores the rent price ratio in agricultural land markets, crucial for evaluating market efficiency, policy needs, and farmer decision‐making. Traditionally, the analyses faced challenges due to the absence of concurrent sale and rent data for the same land, potentially leading to biased results.
Marius Michels +4 more
wiley +1 more source
Impact of Decreased Night Work on Workers' Musculoskeletal Symptoms: A Quasi-Experimental Intervention Study. [PDF]
Lee HE, Choi M, Kim HR, Kawachi I.
europepmc +1 more source
ABSTRACT Over the past three decades, we have mentored a generation of young Japanese surgeons, guiding them to become internationally recognized surgeon‐scientists. Through a unique collaboration between Japanese academic institutions and our laboratories at AntiCancer Inc.
Robert M. Hoffman +2 more
wiley +1 more source
This work presents a deep learning model to autonomously recognize and classify the secretion retention into three levels for patients receiving invasive mechanical ventilation, achieving 89.08% accuracy. This model can be implemented to ventilators by edge computing, whose feasibility is approved.
Shuai Wang +6 more
wiley +1 more source

