Occupational Health and Safety (OHS) is associated with crucial social, economic, cultural and technical issues. A highly specialized OHS sector deals with the photobiological hazards from artificial optical radiation (AOR), which is divided into visible light, UV and IR emitted during various activities and which is legally covered by European Directive 2006/25/EC. Among the enormous amount of sources emitting AOR, the most important non-coherent ones to consider for health effects to the whole optical range, are arcs created during metal welding. This survey presents the effort to assess the complicated exposure limits of the Directive in the controlled environment of a welding laboratory. Sensors covering the UV and blue light range were set to measure typical welding procedures reproduced in the laboratory. Initial results, apart from apparently justifying the use of Personal Protective Equipment (PPE) due to even subsecond overexposures measured, also set the basis to evaluate PPE's properties and support an integrated risk assessment of the complex welding environment. These results can also improve workers' and employer's information and training about radiation hazards, which is a crucial OHS demand.
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http://dx.doi.org/10.1016/j.ejmp.2016.07.001 | DOI Listing |
Comput Med Imaging Graph
January 2025
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; National Key Laboratory of Kidney Diseases, Beijing 100853, China. Electronic address:
In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe noise, image denoising is essential for mitigating the trade-off between acquisition cost and image quality. However, prevailing deep learning methods exhibit uncontrollable and suboptimal performance with limited interpretability, primarily due to neglecting underlying physical model and frequency information.
View Article and Find Full Text PDFPLOS Glob Public Health
January 2025
Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Boston, Massachusetts, United States of America.
Cureus
December 2024
Medical Education, ABWA Medical College, Faisalabad, PAK.
Background: The inclusion of artificial intelligence in medical education, specifically through the use of ChatGPT (OpenAI, San Francisco, CA), has transformed learning and generated many ethical questions. This study aims to analyze the medical students' ethical concerns about using ChatGPT in medical education, focusing on privacy, accuracy, and professional integrity.
Methods: The study format was a cross-sectional survey distributed to 219 medical students at ABWA Medical College, Pakistan.
Insect Sci
January 2025
Department of Computer Science, Aberystwyth University, Aberystwyth, Wales, UK.
Jewel beetles pose significant threats to forestry, and effective traps are needed to monitor and manage them. Green traps often catch more beetles, but purple traps catch a greater proportion of females. Understanding the function and mechanism of this behavior can provide a rationale for trap optimization.
View Article and Find Full Text PDFSci Data
January 2025
Experimental Psychology, University College London, London, United Kingdom.
Communication comprises a wealth of multimodal signals (e.g., gestures, eye gaze, intonation) in addition to speech and there is a growing interest in the study of multimodal language by psychologists, linguists, neuroscientists and computer scientists.
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