: Accurate reconstruction of internal temperature fields from surface temperature data is critical for applications such as non-invasive thermal imaging, particularly in scenarios involving small temperature gradients, like those in the human body. : In this study, we employed 3D convolutional neural networks (CNNs) to predict internal temperature fields. The network's performance was evaluated under both ideal and non-ideal conditions, incorporating noise and background temperature variations.
View Article and Find Full Text PDFSwimming pools and jacuzzis can pose significant public health risks as potential sources of infections. The present study aimed to evaluate the prevalence and concentration of microbiological indicators in recreational water facilities in Thessaloniki, Northern Greece, focusing on their hygiene status before and after the COVID-19 pandemic. Between January 2018 and December 2022, 1114 water samples were analyzed by the regional Water Hygiene Laboratory at Aristotle University of Thessaloniki, using standardized ISO methods.
View Article and Find Full Text PDFBackground: This study aimed to explore in depth the lived experience and quality of life outcomes in patients receiving automated peritoneal dialysis (APD) treatment.
Methods: The study adhered to the standards of the Consolidated Criteria for Reporting Qualitative Research. A total of 19 APD patients were recruited and assessed using in-depth semi-structured interviews on various aspects of life with respect to APD modality.
Background: Patients with lung cancer face a heightened risk of atherosclerosis-related cardiovascular events. Despite the strong scientific rationale, there is currently a lack of clinical evidence examining the impact of immune checkpoint inhibitors (ICIs) on the advancement of atherosclerosis in patients with lung cancer. The objective of our study was to investigate whether there is a correlation between ICIs and the accelerated progression of atherosclerosis among individuals with lung cancer.
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