XtremWeb-CH (XWCH) is a volunteer computing middleware that makes it easy for scientists and industrials to deploy and execute their parallel and distributed applications on a public-resource computing infrastructure. XWCH supports various high performance applications, including those having large storage and communication requirements. Two high performance applications were ported and deployed on an XWCH platform. The first one is the Phylip package of programs that is employed for inferring phylogenies (evolutionary trees). It is the most widely distributed phylogeny package and has been used to build the largest number of published trees. Some modules of Phylip are CPU time consuming; their sequential version cannot be applied to a large number of sequences. The second application ported on XWCH is a medical application used to generate temporal dynamic neuronal maps. The application,named NeuroWeb,is used to better understand the connectivity and activity of neurons. NeuroWeb is a data and CPU intensive application. This paper describes the different components of an XWCH platform and the lessons learned from gridifying Phylip and NeuroWeb. It also details the new features and extensions, which are being added to XWCH in order to support new types of applications.
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Bioelectromagnetics
January 2025
Seibersdorf Labor GmbH, Seibersdorf, Austria.
The electrical conductivity of human tissues is a major source of uncertainty when modelling the interactions between electromagnetic fields and the human body. The aim of this study is to estimate human tissue conductivities in vivo over the low-frequency range, from 30 Hz to 1 MHz. Noninvasive impedance measurements, medical imaging, and 3D surface scanning were performed on the forearms of ten volunteer test subjects.
View Article and Find Full Text PDFIntroduction: Understanding how a research sample compares to the population from which it is drawn can help inform future recruitment planning. We compared the Wisconsin Alzheimer's Disease Research Center (WADRC) participant sample to the Wisconsin state population (WI-pop) on key demographic, social exposome, and vascular risk measures.
Methods: The WADRC sample included 930 participants.
Digit Health
January 2025
Division of Rheumatology, Department of Medicine (DMED), ASUFC, University of Udine, Udine, Italy.
Background: Immersive Virtual Reality (VR) has been applied in pain management for various conditions, but its use in fibromyalgia (FM) remains underexplored. While physical activity plays a role in treating FM, patients' low tolerance often limits its effectiveness. After reviewing the literature on VR and games for FM, we designed a novel VR exergame to assist FM patients in performing physical activity, and evaluate its feasibility.
View Article and Find Full Text PDFSci Rep
January 2025
Pharmacy Department, Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, NE1 4LP, England, UK.
Prescribing errors are a source of preventable harm in healthcare, which may be mitigated using Electronic Prescribing (EP) systems. Anyone who routinely prescribes medication could benefit from digitally assisted automated checks to identify whether a prescription should potentially not be allowed (e.g.
View Article and Find Full Text PDFPLoS One
January 2025
Division of Biological Sciences, US Fish and Wildlife Southwest Regional Office, Albuquerque, New Mexico, United States of America.
There is growing interest in using deep learning models to automate wildlife detection in aerial imaging surveys to increase efficiency, but human-generated annotations remain necessary for model training. However, even skilled observers may diverge in interpreting aerial imagery of complex environments, which may result in downstream instability of models. In this study, we present a framework for assessing annotation reliability by calculating agreement metrics for individual observers against an aggregated set of annotations generated by clustering multiple observers' observations and selecting the mode classification.
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