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A systematic review of features and content quality of Arabic mental mHealth apps.

Front Digit Health

December 2024

Discipline of Biomedical Engineering, School of Electrical and Mechanical Engineering, The University of Adelaide, Adelaide, SA, Australia.

Introduction: Anxiety and depression are major causes of disability in Arab countries, yet resources for mental health services are insufficient. Mobile devices may improve mental health care delivery (mental m-Health), but the Arab region's mental m-Health app landscape remains under-documented. This study aims to systematically assess the features, quality, and digital safety of mental m-Health apps available in the Arab marketplace.

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Objective: To evaluate the value of respiratory specimens collected via different sampling methods combined with metagenomic next-generation sequencing (mNGS) in the etiological diagnosis of severe pneumonia.

Methods: A total of 117 patients with severe pneumonia between 2019 and 2024 were included in this study, with 60 patients undergoing endotracheal aspiration (ETA) and 57 undergoing bronchoalveolar lavage (BAL), respectively. Patient records were retrospectively reviewed.

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Optimal Sensor Placement for Motion Tracking of Soft Wearables Using Bayesian Sampling.

Soft Robot

December 2024

Department of Mechanical Engineering, Institute of Advanced Machines and Design, Institute of Engineering Research, Seoul National University, Seoul, Republic of Korea.

Soft sensors integrated or attached to robots or human bodies enable rapid and accurate estimation of the physical states of the target systems, including position, orientation, and force. While the use of a number of sensors enhances precision and reliability in estimation, it may constrain the movement of the target system or make the entire system complex and bulky. This article proposes a rapid, efficient framework for determining where to place the sensors on the system given the limited number of available sensors.

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This study aimed to determine optimal washing and drying methods for maintaining the functionality of silver-coated conductive knitted fabrics, commonly used in wearable smart products. By investigating changes in the physical, chemical, and electrical properties of these fabrics under various care conditions, we sought to provide recommendations for their proper maintenance. Results showed that mechanical friction during washing, combined with the chemical effect of detergent and the effects of machine drying, led to peeling and oxidation of the silver layer, resulting in changes to the fabric's appearance, color and increased surface resistance.

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Background: has emerged as an important nosocomial opportunistic pathogen, often associated with serious infections. We investigated the antimicrobial resistance trends, predisposing factors, and infection outcomes associated with isolated in a secondary-care hospital in Oman.

Materials And Methods: A retrospective study was conducted at a secondary-care hospital in the northern region of Oman after receiving approval from the research ethics and approval committee of Oman.

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