To assess the impact of a school-based health intervention on adolescents' health knowledge, psychosocial assets and health behaviors, including comparisons of implementation mode: remote, hybrid or in-person. The Stanford Youth Diabetes Coaches Program, an 8-week, school-based health promotion and coaching skills program, was offered to adolescents (ages 14-18 years) from four low-income US communities. Mode of program implementation was remote, hybrid or in-person. Participants completed online pre- and postsurveys. Analysis included paired t-tests, linear regression and qualitative coding. From Fall 2020 to Fall 2021, 262 adolescents enrolled and 179 finished the program and completed pre- and postsurveys. Of the 179, 80% were female, with a mean age of 15.9 years; 22% were Asian; 8% were Black or African American; 25% were White; and 40% were Hispanic. About 115 participants were remote, 25 were hybrid and 39 were in-person. Across all participants, significant improvements (P < 0.01) were reported in health knowledge, psychosocial assets (self-esteem, self-efficacy and problem-solving) and health behaviors (physical activity, nutrition and stress reduction). After adjusting for sex and age, these improvements were roughly equivalent across the three modes of delivery. Participation was associated with significant improvements in adolescent health behaviors. Furthermore, remote mode of instruction was just as effective as in-person and hybrid modes.
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Sci Rep
January 2025
Department of Wildlife Fisheries and Aquaculture, College of Forest Resources, Mississippi State University, Mississippi State, MS, 39762-9690, USA.
This study addresses the significant issue of rapid land use and land cover (LULC) changes in Lahore District, which is critical for supporting ecological management and sustainable land-use planning. Understanding these changes is crucial for mitigating adverse environmental impacts and promoting sustainable development. The main goal is to evaluate historical LULC changes from 1994 to 2024 and forecast future trends for 2034 and 2044 utilizing the CA-Markov hybrid model combined with GIS methodologies.
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January 2025
Department of Automation, "Dunarea de Jos" University of Galati, 800008 Galati, Romania.
This paper deals with a "digital twin" (DT) approach for processing, reprocessing, and scrapping (P/R/S) technology running on a modular production system (MPS) assisted by a mobile cyber-physical robotic system (MCPRS). The main hardware architecture consists of four line-shaped workstations (WSs), a wheeled mobile robot (WMR) equipped with a robotic manipulator (RM) and a mobile visual servoing system (MVSS) mounted on the end effector. The system architecture integrates a hierarchical control system where each of the four WSs, in the MPS, is controlled by a Programable Logic Controller (PLC), all connected via Profibus DP to a central PLC.
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January 2025
Institut de Recherche en Informatique de Toulouse, IRIT UMR5505 CNRS, 31400 Toulouse, France.
This review explores the applications of Convolutional Neural Networks (CNNs) in smart agriculture, highlighting recent advancements across various applications including weed detection, disease detection, crop classification, water management, and yield prediction. Based on a comprehensive analysis of more than 115 recent studies, coupled with a bibliometric study of the broader literature, this paper contextualizes the use of CNNs within Agriculture 5.0, where technological integration optimizes agricultural efficiency.
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January 2025
Department of Civil Engineering, Myongji College, Seoul 03656, Republic of Korea.
Conventional approaches for the structural health monitoring of infrastructures often rely on physical sensors or targets attached to structural members, which require considerable preparation, maintenance, and operational effort, including continuous on-site adjustments. This paper presents an image-driven hybrid structural analysis technique that combines digital image processing (DIP) and regression analysis with a continuum point cloud method (CPCM) built on a particle-based strong formulation. Polynomial regressions capture the boundary shape change due to the structural loading and precisely identify the edge and corner coordinates of the deformed structure.
View Article and Find Full Text PDFAdv Healthc Mater
January 2025
Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zürich, Winterthurerstrasse 190, Zurich, 8057, Switzerland.
Efficient drug delivery remains a significant challenge in modern medicine and pharmaceutical research. Micrometer-scale robots have recently emerged as a promising solution to enhance the precision of drug administration through remotely controlled navigation within microvascular networks. Real-time tracking is crucial for accurate guidance and confirmation of target arrival.
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