This exemplar highlights how geospatial information technology was effective in supporting academic practice, faculty outreach, and education initiatives at the University of Mississippi School of Nursing. Using this cutting-edge technology created a community-based prototype for fully integrating point-of-service research, practice, and academics into a cohesive strategy to influence change within the health care delivery system. This exemplar discusses ways this knowledge benefits practice and curriculum development; informs critical decision making affecting the people we serve; underscores the vital role nurses play in linking this technology to practice; and develops community residents as partners in their own health and that of the community.
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http://dx.doi.org/10.3928/01484834-20040201-01 | DOI Listing |
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June 2025
Department of Computer Engineering, Pimpri Chinchwad College of Engineering, Nigdi, Pune 411044, India.
Recent advancements in artificial intelligence (AI) have increased interest in intelligent transportation systems, particularly autonomous vehicles. Safe navigation in traffic-heavy environments requires accurate road scene segmentation, yet traditional computer vision methods struggle with complex scenarios. This study emphasizes the role of deep learning in improving semantic segmentation using datasets like the Indian Driving Dataset (IDD), which presents unique challenges in chaotic road conditions.
View Article and Find Full Text PDFInt J Equity Health
January 2025
Global Health Policy and Data Institute, San Diego, CA, USA.
Throughout the COVID-19 pandemic, underserved populations, such as racial and ethnic minority communities, were disproportionately impacted by illness and death. Ensuring people from diverse backgrounds have the ability to participate in clinical trials is key to advancing health equity. We sought to analyze the spatial variability in locations of COVID-19 trials sites and to test associations with demographic correlates.
View Article and Find Full Text PDFEnviron Manage
January 2025
Department of Geoecology, Institute of Geosciences and Geography, Martin Luther University, Halle-Wittenberg, Halle (Saale), Germany.
In the face of unabated urban expansion, understanding the intrinsic characteristics of landscape structure is pertinent to preserving ecological diversity and managing the supply of ecosystem services. This study integrates machine-learning-based geospatial and landscape ecological techniques to assess the dynamics of landscape structure in cities of the rainforest (Akure and Owerri) and Guinea savanna (Makurdi and Minna) ecological regions of Nigeria between 1986 and 2022. Supervised classification using the random forest (RF) machine-learning classifier was performed on Landsat images on the Google Earth Engine (GEE) platform, and landscape metrics were calculated with FRAGSTATS to assess landscape composition, configuration, and connectivity.
View Article and Find Full Text PDFSci Data
January 2025
Department of Biology, McGill University, Montreal, Canada.
Arctic coasts constitute the critical interface between land and sea, and are subject to rapid changes caused by a warming climate. Current trends throughout the Arctic show increasing erosion trends, while other parts of the coast are experiencing prograding trends. Until now, a vast majority of our knowledge of Arctic coastal evolution is confined to site-specific studies with limited geospatial representation.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Nectar Technologies Inc., 6250 Rue Hutchison #302, Montréal, QC, Canada. Electronic address:
Honey bees (Apis mellifera) play an important role in our agricultural systems. In recent years, beekeepers have reported high colony mortality rates in several parts of the world. Inadequate foraging landscapes are often cited as a major factor deterring honey bee colony health.
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