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Tracking the Ghosts of the Himalayas: Snow Leopard Conservation Insights From Satellite Collar Data.
Ecol Evol
January 2025
Département de Biologie, Chimie et Géographie Université du Québec à Rimouski Rimouski Quebec Canada.
This study presents the first movement analysis of snow leopards () using satellite telemetry data, focusing on the northeastern Himalayas of Nepal. By examining GPS-based satellite collar data between 2013 and 2017 from five collared snow leopards (effectively three individuals), the research uncovered distinct movement patterns, activity budgeting and home range utilisation from one adult male and two sub adult females. Hidden Markov models (HMMs) revealed three behavioural states based on the movement patterns-slow (indicative of resting), moderate and fast (associated with travelling) and demonstrated that the time of day influenced their behavioural state.
View Article and Find Full Text PDFA big data analysis algorithm for massive sensor medical images.
PeerJ Comput Sci
November 2024
Research Center, Future University in Egypt, New Cairo, Egypt.
Article Synopsis
- Big data analytics is revolutionizing clinical decision-making by utilizing vast healthcare data to create evidence-based solutions, but it raises significant privacy and security concerns, especially regarding sensitive medical images stored in the cloud.
- The proposed project aims to enhance patient care through a machine learning-based anomaly detection system for medical images, addressing current limitations in existing detection methods that struggle with resource consumption and real-time performance.
- The research focuses on improving data processing techniques, including feature selection and handling missing values, employing advanced algorithms like recursive feature elimination and dynamic principal component analysis for more effective anomaly detection.
Compact Arterial Monitoring Device Use in Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA): A Simple Validation Study in Swine.
Cureus
October 2024
Department of Anesthesiology, Uniformed Services University of the Health Sciences, Bethesda, USA.
Article Synopsis
- - Hemorrhage is the main cause of preventable death in trauma situations, leading to military and civilian advancements in medical practices, particularly through the use of tourniquets to manage extremity bleeding and save lives.
- - While tourniquets have significantly decreased deaths from bleeding in military settings, noncompressible hemorrhage still poses a major risk, especially before patients receive definitive medical care.
- - The study explores using a small, disposable pressure monitor during resuscitative endovascular balloon occlusion of the aorta (REBOA) to enhance blood pressure monitoring, facilitate better resuscitation practices, and reduce the need for blood products in extreme environments.
Vegetation cover, topography, and low-traffic roads influence Sonoran desert tortoise (Gopherus morafkai) movement and habitat selection.
Mov Ecol
September 2024
Department of Natural Resource Management, Texas Tech University, Goddard Building, Box 42125, Lubbock, TX, 79409-2125, USA.
Background: Anthropogenic activities occurring throughout the Sonoran Desert are replacing and fragmenting habitat and reducing landscape connectivity for the Sonoran desert tortoise (Gopherus morafkai). Understanding how the structure of the landscape influences tortoise habitat use and movement can help develop strategies for mitigating the impacts of these landscape alterations, which are conservation actions needed to support the species' long-term persistence. However, how natural and anthropogenic features influence fine-scale habitat use and movement of Sonoran desert tortoises remains unclear.
View Article and Find Full Text PDFA New Method for Low Density Distribution Modeling and Near Threatened Species: The Study Case of Plectrohyla Guatemalensis.
Bull Math Biol
June 2024
Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Mexico City, Mexico.
We introduce a model that can be used for the description of the distribution of species when there is scarcity of data, based on our previous work (Ballesteros et al. J Math Biol 85(4):31, 2022). We address challenges in modeling species that are seldom observed in nature, for example species included in The International Union for Conservation of Nature's Red List of Threatened Species (IUCN 2023).
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