This article presents an asset-level security risk management framework to assist stakeholders of critical assets with allocating limited budgets for enhancing their safety and security against terrorist attack. The proposed framework models the security system of an asset, considers various threat scenarios, and models the sequential decision framework of attackers during the attack. Its novel contributions are the introduction of the notion of partial neutralization of attackers by defenders, estimation of total loss from successful, partially successful, and unsuccessful actions of attackers at various stages of an attack, and inclusion of the effects of these losses on the choices made by terrorists at various stages of the attack. The application of the proposed method is demonstrated in an example dealing with security risk management of a U.S. commercial airport, in which a set of plausible threat scenarios and risk mitigation options are considered. It is found that a combination of providing blast-resistant cargo containers and a video surveillance system on the airport perimeter fence is the best option based on minimum expected life-cycle cost considering a 10-year service period.
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http://dx.doi.org/10.1111/risa.12266 | DOI Listing |
JAMA Netw Open
January 2025
Division of Surgical Oncology, University of Utah, Salt Lake City.
Importance: An increasing number of older adults are undergoing surgery. Older adults face significant challenges throughout the spectrum of perioperative care. No frameworks exist to support primary care clinicians in helping older adults navigate perioperative care beyond preoperative medical clearance.
View Article and Find Full Text PDFACS Sens
January 2025
Department of Engineering Physics, McMaster University, 1280 Main Street West, L8S 4L8 Hamilton, Ontario, Canada.
Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds based on receiver operating characteristic (ROC) curves, which can be limited in accuracy for complex and variable signals. To address these limitations, we developed a framework that facilitates the application of machine learning (ML) to diagnostic data for the binary classification of clinical samples, when using real-time electrochemical measurements. The framework was applied to a real-time multimeric aptamer assay (RT-MAp) that captures single-frequency (12.
View Article and Find Full Text PDFJ Orthop Sports Phys Ther
February 2025
On-pitch rehabilitation is a crucial part of returning to sport after injury in elite soccer. The () initially offered a framework for practitioners to plan on-pitch rehabilitation, focusing on physical preparation and sport specificity. However, our experiences with the , combined with recent research in injury neurophysiology, point to a need for an updated model that integrates practice design and physical-cognitive interactions.
View Article and Find Full Text PDFJ Evid Based Soc Work (2019)
January 2025
College of Social Work, University of Kentucky, Lexington, Kentucky, US.
Purpose: This scoping review explored the nature and challenges of transnational family caregiving. International migration and global aging have resulted in growing instances of transnational family caregiving, which involves providing care for older adults across national borders. However, little is known about the realities of such caregiving.
View Article and Find Full Text PDFEcol Appl
January 2025
Smithsonian National Zoo and Conservation Biology Institute, Conservation Ecology Center, Front Royal, Virginia, USA.
Fencing is one of the most widely utilized tools for reducing human-wildlife conflict in agricultural landscapes. However, the increasing global footprint of fencing exceeds millions of kilometers and has unintended consequences for wildlife, including habitat fragmentation, movement restriction, entanglement, and mortality. Here, we present a novel and quantitative approach to prioritize fence removal within historic migratory pathways of white-bearded wildebeest (Connochaetes taurinus) across Kenya's Greater Masai Mara Ecosystem.
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