A DECISION PROCESS FOR SURFACE MEDICAL EVACUATION ROUTING UNDER ADVERSARY THREAT AND UNCERTAIN DEMAND USING ONLINE OPTIMIZATION

Emerging threats have focused U.S. Navy operating concepts on agile, distributed tactical forces in the littoral and maritime zones. Given the nature of the threat and its location, medical evacuation via air may be infeasible due to hostile conditions or distance, requiring a shift to a surface or subsurface strategy. Medical demand and adversary actions are unpredictable in warfare, therefore a decision process for routing that accounts for uncertainty is required. Using the principles of the U.S. Marine Corps Rapid Response Planning Process and online optimization, we propose a decision process for surface medical evacuation routing against an adversary given uncertain demand that can be applied to manned and autonomous transport operations. We showcase the computational tractability of the decision process by developing an algorithm to route a medical transport through a network then implement the algorithm as a simulation model in Python. The base case of the model is compared to two modified cases under perfect information to discuss the risks of modeling with inappropriate assumptions. Multiple runs of the simulation model are then used to propose a process to develop a distance multiplier to estimate the impact of adversary presence in existing simulation models without a complete re-design.Outstanding ThesisLieutenant, United States NavyApproved for public release. Distribution is unlimited

2017 cardiovascular and stroke endpoint definitions for clinical trials

This publication describes uniform definitions for cardiovascular and stroke outcomes developed by the Standardized Data Collection for Cardiovascular Trials Initiative and the U.S. Food and Drug Administration (FDA). The FDA established the Standardized Data Collection for Cardiovascular Trials Initiative in 2009 to simplify the design and conduct of clinical trials intended to support marketing applications. The writing committee recognizes that these definitions may be used in other types of clinical trials and clinical care processes where appropriate. Use of these definitions at the FDA has enhanced the ability to aggregate data within and across medical product development programs, conduct meta-analyses to evaluate cardiovascular safety, integrate data from multiple trials, and compare effectiveness of drugs and devices. Further study is needed to determine whether prospective data collection using these common definitions improves the design, conduct, and interpretability of the results of clinical trials

2017 cardiovascular and stroke endpoint definitions for clinical trials

This publication describes uniform definitions for cardiovascular and stroke outcomes developed by the Standardized Data Collection for Cardiovascular Trials Initiative and the US Food and Drug Administration (FDA). The FDA established the Standardized Data Collection for Cardiovascular Trials Initiative in 2009 to simplify the design and conduct of clinical trials intended to support marketing applications. The writing committee recognizes that these definitions may be used in other types of clinical trials and clinical care processes where appropriate. Use of these definitions at the FDA has enhanced the ability to aggregate data within and across medical product development programs, conduct meta-analyses to evaluate cardiovascular safety, integrate data from multiple trials, and compare effectiveness of drugs and devices. Further study is needed to determine whether prospective data collection using these common definitions improves the design, conduct, and interpretability of the results of clinical trials

Astro2020: Decadal Survey on Astronomy and Astrophysics : State of the Profession Considerations for Laboratory Astrophysics

International audienceAstrophysics advances, in part, through laboratory astrophysics studies of the underlying processes controlling the observed properties of the Cosmos. These studies encompass both theoretical and experimental research. Robust support for laboratory astrophysics is critically needed to maximize the scientific return of astronomical observations

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International audienceIn this article, the name of the GLORIA-AF investigator Anastasios Kollias was given incorrectly as Athanasios Kollias in the Acknowledgements. The original article has been corrected