Development and usability testing of a fully immersive VR simulation for REBOA training.

BACKGROUND Resuscitative endovascular balloon occlusion of the aorta (REBOA) is a potentially life-saving procedure for bleeding trauma patients. Being a rare and complex procedure performed in extreme situations, repetitive training of REBOA teams is critical. Evidence-based guidelines on how to train REBOA are missing, although simulation-based training has been shown to be effective but can be costly and complex. We aimed to determine the feasibility and acceptance of REBOA training using a fully immersive virtual reality (VR) REBOA simulation, as well as assess the confidence in conducting the REBOA procedure before and after the training. METHODS Prospective feasibility pilot study of prehospital emergency physicians and paramedics in Bern, Switzerland, from November 2020 until March 2021. Baseline characteristics of trainees, prior training and experience in REBOA and with VR, variables of media use (usability: system usability scale, immersion/presence: Slater-Usoh-Steed, workload: NASA-TLX, user satisfaction: USEQ) as well as confidence prior and after VR training were accessed. RESULTS REBOA training in VR was found to be feasible without relevant VR-specific side-effects. Usability (SUS median 77.5, IQR 71.3-85) and sense of presence and immersion (Slater-Usoh-Steed median 4.8, IQR 3.8-5.5) were good, the workload without under-nor overstraining (NASA-TLX median 39, IQR 32.8-50.2) and user satisfaction high (USEQ median 26, IQR 23-29). Confidence of trainees in conducting REBOA increased significantly after training (p < 0.001). CONCLUSIONS Procedural training of the REBOA procedure in immersive virtual reality is possible with a good acceptance and high usability. REBOA VR training can be an important part of a training curriculum, with the virtual reality-specific advantages of a time- and instructor-independent learning

Remarkable change in age-specific breast cancer incidence in the Swiss canton of Geneva and its possible relation with the use of hormone replacement therapy

BACKGROUND: This article aims to explain the reasons for the remarkable change in age of breast cancer occurrence in the Swiss canton of Geneva. METHODS: We used population-based data from the Geneva cancer registry, which collects information on method of detection, stage and tumour characteristics since 1975. For patients diagnosed between 1997–2003, we obtained additional information on use of hormone replacement therapy from a large prospective study on breast cancer. Using generalized log linear regression analysis, we compared age-specific incidence rates with respect to period, stage, oestrogen receptor status, method of detection and use of hormone replacement therapy. RESULTS: In the periods 1975–1979 and 1985–1989, breast cancer risk increased with age, showing the highest incidence rates among women aged ≥ 85 years. From 1997, the age-specific incidence curve changed completely (p < 0.0001), showing an incidence peak at 60–64 years and a reduced incidence among elderly women. This incidence peak concerned mainly early stage and oestrogen positive cancers and was exclusively observed among women who ever used hormone replacement therapy, regardless whether the tumour was screen-detected or not. CONCLUSION: The increasing prevalence of hormone replacement therapy use during the 1990s could explain the important change in age-specific breast cancer incidence, not only by increasing breast cancer risk, but also by revealing breast cancer at an earlier age

Conceptual Model and Architecture of MAFTIA

This deliverable builds on the work reported in [MAFTIA 2000] and [Powell and Stroud 2001]. It contains a further refinement of the MAFTIA conceptual model and a revised discussion of the MAFTIA architecture. It also introduces the work done in MAFTIA on verification and assessment of security properties, which is reported on in more detail in [Adelsbach and Creese 2003

Track D Social Science, Human Rights and Political Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138414/1/jia218442.pd

Behavioral distance measurement using hidden markov models

Abstract. The behavioral distance between two processes is a measure of the deviation of their behaviors. Behavioral distance has been proposed for detecting the compromise of a process, by computing its behavioral distance from another process executed on the same input. Provided that the two processes are diverse and so unlikely to fall prey to the same attacks, an increase in behavioral distance might indicate the compromise of one of them. In this paper we propose a new approach to behavioral distance calculation using a new type of Hidden Markov Model. We also empirically evaluate the intrusion detection capability of our proposal when used to measure the distance between the system-call behaviors of diverse web servers. Our experiments show that it detects intrusions with substantially greater accuracy and with performance overhead comparable to that of prior proposals

Additional file 1 of Development and usability testing of a fully immersive VR simulation for REBOA training

Additional file 1. Some free-text comments from participants. Free-text responses were collected with an open response item. Comments of the participants generally indicated a good acceptance. However, critical aspects were illuminated as well