VR-Decision : a Prototype for Experimenting the Benefits of Virtual Reality in Military Operations Planning

Le processus militaire de planification d’opérations subit une transformation : si aujourd’hui les experts sont pour la plupart du temps localisés au même endroit, la réduction de la vulnérabilité des structures physiques doit passer par leur éclatement, en permettant la répartition des membres des états-majors dans des lieux différents. Dans cette optique, la réalité virtuelle paraît appropriée pour ouvrir la voie à des dispositifs offrant de nouvelles possibilités de visualisation, d’interaction et de collaboration synchrone à distance. Le projet VR-Decision a pour objectif d’évaluer les apports de la réalité virtuelle pour une activité collaborative de planification militaire au niveau opératif. Dans cet article, nous présentons le prototype que nous développons, ainsi que le processus ayant conduit à sa conception.The military process of planning operations is undergoing a transformation: if today the experts are mostly located in the same place, the reduction of the vulnerability of the physical structures must pass by their splitting, by allowing the distribution of the members of the staff in different places. From this point of view, virtual reality seems appropriate to open the way to devices offering new possibilities of visualization, interaction and synchronous remote collaboration. The VR-Decision project aims at evaluating the contribution of virtual reality to a collaborative military planning activity at the operational level. In this article, we present the prototype we are developing, as well as the process that led to its conception

Effets de la distance, de la luminosité et de l’angle de calibration sur la précision et la justesse de lunettes d’eye-tracking : une étude exploratoire

Les systèmes d’eye-tracking permettent d’étudier les comportements visuels. Pour que les données de ces systèmes soient précises, la calibration est primordiale. Une bonne calibration se traduit par des valeurs de précision et de justesse faibles. Dans cette étude exploratoire, pour évaluer l’effet de la distance, de la luminosité et de l’angle de calibration sur la précision et la justesse de lunettes d’eye-tracking, des mesures ont été effectuées en champ visuel proche, intermédiaire et éloigné sur un écran de calibrage. Neuf combinaisons de calibration ont été testées selon un plan en carré latin. La distance, la luminosité et l’angle de calibration n’ont pas d’effet significatif sur la précision et la justesse des lunettes. A l’inverse, la précision et la justesse des lunettes sont meilleures en champ éloigné, qu’en champ proche et intermédiaire. Ces résultats montrent que les lunettes d’eye-tracking sont davantage adaptées à des études de terrain

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Essential omega-3 fatty acids tune microglial phagocytosis of synaptic elements in the mouse developing brain

AbstractOmega-3 fatty acids (n-3 PUFAs) are essential for the functional maturation of the brain. Westernization of dietary habits in both developed and developing countries is accompanied by a progressive reduction in dietary intake of n-3 PUFAs. Low maternal intake of n-3 PUFAs has been linked to neurodevelopmental diseases in Humans. However, the n-3 PUFAs deficiency-mediated mechanisms affecting the development of the central nervous system are poorly understood. Active microglial engulfment of synapses regulates brain development. Impaired synaptic pruning is associated with several neurodevelopmental disorders. Here, we identify a molecular mechanism for detrimental effects of low maternal n-3 PUFA intake on hippocampal development in mice. Our results show that maternal dietary n-3 PUFA deficiency increases microglia-mediated phagocytosis of synaptic elements in the rodent developing hippocampus, partly through the activation of 12/15-lipoxygenase (LOX)/12-HETE signaling, altering neuronal morphology and affecting cognitive performance of the offspring. These findings provide a mechanistic insight into neurodevelopmental defects caused by maternal n-3 PUFAs dietary deficiency.Infrastructure de Recherche Translationnelle pour les Biothérapies en NeurosciencesProgram Initiative d’Excellenc

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

The machine as a partner: Human-machine teaming design using the PRODEC method

BACKGROUND: Human-machine teaming (HMT) typically combines perspectives from systems engineering, artificial intelligence (AI) and human-centered design (HCD), to achieve human systems integration (HSI) through the development of an integrative systems representation that encapsulates human and machine attributes and properties. OBJECTIVE: The study explores the main factors contributing to performance, trust and collaboration between expert human operators and increasingly autonomous machines, by developing and using the PRODEC method. PRODEC supports HSI by improving the agile HCD of advanced sociotechnical systems at work, which qualify as human-machine teamwork. METHODS: PRODEC incorporates scenario-based design and human-in-the-loop simulation at design and development time of a sociotechnical system. It is associated with the concept of digital twin. A systemic representation was developed and used, associated with metrics for the evaluation of human-machine teams. RESULTS: The study is essentially methodological. In practice, PRODEC has been used and validated in the MOHICAN project that dealt with the integration of pilots and virtual assistants onboard advanced fighter aircraft. It enabled the development of appropriate metrics and criteria of performance, trust, collaboration, and tangibility (i.e., issues of complexity, maturity, flexibility, stability, and sustainability), which were associated with the identification of emergent functions that help redesign and recalibrate the air combat virtual assistant as well as fighter pilot training. CONCLUSION: PRODEC addresses the crucial issue of how AI systems could and should influence requirements and design of sociotechnical systems that support human work, particularly in contexts of high uncertainty. However, PRODEC is still work in progress and advanced visualization techniques and tools are needed to increase physical and figurative tangibility

Syst. Eng.

AbstractThe purpose of the PRODEC scenario‐based design method is the incremental cross‐fertilization and refinement of procedural scenarios and declarative configurations. It uses virtual prototypes of the developed systems (mainly life‐critical systems) to conduct human‐in‐the‐loop simulations (HITLSs). Based on human systems integration (HSI) principles and criteria, as well as expertise and experience in the domain at stake, this HSI approach grounded in virtual environments requires a clear definition of physical and cognitive tangibility metrics to assess the distance between virtual and tangible (grasp) dimensions of the system being developed when it is put to work. PRODEC considers human and machine systems described in terms of structures and functions incrementally designed using procedural scenarios (i.e., stories) in task and activity networks, which provide life to declarative configurations (i.e., system's functions and structures). This active modeling and simulation process enables the discovery of emergent structures and functions of the system being developed when it is virtually operated. PRODEC's use is illustrated in an example. We discuss the use of PRODEC and its results as to how they can be used with digital twins

Relationships Between Personality Factors, Stress and GPA

•Has undergraduate stress increased over the years? •Is Conscientiousness positively correlated with GPA? •Is Neuroticism positively correlated with stress? •Investigate the correlation between neuroticism and GPA. •Investigate correlations between other traits, GPA, and stress

Classification with Synthetic Radio Data for Real-life Environment Sensing

International audienceIn sensing-enabled mobile infrastructure, the network itself acts as a whole sensor by leveraging radio data or signals collected within Base Stations (BSs). This data is exploited for the development of data-driven machine learning solutions to augment network's capabilities. Nevertheless, largescale qualitative data is required for achieving high accuracy learning. However, their training phase leads to prohibitive cost and heavy constraints on data collection and storage that are not desirable for network. To overcome this problem, we propose to use synthetic data instead of real data for training machine learning models to avoid high cost data sharing/storage. In this paper, we are interested in real-life Environment Sensing Network in a context of limited data amount sharing. We focus on Indoor-Outdoor Detection (IOD) using unsupervised machine learning classification models. For this purpose, experiments are conducted following the paradigm of Training on Synthetic data and Testing on Real Data (TSTR). We conduct a comparative study of four well-known generative models, that are able to generate synthetic 3GPP radio data with similar distribution than the source data. We investigate the quality of these synthetic generated radio data according to three dimensions: distribution similarity, data variability and detection capability. The classification models trained with synthetic generated data are tested in real-life context to infer whether a user connected to the network is inside or outside a building. The study shows convincing results with an Indoor/Outdoor unsupervised classification performance up to 80% of F1−score like in real-life data training scenarios