Introduction: Overcrowded emergency departments (ED) and undifferentiated patients make the provision of care and resources challenging. We examined whether machine learning algorithms could identi...

5G has opened up possibilities of introducing new use cases and business models that could not be perceived before. In the context of public safety, 5G offers immense opportunities towards enhancing mission success and situation awareness during emergency management. This paper introduces Back-Situation Awareness (BSA) application enabling early warning/notification to vehicles of an approaching emergency vehicle indicating its presence and the time it will arrive. Such an application is expected to give drivers enough time to create a safety corridor for the emergency vehicle to pass through safely and unhindered. We provide details on the system and application design of the BSA application leveraging Multi-Access Edge Computing (MEC) systems that complement the 5G mobile communication system. An evaluation of the application is provided by using data measurements and indicating the accuracy of the computation and notification of the Estimated Time of Arrival (ETA) based on the ETSI C-ITS protocol messages.

ABSTRACT Research on the effect of school uniforms on school attendance in low income countries is scarce. Building on a meta-analysis of the available literature, this paper analyses primary survey data collected (n = 462) in Mongolia on students’ perceptions of school uniforms. The findings reveal that it is not only the cost of uniforms that matters, but also poor students’ feelings of exclusion when the majority of students in a school wear uniforms. The poor drop out from school when their symbolic association with the majority is visibly broken through their inability to afford and wear school uniforms. The study suggests that school uniform policies in low income countries are fraught with complications. Instead of creating cohesion, such policies are more likely to affect poor students’ negative perceptions of themselves and play a strong role in dropout rates.

Mammograms contain information that predicts breast cancer risk. We developed two novel mammogram‐based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). Their risk prediction when fitted together, and with an established measure of conventional mammographic density (Cumulus), is not known. We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen‐detected cases and 1197 matched controls; and 354 younger‐diagnosis cases and 944 controls frequency‐matched for age at mammogram. We conducted conditional and unconditional logistic regression analyses of individually‐ and frequency‐matched studies, respectively. We estimated measure‐specific risk gradients as the change in odds per standard deviation of controls after adjusting for age and body mass index (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). For interval, screen‐detected and younger‐diagnosis cancer risks, the best fitting models (OPERAs [95% confidence intervals]) involved: Cumulus (1.81 [1.41‐2.31]) and Cirrus (1.72 [1.38‐2.14]); Cirrus (1.49 [1.32‐1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27‐1.68]), respectively. The AUCs were: 0.73 [0.68‐0.77], 0.63 [0.60‐0.66], and 0.72 [0.69‐0.75], respectively. Combined, our new mammogram‐based measures have twice the risk gradient for screen‐detected and younger‐diagnosis breast cancer (P ≤ 10−12), have at least the same discriminatory power as the current polygenic risk score, and are more correlated with causal factors than conventional mammographic density. Discovering more information about breast cancer risk from mammograms could help enable risk‐based personalised breast screening.

Due to its high lethality among older people, the safety of nursing homes has been of central importance during the COVID-19 pandemic. With test procedures and vaccines becoming available at scale, nursing homes might relax prohibitory measures while controlling the spread of infections. By control we mean that each index case infects less than one other person on average. Here, we develop an agent-based epidemiological model for the spread of SARS-CoV-2 calibrated to Austrian nursing homes to identify optimal prevention strategies. We find that the effectiveness of mitigation testing depends critically on test turnover time (time until test result), the detection threshold of tests and mitigation testing frequencies. Under realistic conditions and in absence of vaccinations, we find that mitigation testing of employees only might be sufficient to control outbreaks if tests have low turnover times and detection thresholds. If vaccines that are 60% effective against high viral load and transmission are available, control is achieved if 80% or more of the residents are vaccinated, even without mitigation testing and if residents are allowed to have visitors. Since these results strongly depend on vaccine efficacy against infection, retention of testing infrastructures, regular testing and sequencing of virus genomes is advised to enable early identification of new variants of concern.

High-harmonic generation by aligned diatomic molecules in orthogonally po-larized two-color laser fields is considered using the molecular strong-field approximation. Regions of the parameter space with large harmonic ellipticity are identified.

The search for effective coronavirus disease (COVID-19) therapy has attracted a great deal of scientific interest due to its unprecedented health care system overload worldwide. We have carried out a study to investigate the in silico effects of the most abundant pomegranate peel extract constituents on the multi-step process of serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) internalization in the host cells. Binding affinities and interactions of ellagic acid, gallic acid, punicalagin and punicalin were studied on four selected protein targets with a significant and confirmed role in the process of the entry of virus into a host cell. The protein targets used in this study were: SARS-CoV-2 spike glycoprotein, angiotensin-converting enzyme 2, furin and transmembrane serine protease 2. The results showed that the constituents of pomegranate peel extracts, namely punicalagin and punicalin had very promising potential for significant interactions with the selected protein targets and were therefore deemed good candidates for further in vitro and in vivo evaluation.

Abstract This article examines the social and political effects produced by the most recent wave of emigration in postwar Bosnia, widely understood to be the result of continued political instability and economic decline that followed the 1992–95 war. Drawing on ethnographic research in a deindustrialized Bosnian town and analysis of popular discourses seeking to make sense of this new wave of departures, I show how the phenomenon of postwar exit impacts those staying behind and inspires new forms of reflection that link past histories of violence to more recent forms of dispossession. The emergence of such forms of historical consciousness reveals that postwar migration is haunted both by the memory of wartime expulsions and ethnic cleansing, as well as by the often-unacknowledged violence of postwar economic restructuring glossed as the postsocialist transition. In asking what happens to nationalist regimes, as well as scholarship on nationalist politics, when the “people” leave, I demonstrate the need to analyze the ongoing out-migration both in terms of Bosnia’s historical specificity and global political-economic dynamics. In so doing, I show how absences created by these departures create new vantage points that bring to light and expose unsettling political configurations left behind by the Bosnian war.

Fluid-Structure Interaction (FSI) simulations have applications to a wide range of engineering areas. One popular technique to solve FSI problems is the Arbitrary Lagrangian-Eulerian (ALE) method. Both academic and industry communities developed codes to implement the ALE method. One of them is Alya, a Finite Element Method (FEM) based code developed in Barcelona Supercomputing Center (BSC). By analyzing the application on a simplified artery case and compared to another commercial code, which is Finite Volume Method (FVM) based, this paper discusses the mathematical background of the solver for domains, and carries out verification work on Alya’s FSI capability. The results show that while both codes provide comparable FSI results, Alya has exhibited better robustness due to its Subgrid Scale (SGS) technique for stabilization of convective term and the subsequent numerical treatments. Thus this code opens the door for more extensive use of higher fidelity finite element based FSI methods in future.