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Body image disturbance, consisting of an affective (body dissatisfaction) and perceptual (body distortion) component, is not only found in eating disorders, but is also present in healthy individuals, affecting their psychological well-being and everyday life. A higher body mass index is associated with higher body dissatisfaction, whereas results in relation to body distortion are mixed. Furthermore, body dissatisfaction is associated with a weight-related attentional bias. This study aimed to investigate the mediating role of a weight-related attentional bias in the relationship between body mass index and body image disturbance. Forty-one college women took part in a virtual reality and eye tracking procedure, in which the illusion of owning a virtual avatar with their body measurements was induced. During this procedure, body-related attentional bias was measured and afterwards body image disturbance was assessed. Mediation analysis revealed that weight-related attentional bias mediated the relationship between body mass index and body dissatisfaction (but not distortion). These findings suggest that modifying weight-related attentional bias would be a useful treatment target for improving body dissatisfaction. In addition, virtual reality technology could serve as an innovative method for modifying attentional bias in an ecologically valid way. HIGHLIGHTS: This Virtual Reality and Eye-Tracking study expands our knowledge about the relation between body mass index, body-related attention and body image disturbances. The results suggest that attentional bias towards weight-related body parts mediates the relation between BMI and body dissatisfaction. On the contrary, the relation between BMI and body distortion was not significant.

Body image disturbances (BIDs) have been widely studied using virtual reality (VR) devices that induce a full body illusion (FBI) and allow manipulation of the individual's perceptual and affective experiences of the body. This study aimed to assess whether the induction of the FBI over a virtual body would produce changes in body-related anxiety and BIDs using a new whole-body visuo-tactile stimulation procedure. Fifty non-clinical participants were randomly assigned to synchronous or asynchronous visuo-tactile groups. During the pre-assessment, all participants filled in BIDs and body-anxiety questionnaires. Then, they were embodied into two virtual bodies (VBs): firstly, with their real measurements, and secondly, with a larger-size body. Body image disturbances, body anxiety, fear of gaining weight, and FBI levels were assessed after exposure to each avatar. All participants in both conditions showed higher levels of BIDs and body anxiety after owning the larger-size VB than after owning the real-size VB (p < 0.05). The synchronous visuo-tactile group had higher scores, although the differences did not reach statistical significance. This study provides evidence of the usefulness of this new embodiment-based technique to induce changes in BIDs or body anxiety in a non-clinical sample, being suitable for use in future body image interventions.

In pre-hospital health care the call center plays an important role in the coordination of emergency medical services (EMS). An EMS call center handles inbound requests for EMS and dispatches an ambulance if necessary. The time needed for triage and dispatch is part of the total response time to the request, which, in turn, is an indicator for the quality of EMS. Calls entering an efficient EMS call center must have short waiting times, centralists should perform the triage efficiently and the dispatch of ambulances must be adequate and swift. This paper presents a detailed discrete event simulation model for EMS call centers. The model provides insight into the EMS call center processes and can be used to address strategic issues, such as capacity and workforce planning. We analyse results of the model that are based on real EMS call center data to illustrate the usefulness of the model.

To increase a 3D printer's throughput and decrease the print objects' lead times, composing good batches for 3D printers in high-volume 3D printing environments is of great importance. Since manual planners cannot oversee the whole production planning, they tend to make sub-optimal decisions. This paper presents a two-stage procedure that automatically generates batches for multiple 3D printers. The first stage consists of allocating objects to a batch. This problem is an extension of the classical one-dimensional bin packing problem by including lateness and object size mixture requirements. In the second stage, the positions of the print objects in a tray are determined by using third party three-dimensional packing software. By simulating the production planning of Shapeways, a popular 3D printing marketplace, model parameters are calibrated and the performance of the two-stage procedure is evaluated. The results show an increase of the throughput of the 3D-printers by approximately 10% in comparison with manually created batches.

A key challenge for an efficient splitting technique is defining the importance function. If the rare event set consists of multiple separated subsets this challenge becomes bigger since the most likely path to the rare event set may be very different from the most likely path to an intermediate level. We propose to mitigate this problem of path deviation by estimating the subset probabilities separately using a modified splitting technique. We compare the proposed separated splitting technique with a standard splitting technique by estimating the probability of entering either of two separated intervals on the real line. The squared relative error of the estimator is shown to be significantly higher when using standard splitting than when using separated splitting. We show that this difference increases if the rare event probability becomes smaller, illustrating the advantage of the separated splitting technique.

Safety planning for crowd evacuation is an important and active research topic nowadays. One important issue is to devise the evacuation plans of individuals in emergency situations so as to reduce the total evacuation time. This paper proposes a novel evolutionary algorithm (EA)-based methodology, together with agent-based crowd simulation, to solve the evacuation planning problem. The proposed method features a novel segmentation strategy which divides the entire evacuation region into sub-regions based on a discriminant function. Each sub-region is assigned with an exit gate, and individuals in a sub-region will run toward the corresponding exit gate for evacuation. In this way, the evacuation planning problem is converted to a symbolic regression problem. Then an evolutionary algorithm, using agent-based crowd simulation as fitness function, is developed to search for the global optimal solution. The simulation results on different scenarios demonstrate that the proposed method is effective to reduce the evacuation time.

Background: Device-associated healthcare-acquired infections (DA-HAI) pose a threat to patient safety, particularly in the intensive care unit (ICU). We report the results of the International Infection Control Consortium (INICC) study conducted in Turkey from August 2003 through October 2012. Methods: A DA-HAI surveillance study in 63 adult, paediatric ICUs and neonatal ICUs (NICUs) from 29 hospitals, in 19 cities using the methods and definitions of the U.S. NHSN and INICC methods. Results: We collected prospective data from 94,498 ICU patients for 647,316 bed days. Pooled DA-HAI rates for adult and paediatric ICUs were 11.1 central line-associated bloodstream infections (CLABSIs) per 1000 central line (CL)-days, 21.4 ventilator-associated pneumonias (VAPs) per 1000 mechanical ventilator (MV)-days and 7.5 catheter-associated urinary tract infections (CAUTIs) per 1000 urinary catheter-days. Pooled DA-HAI rates for NICUs were 30 CLABSIs per 1000 CL-days, and 15.8 VAPs per 1000 MV-days. Extra length of stay (LOS) in adult and paediatric ICUs was 19.4 for CLABSI, 8.7 for VAP and 10.1 for CAUTI. Extra LOS in NICUs was 13.1 for patients with CLABSI and 16.2 for patients with VAP. Extra crude mortality was 12% for CLABSI, 19.4% for VAP and 10.5% for CAUTI in ICUs, and 15.4% for CLABSI and 10.5% for VAP in NICUs. Pooled device use (DU) ratios for adult and paediatric ICUs were 0.54 for MV, 0.65 for CL and 0.88 for UC, and 0.12 for MV, and 0.09 for CL in NICUs. The CLABSI rate was 8.5 per 1,000 CL days in the Medical Surgical ICUs included in this study, which is higher than the INICC report rate of 4.9, and more than eight times higher than the NHSN rate of 0.9. Similarly, the VAP and CAUTI rates were higher compared with U. S. NHSN (22.3 vs. 1.1 for VAP; 7.9 vs. 1.2 for CAUTI) and with the INICC report (22.3 vs. 16.5 in VAP; 7.9 vs. 5.3 in CAUTI). Conclusions: DA-HAI rates and DU ratios in our ICUs were higher than those reported in the INICC global report and in the US NHSN report.