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OBJECTIVES: The present study investigates whether space syntax offers appropriate tools for identifying risks of aggression, interventional opportunities, and environmental design strategies to reduce the risk of Type II violence in emergency departments. BACKGROUND: Although healthcare workers are a relatively small percentage of the U.S. workforce, they sustain almost 75% of workplace assaults. Poor environmental design has been identified as an antecedent to aggression by patients and/or their companions. METHOD: Guided by Rational Choice Theory, Lifestyle Exposure Theory, Routine Activity Theory, and Crime Prevention through Environmental Design (CPTED), the study uses five visibility graph analysis (VGA) measures: visibility, control, controllability, mean visual depth, and occlusivity. Three U.S. hospital-based emergency departments were selected. First, a VGA was performed on all three layouts. A second VGA was performed after excluding unconnected spaces, and a third was performed on key patient and staff areas. Last, a fourth VGA was conducted after performing physical modifications to the three departments. RESULTS: Statistical analysis revealed significant differences in VGA measures not only between different layouts but also between the original and modified layouts. Specifically, small changes created by architectural features can affect visual access and exposure as measured by space syntax. Alcove-style spaces in key staff areas are also associated with limited visual control of the local environment. Typically, in smaller zones, central staff workstations afford better control of patient spaces. CONCLUSION: This study shows that space syntax analysis is a useful tool for identifying risks of aggression in hospital spaces and for identifying interventional opportunities.

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Background: Autonomic nerve system (ANS) plays an important role in regulating cardiovascular function and cerebrovascular function. Traditional heart rate variation (HRV) and emerging skin sympathetic nerve activity (SKNA) analyses from ultra-short-time (UST) data cannot fully reveal neural activity, thereby quantitatively reflect ANS intensity. Methods: Electrocardiogram and SKNA from sixteen patients (seven cerebral hemorrhage (CH) patients and nine control group (CO) patients) were recorded using a portable device. Ten derived HRV (mean, standard deviation and root mean square difference of sinus RR intervals (NNmean, SDNN and RMSSD), ultra-low frequency (<0.003 Hz, uLF), very low frequency ([0.003 Hz, 0.04 Hz), vLF), low frequency ([0.04 Hz, 0.15 Hz), LF) and high frequency power ([0.15 Hz, 0.4 Hz), HF), ratio of LF to HF (LF/HF), the standard deviation of instantaneous beat-to-beat R-R interval variability (SD1), and approximate entropy (ApEn)) and ten visibility graph (VG) features (diameter (Dia), average node degree (aND), average shortest-path length (aSPL), clustering coefficient (CC), average closeness centrality (aCC), transitivity (Trans), average degree centrality (aDC), link density (LD), sMetric (sM) and graph energy (GE) of the constructed complex network) were compared on 5-min and UST segments to verify their validity and robustness in discriminating CH and CO under different data lengths. Besides, their potential for quantifying ANS-Load were also investigated. Results: The validation results of HRV and VG features in discriminating CH from CO showed that VG features were more clearly distinguishable between the two groups than HRV features. For effectiveness evaluation of analyzing ANS on UST segment, the NNmean, SDNN, RMSSD, LF, HF and LF/HF in HRV features and the CC, Trans, Dia and GE of VG features remained stable in both activated and inactivated segments across all data lengths. The capability of HRV and VG features in quantifying ANS-Load were evaluated and compared under different ANS-Load, the results showed that most HRV features (SDNN, LFHF, RMSSD, vLF, LF and HF) and almost all VG features were correlated to sympathetic nerve activity intensity. Conclusions: The proposed autonomic nervous activity analysis method based on VG and SKNA offers a new insight into ANS assessment in UST segments and ANS-Load quantification.

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This paper examines visitors' movement patterns at the Broad Museum designed by Zaha Hadid. Characterized with free, open, and generally unbound spaces, visitors explore a curated exhibition at their own pace, route, and agenda. Unlike most other public environments, a museum lends visitors greater choice and control, and does not hold the social or spatial expectations of other facility types that might subject the visitor's path of travel. In this study, 72 visitors were observed. A space syntax-based visibility graph analysis (VGA) was then performed to compute the visibility exposure and the spatial position of each exhibit within the museum. Negative binomial regression was used to look at the effects of spatial variables on visitors' wayfinding, contact, and engagement with the pieces. Results showed that both the amount of visibility area around each exhibit, and its spatial position measured using space syntax techniques explained why visitors established a contact with the piece and their wayfinding behavior. Interestingly, however, the saliency of exhibits along with spatial variables were both strong predictors for why people arriving in groups split to engage with that particular exhibit. The simulation used in this study could be useful in curatorial decisions.

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The physical spaces within which organisms live affect their biology and in many cases can be considered part of their extended phenotype. The nests of social insect societies have a fundamental impact on their ability to function as complex superorganisms. Ants in many species excavate elaborate subterranean nests, but others inhabit relatively small pre-formed cavities within rock crevices and hollow seeds. Temnothorax ants, which often nest within acorns, have become a model system for studying collective decision making. While these ants have demonstrated remarkable degrees of rationality and consistent precision with regard to their nest choices, never before has the fine scale internal architecture and spatial organization of their nests been investigated. We used X-ray microtomography to record high-resolution three-dimensional (3D) scans of Temnothorax colonies within their acorns. These data were then quantified using image segmentation and surface-based 3D visibility graph analysis, a new computational methodology for analysing spatial structures. The visibility graph analysis method integrates knowledge from the field of architecture with the empirical study of animal-built structures, thus providing the first methodological cross-disciplinary synergy of these two research areas. We found a surprisingly high surface area and degree of spatial heterogeneity within the acorn nests. Specific regions, such as those associated with the locations of queens and brood, were significantly more conducive to connectivity than others. From an architect's point of view, spatial analysis research has never focused on all-surface 3D movement, as we describe within ant nests. Therefore, we believe our approach will provide new methods for understanding both human design and the comparative biology of habitat spaces.This article is part of the theme issue 'Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour'.

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