Extremely large scale simulation of a Kardar-Parisi-Zhang model using graphics cards

The octahedron model introduced recently has been implemented onto graphics cards, which permits extremely large scale simulations via binary lattice gases and bit coded algorithms. We confirm scaling behaviour belonging to the 2d Kardar-Parisi-Zhang universality class and find a surface growth exponent: beta=0.2415(15) on 2^17 x 2^17 systems, ruling out beta=1/4 suggested by field theory. The maximum speed-up with respect to a single CPU is 240. The steady state has been analysed by finite size scaling and a growth exponent alpha=0.393(4) is found. Correction to scaling exponents are computed and the power-spectrum density of the steady state is determined. We calculate the universal scaling functions, cumulants and show that the limit distribution can be obtained by the sizes considered. We provide numerical fitting for the small and large tail behaviour of the steady state scaling function of the interface width.Comment: 7 pages, 8 figures, slightly modified, accepted version for PR

Effects of Virtual Reality During Rowing Ergometry on Metabolic and Performance Parameters

Physical activity and moderate or intense exercise improve musculoskeletal and metabolic health; however, approximately 80% of Americans do not meet the minimum exercise recommendations from the American College of Sports Medicine (ACSM) or the Centers for Disease Control (CDC). Exercise intensity may be the most important factor in eliciting positive physical outcomes with exercise. PURPOSE: To assess the effectiveness of a proprietary virtual reality (VR) interface to increase metabolic and physical performance during rowing ergometry. METHODS: A novel VR software program for rowing ergometry was developed. Subsequently, sixteen apparently healthy, recreationally active individuals (12M, 4F; 35.5 ± 13.9 y; 174.5 ± 10.1 cm; 80.4 ± 12.8 kg; VO2max: 38.1 ± 5.6 mL/kg/min) were familiarized with the rowing ergometer and VR software, and then completed a VO2max test during two separate sessions. Finally, subjects performed four, 30-min rowing sessions in a randomized, counterbalanced order at maximal voluntary intensity in four different conditions: 1) no augmented visual or audio stimuli (CON), 2) no augmented visual stimuli with self-selected music (MUS), 3) screen-based environmental display (SB), and 4) a virtual reality environment (VR). Oxygen consumption, ventilation, heart rate, and the respiratory exchange ratio (RER) were measured continuously during the four experimental sessions; these data were then averaged over each 30-min testing period. Power output (W) and distance rowed (m) were measured and similarly reduced. Data (mean ± SD) were analyzed by repeated measures ANOVA and appropriate Tukey’s post hoc tests. Alpha was set at P \u3c 0.05. RESULTS: Oxygen consumption (CON: 2.23 ± 0.63 L/min; MUS: 2.30 ± 0.63 L/min; SB: 2.23 ± 0.71 L/min; VR: 2.19 ± 0.69 L/min), ventilation (CON: 74.2 ± 21.0 L/min; MUS: 77.5 ± 20.5 L/min; SB: 73.4 ± 23.9 L/min; VR: 71.7 ± 23.8 L/min), heart rate (CON: 154 ± 16 bpm; MUS: 156 ± 17 bpm; SB: 152 ± 23 bpm; VR: 154 ± 17 bpm), and RER (CON: 0.94 ± 0.04; MUS: 0.95 ± 0.04; SB: 0.94 ± 0.04; VR: 0.93 ± 0.05) were not different between conditions (all P \u3e 0.05). Performance outcomes also did not differ between conditions (CON: 126 ± 40 W, 6337 ± 763 m; MUS: 130 ± 42 W, 6486 ± 617 m; SB: 128 ± 46 W, 6358 ± 862 m; VR: 124 W ± 44 W, 6294 ± 849 m; all P \u3e 0.05). CONCLUSION: The pilot version of the VR software for rowing ergometry did not increase voluntary effort as determined by metabolic or physical performance outputs. Added features, such as greater immersion for reluctant exercisers, and competitive elements for highly motivated individuals, may elicit greater voluntary exertion with VR in rowing ergometry. Moreover, such applications may be more beneficial and improve exercise enjoyment in less experienced exercises who are not accustomed to high exercise intensities

Effects of Virtual Reality During Rowing Ergometry on Presence, Perceived Exertion, and Exercise Enjoyment

Physical inactivity is associated with a host of negative health outcomes. Approximately 80% of Americans do not meet minimum levels of recommended physical activity. Virtual reality (VR) may improve exercise outcomes by enhancing presence, decreasing perceived exertion, and increasing exercise enjoyment. PURPOSE: To assess the effects of a proprietary VR interface on presence, perceived exertion, and exercise enjoyment during rowing ergometry. METHODS: First, we developed a novel VR software program for rowing ergometry. Subsequently, sixteen apparently healthy, recreationally active individuals (12M, 4F; 35.5 ± 13.9 y; 174.5 ± 10.1 cm; 80.4 ± 12.8 kg; VO2max: 38.1 ± 5.6 mL/kg/min) were familiarized with the rowing ergometer and VR software, and then completed a VO2max test during two separate sessions. Finally, subjects performed four, 30-min rowing sessions in a randomized, counterbalanced order at maximal voluntary intensity in four different conditions: 1) no augmented visual or audio stimuli (CON), 2) no augmented visual stimuli with self-selected music (MUS), 3) screen-based environmental display (SB), and 4) a virtual reality environment (VR). Presence (Spatial Presence Experience Scale), perceived exertion (Borg 6-20 scale), and enjoyment (Exercise-Induced Feelings Inventory) were assessed using questionnaires. Data (mean ± SD) were analyzed by repeated measures ANOVA and appropriate Tukey’s post hoc tests. Alpha was set at P \u3c 0.05. RESULTS: Eight of twenty spatial presence items indicated an enhanced experience in VR vs. SB (P \u3c 0.05). Perceived exertion (CON: 14.7 ± 2.1; MUS: 14.9 ± 2.0; SB: 15.2 ± 2.5; VR: 14.9 ± 1.7) and exercise-induced feelings were not different between conditions (P \u3e 0.05). CONCLUSION: The pilot version of the VR software for rowing ergometry did not reduce perceived exertion or increase exercise enjoyment in recreationally active individuals, although it did facilitate improved user presence compared to a screen-based enhanced environment. Added features, such as better coupling of rowing intensity to boat velocity in VR may further enhance presence and immersion, thereby decreasing perceived exertion and increasing exercise enjoyment

Community Policing: Broken Windows, Community Building, and Satisfaction with the Police

The concept of community policing dominates the law enforcement profession today. One would be hard pressed to find an advertisement for a police chief’s position that does not require a thorough understanding of this method of policing. Like the Kansas City preventive patrol experiment and the Rand report on the criminal investigation process, the call for community policing has led to dramatic changes in the way that police carry out their responsibilities. In spite of its popularity, there have been a number of challenges to community policing from social scientists who are particularly concerned about the ‘broken windows’ model of policing. These challenges have not been received well by the law enforcement community, which argues that sociologists are wedded to the idea that crime is caused by the structural features of capitalist society, including economic injustice, racism, and poverty. The purpose of this article is to bridge the gap between these two positions. Yes, there is a place for community policing, and, yes, social problems do contribute to crime. The article starts by reviewing the development of community policing in the United States. An analysis of the theoretical constructs that support community policing then follows. Finally, we argue that there is sound theoretical evidence to support community policing, particularly those programmes that improve citizen satisfaction with the manner in which police carry out their responsibilities

Obtaining New Insights for Biodiversity Conservation from Broad-Scale Citizen Science Data

Increasing public engagement in volunteer science1, either through data collection2 or processing3, is both raising public awareness of science and gathering useful information for scientists. While the payoffs of citizen science4 are potentially large, achieving them requires new approaches to data management and analysis that can only result from strong cross-disciplinary collaborations. This is especially true in ecology and conservation biology, where historically the understanding of species’ responses to environmental change has been constrained by the limited spatial5 or temporal scale6 of available data. Here we describe collaborative research in ecology, computer science, and statistics to generate essential information for conservation management of North American birds: accurate dynamic bird distributions models based on habitat associations across much of North America. Unique is our ability to describe the broad-scale dynamics of seasonal bird distributions and the associated seasonal patterns of habitat use. Our source of bird distribution data is eBird7, an online bird checklist program that currently gathers more than 74,000 checklists monthly from a large network of contributors. Our results were made possible through a data intensive scientific workflow8 that includes analytical methods merged from the fields of machine learning and statistics. We believe that this novel approach of data collection, synthesis, analysis, and visualization will serve as a hallmark for future research initiatives, with broad applicability across many scientific domains

Community‐Engaged Neighborhood Revitalization and Empowerment: Busy Streets Theory in Action

Busy streets theory predicts that engaging residents in physical revitalization of neighborhoods will facilitate community empowerment through the development of sense of community, social cohesion, collective efficacy, social capital, and behavioral action. Establishing safe environments fosters positive street activity, which reinforces neighborhood social relationships. A community‐engaged approach to crime prevention through environmental design (CE‐CPTED) is one promising approach to creating busy streets because it engages residents in collaborative interactions to promote safer environments. Yet, few researchers have studied how CE‐CPTED may be associated with busy streets. We interviewed 18 residents and stakeholders implementing CE‐CPTED in Flint, Michigan. We studied three neighborhoods with different levels of resident control over CE‐CPTED. Participants described how CE‐CPTED implementation affected their neighborhood. Participants from all three neighborhoods reported that CE‐CPTED was associated with positive street activity, sense of community, and collective efficacy. Participants from neighborhoods with higher resident control of CE‐CPTED reported more social capital and behavioral action than those from neighborhoods with less resident control. Our findings support busy streets theory: Community engagement in neighborhood improvement enhanced community empowerment. CE‐CPTED that combines physical revitalization with resident engagement and control creates a potent synergy for promoting safe and healthy neighborhoods.HighlightsBusy streets theory supported in qualitative study of neighborhoods in a rust belt city.Community engaged neighborhood improvement enhances psychological empowerment.Resident control of neighborhood revitalization results in most empowered outcomes of busy streets.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154635/1/ajcp12358_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154635/2/ajcp12358.pd

Aging of the (2+1)-dimensional Kardar-Parisi-Zhang model

Extended dynamical simulations have been performed on a 2+1 dimensional driven dimer lattice gas model to estimate ageing properties. The auto-correlation and the auto-response functions are determined and the corresponding scaling exponents are tabulated. Since this model can be mapped onto the 2+1 dimensional Kardar-Parisi-Zhang surface growth model, our results contribute to the understanding of the universality class of that basic system.Comment: 6 pages, 5 figs, 1 table, accepted version in PR

Comparison of Different Parallel Implementations of the 2+1-Dimensional KPZ Model and the 3-Dimensional KMC Model

We show that efficient simulations of the Kardar-Parisi-Zhang interface growth in 2 + 1 dimensions and of the 3-dimensional Kinetic Monte Carlo of thermally activated diffusion can be realized both on GPUs and modern CPUs. In this article we present results of different implementations on GPUs using CUDA and OpenCL and also on CPUs using OpenCL and MPI. We investigate the runtime and scaling behavior on different architectures to find optimal solutions for solving current simulation problems in the field of statistical physics and materials science.Comment: 14 pages, 8 figures, to be published in a forthcoming EPJST special issue on "Computer simulations on GPU