Thermal and cardiovascular strain imposed by motorcycle protective clothing under Australian summer conditions

Motorcycle protective clothing can be uncomfortably hot during summer, and this experiment was designed to evaluate the physiological significance of that burden. Twelve males participated in four, 90-min trials (cycling 30 W) across three environments (25, 30, 35 °C [all 40% relative humidity]). Clothing was modified between full and minimal injury protection. Both ensembles were tested at 25 °C, with only the more protective ensemble investigated at 30 and 35 °C. At 35 °C, auditory canal temperature rose at 0.02 °C min^?1 (SD 0.005), deviating from all other trials (p < 0.05). The thresholds for moderate (>38.5 °C) and profound hyperthermia (>40.0 °C) were predicted to occur within 105 min (SD 20.6) and 180 min (SD 33.0), respectively. Profound hyperthermia might eventuate in ~10 h at 30 °C, but should not occur at 25 °C. These outcomes demonstrate a need to enhance the heat dissipation capabilities of motorcycle clothing designed for summer use in hot climates, but without compromising impact protection.

Practitioner’s Summary:

Motorcycle protective clothing can be uncomfortably hot during summer. This experiment was designed to evaluate the physiological significance of this burden across climatic states. In the heat, moderate (>38.5 °C) and profound hyperthermia (>40.0 °C) were predicted to occur within 105 and 180 min, respectively.     

Event‐triggered distributed constrained consensus

We consider a distributed consensus problem for continuous‐time multi‐agent systems with set constraints on the final states. To save communication costs, an event‐triggered communication‐based protocol is proposed. By comparing its own instantaneous state with the one previously broadcasted to neighbours, each agent determines the next communication time. Based on this event‐triggered communication, each agent is not required to continuously monitor its neighbours' state and the communication only happens at discrete time instants. We show that, under some mild conditions, the constrained consensus of the multi‐agent system with the proposed protocol can be achieved with an exponential convergence rate. A lower bound of the transmission time intervals is provided that can be adjusted by choosing different values of parameters. Numerical examples illustrate the results. Copyright © 2016 John Wiley & Sons, Ltd.     

The impact of map orientation and generalisation on congestion decisions: a comparison of schematic-egocentric and topographic-allocentric maps

Map information for drivers is usually presented in an allocentric-topographic form (as with printed maps) or in an egocentric-schematic form (as with road signs). The advent of new variable message boards on UK motorways raises the possibility of presenting road maps to reflect congestion ahead. Should these maps be allocentric-topographic or egocentric-schematic? This was assessed in an eye tracking study, with participants viewing maps of a motorway network in order to identify whether any congestion was relevant to their intended route. The schematic-egocentric maps were responded to most accurately with shorter fixation durations suggesting easier processing. In particular, the driver's entrance and intended exit from the map were attended to more in the allocentric maps. Individual differences in mental rotation ability also seem to contribute to poor performance on allocentric maps. The results favour schematic-egocentric maps for roadside congestion information, but also provide theoretical insights into map-rotation and individual differences. Statement of Relevance: This study informs designers and policy makers about optimum representations of traffic congestion on roadside variable message signs and, furthermore, demonstrates that individual differences contribute to problems with processing certain sign types. Schematic-egocentric representations of a motorway network produced the best results, as noted in behavioural and eye movement measures.     

Fuzzy clustering of time series in the frequency domain

Traditional and fuzzy cluster analyses are applicable to variables whose values are uncorrelated. Hence, in order to cluster time series data which are usually serially correlated, one needs to extract features from the time series, the values of which are uncorrelated. The periodogram which is an estimator of the spectral density function of a time series is a feature that can be used in the cluster analysis of time series because its ordinates are uncorrelated. Additionally, the normalized periodogram and the logarithm of the normalized periodogram are also features that can be used. In this paper, we consider a fuzzy clustering approach for time series based on the estimated cepstrum. The cepstrum is the spectrum of the logarithm of the spectral density function. We show in our simulation studies for the typical generating processes that have been considered, fuzzy clustering based on the cepstral coefficients performs very well compared to when it is based on other features.     

Stability analysis of networked control systems subject to packet-dropouts and finite-level quantization

This paper is concerned with the stability analysis of a networked control system, wherein communication from the controller to the plant input is through a digital channel subject to packet-dropouts and finite-level quantization. No acknowledgments of receipt are available to the controller. To alleviate the effect of packet-dropouts, the controller transmits tentative plant input sequences. Within this setup, we derive a sufficient condition for small ?^∞ signal ?^∞ stability of the networked control system. This condition requires the maximum number of consecutive packet-dropouts to be bounded. We also elucidate the trade-off which exists between the disturbance attenuation and the step size of the quantizer and the maximum number of consecutive packet-dropouts.     

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models.     

The Dynamical Hypothesis in Cognitive Science: A Review Essay of Mind As Motion

Minds and Machines -     

Oxidation Kinetics of Chemically Vapor-Deposited Silicon Carbide in Wet Oxygen

The oxidation kinetics of chemically vapor-deposited SiC in dry oxygen and wet oxygen ( P _H2O= 0.1 atm) at temperatures between 1200° and 1400°C were monitored using thermogravimetric analysis. It was found that in a clean environment, 10% water vapor enhanced the oxidation kinetics of SiC only very slightly compared to rates found in dry oxygen. Oxidation kinetics were examined in terms of the Deal and Grove model for oxidation of silicon. It was found that in an environment containing even small amounts of impurities, such as high-purity Al₂O₃ reaction tubes containing 200 ppm Na, water vapor enhanced the transport of these impurities to the oxidation sample. Oxidation rates increased under these conditions presumably because of the formation of less protective sodium alumino-silicate scales.     

A novel combined electrochemical-magnetic method for water treatment

Electrocoagulation (EC) is a wastewater treatment process in which aqueous pollutants can be removed by adsorption, entrapment, precipitation or coalescence during a coagulation step produced by electrochemically generated metallic species. When using Fe as the sacrificial electrode, Fe(2+) and Fe(3+) ions are formed. As Fe(3+) species are paramagnetic, this property can in principle be used to facilitate their removal through the application of a magnetic field. In the present work we present a proof-of-concept for a combined electrochemical-magnetic method for pollutant removal. For this approach, the amounts of Fe(2+) and Fe(3+) produced in an EC cell at various voltages were measured by spectroscopic methods to confirm that Fe(3+) species predominate (up to 84%). The effectiveness of the presence of a magnetic field in the precipitation of coagulants from a suspension was confirmed by monitoring the turbidity change versus time with and without exposure to a magnetic field, up to a 30% improvement.     

Population shift bias in tests of space–time interaction

Common to all tests of space–time interaction is the assumption that the population underlying the events of interest exhibits a trajectory of growth that is consistent through time and across space. In practice, however, this assumption is often untenable and, when violated, can introduce population shift bias into the results of these tests. While this problem is widely recognized, more work remains to compare its effect across tests and to determine the extent to which it is a problem for study short periods. This paper quantifies and compares the population shift bias present in the results of the Knox, Mantel, and Jacquez tests of space–time interaction. A simulation study is carried out which quantifies the bias present in each test across a variety of population movement scenarios. Results show a positive relationship between population shift bias and the heterogeneity in population growth across all the tests. They also demonstrate variability in the size of the bias across the three tests for space–time interaction considered. Finally, the results illustrate that population shift bias can be a serious problem for short study periods. Collectively, these findings suggest that an unbiased approach to assessing the significance of space–time interaction test results is needed whenever spatially heterogeneous population change is identified within a study area.