The effect of varied test instructions on neuropsychological performance following mild traumatic brain injury : an investigation of ‘diagnosis threat’

Diagnosis threat is a psychosocial factor that has been proposed to contribute to poor outcomes following mild traumatic brain injury (mTBI). This threat is thought to impair the cognitive test performance of individuals with mTBI because of negative injury stereotypes. University students (N= 45, 62.2% female) with a history of mTBI were randomly allocated to a diagnosis threat (DT, n=15), reduced threat (DT-reduced, n=15) or neutral (n=15) group. The reduced threat condition invoked a positive stereotype (i.e., that people with mTBI can perform well on cognitive tests). All participants were given neutral instructions before they completed baseline tests of: a) objective cognitive function across a number of domains; b) psychological symptoms; and, c) PCS symptoms, including self-reported cognitive and emotional difficulties. Participants then received either neutral, DT or DT-reduced instructions, before repeating the tests. Results were analyzed using separate mixed model ANOVAs; one for each dependent measure. The only significant result was for the 2 X 3 ANOVA on an objective test of attention/working memory, Digit Span, p<.05, such that the DT-reduced group performed better than the other groups, which were not different from each other. Although not consistent with predictions or earlier DT studies, the absence of group differences on most tests fits with several recent DT findings. The results of this study suggest that it is timely to reconsider the role of DT as a unique contributor to poor mTBI outcome.

Modeling the viability of the free-ranging cheetah population in Namibia : an object-oriented Bayesian network approach

Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object-oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free-ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free-ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free-ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi-expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free-ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.

Structure, magnetism and colour in simple bis­(phosphine)nickel(II) dihalide complexes : an experimental and theoretical investigation

The complex [1,2-bis­(di-tert-butyl­phosphan­yl)ethane-[kappa]2P,P']di­iodido­nickel(II), [NiI2(C18H40P2] or (dtbpe-[kappa]2P)NiI2, [dtbpe is 1,2-bis­(di-tert-butyl­phosphan­yl)ethane], is bright blue-green in the solid state and in solution, but, contrary to the structure predicted for a blue or green nickel(II) bis­(phos­phine) complex, it is found to be close to square planar in the solid state. The solution structure is deduced to be similar, because the optical spectra measured in solution and in the solid state contain similar absorptions. In solution at room temperature, no 31P{1H} NMR resonance is observed, but the very small solid-state magnetic moment at temperatures down to 4 K indicates that the weak paramagnetism of this nickel(II) complex can be ascribed to temperature independent paramagnetism, and that the complex has no unpaired electrons. The red [1,2-bis­(di-tert-butyl­phosphan­yl)ethane-[kappa]2P,P']di­chlorido­nickel(II), [NiCl2(C18H40P2] or (dtbpe-[kappa]2P)NiCl2, is very close to square planar and very weakly paramagnetic in the solid state and in solution, while the maroon [1,2-bis­(di-tert-butyl­phosphan­yl)ethane-[kappa]2P,P']di­bromido­nickel(II), [NiBr2(C18H40P2] or (dtbpe-[kappa]2P)NiBr2, is isostructural with the diiodide in the solid state, and displays paramagnetism inter­mediate between that of the dichloride and the diiodide in the solid state and in solution. Density functional calculations demonstrate that distortion from an ideal square plane for these complexes occurs on a flat potential energy surface. The calculations reproduce the observed structures and colours, and explain the trends observed for these and similar complexes. Although theoretical investigation identified magnetic-dipole-allowed excitations that are characteristic for temperature-independent paramagnetism (TIP), theory predicts the mol­ecules to be diamagnetic.

Reliability of spatiotemporal and kinetic gait parameters determined by a new instrumented treadmill system

Background Despite the emerging use of treadmills integrated with pressure platforms as outcome tools in both clinical and research settings, published evidence regarding the measurement properties of these new systems is limited. This study evaluated the within– and between–day repeatability of spatial, temporal and vertical ground reaction forces measured by a treadmill system instrumented with a capacitance–based pressure platform. Methods Thirty three healthy adults (mean age, 21.5 ± 2.8 years; height, 168.4 ± 9.9 cm; and mass, 67.8 ± 18.6 kg), walked barefoot on a treadmill system (FDM–THM–S, Zebris Medical GmbH) on three separate occasions. For each testing session, participants set their preferred pace but were blinded to treadmill speed. Spatial (foot rotation, step width, stride and step length), temporal (stride and step times, duration of stance, swing and single and double support) and peak vertical ground reaction force variables were collected over a 30–second capture period, equating to an average of 52 ± 5 steps of steady–state walking. Testing was repeated one week following the initial trial and again, for a third time, 20 minutes later. Repeated measures ANOVAs within a generalized linear modelling framework were used to assess between–session differences in gait parameters. Agreement between gait parameters measured within the same day (session 2 and 3) and between days (session 1 and 2; 1 and 3) were evaluated using the 95% repeatability coefficient. Results There were statistically significant differences in the majority (14/16) of temporal, spatial and kinetic gait parameters over the three test sessions (P < .01). The minimum change that could be detected with 95% confidence ranged between 3% and 17% for temporal parameters, 14% and 33% for spatial parameters, and 4% and 20% for kinetic parameters between days. Within–day repeatability was similar to that observed between days. Temporal and kinetic gait parameters were typically more consistent than spatial parameters. The 95% repeatability coefficient for vertical force peaks ranged between ± 53 and ± 63 N. Conclusions The limits of agreement in spatial parameters and ground reaction forces for the treadmill system encompass previously reported changes with neuromuscular pathology and footwear interventions. These findings provide clinicians and researchers with an indication of the repeatability and sensitivity of the Zebris treadmill system to detect changes in common spatiotemporal gait parameters and vertical ground reaction forces.

Modeling users’ web search behavior and their cognitive styles

Previous studies have shown that users’ cognitive styles play an important role during Web searching. However, only limited studies have showed the relationship between cognitive styles and Web search behavior. Most importantly, it is not clear which components of Web search behavior are influenced by cognitive styles. This paper examines the relationships between users’ cognitive styles and their Web searching and develops a model that portrays the relationship. The study uses qualitative and quantitative analyses to inform the study results based on data gathered from 50 participants. A questionnaire was utilised to collect participants’ demographic information, and Riding’s (1991) Cognitive Style Analysis (CSA) test to assess their cognitive styles. Results show that users’ cognitive styles influenced their information searching strategies, query reformulation behaviour, Web navigational styles and information processing approaches. The user model developed in this study depicts the fundamental relationships between users’ Web search behavior and their cognitive styles. Modeling Web search behavior with a greater understanding of user’s cognitive styles can help information science researchers and information systems designers to bridge the semantic gap between the user and the systems. Implications of the research for theory and practice, and future work are discussed.

Modeling predictors of risky drug use behavior among male street laborers in urban Vietnam

Background The application of theoretical frameworks for modeling predictors of drug risk among male street laborers remains limited. The objective of this study was to test a modified version of the IMB (Information-Motivation-Behavioral Skills Model), which includes psychosocial stress, and compare this modified version with the original IMB model in terms of goodness-of-fit to predict risky drug use behavior among this population. Methods In a cross-sectional study, social mapping technique was conducted to recruit 450 male street laborers from 135 street venues across 13 districts of Hanoi city, Vietnam, for face-to-face interviews. Structural equation modeling (SEM) was used to analyze data from interviews. Results Overall measures of fit via SEM indicated that the original IMB model provided a better fit to the data than the modified version. Although the former model was able to predict a lesser variance than the latter (55% vs. 62%), it was of better fit. The findings suggest that men who are better informed and motivated for HIV prevention are more likely to report higher behavioral skills, which, in turn, are less likely to be engaged in risky drug use behavior. Conclusions This was the first application of the modified IMB model for drug use in men who were unskilled, unregistered laborers in urban settings. An AIDS prevention program for these men should not only distribute information and enhance motivations for HIV prevention, but consider interventions that could improve self-efficacy for preventing HIV infection. Future public health research and action may also consider broader factors such as structural social capital and social policy to alter the conditions that drive risky drug use among these men.

Establishing definitions and modeling public transport travel time variability

Public transport travel time variability (PTTV) is essential for understanding deteriorations in the reliability of travel time, optimizing transit schedules and route choices. This paper establishes key definitions of PTTV in which firstly include all buses, and secondly include only a single service from a bus route. The paper then analyses the day-to-day distribution of public transport travel time by using Transit Signal Priority data. A comprehensive approach using both parametric bootstrapping Kolmogorov-Smirnov test and Bayesian Information Creation technique is developed, recommends Lognormal distribution as the best descriptor of bus travel time on urban corridors. The probability density function of Lognormal distribution is finally used for calculating probability indicators of PTTV. The findings of this study are useful for both traffic managers and statisticians for planning and researching the transit systems.

Posttraumatic stress disorder and traumatic stress : from bench to bedside, from war to disaster

War is a tragic event and its mental health consequences can be profound. Recent studies indicate substantial rates of posttraumatic stress disorder and other behavioral alterations because of war exposure. Understanding the psychological, behavioral, and neurobiological mechanism of mental health and behavioral changes related to war exposure is critical to helping those in need of care. Substantial work to encourage bench to bedside to community knowledge and communication is a core component of addressing this world health need.

Distribution harmonic state estimation based on a modified PSO considering parameters uncertainty

This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).

Distribution harmonic state estimation based on a hybrid PSO and SA algorithm considering parameters uncertainty

This paper presents a new algorithm based on a Hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) called PSO-SA to estimate harmonic state variables in distribution networks. The proposed algorithm performs estimation for both amplitude and phase of each harmonic currents injection by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WT). The main feature of proposed PSO-SA algorithm is to reach quickly around the global optimum by PSO with enabling a mutation function and then to find that optimum by SA searching algorithm. Simulation results on IEEE 34 bus radial and a realistic 70-bus radial test networks are presented to demonstrate the speed and accuracy of proposed Distribution Harmonic State Estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO and Honey Bees Mating Optimization (HBMO) algorithm.

The influence of Monte Carlo source parameters on detector design and dose perturbation in small field dosimetry

To obtain accurate Monte Carlo simulations of small radiation fields, it is important model the initial source parameters (electron energy and spot size) accurately. However recent studies have shown that small field dosimetry correction factors are insensitive to these parameters. The aim of this work is to extend this concept to test if these parameters affect dose perturbations in general, which is important for detector design and calculating perturbation correction factors. The EGSnrc C++ user code cavity was used for all simulations. Varying amounts of air between 0 and 2 mm were deliberately introduced upstream to a diode and the dose perturbation caused by the air was quantified. These simulations were then repeated using a range of initial electron energies (5.5 to 7.0 MeV) and electron spot sizes (0.7 to 2.2 FWHM). The resultant dose perturbations were large. For example 2 mm of air caused a dose reduction of up to 31% when simulated with a 6 mm field size. However these values did not vary by more than 2 % when simulated across the full range of source parameters tested. If a detector is modified by the introduction of air, one can be confident that the response of the detector will be the same across all similar linear accelerators and the Monte Carlo modelling of each machine is not required.

An algebraic approach for determination of DG parameters to support voltage profiles in radial distribution networks

Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of Distributed Generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. This paper addresses the issue of improving the network voltage profile in distribution systems by installing a DG of the most suitable size, at a suitable location. An analytical approach is developed based on algebraic equations for uniformly distributed loads to determine the optimal operation, size and location of the DG in order to achieve required levels of network voltage. The developed method is simple to use for conceptual design and analysis of distribution system expansion with a DG and suitable for a quick estimation of DG parameters (such as optimal operating angle, size and location of a DG system) in a radial network. A practical network is used to verify the proposed technique and test results are presented.

Use of simple pharmacokinetic modeling to characterize exposure of Australians to perfluorooctanoic acid and perfluorooctane sulfonic acid

Perflurooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) have been used for a variety of applications including fluoropolymer processing, fire-fighting foams and surface treatments since the 1950s. Both PFOS and PFOA are polyfluoroalkyl chemicals (PFCs), man-made compounds that are persistent in the environment and humans; some PFCs have shown adverse effects in laboratory animals. Here we describe the application of a simple one compartment pharmacokinetic model to estimate total intakes of PFOA and PFOS for the general population of urban areas on the east coast of Australia. Key parameters for this model include the elimination rate constants and the volume of distribution within the body. A volume of distribution was calibrated for PFOA to a value of 170ml/kgbw using data from two communities in the United States where the residents' serum concentrations could be assumed to result primarily from a known and characterized source, drinking water contaminated with PFOA by a single fluoropolymer manufacturing facility. For PFOS, a value of 230ml/kgbw was used, based on adjustment of the PFOA value. Applying measured Australian serum data to the model gave mean+/-standard deviation intake estimates of PFOA of 1.6+/-0.3ng/kgbw/day for males and females >12years of age combined based on samples collected in 2002-2003 and 1.3+/-0.2ng/kg bw/day based on samples collected in 2006-2007. Mean intakes of PFOS were 2.7+/-0.5ng/kgbw/day for males and females >12years of age combined based on samples collected in 2002-2003, and 2.4+/-0.5ng/kgbw/day for the 2006-2007 samples. ANOVA analysis was run for PFOA intake and demonstrated significant differences by age group (p=0.03), sex (p=0.001) and date of collection (p<0.001). Estimated intake rates were highest in those aged >60years, higher in males compared to females, and higher in 2002-2003 compared to 2006-2007. The same results were seen for PFOS intake with significant differences by age group (p<0.001), sex (p=0.001) and date of collection (p=0.016).

Surface dosimetry for very small X-ray beams

Introduction The dose to skin surface is an important factor for many radiotherapy treatment techniques. It is known that TPS predicted surface doses can be significantly different from actual ICRP skin doses as defined at 70 lm. A number of methods have been implemented for the accurate determination of surface dose including use of specific dosimeters such as TLDs and radiochromic film as well as Monte Carlo calculations. Stereotactic radiosurgery involves delivering very high doses per treatment fraction using small X-ray fields. To date, there has been limited data on surface doses for these very small field sizes. The purpose of this work is to evaluate surface doses by both measurements and Monte Carlo calculations for very small field sizes. Methods All measurements were performed on a Novalis Tx linear accelerator which has a 6 MV SRS X-ray beam mode which uses a specially thin flattening filter. Beam collimation was achieved by circular cones with apertures that gave field sizes ranging from 4 to 30 mm at the isocentre. The relative surface doses were measured using Gafchromic EBT3 film which has the active layer at a depth similar to the ICRP skin dose depth. Monte Carlo calculations were performed using the BEAMnrc/EGSnrc Monte Carlo codes (V4 r225). The specifications of the linear accelerator, including the collimator, were provided by the manufacturer. Optimisation of the incident X-ray beam was achieved by an iterative adjustment of the energy, spatial distribution and radial spread of the incident electron beam striking the target. The energy cutoff parameters were PCUT = 0.01 MeV and ECUT = 0.700 - MeV. Directional bremsstrahlung splitting was switched on for all BEAMnrc calculations. Relative surface doses were determined in a layer defined in a water phantom of the same thickness and depth as compared to the active later in the film. Results Measured surface doses using the EBT3 film varied between 13 and 16 % for the different cones with an uncertainty of 3 %. Monte Carlo calculated surface doses were in agreement to better than 2 % to the measured doses for all the treatment cones. Discussion and conclusions This work has shown the consistency of surface dose measurements using EBT3 film with Monte Carlo predicted values within the uncertainty of the measurements. As such, EBT3 film is recommended for in vivo surface dose measurements.

Modeling nitrous oxide emissions from irrigated agriculture : testing DayCent with high-frequency measurements

A unique high temporal frequency dataset from an irrigated cotton-wheat rotation was used to test the agroecosystem model DayCent to simulate daily N2O emissions from sub-tropical vertisols under different irrigation intensities. DayCent was able to simulate the effect of different irrigation intensities on N2O fluxes and yield, although it tended to overestimate seasonal fluxes during the cotton season. DayCent accurately predicted soil moisture dynamics and the timing and magnitude of high fluxes associated with fertilizer additions and irrigation events. At the daily scale we found a good correlation of predicted vs. measured N2O fluxes (r2 = 0.52), confirming that DayCent can be used to test agricultural practices for mitigating N2O emission from irrigated cropping systems. A 25 year scenario analysis indicated that N2O losses from irrigated cotton-wheat rotations on black vertisols in Australia can be substantially reduced by an optimized fertilizer and irrigation management system (i.e. frequent irrigation, avoidance of excessive fertiliser application), while sustaining maximum yield potentials.