Visualization of predictive distributions for discrete spatial-temporal log Cox processes approximated with MCMC

An important aspect of decision support systems involves applying sophisticated and flexible statistical models to real datasets and communicating these results to decision makers in interpretable ways. An important class of problem is the modelling of incidence such as fire, disease etc. Models of incidence known as point processes or Cox processes are particularly challenging as they are ‘doubly stochastic’ i.e. obtaining the probability mass function of incidents requires two integrals to be evaluated. Existing approaches to the problem either use simple models that obtain predictions using plug-in point estimates and do not distinguish between Cox processes and density estimation but do use sophisticated 3D visualization for interpretation. Alternatively other work employs sophisticated non-parametric Bayesian Cox process models, but do not use visualization to render interpretable complex spatial temporal forecasts. The contribution here is to fill this gap by inferring predictive distributions of Gaussian-log Cox processes and rendering them using state of the art 3D visualization techniques. This requires performing inference on an approximation of the model on a discretized grid of large scale and adapting an existing spatial-diurnal kernel to the log Gaussian Cox process context.

An additive model for spatio-temporal smoothing of cancer mortality rates

In this paper, a Bayesian hierarchical model is used to anaylze the female breast cancer mortality rates for the State of Missouri from 1969 through 2001. The logit transformations of the mortality rates are assumed to be linear over the time with additive spatial and age effects as intercepts and slopes. Objective priors of the hierarchical model are explored. The Bayesian estimates are quite robustness in terms change of the hyperparamaters. The spatial correlations are appeared in both intercepts and slopes.

Terrorism risk, resilience and volatility : a comparison of terrorism patterns in three Southeast Asian countries

Objective This article explores patterns of terrorist activity over the period from 2000 through 2010 across three target countries: Indonesia, the Philippines and Thailand. Methods We use self-exciting point process models to create interpretable and replicable metrics for three key terrorism concepts: risk, resilience and volatility, as defined in the context of terrorist activity. Results Analysis of the data shows significant and important differences in the risk, volatility and resilience metrics over time across the three countries. For the three countries analysed, we show that risk varied on a scale from 0.005 to 1.61 “expected terrorist attacks per day”, volatility ranged from 0.820 to 0.994 “additional attacks caused by each attack”, and resilience, as measured by the number of days until risk subsides to a pre-attack level, ranged from 19 to 39 days. We find that of the three countries, Indonesia had the lowest average risk and volatility, and the highest level of resilience, indicative of the relatively sporadic nature of terrorist activity in Indonesia. The high terrorism risk and low resilience in the Philippines was a function of the more intense, less clustered pattern of terrorism than what was evident in Indonesia. Conclusions Mathematical models hold great promise for creating replicable, reliable and interpretable “metrics” to key terrorism concepts such as risk, resilience and volatility.

Knitted images : drawing patterns

This Arts Based Education Research (Eisner 2008) work provides potent opportunity to consider different problems and challenges that impact on the progress of research (art as data making) and the theories being explored. It provides opportunity to transport ideas across between research activity, and teaching practices...

Jacobian-free Newton-Krylov methods with GPU acceleration for computing nonlinear ship wave patterns

The nonlinear problem of steady free-surface flow past a submerged source is considered as a case study for three-dimensional ship wave problems. Of particular interest is the distinctive wedge-shaped wave pattern that forms on the surface of the fluid. By reformulating the governing equations with a standard boundary-integral method, we derive a system of nonlinear algebraic equations that enforce a singular integro-differential equation at each midpoint on a two-dimensional mesh. Our contribution is to solve the system of equations with a Jacobian-free Newton-Krylov method together with a banded preconditioner that is carefully constructed with entries taken from the Jacobian of the linearised problem. Further, we are able to utilise graphics processing unit acceleration to significantly increase the grid refinement and decrease the run-time of our solutions in comparison to schemes that are presently employed in the literature. Our approach provides opportunities to explore the nonlinear features of three-dimensional ship wave patterns, such as the shape of steep waves close to their limiting configuration, in a manner that has been possible in the two-dimensional analogue for some time.

Temporal and functional changes in glycosaminoglycan expression during osteogenesis

Heparan sulfate proteoglycans (HSPGs) are complex and labile macromolecular moieties on the surfaces of cells that control the activities of a range of extracellular proteins, particularly those driving growth and regeneration. Here, we examine the biosynthesis of heparan sulfate (HS) sugars produced by cultured MC3T3-E1 mouse calvarial pre-osteoblast cells in order to explore the idea that changes in HS activity in turn drive phenotypic development during osteogenesis. Cells grown for 5 days under proliferating conditions were compared to cells grown for 20 days under mineralizing conditions with respect to their phenotype, the forms of HS core protein produced, and their HS sulfotransferase biosynthetic enzyme levels. RQ-PCR data was supported by the results from the purification of day 5 and day 20 HS forms by anionic exchange chromatography. The data show that cells in active growth phases produce more complex forms of sugar than cells that have become relatively quiescent during active mineralization, and that these in turn can differentially influence rates of cell growth when added exogenously back to preosteoblasts.

Mid-Holocene sea-level and coral reef demise : U-Th dating of subfossil corals in Moreton Bay, Australia

It is increasingly apparent that sea-level data (e.g. microfossil transfer functions, dated coral microatolls and direct observations from satellite and tidal gauges) vary temporally and spatially at regional to local scales, thus limiting our ability to model future sea-level rise for many regions. Understanding sealevel response at ‘far-field’ locations at regional scales is fundamental for formulating more relevant sea-level rise susceptibility models within these regions under future global change projections. Fossil corals and reefs in particular are valuable tools for reconstructing past sea levels and possible environmental phase shifts beyond the temporal constraints of instrumental records. This study used abundant surface geochronological data based on in situ subfossil corals and precise elevation surveys to determine previous sea level in Moreton Bay, eastern Australia, a far-field site. A total of 64 U-Th dates show that relative sea level was at least 1.1 m above modern lowest astronomical tide (LAT) from at least ˜6600 cal. yr BP. Furthermore, a rapid synchronous demise in coral reef growth occurred in Moreton Bay ˜5800 cal. yr BP, coinciding with reported reef hiatus periods in other areas around the Indo-Pacific region. Evaluating past reef growth patterns and phases allows for a better interpretation of anthropogenic forcing versus natural environmental/climatic cycles that effect reef formation and demise at all scales and may allow better prediction of reef response to future global change.

Tracking spatio temporal movement of human in terms of space utilization using media access control address data

Using Media-Access-Control (MAC) address for data collection and tracking is a capable and cost effective approach as the traditional ways such as surveys and video surveillance have numerous drawbacks and limitations. Positioning cell-phones by Global System for Mobile communication was considered an attack on people's privacy. MAC addresses just keep a unique log of a WiFi or Bluetooth enabled device for connecting to another device that has not potential privacy infringements. This paper presents the use of MAC address data collection approach for analysis of spatio-temporal dynamics of human in terms of shared space utilization. This paper firstly discuses the critical challenges and key benefits of MAC address data as a tracking technology for monitoring human movement. Here, proximity-based MAC address tracking is postulated as an effective methodology for analysing the complex spatio-temporal dynamics of human movements at shared zones such as lounge and office areas. A case study of university staff lounge area is described in detail and results indicates a significant added value of the methodology for human movement tracking. By analysis of MAC address data in the study area, clear statistics such as staff’s utilisation frequency, utilisation peak periods, and staff time spent is obtained. The analyses also reveal staff’s socialising profiles in terms of group and solo gathering. The paper is concluded with a discussion on why MAC address tracking offers significant advantages for tracking human behaviour in terms of shared space utilisation with respect to other and more prominent technologies, and outlines some of its remaining deficiencies.

An investigation of the pre-irradiation temporal stability of PAGAT gel dosimeter

In this work we examine two aspects of the PAGAT gel dosimeter. The first aspect studied is determination of a stable range of concentrations of the anti-oxidant Tetrakis Hydroxy Phosphonium Chloride (THPC). Once the desired THPC concentration is determined, we proceed to an investigation into the effect of pre-irradiation storage time and how this affects the dose response of the gel.

General self-efficacy influences affective task reactions during a work simulation : the temporal effects of changes in workload at different levels of control

This study investigated the effects of workload, control, and general self-efficacy on affective task reactions (i.e., demands-ability fit, active coping, and anxiety) during a work simulation. The main goals were: (1) to determine the extent general self-efficacy moderates the effects of demand and control on affective task reactions, and; (2) to determine if this varies as a function of changes in workload. Participants (N=141) completed an inbox activity under conditions of low or high control and within low and high workload conditions. The order of trials varied so that workload increased or decreased. Results revealed individuals with high general self-efficacy reported better demands-abilities fit and active coping as well as less anxiety. Three interactive effects were found. First, it was found that high control increased demands-abilities fit from trial 1 to trial 2, but only when workload decreased. Second, it was found that low efficacious individuals active coping increased in trial 2, but only under high control. Third, it was found that high control helped high efficacious individuals manage anxiety when workload decreased. However, for individuals with low general self-efficacy, neither high nor low control alleviated anxiety (i.e., whether workload increased or decreased over time).

Physical activity recognition from accelerometer data using a multi-scale ensemble method

Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

Physical activity patterns of inner-city elementary schoolchildren

Purpose This study aimed to objectively measure the physical activity (PA) characteristics of a racially and ethnically diverse sample of inner-city elementary schoolchildren and to examine the influence of sex, race/ethnicity, grade level, and weight status on PA. Methods A total of 470 students in grades 4-6 from six inner-city schools in Philadelphia wore an ActiGraph GT3X+ accelerometer (Actigraph, Pensacola, FL) for up to 7 d. The resultant data were uploaded to a customized Visual Basic EXCEL macro to determine the time spent in sedentary (SED), light-intensity PA (LPA), and moderate- to vigorous-intensity PA (MVPA). Results On average, students accumulated 48 min of MVPA daily. Expressed as a percentage of monitoring time, students were sedentary for 63% of the time, in LPA 31% of the time, and in MVPA 6% of the time. Across all race/ethnicity and grade level groups, boys exhibited significantly higher levels of MVPA than girls did; fifth-grade boys exhibited significantly lower MVPA levels than fourth-and sixth-grade boys did, and sixth-grade girls exhibited significantly lower MVPA levels than fourth-and fifth-grade girls did. Hispanic children exhibited lower levels of MVPA than children from other racial/ethnic groups did, and overweight and obese children exhibited significantly lower MVPA levels than children in the healthy weight range did. Across the entire sample, only 24.3% met the current public health guidelines for PA. Physical inactivity was significantly greater among females, Hispanics, and overweight and obese students. Conclusions Fewer than one in four inner-city schoolchildren accumulated the recommended 60 min of MVPA daily. These findings highlight the need for effective and sustainable programs to promote PA in inner-city youth.

Patterns of accelerometer-assessed sedentary behavior in older women

Recent studies suggest a high volume of sedentary behavior may be a risk factor for adverse health outcomes.1 However, few data exist on how this behavior is patterned (eg, does most sedentary behavior occur in a few long bouts or in many short bouts?) and whether sedentary patterns are relevant for health. We examined details of sedentary behavior among older women. Because physical activity is influenced by age, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), and smoking status, we further examined sedentary behavior in relation to these characteristics.

Life transitions and changing physical activity patterns in young women

Background Physical activity (PA) patterns are likely to change in young adulthood in line with changes in lifestyle that occur in the transition from adolescence to adulthood. The aim of this study was to ascertain whether key life events experienced by young women in their early twenties are associated with increasing levels of inactivity. Methods This was a 4-year follow-up of 7281 participants (aged 18 to 23 years at baseline) in the Australian Longitudinal Study of Women’s Health, with self-reported measures of PA, life events, body mass index (BMI), and sociodemographic variables. Results The cross-sectional data indicated no change in PA between baseline (57% “active”) and follow-up (56% “active”). However, for almost 40% of the sample, PA category changed between baseline and follow-up, with approximately 20% of the women changing from being “active” to “inactive,” and another 20% changing from being “inactive” to “active.” After adjustment for age, other sociodemographic variables, BMI, and PA at baseline, women who reported getting married, having a first or subsequent child, or beginning paid work were more likely to be inactive at follow-up than those who did not report these events. Conclusions The results suggest that life events such as getting married, having children, and starting work are associated with decreased levels of PA in young adult women. Strategies are needed to promote maintenance of activity at the time when most women experience these key life-stage transitions.