Spatiotemporal segmentation based on two-dimensional spatiotemporal entropic thresholding

A novel spatiotemporal segmentation technique is further developed for extracting uncovered background and moving objects from the image sequences, then the following motion estimation is performed only on the regions corresponding to moving objects. The frame difference contrast (FCON) and local variance contrast (LCON), which are related to the temporal and spatial homogeneity of the image sequence, are selected to form the 2-D spatiotemporal entropy. Then the spatial segmentation threshold is determined by maximizing the 2-D spatiotemporal entropy, and the temporal segmentation point is selected to minimize the complexity measure for image sequence coding. Since both temporal and spatial correlation of an image sequence are exploited, this proposed spatiotemporal segmentation technique can further be used to determine the positions of reference frames adaptively, hence resulting in a low bit rate. Experimental results show that this segmentation-based coding scheme is more efficient than usual fixed-size coding algorithms. (C) 1997 Society of Photo-Optical Instrumentation Engineers.

Preliminary spatiotemporal analysis of the association between socio-environmental factors and suicide

Background: The seasonality of suicide has long been recognised. However, little is known about the relative importance of socio-environmental factors in the occurrence of suicide in different geographical areas. This study examined the association of climate, socioeconomic and demographic factors with suicide in Queensland, Australia, using a spatiotemporal approach. Methods: Seasonal data on suicide, demographic variables and socioeconomic indexes for areas in each Local Government Area (LGA) between 1999 and 2003 were acquired from the Australian Bureau of Statistics. Climate data were supplied by the Australian Bureau of Meteorology. A multivariable generalized estimating equation model was used to examine the impact of socio-environmental factors on suicide. Results: The preliminary data analyses show that far north Queensland had the highest suicide incidence (e.g., Cook and Mornington Shires), while the south-western areas had the lowest incidence (e.g., Barcoo and Bauhinia Shires) in all the seasons. Maximum temperature, unemployment rate, the proportion of Indigenous population and the proportion of population with low individual income were statistically significantly and positively associated with suicide. There were weaker but not significant associations for other variables. Conclusions: Maximum temperature, the proportion of Indigenous population and unemployment rate appeared to be major determinants of suicide at a LGA level in Queensland.

Bayesian spatiotemporal analysis of socio-ecologic drivers of Ross River Virus transmission in Queensland, Australia

This study aims to examine the impact of socio-ecologic factors on the transmission of Ross River virus (RRV) infection and to identify areas prone to social and ecologic-driven epidemics in Queensland, Australia. We used a Bayesian spatiotemporal conditional autoregressive model to quantify the relationship between monthly variation of RRV incidence and socio-ecologic factors and to determine spatiotemporal patterns. Our results show that the average increase in monthly RRV incidence was 2.4% (95% credible interval (CrI): 0.1–4.5%) and 2.0% (95% CrI: 1.6–2.3%) for a 1°C increase in monthly average maximum temperature and a 10 mm increase in monthly average rainfall, respectively. A significant spatiotemporal variation and interactive effect between temperature and rainfall on RRV incidence were found. No association between Socio-economic Index for Areas (SEIFA) and RRV was observed. The transmission of RRV in Queensland, Australia appeared to be primarily driven by ecologic variables rather than social factors.

Risk factor analysis and spatiotemporal CART model of cryptosporidiosis in Queensland, Australia

Background: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. ----- ----- Methods: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia. ----- ----- Results: The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models. ----- ----- Conclusions: The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.

Spatiotemporal investigations of DNA damage repair using microbeams

Cellular response to radiation damage is made by a complex network of pathways and feedback loops whose spatiotemporal organisation is still unclear despite its decisive role in determining the fate of the damaged cell. Revealing the dynamic sequence of the repair proteins is therefore critical in understanding how the DNA repair mechanisms work. There are also still open questions regarding the possible movement of damaged chromatin domains and its role as trigger for lesion recognition and signalling in the DNA repair context. The single-cell approach and the high spatial resolution offered by microbeams provide the perfect tool to study and quantify the dynamic processes associated with the induction and repair of DNA damage. We have followed the development of radiation-induced foci for three DNA damage markers (i.e. γ-H2AX, 53BP1 and hSSB1) using normal fibroblasts (AG01522), human breast adenocarcinoma cells (MCF7) and human fibrosarcoma cells (HT1080) stably transfected with yellow fluorescent protein fusion proteins following irradiation with the QUB X-ray microbeam (carbon X-rays <2 µm spot). The size and intensity of the foci has been analysed as a function of dose and time post-irradiation to investigate the dynamics of the above-mentioned DNA repair processes and monitor the remodelling of chromatin structure that the cell undergoes to deal with DNA damage.

A spatiotemporal analysis of gait freezing and the impact of pedunculopontine nucleus stimulation

Gait freezing is an episodic arrest of locomotion due to an inability to take normal steps. Pedunculopontine nucleus stimulation is an emerging therapy proposed to improve gait freezing, even where refractory to medication. However, the efficacy and precise effects of pedunculopontine nucleus stimulation on Parkinsonian gait disturbance are not established. The clinical application of this new therapy is controversial and it is unknown if bilateral stimulation is more effective than unilateral. Here, in a double-blinded study using objective spatiotemporal gait analysis, we assessed the impact of unilateral and bilateral pedunculopontine nucleus stimulation on triggered episodes of gait freezing and on background deficits of unconstrained gait in Parkinson’s disease. Under experimental conditions, while OFF medication, Parkinsonian patients with severe gait freezing implanted with pedunculopontine nucleus stimulators below the pontomesencephalic junction were assessed during three conditions; off stimulation, unilateral stimulation and bilateral stimulation. Results were compared to Parkinsonian patients without gait freezing matched for disease severity and healthy controls. Pedunculopontine nucleus stimulation improved objective measures of gait freezing, with bilateral stimulation more effective than unilateral. During unconstrained walking, Parkinsonian patients who experience gait freezing had reduced step length and increased step length variability compared to patients without gait freezing; however, these deficits were unchanged by pedunculopontine nucleus stimulation. Chronic pedunculopontine nucleus stimulation improved Freezing of Gait Questionnaire scores, reflecting a reduction of the freezing encountered in patients’ usual environments and medication states. This study provides objective, double-blinded evidence that in a specific subgroup of Parkinsonian patients, stimulation of a caudal pedunculopontine nucleus region selectively improves gait freezing but not background deficits in step length. Bilateral stimulation was more effective than unilateral.

Scoring-thresholding pattern based text classifier

A big challenge for classification on text is the noisy of text data. It makes classification quality low. Many classification process can be divided into two sequential steps scoring and threshold setting (thresholding). Therefore to deal with noisy data problem, it is important to describe positive feature effectively scoring and to set a suitable threshold. Most existing text classifiers do not concentrate on these two jobs. In this paper, we propose a novel text classifier with pattern-based scoring that describe positive feature effectively, followed by threshold setting. The thresholding is based on score of training set, make it is simple to implement in other scoring methods. Experiment shows that our pattern-based classifier is promising.

Spatiotemporal modelling in estimation of nitrous oxide emissions from soil

Nitrous oxide is a major greenhouse gas emission. The aim of this research was to develop and apply statistical models to characterize the complex spatial and temporal variation in nitrous oxide emissions from soils under different land use conditions. This is critical when developing site-specific management plans to reduce nitrous oxide emissions. These studies can improve predictions and increase our understanding of environmental factors that influence nitrous oxide emissions. They also help to identify areas for future research, which can further improve the prediction of nitrous oxide in practice.

Spatiotemporal model or time series model for assessing city-wide temperature effects on mortality?

Most studies examining the temperature–mortality association in a city used temperatures from one site or the average from a network of sites. This may cause measurement error as temperature varies across a city due to effects such as urban heat islands. We examined whether spatiotemporal models using spatially resolved temperatures produced different associations between temperature and mortality compared with time series models that used non-spatial temperatures. We obtained daily mortality data in 163 areas across Brisbane city, Australia from 2000 to 2004. We used ordinary kriging to interpolate spatial temperature variation across the city based on 19 monitoring sites. We used a spatiotemporal model to examine the impact of spatially resolved temperatures on mortality. Also, we used a time series model to examine non-spatial temperatures using a single site and the average temperature from three sites. We used squared Pearson scaled residuals to compare model fit. We found that kriged temperatures were consistent with observed temperatures. Spatiotemporal models using kriged temperature data yielded slightly better model fit than time series models using a single site or the average of three sites' data. Despite this better fit, spatiotemporal and time series models produced similar associations between temperature and mortality. In conclusion, time series models using non-spatial temperatures were equally good at estimating the city-wide association between temperature and mortality as spatiotemporal models.

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.

Predicting shot locations in tennis using spatiotemporal data

Over the past decade, vision-based tracking systems have been successfully deployed in professional sports such as tennis and cricket for enhanced broadcast visualizations as well as aiding umpiring decisions. Despite the high-level of accuracy of the tracking systems and the sheer volume of spatiotemporal data they generate, the use of this high quality data for quantitative player performance and prediction has been lacking. In this paper, we present a method which predicts the location of a future shot based on the spatiotemporal parameters of the incoming shots (i.e. shot speed, location, angle and feet location) from such a vision system. Having the ability to accurately predict future short-term events has enormous implications in the area of automatic sports broadcasting in addition to coaching and commentary domains. Using Hawk-Eye data from the 2012 Australian Open Men's draw, we utilize a Dynamic Bayesian Network to model player behaviors and use an online model adaptation method to match the player's behavior to enhance shot predictability. To show the utility of our approach, we analyze the shot predictability of the top 3 players seeds in the tournament (Djokovic, Federer and Nadal) as they played the most amounts of games.

Spatiotemporal patterns of Japanese Encephalitis in China, 2002–2010

OBJECTIVE The aim of the study is to examine the spatiotemporal pattern of Japanese Encephalitis (JE) in mainland China during 2002-2010. Specific objectives of the study were to quantify the temporal variation in incidence of JE cases, to determine if clustering of JE cases exists, to detect high risk spatiotemporal clusters of JE cases and to provide evidence-based preventive suggestions to relevant stakeholders. METHODS Monthly JE cases at the county level in mainland China during 2002-2010 were obtained from the China Information System for Diseases Control and Prevention (CISDCP). For the purpose of the analysis, JE case counts for nine years were aggregated into four temporal periods (2002; 2003-2005; 2006; and 2007-2010). Local Indicators of Spatial Association and spatial scan statistics were performed to detect and evaluate local high risk space-time clusters. RESULTS JE incidence showed a decreasing trend from 2002 to 2005 but peaked in 2006, then fluctuated over the study period. Spatial cluster analysis detected high value clusters, mainly located in Southwestern China. Similarly, we identified a primary spatiotemporal cluster of JE in Southwestern China between July and August, with the geographical range of JE transmission increasing over the past years. CONCLUSION JE in China is geographically clustered and its spatial extent dynamically changed during the last nine years in mainland China. This indicates that risk factors for JE infection are likely to be spatially heterogeneous. The results may assist national and local health authorities in the development/refinement of a better preventive strategy and increase the effectiveness of public health interventions against JE transmission.