Spatiotemporal Variation of China’s State-Owned Construction Land Supply from 2003 to 2014

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Min Jiang

2016-11-01

Full Text Available State-owned construction land is the dominant legal land source for construction in China and its supply influences urban expansion, house prices, and economic development, among other factors. Surprisingly, limited attention has been directly devoted to the spatiotemporal variation in land supply or the driving factors. This paper applied a centroid model and hotspot analysis, and created a newly increased construction land dependence-degree index (NCD to present the spatiotemporal variations of China’s construction land supply magnitude and pattern from 2003 to 2014, using land supply data from 339 cities. A two-way fixed effect model was introduced to reveal the influence of the socio-economic driving factors. The results showed that China’s state-owned construction land supply area (CLSA and newly increased construction land supply area (NCSA both increased during the period from 2003 to 2014, the geographic centroid of CLSA and NCSA moved northwest. NCD showed an overall increasing trend, and hotspots with high NCD migrated from the east region to the west region and shifted from an “east hot and west cold” pattern in 2003 to an “east cold and west hot” pattern in 2014. The gross domestic product (GDP has a U-shape effect on CLSA and NCD. The population, average annual wage of workers, and investment in fixed assets (fiv have positive effects on CLSA, and fiv also has a positive effect on NCD. The increasing ratio of tertiary industry added value to secondary industry added value reduces CLSA and NCD, and the effects of state policies vary from year to year. Different land supply policies should be implemented for cities in different development stages.

Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon.

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Putman, Nathan F; Jenkins, Erica S; Michielsens, Catherine G J; Noakes, David L G

2014-10-06

Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Spatiotemporal Variation of Driving Forces for Settlement Expansion in Different Types of Counties

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Guanglong Dong

2015-12-01

Full Text Available Understanding the process of settlement expansion and the spatiotemporal variation of driving forces is the foundation of rational and specific planning for sustainable development. However, little attention has been paid to the spatiotemporal differences of driving forces among different counties, especially when they are representatives of different development types. This study used Guanyun, Kunshan and Changshu as case studies, and binary logistic regression was employed. The results showed that the expansion rates of Kunshan and Changshu were 5.55 and 3.93 times higher than that of Guanyun. The combinations and relative importance of drivers varied with counties and periods. The change in the number of driving forces can be divided into three stages: increasing stage, decreasing stage, and stable stage. In the relatively developed counties, Kunshan and Changshu, the importance of population is decreased, while it remain an important factor in the less developed county, Guanyun. In addition, the effect of GDP stays the same in Kunshan while it becomes the most important factor in Changshu. The distance to the main road and the distance to town are increasingly important in Kunshan and Guanyun, and distance to town has been the only common factor in the last period, indicating the discrepancy is increased. The relative importance of distance to a lake in Kunshan and Changshu increased, reflecting the role of increasing tourism in accelerating settlement expansion.

Variation in predator foraging behavior changes predator-prey spatio-temporal dynamics

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1. Foraging underlies the ability of all animals to acquire essential resources and, thus, provides a critical link to understanding population dynamics. A key issue is how variation in foraging behavior affects foraging efficiency and predator-prey interactions in spatially-heterogeneous environmen...

[Spatiotemporal variation of vegetation in northern Shaanxi of Northwest China based on SPOT-VGT NDVI].

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Yang, Yan-Zheng; Zhao, Peng-Xiang; Hao, Hong-Ke; Chang, Ming

2012-07-01

By using 1998-2010 SPOT-VGT NDVI images, this paper analyzed the spatiotemporal variation of vegetation in northern Shaanxi. In 1998-2010, the NDVI in northern Shaanxi had an obvious seasonal variation. The average monthly NDVI was the minimum (0.14) in January and the maximum (0.46) in August, with a mean value of 0.28. The average annual NDVI presented an overall increasing trend, indicating that the vegetation in this area was in restoring. Spatially, the restoration of vegetation in this area was concentrated in central south part, and the degradation mainly occurred in the north of the Great Wall. Air temperature and precipitation were the important climate factors affecting the variation of vegetation, with the linear correlation coefficients to NDVI being 0.72 and 0.58, respectively. The regions with better restored vegetation were mainly on the slopes of 15 degrees-25 degrees, indicating that the Program of Conversion of Cropland to Forestland and Grassland had a favorable effect in the vegetation restoration in northern Shaanxi.

Linking habitat selection to fitness-related traits in herbivores: the role of the energy landscape

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Ryan A. Long; R. T. Bowyer; Warren P. Porter; Paul Mathewson; Kevin L. Monteith; Scott L. Findholt; Brian L. Dick; John G. Kie

2016-01-01

Animals may partially overcome environmental constraints on fitness by behaviorally adjusting their exposure to costs and supplies of energy. Few studies, however, have linked spatiotemporal variation in the energy landscape to behaviorally mediated measures of performance that ostensibly influence individual fitness. We hypothesized that strength of selection by North...

Spatiotemporal exploratory models for broad-scale survey data.

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Fink, Daniel; Hochachka, Wesley M; Zuckerberg, Benjamin; Winkler, David W; Shaby, Ben; Munson, M Arthur; Hooker, Giles; Riedewald, Mirek; Sheldon, Daniel; Kelling, Steve

2010-12-01

The distributions of animal populations change and evolve through time. Migratory species exploit different habitats at different times of the year. Biotic and abiotic features that determine where a species lives vary due to natural and anthropogenic factors. This spatiotemporal variation needs to be accounted for in any modeling of species' distributions. In this paper we introduce a semiparametric model that provides a flexible framework for analyzing dynamic patterns of species occurrence and abundance from broad-scale survey data. The spatiotemporal exploratory model (STEM) adds essential spatiotemporal structure to existing techniques for developing species distribution models through a simple parametric structure without requiring a detailed understanding of the underlying dynamic processes. STEMs use a multi-scale strategy to differentiate between local and global-scale spatiotemporal structure. A user-specified species distribution model accounts for spatial and temporal patterning at the local level. These local patterns are then allowed to "scale up" via ensemble averaging to larger scales. This makes STEMs especially well suited for exploring distributional dynamics arising from a variety of processes. Using data from eBird, an online citizen science bird-monitoring project, we demonstrate that monthly changes in distribution of a migratory species, the Tree Swallow (Tachycineta bicolor), can be more accurately described with a STEM than a conventional bagged decision tree model in which spatiotemporal structure has not been imposed. We also demonstrate that there is no loss of model predictive power when a STEM is used to describe a spatiotemporal distribution with very little spatiotemporal variation; the distribution of a nonmigratory species, the Northern Cardinal (Cardinalis cardinalis).

Evaluation of spatial and spatiotemporal estimation methods in simulation of precipitation variability patterns

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Bayat, Bardia; Zahraie, Banafsheh; Taghavi, Farahnaz; Nasseri, Mohsen

2013-08-01

Identification of spatial and spatiotemporal precipitation variations plays an important role in different hydrological applications such as missing data estimation. In this paper, the results of Bayesian maximum entropy (BME) and ordinary kriging (OK) are compared for modeling spatial and spatiotemporal variations of annual precipitation with and without incorporating elevation variations. The study area of this research is Namak Lake watershed located in the central part of Iran with an area of approximately 90,000 km2. The BME and OK methods have been used to model the spatial and spatiotemporal variations of precipitation in this watershed, and their performances have been evaluated using cross-validation statistics. The results of the case study have shown the superiority of BME over OK in both spatial and spatiotemporal modes. The results have shown that BME estimates are less biased and more accurate than OK. The improvements in the BME estimates are mostly related to incorporating hard and soft data in the estimation process, which resulted in more detailed and reliable results. Estimation error variance for BME results is less than OK estimations in the study area in both spatial and spatiotemporal modes.

Spatiotemporal Variation of Stress Drop During the 2008 Mogul, Nevada, Earthquake Swarm

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Ruhl, C. J.; Abercrombie, R. E.; Smith, K. D.

2017-10-01

We estimate stress drops for 148 shallow (function-derived spectral ratios. Near-source, temporary broadband seismometers deployed before the Mw4.9 main shock provide high-quality records of many foreshocks and aftershocks, and an ideal opportunity to investigate uncertainties in corner frequency measurement as well as stress drop (Δσ) variation related to space, time, depth, mechanism, and magnitude. We explore uncertainties related to source model, measurement approach, cross-correlation limit, and frequency bandwidth. P (S) wave Δσ results range from 0.2 ± 0.15 (0.3 ± 0.15) to 36±20 (58±7) MPa, a variation greater than the error range of each individual estimate. Although this variation is not explained simply by any one parameter, spatiotemporal variation along the main shock fault plane is distinct: coherent clusters of high and low Δσ earthquakes are seen, and high-Δσ foreshocks correlate with an area of reduced aftershock productivity. These observations are best explained by a difference in rheology along the fault plane. Average Δσs of 3.9±1.1 (4.0±1.1) MPa using P (S) are similar to those found for earthquakes in a variety of settings, implying that these shallow, potentially fluid-driven earthquakes do not have systematically lower Δσ than average tectonic earthquakes ( 4 MPa) and, therefore, have similar (or higher, due to proximity to the surface) expected ground motions compared to typical earthquakes. The unprecedented detail achieved for these shallow, small-magnitude earthquakes confirms that Δσ, when measured precisely, is a valuable observation of physically meaningful fault zone properties and earthquake behavior.

Spatiotemporal variation of PM1 pollution in China

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Chen, Gongbo; Morawska, Lidia; Zhang, Wenyi; Li, Shanshan; Cao, Wei; Ren, Hongyan; Wang, Boguang; Wang, Hao; Knibbs, Luke D.; Williams, Gail; Guo, Jianping; Guo, Yuming

2018-04-01

Understanding spatiotemporal variation of PM1 (mass concentrations of particles with aerodynamic diameter health, which is potentially more severe for its deeper penetrating capability into human bodies compared with larger particles. This study aimed to quantify the spatial and temporal distribution of PM1 across China as well as its ratio with PM2.5 (additive models were employed to examine the relationships between PM1 and meteorological parameters. We showed that PM1 concentrations were the lowest in summer and the highest in winter. Across China, the PM1/PM2.5 ratios ranged from 0.75-0.88, reaching higher levels in January and lower in August. For spatial distribution, higher PM1/PM2.5 ratios (>0.9) were observed in North-Eastern China, North China Plain, coastal areas of Eastern China and Sichuan Basin while lower ratios (<0.7) were present in remote areas in North-Western and Northern China (e.g., Xinjiang, Tibet and Inner Mongolia). Higher PM1/PM2.5 ratios were observed on heavily polluted days and lower ratios on clean days. The high PM1/PM2.5 ratios observed in China suggest that smaller particles, PM1 fraction, are key drivers of air pollution, and that they effectively account for the majority of PM2.5 concentrations. This emphasised the role of combustion process and secondary particle formation, the sources of PM1, and the significance of controlling them.

Spatiotemporal Variation in Mangrove Chlorophyll Concentration Using Landsat 8

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Julio Pastor-Guzman

2015-11-01

Full Text Available There is a need to develop indicators of mangrove condition using remotely sensed data. However, remote estimation of leaf and canopy biochemical properties and vegetation condition remains challenging. In this paper, we (i tested the performance of selected hyperspectral and broad band indices to predict chlorophyll concentration (CC on mangrove leaves and (ii showed the potential of Landsat 8 for estimation of mangrove CC at the landscape level. Relative leaf CC and leaf spectral response were measured at 12 Elementary Sampling Units (ESU distributed along the northwest coast of the Yucatan Peninsula, Mexico. Linear regression models and coefficients of determination were computed to measure the association between CC and spectral response. At leaf level, the narrow band indices with the largest correlation with CC were Vogelmann indices and the MTCI (R2 > 0.5. Indices with spectral bands around the red edge (705–753 nm were more sensitive to mangrove leaf CC. At the ESU level Landsat 8 NDVI green, which uses the green band in its formulation explained most of the variation in CC (R2 > 0.8. Accuracy assessment between estimated CC and observed CC using the leave-one-out cross-validation (LOOCV method yielded a root mean squared error (RMSE = 15 mg·cm−2, and R2 = 0.703. CC maps showing the spatiotemporal variation of CC at landscape scale were created using the linear model. Our results indicate that Landsat 8 NDVI green can be employed to estimate CC in large mangrove areas where ground networks cannot be applied, and mapping techniques based on satellite data, are necessary. Furthermore, using upcoming technologies that will include two bands around the red edge such as Sentinel 2 will improve mangrove monitoring at higher spatial and temporal resolutions.

Spatiotemporal psychopathology I: No rest for the brain's resting state activity in depression? Spatiotemporal psychopathology of depressive symptoms.

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Northoff, Georg

2016-01-15

Despite intense neurobiological investigation in psychiatric disorders like major depressive disorder (MDD), the basic disturbance that underlies the psychopathological symptoms of MDD remains, nevertheless, unclear. Neuroimaging has focused mainly on the brain's extrinsic activity, specifically task-evoked or stimulus-induced activity, as related to the various sensorimotor, affective, cognitive, and social functions. Recently, the focus has shifted to the brain's intrinsic activity, otherwise known as its resting state activity. While various abnormalities have been observed during this activity, their meaning and significance for depression, along with its various psychopathological symptoms, are yet to be defined. Based on findings in healthy brain resting state activity and its particular spatial and temporal structure - defined in a functional and physiological sense rather than anatomical and structural - I claim that the various depressive symptoms are spatiotemporal disturbances of the resting state activity and its spatiotemporal structure. This is supported by recent findings that link ruminations and increased self-focus in depression to abnormal spatial organization of resting state activity. Analogously, affective and cognitive symptoms like anhedonia, suicidal ideation, and thought disorder can be traced to an increased focus on the past, increased past-focus as basic temporal disturbance o the resting state. Based on these findings, I conclude that the various depressive symptoms must be conceived as spatiotemporal disturbances of the brain's resting state's activity and its spatiotemporal structure. Importantly, this entails a new form of psychopathology, "Spatiotemporal Psychopathology" that directly links the brain and psyche, therefore having major diagnostic and therapeutic implications for clinical practice. Copyright © 2015 Elsevier B.V. All rights reserved.

Size-dependent diffusion promotes the emergence of spatiotemporal patterns

DEFF Research Database (Denmark)

Zhang, Lai; Thygesen, Uffe Høgsbro; Banerjee, Malay

2014-01-01

intraspecific physiological variations at the individual level. Here we explore the impacts of size variation within species resulting from individual ontogeny, on the emergence of spatiotemporal patterns in a fully size-structured population model. We found that size dependency of animal's diffusivity greatly......, we found that the single-generation cycle is more likely to drive spatiotemporal patterns compared to predator-prey cycles, meaning that the mechanism of Hopf bifurcation might be more common than hitherto appreciated since the former cycle is more widespread than the latter in case of interacting...

Low-dose 4D cone-beam CT via joint spatiotemporal regularization of tensor framelet and nonlocal total variation

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Han, Hao; Gao, Hao; Xing, Lei

2017-08-01

Excessive radiation exposure is still a major concern in 4D cone-beam computed tomography (4D-CBCT) due to its prolonged scanning duration. Radiation dose can be effectively reduced by either under-sampling the x-ray projections or reducing the x-ray flux. However, 4D-CBCT reconstruction under such low-dose protocols is prone to image artifacts and noise. In this work, we propose a novel joint regularization-based iterative reconstruction method for low-dose 4D-CBCT. To tackle the under-sampling problem, we employ spatiotemporal tensor framelet (STF) regularization to take advantage of the spatiotemporal coherence of the patient anatomy in 4D images. To simultaneously suppress the image noise caused by photon starvation, we also incorporate spatiotemporal nonlocal total variation (SNTV) regularization to make use of the nonlocal self-recursiveness of anatomical structures in the spatial and temporal domains. Under the joint STF-SNTV regularization, the proposed iterative reconstruction approach is evaluated first using two digital phantoms and then using physical experiment data in the low-dose context of both under-sampled and noisy projections. Compared with existing approaches via either STF or SNTV regularization alone, the presented hybrid approach achieves improved image quality, and is particularly effective for the reconstruction of low-dose 4D-CBCT data that are not only sparse but noisy.

The influence of weather and lemmings on spatiotemporal variation in the abundance of multiple avian guilds in the arctic.

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Barry G Robinson

Full Text Available Climate change is occurring more rapidly in the Arctic than other places in the world, which is likely to alter the distribution and abundance of migratory birds breeding there. A warming climate can provide benefits to birds by decreasing spring snow cover, but increases in the frequency of summer rainstorms, another product of climate change, may reduce foraging opportunities for insectivorous birds. Cyclic lemming populations in the Arctic also influence bird abundance because Arctic foxes begin consuming bird eggs when lemmings decline. The complex interaction between summer temperature, precipitation, and the lemming cycle hinder our ability to predict how Arctic-breeding birds will respond to climate change. The main objective of this study was to investigate the relationship between annual variation in weather, spring snow cover, lemming abundance and spatiotemporal variation in the abundance of multiple avian guilds in a tundra ecosystem in central Nunavut, Canada: songbirds, shorebirds, gulls, loons, and geese. We spatially stratified our study area based on vegetation productivity, terrain ruggedness, and freshwater abundance, and conducted distance sampling to estimate strata-specific densities of each guild during the summers of 2010-2012. We also monitored temperature, rainfall, spring snow cover, and lemming abundance each year. Spatial variation in bird abundance matched what was expected based on previous ecological knowledge, but weather and lemming abundance also significantly influenced the abundance of some guilds. In particular, songbirds were less abundant during the cool, wet summer with moderate snow cover, and shorebirds and gulls declined with lemming abundance. The abundance of geese did not vary over time, possibly because benefits created by moderate spring snow cover were offset by increased fox predation when lemmings were scarce. Our study provides an example of a simple way to monitor the correlation between

Spatio-temporal variation of fish taxonomic composition in a South-East Asian flood-pulse system.

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Kong, Heng; Chevalier, Mathieu; Laffaille, Pascal; Lek, Sovan

2017-01-01

The Tonle Sap Lake (TSL) is a flood-pulse system. It is the largest natural lake in South-East Asia and constitutes one of the largest fisheries over the world, supporting the livelihood of million peoples. Nonetheless, the Mekong River Basin is changing rapidly due to accelerating water infrastructure development (hydropower, irrigation, flood control, and water supply) and climate change, bringing considerable modifications to the annual flood-pulse of the TSL. Such modifications are expected to have strong impacts on fish biodiversity and abundance. This paper aims to characterize the spatio-temporal variations of fish taxonomic composition and to highlights the underlying determinants of these variations. For this purpose, we used data collected from a community catch monitoring program conducted at six sites during 141 weeks, covering two full hydrological cycles. For each week, we estimated beta diversity as the total variance of the site-by-species community matrix and partitioned it into Local Contribution to Beta Diversity (LCBD) and Species Contribution to Beta Diversity (SCBD). We then performed multiple linear regressions to determine whether species richness, species abundances and water level explained the temporal variation in the contribution of site and species to beta diversity. Our results indicate strong temporal variation of beta diversity due to differential contributions of sites and species to the spatial variation of fish taxonomic composition. We further found that the direction, the shape and the relative effect of species richness, abundances and water level on temporal variation in LCBD and SCBD values greatly varied among sites, thus suggesting spatial variation in the processes leading to temporal variation in community composition. Overall, our results suggest that fish taxonomic composition is not homogeneously distributed over space and time and is likely to be impacted in the future if the flood-pulse dynamic of the system is

[Ciliate diversity and spatiotemporal variation in surface sediments of Yangtze River estuary hypoxic zone].

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Feng, Zhao; Kui-Dong, Xu; Zhao-Cui, Meng

2012-12-01

By using denaturing gradient gel electrophoresis (DGGE) and sequencing as well as Ludox-QPS method, an investigation was made on the ciliate diversity and its spatiotemporal variation in the surface sediments at three sites of Yangtze River estuary hypoxic zone in April and August 2011. The ANOSIM analysis indicated that the ciliate diversity had significant difference among the sites (R = 0.896, P = 0.0001), but less difference among seasons (R = 0.043, P = 0.207). The sequencing of 18S rDNA DGGE bands revealed that the most predominant groups were planktonic Choreotrichia and Oligotrichia. The detection by Ludox-QPS method showed that the species number and abundance of active ciliates were maintained at a higher level, and increased by 2-5 times in summer, as compared with those in spring. Both the Ludox-QPS method and the DGGE technique detected that the ciliate diversity at the three sites had the similar variation trend, and the Ludox-QPS method detected that there was a significant variation in the ciliate species number and abundance between different seasons. The species number detected by Ludox-QPS method was higher than that detected by DGGE bands. Our study indicated that the ciliates in Yangtze River estuary hypoxic zone had higher diversity and abundance, with the potential to supply food for the polyps of jellyfish.

Imbalance of positive and negative links induces regularity

International Nuclear Information System (INIS)

Kamal, Neeraj Kumar; Sinha, Sudeshna

2011-01-01

Research highlights: → We consider the behaviour of a random weighted network with chaotic neuronal dynamics at the nodes. → We investigate the effect of the balance of positive and negative links on dynamical regularity. → We find that when the connections are predominantly excitatory or inhibitory, one obtains a spatiotemporal fixed point. → However, when the links are balanced, the chaotic nature of the nodal dynamics of the uncoupled case is preserved. → Further we observe that larger network size leads to greater spatiotemporal regularity. - Abstract: We investigate the effect of the interplay of positive and negative links, on the dynamical regularity of a random weighted network, with neuronal dynamics at the nodes. We investigate how the mean J-bar and the variance of the weights of links, influence the spatiotemporal regularity of this dynamical network. We find that when the connections are predominantly positive (i.e. the links are mostly excitatory, with J-bar>0) the spatiotemporal fixed point is stable. A similar trend is observed when the connections are predominantly negative (i.e. the links are mostly inhibitory, with J-bar<0). However, when the positive and negative feedback is quite balanced (namely, when the mean of the connection weights is close to zero) one observes spatiotemporal chaos. That is, the balance of excitatory and inhibitory connections preserves the chaotic nature of the uncoupled case. To be brought to an inactive state one needs one type of connection (either excitatory or inhibitory) to dominate. Further we observe that larger network size leads to greater spatiotemporal regularity. We rationalize our observations through mean field analysis of the network dynamics.

Spatiotemporal variation characteristics and related affecting factors of dissolved carbohydrates in the East China Sea

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He, Zhen; Wang, Qi; Yang, Gui-Peng; Gao, Xian-Chi; Wu, Guan-Wei

2015-10-01

Carbohydrates are the largest identified fraction of dissolved organic carbon and play an important role in biogeochemical cycling in the ocean. Seawater samples were collected from the East China Sea (ECS) during June and October 2012 to study the spatiotemporal distributions of total dissolved carbohydrates (TCHOs) constituents, including dissolved monosaccharides (MCHOs) and polysaccharides (PCHOs). The concentrations of TCHOs, MCHOs and PCHOs showed significant differences between summer and autumn 2012, and exhibited an evident diurnal variation, with high values occurring in the daytime. Phytoplankton biomass was identified as the primary factor responsible for seasonal and diurnal variations of dissolved carbohydrates in the ECS. The TCHOs, MCHOs and PCHOs distributions in the study area displayed similar distribution patterns, with high concentrations appearing in the coastal water. The influences of chlorophyll-a, salinity and nutrients on the distributions of these carbohydrates were examined. A carbohydrate enrichment in the near-bottom water was found at some stations, implying that there might be an important source of carbohydrate in the deep water or bottom sediment.

[Spatiotemporal variation of soil pH in Guangdong Province of China in past 30 years].

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Guo, Zhi-Xing; Wang, Jing; Chai, Min; Chen, Ze-Peng; Zhan, Zhen-Shou; Zheng, Wu-Ping; Wei, Xiu-Guo

2011-02-01

Based on the 1980s' soil inventory data and the 2002-2007 soil pH data of Guangdong Province, the spatiotemporal variation of soil pH in the Province in past 30 years was studied. In the study period, the spatial distribution pattern of soil pH in the Province had less change (mainly acidic), except that in Pearl River Delta and parts of Qingyuan and Shaoguan (weak alkaline). The overall variation of soil pH was represented as acidification, with the average pH value changed from 5.70 to 5.44. Among the soil types in the Province, alluvial soil had an increased pH, lateritic red soil, paddy soil, and red soil had a large decrement of pH value, and lime soil was most obvious in the decrease of pH value and its area percentage. The soil acidification was mainly induced by soil characteristics, some natural factors such as acid rain, and human factors such as unreasonable fertilization and urbanization. In addition, industrialization and mining increased the soil pH in some areas.

Spatiotemporal Psychopathology II: How does a psychopathology of the brain's resting state look like? Spatiotemporal approach and the history of psychopathology.

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Northoff, Georg

2016-01-15

Psychopathology as the investigation and classification of experience, behavior and symptoms in psychiatric patients is an old discipline that ranges back to the end of the 19th century. Since then different approaches to psychopathology have been suggested. Recent investigations showing abnormalities in the brain on different levels raise the question how the gap between brain and psyche, between neural abnormalities and alteration in experience and behavior can be bridged. Historical approaches like descriptive (Jaspers) and structural (Minkoswki) psychopathology as well as the more current phenomenological psychopathology (Paarnas, Fuchs, Sass, Stanghellini) remain on the side of the psyche giving detailed description of the phenomenal level of experience while leaving open the link to the brain. In contrast, the recently introduced Research Domain Classification (RDoC) aims at explicitly linking brain and psyche by starting from so-called 'neuro-behavioral constructs'. How does Spatiotemporal Psychopathology, as demonstrated in the first paper on depression, stand in relation to these approaches? In a nutshell, Spatiotemporal Psychopathology aims to bridge the gap between brain and psyche. Specifically, as demonstrated in depression in the first paper, the focus is on the spatiotemporal features of the brain's intrinsic activity and how they are transformed into corresponding spatiotemporal features in experience on the phenomenal level and behavioral changes, which can well account for the symptoms in these patients. This second paper focuses on some of the theoretical background assumptions in Spatiotemporal Psychopathology by directly comparing it to descriptive, structural, and phenomenological psychopathology as well as to RDoC. Copyright © 2015 Elsevier B.V. All rights reserved.

Joint level-set and spatio-temporal motion detection for cell segmentation.

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Boukari, Fatima; Makrogiannis, Sokratis

2016-08-10

Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan

Annotating spatio-temporal datasets for meaningful analysis in the Web

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Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

2014-05-01

More and more environmental datasets that vary in space and time are available in the Web. This comes along with an advantage of using the data for other purposes than originally foreseen, but also with the danger that users may apply inappropriate analysis procedures due to lack of important assumptions made during the data collection process. In order to guide towards a meaningful (statistical) analysis of spatio-temporal datasets available in the Web, we have developed a Higher-Order-Logic formalism that captures some relevant assumptions in our previous work [1]. It allows to proof on meaningful spatial prediction and aggregation in a semi-automated fashion. In this poster presentation, we will present a concept for annotating spatio-temporal datasets available in the Web with concepts defined in our formalism. Therefore, we have defined a subset of the formalism as a Web Ontology Language (OWL) pattern. It allows capturing the distinction between the different spatio-temporal variable types, i.e. point patterns, fields, lattices and trajectories, that in turn determine whether a particular dataset can be interpolated or aggregated in a meaningful way using a certain procedure. The actual annotations that link spatio-temporal datasets with the concepts in the ontology pattern are provided as Linked Data. In order to allow data producers to add the annotations to their datasets, we have implemented a Web portal that uses a triple store at the backend to store the annotations and to make them available in the Linked Data cloud. Furthermore, we have implemented functions in the statistical environment R to retrieve the RDF annotations and, based on these annotations, to support a stronger typing of spatio-temporal datatypes guiding towards a meaningful analysis in R. [1] Stasch, C., Scheider, S., Pebesma, E., Kuhn, W. (2014): "Meaningful spatial prediction and aggregation", Environmental Modelling & Software, 51, 149-165.

The spatiotemporal variation in evapotranspiration of terrestrial ecosystems in China between 1982-2015

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Lian, X.; Piao, S.; Li, X.

2017-12-01

Evapotranspiration (ET) is one of the most important fluxes in the terrestrial ecosystem, and play a vital role in regulating atmosphere-hydrosphere-biosphere interaction. Several studies have suggested that global ET has significantly increased in the past several decades, and that such increase has exhibited big spatial variability, but there are few detailed studies on the spatio-temporal change in ET over China. Combining remote-sensing and ground-based observations with a machine learning approach (model tree ensemble, MTE), this study investigate the spatiotemporal variation in ET in China during 1982 and 2015. Our results showed that mean annual ET in China is 552±14mm year-1, which is within range of estimates by previous studies (from 430 mm year-1 to 555 mm year-1). ET spatially decreases from southeast to northwest, with highest value appeared in humidity regions (more than 1400 mm year-1) and lowest value in arid regions (less than 200 mm year-1). Over the past three decades, ET in China significantly increased by 1.07 mm year-2 with remarkable spatial heterogeneity. The largest increase in ET appears in the eastern periphery of SiChuan Basin, which may be related to increase in temperature, solar radiation as well as enhancing vegetation productivity. Only 20% of study area show decrease in ET, which is mainly located in parts of the southeast, southwest and northeast of China. The regional decrease in ET is likely to be contributed by decrease in solar radiation and relative humidity. Although our finding of the significant increase in China's ET at the country scale is supported by five different ET products, there are still less agreement on the change in ET at the regional scale among different ET products.

Assessment of microscale spatio-temporal variation of air pollution at an urban hotspot in Madrid (Spain) through an extensive field campaign

Science.gov (United States)

Borge, Rafael; Narros, Adolfo; Artíñano, Begoña; Yagüe, Carlos; Gómez-Moreno, Francisco Javier; de la Paz, David; Román-Cascón, Carlos; Díaz, Elías; Maqueda, Gregorio; Sastre, Mariano; Quaassdorff, Christina; Dimitroulopoulou, Chrysanthi; Vardoulakis, Sotiris

2016-09-01

Poor urban air quality is one of the main environmental concerns worldwide due to its implications for population exposure and health-related issues. However, the development of effective abatement strategies in cities requires a consistent and holistic assessment of air pollution processes, taking into account all the relevant scales within a city. This contribution presents the methodology and main results of an intensive experimental campaign carried out in a complex pollution hotspot in Madrid (Spain) under the TECNAIRE-CM research project, which aimed at understanding the microscale spatio-temporal variation of ambient concentration levels in areas where high pollution values are recorded. A variety of instruments were deployed during a three-week field campaign to provide detailed information on meteorological and micrometeorological parameters and spatio-temporal variations of the most relevant pollutants (NO2 and PM) along with relevant information needed to simulate pedestrian fluxes. The results show the strong dependence of ambient concentrations on local emissions and meteorology that turns out in strong spatial and temporal variations, with gradients up to 2 μg m-3 m-1 for NO2 and 55 μg m-3 min-1 for PM10. Pedestrian exposure to these pollutants also presents strong variations temporally and spatially but it concentrates on pedestrian crossings and bus stops. The analysis of the results show that the high concentration levels found in urban hotspots depend on extremely complex dynamic processes that cannot be captured by routinely measurements made by air quality monitoring stations used for regulatory compliance assessment. The large influence from local traffic in the concentration fields highlights the need for a detailed description of specific variables that determine emissions and dispersion at microscale level. This also indicates that city-scale interventions may be complemented with local control measures and exposure management, to improve

Hand, foot and mouth disease: spatiotemporal transmission and climate.

Science.gov (United States)

Wang, Jin-feng; Guo, Yan-Sha; Christakos, George; Yang, Wei-Zhong; Liao, Yi-Lan; Li, Zhong-Jie; Li, Xiao-Zhou; Lai, Sheng-Jie; Chen, Hong-Yan

2011-04-05

The Hand-Foot-Mouth Disease (HFMD) is the most common infectious disease in China, its total incidence being around 500,000~1,000,000 cases per year. The composite space-time disease variation is the result of underlining attribute mechanisms that could provide clues about the physiologic and demographic determinants of disease transmission and also guide the appropriate allocation of medical resources to control the disease. HFMD cases were aggregated into 1456 counties and during a period of 11 months. Suspected climate attributes to HFMD were recorded monthly at 674 stations throughout the country and subsequently interpolated within 1456 × 11 cells across space-time (same as the number of HFMD cases) using the Bayesian Maximum Entropy (BME) method while taking into consideration the relevant uncertainty sources. The dimensionalities of the two datasets together with the integrated dataset combining the two previous ones are very high when the topologies of the space-time relationships between cells are taken into account. Using a self-organizing map (SOM) algorithm the dataset dimensionality was effectively reduced into 2 dimensions, while the spatiotemporal attribute structure was maintained. 16 types of spatiotemporal HFMD transmission were identified, and 3-4 high spatial incidence clusters of the HFMD types were found throughout China, which are basically within the scope of the monthly climate (precipitation) types. HFMD propagates in a composite space-time domain rather than showing a purely spatial and purely temporal variation. There is a clear relationship between HFMD occurrence and climate. HFMD cases are geographically clustered and closely linked to the monthly precipitation types of the region. The occurrence of the former depends on the later.

Spatio-Temporal Variations of Microphytobenthos in the Botafogo and Siri estuaries (norteast - Brazil

Directory of Open Access Journals (Sweden)

Priscila Porchat de Assis Murolo

2006-03-01

Full Text Available Spatio-temporal variations of microphytobenthic biomass were investigated in the Botafogo and Siri estuaries, Pernambuco - Brazil. Samples were taken during low water (bi-monthly from February to December, 2003. Three sampling stations were located in each estuary, in both midlittoral and sublittoral areas. Clear spatial and temporal variations were found for both chlorophyll-a and phaeopigment concentrations. In Botafogo, chlorophyll-a had 34% of total variation explained by MRA from nitrogen and phosphorus concentrations, while only 16% of total variation was thus explained from nitrogen concentration in the Siri estuary. Phaeopigments had 39% of total variation explained by MRA from nitrogen concentration and salinity in the Botafogo estuary and 58% of total variation was similarly explained from nitrogen concentration in the Siri estuary. Nitrogen was discriminated by the b coefficients as the most important factor in the explanation of the microphytobenthic pigments variations in the Botafogo estuary. The data of this study emphasize the role of nutrients and suggest that both estuaries show evidence of eutrophication.Variações espaço-temporais da biomassa do microfitobentos foram investigadas nos estuários dos rios Botafogo e Siri em Pernambuco, Brasil. As amostragens foram realizadas em baixa-mar (bimestralmente de fevereiro a dezembro de 2003. Em cada estuário foram determinadas três estações de amostragem no médio- e no infralitoral. Fortes variações espaciais e temporais foram verificadas nas concentrações tanto de clorofila-a como de feopigmentos. No estuário do Botafogo, a clorofila-a teve 34% do total da sua variação explicada pela análise de regressão múltipla (MRA baseada nas concentrações de nitrogênio e de fósforo, enquanto no estuário do Siri somente 16% dessa variação foi explicada pela MRA baseada na concentração de nitrogênio. Feopigmentos apresentou 39% de sua variação total explicada pela MRA

Theta variation and spatiotemporal scaling along the septotemporal axis of the hippocampus

Directory of Open Access Journals (Sweden)

Lauren L Long

2015-03-01

Full Text Available Hippocampal theta has been related to locomotor speed, attention, anxiety, sensorimotor integration and memory among other emergent phenomena. One difficulty in understanding the function of theta is that the hippocampus (HPC modulates voluntary behavior at the same time that it processes sensory input. Both functions are correlated with characteristic changes in theta indices. The current review highlights a series of studies examining theta local field potential (LFP signals across the septotemporal or longitudinal axis of the HPC. While the theta signal is coherent throughout the entirety of the HPC, the amplitude, but not the frequency, of theta varies significantly across its three-dimensional expanse. We suggest that the theta signal offers a rich vein of information about how distributed neuronal ensembles support emergent function. Further, we speculate that emergent function across the long axis varies with respect to spatiotemporal scale. Thus, septal hippocampus processes details of the proximal spatiotemporal environment while more temporal aspects process larger spaces and wider time-scales. The degree to which emergent functions are supported by the synchronization of theta across the septotemporal axis is an open question. Our working model is that theta synchrony serves to bind ensembles representing varying resolutions of spatiotemporal information at interdependent septotemporal areas of the HPC. Such synchrony and cooperative interactions along the septotemporal axis likely support memory formation and subsequent consolidation and retrieval.

Hand, foot and mouth disease: spatiotemporal transmission and climate

Directory of Open Access Journals (Sweden)

Li Xiao-Zhou

2011-04-01

Full Text Available Abstract Background The Hand-Foot-Mouth Disease (HFMD is the most common infectious disease in China, its total incidence being around 500,000 ~1,000,000 cases per year. The composite space-time disease variation is the result of underlining attribute mechanisms that could provide clues about the physiologic and demographic determinants of disease transmission and also guide the appropriate allocation of medical resources to control the disease. Methods and Findings HFMD cases were aggregated into 1456 counties and during a period of 11 months. Suspected climate attributes to HFMD were recorded monthly at 674 stations throughout the country and subsequently interpolated within 1456 × 11 cells across space-time (same as the number of HFMD cases using the Bayesian Maximum Entropy (BME method while taking into consideration the relevant uncertainty sources. The dimensionalities of the two datasets together with the integrated dataset combining the two previous ones are very high when the topologies of the space-time relationships between cells are taken into account. Using a self-organizing map (SOM algorithm the dataset dimensionality was effectively reduced into 2 dimensions, while the spatiotemporal attribute structure was maintained. 16 types of spatiotemporal HFMD transmission were identified, and 3-4 high spatial incidence clusters of the HFMD types were found throughout China, which are basically within the scope of the monthly climate (precipitation types. Conclusions HFMD propagates in a composite space-time domain rather than showing a purely spatial and purely temporal variation. There is a clear relationship between HFMD occurrence and climate. HFMD cases are geographically clustered and closely linked to the monthly precipitation types of the region. The occurrence of the former depends on the later.

Spatio-temporal variation in chemical characteristics of PM10 over Indo Gangetic Plain of India.

Science.gov (United States)

Sharma, S K; Mandal, T K; Srivastava, M K; Chatterjee, A; Jain, Srishti; Saxena, M; Singh, B P; Saraswati; Sharma, A; Adak, A; K Ghosh, S

2016-09-01

The paper presents the spatio-temporal variation of chemical compositions (organic carbon (OC), elemental carbon (EC), and water-soluble inorganic ionic components (WSIC)) of particulate matter (PM10) over three locations (Delhi, Varanasi, and Kolkata) of Indo Gangetic Plain (IGP) of India for the year 2011. The observational sites are chosen to represent the characteristics of upper (Delhi), middle (Varanasi), and lower (Kolkata) IGP regions as converse to earlier single-station observation. Average mass concentration of PM10 was observed higher in the middle IGP (Varanasi 206.2 ± 77.4 μg m(-3)) as compared to upper IGP (Delhi 202.3 ± 74.3 μg m(-3)) and lower IGP (Kolkata 171.5 ± 38.5 μg m(-3)). Large variation in OC values from 23.57 μg m(-3) (Delhi) to 12.74 μg m(-3) (Kolkata) indicating role of formation of secondary aerosols, whereas EC have not shown much variation with maximum concentration over Delhi (10.07 μg m(-3)) and minimum over Varanasi (7.72 μg m(-3)). As expected, a strong seasonal variation was observed in the mass concentration of PM10 as well as in its chemical composition over the three locations. Principal component analysis (PCA) identifies the contribution of secondary aerosol, biomass burning, fossil fuel combustion, vehicular emission, and sea salt to PM10 mass concentration at the observational sites of IGP, India. Backward trajectory analysis indicated the influence of continental type aerosols being transported from the Bay of Bengal, Pakistan, Afghanistan, Rajasthan, Gujarat, and surrounding areas to IGP region.

Two decades of spatiotemporal variations in subduction zone coupling offshore Japan

Science.gov (United States)

Loveless, John P.; Meade, Brendan J.

2016-02-01

Spatial patterns of interplate coupling on global subduction zones can be used to guide seismic hazard assessment, but estimates of coupling are often constrained using a limited temporal range of geodetic data. Here we analyze ∼19 years of geodetic observations from the GEONET network to assess time-dependent variations in the spatial distribution of coupling on the subduction zones offshore Japan. We divide the position time series into five, ∼3.75-year epochs each decomposed into best-fit velocity, annual periodic signals, coseismic offsets, and postseismic effects following seven major earthquakes. Nominally interseismic velocities are interpreted in terms of a combination of tectonic block motions and earthquake cycle activity. The duration of the inferred postseismic activity covaries with the linear velocity. To address this trade-off, we assume that the nominally interseismic velocity at each station varies minimally from epoch to epoch. This approach is distinct from prior time-series analysis across the earthquake cycle in that position data are not detrended using preseismic velocity, which inherently assumes that interseismic processes are spatially stable through time, but rather the best-fit velocity at each station may vary between epochs. These velocities reveal significant consistency since 1996 in the spatial distribution of coupling on the Nankai subduction zone, with variation limited primarily to the Tokai and Bungo Channel regions, where long-term slow slip events have occurred, and persistently coupled regions coincident with areas that slipped during historic great earthquakes. On the Sagami subduction zone south of Tokyo, we also estimate relatively stable coupling through time. On the Japan-Kuril Trench, we image significant coupling variations owing to effects of the 1994 MW = 7.7 Sanriku-oki, 2003 MW = 8.2 Tokachi-oki, and 2011 MW = 9.0 Tohoku-oki earthquakes. In particular, strong coupling becomes more spatially extensive following

Spatiotemporal monitoring of soil water content profiles in an irrigated field using probabilistic inversion of time-lapse EMI data

Science.gov (United States)

Moghadas, Davood; Jadoon, Khan Zaib; McCabe, Matthew F.

2017-12-01

Monitoring spatiotemporal variations of soil water content (θ) is important across a range of research fields, including agricultural engineering, hydrology, meteorology and climatology. Low frequency electromagnetic induction (EMI) systems have proven to be useful tools in mapping soil apparent electrical conductivity (σa) and soil moisture. However, obtaining depth profile water content is an area that has not been fully explored using EMI. To examine this, we performed time-lapse EMI measurements using a CMD mini-Explorer sensor along a 10 m transect of a maize field over a 6 day period. Reference data were measured at the end of the profile via an excavated pit using 5TE capacitance sensors. In order to derive a time-lapse, depth-specific subsurface image of electrical conductivity (σ), we applied a probabilistic sampling approach, DREAM(ZS) , on the measured EMI data. The inversely estimated σ values were subsequently converted to θ using the Rhoades et al. (1976) petrophysical relationship. The uncertainties in measured σa, as well as inaccuracies in the inverted data, introduced some discrepancies between estimated σ and reference values in time and space. Moreover, the disparity between the measurement footprints of the 5TE and CMD Mini-Explorer sensors also led to differences. The obtained θ permitted an accurate monitoring of the spatiotemporal distribution and variation of soil water content due to root water uptake and evaporation. The proposed EMI measurement and modeling technique also allowed for detecting temporal root zone soil moisture variations. The time-lapse θ monitoring approach developed using DREAM(ZS) thus appears to be a useful technique to understand spatiotemporal patterns of soil water content and provide insights into linked soil moisture vegetation processes and the dynamics of soil moisture/infiltration processes.

Spatiotemporal monitoring of soil water content profiles in an irrigated field using probabilistic inversion of time-lapse EMI data

KAUST Repository

Moghadas, Davood

2017-10-17

Monitoring spatiotemporal variations of soil water content (θ) is important across a range of research fields, including agricultural engineering, hydrology, meteorology and climatology. Low frequency electromagnetic induction (EMI) systems have proven to be useful tools in mapping soil apparent electrical conductivity (σa) and soil moisture. However, obtaining depth profile water content is an area that has not been fully explored using EMI. To examine this, we performed time-lapse EMI measurements using a CMD mini-Explorer sensor along a 10 m transect of a maize field over a 6 day period. Reference data were measured at the end of the profile via an excavated pit using 5TE capacitance sensors. In order to derive a time-lapse, depth-specific subsurface image of electrical conductivity (σ), we applied a probabilistic sampling approach, DREAM(ZS), on the measured EMI data. The inversely estimated σ values were subsequently converted to θ using the Rhoades et al. (1976) petrophysical relationship. The uncertainties in measured σa, as well as inaccuracies in the inverted data, introduced some discrepancies between estimated σ and reference values in time and space. Moreover, the disparity between the measurement footprints of the 5TE and CMD Mini-Explorer sensors also led to differences. The obtained θ permitted an accurate monitoring of the spatiotemporal distribution and variation of soil water content due to root water uptake and evaporation. The proposed EMI measurement and modeling technique also allowed for detecting temporal root zone soil moisture variations. The time-lapse θ monitoring approach developed using DREAM(ZS) thus appears to be a useful technique to understand spatiotemporal patterns of soil water content and provide insights into linked soil moisture vegetation processes and the dynamics of soil moisture/infiltration processes.

Spatiotemporal monitoring of soil water content profiles in an irrigated field using probabilistic inversion of time-lapse EMI data

KAUST Repository

Moghadas, Davood; Jadoon, Khan Zaib; McCabe, Matthew

2017-01-01

Monitoring spatiotemporal variations of soil water content (θ) is important across a range of research fields, including agricultural engineering, hydrology, meteorology and climatology. Low frequency electromagnetic induction (EMI) systems have proven to be useful tools in mapping soil apparent electrical conductivity (σa) and soil moisture. However, obtaining depth profile water content is an area that has not been fully explored using EMI. To examine this, we performed time-lapse EMI measurements using a CMD mini-Explorer sensor along a 10 m transect of a maize field over a 6 day period. Reference data were measured at the end of the profile via an excavated pit using 5TE capacitance sensors. In order to derive a time-lapse, depth-specific subsurface image of electrical conductivity (σ), we applied a probabilistic sampling approach, DREAM(ZS), on the measured EMI data. The inversely estimated σ values were subsequently converted to θ using the Rhoades et al. (1976) petrophysical relationship. The uncertainties in measured σa, as well as inaccuracies in the inverted data, introduced some discrepancies between estimated σ and reference values in time and space. Moreover, the disparity between the measurement footprints of the 5TE and CMD Mini-Explorer sensors also led to differences. The obtained θ permitted an accurate monitoring of the spatiotemporal distribution and variation of soil water content due to root water uptake and evaporation. The proposed EMI measurement and modeling technique also allowed for detecting temporal root zone soil moisture variations. The time-lapse θ monitoring approach developed using DREAM(ZS) thus appears to be a useful technique to understand spatiotemporal patterns of soil water content and provide insights into linked soil moisture vegetation processes and the dynamics of soil moisture/infiltration processes.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

Science.gov (United States)

Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

Spatiotemporal variability in carbon exchange fluxes across the Sahel

DEFF Research Database (Denmark)

Tagesson, Håkan Torbern; Fensholt, Rasmus; Cappelaere, Bernard

2016-01-01

for semi-arid ecosystems. We have synthesized data on the land-atmosphere exchange of CO2 measured with the eddy covariance technique from the six existing sites across the Sahel, one of the largest semi-arid regions in the world. The overall aim of the study is to analyse and quantify the spatiotemporal...... variability in these fluxes and to analyse to which degree spatiotemporal variation can be explained by hydrological, climatic, edaphic and vegetation variables. All ecosystems were C sinks (average ± total error -162 ± 48 g C m-2 y-1), but were smaller when strongly impacted by anthropogenic influences...

Building spatio-temporal database model based on ontological approach using relational database environment

International Nuclear Information System (INIS)

Mahmood, N.; Burney, S.M.A.

2017-01-01

Everything in this world is encapsulated by space and time fence. Our daily life activities are utterly linked and related with other objects in vicinity. Therefore, a strong relationship exist with our current location, time (including past, present and future) and event through with we are moving as an object also affect our activities in life. Ontology development and its integration with database are vital for the true understanding of the complex systems involving both spatial and temporal dimensions. In this paper we propose a conceptual framework for building spatio-temporal database model based on ontological approach. We have used relational data model for modelling spatio-temporal data content and present our methodology with spatio-temporal ontological accepts and its transformation into spatio-temporal database model. We illustrate the implementation of our conceptual model through a case study related to cultivated land parcel used for agriculture to exhibit the spatio-temporal behaviour of agricultural land and related entities. Moreover, it provides a generic approach for designing spatiotemporal databases based on ontology. The proposed model is capable to understand the ontological and somehow epistemological commitments and to build spatio-temporal ontology and transform it into a spatio-temporal data model. Finally, we highlight the existing and future research challenges. (author)

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

Science.gov (United States)

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

Bayesian spatio-temporal modeling of particulate matter concentrations in Peninsular Malaysia

Science.gov (United States)

Manga, Edna; Awang, Norhashidah

2016-06-01

This article presents an application of a Bayesian spatio-temporal Gaussian process (GP) model on particulate matter concentrations from Peninsular Malaysia. We analyze daily PM10 concentration levels from 35 monitoring sites in June and July 2011. The spatiotemporal model set in a Bayesian hierarchical framework allows for inclusion of informative covariates, meteorological variables and spatiotemporal interactions. Posterior density estimates of the model parameters are obtained by Markov chain Monte Carlo methods. Preliminary data analysis indicate information on PM10 levels at sites classified as industrial locations could explain part of the space time variations. We include the site-type indicator in our modeling efforts. Results of the parameter estimates for the fitted GP model show significant spatio-temporal structure and positive effect of the location-type explanatory variable. We also compute some validation criteria for the out of sample sites that show the adequacy of the model for predicting PM10 at unmonitored sites.

Synchronization of spatiotemporal chaotic systems by feedback control

International Nuclear Information System (INIS)

Lai, Y.; Grebogi, C.

1994-01-01

We demonstrate that two identical spatiotemporal chaotic systems can be synchronized by (1) linking one or a few of their dynamical variables, and (2) applying a small feedback control to one of the systems. Numerical examples using the diffusively coupled logistic map lattice are given. The effect of noise and the limitation of the technique are discussed

Spatiotemporal variations in metal accumulation, RNA/DNA ratio and energy reserve in Perna viridis transplanted along a marine pollution gradient in Hong Kong.

Science.gov (United States)

Yeung, Jamius W Y; Zhou, Guang-Jie; Leung, Kenneth M Y

2017-11-30

We examined spatiotemporal variations of metal levels and three growth related biomarkers, i.e., RNA/DNA ratio (RD), total energy reserve (Et) and condition index (CI), in green-lipped mussels Perna viridis transplanted into five locations along a pollution gradient in the marine environment of Hong Kong over 120days of deployment. There were significant differences in metal levels and biomarker responses among the five sites and six time points. Mussels in two clean sites displayed better CI and significantly lower levels of Ag, Cu, Pb and Zn in their tissues than the other sites. Temporal patterns of RD in P. viridis were found to be site-specific. Across all sites, Et decreased in P. viridis over the deployment period, though the rate of decrease varied significantly among the sites. Therefore, temporal variation of biomarkers should be taken to consideration in mussel-watch programs because such information can help discriminate pollution-induced change from natural variation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatiotemporal Interpolation of Rainfall by Combining BME Theory and Satellite Rainfall Estimates

Directory of Open Access Journals (Sweden)

Tingting Shi

2015-09-01

Full Text Available The accurate assessment of spatiotemporal rainfall variability is a crucial and challenging task in many hydrological applications, mainly due to the lack of a sufficient number of rain gauges. The purpose of the present study is to investigate the spatiotemporal variations of annual and monthly rainfall over Fujian province in China by combining the Bayesian maximum entropy (BME method and satellite rainfall estimates. Specifically, based on annual and monthly rainfall data at 20 meteorological stations from 2000 to 2012, (1 the BME method with Tropical Rainfall Measuring Mission (TRMM estimates considered as soft data, (2 ordinary kriging (OK and (3 cokriging (CK were employed to model the spatiotemporal variations of rainfall in Fujian province. Subsequently, the performance of these methods was evaluated using cross-validation statistics. The results demonstrated that BME with TRMM as soft data (BME-TRMM performed better than the other two methods, generating rainfall maps that represented the local rainfall disparities in a more realistic manner. Of the three interpolation (mapping methods, the mean absolute error (MAE and root mean square error (RMSE values of the BME-TRMM method were the smallest. In conclusion, the BME-TRMM method improved spatiotemporal rainfall modeling and mapping by integrating hard data and soft information. Lastly, the study identified new opportunities concerning the application of TRMM rainfall estimates.

Current understanding of the driving mechanisms for spatiotemporal variations of atmospheric speciated mercury: a review

Directory of Open Access Journals (Sweden)

H. Mao

2016-10-01

Full Text Available Atmospheric mercury (Hg is a global pollutant and thought to be the main source of mercury in oceanic and remote terrestrial systems, where it becomes methylated and bioavailable; hence, atmospheric mercury pollution has global consequences for both human and ecosystem health. Understanding of spatial and temporal variations of atmospheric speciated mercury can advance our knowledge of mercury cycling in various environments. This review summarized spatiotemporal variations of total gaseous mercury or gaseous elemental mercury (TGM/GEM, gaseous oxidized mercury (GOM, and particulate-bound mercury (PBM in various environments including oceans, continents, high elevation, the free troposphere, and low to high latitudes. In the marine boundary layer (MBL, the oxidation of GEM was generally thought to drive the diurnal and seasonal variations of TGM/GEM and GOM in most oceanic regions, leading to lower GEM and higher GOM from noon to afternoon and higher GEM during winter and higher GOM during spring–summer. At continental sites, the driving mechanisms of TGM/GEM diurnal patterns included surface and local emissions, boundary layer dynamics, GEM oxidation, and for high-elevation sites mountain–valley winds, while oxidation of GEM and entrainment of free tropospheric air appeared to control the diurnal patterns of GOM. No pronounced diurnal variation was found for Tekran measured PBM at MBL and continental sites. Seasonal variations in TGM/GEM at continental sites were attributed to increased winter combustion and summertime surface emissions, and monsoons in Asia, while those in GOM were controlled by GEM oxidation, free tropospheric transport, anthropogenic emissions, and wet deposition. Increased PBM at continental sites during winter was primarily due to local/regional coal and wood combustion emissions. Long-term TGM measurements from the MBL and continental sites indicated an overall declining trend. Limited measurements suggested TGM

Current understanding of the driving mechanisms for spatiotemporal variations of atmospheric speciated mercury: a review

Science.gov (United States)

Mao, Huiting; Cheng, Irene; Zhang, Leiming

2016-10-01

Atmospheric mercury (Hg) is a global pollutant and thought to be the main source of mercury in oceanic and remote terrestrial systems, where it becomes methylated and bioavailable; hence, atmospheric mercury pollution has global consequences for both human and ecosystem health. Understanding of spatial and temporal variations of atmospheric speciated mercury can advance our knowledge of mercury cycling in various environments. This review summarized spatiotemporal variations of total gaseous mercury or gaseous elemental mercury (TGM/GEM), gaseous oxidized mercury (GOM), and particulate-bound mercury (PBM) in various environments including oceans, continents, high elevation, the free troposphere, and low to high latitudes. In the marine boundary layer (MBL), the oxidation of GEM was generally thought to drive the diurnal and seasonal variations of TGM/GEM and GOM in most oceanic regions, leading to lower GEM and higher GOM from noon to afternoon and higher GEM during winter and higher GOM during spring-summer. At continental sites, the driving mechanisms of TGM/GEM diurnal patterns included surface and local emissions, boundary layer dynamics, GEM oxidation, and for high-elevation sites mountain-valley winds, while oxidation of GEM and entrainment of free tropospheric air appeared to control the diurnal patterns of GOM. No pronounced diurnal variation was found for Tekran measured PBM at MBL and continental sites. Seasonal variations in TGM/GEM at continental sites were attributed to increased winter combustion and summertime surface emissions, and monsoons in Asia, while those in GOM were controlled by GEM oxidation, free tropospheric transport, anthropogenic emissions, and wet deposition. Increased PBM at continental sites during winter was primarily due to local/regional coal and wood combustion emissions. Long-term TGM measurements from the MBL and continental sites indicated an overall declining trend. Limited measurements suggested TGM/GEM increasing from the

Coexistence of collapse and stable spatiotemporal solitons in multimode fibers

Science.gov (United States)

Shtyrina, Olga V.; Fedoruk, Mikhail P.; Kivshar, Yuri S.; Turitsyn, Sergei K.

2018-01-01

We analyze spatiotemporal solitons in multimode optical fibers and demonstrate the existence of stable solitons, in a sharp contrast to earlier predictions of collapse of multidimensional solitons in three-dimensional media. We discuss the coexistence of blow-up solutions and collapse stabilization by a low-dimensional external potential in graded-index media, and also predict the existence of stable higher-order nonlinear waves such as dipole-mode spatiotemporal solitons. To support the main conclusions of our numerical studies we employ a variational approach and derive analytically the stability criterion for input powers for the collapse stabilization.

Spiking neural network for recognizing spatiotemporal sequences of spikes

International Nuclear Information System (INIS)

Jin, Dezhe Z.

2004-01-01

Sensory neurons in many brain areas spike with precise timing to stimuli with temporal structures, and encode temporally complex stimuli into spatiotemporal spikes. How the downstream neurons read out such neural code is an important unsolved problem. In this paper, we describe a decoding scheme using a spiking recurrent neural network. The network consists of excitatory neurons that form a synfire chain, and two globally inhibitory interneurons of different types that provide delayed feedforward and fast feedback inhibition, respectively. The network signals recognition of a specific spatiotemporal sequence when the last excitatory neuron down the synfire chain spikes, which happens if and only if that sequence was present in the input spike stream. The recognition scheme is invariant to variations in the intervals between input spikes within some range. The computation of the network can be mapped into that of a finite state machine. Our network provides a simple way to decode spatiotemporal spikes with diverse types of neurons

Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system

Energy Technology Data Exchange (ETDEWEB)

Banerjee, Tanmoy, E-mail: tbanerjee@phys.buruniv.ac.in; Paul, Bishwajit; Sarkar, B. C. [Department of Physics, University of Burdwan, Burdwan, West Bengal 713 104 (India)

2014-03-15

We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strength the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.

Spatiotemporal object history affects the selection of task-relevant properties

NARCIS (Netherlands)

Schreij, D.B.B.; Olivers, C.N.L.

2013-01-01

For stable perception, we maintain mental representations of objects across space and time. Whatinformation is linked to such a representation? In this study, we extended our work showing that the spatiotemporal history of an object affects the way the object is attended the next time it is

Spatio-Temporal Rule Mining

DEFF Research Database (Denmark)

Gidofalvi, Gyozo; Pedersen, Torben Bach

2005-01-01

Recent advances in communication and information technology, such as the increasing accuracy of GPS technology and the miniaturization of wireless communication devices pave the road for Location-Based Services (LBS). To achieve high quality for such services, spatio-temporal data mining techniques...... are needed. In this paper, we describe experiences with spatio-temporal rule mining in a Danish data mining company. First, a number of real world spatio-temporal data sets are described, leading to a taxonomy of spatio-temporal data. Second, the paper describes a general methodology that transforms...... the spatio-temporal rule mining task to the traditional market basket analysis task and applies it to the described data sets, enabling traditional association rule mining methods to discover spatio-temporal rules for LBS. Finally, unique issues in spatio-temporal rule mining are identified and discussed....

A BAYESIAN SPATIAL AND TEMPORAL MODELING APPROACH TO MAPPING GEOGRAPHIC VARIATION IN MORTALITY RATES FOR SUBNATIONAL AREAS WITH R-INLA.

Science.gov (United States)

Khana, Diba; Rossen, Lauren M; Hedegaard, Holly; Warner, Margaret

2018-01-01

Hierarchical Bayes models have been used in disease mapping to examine small scale geographic variation. State level geographic variation for less common causes of mortality outcomes have been reported however county level variation is rarely examined. Due to concerns about statistical reliability and confidentiality, county-level mortality rates based on fewer than 20 deaths are suppressed based on Division of Vital Statistics, National Center for Health Statistics (NCHS) statistical reliability criteria, precluding an examination of spatio-temporal variation in less common causes of mortality outcomes such as suicide rates (SRs) at the county level using direct estimates. Existing Bayesian spatio-temporal modeling strategies can be applied via Integrated Nested Laplace Approximation (INLA) in R to a large number of rare causes of mortality outcomes to enable examination of spatio-temporal variations on smaller geographic scales such as counties. This method allows examination of spatiotemporal variation across the entire U.S., even where the data are sparse. We used mortality data from 2005-2015 to explore spatiotemporal variation in SRs, as one particular application of the Bayesian spatio-temporal modeling strategy in R-INLA to predict year and county-specific SRs. Specifically, hierarchical Bayesian spatio-temporal models were implemented with spatially structured and unstructured random effects, correlated time effects, time varying confounders and space-time interaction terms in the software R-INLA, borrowing strength across both counties and years to produce smoothed county level SRs. Model-based estimates of SRs were mapped to explore geographic variation.

Mapping child maltreatment risk: a 12-year spatio-temporal analysis of neighborhood influences.

Science.gov (United States)

Gracia, Enrique; López-Quílez, Antonio; Marco, Miriam; Lila, Marisol

2017-10-18

'Place' matters in understanding prevalence variations and inequalities in child maltreatment risk. However, most studies examining ecological variations in child maltreatment risk fail to take into account the implications of the spatial and temporal dimensions of neighborhoods. In this study, we conduct a high-resolution small-area study to analyze the influence of neighborhood characteristics on the spatio-temporal epidemiology of child maltreatment risk. We conducted a 12-year (2004-2015) small-area Bayesian spatio-temporal epidemiological study with all families with child maltreatment protection measures in the city of Valencia, Spain. As neighborhood units, we used 552 census block groups. Cases were geocoded using the family address. Neighborhood-level characteristics analyzed included three indicators of neighborhood disadvantage-neighborhood economic status, neighborhood education level, and levels of policing activity-, immigrant concentration, and residential instability. Bayesian spatio-temporal modelling and disease mapping methods were used to provide area-specific risk estimations. Results from a spatio-temporal autoregressive model showed that neighborhoods with low levels of economic and educational status, with high levels of policing activity, and high immigrant concentration had higher levels of substantiated child maltreatment risk. Disease mapping methods were used to analyze areas of excess risk. Results showed chronic spatial patterns of high child maltreatment risk during the years analyzed, as well as stability over time in areas of low risk. Areas with increased or decreased child maltreatment risk over the years were also observed. A spatio-temporal epidemiological approach to study the geographical patterns, trends over time, and the contextual determinants of child maltreatment risk can provide a useful method to inform policy and action. This method can offer a more accurate description of the problem, and help to inform more

Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal adjustment scale

Science.gov (United States)

Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.

2012-01-01

State updating of distributed rainfall-runoff models via streamflow assimilation is subject to overfitting because large dimensionality of the state space of the model may render the assimilation problem seriously under-determined. To examine the issue in the context of operational hydrology, we carry out a set of real-world experiments in which streamflow data is assimilated into gridded Sacramento Soil Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM) with the variational data assimilation technique. Study basins include four basins in Oklahoma and five basins in Texas. To assess the sensitivity of data assimilation performance to dimensionality reduction in the control vector, we used nine different spatiotemporal adjustment scales, where state variables are adjusted in a lumped, semi-distributed, or distributed fashion and biases in precipitation and potential evaporation (PE) are adjusted hourly, 6-hourly, or kept time-invariant. For each adjustment scale, three different streamflow assimilation scenarios are explored, where streamflow observations at basin interior points, at the basin outlet, or at both interior points and the outlet are assimilated. The streamflow assimilation experiments with nine different basins show that the optimum spatiotemporal adjustment scale varies from one basin to another and may be different for streamflow analysis and prediction in all of the three streamflow assimilation scenarios. The most preferred adjustment scale for seven out of nine basins is found to be the distributed, hourly scale, despite the fact that several independent validation results at this adjustment scale indicated the occurrence of overfitting. Basins with highly correlated interior and outlet flows tend to be less sensitive to the adjustment scale and could benefit more from streamflow assimilation. In comparison to outlet flow assimilation, interior flow

Bayesian Spatiotemporal Analysis of Socio-Ecologic Drivers of Ross River Virus Transmission in Queensland, Australia

Science.gov (United States)

Hu, Wenbiao; Clements, Archie; Williams, Gail; Tong, Shilu; Mengersen, Kerrie

2010-01-01

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. PMID:20810846

Suitable landscape classification systems for quantifying spatiotemporal development of riverine ecosystem services

NARCIS (Netherlands)

Koopman, K.R.; Augustijn, Dionysius C.M.; Breure, A.M.; Lenders, H.J.R.; Leuven, R.S.E.W.

River systems provide numerous ecosystem services that contribute to human well-being. Biophysical quantification of spatiotemporal development of ecosystem services is useful for environmental impact assessments or scenario analyses of river management and could be done by linking biophysical

[Spatiotemporal variations of natural wetland CH4 emissions over China under future climate change].

Science.gov (United States)

Liu, Jian-gong; Zhu, Qiu-an; Shen, Yan; Yang, Yan-zheng; Luo, Yun-peng; Peng, Chang-hui

2015-11-01

Based on a new process-based model, TRIPLEX-GHG, this paper analyzed the spatio-temporal variations of natural wetland CH4 emissions over China under different future climate change scenarios. When natural wetland distributions were fixed, the amount of CH4 emissions from natural wetland ecosystem over China would increase by 32.0%, 55.3% and 90.8% by the end of 21st century under three representative concentration pathways (RCPs) scenarios, RCP2. 6, RCP4.5 and RCP8.5, respectively, compared with the current level. Southern China would have higher CH4 emissions compared to that from central and northern China. Besides, there would be relatively low emission fluxes in western China while relatively high emission fluxes in eastern China. Spatially, the areas with relatively high CH4 emission fluxes would be concentrated in the middle-lower reaches of the Yangtze River, the Northeast and the coasts of the Pearl River. In the future, most natural wetlands would emit more CH4 for RCP4.5 and RCP8.5 than that of 2005. However, under RCP2.6 scenario, the increasing trend would be curbed and CH4 emissions (especially from the Qinghai-Tibet Plateau) begin to decrease in the late 21st century.

Spatiotemporal Data Mining: A Computational Perspective

Directory of Open Access Journals (Sweden)

Shashi Shekhar

2015-10-01

Full Text Available Explosive growth in geospatial and temporal data as well as the emergence of new technologies emphasize the need for automated discovery of spatiotemporal knowledge. Spatiotemporal data mining studies the process of discovering interesting and previously unknown, but potentially useful patterns from large spatiotemporal databases. It has broad application domains including ecology and environmental management, public safety, transportation, earth science, epidemiology, and climatology. The complexity of spatiotemporal data and intrinsic relationships limits the usefulness of conventional data science techniques for extracting spatiotemporal patterns. In this survey, we review recent computational techniques and tools in spatiotemporal data mining, focusing on several major pattern families: spatiotemporal outlier, spatiotemporal coupling and tele-coupling, spatiotemporal prediction, spatiotemporal partitioning and summarization, spatiotemporal hotspots, and change detection. Compared with other surveys in the literature, this paper emphasizes the statistical foundations of spatiotemporal data mining and provides comprehensive coverage of computational approaches for various pattern families. ISPRS Int. J. Geo-Inf. 2015, 4 2307 We also list popular software tools for spatiotemporal data analysis. The survey concludes with a look at future research needs.

Spatiotemporal distribution and variation of GPP in the Greater Khingan Mountains from 1982 to 2015

Science.gov (United States)

Hu, L.; Fan, W.; Liu, S.; Ren, H.; Xu, X.

2017-12-01

GPP (Gross Primary Productivity) is an important index to reflect the productivity of plants because it refers to the organic accumulated by green plants on land through assimilating the carbon dioxide in the atmosphere by photosynthesis and a serial of physiological processes in plants. Therefore, GPP plays a significant role in studying the carbon sink of terrestrial ecosystem and plants' reaction to global climate change. Remote sensing provides an efficient way to estimate GPP at regional and global scales and its products can be used to monitor the spatiotemporal variation of terrestrial ecosystem.As the Greater Khingan Mountains is the only bright coniferous forest of cool temperate zone in China and accounts for about 30% of the forest in China. This region is sensitive to climate change, but its forest coverage presented a significant variation due to fire disasters, excessive deforestation and so on. Here, we aimed at studying the variation pattern of GPP in the Greater Khingan Mountains and further found impact factors for the change in order to improve the understanding of what have and will happen on plants and carbon cycle under climate change.Based on GPP product from the GLASS program, we first studied spatial distribution of plants in the Greater Khingan Mountains from 1982 to 2015. With a linear regression model, seasonal and inter-annual GPP variability were explored on pixel and regional scale. We analyzed some climatic factors (e.g. temperature and precipitation) and terrain in order to find the driven factors for the GPP variations. The Growing Season Length (GSL) was also regarded as a factor and was retrieved from GIMMS 3g NDVI datasets using dynamic threshold method. We found that GPP in study area linearly decreased with the increasing elevation. Both annual accumulated GPP (AAG) and maximum daily GPP (during mid-June to mid-July) gained obvious improvement over the past 34 years under climate warming and drying (Fig.1 and Fig.2). Further

Exploring the spatio-temporal interrelation between groundwater and surface water by using the self-organizing maps

Science.gov (United States)

Chen, I.-Ting; Chang, Li-Chiu; Chang, Fi-John

2018-01-01

In this study, we propose a soft-computing methodology to visibly explore the spatio-temporal groundwater variations of the Kuoping River basin in southern Taiwan. The self-organizing map (SOM) is implemented to investigate the interactive mechanism between surface water and groundwater over the river basin based on large high-dimensional data sets coupled with their occurrence times. We find that extracting the occurrence time from each 30-day moving average data set in the clustered neurons of the SOM is a crucial step to learn the spatio-temporal interaction between surface water and groundwater. We design 2-D Topological Bubble Map to summarize all the groundwater values of four aquifers in a neuron, which can visibly explore the major features of the groundwater in the vertical direction. The constructed SOM topological maps nicely display that: (1) the groundwater movement, in general, extends from the eastern area to the western, where groundwater in the eastern area can be easily recharged from precipitation in wet seasons and discharged into streams during dry seasons due to the high permeability in this area; (2) the water movements in the four aquifers of the study area are quite different, and the seasonal variations of groundwater in the second and third aquifers are larger than those of the others; and (3) the spatial distribution and seasonal variations of groundwater and surface water are comprehensively linked together over the constructed maps to present groundwater characteristics and the interrelation between groundwater and surface water. The proposed modeling methodology not only can classify the large complex high-dimensional data sets into visible topological maps to effectively facilitate the quantitative status of regional groundwater resources but can also provide useful elaboration for future groundwater management.

Spatio-temporal reasoning and decision support tools

OpenAIRE

Renso, Chiara; Wachowicz, Monica

2014-01-01

Currently, mobility data is revolutionizing the traditional fields of spatio-temporal reasoning and decision making analysis, not only to scale-up to the large and growing data volumes, but also to address complex questions related to change, trends, duration, and evolution. In mobility data, space and time are inextricably linked, since humans, robots and systems that dynamically act, and interact within social networks, are embedded in space, and any change is often the result of actions an...

Spatio-temporal population genetics of the Danish pine marten (Martes martes)

DEFF Research Database (Denmark)

Pertoldi, Cino; Barker, Stuart F.; Madsen, Aksel Bo

2008-01-01

A spatio-temporal study of genetic variation in the Danish pine marten (Martes martes) populations from the Jutland peninsula and from the island of Sealand was performed using 11 microsatellite markers. Samples obtained from 1892 to 2003 were subdivided into historical (prior to 1970) and recent...

Electrical Resistance Tomography for Visualization of Moving Objects Using a Spatiotemporal Total Variation Regularization Algorithm

Directory of Open Access Journals (Sweden)

Bo Chen

2018-05-01

Full Text Available Electrical resistance tomography (ERT has been considered as a data collection and image reconstruction method in many multi-phase flow application areas due to its advantages of high speed, low cost and being non-invasive. In order to improve the quality of the reconstructed images, the Total Variation algorithm attracts abundant attention due to its ability to solve large piecewise and discontinuous conductivity distributions. In industrial processing tomography (IPT, techniques such as ERT have been used to extract important flow measurement information. For a moving object inside a pipe, a velocity profile can be calculated from the cross correlation between signals generated from ERT sensors. Many previous studies have used two sets of 2D ERT measurements based on pixel-pixel cross correlation, which requires two ERT systems. In this paper, a method for carrying out flow velocity measurement using a single ERT system is proposed. A novel spatiotemporal total variation regularization approach is utilised to exploit sparsity both in space and time in 4D, and a voxel-voxel cross correlation method is adopted for measurement of flow profile. Result shows that the velocity profile can be calculated with a single ERT system and that the volume fraction and movement can be monitored using the proposed method. Both semi-dynamic experimental and static simulation studies verify the suitability of the proposed method. For in plane velocity profile, a 3D image based on temporal 2D images produces velocity profile with accuracy of less than 1% error and a 4D image for 3D velocity profiling shows an error of 4%.

Spatiotemporal mapping of ground water pollution in a Greek lignite basin, using geostatistics

Energy Technology Data Exchange (ETDEWEB)

Modis, K. [National Technical Univ. of Athens, Athens (Greece)

2010-07-01

An issue of significant interest in the mining industry in Greece is the occurrence of chemical pollutants in ground water. Ammonium, nitrites and nitrates concentrations have been monitored through an extensive sampling network in the Ptolemais lignite opencast mining area in Greece. Due to intensive mining efforts in the area, the surface topology is continuously altered, affecting the life span of the water boreholes and resulting in messy spatiotemporal distribution of data. This paper discussed the spatiotemporal mapping of ground water pollution in the Ptolemais lignite basin, using geostatistics. More specifically, the spatiotemporal distribution of ground water contamination was examined by the application of the bayesian maximum entropy theory which allows merging spatial and temporal estimations in a single model. The paper provided a description of the site and discussed the materials and methods, including samples and statistics; variography; and spatiotemporal mapping. It was concluded that in the case of the Ptolemais mining area, results revealed an underlying average yearly variation pattern of pollutant concentrations. Inspection of the produced spatiotemporal maps demonstrated a continuous increase in the risk of ammonium contamination, while risk for the other two pollutants appeared in hot spots. 18 refs., 1 tab., 7 figs.

Spatiotemporal mapping of ground water pollution in a Greek lignite basin, using geostatistics

International Nuclear Information System (INIS)

Modis, K.

2010-01-01

An issue of significant interest in the mining industry in Greece is the occurrence of chemical pollutants in ground water. Ammonium, nitrites and nitrates concentrations have been monitored through an extensive sampling network in the Ptolemais lignite opencast mining area in Greece. Due to intensive mining efforts in the area, the surface topology is continuously altered, affecting the life span of the water boreholes and resulting in messy spatiotemporal distribution of data. This paper discussed the spatiotemporal mapping of ground water pollution in the Ptolemais lignite basin, using geostatistics. More specifically, the spatiotemporal distribution of ground water contamination was examined by the application of the bayesian maximum entropy theory which allows merging spatial and temporal estimations in a single model. The paper provided a description of the site and discussed the materials and methods, including samples and statistics; variography; and spatiotemporal mapping. It was concluded that in the case of the Ptolemais mining area, results revealed an underlying average yearly variation pattern of pollutant concentrations. Inspection of the produced spatiotemporal maps demonstrated a continuous increase in the risk of ammonium contamination, while risk for the other two pollutants appeared in hot spots. 18 refs., 1 tab., 7 figs.

Spatiotemporal Object History Affects the Selection of Task-Relevant Properties

Science.gov (United States)

Schreij, Daniel; Olivers, Christian N. L.

2013-01-01

For stable perception, we maintain mental representations of objects across space and time. What information is linked to such a representation? In this study, we extended our work showing that the spatiotemporal history of an object affects the way the object is attended the next time it is encountered. Observers conducted a visual search for a…

Characterizing spatiotemporal variations of chromophoric dissolved organic matter in headwater catchment of a key drinking water source in China.

Science.gov (United States)

Chen, Yihan; Yu, Kaifeng; Zhou, Yongqiang; Ren, Longfei; Kirumba, George; Zhang, Bo; He, Yiliang

2017-12-01

Natural surface drinking water sources with the increasing chromophoric dissolved organic matter (CDOM) have profound influences on the aquatic environment and drinking water safety. Here, this study investigated the spatiotemporal variations of CDOM in Fengshuba Reservoir and its catchments in China. Twenty-four surface water samples, 45 water samples (including surface water, middle water, and bottom water), and 15 pore water samples were collected from rivers, reservoir, and sediment of the reservoir, respectively. Then, three fluorescent components, namely two humic-like components (C1 and C2) and a tryptophan-like component (C3), were identified from the excitation-emission matrix coupled with parallel factor analysis (EEM-PARAFAC) for all samples. For spatial distributions, the levels of CDOM and two humic-like components in the reservoir were significantly lower than those in the upstream rivers (p CDOM and humic-like matters from the surrounding catchment. For temporal variations, the mean levels of CDOM and three fluorescent components did not significantly change in rivers, suggesting that perennial anthropic activity maybe an important factor impacting the concentration and composition of river CDOM but not the precipitation and runoff. However, these mean values of CDOM for the bulk waters of the reservoir changed markedly along with seasonal variations, indicating that the hydrological processes in the reservoir could control the quality and quantity of CDOM. The different correlations between the fluorescent components and primary water parameters in the river, reservoir, and pore water samples further suggest that the reservoir is an important factor regulating the migration and transformation of FDOM along with the variations of different environmental gradients.

Modelling spatio-temporal variability of Mytilus edulis (L.) growth by forcing a dynamic energy budget model with satellite-derived environmental data

Science.gov (United States)

Thomas, Yoann; Mazurié, Joseph; Alunno-Bruscia, Marianne; Bacher, Cédric; Bouget, Jean-François; Gohin, Francis; Pouvreau, Stéphane; Struski, Caroline

2011-11-01

In order to assess the potential of various marine ecosystems for shellfish aquaculture and to evaluate their carrying capacities, there is a need to clarify the response of exploited species to environmental variations using robust ecophysiological models and available environmental data. For a large range of applications and comparison purposes, a non-specific approach based on 'generic' individual growth models offers many advantages. In this context, we simulated the response of blue mussel ( Mytilus edulis L.) to the spatio-temporal fluctuations of the environment in Mont Saint-Michel Bay (North Brittany) by forcing a generic growth model based on Dynamic Energy Budgets with satellite-derived environmental data (i.e. temperature and food). After a calibration step based on data from mussel growth surveys, the model was applied over nine years on a large area covering the entire bay. These simulations provide an evaluation of the spatio-temporal variability in mussel growth and also show the ability of the DEB model to integrate satellite-derived data and to predict spatial and temporal growth variability of mussels. Observed seasonal, inter-annual and spatial growth variations are well simulated. The large-scale application highlights the strong link between food and mussel growth. The methodology described in this study may be considered as a suitable approach to account for environmental effects (food and temperature variations) on physiological responses (growth and reproduction) of filter feeders in varying environments. Such physiological responses may then be useful for evaluating the suitability of coastal ecosystems for shellfish aquaculture.

Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors

Science.gov (United States)

Schöll, Eckehard

2005-08-01

Nonlinear transport phenomena are an increasingly important aspect of modern semiconductor research. This volume deals with complex nonlinear dynamics, pattern formation, and chaotic behavior in such systems. It bridges the gap between two well-established fields: the theory of dynamic systems and nonlinear charge transport in semiconductors. This unified approach helps reveal important electronic transport instabilities. The initial chapters lay a general framework for the theoretical description of nonlinear self-organized spatio-temporal patterns, such as current filaments, field domains, fronts, and analysis of their stability. Later chapters consider important model systems in detail: impact ionization induced impurity breakdown, Hall instabilities, superlattices, and low-dimensional structures. State-of-the-art results include chaos control, spatio-temporal chaos, multistability, pattern selection, activator-inhibitor kinetics, and global coupling, linking fundamental issues to electronic device applications. This book will be of great value to semiconductor physicists and nonlinear scientists alike.

Behavioral adjustments of African herbivores to predation risk by lions: spatiotemporal variations influence habitat use.

Science.gov (United States)

Valeix, M; Loveridge, A J; Chamaillé-Jammes, S; Davidson, Z; Murindagomo, F; Fritz, H; Macdonald, D W

2009-01-01

Predators may influence their prey populations not only through direct lethal effects, but also through indirect behavioral changes. Here, we combined spatiotemporal fine-scale data from GPS radio collars on lions with habitat use information on 11 African herbivores in Hwange National Park (Zimbabwe) to test whether the risk of predation by lions influenced the distribution of herbivores in the landscape. Effects of long-term risk of predation (likelihood of lion presence calculated over four months) and short-term risk of predation (actual presence of lions in the vicinity in the preceding 24 hours) were contrasted. The long-term risk of predation by lions appeared to influence the distributions of all browsers across the landscape, but not of grazers. This result strongly suggests that browsers and grazers, which face different ecological constraints, are influenced at different spatial and temporal scales in the variation of the risk of predation by lions. The results also show that all herbivores tend to use more open habitats preferentially when lions are in their vicinity, probably an effective anti-predator behavior against such an ambush predator. Behaviorally induced effects of lions may therefore contribute significantly to structuring African herbivore communities, and hence possibly their effects on savanna ecosystems.

Differentiating the Spatiotemporal Distribution of Natural and Anthropogenic Processes on River Water-Quality Variation Using a Self-Organizing Map With Factor Analysis.

Science.gov (United States)

Wang, Yeuh-Bin; Liu, Chen-Wuing; Lee, Jin-Jing

2015-08-01

To elucidate the historical improvement and advanced measure of river water quality in the Taipei metropolitan area, this study applied the self-organizing map (SOM) technique with factor analysis (FA) to differentiate the spatiotemporal distribution of natural and anthropogenic processes on river water-quality variation spanning two decades. The SOM clustered river water quality into five groups: very low pollution, low pollution, moderate pollution, high pollution, and very high pollution. FA was then used to extract four latent factors that dominated water quality from 1991 to 2011 including three anthropogenic process factors (organic, industrial, and copper pollution) and one natural process factor [suspended solids (SS) pollution]. The SOM revealed that the water quality improved substantially over time. However, the downstream river water quality was still classified as high pollution because of an increase in anthropogenic activity. FA showed the spatiotemporal pattern of each factor score decreasing over time, but the organic pollution factor downstream of the Tamsui River, as well as the SS factor scores in the upstream major tributary (the Dahan Stream), remained within the high pollution level. Therefore, we suggest that public sewage-treatment plants should be upgraded from their current secondary biological processing to advanced treatment processing. The conservation of water and soil must also be reinforced to decrease the SS loading of the Dahan Stream from natural erosion processes in the future.

Quantification of annual wildfire risk; A spatio-temporal point process approach.

Directory of Open Access Journals (Sweden)

Paula Pereira

2013-10-01

Full Text Available Policy responses for local and global firemanagement depend heavily on the proper understanding of the fire extent as well as its spatio-temporal variation across any given study area. Annual fire risk maps are important tools for such policy responses, supporting strategic decisions such as location-allocation of equipment and human resources. Here, we define risk of fire in the narrow sense as the probability of its occurrence without addressing the loss component. In this paper, we study the spatio-temporal point patterns of wildfires and model them by a log Gaussian Cox processes. Themean of predictive distribution of randomintensity function is used in the narrow sense, as the annual fire risk map for next year.

Bayesian spatio-temporal analysis and geospatial risk factors of human monocytic ehrlichiosis.

Directory of Open Access Journals (Sweden)

Ram K Raghavan

Full Text Available Variations in spatio-temporal patterns of Human Monocytic Ehrlichiosis (HME infection in the state of Kansas, USA were examined and the relationship between HME relative risk and various environmental, climatic and socio-economic variables were evaluated. HME data used in the study was reported to the Kansas Department of Health and Environment between years 2005-2012, and geospatial variables representing the physical environment [National Land cover/Land use, NASA Moderate Resolution Imaging Spectroradiometer (MODIS], climate [NASA MODIS, Prediction of Worldwide Renewable Energy (POWER], and socio-economic conditions (US Census Bureau were derived from publicly available sources. Following univariate screening of candidate variables using logistic regressions, two Bayesian hierarchical models were fit; a partial spatio-temporal model with random effects and a spatio-temporal interaction term, and a second model that included additional covariate terms. The best fitting model revealed that spatio-temporal autocorrelation in Kansas increased steadily from 2005-2012, and identified poverty status, relative humidity, and an interactive factor, 'diurnal temperature range x mixed forest area' as significant county-level risk factors for HME. The identification of significant spatio-temporal pattern and new risk factors are important in the context of HME prevention, for future research in the areas of ecology and evolution of HME, and as well as climate change impacts on tick-borne diseases.

Estimating mobility using sparse data: Application to human genetic variation.

Science.gov (United States)

Loog, Liisa; Mirazón Lahr, Marta; Kovacevic, Mirna; Manica, Andrea; Eriksson, Anders; Thomas, Mark G

2017-11-14

Mobility is one of the most important processes shaping spatiotemporal patterns of variation in genetic, morphological, and cultural traits. However, current approaches for inferring past migration episodes in the fields of archaeology and population genetics lack either temporal resolution or formal quantification of the underlying mobility, are poorly suited to spatially and temporally sparsely sampled data, and permit only limited systematic comparison between different time periods or geographic regions. Here we present an estimator of past mobility that addresses these issues by explicitly linking trait differentiation in space and time. We demonstrate the efficacy of this estimator using spatiotemporally explicit simulations and apply it to a large set of ancient genomic data from Western Eurasia. We identify a sequence of changes in human mobility from the Late Pleistocene to the Iron Age. We find that mobility among European Holocene farmers was significantly higher than among European hunter-gatherers both pre- and postdating the Last Glacial Maximum. We also infer that this Holocene rise in mobility occurred in at least three distinct stages: the first centering on the well-known population expansion at the beginning of the Neolithic, and the second and third centering on the beginning of the Bronze Age and the late Iron Age, respectively. These findings suggest a strong link between technological change and human mobility in Holocene Western Eurasia and demonstrate the utility of this framework for exploring changes in mobility through space and time. Copyright © 2017 the Author(s). Published by PNAS.

Spatiotemporal Data Organization and Application Research

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Tan, C.; Yan, S.

2017-09-01

Organization and management of spatiotemporal data is a key support technology for intelligence in all fields of the smart city. The construction of a smart city cannot be realized without spatiotemporal data. Oriented to support intelligent applications this paper proposes an organizational model for spatiotemporal data, and details the construction of a spatiotemporal big data calculation, analysis, and service framework for highly efficient management and intelligent application of spatiotemporal data for the entire data life cycle.

Extensive spatio-temporal assessment of flood events by application of pair-copulas

Directory of Open Access Journals (Sweden)

M. Schulte

2015-06-01

Full Text Available Although the consequences of floods are strongly related to their peak discharges, a statistical classification of flood events that only depends on these peaks may not be sufficient for flood risk assessments. In many cases, the flood risk depends on a number of event characteristics. In case of an extreme flood, the whole river basin may be affected instead of a single watershed, and there will be superposition of peak discharges from adjoining catchments. These peaks differ in size and timing according to the spatial distribution of precipitation and watershed-specific processes of flood formation. Thus, the spatial characteristics of flood events should be considered as stochastic processes. Hence, there is a need for a multivariate statistical approach that represents the spatial interdependencies between floods from different watersheds and their coincidences. This paper addresses the question how these spatial interdependencies can be quantified. Each flood event is not only assessed with regard to its local conditions but also according to its spatio-temporal pattern within the river basin. In this paper we characterise the coincidence of floods by trivariate Joe-copula and pair-copulas. Their ability to link the marginal distributions of the variates while maintaining their dependence structure characterizes them as an adequate method. The results indicate that the trivariate copula model is able to represent the multivariate probabilities of the occurrence of simultaneous flood peaks well. It is suggested that the approach of this paper is very useful for the risk-based design of retention basins as it accounts for the complex spatio-temporal interactions of floods.

Spatio-temporal variations of PM2.5 emission in China from 2005 to 2014.

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Jin, Qiang; Fang, Xinyue; Wen, Bo; Shan, Aidang

2017-09-01

With the rapid development of economy, air pollution has become increasingly serious nowadays in China, especially for the PM2.5. In this paper, the Spatio-temporal variations of PM2.5 emission over the past decade, from 2005 to 2014, were researched by cartograms. Meanwhile, a complex network technology was adopted to study the spatial auto-correlation of PM2.5 emission. The results showed that every province in China suffered a disparate increment in PM2.5 emission during the past ten years and also indicated that provinces in the same region had a huge influence on each other. There were three sectors including the thermal power, biomass burning and building materials that constituted the major sources of PM2.5 emission and they had different changing trends. There existed a dramatic difference in the east and west of China considering that the amount of PM2.5 was closely related to gross domestic product (GDP) and population. With higher GDP and population, eastern provinces emitted the most amount of PM2.5. Normalization results proposed that most of the provinces were PM2.5 exporting provinces in the southeast of China while most in the northwest were importing provinces. This study can help the policy-makers understand the distribution characteristics of PM2.5 emission and propose the effective strategy to mitigate the pollution of haze. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatiotemporal variation in the reproductive ecology of two parapatric subspecies of Oenothera cespitosa (Onagraceae).

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Artz, Derek R; Villagra, Cristian A; Raguso, Robert A

2010-09-01

• Flowering plants that rely on pollinators for most of their reproduction may experience unpredictable and inconsistent availability of effective pollinators throughout their reproductive lifetime. We investigated the reproductive ecology of two subspecies of the tufted evening primrose, Oenothera cespitosa, which occupy geographically and edaphically distinct habitats in western North America: O. cespitosa subsp. navajoensis inhabits sandstone soils on open sites or rocky slopes in the Colorado Plateau and O. cespitosa subsp. cespitosa grows in clay soils on talus slopes and exposed rocky ridges in the western Great Plains and northern Rocky Mountains of the United States. • Pollen augmentation and selfing experiments, floral visitor observations, and single-visit effectiveness experiments were conducted over 4 years to examine the breeding system and spatiotemporal variation in pollinator behavior, assemblage, and abundance at different populations for each subspecies. • Both subspecies of O. cespitosa were self-incompatible and pollen-limited, suggesting that the relative abundance, effectiveness, and movement patterns of different insects as pollinators influenced the quality and quantity of seed production in these plants. Medium-sized vespertine hawkmoths (Hyles lineata, Sphinx vashti) were effective pollinators when present, as were large matinal bees (Anthophora affabilis, A. dammersi, Xylocopa tabaniformis androleuca), whereas small oligolectic Lasioglossum bees primarily functioned as pollen thieves in the evening and morning. • These findings highlight the importance of variability of pollinator composition and abundance in the evolution of plant breeding systems and reproductive success at varying spatial and temporal scales.

Analysis of spastic gait in cervical myelopathy: Linking compression ratio to spatiotemporal and pedobarographic parameters.

Science.gov (United States)

Nagai, Taro; Takahashi, Yasuhito; Endo, Kenji; Ikegami, Ryo; Ueno, Ryuichi; Yamamoto, Kengo

2018-01-01

Gait dysfunction associated with spasticity and hyperreflexia is a primary symptom in patients with compression of cervical spinal cord. The objective of this study was to link maximum compression ratio (CR) to spatiotemporal/pedobarographic parameters. Quantitative gait analysis was performed by using a pedobarograph in 75 elderly males with a wide range of cervical compression severity. CR values were characterized on T1-weighted magnetic resonance imaging (MRI). Statistical significances in gait analysis parameters (speed, cadence, stride length, step with, and toe-out angle) were evaluated among different CR groups by the non-parametric Kruskal-Wallis test followed by the Mann-Whitney U test using Bonferroni correction. The Spearman test was performed to verify correlations between CR and gait parameters. The Kruskal-Wallis test revealed significant decline in gait speed and stride length and significant increase in toe-out angle with progression of cervical compression myelopathy. The post-hoc Mann-Whitney U test showed significant differences in these parameters between the control group (0.45test revealed that CR was significantly correlated with speed, cadence, stride length, and toe-out angle. Gait speed, stride length, and toe-out angle can serve as useful indexes for evaluating progressive gait abnormality in cervical myelopathy. Our findings suggest that CR≤0.25 is associated with significantly poorer gait performance. Nevertheless, future prospective studies are needed to determine a potential benefit from decompressive surgery in such severe compression patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Multiple Brain Markers are Linked to Age-Related Variation in Cognition

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Hedden, Trey; Schultz, Aaron P.; Rieckmann, Anna; Mormino, Elizabeth C.; Johnson, Keith A.; Sperling, Reisa A.; Buckner, Randy L.

2016-01-01

Age-related alterations in brain structure and function have been challenging to link to cognition due to potential overlapping influences of multiple neurobiological cascades. We examined multiple brain markers associated with age-related variation in cognition. Clinically normal older humans aged 65–90 from the Harvard Aging Brain Study (N = 186) were characterized on a priori magnetic resonance imaging markers of gray matter thickness and volume, white matter hyperintensities, fractional anisotropy (FA), resting-state functional connectivity, positron emission tomography markers of glucose metabolism and amyloid burden, and cognitive factors of processing speed, executive function, and episodic memory. Partial correlation and mediation analyses estimated age-related variance in cognition shared with individual brain markers and unique to each marker. The largest relationships linked FA and striatum volume to processing speed and executive function, and hippocampal volume to episodic memory. Of the age-related variance in cognition, 70–80% was accounted for by combining all brain markers (but only ∼20% of total variance). Age had significant indirect effects on cognition via brain markers, with significant markers varying across cognitive domains. These results suggest that most age-related variation in cognition is shared among multiple brain markers, but potential specificity between some brain markers and cognitive domains motivates additional study of age-related markers of neural health. PMID:25316342

Effects of Heterogeneity and Uncertainties in Sources and Initial and Boundary Conditions on Spatiotemporal Variations of Groundwater Levels

Science.gov (United States)

Zhang, Y. K.; Liang, X.

2014-12-01

Effects of aquifer heterogeneity and uncertainties in source/sink, and initial and boundary conditions in a groundwater flow model on the spatiotemporal variations of groundwater level, h(x,t), were investigated. Analytical solutions for the variance and covariance of h(x, t) in an unconfined aquifer described by a linearized Boussinesq equation with a white noise source/sink and a random transmissivity field were derived. It was found that in a typical aquifer the error in h(x,t) in early time is mainly caused by the random initial condition and the error reduces as time goes to reach a constant error in later time. The duration during which the effect of the random initial condition is significant may last a few hundred days in most aquifers. The constant error in groundwater in later time is due to the combined effects of the uncertain source/sink and flux boundary: the closer to the flux boundary, the larger the error. The error caused by the uncertain head boundary is limited in a narrow zone near the boundary but it remains more or less constant over time. The effect of the heterogeneity is to increase the variation of groundwater level and the maximum effect occurs close to the constant head boundary because of the linear mean hydraulic gradient. The correlation of groundwater level decreases with temporal interval and spatial distance. In addition, the heterogeneity enhances the correlation of groundwater level, especially at larger time intervals and small spatial distances.

Propagation and spatiotemporal coupling characteristics of ultra-short Gaussian vortex pulse

Science.gov (United States)

Nie, Jianye; Liu, Guodong; Zhang, Rongzhu

2018-05-01

Based on Collins diffraction integral formula, the propagation equation of ultra-short Gaussian vortex pulse beam has been derived. Using the equation, the intensity distribution variations of vortex pulse in the propagation process are calculated. Specially, the spatiotemporal coupling characteristics of ultra-short vortex beams are discussed in detail. The results show that some key parameters, such as transverse distance, transmission distance, pulse width and topological charge number will influence the spatiotemporal coupling characteristics significantly. With the increasing of transverse distance, the waveforms of the pulses distort obviously. And when transmission distance is far than 50 mm, the distribution curve of transverse intensity gradually changes into a Gaussian type. In addition, initial pulse width will affect the distribution of light field, however, when initial pulse width is larger than 3 fs, the spatiotemporal coupling effect will be insignificant. Topological charge number does not affect the time delay characteristics, since with the increasing of topological charge number, the waveform of the pulse distorts gradually but the time delay does not occur.

Spatiotemporal variations of hydrogeochemistry and its controlling factors in the Gandaki River Basin, Central Himalaya Nepal.

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Pant, Ramesh Raj; Zhang, Fan; Rehman, Faizan Ur; Wang, Guanxing; Ye, Ming; Zeng, Chen; Tang, Handuo

2018-05-01

The characterization and assessment of water quality in the head water region of Himalaya is necessary, given the immense importance of this region in sustaining livelihoods of people and maintaining ecological balance. A total of 165 water samples were collected from 55 sites during pre-monsoon, monsoon and post-monsoon seasons in 2016 from the Gandaki River Basin of the Central Himalaya, Nepal. The pH, EC values and TDS concentrations were measured in-situ and the concentrations of major ions (Ca 2+ , Mg 2+ , K + , Na + , Cl - , SO 4 2- , NO 3 - ) and Si were analyzed in laboratory. Correlation matrices, paired t-test, cluster analysis, principal component analysis (PCA), the Piper, Gibbs, and Mixing plots, and saturation index were applied to the measurements for evaluating spatiotemporal variation of the major ions. The results reveal mildly alkaline pH values and the following pattern of average ionic dominance: Ca 2+ >Mg 2+ >Na + >K + for cations and HCO 3 - >SO 4 2 - >Cl - >NO 3 - for anions. The results of PCA, Gibbs plot and the ionic relationships displayed the predominance of geogenic weathering processes in areas with carbonate dominant lithology. This conclusion is supported by geochemically different water facies identified in the Piper plot as Ca-HCO 3 (83.03%), mixed Ca-Mg-Cl (12.73.0%) and Ca-Cl (4.24%). Pronounced spatiotemporal heterogeneity demonstrates the influence of climatic, geogenic and anthropogenic conditions. For instance, the Ca 2+ -SO 4 2- , Mg 2+ -SO 4 2- and Na + -Cl - pairs exhibit strong positive correlation with each other in the upstream region, whereas relatively weak correlation in the downstream region, likely indicating the influence of evapo-crystallization processes in the upstream region. Analyses of the suitability of the water supply for drinking and irrigation reveal that the river has mostly retained its natural water quality but poses safety concern at a few locations. Knowledge obtained through this study can

The spatiotemporal variation analysis of virtual water for agriculture and livestock husbandry: A study for Jilin Province in China.

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Ma, Xiaolei; Ma, Yanji

2017-05-15

With the rapid development of economic, water crisis is becoming more and more serious and would be an important obstacle to the sustainable development of society. Virtual water theory and its applications in agriculture can provide important strategies for realizing the reasonable utilization and sustainable development of water resources. Using the Penman-Monteith model and Theil index combining the CROPWAT software, this work takes Jilin Province as study area quantifying the virtual water content of agriculture and livestock husbandry and giving a comprehensive evaluation of their spatiotemporal structure evolution. This study aims to help make clear the water consumption of agriculture and livestock husbandry, and offer advice on rational water utilization and agricultural structure adjustment. The results show that the total virtual water (TVW) proportion of agriculture presents a gradual growth trend while that of livestock husbandry reduces during the study period. In space, central Jilin shows the highest virtual water content of agriculture as well as livestock husbandry, the TVW in central Jilin is about 35.8billionm 3 . The TVW of maize is highest among six studied crops, and the cattle shows the highest TVW in the four kinds of animals. The distribution of TVW calculated by us and the distribution of actual water resources have remarkable difference, which leads to the increase of water consumption and cost of agricultural production. Finally, we discuss the driving force of the spatiotemporal variation of the TVW for agriculture and livestock husbandry, and also give some advises for the planting structural adjustment. This work is helpful for the sustainable development of agricultural and livestock husbandry and realizing efficient utilization of water resources. Copyright © 2017 Elsevier B.V. All rights reserved.

Genetic Variation Linked to Lung Cancer Survival in White Smokers | Center for Cancer Research

Science.gov (United States)

CCR investigators have discovered evidence that links lung cancer survival with genetic variations (called single nucleotide polymorphisms) in the MBL2 gene, a key player in innate immunity. The variations in the gene, which codes for a protein called the mannose-binding lectin, occur in its promoter region, where the RNA polymerase molecule binds to start transcription, and in the first exon that is responsible for the correct structure of MBL. The findings appear in the September 19, 2007, issue of the Journal of the National Cancer Institute.

A Closer Look on Spatiotemporal Variations of Dissolved Oxygen in Waste Stabilization Ponds Using Mixed Models

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Long Ho

2018-02-01

Full Text Available Dissolved oxygen is an essential controlling factor in the performance of facultative and maturation ponds since both take many advantages of algal photosynthetic oxygenation. The rate of this photosynthesis strongly depends on the time during the day and the location in a pond system, whose roles have been overlooked in previous guidelines of pond operation and maintenance (O&M. To elucidate these influences, a linear mixed effect model (LMM was built on the data collected from three intensive sampling campaigns in a waste stabilization pond in Cuenca, Ecuador. Within two parallel lines of facultative and maturation ponds, nine locations were sampled at two depths in each pond. In general, the output of the mixed model indicated high spatial autocorrelations of data and wide spatiotemporal variations of the oxygen level among and within the ponds. Particularly, different ponds showed different patterns of oxygen dynamics, which were associated with many factors including flow behavior, sludge accumulation, algal distribution, influent fluctuation, and pond function. Moreover, a substantial temporal change in the oxygen level between day and night, from zero to above 20 mg O2·L−1, was observed. Algal photosynthetic activity appeared to be the main reason for these variations in the model, as it was facilitated by intensive solar radiation at high altitude. Since these diurnal and spatial patterns can supply a large amount of useful information on pond performance, insightful recommendations on dissolved oxygen (DO monitoring and regulations were delivered. More importantly, as a mixed model showed high predictive performance, i.e., high goodness-of-fit (R2 of 0.94, low values of mean absolute error, we recommended this advanced statistical technique as an effective tool for dealing with high autocorrelation of data in pond systems.

Spatio-temporal patterns of Cu contamination in mosses using geostatistical estimation

International Nuclear Information System (INIS)

Martins, Anabela; Figueira, Rui; Sousa, António Jorge; Sérgio, Cecília

2012-01-01

Several recent studies have reported temporal trends in metal contamination in mosses, but such assessments did not evaluate uncertainty in temporal changes, therefore providing weak statistical support for time comparisons. Furthermore, levels of contaminants in the environment change in both space and time, requiring space-time modelling methods for map estimation. We propose an indicator of spatial and temporal variation based on space-time estimation by indicator kriging, where uncertainty at each location is estimated from the local distribution function, thereby calculating variability intervals for comparison between several biomonitoring dates. This approach was exemplified using copper concentrations in mosses from four Portuguese surveys (1992, 1997, 2002 and 2006). Using this approach, we identified a general decrease in copper contamination, but spatial patterns were not uniform, and from the uncertainty intervals, changes could not be considered significant in the majority of the study area. - Highlights: ► We estimated copper contamination in mosses by spatio-temporal kriging between 1992 and 2006. ► We determined local distribution functions to define variation intervals at each location. ► Significance of temporal changes is assessed using an indicator based on uncertainty interval. ► There is general decrease in copper contamination, but spatial patterns are not uniform. - The contamination of copper in mosses was estimated by spatio-temporal kriging, with determination of uncertainty classes in the temporal variation.

Spatio-temporal problems of locomotion control

International Nuclear Information System (INIS)

Smolyaninov, Vladimir V

2000-01-01

The problem of the spatio-temporal construction of legged movements involves structural freedoms due to the multi-link structure of the extremities, kinematic freedoms of the stepping cycle, and interextremity coordination freedoms, whose purposive organization is established by means of appropriate synergies, i.e. additional functional links the brain's control system forms. The main focus of attention in this work is on the kinematic and coordination synergies of the legged movements of humans and animals. The comparative historical analysis of experimental data and modelling metaphors concentrates on obtaining a unified description, whereas the ultimate mathematical metaphor reduces to space-time geometry, with base step synergies as its invariants. Thus, the concept of a synergetic organization for biomechanical movement freedoms is transformed to the geochronometry concept, actually a modification of Minkowskian geometry. To determine the spectrum of possible geochronometries, the consequences of a generalized 'postulate of a constant speed of light' are studied and different models of wave chronometers compared. (reviews of topical problems)

Sources of variation in an enzyme-linked immunoassay of bluetongue virus in Culicoides variipennis (Diptera: Ceratopogonidae).

Science.gov (United States)

Tabachnick, W J; Mecham, J O

1991-03-01

An enzyme-linked immunoassay for detecting bluetongue virus in infected Culicoides variipennis was evaluated using a nested analysis of variance to determine sources of experimental error in the procedure. The major source of variation was differences among individual insects (84% of the total variance). Storing insects at -70 degrees C for two months contributed to experimental variation in the ELISA reading (14% of the total variance) and should be avoided. Replicate assays of individual insects were shown to be unnecessary, since variation among replicate wells and plates was minor (2% of the total variance).

Spatio-temporal variation in density of microphytoplankton genera in ...

African Journals Online (AJOL)

This seasonal shift may reflect how these species respond differently to environmental change, which could have implications for primary production at spatial and temporal scales. Keywords: chlorophyll a, cyanobacteria, diatoms, dinoflagellates, interannual variation, physico-chemical, seasonal variation. African Journal of ...

Spatiotemporal Modeling of Community Risk

Science.gov (United States)

2016-03-01

Ertugay, and Sebnem Duzgun, “Exploratory and Inferential Methods for Spatio-Temporal Analysis of Residential Fire Clustering in Urban Areas,” Fire ...response in communities.”26 In “Exploratory and Inferential Methods for Spatio-temporal Analysis of Residential Fire Clustering in Urban Areas,” Ceyhan...of fire resources spread across the community. Spatiotemporal modeling shows that actualized risk is dynamic and relatively patterned. Though

Spatiotemporal matrix image formation for programmable ultrasound scanners

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Berthon, Beatrice; Morichau-Beauchant, Pierre; Porée, Jonathan; Garofalakis, Anikitos; Tavitian, Bertrand; Tanter, Mickael; Provost, Jean

2018-02-01

As programmable ultrasound scanners become more common in research laboratories, it is increasingly important to develop robust software-based image formation algorithms that can be obtained in a straightforward fashion for different types of probes and sequences with a small risk of error during implementation. In this work, we argue that as the computational power keeps increasing, it is becoming practical to directly implement an approximation to the matrix operator linking reflector point targets to the corresponding radiofrequency signals via thoroughly validated and widely available simulations software. Once such a spatiotemporal forward-problem matrix is constructed, standard and thus highly optimized inversion procedures can be leveraged to achieve very high quality images in real time. Specifically, we show that spatiotemporal matrix image formation produces images of similar or enhanced quality when compared against standard delay-and-sum approaches in phantoms and in vivo, and show that this approach can be used to form images even when using non-conventional probe designs for which adapted image formation algorithms are not readily available.

Spatiotemporal variations in CO2 flux in a fringing reef simulated using a novel carbonate system dynamics model

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Watanabe, A.; Yamamoto, T.; Nadaoka, K.; Maeda, Y.; Miyajima, T.; Tanaka, Y.; Blanco, A. C.

2013-03-01

A carbonate system dynamics (CSD) model was developed in a fringing reef on the east coast of Ishigaki Island, southwest Japan, by incorporating organic and inorganic carbon fluxes (photosynthesis and calcification), air-sea gas exchanges, and benthic cover of coral and seagrass into a three-dimensional hydrodynamic model. The CSD model could reproduce temporal variations in dissolved inorganic carbon (DIC) and total alkalinity in coral zones, but not in seagrass meadows. The poor reproduction in seagrass meadows can be attributed to significant contributions of submarine groundwater discharge as well as misclassification of remotely sensed megabenthos in this area. In comparison with offshore areas, the reef acted as a CO2 sink during the observation period when it was averaged over 24 h. The CSD model also indicated large spatiotemporal differences in the carbon dioxide (CO2) sink/source, possibly related to hydrodynamic features such as effective offshore seawater exchange and neap/spring tidal variation. This suggests that the data obtained from a single point observation may lead to misinterpretation of the overall trend and thus should be carefully considered. The model analysis also showed that the advective flux of DIC from neighboring grids is several times greater than local biological flux of DIC and is three orders of magnitude greater than the air-sea gas flux at the coral zone. Sensitivity tests in which coral or seagrass covers were altered revealed that the CO2 sink potential was much more sensitive to changes in coral cover than seagrass cover.

Spatiotemporal Scaling Effect on Rainfall Network Design Using Entropy

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Chiang Wei

2014-08-01

Full Text Available Because of high variation in mountainous areas, rainfall data at different spatiotemporal scales may yield potential uncertainty for network design. However, few studies focus on the scaling effect on both the spatial and the temporal scale. By calculating the maximum joint entropy of hourly typhoon events, monthly, six dry and wet months and annual rainfall between 1992 and 2012 for 1-, 3-, and 5-km grids, the relocated candidate rain gauges in the National Taiwan University Experimental Forest of Central Taiwan are prioritized. The results show: (1 the network exhibits different locations for first prioritized candidate rain gauges for different spatiotemporal scales; (2 the effect of spatial scales is insignificant compared to temporal scales; and (3 a smaller number and a lower percentage of required stations (PRS reach stable joint entropy for a long duration at finer spatial scale. Prioritized candidate rain gauges provide key reference points for adjusting the network to capture more accurate information and minimize redundancy.

Spatio-temporal Variations of Abundance, Biomass, and ...

African Journals Online (AJOL)

The spatio-seasonal variations of Pseudodiaptomus hessei abundance, biomass and reproductive parameters were investigated in the Grand-Lahou lagoon at five stations during the dry and wet (or rainy) seasons from September 2005 to August 2006. In all sampling stations, abundance and biomass of P. hessei in the dry ...

Spatiotemporal chaos from bursting dynamics

International Nuclear Information System (INIS)

Berenstein, Igal; De Decker, Yannick

2015-01-01

In this paper, we study the emergence of spatiotemporal chaos from mixed-mode oscillations, by using an extended Oregonator model. We show that bursting dynamics consisting of fast/slow mixed mode oscillations along a single attractor can lead to spatiotemporal chaotic dynamics, although the spatially homogeneous solution is itself non-chaotic. This behavior is observed far from the Hopf bifurcation and takes the form of a spatiotemporal intermittency where the system locally alternates between the fast and the slow phases of the mixed mode oscillations. We expect this form of spatiotemporal chaos to be generic for models in which one or several slow variables are coupled to activator-inhibitor type of oscillators

Elimination of spiral waves and spatiotemporal chaos by the pulse with a specific spatiotemporal configuration

International Nuclear Information System (INIS)

Yuan Guoyong; Yang Shiping; Wang Guangrui; Chen Shigang

2008-01-01

Spiral waves and spatiotemporal chaos are sometimes harmful and should be controlled. In this paper spiral waves and spatiotemporal chaos are successfully eliminated by the pulse with a very specific spatiotemporal configuration. The excited position D of spiral waves or spatiotemporal chaos is first recorded at an arbitrary time (t 0 ). When the system at the domain D enters a recovering state, the external pulse is injected into the domain. If the intensity and the working time of the pulse are appropriate, spiral waves and spatiotemporal chaos can finally be eliminated because counter-directional waves can be generated by the pulse. There are two advantages in the method. One is that the tip can be quickly eliminated together with the body of spiral wave, and the other is that the injected pulse may be weak and the duration can be very short so that the original system is nearly not affected, which is important for practical applications

Spatio-temporal variations in climate, primary productivity and efficiency of water and carbon use of the land cover types in Sudan and Ethiopia.

Science.gov (United States)

Khalifa, Muhammad; Elagib, Nadir Ahmed; Ribbe, Lars; Schneider, Karl

2018-05-15

The impact of climate variability on the Net Primary Productivity (NPP) of different land cover types and the reaction of NPP to drought conditions are still unclear, especially in Sub-Saharan Africa. This research utilizes public-domain data for the period 2000 through 2013 to analyze these aspects for several land cover types in Sudan and Ethiopia, as examples of data-scarce countries. Spatio-temporal variation in NPP, water use efficiency (WUE) and carbon use efficiency (CUE) for several land covers were correlated with variations in precipitation, temperature and drought at different time scales, i.e. 1, 3, 6 and 12months using Standardized Precipitation Evapotranspiration Index (SPEI) datasets. WUE and CUE were estimated as the ratios of NPP to actual evapotranspiration and NPP to Gross Primary Productivity (GPP), respectively. Results of this study revealed that NPP, WUE and CUE of the different land cover types in Ethiopia have higher magnitudes than their counterparts in Sudan. Moreover, they exhibit higher sensitivity to drought and variation in precipitation. Whereas savannah represents the most sensitive land cover to drought, croplands and permanent wetlands are the least sensitive ones. The inter-annual variation in NPP, WUE and CUE in Ethiopia is likely to be driven by a drought of time scale of three months. No statistically significant correlation was found for Sudan between the inter-annual variations in these indicators with drought at any of the time scales considered in the study. Our findings are useful from the view point of both food security for a growing population and mitigation to climate change as discussed in the present study. Copyright © 2017 Elsevier B.V. All rights reserved.

Investigating fine-scale spatio-temporal predator-prey patterns in dynamic marine ecosystems: a functional data analysis approach

NARCIS (Netherlands)

Embling, C.B.; Illian, J.; Armstrong, E.; van der Kooij, J.; Sharples, J.; Camphuysen, K.C.J.; Scott, B.E.

2012-01-01

1. Spatial management of marine ecosystems requires detailed knowledge of spatio-temporal mechanisms linking physical and biological processes. Tidal currents, the main driver of ecosystem dynamics in temperate coastal ecosystems, influence predator foraging ecology by affecting prey distribution

Tensor-based spatiotemporal saliency detection

Science.gov (United States)

Dou, Hao; Li, Bin; Deng, Qianqian; Zhang, LiRui; Pan, Zhihong; Tian, Jinwen

2018-03-01

This paper proposes an effective tensor-based spatiotemporal saliency computation model for saliency detection in videos. First, we construct the tensor representation of video frames. Then, the spatiotemporal saliency can be directly computed by the tensor distance between different tensors, which can preserve the complete temporal and spatial structure information of object in the spatiotemporal domain. Experimental results demonstrate that our method can achieve encouraging performance in comparison with the state-of-the-art methods.

Potential of electrical resistivity tomography and muon density imaging to study spatio-temporal variations in the sub-surface

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Lesparre, Nolwenn; Cabrera, Justo; Courbet, Christelle

2015-04-01

We explore the capacity of electrical resistivity tomography and muon density imaging to detect spatio-temporal variations of the medium surrounding a regional fault crossing the underground platform of Tournemire (Aveyron, France). The studied Cernon fault is sub-vertical and intersects perpendicularly the tunnel of Tournemire and extends to surface. The fault separates clay and limestones layers of the Dogger from limestones layers of the Lias. The Cernon fault presents a thickness of a ten of meters and drives water from an aquifer circulating at the top of the Dogger clay layer to the tunnel. An experiment combining electrical resistivity imaging and muon density imaging was setup taking advantage of the tunnel presence. A specific array of electrodes were set up, adapted for the characterization of the fault. Electrodes were placed along the tunnel as well as at the surface above the tunnel on both sides of the fault in order to acquire data in transmission across the massif to better cover the sounded medium. Electrical resistivity is particularly sensitive to water presence in the medium and thus carry information on the main water flow paths and on the pore space saturation. At the same time a muon sensor was placed in the tunnel under the fault region to detect muons coming from the sky after their crossing of the rock medium. Since the muon flux is attenuated as function of the quantity of matter crossed, muons flux measurements supply information on the medium average density along muons paths. The sensor presents 961 angles of view so measurements performed from one station allows a comparison of the muon flux temporal variations along the fault as well as in the medium surrounding the fault. As the water saturation of the porous medium fluctuates through time the medium density might indeed present sensible variations as shown by gravimetric studies. During the experiment important rainfalls occurred leading variations of the medium properties

Integrating movement ecology with biodiversity research - exploring new avenues to address spatiotemporal biodiversity dynamics.

Science.gov (United States)

Jeltsch, Florian; Bonte, Dries; Pe'er, Guy; Reineking, Björn; Leimgruber, Peter; Balkenhol, Niko; Schröder, Boris; Buchmann, Carsten M; Mueller, Thomas; Blaum, Niels; Zurell, Damaris; Böhning-Gaese, Katrin; Wiegand, Thorsten; Eccard, Jana A; Hofer, Heribert; Reeg, Jette; Eggers, Ute; Bauer, Silke

2013-01-01

Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of 'movement ecology'. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide 'mobile links' between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through 'equalizing' and 'stabilizing' mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.

Assessing vegetation response to climatic variations and human activities: spatiotemporal NDVI variations in the Hexi Corridor and surrounding areas from 2000 to 2010

Science.gov (United States)

Guan, Qingyu; Yang, Liqin; Guan, Wenqian; Wang, Feifei; Liu, Zeyu; Xu, Chuanqi

2018-03-01

Vegetation cover is a commonly used indicator for evaluating terrestrial environmental conditions, and for revealing environmental evolution and transitions. Spatiotemporal variations in the vegetation cover of the Hexi Corridor and surrounding areas from 2000 to 2010 were investigated using MODIS NDVI data, and the causes of vegetation cover changes were analyzed, considering both climatic variability and human activities. The vegetation cover of the study area increased during 2000-2010. The greenness of the vegetation showed a significant increase from the northwest to the southeast, which was similar to the spatial distribution of the annual precipitation. Variations in vegetation have a close relationship with those in precipitation within the Qilian Mountains region, but the NDVI is negatively correlated with precipitation in oasis areas. Increasing temperatures led to drought, inhibiting vegetation growth in summer; however, increasing temperatures may have also advanced and prolonged the growing periods in spring and autumn. The NDVI showed a slight degradation in March and July, primarily in the Qilian Mountains, and especially the Wushao Mountains. In March, due to low temperatures, the metabolism rate of vegetation was too slow to enable strong plant growth in high elevations of the Qilian Mountains. In July, increasing temperatures enhanced the intensity of transpiration and decreasing precipitation reduced the moisture available to plants, producing a slight degradation of vegetation in the Qilian Mountains. In May and August, the NDVI showed a significant improvement, primarily in the artificial oases and the Qilian Mountains. Abundant precipitation provided the necessary water for plant growth, and suitable temperatures increased the efficiency of photosynthesis, resulting in a significant improvement of vegetation in the Qilian Mountains. The improvement of production technologies, especially in irrigation, has been beneficial to the growth of

A Tracking Analyst for large 3D spatiotemporal data from multiple sources (case study: Tracking volcanic eruptions in the atmosphere)

Science.gov (United States)

Gad, Mohamed A.; Elshehaly, Mai H.; Gračanin, Denis; Elmongui, Hicham G.

2018-02-01

This research presents a novel Trajectory-based Tracking Analyst (TTA) that can track and link spatiotemporally variable data from multiple sources. The proposed technique uses trajectory information to determine the positions of time-enabled and spatially variable scatter data at any given time through a combination of along trajectory adjustment and spatial interpolation. The TTA is applied in this research to track large spatiotemporal data of volcanic eruptions (acquired using multi-sensors) in the unsteady flow field of the atmosphere. The TTA enables tracking injections into the atmospheric flow field, the reconstruction of the spatiotemporally variable data at any desired time, and the spatiotemporal join of attribute data from multiple sources. In addition, we were able to create a smooth animation of the volcanic ash plume at interactive rates. The initial results indicate that the TTA can be applied to a wide range of multiple-source data.

Quantitative microbiome profiling links gut community variation to microbial load.

Science.gov (United States)

Vandeputte, Doris; Kathagen, Gunter; D'hoe, Kevin; Vieira-Silva, Sara; Valles-Colomer, Mireia; Sabino, João; Wang, Jun; Tito, Raul Y; De Commer, Lindsey; Darzi, Youssef; Vermeire, Séverine; Falony, Gwen; Raes, Jeroen

2017-11-23

Current sequencing-based analyses of faecal microbiota quantify microbial taxa and metabolic pathways as fractions of the sample sequence library generated by each analysis. Although these relative approaches permit detection of disease-associated microbiome variation, they are limited in their ability to reveal the interplay between microbiota and host health. Comparative analyses of relative microbiome data cannot provide information about the extent or directionality of changes in taxa abundance or metabolic potential. If microbial load varies substantially between samples, relative profiling will hamper attempts to link microbiome features to quantitative data such as physiological parameters or metabolite concentrations. Saliently, relative approaches ignore the possibility that altered overall microbiota abundance itself could be a key identifier of a disease-associated ecosystem configuration. To enable genuine characterization of host-microbiota interactions, microbiome research must exchange ratios for counts. Here we build a workflow for the quantitative microbiome profiling of faecal material, through parallelization of amplicon sequencing and flow cytometric enumeration of microbial cells. We observe up to tenfold differences in the microbial loads of healthy individuals and relate this variation to enterotype differentiation. We show how microbial abundances underpin both microbiota variation between individuals and covariation with host phenotype. Quantitative profiling bypasses compositionality effects in the reconstruction of gut microbiota interaction networks and reveals that the taxonomic trade-off between Bacteroides and Prevotella is an artefact of relative microbiome analyses. Finally, we identify microbial load as a key driver of observed microbiota alterations in a cohort of patients with Crohn's disease, here associated with a low-cell-count Bacteroides enterotype (as defined through relative profiling).

Spatio-Temporal Variation and Monsoon Effect on the Temperature Lapse Rate of a Subtropical Island

Directory of Open Access Journals (Sweden)

Ching-An Chiu

2014-01-01

Full Text Available Temperature lapse rate (TLR has been widely used in the prediction of mountain climate and vegetation and in many ecological models. The aims of this paper are to explore the spatio-temporal variations and monsoon effects on the TLR in the subtropical island of Taiwan with its steep Central Mountain Region (CMR. A TLR analysis using the 32-year monthly mean air temperatures and elevations from 219 weather stations (sea level to 3852 m a.s.l. was performed based on different geographical regions and monsoon exposures. The results revealed that the average TLR for all of Taiwan is -5.17°C km-1, with a general tendency to be steeper in summer and shallower in winter. The results are also shallower than the typical or global average TLR of -6.5°C km-1. During the prevailing northeast monsoon season (winter, the TLR exhibits a contrast between the windward side (steeper, -5.97°C km-1 and the leeward side (shallower, -4.51°C km-1. From the diagnosis on spatial characteristics of monthly cloud amount and vertical atmospheric profiles, this contrasting phenomenon may be explained by the warming effect of onshore stratus clouds (500 - 2500 m depth on cold and dry Siberian monsoon air on the windward side of the CMR. On the southwestern leeward side of the CMR, the low-level (1500 m, the weak ventilation atmosphere and temperature inversion make the TLR shallower than on the windward side.

Not the time or the place: the missing spatio-temporal link in publicly available genetic data.

Science.gov (United States)

Pope, Lisa C; Liggins, Libby; Keyse, Jude; Carvalho, Silvia B; Riginos, Cynthia

2015-08-01

Genetic data are being generated at unprecedented rates. Policies of many journals, institutions and funding bodies aim to ensure that these data are publicly archived so that published results are reproducible. Additionally, publicly archived data can be 'repurposed' to address new questions in the future. In 2011, along with other leading journals in ecology and evolution, Molecular Ecology implemented mandatory public data archiving (the Joint Data Archiving Policy). To evaluate the effect of this policy, we assessed the genetic, spatial and temporal data archived for 419 data sets from 289 articles in Molecular Ecology from 2009 to 2013. We then determined whether archived data could be used to reproduce analyses as presented in the manuscript. We found that the journal's mandatory archiving policy has had a substantial positive impact, increasing genetic data archiving from 49 (pre-2011) to 98% (2011-present). However, 31% of publicly archived genetic data sets could not be recreated based on information supplied in either the manuscript or public archives, with incomplete data or inconsistent codes linking genetic data and metadata as the primary reasons. While the majority of articles did provide some geographic information, 40% did not provide this information as geographic coordinates. Furthermore, a large proportion of articles did not contain any information regarding date of sampling (40%). Although the inclusion of spatio-temporal data does require an increase in effort, we argue that the enduring value of publicly accessible genetic data to the molecular ecology field is greatly compromised when such metadata are not archived alongside genetic data. © 2015 John Wiley & Sons Ltd.

Linkages of fracture network geometry and hydro-mechanical properties to spatio-temporal variations of seismicity in Koyna-Warna Seismic Zone

Science.gov (United States)

Selles, A.; Mikhailov, V. O.; Arora, K.; Ponomarev, A.; Gopinadh, D.; Smirnov, V.; Srinu, Y.; Satyavani, N.; Chadha, R. K.; Davulluri, S.; Rao, N. P.

2017-12-01

Well logging data and core samples from the deep boreholes in the Koyna-Warna Seismic Zone (KWSZ) provided a glimpse of the 3-D fracture network responsible for triggered earthquakes in the region. The space-time pattern of earthquakes during the last five decades show strong linkage of favourably oriented fractures system deciphered from airborne LiDAR and borehole structural logging to the seismicity. We used SAR interferometry data on surface displacements to estimate activity of the inferred faults. The failure in rocks at depths is largely governed by overlying lithostatic and pore fluid pressure in the rock matrix which are subject to change in space and time. While lithostatic pressure tends to increase with depth pore pressure is prone to fluctuations due to any change in the hydrological regime. Based on the earthquake catalogue data, the seasonal variations in seismic activity associated with annual fluctuations in the reservoir water level were analyzed over the time span of the entire history of seismological observations in this region. The regularities in the time changes in the structure of seasonal variations are revealed. An increase in pore fluid pressure can result in rock fracture and oscillating pore fluid pressures due to a reservoir loading and unloading cycles can cause iterative and cumulative damage, ultimately resulting in brittle failure under relatively low effective mean stress conditions. These regularities were verified by laboratory physical modeling. Based on our observations of main trends of spatio-temporal variations in seismicity as well as the spatial distribution of fracture network a conceptual model is presented to explain the triggered earthquakes in the KWSZ. The work was supported under the joint Russian-Indian project of the Russian Science Foundation (RSF) and the Department of Science and Technology (DST) of India (RSF project no. 16-47-02003 and DST project INT/RUS/RSF/P-13).

Spatio-temporal statistical models with applications to atmospheric processes

International Nuclear Information System (INIS)

Wikle, C.K.

1996-01-01

This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model

Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia

Science.gov (United States)

Naish, Suchithra; Hu, Wenbiao; Mengersen, Kerrie; Tong, Shilu

2011-01-01

Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,pQueensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland. PMID:22022430

Spatio-temporal changes in precipitation over Beijing-Tianjin-Hebei region, China

Science.gov (United States)

Zhao, Na; Yue, Tianxiang; Li, Han; Zhang, Lili; Yin, Xiaozhe; Liu, Yi

2018-04-01

Changes in precipitation have a large effect on human society and are of primary importance for many scientific fields such as hydrology, agriculture and eco-environmental sciences. The present study intended to investigate the spatio-temporal characteristics of precipitation in Beijing-Tianjin-Hebei (BTH) region by using 316 meteorological stations during the period 1965-2014. Geographical Weighted Regression (GWR) method and High Accuracy Surface Modeling (HASM) method were applied to produce the precipitation patterns at different time scales. Mann-Kendall (MK) statistical test was applied to analyze the precipitation temporal variations. Results indicated that annual precipitation over the past 50 years appeared to be a non-periodic oscillation phenomenon; the number of wet years was approximately the same as that of dry years; significant positive trends were observed in spring during 1978-2014 and summer during 1996-2014; on the whole, precipitation in May, June, September, and December showed increasing trends at the 95% confidence level; and significant positive trends were also identified in July during 2000-2013 and August during 1997-2010, while slight decreasing trends were observed in February and November. Summer (June, July, and August) was the wettest season, accounting for 68.73% of annual totals in BTH. In general, northeastern BTH received the highest range of precipitation while northwestern area had the lowest. It was found that precipitation variation in this region had been closely linked to latitude, Digital Elevation Model (DEM), distance to the sea, and urbanization rate. In addition, land use played an important role in the decadal precipitation changes in BTH.

Fine-scale spatio-temporal variation in tiger Panthera tigris diet: Effect of study duration and extent on estimates of tiger diet in Chitwan National Park, Nepal

Science.gov (United States)

Kapfer, Paul M.; Streby, Henry M.; Gurung, B.; Simcharoen, A.; McDougal, C.C.; Smith, J.L.D.

2011-01-01

Attempts to conserve declining tiger Panthera tigris populations and distributions have experienced limited success. The poaching of tiger prey is a key threat to tiger persistence; a clear understanding of tiger diet is a prerequisite to conserve dwindling populations. We used unpublished data on tiger diet in combination with two previously published studies to examine fine-scale spatio-temporal changes in tiger diet relative to prey abundance in Chitwan National Park, Nepal, and aggregated data from the three studies to examine the effect that study duration and the size of the study area have on estimates of tiger diet. Our results correspond with those of previous studies: in all three studies, tiger diet was dominated by members of Cervidae; small to medium-sized prey was important in one study. Tiger diet was unrelated to prey abundance, and the aggregation of studies indicates that increasing study duration and study area size both result in increased dietary diversity in terms of prey categories consumed, and increasing study duration changed which prey species contributed most to tiger diet. Based on our results, we suggest that managers focus their efforts on minimizing the poaching of all tiger prey, and that future studies of tiger diet be of long duration and large spatial extent to improve our understanding of spatio-temporal variation in estimates of tiger diet. ?? 2011 Wildlife Biology, NKV.

[Spatiotemporal variation of Populus euphratica's radial increment at lower reaches of Tarim River after ecological water transfer].

Science.gov (United States)

An, Hong-Yan; Xu, Hai-Liang; Ye, Mao; Yu, Pu-Ji; Gong, Jun-Jun

2011-01-01

Taking the Populus euphratica at lower reaches of Tarim River as test object, and by the methods of tree dendrohydrology, this paper studied the spatiotemporal variation of P. euphratic' s branch radial increment after ecological water transfer. There was a significant difference in the mean radial increment before and after ecological water transfer. The radial increment after the eco-water transfer was increased by 125%, compared with that before the water transfer. During the period of ecological water transfer, the radial increment was increased with increasing water transfer quantity, and there was a positive correlation between the annual radial increment and the total water transfer quantity (R2 = 0.394), suggesting that the radial increment of P. euphratica could be taken as the performance indicator of ecological water transfer. After the ecological water transfer, the radial increment changed greatly with the distance to the River, i.e. , decreased significantly along with the increasing distance to the River (P = 0.007). The P. euphratic' s branch radial increment also differed with stream segment (P = 0.017 ), i.e. , the closer to the head-water point (Daxihaizi Reservoir), the greater the branch radial increment. It was considered that the limited effect of the current ecological water transfer could scarcely change the continually deteriorating situation of the lower reaches of Tarim River.

Spatio-temporal modelling of wind speed variations and extremes in the Caribbean and the Gulf of Mexico

Science.gov (United States)

Rychlik, Igor; Mao, Wengang

2018-02-01

The wind speed variability in the North Atlantic has been successfully modelled using a spatio-temporal transformed Gaussian field. However, this type of model does not correctly describe the extreme wind speeds attributed to tropical storms and hurricanes. In this study, the transformed Gaussian model is further developed to include the occurrence of severe storms. In this new model, random components are added to the transformed Gaussian field to model rare events with extreme wind speeds. The resulting random field is locally stationary and homogeneous. The localized dependence structure is described by time- and space-dependent parameters. The parameters have a natural physical interpretation. To exemplify its application, the model is fitted to the ECMWF ERA-Interim reanalysis data set. The model is applied to compute long-term wind speed distributions and return values, e.g., 100- or 1000-year extreme wind speeds, and to simulate random wind speed time series at a fixed location or spatio-temporal wind fields around that location.

Spatiotemporal optical solitons

International Nuclear Information System (INIS)

Malomed, Boris A; Mihalache, Dumitru; Wise, Frank; Torner, Lluis

2005-01-01

In the course of the past several years, a new level of understanding has been achieved about conditions for the existence, stability, and generation of spatiotemporal optical solitons, which are nondiffracting and nondispersing wavepackets propagating in nonlinear optical media. Experimentally, effectively two-dimensional (2D) spatiotemporal solitons that overcome diffraction in one transverse spatial dimension have been created in quadratic nonlinear media. With regard to the theory, fundamentally new features of light pulses that self-trap in one or two transverse spatial dimensions and do not spread out in time, when propagating in various optical media, were thoroughly investigated in models with various nonlinearities. Stable vorticity-carrying spatiotemporal solitons have been predicted too, in media with competing nonlinearities (quadratic-cubic or cubic-quintic). This article offers an up-to-date survey of experimental and theoretical results in this field. Both achievements and outstanding difficulties are reviewed, and open problems are highlighted. Also briefly described are recent predictions for stable 2D and 3D solitons in Bose-Einstein condensates supported by full or low-dimensional optical lattices. (review article)

Genetic determination of human facial morphology: links between cleft-lips and normal variation.

Science.gov (United States)

Boehringer, Stefan; van der Lijn, Fedde; Liu, Fan; Günther, Manuel; Sinigerova, Stella; Nowak, Stefanie; Ludwig, Kerstin U; Herberz, Ruth; Klein, Stefan; Hofman, Albert; Uitterlinden, Andre G; Niessen, Wiro J; Breteler, Monique M B; van der Lugt, Aad; Würtz, Rolf P; Nöthen, Markus M; Horsthemke, Bernhard; Wieczorek, Dagmar; Mangold, Elisabeth; Kayser, Manfred

2011-11-01

Recent genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with non-syndromic cleft lip with or without cleft palate (NSCL/P), and other previous studies showed distinctly differing facial distance measurements when comparing unaffected relatives of NSCL/P patients with normal controls. Here, we test the hypothesis that genetic loci involved in NSCL/P also influence normal variation in facial morphology. We tested 11 SNPs from 10 genomic regions previously showing replicated evidence of association with NSCL/P for association with normal variation of nose width and bizygomatic distance in two cohorts from Germany (N=529) and the Netherlands (N=2497). The two most significant associations found were between nose width and SNP rs1258763 near the GREM1 gene in the German cohort (P=6 × 10(-4)), and between bizygomatic distance and SNP rs987525 at 8q24.21 near the CCDC26 gene (P=0.017) in the Dutch sample. A genetic prediction model explained 2% of phenotype variation in nose width in the German and 0.5% of bizygomatic distance variation in the Dutch cohort. Although preliminary, our data provide a first link between genetic loci involved in a pathological facial trait such as NSCL/P and variation of normal facial morphology. Moreover, we present a first approach for understanding the genetic basis of human facial appearance, a highly intriguing trait with implications on clinical practice, clinical genetics, forensic intelligence, social interactions and personal identity.

Spatio-Temporal Data Exchange Standards

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Schmidt, Albrecht

2003-01-01

We believe that research that concerns aspects of spatio-temporal data management may benefit from taking into account the various standards for spatio-temporal data formats. For example, this may contribute to rendering prototype software “open” and more readily useful. This paper thus identifies...... and briefly surveys standardization in relation to primarily the exchange and integration of spatio-temporal data. An overview of several data exchange languages is offered, along with reviews their potential for facilitating the collection of test data and the leveraging of prototypes. The standards, most...... of which are XML-based, lend themselves to the integration of prototypes into middleware architectures, e.g., as Web services....

The influence of long-range links on spiral waves and their application for control

International Nuclear Information System (INIS)

Qian Yu

2012-01-01

The influence of long-range links on spiral waves in an excitable medium has been investigated. Spatiotemporal dynamics in an excitable small-world network transform remarkably when we increase the long-range connection probability P. Spiral waves with few perturbations, broken spiral waves, pseudo spiral turbulence, synchronous oscillations, and homogeneous rest state are discovered under different network structures. Tip number is selected to detect non-equilibrium phase transition between different spatiotemporal patterns. The Kuramoto order parameter is used to identify these patterns and explain the emergence of the rest state. Finally, we use long-range links to successfully control spiral waves and spiral turbulence. (interdisciplinary physics and related areas of science and technology)

Second-order analysis of structured inhomogeneous spatio-temporal point processes

DEFF Research Database (Denmark)

Møller, Jesper; Ghorbani, Mohammad

Statistical methodology for spatio-temporal point processes is in its infancy. We consider second-order analysis based on pair correlation functions and K-functions for first general inhomogeneous spatio-temporal point processes and second inhomogeneous spatio-temporal Cox processes. Assuming...... spatio-temporal separability of the intensity function, we clarify different meanings of second-order spatio-temporal separability. One is second-order spatio-temporal independence and relates e.g. to log-Gaussian Cox processes with an additive covariance structure of the underlying spatio......-temporal Gaussian process. Another concerns shot-noise Cox processes with a separable spatio-temporal covariance density. We propose diagnostic procedures for checking hypotheses of second-order spatio-temporal separability, which we apply on simulated and real data (the UK 2001 epidemic foot and mouth disease data)....

Spatiotemporally Representative and Cost-Efficient Sampling Design for Validation Activities in Wanglang Experimental Site

Directory of Open Access Journals (Sweden)

Gaofei Yin

2017-11-01

Full Text Available Spatiotemporally representative Elementary Sampling Units (ESUs are required for capturing the temporal variations in surface spatial heterogeneity through field measurements. Since inaccessibility often coexists with heterogeneity, a cost-efficient sampling design is mandatory. We proposed a sampling strategy to generate spatiotemporally representative and cost-efficient ESUs based on the conditioned Latin hypercube sampling scheme. The proposed strategy was constrained by multi-temporal Normalized Difference Vegetation Index (NDVI imagery, and the ESUs were limited within a sampling feasible region established based on accessibility criteria. A novel criterion based on the Overlapping Area (OA between the NDVI frequency distribution histogram from the sampled ESUs and that from the entire study area was used to assess the sampling efficiency. A case study in Wanglang National Nature Reserve in China showed that the proposed strategy improves the spatiotemporally representativeness of sampling (mean annual OA = 74.7% compared to the single-temporally constrained (OA = 68.7% and the random sampling (OA = 63.1% strategies. The introduction of the feasible region constraint significantly reduces in-situ labour-intensive characterization necessities at expenses of about 9% loss in the spatiotemporal representativeness of the sampling. Our study will support the validation activities in Wanglang experimental site providing a benchmark for locating the nodes of automatic observation systems (e.g., LAINet which need a spatially distributed and temporally fixed sampling design.

a Web-Based Interactive Platform for Co-Clustering Spatio-Temporal Data

Science.gov (United States)

Wu, X.; Poorthuis, A.; Zurita-Milla, R.; Kraak, M.-J.

2017-09-01

Since current studies on clustering analysis mainly focus on exploring spatial or temporal patterns separately, a co-clustering algorithm is utilized in this study to enable the concurrent analysis of spatio-temporal patterns. To allow users to adopt and adapt the algorithm for their own analysis, it is integrated within the server side of an interactive web-based platform. The client side of the platform, running within any modern browser, is a graphical user interface (GUI) with multiple linked visualizations that facilitates the understanding, exploration and interpretation of the raw dataset and co-clustering results. Users can also upload their own datasets and adjust clustering parameters within the platform. To illustrate the use of this platform, an annual temperature dataset from 28 weather stations over 20 years in the Netherlands is used. After the dataset is loaded, it is visualized in a set of linked visualizations: a geographical map, a timeline and a heatmap. This aids the user in understanding the nature of their dataset and the appropriate selection of co-clustering parameters. Once the dataset is processed by the co-clustering algorithm, the results are visualized in the small multiples, a heatmap and a timeline to provide various views for better understanding and also further interpretation. Since the visualization and analysis are integrated in a seamless platform, the user can explore different sets of co-clustering parameters and instantly view the results in order to do iterative, exploratory data analysis. As such, this interactive web-based platform allows users to analyze spatio-temporal data using the co-clustering method and also helps the understanding of the results using multiple linked visualizations.

Spatio-temporal variations in phytoplankton community structure in ...

African Journals Online (AJOL)

OMARI

2013-09-06

Sep 6, 2013 ... estimating potential fish yield (Descy et al., 2005), .... populations have been conducted in open waters Lake ... Victoria basin Kenya which was stratified in terms of altitude .... Mean monthly variation of surface water pH values in small water bodies ..... Although there was optimal temperature, pH, D.O.

Semi-supervised tracking of extreme weather events in global spatio-temporal climate datasets

Science.gov (United States)

Kim, S. K.; Prabhat, M.; Williams, D. N.

2017-12-01

Deep neural networks have been successfully applied to solve problem to detect extreme weather events in large scale climate datasets and attend superior performance that overshadows all previous hand-crafted methods. Recent work has shown that multichannel spatiotemporal encoder-decoder CNN architecture is able to localize events in semi-supervised bounding box. Motivated by this work, we propose new learning metric based on Variational Auto-Encoders (VAE) and Long-Short-Term-Memory (LSTM) to track extreme weather events in spatio-temporal dataset. We consider spatio-temporal object tracking problems as learning probabilistic distribution of continuous latent features of auto-encoder using stochastic variational inference. For this, we assume that our datasets are i.i.d and latent features is able to be modeled by Gaussian distribution. In proposed metric, we first train VAE to generate approximate posterior given multichannel climate input with an extreme climate event at fixed time. Then, we predict bounding box, location and class of extreme climate events using convolutional layers given input concatenating three features including embedding, sampled mean and standard deviation. Lastly, we train LSTM with concatenated input to learn timely information of dataset by recurrently feeding output back to next time-step's input of VAE. Our contribution is two-fold. First, we show the first semi-supervised end-to-end architecture based on VAE to track extreme weather events which can apply to massive scaled unlabeled climate datasets. Second, the information of timely movement of events is considered for bounding box prediction using LSTM which can improve accuracy of localization. To our knowledge, this technique has not been explored neither in climate community or in Machine Learning community.

Analysis and modelling of spatio-temporal properties of daily rainfall over the Danube basin

Science.gov (United States)

Serinaldi, F.; Kilsby, C. G.

2012-04-01

Central and Eastern Europe are prone to severe floods due to heavy rainfall that cause societal and economic damages, ranging from agriculture to water resources, from the insurance/reinsurance sector to the energy industry. To improve the flood risk analysis, a better characterisation and modelling of the rainfall patterns over this area, which involves the Danube river watershed, is strategically important. In this study, we analyse the spatio-temporal properties of a large data set of daily rainfall time series from 15 countries in the Central Eastern Europe through different lagged and non-lagged indices of associations that quantify both the overall dependence and extreme dependence of pairwise observations. We also show that these measures are linked to each other and can be written in a unique and coherent notation within the copula framework. Moreover, the lagged version of these measures allows exploring some important spatio-temporal properties of the rainfall fields. The exploratory analysis is complemented by the preliminary results of a spatio-temporal rainfall simulation performed via a compound model based upon the Generalized Additive Models for Location, Scale and Shape (GAMLSS) and meta-elliptical multivariate distributions.

Aspects of second-order analysis of structured inhomogeneous spatio-temporal processes

DEFF Research Database (Denmark)

Møller, Jesper; Ghorbani, Mohammad

2012-01-01

Statistical methodology for spatio-temporal point processes is in its infancy. We consider second-order analysis based on pair correlation functions and K-functions for general inhomogeneous spatio-temporal point processes and for inhomogeneous spatio-temporal Cox processes. Assuming spatio......-temporal separability of the intensity function, we clarify different meanings of second-order spatio-temporal separability. One is second-order spatio-temporal independence and relates to log-Gaussian Cox processes with an additive covariance structure of the underlying spatio-temporal Gaussian process. Another...... concerns shot-noise Cox processes with a separable spatio-temporal covariance density. We propose diagnostic procedures for checking hypotheses of second-order spatio-temporal separability, which we apply on simulated and real data....

Investigation of Roadway Geometric and Traffic Flow Factors for Vehicle Crashes Using Spatiotemporal Interaction

Science.gov (United States)

Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.

2017-09-01

Traffic safety is a major concern in the transportation industry due to immense monetary and emotional burden caused by crashes of various severity levels, especially the injury and fatality ones. To reduce such crashes on all public roads, the safety management processes are commonly implemented which include network screening, problem diagnosis, countermeasure identification, and project prioritization. The selection of countermeasures for potential mitigation of crashes is governed by the influential factors which impact roadway crashes. Crash prediction model is the tool widely adopted by safety practitioners or researchers to link various influential factors to crash occurrences. Many different approaches have been used in the past studies to develop better fitting models which also exhibit prediction accuracy. In this study, a crash prediction model is developed to investigate the vehicular crashes occurring at roadway segments. The spatial and temporal nature of crash data is exploited to form a spatiotemporal model which accounts for the different types of heterogeneities among crash data and geometric or traffic flow variables. This study utilizes the Poisson lognormal model with random effects, which can accommodate the yearly variations in explanatory variables and the spatial correlations among segments. The dependency of different factors linked with roadway geometric, traffic flow, and road surface type on vehicular crashes occurring at segments was established as the width of lanes, posted speed limit, nature of pavement, and AADT were found to be correlated with vehicle crashes.

INVESTIGATION OF ROADWAY GEOMETRIC AND TRAFFIC FLOW FACTORS FOR VEHICLE CRASHES USING SPATIOTEMPORAL INTERACTION

Directory of Open Access Journals (Sweden)

G. Gill

2017-09-01

Full Text Available Traffic safety is a major concern in the transportation industry due to immense monetary and emotional burden caused by crashes of various severity levels, especially the injury and fatality ones. To reduce such crashes on all public roads, the safety management processes are commonly implemented which include network screening, problem diagnosis, countermeasure identification, and project prioritization. The selection of countermeasures for potential mitigation of crashes is governed by the influential factors which impact roadway crashes. Crash prediction model is the tool widely adopted by safety practitioners or researchers to link various influential factors to crash occurrences. Many different approaches have been used in the past studies to develop better fitting models which also exhibit prediction accuracy. In this study, a crash prediction model is developed to investigate the vehicular crashes occurring at roadway segments. The spatial and temporal nature of crash data is exploited to form a spatiotemporal model which accounts for the different types of heterogeneities among crash data and geometric or traffic flow variables. This study utilizes the Poisson lognormal model with random effects, which can accommodate the yearly variations in explanatory variables and the spatial correlations among segments. The dependency of different factors linked with roadway geometric, traffic flow, and road surface type on vehicular crashes occurring at segments was established as the width of lanes, posted speed limit, nature of pavement, and AADT were found to be correlated with vehicle crashes.

Pollination Biology and Spatio-Temporal Structuring of Some Major Acacia Species (Leguminosae) of the Arabian Peninsula

International Nuclear Information System (INIS)

Adgaba, N.; Alghamidi, A.; Tadesse, Y.; Getachew, A.; Ansari, M. J.

2016-01-01

Acacias are the dominant woody plant species distributed over the vast tracts of land throughout the Arabian Peninsula. However, information on spatio-temporal structuring and pollination biology of the species is not precisely available. To determine whether any variations exist among the Acacia species in their temporal distribution, their flowering period was determined through monitoring the commencing, peaking and ending of flowering of each species. Moreover, if any variations exist in release of floral rewards among the different co-existing and co-flowering species as mechanisms of partitioning of pollinators, to minimize competition for pollination, the progress of their anthesis over time was recorded by scoring polyads to anthers ratio at different hours of a day. In addition, the amount and dynamics of nectar sugar per inflorescence (N =225/species) was determined following flower nectar sugar washing technique. Types and frequencies of flower visitors and their preferences were determined by recording the visitors 6 times a day. The current study revealed that the Acacia species of the Arabian Peninsula are spatio-temporally structured: some species co-exist yet have different flowering seasons, whereas others co-exist, flowering concurrently yet exhibit a shift in their time of peak flowering and in the time at which the peak pollen is released during the day. This study demonstrates that all Acacia species examined secrete a considerable amount of nectar (2.24+-1.72 -10.02+-4.0mg/inflorescence) which serves as a floral reward for pollinators. Insects of the Order Hymenoptera are the most prevalent visitors to Acacia species in the region. The variations in spatio-temporal structuring of the Acaciaspecies could be due to their adaptation of reducing competition for pollinators and minimizing hetero-specific pollen transfer. (author)

[Spatiotemporal variation characteristics and related affecting factors of actual evapotranspiration in the Hun-Taizi River Basin, Northeast China].

Science.gov (United States)

Feng, Xue; Cai, Yan-Cong; Guan, De-Xin; Jin, Chang-Jie; Wang, An-Zhi; Wu, Jia-Bing; Yuan, Feng-Hui

2014-10-01

Based on the meteorological and hydrological data from 1970 to 2006, the advection-aridity (AA) model with calibrated parameters was used to calculate evapotranspiration in the Hun-Taizi River Basin in Northeast China. The original parameter of the AA model was tuned according to the water balance method and then four subbasins were selected to validate. Spatiotemporal variation characteristics of evapotranspiration and related affecting factors were analyzed using the methods of linear trend analysis, moving average, kriging interpolation and sensitivity analysis. The results showed that the empirical parameter value of 0.75 of AA model was suitable for the Hun-Taizi River Basin with an error of 11.4%. In the Hun-Taizi River Basin, the average annual actual evapotranspiration was 347.4 mm, which had a slightly upward trend with a rate of 1.58 mm · (10 a(-1)), but did not change significantly. It also indicated that the annual actual evapotranspiration presented a single-peaked pattern and its peak value occurred in July; the evapotranspiration in summer was higher than in spring and autumn, and it was the smallest in winter. The annual average evapotranspiration showed a decreasing trend from the northwest to the southeast in the Hun-Taizi River Basin from 1970 to 2006 with minor differences. Net radiation was largely responsible for the change of actual evapotranspiration in the Hun-Taizi River Basin.

SPATIOTEMPORAL CONTRAST SENSITIVITY OF EARLY VISION

NARCIS (Netherlands)

Hateren, J.H. van

Based on the spatial and temporal statistics of natural images, a theory is developed that specifies spatiotemporal filters that maximize the flow of information through noisy channels of limited dynamic range. Sensitivities resulting from these spatiotemporal filters are very similar to the human

The Link between Microbial Diversity and Nitrogen Cycling in Marine Sediments Is Modulated by Macrofaunal Bioturbation.

Science.gov (United States)

Yazdani Foshtomi, Maryam; Braeckman, Ulrike; Derycke, Sofie; Sapp, Melanie; Van Gansbeke, Dirk; Sabbe, Koen; Willems, Anne; Vincx, Magda; Vanaverbeke, Jan

2015-01-01

The marine benthic nitrogen cycle is affected by both the presence and activity of macrofauna and the diversity of N-cycling microbes. However, integrated research simultaneously investigating macrofauna, microbes and N-cycling is lacking. We investigated spatio-temporal patterns in microbial community composition and diversity, macrofaunal abundance and their sediment reworking activity, and N-cycling in seven subtidal stations in the Southern North Sea. Our results indicated that bacteria (total and β-AOB) showed more spatio-temporal variation than archaea (total and AOA) as sedimentation of organic matter and the subsequent changes in the environment had a stronger impact on their community composition and diversity indices in our study area. However, spatio-temporal patterns of total bacterial and β-AOB communities were different and related to the availability of ammonium for the autotrophic β-AOB. Highest bacterial richness and diversity were observed in June at the timing of the phytoplankton bloom deposition, while richness of β-AOB as well as AOA peaked in September. Total archaeal community showed no temporal variation in diversity indices. Distance based linear models revealed that, independent from the effect of grain size and the quality and quantity of sediment organic matter, nitrification and N-mineralization were affected by respectively the diversity of metabolically active β-AOB and AOA, and the total bacteria, near the sediment-water interface. Separate models demonstrated a significant and independent effect of macrofaunal activities on community composition and richness of total bacteria, and diversity indices of metabolically active AOA. Diversity of β-AOB was significantly affected by macrofaunal abundance. Our results support the link between microbial biodiversity and ecosystem functioning in marine sediments, and provided broad correlative support for the hypothesis that this relationship is modulated by macrofaunal activity. We

The Link between Microbial Diversity and Nitrogen Cycling in Marine Sediments Is Modulated by Macrofaunal Bioturbation.

Directory of Open Access Journals (Sweden)

Maryam Yazdani Foshtomi

Full Text Available The marine benthic nitrogen cycle is affected by both the presence and activity of macrofauna and the diversity of N-cycling microbes. However, integrated research simultaneously investigating macrofauna, microbes and N-cycling is lacking. We investigated spatio-temporal patterns in microbial community composition and diversity, macrofaunal abundance and their sediment reworking activity, and N-cycling in seven subtidal stations in the Southern North Sea.Our results indicated that bacteria (total and β-AOB showed more spatio-temporal variation than archaea (total and AOA as sedimentation of organic matter and the subsequent changes in the environment had a stronger impact on their community composition and diversity indices in our study area. However, spatio-temporal patterns of total bacterial and β-AOB communities were different and related to the availability of ammonium for the autotrophic β-AOB. Highest bacterial richness and diversity were observed in June at the timing of the phytoplankton bloom deposition, while richness of β-AOB as well as AOA peaked in September. Total archaeal community showed no temporal variation in diversity indices.Distance based linear models revealed that, independent from the effect of grain size and the quality and quantity of sediment organic matter, nitrification and N-mineralization were affected by respectively the diversity of metabolically active β-AOB and AOA, and the total bacteria, near the sediment-water interface. Separate models demonstrated a significant and independent effect of macrofaunal activities on community composition and richness of total bacteria, and diversity indices of metabolically active AOA. Diversity of β-AOB was significantly affected by macrofaunal abundance. Our results support the link between microbial biodiversity and ecosystem functioning in marine sediments, and provided broad correlative support for the hypothesis that this relationship is modulated by macrofaunal

Spatiotemporal variation of watershed health propensity through reliability-resilience-vulnerability based drought index (case study: Shazand Watershed in Iran).

Science.gov (United States)

Sadeghi, Seyed Hamidreza; Hazbavi, Zeinab

2017-06-01

Quantitative response of the watershed health to climate variability is of critical importance for watershed managers. However, existing studies seldom considered the impact of climate variability on watershed health. The present study therefore aimed to analyze the temporal and spatial variability of reliability (R el ), resilience (R es ) and vulnerability (V ul ) indicators in node years of 1986, 1998, 2008 and 2014 in connection with Standardized Precipitation Index (SPI) for 24 sub-watersheds in the Shazand Watershed of Markazi Province in Iran. The analysis was based on rainfall variability as one of the main climatic drivers. To achieve the study purposes, the monthly rainfall time series of eight rain gauge stations distributed across the watershed or neighboring areas were analyzed and corresponding SPIs and R el R es V ul indicators were calculated. Ultimately, the spatial variation of SPI oriented R el R es V ul was mapped for the study watershed using Geographic Information System (GIS). The average and standard deviation of SPI-R el R es V ul index for the study years of 1986, 1998, 2008 and 2014 was obtained 0.240±0.025, 0.290±0.036, 0.077±0.0280 and 0.241±0.081, respectively. In overall, the results of the study proved the spatiotemporal variations of SPI-R el R es V ul watershed health index in the study area. Accordingly, all the sub-watersheds of the Shazand Watershed were grouped in unhealthy and very unhealthy conditions in all the study years. For 1986 and 1998 all the sub-watersheds were assessed in unhealthy status. Whilst, it declined to very unhealthy condition in 2008 and then some 75% of the watershed ultimately referred again to unhealthy and the rest still remained under very unhealthy conditions in 2014. Copyright © 2017 Elsevier B.V. All rights reserved.

SPATIOTEMPORAL PATTERNS AND ITS INSTABILITY OF LAND USE CHANGE IN FIVE CHINESE NODE CITIES OF THE BELT AND ROAD

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B. Quan

2017-09-01

Full Text Available It has long recognized that there exists three different terrain belt in China, i.e. east, central, and west can have very different impacts on the land use changes. It is therefore better understand how spatiotemporal patterns linked with processes and instability of land use change are evolving in China across different regions. This paper compares trends of the similarities and differences to understand the spatiotemporal characteristics and the linked processes i.e. states, incidents and instability of land use change of 5 Chinese cities which are located in the nodes of The Silk Road in China. The results show that on the whole, the more land transfer times and the more land categories involved changes happens in Quanzhou City, one of eastern China than those in central and western China. Basically, cities in central and western China such as Changsha, Kunming and Urumuqi City become instable while eastern city like Quanzhou City turns to be stable over time.

Spatiotemporal Patterns and its Instability of Land Use Change in Five Chinese Node Cities of the Belt and Road

Science.gov (United States)

Quan, B.; Guo, T.; Liu, P. L.; Ren, H. G.

2017-09-01

It has long recognized that there exists three different terrain belt in China, i.e. east, central, and west can have very different impacts on the land use changes. It is therefore better understand how spatiotemporal patterns linked with processes and instability of land use change are evolving in China across different regions. This paper compares trends of the similarities and differences to understand the spatiotemporal characteristics and the linked processes i.e. states, incidents and instability of land use change of 5 Chinese cities which are located in the nodes of The Silk Road in China. The results show that on the whole, the more land transfer times and the more land categories involved changes happens in Quanzhou City, one of eastern China than those in central and western China. Basically, cities in central and western China such as Changsha, Kunming and Urumuqi City become instable while eastern city like Quanzhou City turns to be stable over time.

Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

Energy Technology Data Exchange (ETDEWEB)

Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M.; Young, Vincent B.; Jansson, Janet K.; Fredricks, David N.; Borenstein, Elhanan; Sanchez, Laura M.

2015-12-22

Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in

A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates

OpenAIRE

Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne

2013-01-01

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implem...

4D cone beam CT via spatiotemporal tensor framelet

International Nuclear Information System (INIS)

Gao, Hao; Li, Ruijiang; Xing, Lei; Lin, Yuting

2012-01-01

Purpose: On-board 4D cone beam CT (4DCBCT) offers respiratory phase-resolved volumetric imaging, and improves the accuracy of target localization in image guided radiation therapy. However, the clinical utility of this technique has been greatly impeded by its degraded image quality, prolonged imaging time, and increased imaging dose. The purpose of this letter is to develop a novel iterative 4DCBCT reconstruction method for improved image quality, increased imaging speed, and reduced imaging dose. Methods: The essence of this work is to introduce the spatiotemporal tensor framelet (STF), a high-dimensional tensor generalization of the 1D framelet for 4DCBCT, to effectively take into account of highly correlated and redundant features of the patient anatomy during respiration, in a multilevel fashion with multibasis sparsifying transform. The STF-based algorithm is implemented on a GPU platform for improved computational efficiency. To evaluate the method, 4DCBCT full-fan scans were acquired within 30 s, with a gantry rotation of 200°; STF is also compared with a state-of-art reconstruction method via spatiotemporal total variation regularization. Results: Both the simulation and experimental results demonstrate that STF-based reconstruction achieved superior image quality. The reconstruction of 20 respiratory phases took less than 10 min on an NVIDIA Tesla C2070 GPU card. The STF codes are available at https://sites.google.com/site/spatiotemporaltensorframelet . Conclusions: By effectively utilizing the spatiotemporal coherence of the patient anatomy among different respiratory phases in a multilevel fashion with multibasis sparsifying transform, the proposed STF method potentially enables fast and low-dose 4DCBCT with improved image quality.

4D cone beam CT via spatiotemporal tensor framelet

Energy Technology Data Exchange (ETDEWEB)

Gao, Hao, E-mail: hao.gao@emory.edu [Departments of Mathematics and Computer Science, and Radiology and Imaging Sciences, Emory University, Atlanta, Georgia 30322 (United States); Li, Ruijiang; Xing, Lei [Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States); Lin, Yuting [Department of Radiological Sciences, University of California, Irvine, California 92697 (United States)

2012-11-15

Purpose: On-board 4D cone beam CT (4DCBCT) offers respiratory phase-resolved volumetric imaging, and improves the accuracy of target localization in image guided radiation therapy. However, the clinical utility of this technique has been greatly impeded by its degraded image quality, prolonged imaging time, and increased imaging dose. The purpose of this letter is to develop a novel iterative 4DCBCT reconstruction method for improved image quality, increased imaging speed, and reduced imaging dose. Methods: The essence of this work is to introduce the spatiotemporal tensor framelet (STF), a high-dimensional tensor generalization of the 1D framelet for 4DCBCT, to effectively take into account of highly correlated and redundant features of the patient anatomy during respiration, in a multilevel fashion with multibasis sparsifying transform. The STF-based algorithm is implemented on a GPU platform for improved computational efficiency. To evaluate the method, 4DCBCT full-fan scans were acquired within 30 s, with a gantry rotation of 200°; STF is also compared with a state-of-art reconstruction method via spatiotemporal total variation regularization. Results: Both the simulation and experimental results demonstrate that STF-based reconstruction achieved superior image quality. The reconstruction of 20 respiratory phases took less than 10 min on an NVIDIA Tesla C2070 GPU card. The STF codes are available at https://sites.google.com/site/spatiotemporaltensorframelet . Conclusions: By effectively utilizing the spatiotemporal coherence of the patient anatomy among different respiratory phases in a multilevel fashion with multibasis sparsifying transform, the proposed STF method potentially enables fast and low-dose 4DCBCT with improved image quality.

The spatial and temporal variations of nematofauna of recovering ...

African Journals Online (AJOL)

The spatio-temporal variations in physical sediment characteristics and nematode community assemblages were investigated and compared between a natural, a 10-year reforested, and a degraded Rhizophora mucronata mangrove ecosystem in Gazi Bay, Kenya. PCA showed a clear separation of the degraded site from ...

Detecting spatio-temporal modes in multivariate data by entropy field decomposition

International Nuclear Information System (INIS)

Frank, Lawrence R; Galinsky, Vitaly L

2016-01-01

A new data analysis method that addresses a general problem of detecting spatio-temporal variations in multivariate data is presented. The method utilizes two recent and complimentary general approaches to data analysis, information field theory (IFT) and entropy spectrum pathways (ESPs). Both methods reformulate and incorporate Bayesian theory, thus use prior information to uncover underlying structure of the unknown signal. Unification of ESP and IFT creates an approach that is non-Gaussian and nonlinear by construction and is found to produce unique spatio-temporal modes of signal behavior that can be ranked according to their significance, from which space–time trajectories of parameter variations can be constructed and quantified. Two brief examples of real world applications of the theory to the analysis of data bearing completely different, unrelated nature, lacking any underlying similarity, are also presented. The first example provides an analysis of resting state functional magnetic resonance imaging data that allowed us to create an efficient and accurate computational method for assessing and categorizing brain activity. The second example demonstrates the potential of the method in the application to the analysis of a strong atmospheric storm circulation system during the complicated stage of tornado development and formation using data recorded by a mobile Doppler radar. Reference implementation of the method will be made available as a part of the QUEST toolkit that is currently under development at the Center for Scientific Computation in Imaging. (paper)

Hierarchical Bayesian modeling of spatio-temporal patterns of lung cancer incidence risk in Georgia, USA: 2000-2007

Science.gov (United States)

Yin, Ping; Mu, Lan; Madden, Marguerite; Vena, John E.

2014-10-01

Lung cancer is the second most commonly diagnosed cancer in both men and women in Georgia, USA. However, the spatio-temporal patterns of lung cancer risk in Georgia have not been fully studied. Hierarchical Bayesian models are used here to explore the spatio-temporal patterns of lung cancer incidence risk by race and gender in Georgia for the period of 2000-2007. With the census tract level as the spatial scale and the 2-year period aggregation as the temporal scale, we compare a total of seven Bayesian spatio-temporal models including two under a separate modeling framework and five under a joint modeling framework. One joint model outperforms others based on the deviance information criterion. Results show that the northwest region of Georgia has consistently high lung cancer incidence risk for all population groups during the study period. In addition, there are inverse relationships between the socioeconomic status and the lung cancer incidence risk among all Georgian population groups, and the relationships in males are stronger than those in females. By mapping more reliable variations in lung cancer incidence risk at a relatively fine spatio-temporal scale for different Georgian population groups, our study aims to better support healthcare performance assessment, etiological hypothesis generation, and health policy making.

Genotype-phenotype variations in five Spanish families with Norrie disease or X-linked FEVR.

Science.gov (United States)

Riveiro-Alvarez, Rosa; Trujillo-Tiebas, Maria José; Gimenez-Pardo, Ascension; Garcia-Hoyos, Maria; Cantalapiedra, Diego; Lorda-Sanchez, Isabel; Rodriguez de Alba, Marta; Ramos, Carmen; Ayuso, Carmen

2005-09-02

Norrie disease (OMIM 310600) is a rare X-linked disorder characterized by congenital blindness in males. Approximately 40 to 50% of the cases develop deafness and mental retardation. X-linked familial exudative vitreoretinopathy (XL-FEVR) is a hereditary ocular disorder characterized by a failure of peripheral retinal vascularization. Both X-linked disorders are due to mutations in the NDP gene, which encodes a 133 amino acid protein called Norrin, but autosomal recessive (AR) and autosomal dominant (AD) forms of FEVR have also been described. In this study, we report the molecular findings and the related phenotype in five Spanish families affected with Norrie disease or XL-FEVR due to mutations of the NDP gene. The study was conducted in 45 subjects from five Spanish families. These families were clinically diagnosed with Norrie disease or similar conditions. The three exons of the NDP gene were analyzed by automatic DNA sequencing. Haplotype analyses were also performed. Two new nonsense mutations, apart from other mutations previously described in the NDP gene, were found in those patients affected with ND or X-linked FEVR. An important genotype-phenotype variation was found in relation to the different mutations of the NDP gene. In fact, the same mutation may be responsible for different phenotypes. We speculate that there might be other molecular factors that interact in the retina with Norrin, which contribute to the resultant phenotypes.

Spatiotemporal Variations of Extreme Precipitation under a Changing Climate in the Three Gorges Reservoir Area (TGRA

Directory of Open Access Journals (Sweden)

Mingquan Lü

2018-01-01

Full Text Available The Three Gorges Dam (TGD is one of the largest hydroelectric projects in the world. Monitoring the spatiotemporal distribution of extreme precipitation offers valuable information for adaptation and mitigation strategies and reservoir management schemes. This study examined variations in extreme precipitation over the Three Gorges Reservoir area (TGRA in China to investigate the potential role of climate warming and Three Gorges Reservoir (TGR. The trends in extreme precipitation over the TGRA were investigated using the iterative-based Mann–Kendall (MK test and Sen’s slope estimator, based on weather station daily data series and TRMM (Tropical Rainfall Measuring Mission data series. The mean and density distribution of extreme precipitation indices between pre-dam and post-dam, pre-1985 and post-1985, and near and distant reservoir area were assessed by the Mann–Whitney test and the Kolmogorov–Smirnov test. The ratio of extreme precipitation to non-extreme precipitation became larger. The precipitation was characterized by increases in heavy precipitation as well as decreases in light and moderate rain. Comparing extreme precipitation indices between pre-1985 (cooling and post-1985 (warming indicated extreme precipitation has changed to become heavier. Under climate warming, the precipitation amount corresponding to more than the 95th percentile increased at the rate of 6.48%/°C. Results from comparing extreme precipitation for the pre- and post-dam, near reservoir area (NRA and away from the reservoir area (ARA imply an insignificant role of the TGR on rainfall extremes over the TGRA. Moreover, the impoundment of TGR did not exert detectable impacts on the surface relative humidity (RH and water vapor pressure (WP.

Spatio-Temporal Variation and Impact Factors for Vegetation Carbon Sequestration and Oxygen Production Based on Rocky Desertification Control in the Karst Region of Southwest China

Directory of Open Access Journals (Sweden)

Mingyang Zhang

2016-01-01

Full Text Available The Grain to Green Program (GTGP and eco-environmental emigration have been employed to alleviate poverty and control rocky desertification in the Southwest China Karst region. Carbon sequestration and oxygen production (CSOP is used to indicate major ecological changes, because they involve complex processes of material circulation and energy flow. Using remote sensing images and weather records, the spatiotemporal variation of CSOP was analyzed in a typical karst region of northwest Guangxi, China, during 2000–2010 to determine the effects of the Chinese government’s ecological rehabilitation initiatives implemented in 1999. An increase with substantial annual change and a significant increase (20.94%, p < 0.05 in variation were found from 2000 to 2010. CSOP had a highly clustered distribution in 2010 and was correlated with precipitation and temperature (9.18% and 8.96%, respectively, p < 0.05. CSOP was significantly suppressed by human activities (p < 0.01, r = −0.102 but was consistent with the intensity of GTGP (43.80% positive. The power spectrum of CSOP was consistent with that of the gross domestic product. These results indicate that ecological services were improved by rocky desertification control in a typical karst region. The results may provide information to evaluate the efficiency of ecological reconstruction projects.

Physico-chemical characteristics and methanogen communities in swine and dairy manure storage tanks: spatio-temporal variations and impact on methanogenic activity.

Science.gov (United States)

Barret, Maialen; Gagnon, Nathalie; Topp, Edward; Masse, Lucie; Massé, Daniel I; Talbot, Guylaine

2013-02-01

Greenhouse gas emissions represent a major environmental problem associated with the management of manure from the livestock industry. Methane is the primary GHG emitted during manure outdoor storage. In this paper, the variability of two swine and two dairy manure storage tanks was surveyed, in terms of physico-chemical and microbiological parameters. The impact of the inter-tank and spatio-temporal variations of these parameters on the methanogenic activity of manure was ascertained. A Partial Least Square regression was carried out, which demonstrated that physico-chemical as well as microbiological parameters had a major influence on the methanogenic activity. Among the 19 parameters included in the regression, the concentrations of VFAs had the strongest negative influence on the methane emission rate of manure, resulting from their well-known inhibitory effect. The relative abundance of two amplicons in archaeal fingerprints was found to positively influence the methanogenic activity, suggesting that Methanoculleus spp. and possibly Methanosarcina spp. are major contributors to methanogenesis in storage tanks. This work gave insights into the mechanisms, which drive methanogenesis in swine and dairy manure storage tanks. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Periodic transients linked to a variation in reactivity; Transitoires de periode lies a une variation de reactivite

Energy Technology Data Exchange (ETDEWEB)

Furet, J; Weil, J [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1961-07-01

We study here the influence of the transient, linked to a variation in reactivity, on the measurement of the period, this measurement being made from the logarithmic differential of the power and being defined by 1/T 1/p(dp/dt). We show that the adjustment of the thresholds of period safety is often incompatible with the velocities of liberation of reactivity. A compromise is then necessary between the speed of response of the periodimeter and the speed with which the reactivity is liberated. This makes it necessary to have rapid security devices for the power levels in the piles in which the speeds of liberation of the reactivity are high. (author) [French] On etudie ici l'influence du transitoire lie a une variation de la reactivite sur la mesure de la periode, cette mesure etant faite a partir de la derivee logarithmique de la puissance et etant definie par 1/T 1/p(dp/dt). On montre que le reglage des seuils de securite periode est souvent incompatible avec les vitesses de liberation de reactivite. Il y a alors un compromis a faire entre la vitesse de reponse du periodemetre et la vitesse de liberation de reactivite. Ceci impose de disposer de securites rapides sur les niveaux de puissance, dans les piles ou les vitesses de liberation de reactivite sont importantes. (auteur)

Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint

Science.gov (United States)

Tarabalka, Yuliya; Charpiat, Guillaume; Brucker, Ludovic; Menze, Bjoern H.

2014-01-01

We propose a new method for joint segmentation of monotonously growing or shrinking shapes in a time sequence of noisy images. The task of segmenting the image time series is expressed as an optimization problem using the spatio-temporal graph of pixels, in which we are able to impose the constraint of shape growth or of shrinkage by introducing monodirectional infinite links connecting pixels at the same spatial locations in successive image frames. The globally optimal solution is computed with a graph cut. The performance of the proposed method is validated on three applications: segmentation of melting sea ice floes and of growing burned areas from time series of 2D satellite images, and segmentation of a growing brain tumor from sequences of 3D medical scans. In the latter application, we impose an additional intersequences inclusion constraint by adding directed infinite links between pixels of dependent image structures.

Spatio-Temporal Data Construction

Directory of Open Access Journals (Sweden)

Hai Ha Le

2013-08-01

Full Text Available On the route to a spatio-temporal geoscience information system, an appropriate data model for geo-objects in space and time has been developed. In this model, geo-objects are represented as sequences of geometries and properties with continuous evolution in each time interval. Because geomodeling software systems usually model objects at specific time instances, we want to interpolate the geometry and properties from two models of an object with only geometrical constraints (no physical or mechanical constraints. This process is called spatio-temporal data construction or morphological interpolation of intermediate geometries. This paper is strictly related to shape morphing, shape deformation, cross-parameterization and compatible remeshing and is only concerned with geological surfaces. In this study, two main sub-solutions construct compatible meshes and find trajectories in which vertices of the mesh evolve. This research aims to find an algorithm to construct spatio-temporal data with some constraints from the geosciences, such as cutting surfaces by faulting or fracturing phenomena and evolving boundaries attached to other surfaces. Another goal of this research is the implementation of the algorithm in a software product, namely a gOcad plug-in. The four main procedures of the algorithm are cutting the surfaces, setting up constraints, partitioning and calculating the parameterizations and trajectories. The software has been tested to construct data for a salt dome and other surfaces in regard to the geological processes of faulting, deposition and erosion. The result of this research is an algorithm and software for the construction of spatio-temporal data.

Towards understanding of the spatio-temporal composition of Terrestrial Water Storage variations in Northern Latitudes using a model-data fusion approach

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Trautmann, Tina; Koirala, Sujan; Carvalhais, Nuno; Niemann, Christoph; Fink, Manfred; Jung, Martin

2017-04-01

Understanding variations in the terrestrial water storage (TWS) and its components is essential to gain insights into the dynamics of the hydrological cycle, and to assess temporal and spatial variations of water availability under global changes. We investigated spatio-temporal patterns of TWS variations and their composition in the humid regions of northern mid-to-high latitudes during 2001-2014 by using a simple hydrological model with few effective parameters. Compared to traditional modelling studies, our simple model was informed and constrained by multiple state-of-the-art earth observation products including TWS from Gravity Recovery and Climate Experiment (GRACE) satellites (Wiese 2015), Snow Water Equivalent (SWE) from GlobSnow project (Loujous et al. 2014), evapotranspiration fluxes from eddy covariance measurements (Tramontana et al. 2016), and gridded runoff estimates for Europe (Gudmundsson & Seneviratne 2016). Thorough evaluation of model demonstrates that the model reproduces the observed patterns of hydrological fluxes and states well. The validated model results are then used to assess the contributions of snow pack, soil moisture and groundwater on the integrated TWS across spatial (local grid scale, spatially integrated) and temporal (seasonal, inter-annual) scales. Interestingly, our results show that TWS variations on different scales are dominated by different components. On both, seasonal and inter-annual time scales, the spatially integrated TWS signal mainly originates from dynamics of snow pack. On the local grid scale, mean seasonal TWS variations are driven by snow dynamics as well, whereas inter-annual variations are found to originate from soil moisture availability. Thus, we show that the determinants of TWS variations are scale-dependent, while coincidently underline the potential of model-data fusion techniques to gain insights into the complex hydrological system. References: Gudmundsson, L. and S. I. Seneviratne (2016

Spatiotemporal Variation of Karst Ecosystem Service Values and Its Correlation with Environmental Factors in Northwest Guangxi, China

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Zhang, Mingyang; Zhang, Chunhua; Wang, Kelin; Yue, Yuemin; Qi, Xiangkun; Fan, Feide

2011-11-01

In this investigation we analyzed the spatiotemporal variation of ecosystem service values (ESVs) and its correlation with numerous environmental factors (EFs) for the karst region of Northwest Guangxi, China, from 1985 to 2005 using remote sensing, geographic information systems (GIS) and statistical techniques. The results indicate that historically ESVs for this karst region decreased from 1985 (109.652 billion Yuan) to 1990 (88.789 billion Yuan) and then increased at the turn of the twenty-first century. However, the ESVs in both 2000 (103.384 billion Yuan) and 2005 (106.257 billion Yuan) never achieved the level recorded in 1985. The total of nutrient cycling, organic production and gas regulation combined were 72.69, 64.57, 70.18 and 72.10% of ESVs in 1985, 1990, 2000 and 2005, respectively. In contrast, the ESVs of water conservation, soil reservation, recreation and culture were determined to be relatively low contributing only 17.44, 23.82, 19.26 and 24.76% of total ESVs, respectively, during these four years. With regards to the spatial distribution of ESVs, larger values were recorded in the west and smaller ones recorded in the east. The most significant factors that were deemed to influence ESVs are annual rainfall, per capita cropland, slope and vegetation coverage. Annual rainfall and slope exert a negative force, whereas per capita cropland and vegetation coverage exert a positive force on ESVs. The results of the study would suggest that ecosystem conditions of this important karst region have been improved as the result of the implementation of rocky desertification control policies.

The Voronoi spatio-temporal data structure

Science.gov (United States)

Mioc, Darka

2002-04-01

Current GIS models cannot integrate the temporal dimension of spatial data easily. Indeed, current GISs do not support incremental (local) addition and deletion of spatial objects, and they can not support the temporal evolution of spatial data. Spatio-temporal facilities would be very useful in many GIS applications: harvesting and forest planning, cadastre, urban and regional planning, and emergency planning. The spatio-temporal model that can overcome these problems is based on a topological model---the Voronoi data structure. Voronoi diagrams are irregular tessellations of space, that adapt to spatial objects and therefore they are a synthesis of raster and vector spatial data models. The main advantage of the Voronoi data structure is its local and sequential map updates, which allows us to automatically record each event and performed map updates within the system. These map updates are executed through map construction commands that are composed of atomic actions (geometric algorithms for addition, deletion, and motion of spatial objects) on the dynamic Voronoi data structure. The formalization of map commands led to the development of a spatial language comprising a set of atomic operations or constructs on spatial primitives (points and lines), powerful enough to define the complex operations. This resulted in a new formal model for spatio-temporal change representation, where each update is uniquely characterized by the numbers of newly created and inactivated Voronoi regions. This is used for the extension of the model towards the hierarchical Voronoi data structure. In this model, spatio-temporal changes induced by map updates are preserved in a hierarchical data structure that combines events and corresponding changes in topology. This hierarchical Voronoi data structure has an implicit time ordering of events visible through changes in topology, and it is equivalent to an event structure that can support temporal data without precise temporal

Determining wetland spatial extent and seasonal variations of the ...

African Journals Online (AJOL)

This study, done in the Witbank Dam Catchment in Mpumalanga Province of South Africa, explores a remote-sensing technique to delineate wetland extent and assesses the seasonal variations of the inundated area. The objective was to monitor the spatio-temporal changes of wetlands over time through remote sensing ...

Explaining health care expenditure variation: large-sample evidence using linked survey and health administrative data.

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Ellis, Randall P; Fiebig, Denzil G; Johar, Meliyanni; Jones, Glenn; Savage, Elizabeth

2013-09-01

Explaining individual, regional, and provider variation in health care spending is of enormous value to policymakers but is often hampered by the lack of individual level detail in universal public health systems because budgeted spending is often not attributable to specific individuals. Even rarer is self-reported survey information that helps explain this variation in large samples. In this paper, we link a cross-sectional survey of 267 188 Australians age 45 and over to a panel dataset of annual healthcare costs calculated from several years of hospital, medical and pharmaceutical records. We use this data to distinguish between cost variations due to health shocks and those that are intrinsic (fixed) to an individual over three years. We find that high fixed expenditures are positively associated with age, especially older males, poor health, obesity, smoking, cancer, stroke and heart conditions. Being foreign born, speaking a foreign language at home and low income are more strongly associated with higher time-varying expenditures, suggesting greater exposure to adverse health shocks. Copyright © 2013 John Wiley & Sons, Ltd.

Spatiotemporal Wave Patterns: Information Dynamics

Energy Technology Data Exchange (ETDEWEB)

Mikhail Rabinovich; Lev Tsimring

2006-01-20

Pattern formation has traditionally been studied in non-equilibrium physics from the viewpoint of describing the basic structures and their interactions. While this is still an important area of research, the emphasis in the last few years has shifted towards analysis of specific properties of patterns in various complex media. For example, diverse and unexpected phenomena occur in neuro-like media that are characterized by highly non-trivial local dynamics. We carried out an active research program on analysis of spatio-temporal patterns in various physical systems (convection, oscillating fluid layer, soap film), as well as in neuro-like media, with an emphasis on informational aspects of the dynamics. Nonlinear nonequilibrium media and their discrete analogs have a unique ability to represent, memorize, and process the information contained in spatio-temporal patterns. Recent neurophysiological experiments demonstrated a certain universality of spatio-temporal representation of information by neural ensembles. Information processing is also revealed in the spatio-temporal dynamics of cellular patterns in nonequilibrium media. It is extremely important for many applications to study the informational aspects of these dynamics, including the origins and mechanisms of information generation, propagation and storage. Some of our results are: the discovery of self-organization of periodically oscillatory patterns in chaotic heterogeneous media; the analysis of the propagation of the information along a chaotic media as function of the entropy of the signal; the analysis of wave propagation in discrete non-equilibrium media with autocatalytic properties, which simulates the calcium dynamics in cellular membranes. Based on biological experiments we suggest the mechanism by which the spatial sensory information is transferred into the spatio-temporal code in the neural media. We also found a new mechanism of self-pinning in cellular structures and the related phenomenon

Widespread Micropollutant Monitoring in the Hudson River Estuary Reveals Spatiotemporal Micropollutant Clusters and Their Sources.

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Carpenter, Corey M G; Helbling, Damian E

2018-06-05

The objective of this study was to identify sources of micropollutants in the Hudson River Estuary (HRE). We collected 127 grab samples at 17 sites along the HRE over 2 years and screened for up to 200 micropollutants. We quantified 168 of the micropollutants in at least one of the samples. Atrazine, gabapentin, metolachlor, and sucralose were measured in every sample. We used data-driven unsupervised methods to cluster the micropollutants on the basis of their spatiotemporal occurrence and normalized-concentration patterns. Three major clusters of micropollutants were identified: ubiquitous and mixed-use (core micropollutants), sourced from sewage treatment plant outfalls (STP micropollutants), and derived from diffuse upstream sources (diffuse micropollutants). Each of these clusters was further refined into subclusters that were linked to specific sources on the basis of relationships identified through geospatial analysis of watershed features. Evaluation of cumulative loadings of each subcluster revealed that the Mohawk River and Rondout Creek are major contributors of most core micropollutants and STP micropollutants and the upper HRE is a major contributor of diffuse micropollutants. These data provide the first comprehensive evaluation of micropollutants in the HRE and define distinct spatiotemporal micropollutant clusters that are linked to sources and conserved across surface water systems around the world.

Trait- and size-based descriptions of trophic links in freshwater food webs: current status and perspectives

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David S. Boukal

2014-04-01

Full Text Available Biotic interactions in aquatic communities are dominated by predation, and the distribution of trophic link strengths in aquatic food webs crucially impacts their dynamics and stability. Although individual body size explains a large proportion of variation in trophic link strengths in aquatic habitats, current predominately body size-based views can gain additional realism by incorporating further traits. Functional traits that potentially affect the strength of trophic links can be classified into three groups: i body size, ii traits that identify the spatiotemporal overlap between the predators and their prey, and iii predator foraging and prey vulnerability traits, which are readily available for many taxa. Relationship between these trait groups and trophic link strength may be further modified by population densities, habitat complexity, temperature and other abiotic factors. I propose here that this broader multi-trait framework can utilize concepts, ideas and existing data from research on metabolic ecology, ecomorphology, animal personalities and role of habitats in community structuring. The framework can be used to investigate non-additive effects of traits on trophic interactions, shed more light on the structuring of local food webs and evaluate the merits of taxonomic and functional group approaches in the description of predator-prey interactions. Development of trait- and size-based descriptions of food webs could be particularly fruitful in limnology given the relative paucity of well resolved datasets in standing waters. 

Spatio-temporal networks: reachability, centrality and robustness.

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Williams, Matthew J; Musolesi, Mirco

2016-06-01

Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks.

Atmospheric deposition of polycyclic aromatic hydrocarbons (PAHs) in Shanghai: the spatio-temporal variation and source identification

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Cheng, Chen; Bi, Chunjuan; Wang, Dongqi; Yu, Zhongjie; Chen, Zhenlou

2018-03-01

This study investigated the dry and wet deposition fluxes of atmospheric polycyclic aromatic hydrocarbons (PAHs) in Shanghai, China. The flux sources were traced based on composition and spatio-temporal variation. The results show that wet deposition concentrations of PAHs ranged from 0.07 to 0.67 mg·L-1 and were correlated with temperature ( P<0.05). Dry deposition of PAHs concentrations ranged from 3.60-92.15 mg·L-1 and were higher in winter and spring than in summer and autumn. The annual PAH average fluxes were 0.631 mg·m-2·d-1 and 4.06 mg·m-2·d-1 for wet and dry deposition, respectively. The highest wet deposition of PAH fluxes was observed in summer, while dry deposition fluxes were higher in winter and spring. Atmospheric PAHs were deposited as dry deposition in spring and winter, yet wet deposition was the dominant pathway during summer. Total atmospheric PAH fluxes were higher in the northern areas than in the southern areas of Shanghai, and were also observed to be higher in winter and spring. Annual deposition of atmospheric PAHs was about 10.8 t in across all of Shanghai. Wet deposition of PAHs was primarily composed of two, three, or four rings, while dry deposition of PAHs was composed of four, five, or six rings. The atmospheric PAHs, composed of four, five, or six rings, primarily existed in the form of particulates. Coal combustion and vehicle emissions were the dominant sources of PAH in the observed area of downtown Shanghai. In suburban areas, industrial pollution, from sources such as coke oven, incinerator, and oil fired power plant, was as significant as vehicle emissions in contributing to the deposition of PAHs.

Analyzing Spatiotemporal Anomalies through Interactive Visualization

Directory of Open Access Journals (Sweden)

Tao Zhang

2014-06-01

Full Text Available As we move into the big data era, data grows not just in size, but also in complexity, containing a rich set of attributes, including location and time information, such as data from mobile devices (e.g., smart phones, natural disasters (e.g., earthquake and hurricane, epidemic spread, etc. We are motivated by the rising challenge and build a visualization tool for exploring generic spatiotemporal data, i.e., records containing time location information and numeric attribute values. Since the values often evolve over time and across geographic regions, we are particularly interested in detecting and analyzing the anomalous changes over time/space. Our analytic tool is based on geographic information system and is combined with spatiotemporal data mining algorithms, as well as various data visualization techniques, such as anomaly grids and anomaly bars superimposed on the map. We study how effective the tool may guide users to find potential anomalies through demonstrating and evaluating over publicly available spatiotemporal datasets. The tool for spatiotemporal anomaly analysis and visualization is useful in many domains, such as security investigation and monitoring, situation awareness, etc.

Unsupervised Learning of Spatiotemporal Features by Video Completion

OpenAIRE

Nallabolu, Adithya Reddy

2017-01-01

In this work, we present an unsupervised representation learning approach for learning rich spatiotemporal features from videos without the supervision from semantic labels. We propose to learn the spatiotemporal features by training a 3D convolutional neural network (CNN) using video completion as a surrogate task. Using a large collection of unlabeled videos, we train the CNN to predict the missing pixels of a spatiotemporal hole given the remaining parts of the video through minimizing per...

Spatiotemporal Co-variability of Surface Climate for Renewable Energy across the Contiguous United States: Role of the North Atlantic Subtropical High

Science.gov (United States)

Doering, K.; Steinschneider, S.

2017-12-01

The variability of renewable energy supply and drivers of demand across space and time largely determines the energy balance within power systems with a high penetration of renewable technologies. This study examines the joint spatiotemporal variability of summertime climate linked to renewable energy production (precipitation, wind speeds, insolation) and energy demand (temperature) across the contiguous United States (CONUS) between 1948 and 2015. Canonical correlation analysis is used to identify the major modes of joint variability between summer wind speeds and precipitation and related patterns of insolation and temperature. Canonical variates are then related to circulation anomalies to identify common drivers of the joint modes of climate variability. Results show that the first two modes of joint variability between summer wind speeds and precipitation exhibit pan-US dipole patterns with centers of action located in the eastern and central CONUS. Temperature and insolation also exhibit related US-wide dipoles. The relationship between canonical variates and lower-tropospheric geopotential height indicates that these modes are related to variability in the North Atlantic subtropical high (NASH). This insight can inform optimal strategies for siting renewables in an interconnected electric grid, and has implications for the impacts of climate variability and change on renewable energy systems.

Comparison of Spatiotemporal Fusion Models: A Review

Directory of Open Access Journals (Sweden)

Bin Chen

2015-02-01

Full Text Available Simultaneously capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Spatiotemporal fusion has gained wide interest in various applications for its superiority in integrating both fine spatial resolution and frequent temporal coverage. Though many advances have been made in spatiotemporal fusion model development and applications in the past decade, a unified comparison among existing fusion models is still limited. In this research, we classify the models into three categories: transformation-based, reconstruction-based, and learning-based models. The objective of this study is to (i compare four fusion models (STARFM, ESTARFM, ISTAFM, and SPSTFM under a one Landsat-MODIS (L-M pair prediction mode and two L-M pair prediction mode using time-series datasets from the Coleambally irrigation area and Poyang Lake wetland; (ii quantitatively assess prediction accuracy considering spatiotemporal comparability, landscape heterogeneity, and model parameter selection; and (iii discuss the advantages and disadvantages of the three categories of spatiotemporal fusion models.

Simultaneous spatio-temporal focusing for tissue manipulation

Directory of Open Access Journals (Sweden)

Squier J.

2013-11-01

Full Text Available Simultaneous spatiotemporal focusing (SSTF is applied to lens tissue and compared directly with standard femtosecond micromachining of the tissue at the same numerical aperture. Third harmonic generation imaging is used for spatio-temporal characterization of the processing conditions obtained with both a standard and SSTF focus.

Spatiotemporal variation of long-term drought propensity through reliability-resilience-vulnerability based Drought Management Index

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Chanda, Kironmala; Maity, Rajib; Sharma, Ashish; Mehrotra, Rajeshwar

2014-10-01

This paper characterizes the long-term, spatiotemporal variation of drought propensity through a newly proposed, namely Drought Management Index (DMI), and explores its predictability in order to assess the future drought propensity and adapt drought management policies for a location. The DMI was developed using the reliability-resilience-vulnerability (RRV) rationale commonly used in water resources systems analysis, under the assumption that depletion of soil moisture across a vertical soil column is equivalent to the operation of a water supply reservoir, and that drought should be managed not simply using a measure of system reliability, but should also take into account the readiness of the system to bounce back from drought to a normal state. Considering India as a test bed, 5 year long monthly gridded (0.5° Lat × 0.5° Lon) soil moisture data are used to compute the RRV at each grid location falling within the study domain. The Permanent Wilting Point (PWP) is used as the threshold, indicative of transition into water stress. The association between resilience and vulnerability is then characterized through their joint probability distribution ascertained using Plackett copula models for four broad soil types across India. The joint cumulative distribution functions (CDF) of resilience and vulnerability form the basis for estimating the DMI as a five-yearly time series at each grid location assessed. The status of DMI over the past 50 years indicate that drought propensity is consistently low toward northern and north eastern parts of India but higher in the western part of peninsular India. Based on the observed past behavior of DMI series on a climatological time scale, a DMI prediction model comprising deterministic and stochastic components is developed. The predictability of DMI for a lead time of 5 years is found to vary across India, with a Pearson correlation coefficient between observed and predicted DMI above 0.6 over most of the study area

Integrating GIS and ABM to Explore Spatiotemporal Dynamics

Science.gov (United States)

Sun, M.; Jiang, Y.; Yang, C.

2013-12-01

Agent-based modeling as a methodology for the bottom-up exploration with the account of adaptive behavior and heterogeneity of system components can help discover the development and pattern of the complex social and environmental system. However, ABM is a computationally intensive process especially when the number of system components becomes large and the agent-agent/agent-environmental interaction is modeled very complex. Most of traditional ABM frameworks developed based on CPU do not have a satisfying computing capacity. To address the problem and as the emergence of advanced techniques, GPU computing with CUDA can provide powerful parallel structure to enable the complex simulation of spatiotemporal dynamics. In this study, we first develop a GPU-based ABM system. Secondly, in order to visualize the dynamics generated from the movement of agent and the change of agent/environmental attributes during the simulation, we integrate GIS into the ABM system. Advanced geovisualization technologies can be utilized for representing the spatiotemporal change events, such as proper 2D/3D maps with state-of-the-art symbols, space-time cube and multiple layers each of which presents pattern in one time-stamp, etc. Thirdly, visual analytics which include interactive tools (e.g. grouping, filtering, linking, etc.) is included in our ABM-GIS system to help users conduct real-time data exploration during the progress of simulation. Analysis like flow analysis and spatial cluster analysis can be integrated according to the geographical problem we want to explore.

Placing invasive species management in a spatiotemporal context.

Science.gov (United States)

Baker, Christopher M; Bode, Michael

2016-04-01

Invasive species are a worldwide issue, both ecologically and economically. A large body of work focuses on various aspects of invasive species control, including how to allocate control efforts to eradicate an invasive population as cost effectively as possible: There are a diverse range of invasive species management problems, and past mathematical analyses generally focus on isolated examples, making it hard to identify and understand parallels between the different contexts. In this study, we use a single spatiotemporal model to tackle the problem of allocating control effort for invasive species when suppressing an island invasive species, and for long-term spatial suppression projects. Using feral cat suppression as an illustrative example, we identify the optimal resource allocation for island and mainland suppression projects. Our results demonstrate how using a single model to solve different problems reveals similar characteristics of the solutions in different scenarios. As well as illustrating the insights offered by linking problems through a spatiotemporal model, we also derive novel and practically applicable results for our case studies. For temporal suppression projects on islands, we find that lengthy projects are more cost effective and that rapid control projects are only economically cost effective when population growth rates are high or diminishing returns on control effort are low. When suppressing invasive species around conservation assets (e.g., national parks or exclusion fences), we find that the size of buffer zones should depend on the ratio of the species growth and spread rate.

Calibration of a parsimonious distributed ecohydrological daily model in a data-scarce basin by exclusively using the spatio-temporal variation of NDVI

Science.gov (United States)

Ruiz-Pérez, Guiomar; Koch, Julian; Manfreda, Salvatore; Caylor, Kelly; Francés, Félix

2017-12-01

Ecohydrological modeling studies in developing countries, such as sub-Saharan Africa, often face the problem of extensive parametrical requirements and limited available data. Satellite remote sensing data may be able to fill this gap, but require novel methodologies to exploit their spatio-temporal information that could potentially be incorporated into model calibration and validation frameworks. The present study tackles this problem by suggesting an automatic calibration procedure, based on the empirical orthogonal function, for distributed ecohydrological daily models. The procedure is tested with the support of remote sensing data in a data-scarce environment - the upper Ewaso Ngiro river basin in Kenya. In the present application, the TETIS-VEG model is calibrated using only NDVI (Normalized Difference Vegetation Index) data derived from MODIS. The results demonstrate that (1) satellite data of vegetation dynamics can be used to calibrate and validate ecohydrological models in water-controlled and data-scarce regions, (2) the model calibrated using only satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet and (3) the proposed automatic calibration methodology works satisfactorily and it allows for a straightforward incorporation of spatio-temporal data into the calibration and validation framework of a model.

Decoding spatiotemporal spike sequences via the finite state automata dynamics of spiking neural networks

International Nuclear Information System (INIS)

Jin, Dezhe Z

2008-01-01

Temporally complex stimuli are encoded into spatiotemporal spike sequences of neurons in many sensory areas. Here, we describe how downstream neurons with dendritic bistable plateau potentials can be connected to decode such spike sequences. Driven by feedforward inputs from the sensory neurons and controlled by feedforward inhibition and lateral excitation, the neurons transit between UP and DOWN states of the membrane potentials. The neurons spike only in the UP states. A decoding neuron spikes at the end of an input to signal the recognition of specific spike sequences. The transition dynamics is equivalent to that of a finite state automaton. A connection rule for the networks guarantees that any finite state automaton can be mapped into the transition dynamics, demonstrating the equivalence in computational power between the networks and finite state automata. The decoding mechanism is capable of recognizing an arbitrary number of spatiotemporal spike sequences, and is insensitive to the variations of the spike timings in the sequences

Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs.

Science.gov (United States)

Gu, Qing; Wang, Ke; Li, Jiadan; Ma, Ligang; Deng, Jinsong; Zheng, Kefeng; Zhang, Xiaobin; Sheng, Li

2015-10-20

It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006-2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.

Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs

Directory of Open Access Journals (Sweden)

Qing Gu

2015-10-01

Full Text Available It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006–2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes. According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.

Quantile-based Bayesian maximum entropy approach for spatiotemporal modeling of ambient air quality levels.

Science.gov (United States)

Yu, Hwa-Lung; Wang, Chih-Hsin

2013-02-05

Understanding the daily changes in ambient air quality concentrations is important to the assessing human exposure and environmental health. However, the fine temporal scales (e.g., hourly) involved in this assessment often lead to high variability in air quality concentrations. This is because of the complex short-term physical and chemical mechanisms among the pollutants. Consequently, high heterogeneity is usually present in not only the averaged pollution levels, but also the intraday variance levels of the daily observations of ambient concentration across space and time. This characteristic decreases the estimation performance of common techniques. This study proposes a novel quantile-based Bayesian maximum entropy (QBME) method to account for the nonstationary and nonhomogeneous characteristics of ambient air pollution dynamics. The QBME method characterizes the spatiotemporal dependence among the ambient air quality levels based on their location-specific quantiles and accounts for spatiotemporal variations using a local weighted smoothing technique. The epistemic framework of the QBME method can allow researchers to further consider the uncertainty of space-time observations. This study presents the spatiotemporal modeling of daily CO and PM10 concentrations across Taiwan from 1998 to 2009 using the QBME method. Results show that the QBME method can effectively improve estimation accuracy in terms of lower mean absolute errors and standard deviations over space and time, especially for pollutants with strong nonhomogeneous variances across space. In addition, the epistemic framework can allow researchers to assimilate the site-specific secondary information where the observations are absent because of the common preferential sampling issues of environmental data. The proposed QBME method provides a practical and powerful framework for the spatiotemporal modeling of ambient pollutants.

Spatiotemporal evolution of the completeness magnitude of the Icelandic earthquake catalogue from 1991 to 2013

Science.gov (United States)

Panzera, Francesco; Mignan, Arnaud; Vogfjörð, Kristin S.

2017-07-01

In 1991, a digital seismic monitoring network was installed in Iceland with a digital seismic system and automatic operation. After 20 years of operation, we explore for the first time its nationwide performance by analysing the spatiotemporal variations of the completeness magnitude. We use the Bayesian magnitude of completeness (BMC) method that combines local completeness magnitude observations with prior information based on the density of seismic stations. Additionally, we test the impact of earthquake location uncertainties on the BMC results, by filtering the catalogue using a multivariate analysis that identifies outliers in the hypocentre error distribution. We find that the entire North-to-South active rift zone shows a relatively low magnitude of completeness Mc in the range 0.5-1.0, highlighting the ability of the Icelandic network to detect small earthquakes. This work also demonstrates the influence of earthquake location uncertainties on the spatiotemporal magnitude of completeness analysis.

The investigation of spatiotemporal variations of land surface temperature based on land use changes using NDVI in southwest of Iran

Science.gov (United States)

Fathizad, Hassan; Tazeh, Mahdi; Kalantari, Saeideh; Shojaei, Saeed

2017-10-01

Land use changes can bring about changes in land surface temperature (LST) which is influenced by climatic conditions and physical characteristics of the land surface. In this study, spatiotemporal variations of land surface temperature have been investigated in the desert area of Dasht-e-Abbas, Ilam, based on a variety of land use changes. The investigated periods for the study include 1990, 2000 and 2010 using Landsat image data. First, in mapping land use we used the Fuzzy ARTMAP Neural Network Classification method followed by determination of the NDVI Index to estimate land surface temperature. The results show an increase in LST in areas where degradation, land use and land cover changes have occurred. In 1990, 2000 and 2010, the average land surface temperature of the Fair Rangelands was 26.72 °C, 30.06 °C and 30.95 °C, respectively. This rangeland has been reduced by about 5%. For poor rangelands, the average LSTs were 26.95, 32.83 and 34.49 Cº, respectively which had a 18% reduction. In 1990, 2000 and 2010, the average land surface temperatures of agricultural lands were 24.31 °C, 27.87 °C and 28.61 °C, respectively which has been an increasing trend. The reason can be attributed to changes in cropping patterns of the study area.

Spatiotemporal Variation and Abrupt Change Analysis of Temperature from 1960 to 2012 in the Huang-Huai-Hai Plain, China

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Yanyu Yin

2015-01-01

Full Text Available Based on a monthly dataset of temperature time series (1960–2012 in the Huang-Huai-Hai Plain of China (HHHPC, spatiotemporal variation and abrupt change analysis of temperature were examined by moving average, linear regression, spline interpolation, Mann-Kendall test, and moving t-test. Major conclusions were listed as follows. (1 Annual and seasonal temperature increased with different rates on the process of fluctuating changes during 1960~2012. The upward trend was 0.22°C 10a−1 for annual temperature, while it was very significant in winter (0.34°C 10a−1 and spring (0.31°C 10a−1, moderately significant in autumn (0.21°C 10a−1, and nonsignificant in summer (0.05°C 10a−1. (2 The spatial changes of annual and seasonal temperature were similar. The temperature increased significantly in Beijing and its adjacent regions, while it was nonsignificant in the central and southern regions. (3 The spring, autumn, winter, and annual temperature had warm abrupt change. The abrupt change time for winter temperature was in the late 1970s, while it was in the late 1980s and early 1990s for spring, autumn, and annual temperature. (4 Macroscopic effects of global and regional climate warming and human activities were probably responsible for the temperature changes. The climate warming would influence the hydrological cycle and agricultural crops in the study area.

Visualization and assessment of spatio-temporal covariance properties

KAUST Repository

Huang, Huang

2017-11-23

Spatio-temporal covariances are important for describing the spatio-temporal variability of underlying random fields in geostatistical data. For second-order stationary random fields, there exist subclasses of covariance functions that assume a simpler spatio-temporal dependence structure with separability and full symmetry. However, it is challenging to visualize and assess separability and full symmetry from spatio-temporal observations. In this work, we propose a functional data analysis approach that constructs test functions using the cross-covariances from time series observed at each pair of spatial locations. These test functions of temporal lags summarize the properties of separability or symmetry for the given spatial pairs. We use functional boxplots to visualize the functional median and the variability of the test functions, where the extent of departure from zero at all temporal lags indicates the degree of non-separability or asymmetry. We also develop a rank-based nonparametric testing procedure for assessing the significance of the non-separability or asymmetry. Essentially, the proposed methods only require the analysis of temporal covariance functions. Thus, a major advantage over existing approaches is that there is no need to estimate any covariance matrix for selected spatio-temporal lags. The performances of the proposed methods are examined by simulations with various commonly used spatio-temporal covariance models. To illustrate our methods in practical applications, we apply it to real datasets, including weather station data and climate model outputs.

Dynamic decomposition of spatiotemporal neural signals.

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Luca Ambrogioni

2017-05-01

Full Text Available Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals.

Assessment of spatio-temporal variations in surface water quality of ...

African Journals Online (AJOL)

MANN

2012-10-02

Oct 2, 2012 ... 1School of Biological and Environmental Sciences, Shoolini University, Solan, H.P.- 173229, India. 2Department ... variation. Of late, multivariate statistical techniques such ..... Statistical Package for the Social Sciences 10.0.

Spatio-temporal variation in age structure and abundance of the endangered snail kite: Pooling across regions masks a declining and aging population

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Reichert, Brian E.; Kendall, William L.; Fletcher, Robert J.; Kitchens, Wiley M.

2016-01-01

While variation in age structure over time and space has long been considered important for population dynamics and conservation, reliable estimates of such spatio-temporal variation in age structure have been elusive for wild vertebrate populations. This limitation has arisen because of problems of imperfect detection, the potential for temporary emigration impacting assessments of age structure, and limited information on age. However, identifying patterns in age structure is important for making reliable predictions of both short- and long-term dynamics of populations of conservation concern. Using a multistate superpopulation estimator, we estimated region-specific abundance and age structure (the proportion of individuals within each age class) of a highly endangered population of snail kites for two separate regions in Florida over 17 years (1997–2013). We find that in the southern region of the snail kite—a region known to be critical for the long-term persistence of the species—the population has declined significantly since 1997, and during this time, it has increasingly become dominated by older snail kites (> 12 years old). In contrast, in the northern region—a region historically thought to serve primarily as drought refugia—the population has increased significantly since 2007 and age structure is more evenly distributed among age classes. Given that snail kites show senescence at approximately 13 years of age, where individuals suffer higher mortality rates and lower breeding rates, these results reveal an alarming trend for the southern region. Our work illustrates the importance of accounting for spatial structure when assessing changes in abundance and age distribution and the need for monitoring of age structure in imperiled species.

Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures

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Deilami, Kaveh; Kamruzzaman, Md.; Liu, Yan

2018-05-01

Despite research on urban heat island (UHI) effect has increased exponentially over the last few decades, a systematic review of factors contributing to UHI effect has scarcely been reported in the literature. This paper provides a systematic and overarching review of different spatial and temporal factors affecting the UHI effect. UHI is a phenomenon when urban areas experience a higher temperature than their surrounding non-urban areas and is considered as a critical factor contributing to global warming, heat related mortalities, and unpredictable climatic changes. Therefore, there is a pressing need to identify the spatio-temporal factors that contribute to (or mitigate) the UHI effect in order to develop a thorough understanding of their causal mechanism so that these are addressed through urban planning policies. This paper systematically identified 75 eligible studies on UHI effect and reviews the nature and type of satellite images used, the techniques applied to classify land cover/use changes, the models to assess the link between spatio-temporal factors and UHI effect, and the effects of these factors on UHI. The review results show that: a) 54% of the studies used Landsat TM images for modelling the UHI effect followed by Landsat ETM (34%), and MODIS (28%); b) land cover indices (46%), followed by supervised classification (17%) were the dominant methods to derive land cover/use changes associated with UHI effect; c) ordinary least square regression is the most commonly applied method (68%) to investigate the link between different spatio-temporal factors and the UHI effect followed by comparative analysis (33%); and d) the most common factors affecting the UHI effect as reported in the reviewed studies, include vegetation cover (44%), season (33%), built-up area (28%), day/night (25%), population density (14%), water body (12%) together with others. This research discusses the findings in policy terms and provides directions for future research.

Modelling daily PM2.5 concentrations at high spatio-temporal resolution across Switzerland.

Science.gov (United States)

de Hoogh, Kees; Héritier, Harris; Stafoggia, Massimo; Künzli, Nino; Kloog, Itai

2018-02-01

Spatiotemporal resolved models were developed predicting daily fine particulate matter (PM 2.5 ) concentrations across Switzerland from 2003 to 2013. Relatively sparse PM 2.5 monitoring data was supplemented by imputing PM 2.5 concentrations at PM 10 sites, using PM 2.5 /PM 10 ratios at co-located sites. Daily PM 2.5 concentrations were first estimated at a 1 × 1km resolution across Switzerland, using Multiangle Implementation of Atmospheric Correction (MAIAC) spectral aerosol optical depth (AOD) data in combination with spatiotemporal predictor data in a four stage approach. Mixed effect models (1) were used to predict PM 2.5 in cells with AOD but without PM 2.5 measurements (2). A generalized additive mixed model with spatial smoothing was applied to generate grid cell predictions for those grid cells where AOD was missing (3). Finally, local PM 2.5 predictions were estimated at each monitoring site by regressing the residuals from the 1 × 1km estimate against local spatial and temporal variables using machine learning techniques (4) and adding them to the stage 3 global estimates. The global (1 km) and local (100 m) models explained on average 73% of the total,71% of the spatial and 75% of the temporal variation (all cross validated) globally and on average 89% (total) 95% (spatial) and 88% (temporal) of the variation locally in measured PM 2.5 concentrations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Controlling spatiotemporal chaos in one- and two-dimensional coupled logistic map lattices

International Nuclear Information System (INIS)

Astakhov, V.V.; Anishchenko, V.S.; Strelkova, G.I.; Shabunin, A.V.

1996-01-01

A method of control of spatiotemporal chaos in lattices of coupled maps is proposed in this work. Forms of spatiotemporal perturbations of a system parameter are analytically determined for one- and two-dimensional logistic map lattices with different kinds of coupling to stabilize chosen spatiotemporal states previously unstable. The results are illustrated by numerical simulation. Controlled transition from the regime of spatiotemporal chaos to the previously chosen regular spatiotemporal patterns is demonstrated. copyright 1996 American Institute of Physics

Non parametric, self organizing, scalable modeling of spatiotemporal inputs: the sign language paradigm.

Science.gov (United States)

Caridakis, G; Karpouzis, K; Drosopoulos, A; Kollias, S

2012-12-01

Modeling and recognizing spatiotemporal, as opposed to static input, is a challenging task since it incorporates input dynamics as part of the problem. The vast majority of existing methods tackle the problem as an extension of the static counterpart, using dynamics, such as input derivatives, at feature level and adopting artificial intelligence and machine learning techniques originally designed for solving problems that do not specifically address the temporal aspect. The proposed approach deals with temporal and spatial aspects of the spatiotemporal domain in a discriminative as well as coupling manner. Self Organizing Maps (SOM) model the spatial aspect of the problem and Markov models its temporal counterpart. Incorporation of adjacency, both in training and classification, enhances the overall architecture with robustness and adaptability. The proposed scheme is validated both theoretically, through an error propagation study, and experimentally, on the recognition of individual signs, performed by different, native Greek Sign Language users. Results illustrate the architecture's superiority when compared to Hidden Markov Model techniques and variations both in terms of classification performance and computational cost. Copyright © 2012 Elsevier Ltd. All rights reserved.

Bayesian spatio-temporal modelling of tobacco-related cancer mortality in Switzerland

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Verena Jürgens

2013-05-01

Full Text Available Tobacco smoking is a main cause of disease in Switzerland; lung cancer being the most common cancer mortality in men and the second most common in women. Although disease-specific mortality is decreasing in men, it is steadily increasing in women. The four language regions in this country might play a role in this context as they are influenced in different ways by the cultural and social behaviour of neighbouring countries. Bayesian hierarchical spatio-temporal, negative binomial models were fitted on subgroup-specific death rates indirectly standardized by national references to explore age- and gender-specific spatio-temporal patterns of mortality due to lung cancer and other tobacco-related cancers in Switzerland for the time period 1969-2002. Differences influenced by linguistic region and life in rural or urban areas were also accounted for. Male lung cancer mortality was found to be rather homogeneous in space, whereas women were confirmed to be more affected in urban regions. Compared to the German-speaking part, female mortality was higher in the French-speaking part of the country, a result contradicting other reports of similar comparisons between France and Germany. The spatio-temporal patterns of mortality were similar for lung cancer and other tobacco-related cancers. The estimated mortality maps can support the planning in health care services and evaluation of a national tobacco control programme. Better understanding of spatial and temporal variation of cancer of the lung and other tobacco-related cancers may help in allocating resources for more effective screening, diagnosis and therapy. The methodology can be applied to similar studies in other settings.

Spatiotemporal patterns formed by deformed adhesive in peeling

International Nuclear Information System (INIS)

Yamazaki, Yoshihiro; Toda, Akihiko

2007-01-01

Dynamical properties of peeling an adhesive tape are investigated experimentally as an analogy of sliding friction. An adhesive tape is peeled by pulling an elastic spring connected to the tape. Controlling its spring constant k and pulling speed V, peel force is measured and spatiotemporal patterns formed on the peeled tape by deformed adhesive are observed. It is found that there exist two kinds of adhesive state in peeling front. The emergence of multiple states is caused by the stability of a characteristic structure (tunnel structure) formed by deformed adhesive. Tunnel structures are distributed spatiotemporally on adhesive tape after peeling. Based on the spatiotemporal distribution, a morphology-dynamical phase diagram is constructed on k-V space and is divided into the four regions: (A) uniform pattern with tunnel structure, (B) uniform pattern without tunnel structure, (C) striped pattern with oscillatory peeling, and (D) spatiotemporally coexistent pattern

Mortality from Suicide in the Municipalities of Mainland Portugal: Spatio-Temporal Evolution between 1980 and 2015

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Adriana Loureiro

2018-01-01

Full Text Available Introduction: Suicide is considered a public health priority. It is a complex phenomenon resulting from the interaction of several factors, which do not depend solely on individual conditions. This study analyzes the spatio-temporal evolution of suicide mortality between 1980 and 2015, identifying areas of high risk, and their variation, in the 278 municipalities of Continental Portugal. Material and Methods: Based on the number of self-inflicted injuries and deaths from suicide and the resident population, the spatio-temporal evolution of the suicide mortality rate was assessed via: i a Poisson joinpoint regression model, and ii spatio-temporal clustering methods. Results: The suicide mortality rate evolution showed statistically significant increases over three periods (1980 - 1984; 1999 - 2002 and 2006 - 2015 and two statistically significant periods of decrease (1984 - 1995 and 1995 - 1999. The spatio-temporal analysis identified five clusters of high suicide risk (relative risk >1 and four clusters of low suicide risk (relative risk < 1. Discussion: The periods when suicide mortality increases seem to overlap with times of economic and financial instability. The geographical pattern of suicide risk has changed: presently, the suicide rates from the municipalities in the Center and North are showing more similarity with those seen in the South, thus increasing the ruralization of the phenomenon of suicide. Conclusion: Between 1980 and 2015 the spacio-temporal pattern of mortality from suicide has been changing and is a phenomenon that is currently experiencing a growing trend (since 2006 and is of higher risk in rural areas.

Spatio-Temporal Multiway Data Decomposition Using Principal Tensor Analysis on k-Modes: The R Package PTAk

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Didier G. Leibovici

2010-10-01

Full Text Available The purpose of this paper is to describe the R package {PTAk and how the spatio-temporal context can be taken into account in the analyses. Essentially PTAk( is a multiway multidimensional method to decompose a multi-entries data-array, seen mathematically as a tensor of any order. This PTAk-modes method proposes a way of generalizing SVD (singular value decomposition, as well as some other well known methods included in the R package, such as PARAFAC or CANDECOMP and the PCAn-modes or Tucker-n model. The example datasets cover different domains with various spatio-temporal characteristics and issues: (i~medical imaging in neuropsychology with a functional MRI (magnetic resonance imaging study, (ii~pharmaceutical research with a pharmacodynamic study with EEG (electro-encephaloegraphic data for a central nervous system (CNS drug, and (iii~geographical information system (GIS with a climatic dataset that characterizes arid and semi-arid variations. All the methods implemented in the R package PTAk also support non-identity metrics, as well as penalizations during the optimization process. As a result of these flexibilities, together with pre-processing facilities, PTAk constitutes a framework for devising extensions of multidimensional methods such ascorrespondence analysis, discriminant analysis, and multidimensional scaling, also enabling spatio-temporal constraints.

Spatiotemporal Variation and the Role of Wildlife in Seasonal Water Quality Declines in the Chobe River, Botswana.

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J Tyler Fox

Full Text Available Sustainable management of dryland river systems is often complicated by extreme variability of precipitation in time and space, especially across large catchment areas. Understanding regional water quality changes in southern African dryland rivers and wetland systems is especially important because of their high subsistence value and provision of ecosystem services essential to both public and animal health. We quantified seasonal variation of Escherichia coli (E. coli and Total Suspended Solids (TSS in the Chobe River using spatiotemporal and geostatistical modeling of water quality time series data collected along a transect spanning a mosaic of protected, urban, and developing urban land use. We found significant relationships in the dry season between E. coli concentrations and protected land use (p = 0.0009, floodplain habitat (p = 0.016, and fecal counts from elephant (p = 0.017 and other wildlife (p = 0.001. Dry season fecal loading by both elephant (p = 0.029 and other wildlife (p = 0.006 was also an important predictor of early wet season E. coli concentrations. Locations of high E. coli concentrations likewise showed close spatial agreement with estimates of wildlife biomass derived from aerial survey data. In contrast to the dry season, wet season bacterial water quality patterns were associated only with TSS (p<0.0001, suggesting storm water and sediment runoff significantly influence E. coli loads. Our data suggest that wildlife populations, and elephants in particular, can significantly modify river water quality patterns. Loss of habitat and limitation of wildlife access to perennial rivers and floodplains in water-restricted regions may increase the impact of species on surface water resources. Our findings have important implications to land use planning in southern Africa's dryland river ecosystems.

Spatiotemporal phenological changes in fall foliage peak coloration in deciduous forest and the responses to climatic variation

Science.gov (United States)

Xie, Y.; Wilson, A. M.

2017-12-01

Plant phenology studies typically focus on the beginning and end of the growing season in temperate forests. We know too little about fall foliage peak coloration, which is a bioindicator of plant response in autumn to environmental changes, an important visual cue in fall associated with animal activities, and a key element in fall foliage ecotourism. Spatiotemporal changes in timing of fall foliage peak coloration of temperate forests and the associated environmental controls are not well understood. In this study, we examined multiple color indices to estimate Land Surface Phenology (LSP) of fall foliage peak coloration of deciduous forest in the northeastern USA using Moderate Resolution Imaging Spectroradiometer (MODIS) daily imagery from 2000 to 2015. We used long term phenology ground observations to validate our estimated LSP, and found that Visible Atmospherically Resistant Index (VARI) and Plant Senescence Reflectance Index (PSRI) were good metrics to estimate peak and end of leaf coloration period of deciduous forest. During the past 16 years, the length of period with peak fall foliage color of deciduous forest at southern New England and northern Appalachian forests regions became longer (0.3 7.7 days), mainly driven by earlier peak coloration. Northern New England, southern Appalachian forests and Ozark and Ouachita mountains areas had shorter period (‒0.2 ‒9.2 days) mainly due to earlier end of leaf coloration. Changes in peak and end of leaf coloration not only were associated with changing temperature in spring and fall, but also to drought and heat in summer, and heavy precipitation in both summer and fall. The associations between leaf peak coloration phenology and climatic variations were not consistent among ecoregions. Our findings suggested divergent change patterns in fall foliage peak coloration phenology in deciduous forests, and improved our understanding in the environmental control on timing of fall foliage color change.

A hybrid spatio-temporal data indexing method for trajectory databases.

Science.gov (United States)

Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

2014-07-21

In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.

A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

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Shengnan Ke

2014-07-01

Full Text Available In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.

A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

Science.gov (United States)

Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

2014-01-01

In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type. PMID:25051028

Detecting spatiotemporal clusters of accidental poisoning mortality among Texas counties, U.S., 1980 – 2001

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Harris Ann

2004-10-01

Full Text Available Abstract Background Accidental poisoning is one of the leading causes of injury in the United States, second only to motor vehicle accidents. According to the Centers for Disease Control and Prevention, the rates of accidental poisoning mortality have been increasing in the past fourteen years nationally. In Texas, mortality rates from accidental poisoning have mirrored national trends, increasing linearly from 1981 to 2001. The purpose of this study was to determine if there are spatiotemporal clusters of accidental poisoning mortality among Texas counties, and if so, whether there are variations in clustering and risk according to gender and race/ethnicity. The Spatial Scan Statistic in combination with GIS software was used to identify potential clusters between 1980 and 2001 among Texas counties, and Poisson regression was used to evaluate risk differences. Results Several significant (p Conclusion The findings of the present study provide evidence for the existence of accidental poisoning mortality clusters in Texas, demonstrate the persistence of these clusters into the present decade, and show the spatiotemporal variations in risk and clustering of accidental poisoning deaths by gender and race/ethnicity. By quantifying disparities in accidental poisoning mortality by place, time and person, this study demonstrates the utility of the spatial scan statistic combined with GIS and regression methods in identifying priority areas for public health planning and resource allocation.

Regionalised spatiotemporal rainfall and temperature models for flood studies in the Basque Country, Spain

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P. Cowpertwait

2013-02-01

Full Text Available A spatiotemporal point process model of rainfall is fitted to data taken from three homogeneous regions in the Basque Country, Spain. The model is the superposition of two spatiotemporal Neyman–Scott processes, in which rain cells are modelled as discs with radii that follow exponential distributions. In addition, the model includes a parameter for the radius of storm discs, so that rain only occurs when both a cell and a storm disc overlap a point. The model is fitted to data for each month, taken from each of the three homogeneous regions, using a modified method of moments procedure that ensures a smooth seasonal variation in the parameter estimates.

Daily temperature data from 23 sites are used to fit a stochastic temperature model. A principal component analysis of the maximum daily temperatures across the sites indicates that 92% of the variance is explained by the first component, implying that this component can be used to account for spatial variation. A harmonic equation with autoregressive error terms is fitted to the first principal component. The temperature model is obtained by regressing the maximum daily temperature on the first principal component, an indicator variable for the region, and altitude. This, together with scaling and a regression model of temperature range, enables hourly temperatures to be predicted. Rainfall is included as an explanatory variable but has only a marginal influence when predicting temperatures.

A distributed model (TETIS; Francés et al., 2007 is calibrated for a selected catchment. Five hundred years of data are simulated using the rainfall and temperature models and used as input to the calibrated TETIS model to obtain simulated discharges to compare with observed discharges. Kolmogorov–Smirnov tests indicate that there is no significant difference in the distributions of observed and simulated maximum flows at the same sites, thus supporting the use of the spatiotemporal

Spatio-Temporal Variability of the Phase of Total Ozone Quasi-Decennial Oscillations

Science.gov (United States)

Visheratin, K. N.

2017-12-01

The SBUV/SBUV2 (65° S-65° N) and Bodeker Scientific (90° S-90° N) satellite databases have been used for composite and cross-wavelet analyses of the spatio-temporal variability of phase relations between a 11-year cycle of solar activity (SA) and quasi-decennial oscillations (QDOs) of total ozone content (TOC). For globally average TOC values, the QDO maxima coincide in phase with the solar-activity maxima, and amplitude variations of TOC correlate with those of the 11-year solar cycle. According to the analysis of amplitude and phase of QDOs for the zonal average TOC fields, a QDO amplitude is about 6-7 Dobson Units (DU) in the high northern and southern latitudes, and it does not exceed 2-3 DU in the tropic regions. The latitudinal TOC variations are distinguished by a delay of the quasi-decennial oscillation phase in the southern latitudes in comparison with the northern latitudes. The TOC maxima phase coincides with the SA maxima phase in the tropic regions; the TOC variations go ahead of the SA variations, on average, in moderate and high latitudes of the Northern Hemisphere; the TOC variations are behind the SA variations in the Southern Hemisphere. The phase delay between TOC QDO maxima in the northern and southern latitudes appears to increase in the course of time, and the TOC quasi-decennial variations in the Arctic and Antarctic subpolar regions occur approximately in an antiphase over the last two decades.

Speed, speed variation and crash relationships for urban arterials.

Science.gov (United States)

Wang, Xuesong; Zhou, Qingya; Quddus, Mohammed; Fan, Tianxiang; Fang, Shou'en

2018-04-01

Speed and speed variation are closely associated with traffic safety. There is, however, a dearth of research on this subject for the case of urban arterials in general, and in the context of developing nations. In downtown Shanghai, the traffic conditions in each direction are very different by time of day, and speed characteristics during peak hours are also greatly different from those during off-peak hours. Considering that traffic demand changes with time and in different directions, arterials in this study were divided into one-way segments by the direction of flow, and time of day was differentiated and controlled for. In terms of data collection, traditional fixed-based methods have been widely used in previous studies, but they fail to capture the spatio-temporal distributions of speed along a road. A new approach is introduced to estimate speed variation by integrating spatio-temporal speed fluctuation of a single vehicle with speed differences between vehicles using taxi-based high frequency GPS data. With this approach, this paper aims to comprehensively establish a relationship between mean speed, speed variation and traffic crashes for the purpose of formulating effective speed management measures, specifically using an urban dataset. From a total of 234 one-way road segments from eight arterials in Shanghai, mean speed, speed variation, geometric design features, traffic volume, and crash data were collected. Because the safety effects of mean speed and speed variation may vary at different segment lengths, arterials with similar signal spacing density were grouped together. To account for potential correlations among these segments, a hierarchical Poisson log-normal model with random effects was developed. Results show that a 1% increase in mean speed on urban arterials was associated with a 0.7% increase in total crashes, and larger speed variation was also associated with increased crash frequency. Copyright © 2018 Elsevier Ltd. All rights

Spatiotemporal representation of cardiac vectorcardiogram (VCG signals

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Yang Hui

2012-03-01

Full Text Available Abstract Background Vectorcardiogram (VCG signals monitor both spatial and temporal cardiac electrical activities along three orthogonal planes of the body. However, the absence of spatiotemporal resolution in conventional VCG representations is a major impediment for medical interpretation and clinical usage of VCG. This is especially so because time-domain features of 12-lead ECG, instead of both spatial and temporal characteristics of VCG, are widely used for the automatic assessment of cardiac pathological patterns. Materials and methods We present a novel representation approach that captures critical spatiotemporal heart dynamics by displaying the real time motion of VCG cardiac vectors in a 3D space. Such a dynamic display can also be realized with only one lead ECG signal (e.g., ambulatory ECG through an alternative lag-reconstructed ECG representation from nonlinear dynamics principles. Furthermore, the trajectories are color coded with additional dynamical properties of space-time VCG signals, e.g., the curvature, speed, octant and phase angles to enhance the information visibility. Results In this investigation, spatiotemporal VCG signal representation is used to characterize various spatiotemporal pathological patterns for healthy control (HC, myocardial infarction (MI, atrial fibrillation (AF and bundle branch block (BBB. The proposed color coding scheme revealed that the spatial locations of the peak of T waves are in the Octant 6 for the majority (i.e., 74 out of 80 of healthy recordings in the PhysioNet PTB database. In contrast, the peak of T waves from 31.79% (117/368 of MI subjects are found to remain in Octant 6 and the rest (68.21% spread over all other octants. The spatiotemporal VCG signal representation is shown to capture the same important heart characteristics as the 12-lead ECG plots and more. Conclusions Spatiotemporal VCG signal representation is shown to facilitate the characterization of space-time cardiac

Spatio-temporal variations in biochemical composition, condition index and percentage edibility of the clam, Paphia malabarica (Chemnitz) from estuarine regions of Goa

Digital Repository Service at National Institute of Oceanography (India)

Nagvenkar, S.S.; Jagtap, T.G.

and ambient environmental parameters were also established. Significant (P <0.001) spatio-temporal changes in biochemical composition, CI and PE were noticed. Protein content was higher (15.64-86.79%) round the year, followed by carbohydrate (4...

Spatio-temporal variation in δ13CDIC of a tropical eutrophic estuary (Cochin estuary, India) and adjacent Arabian Sea

Science.gov (United States)

Bhavya, P. S.; Kumar, Sanjeev; Gupta, G. V. M.; Sudharma, K. V.; Sudheesh, V.

2018-02-01

Carbon isotopic composition of dissolved inorganic carbon (δ13CDIC) in the Cochin estuary, a tropical eutrophic estuary along the southwest coast of India, and the adjacent coastal Arabian Sea was measured to understand spatio-temporal variability in sources and processes controlling inorganic carbon (C) dynamics in this estuarine-coastal system. δ13CDIC in the Cochin estuary showed wide variation during three different seasons (premonsoon: - 12.2 to - 3.26‰; monsoon: - 13.6 to - 5.69‰; and postmonsoon: - 6.34 to + 0.79‰). Detailed mixing curve approximation modeling along with relationships of δ13CDIC with dissolved oxygen and nutrients suggest dominant role of freshwater mixing and degassing of CO2 on DIC dynamics during wet seasons (premonsoon and monsoon). Excess CO2 brought in by rivers and in situ production due to respiration in the Cochin estuary result into one of the highest pCO2 observed in estuarine systems, leading to its degassing. During postmonsoon, a relatively dry period with high salinity, calcite precipitation was a major process with calcite saturation index > 1 at few locations. Relatively lower average surface values of δ13CDIC in the coastal Arabian Sea (premonsoon: + 0.95‰; monsoon: + 0.88‰; and postmonsoon: + 0.66‰) compared to the predicted open ocean value along with mixing curve modeling suggest dominance of respiration/organic matter (OM) degradation over primary productivity. Estuarine influence on coastal DIC dynamics was observed in nearshore region ( 10 km), whereas evidence of upwelling was found at farther locations.

Linking Genetic Variation in Adaptive Plant Traits to Climate in Tetraploid and Octoploid Basin Wildrye [Leymus cinereus (Scribn. & Merr.) A. Love] in the Western U.S.

Science.gov (United States)

Johnson, R C; Vance-Borland, Ken

2016-01-01

Few studies have assessed how ploidy type within a species affects genetic variation among populations in relation to source climates. Basin wildrye (Leymus cinereus (Scribn. & Merr.) A. Love) is a large bunchgrass common in the intermountain Western U.S. found in both octoploid and tetraploid types. In common gardens at two sites over two years differences in both ploidy type and genetic variation within ploidy were observed in phenology, morphology, and production traits on 57 octoploid and 52 tetraploid basin wildrye from the intermountain Western U.S. (Ptypes. Still, among populations octoploids often had greater genetic variation for traits and occupied more diverse climates than tetraploids. Genetic variation for both ploidy types was linked to source climates in canonical correlation analysis, with the first two variates explaining 70% of the variation. Regression of those canonical variates with seed source climate variables produced models that explained 64% and 38% of the variation, respectively, and were used to map 15 seed zones covering 673,258 km2. Utilization of these seed zones will help ensure restoration with adaptive seed sources for both ploidy types. The link between genetic traits and seed source climates suggests climate driven natural selection and adaptive evolution in basin wildrye. The more diverse climates occupied by octoploids and higher trait variation suggests a higher capacity for ecological differentiation than tetraploids in the intermountain Western U.S.

Full-Scale Approximations of Spatio-Temporal Covariance Models for Large Datasets

KAUST Repository

Zhang, Bohai

2014-01-01

Various continuously-indexed spatio-temporal process models have been constructed to characterize spatio-temporal dependence structures, but the computational complexity for model fitting and predictions grows in a cubic order with the size of dataset and application of such models is not feasible for large datasets. This article extends the full-scale approximation (FSA) approach by Sang and Huang (2012) to the spatio-temporal context to reduce computational complexity. A reversible jump Markov chain Monte Carlo (RJMCMC) algorithm is proposed to select knots automatically from a discrete set of spatio-temporal points. Our approach is applicable to nonseparable and nonstationary spatio-temporal covariance models. We illustrate the effectiveness of our method through simulation experiments and application to an ozone measurement dataset.

Synthesizing spatiotemporally sparse smartphone sensor data for bridge modal identification

Science.gov (United States)

Ozer, Ekin; Feng, Maria Q.

2016-08-01

Smartphones as vibration measurement instruments form a large-scale, citizen-induced, and mobile wireless sensor network (WSN) for system identification and structural health monitoring (SHM) applications. Crowdsourcing-based SHM is possible with a decentralized system granting citizens with operational responsibility and control. Yet, citizen initiatives introduce device mobility, drastically changing SHM results due to uncertainties in the time and the space domains. This paper proposes a modal identification strategy that fuses spatiotemporally sparse SHM data collected by smartphone-based WSNs. Multichannel data sampled with the time and the space independence is used to compose the modal identification parameters such as frequencies and mode shapes. Structural response time history can be gathered by smartphone accelerometers and converted into Fourier spectra by the processor units. Timestamp, data length, energy to power conversion address temporal variation, whereas spatial uncertainties are reduced by geolocation services or determining node identity via QR code labels. Then, parameters collected from each distributed network component can be extended to global behavior to deduce modal parameters without the need of a centralized and synchronous data acquisition system. The proposed method is tested on a pedestrian bridge and compared with a conventional reference monitoring system. The results show that the spatiotemporally sparse mobile WSN data can be used to infer modal parameters despite non-overlapping sensor operation schedule.

Spatio-temporal variation of precipitation in the Three-River Headwater Region from 1961 to 2010

Institute of Scientific and Technical Information of China (English)

YI Xiangsheng; LI Guosheng; YIN Yanyu

2013-01-01

Based on a monthly dataset of precipitation time series (1961-2010) from 12 meteorological stations across the Three-River Headwater Region (THRHR) of Qinghai Province,China,the spatio-temporal variation and abrupt change analysis of precipitation were examined by using moving average,linear regression,spline interpolation,the Mann-Kendall test and so on.Major conclusions were as follows.(1) The long-term annual and seasonal precipitation in the study area indicated an increasing trend with some oscillations during 1961-2010; however,the summer precipitation in the Lantsang (Lancang) River Headwater Region (LARHR),and the autumn precipitation in the Yangtze River Headwater Region (YERHR) of the THRHR decreased in the same period.(2) The amount of annual precipitation in the THRHR and its three sub-headwater regions was greater in the 1980s and 2000s.The springs were fairly wet after the 1970s,while the summers were relatively wet in the 1960s,1980s and 2000s.In addition,the amount of precipitation in the autumn was greater in the 1970s and 1980s,but it was relatively less for the winter precipitation,except in the 1990s.(3) The normal values of spring,summer,winter and annual precipitation in the THRHR and its three sub-headwater regions all increased,but the normal value of summer precipitation in the LARHR had a negative trend and the normal value of winter precipitation declined in general.(4) The spring and winter precipitation increased in most of the THRHR.The summer,autumn and annual precipitation increased mainly in the marginal area of the west and north and decreased in the regions of Yushu,Zaduo,Jiuzhi and Banma.(5) The spring and winter precipitation in the THRHR and its three sub-headwater regions showed an abrupt change,except for the spring precipitation in the YARHR.The abrupt changes of spring precipitation were mainly in the late 1980s and early 1990s,while the abrupt changes of winter precipitation were primary in the mid-to late 1970s

A hybrid spatiotemporal drought forecasting model for operational use

Science.gov (United States)

Vasiliades, L.; Loukas, A.

2010-09-01

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

A spatiotemporal mixed model to assess the influence of environmental and socioeconomic factors on the incidence of hand, foot and mouth disease

Directory of Open Access Journals (Sweden)

Lianfa Li

2018-02-01

Full Text Available Abstract Background As a common infectious disease, hand, foot and mouth disease (HFMD is affected by multiple environmental and socioeconomic factors, and its pathogenesis is complex. Furthermore, the transmission of HFMD is characterized by strong spatial clustering and autocorrelation, and the classical statistical approach may be biased without consideration of spatial autocorrelation. In this paper, we propose to embed spatial characteristics into a spatiotemporal additive model to improve HFMD incidence assessment. Methods Using incidence data (6439 samples from 137 monitoring district for Shandong Province, China, along with meteorological, environmental and socioeconomic spatial and spatiotemporal covariate data, we proposed a spatiotemporal mixed model to estimate HFMD incidence. Geo-additive regression was used to model the non-linear effects of the covariates on the incidence risk of HFMD in univariate and multivariate models. Furthermore, the spatial effect was constructed to capture spatial autocorrelation at the sub-regional scale, and clusters (hotspots of high risk were generated using spatiotemporal scanning statistics as a predictor. Linear and non-linear effects were compared to illustrate the usefulness of non-linear associations. Patterns of spatial effects and clusters were explored to illustrate the variation of the HFMD incidence across geographical sub-regions. To validate our approach, 10-fold cross-validation was conducted. Results The results showed that there were significant non-linear associations of the temporal index, spatiotemporal meteorological factors and spatial environmental and socioeconomic factors with HFMD incidence. Furthermore, there were strong spatial autocorrelation and clusters for the HFMD incidence. Spatiotemporal meteorological parameters, the normalized difference vegetation index (NDVI, the temporal index, spatiotemporal clustering and spatial effects played important roles as predictors in

Temporal and spatiotemporal variability in comprehensive forearm skin microcirculation assessment during occlusion protocols.

Science.gov (United States)

Strömberg, Tomas; Sjöberg, Folke; Bergstrand, Sara

2017-09-01

Forearm skin hyperemia during release after brachial occlusion has been proposed for evaluating peripheral arterial disease and endothelial dysfunction. We used a novel fiberoptic system integrating Laser Doppler Flowmetry and Diffuse Reflectance Spectroscopy for a comprehensive pointwise model based microcirculation characterization. The aim was to evaluate and compare the temporal and the spatiotemporal variabilities in forearm skin microcirculation parameters (speed resolved perfusion; low speed 10mm/s, and total perfusion (Perf SR, tot ); the concentration and oxygenation of red blood cells, C RBC and S O2 ). Ten healthy subjects underwent arterial and venous forearm occlusions (AO, VO), repeated within one week. The repeatability was calculated as the coefficient of variation (CV) and the agreement as the intra-class correlation coefficient (ICC). The temporal CVs for conventional perfusion, Perf conv , Perf SR, tot , C RBC and S O2 were 14%, 12%, 9% and 9%, respectively, while the ICC were >0.75 (excellent). The perfusion measures generally had a higher spatiotemporal than temporal variability, which was not the case for S O2 and C RBC . The corresponding spatiotemporal CVs were 33%, 32%, 18% and 15%, respectively. During VO, C RBC had a CV0.40 (fair-good), and after release this was the case for C RBC (AO and VO), S O2 (VO) and Perf SR, fair-good agreement were: C RBC during and after release of VO, the Perf SR, value of these parameters in discriminating endothelial function remains to be studied. Copyright © 2017 Elsevier Inc. All rights reserved.

Enzyme-linked immunosorbent assay characterization of Basal variation and heritability of systemic microfibrillar-associated protein 4

DEFF Research Database (Denmark)

Sækmose, Susanne Gjørup; Schlosser, Anders; Holst, René

2013-01-01

Microfibrillar-associated protein 4 (MFAP4) is a systemic biomarker that is significantly elevated in samples from patients suffering from hepatic cirrhosis. The protein is generally localized to elastic fibers and other connective tissue fibers in the extracellular matrix (ECM), and variation...... in systemic MFAP4 (sMFAP4) has the potential to reflect diverse diseases with increased ECM turnover. Here, we aimed to validate an enzyme-linked immunosorbent assay (ELISA) for the measurement of sMFAP4 with an emphasis on the robustness of the assay. Moreover, we aimed to determine confounders influencing...

Spatiotemporal drought forecasting using nonlinear models

Science.gov (United States)

Vasiliades, Lampros; Loukas, Athanasios

2010-05-01

Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with

Spatiotemporal drought variability of the eastern Tibetan Plateau during the last millennium

Science.gov (United States)

Deng, Yang; Gou, Xiaohua; Gao, Linlin; Yang, Meixue; Zhang, Fen

2017-09-01

Tibetan Plateau is the headwater region of many major Asian rivers and very susceptive to climate change. Therefore, knowledge about climate and its spatiotemporal variability in this area is very important for ecological conservation, water resource management and social development. The aim of this study was to reconstruct and analyze the hydroclimate variation on eastern Tibetan Plateau (ETP) over many centuries and explore possible forcing factors on regional hydroclimate variability. We used 118 tree-ring chronologies from ETP to reconstruct the gridded May-July Standardized Precipitation Evapotranspiration Index for the ETP over the last millennium. The reconstruction was developed using an ensemble point-by-point reconstruction method, and a searching region method was used to locate the candidate tree-ring chronologies. The reconstructions have nicely captured the spatial and temporal features of the regional drought variation. The drought variations in south and north of 32.5°N are notably different, which may be related to the divergence influence of North Atlantic Oscillation on the climate systems in the south and north, as well as differences in local climate. Spectral analysis and series comparison suggest that the drought variation in the northeastern Tibetan Plateau has been possibly influenced by solar activity on centurial and longer time scale.

Spatio-temporal scaling of channels in braided streams.

Science.gov (United States)

A.G. Hunt; G.E. Grant; V.K. Gupta

2006-01-01

The spatio-temporal scaling relationship for individual channels in braided streams is shown to be identical to the spatio-temporal scaling associated with constant Froude number, e.g., Fr = l. A means to derive this relationship is developed from a new theory of sediment transport. The mechanism by which the Fr = l condition apparently governs the scaling seems to...

Visual representation of spatiotemporal structure

Science.gov (United States)

Schill, Kerstin; Zetzsche, Christoph; Brauer, Wilfried; Eisenkolb, A.; Musto, A.

1998-07-01

The processing and representation of motion information is addressed from an integrated perspective comprising low- level signal processing properties as well as higher-level cognitive aspects. For the low-level processing of motion information we argue that a fundamental requirement is the existence of a spatio-temporal memory. Its key feature, the provision of an orthogonal relation between external time and its internal representation, is achieved by a mapping of temporal structure into a locally distributed activity distribution accessible in parallel by higher-level processing stages. This leads to a reinterpretation of the classical concept of `iconic memory' and resolves inconsistencies on ultra-short-time processing and visual masking. The spatial-temporal memory is further investigated by experiments on the perception of spatio-temporal patterns. Results on the direction discrimination of motion paths provide evidence that information about direction and location are not processed and represented independent of each other. This suggests a unified representation on an early level, in the sense that motion information is internally available in form of a spatio-temporal compound. For the higher-level representation we have developed a formal framework for the qualitative description of courses of motion that may occur with moving objects.

Observed variations in U.S. frost timing linked to atmospheric circulation patterns.

Science.gov (United States)

Strong, Courtenay; McCabe, Gregory J

2017-05-23

Several studies document lengthening of the frost-free season within the conterminous United States (U.S.) over the past century, and report trends in spring and fall frost timing that could stem from hemispheric warming. In the absence of warming, theory and case studies link anomalous frost timing to atmospheric circulation anomalies. However, recent efforts to relate a century of observed changes in U.S. frost timing to various atmospheric circulations yielded only modest correlations, leaving the relative importance of circulation and warming unclear. Here, we objectively partition the U.S. into four regions and uncover atmospheric circulations that account for 25-48% of spring and fall-frost timing. These circulations appear responsive to historical warming, and they consistently account for more frost timing variability than hemispheric or regional temperature indices. Reliable projections of future variations in growing season length depend on the fidelity of these circulation patterns in global climate models.

Linking canopy reflectance to crop structure and photosynthesis to capture and interpret spatiotemporal dimensions of per-field photosynthetic productivity

Science.gov (United States)

Xue, Wei; Jeong, Seungtaek; Ko, Jonghan; Tenhunen, John

2017-03-01

Nitrogen and water availability alter canopy structure and physiology, and thus crop growth, yielding large impacts on ecosystem-regulating/production provisions. However, to date, explicitly quantifying such impacts remains challenging partially due to lack of adequate methodology to capture spatial dimensions of ecosystem changes associated with nitrogen and water effects. A data fitting, where close-range remote-sensing measurements of vegetation indices derived from a handheld instrument and an unmanned aerial vehicle (UAV) system are linked to in situ leaf and canopy photosynthetic traits, was applied to capture and interpret inter- and intra-field variations in gross primary productivity (GPP) in lowland rice grown under flooded conditions (paddy rice, PD) subject to three nitrogen application rates and under rainfed conditions (RF) in an East Asian monsoon region of South Korea. Spatial variations (SVs) in both GPP and light use efficiency (LUEcabs) early in the growing season were enlarged by nitrogen addition. The nutritional effects narrowed over time. A shift in planting culture from flooded to rainfed conditions strengthened SVs in GPP and LUEcabs. Intervention of prolonged drought late in the growing season dramatically intensified SVs that were supposed to seasonally decrease. Nevertheless, nitrogen addition effects on SV of LUEcabs at the early growth stage made PD fields exert greater SVs than RF fields. SVs of GPP across PD and RF rice fields were likely related to leaf area index (LAI) development less than to LUEcabs, while numerical analysis suggested that considering strength in LUEcabs and its spatial variation for the same crop type tends to be vital for better evaluation in landscape/regional patterns of ecosystem photosynthetic productivity at critical phenology stages.

Spatiotemporal variation of crown-scale stomatal conductance in an arid Vitis vinifera L. cv. Merlot vineyard: direct effects of hydraulic properties and indirect effects of canopy leaf area.

Science.gov (United States)

Zhang, Yanqun; Oren, Ram; Kang, Shaozhong

2012-03-01

Vineyards were planted in the arid region of northwest China to meet the local economic strategy while reducing agricultural water use. Sap flow, environmental variables, a plant characteristic (sapwood-to-leaf area ratio, A(s)/A(l)) and a canopy characteristic (leaf area index, L) were measured in a vineyard in the region during the growing season of 2009, and hourly canopy stomatal conductance (G(si)) was estimated for individual vines to quantify the relationships between G(si) and these variables. After accounting for the effects of vapor pressure deficit (D) and solar radiation (R(s)) on G(si), much of the remaining variation of reference G(si) (G(siR)) was driven by that of leaf-specific hydraulic conductivity, which in turn was driven by that of A(s)/A(l). After accounting for that effect on G(siR), appreciable temporal variation remained in the decline rate of G(siR) with decreasing vineyard-averaged relative extractable soil water (θ(E)). This variation was related to the differential decline ofθ(E) near each monitored vine, decreasing faster between irrigation events near vines where L was greater, thus adding to the spatiotemporal variation of G(siR) observed in the vineyard. We also found that the vines showed isohydric-like behavior whenθ(E) was low, but switched to anisohydric-like behavior with increasingθ(E). Modeledθ(E) and associated G(s) of a canopy with even L (1.9 m(2) m(-2)) were greater than that of the same average L but split between the lowest and highest L observed along sections of rows in the vineyard (1.2 and 2.6 m(2) m(-2)) by 6 and 12%, respectively. Our results suggest that managing sectional L near the average, rather than allowing a wide variation, can reduce soil water depletion, maintaining G(s) higher, thus potentially enhancing yield.

Transitions to spatiotemporal chaos and turbulence of flute instabilities in a low-β magnetized plasma

International Nuclear Information System (INIS)

Brochard, F.; Gravier, E.; Bonhomme, G.

2006-01-01

The spatiotemporal transition scenario of flute instabilities from a regular to a turbulent state is experimentally investigated in the low-β plasma column of a thermionic discharge. The same transition scenario, i.e., the Ruelle-Takens route to turbulence, is found for both the Kelvin-Helmholtz and the Rayleigh-Taylor instabilities. It is demonstrated that the transition can be more or less smooth, according to the discharge mode. In both cases, a strong radial dependence is observed, which is linked to the velocity shear layer in the case of the Kelvin-Helmholtz instability

A Spatiotemporal Multi-View-Based Learning Method for Short-Term Traffic Forecasting

Directory of Open Access Journals (Sweden)

Shifen Cheng

2018-06-01

Full Text Available Short-term traffic forecasting plays an important part in intelligent transportation systems. Spatiotemporal k-nearest neighbor models (ST-KNNs have been widely adopted for short-term traffic forecasting in which spatiotemporal matrices are constructed to describe traffic conditions. The performance of the models is closely related to the spatial dependencies, the temporal dependencies, and the interaction of spatiotemporal dependencies. However, these models use distance functions and correlation coefficients to identify spatial neighbors and measure the temporal interaction by only considering the temporal closeness of traffic, which result in existing ST-KNNs that cannot fully reflect the essential features of road traffic. This study proposes an improved spatiotemporal k-nearest neighbor model for short-term traffic forecasting by utilizing a multi-view learning algorithm named MVL-STKNN that fully considers the spatiotemporal dependencies of traffic data. First, the spatial neighbors for each road segment are automatically determined using cross-correlation under different temporal dependencies. Three spatiotemporal views are built on the constructed spatiotemporal closeness, periodic, and trend matrices to represent spatially heterogeneous traffic states. Second, a spatiotemporal weighting matrix is introduced into the ST-KNN model to recognize similar traffic patterns in the three spatiotemporal views. Finally, the results of traffic pattern recognition under these three spatiotemporal views are aggregated by using a neural network algorithm to describe the interaction of spatiotemporal dependencies. Extensive experiments were conducted using real vehicular-speed datasets collected on city roads and expressways. In comparison with baseline methods, the results show that the MVL-STKNN model greatly improves short-term traffic forecasting by lowering the mean absolute percentage error between 28.24% and 46.86% for the city road dataset and

A Mixed Land Cover Spatio-temporal Data Model Based on Object-oriented and Snapshot

Directory of Open Access Journals (Sweden)

LI Yinchao

2016-07-01

Full Text Available Spatio-temporal data model (STDM is one of the hot topics in the domains of spatio-temporal database and data analysis. There is a common view that a universal STDM is always of high complexity due to the various situation of spatio-temporal data. In this article, a mixed STDM is proposed based on object-oriented and snapshot models for modelling and analyzing landcover change (LCC. This model uses the object-oriented STDM to describe the spatio-temporal processes of land cover patches and organize their spatial and attributive properties. In the meantime, it uses the snapshot STDM to present the spatio-temporal distribution of LCC on the whole via snapshot images. The two types of models are spatially and temporally combined into a mixed version. In addition to presenting the spatio-temporal events themselves, this model could express the transformation events between different classes of spatio-temporal objects. It can be used to create database for historical data of LCC, do spatio-temporal statistics, simulation and data mining with the data. In this article, the LCC data in Heilongjiang province is used for case study to validate spatio-temporal data management and analysis abilities of mixed STDM, including creating database, spatio-temporal query, global evolution analysis and patches spatio-temporal process expression.

Analysis of the Spatial Variation of Network-Constrained Phenomena Represented by a Link Attribute Using a Hierarchical Bayesian Model

Directory of Open Access Journals (Sweden)

Zhensheng Wang

2017-02-01

Full Text Available The spatial variation of geographical phenomena is a classical problem in spatial data analysis and can provide insight into underlying processes. Traditional exploratory methods mostly depend on the planar distance assumption, but many spatial phenomena are constrained to a subset of Euclidean space. In this study, we apply a method based on a hierarchical Bayesian model to analyse the spatial variation of network-constrained phenomena represented by a link attribute in conjunction with two experiments based on a simplified hypothetical network and a complex road network in Shenzhen that includes 4212 urban facility points of interest (POIs for leisure activities. Then, the methods named local indicators of network-constrained clusters (LINCS are applied to explore local spatial patterns in the given network space. The proposed method is designed for phenomena that are represented by attribute values of network links and is capable of removing part of random variability resulting from small-sample estimation. The effects of spatial dependence and the base distribution are also considered in the proposed method, which could be applied in the fields of urban planning and safety research.

Uncertainty principle, steady state and spatiotemporal evolution in the systemic analysis of the socioenvironmental relations in tourism.

Directory of Open Access Journals (Sweden)

Heros Augusto Santos Lobo

2012-04-01

Full Text Available The general theory of systems is based in the integrated analysis of the spatiotemporal relations among the components, the system matrix and also the arising processes. In tourist systems, the current studies are focused on the description of its components and in some of its interaction relationships. The present contribution focuses on the processes between the components and the matrix of the tourist systems, considering the inherent complexity of open systems, its homeostasis and entropy in function of the carrying capacity of processing the received inputs, and also some questions linked to the steady state, the self-maintenance and the collapse of tourist system generated by structural-deterministic or stochastic causes. In the final considerations, the low similarity of the processes developed in different tourist systems and also in different spatiotemporal conditions in the same system are raised, highlighting the practical impossibility of universal models generation to the tourist systems.

Spatiotemporal variations of inorganic nutrients along the Jiangsu coast, China, and the occurrence of macroalgal blooms (green tides) in the southern Yellow Sea.

Science.gov (United States)

Li, Hongmei; Zhang, Yongyu; Tang, Hongjie; Shi, Xiaoyong; Rivkin, Richard B; Legendre, Louis

2017-03-01

Large macroalgal blooms (i.e. green tides of Ulva prolifera) occurred in the southern Yellow Sea, China, yearly from 2007 to 2016. They were among the largest of such outbreaks around the world, and these blooms likely originated along the coast of the Jiangsu Province, China. Understanding the roles of nutrients in the onset of these macroalgal blooms is needed to identify their origin. This study analyzes the spatiotemporal variations in dissolved inorganic nitrogen and phosphorus (DIN and PO 4 -P) and the N/P ratio along the Jiangsu coast from 1996 to 2014 during late-March to April, the months which corresponds to the pre-bloom period of green tides since 2007. A zone of high DIN and PO 4 -P concentrations has developed along the Jiangsu coast, between the cities of Sheyang and Nantong, since 1996. There was an 18-year trend of increasing DIN concentrations during the pre-bloom period as well as a positive correlation between the U. prolifera biomass and DIN concentrations. Nutrient inputs from rivers and mariculture in the Jiangsu Province may have provided nitrogen that contributed the magnitude of macroalgal blooms that subsequently spread into the southern Yellow Sea. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying Spatiotemporal Dynamics of Solar Radiation over the Northeast China Based on ACO-BPNN Model and Intensity Analysis

Directory of Open Access Journals (Sweden)

Xiangqian Li

2017-01-01

Full Text Available Reliable information on the spatiotemporal dynamics of solar radiation plays a crucial role in studies relating to global climate change. In this study, a new backpropagation neural network (BPNN model optimized with an Ant Colony Optimization (ACO algorithm was developed to generate the ACO-BPNN model, which had demonstrated superior performance for simulating solar radiation compared to traditional BPNN modelling, for Northeast China. On this basis, we applied an intensity analysis to investigate the spatiotemporal variation of solar radiation from 1982 to 2010 over the study region at three levels: interval, category, and conversion. Research findings revealed that (1 the solar radiation resource in the study region increased from the 1980s to the 2000s and the average annual rate of variation from the 1980s to the 1990s was lower than that from the 1990s to the 2000s and (2 the gains and losses of solar radiation at each level were in different conditions. The poor, normal, and comparatively abundant levels were transferred to higher levels, whereas the abundant level was transferred to lower levels. We believe our findings contribute to implementing ad hoc energy management strategies to optimize the use of solar radiation resources and provide scientific suggestions for policy planning.

Experimental devices for the spatio-temporal characterization of femtosecond high-power laser chains

International Nuclear Information System (INIS)

Gallet, Valentin

2014-01-01

One of the advantages of high-power femtosecond lasers (TW-PW) is to obtain, at the focus of a focusing optic, very high intensities up to 10 22 W.cm -2 (i.e. an electric field of 2.7 PV.m -1 . Therefore, these lasers chains necessarily deliver beams with large diameter (up to 40 cm) and very short pulses (of the order of tens of femto-seconds). As a consequence, the spatial and temporal properties of the pulse are generally not independent. Such dependence, called spatial-temporal coupling has the effect of increasing the pulse duration and the size of the focal spot, which can lead to a significant reduction of the maximum intensity at the focus. Metrology devices commonly used on these high-power femtosecond lasers allow retrieving the spatial and temporal profiles of the pulse only in an independent manner. The aim of this thesis was to develop techniques for measuring spatio-temporal couplings in order to quantify their effect and correct them in order to obtain the maximum intensity at focus. First of all, we adapted an existing technique of spatio-temporal characterization to the measurement of TW lasers. To avoid the issues induced at the focus, such as those related to jittering, measurements were performed on the collimated beam. By adding a reference source to the original device, we managed to take into account the measurement artifacts due to thermal and mechanical variations affecting the interferometer. With this improvement, it was possible to reconstruct the complete spatio-temporal profile of the beam, particularly its wavefront. However, the limitations imposed by this technique led to the development of a new measurement device. Based on a cross-correlation, this technique consists of making the laser beam to interfere with a part of itself, small enough not to be spatio-temporally distorted. We have also implemented a variant of this device for a single-shot measurement along one transverse dimension of the pulse. Using these techniques, we

A stream cipher based on a spatiotemporal chaotic system

International Nuclear Information System (INIS)

Li Ping; Li Zhong; Halang, Wolfgang A.; Chen Guanrong

2007-01-01

A stream cipher based on a spatiotemporal chaotic system is proposed. A one-way coupled map lattice consisting of logistic maps is served as the spatiotemporal chaotic system. Multiple keystreams are generated from the coupled map lattice by using simple algebraic computations, and then are used to encrypt plaintext via bitwise XOR. These make the cipher rather simple and efficient. Numerical investigation shows that the cryptographic properties of the generated keystream are satisfactory. The cipher seems to have higher security, higher efficiency and lower computation expense than the stream cipher based on a spatiotemporal chaotic system proposed recently

Spatio-temporal Hotelling observer for signal detection from image sequences.

Science.gov (United States)

Caucci, Luca; Barrett, Harrison H; Rodriguez, Jeffrey J

2009-06-22

Detection of signals in noisy images is necessary in many applications, including astronomy and medical imaging. The optimal linear observer for performing a detection task, called the Hotelling observer in the medical literature, can be regarded as a generalization of the familiar prewhitening matched filter. Performance on the detection task is limited by randomness in the image data, which stems from randomness in the object, randomness in the imaging system, and randomness in the detector outputs due to photon and readout noise, and the Hotelling observer accounts for all of these effects in an optimal way. If multiple temporal frames of images are acquired, the resulting data set is a spatio-temporal random process, and the Hotelling observer becomes a spatio-temporal linear operator. This paper discusses the theory of the spatio-temporal Hotelling observer and estimation of the required spatio-temporal covariance matrices. It also presents a parallel implementation of the observer on a cluster of Sony PLAYSTATION 3 gaming consoles. As an example, we consider the use of the spatio-temporal Hotelling observer for exoplanet detection.

Optimization of Spatiotemporal Apertures in Channel Sounding

DEFF Research Database (Denmark)

Pedersen, Troels; Pedersen, Claus; Yin, Xuefeng

2008-01-01

a spatiotemporal model which can describe parallel as well as switched sounding systems. The proposed model is applicable for arbitrary layouts of the spatial arrays. To simplify the derivations we investigate the special case of linear spatial arrays. However, the results obtained for linear arrays can......In this paper we investigate the impact of the spatio-temporal aperture of a channel sounding system equipped with antenna arrays at the transmitter and receiver on the accuracy of joint estimation of Doppler frequency and bi-direction. The contribution of this work is three-fold. Firstly, we state...... be generalized to arbitrary arrays. Secondly, we give the necessary and sufficient conditions for a spatio-temporal array to yield the minimum Cramér-Rao lower bound in the single-path case and Bayesian Cramér-Rao Lower Bound in the multipath case. The obtained conditions amount to an orthogonality condition...

Variations of extreme rainfall in space and time

DEFF Research Database (Denmark)

Gregersen, Ida Bülow; Madsen, H.; Rosbjerg, Dan

2012-01-01

variation, whereas annual variations are related to changes in the average Danish summer precipitation, the average Danish summer temperature and the East Atlantic pattern. The spatio-temporal Poisson regression model was found to be a helpful tool when comparing the internal importance of these variables......In the ongoing climate change discussion, methods for identification of variability governed by climate change are important tools. The magnitude of variables that can describe this variability should be compared with magnitudes of variables describing variability in a stationary setting....... This study focuses on variations of extreme rainfall events, observed at 70 different locations in Denmark over a period of 31 years. The aim is to identify and compare variables, both spatially and temporally, which can explain different parts of the variability in this data set. Assuming that the number...

Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China.

Science.gov (United States)

Ye, Zirong; Xu, Li; Zhou, Zi; Wu, Yafei; Fang, Ya

2018-01-02

Most previous research on the disparities of hypertension risk has neither simultaneously explored the spatio-temporal disparities nor considered the spatial information contained in the samples, thus the estimated results may be unreliable. Our study was based on the China Health and Nutrition Survey (CHNS), including residents over 12 years old in seven provinces from 1991 to 2011. Bayesian B-spline was used in the extended shared component model (SCM) for fitting temporal-related variation to explore spatio-temporal distribution in the odds ratio (OR) of hypertension, reveal gender variation, and explore latent risk factors. Our results revealed that the prevalence of hypertension increased from 14.09% in 1991 to 32.37% in 2011, with men experiencing a more obvious change than women. From a spatial perspective, a standardized prevalence ratio (SPR) remaining at a high level was found in Henan and Shandong for both men and women. Meanwhile, before 1997, the temporal distribution of hypertension risk for both men and women remained low. After that, notably since 2004, the OR of hypertension in each province increased to a relatively high level, especially in Northern China. Notably, the OR of hypertension in Shandong and Jiangsu, which was over 1.2, continuously stood out after 2004 for males, while that in Shandong and Guangxi was relatively high for females. The findings suggested that obvious spatial-temporal patterns for hypertension exist in the regions under research and this pattern was quite different between men and women.

Estimating repetitive spatiotemporal patterns from resting-state brain activity data.

Science.gov (United States)

Takeda, Yusuke; Hiroe, Nobuo; Yamashita, Okito; Sato, Masa-Aki

2016-06-01

Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Spatiotemporal Diffusive Evolution and Fractal Structure of Ground Motion

Science.gov (United States)

Suwada, Tsuyoshi

2018-02-01

The spatiotemporal diffusive evolution and fractal structure of ground motion have been investigated at the in-ground tunnel of the KEK B-Factory (KEKB) injector linear accelerator (linac). The slow dynamic fluctuating displacements of the tunnel floor are measured in real time with a new remote-controllable sensing system based on a laser-based alignment system. Based on spatiotemporal analyses with linear-regression models, which were applied in both the time and frequency domains to time-series data recorded over a period of approximately 8 months, both coherent and stochastic components in the displacements of the tunnel floor were clearly observed along the entire length of the linac. In particular, it was clearly observed that the stochastic components exhibited characteristic spatiotemporal diffusive evolution with the fractal structure and fractional dimension. This report describes in detail the experimental techniques and analyses of the spatiotemporal diffusive evolution of ground motion observed at the in-ground tunnel of the injector linac using a real-time remote-controllable sensing system.

Seasonal and among-stream variation in predator encounter rates for fish prey

Science.gov (United States)

Bret C. Harvey; Rodney J. Nakamoto

2013-01-01

Recognition that predators have indirect effects on prey populations that may exceed their direct consumptive effects highlights the need for a better understanding of spatiotemporal variation in predator–prey interactions. We used photographic monitoring of tethered Rainbow Trout Oncorhynchus mykiss and Cutthroat Trout O. clarkii to quantify predator encounter rates...

Indeterminacy and Spatiotemporal Data

DEFF Research Database (Denmark)

Pfoser, D.; Tryfona, N.; Jensen, Christian Søndergaard

2005-01-01

For some spatiotemporal applications, it can be assumed that the modeled world is precise and bounded, and that our record of it is precise. While these simplifying assumptions are sufficient in applications like a land information system, they are unnecessarily crude for many other applications...

Spatiotemporal variations in the abundance and composition of bulk and chromophoric dissolved organic matter in seasonally hypoxia-influenced Green Bay, Lake Michigan, USA.

Science.gov (United States)

DeVilbiss, Stephen E; Zhou, Zhengzhen; Klump, J Val; Guo, Laodong

2016-09-15

Green Bay, Lake Michigan, USA, is the largest freshwater estuary in the Laurentian Great Lakes and receives disproportional terrestrial inputs as a result of a high watershed to bay surface area ratio. While seasonal hypoxia and the formation of "dead zones" in Green Bay have received increasing attention, there are no systematic studies on the dynamics of dissolved organic matter (DOM) and its linkage to the development of hypoxia. During summer 2014, bulk dissolved organic carbon (DOC) analysis, UV-vis spectroscopy, and fluorescence excitation-emission matrices (EEMs) coupled with PARAFAC analysis were used to quantify the abundance, composition and source of DOM and their spatiotemporal variations in Green Bay, Lake Michigan. Concentrations of DOC ranged from 202 to 571μM-C (average=361±73μM-C) in June and from 279 to 610μM-C (average=349±64μM-C) in August. In both months, absorption coefficient at 254nm (a254) was strongly correlated to bulk DOC and was most abundant in the Fox River, attesting a dominant terrestrial input. Non-chromophoric DOC comprised, on average, ~32% of bulk DOC in June with higher terrestrial DOM and ~47% in August with higher aquagenic DOM, indicating that autochthonous and more degraded DOM is of lower optical activity. PARAFAC modeling on EEM data resulted in four major fluorescent DOM components, including two terrestrial humic-like, one aquagenic humic-like, and one protein-like component. Variations in the abundance of DOM components further supported changes in DOM sources. Mixing behavior of DOM components also indicated that while bulk DOM behaved quasi-conservatively, significant compositional changes occurred during transport from the Fox River to the open bay. Copyright © 2016 Elsevier B.V. All rights reserved.

Non-reciprocal elastic wave propagation in 2D phononic membranes with spatiotemporally varying material properties

Science.gov (United States)

Attarzadeh, M. A.; Nouh, M.

2018-05-01

One-dimensional phononic materials with material fields traveling simultaneously in space and time have been shown to break elastodynamic reciprocity resulting in unique wave propagation features. In the present work, a comprehensive mathematical analysis is presented to characterize and fully predict the non-reciprocal wave dispersion in two-dimensional space. The analytical dispersion relations, in the presence of the spatiotemporal material variations, are validated numerically using finite 2D membranes with a prescribed number of cells. Using omnidirectional excitations at the membrane's center, wave propagations are shown to exhibit directional asymmetry that increases drastically in the direction of the material travel and vanishes in the direction perpendicular to it. The topological nature of the predicted dispersion in different propagation directions are evaluated using the computed Chern numbers. Finally, the degree of the 2D non-reciprocity is quantified using a non-reciprocity index (NRI) which confirms the theoretical dispersion predictions as well as the finite simulations. The presented framework can be extended to plate-type structures as well as 3D spatiotemporally modulated phononic crystals.

Spatio-temporal modelling of zero-inflated deep-sea shrimp data by Tweedie generalized additive

Directory of Open Access Journals (Sweden)

Simona Arcuti

2013-10-01

Full Text Available In theMediterrean Sea the population features of demersal resources fluctuate over spatial and temporal scales due to the variability of abiotic and biotic factors as well as to human activities. The two shrimps Parapenaeus longirostris and Aristaeomorpha foliacea are among the most important deep-sea demersal resources in the North-Western Ionian Sea. Their changes in terms of density, biomass andmedian length induced by anthropogenic and environmental variables (fishing effort, sea surface temperature, precipitations, Winter North Atlantic Oscillation (NAO and Annual MediterraneanOscillation (MO indices were investigated. Biological data were collected during trawl surveys carried out from 1995 to 2006 as part of the international program MEDITS (International Bottom Trawl Survey in the Mediterranean. Generalized AdditiveModels were used to evaluate the spatio-temporal variation of both species, together with the possible nonlinear effects of biotic and abiotic factors. Density and biomass were assumed to be distributed according to a member of the Tweedie family in order to account for zero-inflation in the relative data. Spacetime interaction was consideredwithin a non-separablemodel with smooth spatio-temporal component based on tensor product splines. The results show significant spatio-temporal and depth effects in the three population parameters of these resources. Winter NAO index significantly influenced the density, biomass and length of P. longirostris. Sea surface temperature significantly influenced the size of this species and the three population features of A. foliacea. The size of this shrimp resulted also influenced negatively by fishing effort and positively by the MO index.

Guess Where? Actor-Supervision for Spatiotemporal Action Localization

KAUST Repository

Escorcia, Victor

2018-04-05

This paper addresses the problem of spatiotemporal localization of actions in videos. Compared to leading approaches, which all learn to localize based on carefully annotated boxes on training video frames, we adhere to a weakly-supervised solution that only requires a video class label. We introduce an actor-supervised architecture that exploits the inherent compositionality of actions in terms of actor transformations, to localize actions. We make two contributions. First, we propose actor proposals derived from a detector for human and non-human actors intended for images, which is linked over time by Siamese similarity matching to account for actor deformations. Second, we propose an actor-based attention mechanism that enables the localization of the actions from action class labels and actor proposals and is end-to-end trainable. Experiments on three human and non-human action datasets show actor supervision is state-of-the-art for weakly-supervised action localization and is even competitive to some fully-supervised alternatives.

Guess Where? Actor-Supervision for Spatiotemporal Action Localization

KAUST Repository

Escorcia, Victor; Dao, Cuong D.; Jain, Mihir; Ghanem, Bernard; Snoek, Cees

2018-01-01

This paper addresses the problem of spatiotemporal localization of actions in videos. Compared to leading approaches, which all learn to localize based on carefully annotated boxes on training video frames, we adhere to a weakly-supervised solution that only requires a video class label. We introduce an actor-supervised architecture that exploits the inherent compositionality of actions in terms of actor transformations, to localize actions. We make two contributions. First, we propose actor proposals derived from a detector for human and non-human actors intended for images, which is linked over time by Siamese similarity matching to account for actor deformations. Second, we propose an actor-based attention mechanism that enables the localization of the actions from action class labels and actor proposals and is end-to-end trainable. Experiments on three human and non-human action datasets show actor supervision is state-of-the-art for weakly-supervised action localization and is even competitive to some fully-supervised alternatives.

Effective and efficient analysis of spatio-temporal data

Science.gov (United States)

Zhang, Zhongnan

Spatio-temporal data mining, i.e., mining knowledge from large amount of spatio-temporal data, is a highly demanding field because huge amounts of spatio-temporal data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collection data far exceeded human's ability to analyze which make it crucial to develop analysis tools. Recent studies on data mining have extended to the scope of data mining from relational and transactional datasets to spatial and temporal datasets. Among the various forms of spatio-temporal data, remote sensing images play an important role, due to the growing wide-spreading of outer space satellites. In this dissertation, we proposed two approaches to analyze the remote sensing data. The first one is about applying association rules mining onto images processing. Each image was divided into a number of image blocks. We built a spatial relationship for these blocks during the dividing process. This made a large number of images into a spatio-temporal dataset since each image was shot in time-series. The second one implemented co-occurrence patterns discovery from these images. The generated patterns represent subsets of spatial features that are located together in space and time. A weather analysis is composed of individual analysis of several meteorological variables. These variables include temperature, pressure, dew point, wind, clouds, visibility and so on. Local-scale models provide detailed analysis and forecasts of meteorological phenomena ranging from a few kilometers to about 100 kilometers in size. When some of above meteorological variables have some special change tendency, some kind of severe weather will happen in most cases. Using the discovery of association rules, we found that some special meteorological variables' changing has tight relation with some severe weather situation that will happen

Linking Genetic Variation in Adaptive Plant Traits to Climate in Tetraploid and Octoploid Basin Wildrye [Leymus cinereus (Scribn. & Merr. A. Love] in the Western U.S.

Directory of Open Access Journals (Sweden)

R C Johnson

Full Text Available Few studies have assessed how ploidy type within a species affects genetic variation among populations in relation to source climates. Basin wildrye (Leymus cinereus (Scribn. & Merr. A. Love is a large bunchgrass common in the intermountain Western U.S. found in both octoploid and tetraploid types. In common gardens at two sites over two years differences in both ploidy type and genetic variation within ploidy were observed in phenology, morphology, and production traits on 57 octoploid and 52 tetraploid basin wildrye from the intermountain Western U.S. (P<0.01. Octoploids had larger leaves, longer culms, and greater crown circumference than tetraploids but the numerical ranges of plant traits and their source climates overlapped between ploidy types. Still, among populations octoploids often had greater genetic variation for traits and occupied more diverse climates than tetraploids. Genetic variation for both ploidy types was linked to source climates in canonical correlation analysis, with the first two variates explaining 70% of the variation. Regression of those canonical variates with seed source climate variables produced models that explained 64% and 38% of the variation, respectively, and were used to map 15 seed zones covering 673,258 km2. Utilization of these seed zones will help ensure restoration with adaptive seed sources for both ploidy types. The link between genetic traits and seed source climates suggests climate driven natural selection and adaptive evolution in basin wildrye. The more diverse climates occupied by octoploids and higher trait variation suggests a higher capacity for ecological differentiation than tetraploids in the intermountain Western U.S.

Dynamical topology and statistical properties of spatiotemporal chaos.

Science.gov (United States)

Zhuang, Quntao; Gao, Xun; Ouyang, Qi; Wang, Hongli

2012-12-01

For spatiotemporal chaos described by partial differential equations, there are generally locations where the dynamical variable achieves its local extremum or where the time partial derivative of the variable vanishes instantaneously. To a large extent, the location and movement of these topologically special points determine the qualitative structure of the disordered states. We analyze numerically statistical properties of the topologically special points in one-dimensional spatiotemporal chaos. The probability distribution functions for the number of point, the lifespan, and the distance covered during their lifetime are obtained from numerical simulations. Mathematically, we establish a probabilistic model to describe the dynamics of these topologically special points. In spite of the different definitions in different spatiotemporal chaos, the dynamics of these special points can be described in a uniform approach.

Evaluating the disparity of female breast cancer mortality among racial groups - a spatiotemporal analysis

Directory of Open Access Journals (Sweden)

Jacobson Holly

2004-02-01

Full Text Available Abstract Background The literature suggests that the distribution of female breast cancer mortality demonstrates spatial concentration. There remains a lack of studies on how the mortality burden may impact racial groups across space and over time. The present study evaluated the geographic variations in breast cancer mortality in Texas females according to three predominant racial groups (non-Hispanic White, Black, and Hispanic females over a twelve-year period. It sought to clarify whether the spatiotemporal trend might place an uneven burden on particular racial groups, and whether the excess trend has persisted into the current decade. Methods The Spatial Scan Statistic was employed to examine the geographic excess of breast cancer mortality by race in Texas counties between 1990 and 2001. The statistic was conducted with a scan window of a maximum of 90% of the study period and a spatial cluster size of 50% of the population at risk. The next scan was conducted with a purely spatial option to verify whether the excess mortality persisted further. Spatial queries were performed to locate the regions of excess mortality affecting multiple racial groups. Results The first scan identified 4 regions with breast cancer mortality excess in both non-Hispanic White and Hispanic female populations. The most likely excess mortality with a relative risk of 1.12 (p = 0.001 occurred between 1990 and 1996 for non-Hispanic Whites, including 42 Texas counties along Gulf Coast and Central Texas. For Hispanics, West Texas with a relative risk of 1.18 was the most probable region of excess mortality (p = 0.001. Results of the second scan were identical to the first. This suggested that the excess mortality might not persist to the present decade. Spatial queries found that 3 counties in Southeast and 9 counties in Central Texas had excess mortality involving multiple racial groups. Conclusion Spatiotemporal variations in breast cancer mortality affected racial

Developing Integrated Remote Sensing and Geographical Information Sciences Procedures to Assess Impacts of Climate Variations on Spatio-Temporal Distribution of Mangroves

Science.gov (United States)

Qaisar, Maha

2016-07-01

Pakistan's periled treasures of mangroves require protection from devastating anthropogenic activities, which can only be achieved through the identification and management of this habitat. The primary objective of this study is to identify the potential habitat of mangroves along the coastline of Pakistan with the help of Remote Sensing (RS) and Geographical Information System (GIS) techniques. Once the mangroves were identified, species of mangroves need to be separated through Object Based Image Analysis (OBIA) which gave the area of mangroves and non mangroves sites. Later other parameters of Sea Surface Temperature, Sea Surface Salinity, chlorophyll-a along with altimetry data were used to assess the climatic variations on the spatio-temporal distribution of mangroves. Since mangroves provide economical, ecological, biological indication of Coastal Change or Sea Level Rise. Therefore, this provides a strong platform to assess the climatic variations which are posing negative impacts on the mangroves ecosystem. The results indicate that mangroves are present throughout along the coastline, proving that Pakistan is rich in these diverse ecosystems. Pakistan being at important geo strategic position can also benefit from its vast mangroves and other coastal resources such as coral reefs and fish varieties. Moreover, coastal zone management through involvement of the local community and establishment of Marine Protected Area (MPA) is the need of the hour to avoid deforestation of mangroves, which can prove to be deadly damaging for the fish populace since it provides habitats to various marine animals. However, the established relationship among SST, SSS, chlorophyll-a and altimetry data assisted to know the suitable sites for mangroves. But due to enhanced climatic impacts these relationships are distorted which has posed devastating effects on the growth and distribution of mangroves. Study area was Karachi Coast, Pakistan. The total area of Karachi is about 70

Elemental Spatiotemporal Variations of Total Suspended Particles in Jeddah City

OpenAIRE

Kadi, Mohammad W.

2014-01-01

Elements associated with total suspended particulate matter (TSP) in Jeddah city were determined. Using high-volume samplers, TSP samples were simultaneously collected over a one-year period from seven sampling sites. Samples were analyzed for Al, Ba, Ca, Cu, Mg, Fe, Mn, Zn, Ti, V, Cr, Co, Ni, As, and Sr. Results revealed great dependence of element contents on spatial and temporal variations. Two sites characterized by busy roads, workshops, heavy population, and heavy trucking have high lev...

Ethnic variations in immigrant poverty exit and female employment: the missing link.

Science.gov (United States)

Kaida, Lisa

2015-04-01

Despite widespread interest in poverty among recent immigrants and female immigrant employment, research on the link between the two is limited. This study evaluates the effect of recently arrived immigrant women's employment on the exit from family poverty and considers the implications for ethnic differences in poverty exit. It uses the bivariate probit model and the Fairlie decomposition technique to analyze data from the Longitudinal Survey of Immigrants to Canada (LSIC), a nationally representative survey of immigrants arriving in Canada, 2000-2001. Results show that the employment of recently arrived immigrant women makes a notable contribution to lifting families out of poverty. Moreover, the wide ethnic variations in the probability of exit from poverty between European and non-European groups are partially explained by the lower employment rates among non-European women. The results suggest that the equal earner/female breadwinner model applies to low-income recent immigrant families in general, but the male breadwinner model explains the low probability of poverty exit among select non-European groups whose female employment rates are notably low.

Spatio-temporal Eigenvector Filtering: Application on Bioenergy Crop Impacts

Science.gov (United States)

Wang, M.; Kamarianakis, Y.; Georgescu, M.

2017-12-01

A suite of 10-year ensemble-based simulations was conducted to investigate the hydroclimatic impacts due to large-scale deployment of perennial bioenergy crops across the continental United States. Given the large size of the simulated dataset (about 60Tb), traditional hierarchical spatio-temporal statistical modelling cannot be implemented for the evaluation of physics parameterizations and biofuel impacts. In this work, we propose a filtering algorithm that takes into account the spatio-temporal autocorrelation structure of the data while avoiding spatial confounding. This method is used to quantify the robustness of simulated hydroclimatic impacts associated with bioenergy crops to alternative physics parameterizations and observational datasets. Results are evaluated against those obtained from three alternative Bayesian spatio-temporal specifications.

Spatiotemporal radiotherapy planning using a global optimization approach

Science.gov (United States)

Adibi, Ali; Salari, Ehsan

2018-02-01

This paper aims at quantifying the extent of potential therapeutic gain, measured using biologically effective dose (BED), that can be achieved by altering the radiation dose distribution over treatment sessions in fractionated radiotherapy. To that end, a spatiotemporally integrated planning approach is developed, where the spatial and temporal dose modulations are optimized simultaneously. The concept of equivalent uniform BED (EUBED) is used to quantify and compare the clinical quality of spatiotemporally heterogeneous dose distributions in target and critical structures. This gives rise to a large-scale non-convex treatment-plan optimization problem, which is solved using global optimization techniques. The proposed spatiotemporal planning approach is tested on two stylized cancer cases resembling two different tumor sites and sensitivity analysis is performed for radio-biological and EUBED parameters. Numerical results validate that spatiotemporal plans are capable of delivering a larger BED to the target volume without increasing the BED in critical structures compared to conventional time-invariant plans. In particular, this additional gain is attributed to the irradiation of different regions of the target volume at different treatment sessions. Additionally, the trade-off between the potential therapeutic gain and the number of distinct dose distributions is quantified, which suggests a diminishing marginal gain as the number of dose distributions increases.

Spatio-temporal databases complex motion pattern queries

CERN Document Server

Vieira, Marcos R

2013-01-01

This brief presents several new query processing techniques, called complex motion pattern queries, specifically designed for very large spatio-temporal databases of moving objects. The brief begins with the definition of flexible pattern queries, which are powerful because of the integration of variables and motion patterns. This is followed by a summary of the expressive power of patterns and flexibility of pattern queries. The brief then present the Spatio-Temporal Pattern System (STPS) and density-based pattern queries. STPS databases contain millions of records with information about mobi

Transition to turbulence via spatiotemporal intermittency in stimulated Raman backscattering

International Nuclear Information System (INIS)

Skoric, M.M.; Jovanovic, M.S.; Rajkovic, M.R.

1996-01-01

The spatiotemporal evolution of stimulated Raman backscattering in a bounded, uniform, weakly dissipative plasma is studied. The nonlinear model of a three-wave interaction involves a quadratic coupling of slowly varying complex amplitudes of the laser pump, the backscattered and the electron plasma wave. The corresponding set of coupled partial differential equations with nonlinear phase detuning that is taken into account is solved numerically in space time with fixed nonzero source boundary conditions. The study of the above open, convective, weakly confined system reveals a quasiperiodic transition to spatiotemporal chaos via spatiotemporal intermittency. In the analysis of transitions a dual scheme borrowed from fields of nonlinear dynamics and statistical physics is applied. An introduction of a nonlinear three-wave interaction to a growing family of paradigmatic equations which exhibit a route to turbulence via spatiotemporal intermittency is outlined in this work. copyright 1996 The American Physical Society

Photo-triggered fluorescent theranostic prodrugs as DNA alkylating agents for mechlorethamine release and spatiotemporal monitoring.

Science.gov (United States)

Cao, Yanting; Pan, Rong; Xuan, Weimin; Wei, Yongyi; Liu, Kejian; Zhou, Jiahong; Wang, Wei

2015-06-28

We describe a new theranostic strategy for selective delivery and spatiotemporal monitoring of mechlorethamine, a DNA alkylating agent. A photo-responsive prodrug is designed and composed of a photolabile o-nitrophenylethyl group, a DNA alkylating mechlorethamine drug and a coumarin fluorophore. Masking of the "N" in mechlorethamine in a positively charged state in the prodrug renders it inactive, non-toxic, selective and non-fluorescent. Indeed, the stable prodrug shows negligible cytotoxicity towards normal cells with and without UV activation and is completely non-fluorescent. However, upon photo-irradiation, the active mechlorethamine is released and induces efficient DNA cross-links, accompanied by a strong fluorescence enhancement (152 fold). Furthermore, DNA cross-linking activity from the release can be transformed into anticancer activity observed in in vitro studies of tumor cells. Importantly, the drug release progress and the movement can be conveniently monitored by fluorescence spectroscopy. The mechanistic study proves that the DNA cross-linking activity is mainly due to the release of DNA alkylating mechlorethamine. Altogether, the studies show the power of the theranostic strategy for efficient therapy in cancer treatment.

The CTBTO Link to the database of the International Seismological Centre (ISC)

Science.gov (United States)

Bondar, I.; Storchak, D. A.; Dando, B.; Harris, J.; Di Giacomo, D.

2011-12-01

The CTBTO Link to the database of the International Seismological Centre (ISC) is a project to provide access to seismological data sets maintained by the ISC using specially designed interactive tools. The Link is open to National Data Centres and to the CTBTO. By means of graphical interfaces and database queries tailored to the needs of the monitoring community, the users are given access to a multitude of products. These include the ISC and ISS bulletins, covering the seismicity of the Earth since 1904; nuclear and chemical explosions; the EHB bulletin; the IASPEI Reference Event list (ground truth database); and the IDC Reviewed Event Bulletin. The searches are divided into three main categories: The Area Based Search (a spatio-temporal search based on the ISC Bulletin), the REB search (a spatio-temporal search based on specific events in the REB) and the IMS Station Based Search (a search for historical patterns in the reports of seismic stations close to a particular IMS seismic station). The outputs are HTML based web-pages with a simplified version of the ISC Bulletin showing the most relevant parameters with access to ISC, GT, EHB and REB Bulletins in IMS1.0 format for single or multiple events. The CTBTO Link offers a tool to view REB events in context within the historical seismicity, look at observations reported by non-IMS networks, and investigate station histories and residual patterns for stations registered in the International Seismographic Station Registry.

Linking global climate and temperature variability to widespread amphibian declines putatively caused by disease.

Science.gov (United States)

Rohr, Jason R; Raffel, Thomas R

2010-05-04

The role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial, and the effect of climatic variability, in particular, has largely been ignored. For instance, it was recently revealed that the proposed link between climate change and widespread amphibian declines, putatively caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd), was tenuous because it was based on a temporally confounded correlation. Here we provide temporally unconfounded evidence that global El Niño climatic events drive widespread amphibian losses in genus Atelopus via increased regional temperature variability, which can reduce amphibian defenses against pathogens. Of 26 climate variables tested, only factors associated with temperature variability could account for the spatiotemporal patterns of declines thought to be associated with Bd. Climatic predictors of declines became significant only after controlling for a pattern consistent with epidemic spread (by temporally detrending the data). This presumed spread accounted for 59% of the temporal variation in amphibian losses, whereas El Niño accounted for 59% of the remaining variation. Hence, we could account for 83% of the variation in declines with these two variables alone. Given that global climate change seems to increase temperature variability, extreme climatic events, and the strength of Central Pacific El Niño episodes, climate change might exacerbate worldwide enigmatic declines of amphibians, presumably by increasing susceptibility to disease. These results suggest that changes to temperature variability associated with climate change might be as significant to biodiversity losses and disease emergence as changes to mean temperature.

Comparison of Spatiotemporal Mapping Techniques for Enormous Etl and Exploitation Patterns

Science.gov (United States)

Deiotte, R.; La Valley, R.

2017-10-01

The need to extract, transform, and exploit enormous volumes of spatiotemporal data has exploded with the rise of social media, advanced military sensors, wearables, automotive tracking, etc. However, current methods of spatiotemporal encoding and exploitation simultaneously limit the use of that information and increase computing complexity. Current spatiotemporal encoding methods from Niemeyer and Usher rely on a Z-order space filling curve, a relative of Peano's 1890 space filling curve, for spatial hashing and interleaving temporal hashes to generate a spatiotemporal encoding. However, there exist other space-filling curves, and that provide different manifold coverings that could promote better hashing techniques for spatial data and have the potential to map spatiotemporal data without interleaving. The concatenation of Niemeyer's and Usher's techniques provide a highly efficient space-time index. However, other methods have advantages and disadvantages regarding computational cost, efficiency, and utility. This paper explores the several methods using a range of sizes of data sets from 1K to 10M observations and provides a comparison of the methods.

COMPARISON OF SPATIOTEMPORAL MAPPING TECHNIQUES FOR ENORMOUS ETL AND EXPLOITATION PATTERNS

Directory of Open Access Journals (Sweden)

R. Deiotte

2017-10-01

Full Text Available The need to extract, transform, and exploit enormous volumes of spatiotemporal data has exploded with the rise of social media, advanced military sensors, wearables, automotive tracking, etc. However, current methods of spatiotemporal encoding and exploitation simultaneously limit the use of that information and increase computing complexity. Current spatiotemporal encoding methods from Niemeyer and Usher rely on a Z-order space filling curve, a relative of Peano’s 1890 space filling curve, for spatial hashing and interleaving temporal hashes to generate a spatiotemporal encoding. However, there exist other space-filling curves, and that provide different manifold coverings that could promote better hashing techniques for spatial data and have the potential to map spatiotemporal data without interleaving. The concatenation of Niemeyer’s and Usher’s techniques provide a highly efficient space-time index. However, other methods have advantages and disadvantages regarding computational cost, efficiency, and utility. This paper explores the several methods using a range of sizes of data sets from 1K to 10M observations and provides a comparison of the methods.

Research on spatio-temporal database techniques for spatial information service

Science.gov (United States)

Zhao, Rong; Wang, Liang; Li, Yuxiang; Fan, Rongshuang; Liu, Ping; Li, Qingyuan

2007-06-01

Geographic data should be described by spatial, temporal and attribute components, but the spatio-temporal queries are difficult to be answered within current GIS. This paper describes research into the development and application of spatio-temporal data management system based upon GeoWindows GIS software platform which was developed by Chinese Academy of Surveying and Mapping (CASM). Faced the current and practical requirements of spatial information application, and based on existing GIS platform, one kind of spatio-temporal data model which integrates vector and grid data together was established firstly. Secondly, we solved out the key technique of building temporal data topology, successfully developed a suit of spatio-temporal database management system adopting object-oriented methods. The system provides the temporal data collection, data storage, data management and data display and query functions. Finally, as a case study, we explored the application of spatio-temporal data management system with the administrative region data of multi-history periods of China as the basic data. With all the efforts above, the GIS capacity of management and manipulation in aspect of time and attribute of GIS has been enhanced, and technical reference has been provided for the further development of temporal geographic information system (TGIS).

An evaluation of space time cube representation of spatiotemporal patterns.

Science.gov (United States)

Kristensson, Per Ola; Dahlbäck, Nils; Anundi, Daniel; Björnstad, Marius; Gillberg, Hanna; Haraldsson, Jonas; Mårtensson, Ingrid; Nordvall, Mathias; Ståhl, Josefine

2009-01-01

Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns.

Spatiotemporal Patterns of Carbon Emissions and Taxi Travel Using GPS Data in Beijing

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Jinlei Zhang

2018-02-01

Full Text Available Taxis are significant contributors to carbon dioxide emissions due to their frequent usage, yet current research into taxi carbon emissions is insufficient. Emerging data sources and big data–mining techniques enable analysis of carbon emissions, which contributes to their reduction and the promotion of low-carbon societies. This study uses taxi GPS data to reconstruct taxi trajectories in Beijing. We then use the carbon emission calculation model based on a taxi fuel consumption algorithm and the carbon dioxide emission factor to calculate emissions and apply a visualization method called kernel density analysis to obtain the dynamic spatiotemporal distribution of carbon emissions. Total carbon emissions show substantial temporal variations during the day, with maximum values from 10:00–11:00 (57.53 t, which is seven times the minimum value of 7.43 t (from 03:00–04:00. Carbon emissions per kilometer at the network level are steady throughout the day (0.2 kg/km. The Airport Expressway, Ring Roads, and large intersections within the 5th Ring Road maintain higher carbon emissions than other areas. Spatiotemporal carbon emissions and travel patterns differ between weekdays and weekends, especially during morning rush hours. This research provides critical insights for taxi companies, authorities, and future studies.

Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques.

Science.gov (United States)

Chang, Fi-John; Chen, Pin-An; Chang, Li-Chiu; Tsai, Yu-Hsuan

2016-08-15

This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system. The Dahan River in Taiwan is used as a study case, where ten-year seasonal water quality data collected at seven monitoring stations along the river are used for model training and validation. Results demonstrate that the NARX network can suitably capture the important dynamic features and remarkably outperforms the BPNN model, and the SMS can effectively identify key input factors, suitably overcome data scarcity, significantly increase model reliability, satisfactorily estimate site-specific TP concentration at seven monitoring stations simultaneously, and adequately reconstruct seasonal TP data into a monthly scale. The proposed SMS can reliably model the dynamic spatio-temporal water pollution variation in a river system for missing, hazardous or costly data of interest. Copyright © 2016 Elsevier B.V. All rights reserved.

Rainfall spatiotemporal variability relation to wetlands hydroperiods

Science.gov (United States)

Serrano-Hidalgo, Carmen; Guardiola-Albert, Carolina; Fernandez-Naranjo, Nuria

2017-04-01

Doñana natural space (Southwestern Spain) is one of the largest protected wetlands in Europe. The wide marshes present in this natural space have such ecological value that this wetland has been declared a Ramsar reserve in 1982. Apart from the extensive marsh, there are also small lagoons and seasonally flooded areas which are likewise essential to maintain a wide variety of valuable habitats. Hydroperiod, the length of time each point remains flooded along an annual cycle, is a critical ecological parameter that shapes aquatic plants and animals distribution and determines available habitat for many of the living organisms in the marshes. Recently, there have been published two different works estimating the hydroperiod of Doñana lagoons with Landsat Time Series images (Cifuentes et al., 2015; Díaz-Delgado et al., 2016). In both works the flooding cycle hydroperiod in Doñana marshes reveals a flooding regime mainly driven by rainfall, evapotranspiration, topography and local hydrological management actions. The correlation found between rainfall and hydroperiod is studied differently in both works. While in one the rainfall is taken from one raingauge (Cifuentes et al., 2015), the one performed by Díaz-Delgado (2016) uses annual rainfall maps interpolated with the inverse of the distance method. The rainfall spatiotemporal variability in this area can be highly significant; however the amount of this importance has not been quantified at the moment. In the present work the geostatistical tool known as spatiotemporal variogram is used to study the rainfall spatiotemporal variability. The spacetime package implemented in R (Pebesma, 2012) facilities its computation from a high rainfall data base of more than 100 raingauges from 1950 to 2016. With the aid of these variograms the rainfall spatiotemporal variability is quantified. The principal aim of the present work is the study of the relation between the rainfall spatiotemporal variability and the

Robust seismicity forecasting based on Bayesian parameter estimation for epidemiological spatio-temporal aftershock clustering models.

Science.gov (United States)

Ebrahimian, Hossein; Jalayer, Fatemeh

2017-08-29

In the immediate aftermath of a strong earthquake and in the presence of an ongoing aftershock sequence, scientific advisories in terms of seismicity forecasts play quite a crucial role in emergency decision-making and risk mitigation. Epidemic Type Aftershock Sequence (ETAS) models are frequently used for forecasting the spatio-temporal evolution of seismicity in the short-term. We propose robust forecasting of seismicity based on ETAS model, by exploiting the link between Bayesian inference and Markov Chain Monte Carlo Simulation. The methodology considers the uncertainty not only in the model parameters, conditioned on the available catalogue of events occurred before the forecasting interval, but also the uncertainty in the sequence of events that are going to happen during the forecasting interval. We demonstrate the methodology by retrospective early forecasting of seismicity associated with the 2016 Amatrice seismic sequence activities in central Italy. We provide robust spatio-temporal short-term seismicity forecasts with various time intervals in the first few days elapsed after each of the three main events within the sequence, which can predict the seismicity within plus/minus two standard deviations from the mean estimate within the few hours elapsed after the main event.

Spatiotemporal Data Mining, Analysis, and Visualization of Human Activity Data

Science.gov (United States)

Li, Xun

2012-01-01

This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data…

Markovian Limit of a Spatio-Temporal Correlated Open Systems

Science.gov (United States)

Monnai, T.

Large fluctuation of Brownian particles is affected by the finiteness of the correlation length of the background noise field. Indeed a Fokker—Planck equation is derived in a Markovian limit of a spatio-temporal short correlated noise. Corresponding kinetic quantities are renormalized due to the spatio-temporal memory. We also investigate the case of open system by connecting a thermostat to the system.

Investigation of Spatiotemporal Pattern of Drought in North Korea Using Remote Sensing and GIS

Science.gov (United States)

Yu, J.; Lee, K. S.

2015-12-01

Drought, as one of the severest disasters in the world, have attracted the attention of researchers and general public. Sometimes even short, intense droughts can cause significant damages to the natural environment as well as the economy. In recent years, North Korea (NK) has been suffering severe droughts. Yet, the thorough field investigation of drought disaster conditions in NK is impossible now. Thus, it is necessary to get more information of drought conditions to restore the damaged environment in NK after unification. RS data can be used to monitor vegetation, bare soil conditions, especially in inaccessible regions. This information can be used to derive spatial variation of drought conditions. Thus, the spatiotemporal pattern of drought conditions in NK using multi-sensor RS data and available meteorological data were investigated in this study. The RS data---MODIS NDVI (MOD13A3) and LST (Land Surface Temperature) (MOD11A2) from 2000 to 2014 which obtain the vegetation health conditions were used to derive two operationally used agricultural drought indices: Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). The in-situ precipitation data from 27 weather stations from 1981 to 2014 were used for identifying the relative dry/wet years and acquiring meteorological drought index Standardized Precipitation Index (SPI). The correlations between the agricultural drought indices and metrological drought index were derived. These data were stored in GIS and used for spatial analysis to figure out the spatiotemporal pattern of drought in NK. The spatiotemporal information of NK drought in this study can provide the basic information for restoring the drought damaged field after the unification of Korea.

Spatiotemporal transmission dynamics of hemorrhagic fever with renal syndrome in China, 2005-2012.

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Wen-Yi Zhang

2014-11-01

Full Text Available Hemorrhagic fever with renal syndrome (HFRS is a rodent-borne disease caused by many serotypes of hantaviruses. In China, HFRS has been recognized as a severe public health problem with 90% of the total reported cases in the world. This study describes the spatiotemporal dynamics of HFRS cases in China and identifies the regions, time, and populations at highest risk, which could help the planning and implementation of key preventative measures.Data on all reported HFRS cases at the county level from January 2005 to December 2012 were collected from Chinese Center for Disease Control and Prevention. Geographic Information System-based spatiotemporal analyses including Local Indicators of Spatial Association and Kulldorff's space-time scan statistic were performed to detect local high-risk space-time clusters of HFRS in China. In addition, cases from high-risk and low-risk counties were compared to identify significant demographic differences.A total of 100,868 cases were reported during 2005-2012 in mainland China. There were significant variations in the spatiotemporal dynamics of HFRS. HFRS cases occurred most frequently in June, November, and December. There was a significant positive spatial autocorrelation of HFRS incidence during the study periods, with Moran's I values ranging from 0.46 to 0.56 (P<0.05. Several distinct HFRS cluster areas were identified, mainly concentrated in northeastern, central, and eastern of China. Compared with cases from low-risk areas, a higher proportion of cases were younger, non-farmer, and floating residents in high-risk counties.This study identified significant space-time clusters of HFRS in China during 2005-2012 indicating that preventative strategies for HFRS should be particularly focused on the northeastern, central, and eastern of China to achieve the most cost-effective outcomes.

Effects of Changing Weather, Oceanographic Conditions, and Land Uses on Spatio-Temporal Variation of Sedimentation Dynamics along Near-Shore Coral Reefs

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Abimarie Otaño-Cruz

2017-08-01

Full Text Available Sedimentation is a critical threat to coral reefs worldwide. Major land use alteration at steep, highly erodible semi-arid islands accelerates the potential of soil erosion, runoff, and sedimentation stress to nearshore coral reefs during extreme rainfall events. The goal of this study was to assess spatio-temporal variation of sedimentation dynamics across nearshore coral reefs as a function of land use patterns, weather and oceanographic dynamics, to identify marine ecosystem conservation strategies. Sediment was collected at a distance gradient from shore at Bahia Tamarindo (BTA and Punta Soldado (PSO coral reefs at Culebra Island, Puerto Rico. Sediment texture and composition were analyzed by dry sieving and loss-on-ignition techniques, and were contrasted with environmental variables for the research period (February 2014 to April 2015. Rainfall and oceanographic data were analyzed to address their potential role on affecting sediment distribution with BEST BIO-ENV, RELATE correlation, and linear regression analysis. A significant difference in sedimentation rate was observed by time and distance from shore (PERMANOVA, p < 0.0100, mostly attributed to higher sediment exposure at reef zones closer to shore due to strong relationships with coastal runoff. Sedimentation rate positively correlated with strong rainfall events (Rho = 0.301, p = 0.0400 associated with storms and rainfall intensity exceeding 15 mm/h. At BTA, sediment deposited were mostly composed of sand, suggesting a potential influence of resuspension produced by waves and swells. In contrast, PSO sediments were mostly composed of silt-clay and terrigenous material, mainly attributed to a deforestation event that occurred at adjacent steep sub-watershed during the study period. Spatial and temporal variation of sedimentation pulses and terrigenous sediment input implies that coral reefs exposure to sediment stress is determined by local land use patterns, weather, and

Guidelines for Assessment of Gait and Reference Values for Spatiotemporal Gait Parameters in Older Adults: The Biomathics and Canadian Gait Consortiums Initiative

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Olivier Beauchet

2017-08-01

Full Text Available Background: Gait disorders, a highly prevalent condition in older adults, are associated with several adverse health consequences. Gait analysis allows qualitative and quantitative assessments of gait that improves the understanding of mechanisms of gait disorders and the choice of interventions. This manuscript aims (1 to give consensus guidance for clinical and spatiotemporal gait analysis based on the recorded footfalls in older adults aged 65 years and over, and (2 to provide reference values for spatiotemporal gait parameters based on the recorded footfalls in healthy older adults free of cognitive impairment and multi-morbidities.Methods: International experts working in a network of two different consortiums (i.e., Biomathics and Canadian Gait Consortium participated in this initiative. First, they identified items of standardized information following the usual procedure of formulation of consensus findings. Second, they merged databases including spatiotemporal gait assessments with GAITRite® system and clinical information from the “Gait, cOgnitiOn & Decline” (GOOD initiative and the Generation 100 (Gen 100 study. Only healthy—free of cognitive impairment and multi-morbidities (i.e., ≤ 3 therapeutics taken daily—participants aged 65 and older were selected. Age, sex, body mass index, mean values, and coefficients of variation (CoV of gait parameters were used for the analyses.Results: Standardized systematic assessment of three categories of items, which were demographics and clinical information, and gait characteristics (clinical and spatiotemporal gait analysis based on the recorded footfalls, were selected for the proposed guidelines. Two complementary sets of items were distinguished: a minimal data set and a full data set. In addition, a total of 954 participants (mean age 72.8 ± 4.8 years, 45.8% women were recruited to establish the reference values. Performance of spatiotemporal gait parameters based on the recorded

Spatio-temporal data analytics for wind energy integration

CERN Document Server

Yang, Lei; Zhang, Junshan

2014-01-01

This SpringerBrief presents spatio-temporal data analytics for wind energy integration using stochastic modeling and optimization methods. It explores techniques for efficiently integrating renewable energy generation into bulk power grids. The operational challenges of wind, and its variability are carefully examined. A spatio-temporal analysis approach enables the authors to develop Markov-chain-based short-term forecasts of wind farm power generation. To deal with the wind ramp dynamics, a support vector machine enhanced Markov model is introduced. The stochastic optimization of economic di

Quantitative variation in obesity-related traits and insulin precursors linked to the OB gene region on human chromosome 7

Energy Technology Data Exchange (ETDEWEB)

Duggirala, R.; Stern, M.P.; Reinhart, L.J. [Univ. of Texas Health Science Center, San Antonio, TX (United States)] [and others

1996-09-01

Despite the evidence that human obesity has strong genetic determinants, efforts at identifying specific genes that influence human obesity have largely been unsuccessful. Using the sibship data obtained from 32 low-income Mexican American pedigrees ascertained on a type II diabetic proband and a multipoint variance-components method, we tested for linkage between various obesity-related traits plus associated metabolic traits and 15 markers on human chromosome 7. We found evidence for linkage between markers in the OB gene region and various traits, as follows: D7S514 and extremity skinfolds (LOD = 3.1), human carboxypeptidase A1 (HCPA1) and 32,33-split proinsulin level (LOD = 4.2), and HCPA1 and proinsulin level (LOD = 3.2). A putative susceptibility locus linked to the marker D7S514 explained 56% of the total phenotypic variation in extremity skinfolds. Variation at the HCPA1 locus explained 64% of phenotypic variation in proinsulin level and {approximately}73% of phenotypic variation in split proinsulin concentration, respectively. Weaker evidence for linkage to several other obesity-related traits (e.g., waist circumference, body-mass index, fat mass by bioimpedance, etc.) was observed for a genetic location, which is {approximately}15 cM telomeric to OB. In conclusion, our study reveals that the OB region plays a significant role in determining the phenotypic variation of both insulin precursors and obesity-related traits, at least in Mexican Americans. 66 refs., 3 figs., 4 tabs.

Spatiotemporal patterns and predictability of cyberattacks.

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Yu-Zhong Chen

Full Text Available A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term "spatio" refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack "fingerprints" and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches.

Spatio-temporal variation of organotin compounds in seawater and sediments from Cape Town harbour, South Africa using gas chromatography with flame photometric detector (GC-FPD

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Hussein K. Okoro

2016-01-01

Full Text Available The spatio-temporal variation of two organotin compounds (OTCs of tributyltin and triphenyltin in the seawater and sediment of Cape Town harbour was investigated. The organotin compounds were determined by GC-FPD following prior extraction with 0.02% tropolone. The concentration of OTCs varies for locations in Cape Town harbour. The concentration of OTCs in seawater ranges from 0.067 ± 0.01 to 111.290 ± 32.20 × 10−3 μg/l for TBT while that of TPT ranges between between ND ± SD and 23008.0 ± 0.03 × 10−3 μg/l respectively between locations. Relatively higher concentrations were measured for TBT and TPT during summer than in winter and spring seasons (p ⩽ 0.05. Apparently, the observed high or low values recorded for TBT in Cape Town harbour could be the result of an increase or decrease in the traffic of ships and boats. TBT was detected in all the sediment samples analysed except for location 9 (entrance to harbour, the two control sites (which are located far away from the inner harbour where boating activities are taking place, and location 12 (Robinson dry dock 2 where the samples were not at all found. For the control sites, antifouling compounds TBT and TPT were not detected throughout except for TBT that was found in control A during summer. The seasonal variation of OTC abundance in sediment was also investigated. The results indicated that TBT is present throughout the seasons but is predominantly present in this order summer > winter > spring.

Spatio-Temporal Variation and Futuristic Emission Scenario of Ambient Nitrogen Dioxide over an Urban Area of Eastern India Using GIS and Coupled AERMOD-WRF Model.

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Sharadia Dey

Full Text Available The present study focuses on the spatio-temporal variation of nitrogen dioxide (NO2 during June 2013 to May 2015 and its futuristic emission scenario over an urban area (Durgapur of eastern India. The concentration of ambient NO2 shows seasonal as well as site specific characteristics. The site with high vehicular density (Muchipara shows highest NO2 concentration followed by industrial site (DVC- DTPS Colony and the residential site (B Zone, respectively. The seasonal variation of ambient NO2 over the study area is portrayed by means of Geographical Information System based Digital Elevation Model. Out of the total urban area under consideration (114.982 km2, the concentration of NO2 exceeded the National Ambient Air Quality Standard (NAAQS permissible limit over an area of 5.000 km2, 0.786 km2 and 0.653 km2 in post monsoon, winter and pre monsoon, respectively. Wind rose diagrams, correlation and regression analyses show that meteorology plays a crucial role in dilution and dispersion of NO2 near the earth's surface. Principal component analysis identifies vehicular source as the major source of NO2 in all the seasons over the urban region. Coupled AMS/EPA Regulatory Model (AERMOD-Weather Research and Forecasting (WRF model is used for predicting the concentration of NO2. Comparison of the observed and simulated data shows that the model overestimates the concentration of NO2 in all the seasons (except winter. The results show that coupled AERMOD-WRF model can overcome the unavailability of hourly surface as well as upper air meteorological data required for predicting the pollutant concentration, but improvement of emission inventory along with better understanding of the sinks and sources of ambient NO2 is essential for capturing the more realistic scenario.

Genetic Variation in Cardiomyopathy and Cardiovascular Disorders.

Science.gov (United States)

McNally, Elizabeth M; Puckelwartz, Megan J

2015-01-01

With the wider deployment of massively-parallel, next-generation sequencing, it is now possible to survey human genome data for research and clinical purposes. The reduced cost of producing short-read sequencing has now shifted the burden to data analysis. Analysis of genome sequencing remains challenged by the complexity of the human genome, including redundancy and the repetitive nature of genome elements and the large amount of variation in individual genomes. Public databases of human genome sequences greatly facilitate interpretation of common and rare genetic variation, although linking database sequence information to detailed clinical information is limited by privacy and practical issues. Genetic variation is a rich source of knowledge for cardiovascular disease because many, if not all, cardiovascular disorders are highly heritable. The role of rare genetic variation in predicting risk and complications of cardiovascular diseases has been well established for hypertrophic and dilated cardiomyopathy, where the number of genes that are linked to these disorders is growing. Bolstered by family data, where genetic variants segregate with disease, rare variation can be linked to specific genetic variation that offers profound diagnostic information. Understanding genetic variation in cardiomyopathy is likely to help stratify forms of heart failure and guide therapy. Ultimately, genetic variation may be amenable to gene correction and gene editing strategies.

Exploring the Spatiotemporal Organization of Membrane Proteins in Living Plant Cells.

Science.gov (United States)

Wang, Li; Xue, Yiqun; Xing, Jingjing; Song, Kai; Lin, Jinxing

2018-04-29

Plasma membrane proteins have important roles in transport and signal transduction. Deciphering the spatiotemporal organization of these proteins provides crucial information for elucidating the links between the behaviors of different molecules. However, monitoring membrane proteins without disrupting their membrane environment remains difficult. Over the past decade, many studies have developed single-molecule techniques, opening avenues for probing the stoichiometry and interactions of membrane proteins in their native environment by providing nanometer-scale spatial information and nanosecond-scale temporal information. In this review, we assess recent progress in the development of labeling and imaging technology for membrane protein analysis. We focus in particular on several single-molecule techniques for quantifying the dynamics and assembly of membrane proteins. Finally, we provide examples of how these new techniques are advancing our understanding of the complex biological functions of membrane proteins.

Research of Cadastral Data Modelling and Database Updating Based on Spatio-temporal Process

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ZHANG Feng

2016-02-01

Full Text Available The core of modern cadastre management is to renew the cadastre database and keep its currentness,topology consistency and integrity.This paper analyzed the changes and their linkage of various cadastral objects in the update process.Combined object-oriented modeling technique with spatio-temporal objects' evolution express,the paper proposed a cadastral data updating model based on the spatio-temporal process according to people's thought.Change rules based on the spatio-temporal topological relations of evolution cadastral spatio-temporal objects are drafted and further more cascade updating and history back trace of cadastral features,land use and buildings are realized.This model implemented in cadastral management system-ReGIS.Achieved cascade changes are triggered by the direct driving force or perceived external events.The system records spatio-temporal objects' evolution process to facilitate the reconstruction of history,change tracking,analysis and forecasting future changes.

An implicit spatiotemporal shape model for human activity localization and recognition

NARCIS (Netherlands)

Oikonomopoulos, A.; Patras, I.; Pantic, Maja

2009-01-01

In this paper we address the problem of localisation and recognition of human activities in unsegmented image sequences. The main contribution of the proposed method is the use of an implicit representation of the spatiotemporal shape of the activity which relies on the spatiotemporal localization

Limited mobility of target pests crucially lowers controllability when sterile insect releases are spatiotemporally biased.

Science.gov (United States)

Ikegawa, Yusuke; Himuro, Chihiro

2017-05-21

The sterile insect technique (SIT) is a genetic pest control method wherein mass-reared sterile insects are periodically released into the wild, thereby impeding the successful reproduction of fertile pests. In Okinawa Prefecture, Japan, the SIT has been implemented to eradicate the West Indian sweet potato weevil Euscepes postfasciatus (Fairmaire), which is a flightless agricultural pest of sweet potatoes. It is known that E. postfasciatus is much less mobile than other insects to which the SIT has been applied. However, previous theoretical studies have rarely examined effects of low mobility of target pests and variation in the spatiotemporal evenness of sterile insect releases. To theoretically examine the effects of spatiotemporal evenness on the regional eradication of less mobile pests, we constructed a simple two-patch population model comprised of a pest and sterile insect moving between two habitats, and numerically simulated different release strategies (varying the number of released sterile insects and release intervals). We found that spatially biased releases allowed the pest to spatially escape from the sterile insect, and thus intensively lowered its controllability. However, we showed that the temporally counterbalancing spatially biased releases by swapping the number of released insects in the two habitats at every release (called temporal balancing) could greatly mitigate this negative effect and promote the controllability. We also showed that the negative effect of spatiotemporally biased releases was a result of the limited mobility of the target insect. Although directed dispersal of the insects in response to habitats of differing quality could lower the controllability in the more productive habitat, the temporal balancing could promote and eventually maximize the controllability as released insects increased. Copyright © 2017 Elsevier Ltd. All rights reserved.

What Is Spatio-Temporal Data Warehousing?

Science.gov (United States)

Vaisman, Alejandro; Zimányi, Esteban

In the last years, extending OLAP (On-Line Analytical Processing) systems with spatial and temporal features has attracted the attention of the GIS (Geographic Information Systems) and database communities. However, there is no a commonly agreed definition of what is a spatio-temporal data warehouse and what functionality such a data warehouse should support. Further, the solutions proposed in the literature vary considerably in the kind of data that can be represented as well as the kind of queries that can be expressed. In this paper we present a conceptual framework for defining spatio-temporal data warehouses using an extensible data type system. We also define a taxonomy of different classes of queries of increasing expressive power, and show how to express such queries using an extension of the tuple relational calculus with aggregated functions.

Spatio-temporal modeling of nonlinear distributed parameter systems

CERN Document Server

Li, Han-Xiong

2011-01-01

The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s

Visualization of Spatio-Temporal Relations in Movement Event Using Multi-View

Science.gov (United States)

Zheng, K.; Gu, D.; Fang, F.; Wang, Y.; Liu, H.; Zhao, W.; Zhang, M.; Li, Q.

2017-09-01

Spatio-temporal relations among movement events extracted from temporally varying trajectory data can provide useful information about the evolution of individual or collective movers, as well as their interactions with their spatial and temporal contexts. However, the pure statistical tools commonly used by analysts pose many difficulties, due to the large number of attributes embedded in multi-scale and multi-semantic trajectory data. The need for models that operate at multiple scales to search for relations at different locations within time and space, as well as intuitively interpret what these relations mean, also presents challenges. Since analysts do not know where or when these relevant spatio-temporal relations might emerge, these models must compute statistical summaries of multiple attributes at different granularities. In this paper, we propose a multi-view approach to visualize the spatio-temporal relations among movement events. We describe a method for visualizing movement events and spatio-temporal relations that uses multiple displays. A visual interface is presented, and the user can interactively select or filter spatial and temporal extents to guide the knowledge discovery process. We also demonstrate how this approach can help analysts to derive and explain the spatio-temporal relations of movement events from taxi trajectory data.

VISUALIZATION OF SPATIO-TEMPORAL RELATIONS IN MOVEMENT EVENT USING MULTI-VIEW

Directory of Open Access Journals (Sweden)

K. Zheng

2017-09-01

Full Text Available Spatio-temporal relations among movement events extracted from temporally varying trajectory data can provide useful information about the evolution of individual or collective movers, as well as their interactions with their spatial and temporal contexts. However, the pure statistical tools commonly used by analysts pose many difficulties, due to the large number of attributes embedded in multi-scale and multi-semantic trajectory data. The need for models that operate at multiple scales to search for relations at different locations within time and space, as well as intuitively interpret what these relations mean, also presents challenges. Since analysts do not know where or when these relevant spatio-temporal relations might emerge, these models must compute statistical summaries of multiple attributes at different granularities. In this paper, we propose a multi-view approach to visualize the spatio-temporal relations among movement events. We describe a method for visualizing movement events and spatio-temporal relations that uses multiple displays. A visual interface is presented, and the user can interactively select or filter spatial and temporal extents to guide the knowledge discovery process. We also demonstrate how this approach can help analysts to derive and explain the spatio-temporal relations of movement events from taxi trajectory data.

Characterization of the Spatial and Temporal Variations of Submarine Groundwater Discharge Using Electrical Resistivity and Seepage Measurements

Science.gov (United States)

Durand, Josephine Miryam Kalyanie

Submarine groundwater discharge (SGD) encompasses all fluids crossing the sediment/ocean interface, regardless of their origin, composition or driving forces. SGD provides a pathway for terrestrial contaminants that can significantly impact coastal ecosystems. Overexploitation of groundwater resources can decrease SGD which favors seawater intrusion at depth. Understanding SGD is therefore crucial for water quality and resource management. Quantifying SGD is challenging due to its diffuse and heterogeneous nature, in addition to significant spatio-temporal variations at multiple scales. In this thesis, an integrated approach combining electrical resistivity (ER) surveys, conductivity and temperature point measurements, seepage rates using manual and ultrasonic seepage meters, and pore fluid salinities was used to characterize SGD spatio-temporal variations and their implications for contaminant transport at several locations on Long Island, NY. The influence of surficial sediments on SGD distribution was investigated in Stony Brook Harbor. A low-permeability mud layer, actively depositing in the harbor, limits SGD at the shoreline, prevents mixing with seawater and channels a significant volume of freshwater offshore. SGD measured at locations without mud is high and indicates significant mixing between porewater and seawater. A 2D steady-state density-difference numerical model of the harbor was developed using SEAWAT and was validated by our field observations. Temporal variations of SGD due to semi-diurnal tidal forcing were studied in West Neck Bay, Shelter Island, using a 12-hr time-lapse ER survey together with continuous salinity and seepage measurements in the intertidal zone. The observed dynamic patterns of groundwater flux and salinity distribution disagree with published standard transient state numerical models, suggesting the need for developing more specific models of non-homogeneous anisotropic aquifers. SGD distribution and composition were

Soil Moisture Retrieval and Spatiotemporal Pattern Analysis Using Sentinel-1 Data of Dahra, Senegal

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Zhiqu Liu

2017-11-01

Full Text Available The spatiotemporal pattern of soil moisture is of great significance for the understanding of the water exchange between the land surface and the atmosphere. The two-satellite constellation of the Sentinel-1 mission provides C-band synthetic aperture radar (SAR observations with high spatial and temporal resolutions, which are suitable for soil moisture monitoring. In this paper, we aim to assess the capability of pattern analysis based on the soil moisture retrieved from Sentinel-1 time-series data of Dahra in Senegal. The look-up table (LUT method is used in the retrieval with the backscattering coefficients that are simulated by the advanced integrated equation Model (AIEM for the soil layer and the Michigan microwave canopy scattering (MIMICS model for the vegetation layer. The temporal trend of Sentinel-1A soil moisture is evaluated by the ground measurements from the site at Dahra, with an unbiased root-mean-squared deviation (ubRMSD of 0.053 m3/m3, a mean average deviation (MAD of 0.034 m3/m3, and an R value of 0.62. The spatial variation is also compared with the existing microwave products at a coarse scale, which confirms the reliability of the Sentinel-1A soil moisture. The spatiotemporal patterns are analyzed by empirical orthogonal functions (EOF, and the geophysical factors that are affecting soil moisture are discussed. The first four EOFs of soil moisture explain 77.2% of the variance in total and the primary EOF explains 66.2%, which shows the dominant pattern at the study site. Soil texture and the normalized difference vegetation index are more closely correlated with the primary pattern than the topography and temperature in the study area. The investigation confirms the potential for soil moisture retrieval and spatiotemporal pattern analysis using Sentinel-1 images.

Self-organization of spatio-temporal earthquake clusters

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S. Hainzl

2000-01-01

Full Text Available Cellular automaton versions of the Burridge-Knopoff model have been shown to reproduce the power law distribution of event sizes; that is, the Gutenberg-Richter law. However, they have failed to reproduce the occurrence of foreshock and aftershock sequences correlated with large earthquakes. We show that in the case of partial stress recovery due to transient creep occurring subsequently to earthquakes in the crust, such spring-block systems self-organize into a statistically stationary state characterized by a power law distribution of fracture sizes as well as by foreshocks and aftershocks accompanying large events. In particular, the increase of foreshock and the decrease of aftershock activity can be described by, aside from a prefactor, the same Omori law. The exponent of the Omori law depends on the relaxation time and on the spatial scale of transient creep. Further investigations concerning the number of aftershocks, the temporal variation of aftershock magnitudes, and the waiting time distribution support the conclusion that this model, even "more realistic" physics in missed, captures in some ways the origin of the size distribution as well as spatio-temporal clustering of earthquakes.

Wave fronts and spatiotemporal chaos in an array of coupled Lorenz oscillators

International Nuclear Information System (INIS)

Pazo, Diego; Montejo, Noelia; Perez-Munuzuri, Vicente

2001-01-01

The effects of coupling strength and single-cell dynamics (SCD) on spatiotemporal pattern formation are studied in an array of Lorenz oscillators. Different spatiotemporal structures (stationary patterns, propagating wave fronts, short wavelength bifurcation) arise for bistable SCD, and two well differentiated types of spatiotemporal chaos for chaotic SCD (in correspondence with the transition from stationary patterns to propagating fronts). Wave-front propagation in the bistable regime is studied in terms of global bifurcation theory, while a short wavelength pattern region emerges through a pitchfork bifurcation

A flexible spatiotemporal method for fusing satellite images with different resolutions

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Xiaolin Zhu; Eileen H. Helmer; Feng Gao; Desheng Liu; Jin Chen; Michael A. Lefsky

2016-01-01

Studies of land surface dynamics in heterogeneous landscapes often require remote sensing datawith high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta Fusion (FSDAF) method, to generate synthesized frequent high spatial...

Towards linked open gene mutations data

Science.gov (United States)

2012-01-01

Background With the advent of high-throughput technologies, a great wealth of variation data is being produced. Such information may constitute the basis for correlation analyses between genotypes and phenotypes and, in the future, for personalized medicine. Several databases on gene variation exist, but this kind of information is still scarce in the Semantic Web framework. In this paper, we discuss issues related to the integration of mutation data in the Linked Open Data infrastructure, part of the Semantic Web framework. We present the development of a mapping from the IARC TP53 Mutation database to RDF and the implementation of servers publishing this data. Methods A version of the IARC TP53 Mutation database implemented in a relational database was used as first test set. Automatic mappings to RDF were first created by using D2RQ and later manually refined by introducing concepts and properties from domain vocabularies and ontologies, as well as links to Linked Open Data implementations of various systems of biomedical interest. Since D2RQ query performances are lower than those that can be achieved by using an RDF archive, generated data was also loaded into a dedicated system based on tools from the Jena software suite. Results We have implemented a D2RQ Server for TP53 mutation data, providing data on a subset of the IARC database, including gene variations, somatic mutations, and bibliographic references. The server allows to browse the RDF graph by using links both between classes and to external systems. An alternative interface offers improved performances for SPARQL queries. The resulting data can be explored by using any Semantic Web browser or application. Conclusions This has been the first case of a mutation database exposed as Linked Data. A revised version of our prototype, including further concepts and IARC TP53 Mutation database data sets, is under development. The publication of variation information as Linked Data opens new perspectives

Towards linked open gene mutations data.

Science.gov (United States)

Zappa, Achille; Splendiani, Andrea; Romano, Paolo

2012-03-28

With the advent of high-throughput technologies, a great wealth of variation data is being produced. Such information may constitute the basis for correlation analyses between genotypes and phenotypes and, in the future, for personalized medicine. Several databases on gene variation exist, but this kind of information is still scarce in the Semantic Web framework. In this paper, we discuss issues related to the integration of mutation data in the Linked Open Data infrastructure, part of the Semantic Web framework. We present the development of a mapping from the IARC TP53 Mutation database to RDF and the implementation of servers publishing this data. A version of the IARC TP53 Mutation database implemented in a relational database was used as first test set. Automatic mappings to RDF were first created by using D2RQ and later manually refined by introducing concepts and properties from domain vocabularies and ontologies, as well as links to Linked Open Data implementations of various systems of biomedical interest. Since D2RQ query performances are lower than those that can be achieved by using an RDF archive, generated data was also loaded into a dedicated system based on tools from the Jena software suite. We have implemented a D2RQ Server for TP53 mutation data, providing data on a subset of the IARC database, including gene variations, somatic mutations, and bibliographic references. The server allows to browse the RDF graph by using links both between classes and to external systems. An alternative interface offers improved performances for SPARQL queries. The resulting data can be explored by using any Semantic Web browser or application. This has been the first case of a mutation database exposed as Linked Data. A revised version of our prototype, including further concepts and IARC TP53 Mutation database data sets, is under development.The publication of variation information as Linked Data opens new perspectives: the exploitation of SPARQL searches on

[DIAGNOSTIC VARIATIONS OF X-LINKED MUSCULAR DYSTROPHY WITH CONTRACTURES].

Science.gov (United States)

Kvirkvelia, N; Shakarishvili, R; Gugutsidze, D; Khizanishvili, N

2015-01-01

Case report with review describes X-linked muscular dystrophy with contractures in 28 years old man and his cousin. The disease revealed itself in an early stage (age 5-10), the process was progressing with apparent tendons retraction and contraction, limited movement in the areas of the neck and back of spine, atrophy of shoulder and pelvic yard and back muscles. Intellect was intact. Cardyomyopathy was exhibited. CK was normal. EMG showed classic myopathic features. Muscle biopsy showed different caliber groups of muscle fibers, growth of endo-perimesial connective tissue. Clinical manifestations together with electrophysiological and histological data suggest consistency with Rotthauwe-Mortier-Bayer X-linked muscular dystrophy.

ELASTIC CLOUD COMPUTING ARCHITECTURE AND SYSTEM FOR HETEROGENEOUS SPATIOTEMPORAL COMPUTING

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X. Shi

2017-10-01

Full Text Available Spatiotemporal computation implements a variety of different algorithms. When big data are involved, desktop computer or standalone application may not be able to complete the computation task due to limited memory and computing power. Now that a variety of hardware accelerators and computing platforms are available to improve the performance of geocomputation, different algorithms may have different behavior on different computing infrastructure and platforms. Some are perfect for implementation on a cluster of graphics processing units (GPUs, while GPUs may not be useful on certain kind of spatiotemporal computation. This is the same situation in utilizing a cluster of Intel's many-integrated-core (MIC or Xeon Phi, as well as Hadoop or Spark platforms, to handle big spatiotemporal data. Furthermore, considering the energy efficiency requirement in general computation, Field Programmable Gate Array (FPGA may be a better solution for better energy efficiency when the performance of computation could be similar or better than GPUs and MICs. It is expected that an elastic cloud computing architecture and system that integrates all of GPUs, MICs, and FPGAs could be developed and deployed to support spatiotemporal computing over heterogeneous data types and computational problems.

Elastic Cloud Computing Architecture and System for Heterogeneous Spatiotemporal Computing

Science.gov (United States)

Shi, X.

2017-10-01

Spatiotemporal computation implements a variety of different algorithms. When big data are involved, desktop computer or standalone application may not be able to complete the computation task due to limited memory and computing power. Now that a variety of hardware accelerators and computing platforms are available to improve the performance of geocomputation, different algorithms may have different behavior on different computing infrastructure and platforms. Some are perfect for implementation on a cluster of graphics processing units (GPUs), while GPUs may not be useful on certain kind of spatiotemporal computation. This is the same situation in utilizing a cluster of Intel's many-integrated-core (MIC) or Xeon Phi, as well as Hadoop or Spark platforms, to handle big spatiotemporal data. Furthermore, considering the energy efficiency requirement in general computation, Field Programmable Gate Array (FPGA) may be a better solution for better energy efficiency when the performance of computation could be similar or better than GPUs and MICs. It is expected that an elastic cloud computing architecture and system that integrates all of GPUs, MICs, and FPGAs could be developed and deployed to support spatiotemporal computing over heterogeneous data types and computational problems.

Spatio-Temporal Distribution of Landslides in Java and the Triggering Factors

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Danang Sri Hadmoko

2017-07-01

Full Text Available Java Island, the most populated island of Indonesia, is prone to landslide disasters. Their occurrence and impact have increased mainly as the result of natural factors, aggravated by human imprint. This paper is intended to analyse: (1 the spatio-temporal variation of landslides in Java during short term and long-term periods, and (2 their causative factors such as rainfall, topography, geology, earthquakes, and land-use. The evaluation spatially and temporally of historical landslides and consequences were based on the landslide database covering the period of 1981 – 2007 in the GIS environment. Database showed that landslides distributed unevenly between West Java (67 %, Central Java (29 % and East Java (4 %. Slope failures were most abundant on the very intensively weathered zone of old volcanic materials on slope angles of 30O – 40O. Rainfall threshold analysis showed that shallow landslides and deep-seated landslides were triggered by rainfall events of 300 – 600 mm and > 600 mm respectively of antecedent rainfall during 30 consecutive days, and many cases showed that the landslides were not always initiated by intense rainfall during the landslide day. Human interference plays an important role in landslide occurrence through land conversion from natural forest to dryland agriculture which was the host of most of landslides in Java. These results and methods can be used as valuable information on the spatio-temporal characteristics of landslides in Java and their relationship with causative factors, thereby providing a sound basis for landslide investigation in more detail.

Validation and Spatiotemporal Distribution of GEOS-5-Based Planetary Boundary Layer Height and Relative Humidity in China

Science.gov (United States)

Si, Yidan; Li, Shenshen; Chen, Liangfu; Yu, Chao; Wang, Zifeng; Wang, Yang; Wang, Hongmei

2018-04-01

Few studies have specifically focused on the validation and spatiotemporal distribution of planetary boundary layer height (PBLH) and relative humidity (RH) data in China. In this analysis, continuous PBLH and surface-level RH data simulated from GEOS-5 between 2004 and 2012, were validated against ground-based observations. Overall, the simulated RH was consistent with the statistical data from meteorological stations, with a correlation coefficient of 0.78 and a slope of 0.9. However, the simulated PBLH was underestimated compared to LIDAR data by a factor of approximately two, which was primarily because of poor simulation in late summer and early autumn. We further examined the spatiotemporal distribution characteristics of two factors in four regions—North China, South China, Northwest China, and the Tibetan Plateau. The results showed that the annual PBLH trends in all regions were fairly moderate but sensitive to solar radiation and precipitation, which explains why the PBLH values were ranked in order from largest to smallest as follows: Tibetan Plateau, Northwest China, North China, and South China. Strong seasonal variation of the PBLH exhibited high values in summer and low values in winter, which was also consistent with the turbulent vertical exchange. Not surprisingly, the highest RH in South China and the lowest RH in desert areas of Northwest China (less than 30%). Seasonally, South China exhibited little variation, whereas Northwest China exhibited its highest humidity in winter and lowest humidity in spring, the maximum values in the other regions were obtained from July to September.

Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

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Haiyang Yu

2017-06-01

Full Text Available Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs, for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs and long short-term memory (LSTM neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.

Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks.

Science.gov (United States)

Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei

2017-06-26

Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.

Artificial neural network does better spatiotemporal compressive sampling

Science.gov (United States)

Lee, Soo-Young; Hsu, Charles; Szu, Harold

2012-06-01

Spatiotemporal sparseness is generated naturally by human visual system based on artificial neural network modeling of associative memory. Sparseness means nothing more and nothing less than the compressive sensing achieves merely the information concentration. To concentrate the information, one uses the spatial correlation or spatial FFT or DWT or the best of all adaptive wavelet transform (cf. NUS, Shen Shawei). However, higher dimensional spatiotemporal information concentration, the mathematics can not do as flexible as a living human sensory system. The reason is obviously for survival reasons. The rest of the story is given in the paper.

Variation in the Norwegian gyre and its links to the termohaline circulation (THC).

Science.gov (United States)

Gunnarson, B. E.; Linderholm, H. W.; Wilson, R.; Rydval, M.

2017-12-01

Summer temperature patterns in Scandinavia are partly governed by variations in the North Atlantic drift (being part of the Gulf Stream) causing northern Europe to be warmer than similar latitudes. Observation show that northwestern European climate is strongly link to sea surface temperature (SST) and the ocean circulation (the Norwegian gyre, NG) in the Norwegian Sea. On decadal- multidecadal time scales, there is also positive association with the sub-tropical gyre, but also a weaker (and negative) connection to the sub Polar gyre (SPG) which is linked to the thermohaline circulation (THC). The negative correlations occur only during the April-June and July-September (JAS) seasons, when the ocean mixed layer is shallow in the North Atlantic. A network of Maximum Latewood Density (MXD) tree-ring chronologies from 7 sites in Northern Scandinavia, 1 in central Scotland and 1 in Labrador was used to identifying SST influences on local to regional summer temperatures patterns during 1901-20XX. The sites represent tree growth strongly correlated with mean JAS temperatures (Fennoscandia r > 0.7, Scotland r > 0.6, Labrador r > 0.5). Both the Scotland and Labrador chronologies correlates only with SST from adjacent coastal areas. The Fennoscandian chronologies showed strong and temporally consistent correlations with SST across the NG (r > 0.5), but also positive correlations of the same magnitude across the sub-tropical gyre. In addition, a negative, but weaker, correlation was found over the SPG domain. Climate models (PMIP5) were not able to reproduce the correlation patterns evident in both observations and tree-ring data. The tripolar correlation pattern suggests that North Atlantic SST influences summer temperature variability in Northern Fennoscandia, illustrating the potential for using tree-rings to reconstruct the THC and the heat transport towards the North Atlantic region and atmosphere- ocean interaction back in time.

Estimating the state of large spatio-temporally chaotic systems

International Nuclear Information System (INIS)

Ott, E.; Hunt, B.R.; Szunyogh, I.; Zimin, A.V.; Kostelich, E.J.; Corazza, M.; Kalnay, E.; Patil, D.J.; Yorke, J.A.

2004-01-01

We consider the estimation of the state of a large spatio-temporally chaotic system from noisy observations and knowledge of a system model. Standard state estimation techniques using the Kalman filter approach are not computationally feasible for systems with very many effective degrees of freedom. We present and test a new technique (called a Local Ensemble Kalman Filter), generally applicable to large spatio-temporally chaotic systems for which correlations between system variables evaluated at different points become small at large separation between the points

Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA.

Science.gov (United States)

Cao, Xiaodong; MacNaughton, Piers; Deng, Zhengyi; Yin, Jie; Zhang, Xi; Allen, Joseph G

2018-02-02

Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA), USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface) was employed to quantify the sentiment scores conveyed by tweets on a large scale. Then we statistically analyzed the sentiment scores across different spaces and times. A multivariate linear mixed-effects model was used to quantify the fixed effects of land use and the time period on the variations in sentiment scores, considering the clustering effect of users. The results exposed clear spatiotemporal patterns of users' sentiment. Higher sentiment scores were mainly observed in the commercial and public areas, during the noon/evening and on weekends. Our findings suggest that social media outputs can be used to better understand the spatial and temporal patterns of public happiness and well-being in cities and regions.

Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA

Directory of Open Access Journals (Sweden)

Xiaodong Cao

2018-02-01

Full Text Available Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA, USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface was employed to quantify the sentiment scores conveyed by tweets on a large scale. Then we statistically analyzed the sentiment scores across different spaces and times. A multivariate linear mixed-effects model was used to quantify the fixed effects of land use and the time period on the variations in sentiment scores, considering the clustering effect of users. The results exposed clear spatiotemporal patterns of users’ sentiment. Higher sentiment scores were mainly observed in the commercial and public areas, during the noon/evening and on weekends. Our findings suggest that social media outputs can be used to better understand the spatial and temporal patterns of public happiness and well-being in cities and regions.

Statistical methods for spatio-temporal systems

CERN Document Server

Finkenstadt, Barbel

2006-01-01

Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities.Contributed by leading researchers in the field, each self-contained chapter starts with an introduction of the topic and progresses to recent research results. Presenting specific examples of epidemic data of bovine tuberculosis, gastroenteric disease, and the U.K. foot-and-mouth outbreak, the first chapter uses stochastic models, such as point process models, to provide the probabilistic backbone that facilitates statistical inference from data. The next chapter discusses the critical issue of modeling random growth objects in diverse biological systems, such as bacteria colonies, tumors, and plant populations. The subsequent chapter examines data transformation tools using examples from ecology and air quality data, followed by a chapter on space-time co...

Assessment of spatio-temporal gait parameters from trunk accelerations during human walking

NARCIS (Netherlands)

Zijlstra, W; Hof, AL

2003-01-01

This paper studies the feasibility of an analysis of spatio-temporal gait parameters based upon accelerometry. To this purpose, acceleration patterns of the trunk and their relationships with spatio-temporal gait parameters were analysed in healthy subjects. Based on model predictions of the body's

An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics

Science.gov (United States)

Williams, Perry J.; Hooten, Mevin B.; Womble, Jamie N.; Esslinger, George G.; Bower, Michael R.; Hefley, Trevor J.

2017-01-01

Ecological invasions and colonizations occur dynamically through space and time. Estimating the distribution and abundance of colonizing species is critical for efficient management or conservation. We describe a statistical framework for simultaneously estimating spatiotemporal occupancy and abundance dynamics of a colonizing species. Our method accounts for several issues that are common when modeling spatiotemporal ecological data including multiple levels of detection probability, multiple data sources, and computational limitations that occur when making fine-scale inference over a large spatiotemporal domain. We apply the model to estimate the colonization dynamics of sea otters (Enhydra lutris) in Glacier Bay, in southeastern Alaska.

Linking Soil Moisture Variation and Abundance of Plants to Geomorphic Processes: A Generalized Model for Erosion-Uplifting Landscapes

Science.gov (United States)

Ding, Junyan; Johnson, Edward A.; Martin, Yvonne E.

2018-03-01

The diffusive and advective erosion-created landscapes have similar structure (hillslopes and channels) across different scales regardless of variations in drivers and controls. The relative magnitude of diffusive erosion to advective erosion (D/K ratio) in a landscape development model controls hillslope length, shape, and drainage density, which regulate soil moisture variation, one of the critical resources of plants, through the contributing area (A) and local slope (S) represented by a topographic index (TI). Here we explore the theoretical relation between geomorphic processes, TI, and the abundance and distribution of plants. We derived an analytical model that expresses the TI with D, K, and A. This gives us the relation between soil moisture variation and geomorphic processes. Plant tolerance curves are used to link plant performance to soil moisture. Using the hypothetical tolerance curves of three plants, we show that the abundance and distribution of xeric, mesic, and hydric plants on the landscape are regulated by the D/K ratio. Where diffusive erosion is the major erosion process (large D/K ratio), mesic plants have higher abundance relative to xeric and hydric plants and the landscape has longer and convex-upward hillslope and low channel density. Increasing the dominance of advective erosion increases relative abundance of xeric and hydric plants dominance, and the landscape has short and concave hillslope and high channel density.

Spatio-Temporal Saliency Perception via Hypercomplex Frequency Spectral Contrast

Directory of Open Access Journals (Sweden)

Zhiqiang Tian

2013-03-01

Full Text Available Salient object perception is the process of sensing the salient information from the spatio-temporal visual scenes, which is a rapid pre-attention mechanism for the target location in a visual smart sensor. In recent decades, many successful models of visual saliency perception have been proposed to simulate the pre-attention behavior. Since most of the methods usually need some ad hoc parameters or high-cost preprocessing, they are difficult to rapidly detect salient object or be implemented by computing parallelism in a smart sensor. In this paper, we propose a novel spatio-temporal saliency perception method based on spatio-temporal hypercomplex spectral contrast (HSC. Firstly, the proposed HSC algorithm represent the features in the HSV (hue, saturation and value color space and features of motion by a hypercomplex number. Secondly, the spatio-temporal salient objects are efficiently detected by hypercomplex Fourier spectral contrast in parallel. Finally, our saliency perception model also incorporates with the non-uniform sampling, which is a common phenomenon of human vision that directs visual attention to the logarithmic center of the image/video in natural scenes. The experimental results on the public saliency perception datasets demonstrate the effectiveness of the proposed approach compared to eleven state-of-the-art approaches. In addition, we extend the proposed model to moving object extraction in dynamic scenes, and the proposed algorithm is superior to the traditional algorithms.

Oscillations, complex spatiotemporal behavior, and information transport in networks of excitatory and inhibitory neurons

International Nuclear Information System (INIS)

Destexhe, A.

1994-01-01

Various types of spatiotemporal behavior are described for two-dimensional networks of excitatory and inhibitory neurons with time delayed interactions. It is described how the network behaves as several structural parameters are varied, such as the number of neurons, the connectivity, and the values of synaptic weights. A transition from spatially uniform oscillations to spatiotemporal chaos via intermittentlike behavior is observed. The properties of spatiotemporally chaotic solutions are investigated by evaluating the largest positive Lyapunov exponent and the loss of correlation with distance. Finally, properties of information transport are evaluated during uniform oscillations and spatiotemporal chaos. It is shown that the diffusion coefficient increases significantly in the spatiotemporal phase similar to the increase of transport coefficients at the onset of fluid turbulence. It is proposed that such a property should be seen in other media, such as chemical turbulence or networks of oscillators. The possibility of measuring information transport from appropriate experiments is also discussed

Spatio-Temporal Data Mining for Location-Based Services

DEFF Research Database (Denmark)

Gidofalvi, Gyozo

. The objectives of the presented thesis are three-fold. First, to extend popular data mining methods to the spatio-temporal domain. Second, to demonstrate the usefulness of the extended methods and the derived knowledge in promising LBS examples. Finally, to eliminate privacy concerns in connection with spatio......-temporal data mining by devising systems for privacy-preserving location data collection and mining.......Location-Based Services (LBS) are continuously gaining popularity. Innovative LBSes integrate knowledge about the users into the service. Such knowledge can be derived by analyzing the location data of users. Such data contain two unique dimensions, space and time, which need to be analyzed...

Spatio-temporal modeling for residential burglary

NARCIS (Netherlands)

Mahfoud, M.; Bhulai, Sandjai; van der Mei, R.D.; Bhulai, Sandjai; Kardaras, Dimitris

2017-01-01

Spatio-temporal modeling is widely recognized as a promising means for predicting crime patterns. Despite their enormous potential, the available methods are still in their infancy. A lot of research focuses on crime hotspot detection and geographic crime clusters, while a systematic approach to

INCREMENTAL PRINCIPAL COMPONENT ANALYSIS BASED OUTLIER DETECTION METHODS FOR SPATIOTEMPORAL DATA STREAMS

Directory of Open Access Journals (Sweden)

A. Bhushan

2015-07-01

Full Text Available In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

A FRAMEWORK FOR ONLINE SPATIO-TEMPORAL DATA VISUALIZATION BASED ON HTML5

Directory of Open Access Journals (Sweden)

B. Mao

2012-07-01

Full Text Available Web is entering a new phase – HTML5. New features of HTML5 should be studied for online spatio-temporal data visualization. In the proposed framework, spatio-temporal data is stored in the data server and is sent to user browsers with WebSocket. Public geo-data such as Internet digital map is integrated into the browsers. Then animation is implemented through the canvas object defined by the HTML5 specification. To simulate the spatio-temporal data source, we collected the daily location of 15 users with GPS tracker. The current positions of the users are collected every minute and are recorded in a file. Based on this file, we generate a real time spatio-temporal data source which sends out current user location every second.By enlarging the real time scales by 60 times, we can observe the movement clearly. The data transmitted with WebSocket is the coordinates of users' current positions, which will can be demonstrated in client browsers.

Spatio-temporal variations in the composition of organic matter in surface sediments of a mangrove receiving shrimp farm effluents (New Caledonia)

International Nuclear Information System (INIS)

Aschenbroich, Adélaïde; Marchand, Cyril; Molnar, Nathalie; Deborde, Jonathan; Hubas, Cédric; Rybarczyk, Hervé; Meziane, Tarik

2015-01-01

In order to investigate spatio-temporal variations in the composition and origin of the benthic organic matter (OM) at the sediment surface in mangrove receiving shrimp farm effluents, fatty acid (FA) biomarkers, natural stable isotopes (δ 13 C and δ 15 N), C:N ratios and chlorophyll-a (chl-a) concentrations were determined during the active and the non-active period of the farm. Fatty acid compositions in surface sediments within the mangrove forest indicated that organic matter inputs varied along the year as a result of farm activity. Effluents were the source of fresh particulate organic matter for the mangrove, as evidenced by the unsaturated fatty acid (UFA) distribution. The anthropogenic MUFA 18:1ω9 was not only accumulated at the sediment surface in some parts of the mangrove, but was also exported to the seafront. Direct release of bacteria and enhanced in situ production of fungi, as revealed by specific FAs, stimulated mangrove litter decomposition under effluent runoff condition. Also, microalgae released from ponds contributed to maintain high benthic chl-a concentrations in mangrove sediments in winter and to a shift in microphytobenthic community assemblage. Primary production was high whether the farm released effluent or not which questioned the temporary effect of shrimp farm effluent on benthic microalgae dynamic. This study outlined that mangrove benthic organic matter was qualitatively and quantitatively affected by shrimp farm effluent release and that responses to environmental condition changes likely depended on mangrove stand characteristics. - Highlights: • Fatty acid 18:1ω9 is a relevant marker to monitor effluent pathway in the mangrove. • OM nature and distribution at sediment surface varied in relation to farm activity. • Enhancement of litter-decomposer biomass and activity stimulates litter degradation. • Diatoms dominate the microalgae community under effluent runoff conditions. • Chl-a concentrations suggest

Spatio-temporal variations in the composition of organic matter in surface sediments of a mangrove receiving shrimp farm effluents (New Caledonia)

Energy Technology Data Exchange (ETDEWEB)

Aschenbroich, Adélaïde, E-mail: adelaide.aschenbroich@univ-brest.fr [UMR BOREA 7208 CNRS/MNHN/UPMC/IRD/UCBN, Muséum National d' Histoire Naturelle, CP 53, 61 rue Buffon, 75231 Paris cedex 5 (France); Marchand, Cyril [Institut de Recherche pour le Développement (IRD), UMR 7590, UR 206, BP A5, 98848 Nouméa, New Caledonia (France); Molnar, Nathalie [UMR BOREA 7208 CNRS/MNHN/UPMC/IRD/UCBN, Muséum National d' Histoire Naturelle, CP 53, 61 rue Buffon, 75231 Paris cedex 5 (France); Institut de Recherche pour le Développement (IRD), UMR 7590, UR 206, BP A5, 98848 Nouméa, New Caledonia (France); Deborde, Jonathan [Institut de Recherche pour le Développement (IRD), UMR 7590, UR 206, BP A5, 98848 Nouméa, New Caledonia (France); Hubas, Cédric; Rybarczyk, Hervé; Meziane, Tarik [UMR BOREA 7208 CNRS/MNHN/UPMC/IRD/UCBN, Muséum National d' Histoire Naturelle, CP 53, 61 rue Buffon, 75231 Paris cedex 5 (France)

2015-04-15

In order to investigate spatio-temporal variations in the composition and origin of the benthic organic matter (OM) at the sediment surface in mangrove receiving shrimp farm effluents, fatty acid (FA) biomarkers, natural stable isotopes (δ{sup 13}C and δ{sup 15}N), C:N ratios and chlorophyll-a (chl-a) concentrations were determined during the active and the non-active period of the farm. Fatty acid compositions in surface sediments within the mangrove forest indicated that organic matter inputs varied along the year as a result of farm activity. Effluents were the source of fresh particulate organic matter for the mangrove, as evidenced by the unsaturated fatty acid (UFA) distribution. The anthropogenic MUFA 18:1ω9 was not only accumulated at the sediment surface in some parts of the mangrove, but was also exported to the seafront. Direct release of bacteria and enhanced in situ production of fungi, as revealed by specific FAs, stimulated mangrove litter decomposition under effluent runoff condition. Also, microalgae released from ponds contributed to maintain high benthic chl-a concentrations in mangrove sediments in winter and to a shift in microphytobenthic community assemblage. Primary production was high whether the farm released effluent or not which questioned the temporary effect of shrimp farm effluent on benthic microalgae dynamic. This study outlined that mangrove benthic organic matter was qualitatively and quantitatively affected by shrimp farm effluent release and that responses to environmental condition changes likely depended on mangrove stand characteristics. - Highlights: • Fatty acid 18:1ω9 is a relevant marker to monitor effluent pathway in the mangrove. • OM nature and distribution at sediment surface varied in relation to farm activity. • Enhancement of litter-decomposer biomass and activity stimulates litter degradation. • Diatoms dominate the microalgae community under effluent runoff conditions. • Chl-a concentrations suggest

Tensor analysis methods for activity characterization in spatiotemporal data

Energy Technology Data Exchange (ETDEWEB)

Haass, Michael Joseph; Van Benthem, Mark Hilary; Ochoa, Edward M

2014-03-01

Tensor (multiway array) factorization and decomposition offers unique advantages for activity characterization in spatio-temporal datasets because these methods are compatible with sparse matrices and maintain multiway structure that is otherwise lost in collapsing for regular matrix factorization. This report describes our research as part of the PANTHER LDRD Grand Challenge to develop a foundational basis of mathematical techniques and visualizations that enable unsophisticated users (e.g. users who are not steeped in the mathematical details of matrix algebra and mulitway computations) to discover hidden patterns in large spatiotemporal data sets.

Routes to spatiotemporal chaos in Kerr optical frequency combs.

Science.gov (United States)

Coillet, Aurélien; Chembo, Yanne K

2014-03-01

We investigate the various routes to spatiotemporal chaos in Kerr optical frequency combs, obtained through pumping an ultra-high Q-factor whispering-gallery mode resonator with a continuous-wave laser. The Lugiato-Lefever model is used to build bifurcation diagrams with regards to the parameters that are externally controllable, namely, the frequency and the power of the pumping laser. We show that the spatiotemporal chaos emerging from Turing patterns and solitons display distinctive dynamical features. Experimental spectra of chaotic Kerr combs are also presented for both cases, in excellent agreement with theoretical spectra.

Spatiotemporal Characterization of Ambient PM2.5 Concentrations in Shandong Province (China).

Science.gov (United States)

Yang, Yong; Christakos, George

2015-11-17

China experiences severe particulate matter (PM) pollution problems closely linked to its rapid economic growth. Advancing the understanding and characterization of spatiotemporal air pollution distribution is an area where improved quantitative methods are of great benefit to risk assessment and environmental policy. This work uses the Bayesian maximum entropy (BME) method to assess the space-time variability of PM2.5 concentrations and predict their distribution in the Shandong province, China. Daily PM2.5 concentrations obtained at air quality monitoring sites during 2014 were used. On the basis of the space-time PM2.5 distributions generated by BME, we performed three kinds of querying analysis to reveal the main distribution features. The results showed that the entire region of interest is seriously polluted (BME maps identified heavy pollution clusters during 2014). Quantitative characterization of pollution severity included both pollution level and duration. The number of days during which regional PM2.5 exceeded 75, 115, 150, and 250 μg m(-3) varied: 43-253, 13-128, 4-66, and 0-15 days, respectively. The PM2.5 pattern exhibited an increasing trend from east to west, with the western part of Shandong being a heavily polluted area (PM2.5 exceeded 150 μg m(-3) during long time periods). Pollution was much more serious during winter than during other seasons. Site indicators of PM2.5 pollution intensity and space-time variation were used to assess regional uncertainties and risks with their interpretation depending on the pollutant threshold. The observed PM2.5 concentrations exceeding a specified threshold increased almost linearly with increasing threshold value, whereas the relative probability of excess pollution decreased sharply with increasing threshold.

How about a Bayesian M/EEG imaging method correcting for incomplete spatio-temporal priors

DEFF Research Database (Denmark)

Stahlhut, Carsten; Attias, Hagai T.; Sekihara, Kensuke

2013-01-01

previous spatio-temporal inverse M/EEG models, the proposed model benefits of consisting of two source terms, namely, a spatio-temporal pattern term limiting the source configuration to a spatio-temporal subspace and a source correcting term to pick up source activity not covered by the spatio......-temporal prior belief. We have tested the model on both artificial data and real EEG data in order to demonstrate the efficacy of the model. The model was tested at different SNRs (-10.0,-5.2, -3.0, -1.0, 0, 0.8, 3.0 dB) using white noise. At all SNRs the sAquavit performs best in AUC measure, e.g. at SNR=0d...

The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Discovering, Exploring, and Mapping Spatiotemporal Patterns Across Heterogenous Space-Time Data

Science.gov (United States)

Morton, A.; Stewart, R.; Held, E.; Piburn, J.; Allen, M. R.; McManamay, R.; Sanyal, J.; Sorokine, A.; Bhaduri, B. L.

2017-12-01

Spatiotemporal (ST) analytics applied to major spatio-temporal data sources from major vendors such as USGS, NOAA, World Bank and World Health Organization have tremendous value in shedding light on the evolution of physical, cultural, and geopolitical landscapes on a local and global level. Especially powerful is the integration of these physical and cultural datasets across multiple and disparate formats, facilitating new interdisciplinary analytics and insights. Realizing this potential first requires an ST data model that addresses challenges in properly merging data from multiple authors, with evolving ontological perspectives, semantical differences, changing attributes, and content that is textual, numeric, categorical, and hierarchical. Equally challenging is the development of analytical and visualization approaches that provide a serious exploration of this integrated data while remaining accessible to practitioners with varied backgrounds. The WSTAMP project at the Oak Ridge National Laboratory has yielded two major results in addressing these challenges: 1) development of the WSTAMP database, a significant advance in ST data modeling that integrates 16000+ attributes covering 200+ countries for over 50 years from over 30 major sources and 2) a novel online ST exploratory and analysis tool providing an array of modern statistical and visualization techniques for analyzing these data temporally, spatially, and spatiotemporally under a standard analytic workflow. We report on these advances, provide an illustrative case study, and inform how others may freely access the tool.

Spatiotemporal and plantar pressure patterns of 1000 healthy individuals aged 3-101 years.

Science.gov (United States)

McKay, Marnee J; Baldwin, Jennifer N; Ferreira, Paulo; Simic, Milena; Vanicek, Natalie; Wojciechowski, Elizabeth; Mudge, Anita; Burns, Joshua

2017-10-01

The purpose of this study was to establish normative reference values for spatiotemporal and plantar pressure parameters, and to investigate the influence of demographic, anthropometric and physical characteristics. In 1000 healthy males and females aged 3-101 years, spatiotemporal and plantar pressure data were collected barefoot with the Zeno™ walkway and Emed ® platform. Correlograms were developed to visualise the relationships between widely reported spatiotemporal and pressure variables with demographic (age, gender), anthropometric (height, mass, waist circumference) and physical characteristics (ankle strength, ankle range of motion, vibration perception) in children aged 3-9 years, adolescents aged 10-19 years, adults aged 20-59 years and older adults aged over 60 years. A comprehensive catalogue of 31 spatiotemporal and pressure variables were generated from 1000 healthy individuals. The key findings were that gait velocity was stable during adolescence and adulthood, while children and older adults walked at a comparable slower speed. Peak pressures increased during childhood to older adulthood. Children demonstrated highest peak pressures beneath the rearfoot whilst adolescents, adults and older adults demonstrated highest pressures at the forefoot. Main factors influencing spatiotemporal and pressure parameters were: increased age, height, body mass and waist circumference, as well as ankle dorsiflexion and plantarflexion strength. This study has established whole of life normative reference values of widely used spatiotemporal and plantar pressure parameters, and revealed changes to be expected across the lifespan. Copyright © 2017 Elsevier B.V. All rights reserved.

Compressing spatio-temporal trajectories

DEFF Research Database (Denmark)

Gudmundsson, Joachim; Katajainen, Jyrki; Merrick, Damian

2009-01-01

such that the most common spatio-temporal queries can still be answered approximately after the compression has taken place. In the process, we develop an implementation of the Douglas–Peucker path-simplification algorithm which works efficiently even in the case where the polygonal path given as input is allowed...... to self-intersect. For a polygonal path of size n, the processing time is O(nlogkn) for k=2 or k=3 depending on the type of simplification....

Evaluation of high resolution spatio-temporal precipitation extremes from a stochastic weather generator

DEFF Research Database (Denmark)

Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten

2017-01-01

Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...... gauges in the model area. The spatiotemporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatiotemporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying on precipitation output...

Temporal variations in supraglacial debris distribution on Baltoro Glacier, Karakoram between 2001 and 2012

Science.gov (United States)

Gibson, Morgan J.; Glasser, Neil F.; Quincey, Duncan J.; Mayer, Christoph; Rowan, Ann V.; Irvine-Fynn, Tristram D. L.

2017-10-01

Distribution of supraglacial debris in a glacier system varies spatially and temporally due to differing rates of debris input, transport and deposition. Supraglacial debris distribution governs the thickness of a supraglacial debris layer, an important control on the amount of ablation that occurs under such a debris layer. Characterising supraglacial debris layer thickness on a glacier is therefore key to calculating ablation across a glacier surface. The spatial pattern of debris thickness on Baltoro Glacier has previously been calculated for one discrete point in time (2004) using satellite thermal data and an empirically based relationship between supraglacial debris layer thickness and debris surface temperature identified in the field. Here, the same empirically based relationship was applied to two further datasets (2001, 2012) to calculate debris layer thickness across Baltoro Glacier for three discrete points over an 11-year period (2001, 2004, 2012). Surface velocity and sediment flux were also calculated, as well as debris thickness change between periods. Using these outputs, alongside geomorphological maps of Baltoro Glacier produced for 2001, 2004 and 2012, spatiotemporal changes in debris distribution for a sub-decadal timescale were investigated. Sediment flux remained constant throughout the 11-year period. The greatest changes in debris thickness occurred along medial moraines, the locations of mass movement deposition and areas of interaction between tributary glaciers and the main glacier tongue. The study confirms the occurrence of spatiotemporal changes in supraglacial debris layer thickness on sub-decadal timescales, independent of variation in surface velocity. Instead, variation in rates of debris distribution are primarily attributed to frequency and magnitude of mass movement events over decadal timescales, with climate, regional uplift and erosion rates expected to control debris inputs over centurial to millennial timescales. Inclusion

Energy prediction using spatiotemporal pattern networks

Energy Technology Data Exchange (ETDEWEB)

Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun; Henze, Gregor P.; Sarkar, Soumik

2017-11-01

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated by the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.

SPAN: spike pattern association neuron for learning spatio-temporal sequences

OpenAIRE

Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

2012-01-01

Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN — a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the prec...

Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

Science.gov (United States)

Hussain, Ijaz; Spöck, Gunter; Pilz, Jürgen; Yu, Hwa-Lung

2010-08-01

Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space-time heterogeneity of rainfall observations make space-time estimation of precipitation a challenging task. In this paper we propose a Box-Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space-time monthly precipitation in the monsoon periods during 1974-2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space-time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.

GISpark: A Geospatial Distributed Computing Platform for Spatiotemporal Big Data

Science.gov (United States)

Wang, S.; Zhong, E.; Wang, E.; Zhong, Y.; Cai, W.; Li, S.; Gao, S.

2016-12-01

Geospatial data are growing exponentially because of the proliferation of cost effective and ubiquitous positioning technologies such as global remote-sensing satellites and location-based devices. Analyzing large amounts of geospatial data can provide great value for both industrial and scientific applications. Data- and compute- intensive characteristics inherent in geospatial big data increasingly pose great challenges to technologies of data storing, computing and analyzing. Such challenges require a scalable and efficient architecture that can store, query, analyze, and visualize large-scale spatiotemporal data. Therefore, we developed GISpark - a geospatial distributed computing platform for processing large-scale vector, raster and stream data. GISpark is constructed based on the latest virtualized computing infrastructures and distributed computing architecture. OpenStack and Docker are used to build multi-user hosting cloud computing infrastructure for GISpark. The virtual storage systems such as HDFS, Ceph, MongoDB are combined and adopted for spatiotemporal data storage management. Spark-based algorithm framework is developed for efficient parallel computing. Within this framework, SuperMap GIScript and various open-source GIS libraries can be integrated into GISpark. GISpark can also integrated with scientific computing environment (e.g., Anaconda), interactive computing web applications (e.g., Jupyter notebook), and machine learning tools (e.g., TensorFlow/Orange). The associated geospatial facilities of GISpark in conjunction with the scientific computing environment, exploratory spatial data analysis tools, temporal data management and analysis systems make up a powerful geospatial computing tool. GISpark not only provides spatiotemporal big data processing capacity in the geospatial field, but also provides spatiotemporal computational model and advanced geospatial visualization tools that deals with other domains related with spatial property. We

Visual memory performance for color depends on spatiotemporal context.

Science.gov (United States)

Olivers, Christian N L; Schreij, Daniel

2014-10-01

Performance on visual short-term memory for features has been known to depend on stimulus complexity, spatial layout, and feature context. However, with few exceptions, memory capacity has been measured for abruptly appearing, single-instance displays. In everyday life, objects often have a spatiotemporal history as they or the observer move around. In three experiments, we investigated the effect of spatiotemporal history on explicit memory for color. Observers saw a memory display emerge from behind a wall, after which it disappeared again. The test display then emerged from either the same side as the memory display or the opposite side. In the first two experiments, memory improved for intermediate set sizes when the test display emerged in the same way as the memory display. A third experiment then showed that the benefit was tied to the original motion trajectory and not to the display object per se. The results indicate that memory for color is embedded in a richer episodic context that includes the spatiotemporal history of the display.

Selecting salient frames for spatiotemporal video modeling and segmentation.

Science.gov (United States)

Song, Xiaomu; Fan, Guoliang

2007-12-01

We propose a new statistical generative model for spatiotemporal video segmentation. The objective is to partition a video sequence into homogeneous segments that can be used as "building blocks" for semantic video segmentation. The baseline framework is a Gaussian mixture model (GMM)-based video modeling approach that involves a six-dimensional spatiotemporal feature space. Specifically, we introduce the concept of frame saliency to quantify the relevancy of a video frame to the GMM-based spatiotemporal video modeling. This helps us use a small set of salient frames to facilitate the model training by reducing data redundancy and irrelevance. A modified expectation maximization algorithm is developed for simultaneous GMM training and frame saliency estimation, and the frames with the highest saliency values are extracted to refine the GMM estimation for video segmentation. Moreover, it is interesting to find that frame saliency can imply some object behaviors. This makes the proposed method also applicable to other frame-related video analysis tasks, such as key-frame extraction, video skimming, etc. Experiments on real videos demonstrate the effectiveness and efficiency of the proposed method.

AN ADAPTIVE ORGANIZATION METHOD OF GEOVIDEO DATA FOR SPATIO-TEMPORAL ASSOCIATION ANALYSIS

Directory of Open Access Journals (Sweden)

C. Wu

2015-07-01

Full Text Available Public security incidents have been increasingly challenging to address with their new features, including large-scale mobility, multi-stage dynamic evolution, spatio-temporal concurrency and uncertainty in the complex urban environment, which require spatio-temporal association analysis among multiple regional video data for global cognition. However, the existing video data organizational methods that view video as a property of the spatial object or position in space dissever the spatio-temporal relationship of scattered video shots captured from multiple video channels, limit the query functions on interactive retrieval between a camera and its video clips and hinder the comprehensive management of event-related scattered video shots. GeoVideo, which maps video frames onto a geographic space, is a new approach to represent the geographic world, promote security monitoring in a spatial perspective and provide a highly feasible solution to this problem. This paper analyzes the large-scale personnel mobility in public safety events and proposes a multi-level, event-related organization method with massive GeoVideo data by spatio-temporal trajectory. This paper designs a unified object identify(ID structure to implicitly store the spatio-temporal relationship of scattered video clips and support the distributed storage management of massive cases. Finally, the validity and feasibility of this method are demonstrated through suspect tracking experiments.

High Resolution Spatiotemporal Climate Reconstruction and Variability in East Asia during Little Ice Age

Science.gov (United States)

Lin, K. H. E.; Wang, P. K.; Lee, S. Y.; Liao, Y. C.; Fan, I. C.; Liao, H. M.

2017-12-01

different climate regimes that can be linked to the dynamism of large atmospheric circulation and East Asian monsoon. Spatiotemporal analysis of extreme events such as typhoons and extreme droughts also indicated similar patterns. More detailed analysis are undertaken to explain the physical mechanisms that can drive these changes.

Spatiotemporal dynamics of word retrieval in speech production revealed by cortical high-frequency band activity.

Science.gov (United States)

Riès, Stephanie K; Dhillon, Rummit K; Clarke, Alex; King-Stephens, David; Laxer, Kenneth D; Weber, Peter B; Kuperman, Rachel A; Auguste, Kurtis I; Brunner, Peter; Schalk, Gerwin; Lin, Jack J; Parvizi, Josef; Crone, Nathan E; Dronkers, Nina F; Knight, Robert T

2017-06-06

Word retrieval is core to language production and relies on complementary processes: the rapid activation of lexical and conceptual representations and word selection, which chooses the correct word among semantically related competitors. Lexical and conceptual activation is measured by semantic priming. In contrast, word selection is indexed by semantic interference and is hampered in semantically homogeneous (HOM) contexts. We examined the spatiotemporal dynamics of these complementary processes in a picture naming task with blocks of semantically heterogeneous (HET) or HOM stimuli. We used electrocorticography data obtained from frontal and temporal cortices, permitting detailed spatiotemporal analysis of word retrieval processes. A semantic interference effect was observed with naming latencies longer in HOM versus HET blocks. Cortical response strength as indexed by high-frequency band (HFB) activity (70-150 Hz) amplitude revealed effects linked to lexical-semantic activation and word selection observed in widespread regions of the cortical mantle. Depending on the subsecond timing and cortical region, HFB indexed semantic interference (i.e., more activity in HOM than HET blocks) or semantic priming effects (i.e., more activity in HET than HOM blocks). These effects overlapped in time and space in the left posterior inferior temporal gyrus and the left prefrontal cortex. The data do not support a modular view of word retrieval in speech production but rather support substantial overlap of lexical-semantic activation and word selection mechanisms in the brain.

Plant diversity increases spatio?temporal niche complementarity in plant?pollinator interactions

OpenAIRE

Venjakob, Christine; Klein, Alexandra?Maria; Ebeling, Anne; Tscharntke, Teja; Scherber, Christoph

2016-01-01

Ongoing biodiversity decline impairs ecosystem processes, including pollination. Flower visitation, an important indicator of pollination services, is influenced by plant species richness. However, the spatio-temporal responses of different pollinator groups to plant species richness have not yet been analyzed experimentally. Here, we used an experimental plant species richness gradient to analyze plant-pollinator interactions with an unprecedented spatio-temporal resolution. We observed four...

Spatio-temporal flow maps for visualizing movement and contact patterns

Directory of Open Access Journals (Sweden)

Bing Ni

2017-03-01

Full Text Available The advanced telecom technologies and massive volumes of intelligent mobile phone users have yielded a huge amount of real-time data of people’s all-in-one telecommunication records, which we call telco big data. With telco data and the domain knowledge of an urban city, we are now able to analyze the movement and contact patterns of humans in an unprecedented scale. Flow map is widely used to display the movements of humans from one single source to multiple destinations by representing locations as nodes and movements as edges. However, it fails the task of visualizing both movement and contact data. In addition, analysts often need to compare and examine the patterns side by side, and do various quantitative analysis. In this work, we propose a novel spatio-temporal flow map layout to visualize when and where people from different locations move into the same places and make contact. We also propose integrating the spatiotemporal flow maps into existing spatiotemporal visualization techniques to form a suite of techniques for visualizing the movement and contact patterns. We report a potential application the proposed techniques can be applied to. The results show that our design and techniques properly unveil hidden information, while analysis can be achieved efficiently. Keywords: Spatio-temporal data, Flow map, Urban mobility

Estimation of the spatiotemporal evolution of slow slip events in the Tokai region, central Japan, during 1994 - 2016 using GNSS data

Science.gov (United States)

Sakaue, H.; Nishimura, T.; Fukuda, J.; Kato, T.

2017-12-01

In the Tokai region, central Japan, the long-term slow slip events (L-SSEs) observed on the subducting Philippine Sea Plate (PSP) from 2000 to 2005 and since 2013. Moreover, many short-term slow slip events (S-SSEs) have been observed in the Tokai region since 1996. Sakaue et al. (2017) reported that the spatiotemporal evolution of an L-SSE and S-SSEs on the PSP beneath the Tokai region from 2013 to 2015. This study is probably the first case that migration of slip for S-SSE (Mw GPS Research) in the Tokai region. It is well known that GNSS time series have many systematic signals that do not result from SSEs. These systematic signals include, for example, seasonal variations, cosiesmic and post-seismic deformation of the 2004 off Southeast Kii Peninsula eqrthquake and the 2011 Tohoku-oki earthquake (Mw. 9.0), crustal deformation of volcanic activity on Miyake-jima island and so on. After removing these systematic signals, we applied a modified Network Inversion Filter (NIF) [Fukuda et al., 2008]. The original NIF [Segall & Matthews, 1997] assumes a constant hyperparameter for the temporal smoothing of slip rates and thus often results in oversmoothing of slip rates. The modified NIF assumes a time-variable hyperparameter, so that changes in slip rates are effectively extracted from GNSS time series.The results indicate that not only the spatiotemporal evolutions of the 2000 Tokai L-SSE and the 2013 L-SSE but also the spatiotemporal evolution of S-SSEs are estimated. We will present a comparison of the spatiotemporal evolutions between the 2000 Tokai L-SSE and the 2013 L-SSE and possible dependence of the occurrence style of S-SSEs on the occurrence of the L-SSEs.

On the foundation of a variational principle for decaying systems

International Nuclear Information System (INIS)

Szasz, G.I.

1976-01-01

Taking into account the circumstances that the decay of an unstable microscopic system into two fragments is established by the counting of one of the decay products in a detector, the observed exponential decay law then asserts only knowledge of the spatiotemporal behaviour of the probability density (and therewith knowledge of the decaying state) at a large finite distance from the site of decay. We therefore formulate a variational principle, of which stationary functions show this decay behaviour. In addition to the resonant wave functions there are also solutions of the variational principle, which decrease exponentially with increasing distance, i.e., functions which could be used to describe the bound states. As the time-dependent treatment shows, the decaying states cannot occur in isolation in a scattering process. The mathematical characterisation of the decaying states via a variational principle is incorporated in a theory of open physical systems. In contradiction to the variational principle of Schroedinger our principle does not provide complete knowledge of the quantum states, but this is not needed in order to describe the decay. (orig.) [de

Spatiotemporal shoreline dynamics of Namibian coastal lagoons derived by a dense remote sensing time series approach

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Behling, Robert; Milewski, Robert; Chabrillat, Sabine

2018-06-01

This paper proposes the remote sensing time series approach WLMO (Water-Land MOnitor) to monitor spatiotemporal shoreline changes. The approach uses a hierarchical classification system based on temporal MNDWI-trajectories with the goal to accommodate typical uncertainties in remote sensing shoreline extraction techniques such as existence of clouds and geometric mismatches between images. Applied to a dense Landsat time series between 1984 and 2014 for the two Namibian coastal lagoons at Walvis Bay and Sandwich Harbour the WLMO was able to identify detailed accretion and erosion progressions at the sand spits forming these lagoons. For both lagoons a northward expansion of the sand spits of up to 1000 m was identified, which corresponds well with the prevailing northwards directed ocean current and wind processes that are responsible for the material transport along the shore. At Walvis Bay we could also show that in the 30 years of analysis the sand spit's width has decreased by more than a half from 750 m in 1984-360 m in 2014. This ongoing cross-shore erosion process is a severe risk for future sand spit breaching, which would expose parts of the lagoon and the city to the open ocean. One of the major advantages of WLMO is the opportunity to analyze detailed spatiotemporal shoreline changes. Thus, it could be shown that the observed long-term accretion and erosion processes underwent great variations over time and cannot a priori be assumed as linear processes. Such detailed spatiotemporal process patterns are a prerequisite to improve the understanding of the processes forming the Namibian shorelines. Moreover, the approach has also the potential to be used in other coastal areas, because the focus on MNDWI-trajectories allows the transfer to many multispectral satellite sensors (e.g. Sentinel-2, ASTER) available worldwide.

Reliable Collaborative Filtering on Spatio-Temporal Privacy Data

Directory of Open Access Journals (Sweden)

Zhen Liu

2017-01-01

Full Text Available Lots of multilayer information, such as the spatio-temporal privacy check-in data, is accumulated in the location-based social network (LBSN. When using the collaborative filtering algorithm for LBSN location recommendation, one of the core issues is how to improve recommendation performance by combining the traditional algorithm with the multilayer information. The existing approaches of collaborative filtering use only the sparse user-item rating matrix. It entails high computational complexity and inaccurate results. A novel collaborative filtering-based location recommendation algorithm called LGP-CF, which takes spatio-temporal privacy information into account, is proposed in this paper. By mining the users check-in behavior pattern, the dataset is segmented semantically to reduce the data size that needs to be computed. Then the clustering algorithm is used to obtain and narrow the set of similar users. User-location bipartite graph is modeled using the filtered similar user set. Then LGP-CF can quickly locate the location and trajectory of users through message propagation and aggregation over the graph. Through calculating users similarity by spatio-temporal privacy data on the graph, we can finally calculate the rating of recommendable locations. Experiments results on the physical clusters indicate that compared with the existing algorithms, the proposed LGP-CF algorithm can make recommendations more accurately.

Stochastic resonance based on modulation instability in spatiotemporal chaos.

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Han, Jing; Liu, Hongjun; Huang, Nan; Wang, Zhaolu

2017-04-03

A novel dynamic of stochastic resonance in spatiotemporal chaos is presented, which is based on modulation instability of perturbed partially coherent wave. The noise immunity of chaos can be reinforced through this effect and used to restore the coherent signal information buried in chaotic perturbation. A theoretical model with fluctuations term is derived from the complex Ginzburg-Landau equation via Wigner transform. It shows that through weakening the nonlinear threshold and triggering energy redistribution, the coherent component dominates the instability damped by incoherent component. The spatiotemporal output showing the properties of stochastic resonance may provide a potential application of signal encryption and restoration.

Secondary Instabilities and Spatiotemporal Chaos in Parametric Surface Waves

International Nuclear Information System (INIS)

Zhang, W.; Vinals, J.

1995-01-01

A 2D model is introduced to study the onset of parametric surface waves, their secondary instabilities, and the transition to spatiotemporal chaos. We obtain the stability boundary of a periodic standing wave above onset against Eckhaus, zigzag, and transverse amplitude modulations (TAM), as a function of the control parameter var-epsilon and the wavelength of the pattern. The Eckhaus and TAM boundaries cross at a finite value of var-epsilon, thus explaining the finite threshold for the TAM observed experimentally. At larger values of var-epsilon, a numerical solution reveals a transition to spatiotemporal chaotic states mediated by the TAM instability

Spatial and spatio-temporal bayesian models with R - INLA

CERN Document Server

Blangiardo, Marta

2015-01-01

Dedication iiiPreface ix1 Introduction 11.1 Why spatial and spatio-temporal statistics? 11.2 Why do we use Bayesian methods for modelling spatial and spatio-temporal structures? 21.3 Why INLA? 31.4 Datasets 32 Introduction to 212.1 The language 212.2 objects 222.3 Data and session management 342.4 Packages 352.5 Programming in 362.6 Basic statistical analysis with 393 Introduction to Bayesian Methods 533.1 Bayesian Philosophy 533.2 Basic Probability Elements 573.3 Bayes Theorem 623.4 Prior and Posterior Distributions 643.5 Working with the Posterior Distribution 663.6 Choosing the Prior Distr

Mobile technologies and the spatiotemporal configurations of institutional practice

DEFF Research Database (Denmark)

Shklovski, Irina; Troshynski, Emily; Dourish, Paul

2015-01-01

are specifically concerned with what happens to institutional roles, power relationships, and decision-making processes when a particular type of information—that of spatiotemporal location of people—is made into a technologically tradable object through the use of location-based systems. We examine...... in which broad adoption of location-based and mobile technologies has the capacity to radically reconfigure the spatiotemporal arrangement of institutional processes. The presence of digital location traces creates new forms of institutional accountability, facilitates a shift in the understood relation...... between location and action, and necessitates new models of interpretation and sense making in practice....

Spatiotemporal chaos and two-dimensional dissipative rogue waves in Lugiato-Lefever model

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Panajotov, Krassimir; Clerc, Marcel G.; Tlidi, Mustapha

2017-06-01

Driven nonlinear optical cavities can exhibit complex spatiotemporal dynamics. We consider the paradigmatic Lugiato-Lefever model describing driven nonlinear optical resonator. This model is one of the most-studied nonlinear equations in optics. It describes a large spectrum of nonlinear phenomena from bistability, to periodic patterns, localized structures, self-pulsating localized structures and to a complex spatiotemporal behavior. The model is considered also as prototype model to describe several optical nonlinear devices such as Kerr media, liquid crystals, left handed materials, nonlinear fiber cavity, and frequency comb generation. We focus our analysis on a spatiotemporal chaotic dynamics in one-dimension. We identify a route to spatiotemporal chaos through an extended quasiperiodicity. We have estimated the Kaplan-Yorke dimension that provides a measure of the strange attractor complexity. Likewise, we show that the Lugiato-Leferver equation supports rogues waves in two-dimensional settings. We characterize rogue-wave formation by computing the probability distribution of the pulse height. Contribution to the Topical Issue "Theory and Applications of the Lugiato-Lefever Equation", edited by Yanne K. Chembo, Damia Gomila, Mustapha Tlidi, Curtis R. Menyuk.

Approximate spatio-temporal top-k publish/subscribe

KAUST Repository

Chen, Lisi

2018-04-26

Location-based publish/subscribe plays a significant role in mobile information disseminations. In this light, we propose and study a novel problem of processing location-based top-k subscriptions over spatio-temporal data streams. We define a new type of approximate location-based top-k subscription, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription, that continuously feeds users with relevant spatio-temporal messages by considering textual similarity, spatial proximity, and information freshness. Different from existing location-based top-k subscriptions, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription can automatically adjust the triggering condition by taking the triggering score of other subscriptions into account. The group filtering efficacy can be substantially improved by sacrificing the publishing result quality with a bounded guarantee. We conduct extensive experiments on two real datasets to demonstrate the performance of the developed solutions.

Approximate spatio-temporal top-k publish/subscribe

KAUST Repository

Chen, Lisi; Shang, Shuo

2018-01-01

Location-based publish/subscribe plays a significant role in mobile information disseminations. In this light, we propose and study a novel problem of processing location-based top-k subscriptions over spatio-temporal data streams. We define a new type of approximate location-based top-k subscription, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription, that continuously feeds users with relevant spatio-temporal messages by considering textual similarity, spatial proximity, and information freshness. Different from existing location-based top-k subscriptions, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription can automatically adjust the triggering condition by taking the triggering score of other subscriptions into account. The group filtering efficacy can be substantially improved by sacrificing the publishing result quality with a bounded guarantee. We conduct extensive experiments on two real datasets to demonstrate the performance of the developed solutions.

Spatio-temporal modeling of 210Pb transportation in lake environments

International Nuclear Information System (INIS)

Kuelahci, Fatih; Sen, Zekai

2009-01-01

Radioactive particle movement analysis in any environment gives valuable information about the effects of the concerned environment on the particle and the transportation phenomenon. In this study, the spatio-temporal point cumulative semivariogram (STPCSV) approach is proposed for the analysis of the spatio-temporal changes in the radioactive particle movement within a surface water body. This methodology is applied to the 210 Pb radioactive isotope measurements at 44 stations, which are determined beforehand in order to characterize the Keban Dam water environment on the Euphrates River in the southeastern part of Turkey. It considers the contributions coming from all the stations and provides information about the spatio-temporal behavior of 210 Pb in the water environment. After having identified the radii of influences at each station it is possible to draw maps for further interpretations. In order to see holistically the spatial changes of the radioisotope after 1st, 3rd and 5th hours, the radius of influence maps are prepared and interpreted accordingly.

The role of climate and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria

Science.gov (United States)

Abdussalam, Auwal; Thornes, John; Leckebusch, Gregor

2015-04-01

Nigeria has a number of climate-sensitive infectious diseases; one of the most important of these diseases that remains a threat to public health is cholera. This study investigates the influences of both meteorological and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria. A stepwise multiple regression models are used to estimate the influence of the year-to-year variations of cholera cases and deaths for individual states in the country and as well for three groups of states that are classified based on annual rainfall amount. Specifically, seasonal mean maximum and minimum temperatures and annual rainfall totals were analysed with annual aggregate count of cholera cases and deaths, taking into account of the socioeconomic factors that are potentially enhancing vulnerability such as: absolute poverty, adult literacy, access to pipe borne water and population density. Result reveals that the most important explanatory meteorological and socioeconomic variables in explaining the spatiotemporal variability of the disease are rainfall totals, seasonal mean maximum temperature, absolute poverty, and accessibility to pipe borne water. The influences of socioeconomic factors appeared to be more pronounced in the northern part of the country, and vice-versa in the case of meteorological factors. Also, cross validated models output suggests a strong possibility of disease prediction, which will help authorities to put effective control measures in place which depend on prevention, and or efficient response.

Genetic and biochemical analysis reveals linked QTLs determining natural variation for fruit post-harvest water loss in pepper (Capsicum).

Science.gov (United States)

Popovsky-Sarid, Sigal; Borovsky, Yelena; Faigenboim, Adi; Parsons, Eugene P; Lohrey, Gregory T; Alkalai-Tuvia, Sharon; Fallik, Elazar; Jenks, Matthew A; Paran, Ilan

2017-02-01

Molecular markers linked to QTLs controlling post-harvest fruit water loss in pepper may be utilized to accelerate breeding for improved shelf life and inhibit over-ripening before harvest. Bell pepper (Capsicum annuum L.) is an important vegetable crop world-wide. However, marketing is limited by the relatively short shelf life of the fruit due to water loss and decay that occur during prolonged storage. Towards breeding pepper with reduced fruit post-harvest water loss (PWL), we studied the genetic, physiological and biochemical basis for natural variation of PWL. We performed quantitative trait locus (QTL) mapping of fruit PWL in multiple generations of an interspecific cross of pepper, which resulted in the identification of two linked QTLs on chromosome 10 that control the trait. We further developed near-isogenic lines (NILs) for characterization of the QTL effects. Transcriptome analysis of the NILs allowed the identification of candidate genes associated with fruit PWL-associated traits such as cuticle biosynthesis, cell wall metabolism and fruit ripening. Significant differences in PWL between the NILs in the immature fruit stage, differentially expressed cuticle-associated genes and differences in the content of specific chemical constituents of the fruit cuticle, indicated a likely influence of cuticle composition on the trait. Reduced PWL in the NILs was associated with delayed over-ripening before harvest, low total soluble solids before storage, and reduced fruit softening after storage. Our study enabled a better understanding of the genetic and biological processes controlling natural variation in fruit PWL in pepper. Furthermore, the genetic materials and molecular markers developed in this study may be utilized to breed peppers with improved shelf life and inhibited over-ripening before harvest.

Spatio-temporal resolved diagnostics of the single filament barrier discharge in air

International Nuclear Information System (INIS)

Wagner, H.E.; Brandenburg, R.; Michel, P.; Kozlov, K.V.

2001-01-01

First experimental results on the spatio-temporal development of single filaments of DBDs in dry air at atmospheric pressure are presented. The measurements allow a detailed visualisation and interpretation of the streamer development. In combination with the kinetic model they are used to get information on the spatiotemporal development of the reduced field-strength E/n, too

Spatiotemporal Features of the Three-Dimensional Architectural Landscape in Qingdao, China.

Science.gov (United States)

Zhang, Peifeng

2015-01-01

The evolution and development of the three-dimensional (3D) architectural landscape is the basis of proper urban planning, eco-environment construction and the improvement of environmental quality. This paper presents the spatiotemporal characteristics of the 3D architectural landscape of the Shinan and Shibei districts in Qingdao, China, based on buildings' 3D information extracted from Quickbird images from 2003 to 2012, supported by Barista, landscape metrics and GIS. The results demonstrated that: (1) Shinan and Shibei districts expanded vertically and urban land use intensity increased noticeably from year to year. (2) Significant differences in the 3D architectural landscape existed among the western, central and eastern regions, and among the 26 sub-districts over the study period. The differentiation was consistent with the diverse development history, function and planning of the two districts. Finally, we found that population correlates positively with the variation in the 3D architectural landscape. This research provides an important reference for related studies, urban planning and eco-city construction.

Spatiotemporal Correlations between Water Footprint and Agricultural Inputs: A Case Study of Maize Production in Northeast China

Directory of Open Access Journals (Sweden)

Peili Duan

2015-07-01

Full Text Available To effectively manage water resources in agricultural production, it is necessary to understand the spatiotemporal variation of the water footprint (WF and the influences of agricultural inputs. Employing spatial autocorrelation analysis and a geographically weighted regression (GWR model, we explored the spatial variations of the WF and their relationships with agricultural inputs from 1998 to 2012 in Northeast China. The results indicated that: (1 the spatial distribution of WFs for the 36 major maize production prefectures was heterogeneous in Northeast China; (2 a cluster of high WFs was found in southeast Liaoning Province, while a cluster of low WFs was found in central Jilin Province, and (3 spatial and temporal differentiation in the correlations between the WF of maize production and agricultural inputs existed according to the GWR model. These correlations increased over time. Our results suggested that localized strategies for reducing the WF should be formulated based on specific relationships between the WF and agricultural inputs.

Diurnal variation of the human adipose transcriptome and the link to metabolic disease

Directory of Open Access Journals (Sweden)

Lamb John

2009-02-01

Full Text Available Abstract Background Circadian (diurnal rhythm is an integral part of the physiology of the body; specifically, sleep, feeding behavior and metabolism are tightly linked to the light-dark cycle dictated by earth's rotation. Methods The present study examines the effect of diurnal rhythm on gene expression in the subcutaneous adipose tissue of overweight to mildly obese, healthy individuals. In this well-controlled clinical study, adipose biopsies were taken in the morning, afternoon and evening from individuals in three study arms: treatment with the weight loss drug sibutramine/fasted, placebo/fed and placebo/fasted. Results The results indicated that diurnal rhythm was the most significant driver of gene expression variation in the human adipose tissue, with at least 25% of the genes having had significant changes in their expression levels during the course of the day. The mRNA expression levels of core clock genes at a specific time of day were consistent across multiple subjects on different days in all three arms, indicating robust diurnal regulation irrespective of potential confounding factors. The genes essential for energy metabolism and tissue physiology were part of the diurnal signature. We hypothesize that the diurnal transition of the expression of energy metabolism genes reflects the shift in the adipose tissue from an energy-expending state in the morning to an energy-storing state in the evening. Consistent with this hypothesis, the diurnal transition was delayed by fasting and treatment with sibutramine. Finally, an in silico comparison of the diurnal signature with data from the publicly-available Connectivity Map demonstrated a significant association with transcripts that were repressed by mTOR inhibitors, suggesting a possible link between mTOR signaling, diurnal gene expression and metabolic regulation. Conclusion Diurnal rhythm plays an important role in the physiology and regulation of energy metabolism in the adipose

Dynamical Properties of Transient Spatio-Temporal Patterns in Bacterial Colony of Proteus mirabilis

Science.gov (United States)

Watanabe, Kazuhiko; Wakita, Jun-ichi; Itoh, Hiroto; Shimada, Hirotoshi; Kurosu, Sayuri; Ikeda, Takemasa; Yamazaki, Yoshihiro; Matsuyama, Tohey; Matsushita, Mitsugu

2002-02-01

Spatio-temporal patterns emerged inside a colony of bacterial species Proteus mirabilis on the surface of nutrient-rich semisolid agar medium have been investigated. We observed various patterns composed of the following basic types: propagating stripe, propagating stripe with fixed dislocation, expanding and shrinking target, and rotating spiral. The remarkable point is that the pattern changes immediately when we alter the position for observation, but it returns to the original if we restore the observing position within a few minutes. We further investigated mesoscopic and microscopic properties of the spatio-temporal patterns. It turned out that whenever the spatio-temporal patterns are observed in a colony, the areas are composed of two superimposed monolayers of elongated bacterial cells. In each area they are aligned almost parallel with each other like a two-dimensional nematic liquid crystal, and move collectively and independently of another layer. It has been found that the observed spatio-temporal patterns are explained as the moiré effect.

Occurrence, ecological risk assessment, and spatio-temporal variation of polychlorinated biphenyls (PCBs) in water and sediments along River Ravi and its northern tributaries, Pakistan.

Science.gov (United States)

Baqar, Mujtaba; Sadef, Yumna; Ahmad, Sajid Rashid; Mahmood, Adeel; Qadir, Abdul; Aslam, Iqra; Li, Jun; Zhang, Gan

2017-12-01

Ecological risk assessment, spatio-temporal variation, and source apportionment of polychlorinated biphenyls (PCBs) were studied in surface sediments and water from River Ravi and its three northern tributaries (Nullah Deg, Nullah Basantar, and Nullah Bein) in Pakistan. In total, 35 PCB congeners were analyzed along 27 sampling stations in pre-monsoon and post-monsoon seasons. The ∑ 35 PCB concentration ranged from 1.06 to 95.76 ng/g (dw) in sediments and 1.94 to 11.66 ng/L in water samples, with hexa-CBs and tetra-CBs as most dominant homologs in sediments and water matrixes, respectively. The ∑ 8 DL-PCB levels were 0.33-22.13 ng/g (dw) and 0.16-1.95 ng/L in sediments and water samples, respectively. The WHO-toxic equivalent values were ranged from 1.18 × 10 -6 to 0.012 ng/L and 1.8 × 10 -6 to 0.031 ng/g in water and sediments matrixes, respectively. The ecological risk assessment indicates considerable potential ecological risk during pre-monsoon season ([Formula: see text] = 95.17) and moderate potential ecological risk during post-monsoon season ([Formula: see text] = 49.11). The industrial and urban releases were recognized as key ongoing sources for high PCB levels in environment. Therefore, we recommend more freshwater ecological studies to be conducted in the study area and firm regulatory initiatives are required to be taken in debt to the Stockholm Convention, 2001 to cop up with PCB contamination on emergency basis.

Global spatiotemporal distribution of soil respiration modeled using a global database

Science.gov (United States)

Hashimoto, S.; Carvalhais, N.; Ito, A.; Migliavacca, M.; Nishina, K.; Reichstein, M.

2015-07-01

The flux of carbon dioxide from the soil to the atmosphere (soil respiration) is one of the major fluxes in the global carbon cycle. At present, the accumulated field observation data cover a wide range of geographical locations and climate conditions. However, there are still large uncertainties in the magnitude and spatiotemporal variation of global soil respiration. Using a global soil respiration data set, we developed a climate-driven model of soil respiration by modifying and updating Raich's model, and the global spatiotemporal distribution of soil respiration was examined using this model. The model was applied at a spatial resolution of 0.5°and a monthly time step. Soil respiration was divided into the heterotrophic and autotrophic components of respiration using an empirical model. The estimated mean annual global soil respiration was 91 Pg C yr-1 (between 1965 and 2012; Monte Carlo 95 % confidence interval: 87-95 Pg C yr-1) and increased at the rate of 0.09 Pg C yr-2. The contribution of soil respiration from boreal regions to the total increase in global soil respiration was on the same order of magnitude as that of tropical and temperate regions, despite a lower absolute magnitude of soil respiration in boreal regions. The estimated annual global heterotrophic respiration and global autotrophic respiration were 51 and 40 Pg C yr-1, respectively. The global soil respiration responded to the increase in air temperature at the rate of 3.3 Pg C yr-1 °C-1, and Q10 = 1.4. Our study scaled up observed soil respiration values from field measurements to estimate global soil respiration and provide a data-oriented estimate of global soil respiration. The estimates are based on a semi-empirical model parameterized with over one thousand data points. Our analysis indicates that the climate controls on soil respiration may translate into an increasing trend in global soil respiration and our analysis emphasizes the relevance of the soil carbon flux from soil to

Spatio-temporal distribution of global solar radiation for Mexico using GOES data

Science.gov (United States)

Bonifaz, R.; Cuahutle, M.; Valdes, M.; Riveros, D.

2013-05-01

Increased need of sustainable and renewable energies around the world requires studies about the amount and distribution of such types of energies. Global solar radiation distribution in space and time is a key component on order to know the availability of the energy for different applications. Using GOES hourly data, the heliosat model was implemented for Mexico. Details about the model and its components are discussed step by stem an once obtained the global solar radiation images, different time datasets (hourly, daily, monthly and seasonal) were built in order to know the spatio-temporal behavior of this type of energy. Preliminary maps of the available solar global radiation energy for Mexico are presented, the amount and variation of the solar radiation by regions are analyzed and discussed. Future work includes a better parametrization of the model using calibrated ground stations data and more use of more complex models for better results.

Enzyme-linked immunosorbent assay characterization of basal variation and heritability of systemic microfibrillar-associated protein 4.

Directory of Open Access Journals (Sweden)

Susanne Gjørup Sækmose

Full Text Available BACKGROUND: Microfibrillar-associated protein 4 (MFAP4 is a systemic biomarker that is significantly elevated in samples from patients suffering from hepatic cirrhosis. The protein is generally localized to elastic fibers and other connective tissue fibers in the extracellular matrix (ECM, and variation in systemic MFAP4 (sMFAP4 has the potential to reflect diverse diseases with increased ECM turnover. Here, we aimed to validate an enzyme-linked immunosorbent assay (ELISA for the measurement of sMFAP4 with an emphasis on the robustness of the assay. Moreover, we aimed to determine confounders influencing the basal sMFAP4 variability and the genetic contribution to the basal variation. METHODS: The sandwich ELISA was based on two monoclonal anti-MFAP4 antibodies and was optimized and calibrated with a standard of recombinant MFAP4. The importance of pre-analytical sample handling was evaluated regarding sample tube type, time, and temperature conditions. The mean value structure and variance structure was determined in a twin cohort including 1,417 Danish twins (age 18-67 years by mixed-effect linear regression modeling. RESULTS: The practical working range of the sandwich ELISA was estimated to be 4-75 U/ml. The maximum intra- and inter-assay variation was estimated to be 8.7% and 6.6%, respectively. Sample handling and processing appeared to influence MFAP4 measurements only marginally. The average concentration of sMFAP4 in the serum was 18.9 ± 8.4 (SD U/ml in the twin cohort (95% CI: 18.5-19.4, median sMFAP4 17.3 U/ml. The mean structure model was demonstrated to include waist-hip ratio, age, and cigarette smoking status in interactions with gender. A relatively low heritability of h(2 = 0.24 was found after applying a model including additive genetic factors and shared and non-shared environmental factors. CONCLUSIONS: The described ELISA provides robust measures of the liver fibrosis marker sMFAP4. The low heritability and the relatively

A distributed network of low-cost continuous reading sensors to measure spatiotemporal variations of PM2.5 in Xi'an, China

International Nuclear Information System (INIS)

Gao, Meiling; Cao, Junji; Seto, Edmund

2015-01-01

Fine particulate matter (PM2.5) is a growing public health concern especially in industrializing countries but existing monitoring networks are unable to properly characterize human exposures due to low resolution spatiotemporal data. Low-cost portable monitors can supplement existing networks in both developed and industrializing regions to increase density of sites and data. This study tests the performance of a low-cost sensor in high concentration urban environments. Seven Portable University of Washington Particle (PUWP) monitors were calibrated with optical and gravimetric PM2.5 reference monitors in Xi'an, China in December 2013. Pairwise correlations between the raw PUWP and the reference monitors were high (R 2  = 0.86–0.89). PUWP monitors were also simultaneously deployed at eight sites across Xi'an alongside gravimetric PM2.5 monitors (R 2  = 0.53). The PUWP monitors were able to identify the High-technology Zone site as a potential PM2.5 hotspot with sustained high concentrations compared to the city average throughout the day. - Highlights: • A $15 portable PM sensor demonstrated high correlations with reference monitors. • The sensor can be deployed in high PM2.5 urban environments. • The sensor can improve spatiotemporal resolution of data from existing monitoring networks. - This reliable low-cost portable PM sensor could help improve monitoring and management of urban air pollution to help protect public health in both developed and developing areas

Effects of land cover and regional climate variations on long-term spatiotemporal changes in sagebrush ecosystems

Science.gov (United States)

Xian, George Z.; Homer, Collin G.; Aldridge, Cameron L.

2012-01-01

This research investigated the effects of climate and land cover change on variation in sagebrush ecosystems. We combined information of multi-year sagebrush distribution derived from multitemporal remote sensing imagery and climate data to study the variation patterns of sagebrush ecosystems under different potential disturbances. We found that less than 40% of sagebrush ecosystem changes involved abrupt changes directly caused by landscape transformations and over 60% of the variations involved gradual changes directly related to climatic perturbations. The primary increases in bare ground and declines in sagebrush vegetation abundance were significantly correlated with the 1996-2006 decreasing trend in annual precipitation.

Investigation of the physical and chemical characteristics of rural solid waste in China and its spatiotemporal distributions.

Science.gov (United States)

Wu, Xiaohui; Yue, Bo; Huang, Qifei; Wang, Qi; Li, Zhilong; Wang, Yutang; Yu, Junying

2018-04-13

Despite governmental efforts toward the development of policies, funds, and technologies, the inherent characteristics of rural solid waste (RSW) discharge have led to great difficulties in RSW pollution control. However, establishing a realistic management strategy requires greater knowledge of RSW generation. Therefore, the RSW of 72 typical towns and villages from 12 provinces of China was analyzed for physicochemical characteristics, as well as its spatiotemporal distribution. The largest proportion of kitchen waste, coal ash, plastic, and paper of RSW was 33.70% ± 17.87%, 26.50% ± 17.61%, 13.48% ± 5.68%, and 10.75% ± 5.75%, respectively, in 2015. Although RSW had the potential for composting, it was still necessary to pay special attention to heavy metals pollution of RSW. The spatiotemporal distributions of RSW components were extremely non-homogenous, and significant variations existed in the kitchen residue, coal ash, plastic, and paper because of differences in economic growth, climatic changes, dietary habits, energy consumption structure, and consumer preferences. No obvious differences in RSW components were observed between villages and market towns. Overall, RSW treatment and management approaches should be considered based on local conditions of RSW generation.

Spatial and temporal variations of thaw layer thickness and its controlling factors identified using time-lapse electrical resistivity tomography and hydro-thermal modeling

Science.gov (United States)

Tran, Anh Phuong; Dafflon, Baptiste; Bisht, Gautam; Hubbard, Susan S.

2018-06-01

Quantitative understanding of controls on thaw layer thickness (TLT) dynamics in the Arctic peninsula is essential for predictive understanding of permafrost degradation feedbacks to global warming and hydrobiochemical processes. This study jointly interprets electrical resistivity tomography (ERT) measurements and hydro-thermal numerical simulation results to assess spatiotemporal variations of TLT and to determine its controlling factors in Barrow, Alaska. Time-lapse ERT measurements along a 35-m transect were autonomously collected from 2013 to 2015 and inverted to obtain soil electrical resistivity. Based on several probe-based TLT measurements and co-located soil electrical resistivity, we estimated the electrical resistivity thresholds associated with the boundary between the thaw layer and permafrost using a grid search optimization algorithm. Then, we used the obtained thresholds to derive the TLT from all soil electrical resistivity images. The spatiotemporal analysis of the ERT-derived TLT shows that the TLT at high-centered polygons (HCPs) is smaller than that at low-centered polygons (LCPs), and that both thawing and freezing occur earlier at the HCPs compared to the LCPs. In order to provide a physical explanation for dynamics in the thaw layer, we performed 1-D hydro-thermal simulations using the community land model (CLM). Simulation results showed that air temperature and precipitation jointly govern the temporal variations of TLT, while the topsoil organic content (SOC) and polygon morphology are responsible for its spatial variations. When the topsoil SOC and its thickness increase, TLT decreases. Meanwhile, at LCPs, a thicker snow layer and saturated soil contribute to a thicker TLT and extend the time needed for TLT to freeze and thaw. This research highlights the importance of combination of measurements and numerical modeling to improve our understanding spatiotemporal variations and key controls of TLT in cold regions.

Spatiotemporal variation of bacterial community composition and possible controlling factors in tropical shallow lagoons.

Science.gov (United States)

Laque, Thaís; Farjalla, Vinicius F; Rosado, Alexandre S; Esteves, Francisco A

2010-05-01

Bacterial community composition (BCC) has been extensively related to specific environmental conditions. Tropical coastal lagoons present great temporal and spatial variation in their limnological conditions, which, in turn, should influence the BCC. Here, we sought for the limnological factors that influence, in space and time, the BCC in tropical coastal lagoons (Rio de Janeiro State, Brazil). The Visgueiro lagoon was sampled monthly for 1 year and eight lagoons were sampled once for temporal and spatial analysis, respectively. BCC was evaluated by bacteria-specific PCR-DGGE methods. Great variations were observed in limnological conditions and BCC on both temporal and spatial scales. Changes in the BCC of Visgueiro lagoon throughout the year were best related to salinity and concentrations of NO (3) (-) , dissolved phosphorus and chlorophyll-a, while changes in BCC between lagoons were best related to salinity and dissolved phosphorus concentration. Salinity has a direct impact on the integrity of the bacterial cell, and it was previously observed that phosphorus is the main limiting nutrient to bacterial growth in these lagoons. Therefore, we conclude that great variations in limnological conditions of coastal lagoons throughout time and space resulted in different BCCs and salinity and nutrient concentration, particularly dissolved phosphorus, are the main limnological factors influencing BCC in these tropical coastal lagoons.

The Spatiotemporal pattern and driving forces of the paddy in the Northeastern China

Science.gov (United States)

Du, G.; Li, Q.; Chun, X.

2017-12-01

The cropland is the production place that protects the regional food security, and the paddy is the main part of the cropland. Since the 21st century, the China's socio-economy has been grown, the structure of the cropland has significantly changed. The Northeast region has gradually become one of the major commodity grain production bases. Meanwhile, the paddy also has gradually increased year by year. Therefore, it is necessary that analyze the tempo-spatial characteristics and the influencing factors of the northeast in China, and the results provide the basis that reveals the change of cropland structure and its causes.In this study, we use the spatial models of GIS and mathematical statistics methods to analyze the tempo-spatial characteristics and the influencing facts of the paddy in the Northeastern China with the spatial data from 2000 to 2015. In order to fully characterize the spatiotemporal characteristics of the paddy, we choose single land use type dynamic degree and land use extension index to quantitatively describe the change degree and the speed of the regional paddy, and the characteristics are visualized with "3S" means. Meanwhile, the relative change rate and the center of gravity model are chosen to explore the region differences and the distribution of the distribution center of paddy field change in Northeast China. In addition, in order to further reveal the cause of the paddy change, we use the OLS, SAM or SEM models to analyze the main influencing factors of spatiotemporal variation of the paddy field.

Visual search of cyclic spatio-temporal events

Science.gov (United States)

Gautier, Jacques; Davoine, Paule-Annick; Cunty, Claire

2018-05-01

The analysis of spatio-temporal events, and especially of relationships between their different dimensions (space-time-thematic attributes), can be done with geovisualization interfaces. But few geovisualization tools integrate the cyclic dimension of spatio-temporal event series (natural events or social events). Time Coil and Time Wave diagrams represent both the linear time and the cyclic time. By introducing a cyclic temporal scale, these diagrams may highlight the cyclic characteristics of spatio-temporal events. However, the settable cyclic temporal scales are limited to usual durations like days or months. Because of that, these diagrams cannot be used to visualize cyclic events, which reappear with an unusual period, and don't allow to make a visual search of cyclic events. Also, they don't give the possibility to identify the relationships between the cyclic behavior of the events and their spatial features, and more especially to identify localised cyclic events. The lack of possibilities to represent the cyclic time, outside of the temporal diagram of multi-view geovisualization interfaces, limits the analysis of relationships between the cyclic reappearance of events and their other dimensions. In this paper, we propose a method and a geovisualization tool, based on the extension of Time Coil and Time Wave, to provide a visual search of cyclic events, by allowing to set any possible duration to the diagram's cyclic temporal scale. We also propose a symbology approach to push the representation of the cyclic time into the map, in order to improve the analysis of relationships between space and the cyclic behavior of events.

The use of spatio-temporal correlation to forecast critical transitions

Science.gov (United States)

Karssenberg, Derek; Bierkens, Marc F. P.

2010-05-01

Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in

Spatiotemporal complexity in coupled map lattices

International Nuclear Information System (INIS)

Kaneko, Kunihiko

1986-01-01

Some spatiotemporal patterns of couple map lattices are presented. The chaotic kink-like motions are shown for the phase motion of the coupled circle lattices. An extension of the couple map lattice approach to Hamiltonian dynamics is briefly reported. An attempt to characterize the high-dimensional attractor by the extension of the correlation dimension is discussed. (author)

Elemental Spatiotemporal Variations of Total Suspended Particles in Jeddah City

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Mohammad W. Kadi

2014-01-01

Full Text Available Elements associated with total suspended particulate matter (TSP in Jeddah city were determined. Using high-volume samplers, TSP samples were simultaneously collected over a one-year period from seven sampling sites. Samples were analyzed for Al, Ba, Ca, Cu, Mg, Fe, Mn, Zn, Ti, V, Cr, Co, Ni, As, and Sr. Results revealed great dependence of element contents on spatial and temporal variations. Two sites characterized by busy roads, workshops, heavy population, and heavy trucking have high levels of all measured elements. Concentrations of most elements at the two sites exhibit strong spatial gradients and concentrations of elements at these sites are higher than other locations. The highest concentrations of elements were observed during June–August because of dust storms, significant increase in energy consumption, and active surface winds. Enrichment factors of elements at the high-level sites have values in the range >10~60 while for Cu and Zn the enrichment factors are much higher (~0–>700 indicating that greater percentage of TSP composition for these three elements in air comes from anthropogenic activities.

Adjusted functional boxplots for spatio-temporal data visualization and outlier detection

KAUST Repository

Sun, Ying

2011-10-24

This article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio-temporal dependence and the 1.5 times the 50% central region empirical outlier detection rule. Then, we propose to simulate observations without outliers on the basis of a robust estimator of the covariance function of the data. We select the constant factor in the functional boxplot to control the probability of correctly detecting no outliers. Finally, we apply the selected factor to the functional boxplot of the original data. As applications, the factor selection procedure and the adjusted functional boxplots are demonstrated on sea surface temperatures, spatio-temporal precipitation and general circulation model (GCM) data. The outlier detection performance is also compared before and after the factor adjustment. © 2011 John Wiley & Sons, Ltd.

Spatiotemporal Dynamics in Vegetation GPP over the Great Khingan Mountains Using GLASS Products from 1982 to 2015

Directory of Open Access Journals (Sweden)

Ling Hu

2018-03-01

Full Text Available Gross primary productivity (GPP is an important parameter that represents the productivity of vegetation and responses to various ecological environments. The Greater Khingan Mountain (GKM is one of the most important state-owned forest bases, and boreal forests, including the largest primeval cold-temperature bright coniferous forest in China, are widely distributed in the GKM. This study aimed to reveal spatiotemporal vegetation variations in the GKM on the basis of GPP products that were generated by the Global LAnd Surface Satellite (GLASS program from 1982 to 2015. First, we explored the spatiotemporal distribution of vegetation across the GKM. Then we analyzed the relationships between GPP variation and driving factors, including meteorological elements, growing season length (GSL, and Fraction of Photosynthetically Active Radiation (FPAR, to investigate the dominant factor for GPP dynamics. Results demonstrated that (1 the spatial distribution of accumulated GPP (AG in spring, summer, autumn, and the growing season varied due to three main reasons: understory vegetation, altitude, and land cover; (2 interannual AG in summer, autumn, and the growing season significantly increased at the regional scale during the past 34 years under climate warming and drying; (3 interannual changes of accumulated GPP in the growing season (AGG at the pixel scale displayed a rapid expansion in areas with a significant increasing trend (p < 0.05 during the period of 1982–2015 and this trend was caused by the natural forest protection project launched in 1998; and finally, (4 an analysis of driving factors showed that daily sunshine duration in summer was the most important factor for GPP in the GKM and this is different from previous studies, which reported that the GSL plays a crucial role in other areas.

Spatiotemporal variability and modeling of the solar irradiance transmissivity through a boreal forest

Science.gov (United States)

Nadeau, D.; Isabelle, P. E.; Asselin, M. H.; Parent, A. C.; Jutras, S.; Anctil, F.

2017-12-01

Solar irradiance is the largest driver of land-surface exchanges of energy, water and trace gases. Its absorption by a forest canopy generates considerable sensible and latent heat fluxes as well as tree temperature changes. A fraction of the irradiance gets transmitted through the canopy and powers another layer of energy fluxes, which can reach substantial values. Transmitted radiation is also of particular relevance to understory vegetation photosynthesis, snowpack energetics and soil temperature dynamics. Boreal forest canopy transmissivity needs to be quantified to properly reproduce land-atmosphere interactions in the circumpolar boreal biome, but its high spatiotemporal variability makes it a challenging task. The objective of this study is to characterize the spatiotemporal variability in under-canopy radiation and to evaluate the performance of various models in representing plot-scale observations. The study site is located in Montmorency Forest (47°N, 71°W), in southern Quebec, Canada. The vegetation includes mostly juvenile balsam firs, up to 6 to 8 m tall. Since January 2016, a 15-m flux tower measures the four components of radiation, as well as other relevant fluxes and meteorological variables, on a ≈10° northeast-facing slope. In summer 2016, 20 portable weather stations were mounted in a 150 m x 200 m grid around the flux tower. These stations were equipped with silicon-cell pyranometers and provided measurements of downwelling irradiance at a height of 2 m. This setup allowed us to compute irradiance transmissivity and to assess its spatiotemporal variability at the site. First, we show that the average of daily incoming energy varies tremendously across the sites, from 1 MJ/m2 to nearly 9 MJ/m2, due to large variations in canopy structure over short distances. Using a regression tree analysis, we show that transmissivity mostly depends on sun elevation, diffuse fraction of radiation, sky and sun view fraction and wind speed above canopy. We

Dynamic characterizers of spatiotemporal intermittency

OpenAIRE

Gupte, Neelima; Jabeen, Zahera

2006-01-01

Systems of coupled sine circle maps show regimes of spatiotemporally intermittent behaviour with associated scaling exponents which belong to the DP class, as well as regimes of spatially intermittent behaviour (with associated regular dynamical behaviour) which do not belong to the DP class. Both types of behaviour are seen along the bifurcation boundaries of the synchronized solutions, and contribute distinct signatures to the dynamical characterizers of the system, viz. the distribution of...

Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch

KAUST Repository

Xie, Le

2014-01-01

We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models. © 2013 IEEE.

Bayesian spatiotemporal model of fMRI data using transfer functions.

Science.gov (United States)

Quirós, Alicia; Diez, Raquel Montes; Wilson, Simon P

2010-09-01

This research describes a new Bayesian spatiotemporal model to analyse BOLD fMRI studies. In the temporal dimension, we describe the shape of the hemodynamic response function (HRF) with a transfer function model. The spatial continuity and local homogeneity of the evoked responses are modelled by a Gaussian Markov random field prior on the parameter indicating activations. The proposal constitutes an extension of the spatiotemporal model presented in a previous approach [Quirós, A., Montes Diez, R. and Gamerman, D., 2010. Bayesian spatiotemporal model of fMRI data, Neuroimage, 49: 442-456], offering more flexibility in the estimation of the HRF and computational advantages in the resulting MCMC algorithm. Simulations from the model are performed in order to ascertain the performance of the sampling scheme and the ability of the posterior to estimate model parameters, as well as to check the model sensitivity to signal to noise ratio. Results are shown on synthetic data and on a real data set from a block-design fMRI experiment. Copyright (c) 2010 Elsevier Inc. All rights reserved.

UNDERSTANDING SEVERE WEATHER PROCESSES THROUGH SPATIOTEMPORAL RELATIONAL RANDOM FORESTS

Data.gov (United States)

National Aeronautics and Space Administration — UNDERSTANDING SEVERE WEATHER PROCESSES THROUGH SPATIOTEMPORAL RELATIONAL RANDOM FORESTS AMY MCGOVERN, TIMOTHY SUPINIE, DAVID JOHN GAGNE II, NATHANIEL TROUTMAN,...

Spatiotemporal Characteristics for the Depth from Luminance Contrast

Directory of Open Access Journals (Sweden)

Kazuya Matsubara

2011-05-01

Full Text Available Images with higher luminance contrast tend to be perceived closer in depth. To investigate a spatiotemporal characteristic of this effect, we evaluated subjective depth of a test stimulus with various spatial and temporal frequencies. For the purpose, the depth of a reference stimulus was matched to that of the test stimulus by changing the binocular disparity. The results showed that the test stimulus was perceived closer with higher luminance contrast for all conditions. Contrast efficiency was obtained from the contrast that provided the subjective depth for each spatiotemporal frequency. The shape of the contrast efficiency function was spatially low-pass and temporally band-pass. This characteristic is different from the one measure for a detection task. This suggests that only subset of contrast signals are used for depth from contrast.

Spatiotemporal characteristics of heat waves over China in regional climate simulations within the CORDEX-EA project

Science.gov (United States)

Wang, Pinya; Tang, Jianping; Sun, Xuguang; Liu, Jianyong; Juan, Fang

2018-03-01

Using the Weather Research and Forecasting (WRF) model, this paper analyzes the spatiotemporal features of heat waves in 20-year regional climate simulations over East Asia, and investigates the capability of WRF to reproduce observational heat waves in China. Within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX), the WRF model is driven by the ERA-Interim (ERAIN) reanalysis, and five continuous simulations are conducted from 1989 to 2008. Of these, four runs apply the interior spectral nudging (SN) technique with different wavenumbers, nudging variables and nudging coefficients. Model validations show that WRF can reasonably reproduce the spatiotemporal features of heat waves in China. Compared with the experiment without SN, the application of SN is effectie on improving the skill of the model in simulating both the spatial distributions and temporal variations of heat waves of different intensities. The WRF model shows advantages in reproducing the synoptic circulations with SN and therefore yields better representations for heat wave events. Besides, the SN method is able to preserve the variability of large-scale circulations quite well, which in turn adjusts the extreme temperature variability towards the observation. Among the four SN experiments, those with stronger nudging coefficients perform better in modulating both the spatial and temporal features of heat waves. In contrast, smaller nudging coefficients weaken the effects of SN on improving WRF's performances.

Evolution of spatio-temporal drought characteristics: validation, projections and effect of adaptation scenarios

Science.gov (United States)

Vidal, J.-P.; Martin, E.; Kitova, N.; Najac, J.; Soubeyroux, J.-M.

2012-08-01

Drought events develop in both space and time and they are therefore best described through summary joint spatio-temporal characteristics, such as mean duration, mean affected area and total magnitude. This paper addresses the issue of future projections of such characteristics of drought events over France through three main research questions: (1) Are downscaled climate projections able to simulate spatio-temporal characteristics of meteorological and agricultural droughts in France over a present-day period? (2) How such characteristics will evolve over the 21st century? (3) How to use standardized drought indices to represent theoretical adaptation scenarios? These questions are addressed using the Isba land surface model, downscaled climate projections from the ARPEGE General Circulation Model under three emissions scenarios, as well as results from a previously performed 50-yr multilevel and multiscale drought reanalysis over France. Spatio-temporal characteristics of meteorological and agricultural drought events are computed using the Standardized Precipitation Index and the Standardized Soil Wetness Index, respectively, and for time scales of 3 and 12 months. Results first show that the distributions of joint spatio-temporal characteristics of observed events are well simulated by the downscaled hydroclimate projections over a present-day period. All spatio-temporal characteristics of drought events are then found to dramatically increase over the 21st century, with stronger changes for agricultural droughts. Two theoretical adaptation scenarios are eventually built based on hypotheses of adaptation to evolving climate and hydrological normals, either retrospective or prospective. The perceived spatio-temporal characteristics of drought events derived from these theoretical adaptation scenarios show much reduced changes, but they call for more realistic scenarios at both the catchment and national scale in order to accurately assess the combined effect of

Prenatal diagnosis of congenital heart disease using four-dimensional spatio-temporal image correlation (STIC) telemedicine via an Internet link: a pilot study.

Science.gov (United States)

Viñals, F; Mandujano, L; Vargas, G; Giuliano, A

2005-01-01

To assess whether the spatio-temporal image correlation (STIC) acquisition technique can be taught to a general obstetrician by e-mail; whether STIC volume datasets can be transmitted over the Internet; and whether STIC volume datasets analyzed offline at a remote setting can be used to confirm or exclude major cardiac defects (TELE-STIC). This was a prospective study involving 50 pregnant women with gestational ages ranging between 20 and 36 weeks. These patients were selected by two general obstetricians (operators) working in geographically remote areas of Chile. Although both obstetricians were users of equipment capable of four-dimensional (4D) ultrasound with STIC, they lacked skill in the performance of fetal cardiac examination. A dedicated web disk was created to upload the acquired volume datasets using an Internet broadband connection. Offline analysis was performed by a single investigator experienced in fetal echocardiography (the administrator). A telemedicine link via the Internet was possible in all cases. Seventy-seven volume datasets were sent to the web server. A complete cardiac examination according to set criteria was achieved by the administrator in 86% of the cases scanned by one operator and 95% of the cases scanned by the other operator. Three patients had cardiac defects confirmed postnatally, two fetuses had extracardiac anomalies and one fetus had a suspected cardiac defect unconfirmed by second-opinion TELE-STIC. There were two isolated major congenital heart defects. Both patients were given advice by e-mail and teleconference using a web camera about the likely outcome and benefits of scheduling in utero transport to a tertiary care center. STIC volumes can be obtained by operators inexperienced in fetal echocardiography, transmitted via the Internet, and their analysis enables recognition of most of the structures and views necessary to assess fetal cardiac anatomy. The preliminary use of TELE-STIC allowed us to demonstrate that

A Bayesian spatio-temporal geostatistical model with an auxiliary lattice for large datasets

KAUST Repository

Xu, Ganggang

2015-01-01

When spatio-temporal datasets are large, the computational burden can lead to failures in the implementation of traditional geostatistical tools. In this paper, we propose a computationally efficient Bayesian hierarchical spatio-temporal model in which the spatial dependence is approximated by a Gaussian Markov random field (GMRF) while the temporal correlation is described using a vector autoregressive model. By introducing an auxiliary lattice on the spatial region of interest, the proposed method is not only able to handle irregularly spaced observations in the spatial domain, but it is also able to bypass the missing data problem in a spatio-temporal process. Because the computational complexity of the proposed Markov chain Monte Carlo algorithm is of the order O(n) with n the total number of observations in space and time, our method can be used to handle very large spatio-temporal datasets with reasonable CPU times. The performance of the proposed model is illustrated using simulation studies and a dataset of precipitation data from the coterminous United States.

a Comparative Analysis of Spatiotemporal Data Fusion Models for Landsat and Modis Data

Science.gov (United States)

Hazaymeh, K.; Almagbile, A.

2018-04-01

In this study, three documented spatiotemporal data fusion models were applied to Landsat-7 and MODIS surface reflectance, and NDVI. The algorithms included the spatial and temporal adaptive reflectance fusion model (STARFM), sparse representation based on a spatiotemporal reflectance fusion model (SPSTFM), and spatiotemporal image-fusion model (STI-FM). The objectives of this study were to (i) compare the performance of these three fusion models using a one Landsat-MODIS spectral reflectance image pairs using time-series datasets from the Coleambally irrigation area in Australia, and (ii) quantitatively evaluate the accuracy of the synthetic images generated from each fusion model using statistical measurements. Results showed that the three fusion models predicted the synthetic Landsat-7 image with adequate agreements. The STI-FM produced more accurate reconstructions of both Landsat-7 spectral bands and NDVI. Furthermore, it produced surface reflectance images having the highest correlation with the actual Landsat-7 images. This study indicated that STI-FM would be more suitable for spatiotemporal data fusion applications such as vegetation monitoring, drought monitoring, and evapotranspiration.

Spatial Specificity in Spatiotemporal Encoding and Fourier Imaging

Science.gov (United States)

Goerke, Ute

2015-01-01

Purpose Ultrafast imaging techniques based on spatiotemporal-encoding (SPEN), such as RASER (rapid acquisition with sequential excitation and refocusing), is a promising new class of sequences since they are largely insensitive to magnetic field variations which cause signal loss and geometric distortion in EPI. So far, attempts to theoretically describe the point-spread-function (PSF) for the original SPEN-imaging techniques have yielded limited success. To fill this gap a novel definition for an apparent PSF is proposed. Theory Spatial resolution in SPEN-imaging is determined by the spatial phase dispersion imprinted on the acquired signal by a frequency-swept excitation or refocusing pulse. The resulting signal attenuation increases with larger distance from the vertex of the quadratic phase profile. Methods Bloch simulations and experiments were performed to validate theoretical derivations. Results The apparent PSF quantifies the fractional contribution of magnetization to a voxel’s signal as a function of distance to the voxel. In contrast, the conventional PSF represents the signal intensity at various locations. Conclusion The definition of the conventional PSF fails for SPEN-imaging since only the phase of isochromats, but not the amplitude of the signal varies. The concept of the apparent PSF is shown to be generalizable to conventional Fourier- imaging techniques. PMID:26712657

Short spatio-temporal variations in the population dynamics and biology of the deep-water rose shrimp Parapenaeus longirostris (Decapoda: Crustacea in the western Mediterranean

Directory of Open Access Journals (Sweden)

Beatriz Guijarro

2009-03-01

Full Text Available The deep-water rose shrimp Parapenaeus longirostris is a demersal decapod crustacean that is commercially exploited by trawl fleets. The present work compares its population dynamics, biology and condition in two locations (southern and north-western Mallorca in the Balearic Islands, western Mediterranean, separated by a distance of 120 km with different environmental conditions and explores the relationships between the species and certain environmental factors. Six multidisciplinary bimonthly surveys were carried out during 2003 and 2004 in these two locations (between 150 and 750 m depth in order to collect data on the demersal species with bottom trawl, the hydrography (temperature and salinity with CTD casts, and trophic resources (zooplankton in the water column and suprabenthos with Bongo net and Macer-GIROQ sledge respectively and sediments with a Shipeck dredge. The trawl fleets from both locations were monitored by monthly on board sampling and daily landings obtained from sales bills. Additional data was obtained from other trawl surveys. Temporal differences were detected both annually, with a decreasing trend over the last years in species abundance, and seasonally, in the biological indexes analysed. Bathymetric differences were also found in abundance, mean length, sex-ratio and condition of females. There were clear differences between the two locations studied, with higher abundance, condition and mean length and a lower length at first maturity for females in the north-western location. Trophic conditions could act as a link between geo-physical and biological changes. These short spatio-temporal differences could be due to the higher productivity found at this location, with higher density of preferred prey for the studied species together with adequate seafloor topography, sediment composition and hydrographical characteristics.

Comparing infants' use of featural and spatiotemporal information when individuating objects in an event monitoring design

DEFF Research Database (Denmark)

Krøjgaard, Peter

. The results obtained using this design reveal that infants are more successful using spatiotemporal object information than when using featural information. However, recent studies using the less cognitively demanding event monitoring design have revealed that even younger infants are capable of object...... in the present series of experiments in which infants' use of spatiotemporal and featural information is compared directly using the less demanding event monitoring design. The results are discussed in relation to existing empirical evidence......., to what extent infants rely on spatiotemporal or featural object information when individuating objects is currently under debate. Hitherto, infants' use of spatiotemporal and featural object information has only been compared directly using the rather cognitively demanding event mapping design...

Spatio-temporal dynamics of the penetration resistance of recultivated soils formed after open cast mining

Directory of Open Access Journals (Sweden)

A. V. Zhukov

2016-01-01

Full Text Available On the basis of studying the spatio-temporal dynamics of soil penetration resistance we proved the existence of the technozem ecomorphs as above horizon soil formations. Research was carried out at a research center for study of recultivation processes in Ordzhonikidze city. Measurement of soils penetration was made in field conditions using an Eijkelkamp penetrometer on a regular grid at depths of up to50 cmwith intervals of5 cm. Calculation of average values and degrees of variation was performed by means of descriptive statistical tools. The extent of soil penetration spatial dependence was assessed and the existence of ecomorphs was proved by means of geostatistical analysis. The degree of associativity of spatial distribution of indicators of a soil body in different years of research was established by means of correlation analysis. The level of variation in space and in time of  technozem penetration generated on loess-like loams, grey-green, red-brown clays, and also pedozems was revealed. The degree of spatial dependence of  technozem penetration within soil layers and also the linear sizes of ecomorphs as above horizon soil structures was established. The time dynamics of  penetration of various recultozems were described. As a result of research into the spatio-temporal dynamics of penetration of technozems, data confirming the hypothesis of the existence of ecomorphs as above horizon morphological soil formations were obtained. An ecomorphic approach to the study of the morphological structure of technozems is proposed. The comparative characteristics of ecomorphs from various types of technozem are presented. The results obtained solve the problem of combining the higher and lowest levels in the hierarchical system of soil organisation as a natural body, which should raise the efficiency of the analysis of relations of morphological elements as a basis for detailed reconstruction of recultivation processes, soil formation, and

Spatiotemporal chaos of self-replicating spots in reaction-diffusion systems.

Science.gov (United States)

Wang, Hongli; Ouyang, Qi

2007-11-23

The statistical properties of self-replicating spots in the reaction-diffusion Gray-Scott model are analyzed. In the chaotic regime of the system, the spots that dominate the spatiotemporal chaos grow and divide in two or decay into the background randomly and continuously. The rates at which the spots are created and decay are observed to be linearly dependent on the number of spots in the system. We derive a probabilistic description of the spot dynamics based on the statistical independence of spots and thus propose a characterization of the spatiotemporal chaos dominated by replicating spots.

Pattern control and suppression of spatiotemporal chaos using geometrical resonance

International Nuclear Information System (INIS)

Gonzalez, J.A.; Bellorin, A.; Reyes, L.I.; Vasquez, C.; Guerrero, L.E.

2004-01-01

We generalize the concept of geometrical resonance to perturbed sine-Gordon, Nonlinear Schroedinger, phi (cursive,open) Greek 4 , and Complex Ginzburg-Landau equations. Using this theory we can control different dynamical patterns. For instance, we can stabilize breathers and oscillatory patterns of large amplitudes successfully avoiding chaos. On the other hand, this method can be used to suppress spatiotemporal chaos and turbulence in systems where these phenomena are already present. This method can be generalized to even more general spatiotemporal systems. A short report of some of our results has been published in [Europhys. Lett. 64 (2003) 743

Spatio-temporal analysis of smear-positive tuberculosis in the Sidama Zone, southern Ethiopia.

Directory of Open Access Journals (Sweden)

Mesay Hailu Dangisso

Full Text Available Tuberculosis (TB is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. Ethiopia is a country with a high burden of TB, with regional variations in TB case notification rates (CNRs. However, TB program reports are often compiled and reported at higher administrative units that do not show the burden at lower units, so there is limited information about the spatial distribution of the disease. We therefore aim to assess the spatial distribution and presence of the spatio-temporal clustering of the disease in different geographic settings over 10 years in the Sidama Zone in southern Ethiopia.A retrospective space-time and spatial analysis were carried out at the kebele level (the lowest administrative unit within a district to identify spatial and space-time clusters of smear-positive pulmonary TB (PTB. Scan statistics, Global Moran's I, and Getis and Ordi (Gi* statistics were all used to help analyze the spatial distribution and clusters of the disease across settings.A total of 22,545 smear-positive PTB cases notified over 10 years were used for spatial analysis. In a purely spatial analysis, we identified the most likely cluster of smear-positive PTB in 192 kebeles in eight districts (RR= 2, p<0.001, with 12,155 observed and 8,668 expected cases. The Gi* statistic also identified the clusters in the same areas, and the spatial clusters showed stability in most areas in each year during the study period. The space-time analysis also detected the most likely cluster in 193 kebeles in the same eight districts (RR= 1.92, p<0.001, with 7,584 observed and 4,738 expected cases in 2003-2012.The study found variations in CNRs and significant spatio-temporal clusters of smear-positive PTB in the Sidama Zone. The findings can be used to guide TB control programs to devise effective TB control strategies for the geographic areas

Spatiotemporal behavior of microearthquakes over an eruption cycle at 9°50'N East Pacific Rise and Axial Seamount

Science.gov (United States)

Tan, Y. J.; Tolstoy, M.; Waldhauser, F.; Wilcock, W. S. D.; Bohnenstiehl, D. R.

2017-12-01

We explore tidal triggering and other spatiotemporal behavior of microearthquakes as an indicator of the stress state at the mid-ocean ridge environment. Only two mid-ocean ridge sites have had ocean bottom seismic monitoring through an eruption cycle. At the East Pacific Rise (EPR), up to 12 ocean bottom seismometers (OBSs) were deployed and recovered approximately annually in a 4 x 4 km region from October 2003 to January 2007, encompassing an eruption in January 2006. 100,000 precisely located microearthquakes delineate an along-axis oriented hydrothermal circulation cell and mostly concentrate above the axial magma lens at 1.5 km depth (Tolstoy et. al., 2008; Waldhauser et. al., 2011). At Axial Seamount, a seismic network was installed as part of the Ocean Observatory Initiative Cabled Array that has been streaming live data since November 2014, encompassing an eruption in April-May of 2015. In the first year of operation, >100,000 precisely located microearthquakes delineate outward dipping ring faults inferred to have accommodated pre-eruptive inflation and syn-eruptive deflation (Wilcock et. al., 2016). At both EPR and Axial, earthquake timing strongly correlates with semidiurnal tides pre-eruption. This correlation with tides weakens significantly post-eruption. This suggests that in the mid-ocean ridge environment, temporal variation in tidal triggering strength may provide useful insight into the stress state of the system. The large number of earthquakes over an extended time period allows us to look at spatiotemporal variation in tidal triggering strength and microearthquake distribution to infer the stress state of the system with unprecedented temporal coverage and resolution. We will present comparisons of observations at the two sites.

Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium.

Science.gov (United States)

Bittihn, Philip; Berg, Sebastian; Parlitz, Ulrich; Luther, Stefan

2017-09-01

Self-organized activation patterns in excitable media such as spiral waves and spatio-temporal chaos underlie dangerous cardiac arrhythmias. While the interaction of single spiral waves with different types of heterogeneity has been studied extensively, the effect of heterogeneity on fully developed spatio-temporal chaos remains poorly understood. We investigate how the complexity and stability properties of spatio-temporal chaos in the Bär-Eiswirth model of excitable media depend on the heterogeneity of the underlying medium. We employ different measures characterizing the chaoticity of the system and find that the spatial arrangement of multiple discrete lower excitability regions has a strong impact on the complexity of the dynamics. Varying the number, shape, and spatial arrangement of the heterogeneities, we observe strong emergent effects ranging from increases in chaoticity to the complete cessation of chaos, contrasting the expectation from the homogeneous behavior. The implications of our findings for the development and treatment of arrhythmias in the heterogeneous cardiac muscle are discussed.

Design and implementation of segment oriented spatio-temporal model in urban panoramic maps

Science.gov (United States)

Li, Haiting; Fei, Lifan; Peng, Qingshan; Li, Yanhong

2009-10-01

Object-oriented spatio-temporal model is directed by human cognition that each object has what/where/when attributes. The precise and flexible structure of such models supports multi-semantics of space and time. This paper reviews current research of spatio-temporal models using object-oriented approach and proposed a new spatio-temporal model based on segmentation in order to resolve the updating problem of some special GIS system by taking advantages of object-oriented spatio-temporal model and adopting category theory. Category theory can be used as a unifying framework for specifying complex systems and it provides rules on how objects may be joined. It characterizes the segments of object through mappings between them. The segment-oriented spatio-temporal model designed for urban panoramic maps is described and implemented. We take points and polylines as objects in this model in the management of panoramic map data. For the randomness of routes which transportation vehicle adopts each time, road objects in this model are split into some segments by crossing points. The segments still remains polyline type, but the splitting makes it easier to update the panoramic data when new photos are captured. This model is capable of eliminating redundant data and accelerating data access when panoramas are unchanged. For evaluation purpose, the data types and operations are designed and implemented in PostgreSQL and the results of experiments come out to prove that this model is efficient and expedient in the application of urban panoramic maps.

The effect of differential motivation on IRT linking

NARCIS (Netherlands)

Mittelhaëuser, M.A.; Béguin, A.A.; Sijtsma, K.

2015-01-01

The purpose of this study was to investigate whether simulated differential motivation between the stakes for operational tests and anchor items produces an invalid linking result if the Rasch model is used to link the operational tests. This was done for an external anchor design and a variation of

Demographic and spatio-temporal variation in human plague at a persistent focus in Tanzania

DEFF Research Database (Denmark)

Davis, S; Makundi, R H; Machang'u, R S

2006-01-01

Human plague in the Western Usambara Mountains in Tanzania has been a public health problem since the first outbreak in 1980. The wildlife reservoir is unknown and eradication measures that have proved effective elsewhere in Tanzania appear to fail in this region. We use census data from 2002...... and hospital records kept since 1986 to describe the temporal, spatial and demographic variation in human plague. A seasonal peak in cases occurs from December to February with the numbers of cases during this peak varying between 0 and 1150. Variation in incidence, calculated for each village as the mean...... number of cases per thousand inhabitants per year, indicates that human plague is concentrated around a group of three neighbouring, relatively isolated, high-altitude villages; Nywelo, Madala and Gologolo. However, there was no evidence that these villages were acting as a source of infection...

Spatiotemporal alignment of in utero BOLD-MRI series.

Science.gov (United States)

Turk, Esra Abaci; Luo, Jie; Gagoski, Borjan; Pascau, Javier; Bibbo, Carolina; Robinson, Julian N; Grant, P Ellen; Adalsteinsson, Elfar; Golland, Polina; Malpica, Norberto

2017-08-01

To present a method for spatiotemporal alignment of in-utero magnetic resonance imaging (MRI) time series acquired during maternal hyperoxia for enabling improved quantitative tracking of blood oxygen level-dependent (BOLD) signal changes that characterize oxygen transport through the placenta to fetal organs. The proposed pipeline for spatiotemporal alignment of images acquired with a single-shot gradient echo echo-planar imaging includes 1) signal nonuniformity correction, 2) intravolume motion correction based on nonrigid registration, 3) correction of motion and nonrigid deformations across volumes, and 4) detection of the outlier volumes to be discarded from subsequent analysis. BOLD MRI time series collected from 10 pregnant women during 3T scans were analyzed using this pipeline. To assess pipeline performance, signal fluctuations between consecutive timepoints were examined. In addition, volume overlap and distance between manual region of interest (ROI) delineations in a subset of frames and the delineations obtained through propagation of the ROIs from the reference frame were used to quantify alignment accuracy. A previously demonstrated rigid registration approach was used for comparison. The proposed pipeline improved anatomical alignment of placenta and fetal organs over the state-of-the-art rigid motion correction methods. In particular, unexpected temporal signal fluctuations during the first normoxia period were significantly decreased (P quantitative studies of placental function by improving spatiotemporal alignment across placenta and fetal organs. 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:403-412. © 2017 International Society for Magnetic Resonance in Medicine.

Spatiotemporal chaos in coupled logistic maps

International Nuclear Information System (INIS)

Varella Guedes, Andre; Amorim Savi, Marcelo

2010-01-01

The objective of this work is to investigate the spatiotemporal dynamics of coupled logistic maps. These maps are prototypes of high-dimensional dynamical systems and have been used to describe the evolution and pattern formation in different systems. Here, the logistic map lattice is coupled by a power law and, therefore, each map is influenced by other maps in its neighborhood. The Kolmogorov-Sinai entropy density is employed to quantify the complexity of system behavior, permitting a general qualitative understanding of different aspects of system dynamics. Three kinds of boundary conditions are treated and the influence of initial conditions is also of concern. Non-homogeneous maps are investigated, showing interesting aspects of spatiotemporal dynamics. The idea is to analyze the spatial interaction between two qualitative different types of behavior from a grid that is split into two parts. Numerical simulations show what types of conditions present a greater tendency to develop chaotic, periodic and synchronized responses. It should be highlighted that non-homogeneous grids have situations where a chaotic pattern can emerge from two periodic responses and also situations where a periodic pattern can emerge from chaos.

Control of Spiral Waves and Spatiotemporal Chaos by Exciting Travel Wave Trains

International Nuclear Information System (INIS)

Yuan Guoyong; Wang Guangrui; Chen Shigang

2005-01-01

Spiral waves and spatiotemporal chaos usually are harmful and need to be suppressed. In this paper, a method is proposed to control them. Travel wave trains can be generated by periodic excitations near left boundary, spiral waves and spatiotemporal chaos can be eliminated by the trains for some certain excitation periods. Obvious resonant behavior can be observed from the relation between the periods of the trains and excitation ones. The method is against noise.

Using nonlinearity and spatiotemporal property modulation to control effective structural properties: dynamic rods

DEFF Research Database (Denmark)

Thomsen, Jon Juel; Blekhman, Iliya I.

2007-01-01

What are the effective properties of a generally nonlinear material or structure, whose local properties are modulated in both space and time? It has been suggested to use spatiotemporal modulation of structural properties to create materials and structures with adjustable effective properties......, and to call these dynamic materials or spatiotemporal composites. Also, according to theoretical predictions, structural nonlinearity enhances the possibilities of achieving specific effective properties. For example, with an elastic rod having cubical elastic nonlinearities, it seems possible to control......, and exemplified. Then simple approximate analytical expressions are derived for the effective wave speed and natural frequencies for one-dimensional wave propagation in a nonlinear elastic rod, where the spatiotemporal modulation is imposed as a high-frequency standing wave, supposed to be given. Finally the more...

Spatio-temporal factors associated with meningococcal meningitis annual incidence at the health centre level in Niger, 2004-2010.

Science.gov (United States)

Paireau, Juliette; Maïnassara, Halima B; Jusot, Jean-François; Collard, Jean-Marc; Idi, Issa; Moulia-Pelat, Jean-Paul; Mueller, Judith E; Fontanet, Arnaud

2014-05-01

Epidemics of meningococcal meningitis (MM) recurrently strike the African Meningitis Belt. This study aimed at investigating factors, still poorly understood, that influence annual incidence of MM serogroup A, the main etiologic agent over 2004-2010, at a fine spatial scale in Niger. To take into account data dependencies over space and time and control for unobserved confounding factors, we developed an explanatory Bayesian hierarchical model over 2004-2010 at the health centre catchment area (HCCA) level. The multivariate model revealed that both climatic and non-climatic factors were important for explaining spatio-temporal variations in incidence: mean relative humidity during November-June over the study region (posterior mean Incidence Rate Ratio (IRR) = 0.656, 95% Credible Interval (CI) 0.405-0.949) and occurrence of early rains in March in a HCCA (IRR = 0.353, 95% CI 0.239-0.502) were protective factors; a higher risk was associated with the percentage of neighbouring HCCAs having at least one MM A case during the same year (IRR = 2.365, 95% CI 2.078-2.695), the presence of a road crossing the HCCA (IRR = 1.743, 95% CI 1.173-2.474) and the occurrence of cases before 31 December in a HCCA (IRR = 6.801, 95% CI 4.004-10.910). At the study region level, higher annual incidence correlated with greater geographic spread and, to a lesser extent, with higher intensity of localized outbreaks. Based on these findings, we hypothesize that spatio-temporal variability of MM A incidence between years and HCCAs result from variations in the intensity or duration of the dry season climatic effects on disease risk, and is further impacted by factors of spatial contacts, representing facilitated pathogen transmission. Additional unexplained factors may contribute to the observed incidence patterns and should be further investigated.

Partial Fourier techniques in single-shot cross-term spatiotemporal encoded MRI.

Science.gov (United States)

Zhang, Zhiyong; Frydman, Lucio

2018-03-01

Cross-term spatiotemporal encoding (xSPEN) is a single-shot approach with exceptional immunity to field heterogeneities, the images of which faithfully deliver 2D spatial distributions without requiring a priori information or using postacquisition corrections. xSPEN, however, suffers from signal-to-noise ratio penalties due to its non-Fourier nature and due to diffusion losses-especially when seeking high resolution. This study explores partial Fourier transform approaches that, acting along either the readout or the spatiotemporally encoded dimensions, reduce these penalties. xSPEN uses an orthogonal (e.g., z) gradient to read, in direct space, the low-bandwidth (e.g., y) dimension. This substantially changes the nature of partial Fourier acquisitions vis-à-vis conventional imaging counterparts. A suitable theoretical analysis is derived to implement these procedures, along either the spatiotemporally or readout axes. Partial Fourier single-shot xSPEN images were recorded on preclinical and human scanners. Owing to their reduction in the experiments' acquisition times, this approach provided substantial sensitivity gains vis-à-vis previous implementations for a given targeted in-plane resolution. The physical origins of these gains are explained. Partial Fourier approaches, particularly when implemented along the low-bandwidth spatiotemporal dimension, provide several-fold sensitivity advantages at minimal costs to the execution and processing of the single-shot experiments. Magn Reson Med 79:1506-1514, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Spatiotemporal modeling of WNV in mosquitoes in Suffolk County

Data.gov (United States)

U.S. Environmental Protection Agency — R code and dataset to produce spatial models. This dataset is associated with the following publication: Meyer, M., S. Campbell, and J. Johnston. Spatiotemporal...

Spatiotemporal Variation in Surface Urban Heat Island Intensity and Associated Determinants across Major Chinese Cities

Directory of Open Access Journals (Sweden)

Juan Wang

2015-03-01

Full Text Available Urban heat islands (UHIs created through urbanization can have negative impacts on the lives of people living in cities. They may also vary spatially and temporally over a city. There is, thus, a need for greater understanding of these patterns and their causes. While previous UHI studies focused on only a few cities and/or several explanatory variables, this research provides a comprehensive and comparative characterization of the diurnal and seasonal variation in surface UHI intensities (SUHIIs across 67 major Chinese cities. The factors associated with the SUHII were assessed by considering a variety of related social, economic and natural factors using a regression tree model. Obvious seasonal variation was observed for the daytime SUHII, and the diurnal variation in SUHII varied seasonally across China. Interestingly, the SUHII varied significantly in character between northern and southern China. Southern China experienced more intense daytime SUHIIs, while the opposite was true for nighttime SUHIIs. Vegetation had the greatest effect in the day time in northern China. In southern China, annual electricity consumption and the number of public buses were found to be important. These results have important theoretical significance and may be of use to mitigate UHI effects.

Discovery of spatio-temporal patterns from location-based social networks

Science.gov (United States)

Béjar, J.; Álvarez, S.; García, D.; Gómez, I.; Oliva, L.; Tejeda, A.; Vázquez-Salceda, J.

2016-03-01

Location-based social networks (LBSNs) such as Twitter or Instagram are a good source for user spatio-temporal behaviour. These networks collect data from users in such a way that they can be seen as a set of collective and distributed sensors of a geographical area. A low rate sampling of user's location information can be obtained during large intervals of time that can be used to discover complex patterns, including mobility profiles, points of interest or unusual events. These patterns can be used as the elements of a knowledge base for different applications in different domains such as mobility route planning, touristic recommendation systems or city planning. The aim of this paper is twofold, first to analyse the frequent spatio-temporal patterns that users share when living and visiting a city. This behaviour is studied by means of frequent itemsets algorithms in order to establish some associations among visits that can be interpreted as interesting routes or spatio-temporal connections. Second, to analyse how the spatio-temporal behaviour of a large number of users can be segmented in different profiles. These behavioural profiles are obtained by means of clustering algorithms that show the different patterns of behaviour of visitors and citizens. The data analysed were obtained from the public data feeds of Twitter and Instagram within an area surrounding the cities of Barcelona and Milan for a period of several months. The analysis of these data shows that these kinds of algorithms can be successfully applied to data from any city (or general area) to discover useful patterns that can be interpreted on terms of singular places and areas and their temporal relationships.

Control and characterization of spatio-temporal disorder in ...

Indian Academy of Sciences (India)

characterizing the type of spatio-temporal disorder that is embodied in this disordered ... The results from this experiment will shed light on the more general questions ... sponds to only odd or even multiples of the common frequency, ω0. Thus ...

Against Laplacian Reduction of Newtonian Mass to Spatiotemporal Quantities

Science.gov (United States)

Martens, Niels C. M.

2018-03-01

Laplace wondered about the minimal choice of initial variables and parameters corresponding to a well-posed initial value problem. Discussions of Laplace's problem in the literature have focused on choosing between spatiotemporal variables relative to absolute space (i.e. substantivalism) or merely relative to other material bodies (i.e. relationalism) and between absolute masses (i.e. absolutism) or merely mass ratios (i.e. comparativism). This paper extends these discussions of Laplace's problem, in the context of Newtonian Gravity, by asking whether mass needs to be included in the initial state at all, or whether a purely spatiotemporal initial state suffices. It is argued that mass indeed needs to be included; removing mass from the initial state drastically reduces the predictive and explanatory power of Newtonian Gravity.

Spatiotemporal Stochastic Resonance:Theory and Experiment

Science.gov (United States)

Peter, Jung

1996-03-01

The amplification of weak periodic signals in bistable or excitable systems via stochastic resonance has been studied intensively over the last years. We are going one step further and ask: Can noise enhance spatiotemporal patterns in excitable media and can this effect be observed in nature? To this end, we are looking at large, two dimensional arrays of coupled excitable elements. Due to the coupling, excitation can propagate through the array in form of nonlinear waves. We observe target waves, rotating spiral waves and other wave forms. If the coupling between the elements is below a critical threshold, any excitational pattern will die out in the absence of noise. Below this threshold, large scale rotating spiral waves - as they are observed above threshold - can be maintained by a proper level of the noise[1]. Furthermore, their geometric features, such as the curvature can be controlled by the homogeneous noise level[2]. If the noise level is too large, break up of spiral waves and collisions with spontaneously nucleated waves yields spiral turbulence. Driving our array with a spatiotemporal pattern, e.g. a rotating spiral wave, we show that for weak coupling the excitational response of the array shows stochastic resonance - an effect we have termed spatiotemporal stochastic resonance. In the last part of the talk I'll make contact with calcium waves, observed in astrocyte cultures and hippocampus slices[3]. A. Cornell-Bell and collaborators[3] have pointed out the role of calcium waves for long-range glial signaling. We demonstrate the similarity of calcium waves with nonlinear waves in noisy excitable media. The noise level in the tissue is characterized by spontaneous activity and can be controlled by applying neuro-transmitter substances[3]. Noise effects in our model are compared with the effect of neuro-transmitters on calcium waves. [1]P. Jung and G. Mayer-Kress, CHAOS 5, 458 (1995). [2]P. Jung and G. Mayer-Kress, Phys. Rev. Lett.62, 2682 (1995). [3

Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons.

Science.gov (United States)

Oddo, Calogero M; Mazzoni, Alberto; Spanne, Anton; Enander, Jonas M D; Mogensen, Hannes; Bengtsson, Fredrik; Camboni, Domenico; Micera, Silvestro; Jörntell, Henrik

2017-04-04

Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an artificial fingertip equipped with an array of neuromorphic sensors. The artificial fingertip was used to transduce real-world haptic stimuli into spatiotemporal patterns of spikes. These spike patterns were delivered to the skin afferents of the second digit of rats via an array of stimulation electrodes. Combined with low-noise intra- and extracellular recordings from neocortical neurons in vivo, this approach provided a previously inaccessible high resolution analysis of the representation of tactile information in the neocortical neuronal circuitry. The results indicate high information content in individual neurons and reveal multiple novel neuronal tactile coding features such as heterogeneous and complementary spatiotemporal input selectivity also between neighboring neurons. Such neuronal heterogeneity and complementariness can potentially support a very high decoding capacity in a limited population of neurons. Our results also indicate a potential neuroprosthetic approach to communicate with the brain at a very high resolution and provide a potential novel solution for evaluating the degree or state of neurological disease in animal models.

Spatiotemporal behavior and nonlinear dynamics in a phase conjugate resonator

Science.gov (United States)

Liu, Siuying Raymond

1993-01-01

The work described can be divided into two parts. The first part is an investigation of the transient behavior and stability property of a phase conjugate resonator (PCR) below threshold. The second part is an experimental and theoretical study of the PCR's spatiotemporal dynamics above threshold. The time-dependent coupled wave equations for four-wave mixing (FWM) in a photorefractive crystal, with two distinct interaction regions caused by feedback from an ordinary mirror, was used to model the transient dynamics of a PCR below threshold. The conditions for self-oscillation were determined and the solutions were used to define the PCR's transfer function and analyze its stability. Experimental results for the buildup and decay times confirmed qualitatively the predicted behavior. Experiments were carried out above threshold to study the spatiotemporal dynamics of the PCR as a function of Pragg detuning and the resonator's Fresnel number. The existence of optical vortices in the wavefront were identified by optical interferometry. It was possible to describe the transverse dynamics and the spatiotemporal instabilities by modeling the three-dimensional-coupled wave equations in photorefractive FWM using a truncated modal expansion approach.

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System.

Science.gov (United States)

Xiong, Lian; Yang, Liu; Tao, Yang; Xu, Juan; Zhao, Lun

2018-01-14

The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay.

In silico detection of sequence variations modifying transcriptional regulation.

Directory of Open Access Journals (Sweden)

Malin C Andersen

2008-01-01

Full Text Available Identification of functional genetic variation associated with increased susceptibility to complex diseases can elucidate genes and underlying biochemical mechanisms linked to disease onset and progression. For genes linked to genetic diseases, most identified causal mutations alter an encoded protein sequence. Technological advances for measuring RNA abundance suggest that a significant number of undiscovered causal mutations may alter the regulation of gene transcription. However, it remains a challenge to separate causal genetic variations from linked neutral variations. Here we present an in silico driven approach to identify possible genetic variation in regulatory sequences. The approach combines phylogenetic footprinting and transcription factor binding site prediction to identify variation in candidate cis-regulatory elements. The bioinformatics approach has been tested on a set of SNPs that are reported to have a regulatory function, as well as background SNPs. In the absence of additional information about an analyzed gene, the poor specificity of binding site prediction is prohibitive to its application. However, when additional data is available that can give guidance on which transcription factor is involved in the regulation of the gene, the in silico binding site prediction improves the selection of candidate regulatory polymorphisms for further analyses. The bioinformatics software generated for the analysis has been implemented as a Web-based application system entitled RAVEN (regulatory analysis of variation in enhancers. The RAVEN system is available at http://www.cisreg.ca for all researchers interested in the detection and characterization of regulatory sequence variation.

In Silico Detection of Sequence Variations Modifying Transcriptional Regulation

Science.gov (United States)

Andersen, Malin C; Engström, Pär G; Lithwick, Stuart; Arenillas, David; Eriksson, Per; Lenhard, Boris; Wasserman, Wyeth W; Odeberg, Jacob

2008-01-01

Identification of functional genetic variation associated with increased susceptibility to complex diseases can elucidate genes and underlying biochemical mechanisms linked to disease onset and progression. For genes linked to genetic diseases, most identified causal mutations alter an encoded protein sequence. Technological advances for measuring RNA abundance suggest that a significant number of undiscovered causal mutations may alter the regulation of gene transcription. However, it remains a challenge to separate causal genetic variations from linked neutral variations. Here we present an in silico driven approach to identify possible genetic variation in regulatory sequences. The approach combines phylogenetic footprinting and transcription factor binding site prediction to identify variation in candidate cis-regulatory elements. The bioinformatics approach has been tested on a set of SNPs that are reported to have a regulatory function, as well as background SNPs. In the absence of additional information about an analyzed gene, the poor specificity of binding site prediction is prohibitive to its application. However, when additional data is available that can give guidance on which transcription factor is involved in the regulation of the gene, the in silico binding site prediction improves the selection of candidate regulatory polymorphisms for further analyses. The bioinformatics software generated for the analysis has been implemented as a Web-based application system entitled RAVEN (regulatory analysis of variation in enhancers). The RAVEN system is available at http://www.cisreg.ca for all researchers interested in the detection and characterization of regulatory sequence variation. PMID:18208319

Spatiotemporal Features of the Three-Dimensional Architectural Landscape in Qingdao, China.

Directory of Open Access Journals (Sweden)

Peifeng Zhang

Full Text Available The evolution and development of the three-dimensional (3D architectural landscape is the basis of proper urban planning, eco-environment construction and the improvement of environmental quality. This paper presents the spatiotemporal characteristics of the 3D architectural landscape of the Shinan and Shibei districts in Qingdao, China, based on buildings' 3D information extracted from Quickbird images from 2003 to 2012, supported by Barista, landscape metrics and GIS. The results demonstrated that: (1 Shinan and Shibei districts expanded vertically and urban land use intensity increased noticeably from year to year. (2 Significant differences in the 3D architectural landscape existed among the western, central and eastern regions, and among the 26 sub-districts over the study period. The differentiation was consistent with the diverse development history, function and planning of the two districts. Finally, we found that population correlates positively with the variation in the 3D architectural landscape. This research provides an important reference for related studies, urban planning and eco-city construction.

Intraurban Spatiotemporal Variability of Ambient Air Pollutants across Metropolitan St. Louis

Science.gov (United States)

Du, Li

these data. Intraurban spatiotemporal variability for certain species was evaluated in the context of measurement error. For example, for species otherwise considered homogeneous, differential impacts from local point sources at different locations could be identified after comparing the observed day-to-day variations to those contributed by measurement error. In addition, source apportionment modeling was conducted using single- and multi-site datasets to assign measured PM2.5 mass to emission source categories. A suite of approaches were used to aid in the selection of an appropriate number of factors including metrics recently added to the US EPA Positive Matrix Factorization (EPA PMF) modeling software and the sensitivity of modeling results to perturbations on the measurement uncertainties.

Spatiotemporal resonances in mixing of open viscous fluids

DEFF Research Database (Denmark)

Okkels, Fridolin; Tabeling, Patrick

2004-01-01

In this Letter, we reveal a new dynamical phenomenon, called "spatiotemporal resonance," which is expected to take place in a broad range of viscous, periodically forced, open systems. The observation originates from a numerical and theoretical analysis of a micromixer, and is supported...

A novel method for one-way hash function construction based on spatiotemporal chaos

Energy Technology Data Exchange (ETDEWEB)

Ren Haijun [College of Software Engineering, Chongqing University, Chongqing 400044 (China); State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400044 (China)], E-mail: jhren@cqu.edu.cn; Wang Yong; Xie Qing [Key Laboratory of Electronic Commerce and Logistics of Chongqing, Chongqing University of Posts and Telecommunications, Chongqing 400065 (China); Yang Huaqian [Department of Computer and Modern Education Technology, Chongqing Education of College, Chongqing 400067 (China)

2009-11-30

A novel hash algorithm based on a spatiotemporal chaos is proposed. The original message is first padded with zeros if needed. Then it is divided into a number of blocks each contains 32 bytes. In the hashing process, each block is partitioned into eight 32-bit values and input into the spatiotemporal chaotic system. Then, after iterating the system for four times, the next block is processed by the same way. To enhance the confusion and diffusion effect, the cipher block chaining (CBC) mode is adopted in the algorithm. The hash value is obtained from the final state value of the spatiotemporal chaotic system. Theoretic analyses and numerical simulations both show that the proposed hash algorithm possesses good statistical properties, strong collision resistance and high efficiency, as required by practical keyed hash functions.

A novel method for one-way hash function construction based on spatiotemporal chaos

International Nuclear Information System (INIS)

Ren Haijun; Wang Yong; Xie Qing; Yang Huaqian

2009-01-01

A novel hash algorithm based on a spatiotemporal chaos is proposed. The original message is first padded with zeros if needed. Then it is divided into a number of blocks each contains 32 bytes. In the hashing process, each block is partitioned into eight 32-bit values and input into the spatiotemporal chaotic system. Then, after iterating the system for four times, the next block is processed by the same way. To enhance the confusion and diffusion effect, the cipher block chaining (CBC) mode is adopted in the algorithm. The hash value is obtained from the final state value of the spatiotemporal chaotic system. Theoretic analyses and numerical simulations both show that the proposed hash algorithm possesses good statistical properties, strong collision resistance and high efficiency, as required by practical keyed hash functions.

Synchronization of spatiotemporal chaotic systems and application to secure communication of digital image

International Nuclear Information System (INIS)

Wang Xing-Yuan; Zhang Na; Ren Xiao-Li; Zhang Yong-Lei

2011-01-01

Coupled map lattices (CMLs) are taken as examples to study the synchronization of spatiotemporal chaotic systems. In this paper, we use the nonlinear coupled method to implement the synchronization of two coupled map lattices. Through the appropriate separation of the linear term from the nonlinear term of the spatiotemporal chaotic system, we set the nonlinear term as the coupling function and then we can achieve the synchronization of two coupled map lattices. After that, we implement the secure communication of digital image using this synchronization method. Then, the discrete characteristics of the nonlinear coupling spatiotemporal chaos are applied to the discrete pixel of the digital image. After the synchronization of both the communication parties, the receiver can decrypt the original image. Numerical simulations show the effectiveness and the feasibility of the proposed program. (general)

Spatio-temporal patterns in simple models of marine systems

Science.gov (United States)

Feudel, U.; Baurmann, M.; Gross, T.

2009-04-01

Spatio-temporal patterns in marine systems are a result of the interaction of population dynamics with physical transport processes. These physical transport processes can be either diffusion processes in marine sediments or in the water column. We study the dynamics of one population of bacteria and its nutrient in in a simplified model of a marine sediments, taking into account that the considered bacteria possess an active as well as an inactive state, where activation is processed by signal molecules. Furthermore the nutrients are transported actively by bioirrigation and passively by diffusion. It is shown that under certain conditions Turing patterns can occur which yield heterogeneous spatial patterns of the species. The influence of bioirrigation on Turing patterns leads to the emergence of ''hot spots``, i.e. localized regions of enhanced bacterial activity. All obtained patterns fit quite well to observed patterns in laboratory experiments. Spatio-temporal patterns appear in a predator-prey model, used to describe plankton dynamics. These patterns appear due to the simultaneous emergence of Turing patterns and oscillations in the species abundance in the neighborhood of a Turing-Hopf bifurcation. We observe a large variety of different patterns where i) stationary heterogeneous patterns (e.g. hot and cold spots) compete with spatio-temporal patterns ii) slowly moving patterns are embedded in an oscillatory background iii) moving fronts and spiral waves appear.

High spatio-temporal resolution observations of crater-lake temperatures at Kawah Ijen volcano, East Java, Indonesia

Science.gov (United States)

Lewicki, Jennifer L.; Corentin Caudron,; Vincent van Hinsberg,; George Hilley,

2016-01-01

The crater lake of Kawah Ijen volcano, East Java, Indonesia, has displayed large and rapid changes in temperature at point locations during periods of unrest, but measurement techniques employed to-date have not resolved how the lake’s thermal regime has evolved over both space and time. We applied a novel approach for mapping and monitoring variations in crater-lake apparent surface (“skin”) temperatures at high spatial (~32 cm) and temporal (every two minutes) resolution at Kawah Ijen on 18 September 2014. We used a ground-based FLIR T650sc camera with digital and thermal infrared (TIR) sensors from the crater rim to collect (1) a set of visible imagery around the crater during the daytime and (2) a time series of co-located visible and TIR imagery at one location from pre-dawn to daytime. We processed daytime visible imagery with the Structure-from-Motion photogrammetric method to create a digital elevation model onto which the time series of TIR imagery was orthorectified and georeferenced. Lake apparent skin temperatures typically ranged from ~21 to 33oC. At two locations, apparent skin temperatures were ~ 4 and 7 oC less than in-situ lake temperature measurements at 1.5 and 5 m depth, respectively. These differences, as well as the large spatio-temporal variations observed in skin temperatures, were likely largely associated with atmospheric effects such as evaporative cooling of the lake surface and infrared absorption by water vapor and SO2. Calculations based on orthorectified TIR imagery thus yielded underestimates of volcanic heat fluxes into the lake, whereas volcanic heat fluxes estimated based on in-situ temperature measurements (68 to 111 MW) were likely more representative of Kawah Ijen in a quiescent state. The ground-based imaging technique should provide a valuable tool to continuously monitor crater-lake temperatures and contribute insight into the spatio-temporal evolution of these temperatures associated with volcanic activity.

Multiscale recurrence analysis of spatio-temporal data

Science.gov (United States)

Riedl, M.; Marwan, N.; Kurths, J.

2015-12-01

The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

Spatio-temporal patterns of coral recruitment at Vamizi Island ...

African Journals Online (AJOL)

Spatio-temporal patterns of coral recruitment at Vamizi Island, Quirimbas Archipelago, Mozambique. ... Spatial and temporal patterns of recruitment of reef corals were assessed for the first time in Mozambique ... AJOL African Journals Online.

CoNVaQ: a web tool for copy number variation-based association studies

DEFF Research Database (Denmark)

Larsen, Simon Jonas; do Canto, Luisa Matos; Rogatto, Silvia Regina

2018-01-01

Copy number variations (CNVs) are large segments of the genome that are duplicated or deleted. Structural variations in the genome have been linked to many complex diseases. Similar to how genome-wide association studies (GWAS) have helped discover single-nucleotide polymorphisms linked to diseas...

Mapping the Decadal Spatio-temporal Variation of Social Vulnerability to Hydro-climatic Extremes over India

Science.gov (United States)

H, V.; Karmakar, S.; Ghosh, S.

2015-12-01

Human induced global warming is unequivocal and observational studies shows that, this has led to increase in the intensity and frequency of hydro-climatic extremes, most importantly precipitation extreme, heat waves and drought; and also is expected to be increased in the future. The occurrence of these extremes have a devastating effects on nation's economy and on societal well-being. Previous studies on India provided the evidences of significant changes in the precipitation extreme from pre- to post-1950, with huge spatial heterogeneity; and projections of heat waves indicated that significant part of India will experience heat stress conditions in the future. Under these circumstance, it is necessary to develop a nation-wide social vulnerability map to scrutinize the adequacy of existing emergency management. Yet there has been no systematic past efforts on mapping social vulnerability to hydro-climatic extremes at nation-wide for India. Therefore, immediate efforts are required to quantify the social vulnerability, particularly developing country like India, where major transformations in demographic characteristics and development patterns are evident during past decades. In the present study, we perform a comprehensive spatio-temporal social vulnerability analysis by considering multiple sensitive indicators for three decades (1990-2010) which identifies the hot-spots, with higher vulnerability to hydro-climatic extremes. The population datasets are procured from Census of India and the meteorological datasets are obtained from India Meteorological Department (IMD). The study derives interesting results on decadal changes of spatial distribution of risk, considering social vulnerability and hazard to extremes.

Large scale stochastic spatio-temporal modelling with PCRaster

NARCIS (Netherlands)

Karssenberg, D.J.; Drost, N.; Schmitz, O.; Jong, K. de; Bierkens, M.F.P.

2013-01-01

PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model

Role of Temporal Diversity in Inferring Social Ties Based on Spatio-Temporal Data

OpenAIRE

Desai, Deshana; Nisar, Harsh; Bhardawaj, Rishab

2016-01-01

The last two decades have seen a tremendous surge in research on social networks and their implications. The studies includes inferring social relationships, which in turn have been used for target advertising, recommendations, search customization etc. However, the offline experiences of human, the conversations with people and face-to-face interactions that govern our lives interactions have received lesser attention. We introduce DAIICT Spatio-Temporal Network (DSSN), a spatiotemporal data...

Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation

OpenAIRE

Le Wang; Xuhuan Duan; Qilin Zhang; Zhenxing Niu; Gang Hua; Nanning Zheng

2018-01-01

Inspired by the recent spatio-temporal action localization efforts with tubelets (sequences of bounding boxes), we present a new spatio-temporal action localization detector Segment-tube, which consists of sequences of per-frame segmentation masks. The proposed Segment-tube detector can temporally pinpoint the starting/ending frame of each action category in the presence of preceding/subsequent interference actions in untrimmed videos. Simultaneously, the Segment-tube detector produces per-fr...

On the Reproducibility of Label-Free Quantitative Cross-Linking/Mass Spectrometry

Science.gov (United States)

Müller, Fränze; Fischer, Lutz; Chen, Zhuo Angel; Auchynnikava, Tania; Rappsilber, Juri

2018-02-01

Quantitative cross-linking/mass spectrometry (QCLMS) is an emerging approach to study conformational changes of proteins and multi-subunit complexes. Distinguishing protein conformations requires reproducibly identifying and quantifying cross-linked peptides. Here we analyzed the variation between multiple cross-linking reactions using bis[sulfosuccinimidyl] suberate (BS3)-cross-linked human serum albumin (HSA) and evaluated how reproducible cross-linked peptides can be identified and quantified by LC-MS analysis. To make QCLMS accessible to a broader research community, we developed a workflow that integrates the established software tools MaxQuant for spectra preprocessing, Xi for cross-linked peptide identification, and finally Skyline for quantification (MS1 filtering). Out of the 221 unique residue pairs identified in our sample, 124 were subsequently quantified across 10 analyses with coefficient of variation (CV) values of 14% (injection replica) and 32% (reaction replica). Thus our results demonstrate that the reproducibility of QCLMS is in line with the reproducibility of general quantitative proteomics and we establish a robust workflow for MS1-based quantitation of cross-linked peptides.

Neurogenomic signatures of spatiotemporal memories in time-trained forager honey bees

Science.gov (United States)

Naeger, Nicholas L.; Van Nest, Byron N.; Johnson, Jennifer N.; Boyd, Sam D.; Southey, Bruce R.; Rodriguez-Zas, Sandra L.; Moore, Darrell; Robinson, Gene E.

2011-01-01

Honey bees can form distinct spatiotemporal memories that allow them to return repeatedly to different food sources at different times of day. Although it is becoming increasingly clear that different behavioral states are associated with different profiles of brain gene expression, it is not known whether this relationship extends to states that are as dynamic and specific as those associated with foraging-related spatiotemporal memories. We tested this hypothesis by training different groups of foragers from the same colony to collect sucrose solution from one of two artificial feeders; each feeder was in a different location and had sucrose available at a different time, either in the morning or afternoon. Bees from both training groups were collected at both the morning and afternoon training times to result in one set of bees that was undergoing stereotypical food anticipatory behavior and another that was inactive for each time of day. Between the two groups with the different spatiotemporal memories, microarray analysis revealed that 1329 genes were differentially expressed in the brains of honey bees. Many of these genes also varied with time of day, time of training or state of food anticipation. Some of these genes are known to be involved in a variety of biological processes, including metabolism and behavior. These results indicate that distinct spatiotemporal foraging memories in honey bees are associated with distinct neurogenomic signatures, and the decomposition of these signatures into sets of genes that are also influenced by time or activity state hints at the modular composition of this complex neurogenomic phenotype. PMID:21346126

On the expected value and variance for an estimator of the spatio-temporal product density function

DEFF Research Database (Denmark)

Rodríguez-Corté, Francisco J.; Ghorbani, Mohammad; Mateu, Jorge

Second-order characteristics are used to analyse the spatio-temporal structure of the underlying point process, and thus these methods provide a natural starting point for the analysis of spatio-temporal point process data. We restrict our attention to the spatio-temporal product density function......, and develop a non-parametric edge-corrected kernel estimate of the product density under the second-order intensity-reweighted stationary hypothesis. The expectation and variance of the estimator are obtained, and closed form expressions derived under the Poisson case. A detailed simulation study is presented...... to compare our close expression for the variance with estimated ones for Poisson cases. The simulation experiments show that the theoretical form for the variance gives acceptable values, which can be used in practice. Finally, we apply the resulting estimator to data on the spatio-temporal distribution...

Spatiotemporal coding of inputs for a system of globally coupled phase oscillators

Science.gov (United States)

Wordsworth, John; Ashwin, Peter

2008-12-01

We investigate the spatiotemporal coding of low amplitude inputs to a simple system of globally coupled phase oscillators with coupling function g(ϕ)=-sin(ϕ+α)+rsin(2ϕ+β) that has robust heteroclinic cycles (slow switching between cluster states). The inputs correspond to detuning of the oscillators. It was recently noted that globally coupled phase oscillators can encode their frequencies in the form of spatiotemporal codes of a sequence of cluster states [P. Ashwin, G. Orosz, J. Wordsworth, and S. Townley, SIAM J. Appl. Dyn. Syst. 6, 728 (2007)]. Concentrating on the case of N=5 oscillators we show in detail how the spatiotemporal coding can be used to resolve all of the information that relates the individual inputs to each other, providing that a long enough time series is considered. We investigate robustness to the addition of noise and find a remarkable stability, especially of the temporal coding, to the addition of noise even for noise of a comparable magnitude to the inputs.

Spatiotemporal variability of oxygen isotope compositions in three contrasting glacier river catchments in Greenland

DEFF Research Database (Denmark)

Knudsen, N. Tvis; Yde, J.C.; Steffensen, J.P.

2015-01-01

composition is controlled by the proportion between snowmelt and ice melt with episodic inputs of rainwater and occasional storage and release of a specific water component due to changes in the subglacial drainage system. At Kuannersuit Glacier River on the island Qeqertarsuaq, the δ18O characteristics were......Analysis of stable oxygen isotope (δ18O) characteristics is a useful tool to investigate water provenance in glacier river systems. In order to attain knowledge on the diversity of spatio-temporal δ18O variations in glacier rivers, we have examined three glacierized catchments in Greenland...... of diurnal oscillations, and in 2003 there were large diurnal fluctuations in δ18O. At Watson River, a large catchment at the western margin of the Greenland Ice Sheet, the spatial distribution of δ18O in the river system was applied to fingerprint the relative runoff contributions from sub-catchments. Spot...

Transient spatiotemporal chaos in the Morris-Lecar neuronal ring network

Energy Technology Data Exchange (ETDEWEB)

Keplinger, Keegan, E-mail: keegankeplinger@gmail.com; Wackerbauer, Renate, E-mail: rawackerbauer@alaska.edu [Department of Physics, University of Alaska, Fairbanks, Alaska 99775-5920 (United States)

2014-03-15

Transient behavior is thought to play an integral role in brain functionality. Numerical simulations of the firing activity of diffusively coupled, excitable Morris-Lecar neurons reveal transient spatiotemporal chaos in the parameter regime below the saddle-node on invariant circle bifurcation point. The neighborhood of the chaotic saddle is reached through perturbations of the rest state, in which few initially active neurons at an effective spatial distance can initiate spatiotemporal chaos. The system escapes from the neighborhood of the chaotic saddle to either the rest state or to a state of pulse propagation. The lifetime of the chaotic transients is manipulated in a statistical sense through a singular application of a synchronous perturbation to a group of neurons.

Transient spatiotemporal chaos in the Morris-Lecar neuronal ring network.

Science.gov (United States)

Keplinger, Keegan; Wackerbauer, Renate

2014-03-01

Transient behavior is thought to play an integral role in brain functionality. Numerical simulations of the firing activity of diffusively coupled, excitable Morris-Lecar neurons reveal transient spatiotemporal chaos in the parameter regime below the saddle-node on invariant circle bifurcation point. The neighborhood of the chaotic saddle is reached through perturbations of the rest state, in which few initially active neurons at an effective spatial distance can initiate spatiotemporal chaos. The system escapes from the neighborhood of the chaotic saddle to either the rest state or to a state of pulse propagation. The lifetime of the chaotic transients is manipulated in a statistical sense through a singular application of a synchronous perturbation to a group of neurons.

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System

Science.gov (United States)

Xiong, Lian; Tao, Yang; Xu, Juan; Zhao, Lun

2018-01-01

The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay. PMID:29342897

Using climate information to understand the spatio-temporal heterogeneity of a chikungunya outbreak in the presence of widespread asymptomatic infection

Science.gov (United States)

Dommar, C. J.; Lowe, R.; Robinson, M.; Rodó, X.

2013-12-01

The emergence and persistence of human pathogens in the environment represents a constant threat to society, with global implications for human health, economies and ecosystems. Of particular concern are vector-borne diseases, such as dengue, malaria and chikungunya, which are increasing across their traditional ranges and continuing to infiltrate new regions. This unprecedented situation has been partly attributed to the increase in global temperatures in recent decades which has allowed non-native mosquito species to invade and successfully colonise previously inhospitable environments The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. In turn, vector populations are thought to be driven by external environmental variables, such as precipitation and temperature. Furthermore, the ability of asymptomatic individuals to successfully transmit the infection and evade control measures can undermine public health interventions. We employed a stochastic model, which explicitly included asymptomatic and undocumented laboratory confirmed cases, and applied it to a documented outbreak in Cambodia in 2012 (Trapeang Roka village, Kampong Speu Province). The resulting estimate of the reproduction number was considerably higher than values obtained for previous outbreaks and highlights the importance of asymptomatic transmission. Subsequently, we develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals alone is

How spatio-temporal habitat connectivity affects amphibian genetic structure.

Science.gov (United States)

Watts, Alexander G; Schlichting, Peter E; Billerman, Shawn M; Jesmer, Brett R; Micheletti, Steven; Fortin, Marie-Josée; Funk, W Chris; Hapeman, Paul; Muths, Erin; Murphy, Melanie A

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

How spatio-temporal habitat connectivity affects amphibian genetic structure

Science.gov (United States)

Watts, Alexander G.; Schlichting, P; Billerman, S; Jesmer, B; Micheletti, S; Fortin, M.-J.; Funk, W.C.; Hapeman, P; Muths, Erin L.; Murphy, M.A.

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

Spatio-temporal change detection from multidimensional arrays: Detecting deforestation from MODIS time series

Science.gov (United States)

Lu, Meng; Pebesma, Edzer; Sanchez, Alber; Verbesselt, Jan

2016-07-01

Growing availability of long-term satellite imagery enables change modeling with advanced spatio-temporal statistical methods. Multidimensional arrays naturally match the structure of spatio-temporal satellite data and can provide a clean modeling process for complex spatio-temporal analysis over large datasets. Our study case illustrates the detection of breakpoints in MODIS imagery time series for land cover change in the Brazilian Amazon using the BFAST (Breaks For Additive Season and Trend) change detection framework. BFAST includes an Empirical Fluctuation Process (EFP) to alarm the change and a change point time locating process. We extend the EFP to account for the spatial autocorrelation between spatial neighbors and assess the effects of spatial correlation when applying BFAST on satellite image time series. In addition, we evaluate how sensitive EFP is to the assumption that its time series residuals are temporally uncorrelated, by modeling it as an autoregressive process. We use arrays as a unified data structure for the modeling process, R to execute the analysis, and an array database management system to scale computation. Our results point to BFAST as a robust approach against mild temporal and spatial correlation, to the use of arrays to ease the modeling process of spatio-temporal change, and towards communicable and scalable analysis.

Spatio-temporal scaling effects on longshore sediment transport pattern along the nearshore zone

Science.gov (United States)

Khorram, Saeed; Ergil, Mustafa

2018-03-01

A measure of uncertainties, entropy has been employed in such different applications as coastal engineering probability inferences. Entropy sediment transport integration theories present novel visions in coastal analyses/modeling the application and development of which are still far-reaching. Effort has been made in the present paper to propose a method that needs an entropy-power index for spatio-temporal patterns analyses. Results have shown that the index is suitable for marine/hydrological ecosystem components analyses based on a beach area case study. The method makes use of six Makran Coastal monthly data (1970-2015) and studies variables such as spatio-temporal patterns, LSTR (long-shore sediment transport rate), wind speed, and wave height all of which are time-dependent and play considerable roles in terrestrial coastal investigations; the mentioned variables show meaningful spatio-temporal variability most of the time, but explanation of their combined performance is not easy. Accordingly, the use of an entropy-power index can show considerable signals that facilitate the evaluation of water resources and will provide an insight regarding hydrological parameters' interactions at scales as large as beach areas. Results have revealed that an STDDPI (entropy based spatio-temporal disorder dynamics power index) can simulate wave, long-shore sediment transport rate, and wind when granulometry, concentration, and flow conditions vary.

Evaluation of high resolution spatio-temporal precipitation extremes from a stochastic weather generator

DEFF Research Database (Denmark)

Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten

gauges in the model area. The spatio-temporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatio-temporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying onprecipitation output......Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...

Using a weather generator to downscale spatio-temporal precipitation at urban scale

DEFF Research Database (Denmark)

Sørup, Hjalte Jomo Danielsen; Christensen, Ole Bøssing; Arnbjerg-Nielsen, Karsten

In recent years, urban flooding has occurred in Denmark due to very local extreme precipitation events with very short lifetime. Several of these floods have been among the most severe ever experienced. The current study demonstrates the applicability of the Spatio-Temporal Neyman-Scott Rectangular...... the observed spatio-temporal differences at very fine scale for all measured parameters. For downscaling, perturbation with a climate change signal, precipitation from four different regional climate model simulations has been analysed. The analysed models are two runs from the ENSEMBLES (RACMO...

Precursor of transition to turbulence: spatiotemporal wave front.

Science.gov (United States)

Bhaumik, S; Sengupta, T K

2014-04-01

To understand transition to turbulence via 3D disturbance growth, we report here results obtained from the solution of Navier-Stokes equation (NSE) to reproduce experimental results obtained by minimizing background disturbances and imposing deterministic excitation inside the shear layer. A similar approach was adopted in Sengupta and Bhaumik [Phys. Rev. Lett. 107, 154501 (2011)], where a route of transition from receptivity to fully developed turbulent stage was explained for 2D flow in terms of the spatio-temporal wave-front (STWF). The STWF was identified as the unit process of 2D turbulence creation for low amplitude wall excitation. Theoretical prediction of STWF for boundary layer was established earlier in Sengupta, Rao, and Venkatasubbaiah [Phys. Rev. Lett. 96, 224504 (2006)] from the Orr-Sommerfeld equation as due to spatiotemporal instability. Here, the same unit process of the STWF during transition is shown to be present for 3D disturbance field from the solution of governing NSE.

Noise tolerant spatiotemporal chaos computing.

Science.gov (United States)

Kia, Behnam; Kia, Sarvenaz; Lindner, John F; Sinha, Sudeshna; Ditto, William L

2014-12-01

We introduce and design a noise tolerant chaos computing system based on a coupled map lattice (CML) and the noise reduction capabilities inherent in coupled dynamical systems. The resulting spatiotemporal chaos computing system is more robust to noise than a single map chaos computing system. In this CML based approach to computing, under the coupled dynamics, the local noise from different nodes of the lattice diffuses across the lattice, and it attenuates each other's effects, resulting in a system with less noise content and a more robust chaos computing architecture.

Spatiotemporal Assessment of PM2.5-Related Economic Losses from Health Impacts during 2014–2016 in China

Directory of Open Access Journals (Sweden)

Yang Yang

2018-06-01

Full Text Available Background: Particulate air pollution, especially PM2.5, is highly correlated with various adverse health impacts and, ultimately, economic losses for society, however, few studies have undertaken a spatiotemporal assessment of PM2.5-related economic losses from health impacts covering all of the main cities in China. Methods: PM2.5 concentration data were retrieved for 190 Chinese cities for the period 2014–2016. We used a log-linear exposure–response model and monetary valuation methods, such as value of a statistical life (VSL, amended human capital (AHC, and cost of illness to evaluate PM2.5-related economic losses from health impacts at the city level. In addition, Monte Carlo simulation was used to analyze uncertainty. Results: The average economic loss was 0.3% (AHC to 1% (VSL of the total gross domestic product (GDP of 190 Chinese cities from 2014 to 2016. Overall, China experienced a downward trend in total economic losses over the three-year period, but the Beijing–Tianjin–Hebei, Shandong Peninsula, Yangtze River Delta, and Chengdu-Chongqing regions experienced greater annual economic losses. Conclusions: Exploration of spatiotemporal variations in PM2.5-related economic losses from long-term health impacts could provide new information for policymakers regarding priority areas for PM2.5 pollution prevention and control in China.

Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

Science.gov (United States)

Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

2014-08-01

As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good

Spatiotemporal variability of urban growth factors: A global and local perspective on the megacity of Mumbai

Science.gov (United States)

Shafizadeh-Moghadam, Hossein; Helbich, Marco

2015-03-01

The rapid growth of megacities requires special attention among urban planners worldwide, and particularly in Mumbai, India, where growth is very pronounced. To cope with the planning challenges this will bring, developing a retrospective understanding of urban land-use dynamics and the underlying driving-forces behind urban growth is a key prerequisite. This research uses regression-based land-use change models - and in particular non-spatial logistic regression models (LR) and auto-logistic regression models (ALR) - for the Mumbai region over the period 1973-2010, in order to determine the drivers behind spatiotemporal urban expansion. Both global models are complemented by a local, spatial model, the so-called geographically weighted logistic regression (GWLR) model, one that explicitly permits variations in driving-forces across space. The study comes to two main conclusions. First, both global models suggest similar driving-forces behind urban growth over time, revealing that LRs and ALRs result in estimated coefficients with comparable magnitudes. Second, all the local coefficients show distinctive temporal and spatial variations. It is therefore concluded that GWLR aids our understanding of urban growth processes, and so can assist context-related planning and policymaking activities when seeking to secure a sustainable urban future.

A multi-scale modeling framework for individualized, spatiotemporal prediction of drug effects and toxicological risk

Directory of Open Access Journals (Sweden)

Juan Guillermo eDiaz Ochoa

2013-01-01

Full Text Available In this study, we focus on a novel multi-scale modeling approach for spatiotemporal prediction of the distribution of substances and resulting hepatotoxicity by combining cellular models, a 2D liver model, and whole-body model. As a case study, we focused on predicting human hepatotoxicity upon treatment with acetaminophen based on in vitro toxicity data and potential inter-individual variability in gene expression and enzyme activities. By aggregating mechanistic, genome-based in silico cells to a novel 2D liver model and eventually to a whole body model, we predicted pharmacokinetic properties, metabolism, and the onset of hepatotoxicity in an in silico patient. Depending on the concentration of acetaminophen in the liver and the accumulation of toxic metabolites, cell integrity in the liver as a function of space and time as well as changes in the elimination rate of substances were estimated. We show that the variations in elimination rates also influence the distribution of acetaminophen and its metabolites in the whole body. Our results are in agreement with experimental results. What is more, the integrated model also predicted variations in drug toxicity depending on alterations of metabolic enzyme activities. Variations in enzyme activity, in turn, reflect genetic characteristics or diseases of individuals. In conclusion, this framework presents an important basis for efficiently integrating inter-individual variability data into models, paving the way for personalized or stratified predictions of drug toxicity and efficacy.

The application of a hierarchical Bayesian spatiotemporal model for ...

Indian Academy of Sciences (India)

Process (GP) model by using the Gibbs sampling method. The result for ... good indicator of the HBST method. The statistical ... summary and discussion of future works are given .... spatiotemporal package in R language (R core team. 2013).

Spatiotemporal Gait Characteristics Associated with Cognitive Impairment: A Multicenter Cross-Sectional Study, the Intercontinental "Gait, cOgnitiOn & Decline" Initiative.

Science.gov (United States)

Beauchet, Olivier; Blumen, Helena M; Callisaya, Michele L; De Cock, Anne-Marie; Kressig, Reto W; Srikanth, Velandai; Steinmetz, Jean-Paul; Verghese, Joe; Allali, Gilles

2018-01-23

The study aims to determine the spatiotemporal gait parameters and/or their combination(s) that best differentiate between cognitively healthy individuals (CHI), patients with mild cognitive impairment (MCI) and those with mild and moderate dementia, regardless of the etiology of cognitive impairment. A total of 2099 participants (1015 CHI, 478 patients with MCI, 331 patients with mild dementia and 275 with moderate dementia) were selected from the intercontinental "Gait, cOgnitiOn & Decline" (GOOD) initiative, which merged different databases from seven cross-sectional studies. Mean values and coefficients of variation (CoV) of spatiotemporal gait parameters were recorded during usual walking with the GAITRite® system. The severity of cognitive impairment was associated with worse performance on all gait parameters. Stride velocity had the strongest association with cognitive impairment, regardless of cognitive status. High mean value and CoV of stride length characterized moderate dementia, whereas increased CoV of stride time was specific to MCI status. The findings support the existence of specific cognitive impairment-related gait disturbances with differences related to stages of cognitive impairment, which may be used to screen individuals with cognitive impairment. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Recent results on the spatiotemporal modelling and comparative analysis of Black Death and bubonic plague epidemics

Science.gov (United States)

Christakos, G.; Olea, R.A.; Yu, H.-L.

2007-01-01

Background: This work demonstrates the importance of spatiotemporal stochastic modelling in constructing maps of major epidemics from fragmentary information, assessing population impacts, searching for possible etiologies, and performing comparative analysis of epidemics. Methods: Based on the theory previously published by the authors and incorporating new knowledge bases, informative maps of the composite space-time distributions were generated for important characteristics of two major epidemics: Black Death (14th century Western Europe) and bubonic plague (19th-20th century Indian subcontinent). Results: The comparative spatiotemporal analysis of the epidemics led to a number of interesting findings: (1) the two epidemics exhibited certain differences in their spatiotemporal characteristics (correlation structures, trends, occurrence patterns and propagation speeds) that need to be explained by means of an interdisciplinary effort; (2) geographical epidemic indicators confirmed in a rigorous quantitative manner the partial findings of isolated reports and time series that Black Death mortality was two orders of magnitude higher than that of bubonic plague; (3) modern bubonic plague is a rural disease hitting harder the small villages in the countryside whereas Black Death was a devastating epidemic that indiscriminately attacked large urban centres and the countryside, and while the epidemic in India lasted uninterruptedly for five decades, in Western Europe it lasted three and a half years; (4) the epidemics had reverse areal extension features in response to annual seasonal variations. Temperature increase at the end of winter led to an expansion of infected geographical area for Black Death and a reduction for bubonic plague, reaching a climax at the end of spring when the infected area in Western Europe was always larger than in India. Conversely, without exception, the infected area during winter was larger for the Indian bubonic plague; (5) during the

Spatiotemporal climatic, hydrological, and environmental variations based on records of annually laminated lake sediments from northern Poland

Science.gov (United States)

Tylmann, W.; Blanke, L.; Kinder, M.; Loewe, T.; Mayr, C.; Ohlendorf, C.; Zolitschka, B.

2009-12-01

In northern Poland there is the unique opportunity to compare varved lake sediment records with distinct climatic trends along a 700 km long W-E transect. Annually laminated Holocene sediment sequences from Lake Lubinskie, Lake Suminko, Lake Lazduny, and Lake Szurpily were cored for high-resolution multiproxy climate and environmental reconstruction in the framework of the Polish-German project “Northern Polish Lake Research” (NORPOLAR). First results from a 139 cm long gravity core of Lake Lazduny (53°51.4’N, 21°57.3’E) document deposition of an organic (mean organic matter: 13.9%; mean biogenic opal: 9.8%) and highly carbonaceous gyttja (mean calcite content: 61.6%). The finely laminated sediment consists of biochemical varves. Pale spring/summer layers composed of autochthonous carbonates alternate with dark fall/winter layers made of organic and minerogenic detritus. The established chronology for the last 1500 calendar-years is based on thin section analysis supported by independent radiometric dating (C-14, Pb-210). Sedimentological, geochemical and stable isotope analyses were carried out with a decadal temporal resolution. Additionally, non-destructive and high-resolution XRF scanning data reveal a rhythmic variation in the Ca content that reflects seasonal calcite deposition. Redox-sensitive elements like Fe, Mn and S are interpreted to be the response to mean winter temperatures: colder winter temperatures → extended lake ice cover → intensification of meromixis → increased Fe/Mn ratio. In turn, these parameters can be linked to NAO (North Atlantic Oscillation) variability, because a negative NAO is related to colder and drier conditions in northeastern Europe. Climate variability is also mirrored by the δ13C record of the endogenic calcite fraction. In mid-latitude lakes calcite precipitation is dominated by productivity-controlled consumption of the dissolved inorganic carbon (DIC) pool. Thus the δ13C record potentially provides a

A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal optimization

International Nuclear Information System (INIS)

Kim, Minsun; Stewart, Robert D.; Phillips, Mark H.

2015-01-01

Purpose: To investigate the impact of using spatiotemporal optimization, i.e., intensity-modulated spatial optimization followed by fractionation schedule optimization, to select the patient-specific fractionation schedule that maximizes the tumor biologically equivalent dose (BED) under dose constraints for multiple organs-at-risk (OARs). Methods: Spatiotemporal optimization was applied to a variety of lung tumors in a phantom geometry using a range of tumor sizes and locations. The optimal fractionation schedule for a patient using the linear-quadratic cell survival model depends on the tumor and OAR sensitivity to fraction size (α/β), the effective tumor doubling time (T d ), and the size and location of tumor target relative to one or more OARs (dose distribution). The authors used a spatiotemporal optimization method to identify the optimal number of fractions N that maximizes the 3D tumor BED distribution for 16 lung phantom cases. The selection of the optimal fractionation schedule used equivalent (30-fraction) OAR constraints for the heart (D mean ≤ 45 Gy), lungs (D mean ≤ 20 Gy), cord (D max ≤ 45 Gy), esophagus (D max ≤ 63 Gy), and unspecified tissues (D 05 ≤ 60 Gy). To assess plan quality, the authors compared the minimum, mean, maximum, and D 95 of tumor BED, as well as the equivalent uniform dose (EUD) for optimized plans to conventional intensity-modulated radiation therapy plans prescribing 60 Gy in 30 fractions. A sensitivity analysis was performed to assess the effects of T d (3–100 days), tumor lag-time (T k = 0–10 days), and the size of tumors on optimal fractionation schedule. Results: Using an α/β ratio of 10 Gy, the average values of tumor max, min, mean BED, and D 95 were up to 19%, 21%, 20%, and 19% larger than those from conventional prescription, depending on T d and T k used. Tumor EUD was up to 17% larger than the conventional prescription. For fast proliferating tumors with T d less than 10 days, there was no

[Epidemiologic and spatio-temporal characteristics of hepatitis E in China, 2004-2014].

Science.gov (United States)

Liu, Z Q; Zuo, J L; Yan, Q; Fang, Q W; Zhang, T J

2017-10-10

Objective: To describe and analyze the epidemiologic and spatio-temporal characteristics of hepatitis E in China from 2004 to 2014. Methods: Data on the incidence of hepatitis E in 31 provinces (municipality and autonomous region) from 2004 to 2014, were collected. Empirical Mode Decomposition (EMD) was applied to decompose the time-series data to accurately describe the trend of hepatitis E incidence. Mathematic model was used to estimate the annual change of incidence in each age group and the whole province. Software ArcGIS 10.1 and SaTScan 9.01 were used to analyze the spatio-temporal clusters. Results: During 2004-2014, a total of 245 414 hepatitis E cases were reported in China. The overall incidence showed a slight increase ( OR =1.05, 95 %CI : 1.03-1.10). Incidence rates on hepatitis E were discovered different across the provinces, with significant increase appearing in the southern, central and northwestern areas. The highest increase was seen in the elderly, especially in the 65-69 and 70-74 year-olds. Results from the Local spatial autocorrelation analysis showed that the "high-high cluster" was moving from the north to the south and the "low-low cluster" disappeared as time went by. Data from Spatio-temporal scanning showed that there were five spatio-temporal clustering areas across the country. Conclusion: The overall incidence of hepatitis E was on the rise from 2004 to 2014, in China, but with differences seen across the areas and age groups.

Improved kinect-based spatiotemporal and kinematic treadmill gait assessment.

Science.gov (United States)

Eltoukhy, Moataz; Oh, Jeonghoon; Kuenze, Christopher; Signorile, Joseph

2017-01-01

A cost-effective, clinician friendly gait assessment tool that can automatically track patients' anatomical landmarks can provide practitioners with important information that is useful in prescribing rehabilitative and preventive therapies. This study investigated the validity and reliability of the Microsoft Kinect v2 as a potential inexpensive gait analysis tool. Ten healthy subjects walked on a treadmill at 1.3 and 1.6m·s -1 , as spatiotemporal parameters and kinematics were extracted concurrently using the Kinect and three-dimensional motion analysis. Spatiotemporal measures included step length and width, step and stride times, vertical and mediolateral pelvis motion, and foot swing velocity. Kinematic outcomes included hip, knee, and ankle joint angles in the sagittal plane. The absolute agreement and relative consistency between the two systems were assessed using interclass correlations coefficients (ICC2,1), while reproducibility between systems was established using Lin's Concordance Correlation Coefficient (rc). Comparison of ensemble curves and associated 90% confidence intervals (CI90) of the hip, knee, and ankle joint angles were performed to investigate if the Kinect sensor could consistently and accurately assess lower extremity joint motion throughout the gait cycle. Results showed that the Kinect v2 sensor has the potential to be an effective clinical assessment tool for sagittal plane knee and hip joint kinematics, as well as some spatiotemporal temporal variables including pelvis displacement and step characteristics during the gait cycle. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatiotemporal distribution and national measurement of the global carbonate carbon sink.

Science.gov (United States)

Li, Huiwen; Wang, Shijie; Bai, Xiaoyong; Luo, Weijun; Tang, Hong; Cao, Yue; Wu, Luhua; Chen, Fei; Li, Qin; Zeng, Cheng; Wang, Mingming

2018-06-21

The magnitudes, spatial distributions and contributions to global carbon budget of the global carbonate carbon sink (CCS) still remain uncertain, allowing the problem of national measurement of CCS remain unresolved which will directly influence the fairness of global carbon markets and emission trading. Here, based on high spatiotemporal resolution ecological, meteorological raster data and chemical field monitoring data, combining highly reliable machine learning algorithm with the thermodynamic dissolution equilibrium model, we estimated the new CCS of 0.89 ± 0.23 petagrams of carbon per year (Pg C yr -1 ), amounting to 74.50% of global net forest sink and accounting for 28.75% of terrestrial sinks or 46.81% of the missing sink. Our measurement for 142 nations of CCS showed that Russia, Canada, China and the USA contribute over half of the global CCS. We also presented the first global fluxes maps of the CCS with spatial resolution of 0.05°, exhibiting two peaks in equatorial regions (10°S to 10°N) and low latitudes (10°N to 35°N) in Northern Hemisphere. By contrast, there are no peaks in Southern Hemisphere. The greatest average carbon sink flux (CCSF), i.e., 2.12 tC ha -1  yr -1 , for 2000 to 2014 was contributed by tropical rainforest climate near the equator, and the smallest average CCSF was presented in tropical arid zones, showing a magnitude of 0.26 tC ha -1  yr -1 . This research estimated the magnitudes, spatial distributions, variations and contributions to the global carbon budget of the CCS in a higher spatiotemporal representativeness and expandability way, which, via multiple mechanisms, introduced an important sink in the terrestrial carbon sink system and the global missing sink and that can help us further reveal and support our understanding of global rock weathering carbon sequestration, terrestrial carbon sink system and global carbon cycle dynamics which make our understanding of global change more comprehensive

Mangrove forests submitted to depositional processes and salinity variation investigated using satellite images and vegetation structure surveys

OpenAIRE

Cunha-Lignon, M.; Kampel, M.; Menghini, R.P.; Schaeffer-Novelli, Y.; Cintrón, G.; Dahdouh-Guebas, F.

2011-01-01

The current paper examines the growth and spatio-temporal variation of mangrove forests in response to depositional processes and different salinity conditions. Data from mangrove vegetation structure collected at permanent plots and satellite images were used. In the northern sector important environmental changes occurred due to an artificial channel producing modifications in salinity. The southern sector is considered the best conserved mangrove area along the coast of São Paulo State, Br...

Enhancement of peak intensity in a filament core with spatiotemporally focused femtosecond laser pulses

Energy Technology Data Exchange (ETDEWEB)

Zeng Bin; Chu Wei; Li Guihua; Zhang Haisu; Ni Jielei [State Key Laboratory of High Field Laser Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800 (China); Graduate School of Chinese Academy of Sciences, Beijing 100080 (China); Gao Hui; Liu Weiwei [Institute of Modern Optics, Nankai University, Tianjin, 300071 (China); Yao Jinping; Cheng Ya; Xu Zhizhan [State Key Laboratory of High Field Laser Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800 (China); Chin, See Leang [Center for Optics, Photonics and Laser (COPL) and Department of Physics, Engineering Physics and Optics, Universite Laval, Quebec City, QC, G1V 0A6 (Canada)

2011-12-15

We demonstrate that the peak intensity in the filament core, which is inherently limited by the intensity clamping effect during femtosecond laser filamentation, can be significantly enhanced using spatiotemporally focused femtosecond laser pulses. In addition, the filament length obtained by spatiotemporally focused femtosecond laser pulses is {approx}25 times shorter than that obtained by a conventional focusing scheme, resulting in improved high spatial resolution.

Spatiotemporal Dynamics of Scrub Typhus Transmission in Mainland China, 2006-2014.

Science.gov (United States)

Wu, Yi-Cheng; Qian, Quan; Soares Magalhaes, Ricardo J; Han, Zhi-Hai; Hu, Wen-Biao; Haque, Ubydul; Weppelmann, Thomas A; Wang, Yong; Liu, Yun-Xi; Li, Xin-Lou; Sun, Hai-Long; Sun, Yan-Song; Clements, Archie C A; Li, Shen-Long; Zhang, Wen-Yi

2016-08-01

Scrub typhus is endemic in the Asia-Pacific region including China, and the number of reported cases has increased dramatically in the past decade. However, the spatial-temporal dynamics and the potential risk factors in transmission of scrub typhus in mainland China have yet to be characterized. This study aims to explore the spatiotemporal dynamics of reported scrub typhus cases in mainland China between January 2006 and December 2014, to detect the location of high risk spatiotemporal clusters of scrub typhus cases, and identify the potential risk factors affecting the re-emergence of the disease. Monthly cases of scrub typhus reported at the county level between 2006 and 2014 were obtained from the Chinese Center for Diseases Control and Prevention. Time-series analyses, spatiotemporal cluster analyses, and spatial scan statistics were used to explore the characteristics of the scrub typhus incidence. To explore the association between scrub typhus incidence and environmental variables panel Poisson regression analysis was conducted. During the time period between 2006 and 2014 a total of 54,558 scrub typhus cases were reported in mainland China, which grew exponentially. The majority of cases were reported each year between July and November, with peak incidence during October every year. The spatiotemporal dynamics of scrub typhus varied over the study period with high-risk clusters identified in southwest, southern, and middle-eastern part of China. Scrub typhus incidence was positively correlated with the percentage of shrub and meteorological variables including temperature and precipitation. The results of this study demonstrate areas in China that could be targeted with public health interventions to mitigate the growing threat of scrub typhus in the country.

Cellular dynamical mechanisms for encoding the time and place of events along spatiotemporal trajectories in episodic memory.

Science.gov (United States)

Hasselmo, Michael E; Giocomo, Lisa M; Brandon, Mark P; Yoshida, Motoharu

2010-12-31

Understanding the mechanisms of episodic memory requires linking behavioral data and lesion effects to data on the dynamics of cellular membrane potentials and population interactions within brain regions. Linking behavior to specific membrane channels and neurochemicals has implications for therapeutic applications. Lesions of the hippocampus, entorhinal cortex and subcortical nuclei impair episodic memory function in humans and animals, and unit recording data from these regions in behaving animals indicate episodic memory processes. Intracellular recording in these regions demonstrates specific cellular properties including resonance, membrane potential oscillations and bistable persistent spiking that could underlie the encoding and retrieval of episodic trajectories. A model presented here shows how intrinsic dynamical properties of neurons could mediate the encoding of episodic memories as complex spatiotemporal trajectories. The dynamics of neurons allow encoding and retrieval of unique episodic trajectories in multiple continuous dimensions including temporal intervals, personal location, the spatial coordinates and sensory features of perceived objects and generated actions, and associations between these elements. The model also addresses how cellular dynamics could underlie unit firing data suggesting mechanisms for coding continuous dimensions of space, time, sensation and action. Copyright © 2010 Elsevier B.V. All rights reserved.

Nonparametric evaluation of dynamic disease risk: a spatio-temporal kernel approach.

Directory of Open Access Journals (Sweden)

Zhijie Zhang

Full Text Available Quantifying the distributions of disease risk in space and time jointly is a key element for understanding spatio-temporal phenomena while also having the potential to enhance our understanding of epidemiologic trajectories. However, most studies to date have neglected time dimension and focus instead on the "average" spatial pattern of disease risk, thereby masking time trajectories of disease risk. In this study we propose a new idea titled "spatio-temporal kernel density estimation (stKDE" that employs hybrid kernel (i.e., weight functions to evaluate the spatio-temporal disease risks. This approach not only can make full use of sample data but also "borrows" information in a particular manner from neighboring points both in space and time via appropriate choice of kernel functions. Monte Carlo simulations show that the proposed method performs substantially better than the traditional (i.e., frequency-based kernel density estimation (trKDE which has been used in applied settings while two illustrative examples demonstrate that the proposed approach can yield superior results compared to the popular trKDE approach. In addition, there exist various possibilities for improving and extending this method.

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

Science.gov (United States)

Kuo, K. S.; Rilee, M. L.

2017-12-01

Current data processing practice limits the volume and variety of relevant geoscience data that can practically be applied to important problems. File archives in centralized data centers are the principal means by which Earth Science data are accessed. This approach, however, requires laborious search, retrieval, and eventual customization/adaptation for the data to be used. Such fractionation makes it even more difficult to share outcomes, i.e. research artifacts and data products, hampering reusability and repeatability, since end users generally have their own research agenda and preferences as well as scarce resources. Thus, while finding and downloading data files from central data centers are already costly for end users working in their own field, using data products from other disciplines rapidly becomes prohibitive. This curtails scientific productivity, limits avenues of study, and endangers quality and reproducibility. The Spatio-Temporal Adaptive Resolution Encoding ( STARE ) is a unifying scheme that facilitates the indexing, access, and fusion of diverse Earth Science data. STARE implements an innovative encoding of geo-spatiotemporal information, originally developed for aligning datasets with diverse spatiotemporal characteristics in an array database. The spatial component of STARE recursively quadfurcates a root polyhedron, producing a hierarchical scheme for addressing geographic locations and regions. The temporal component of STARE uses conventional date-time units as an indexing hierarchy. The additional encoding of spatial and temporal resolution information in STARE enables comparisons and conditional selections across diverse datasets. Moreover, spatiotemporal set-operations, e.g. union and intersection, are mapped to efficient integer operations with STARE. Applied to existing data models (point, grid, spacecraft swath) and corresponding granules, STARE indexes provide a streamlined description usable as geo-spatiotemporal metadata. When

Preschoolers' use of spatiotemporal history, appearance, and proper name in determining individual identity.

Science.gov (United States)

Gutheil, Grant; Gelman, Susan A; Klein, Eileen; Michos, Katherine; Kelaita, Kara

2008-04-01

Humans construe their environment as composed largely of discrete individuals, which are also members of kinds (e.g., trees, cars, and people). On what basis do young children determine individual identity? How important are featural properties (e.g., physical appearance, name) relative to spatiotemporal history? Two studies examined the relative importance of these factors in preschoolers' and adults' identity judgments. Participants were shown pairs of individuals who looked identical but differed in their spatiotemporal history (e.g., two physically distinct but identical Winnie-the-Pooh dolls), and were asked whether both members in the pair would have access to knowledge that had been supplied to only one of the pairs. The results provide clear support for spatiotemporal history as the primary basis of identity judgments in both preschoolers and adults, and further place issues of identity within the broader cognitive framework of psychological essentialism.

Optimization of spatiotemporally fractionated radiotherapy treatments with bounds on the achievable benefit

Science.gov (United States)

Gaddy, Melissa R.; Yıldız, Sercan; Unkelbach, Jan; Papp, Dávid

2018-01-01

Spatiotemporal fractionation schemes, that is, treatments delivering different dose distributions in different fractions, can potentially lower treatment side effects without compromising tumor control. This can be achieved by hypofractionating parts of the tumor while delivering approximately uniformly fractionated doses to the surrounding tissue. Plan optimization for such treatments is based on biologically effective dose (BED); however, this leads to computationally challenging nonconvex optimization problems. Optimization methods that are in current use yield only locally optimal solutions, and it has hitherto been unclear whether these plans are close to the global optimum. We present an optimization framework to compute rigorous bounds on the maximum achievable normal tissue BED reduction for spatiotemporal plans. The approach is demonstrated on liver tumors, where the primary goal is to reduce mean liver BED without compromising any other treatment objective. The BED-based treatment plan optimization problems are formulated as quadratically constrained quadratic programming (QCQP) problems. First, a conventional, uniformly fractionated reference plan is computed using convex optimization. Then, a second, nonconvex, QCQP model is solved to local optimality to compute a spatiotemporally fractionated plan that minimizes mean liver BED, subject to the constraints that the plan is no worse than the reference plan with respect to all other planning goals. Finally, we derive a convex relaxation of the second model in the form of a semidefinite programming problem, which provides a rigorous lower bound on the lowest achievable mean liver BED. The method is presented on five cases with distinct geometries. The computed spatiotemporal plans achieve 12-35% mean liver BED reduction over the optimal uniformly fractionated plans. This reduction corresponds to 79-97% of the gap between the mean liver BED of the uniform reference plans and our lower bounds on the lowest

Spatio-Temporal Process Simulation of Dam-Break Flood Based on SPH

Science.gov (United States)

Wang, H.; Ye, F.; Ouyang, S.; Li, Z.

2018-04-01

On the basis of introducing the SPH (Smooth Particle Hydrodynamics) simulation method, the key research problems were given solutions in this paper, which ere the spatial scale and temporal scale adapting to the GIS(Geographical Information System) application, the boundary condition equations combined with the underlying surface, and the kernel function and parameters applicable to dam-break flood simulation. In this regards, a calculation method of spatio-temporal process emulation with elaborate particles for dam-break flood was proposed. Moreover the spatio-temporal process was dynamic simulated by using GIS modelling and visualization. The results show that the method gets more information, objectiveness and real situations.

Spatio-temporal joins on symbolic indoor tracking data

DEFF Research Database (Denmark)

Lu, Hua; Yang, Bin; Jensen, Christian S.

2011-01-01

and studies probabilistic, spatio-temporal joins on historical indoor tracking data. Two meaningful types of join are defined. They return object pairs that satisfy spatial join predicates either at a time point or during a time interval. The predicates considered include “same X,” where X is a semantic...

Theoretical analysis of the spatio-temporal structure of bone multicellular units

International Nuclear Information System (INIS)

Buenzli, P R; Pivonka, P; Gardiner, B S; Smith, D W; Dunstan, C R; Mundy, G R

2010-01-01

Bone multicellular units (BMUs) maintain the viability of the skeletal tissue by coordinating locally the sequence of bone resorption and bone formation performed by cells of the osteoclastic and osteoblastic lineage. Understanding the emergence and the net bone balance of such structured microsystems out of the complex network of biochemical interactions between bone cells is fundamental for many bone-related diseases and the evaluation of fracture risk. Based on current experimental knowledge, we propose a spatio-temporal continuum model describing the interactions of osteoblastic and osteoclastic cells. We show that this model admits travelling-wave-like solutions with well-confined cell profiles upon specifying external conditions mimicking the environment encountered in cortical bone remodelling. The shapes of the various cell concentration profiles within this travelling structure are intrinsically linked to the parameters of the model such as differentiation, proliferation, and apoptosis rates of bone cells. The internal structure of BMUs is reproduced, allowing for experimental calibration. The spatial distribution of the key regulatory factors can also be exhibited, which in diseased states could give hints as to the biochemical agent most accountable for the disorder.

Spatiotemporal Features for Asynchronous Event-based Data

Directory of Open Access Journals (Sweden)

Xavier eLagorce

2015-02-01

Full Text Available Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the realiable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time.

Spatiotemporal Interpolation Methods for Solar Event Trajectories

Science.gov (United States)

Filali Boubrahimi, Soukaina; Aydin, Berkay; Schuh, Michael A.; Kempton, Dustin; Angryk, Rafal A.; Ma, Ruizhe

2018-05-01

This paper introduces four spatiotemporal interpolation methods that enrich complex, evolving region trajectories that are reported from a variety of ground-based and space-based solar observatories every day. Our interpolation module takes an existing solar event trajectory as its input and generates an enriched trajectory with any number of additional time–geometry pairs created by the most appropriate method. To this end, we designed four different interpolation techniques: MBR-Interpolation (Minimum Bounding Rectangle Interpolation), CP-Interpolation (Complex Polygon Interpolation), FI-Interpolation (Filament Polygon Interpolation), and Areal-Interpolation, which are presented here in detail. These techniques leverage k-means clustering, centroid shape signature representation, dynamic time warping, linear interpolation, and shape buffering to generate the additional polygons of an enriched trajectory. Using ground-truth objects, interpolation effectiveness is evaluated through a variety of measures based on several important characteristics that include spatial distance, area overlap, and shape (boundary) similarity. To our knowledge, this is the first research effort of this kind that attempts to address the broad problem of spatiotemporal interpolation of solar event trajectories. We conclude with a brief outline of future research directions and opportunities for related work in this area.

Spatio-temporal patterns and source apportionment of pollution in Qiantang River (China) using neural-based modeling and multivariate statistical techniques

Science.gov (United States)

Su, Shiliang; Zhi, Junjun; Lou, Liping; Huang, Fang; Chen, Xia; Wu, Jiaping

Characterizing the spatio-temporal patterns and apportioning the pollution sources of water bodies are important for the management and protection of water resources. The main objective of this study is to describe the dynamics of water quality and provide references for improving river pollution control practices. Comprehensive application of neural-based modeling and different multivariate methods was used to evaluate the spatio-temporal patterns and source apportionment of pollution in Qiantang River, China. Measurement data were obtained and pretreated for 13 variables from 41 monitoring sites for the period of 2001-2004. A self-organizing map classified the 41 monitoring sites into three groups (Group A, B and C), representing different pollution characteristics. Four significant parameters (dissolved oxygen, biochemical oxygen demand, total phosphorus and total lead) were identified by discriminant analysis for distinguishing variations of different years, with about 80% correct assignment for temporal variation. Rotated principal component analysis (PCA) identified four potential pollution sources for Group A (domestic sewage and agricultural pollution, industrial wastewater pollution, mineral weathering, vehicle exhaust and sand mining), five for Group B (heavy metal pollution, agricultural runoff, vehicle exhaust and sand mining, mineral weathering, chemical plants discharge) and another five for Group C (vehicle exhaust and sand mining, chemical plants discharge, soil weathering, biochemical pollution, mineral weathering). The identified potential pollution sources explained 75.6% of the total variances for Group A, 75.0% for Group B and 80.0% for Group C, respectively. Receptor-based source apportionment was applied to further estimate source contributions for each pollution variable in the three groups, which facilitated and supported the PCA results. These results could assist managers to develop optimal strategies and determine priorities for river

Spatio-temporal analysis of Salmonella surveillance data in Thailand

DEFF Research Database (Denmark)

Coutinho Calado Domingues, Ana Rita; Vieira, Antonio; Hendriksen, Rene S.

2014-01-01

This study evaluates the usefulness of spatio-temporal statistical tools to detect outbreaks using routine surveillance data where limited epidemiological information is available. A dataset from 2002 to 2007 containing information regarding date, origin, source and serotype of 29 586 Salmonella ...

Annual spatiotemporal migration schedules in three larger insectivorous birds

DEFF Research Database (Denmark)

Jacobsen, Lars Bo; Jensen, Niels Odder; Willemoes, Mikkel

2017-01-01

Background: Knowledge of spatiotemporal migration patterns is important for our understanding of migration ecology and ultimately conservation of migratory species. We studied the annual migration schedules of European nightjar, a large nocturnal insectivore and compared it with two other larger ...

Climate-driven mathematical models to understand the spatio-temporal heterogeneity of a chikungunya outbreak in the presence of widespread asymptomatic infection

Science.gov (United States)

Dommar, Carlos J.; Robinson, Marguerite; Lowe, Rachel; Conan, Anne; Buchy, Philippe; Tarantola, Arnaud; Rodó, Xavier

2014-05-01

The emergence and persistence of human pathogens in the environment represents a constant threat to society, with global implications for human health, economies and ecosystems. Of particular concern are vector-borne diseases, such as dengue, malaria and chikungunya, which are increasing across their traditional ranges and continuing to infiltrate new regions. This unprecedented situation has been partly attributed to the increase in global temperatures in recent decades which has allowed non-native mosquito species to invade and successfully colonise previously inhospitable environments. The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. In turn, vector populations are thought to be driven by external environmental variables, such as precipitation and temperature. Furthermore, the ability of asymptomatic individuals to successfully transmit the infection and evade control measures can undermine public health interventions. We employed a stochastic model, which explicitly included asymptomatic and undocumented laboratory confirmed cases, and applied it to a documented outbreak in Cambodia in 2012 (Trapeang Roka village, Kampong Speu Province). The resulting estimate of the reproduction number was considerably higher than values obtained for previous outbreaks and highlights the importance of asymptomatic transmission. Subsequently, we develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals alone is

Spatio-temporal analyses of impacts of multiple climatic hazards in a savannah ecosystem of Ghana

Directory of Open Access Journals (Sweden)

Gerald A.B. Yiran, PhD

2016-01-01

Full Text Available Ghana’s savannah ecosystem has been subjected to a number of climatic hazards of varying severity. This paper presents a spatial, time-series analysis of the impacts of multiple hazards on the ecosystem and human livelihoods over the period 1983–2012, using the Upper East Region of Ghana as a case study. Our aim is to understand the nature of hazards (their frequency, magnitude and duration and how they cumulatively affect humans. Primary data were collected using questionnaires, focus group discussions, in-depth interviews and personal observations. Secondary data were collected from documents and reports. Calculations of the standard precipitation index (SPI and crop failure index used rainfall data from 4 weather stations (Manga, Binduri, Vea and Navrongo and crop yield data of 5 major crops (maize, sorghum, millet, rice and groundnuts respectively. Temperature and windstorms were analysed from the observed weather data. We found that temperatures were consistently high and increasing. From the SPI, drought frequency varied spatially from 9 at Binduri to 13 occurrences at Vea; dry spells occurred at least twice every year and floods occurred about 6 times on average, with slight spatial variations, during 1988–2012, a period with consistent data from all stations. Impacts from each hazard varied spatio-temporally. Within the study period, more 70% of years recorded severe crop losses with greater impacts when droughts and floods occur in the same year, especially in low lying areas. The effects of crop losses were higher in districts with no/little irrigation (Talensi, Nabdam, Garu-Tempane, Kassena-Nankana East. Frequency and severity of diseases and sicknesses such as cerebrospinal meningitis, heat rashes, headaches and malaria related to both dry and wet conditions have increased steadily over time. Other impacts recorded with spatio-temporal variations included destruction to housing, displacement, injury and death of people. These

Spatiotemporal Thinking in the Geosciences

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Shipley, T. F.; Manduca, C. A.; Ormand, C. J.; Tikoff, B.

2011-12-01

Reasoning about spatial relations is a critical skill for geoscientists. Within the geosciences different disciplines may reason about different sorts of relationships. These relationships may span vastly different spatial and temporal scales (from the spatial alignment in atoms in crystals to the changes in the shape of plates). As part of work in a research center on spatial thinking in STEM education, we have been working to classify the spatial skills required in geology, develop tests for each spatial skill, and develop the cognitive science tools to promote the critical spatial reasoning skills. Research in psychology, neurology and linguistics supports a broad classification of spatial skills along two dimensions: one versus many objects (which roughly translates to object- focused and navigation focused skills) and static versus dynamic spatial relations. The talk will focus on the interaction of space and time in spatial cognition in the geosciences. We are working to develop measures of skill in visualizing spatiotemporal changes. A new test developed to measure visualization of brittle deformations will be presented. This is a skill that has not been clearly recognized in the cognitive science research domain and thus illustrates the value of interdisciplinary work that combines geosciences with cognitive sciences. Teaching spatiotemporal concepts can be challenging. Recent theoretical work suggests analogical reasoning can be a powerful tool to aid student learning to reason about temporal relations using spatial skills. Recent work in our lab has found that progressive alignment of spatial and temporal scales promotes accurate reasoning about temporal relations at geological time scales.

Variation in readmission and mortality following hospitalisation with a diagnosis of heart failure: prospective cohort study using linked data.

Science.gov (United States)

Korda, Rosemary J; Du, Wei; Day, Cathy; Page, Karen; Macdonald, Peter S; Banks, Emily

2017-03-21

Hospitalisation for heart failure is common and post-discharge outcomes, including readmission and mortality, are often poor and are poorly understood. The purpose of this study was to examine patient- and hospital-level variation in the risk of 30-day unplanned readmission and mortality following discharge from hospital with a diagnosis of heart failure. Prospective cohort study using data from the Sax Institute's 45 and Up Study, linking baseline survey (Jan 2006-April 2009) to hospital and mortality data (to Dec 2011). Primary outcomes in those admitted to hospital with heart failure included unplanned readmission, mortality and combined unplanned readmission/mortality, within 30 days of discharge. Multilevel models quantified the variation in outcomes between hospitals and examined associations with patient- and hospital-level characteristics. There were 5074 participants with a heart failure admission discharged from 251 hospitals; 1052 (21%) had unplanned readmissions, 186 (3.7%) died, and 1146 (23%) had either/both outcomes within 30 days of discharge. Crude outcomes varied across hospitals, but between-hospital variation explained little of the total variation in outcomes (intraclass correlation coefficients (ICC) after inclusion of patient factors: 30-day unplanned readmission ICC = 0.0125 (p = 0.24); death ICC = 0.0000 (p > 0.99); unplanned readmission/death ICC = 0.0266 (p = 0.07)). Patient characteristics associated with a higher risk of unplanned readmission included: being male (male vs female, adjusted odds ratio (aOR) = 1.18, 95% CI: 1.00-1.37); prior hospitalisation for cardiovascular disease (aOR = 1.44, 1.08-1.91) and for anemia (aOR = 1.36, 1.14-1.63); comorbidities at admission (severe vs none: aOR = 1.26, 1.03-1.54); lower body-mass-index (obese vs normal weight: aOR = 0.77, 0.63-0.94); and lower social interaction scores. Similarly, risk of 30-day mortality was associated with patient- rather than

Spatiotemporally resolved characteristics of a gliding arc discharge in a turbulent air flow at atmospheric pressure

DEFF Research Database (Denmark)

Zhu, Jiajian; Gao, Jinlong; Ehn, Andreas

2017-01-01

A gliding arc discharge was generated in a turbulent air flow at atmospheric pressure driven by a 35 kHz alternating current (AC) electric power. The spatiotemporally resolved characteristics of the gliding arc discharge, including glow-type discharges, spark-type discharges, short-cutting events...... and transitions among the different types of discharges, were investigated using simultaneously optical and electrical diagnostics. The glow-type discharge shows sinusoidal-like voltage and current waveforms with a peak current of hundreds of milliamperes. The frequency of the emission intensity variation...... of the glow-type discharge is the same as that of the electronic power dissipated in the plasma column. The glow-type discharge can transfer into a spark discharge characterized by a sharp peak current of several amperes and a sudden increase of the brightness in the plasma column. Transitions can also...

On spatio-temporal Lévy based Cox processes

DEFF Research Database (Denmark)

Prokesova, Michaela; Hellmund, Gunnar; Jensen, Eva Bjørn Vedel

2006-01-01

The paper discusses a new class of models for spatio-temporal Cox point processes. In these models, the driving field is defined by means of an integral of a weight function with respect to a Lévy basis. The relations to other Cox process models studied previously are discussed and formulas for t...

Nonlinear system identification NARMAX methods in the time, frequency, and spatio-temporal domains

CERN Document Server

Billings, Stephen A

2013-01-01

Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) modelThe orthogonal least squares algorithm that allows models to be built term by

Assessing global vegetation activity using spatio-temporal Bayesian modelling

Science.gov (United States)

Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

2016-04-01

This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support

Spatio-temporal variation analysis of hydrochemical characteristics in the Luanhe River Basin, China.

Science.gov (United States)

Xie, Ying; Li, Xuyong; Wang, Huiliang; Li, Wenzan

2013-01-01

The analysis of river pollution and assessment of spatial and temporal variation in hydrochemistry are essential to river water pollution control in the context of rapid economic growth and growing pollution threats in China. In this study, we focused on hydrochemical characteristics of the Luanhe River Basin (China) and evaluation of 12 hydrochemical variables obtained from 32 monitoring stations during 2001-2010. In each study year, the streams were monitored in the three hydrological periods (April, August, and October) to observe differences in the impacts of agricultural activity and rainfall pattern. Multivariate statistical methods were applied to the data set, and the river water hydrochemical characteristics were assessed using the water quality identification index (WQIIM). The results showed that parameters had variable contribution to water quality status in different months except for ammonia nitrogen (NH4-N) and total nitrogen (TN), which were the most important parameters in contributing to water quality variations for all three periods. Results of WQIIM revealed that 18 sites were classified as 'meeting standard' while the other 14 sites were classified as 'not meeting standard', with most of the seriously polluted sites located in urban area, mainly due to discharge of wastewater from domestic and industrial sources. Sites with low pollution level were located primarily in smaller tributaries, whereas sites of medium and high pollution levels were in the main river channel and the larger tributaries. Our findings provide valuable information and guidance for water pollution control and water resource management in the Luanhe River Basin.

Do spatiotemporal parameters and gait variability differ across the lifespan of healthy adults? A systematic review.

Science.gov (United States)

Herssens, Nolan; Verbecque, Evi; Hallemans, Ann; Vereeck, Luc; Van Rompaey, Vincent; Saeys, Wim

2018-06-12

Aging is often associated with changes in the musculoskeletal system, peripheral and central nervous system. These age-related changes often result in mobility problems influencing gait performance. Compensatory strategies are used as a way to adapt to these physiological changes. The aim of this review is to investigate the differences in spatiotemporal and gait variability measures throughout the healthy adult life. This systematic review was conducted according to the PRISMA guidelines and registered in the PROSPERO database (no. CRD42017057720). Databases MEDLINE (Pubmed), Web of Science (Web of Knowledge), Cochrane Library and ScienceDirect were systematically searched until March 2018. Eighteen of the 3195 original studies met the eligibility criteria and were included in this review. The majority of studies reported spatiotemporal and gait variability measures in adults above the age of 65, followed by the young adult population, information of middle-aged adults is lacking. Spatiotemporal parameters and gait variability measures were extracted from 2112 healthy adults between 18 and 98 years old and, in general, tend to deteriorate with increasing age. Variability measures were only reported in an elderly population and show great variety between studies. The findings of this review suggest that most spatiotemporal parameters significantly differ across different age groups. Elderly populations show a reduction of preferred walking speed, cadence, step and stride length, all related to a more cautious gait, while gait variability measures remain stable over time. A preliminary framework of normative reference data is provided, enabling insights into the influence of aging on spatiotemporal parameters, however spatiotemporal parameters of middle-aged adults should be investigated more thoroughly. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatio-temporal Variations of Nitrogen Dioxide over Western China from Satellite Observations during 2005-2013

Science.gov (United States)

Cui, Y.; Lin, J.; Huang, B.; Song, C.

2015-12-01

Western China has experienced rapid urbanization and industrialization since the implementation of National Western Development Strategy by Chinese Government. Most resource-intensive industries and high-pollution factories had been moved from the east coast to Western China after 2000. In this research, the spatial and temporal variations of tropospheric NO2 concentration in 2005 - 2013 is analyzed based on the satellite observations by Ozone Measurement Instrument (OMI). The annual trends and seasonality of tropospheric NO2 over Western China are calculated. The results show that large increases are observed in urban areas and the polluted regions are expanding. Additionally, the seasonal patterns of some regions over Western China are changing significantly and more clean areas tend to changing from the characteristics of natural emissions to those of anthropogenic emissions. The spatial and temporal variations of NO2 concentrations are well responded to the rapid urbanization and industrialization over Western China.

Spatiotemporal variability of marine renewable energy resources in Norway

NARCIS (Netherlands)

Varlas, George; Christakos, Konstantinos; Cheliotis, Ioannis; Papadopoulos, A.; Steeneveld, G.J.

2017-01-01

Marine Renewable Energy (MRE) resources such as wind and wave energy depend on the complex behaviour of weather and climatic conditions which determine the development of MRE technologies, energy grid, supply and prices. This study investigates the spatiotemporal variability of MRE resources along

The Review of Visual Analysis Methods of Multi-modal Spatio-temporal Big Data

Directory of Open Access Journals (Sweden)

ZHU Qing

2017-10-01

Full Text Available The visual analysis of spatio-temporal big data is not only the state-of-art research direction of both big data analysis and data visualization, but also the core module of pan-spatial information system. This paper reviews existing visual analysis methods at three levels:descriptive visual analysis, explanatory visual analysis and exploratory visual analysis, focusing on spatio-temporal big data's characteristics of multi-source, multi-granularity, multi-modal and complex association.The technical difficulties and development tendencies of multi-modal feature selection, innovative human-computer interaction analysis and exploratory visual reasoning in the visual analysis of spatio-temporal big data were discussed. Research shows that the study of descriptive visual analysis for data visualizationis is relatively mature.The explanatory visual analysis has become the focus of the big data analysis, which is mainly based on interactive data mining in a visual environment to diagnose implicit reason of problem. And the exploratory visual analysis method needs a major break-through.

A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal optimization

Energy Technology Data Exchange (ETDEWEB)

Kim, Minsun, E-mail: mk688@uw.edu; Stewart, Robert D. [Department of Radiation Oncology, University of Washington, Seattle, Washington 98195-6043 (United States); Phillips, Mark H. [Departments of Radiation Oncology and Neurological Surgery, University of Washington, Seattle, Washington 98195-6043 (United States)

2015-11-15

Purpose: To investigate the impact of using spatiotemporal optimization, i.e., intensity-modulated spatial optimization followed by fractionation schedule optimization, to select the patient-specific fractionation schedule that maximizes the tumor biologically equivalent dose (BED) under dose constraints for multiple organs-at-risk (OARs). Methods: Spatiotemporal optimization was applied to a variety of lung tumors in a phantom geometry using a range of tumor sizes and locations. The optimal fractionation schedule for a patient using the linear-quadratic cell survival model depends on the tumor and OAR sensitivity to fraction size (α/β), the effective tumor doubling time (T{sub d}), and the size and location of tumor target relative to one or more OARs (dose distribution). The authors used a spatiotemporal optimization method to identify the optimal number of fractions N that maximizes the 3D tumor BED distribution for 16 lung phantom cases. The selection of the optimal fractionation schedule used equivalent (30-fraction) OAR constraints for the heart (D{sub mean} ≤ 45 Gy), lungs (D{sub mean} ≤ 20 Gy), cord (D{sub max} ≤ 45 Gy), esophagus (D{sub max} ≤ 63 Gy), and unspecified tissues (D{sub 05} ≤ 60 Gy). To assess plan quality, the authors compared the minimum, mean, maximum, and D{sub 95} of tumor BED, as well as the equivalent uniform dose (EUD) for optimized plans to conventional intensity-modulated radiation therapy plans prescribing 60 Gy in 30 fractions. A sensitivity analysis was performed to assess the effects of T{sub d} (3–100 days), tumor lag-time (T{sub k} = 0–10 days), and the size of tumors on optimal fractionation schedule. Results: Using an α/β ratio of 10 Gy, the average values of tumor max, min, mean BED, and D{sub 95} were up to 19%, 21%, 20%, and 19% larger than those from conventional prescription, depending on T{sub d} and T{sub k} used. Tumor EUD was up to 17% larger than the conventional prescription. For fast proliferating

Spatio-temporal variability of the North Sea cod recruitment in relation to temperature and zooplankton.

Directory of Open Access Journals (Sweden)

Delphine Nicolas

Full Text Available The North Sea cod (Gadus morhua, L. stock has continuously declined over the past four decades linked with overfishing and climate change. Changes in stock structure due to overfishing have made the stock largely dependent on its recruitment success, which greatly relies on environmental conditions. Here we focus on the spatio-temporal variability of cod recruitment in an effort to detect changes during the critical early life stages. Using International Bottom Trawl Survey (IBTS data from 1974 to 2011, a major spatio-temporal change in the distribution of cod recruits was identified in the late 1990s, characterized by a pronounced decrease in the central and southeastern North Sea stock. Other minor spatial changes were also recorded in the mid-1980s and early 1990s. We tested whether the observed changes in recruits distribution could be related with direct (i.e. temperature and/or indirect (i.e. changes in the quantity and quality of zooplankton prey effects of climate variability. The analyses were based on spatially-resolved time series, i.e. sea surface temperature (SST from the Hadley Center and zooplankton records from the Continuous Plankton Recorder Survey. We showed that spring SST increase was the main driver for the most recent decrease in cod recruitment. The late 1990s were also characterized by relatively low total zooplankton biomass, particularly of energy-rich zooplankton such as the copepod Calanus finmarchicus, which have further contributed to the decline of North Sea cod recruitment. Long-term spatially-resolved observations were used to produce regional distribution models that could further be used to predict the abundance of North Sea cod recruits based on temperature and zooplankton food availability.

Sources and transport of contaminants of emerging concern: A two-year study of occurrence and spatiotemporal variation in a mixed land use watershed.

Science.gov (United States)

Fairbairn, David J; Karpuzcu, M Ekrem; Arnold, William A; Barber, Brian L; Kaufenberg, Elizabeth F; Koskinen, William C; Novak, Paige J; Rice, Pamela J; Swackhamer, Deborah L

2016-05-01

The occurrence and spatiotemporal variation of 26 contaminants of emerging concern (CECs) were evaluated in 68 water samples in 2011-2012 in the Zumbro River watershed, Minnesota, U.S.A. Samples were collected across a range of seasonal/hydrological conditions from four stream sites that varied in associated land use and presence of an upstream wastewater treatment plant (WWTP). Selected CECs included human/veterinary pharmaceuticals, personal care products, pesticides, phytoestrogens, and commercial/industrial compounds. Detection frequencies and concentrations varied, with atrazine, metolachlor, acetaminophen, caffeine, DEET, and trimethoprim detected in more than 70% of samples, acetochlor, mecoprop, carbamazepine, and daidzein detected in 30%-50% of samples, and 4-nonylphenol, cotinine, sulfamethoxazole, erythromycin, tylosin, and carbaryl detected in 10%-30% of samples. The remaining target CECs were not detected in water samples. Three land use-associated trends were observed for the detected CECs. Carbamazepine, 4-nonylphenol, erythromycin, sulfamethoxazole, tylosin, and carbaryl profiles were WWTP-dominated, as demonstrated by more consistent loading and significantly greater concentrations downstream of the WWTP and during low-flow seasons. In contrast, acetaminophen, trimethoprim, DEET, caffeine, cotinine, and mecoprop patterns demonstrated both seasonally-variable non-WWTP-associated and continual WWTP-associated influences. Surface water studies of CECs often target areas near WWTPs. This study suggests that several CECs often characterized as effluent-associated have additional important sources such as septic systems or land-applied biosolids. Finally, agricultural herbicide (atrazine, acetochlor, and metolachlor) profiles were strongly influenced by agricultural land use and seasonal application-runoff, evident by significantly greater concentrations and loadings at upstream sites and in early summer when application and precipitation rates are

EXTRACTING SPATIOTEMPORAL OBJECTS FROM RASTER DATA TO REPRESENT PHYSICAL FEATURES AND ANALYZE RELATED PROCESSES

Directory of Open Access Journals (Sweden)

J. A. Zollweg

2017-10-01

Full Text Available Numerous ground-based, airborne, and orbiting platforms provide remotely-sensed data of remarkable spatial resolution at short time intervals. However, this spatiotemporal data is most valuable if it can be processed into information, thereby creating meaning. We live in a world of objects: cars, buildings, farms, etc. On a stormy day, we don’t see millions of cubes of atmosphere; we see a thunderstorm ‘object’. Temporally, we don’t see the properties of those individual cubes changing, we see the thunderstorm as a whole evolving and moving. There is a need to represent the bulky, raw spatiotemporal data from remote sensors as a small number of relevant spatiotemporal objects, thereby matching the human brain’s perception of the world. This presentation reveals an efficient algorithm and system to extract the objects/features from raster-formatted remotely-sensed data. The system makes use of the Python object-oriented programming language, SciPy/NumPy for matrix manipulation and scientific computation, and export/import to the GeoJSON standard geographic object data format. The example presented will show how thunderstorms can be identified and characterized in a spatiotemporal continuum using a Python program to process raster data from NOAA’s High-Resolution Rapid Refresh v2 (HRRRv2 data stream.

Extracting Spatiotemporal Objects from Raster Data to Represent Physical Features and Analyze Related Processes

Science.gov (United States)

Zollweg, J. A.

2017-10-01

Numerous ground-based, airborne, and orbiting platforms provide remotely-sensed data of remarkable spatial resolution at short time intervals. However, this spatiotemporal data is most valuable if it can be processed into information, thereby creating meaning. We live in a world of objects: cars, buildings, farms, etc. On a stormy day, we don't see millions of cubes of atmosphere; we see a thunderstorm `object'. Temporally, we don't see the properties of those individual cubes changing, we see the thunderstorm as a whole evolving and moving. There is a need to represent the bulky, raw spatiotemporal data from remote sensors as a small number of relevant spatiotemporal objects, thereby matching the human brain's perception of the world. This presentation reveals an efficient algorithm and system to extract the objects/features from raster-formatted remotely-sensed data. The system makes use of the Python object-oriented programming language, SciPy/NumPy for matrix manipulation and scientific computation, and export/import to the GeoJSON standard geographic object data format. The example presented will show how thunderstorms can be identified and characterized in a spatiotemporal continuum using a Python program to process raster data from NOAA's High-Resolution Rapid Refresh v2 (HRRRv2) data stream.