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

PubMed

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.

Geophysical Factor Resolving of Rainfall Mechanism for Super Typhoons by Using Multiple Spatiotemporal Components Analysis

NASA Astrophysics Data System (ADS)

Huang, Chien-Lin; Hsu, Nien-Sheng

2016-04-01

This study develops a novel methodology to resolve the geophysical cause of typhoon-induced rainfall considering diverse dynamic co-evolution at multiple spatiotemporal components. The multi-order hidden patterns of complex hydrological process in chaos are detected to understand the fundamental laws of rainfall mechanism. The discovered spatiotemporal features are utilized to develop a state-of-the-art descriptive statistical model for mechanism validation, modeling and further prediction during typhoons. The time series of hourly typhoon precipitation from different types of moving track, atmospheric field and landforms are respectively precede the signal analytical process to qualify each type of rainfall cause and to quantify the corresponding affected degree based on the measured geophysical atmospheric-hydrological variables. This study applies the developed methodology in Taiwan Island which is constituted by complex diverse landform formation. The identified driving-causes include: (1) cloud height to ground surface; (2) co-movement effect induced by typhoon wind field with monsoon; (3) stem capacity; (4) interaction between typhoon rain band and terrain; (5) structural intensity variance of typhoon; and (6) integrated cloudy density of rain band. Results show that: (1) for the central maximum wind speed exceeding 51 m/sec, Causes (1) and (3) are the primary ones to generate rainfall; (2) for the typhoon moving toward the direction of 155° to 175°, Cause (2) is the primary one; (3) for the direction of 90° to 155°, Cause (4) is the primary one; (4) for the typhoon passing through mountain chain which above 3500 m, Cause (5) is the primary one; and (5) for the moving speed lower than 18 km/hr, Cause (6) is the primary one. Besides, the multiple geophysical component-based precipitation modeling can achieve 81% of average accuracy and 0.732 of average correlation coefficient (CC) within average 46 hours of duration, that improve their predictability.

Spatiotemporal SNP analysis reveals pronounced biocomplexity at the northern range margin of Atlantic cod Gadus morhua

PubMed Central

Therkildsen, Nina Overgaard; Hemmer-Hansen, Jakob; Hedeholm, Rasmus Berg; Wisz, Mary S; Pampoulie, Christophe; Meldrup, Dorte; Bonanomi, Sara; Retzel, Anja; Olsen, Steffen Malskær; Nielsen, Einar Eg

2013-01-01

Accurate prediction of species distribution shifts in the face of climate change requires a sound understanding of population diversity and local adaptations. Previous modeling has suggested that global warming will lead to increased abundance of Atlantic cod (Gadus morhua) in the ocean around Greenland, but the dynamics of earlier abundance fluctuations are not well understood. We applied a retrospective spatiotemporal population genomics approach to examine the temporal stability of cod population structure in this region and to search for signatures of divergent selection over a 78-year period spanning major demographic changes. Analyzing >900 gene-associated single nucleotide polymorphisms in 847 individuals, we identified four genetically distinct groups that exhibited varying spatial distributions with considerable overlap and mixture. The genetic composition had remained stable over decades at some spawning grounds, whereas complete population replacement was evident at others. Observations of elevated differentiation in certain genomic regions are consistent with adaptive divergence between the groups, indicating that they may respond differently to environmental variation. Significantly increased temporal changes at a subset of loci also suggest that adaptation may be ongoing. These findings illustrate the power of spatiotemporal population genomics for revealing biocomplexity in both space and time and for informing future fisheries management and conservation efforts. PMID:23789034

Spatiotemporal SNP analysis reveals pronounced biocomplexity at the northern range margin of Atlantic cod Gadus morhua.

PubMed

Therkildsen, Nina Overgaard; Hemmer-Hansen, Jakob; Hedeholm, Rasmus Berg; Wisz, Mary S; Pampoulie, Christophe; Meldrup, Dorte; Bonanomi, Sara; Retzel, Anja; Olsen, Steffen Malskær; Nielsen, Einar Eg

2013-06-01

Accurate prediction of species distribution shifts in the face of climate change requires a sound understanding of population diversity and local adaptations. Previous modeling has suggested that global warming will lead to increased abundance of Atlantic cod (Gadus morhua) in the ocean around Greenland, but the dynamics of earlier abundance fluctuations are not well understood. We applied a retrospective spatiotemporal population genomics approach to examine the temporal stability of cod population structure in this region and to search for signatures of divergent selection over a 78-year period spanning major demographic changes. Analyzing >900 gene-associated single nucleotide polymorphisms in 847 individuals, we identified four genetically distinct groups that exhibited varying spatial distributions with considerable overlap and mixture. The genetic composition had remained stable over decades at some spawning grounds, whereas complete population replacement was evident at others. Observations of elevated differentiation in certain genomic regions are consistent with adaptive divergence between the groups, indicating that they may respond differently to environmental variation. Significantly increased temporal changes at a subset of loci also suggest that adaptation may be ongoing. These findings illustrate the power of spatiotemporal population genomics for revealing biocomplexity in both space and time and for informing future fisheries management and conservation efforts.

Spontaneous switching among multiple spatio-temporal patterns in three-oscillator systems constructed with oscillatory cells of true slime mold

NASA Astrophysics Data System (ADS)

Takamatsu, Atsuko

2006-11-01

Three-oscillator systems with plasmodia of true slime mold, Physarum polycephalum, which is an oscillatory amoeba-like unicellular organism, were experimentally constructed and their spatio-temporal patterns were investigated. Three typical spatio-temporal patterns were found: rotation ( R), partial in-phase ( PI), and partial anti-phase with double frequency ( PA). In pattern R, phase differences between adjacent oscillators were almost 120 ∘. In pattern PI, two oscillators were in-phase and the third oscillator showed anti-phase against the two oscillators. In pattern PA, two oscillators showed anti-phase and the third oscillator showed frequency doubling oscillation with small amplitude. Actually each pattern is not perfectly stable but quasi-stable. Interestingly, the system shows spontaneous switching among the multiple quasi-stable patterns. Statistical analyses revealed a characteristic in the residence time of each pattern: the histograms seem to have Gamma-like distribution form but with a sharp peak and a tail on the side of long period. That suggests the attractor of this system has complex structure composed of at least three types of sub-attractors: a “Gamma attractor”-involved with several Poisson processes, a “deterministic attractor”-the residence time is deterministic, and a “stable attractor”-each pattern is stable. When the coupling strength was small, only the Gamma attractor was observed and switching behavior among patterns R, PI, and PA almost always via an asynchronous pattern named O. A conjecture is as follows: Internal/external noise exposes each pattern of R, PI, and PA coexisting around bifurcation points: That is observed as the Gamma attractor. As coupling strength increases, the deterministic attractor appears then followed by the stable attractor, always accompanied with the Gamma attractor. Switching behavior could be caused by regular existence of the Gamma attractor.

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

PubMed Central

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

2017-01-01

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. PMID:28533406

A Unified Spatiotemporal Modeling Approach for Predicting Concentrations of Multiple Air Pollutants in the Multi-Ethnic Study of Atherosclerosis and Air Pollution

PubMed Central

Olives, Casey; Kim, Sun-Young; Sheppard, Lianne; Sampson, Paul D.; Szpiro, Adam A.; Oron, Assaf P.; Lindström, Johan; Vedal, Sverre; Kaufman, Joel D.

2014-01-01

Background: Cohort studies of the relationship between air pollution exposure and chronic health effects require predictions of exposure over long periods of time. Objectives: We developed a unified modeling approach for predicting fine particulate matter, nitrogen dioxide, oxides of nitrogen, and black carbon (as measured by light absorption coefficient) in six U.S. metropolitan regions from 1999 through early 2012 as part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Methods: We obtained monitoring data from regulatory networks and supplemented those data with study-specific measurements collected from MESA Air community locations and participants’ homes. In each region, we applied a spatiotemporal model that included a long-term spatial mean, time trends with spatially varying coefficients, and a spatiotemporal residual. The mean structure was derived from a large set of geographic covariates that was reduced using partial least-squares regression. We estimated time trends from observed time series and used spatial smoothing methods to borrow strength between observations. Results: Prediction accuracy was high for most models, with cross-validation R2 (R2CV) > 0.80 at regulatory and fixed sites for most regions and pollutants. At home sites, overall R2CV ranged from 0.45 to 0.92, and temporally adjusted R2CV ranged from 0.23 to 0.92. Conclusions: This novel spatiotemporal modeling approach provides accurate fine-scale predictions in multiple regions for four pollutants. We have generated participant-specific predictions for MESA Air to investigate health effects of long-term air pollution exposures. These successes highlight modeling advances that can be adopted more widely in modern cohort studies. Citation: Keller JP, Olives C, Kim SY, Sheppard L, Sampson PD, Szpiro AA, Oron AP, Lindström J, Vedal S, Kaufman JD. 2015. A unified spatiotemporal modeling approach for predicting concentrations of multiple air pollutants in the Multi

Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar

PubMed Central

Yang, Shouguo; Li, Yong; Zhang, Kunhui; Tang, Weiping

2015-01-01

A novel spatio-temporal 2-dimensional (2-D) processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters’ outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD) and direction of arrival (DOA), and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD) of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results. PMID:26694385

Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar.

PubMed

Yang, Shouguo; Li, Yong; Zhang, Kunhui; Tang, Weiping

2015-12-14

A novel spatio-temporal 2-dimensional (2-D) processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters' outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD) and direction of arrival (DOA), and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD) of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results.

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

PubMed

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.

Enzyme-Responsive Delivery of Multiple Proteins with Spatiotemporal Control.

PubMed

Zhu, Suwei; Nih, Lina; Carmichael, S Thomas; Lu, Yunfeng; Segura, Tatiana

2015-06-24

Orchestrated biological materials such as enzymes and growth factors regulate the growth of tissues and organs. A chirality-controlled, single-protein technology is devised to tailor the spatiotemporally defined delivery of therapeutic proteins in response to natural enzymes present at wound sites. Sustained delivery of one protein and sequential delivery of two proteins are demonstrated for stroke and skin wound healing. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spatio-temporal models of mental processes from fMRI.

PubMed

Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

2011-07-15

Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

Revealing the Sub-Barrier Phase using a Spatiotemporal Interferometer with Orthogonal Two-Color Laser Fields of Comparable Intensity

NASA Astrophysics Data System (ADS)

Han, Meng; Ge, Peipei; Shao, Yun; Liu, Ming-Ming; Deng, Yongkai; Wu, Chengyin; Gong, Qihuang; Liu, Yunquan

2017-08-01

We measure photoelectron momentum distributions of Ar atoms in orthogonally polarized two-color laser fields with comparable intensities. The synthesized laser field is used to manipulate the oscillating tunneling barrier and the subsequent motion of electrons onto two spatial dimensions. The subcycle structures associated with the temporal double-slit interference are spatially separated and enhanced. We use such a spatiotemporal interferometer to reveal sub-barrier phase of strong-field tunneling ionization. This study shows that the tunneling process transfers the initial phase onto momentum distribution. Our work has the implication that the sub-barrier phase plays an indispensable role in photoelectron interference processes.

Asymmetric spatiotemporal chaos induced by a polypoid mass in the excised larynx

PubMed Central

Zhang, Yu; Jiang, Jack J.

2008-01-01

In this paper, asymmetric spatiotemporal chaos induced by a polypoid mass simulating the laryngeal pathology of a vocal polyp is experimentally observed using high-speed imaging in an excised larynx. Spatiotemporal analysis reveals that the normal vocal folds show spatiotemporal correlation and symmetry. Normal vocal fold vibrations are dominated mainly by the first vibratory eigenmode. However, pathological vocal folds with a polypoid mass show broken symmetry and spatiotemporal irregularity. The spatial correlation is decreased. The pathological vocal folds spread vibratory energy across a large number of eigenmodes and induce asymmetric spatiotemporal chaos. High-order eigenmodes show complicated dynamics. Spatiotemporal analysis provides a valuable biomedical application for investigating the spatiotemporal chaotic dynamics of pathological vocal fold systems with a polypoid mass and may represent a valuable clinical tool for the detection of laryngeal mass lesion using high-speed imaging. PMID:19123612

Spatio-temporal Hotelling observer for signal detection from image sequences

PubMed Central

Caucci, Luca; Barrett, Harrison H.; Rodríguez, Jeffrey J.

2010-01-01

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. PMID:19550494

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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.

Spatio-temporal source cluster analysis reveals fronto-temporal auditory change processing differences within a shared autistic and schizotypal trait phenotype.

PubMed

Ford, Talitha C; Woods, Will; Crewther, David P

2017-01-01

Social Disorganisation (SD) is a shared autistic and schizotypal phenotype that is present in the subclinical population. Auditory processing deficits, particularly in mismatch negativity/field (MMN/F) have been reported across both spectrum disorders. This study investigates differences in MMN/F cortical spatio-temporal source activity between higher and lower quintiles of the SD spectrum. Sixteen low (9 female) and 19 high (9 female) SD subclinical adults (18-40years) underwent magnetoencephalography (MEG) during an MMF paradigm where standard tones (50ms) were interrupted by infrequent duration deviants (100ms). Spatio-temporal source cluster analysis with permutation testing revealed no difference between the groups in source activation to the standard tone. To the deviant tone however, there was significantly reduced right hemisphere fronto-temporal and insular cortex activation for the high SD group ( p = 0.038). The MMF, as a product of the cortical response to the deviant minus that to the standard, did not differ significantly between the high and low Social Disorganisation groups. These data demonstrate a deficit in right fronto-temporal processing of an auditory change for those with more of the shared SD phenotype, indicating that right fronto-temporal auditory processing may be associated with psychosocial functioning.

A hybrid spatiotemporal drought forecasting model for operational use

NASA Astrophysics Data System (ADS)

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.

Spatio-temporal dynamics of ocean conditions and forage taxa reveal regional structuring of seabird–prey relationships.

PubMed

Santora, Jarrod A; Schroeder, Isaac D; Field, John C; Wells, Brian K; Sydeman, William J

Studies of predator–prey demographic responses and the physical drivers of such relationships are rare, yet essential for predicting future changes in the structure and dynamics of marine ecosystems. Here, we hypothesize that predator–prey relationships vary spatially in association with underlying physical ocean conditions, leading to observable changes in demographic rates, such as reproduction. To test this hypothesis, we quantified spatio-temporal variability in hydrographic conditions, krill, and forage fish to model predator (seabird) demographic responses over 18 years (1990–2007). We used principal component analysis and spatial correlation maps to assess coherence among ocean conditions, krill, and forage fish, and generalized additive models to quantify interannual variability in seabird breeding success relative to prey abundance. The first principal component of four hydrographic measurements yielded an index that partitioned “warm/weak upwelling” and “cool/strong upwelling” years. Partitioning of krill and forage fish time series among shelf and oceanic regions yielded spatially explicit indicators of prey availability. Krill abundance within the oceanic region was remarkably consistent between years, whereas krill over the shelf showed marked interannual fluctuations in relation to ocean conditions. Anchovy abundance varied on the shelf, and was greater in years of strong stratification, weak upwelling and warmer temperatures. Spatio-temporal variability of juvenile forage fish co-varied strongly with each other and with krill, but was weakly correlated with hydrographic conditions. Demographic responses between seabirds and prey availability revealed spatially variable associations indicative of the dynamic nature of “predator–habitat” relationships. Quantification of spatially explicit demographic responses, and their variability through time, demonstrate the possibility of delineating specific critical areas where the

Visualizing spatiotemporal pulse propagation: first-order spatiotemporal couplings in laser pulses.

PubMed

Rhodes, Michelle; Guang, Zhe; Pease, Jerrold; Trebino, Rick

2017-04-10

Even though a general theory of first-order spatiotemporal couplings exists in the literature, it is often difficult to visualize how these distortions affect laser pulses. In particular, it is difficult to show the spatiotemporal phase of pulses in a meaningful way. Here, we propose a general solution to plotting the electric fields of pulses in three-dimensional space that intuitively shows the effects of spatiotemporal phases. The temporal phase information is color-coded using spectrograms and color response functions, and the beam is propagated to show the spatial phase evolution. Using this plotting technique, we generate two- and three-dimensional images and movies that show the effects of spatiotemporal couplings.

Spatiotemporal clustering of the epigenome reveals rules of dynamic gene regulation

PubMed Central

Yu, Pengfei; Xiao, Shu; Xin, Xiaoyun; Song, Chun-Xiao; Huang, Wei; McDee, Darina; Tanaka, Tetsuya; Wang, Ting; He, Chuan; Zhong, Sheng

2013-01-01

Spatial organization of different epigenomic marks was used to infer functions of the epigenome. It remains unclear what can be learned from the temporal changes of the epigenome. Here, we developed a probabilistic model to cluster genomic sequences based on the similarity of temporal changes of multiple epigenomic marks during a cellular differentiation process. We differentiated mouse embryonic stem (ES) cells into mesendoderm cells. At three time points during this differentiation process, we used high-throughput sequencing to measure seven histone modifications and variants—H3K4me1/2/3, H3K27ac, H3K27me3, H3K36me3, and H2A.Z; two DNA modifications—5-mC and 5-hmC; and transcribed mRNAs and noncoding RNAs (ncRNAs). Genomic sequences were clustered based on the spatiotemporal epigenomic information. These clusters not only clearly distinguished gene bodies, promoters, and enhancers, but also were predictive of bidirectional promoters, miRNA promoters, and piRNAs. This suggests specific epigenomic patterns exist on piRNA genes much earlier than germ cell development. Temporal changes of H3K4me2, unmethylated CpG, and H2A.Z were predictive of 5-hmC changes, suggesting unmethylated CpG and H3K4me2 as potential upstream signals guiding TETs to specific sequences. Several rules on combinatorial epigenomic changes and their effects on mRNA expression and ncRNA expression were derived, including a simple rule governing the relationship between 5-hmC and gene expression levels. A Sox17 enhancer containing a FOXA2 binding site and a Foxa2 enhancer containing a SOX17 binding site were identified, suggesting a positive feedback loop between the two mesendoderm transcription factors. These data illustrate the power of using epigenome dynamics to investigate regulatory functions. PMID:23033340

Thaumarchaeal amoA and nirK Gene Abundance Patterns Reveal Spatiotemporal Dynamics of Ammonia-oxidizing Archaeal Populations in Monterey Bay, CA

NASA Astrophysics Data System (ADS)

Tolar, B. B.; Reji, L.; Smith, J. M.; Chavez, F.; Francis, C.

2016-12-01

Thaumarchaeaota are among the most abundant microorganisms on the planet, and are significant players in the global nitrogen cycle. All cultivated members of the phylum are capable of performing the first and rate-limiting step of nitrification - the aerobic oxidation of ammonia to nitrite. In marine environments, ammonia-oxidizing archaea (AOA) have been found to greatly outnumber their bacterial counterparts. However, much about their ecology remains largely unknown. Monterey Bay, a non-estuarine embayment on the central California coast, is an ideal site for studying the dynamics of natural thaumarchaeal assemblages, given the highly dynamic nature of the Bay waters with seasonal upwelling episodes and the associated steep gradients in environmental variables. In the present study, we examined thaumarchaeal population dynamics in the upper Monterey Bay water column (0-500 m) using multiple molecular markers. Following high-resolution spatiotemporal sampling (i.e., up to 10 depths sampled monthly over a period of 2 years) at two stations in the Bay, we quantified thaumarchaeal functional genes - the ammonia monooxygenase (amoA) gene and its `shallow' and `deep' marine ecotypes, and variants of the marine nitrite reductase (nirK) gene. The abundances of both genes were regressed against environmental variables to gain insights into factors shaping their spatiotemporal dynamics in the Bay. Gene abundances at both stations varied with depth and season, with winter months generally having several orders of magnitude greater abundances. Statistical analyses point to differential controls on the gene abundances, with depth and temperature potentially being the major environmental determinants of thaumarchaeal population size. Our results also highlight the importance of employing multiple marker genes to gain a more highly resolved picture of thaumarchaeal population dynamics in complex environmental systems such as the coastal ocean.

Visualizing spatiotemporal pulse propagation: first-order spatiotemporal couplings in laser pulses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rhodes, Michelle; Guang, Zhe; Pease, Jerrold

2017-04-06

Even though a general theory of first-order spatiotemporal couplings exists in the literature, it is often difficult to visualize how these distortions affect laser pulses. In particular, it is difficult to show the spatiotemporal phase of pulses in a meaningful way. We propose a general solution to plotting the electric fields of pulses in three-dimensional space that intuitively shows the effects of spatiotemporal phases. The temporal phase information is color-coded using spectrograms and color response functions, and the beam is propagated to show the spatial phase evolution. In using this plotting technique, we generate two- and three-dimensional images and moviesmore » that show the effects of spatiotemporal couplings.« less

Spatiotemporal drought forecasting using nonlinear models

NASA Astrophysics Data System (ADS)

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

The influence of spatiotemporal structure of noisy stimuli in decision making.

PubMed

Insabato, Andrea; Dempere-Marco, Laura; Pannunzi, Mario; Deco, Gustavo; Romo, Ranulfo

2014-04-01

Decision making is a process of utmost importance in our daily lives, the study of which has been receiving notable attention for decades. Nevertheless, the neural mechanisms underlying decision making are still not fully understood. Computational modeling has revealed itself as a valuable asset to address some of the fundamental questions. Biophysically plausible models, in particular, are useful in bridging the different levels of description that experimental studies provide, from the neural spiking activity recorded at the cellular level to the performance reported at the behavioral level. In this article, we have reviewed some of the recent progress made in the understanding of the neural mechanisms that underlie decision making. We have performed a critical evaluation of the available results and address, from a computational perspective, aspects of both experimentation and modeling that so far have eluded comprehension. To guide the discussion, we have selected a central theme which revolves around the following question: how does the spatiotemporal structure of sensory stimuli affect the perceptual decision-making process? This question is a timely one as several issues that still remain unresolved stem from this central theme. These include: (i) the role of spatiotemporal input fluctuations in perceptual decision making, (ii) how to extend the current results and models derived from two-alternative choice studies to scenarios with multiple competing evidences, and (iii) to establish whether different types of spatiotemporal input fluctuations affect decision-making outcomes in distinctive ways. And although we have restricted our discussion mostly to visual decisions, our main conclusions are arguably generalizable; hence, their possible extension to other sensory modalities is one of the points in our discussion.

The Influence of Spatiotemporal Structure of Noisy Stimuli in Decision Making

PubMed Central

Deco, Gustavo; Romo, Ranulfo

2014-01-01

Decision making is a process of utmost importance in our daily lives, the study of which has been receiving notable attention for decades. Nevertheless, the neural mechanisms underlying decision making are still not fully understood. Computational modeling has revealed itself as a valuable asset to address some of the fundamental questions. Biophysically plausible models, in particular, are useful in bridging the different levels of description that experimental studies provide, from the neural spiking activity recorded at the cellular level to the performance reported at the behavioral level. In this article, we have reviewed some of the recent progress made in the understanding of the neural mechanisms that underlie decision making. We have performed a critical evaluation of the available results and address, from a computational perspective, aspects of both experimentation and modeling that so far have eluded comprehension. To guide the discussion, we have selected a central theme which revolves around the following question: how does the spatiotemporal structure of sensory stimuli affect the perceptual decision-making process? This question is a timely one as several issues that still remain unresolved stem from this central theme. These include: (i) the role of spatiotemporal input fluctuations in perceptual decision making, (ii) how to extend the current results and models derived from two-alternative choice studies to scenarios with multiple competing evidences, and (iii) to establish whether different types of spatiotemporal input fluctuations affect decision-making outcomes in distinctive ways. And although we have restricted our discussion mostly to visual decisions, our main conclusions are arguably generalizable; hence, their possible extension to other sensory modalities is one of the points in our discussion. PMID:24743140

Single Turnover at Molecular Polymerization Catalysts Reveals Spatiotemporally Resolved Reactions.

PubMed

Easter, Quinn T; Blum, Suzanne A

2017-10-23

Multiple active individual molecular ruthenium catalysts have been pinpointed within growing polynorbornene, thereby revealing information on the reaction dynamics and location that is unavailable through traditional ensemble experiments. This is the first single-turnover imaging of a molecular catalyst by fluorescence microscopy and allows detection of individual monomer reactions at an industrially important molecular ruthenium ring-opening metathesis polymerization (ROMP) catalyst under synthetically relevant conditions (e.g. unmodified industrial catalyst, ambient pressure, condensed phase, ca. 0.03 m monomer). These results further establish the key fundamentals of this imaging technique for characterizing the reactivity and location of active molecular catalysts even when they are the minor components. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The spatiotemporal pattern of Src activation at lipid rafts revealed by diffusion-corrected FRET imaging.

PubMed

Lu, Shaoying; Ouyang, Mingxing; Seong, Jihye; Zhang, Jin; Chien, Shu; Wang, Yingxiao

2008-07-25

Genetically encoded biosensors based on fluorescence resonance energy transfer (FRET) have been widely applied to visualize the molecular activity in live cells with high spatiotemporal resolution. However, the rapid diffusion of biosensor proteins hinders a precise reconstruction of the actual molecular activation map. Based on fluorescence recovery after photobleaching (FRAP) experiments, we have developed a finite element (FE) method to analyze, simulate, and subtract the diffusion effect of mobile biosensors. This method has been applied to analyze the mobility of Src FRET biosensors engineered to reside at different subcompartments in live cells. The results indicate that the Src biosensor located in the cytoplasm moves 4-8 folds faster (0.93+/-0.06 microm(2)/sec) than those anchored on different compartments in plasma membrane (at lipid raft: 0.11+/-0.01 microm(2)/sec and outside: 0.18+/-0.02 microm(2)/sec). The mobility of biosensor at lipid rafts is slower than that outside of lipid rafts and is dominated by two-dimensional diffusion. When this diffusion effect was subtracted from the FRET ratio images, high Src activity at lipid rafts was observed at clustered regions proximal to the cell periphery, which remained relatively stationary upon epidermal growth factor (EGF) stimulation. This result suggests that EGF induced a Src activation at lipid rafts with well-coordinated spatiotemporal patterns. Our FE-based method also provides an integrated platform of image analysis for studying molecular mobility and reconstructing the spatiotemporal activation maps of signaling molecules in live cells.

An evaluation of space time cube representation of spatiotemporal patterns.

PubMed

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 Data Organization and Application Research

NASA Astrophysics Data System (ADS)

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.

Spatiotemporal Dynamics of a Network of Coupled Time-Delay Digital Tanlock Loops

NASA Astrophysics Data System (ADS)

Paul, Bishwajit; Banerjee, Tanmoy; Sarkar, B. C.

The time-delay digital tanlock loop (TDTLs) is an important class of phase-locked loop that is widely used in electronic communication systems. Although nonlinear dynamics of an isolated TDTL has been studied in the past but the collective behavior of TDTLs in a network is an important topic of research and deserves special attention as in practical communication systems separate entities are rarely isolated. In this paper, we carry out the detailed analysis and numerical simulations to explore the spatiotemporal dynamics of a network of a one-dimensional ring of coupled TDTLs with nearest neighbor coupling. The equation representing the network is derived and we carry out analytical calculations using the circulant matrix formalism to obtain the stability criteria. An extensive numerical simulation reveals that with the variation of gain parameter and coupling strength the network shows a variety of spatiotemporal dynamics such as frozen random pattern, pattern selection, spatiotemporal intermittency and fully developed spatiotemporal chaos. We map the distinct dynamical regions of the system in two-parameter space. Finally, we quantify the spatiotemporal dynamics by using quantitative measures like Lyapunov exponent and the average quadratic deviation of the full network.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

The Little ice Age (LIA) is one of the most prominent epochs in paleoclimate reconstruction of the Common Era. While the signals of LIA were generally discovered across hemispheres, wide arrays of regional variability were found, and the reconstructed anomalies were sometimes inconsistent across studies by using various proxy data or historical records. This inconsistency is mainly attributed to limited data coverage at fine resolution that can assist high-resolution climate reconstruction in the continuous spatiotemporal trends. Qing dynasty (1644-1911 CE) of China existed in the coldest period of LIA. Owing to a long-standing tradition that acquired local officials to record odds and social or meteorological events, thousands of local chronicles were left. Zhang eds. (2004) took two decades to compile all these meteorological records in a compendium, for which we then digitized and coded all records into our REACHS database system for reconstructing climate. There were in total 1,435 points (sites) in our database for over 80,000 events in the period of time. After implementing two-rounds coding check for data quality control (accuracy rate 87.2%), multiple indexes were retrieved for reconstructing annually and seasonally resolved temperature and precipitation series for North, Central, and South China. The reconstruction methods include frequency count and grading, with usage of multiple regression models to test sensitivity and to calculate correlations among several reconstructed series. Validation was also conducted through comparison with instrumental data and with other reconstructed series in previous studies. Major research results reveal interannual (3-5 years), decadal (8-12 years), and interdecadal (≈30 years) variabilities with strong regional expressions across East China. Cooling effect was not homogenously distributed in space and time. Flood and drought conditions frequently repeated but the spatiotemporal pattern was variant, indicating likely

Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium.

PubMed

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.

Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium

NASA Astrophysics Data System (ADS)

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.

Neurog1 Genetic Inducible Fate Mapping (GIFM) Reveals the Existence of Complex Spatiotemporal Cyto-Architectures in the Developing Cerebellum.

PubMed

Obana, Edwin A; Lundell, Travis G; Yi, Kevin J; Radomski, Kryslaine L; Zhou, Qiong; Doughty, Martin L

2015-06-01

Neurog1 is a pro-neural basic helix-loop-helix (bHLH) transcription factor expressed in progenitor cells located in the ventricular zone and subsequently the presumptive white matter tracts of the developing mouse cerebellum. We used genetic inducible fate mapping (GIFM) with a transgenic Neurog1-CreER allele to characterize the contributions of Neurog1 lineages to cerebellar circuit formation in mice. GIFM reveals Neurog1-expressing progenitors are fate-mapped to become Purkinje cells and all GABAergic interneuron cell types of the cerebellar cortex but not glia. The spatiotemporal sequence of GIFM is unique to each neuronal cell type. GIFM on embryonic days (E) 10.5 to E12.5 labels Purkinje cells with different medial-lateral settling patterns depending on the day of tamoxifen delivery. GIFM on E11.5 to P7 labels interneurons and the timing of tamoxifen administration correlates with the final inside-to-outside resting position of GABAergic interneurons in the cerebellar cortex. Proliferative status and long-term BrdU retention of GIFM lineages reveals Purkinje cells express Neurog1 around the time they become post-mitotic. In contrast, GIFM labels mitotic and post-mitotic interneurons. Neurog1-CreER GIFM reveals a correlation between the timing of Neurog1 expression and the spatial organization of GABAergic neurons in the cerebellar cortex with possible implications for cerebellar circuit assembly.

Mining moving object trajectories in location-based services for spatio-temporal database update

NASA Astrophysics Data System (ADS)

Guo, Danhuai; Cui, Weihong

2008-10-01

Advances in wireless transmission and mobile technology applied to LBS (Location-based Services) flood us with amounts of moving objects data. Vast amounts of gathered data from position sensors of mobile phones, PDAs, or vehicles hide interesting and valuable knowledge and describe the behavior of moving objects. The correlation between temporal moving patterns of moving objects and geo-feature spatio-temporal attribute was ignored, and the value of spatio-temporal trajectory data was not fully exploited too. Urban expanding or frequent town plan change bring about a large amount of outdated or imprecise data in spatial database of LBS, and they cannot be updated timely and efficiently by manual processing. In this paper we introduce a data mining approach to movement pattern extraction of moving objects, build a model to describe the relationship between movement patterns of LBS mobile objects and their environment, and put up with a spatio-temporal database update strategy in LBS database based on trajectories spatiotemporal mining. Experimental evaluation reveals excellent performance of the proposed model and strategy. Our original contribution include formulation of model of interaction between trajectory and its environment, design of spatio-temporal database update strategy based on moving objects data mining, and the experimental application of spatio-temporal database update by mining moving objects trajectories.

Fine spatiotemporal activity in contracting myometrium revealed by motion-corrected calcium imaging

PubMed Central

Loftus, Fiona C; Shmygol, Anatoly; Richardson, Magnus J E

2014-01-01

Successful childbirth depends on the occurrence of precisely coordinated uterine contractions during labour. Calcium indicator fluorescence imaging is one of the main techniques for investigating the mechanisms governing this physiological process and its pathologies. The effective spatiotemporal resolution of calcium signals is, however, limited by the motion of contracting tissue: structures of interest in the order of microns can move over a hundred times their width during a contraction. The simultaneous changes in local intensity and tissue configuration make motion tracking a non-trivial problem in image analysis and confound many of the standard techniques. This paper presents a method that tracks local motion throughout the tissue and allows for the almost complete removal of motion artefacts. This provides a stabilized calcium signal down to a pixel resolution, which, for the data examined, is in the order of a few microns. As a byproduct of image stabilization, a complete kinematic description of the contraction–relaxation cycle is also obtained. This contains novel information about the mechanical response of the tissue, such as the identification of a characteristic length scale, in the order of 40–50 μm, below which tissue motion is homogeneous. Applied to our data, we illustrate that the method allows for analyses of calcium dynamics in contracting myometrium in unprecedented spatiotemporal detail. Additionally, we use the kinematics of tissue motion to compare calcium signals at the subcellular level and local contractile motion. The computer code used is provided in a freely modifiable form and has potential applicability to in vivo calcium imaging of neural tissue, as well as other smooth muscle tissue. PMID:25085893

Rapid Motion Adaptation Reveals the Temporal Dynamics of Spatiotemporal Correlation between ON and OFF Pathways

PubMed Central

Oluk, Can; Pavan, Andrea; Kafaligonul, Hulusi

2016-01-01

At the early stages of visual processing, information is processed by two major thalamic pathways encoding brightness increments (ON) and decrements (OFF). Accumulating evidence suggests that these pathways interact and merge as early as in primary visual cortex. Using regular and reverse-phi motion in a rapid adaptation paradigm, we investigated the temporal dynamics of within and across pathway mechanisms for motion processing. When the adaptation duration was short (188 ms), reverse-phi and regular motion led to similar adaptation effects, suggesting that the information from the two pathways are combined efficiently at early-stages of motion processing. However, as the adaption duration was increased to 752 ms, reverse-phi and regular motion showed distinct adaptation effects depending on the test pattern used, either engaging spatiotemporal correlation between the same or opposite contrast polarities. Overall, these findings indicate that spatiotemporal correlation within and across ON-OFF pathways for motion processing can be selectively adapted, and support those models that integrate within and across pathway mechanisms for motion processing. PMID:27667401

An Intelligent Polar Cyberinfrastrucuture to Support Spatiotemporal Decision Making

NASA Astrophysics Data System (ADS)

Song, M.; Li, W.; Zhou, X.

2014-12-01

In the era of big data, polar sciences have already faced an urgent demand of utilizing intelligent approaches to support precise and effective spatiotemporal decision-making. Service-oriented cyberinfrastructure has advantages of seamlessly integrating distributed computing resources, and aggregating a variety of geospatial data derived from Earth observation network. This paper focuses on building a smart service-oriented cyberinfrastructure to support intelligent question answering related to polar datasets. The innovation of this polar cyberinfrastructure includes: (1) a problem-solving environment that parses geospatial question in natural language, builds geoprocessing rules, composites atomic processing services and executes the entire workflow; (2) a self-adaptive spatiotemporal filter that is capable of refining query constraints through semantic analysis; (3) a dynamic visualization strategy to support results animation and statistics in multiple spatial reference systems; and (4) a user-friendly online portal to support collaborative decision-making. By means of this polar cyberinfrastructure, we intend to facilitate integration of distributed and heterogeneous Arctic datasets and comprehensive analysis of multiple environmental elements (e.g. snow, ice, permafrost) to provide a better understanding of the environmental variation in circumpolar regions.

Balance and ankle muscle strength predict spatiotemporal gait parameters in individuals with diabetic peripheral neuropathy.

PubMed

Camargo, Marcela R; Barela, José A; Nozabieli, Andréa J L; Mantovani, Alessandra M; Martinelli, Alessandra R; Fregonesi, Cristina E P T

2015-01-01

The aims of this study were to evaluate aspects of balance, ankle muscle strength and spatiotemporal gait parameters in individuals with diabetic peripheral neuropathy (DPN) and verify whether deficits in spatiotemporal gait parameters were associated with ankle muscle strength and balance performance. Thirty individuals with DPN and 30 control individuals have participated. Spatiotemporal gait parameters were evaluated by measuring the time to walk a set distance during self-selected and maximal walking speeds. Functional mobility and balance performance were assessed using the Functional Reach and the Time Up and Go tests. Ankle isometric muscle strength was assessed with a handheld digital dynamometer. Analyses of variance were employed to verify possible differences between groups and conditions. Multiple linear regression analysis was employed to uncover possible predictors of gait deficits. Gait spatiotemporal, functional mobility, balance performance and ankle muscle strength were affected in individuals with DPN. The Time Up and Go test performance and ankle muscle isometric strength were associated to spatiotemporal gait changes, especially during maximal walking speed condition. Functional mobility and balance performance are damaged in DPN and balance performance and ankle muscle strength can be used to predict spatiotemporal gait parameters in individuals with DPN. Copyright © 2015 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Considering spatial heterogeneity in the distributed lag non-linear model when analyzing spatiotemporal data.

PubMed

Chien, Lung-Chang; Guo, Yuming; Li, Xiao; Yu, Hwa-Lung

2018-01-01

The distributed lag non-linear (DLNM) model has been frequently used in time series environmental health research. However, its functionality for assessing spatial heterogeneity is still restricted, especially in analyzing spatiotemporal data. This study proposed a solution to take a spatial function into account in the DLNM, and compared the influence with and without considering spatial heterogeneity in a case study. This research applied the DLNM to investigate non-linear lag effect up to 7 days in a case study about the spatiotemporal impact of fine particulate matter (PM 2.5 ) on preschool children's acute respiratory infection in 41 districts of northern Taiwan during 2005 to 2007. We applied two spatiotemporal methods to impute missing air pollutant data, and included the Markov random fields to analyze district boundary data in the DLNM. When analyzing the original data without a spatial function, the overall PM 2.5 effect accumulated from all lag-specific effects had a slight variation at smaller PM 2.5 measurements, but eventually decreased to relative risk significantly <1 when PM 2.5 increased. While analyzing spatiotemporal imputed data without a spatial function, the overall PM 2.5 effect did not decrease but increased in monotone as PM 2.5 increased over 20 μg/m 3 . After adding a spatial function in the DLNM, spatiotemporal imputed data conducted similar results compared with the overall effect from the original data. Moreover, the spatial function showed a clear and uneven pattern in Taipei, revealing that preschool children living in 31 districts of Taipei were vulnerable to acute respiratory infection. Our findings suggest the necessity of including a spatial function in the DLNM to make a spatiotemporal analysis available and to conduct more reliable and explainable research. This study also revealed the analytical impact if spatial heterogeneity is ignored.

Spatiotemporal variation in the postseismic deformation of the 2011 Tohoku-oki earthquake revealed by seafloor geodetic observations

NASA Astrophysics Data System (ADS)

Tomita, F.; Kido, M.; Ohta, Y.; Hino, R.; Iinuma, T.

2016-12-01

Postseismic deformation following the 2011 Tohoku-oki earthquake has been detected by on- and off-shore geodetic observations. GPS/Acoustic (GPS/A) observations [Watanabe et al., 2014, GRL] just above the coseismic primary rupture area (PRA) show significant landward movement in contrast to the trench-ward movement of the on-shore GPS observations, which can be generally explained by viscoelastic relaxation [Sun et al., 2014, Nature]. Furthermore, Tomita et al. [2015, AGU] demonstrated along-trench variation of the postseismic deformation also using GPS/A observations. In this study, we show detailed spatiotemporal characteristics of the postseismic deformation using updated GPS/A measurement results. We employed 20 GPS/A sites located in Tohoku-oki region and had conducted repeated campaign surveys from Sep. 2012 to May 2016. GPS/A positioning was performed using the method of Kido et al. [2006, EPS]. Then, we calculated postseismic displacement rates by applying a weighted robust linear fitting. The updated results of the postseismic displacement rates are consistent with the characteristic revealed by Tomita et al. [2015] but are estimated with better precision ( 2 cm/yr in 1σ). The sites in the north region of PRA show slight trenchward movement (< 5 cm/yr), while the sites in the south region of PRA show significant trenchward movement (5-15 cm/yr) indicating dominance of the afterslip effects. Moreover, the sites above PRA show significant landward movement (10-15 cm/yr) indicating viscoelastic relaxation and interplate relocking effects. Furthermore, the updated results may show temporal decay of afterslip; the temporally decaying displacements have been observed in the south region of PRA. However, such a temporal decay has not been measured in the region where viscoelastic relaxation causes significant deformation. In the presentation, we will discuss detail spatiotemporal evolution of the postseismic deformation processes from the updated results by

Fine spatiotemporal activity in contracting myometrium revealed by motion-corrected calcium imaging.

PubMed

Loftus, Fiona C; Shmygol, Anatoly; Richardson, Magnus J E

2014-10-15

Successful childbirth depends on the occurrence of precisely coordinated uterine contractions during labour. Calcium indicator fluorescence imaging is one of the main techniques for investigating the mechanisms governing this physiological process and its pathologies. The effective spatiotemporal resolution of calcium signals is, however, limited by the motion of contracting tissue: structures of interest in the order of microns can move over a hundred times their width during a contraction. The simultaneous changes in local intensity and tissue configuration make motion tracking a non-trivial problem in image analysis and confound many of the standard techniques. This paper presents a method that tracks local motion throughout the tissue and allows for the almost complete removal of motion artefacts. This provides a stabilized calcium signal down to a pixel resolution, which, for the data examined, is in the order of a few microns. As a byproduct of image stabilization, a complete kinematic description of the contraction-relaxation cycle is also obtained. This contains novel information about the mechanical response of the tissue, such as the identification of a characteristic length scale, in the order of 40-50 μm, below which tissue motion is homogeneous. Applied to our data, we illustrate that the method allows for analyses of calcium dynamics in contracting myometrium in unprecedented spatiotemporal detail. Additionally, we use the kinematics of tissue motion to compare calcium signals at the subcellular level and local contractile motion. The computer code used is provided in a freely modifiable form and has potential applicability to in vivo calcium imaging of neural tissue, as well as other smooth muscle tissue. © 2014 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.

Spatiotemporal source tuning filter bank for multiclass EEG based brain computer interfaces.

PubMed

Acharya, Soumyadipta; Mollazadeh, Moshen; Murari, Kartikeya; Thakor, Nitish

2006-01-01

Non invasive brain-computer interfaces (BCI) allow people to communicate by modulating features of their electroencephalogram (EEG). Spatiotemporal filtering has a vital role in multi-class, EEG based BCI. In this study, we used a novel combination of principle component analysis, independent component analysis and dipole source localization to design a spatiotemporal multiple source tuning (SPAMSORT) filter bank, each channel of which was tuned to the activity of an underlying dipole source. Changes in the event-related spectral perturbation (ERSP) were measured and used to train a linear support vector machine to classify between four classes of motor imagery tasks (left hand, right hand, foot and tongue) for one subject. ERSP values were significantly (p<0.01) different across tasks and better (p<0.01) than conventional spatial filtering methods (large Laplacian and common average reference). Classification resulted in an average accuracy of 82.5%. This approach could lead to promising BCI applications such as control of a prosthesis with multiple degrees of freedom.

Transient spatiotemporal chaos in the Morris-Lecar neuronal ring network.

PubMed

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.

Precise Spatiotemporal Control of Optogenetic Activation Using an Acousto-Optic Device

PubMed Central

Guo, Yanmeng; Song, Peipei; Zhang, Xiaohui; Zeng, Shaoqun; Wang, Zuoren

2011-01-01

Light activation and inactivation of neurons by optogenetic techniques has emerged as an important tool for studying neural circuit function. To achieve a high resolution, new methods are being developed to selectively manipulate the activity of individual neurons. Here, we report that the combination of an acousto-optic device (AOD) and single-photon laser was used to achieve rapid and precise spatiotemporal control of light stimulation at multiple points in a neural circuit with millisecond time resolution. The performance of this system in activating ChIEF expressed on HEK 293 cells as well as cultured neurons was first evaluated, and the laser stimulation patterns were optimized. Next, the spatiotemporally selective manipulation of multiple neurons was achieved in a precise manner. Finally, we demonstrated the versatility of this high-resolution method in dissecting neural circuits both in the mouse cortical slice and the Drosophila brain in vivo. Taken together, our results show that the combination of AOD-assisted laser stimulation and optogenetic tools provides a flexible solution for manipulating neuronal activity at high efficiency and with high temporal precision. PMID:22174813

Bilinearity in Spatiotemporal Integration of Synaptic Inputs

PubMed Central

Li, Songting; Liu, Nan; Zhang, Xiao-hui; Zhou, Douglas; Cai, David

2014-01-01

Neurons process information via integration of synaptic inputs from dendrites. Many experimental results demonstrate dendritic integration could be highly nonlinear, yet few theoretical analyses have been performed to obtain a precise quantitative characterization analytically. Based on asymptotic analysis of a two-compartment passive cable model, given a pair of time-dependent synaptic conductance inputs, we derive a bilinear spatiotemporal dendritic integration rule. The summed somatic potential can be well approximated by the linear summation of the two postsynaptic potentials elicited separately, plus a third additional bilinear term proportional to their product with a proportionality coefficient . The rule is valid for a pair of synaptic inputs of all types, including excitation-inhibition, excitation-excitation, and inhibition-inhibition. In addition, the rule is valid during the whole dendritic integration process for a pair of synaptic inputs with arbitrary input time differences and input locations. The coefficient is demonstrated to be nearly independent of the input strengths but is dependent on input times and input locations. This rule is then verified through simulation of a realistic pyramidal neuron model and in electrophysiological experiments of rat hippocampal CA1 neurons. The rule is further generalized to describe the spatiotemporal dendritic integration of multiple excitatory and inhibitory synaptic inputs. The integration of multiple inputs can be decomposed into the sum of all possible pairwise integration, where each paired integration obeys the bilinear rule. This decomposition leads to a graph representation of dendritic integration, which can be viewed as functionally sparse. PMID:25521832

Tensor-based spatiotemporal saliency detection

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

A spatiotemporal profile of visual system activation revealed by current source density analysis in the awake macaque.

PubMed

Schroeder, C E; Mehta, A D; Givre, S J

1998-01-01

We investigated the spatiotemporal activation pattern, produced by one visual stimulus, across cerebral cortical regions in awake monkeys. Laminar profiles of postsynaptic potentials and action potentials were indexed with current source density (CSD) and multiunit activity profiles respectively. Locally, we found contrasting activation profiles in dorsal and ventral stream areas. The former, like V1 and V2, exhibit a 'feedforward' profile, with excitation beginning at the depth of Lamina 4, followed by activation of the extragranular laminae. The latter often displayed a multilaminar/columnar profile, with initial responses distributed across the laminae and reflecting modulation rather than excitation; CSD components were accompanied by either no changes or by suppression of action potentials. System-wide, response latencies indicated a large dorsal/ventral stream latency advantage, which generalizes across a wide range of methods. This predicts a specific temporal ordering of dorsal and ventral stream components of visual analysis, as well as specific patterns of dorsal-ventral stream interaction. Our findings support a hierarchical model of cortical organization that combines serial and parallel elements. Critical in such a model is the recognition that processing within a location typically entails multiple temporal components or 'waves' of activity, driven by input conveyed over heterogeneous pathways from the retina.

A spatiotemporal analysis of U.S. station temperature trends over the last century

NASA Astrophysics Data System (ADS)

Capparelli, V.; Franzke, C.; Vecchio, A.; Freeman, M. P.; Watkins, N. W.; Carbone, V.

2013-07-01

This study presents a nonlinear spatiotemporal analysis of 1167 station temperature records from the United States Historical Climatology Network covering the period from 1898 through 2008. We use the empirical mode decomposition method to extract the generally nonlinear trends of each station. The statistical significance of each trend is assessed against three null models of the background climate variability, represented by stochastic processes of increasing temporal correlation length. We find strong evidence that more than 50% of all stations experienced a significant trend over the last century with respect to all three null models. A spatiotemporal analysis reveals a significant cooling trend in the South-East and significant warming trends in the rest of the contiguous U.S. It also shows that the warming trend appears to have migrated equatorward. This shows the complex spatiotemporal evolution of climate change at local scales.

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

PubMed

Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

2011-06-01

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

Spatiotemporal fusion of multiple-satellite aerosol optical depth (AOD) products using Bayesian maximum entropy method

NASA Astrophysics Data System (ADS)

Tang, Qingxin; Bo, Yanchen; Zhu, Yuxin

2016-04-01

Merging multisensor aerosol optical depth (AOD) products is an effective way to produce more spatiotemporally complete and accurate AOD products. A spatiotemporal statistical data fusion framework based on a Bayesian maximum entropy (BME) method was developed for merging satellite AOD products in East Asia. The advantages of the presented merging framework are that it not only utilizes the spatiotemporal autocorrelations but also explicitly incorporates the uncertainties of the AOD products being merged. The satellite AOD products used for merging are the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Level-2 AOD products (MOD04_L2) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue Level 2 AOD products (SWDB_L2). The results show that the average completeness of the merged AOD data is 95.2%,which is significantly superior to the completeness of MOD04_L2 (22.9%) and SWDB_L2 (20.2%). By comparing the merged AOD to the Aerosol Robotic Network AOD records, the results show that the correlation coefficient (0.75), root-mean-square error (0.29), and mean bias (0.068) of the merged AOD are close to those (the correlation coefficient (0.82), root-mean-square error (0.19), and mean bias (0.059)) of the MODIS AOD. In the regions where both MODIS and SeaWiFS have valid observations, the accuracy of the merged AOD is higher than those of MODIS and SeaWiFS AODs. Even in regions where both MODIS and SeaWiFS AODs are missing, the accuracy of the merged AOD is also close to the accuracy of the regions where both MODIS and SeaWiFS have valid observations.

The Influence of Weather and Lemmings on Spatiotemporal Variation in the Abundance of Multiple Avian Guilds in the Arctic

PubMed Central

Robinson, Barry G.; Franke, Alastair; Derocher, Andrew E.

2014-01-01

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 weather, spring snow

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

PubMed

Robinson, Barry G; Franke, Alastair; Derocher, Andrew E

2014-01-01

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 weather, spring snow

Multivariate spatiotemporal visualizations for mobile devices in Flyover Country

NASA Astrophysics Data System (ADS)

Loeffler, S.; Thorn, R.; Myrbo, A.; Roth, R.; Goring, S. J.; Williams, J.

2017-12-01

Visualizing and interacting with complex multivariate and spatiotemporal datasets on mobile devices is challenging due to their smaller screens, reduced processing power, and limited data connectivity. Pollen data require visualizing pollen assemblages spatially, temporally, and across multiple taxa to understand plant community dynamics through time. Drawing from cartography, information visualization, and paleoecology, we have created new mobile-first visualization techniques that represent multiple taxa across many sites and enable user interaction. Using pollen datasets from the Neotoma Paleoecology Database as a case study, the visualization techniques allow ecological patterns and trends to be quickly understood on a mobile device compared to traditional pollen diagrams and maps. This flexible visualization system can be used for datasets beyond pollen, with the only requirements being point-based localities and multiple variables changing through time or depth.

Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2016-01-01

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099

Formally grounding spatio-temporal thinking.

PubMed

Klippel, Alexander; Wallgrün, Jan Oliver; Yang, Jinlong; Li, Rui; Dylla, Frank

2012-08-01

To navigate through daily life, humans use their ability to conceptualize spatio-temporal information, which ultimately leads to a system of categories. Likewise, the spatial sciences rely heavily on conceptualization and categorization as means to create knowledge when they process spatio-temporal data. In the spatial sciences and in related branches of artificial intelligence, an approach has been developed for processing spatio-temporal data on the level of coarse categories: qualitative spatio-temporal representation and reasoning (QSTR). Calculi developed in QSTR allow for the meaningful processing of and reasoning with spatio-temporal information. While qualitative calculi are widely acknowledged in the cognitive sciences, there is little behavioral assessment whether these calculi are indeed cognitively adequate. This is an astonishing conundrum given that these calculi are ubiquitous, are often intended to improve processes at the human-machine interface, and are on several occasions claimed to be cognitively adequate. We have systematically evaluated several approaches to formally characterize spatial relations from a cognitive-behavioral perspective for both static and dynamically changing spatial relations. This contribution will detail our framework, which is addressing the question how formal characterization of space can help us understand how people think with, in, and about space.

Uncertainty assessment of PM2.5 contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data

NASA Astrophysics Data System (ADS)

Yang, Yong; Christakos, George; Huang, Wei; Lin, Chengda; Fu, Peihong; Mei, Yang

2016-04-01

Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indicator simulation (SIS) and indicator kriging techniques. However, these methods cannot be employed to assess multi-temporal data. In this work, a spatiotemporal sequential indicator simulation (STSIS) based on a non-separable spatiotemporal semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations recorded throughout 2014 in Shandong Province, China were used as the experimental dataset. Based on the number of STSIS procedures, we assessed various types of mapping uncertainties, including single-location uncertainties over one day and multiple days and multi-location uncertainties over one day and multiple days. A comparison of the STSIS technique with the SIS technique indicate that a better performance was obtained with the STSIS method.

Uncertainty assessment of PM2.5 contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data.

PubMed

Yang, Yong; Christakos, George; Huang, Wei; Lin, Chengda; Fu, Peihong; Mei, Yang

2016-04-12

Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indicator simulation (SIS) and indicator kriging techniques. However, these methods cannot be employed to assess multi-temporal data. In this work, a spatiotemporal sequential indicator simulation (STSIS) based on a non-separable spatiotemporal semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations recorded throughout 2014 in Shandong Province, China were used as the experimental dataset. Based on the number of STSIS procedures, we assessed various types of mapping uncertainties, including single-location uncertainties over one day and multiple days and multi-location uncertainties over one day and multiple days. A comparison of the STSIS technique with the SIS technique indicate that a better performance was obtained with the STSIS method.

Image Motion Detection And Estimation: The Modified Spatio-Temporal Gradient Scheme

NASA Astrophysics Data System (ADS)

Hsin, Cheng-Ho; Inigo, Rafael M.

1990-03-01

The detection and estimation of motion are generally involved in computing a velocity field of time-varying images. A completely new modified spatio-temporal gradient scheme to determine motion is proposed. This is derived by using gradient methods and properties of biological vision. A set of general constraints is proposed to derive motion constraint equations. The constraints are that the second directional derivatives of image intensity at an edge point in the smoothed image will be constant at times t and t+L . This scheme basically has two stages: spatio-temporal filtering, and velocity estimation. Initially, image sequences are processed by a set of oriented spatio-temporal filters which are designed using a Gaussian derivative model. The velocity is then estimated for these filtered image sequences based on the gradient approach. From a computational stand point, this scheme offers at least three advantages over current methods. The greatest advantage of the modified spatio-temporal gradient scheme over the traditional ones is that an infinite number of motion constraint equations are derived instead of only one. Therefore, it solves the aperture problem without requiring any additional assumptions and is simply a local process. The second advantage is that because of the spatio-temporal filtering, the direct computation of image gradients (discrete derivatives) is avoided. Therefore the error in gradients measurement is reduced significantly. The third advantage is that during the processing of motion detection and estimation algorithm, image features (edges) are produced concurrently with motion information. The reliable range of detected velocity is determined by parameters of the oriented spatio-temporal filters. Knowing the velocity sensitivity of a single motion detection channel, a multiple-channel mechanism for estimating image velocity, seldom addressed by other motion schemes in machine vision, can be constructed by appropriately choosing and

Chimera states in spatiotemporal systems: Theory and Applications

NASA Astrophysics Data System (ADS)

Yao, Nan; Zheng, Zhigang

2016-03-01

In this paper, we propose a retrospective and summary on recent studies of chimera states. Chimera states demonstrate striking inhomogeneous spatiotemporal patterns emerging in homogeneous systems through unexpected spontaneous symmetry breaking, where the consequent spatiotemporal patterns are composed of both coherence and incoherence domains, respectively characterized by the synchronized and desynchronized motions of oscillators. Since the discovery of chimera states by Kuramoto and others, this striking collective behavior has attracted a great deal of research interest in the community of physics and related interdisciplinary fields from both theoretical and experimental viewpoints. In recent works exploring chimera states, rich phenomena such as the spiral wave chimera, multiple cluster chimera, amplitude chimera were observed from various types of model systems. Theoretical framework by means of self-consistency approach and Ott-Antonsen approach were proposed for further understanding to this symmetry-breaking-induced behavior. The stability and robustness of chimera states were also discussed. More importantly, experiments ranging from optical, chemical to mechanical designs successfully approve the existence of chimera states.

Rainfall spatiotemporal variability relation to wetlands hydroperiods

NASA Astrophysics Data System (ADS)

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

Mapping the spatiotemporal evolution of solute transport in articular cartilage explants reveals how cartilage recovers fluid within the contact area during sliding.

PubMed

Graham, Brian T; Moore, Axel C; Burris, David L; Price, Christopher

2018-04-11

The interstitial fluid within articular cartilage shields the matrix from mechanical stresses, reduces friction and wear, enables biochemical processes, and transports solutes into and out of the avascular extracellular matrix. The balanced competition between fluid exudation and recovery under load is thus critical to the mechanical and biological functions of the tissue. We recently discovered that sliding alone can induce rapid solute transport into buried cartilage contact areas via a phenomenon termed tribological rehydration. In this study, we use in situ confocal microscopy measurements to track the spatiotemporal propagation of a small neutral solute into the buried contact area to clarify the fluid mechanics underlying the tribological rehydration phenomenon. Sliding experiments were interrupted by periodic static loading to enable scanning of the entire contact area. Spatiotemporal patterns of solute transport combined with tribological data suggested pressure driven flow through the extracellular matrix from the contact periphery rather than into the surface via a fluid film. Interestingly, these testing interruptions also revealed dynamic, repeatable and history-independent fluid loss and recovery processes consistent with those observed in vivo. Unlike the migrating contact area, which preserves hydration by moving faster than interstitial fluid can flow, our results demonstrate that the stationary contact area can maintain and actively recover hydration through a dynamic competition between load-induced exudation and sliding-induced recovery. The results demonstrate that sliding contributes to the recovery of fluid and solutes by cartilage within the contact area while clarifying the means by which it occurs. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

Diet of a piscivorous seabird reveals spatiotemporal variation in abundance of forage fishes in the Monterey Bay region

NASA Astrophysics Data System (ADS)

Webb, Lisa A.; Harvey, James T.

2015-06-01

Brandt's Cormorant (Phalacrocorax penicillatus) diet was investigated using regurgitated pellets (n = 285) collected on 19 sampling days at three locations during the 2006-07 and 2007-08 nonbreeding seasons in the Monterey Bay region. The efficacy of using nested sieves and the all-structure technique to facilitate prey detection in the pellets was evaluated, but this method did not increase prey enumeration and greatly decreased efficiency. Although 29 prey species were consumed, northern anchovy (Engraulis mordax) dominated and speckled sanddab (Citharichthys stigmaeus) also was important in the diet. Few rockfishes (Sebastes spp.) and market squid (Doryteuthis opalescens) were consumed compared with great prevalence in previous studies during the 1970s. El Niño and La Niña during the study provided a unique opportunity to examine predator response to variation in prey availability. Patterns of prey number and diversity were not consistent among locations. Greatest number and diversity of prey occurred at locations within Monterey Bay during La Niña, results not evident at the outer coast location. Short-term specialization occurred but mean prey diversity indicated a generalist feeding mode. This study demonstrated the importance of periodic sampling at multiple locations within a region to detect spatiotemporal variability in the diet of opportunistic generalists.

Spatiotemporal stochastic models for earth science and engineering applications

NASA Astrophysics Data System (ADS)

Luo, Xiaochun

1998-12-01

Spatiotemporal processes occur in many areas of earth sciences and engineering. However, most of the available theoretical tools and techniques of space-time daft processing have been designed to operate exclusively in time or in space, and the importance of spatiotemporal variability was not fully appreciated until recently. To address this problem, a systematic framework of spatiotemporal random field (S/TRF) models for geoscience/engineering applications is presented and developed in this thesis. The space-tune continuity characterization is one of the most important aspects in S/TRF modelling, where the space-time continuity is displayed with experimental spatiotemporal variograms, summarized in terms of space-time continuity hypotheses, and modelled using spatiotemporal variogram functions. Permissible spatiotemporal covariance/variogram models are addressed through permissibility criteria appropriate to spatiotemporal processes. The estimation of spatiotemporal processes is developed in terms of spatiotemporal kriging techniques. Particular emphasis is given to the singularity analysis of spatiotemporal kriging systems. The impacts of covariance, functions, trend forms, and data configurations on the singularity of spatiotemporal kriging systems are discussed. In addition, the tensorial invariance of universal spatiotemporal kriging systems is investigated in terms of the space-time trend. The conditional simulation of spatiotemporal processes is proposed with the development of the sequential group Gaussian simulation techniques (SGGS), which is actually a series of sequential simulation algorithms associated with different group sizes. The simulation error is analyzed with different covariance models and simulation grids. The simulated annealing technique honoring experimental variograms, is also proposed, providing a way of conditional simulation without the covariance model fitting which is prerequisite for most simulation algorithms. The proposed

Three-dimensional spatiotemporal focusing of holographic patterns

PubMed Central

Hernandez, Oscar; Papagiakoumou, Eirini; Tanese, Dimitrii; Fidelin, Kevin; Wyart, Claire; Emiliani, Valentina

2016-01-01

Two-photon excitation with temporally focused pulses can be combined with phase-modulation approaches, such as computer-generated holography and generalized phase contrast, to efficiently distribute light into two-dimensional, axially confined, user-defined shapes. Adding lens-phase modulations to 2D-phase holograms enables remote axial pattern displacement as well as simultaneous pattern generation in multiple distinct planes. However, the axial confinement linearly degrades with lateral shape area in previous reports where axially shifted holographic shapes were not temporally focused. Here we report an optical system using two spatial light modulators to independently control transverse- and axial-target light distribution. This approach enables simultaneous axial translation of single or multiple spatiotemporally focused patterns across the sample volume while achieving the axial confinement of temporal focusing. We use the system's capability to photoconvert tens of Kaede-expressing neurons with single-cell resolution in live zebrafish larvae. PMID:27306044

Spatiotemporal Patterns of Evapotranspiration in Response to Multiple Environmental Factors Simulated by the Community Land Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Xiaoying; Mao, Jiafu; Thornton, P.

Spatiotemporal patterns of evapotranspiration (ET) over the period from 1982 to 2008 are investigated and attributed to multiple environmental factors using the Community Land Model version 4 (CLM4). Our results show that CLM4 captures the spatial distribution and interannual variability of ET well when compared to observation-based estimates. We find that climate dominates the predicted variability in ET. Elevated atmospheric CO2 concentration also plays an important role in modulating the trend of predicted ET over most land areas, and replaces climate to function as the dominant factor controlling ET changes over the North America, South America and Asia regions. Comparedmore » to the effect of climate and CO2 concentration, the roles of other factors such as nitrogen deposition, land use change and aerosol deposition are less pronounced and regionally dependent. The aerosol deposition contribution is the third most important factor for trends of ET over Europe, while it has the smallest impact over other regions. As ET is a dominant component of the terrestrial water cycle, our results suggest that environmental factors like elevated CO2, nitrogen and aerosol depositions, and land use change, in addition to climate, could have significant impact on future projections of water resources and water cycle dynamics at global and regional scales.« less

A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nomura, K; Seymour, R; Wang, W

2009-02-17

A metascalable (or 'design once, scale on new architectures') parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials based on spatiotemporal data locality principles, which is expected to scale on emerging multipetaflops architectures. The framework consists of: (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms for high complexity problems; (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, while introducing multiple parallelization axes; and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these O(N) algorithms onto a multicore cluster based onmore » hybrid implementation combining message passing and critical section-free multithreading. The EDC-STEP-HCD framework exposes maximal concurrency and data locality, thereby achieving: (1) inter-node parallel efficiency well over 0.95 for 218 billion-atom molecular-dynamics and 1.68 trillion electronic-degrees-of-freedom quantum-mechanical simulations on 212,992 IBM BlueGene/L processors (superscalability); (2) high intra-node, multithreading parallel efficiency (nanoscalability); and (3) nearly perfect time/ensemble parallel efficiency (eon-scalability). The spatiotemporal scale covered by MD simulation on a sustained petaflops computer per day (i.e. petaflops {center_dot} day of computing) is estimated as NT = 2.14 (e.g. N = 2.14 million atoms for T = 1 microseconds).« less

Spatio-temporal scaling effects on longshore sediment transport pattern along the nearshore zone

NASA Astrophysics Data System (ADS)

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.

Sensitivity to Spatiotemporal Percepts Predicts the Perception of Emotion

PubMed Central

Castro, Vanessa L.; Boone, R. Thomas

2015-01-01

The present studies examined how sensitivity to spatiotemporal percepts such as rhythm, angularity, configuration, and force predicts accuracy in perceiving emotion. In Study 1, participants (N = 99) completed a nonverbal test battery consisting of three nonverbal emotion perception tests and two perceptual sensitivity tasks assessing rhythm sensitivity and angularity sensitivity. Study 2 (N = 101) extended the findings of Study 1 with the addition of a fourth nonverbal test, a third configural sensitivity task, and a fourth force sensitivity task. Regression analyses across both studies revealed partial support for the association between perceptual sensitivity to spatiotemporal percepts and greater emotion perception accuracy. Results indicate that accuracy in perceiving emotions may be predicted by sensitivity to specific percepts embedded within channel- and emotion-specific displays. The significance of such research lies in the understanding of how individuals acquire emotion perception skill and the processes by which distinct features of percepts are related to the perception of emotion. PMID:26339111

Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping.

PubMed

Lawson, A B; Carroll, R; Faes, C; Kirby, R S; Aregay, M; Watjou, K

2017-12-01

It is often the case that researchers wish to simultaneously explore the behavior of and estimate overall risk for multiple, related diseases with varying rarity while accounting for potential spatial and/or temporal correlation. In this paper, we propose a flexible class of multivariate spatio-temporal mixture models to fill this role. Further, these models offer flexibility with the potential for model selection as well as the ability to accommodate lifestyle, socio-economic, and physical environmental variables with spatial, temporal, or both structures. Here, we explore the capability of this approach via a large scale simulation study and examine a motivating data example involving three cancers in South Carolina. The results which are focused on four model variants suggest that all models possess the ability to recover simulation ground truth and display improved model fit over two baseline Knorr-Held spatio-temporal interaction model variants in a real data application.

Spatiotemporal Variability of Soil Hydraulic Properties from Field Data and Remote Sensing in the Walnut Gulch Experimental Watershed

NASA Astrophysics Data System (ADS)

Becker, R.; Gebremichael, M.; Marker, M.

2015-12-01

reveal several interesting features on the spatiotemporal variability of soil moisture at multiple scales, and the capabilities and limitations of remote sensing derived products in reproducing them.

High-resolution spatiotemporal strain mapping reveals non-uniform deformation in micropatterned elastomers

NASA Astrophysics Data System (ADS)

Aksoy, B.; Rehman, A.; Bayraktar, H.; Alaca, B. E.

2017-04-01

Micropatterns are generated on a vast selection of polymeric substrates for various applications ranging from stretchable electronics to cellular mechanobiological systems. When these patterned substrates are exposed to external loading, strain field is primarily affected by the presence of microfabricated structures and similarly by fabrication-related defects. The capturing of such nonhomogeneous strain fields is of utmost importance in cases where study of the mechanical behavior with a high spatial resolution is necessary. Image-based non-contact strain measurement techniques are favorable and have recently been extended to scanning tunneling microscope and scanning electron microscope images for the characterization of mechanical properties of metallic materials, e.g. steel and aluminum, at the microscale. A similar real-time analysis of strain heterogeneity in elastomers is yet to be achieved during the entire loading sequence. The available measurement methods for polymeric materials mostly depend on cross-head displacement or precalibrated strain values. Thus, they suffer either from the lack of any real-time analysis, spatiotemporal distribution or high resolution in addition to a combination of these factors. In this work, these challenges are addressed by integrating a tensile stretcher with an inverted optical microscope and developing a subpixel particle tracking algorithm. As a proof of concept, the patterns with a critical dimension of 200 µm are generated on polydimethylsiloxane substrates and strain distribution in the vicinity of the patterns is captured with a high spatiotemporal resolution. In the field of strain measurement, there is always a tradeoff between minimum measurable strain value and spatial resolution. Current noncontact techniques on elastomers can deliver a strain resolution of 0.001% over a minimum length of 5 cm. More importantly, inhomogeneities within this quite large region cannot be captured. The proposed technique can

Size-dependent diffusion promotes the emergence of spatiotemporal patterns

NASA Astrophysics Data System (ADS)

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

2014-07-01

Spatiotemporal patterns, indicating the spatiotemporal variability of individual abundance, are a pronounced scenario in ecological interactions. Most of the existing models for spatiotemporal patterns treat species as homogeneous groups of individuals with average characteristics by ignoring 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 promotes the formation of spatiotemporal patterns, by creating regular spatiotemporal patterns out of temporal chaos. We also found that size-dependent diffusion can substitute large-amplitude base harmonics with spatiotemporal patterns with lower amplitude oscillations but with enriched harmonics. Finally, 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 populations. Due to the ubiquity of individual ontogeny in natural ecosystems we conclude that diffusion variability within populations is a significant driving force for the emergence of spatiotemporal patterns. Our results offer a perspective on self-organized phenomena, and pave a way to understand such phenomena in systems organized as complex ecological networks.

Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.

PubMed

Liu, Kangkang; Zhu, Yanshan; Xia, Yao; Zhang, Yingtao; Huang, Xiaodong; Huang, Jiawei; Nie, Enqiong; Jing, Qinlong; Wang, Guoling; Yang, Zhicong; Hu, Wenbiao; Lu, Jiahai

2018-03-01

This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China. Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF. Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01). The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention.

High Spatiotemporal Resolution Prostate MRI

DTIC Science & Technology

2016-09-01

1 AD AWARD NUMBER: W81XWH-15-1-0341 TITLE: High Spatiotemporal Resolution Prostate MRI PRINCIPAL INVESTIGATOR: Stephen J. Riederer CONTRACTING...REPORT TYPE Annual 3. DATES COVERED 15 Aug 2015 - 14 Aug 2016 4. TITLE AND SUBTITLE High Spatiotemporal Resolution Prostate MRI 5a. CONTRACT NUMBER...improved means using MRI for detecting prostate cancer with the potential for differentiating disease aggressiveness. The hypothesis is that dynamic

Extracting Spatiotemporal Objects from Raster Data to Represent Physical Features and Analyze Related Processes

NASA Astrophysics Data System (ADS)

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.

Biophysical feedbacks mediate carbonate chemistry in coastal ecosystems across spatiotemporal gradients.

PubMed

Silbiger, Nyssa J; Sorte, Cascade J B

2018-01-15

Ocean acidification (OA) projections are primarily based on open ocean environments, despite the ecological importance of coastal systems in which carbonate dynamics are fundamentally different. Using temperate tide pools as a natural laboratory, we quantified the relative contribution of community composition, ecosystem metabolism, and physical attributes to spatiotemporal variability in carbonate chemistry. We found that biological processes were the primary drivers of local pH conditions. Specifically, non-encrusting producer-dominated systems had the highest and most variable pH environments and the highest production rates, patterns that were consistent across sites spanning 11° of latitude and encompassing multiple gradients of natural variability. Furthermore, we demonstrated a biophysical feedback loop in which net community production increased pH, leading to higher net ecosystem calcification. Extreme spatiotemporal variability in pH is, thus, both impacting and driven by biological processes, indicating that shifts in community composition and ecosystem metabolism are poised to locally buffer or intensify the effects of OA.

Spatiotemporal patterns of evapotranspiration along the North American east coast as influenced by multiple environmental changes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Qichun; Tian, Hanqin; Li, Xia

The North American east coast has experienced significant land-use and climate changes since the beginning of the 20th century. In this study, using the Dynamic Land Ecosystem Model 2.0 driven by time-series input data of land use, climate and atmospheric CO 2, we examined how these driving forces have affected the spatiotemporal trends and variability of evapotranspiration (ET) in this region during 1901–2008. Annual ET in the North American east coast during this period was 648.3 ± 38.6 mm/year and demonstrated an increasing trend. Factorial model simulations indicated that climate variability explained 76% of the inter-annual ET variability. Although land-usemore » change only explained 16% of the ET temporal variability, afforestation induced the upward trend of ET and increased annual ET by 12.8 mm/year. Elevated atmospheric CO 2 reduced annual ET by 0.84 mm, and its potential impacts under future atmospheric CO 2 levels could be much larger than estimates for the historical 1901–2008 period. Climate change determined the spatial pattern of ET changes across the entire study area, whereas land-use changes dramatically affected ET in watersheds with significant land conversions. In spite of the multiple benefits from afforestation, its impacts on water resources should be considered in future land-use policy making. As a result, elevated ET may also affect fresh water availability for the increasing social and economic water demands.« less

Spatiotemporal patterns of evapotranspiration along the North American east coast as influenced by multiple environmental changes

DOE PAGES

Yang, Qichun; Tian, Hanqin; Li, Xia; ...

2014-08-08

The North American east coast has experienced significant land-use and climate changes since the beginning of the 20th century. In this study, using the Dynamic Land Ecosystem Model 2.0 driven by time-series input data of land use, climate and atmospheric CO 2, we examined how these driving forces have affected the spatiotemporal trends and variability of evapotranspiration (ET) in this region during 1901–2008. Annual ET in the North American east coast during this period was 648.3 ± 38.6 mm/year and demonstrated an increasing trend. Factorial model simulations indicated that climate variability explained 76% of the inter-annual ET variability. Although land-usemore » change only explained 16% of the ET temporal variability, afforestation induced the upward trend of ET and increased annual ET by 12.8 mm/year. Elevated atmospheric CO 2 reduced annual ET by 0.84 mm, and its potential impacts under future atmospheric CO 2 levels could be much larger than estimates for the historical 1901–2008 period. Climate change determined the spatial pattern of ET changes across the entire study area, whereas land-use changes dramatically affected ET in watersheds with significant land conversions. In spite of the multiple benefits from afforestation, its impacts on water resources should be considered in future land-use policy making. As a result, elevated ET may also affect fresh water availability for the increasing social and economic water demands.« less

Multi-Spatiotemporal Patterns of Residential Burglary Crimes in Chicago: 2006-2016

NASA Astrophysics Data System (ADS)

Luo, J.

2017-10-01

This research attempts to explore the patterns of burglary crimes at multi-spatiotemporal scales in Chicago between 2006 and 2016. Two spatial scales are investigated that are census block and police beat area. At each spatial scale, three temporal scales are integrated to make spatiotemporal slices: hourly scale with two-hour time step from 12:00am to the end of the day; daily scale with one-day step from Sunday to Saturday within a week; monthly scale with one-month step from January to December. A total of six types of spatiotemporal slices will be created as the base for the analysis. Burglary crimes are spatiotemporally aggregated to spatiotemporal slices based on where and when they occurred. For each type of spatiotemporal slices with burglary occurrences integrated, spatiotemporal neighborhood will be defined and managed in a spatiotemporal matrix. Hot-spot analysis will identify spatiotemporal clusters of each type of spatiotemporal slices. Spatiotemporal trend analysis is conducted to indicate how the clusters shift in space and time. The analysis results will provide helpful information for better target policing and crime prevention policy such as police patrol scheduling regarding times and places covered.

Phenology Data Products to Support Assessment and Forecasting of Phenology on Multiple Spatiotemporal Scales

NASA Astrophysics Data System (ADS)

Gerst, K.; Enquist, C.; Rosemartin, A.; Denny, E. G.; Marsh, L.; Moore, D. J.; Weltzin, J. F.

2014-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) serves science and society by promoting a broad understanding of plant and animal phenology and the relationships among phenological patterns and environmental change. The National Phenology Database maintained by USA-NPN now has over 3.7 million records for plants and animals for the period 1954-2014, with the majority of these observations collected since 2008 as part of a broad, national contributory science strategy. These data have been used in a number of science, conservation and resource management applications, including national assessments of historical and potential future trends in phenology, regional assessments of spatio-temporal variation in organismal activity, and local monitoring for invasive species detection. Customizable data downloads are freely available, and data are accompanied by FGDC-compliant metadata, data-use and data-attribution policies, vetted and documented methodologies and protocols, and version control. While users are free to develop custom algorithms for data cleaning, winnowing and summarization prior to analysis, the National Coordinating Office of USA-NPN is developing a suite of standard data products to facilitate use and application by a diverse set of data users. This presentation provides a progress report on data product development, including: (1) Quality controlled raw phenophase status data; (2) Derived phenometrics (e.g. onset, duration) at multiple scales; (3) Data visualization tools; (4) Tools to support assessment of species interactions and overlap; (5) Species responsiveness to environmental drivers; (6) Spatially gridded phenoclimatological products; and (7) Algorithms for modeling and forecasting future phenological responses. The prioritization of these data products is a direct response to stakeholder needs related to informing management and policy decisions. We anticipate that these products will contribute to broad understanding of plant

High Spatiotemporal Resolution Prostate MRI

DTIC Science & Technology

2017-09-01

AWARD NUMBER: W81XWH-15-1-0341 TITLE: High Spatiotemporal Resolution Prostate MRI PRINCIPAL INVESTIGATOR: Stephen J. Riederer, Ph.D...views, opinions and/or findings contained in this report are those of the author(s) and should not be construed as an official Department of the Army...ADDRESS. 1. REPORT DATE September 2017 2. REPORT TYPE Annual 3. DATES COVERED 15 Aug 2016 - 14 Aug 2017 4. TITLE AND SUBTITLE High Spatiotemporal

Collaborative simulation method with spatiotemporal synchronization process control

NASA Astrophysics Data System (ADS)

Zou, Yisheng; Ding, Guofu; Zhang, Weihua; Zhang, Jian; Qin, Shengfeng; Tan, John Kian

2016-10-01

When designing a complex mechatronics system, such as high speed trains, it is relatively difficult to effectively simulate the entire system's dynamic behaviors because it involves multi-disciplinary subsystems. Currently,a most practical approach for multi-disciplinary simulation is interface based coupling simulation method, but it faces a twofold challenge: spatial and time unsynchronizations among multi-directional coupling simulation of subsystems. A new collaborative simulation method with spatiotemporal synchronization process control is proposed for coupling simulating a given complex mechatronics system across multiple subsystems on different platforms. The method consists of 1) a coupler-based coupling mechanisms to define the interfacing and interaction mechanisms among subsystems, and 2) a simulation process control algorithm to realize the coupling simulation in a spatiotemporal synchronized manner. The test results from a case study show that the proposed method 1) can certainly be used to simulate the sub-systems interactions under different simulation conditions in an engineering system, and 2) effectively supports multi-directional coupling simulation among multi-disciplinary subsystems. This method has been successfully applied in China high speed train design and development processes, demonstrating that it can be applied in a wide range of engineering systems design and simulation with improved efficiency and effectiveness.

The spatiotemporal order of signaling events unveils the logic of development signaling.

PubMed

Zhu, Hao; Owen, Markus R; Mao, Yanlan

2016-08-01

Animals from worms and insects to birds and mammals show distinct body plans; however, the embryonic development of diverse body plans with tissues and organs within is controlled by a surprisingly few signaling pathways. It is well recognized that combinatorial use of and dynamic interactions among signaling pathways follow specific logic to control complex and accurate developmental signaling and patterning, but it remains elusive what such logic is, or even, what it looks like. We have developed a computational model for Drosophila eye development with innovated methods to reveal how interactions among multiple pathways control the dynamically generated hexagonal array of R8 cells. We obtained two novel findings. First, the coupling between the long-range inductive signals produced by the proneural Hh signaling and the short-range restrictive signals produced by the antineural Notch and EGFR signaling is essential for generating accurately spaced R8s. Second, the spatiotemporal orders of key signaling events reveal a robust pattern of lateral inhibition conducted by Ato-coordinated Notch and EGFR signaling to collectively determine R8 patterning. This pattern, stipulating the orders of signaling and comparable to the protocols of communication, may help decipher the well-appreciated but poorly defined logic of developmental signaling. The model is available upon request. hao.zhu@ymail.com Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

The spatiotemporal order of signaling events unveils the logic of development signaling

PubMed Central

Zhu, Hao; Owen, Markus R.; Mao, Yanlan

2016-01-01

Motivation: Animals from worms and insects to birds and mammals show distinct body plans; however, the embryonic development of diverse body plans with tissues and organs within is controlled by a surprisingly few signaling pathways. It is well recognized that combinatorial use of and dynamic interactions among signaling pathways follow specific logic to control complex and accurate developmental signaling and patterning, but it remains elusive what such logic is, or even, what it looks like. Results: We have developed a computational model for Drosophila eye development with innovated methods to reveal how interactions among multiple pathways control the dynamically generated hexagonal array of R8 cells. We obtained two novel findings. First, the coupling between the long-range inductive signals produced by the proneural Hh signaling and the short-range restrictive signals produced by the antineural Notch and EGFR signaling is essential for generating accurately spaced R8s. Second, the spatiotemporal orders of key signaling events reveal a robust pattern of lateral inhibition conducted by Ato-coordinated Notch and EGFR signaling to collectively determine R8 patterning. This pattern, stipulating the orders of signaling and comparable to the protocols of communication, may help decipher the well-appreciated but poorly defined logic of developmental signaling. Availability and implementation: The model is available upon request. Contact: hao.zhu@ymail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153573

New type of chimera and mutual synchronization of spatiotemporal structures in two coupled ensembles of nonlocally interacting chaotic maps

NASA Astrophysics Data System (ADS)

Bukh, Andrei; Rybalova, Elena; Semenova, Nadezhda; Strelkova, Galina; Anishchenko, Vadim

2017-11-01

We study numerically the dynamics of a network made of two coupled one-dimensional ensembles of discrete-time systems. The first ensemble is represented by a ring of nonlocally coupled Henon maps and the second one by a ring of nonlocally coupled Lozi maps. We find that the network of coupled ensembles can realize all the spatio-temporal structures which are observed both in the Henon map ensemble and in the Lozi map ensemble while uncoupled. Moreover, we reveal a new type of spatiotemporal structure, a solitary state chimera, in the considered network. We also establish and describe the effect of mutual synchronization of various complex spatiotemporal patterns in the system of two coupled ensembles of Henon and Lozi maps.

Optical Kerr spatiotemporal dark extreme waves

NASA Astrophysics Data System (ADS)

Wabnitz, Stefan; Kodama, Yuji; Baronio, Fabio

2018-02-01

We study the existence and propagation of multidimensional dark non-diffractive and non-dispersive spatiotemporal optical wave-packets in nonlinear Kerr media. We report analytically and confirm numerically the properties of spatiotemporal dark lines, X solitary waves and lump solutions of the (2 + 1)D nonlinear Schr odinger equation (NLSE). Dark lines, X waves and lumps represent holes of light on a continuous wave background. These solitary waves are derived by exploiting the connection between the (2 + 1)D NLSE and a well-known equation of hydrodynamics, namely the (2+1)D Kadomtsev-Petviashvili (KP) equation. This finding opens a novel path for the excitation and control of spatiotemporal optical solitary and rogue waves, of hydrodynamic nature.

Spatio-temporal hotspots of satellite-tracked arctic foxes reveal a large detection range in a mammalian predator.

PubMed

Lai, Sandra; Bêty, Joël; Berteaux, Dominique

2015-01-01

The scale at which animals perceive their environment is a strong fitness determinant, yet few empirical estimates of animal detection ranges exist, especially in mammalian predators. Using daily Argos satellite tracking of 26 adult arctic foxes (Vulpes lagopus) during a single winter in the High Canadian Arctic, we investigated the detection range of arctic foxes by detecting hotspots of fox activity on the sea ice. While maintaining territories in the tundra, these solitary foragers occasionally used the sea ice where they sometimes formed spatio-temporal hotspots, likely scavenging on marine mammal carcasses. We detected 35 movements by 13 individuals forming five hotspots. Foxes often traveled more than 10 km, and up to 40 km, to reach hotspots, which lasted one-two weeks and could gather up to 12 individuals. The likelihood of a fox joining a hotspot was neither influenced by its distance from the hotspot nor by the distance of its home range to the coast. Observed traveling distances may indicate a high detection range in arctic foxes, and our results suggest their ability to detect food sources on the sea ice from their terrestrial home range. While revealing a wide knowledge gap regarding resource detection abilities in mammalian predators, our study provides estimates of detection range useful for interpreting and modeling animal movements. It also allows a better understanding of foraging behavior and navigation capacity in terrestrial predators.

The Voronoi spatio-temporal data structure

NASA Astrophysics Data System (ADS)

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

World Spatiotemporal Analytics and Mapping Project (wstamp): Discovering, Exploring, and Mapping Spatiotemporal Patterns across the World's Largest Open Soruce Data Sets

NASA Astrophysics Data System (ADS)

Stewart, R.; Piburn, J.; Sorokine, A.; Myers, A.; Moehl, J.; White, D.

2015-07-01

The application of spatiotemporal (ST) analytics to integrated data from major sources such as the World Bank, United Nations, and dozens of others holds tremendous potential for shedding new light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. 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, and changing attributes, as well as 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 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 10,000+ attributes covering over 200 nation states spanning 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 discuss the status of this work and report on major findings.

Spatio-temporal Bayesian model selection for disease mapping

PubMed Central

Carroll, R; Lawson, AB; Faes, C; Kirby, RS; Aregay, M; Watjou, K

2016-01-01

Spatio-temporal analysis of small area health data often involves choosing a fixed set of predictors prior to the final model fit. In this paper, we propose a spatio-temporal approach of Bayesian model selection to implement model selection for certain areas of the study region as well as certain years in the study time line. Here, we examine the usefulness of this approach by way of a large-scale simulation study accompanied by a case study. Our results suggest that a special case of the model selection methods, a mixture model allowing a weight parameter to indicate if the appropriate linear predictor is spatial, spatio-temporal, or a mixture of the two, offers the best option to fitting these spatio-temporal models. In addition, the case study illustrates the effectiveness of this mixture model within the model selection setting by easily accommodating lifestyle, socio-economic, and physical environmental variables to select a predominantly spatio-temporal linear predictor. PMID:28070156

Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China

PubMed Central

Xia, Yao; Zhang, Yingtao; Huang, Xiaodong; Huang, Jiawei; Nie, Enqiong; Jing, Qinlong; Wang, Guoling; Yang, Zhicong; Hu, Wenbiao

2018-01-01

Background This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China. Methods Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF. Results Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01). Conclusions The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention. PMID:29561835

Multimodal imaging of repetition priming: Using fMRI, MEG, and intracranial EEG to reveal spatiotemporal profiles of word processing.

PubMed

McDonald, Carrie R; Thesen, Thomas; Carlson, Chad; Blumberg, Mark; Girard, Holly M; Trongnetrpunya, Amy; Sherfey, Jason S; Devinsky, Orrin; Kuzniecky, Rubin; Dolye, Werner K; Cash, Sydney S; Leonard, Matthew K; Hagler, Donald J; Dale, Anders M; Halgren, Eric

2010-11-01

Repetition priming is a core feature of memory processing whose anatomical correlates remain poorly understood. In this study, we use advanced multimodal imaging (functional magnetic resonance imaging (fMRI) and magnetoencephalography; MEG) to investigate the spatiotemporal profile of repetition priming. We use intracranial electroencephalography (iEEG) to validate our fMRI/MEG measurements. Twelve controls completed a semantic judgment task with fMRI and MEG that included words presented once (new, 'N') and words that repeated (old, 'O'). Six patients with epilepsy completed the same task during iEEG recordings. Blood-oxygen level dependent (BOLD) responses for N vs. O words were examined across the cortical surface and within regions of interest. MEG waveforms for N vs. O words were estimated using a noise-normalized minimum norm solution, and used to interpret the timecourse of fMRI. Spatial concordance was observed between fMRI and MEG repetition effects from 350 to 450 ms within bilateral occipitotemporal and medial temporal, left prefrontal, and left posterior temporal cortex. Additionally, MEG revealed widespread sources within left temporoparietal regions, whereas fMRI revealed bilateral reductions in occipitotemporal and left superior frontal, and increases in inferior parietal, precuneus, and dorsolateral prefrontal activity. BOLD suppression in left posterior temporal, left inferior prefrontal, and right occipitotemporal cortex correlated with MEG repetition-related reductions. IEEG responses from all three regions supported the timecourse of MEG and localization of fMRI. Furthermore, iEEG decreases to repeated words were associated with decreased gamma power in several regions, providing evidence that gamma oscillations are tightly coupled to cognitive phenomena and reflect regional activations seen in the BOLD signal. Copyright 2010 Elsevier Inc. All rights reserved.

Multimodal imaging of repetition priming: Using fMRI, MEG, and intracranial EEG to reveal spatiotemporal profiles of word processing

PubMed Central

McDonald, Carrie R.; Thesen, Thomas; Carlson, Chad; Blumberg, Mark; Girard, Holly M.; Trongnetrpunya, Amy; Sherfey, Jason S.; Devinsky, Orrin; Kuzniecky, Rubin; Dolye, Werner K.; Cash, Sydney S.; Leonard, Matt K.; Hagler, Donald J.; Dale, Anders M.; Halgren, Eric

2010-01-01

Repetition priming is a core feature of memory processing whose anatomical correlates remain poorly understood. In this study, we use advanced multimodal imaging (functional magnetic resonance imaging (fMRI) and magnetoencephalography; MEG) to investigate the spatiotemporal profile of repetition priming. We use intracranial electroencephalography (iEEG) to validate our fMRI/MEG measurements. Twelve controls completed a semantic judgment task with fMRI and MEG that included words presented once (new, ‘N’) and words that repeated (old, ‘O’). Six patients with epilepsy completed the same task during iEEG recordings. Blood-oxygen level dependent (BOLD) responses for N vs O words were examined across the cortical surface and within regions of interest. MEG waveforms for N vs O words were estimated using a noise-normalized minimum norm solution, and used to interpret the timecourse of fMRI. Spatial concordance was observed between fMRI and MEG repetition effects from 350–450ms within bilateral occipitotemporal and medial temporal, left prefrontal, and left posterior temporal cortex. Additionally, MEG revealed widespread sources within left temporoparietal regions, whereas fMRI revealed bilateral reductions in occipitotemporal and left superior frontal, and increases in inferior parietal, precuneus, and dorsolateral prefrontal activity. BOLD suppression in left posterior temporal, left inferior prefrontal, and right occipitotemporal cortex correlated with MEG repetition-related reductions. IEEG responses from all three regions supported the timecourse of MEG and localization of fMRI. Furthermore, iEEG decreases to repeated words were associated with decreased gamma power in several regions, providing evidence that gamma oscillations are tightly coupled to cognitive phenomena and reflect regional activations seen in the BOLD signal. PMID:20620212

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

NASA Astrophysics Data System (ADS)

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.

Microclimate Data Improve Predictions of Insect Abundance Models Based on Calibrated Spatiotemporal Temperatures.

PubMed

Rebaudo, François; Faye, Emile; Dangles, Olivier

2016-01-01

A large body of literature has recently recognized the role of microclimates in controlling the physiology and ecology of species, yet the relevance of fine-scale climatic data for modeling species performance and distribution remains a matter of debate. Using a 6-year monitoring of three potato moth species, major crop pests in the tropical Andes, we asked whether the spatiotemporal resolution of temperature data affect the predictions of models of moth performance and distribution. For this, we used three different climatic data sets: (i) the WorldClim dataset (global dataset), (ii) air temperature recorded using data loggers (weather station dataset), and (iii) air crop canopy temperature (microclimate dataset). We developed a statistical procedure to calibrate all datasets to monthly and yearly variation in temperatures, while keeping both spatial and temporal variances (air monthly temperature at 1 km² for the WorldClim dataset, air hourly temperature for the weather station, and air minute temperature over 250 m radius disks for the microclimate dataset). Then, we computed pest performances based on these three datasets. Results for temperature ranging from 9 to 11°C revealed discrepancies in the simulation outputs in both survival and development rates depending on the spatiotemporal resolution of the temperature dataset. Temperature and simulated pest performances were then combined into multiple linear regression models to compare predicted vs. field data. We used an additional set of study sites to test the ability of the results of our model to be extrapolated over larger scales. Results showed that the model implemented with microclimatic data best predicted observed pest abundances for our study sites, but was less accurate than the global dataset model when performed at larger scales. Our simulations therefore stress the importance to consider different temperature datasets depending on the issue to be solved in order to accurately predict species

Microclimate Data Improve Predictions of Insect Abundance Models Based on Calibrated Spatiotemporal Temperatures

PubMed Central

Rebaudo, François; Faye, Emile; Dangles, Olivier

2016-01-01

A large body of literature has recently recognized the role of microclimates in controlling the physiology and ecology of species, yet the relevance of fine-scale climatic data for modeling species performance and distribution remains a matter of debate. Using a 6-year monitoring of three potato moth species, major crop pests in the tropical Andes, we asked whether the spatiotemporal resolution of temperature data affect the predictions of models of moth performance and distribution. For this, we used three different climatic data sets: (i) the WorldClim dataset (global dataset), (ii) air temperature recorded using data loggers (weather station dataset), and (iii) air crop canopy temperature (microclimate dataset). We developed a statistical procedure to calibrate all datasets to monthly and yearly variation in temperatures, while keeping both spatial and temporal variances (air monthly temperature at 1 km² for the WorldClim dataset, air hourly temperature for the weather station, and air minute temperature over 250 m radius disks for the microclimate dataset). Then, we computed pest performances based on these three datasets. Results for temperature ranging from 9 to 11°C revealed discrepancies in the simulation outputs in both survival and development rates depending on the spatiotemporal resolution of the temperature dataset. Temperature and simulated pest performances were then combined into multiple linear regression models to compare predicted vs. field data. We used an additional set of study sites to test the ability of the results of our model to be extrapolated over larger scales. Results showed that the model implemented with microclimatic data best predicted observed pest abundances for our study sites, but was less accurate than the global dataset model when performed at larger scales. Our simulations therefore stress the importance to consider different temperature datasets depending on the issue to be solved in order to accurately predict species

Spatiotemporal canards in neural field equations

NASA Astrophysics Data System (ADS)

Avitabile, D.; Desroches, M.; Knobloch, E.

2017-04-01

Canards are special solutions to ordinary differential equations that follow invariant repelling slow manifolds for long time intervals. In realistic biophysical single-cell models, canards are responsible for several complex neural rhythms observed experimentally, but their existence and role in spatially extended systems is largely unexplored. We identify and describe a type of coherent structure in which a spatial pattern displays temporal canard behavior. Using interfacial dynamics and geometric singular perturbation theory, we classify spatiotemporal canards and give conditions for the existence of folded-saddle and folded-node canards. We find that spatiotemporal canards are robust to changes in the synaptic connectivity and firing rate. The theory correctly predicts the existence of spatiotemporal canards with octahedral symmetry in a neural field model posed on the unit sphere.

Spatiotemporal dynamics and optical vortices in a photorefractive phase-conjugate resonator

NASA Technical Reports Server (NTRS)

Liu, Siuying Raymond; Indebetouw, Guy

1992-01-01

A truncated modal expansion approach is used to study the spatiotemporal dynamics of a phase-conjugate resonator as a function of Bragg detuning. The numerical results reveal a rich variety of behaviors. Emphasis is given to the spatial distribution of optical vortices, their trajectories and their relationship to the beam's spatial coherence. The limitations of the model are discussed and experimental results are presented for comparison with the model's predictions and assessment of its soundness.

VAUD: A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data.

PubMed

Chen, Wei; Huang, Zhaosong; Wu, Feiran; Zhu, Minfeng; Guan, Huihua; Maciejewski, Ross

2017-10-02

Urban data is massive, heterogeneous, and spatio-temporal, posing a substantial challenge for visualization and analysis. In this paper, we design and implement a novel visual analytics approach, Visual Analyzer for Urban Data (VAUD), that supports the visualization, querying, and exploration of urban data. Our approach allows for cross-domain correlation from multiple data sources by leveraging spatial-temporal and social inter-connectedness features. Through our approach, the analyst is able to select, filter, aggregate across multiple data sources and extract information that would be hidden to a single data subset. To illustrate the effectiveness of our approach, we provide case studies on a real urban dataset that contains the cyber-, physical-, and socialinformation of 14 million citizens over 22 days.

Spatio-temporal networks: reachability, centrality and robustness.

PubMed

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.

Selecting a separable parametric spatiotemporal covariance structure for longitudinal imaging data.

PubMed

George, Brandon; Aban, Inmaculada

2015-01-15

Longitudinal imaging studies allow great insight into how the structure and function of a subject's internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures and the spatial from the outcomes of interest being observed at multiple points in a patient's body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on types I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be performed in practice, as well as how covariance structure choice can change inferences about fixed effects. Copyright © 2014 John Wiley & Sons, Ltd.

Selecting a Separable Parametric Spatiotemporal Covariance Structure for Longitudinal Imaging Data

PubMed Central

George, Brandon; Aban, Inmaculada

2014-01-01

Longitudinal imaging studies allow great insight into how the structure and function of a subject’s internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures, and the spatial from the outcomes of interest being observed at multiple points in a patients body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on Type I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the Type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be done in practice, as well as how covariance structure choice can change inferences about fixed effects. PMID:25293361

Spatio-Temporal Process Variability in Watershed Scale Wetland Restoration Planning

NASA Astrophysics Data System (ADS)

Evenson, G. R.

2012-12-01

Watershed scale restoration decision making processes are increasingly informed by quantitative methodologies providing site-specific restoration recommendations - sometimes referred to as "systematic planning." The more advanced of these methodologies are characterized by a coupling of search algorithms and ecological models to discover restoration plans that optimize environmental outcomes. Yet while these methods have exhibited clear utility as decision support toolsets, they may be critiqued for flawed evaluations of spatio-temporally variable processes fundamental to watershed scale restoration. Hydrologic and non-hydrologic mediated process connectivity along with post-restoration habitat dynamics, for example, are commonly ignored yet known to appreciably affect restoration outcomes. This talk will present a methodology to evaluate such spatio-temporally complex processes in the production of watershed scale wetland restoration plans. Using the Tuscarawas Watershed in Eastern Ohio as a case study, a genetic algorithm will be coupled with the Soil and Water Assessment Tool (SWAT) to reveal optimal wetland restoration plans as measured by their capacity to maximize nutrient reductions. Then, a so-called "graphical" representation of the optimization problem will be implemented in-parallel to promote hydrologic and non-hydrologic mediated connectivity amongst existing wetlands and sites selected for restoration. Further, various search algorithm mechanisms will be discussed as a means of accounting for temporal complexities such as post-restoration habitat dynamics. Finally, generalized patterns of restoration plan optimality will be discussed as an alternative and possibly superior decision support toolset given the complexity and stochastic nature of spatio-temporal process variability.

Spatiotemporal assessment and trade-offs of multiple ecosystem services based on land use changes in Zengcheng, China.

PubMed

Sun, Xiao; Li, Feng

2017-12-31

Driven by rapid urbanization, land use change has become a significant factor influencing ecosystem services (ESs). To support the decision-making process of city planners and policy makers, assessing the spatiotemporal changes associated with multiple ESs is vital. In this study, we developed a general structure to assess the changes of multiple ESs in Zengcheng, China. A new index also was developed to measure the comprehensive ecosystem service (CES). Trade-offs of various ESs were analyzed by using correlation analysis. We then designed four alternate scenarios to explore the optimal land use strategies to increase the CES value and minimize trade-offs among various ESs. Results demonstrated that rapid expansion of built-up land and traffic land resulted in a decrease of CES in Zengcheng from 2003 to 2013. Although the water supply, water purification, and vegetable and fruit production services increased, the climate regulation, soil conservation, biodiversity protection, recreation opportunity and grain production services decreased during the ten-year period. Government should implement land use policies and ecological engineering measures to improve soil conservation in the northern region; recreation opportunity in the central region; and carbon storage, water purification, biodiversity protection and recreation opportunity in the southern region. Among all alternative scenarios, woodland buffer and soil conservation scenarios exhibit the highest CES values, indicating that policies such as the "Ecological corridor construction" project and the "Grain for Green" project should be implemented. However, a caveat is that these policies improve the ESs at the expense of food production due to significant trade-off relationships. To minimize the trade-offs, a more sustainable intensification of agriculture should be adopted to increase food production without decreasing other ESs or occupying additional land. The land use strategies and ecological engineering

Atomistic observation and simulation analysis of spatio-temporal fluctuations during radiation-induced amorphization.

PubMed

Watanabe, Seiichi; Hoshino, Misaki; Koike, Takuto; Suda, Takanori; Ohnuki, Soumei; Takahashi, Heishichirou; Lam, Nighi Q

2003-01-01

We performed a dynamical-atomistic study of radiation-induced amorphization in the NiTi intermetallic compound using in situ high-resolution high-voltage electron microscopy and molecular dynamics simulations in connection with image simulation. Spatio-temporal fluctuations as non-equilibrium fluctuations in an energy-dissipative system, due to transient atom-cluster formation during amorphization, were revealed by the present spatial autocorrelation analysis.

A rigorous statistical framework for spatio-temporal pollution prediction and estimation of its long-term impact on health.

PubMed

Lee, Duncan; Mukhopadhyay, Sabyasachi; Rushworth, Alastair; Sahu, Sujit K

2017-04-01

In the United Kingdom, air pollution is linked to around 40000 premature deaths each year, but estimating its health effects is challenging in a spatio-temporal study. The challenges include spatial misalignment between the pollution and disease data; uncertainty in the estimated pollution surface; and complex residual spatio-temporal autocorrelation in the disease data. This article develops a two-stage model that addresses these issues. The first stage is a spatio-temporal fusion model linking modeled and measured pollution data, while the second stage links these predictions to the disease data. The methodology is motivated by a new five-year study investigating the effects of multiple pollutants on respiratory hospitalizations in England between 2007 and 2011, using pollution and disease data relating to local and unitary authorities on a monthly time scale. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Modelling spatiotemporal change using multidimensional arrays Meng

NASA Astrophysics Data System (ADS)

Lu, Meng; Appel, Marius; Pebesma, Edzer

2017-04-01

The large variety of remote sensors, model simulations, and in-situ records provide great opportunities to model environmental change. The massive amount of high-dimensional data calls for methods to integrate data from various sources and to analyse spatiotemporal and thematic information jointly. An array is a collection of elements ordered and indexed in arbitrary dimensions, which naturally represent spatiotemporal phenomena that are identified by their geographic locations and recording time. In addition, array regridding (e.g., resampling, down-/up-scaling), dimension reduction, and spatiotemporal statistical algorithms are readily applicable to arrays. However, the role of arrays in big geoscientific data analysis has not been systematically studied: How can arrays discretise continuous spatiotemporal phenomena? How can arrays facilitate the extraction of multidimensional information? How can arrays provide a clean, scalable and reproducible change modelling process that is communicable between mathematicians, computer scientist, Earth system scientist and stakeholders? This study emphasises on detecting spatiotemporal change using satellite image time series. Current change detection methods using satellite image time series commonly analyse data in separate steps: 1) forming a vegetation index, 2) conducting time series analysis on each pixel, and 3) post-processing and mapping time series analysis results, which does not consider spatiotemporal correlations and ignores much of the spectral information. Multidimensional information can be better extracted by jointly considering spatial, spectral, and temporal information. To approach this goal, we use principal component analysis to extract multispectral information and spatial autoregressive models to account for spatial correlation in residual based time series structural change modelling. We also discuss the potential of multivariate non-parametric time series structural change methods, hierarchical

[Exome sequencing revealed Allan-Herndon-Dudley syndrome underlying multiple disabilities].

PubMed

Arvio, Maria; Philips, Anju K; Ahvenainen, Minna; Somer, Mirja; Kalscheuer, Vera; Järvelä, Irma

2014-01-01

Normal function of the thyroid gland is the cornerstone of a child's mental development and physical growth. We describe a Finnish family, in which the diagnosis of three brothers became clear after investigations that lasted for more than 30 years. Two of the sons have already died. DNA analysis of the third one, a 16-year-old boy, revealed in exome sequencing of the complete X chromosome a mutation in the SLC16A2 gene, i.e. MCT8, coding for a thyroid hormone transport protein. Allan-Herndon-Dudley syndrome was thus shown to be the cause of multiple disabilities.

Using spatiotemporal statistical models to estimate animal abundance and infer ecological dynamics from survey counts

USGS Publications Warehouse

Conn, Paul B.; Johnson, Devin S.; Ver Hoef, Jay M.; Hooten, Mevin B.; London, Joshua M.; Boveng, Peter L.

2015-01-01

Ecologists often fit models to survey data to estimate and explain variation in animal abundance. Such models typically require that animal density remains constant across the landscape where sampling is being conducted, a potentially problematic assumption for animals inhabiting dynamic landscapes or otherwise exhibiting considerable spatiotemporal variation in density. We review several concepts from the burgeoning literature on spatiotemporal statistical models, including the nature of the temporal structure (i.e., descriptive or dynamical) and strategies for dimension reduction to promote computational tractability. We also review several features as they specifically relate to abundance estimation, including boundary conditions, population closure, choice of link function, and extrapolation of predicted relationships to unsampled areas. We then compare a suite of novel and existing spatiotemporal hierarchical models for animal count data that permit animal density to vary over space and time, including formulations motivated by resource selection and allowing for closed populations. We gauge the relative performance (bias, precision, computational demands) of alternative spatiotemporal models when confronted with simulated and real data sets from dynamic animal populations. For the latter, we analyze spotted seal (Phoca largha) counts from an aerial survey of the Bering Sea where the quantity and quality of suitable habitat (sea ice) changed dramatically while surveys were being conducted. Simulation analyses suggested that multiple types of spatiotemporal models provide reasonable inference (low positive bias, high precision) about animal abundance, but have potential for overestimating precision. Analysis of spotted seal data indicated that several model formulations, including those based on a log-Gaussian Cox process, had a tendency to overestimate abundance. By contrast, a model that included a population closure assumption and a scale prior on total

Agent-based modeling of autophagy reveals emergent regulatory behavior of spatio-temporal autophagy dynamics.

PubMed

Börlin, Christoph S; Lang, Verena; Hamacher-Brady, Anne; Brady, Nathan R

2014-09-10

Autophagy is a vesicle-mediated pathway for lysosomal degradation, essential under basal and stressed conditions. Various cellular components, including specific proteins, protein aggregates, organelles and intracellular pathogens, are targets for autophagic degradation. Thereby, autophagy controls numerous vital physiological and pathophysiological functions, including cell signaling, differentiation, turnover of cellular components and pathogen defense. Moreover, autophagy enables the cell to recycle cellular components to metabolic substrates, thereby permitting prolonged survival under low nutrient conditions. Due to the multi-faceted roles for autophagy in maintaining cellular and organismal homeostasis and responding to diverse stresses, malfunction of autophagy contributes to both chronic and acute pathologies. We applied a systems biology approach to improve the understanding of this complex cellular process of autophagy. All autophagy pathway vesicle activities, i.e. creation, movement, fusion and degradation, are highly dynamic, temporally and spatially, and under various forms of regulation. We therefore developed an agent-based model (ABM) to represent individual components of the autophagy pathway, subcellular vesicle dynamics and metabolic feedback with the cellular environment, thereby providing a framework to investigate spatio-temporal aspects of autophagy regulation and dynamic behavior. The rules defining our ABM were derived from literature and from high-resolution images of autophagy markers under basal and activated conditions. Key model parameters were fit with an iterative method using a genetic algorithm and a predefined fitness function. From this approach, we found that accurate prediction of spatio-temporal behavior required increasing model complexity by implementing functional integration of autophagy with the cellular nutrient state. The resulting model is able to reproduce short-term autophagic flux measurements (up to 3�

Spatio-temporal Organization During Ventricular Fibrillation in the Human Heart.

PubMed

Robson, Jinny; Aram, Parham; Nash, Martyn P; Bradley, Chris P; Hayward, Martin; Paterson, David J; Taggart, Peter; Clayton, Richard H; Kadirkamanathan, Visakan

2018-06-01

In this paper, we present a novel approach to quantify the spatio-temporal organization of electrical activation during human ventricular fibrillation (VF). We propose three different methods based on correlation analysis, graph theoretical measures and hierarchical clustering. Using the proposed approach, we quantified the level of spatio-temporal organization during three episodes of VF in ten patients, recorded using multi-electrode epicardial recordings with 30 s coronary perfusion, 150 s global myocardial ischaemia and 30 s reflow. Our findings show a steady decline in spatio-temporal organization from the onset of VF with coronary perfusion. We observed transient increases in spatio-temporal organization during global myocardial ischaemia. However, the decline in spatio-temporal organization continued during reflow. Our results were consistent across all patients, and were consistent with the numbers of phase singularities. Our findings show that the complex spatio-temporal patterns can be studied using complex network analysis.

Gait Profile Score in multiple sclerosis patients with low disability.

PubMed

Morel, Eric; Allali, Gilles; Laidet, Magali; Assal, Frédéric; Lalive, Patrice H; Armand, Stéphane

2017-01-01

Gait abnormalities are subtle in multiple sclerosis (MS) patients with low disability and need to be better determined. As a biomechanical approach, the Gait Profile Score (GPS) is used to assess gait quality by combining nine gait kinematic variables in one single value. This study aims i) to establish if the GPS can detect gait impairments and ii) to compare GPS with discrete spatiotemporal and kinematic parameters in low-disabled MS patients. Thirty-four relapsing-remitting MS patients with an Expanded Disability Status Scale (EDSS) score ≤2 (mean age 36.32±8.72 years; 12 men, 22 women; mean EDSS 1.19±0.8) and twenty-two healthy controls (mean age 36.85±7.87 years; 6 men, 16 women) matched for age, weight, height, body mass index and gender underwent an instrumented gait analysis. No significant difference in GPS values and in spatiotemporal parameters was found between patients and controls. However patients showed a significant alteration at the ankle and pelvis level. GPS fails to identify gait abnormalities in low-disabled MS patients, although kinematic analysis revealed subtle gait alterations. Future studies should investigate other methods to assess gait impairments with a gait score in low-disabled MS patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative assessment of upper extremities motor function in multiple sclerosis.

PubMed

Daunoraviciene, Kristina; Ziziene, Jurgita; Griskevicius, Julius; Pauk, Jolanta; Ovcinikova, Agne; Kizlaitiene, Rasa; Kaubrys, Gintaras

2018-05-18

Upper extremity (UE) motor function deficits are commonly noted in multiple sclerosis (MS) patients and assessing it is challenging because of the lack of consensus regarding its definition. Instrumented biomechanical analysis of upper extremity movements can quantify coordination with different spatiotemporal measures and facilitate disability rating in MS patients. To identify objective quantitative parameters for more accurate evaluation of UE disability and relate it to existing clinical scores. Thirty-four MS patients and 24 healthy controls (CG) performed a finger-to-nose test as fast as possible and, in addition, clinical evaluation kinematic parameters of UE were measured by using inertial sensors. Generally, a higher disability score was associated with an increase of several temporal parameters, like slower task performance. The time taken to touch their nose was longer when the task was fulfilled with eyes closed. Time to peak angular velocity significantly changed in MS patients (EDSS > 5.0). The inter-joint coordination significantly decreases in MS patients (EDSS 3.0-5.5). Spatial parameters indicated that maximal ROM changes were in elbow flexion. Our findings have revealed that spatiotemporal parameters are related to the UE motor function and MS disability level. Moreover, they facilitate clinical rating by supporting clinical decisions with quantitative data.

Spatiotemporal mode-locking in multimode fiber lasers

NASA Astrophysics Data System (ADS)

Wright, Logan G.; Christodoulides, Demetrios N.; Wise, Frank W.

2017-10-01

A laser is based on the electromagnetic modes of its resonator, which provides the feedback required for oscillation. Enormous progress has been made toward controlling the interactions of longitudinal modes in lasers with a single transverse mode. For example, the field of ultrafast science has been built on lasers that lock many longitudinal modes together to form ultrashort light pulses. However, coherent superposition of longitudinal and transverse modes in a laser has received little attention. We show that modal and chromatic dispersions in fiber lasers can be counteracted by strong spatial and spectral filtering. This allows locking of multiple transverse and longitudinal modes to create ultrashort pulses with a variety of spatiotemporal profiles. Multimode fiber lasers thus open new directions in studies of nonlinear wave propagation and capabilities for applications.

Dynamic decomposition of spatiotemporal neural signals

PubMed Central

2017-01-01

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. PMID:28558039

Spatiotemporal neuromodulation therapies engaging muscle synergies improve motor control after spinal cord injury

PubMed Central

Wenger, Nikolaus; Moraud, Eduardo Martin; Gandar, Jerome; Musienko, Pavel; Capogrosso, Marco; Baud, Laetitia; Le Goff, Camille G.; Barraud, Quentin; Pavlova, Natalia; Dominici, Nadia; Minev, Ivan R.; Asboth, Leonie; Hirsch, Arthur; Duis, Simone; Kreider, Julie; Mortera, Andrea; Haverbeck, Oliver; Kraus, Silvio; Schmitz, Felix; DiGiovanna, Jack; van den Brand, Rubia; Bloch, Jocelyne; Detemple, Peter; Lacour, Stéphanie P.; Bézard, Erwan; Micera, Silvestro; Courtine, Grégoire

2016-01-01

Electrical neuromodulation of lumbar segments improves motor control after spinal cord injury in animal models and humans. However, the physiological principles underlying the effect of this intervention remain poorly understood, which has limited this therapeutic approach to continuous stimulation applied to restricted spinal cord locations. Here, we developed novel stimulation protocols that reproduce the natural dynamics of motoneuron activation during locomotion. For this, we computed the spatiotemporal activation pattern of muscle synergies during locomotion in healthy rats. Computer simulations identified optimal electrode locations to target each synergy through the recruitment of proprioceptive feedback circuits. This framework steered the design of spatially selective spinal implants and real–time control software that modulate extensor versus flexor synergies with precise temporal resolution. Spatiotemporal neuromodulation therapies improved gait quality, weight–bearing capacities, endurance and skilled locomotion in multiple rodent models of spinal cord injury. These new concepts are directly translatable to strategies to improve motor control in humans. PMID:26779815

Spatiotemporal database of US congressional elections, 1896–2014

PubMed Central

Wolf, Levi John

2017-01-01

High-quality historical data about US Congressional elections has long provided common ground for electoral studies. However, advances in geographic information science have recently made it efficient to compile, distribute, and analyze large spatio-temporal data sets on the structure of US Congressional districts. A single spatio-temporal data set that relates US Congressional election results to the spatial extent of the constituencies has not yet been developed. To address this, existing high-quality data sets of elections returns were combined with a spatiotemporal data set on Congressional district boundaries to generate a new spatio-temporal database of US Congressional election results that are explicitly linked to the geospatial data about the districts themselves. PMID:28809849

Bridge damage detection using spatiotemporal patterns extracted from dense sensor network

NASA Astrophysics Data System (ADS)

Liu, Chao; Gong, Yongqiang; Laflamme, Simon; Phares, Brent; Sarkar, Soumik

2017-01-01

The alarmingly degrading state of transportation infrastructures combined with their key societal and economic importance calls for automatic condition assessment methods to facilitate smart management of maintenance and repairs. With the advent of ubiquitous sensing and communication capabilities, scalable data-driven approaches is of great interest, as it can utilize large volume of streaming data without requiring detailed physical models that can be inaccurate and computationally expensive to run. Properly designed, a data-driven methodology could enable fast and automatic evaluation of infrastructures, discovery of causal dependencies among various sub-system dynamic responses, and decision making with uncertainties and lack of labeled data. In this work, a spatiotemporal pattern network (STPN) strategy built on symbolic dynamic filtering (SDF) is proposed to explore spatiotemporal behaviors in a bridge network. Data from strain gauges installed on two bridges are generated using finite element simulation for three types of sensor networks from a density perspective (dense, nominal, sparse). Causal relationships among spatially distributed strain data streams are extracted and analyzed for vehicle identification and detection, and for localization of structural degradation in bridges. Multiple case studies show significant capabilities of the proposed approach in: (i) capturing spatiotemporal features to discover causality between bridges (geographically close), (ii) robustness to noise in data for feature extraction, (iii) detecting and localizing damage via comparison of bridge responses to similar vehicle loads, and (iv) implementing real-time health monitoring and decision making work flow for bridge networks. Also, the results demonstrate increased sensitivity in detecting damages and higher reliability in quantifying the damage level with increase in sensor network density.

The spatiotemporal MEG covariance matrix modeled as a sum of Kronecker products.

PubMed

Bijma, Fetsje; de Munck, Jan C; Heethaar, Rob M

2005-08-15

The single Kronecker product (KP) model for the spatiotemporal covariance of MEG residuals is extended to a sum of Kronecker products. This sum of KP is estimated such that it approximates the spatiotemporal sample covariance best in matrix norm. Contrary to the single KP, this extension allows for describing multiple, independent phenomena in the ongoing background activity. Whereas the single KP model can be interpreted by assuming that background activity is generated by randomly distributed dipoles with certain spatial and temporal characteristics, the sum model can be physiologically interpreted by assuming a composite of such processes. Taking enough terms into account, the spatiotemporal sample covariance matrix can be described exactly by this extended model. In the estimation of the sum of KP model, it appears that the sum of the first 2 KP describes between 67% and 93%. Moreover, these first two terms describe two physiological processes in the background activity: focal, frequency-specific alpha activity, and more widespread non-frequency-specific activity. Furthermore, temporal nonstationarities due to trial-to-trial variations are not clearly visible in the first two terms, and, hence, play only a minor role in the sample covariance matrix in terms of matrix power. Considering the dipole localization, the single KP model appears to describe around 80% of the noise and seems therefore adequate. The emphasis of further improvement of localization accuracy should be on improving the source model rather than the covariance model.

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

PubMed

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.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010.

PubMed

Zulu, Leo C; Kalipeni, Ezekiel; Johannes, Eliza

2014-05-23

Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi's estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across 'sub-epidemics' while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV "hotspots" clustered among eleven southern districts/cities while a "coldspot" captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010

PubMed Central

2014-01-01

Background Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi’s estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Methods Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Results Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across ‘sub-epidemics’ while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV “hotspots” clustered among eleven southern districts/cities while a “coldspot” captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time

Spatiotemporal distribution and national measurement of the global carbonate carbon sink.

PubMed

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

Super-resolved Parallel MRI by Spatiotemporal Encoding

PubMed Central

Schmidt, Rita; Baishya, Bikash; Ben-Eliezer, Noam; Seginer, Amir; Frydman, Lucio

2016-01-01

Recent studies described an alternative “ultrafast” scanning method based on spatiotemporal (SPEN) principles. SPEN demonstrates numerous potential advantages over EPI-based alternatives, at no additional expense in experimental complexity. An important aspect that SPEN still needs to achieve for providing a competitive acquisition alternative entails exploiting parallel imaging algorithms, without compromising its proven capabilities. The present work introduces a combination of multi-band frequency-swept pulses simultaneously encoding multiple, partial fields-of-view; together with a new algorithm merging a Super-Resolved SPEN image reconstruction and SENSE multiple-receiving methods. The ensuing approach enables one to reduce both the excitation and acquisition times of ultrafast SPEN acquisitions by the customary acceleration factor R, without compromises in either the ensuing spatial resolution, SAR deposition, or the capability to operate in multi-slice mode. The performance of these new single-shot imaging sequences and their ancillary algorithms were explored on phantoms and human volunteers at 3T. The gains of the parallelized approach were particularly evident when dealing with heterogeneous systems subject to major T2/T2* effects, as is the case upon single-scan imaging near tissue/air interfaces. PMID:24120293

Use of Numerical Groundwater Model and Analytical Empirical Orthogonal Function for Calibrating Spatiotemporal pattern of Pumpage, Recharge and Parameter

NASA Astrophysics Data System (ADS)

Huang, C. L.; Hsu, N. S.; Hsu, F. C.; Liu, H. J.

2016-12-01

This study develops a novel methodology for the spatiotemporal groundwater calibration of mega-quantitative recharge and parameters by coupling a specialized numerical model and analytical empirical orthogonal function (EOF). The actual spatiotemporal patterns of groundwater pumpage are estimated by an originally developed back propagation neural network-based response matrix with the electrical consumption analysis. The spatiotemporal patterns of the recharge from surface water and hydrogeological parameters (i.e. horizontal hydraulic conductivity and vertical leakance) are calibrated by EOF with the simulated error hydrograph of groundwater storage, in order to qualify the multiple error sources and quantify the revised volume. The objective function of the optimization model is minimizing the root mean square error of the simulated storage error percentage across multiple aquifers, meanwhile subject to mass balance of groundwater budget and the governing equation in transient state. The established method was applied on the groundwater system of Chou-Shui River Alluvial Fan. The simulated period is from January 2012 to December 2014. The total numbers of hydraulic conductivity, vertical leakance and recharge from surface water among four aquifers are 126, 96 and 1080, respectively. Results showed that the RMSE during the calibration process was decreased dramatically and can quickly converse within 6th iteration, because of efficient filtration of the transmission induced by the estimated error and recharge across the boundary. Moreover, the average simulated error percentage according to groundwater level corresponding to the calibrated budget variables and parameters of aquifer one is as small as 0.11%. It represent that the developed methodology not only can effectively detect the flow tendency and error source in all aquifers to achieve accurately spatiotemporal calibration, but also can capture the peak and fluctuation of groundwater level in shallow

Synchronization and spatiotemporal patterns in coupled phase oscillators on a weighted planar network

NASA Astrophysics Data System (ADS)

Kagawa, Yuki; Takamatsu, Atsuko

2009-04-01

To reveal the relation between network structures found in two-dimensional biological systems, such as protoplasmic tube networks in the plasmodium of true slime mold, and spatiotemporal oscillation patterns emerged on the networks, we constructed coupled phase oscillators on weighted planar networks and investigated their dynamics. Results showed that the distribution of edge weights in the networks strongly affects (i) the propensity for global synchronization and (ii) emerging ratios of oscillation patterns, such as traveling and concentric waves, even if the total weight is fixed. In-phase locking, traveling wave, and concentric wave patterns were, respectively, observed most frequently in uniformly weighted, center weighted treelike, and periphery weighted ring-shaped networks. Controlling the global spatiotemporal patterns with the weight distribution given by the local weighting (coupling) rules might be useful in biological network systems including the plasmodial networks and neural networks in the brain.

A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

PubMed Central

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

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

PubMed

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 spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London.

PubMed

Rushworth, Alastair; Lee, Duncan; Mitchell, Richard

2014-07-01

It has long been known that air pollution is harmful to human health, as many epidemiological studies have been conducted into its effects. Collectively, these studies have investigated both the acute and chronic effects of pollution, with the latter typically based on individual level cohort designs that can be expensive to implement. As a result of the increasing availability of small-area statistics, ecological spatio-temporal study designs are also being used, with which a key statistical problem is allowing for residual spatio-temporal autocorrelation that remains after the covariate effects have been removed. We present a new model for estimating the effects of air pollution on human health, which allows for residual spatio-temporal autocorrelation, and a study into the long-term effects of air pollution on human health in Greater London, England. The individual and joint effects of different pollutants are explored, via the use of single pollutant models and multiple pollutant indices. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

PubMed

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

2014-09-01

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 implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NO x in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R 2 of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.

Discriminability limits in spatio-temporal stereo block matching.

PubMed

Jain, Ankit K; Nguyen, Truong Q

2014-05-01

Disparity estimation is a fundamental task in stereo imaging and is a well-studied problem. Recently, methods have been adapted to the video domain where motion is used as a matching criterion to help disambiguate spatially similar candidates. In this paper, we analyze the validity of the underlying assumptions of spatio-temporal disparity estimation, and determine the extent to which motion aids the matching process. By analyzing the error signal for spatio-temporal block matching under the sum of squared differences criterion and treating motion as a stochastic process, we determine the probability of a false match as a function of image features, motion distribution, image noise, and number of frames in the spatio-temporal patch. This performance quantification provides insight into when spatio-temporal matching is most beneficial in terms of the scene and motion, and can be used as a guide to select parameters for stereo matching algorithms. We validate our results through simulation and experiments on stereo video.

Atypical Functional Brain Activation during a Multiple Object Tracking Task in Girls with Turner Syndrome: Neurocorrelates of Reduced Spatiotemporal Resolution

ERIC Educational Resources Information Center

Beaton, Elliott A.; Stoddard, Joel; Lai, Song; Lackey, John; Shi, Jianrong; Ross, Judith L.; Simon, Tony J.

2010-01-01

Turner syndrome is associated with spatial and numerical cognitive impairments. We hypothesized that these nonverbal cognitive impairments result from limits in spatial and temporal processing, particularly as it affects attention. To examine spatiotemporal attention in girls with Turner syndrome versus typically developing controls, we used a…

Analysis of Spatiotemporal Characteristics of Pandemic SARS Spread in Mainland China.

PubMed

Cao, Chunxiang; Chen, Wei; Zheng, Sheng; Zhao, Jian; Wang, Jinfeng; Cao, Wuchun

2016-01-01

Severe acute respiratory syndrome (SARS) is one of the most severe emerging infectious diseases of the 21st century so far. SARS caused a pandemic that spread throughout mainland China for 7 months, infecting 5318 persons in 194 administrative regions. Using detailed mainland China epidemiological data, we study spatiotemporal aspects of this person-to-person contagious disease and simulate its spatiotemporal transmission dynamics via the Bayesian Maximum Entropy (BME) method. The BME reveals that SARS outbreaks show autocorrelation within certain spatial and temporal distances. We use BME to fit a theoretical covariance model that has a sine hole spatial component and exponential temporal component and obtain the weights of geographical and temporal autocorrelation factors. Using the covariance model, SARS dynamics were estimated and simulated under the most probable conditions. Our study suggests that SARS transmission varies in its epidemiological characteristics and SARS outbreak distributions exhibit palpable clusters on both spatial and temporal scales. In addition, the BME modelling demonstrates that SARS transmission features are affected by spatial heterogeneity, so we analyze potential causes. This may benefit epidemiological control of pandemic infectious diseases.

An Arabidopsis introgression zone studied at high spatio-temporal resolution: interglacial and multiple genetic contact exemplified using whole nuclear and plastid genomes.

PubMed

Hohmann, Nora; Koch, Marcus A

2017-10-23

Gene flow between species, across ploidal levels, and even between evolutionary lineages is a common phenomenon in the genus Arabidopsis. However, apart from two genetically fully stabilized allotetraploid species that have been investigated in detail, the extent and temporal dynamics of hybridization are not well understood. An introgression zone, with tetraploid A. arenosa introgressing into A. lyrata subsp. petraea in the Eastern Austrian Forealps and subsequent expansion towards pannonical lowlands, was described previously based on morphological observations as well as molecular data using microsatellite and plastid DNA markers. Here we investigate the spatio-temporal context of this suture zone, making use of the potential of next-generation sequencing and whole-genome data. By utilizing a combination of nuclear and plastid genomic data, the extent, direction and temporal dynamics of gene flow are elucidated in detail and Late Pleistocene evolutionary processes are resolved. Analysis of nuclear genomic data significantly recognizes the clinal structure of the introgression zone, but also reveals that hybridization and introgression is more common and substantial than previously thought. Also tetraploid A. lyrata and A. arenosa subsp. borbasii from outside the previously defined suture zone show genomic signals of past introgression. A. lyrata is shown to serve usually as the maternal parent in these hybridizations, but one exception is identified from plastome-based phylogenetic reconstruction. Using plastid phylogenomics with secondary time calibration, the origin of A. lyrata and A. arenosa lineages is pre-dating the last three glaciation complexes (approx. 550,000 years ago). Hybridization and introgression followed during the last two glacial-interglacial periods (since approx. 300,000 years ago) with later secondary contact at the northern and southern border of the introgression zone during the Holocene. Footprints of adaptive introgression in the

Hierarchic spatio-temporal dynamics in glycolysis

NASA Astrophysics Data System (ADS)

Shinjyo, Takahiro; Nakagawa, Yoshiyuki; Ueda, Tetsuo

Yeast extracts exhibit oscillations when the glycolytic system is far away from equilibrium. Spatio-temporal dynamics in this system was studied in the newly developed gel as well as in the solution. Small regions (about 10 um) with very complex shape with high or low concentrations of NADH appeared, and upon these small structures large-scale dynamics were superimposed. Concentration waves propagated, and the source of wave was induced by contact with high ADP. Sink of waves was generated by contacting the reaction gel to two small gels rich in ADP. Upon these spatio-temporal dynamics were superimposed much slower global oscillations throughout the system with a period of about 40 min. Similar dynamics was seen in a solution of yeast extract, but the size of domains was about ten times larger than that in the gel. In this way, the multi-enzyme system of glycolysis exhibits self-organization of hierarchy in spatio-temporal dynamics.

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2016-10-02

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) tomore » compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.« less

Spatiotemporal Change Detection Using Landsat Imagery: the Case Study of Karacabey Flooded Forest, Bursa, Turkey

NASA Astrophysics Data System (ADS)

Akay, A. E.; Gencal, B.; Taş, İ.

2017-11-01

This short paper aims to detect spatiotemporal detection of land use/land cover change within Karacabey Flooded Forest region. Change detection analysis applied to Landsat 5 TM images representing July 2000 and a Landsat 8 OLI representing June 2017. Various image processing tools were implemented using ERDAS 9.2, ArcGIS 10.4.1, and ENVI programs to conduct spatiotemporal change detection over these two images such as band selection, corrections, subset, classification, recoding, accuracy assessment, and change detection analysis. Image classification revealed that there are five significant land use/land cover types, including forest, flooded forest, swamp, water, and other lands (i.e. agriculture, sand, roads, settlement, and open areas). The results indicated that there was increase in flooded forest, water, and other lands, while the cover of forest and swamp decreased.

Integrating GIS and ABM to Explore Spatiotemporal Dynamics

NASA Astrophysics Data System (ADS)

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.

Mining Spatiotemporal Patterns of the Elder's Daily Movement

NASA Astrophysics Data System (ADS)

Chen, C. R.; Chen, C. F.; Liu, M. E.; Tsai, S. J.; Son, N. T.; Kinh, L. V.

2016-06-01

With rapid developments in wearable device technology, a vast amount of spatiotemporal data, such as people's movement and physical activities, are generated. Information derived from the data reveals important knowledge that can contribute a long-term care and psychological assessment of the elders' living condition especially in long-term care institutions. This study aims to develop a method to investigate the spatial-temporal movement patterns of the elders with their outdoor trajectory information. To achieve the goal, GPS based location data of the elderly subjects from long-term care institutions are collected and analysed with geographic information system (GIS). A GIS statistical model is developed to mine the elderly subjects' spatiotemporal patterns with the location data and represent their daily movement pattern at particular time. The proposed method first finds the meaningful trajectory and extracts the frequent patterns from the time-stamp location data. Then, a density-based clustering method is used to identify the major moving range and the gather/stay hotspot in both spatial and temporal dimensions. The preliminary results indicate that the major moving area of the elderly people encompasses their dorm and has a short moving distance who often stay in the same site. Subjects' outdoor appearance are corresponded to their life routine. The results can be useful for understanding elders' social network construction, risky area identification and medical care monitoring.

Key frame extraction based on spatiotemporal motion trajectory

NASA Astrophysics Data System (ADS)

Zhang, Yunzuo; Tao, Ran; Zhang, Feng

2015-05-01

Spatiotemporal motion trajectory can accurately reflect the changes of motion state. Motivated by this observation, this letter proposes a method for key frame extraction based on motion trajectory on the spatiotemporal slice. Different from the well-known motion related methods, the proposed method utilizes the inflexions of the motion trajectory on the spatiotemporal slice of all the moving objects. Experimental results show that although a similar performance is achieved in the single-objective screen, by comparing the proposed method to that achieved with the state-of-the-art methods based on motion energy or acceleration, the proposed method shows a better performance in a multiobjective video.

Evaluating the Spatio-Temporal Factors that Structure Network Parameters of Plant-Herbivore Interactions

PubMed Central

López-Carretero, Antonio; Díaz-Castelazo, Cecilia; Boege, Karina; Rico-Gray, Víctor

2014-01-01

Despite the dynamic nature of ecological interactions, most studies on species networks offer static representations of their structure, constraining our understanding of the ecological mechanisms involved in their spatio-temporal stability. This is the first study to evaluate plant-herbivore interaction networks on a small spatio-temporal scale. Specifically, we simultaneously assessed the effect of host plant availability, habitat complexity and seasonality on the structure of plant-herbivore networks in a coastal tropical ecosystem. Our results revealed that changes in the host plant community resulting from seasonality and habitat structure are reflected not only in the herbivore community, but also in the emergent properties (network parameters) of the plant-herbivore interaction network such as connectance, selectiveness and modularity. Habitat conditions and periods that are most stressful favored the presence of less selective and susceptible herbivore species, resulting in increased connectance within networks. In contrast, the high degree of selectivennes (i.e. interaction specialization) and modularity of the networks under less stressful conditions was promoted by the diversification in resource use by herbivores. By analyzing networks at a small spatio-temporal scale we identified the ecological factors structuring this network such as habitat complexity and seasonality. Our research offers new evidence on the role of abiotic and biotic factors in the variation of the properties of species interaction networks. PMID:25340790

Defining multiple, distinct, and shared spatiotemporal patterns of DNA replication and endoreduplication from 3D image analysis of developing maize (Zea mays L.) root tip nuclei.

PubMed

Bass, Hank W; Hoffman, Gregg G; Lee, Tae-Jin; Wear, Emily E; Joseph, Stacey R; Allen, George C; Hanley-Bowdoin, Linda; Thompson, William F

2015-11-01

Spatiotemporal patterns of DNA replication have been described for yeast and many types of cultured animal cells, frequently after cell cycle arrest to aid in synchronization. However, patterns of DNA replication in nuclei from plants or naturally developing organs remain largely uncharacterized. Here we report findings from 3D quantitative analysis of DNA replication and endoreduplication in nuclei from pulse-labeled developing maize root tips. In both early and middle S phase nuclei, flow-sorted on the basis of DNA content, replicative labeling was widely distributed across euchromatic regions of the nucleoplasm. We did not observe the perinuclear or perinucleolar replicative labeling patterns characteristic of middle S phase in mammals. Instead, the early versus middle S phase patterns in maize could be distinguished cytologically by correlating two quantitative, continuous variables, replicative labeling and DAPI staining. Early S nuclei exhibited widely distributed euchromatic labeling preferentially localized to regions with weak DAPI signals. Middle S nuclei also exhibited widely distributed euchromatic labeling, but the label was preferentially localized to regions with strong DAPI signals. Highly condensed heterochromatin, including knobs, replicated during late S phase as previously reported. Similar spatiotemporal replication patterns were observed for both mitotic and endocycling maize nuclei. These results revealed that maize euchromatin exists as an intermingled mixture of two components distinguished by their condensation state and replication timing. These different patterns might reflect a previously described genome organization pattern, with "gene islands" mostly replicating during early S phase followed by most of the intergenic repetitive regions replicating during middle S phase.

Spatiotemporal Analysis of the Malaria Epidemic in Mainland China, 2004-2014.

PubMed

Huang, Qiang; Hu, Lin; Liao, Qi-Bin; Xia, Jing; Wang, Qian-Ru; Peng, Hong-Juan

2017-08-01

The purpose of this study is to characterize spatiotemporal heterogeneities in malaria distribution at a provincial level and investigate the association between malaria incidence and climate factors from 2004 to 2014 in China to inform current malaria control efforts. National malaria incidence peaked (4.6/100,000) in 2006 and decreased to a very low level (0.21/100,000) in 2014, and the proportion of imported cases increased from 16.2% in 2004 to 98.2% in 2014. Statistical analyses of global and local spatial autocorrelations and purely spatial scan statistics revealed that malaria was localized in Hainan, Anhui, and Yunnan during 2004-2009 and then gradually shifted and clustered in Yunnan after 2010. Purely temporal clusters shortened to less than 5 months during 2012-2014. The two most likely clusters detected using spatiotemporal analysis occurred in Anhui between July 2005 and November 2007 and Yunnan between January 2010 and June 2012. Correlation coefficients for the association between malaria incidence and climate factors sharply decreased after 2010, and there were zero-month lag effects for climate factors during 2010-2014. Overall, the spatiotemporal distribution of malaria in China changed from relatively scattered (2004-2009) to relatively clustered (2010-2014). As the proportion of imported cases increased, the effect of climate factors on malaria incidence has gradually become weaker since 2011. Therefore, new warning systems should be applied to monitor resurgence and outbreaks of malaria in mainland China, and quarantine at borders should be reinforced to control the increasingly trend of imported malaria cases.

Spatiotemporal Distribution of Chinavia hilaris (Hemiptera: Pentatomidae) in Peanut-Cotton Farmscapes

PubMed Central

Tillman, P. Glynn; Cottrell, Ted E.

2015-01-01

The green stink bug, Chinavia hilaris (Say) (Hemiptera: Pentatomidae), is a pest of cotton in the southeastern United States, but little is known concerning its spatiotemporal distribution in agricultural farmscapes. Therefore, spatiotemporal distribution of C. hilaris in farmscapes where cotton fields adjoined peanut was examined weekly. Spatial patterns of C. hilaris counts were analyzed using SADIE (Spatial Analysis by Distance Indices) methodology. Interpolated maps of C. hilaris density were used to visualize abundance and distribution of C. hilaris in crops. For the six peanut-cotton farmscapes studied, the frequency of C. hilaris in cotton (94.8%) was significantly higher than in peanut (5.2%), and nymphs were rarely detected in peanut, indicating that peanut was not a source of C. hilaris into cotton. Significantly, aggregated spatial distributions were detected in cotton. Maps of local clustering indices depicted patches of C. hilaris in cotton, mainly at field edges including the peanut-to-cotton interface. Black cherry (Prunus serotina Ehrh.) and elderberry (Sambucus nigra subsp. canadensis [L.] R. Bolli) grew in habitats adjacent to crops, C. hilaris were captured in pheromone-baited stink bug traps in these habitats, and in most instances, C. hilaris were observed feeding on black cherry and elderberry in these habitats before colonization of cotton. Spatial distribution of C. hilaris in these farmscapes revealed that C. hilaris colonized cotton field edges near these two noncrop hosts. Altogether, these findings suggest that black cherry and elderberry were sources of C. hilaris into cotton. Factors affecting the spatiotemporal dynamics of C. hilaris in peanut-cotton farmscapes are discussed. PMID:26175464

Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

NASA Astrophysics Data System (ADS)

Medyńska-Gulij, Beata; Cybulski, Paweł

2016-06-01

This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

Spatiotemporal optical vortices

NASA Astrophysics Data System (ADS)

Jhajj, Nihal; Larkin, Ilia; Rosenthal, Eric; Zahedpour, Sina; Wahlstrand, Jared; Milchberg, Howard

2017-04-01

We present the first experimental evidence, supported by theory and simulation, of spatiotemporal optical vortices (STOVs). A STOV is an optical vortex with phase and energy circulation in a spatiotemporal plane. Depending on the sign of the material dispersion, the local electromagnetic energy flow is saddle or spiral about the STOV. STOVs are shown to be a fundamental element of the nonlinear collapse and subsequent propagation of short optical pulses in material media. STOVs conserve topological charge, constraining their birth, evolution, and annihilation. We measure a self-generated STOV consisting of a ring-shaped null in the electromagnetic field about which the phase is spiral, forming a dynamic torus that is concentric with and tracks the propagating pulse. Our results, here obtained for optical pulse collapse and filamentation in air, are generalizable to a broad class of nonlinearly propagating waves. Defense Advanced Research Projects Agency (Grant No. W911NF1410372), Air Force Office of Scientific Research (Grant No. FA95501310044), National Science Foundation (Grant No. PHY1301948), and Army Research Office (Grant No. W911NF1410372).

Cubic map algebra functions for spatio-temporal analysis

USGS Publications Warehouse

Mennis, J.; Viger, R.; Tomlin, C.D.

2005-01-01

We propose an extension of map algebra to three dimensions for spatio-temporal data handling. This approach yields a new class of map algebra functions that we call "cube functions." Whereas conventional map algebra functions operate on data layers representing two-dimensional space, cube functions operate on data cubes representing two-dimensional space over a third-dimensional period of time. We describe the prototype implementation of a spatio-temporal data structure and selected cube function versions of conventional local, focal, and zonal map algebra functions. The utility of cube functions is demonstrated through a case study analyzing the spatio-temporal variability of remotely sensed, southeastern U.S. vegetation character over various land covers and during different El Nin??o/Southern Oscillation (ENSO) phases. Like conventional map algebra, the application of cube functions may demand significant data preprocessing when integrating diverse data sets, and are subject to limitations related to data storage and algorithm performance. Solutions to these issues include extending data compression and computing strategies for calculations on very large data volumes to spatio-temporal data handling.

Spatio-temporal mapping of variation potentials in leaves of Helianthus annuus L. seedlings in situ using multi-electrode array

PubMed Central

Zhao, Dong-Jie; Wang, Zhong-Yi; Huang, Lan; Jia, Yong-Peng; Leng, John Q.

2014-01-01

Damaging thermal stimuli trigger long-lasting variation potentials (VPs) in higher plants. Owing to limitations in conventional plant electrophysiological recording techniques, recorded signals are composed of signals originating from all of the cells that are connected to an electrode. This limitation does not enable detailed spatio-temporal distributions of transmission and electrical activities in plants to be visualised. Multi-electrode array (MEA) enables the recording and imaging of dynamic spatio-temporal electrical activities in higher plants. Here, we used an 8 × 8 MEA with a polar distance of 450 μm to measure electrical activities from numerous cells simultaneously. The mapping of the data that were recorded from the MEA revealed the transfer mode of the thermally induced VPs in the leaves of Helianthus annuus L. seedlings in situ. These results suggest that MEA can enable recordings with high spatio-temporal resolution that facilitate the determination of the bioelectrical response mode of higher plants under stress. PMID:24961469

Spatio-temporal mapping of variation potentials in leaves of Helianthus annuus L. seedlings in situ using multi-electrode array.

PubMed

Zhao, Dong-Jie; Wang, Zhong-Yi; Huang, Lan; Jia, Yong-Peng; Leng, John Q

2014-06-25

Damaging thermal stimuli trigger long-lasting variation potentials (VPs) in higher plants. Owing to limitations in conventional plant electrophysiological recording techniques, recorded signals are composed of signals originating from all of the cells that are connected to an electrode. This limitation does not enable detailed spatio-temporal distributions of transmission and electrical activities in plants to be visualised. Multi-electrode array (MEA) enables the recording and imaging of dynamic spatio-temporal electrical activities in higher plants. Here, we used an 8 × 8 MEA with a polar distance of 450 μm to measure electrical activities from numerous cells simultaneously. The mapping of the data that were recorded from the MEA revealed the transfer mode of the thermally induced VPs in the leaves of Helianthus annuus L. seedlings in situ. These results suggest that MEA can enable recordings with high spatio-temporal resolution that facilitate the determination of the bioelectrical response mode of higher plants under stress.

Multiview human activity recognition system based on spatiotemporal template for video surveillance system

NASA Astrophysics Data System (ADS)

Kushwaha, Alok Kumar Singh; Srivastava, Rajeev

2015-09-01

An efficient view invariant framework for the recognition of human activities from an input video sequence is presented. The proposed framework is composed of three consecutive modules: (i) detect and locate people by background subtraction, (ii) view invariant spatiotemporal template creation for different activities, (iii) and finally, template matching is performed for view invariant activity recognition. The foreground objects present in a scene are extracted using change detection and background modeling. The view invariant templates are constructed using the motion history images and object shape information for different human activities in a video sequence. For matching the spatiotemporal templates for various activities, the moment invariants and Mahalanobis distance are used. The proposed approach is tested successfully on our own viewpoint dataset, KTH action recognition dataset, i3DPost multiview dataset, MSR viewpoint action dataset, VideoWeb multiview dataset, and WVU multiview human action recognition dataset. From the experimental results and analysis over the chosen datasets, it is observed that the proposed framework is robust, flexible, and efficient with respect to multiple views activity recognition, scale, and phase variations.

Spatiotemporal characterization of ultrashort optical vortex pulses

NASA Astrophysics Data System (ADS)

Miranda, Miguel; Kotur, Marija; Rudawski, Piotr; Guo, Chen; Harth, Anne; L'Huillier, Anne; Arnold, Cord L.

2017-12-01

We use a spiral phase plate to generate few-cycle optical vortices from an ultrafast titanium:sapphire oscillator and characterize them in the spatiotemporal domain with a recently introduced technique based on spatially resolved Fourier transform spectrometry. The performance of this simple approach to the generation of optical vortices is analysed from a wavelength-dependent perspective as well as in the spatiotemporal domain, allowing us to characterize ultrashort vortex pulses in space, frequency and time.

Spatio-temporal scaling of channels in braided streams.

Treesearch

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

NASA Astrophysics Data System (ADS)

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.

Male reproductive strategy explains spatiotemporal segregation in brown bears

PubMed Central

Steyaert, Sam MJG; Kindberg, Jonas; Swenson, Jon E; Zedrosser, Andreas

2013-01-01

1. Spatiotemporal segregation is often explained by the risk for offspring predation or by differences in physiology, predation risk vulnerability or competitive abilities related to size dimorphism. 2. Most large carnivores are size dimorphic and offspring predation is often intraspecific and related to nonparental infanticide (NPI). NPI can be a foraging strategy, a strategy to reduce competition, or a male reproductive strategy. Spatiotemporal segregation is widespread among large carnivores, but its nature remains poorly understood. 3. We evaluated three hypotheses to explain spatiotemporal segregation in the brown bear, a size-dimorphic large carnivore in which NPI is common; the ‘NPI – foraging/competition hypothesis', i.e. NPI as a foraging strategy or a strategy to reduce competition, the ‘NPI – sexual selection hypothesis’, i.e. infanticide as a male reproductive strategy and the ‘body size hypothesis’, i.e. body-size-related differences in physiology, predation risk vulnerability or competitive ability causes spatiotemporal segregation. To test these hypotheses, we quantified spatiotemporal segregation among adult males, lone adult females and females with cubs-of-the-year, based on GPS-relocation data (2006–2010) and resource selection functions in a Scandinavian population. 4. We found that spatiotemporal segregation was strongest between females with cubs-of-the-year and adult males during the mating season. During the mating season, females with cubs-of-the-year selected their resources, in contrast to adult males, in less rugged landscapes in relative close proximity to certain human-related variables, and in more open habitat types. After the mating season, females with cubs-of-the-year markedly shifted their resource selection towards a pattern more similar to that of their conspecifics. No strong spatiotemporal segregation was apparent between females with cubs-of-the-year and conspecifics during the mating and the postmating

Spatiotemporal profiles of receptive fields of neurons in the lateral posterior nucleus of the cat LP-pulvinar complex.

PubMed

Piché, Marilyse; Thomas, Sébastien; Casanova, Christian

2015-10-01

The pulvinar is the largest extrageniculate thalamic visual nucleus in mammals. It establishes reciprocal connections with virtually all visual cortexes and likely plays a role in transthalamic cortico-cortical communication. In cats, the lateral posterior nucleus (LP) of the LP-pulvinar complex can be subdivided in two subregions, the lateral (LPl) and medial (LPm) parts, which receive a predominant input from the striate cortex and the superior colliculus, respectively. Here, we revisit the receptive field structure of LPl and LPm cells in anesthetized cats by determining their first-order spatiotemporal profiles through reverse correlation analysis following sparse noise stimulation. Our data reveal the existence of previously unidentified receptive field profiles in the LP nucleus both in space and time domains. While some cells responded to only one stimulus polarity, the majority of neurons had receptive fields comprised of bright and dark responsive subfields. For these neurons, dark subfields' size was larger than that of bright subfields. A variety of receptive field spatial organization types were identified, ranging from totally overlapped to segregated bright and dark subfields. In the time domain, a large spectrum of activity overlap was found, from cells with temporally coinciding subfield activity to neurons with distinct, time-dissociated subfield peak activity windows. We also found LP neurons with space-time inseparable receptive fields and neurons with multiple activity periods. Finally, a substantial degree of homology was found between LPl and LPm first-order receptive field spatiotemporal profiles, suggesting a high integration of cortical and subcortical inputs within the LP-pulvinar complex. Copyright © 2015 the American Physiological Society.

Spatio-temporal hierarchical modeling of rates and variability of Holocene sea-level changes in the western North Atlantic and the Caribbean

NASA Astrophysics Data System (ADS)

Ashe, E.; Kopp, R. E.; Khan, N.; Horton, B.; Engelhart, S. E.

2016-12-01

Sea level varies over of both space and time. Prior to the instrumental period, the sea-level record depends upon geological reconstructions that contain vertical and temporal uncertainty. Spatio-temporal statistical models enable the interpretation of RSL and rates of change as well as the reconstruction of the entire sea-level field from such noisy data. Hierarchical models explicitly distinguish between a process level, which characterizes the spatio-temporal field, and a data level, by which sparse proxy data and its noise is recorded. A hyperparameter level depicts prior expectations about the structure of variability in the spatio-temporal field. Spatio-temporal hierarchical models are amenable to several analysis approaches, with tradeoffs regarding computational efficiency and comprehensiveness of uncertainty characterization. A fully-Bayesian hierarchical model (BHM), which places prior probability distributions upon the hyperparameters, is more computationally intensive than an empirical hierarchical model (EHM), which uses point estimates of hyperparameters, derived from the data [1]. Here, we assess the sensitivity of posterior estimates of relative sea level (RSL) and rates to different statistical approaches by varying prior assumptions about the spatial and temporal structure of sea-level variability and applying multiple analytical approaches to Holocene sea-level proxies along the Atlantic coast of North American and the Caribbean [2]. References: 1. N Cressie, Wikle CK (2011) Statistics for spatio-temporal data (John Wiley & Sons). 2. Kahn N et al. (2016). Quaternary Science Reviews (in revision).

A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Minsun, E-mail: mk688@uw.edu; Stewart, Robert D.; Phillips, Mark H.

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 tumormore » 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

Photoactivatable fluorescent probes reveal heterogeneous nanoparticle permeation through biological gels at multiple scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schuster, Benjamin S.; Allan, Daniel B.; Kays, Joshua C.

Diffusion through biological gels is crucial for effective drug delivery using nanoparticles. Here, we demonstrate a new method to measure diffusivity over a large range of length scales – from tens of nanometers to tens of micrometers – using photoactivatable fluorescent nanoparticle probes. We have applied this method to investigate the length-scale dependent mobility of nanoparticles in fibrin gels and in sputum from patients with cystic fibrosis (CF). Nanoparticles composed of poly(lactic-co-glycolic acid), with polyethylene glycol coatings to resist bioadhesion, were internally labeled with caged rhodamine to make the particles photoactivatable. We activated particles within a region of sample usingmore » brief, targeted exposure to UV light, uncaging the rhodamine and causing the particles in that region to become fluorescent. We imaged the subsequent spatiotemporal evolution in fluorescence intensity and observed the collective particle diffusion over tens of minutes and tens of micrometers. We also performed complementary multiple particle tracking experiments on the same particles, extending significantly the range over which particle motion and its heterogeneity can be observed. In fibrin gels, both methods showed an immobile fraction of particles and a mobile fraction that diffused over all measured length scales. In the CF sputum, particle diffusion was spatially heterogeneous and locally anisotropic but nevertheless typically led to unbounded transport extending tens of micrometers within tens of minutes. Lastly, these findings provide insight into the mesoscale architecture of these gels and its role in setting their permeability on physiologically relevant length scales, pointing toward strategies for improving nanoparticle drug delivery.« less

Photoactivatable fluorescent probes reveal heterogeneous nanoparticle permeation through biological gels at multiple scales

DOE PAGES

Schuster, Benjamin S.; Allan, Daniel B.; Kays, Joshua C.; ...

2017-05-31

Diffusion through biological gels is crucial for effective drug delivery using nanoparticles. Here, we demonstrate a new method to measure diffusivity over a large range of length scales – from tens of nanometers to tens of micrometers – using photoactivatable fluorescent nanoparticle probes. We have applied this method to investigate the length-scale dependent mobility of nanoparticles in fibrin gels and in sputum from patients with cystic fibrosis (CF). Nanoparticles composed of poly(lactic-co-glycolic acid), with polyethylene glycol coatings to resist bioadhesion, were internally labeled with caged rhodamine to make the particles photoactivatable. We activated particles within a region of sample usingmore » brief, targeted exposure to UV light, uncaging the rhodamine and causing the particles in that region to become fluorescent. We imaged the subsequent spatiotemporal evolution in fluorescence intensity and observed the collective particle diffusion over tens of minutes and tens of micrometers. We also performed complementary multiple particle tracking experiments on the same particles, extending significantly the range over which particle motion and its heterogeneity can be observed. In fibrin gels, both methods showed an immobile fraction of particles and a mobile fraction that diffused over all measured length scales. In the CF sputum, particle diffusion was spatially heterogeneous and locally anisotropic but nevertheless typically led to unbounded transport extending tens of micrometers within tens of minutes. Lastly, these findings provide insight into the mesoscale architecture of these gels and its role in setting their permeability on physiologically relevant length scales, pointing toward strategies for improving nanoparticle drug delivery.« less

Spatio-temporal activity of lightnings over Greece

NASA Astrophysics Data System (ADS)

Nastos, P. T.; Matsangouras, I. T.; Chronis, T. G.

2012-04-01

Extreme precipitation events are always associated with convective weather conditions driving to intense lightning activity: Cloud to Ground (CG), Ground to Cloud (GC) and Cloud to Cloud (CC). Thus, the study of lightnings, which typically occur during thunderstorms, gives evidence of the spatio-temporal variability of intense precipitation. Lightning is a natural phenomenon in the atmosphere, being a major cause of storm related with deaths and main trigger of forest fires during dry season. Lightning affects the many electrochemical systems of the body causing nerve damage, memory loss, personality change, and emotional problems. Besides, among the various nitrogen oxides sources, the contribution from lightning likely represents the largest uncertainty. An operational lightning detection network (LDN) has been established since 2007 by HNMS, consisting of eight time-of-arrival sensors (TOA), spatially distributed across Greek territory. In this study, the spatial and temporal variability of recorded lightnings (CG, GC and CC) are analyzed over Greece, during the period from January 14, 2008 to December 31, 2009, for the first time. The data for retrieving the location and time-of-occurrence of lightning were acquired from Hellenic National Meteorological Service (HNMS). In addition to the analysis of spatio-temporal activity over Greece, the HNMS-LDN characteristics are also presented. The results of the performed analysis reveal the specific geographical sub-regions associated with lightnings incidence. Lightning activity occurs mainly during the autumn season, followed by summer and spring. Higher frequencies of flashes appear over Ionian and Aegean Sea than over land during winter period against continental mountainous regions during summer period.

Monitoring Urban Greenness Dynamics Using Multiple Endmember Spectral Mixture Analysis

PubMed Central

Gan, Muye; Deng, Jinsong; Zheng, Xinyu; Hong, Yang; Wang, Ke

2014-01-01

Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents’ quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development. PMID:25375176

Risk management in spatio-temporally varying field by true slime mold

NASA Astrophysics Data System (ADS)

Ito, Kentaro; Sumpter, David; Nakagaki, Toshiyuki

Revealing how lower organisms solve complicated problems is a challenging research area, which could reveal the evolutionary origin of biological information processing. Here we report on the ability of a single-celled organism, true slime mold, to find a smart solution of risk management under spatio-temporally varying conditions. We designed test conditions under which there were three food-locations at vertices of equilateral triangle and a toxic light illuminated the organism on alternating halves of the triangle. We found that the organism behavior depended on the period of the repeated illumination, even though the total exposure time was kept the same . A simple mathematical model for the experimental results is proposed from a dynamical system point of view. We discuss our results in the context of a strategy of risk management by Physarum.

Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data.

PubMed

Kolovos, Alexander; Skupin, André; Jerrett, Michael; Christakos, George

2010-09-01

Space-time data analysis and assimilation techniques in atmospheric sciences typically consider input from monitoring measurements. The input is often processed in a manner that acknowledges characteristics of the measurements (e.g., underlying patterns, fluctuation features) under conditions of uncertainty; it also leads to the derivation of secondary information that serves study-oriented goals, and provides input to space-time prediction techniques. We present a novel approach that blends a rigorous space-time prediction model (Bayesian maximum entropy, BME) with a cognitively informed visualization of high-dimensional data (spatialization). The combined BME and spatialization approach (BME-S) is used to study monthly averaged NO2 and mean annual SO4 measurements in California over the 15-year period 1988-2002. Using the original scattered measurements of these two pollutants BME generates spatiotemporal predictions on a regular grid across the state. Subsequently, the prediction network undergoes the spatialization transformation into a lower-dimensional geometric representation, aimed at revealing patterns and relationships that exist within the input data. The proposed BME-S provides a powerful spatiotemporal framework to study a variety of air pollution data sources.

Analysis of Spatiotemporal Characteristics of Pandemic SARS Spread in Mainland China

PubMed Central

Cao, Chunxiang; Zheng, Sheng; Zhao, Jian; Wang, Jinfeng; Cao, Wuchun

2016-01-01

Severe acute respiratory syndrome (SARS) is one of the most severe emerging infectious diseases of the 21st century so far. SARS caused a pandemic that spread throughout mainland China for 7 months, infecting 5318 persons in 194 administrative regions. Using detailed mainland China epidemiological data, we study spatiotemporal aspects of this person-to-person contagious disease and simulate its spatiotemporal transmission dynamics via the Bayesian Maximum Entropy (BME) method. The BME reveals that SARS outbreaks show autocorrelation within certain spatial and temporal distances. We use BME to fit a theoretical covariance model that has a sine hole spatial component and exponential temporal component and obtain the weights of geographical and temporal autocorrelation factors. Using the covariance model, SARS dynamics were estimated and simulated under the most probable conditions. Our study suggests that SARS transmission varies in its epidemiological characteristics and SARS outbreak distributions exhibit palpable clusters on both spatial and temporal scales. In addition, the BME modelling demonstrates that SARS transmission features are affected by spatial heterogeneity, so we analyze potential causes. This may benefit epidemiological control of pandemic infectious diseases. PMID:27597972

Placing invasive species management in a spatiotemporal context.

PubMed

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.

A Spatiotemporal Clustering Approach to Maritime Domain Awareness

DTIC Science & Technology

2013-09-01

1997. [25] M. E. Celebi, “Effective initialization of k-means for color quantization,” 16th IEEE International Conference on Image Processing (ICIP...release; distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Spatiotemporal clustering is the process of grouping...Department of Electrical and Computer Engineering iv THIS PAGE INTENTIONALLY LEFT BLANK v ABSTRACT Spatiotemporal clustering is the process of

A unified framework for gesture recognition and spatiotemporal gesture segmentation.

PubMed

Alon, Jonathan; Athitsos, Vassilis; Yuan, Quan; Sclaroff, Stan

2009-09-01

Within the context of hand gesture recognition, spatiotemporal gesture segmentation is the task of determining, in a video sequence, where the gesturing hand is located and when the gesture starts and ends. Existing gesture recognition methods typically assume either known spatial segmentation or known temporal segmentation, or both. This paper introduces a unified framework for simultaneously performing spatial segmentation, temporal segmentation, and recognition. In the proposed framework, information flows both bottom-up and top-down. A gesture can be recognized even when the hand location is highly ambiguous and when information about when the gesture begins and ends is unavailable. Thus, the method can be applied to continuous image streams where gestures are performed in front of moving, cluttered backgrounds. The proposed method consists of three novel contributions: a spatiotemporal matching algorithm that can accommodate multiple candidate hand detections in every frame, a classifier-based pruning framework that enables accurate and early rejection of poor matches to gesture models, and a subgesture reasoning algorithm that learns which gesture models can falsely match parts of other longer gestures. The performance of the approach is evaluated on two challenging applications: recognition of hand-signed digits gestured by users wearing short-sleeved shirts, in front of a cluttered background, and retrieval of occurrences of signs of interest in a video database containing continuous, unsegmented signing in American Sign Language (ASL).

Mining spatiotemporal patterns of urban dwellers from taxi trajectory data

NASA Astrophysics Data System (ADS)

Mao, Feng; Ji, Minhe; Liu, Ting

2016-06-01

With the widespread adoption of locationaware technology, obtaining long-sequence, massive and high-accuracy spatiotemporal trajectory data of individuals has become increasingly popular in various geographic studies. Trajectory data of taxis, one of the most widely used inner-city travel modes, contain rich information about both road network traffic and travel behavior of passengers. Such data can be used to study the microscopic activity patterns of individuals as well as the macro system of urban spatial structures. This paper focuses on trajectories obtained from GPS-enabled taxis and their applications for mining urban commuting patterns. A novel approach is proposed to discover spatiotemporal patterns of household travel from the taxi trajectory dataset with a large number of point locations. The approach involves three critical steps: spatial clustering of taxi origin-destination (OD) based on urban traffic grids to discover potentially meaningful places, identifying threshold values from statistics of the OD clusters to extract urban jobs-housing structures, and visualization of analytic results to understand the spatial distribution and temporal trends of the revealed urban structures and implied household commuting behavior. A case study with a taxi trajectory dataset in Shanghai, China is presented to demonstrate and evaluate the proposed method.

Effective and efficient analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

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

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

PubMed Central

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,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland 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 patterns of Barmah Forest virus disease in Queensland, Australia.

PubMed

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

2011-01-01

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. 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 (χ(2) = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland 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.

Dynamical topology and statistical properties of spatiotemporal chaos.

PubMed

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.

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

PubMed

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.

Adaptive Local Spatiotemporal Features from RGB-D Data for One-Shot Learning Gesture Recognition.

PubMed

Lin, Jia; Ruan, Xiaogang; Yu, Naigong; Yang, Yee-Hong

2016-12-17

Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF) using fused RGB-D data is proposed. First, motion regions of interest (MRoIs) are adaptively extracted using grayscale and depth velocity variance information to greatly reduce the impact of noise. Then, corners are used as keypoints if their depth, and velocities of grayscale and of depth meet several adaptive local constraints in each MRoI. With further filtering of noise, an accurate and sufficient number of keypoints is obtained within the desired moving body parts (MBPs). Finally, four kinds of multiple descriptors are calculated and combined in extended gradient and motion spaces to represent the appearance and motion features of gestures. The experimental results on the ChaLearn gesture, CAD-60 and MSRDailyActivity3D datasets demonstrate that the proposed feature achieves higher performance compared with published state-of-the-art approaches under the one-shot learning setting and comparable accuracy under the leave-one-out cross validation.

A full time-domain approach to spatio-temporal dynamics of semiconductor lasers. II. Spatio-temporal dynamics

NASA Astrophysics Data System (ADS)

Böhringer, Klaus; Hess, Ortwin

The spatio-temporal dynamics of novel semiconductor lasers is discussed on the basis of a space- and momentum-dependent full time-domain approach. To this means the space-, time-, and momentum-dependent Full-Time Domain Maxwell Semiconductor Bloch equations, derived and discussed in our preceding paper I [K. Böhringer, O. Hess, A full time-domain approach to spatio-temporal dynamics of semiconductor lasers. I. Theoretical formulation], are solved by direct numerical integration. Focussing on the device physics of novel semiconductor lasers that profit, in particular, from recent advances in nanoscience and nanotechnology, we discuss the examples of photonic band edge surface emitting lasers (PBE-SEL) and semiconductor disc lasers (SDLs). It is demonstrated that photonic crystal effects can be obtained for finite crystal structures, and leading to a significant improvement in laser performance such as reduced lasing thresholds. In SDLs, a modern device concept designed to increase the power output of surface-emitters in combination with near-diffraction-limited beam quality, we explore the complex interplay between the intracavity optical fields and the quantum well gain material in SDL structures. Our simulations reveal the dynamical balance between carrier generation due to pumping into high energy states, momentum relaxation of carriers, and stimulated recombination from states near the band edge. Our full time-domain approach is shown to also be an excellent framework for the modelling of the interaction of high-intensity femtosecond and picosecond pulses with semiconductor nanostructures. It is demonstrated that group velocity dispersion, dynamical gain saturation and fast self-phase modulation (SPM) are the main causes for the induced changes and asymmetries in the amplified pulse shape and spectrum of an ultrashort high-intensity pulse. We attest that the time constants of the intraband scattering processes are critical to gain recovery. Moreover, we present

Spatiotemporal Variation in Avian Migration Phenology: Citizen Science Reveals Effects of Climate Change

PubMed Central

Hurlbert, Allen H.; Liang, Zhongfei

2012-01-01

A growing number of studies have documented shifts in avian migratory phenology in response to climate change, and yet there is a large amount of unexplained variation in the magnitude of those responses across species and geographic regions. We use a database of citizen science bird observations to explore spatiotemporal variation in mean arrival dates across an unprecedented geographic extent for 18 common species in North America over the past decade, relating arrival dates to mean minimum spring temperature. Across all species and geographic locations, species shifted arrival dates 0.8 days earlier for every °C of warming of spring temperature, but it was common for some species in some locations to shift as much as 3–6 days earlier per °C. Species that advanced arrival dates the earliest in response to warming were those that migrate more slowly, short distance migrants, and species with broader climatic niches. These three variables explained 63% of the interspecific variation in phenological response. We also identify a latitudinal gradient in the average strength of phenological response, with species shifting arrival earlier at southern latitudes than northern latitudes for the same degree of warming. This observation is consistent with the idea that species must be more phenologically sensitive in less seasonal environments to maintain the same degree of precision in phenological timing. PMID:22384050

Multivariate space-time modelling of multiple air pollutants and their health effects accounting for exposure uncertainty.

PubMed

Huang, Guowen; Lee, Duncan; Scott, E Marian

2018-03-30

The long-term health effects of air pollution are often estimated using a spatio-temporal ecological areal unit study, but this design leads to the following statistical challenges: (1) how to estimate spatially representative pollution concentrations for each areal unit; (2) how to allow for the uncertainty in these estimated concentrations when estimating their health effects; and (3) how to simultaneously estimate the joint effects of multiple correlated pollutants. This article proposes a novel 2-stage Bayesian hierarchical model for addressing these 3 challenges, with inference based on Markov chain Monte Carlo simulation. The first stage is a multivariate spatio-temporal fusion model for predicting areal level average concentrations of multiple pollutants from both monitored and modelled pollution data. The second stage is a spatio-temporal model for estimating the health impact of multiple correlated pollutants simultaneously, which accounts for the uncertainty in the estimated pollution concentrations. The novel methodology is motivated by a new study of the impact of both particulate matter and nitrogen dioxide concentrations on respiratory hospital admissions in Scotland between 2007 and 2011, and the results suggest that both pollutants exhibit substantial and independent health effects. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior.

PubMed

Portugues, Ruben; Feierstein, Claudia E; Engert, Florian; Orger, Michael B

2014-03-19

Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate but ordered pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments systematically reveal the functional architecture of neural circuits underlying a sensorimotor behavior in a vertebrate brain. Copyright © 2014 Elsevier Inc. All rights reserved.

Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior

PubMed Central

Portugues, Ruben; Feierstein, Claudia E.; Engert, Florian; Orger, Michael B.

2014-01-01

Summary Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate, but ordered, pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments reveal, for the first time in a vertebrate, the comprehensive functional architecture of the neural circuits underlying a sensorimotor behavior. PMID:24656252

a Spatiotemporal Aggregation Query Method Using Multi-Thread Parallel Technique Based on Regional Division

NASA Astrophysics Data System (ADS)

Liao, S.; Chen, L.; Li, J.; Xiong, W.; Wu, Q.

2015-07-01

Existing spatiotemporal database supports spatiotemporal aggregation query over massive moving objects datasets. Due to the large amounts of data and single-thread processing method, the query speed cannot meet the application requirements. On the other hand, the query efficiency is more sensitive to spatial variation then temporal variation. In this paper, we proposed a spatiotemporal aggregation query method using multi-thread parallel technique based on regional divison and implemented it on the server. Concretely, we divided the spatiotemporal domain into several spatiotemporal cubes, computed spatiotemporal aggregation on all cubes using the technique of multi-thread parallel processing, and then integrated the query results. By testing and analyzing on the real datasets, this method has improved the query speed significantly.

Rate Dependence of Elementary Rearrangements and Spatiotemporal Correlations in the 3D Flow of Soft Solids

NASA Astrophysics Data System (ADS)

Vasisht, Vishwas V.; Dutta, Sudeep K.; Del Gado, Emanuela; Blair, Daniel L.

2018-01-01

We use a combination of confocal microscopy, rheology, and molecular dynamics simulations to investigate jammed emulsions under shear, by analyzing the 3D droplets rearrangements in the shear frame. Our quantitative analysis of local dynamics reveals elementary nonaffine rearrangements that underlie the onset of the flow at small strains. We find that the mechanism of unjamming and the upturn in the material flow curve are associated to a qualitative change in spatiotemporal correlations of such rearrangements with the applied shear rate. At high shear rates, droplet clusters follow coordinated, stringlike motion. Conversely, at low shear rates, the elementary nonaffine rearrangements exhibit longer-ranged correlations, with complex spatiotemporal patterns. The 3D microscopic details provide novel insights into the specific features of the material flow curve, common to a large class of technologically relevant soft disordered solids and new fundamental ingredients for constitutive models.

Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging

PubMed Central

Gorzolka, Karin; Kölling, Jan; Nattkemper, Tim W.; Niehaus, Karsten

2016-01-01

MALDI mass spectrometry imaging was performed to localize metabolites during the first seven days of the barley germination. Up to 100 mass signals were detected of which 85 signals were identified as 48 different metabolites with highly tissue-specific localizations. Oligosaccharides were observed in the endosperm and in parts of the developed embryo. Lipids in the endosperm co-localized in dependency on their fatty acid compositions with changes in the distributions of diacyl phosphatidylcholines during germination. 26 potentially antifungal hordatines were detected in the embryo with tissue-specific localizations of their glycosylated, hydroxylated, and O-methylated derivates. In order to reveal spatio-temporal patterns in local metabolite compositions, multiple MSI data sets from a time series were analyzed in one batch. This requires a new preprocessing strategy to achieve comparability between data sets as well as a new strategy for unsupervised clustering. The resulting spatial segmentation for each time point sample is visualized in an interactive cluster map and enables simultaneous interactive exploration of all time points. Using this new analysis approach and visualization tool germination-dependent developments of metabolite patterns with single MS position accuracy were discovered. This is the first study that presents metabolite profiling of a cereals’ germination process over time by MALDI MSI with the identification of a large number of peaks of agronomically and industrially important compounds such as oligosaccharides, lipids and antifungal agents. Their detailed localization as well as the MS cluster analyses for on-tissue metabolite profile mapping revealed important information for the understanding of the germination process, which is of high scientific interest. PMID:26938880

Tracking the Spatiotemporal Neural Dynamics of Real-world Object Size and Animacy in the Human Brain.

PubMed

Khaligh-Razavi, Seyed-Mahdi; Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2018-06-07

Animacy and real-world size are properties that describe any object and thus bring basic order into our perception of the visual world. Here, we investigated how the human brain processes real-world size and animacy. For this, we applied representational similarity to fMRI and MEG data to yield a view of brain activity with high spatial and temporal resolutions, respectively. Analysis of fMRI data revealed that a distributed and partly overlapping set of cortical regions extending from occipital to ventral and medial temporal cortex represented animacy and real-world size. Within this set, parahippocampal cortex stood out as the region representing animacy and size stronger than most other regions. Further analysis of the detailed representational format revealed differences among regions involved in processing animacy. Analysis of MEG data revealed overlapping temporal dynamics of animacy and real-world size processing starting at around 150 msec and provided the first neuromagnetic signature of real-world object size processing. Finally, to investigate the neural dynamics of size and animacy processing simultaneously in space and time, we combined MEG and fMRI with a novel extension of MEG-fMRI fusion by representational similarity. This analysis revealed partly overlapping and distributed spatiotemporal dynamics, with parahippocampal cortex singled out as a region that represented size and animacy persistently when other regions did not. Furthermore, the analysis highlighted the role of early visual cortex in representing real-world size. A control analysis revealed that the neural dynamics of processing animacy and size were distinct from the neural dynamics of processing low-level visual features. Together, our results provide a detailed spatiotemporal view of animacy and size processing in the human brain.

Optical Kerr Spatiotemporal Dark-Lump Dynamics of Hydrodynamic Origin

NASA Astrophysics Data System (ADS)

Baronio, Fabio; Wabnitz, Stefan; Kodama, Yuji

2016-04-01

There is considerable fundamental and applicative interest in obtaining nondiffractive and nondispersive spatiotemporal localized wave packets propagating in optical cubic nonlinear or Kerr media. Here, we analytically predict the existence of a novel family of spatiotemporal dark lump solitary wave solutions of the (2 +1 )D nonlinear Schrödinger equation. Dark lumps represent multidimensional holes of light on a continuous wave background. We analytically derive the dark lumps from the hydrodynamic exact soliton solutions of the (2 +1 )D shallow water Kadomtsev-Petviashvili model, inheriting their complex interaction properties. This finding opens a novel path for the excitation and control of optical spatiotemporal waveforms of hydrodynamic footprint and multidimensional optical extreme wave phenomena.

Optical Kerr Spatiotemporal Dark-Lump Dynamics of Hydrodynamic Origin.

PubMed

Baronio, Fabio; Wabnitz, Stefan; Kodama, Yuji

2016-04-29

There is considerable fundamental and applicative interest in obtaining nondiffractive and nondispersive spatiotemporal localized wave packets propagating in optical cubic nonlinear or Kerr media. Here, we analytically predict the existence of a novel family of spatiotemporal dark lump solitary wave solutions of the (2+1)D nonlinear Schrödinger equation. Dark lumps represent multidimensional holes of light on a continuous wave background. We analytically derive the dark lumps from the hydrodynamic exact soliton solutions of the (2+1)D shallow water Kadomtsev-Petviashvili model, inheriting their complex interaction properties. This finding opens a novel path for the excitation and control of optical spatiotemporal waveforms of hydrodynamic footprint and multidimensional optical extreme wave phenomena.

Spatio-temporal Eigenvector Filtering: Application on Bioenergy Crop Impacts

NASA Astrophysics Data System (ADS)

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.

A dynamic spatio-temporal model for spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin; Walsh, Daniel P.

2017-01-01

Analyzing spatial data often requires modeling dependencies created by a dynamic spatio-temporal data generating process. In many applications, a generalized linear mixed model (GLMM) is used with a random effect to account for spatial dependence and to provide optimal spatial predictions. Location-specific covariates are often included as fixed effects in a GLMM and may be collinear with the spatial random effect, which can negatively affect inference. We propose a dynamic approach to account for spatial dependence that incorporates scientific knowledge of the spatio-temporal data generating process. Our approach relies on a dynamic spatio-temporal model that explicitly incorporates location-specific covariates. We illustrate our approach with a spatially varying ecological diffusion model implemented using a computationally efficient homogenization technique. We apply our model to understand individual-level and location-specific risk factors associated with chronic wasting disease in white-tailed deer from Wisconsin, USA and estimate the location the disease was first introduced. We compare our approach to several existing methods that are commonly used in spatial statistics. Our spatio-temporal approach resulted in a higher predictive accuracy when compared to methods based on optimal spatial prediction, obviated confounding among the spatially indexed covariates and the spatial random effect, and provided additional information that will be important for containing disease outbreaks.

Spatiotemporal radiotherapy planning using a global optimization approach

NASA Astrophysics Data System (ADS)

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.

Video quality assessment based on correlation between spatiotemporal motion energies

NASA Astrophysics Data System (ADS)

Yan, Peng; Mou, Xuanqin

2016-09-01

Video quality assessment (VQA) has been a hot research topic because of rapid increase of huge demand of video communications. From the earliest PSNR metric to advanced models that are perceptual aware, researchers have made great progress in this field by introducing properties of human vision system (HVS) into VQA model design. Among various algorithms that model the property of HVS perceiving motion, the spatiotemporal energy model has been validated to be high consistent with psychophysical experiments. In this paper, we take the spatiotemporal energy model into VQA model design by the following steps. 1) According to the pristine spatiotemporal energy model proposed by Adelson et al, we apply the linear filters, which are oriented in space-time and tuned in spatial frequency, to filter the reference and test videos respectively. The outputs of quadrature pairs of above filters are then squared and summed to give two measures of motion energy, which are named rightward and leftward energy responses, respectively. 2) Based on the pristine model, we calculate summation of the rightward and leftward energy responses as spatiotemporal features to represent perceptual quality information for videos, named total spatiotemporal motion energy maps. 3) The proposed FR-VQA model, named STME, is calculated with statistics based on the pixel-wise correlation between the total spatiotemporal motion energy maps of the reference and distorted videos. The STME model was validated on the LIVE VQA Database by comparing with existing FR-VQA models. Experimental results show that STME performs with excellent prediction accuracy and stays in state-of-the-art VQA models.

Comparison of Spatiotemporal Mapping Techniques for Enormous Etl and Exploitation Patterns

NASA Astrophysics Data System (ADS)

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.

Spatio-temporal error growth in the multi-scale Lorenz'96 model

NASA Astrophysics Data System (ADS)

Herrera, S.; Fernández, J.; Rodríguez, M. A.; Gutiérrez, J. M.

2010-07-01

The influence of multiple spatio-temporal scales on the error growth and predictability of atmospheric flows is analyzed throughout the paper. To this aim, we consider the two-scale Lorenz'96 model and study the interplay of the slow and fast variables on the error growth dynamics. It is shown that when the coupling between slow and fast variables is weak the slow variables dominate the evolution of fluctuations whereas in the case of strong coupling the fast variables impose a non-trivial complex error growth pattern on the slow variables with two different regimes, before and after saturation of fast variables. This complex behavior is analyzed using the recently introduced Mean-Variance Logarithmic (MVL) diagram.

Research on spatio-temporal database techniques for spatial information service

NASA Astrophysics Data System (ADS)

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).

A Flexible High-Performance Photoimaging Device Based on Bioinspired Hierarchical Multiple-Patterned Plasmonic Nanostructures.

PubMed

Lee, Yoon Ho; Lee, Tae Kyung; Kim, Hongki; Song, Inho; Lee, Jiwon; Kang, Saewon; Ko, Hyunhyub; Kwak, Sang Kyu; Oh, Joon Hak

2018-03-01

In insect eyes, ommatidia with hierarchical structured cornea play a critical role in amplifying and transferring visual signals to the brain through optic nerves, enabling the perception of various visual signals. Here, inspired by the structure and functions of insect ommatidia, a flexible photoimaging device is reported that can simultaneously detect and record incoming photonic signals by vertically stacking an organic photodiode and resistive memory device. A single-layered, hierarchical multiple-patterned back reflector that can exhibit various plasmonic effects is incorporated into the organic photodiode. The multiple-patterned flexible organic photodiodes exhibit greatly enhanced photoresponsivity due to the increased light absorption in comparison with the flat systems. Moreover, the flexible photoimaging device shows a well-resolved spatiotemporal mapping of optical signals with excellent operational and mechanical stabilities at low driving voltages below half of the flat systems. Theoretical calculation and scanning near-field optical microscopy analyses clearly reveal that multiple-patterned electrodes have much stronger surface plasmon coupling than flat and single-patterned systems. The developed methodology provides a versatile and effective route for realizing high-performance optoelectronic and photonic systems. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characteristics, processes, and causes of the spatio-temporal variabilities of the East Asian monsoon system

NASA Astrophysics Data System (ADS)

Huang, Ronghui; Chen, Jilong; Wang, Lin; Lin, Zhongda

2012-09-01

Recent advances in the study of the characteristics, processes, and causes of spatio-temporal variabilities of the East Asian monsoon (EAM) system are reviewed in this paper. The understanding of the EAM system has improved in many aspects: the basic characteristics of horizontal and vertical structures, the annual cycle of the East Asian summer monsoon (EASM) system and the East Asian winter monsoon (EAWM) system, the characteristics of the spatio-temporal variabilities of the EASM system and the EAWM system, and especially the multiple modes of the EAM system and their spatio-temporal variabilities. Some new results have also been achieved in understanding the atmosphere-ocean interaction and atmosphere-land interaction processes that affect the variability of the EAM system. Based on recent studies, the EAM system can be seen as more than a circulation system, it can be viewed as an atmosphere-ocean-land coupled system, namely, the EAM climate system. In addition, further progress has been made in diagnosing the internal physical mechanisms of EAM climate system variability, especially regarding the characteristics and properties of the East Asia-Pacific (EAP) teleconnection over East Asia and the North Pacific, the "Silk Road" teleconnection along the westerly jet stream in the upper troposphere over the Asian continent, and the dynamical effects of quasi-stationary planetary wave activity on EAM system variability. At the end of the paper, some scientific problems regarding understanding the EAM system variability are proposed for further study.

Spatio-temporal Outlier Detection in Precipitation Data

NASA Astrophysics Data System (ADS)

Wu, Elizabeth; Liu, Wei; Chawla, Sanjay

The detection of outliers from spatio-temporal data is an important task due to the increasing amount of spatio-temporal data available and the need to understand and interpret it. Due to the limitations of current data mining techniques, new techniques to handle this data need to be developed. We propose a spatio-temporal outlier detection algorithm called Outstretch, which discovers the outlier movement patterns of the top-k spatial outliers over several time periods. The top-k spatial outliers are found using the Exact-Grid Top- k and Approx-Grid Top- k algorithms, which are an extension of algorithms developed by Agarwal et al. [1]. Since they use the Kulldorff spatial scan statistic, they are capable of discovering all outliers, unaffected by neighbouring regions that may contain missing values. After generating the outlier sequences, we show one way they can be interpreted, by comparing them to the phases of the El Niño Southern Oscilliation (ENSO) weather phenomenon to provide a meaningful analysis of the results.

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

ERIC Educational Resources Information Center

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…

Organic nanoparticle systems for spatiotemporal control of multimodal chemotherapy

PubMed Central

Meng, Fanfei; Han, Ning; Yeo, Yoon

2017-01-01

Introduction Chemotherapeutic drugs are used in combination to target multiple mechanisms involved in cancer cell survival and proliferation. Carriers are developed to deliver drug combinations to common target tissues in optimal ratios and desirable sequences. Nanoparticles (NP) have been a popular choice for this purpose due to their ability to increase the circulation half-life and tumor accumulation of a drug. Areas covered We review organic NP carriers based on polymers, proteins, peptides, and lipids for simultaneous delivery of multiple anticancer drugs, drug/sensitizer combinations, drug/photodynamic- or photothermal therapy combinations, and drug/gene therapeutics with examples in the past three years. Sequential delivery of drug combinations, based on either sequential administration or built-in release control, is introduced with an emphasis on the mechanistic understanding of such control. Expert opinion Recent studies demonstrate how a drug carrier can contribute to co-localizing drug combinations in optimal ratios and dosing sequences to maximize the synergistic effects. We identify several areas for improvement in future research, including the choice of drug combinations, circulation stability of carriers, spatiotemporal control of drug release, and the evaluation and clinical translation of combination delivery. PMID:27476442

Multiple remote sensing data sources to assess spatio-temporal patterns of fire incidence over Campos Amazônicos Savanna Vegetation Enclave (Brazilian Amazon).

PubMed

Alves, Daniel Borini; Pérez-Cabello, Fernando

2017-12-01

Fire activity plays an important role in the past, present and future of Earth system behavior. Monitoring and assessing spatial and temporal fire dynamics have a fundamental relevance in the understanding of ecological processes and the human impacts on different landscapes and multiple spatial scales. This work analyzes the spatio-temporal distribution of burned areas in one of the biggest savanna vegetation enclaves in the southern Brazilian Amazon, from 2000 to 2016, deriving information from multiple remote sensing data sources (Landsat and MODIS surface reflectance, TRMM pluviometry and Vegetation Continuous Field tree cover layers). A fire scars database with 30 m spatial resolution was generated using a Landsat time series. MODIS daily surface reflectance was used for accurate dating of the fire scars. TRMM pluviometry data were analyzed to dynamically establish time limits of the yearly dry season and burning periods. Burned area extent, frequency and recurrence were quantified comparing the results annually/seasonally. Additionally, Vegetation Continuous Field tree cover layers were used to analyze fire incidence over different types of tree cover domains. In the last seventeen years, 1.03millionha were burned within the study area, distributed across 1432 fire occurrences, highlighting 2005, 2010 and 2014 as the most affected years. Middle dry season fires represent 86.21% of the total burned areas and 32.05% of fire occurrences, affecting larger amount of higher density tree surfaces than other burning periods. The results provide new insights into the analysis of burned areas of the neotropical savannas, spatially and statistically reinforcing important aspects linked to the seasonality patterns of fire incidence in this landscape. Copyright © 2017 Elsevier B.V. All rights reserved.

Metabarcoding reveals environmental factors influencing spatio-temporal variation in pelagic micro-eukaryotes.

PubMed

Brannock, Pamela M; Ortmann, Alice C; Moss, Anthony G; Halanych, Kenneth M

2016-08-01

Marine environments harbour a vast diversity of micro-eukaryotic organisms (protists and other small eukaryotes) that play important roles in structuring marine ecosystems. However, micro-eukaryote diversity is not well understood. Likewise, knowledge is limited regarding micro-eukaryote spatial and seasonal distribution, especially over long temporal scales. Given the importance of this group for mobilizing energy from lower trophic levels near the base of the food chain to larger organisms, assessing community stability, diversity and resilience is important to understand ecosystem health. Herein, we use a metabarcoding approach to examine pelagic micro-eukaryote communities over a 2.5-year time series. Bimonthly surface sampling (July 2009 to December 2011) was conducted at four locations within Mobile Bay (Bay) and along the Alabama continental shelf (Shelf). Alpha-diversity only showed significant differences in Shelf sites, with the greatest differences observed between summer and winter. Beta-diversity showed significant differences in community composition in relation to season and the Bay was dominated by diatoms, while the Shelf was characterized by dinoflagellates and copepods. The northern Gulf of Mexico is heavily influenced by the Mobile River Basin, which brings low-salinity nutrient-rich water mostly during winter and spring. Community composition was correlated with salinity, temperature and dissolved silicate. However, species interactions (e.g. predation and parasitism) may also contribute to the observed variation, especially on the Shelf, which warrants further exploration. Metabarcoding revealed clear patterns in surface pelagic micro-eukaryote communities that were consistent over multiple years, demonstrating how these techniques could be greatly beneficial to ecological monitoring and management over temporal scales. © 2016 John Wiley & Sons Ltd.

Spatio-Temporal Cellular Imaging of Polymer-pDNA Nanocomplexes Affords In Situ Morphology and Trafficking Trends

PubMed Central

Ingle, Nilesh P.; Lian, Xue; Reineke, Theresa M.

2013-01-01

Synthetic polymers are ubiquitous in the development of drug and polynucleotide delivery vehicles, offering promise for personalized medicine. However, the polymer structure plays a central yet elusive role in dictating the efficacy, safety, mechanisms, and kinetics of therapeutic transport in a spatial and temporal manner. Here, we decipher the intracellular evolutionary pathways pertaining to shape, size, location, and mechanism of four structurally-divergent polymer vehicles (Tr455, Tr477, jetPEI™ and Glycofect™) that create colloidal nanoparticles (polyplexes) when complexed with fluorescently-labeled plasmid DNA (pDNA). Multiple high resolution tomographic images of whole HeLa (human cervical adenocarcinoma) cells were captured via confocal microscopy at 4, 8, 12 and 24 hours. The images were reconstructed to visualize and quantify trends in situ in a four-dimensional spatio-temporal manner. The data revealed heretofore-unseen images of polyplexes in situ and structure-function relationships, i.e., Glycofect™ polyplexes are trafficked as the smallest polyplex complexes and Tr455 polyplexes have expedited translocation to the perinuclear region. Also, all of the polyplex types appeared to be preferentially internalized and trafficked via early endosomes affiliated with caveolae, a Rab-5-dependent pathway, actin, and microtubules. PMID:24007201

Mercury Toolset for Spatiotemporal Metadata

NASA Technical Reports Server (NTRS)

Wilson, Bruce E.; Palanisamy, Giri; Devarakonda, Ranjeet; Rhyne, B. Timothy; Lindsley, Chris; Green, James

2010-01-01

Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily) harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

Mercury Toolset for Spatiotemporal Metadata

NASA Astrophysics Data System (ADS)

Devarakonda, Ranjeet; Palanisamy, Giri; Green, James; Wilson, Bruce; Rhyne, B. Timothy; Lindsley, Chris

2010-06-01

Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily)harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banerjee, Tanmoy, E-mail: tbanerjee@phys.buruniv.ac.in; Paul, Bishwajit; Sarkar, B. C.

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 strengthmore » 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.« less

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

PubMed

Banerjee, Tanmoy; Paul, Bishwajit; Sarkar, B C

2014-03-01

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

NASA Astrophysics Data System (ADS)

Banerjee, Tanmoy; Paul, Bishwajit; Sarkar, B. C.

2014-03-01

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.

The range of the mange: Spatiotemporal patterns of sarcoptic mange in red foxes (Vulpes vulpes) as revealed by camera trapping

PubMed Central

Odden, Morten; Linnell, John D. C.; Odden, John

2017-01-01

Sarcoptic mange is a widely distributed disease that affects numerous mammalian species. We used camera traps to investigate the apparent prevalence and spatiotemporal dynamics of sarcoptic mange in a red fox population in southeastern Norway. We monitored red foxes for five years using 305 camera traps distributed across an 18000 km2 area. A total of 6581 fox events were examined to visually identify mange compatible lesions. We investigated factors associated with the occurrence of mange by using logistic models within a Bayesian framework, whereas the spatiotemporal dynamics of the disease were analysed with space-time scan statistics. The apparent prevalence of the disease fluctuated over the study period with a mean of 3.15% and credible interval [1.25, 6.37], and our best logistic model explaining the presence of red foxes with mange-compatible lesions included time since the beginning of the study and the interaction between distance to settlement and season as explanatory variables. The scan analyses detected several potential clusters of the disease that varied in persistence and size, and the locations in the cluster with the highest probability were closer to human settlements than the other survey locations. Our results indicate that red foxes in an advanced stage of the disease are most likely found closer to human settlements during periods of low wild prey availability (winter). We discuss different potential causes. Furthermore, the disease appears to follow a pattern of small localized outbreaks rather than sporadic isolated events. PMID:28423011

Global exosome transcriptome profiling reveals biomarkers for multiple sclerosis.

PubMed

Selmaj, Igor; Cichalewska, Maria; Namiecinska, Magdalena; Galazka, Grazyna; Horzelski, Wojciech; Selmaj, Krzysztof W; Mycko, Marcin P

2017-05-01

Accumulating evidence supports a role for exosomes in immune regulation. In this study, we investigated the total circulating exosome transcriptome in relapsing-remitting multiple sclerosis (RRMS) patients and healthy controls (HC). Next generation sequencing (NGS) was used to define the global RNA profile of serum exosomes in 19 RRMS patients (9 in relapse, 10 in remission) and 10 HC. We analyzed 5 million reads and >50,000 transcripts per sample, including a detailed analysis of microRNAs (miRNAs) differentially expressed in RRMS. The discovery set data were validated by quantification using digital quantitative polymerase chain reaction with an independent cohort of 63 RRMS patients (33 in relapse, 30 in remission) and 32 HC. Exosomal RNA NGS revealed that of 15 different classes of transcripts detected, 4 circulating exosomal sequences within the miRNA category were differentially expressed in RRMS patients versus HC: hsa-miR-122-5p, hsa-miR-196b-5p, hsa-miR-301a-3p, and hsa-miR-532-5p. Serum exosomal expression of these miRNAs was significantly decreased during relapse in RRMS. These miRNAs were also decreased in patients with a gadolinium enhancement on brain magnetic resonance imaging. In vitro secretion of these miRNAs by peripheral blood mononuclear cells was also significantly impaired in RRMS. These data show that circulating exosomes have a distinct RNA profile in RRMS. Because putative targets for these miRNAs include the signal transducer and activator of transcription 3 and the cell cycle regulator aryl hydrocarbon receptor, the data suggest a disturbed cell-to-cell communication in this disease. Thus, exosomal miRNAs might represent a useful biomarker to distinguish multiple sclerosis relapse. Ann Neurol 2017;81:703-717. © 2017 American Neurological Association.

Transition to spatiotemporal chaos in a two-dimensional hydrodynamic system.

PubMed

Pirat, Christophe; Naso, Aurore; Meunier, Jean-Louis; Maïssa, Philippe; Mathis, Christian

2005-04-08

We study the transition to spatiotemporal chaos in a two-dimensional hydrodynamic experiment where liquid columns take place in the gravity induced instability of a liquid film. The film is formed below a plane grid which is used as a porous media and is continuously supplied with a controlled flow rate. This system can be either ordered (on a hexagonal structure) or disordered depending on the flow rate. We observe, for the first time in an initially structured state, a subcritical transition to spatiotemporal disorder which arises through spatiotemporal intermittency. Statistics of numbers, creations, and fusions of columns are investigated. We exhibit a critical behavior close to the directed percolation one.

From Flashes to Edges to Objects: Recovery of Local Edge Fragments Initiates Spatiotemporal Boundary Formation

PubMed Central

Erlikhman, Gennady; Kellman, Philip J.

2016-01-01

Spatiotemporal boundary formation (SBF) is the perception of illusory boundaries, global form, and global motion from spatially and temporally sparse transformations of texture elements (Shipley and Kellman, 1993a, 1994; Erlikhman and Kellman, 2015). It has been theorized that the visual system uses positions and times of element transformations to extract local oriented edge fragments, which then connect by known interpolation processes to produce larger contours and shapes in SBF. To test this theory, we created a novel display consisting of a sawtooth arrangement of elements that disappeared and reappeared sequentially. Although apparent motion along the sawtooth would be expected, with appropriate spacing and timing, the resulting percept was of a larger, moving, illusory bar. This display approximates the minimal conditions for visual perception of an oriented edge fragment from spatiotemporal information and confirms that such events may be initiating conditions in SBF. Using converging objective and subjective methods, experiments showed that edge formation in these displays was subject to a temporal integration constraint of ~80 ms between element disappearances. The experiments provide clear support for models of SBF that begin with extraction of local edge fragments, and they identify minimal conditions required for this process. We conjecture that these results reveal a link between spatiotemporal object perception and basic visual filtering. Motion energy filters have usually been studied with orientation given spatially by luminance contrast. When orientation is not given in static frames, these same motion energy filters serve as spatiotemporal edge filters, yielding local orientation from discrete element transformations over time. As numerous filters of different characteristic orientations and scales may respond to any simple SBF stimulus, we discuss the aperture and ambiguity problems that accompany this conjecture and how they might be resolved

Spatiotemporal Interpolation for Environmental Modelling

PubMed Central

Susanto, Ferry; de Souza, Paulo; He, Jing

2016-01-01

A variation of the reduction-based approach to spatiotemporal interpolation (STI), in which time is treated independently from the spatial dimensions, is proposed in this paper. We reviewed and compared three widely-used spatial interpolation techniques: ordinary kriging, inverse distance weighting and the triangular irregular network. We also proposed a new distribution-based distance weighting (DDW) spatial interpolation method. In this study, we utilised one year of Tasmania’s South Esk Hydrology model developed by CSIRO. Root mean squared error statistical methods were performed for performance evaluations. Our results show that the proposed reduction approach is superior to the extension approach to STI. However, the proposed DDW provides little benefit compared to the conventional inverse distance weighting (IDW) method. We suggest that the improved IDW technique, with the reduction approach used for the temporal dimension, is the optimal combination for large-scale spatiotemporal interpolation within environmental modelling applications. PMID:27509497

An event-version-based spatio-temporal modeling approach and its application in the cadastral management

NASA Astrophysics Data System (ADS)

Li, Yangdong; Han, Zhen; Liao, Zhongping

2009-10-01

Spatiality, temporality, legality, accuracy and continuality are characteristic of cadastral information, and the cadastral management demands that the cadastral data should be accurate, integrated and updated timely. It's a good idea to build an effective GIS management system to manage the cadastral data which are characterized by spatiality and temporality. Because no sound spatio-temporal data models have been adopted, however, the spatio-temporal characteristics of cadastral data are not well expressed in the existing cadastral management systems. An event-version-based spatio-temporal modeling approach is first proposed from the angle of event and version. Then with the help of it, an event-version-based spatio-temporal cadastral data model is built to represent spatio-temporal cadastral data. At last, the previous model is used in the design and implementation of a spatio-temporal cadastral management system. The result of the application of the system shows that the event-version-based spatio-temporal data model is very suitable for the representation and organization of cadastral data.

A Flexible Spatiotemporal Method for Fusing Satellite Images with Different Resolutions

USDA-ARS?s Scientific Manuscript database

Studies of land surface dynamics in heterogeneous landscapes often require remote sensing data with 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 ...

Adaptive Local Spatiotemporal Features from RGB-D Data for One-Shot Learning Gesture Recognition

PubMed Central

Lin, Jia; Ruan, Xiaogang; Yu, Naigong; Yang, Yee-Hong

2016-01-01

Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF) using fused RGB-D data is proposed. First, motion regions of interest (MRoIs) are adaptively extracted using grayscale and depth velocity variance information to greatly reduce the impact of noise. Then, corners are used as keypoints if their depth, and velocities of grayscale and of depth meet several adaptive local constraints in each MRoI. With further filtering of noise, an accurate and sufficient number of keypoints is obtained within the desired moving body parts (MBPs). Finally, four kinds of multiple descriptors are calculated and combined in extended gradient and motion spaces to represent the appearance and motion features of gestures. The experimental results on the ChaLearn gesture, CAD-60 and MSRDailyActivity3D datasets demonstrate that the proposed feature achieves higher performance compared with published state-of-the-art approaches under the one-shot learning setting and comparable accuracy under the leave-one-out cross validation. PMID:27999337

Spatiotemporal Patterns and Predictability of Cyberattacks

PubMed Central

Chen, Yu-Zhong; Huang, Zi-Gang; Xu, Shouhuai; Lai, Ying-Cheng

2015-01-01

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. PMID:25992837

Spatiotemporal patterns and predictability of cyberattacks.

PubMed

Chen, Yu-Zhong; Huang, Zi-Gang; Xu, Shouhuai; Lai, Ying-Cheng

2015-01-01

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.

Intrinsic islet heterogeneity and gap junction coupling determine spatiotemporal Ca²⁺ wave dynamics.

PubMed

Benninger, Richard K P; Hutchens, Troy; Head, W Steven; McCaughey, Michael J; Zhang, Min; Le Marchand, Sylvain J; Satin, Leslie S; Piston, David W

2014-12-02

Insulin is released from the islets of Langerhans in discrete pulses that are linked to synchronized oscillations of intracellular free calcium ([Ca(2+)]i). Associated with each synchronized oscillation is a propagating calcium wave mediated by Connexin36 (Cx36) gap junctions. A computational islet model predicted that waves emerge due to heterogeneity in β-cell function throughout the islet. To test this, we applied defined patterns of glucose stimulation across the islet using a microfluidic device and measured how these perturbations affect calcium wave propagation. We further investigated how gap junction coupling regulates spatiotemporal [Ca(2+)]i dynamics in the face of heterogeneous glucose stimulation. Calcium waves were found to originate in regions of the islet having elevated excitability, and this heterogeneity is an intrinsic property of islet β-cells. The extent of [Ca(2+)]i elevation across the islet in the presence of heterogeneity is gap-junction dependent, which reveals a glucose dependence of gap junction coupling. To better describe these observations, we had to modify the computational islet model to consider the electrochemical gradient between neighboring β-cells. These results reveal how the spatiotemporal [Ca(2+)]i dynamics of the islet depend on β-cell heterogeneity and cell-cell coupling, and are important for understanding the regulation of coordinated insulin release across the islet. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Instabilities and spatiotemporal patterns behind predator invasions with nonlocal prey competition.

PubMed

Merchant, Sandra M; Nagata, Wayne

2011-12-01

We study the influence of nonlocal intraspecies prey competition on the spatiotemporal patterns arising behind predator invasions in two oscillatory reaction-diffusion integro-differential models. We use three common types of integral kernels as well as develop a caricature system, to describe the influence of the standard deviation and kurtosis of the kernel function on the patterns observed. We find that nonlocal competition can destabilize the spatially homogeneous state behind the invasion and lead to the formation of complex spatiotemporal patterns, including stationary spatially periodic patterns, wave trains and irregular spatiotemporal oscillations. In addition, the caricature system illustrates how large standard deviation and low kurtosis facilitate the formation of these spatiotemporal patterns. This suggests that nonlocal competition may be an important mechanism underlying spatial pattern formation, particularly in systems where the competition between individuals varies over space in a platykurtic manner. Copyright © 2011 Elsevier Inc. All rights reserved.

Detailed spatiotemporal impacts of El Niño on phytoplankton biomass in the South China Sea

NASA Astrophysics Data System (ADS)

Siswanto, Eko; Ye, Haijun; Yamazaki, Dai; Tang, DanLing

2017-04-01

The lagging and leading correlations among satellite observations, reanalyzed biogeophysical data, and the Nino3.4 El Niño index were investigated to reveal the impacts of El Niño on the phytoplankton biomass (chlorophyll a [Chl a]) in the South China Sea (SCS), in an attempt to identify the probable responsible factors in greater spatiotemporal detail. A basin-scale high Chl a concentration during the developing phase of El Niño changed to basin-scale low Chl a during the weakening phase. Cyclonic wind circulation in the northern basin, increased wind speed in the southern basin, and strengthened upwelling off the Vietnamese coast likely caused a basin-scale nutrient increase during the developing phase of an El Niño event; the opposite conditions led to low nutrient levels during the weakening phase. Decreases in Chl a east of the Vietnamese coast and northwest of Borneo Island were due to decreases in nutrients supplied by rivers. These spatiotemporal changes are considered biogeophysical responses to a variety of types of El Niño. Regardless of the El Niño type, reanalyzing biogeophysical data sets during central Pacific warming separately from those during eastern Pacific warming is recommended for a more robust understanding of the detailed spatiotemporal impacts of different El Niño types on the biogeophysical environment of the SCS.

The influence of natural factors on the spatio-temporal distribution of Oncomelania hupensis.

PubMed

Cheng, Gong; Li, Dan; Zhuang, Dafang; Wang, Yong

2016-12-01

We analyzed the influence of natural factors, such as temperature, rainfall, vegetation and hydrology, on the spatio-temporal distribution of Oncomelania hupensis and explored the leading factors influencing these parameters. The results will provide reference methods and theoretical a basis for the schistosomiasis control. GIS (Geographic Information System) spatial display and analysis were used to describe the spatio-temporal distribution of Oncomelania hupensis in the study area (Dongting Lake in Hunan Province) from 2004 to 2011. Correlation analysis was used to detect the natural factors associated with the spatio-temporal distribution of O. hupensis. Spatial regression analysis was used to quantitatively analyze the effects of related natural factors on the spatio-temporal distribution of snails and explore the dominant factors influencing this parameter. (1) Overall, the spatio-temporal distribution of O. hupensis was governed by the comprehensive effects of natural factors. In the study area, the average density of living snails showed a downward trend, with the exception of a slight rebound in 2009. The density of living snails showed significant spatial clustering, and the degree of aggregation was initially weak but enhanced later. Regions with high snail density and towns with an HH distribution pattern were mostly distributed in the plain areas in the northwestern and inlet and outlet of the lake. (2) There were space-time differences in the influence of natural factors on the spatio-temporal distribution of O. hupensis. Temporally, the comprehensive influence of natural factors on snail distribution increased first and then decreased. Natural factors played an important role in snail distribution in 2005, 2006, 2010 and 2011. Spatially, it decreased from the northeast to the southwest. Snail distributions in more than 20 towns located along the Yuanshui River and on the west side of the Lishui River were less affected by natural factors, whereas

Single-molecule chemo-mechanical unfolding reveals multiple transition state barriers in a small single-domain protein

NASA Astrophysics Data System (ADS)

Guinn, Emily J.; Jagannathan, Bharat; Marqusee, Susan

2015-04-01

A fundamental question in protein folding is whether proteins fold through one or multiple trajectories. While most experiments indicate a single pathway, simulations suggest proteins can fold through many parallel pathways. Here, we use a combination of chemical denaturant, mechanical force and site-directed mutations to demonstrate the presence of multiple unfolding pathways in a simple, two-state folding protein. We show that these multiple pathways have structurally different transition states, and that seemingly small changes in protein sequence and environment can strongly modulate the flux between the pathways. These results suggest that in vivo, the crowded cellular environment could strongly influence the mechanisms of protein folding and unfolding. Our study resolves the apparent dichotomy between experimental and theoretical studies, and highlights the advantage of using a multipronged approach to reveal the complexities of a protein's free-energy landscape.

What Is Spatio-Temporal Data Warehousing?

NASA Astrophysics Data System (ADS)

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.

Spatiotemporal dynamics of the spin transition in [Fe (HB(tz)3) 2] single crystals

NASA Astrophysics Data System (ADS)

Ridier, Karl; Rat, Sylvain; Shepherd, Helena J.; Salmon, Lionel; Nicolazzi, William; Molnár, Gábor; Bousseksou, Azzedine

2017-10-01

The spatiotemporal dynamics of the spin transition have been thoroughly investigated in single crystals of the mononuclear spin-crossover (SCO) complex [Fe (HB (tz )3)2] (tz = 1 ,2 ,4-triazol-1-yl) by optical microscopy. This compound exhibits an abrupt spin transition centered at 334 K with a narrow thermal hysteresis loop of ˜1 K (first-order transition). Most single crystals of this compound reveal exceptional resilience upon repeated switching (several hundred cycles), which allowed repeatable and quantitative measurements of the spatiotemporal dynamics of the nucleation and growth processes to be carried out. These experiments revealed remarkable properties of the thermally induced spin transition: high stability of the thermal hysteresis loop, unprecedented large velocities of the macroscopic low-spin/high-spin phase boundaries up to 500 µm/s, and no visible dependency on the temperature scan rate. We have also studied the dynamics of the low-spin → high-spin transition induced by a local photothermal excitation generated by a spatially localized (Ø = 2 μ m ) continuous laser beam. Interesting phenomena have been evidenced both in quasistatic and dynamic conditions (e.g., threshold effects and long incubation periods, thermal activation of the phase boundary propagation, stabilization of the crystal in a stationary biphasic state, and thermal cutoff frequency). These measurements demonstrated the importance of thermal effects in the transition dynamics, and they enabled an accurate determination of the thermal properties of the SCO compound in the framework of a simple theoretical model.

A spatio-temporal analysis of suicide in El Salvador.

PubMed

Carcach, Carlos

2017-04-20

In 2012, international statistics showed El Salvador's suicide rate as 40th in the world and the highest in Latin America. Over the last 15 years, national statistics show the suicide death rate declining as opposed to an increasing rate of homicide. Though completed suicide is an important social and health issue, little is known about its prevalence, incidence, etiology and spatio-temporal behavior. The primary objective of this study was to examine completed suicide and homicide using the stream analogy to lethal violence within a spatio-temporal framework. A Bayesian model was applied to examine the spatio-temporal evolution of the tendency of completed suicide over homicide in El Salvador. Data on numbers of suicides and homicides at the municipal level were obtained from the Instituto de Medicina Legal (IML) and population counts, from the Dirección General de Estadística y Censos (DIGESTYC), for the period of 2002 to 2012. Data on migration were derived from the 2007 Population Census, and inequality data were obtained from a study by Damianović, Valenzuela and Vera. The data reveal a stable standardized rate of total lethal violence (completed suicide plus homicide) across municipalities over time; a decline in suicide; and a standardized suicide rate decreasing with income inequality but increasing with social isolation. Municipalities clustered in terms of both total lethal violence and suicide standardized rates. Spatial effects for suicide were stronger among municipalities located in the north-east and center-south sides of the country. New clusters of municipalities with large suicide standardized rates were detected in the north-west, south-west and center-south regions, all of which are part of time-stable clusters of homicide. Prevention efforts to reduce income inequality and mitigate the negative effects of weak relational systems should focus upon municipalities forming time-persistent clusters with a large rate of death by suicide. In

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

Fast multidimensional ensemble empirical mode decomposition for the analysis of big spatio-temporal datasets.

PubMed

Wu, Zhaohua; Feng, Jiaxin; Qiao, Fangli; Tan, Zhe-Min

2016-04-13

In this big data era, it is more urgent than ever to solve two major issues: (i) fast data transmission methods that can facilitate access to data from non-local sources and (ii) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and a fast algorithm. This paper introduces the recently developed adaptive and spatio-temporally local analysis method, namely the fast multidimensional ensemble empirical mode decomposition (MEEMD), for the analysis of a large spatio-temporal dataset. The original MEEMD uses ensemble empirical mode decomposition to decompose time series at each spatial grid and then pieces together the temporal-spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking advantage of the high efficiency of the expression using principal component analysis/empirical orthogonal function analysis for spatio-temporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. We also explain the basic principles behind the fast MEEMD through decomposing principal components instead of original grid-wise time series to speed up computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (i) compress data with a compression rate of one to two orders; and (ii) speed-up the MEEMD algorithm by one to two orders. © 2016 The Authors.

Spatiotemporal Coding of Individual Chemicals by the Gustatory System

PubMed Central

Reiter, Sam; Campillo Rodriguez, Chelsey; Sun, Kui

2015-01-01

Four of the five major sensory systems (vision, olfaction, somatosensation, and audition) are thought to use different but partially overlapping sets of neurons to form unique representations of vast numbers of stimuli. The only exception is gustation, which is thought to represent only small numbers of basic taste categories. However, using new methods for delivering tastant chemicals and making electrophysiological recordings from the tractable gustatory system of the moth Manduca sexta, we found chemical-specific information is as follows: (1) initially encoded in the population of gustatory receptor neurons as broadly distributed spatiotemporal patterns of activity; (2) dramatically integrated and temporally transformed as it propagates to monosynaptically connected second-order neurons; and (3) observed in tastant-specific behavior. Our results are consistent with an emerging view of the gustatory system: rather than constructing basic taste categories, it uses a spatiotemporal population code to generate unique neural representations of individual tastant chemicals. SIGNIFICANCE STATEMENT Our results provide a new view of taste processing. Using a new, relatively simple model system and a new set of techniques to deliver taste stimuli and to examine gustatory receptor neurons and their immediate followers, we found no evidence for labeled line connectivity, or basic taste categories such as sweet, salty, bitter, and sour. Rather, individual tastant chemicals are represented as patterns of spiking activity distributed across populations of receptor neurons. These representations are transformed substantially as multiple types of receptor neurons converge upon follower neurons, leading to a combinatorial coding format that uniquely, rapidly, and efficiently represents individual taste chemicals. Finally, we found that the information content of these neurons can drive tastant-specific behavior. PMID:26338341

Spatio-temporal conditional inference and hypothesis tests for neural ensemble spiking precision

PubMed Central

Harrison, Matthew T.; Amarasingham, Asohan; Truccolo, Wilson

2014-01-01

The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatio-temporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference, not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatio-temporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis testing adjustments and to design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peri-stimulus time histogram (PSTH) or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable in other areas of neurostatistical analysis. PMID:25380339

The proximal-to-distal sequence in upper-limb motions on multiple levels and time scales.

PubMed

Serrien, Ben; Baeyens, Jean-Pierre

2017-10-01

The proximal-to-distal sequence is a phenomenon that can be observed in a large variety of motions of the upper limbs in both humans and other mammals. The mechanisms behind this sequence are not completely understood and motor control theories able to explain this phenomenon are currently incomplete. The aim of this narrative review is to take a theoretical constraints-led approach to the proximal-to-distal sequence and provide a broad multidisciplinary overview of relevant literature. This sequence exists at multiple levels (brain, spine, muscles, kinetics and kinematics) and on multiple time scales (motion, motor learning and development, growth and possibly even evolution). We hypothesize that the proximodistal spatiotemporal direction on each time scale and level provides part of the organismic constraints that guide the dynamics at the other levels and time scales. The constraint-led approach in this review may serve as a first onset towards integration of evidence and a framework for further experimentation to reveal the dynamics of the proximal-to-distal sequence. Copyright © 2017 Elsevier B.V. All rights reserved.

How Question Types Reveal Student Thinking: An Experimental Comparison of Multiple-True-False and Free-Response Formats

PubMed Central

Hubbard, Joanna K.; Potts, Macy A.; Couch, Brian A.

2017-01-01

Assessments represent an important component of undergraduate courses because they affect how students interact with course content and gauge student achievement of course objectives. To make decisions on assessment design, instructors must understand the affordances and limitations of available question formats. Here, we use a crossover experimental design to identify differences in how multiple-true-false (MTF) and free-response (FR) exam questions reveal student thinking regarding specific conceptions. We report that correct response rates correlate across the two formats but that a higher percentage of students provide correct responses for MTF questions. We find that MTF questions reveal a high prevalence of students with mixed (correct and incorrect) conceptions, while FR questions reveal a high prevalence of students with partial (correct and unclear) conceptions. These results suggest that MTF question prompts can direct students to address specific conceptions but obscure nuances in student thinking and may overestimate the frequency of particular conceptions. Conversely, FR questions provide a more authentic portrait of student thinking but may face limitations in their ability to diagnose specific, particularly incorrect, conceptions. We further discuss an intrinsic tension between question structure and diagnostic capacity and how instructors might use multiple formats or hybrid formats to overcome these obstacles. PMID:28450446

A flexible spatiotemporal method for fusing satellite images with different resolutions

Treesearch

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...

Spatiotemporal analysis of dengue fever in Nepal from 2010 to 2014.

PubMed

Acharya, Bipin Kumar; Cao, ChunXiang; Lakes, Tobia; Chen, Wei; Naeem, Shahid

2016-08-22

Due to recent emergence, dengue is becoming one of the major public health problems in Nepal. The numbers of reported dengue cases in general and the area with reported dengue cases are both continuously increasing in recent years. However, spatiotemporal patterns and clusters of dengue have not been investigated yet. This study aims to fill this gap by analyzing spatiotemporal patterns based on monthly surveillance data aggregated at district. Dengue cases from 2010 to 2014 at district level were collected from the Nepal government's health and mapping agencies respectively. GeoDa software was used to map crude incidence, excess hazard and spatially smoothed incidence. Cluster analysis was performed in SaTScan software to explore spatiotemporal clusters of dengue during the above-mentioned time period. Spatiotemporal distribution of dengue fever in Nepal from 2010 to 2014 was mapped at district level in terms of crude incidence, excess risk and spatially smoothed incidence. Results show that the distribution of dengue fever was not random but clustered in space and time. Chitwan district was identified as the most likely cluster and Jhapa district was the first secondary cluster in both spatial and spatiotemporal scan. July to September of 2010 was identified as a significant temporal cluster. This study assessed and mapped for the first time the spatiotemporal pattern of dengue fever in Nepal. Two districts namely Chitwan and Jhapa were found highly affected by dengue fever. The current study also demonstrated the importance of geospatial approach in epidemiological research. The initial result on dengue patterns and risk of this study may assist institutions and policy makers to develop better preventive strategies.

Elastic Cloud Computing Architecture and System for Heterogeneous Spatiotemporal Computing

NASA Astrophysics Data System (ADS)

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.

A Spatio-Temporally Explicit Random Encounter Model for Large-Scale Population Surveys

PubMed Central

Jousimo, Jussi; Ovaskainen, Otso

2016-01-01

Random encounter models can be used to estimate population abundance from indirect data collected by non-invasive sampling methods, such as track counts or camera-trap data. The classical Formozov–Malyshev–Pereleshin (FMP) estimator converts track counts into an estimate of mean population density, assuming that data on the daily movement distances of the animals are available. We utilize generalized linear models with spatio-temporal error structures to extend the FMP estimator into a flexible Bayesian modelling approach that estimates not only total population size, but also spatio-temporal variation in population density. We also introduce a weighting scheme to estimate density on habitats that are not covered by survey transects, assuming that movement data on a subset of individuals is available. We test the performance of spatio-temporal and temporal approaches by a simulation study mimicking the Finnish winter track count survey. The results illustrate how the spatio-temporal modelling approach is able to borrow information from observations made on neighboring locations and times when estimating population density, and that spatio-temporal and temporal smoothing models can provide improved estimates of total population size compared to the FMP method. PMID:27611683

Revealing Compartmentalized Diffusion in Living Cells with Interferometric Scattering Microscopy.

PubMed

de Wit, Gabrielle; Albrecht, David; Ewers, Helge; Kukura, Philipp

2018-06-19

The spatiotemporal organization and dynamics of the plasma membrane and its constituents are central to cellular function. Fluorescence-based single-particle tracking has emerged as a powerful approach for studying the single molecule behavior of plasma-membrane-associated events because of its excellent background suppression, at the expense of imaging speed and observation time. Here, we show that interferometric scattering microscopy combined with 40 nm gold nanoparticle labeling can be used to follow the motion of membrane proteins in the plasma membrane of live cultured mammalian cell lines and hippocampal neurons with up to 3 nm precision and 25 μs temporal resolution. The achievable spatiotemporal precision enabled us to reveal signatures of compartmentalization in neurons likely caused by the actin cytoskeleton. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Artificial neural network does better spatiotemporal compressive sampling

NASA Astrophysics Data System (ADS)

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.

Research on target tracking algorithm based on spatio-temporal context

NASA Astrophysics Data System (ADS)

Li, Baiping; Xu, Sanmei; Kang, Hongjuan

2017-07-01

In this paper, a novel target tracking algorithm based on spatio-temporal context is proposed. During the tracking process, the camera shaking or occlusion may lead to the failure of tracking. The proposed algorithm can solve this problem effectively. The method use the spatio-temporal context algorithm as the main research object. We get the first frame's target region via mouse. Then the spatio-temporal context algorithm is used to get the tracking targets of the sequence of frames. During this process a similarity measure function based on perceptual hash algorithm is used to judge the tracking results. If tracking failed, reset the initial value of Mean Shift algorithm for the subsequent target tracking. Experiment results show that the proposed algorithm can achieve real-time and stable tracking when camera shaking or target occlusion.

Multiple Roles of Integrin-Linked Kinase in Epidermal Development, Maturation and Pigmentation Revealed by Molecular Profiling

PubMed Central

Judah, David; Rudkouskaya, Alena; Wilson, Ryan; Carter, David E.; Dagnino, Lina

2012-01-01

Integrin-linked kinase (ILK) is an important scaffold protein that mediates a variety of cellular responses to integrin stimulation by extracellular matrix proteins. Mice with epidermis-restricted inactivation of the Ilk gene exhibit pleiotropic phenotypic defects, including impaired hair follicle morphogenesis, reduced epidermal adhesion to the basement membrane, compromised epidermal integrity, as well as wasting and failure to thrive leading to perinatal death. To better understand the underlying molecular mechanisms that cause such a broad range of alterations, we investigated the impact of Ilk gene inactivation on the epidermis transcriptome. Microarray analysis showed over 700 differentially regulated mRNAs encoding proteins involved in multiple aspects of epidermal function, including keratinocyte differentiation and barrier formation, inflammation, regeneration after injury, and fundamental epidermal developmental pathways. These studies also revealed potential effects on genes not previously implicated in ILK functions, including those important for melanocyte and melanoblast development and function, regulation of cytoskeletal dynamics, and homeobox genes. This study shows that ILK is a critical regulator of multiple aspects of epidermal function and homeostasis, and reveals the previously unreported involvement of ILK not only in epidermal differentiation and barrier formation, but also in melanocyte genesis and function. PMID:22574216

Multiple roles of integrin-linked kinase in epidermal development, maturation and pigmentation revealed by molecular profiling.

PubMed

Judah, David; Rudkouskaya, Alena; Wilson, Ryan; Carter, David E; Dagnino, Lina

2012-01-01

Integrin-linked kinase (ILK) is an important scaffold protein that mediates a variety of cellular responses to integrin stimulation by extracellular matrix proteins. Mice with epidermis-restricted inactivation of the Ilk gene exhibit pleiotropic phenotypic defects, including impaired hair follicle morphogenesis, reduced epidermal adhesion to the basement membrane, compromised epidermal integrity, as well as wasting and failure to thrive leading to perinatal death. To better understand the underlying molecular mechanisms that cause such a broad range of alterations, we investigated the impact of Ilk gene inactivation on the epidermis transcriptome. Microarray analysis showed over 700 differentially regulated mRNAs encoding proteins involved in multiple aspects of epidermal function, including keratinocyte differentiation and barrier formation, inflammation, regeneration after injury, and fundamental epidermal developmental pathways. These studies also revealed potential effects on genes not previously implicated in ILK functions, including those important for melanocyte and melanoblast development and function, regulation of cytoskeletal dynamics, and homeobox genes. This study shows that ILK is a critical regulator of multiple aspects of epidermal function and homeostasis, and reveals the previously unreported involvement of ILK not only in epidermal differentiation and barrier formation, but also in melanocyte genesis and function.

Spatiotemporal Analysis of Copper Homeostasis in Populus trichocarpa Reveals an Integrated Molecular Remodeling for a Preferential Allocation of Copper to Plastocyanin in the Chloroplasts of Developing Leaves1[C][W][OA

PubMed Central

Ravet, Karl; Danford, Forest L.; Dihle, Alysha; Pittarello, Marco; Pilon, Marinus

2011-01-01

Plastocyanin, which requires copper (Cu) as a cofactor, is an electron carrier in the thylakoid lumen and essential for photoautotrophic growth of plants. The Cu microRNAs, which are expressed during Cu deprivation, down-regulate several transcripts that encode for Cu proteins. Since plastocyanin is not targeted by the Cu microRNAs, a cofactor economy model has been proposed in which plants prioritize Cu for use in photosynthetic electron transport. However, defects in photosynthesis are classic symptoms of Cu deprivation, and priorities in Cu cofactor delivery have not been determined experimentally. Using hydroponically grown Populus trichocarpa (clone Nisqually-1), we have established a physiological and molecular baseline for the response to Cu deficiency. An integrated analysis showed that Cu depletion strongly reduces the activity of several Cu proteins including plastocyanin, and consequently, photosynthesis and growth are decreased. Whereas plastocyanin mRNA levels were only mildly affected by Cu depletion, this treatment strongly affected the expression of other Cu proteins via Cu microRNA-mediated transcript down-regulation. Polyphenol oxidase was newly identified as Cu regulated and targeted by a novel Cu microRNA, miR1444. Importantly, a spatiotemporal analysis after Cu resupply to previously depleted plants revealed that this micronutrient is preferentially allocated to developing photosynthetic tissues. Plastocyanin and photosynthetic electron transport efficiency were the first to recover after Cu addition, whereas recovery of the other Cu-dependent activities was delayed. Our findings lend new support to the hypothesis that the Cu microRNAs serve to mediate a prioritization of Cu cofactor use. These studies also highlight poplar as an alternative sequenced model for spatiotemporal analyses of nutritional homeostasis. PMID:21941002

Spatiotemporal mapping of sex differences during attentional processing.

PubMed

Neuhaus, Andres H; Opgen-Rhein, Carolin; Urbanek, Carsten; Gross, Melanie; Hahn, Eric; Ta, Thi Minh Tam; Koehler, Simone; Dettling, Michael

2009-09-01

Functional neuroimaging studies have increasingly aimed at approximating neural substrates of human cognitive sex differences elicited by visuospatial challenge. It has been suggested that females and males use different behaviorally relevant neurocognitive strategies. In females, greater right prefrontal cortex activation has been found in several studies. The spatiotemporal dynamics of neural events associated with these sex differences is still unclear. We studied 22 female and 22 male participants matched for age, education, and nicotine with 29-channel-electroencephalogram recorded under a visual selective attention paradigm, the Attention Network Test. Visual event-related potentials (ERP) were topographically analyzed and neuroelectric sources were estimated. In absence of behavioral differences, ERP analysis revealed a novel frontal-occipital second peak of visual N100 that was significantly increased in females relative to males. Further, in females exclusively, a corresponding central ERP component at around 220 ms was found; here, a strong correlation between stimulus salience and sex difference of the central ERP component amplitude was observed. Subsequent source analysis revealed increased cortical current densities in right rostral prefrontal (BA 10) and occipital cortex (BA 19) in female subjects. This is the first study to report on a tripartite association between sex differences in ERPs, visual stimulus salience, and right prefrontal cortex activation during attentional processing. 2009 Wiley-Liss, Inc.

Intrinsic and Extrinsic Evaluation of Spatiotemporal Text Representations in Twitter Streams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, Lawrence A.; Shaffer, Kyle J.; Arendt, Dustin L.

Language in social media is a dynamic system, constantly evolving and adapting, with words and concepts rapidly emerging, disappearing, and changing their meaning. These changes can be estimated using word representations in context, over time and across locations. A number of methods have been proposed to track these spatiotemporal changes but no general method exists to evaluate the quality of these representations. Previous work largely focused on qualitative evaluation, which we improve by proposing a set of visualizations that highlight changes in text representation over both space and time. We demonstrate usefulness of novel spatiotemporal representations to explore and characterizemore » specific aspects of the corpus of tweets collected from European countries over a two-week period centered around the terrorist attacks in Brussels in March 2016. In addition, we quantitatively evaluate spatiotemporal representations by feeding them into a downstream classification task – event type prediction. Thus, our work is the first to provide both intrinsic (qualitative) and extrinsic (quantitative) evaluation of text representations for spatiotemporal trends.« less

Molecular epidemiology and spatiotemporal analysis of hospital-acquired Acinetobacter baumannii infection in a tertiary care hospital in southern Thailand.

PubMed

Chusri, S; Chongsuvivatwong, V; Rivera, J I; Silpapojakul, K; Singkhamanan, K; McNeil, E; Doi, Y

2017-01-01

Acinetobacter baumannii is a major hospital-acquired pathogen in Thailand that has a negative effect on patient survival. The nature of its transmission is poorly understood. To investigate the genotypic and spatiotemporal pattern of A. baumannii infection at a hospital in Thailand. The medical records of patients infected with A. baumannii at an 800-bed tertiary care hospital in southern Thailand between January 2010 and December 2011 were reviewed retrospectively. A. baumannii was identified at the genomospecies level. Carbapenemase genes were identified among carbapenem-resistant isolates associated with A. baumannii infection. A spatiotemporal analysis was performed by admission ward, time of infection and pulsed-field gel electrophoresis (PFGE) groups of A. baumannii. Nine PFGE groups were identified among the 197 A. baumannii infections. All A. baumannii isolates were assigned to International Clonal Lineage II. bla OXA-23 was the most prevalent carbapenemase gene. Outbreaks were observed mainly in respiratory and intensive care units. The association between PFGE group and hospital unit was significant. Spatiotemporal analysis identified 20 clusters of single PFGE group infections. Approximately half of the clusters involved multiple hospital units simultaneously. A. baumannii transmitted both within and between hospital wards. Better understanding and control of the transmission of A. baumannii are needed. Copyright © 2016 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Nanoscale Spatiotemporal Diffusion Modes Measured by Simultaneous Confocal and Stimulated Emission Depletion Nanoscopy Imaging.

PubMed

Schneider, Falk; Waithe, Dominic; Galiani, Silvia; Bernardino de la Serna, Jorge; Sezgin, Erdinc; Eggeling, Christian

2018-06-19

The diffusion dynamics in the cellular plasma membrane provide crucial insights into molecular interactions, organization, and bioactivity. Beam-scanning fluorescence correlation spectroscopy combined with super-resolution stimulated emission depletion nanoscopy (scanning STED-FCS) measures such dynamics with high spatial and temporal resolution. It reveals nanoscale diffusion characteristics by measuring the molecular diffusion in conventional confocal mode and super-resolved STED mode sequentially for each pixel along the scanned line. However, to directly link the spatial and the temporal information, a method that simultaneously measures the diffusion in confocal and STED modes is needed. Here, to overcome this problem, we establish an advanced STED-FCS measurement method, line interleaved excitation scanning STED-FCS (LIESS-FCS), that discloses the molecular diffusion modes at different spatial positions with a single measurement. It relies on fast beam-scanning along a line with alternating laser illumination that yields, for each pixel, the apparent diffusion coefficients for two different observation spot sizes (conventional confocal and super-resolved STED). We demonstrate the potential of the LIESS-FCS approach with simulations and experiments on lipid diffusion in model and live cell plasma membranes. We also apply LIESS-FCS to investigate the spatiotemporal organization of glycosylphosphatidylinositol-anchored proteins in the plasma membrane of live cells, which, interestingly, show multiple diffusion modes at different spatial positions.

BME Estimation of Residential Exposure to Ambient PM10 and Ozone at Multiple Time Scales

PubMed Central

Yu, Hwa-Lung; Chen, Jiu-Chiuan; Christakos, George; Jerrett, Michael

2009-01-01

Background Long-term human exposure to ambient pollutants can be an important contributing or etiologic factor of many chronic diseases. Spatiotemporal estimation (mapping) of long-term exposure at residential areas based on field observations recorded in the U.S. Environmental Protection Agency’s Air Quality System often suffer from missing data issues due to the scarce monitoring network across space and the inconsistent recording periods at different monitors. Objective We developed and compared two upscaling methods: UM1 (data aggregation followed by exposure estimation) and UM2 (exposure estimation followed by data aggregation) for the long-term PM10 (particulate matter with aerodynamic diameter ≤ 10 μm) and ozone exposure estimations and applied them in multiple time scales to estimate PM and ozone exposures for the residential areas of the Health Effects of Air Pollution on Lupus (HEAPL) study. Method We used Bayesian maximum entropy (BME) analysis for the two upscaling methods. We performed spatiotemporal cross-validations at multiple time scales by UM1 and UM2 to assess the estimation accuracy across space and time. Results Compared with the kriging method, the integration of soft information by the BME method can effectively increase the estimation accuracy for both pollutants. The spatiotemporal distributions of estimation errors from UM1 and UM2 were similar. The cross-validation results indicated that UM2 is generally better than UM1 in exposure estimations at multiple time scales in terms of predictive accuracy and lack of bias. For yearly PM10 estimations, both approaches have comparable performance, but the implementation of UM1 is associated with much lower computation burden. Conclusion BME-based upscaling methods UM1 and UM2 can assimilate core and site-specific knowledge bases of different formats for long-term exposure estimation. This study shows that UM1 can perform reasonably well when the aggregation process does not alter the

Task-relevant information is prioritized in spatiotemporal contextual cueing.

PubMed

Higuchi, Yoko; Ueda, Yoshiyuki; Ogawa, Hirokazu; Saiki, Jun

2016-11-01

Implicit learning of visual contexts facilitates search performance-a phenomenon known as contextual cueing; however, little is known about contextual cueing under situations in which multidimensional regularities exist simultaneously. In everyday vision, different information, such as object identity and location, appears simultaneously and interacts with each other. We tested the hypothesis that, in contextual cueing, when multiple regularities are present, the regularities that are most relevant to our behavioral goals would be prioritized. Previous studies of contextual cueing have commonly used the visual search paradigm. However, this paradigm is not suitable for directing participants' attention to a particular regularity. Therefore, we developed a new paradigm, the "spatiotemporal contextual cueing paradigm," and manipulated task-relevant and task-irrelevant regularities. In four experiments, we demonstrated that task-relevant regularities were more responsible for search facilitation than task-irrelevant regularities. This finding suggests our visual behavior is focused on regularities that are relevant to our current goal.

Micro-precise spatiotemporal delivery system embedded in 3D printing for complex tissue regeneration.

PubMed

Tarafder, Solaiman; Koch, Alia; Jun, Yena; Chou, Conrad; Awadallah, Mary R; Lee, Chang H

2016-04-25

Three dimensional (3D) printing has emerged as an efficient tool for tissue engineering and regenerative medicine, given its advantages for constructing custom-designed scaffolds with tunable microstructure/physical properties. Here we developed a micro-precise spatiotemporal delivery system embedded in 3D printed scaffolds. PLGA microspheres (μS) were encapsulated with growth factors (GFs) and then embedded inside PCL microfibers that constitute custom-designed 3D scaffolds. Given the substantial difference in the melting points between PLGA and PCL and their low heat conductivity, μS were able to maintain its original structure while protecting GF's bioactivities. Micro-precise spatial control of multiple GFs was achieved by interchanging dispensing cartridges during a single printing process. Spatially controlled delivery of GFs, with a prolonged release, guided formation of multi-tissue interfaces from bone marrow derived mesenchymal stem/progenitor cells (MSCs). To investigate efficacy of the micro-precise delivery system embedded in 3D printed scaffold, temporomandibular joint (TMJ) disc scaffolds were fabricated with micro-precise spatiotemporal delivery of CTGF and TGFβ3, mimicking native-like multiphase fibrocartilage. In vitro, TMJ disc scaffolds spatially embedded with CTGF/TGFβ3-μS resulted in formation of multiphase fibrocartilaginous tissues from MSCs. In vivo, TMJ disc perforation was performed in rabbits, followed by implantation of CTGF/TGFβ3-μS-embedded scaffolds. After 4 wks, CTGF/TGFβ3-μS embedded scaffolds significantly improved healing of the perforated TMJ disc as compared to the degenerated TMJ disc in the control group with scaffold embedded with empty μS. In addition, CTGF/TGFβ3-μS embedded scaffolds significantly prevented arthritic changes on TMJ condyles. In conclusion, our micro-precise spatiotemporal delivery system embedded in 3D printing may serve as an efficient tool to regenerate complex and inhomogeneous tissues.

Audio-Visual Speaker Diarization Based on Spatiotemporal Bayesian Fusion.

PubMed

Gebru, Israel D; Ba, Sileye; Li, Xiaofei; Horaud, Radu

2018-05-01

Speaker diarization consists of assigning speech signals to people engaged in a dialogue. An audio-visual spatiotemporal diarization model is proposed. The model is well suited for challenging scenarios that consist of several participants engaged in multi-party interaction while they move around and turn their heads towards the other participants rather than facing the cameras and the microphones. Multiple-person visual tracking is combined with multiple speech-source localization in order to tackle the speech-to-person association problem. The latter is solved within a novel audio-visual fusion method on the following grounds: binaural spectral features are first extracted from a microphone pair, then a supervised audio-visual alignment technique maps these features onto an image, and finally a semi-supervised clustering method assigns binaural spectral features to visible persons. The main advantage of this method over previous work is that it processes in a principled way speech signals uttered simultaneously by multiple persons. The diarization itself is cast into a latent-variable temporal graphical model that infers speaker identities and speech turns, based on the output of an audio-visual association process, executed at each time slice, and on the dynamics of the diarization variable itself. The proposed formulation yields an efficient exact inference procedure. A novel dataset, that contains audio-visual training data as well as a number of scenarios involving several participants engaged in formal and informal dialogue, is introduced. The proposed method is thoroughly tested and benchmarked with respect to several state-of-the art diarization algorithms.

Spatio-temporal dynamics induced by competing instabilities in two asymmetrically coupled nonlinear evolution equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schüler, D.; Alonso, S.; Bär, M.

2014-12-15

Pattern formation often occurs in spatially extended physical, biological, and chemical systems due to an instability of the homogeneous steady state. The type of the instability usually prescribes the resulting spatio-temporal patterns and their characteristic length scales. However, patterns resulting from the simultaneous occurrence of instabilities cannot be expected to be simple superposition of the patterns associated with the considered instabilities. To address this issue, we design two simple models composed by two asymmetrically coupled equations of non-conserved (Swift-Hohenberg equations) or conserved (Cahn-Hilliard equations) order parameters with different characteristic wave lengths. The patterns arising in these systems range from coexistingmore » static patterns of different wavelengths to traveling waves. A linear stability analysis allows to derive a two parameter phase diagram for the studied models, in particular, revealing for the Swift-Hohenberg equations, a co-dimension two bifurcation point of Turing and wave instability and a region of coexistence of stationary and traveling patterns. The nonlinear dynamics of the coupled evolution equations is investigated by performing accurate numerical simulations. These reveal more complex patterns, ranging from traveling waves with embedded Turing patterns domains to spatio-temporal chaos, and a wide hysteretic region, where waves or Turing patterns coexist. For the coupled Cahn-Hilliard equations the presence of a weak coupling is sufficient to arrest the coarsening process and to lead to the emergence of purely periodic patterns. The final states are characterized by domains with a characteristic length, which diverges logarithmically with the coupling amplitude.« less

Spatio-temporal dynamics induced by competing instabilities in two asymmetrically coupled nonlinear evolution equations.

PubMed

Schüler, D; Alonso, S; Torcini, A; Bär, M

2014-12-01

Pattern formation often occurs in spatially extended physical, biological, and chemical systems due to an instability of the homogeneous steady state. The type of the instability usually prescribes the resulting spatio-temporal patterns and their characteristic length scales. However, patterns resulting from the simultaneous occurrence of instabilities cannot be expected to be simple superposition of the patterns associated with the considered instabilities. To address this issue, we design two simple models composed by two asymmetrically coupled equations of non-conserved (Swift-Hohenberg equations) or conserved (Cahn-Hilliard equations) order parameters with different characteristic wave lengths. The patterns arising in these systems range from coexisting static patterns of different wavelengths to traveling waves. A linear stability analysis allows to derive a two parameter phase diagram for the studied models, in particular, revealing for the Swift-Hohenberg equations, a co-dimension two bifurcation point of Turing and wave instability and a region of coexistence of stationary and traveling patterns. The nonlinear dynamics of the coupled evolution equations is investigated by performing accurate numerical simulations. These reveal more complex patterns, ranging from traveling waves with embedded Turing patterns domains to spatio-temporal chaos, and a wide hysteretic region, where waves or Turing patterns coexist. For the coupled Cahn-Hilliard equations the presence of a weak coupling is sufficient to arrest the coarsening process and to lead to the emergence of purely periodic patterns. The final states are characterized by domains with a characteristic length, which diverges logarithmically with the coupling amplitude.

Spatiotemporally Resolved Acoustics in a Photoelastic Granular Material

NASA Astrophysics Data System (ADS)

Owens, Eli; Daniels, Karen

2010-03-01

In granular materials, stress transmission is manifested as force chains that propagate through the material in a branching structure. We send acoustic pulses into a two dimensional photoelastic granular material in which force chains are visible and investigate how the force chains influence the amplitude, speed, and dispersion of the sound waves. We observe particle scale dynamics using two methods, movies which provide spatiotemporally resolved measurements and accelerometers within individual grains. The movies allow us to visualize the sound's path through the material, revealing that the sound travels primarily along the force chains. Using the brightness of the photoelastic particles as a measure of the force chain strength, we observe that the sound travels both faster and at higher amplitude along the strong force chains. An exception to this trend is seen in transient force chains that only exist while the sound is closing particle contacts. We also measure the frequency dependence of the amplitude, speed, and dispersion of the sound wave.

Supporting user-defined granularities in a spatiotemporal conceptual model

USGS Publications Warehouse

Khatri, V.; Ram, S.; Snodgrass, R.T.; O'Brien, G. M.

2002-01-01

Granularities are integral to spatial and temporal data. A large number of applications require storage of facts along with their temporal and spatial context, which needs to be expressed in terms of appropriate granularities. For many real-world applications, a single granularity in the database is insufficient. In order to support any type of spatial or temporal reasoning, the semantics related to granularities needs to be embedded in the database. Specifying granularities related to facts is an important part of conceptual database design because under-specifying the granularity can restrict an application, affect the relative ordering of events and impact the topological relationships. Closely related to granularities is indeterminacy, i.e., an occurrence time or location associated with a fact that is not known exactly. In this paper, we present an ontology for spatial granularities that is a natural analog of temporal granularities. We propose an upward-compatible, annotation-based spatiotemporal conceptual model that can comprehensively capture the semantics related to spatial and temporal granularities, and indeterminacy without requiring new spatiotemporal constructs. We specify the formal semantics of this spatiotemporal conceptual model via translation to a conventional conceptual model. To underscore the practical focus of our approach, we describe an on-going case study. We apply our approach to a hydrogeologic application at the United States Geologic Survey and demonstrate that our proposed granularity-based spatiotemporal conceptual model is straightforward to use and is comprehensive.

Spatio-temporal cluster detection of chickenpox in Valencia, Spain in the period 2008-2012.

PubMed

Iftimi, Adina; Martínez-Ruiz, Francisco; Míguez Santiyán, Ana; Montes, Francisco

2015-05-18

Chickenpox is a highly contagious airborne disease caused by Varicella zoster, which affects nearly all non-immune children worldwide with an annual incidence estimated at 80-90 million cases. To analyze the spatiotemporal pattern of the chickenpox incidence in the city of Valencia, Spain two complementary statistical approaches were used. First, we evaluated the existence of clusters and spatio-temporal interaction; secondly, we used this information to find the locations of the spatio-temporal clusters via the space-time permutation model. The first method used detects any aggregation in our data but does not provide the spatial and temporal information. The second method gives the locations, areas and time-frame for the spatio-temporal clusters. An overall decreasing time trend, a pronounced 12-monthly periodicity and two complementary periods were observed. Several areas with high incidence, surrounding the center of the city were identified. The existence of aggregation in time and space was observed, and a number of spatio-temporal clusters were located.

Multiple maternal origins of Indonesian crowing chickens revealed by mitochondrial DNA analysis.

PubMed

Ulfah, Maria; Perwitasari, Dyah; Jakaria, Jakaria; Muladno, Muhammad; Farajallah, Achmad

2017-03-01

The utilization of Indonesian crowing chickens is increasing; as such, assessing their genetic structures is important to support the conservation of their genetic resources. This study analyzes the matrilineal evolution of Indonesian crowing chickens based on the mtDNA displacement loop D-loop region to clarify their phylogenetic relationships, possible maternal origin, and possible routes of chicken dispersal. The neighbor-joining tree reveals that the majority of Indonesian crowing chickens belong to haplogroups B, D, and E, but haplogroup D harbored most of them. The Bayesian analysis also reveals that Indonesian crowing chickens derive from Bekisar chicken, a hybrid of the green junglefowl, suggesting the possible contribution of green junglefowl to chicken domestication. There appear at least three maternal lineages of Indonesian chicken origins indicated by the median network profile of mtDNA D-loop haplotypes, namely (1) Chinese; (2) Chinese, Indian, and other Southeast Asian chickens; and (3) Indian, Chinese, Southeast Asian, Japanese, and European chickens. Chicken domestication might be centered in China, India, Indonesia, and other Southeast Asian countries, supporting multiple maternal origins of Indonesian crowing chickens. A systematic breeding program of indigenous chickens will be very important to retain the genetic diversity for future use and conservation.

[Spatio-temporal problems of geographic information system in marine fishery].

PubMed

Su, Fenzhen; Zhou, Chenghu; Du, Yunyan; Zhang, Tianyu; Shao, Quanqin

2003-09-01

In marine fisheries, it is very important to understand and grasp the spatio-temporal nature. Geographical Information System (GIS) has been applied to describe or forecast the dynamic trend of resources or to set up evaluation model, which is one of high technologies in modern marine fisheries. Based on the review of the development of marine fishery GIS (MFGIS), four spatio-temporal problems it occurred were discussed, and the possible resolutions were prospected.

Incremental Principal Component Analysis Based Outlier Detection Methods for Spatiotemporal Data Streams

NASA Astrophysics Data System (ADS)

Bhushan, A.; Sharker, M. H.; Karimi, H. A.

2015-07-01

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.

Routes to spatiotemporal chaos in Kerr optical frequency combs.

PubMed

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 Coding of Individual Chemicals by the Gustatory System.

PubMed

Reiter, Sam; Campillo Rodriguez, Chelsey; Sun, Kui; Stopfer, Mark

2015-09-02

Four of the five major sensory systems (vision, olfaction, somatosensation, and audition) are thought to use different but partially overlapping sets of neurons to form unique representations of vast numbers of stimuli. The only exception is gustation, which is thought to represent only small numbers of basic taste categories. However, using new methods for delivering tastant chemicals and making electrophysiological recordings from the tractable gustatory system of the moth Manduca sexta, we found chemical-specific information is as follows: (1) initially encoded in the population of gustatory receptor neurons as broadly distributed spatiotemporal patterns of activity; (2) dramatically integrated and temporally transformed as it propagates to monosynaptically connected second-order neurons; and (3) observed in tastant-specific behavior. Our results are consistent with an emerging view of the gustatory system: rather than constructing basic taste categories, it uses a spatiotemporal population code to generate unique neural representations of individual tastant chemicals. Our results provide a new view of taste processing. Using a new, relatively simple model system and a new set of techniques to deliver taste stimuli and to examine gustatory receptor neurons and their immediate followers, we found no evidence for labeled line connectivity, or basic taste categories such as sweet, salty, bitter, and sour. Rather, individual tastant chemicals are represented as patterns of spiking activity distributed across populations of receptor neurons. These representations are transformed substantially as multiple types of receptor neurons converge upon follower neurons, leading to a combinatorial coding format that uniquely, rapidly, and efficiently represents individual taste chemicals. Finally, we found that the information content of these neurons can drive tastant-specific behavior. Copyright © 2015 the authors 0270-6474/15/3512309-13$15.00/0.

BioenergyKDF: Enabling Spatiotemporal Data Synthesis and Research Collaboration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Myers, Aaron T; Movva, Sunil; Karthik, Rajasekar

2014-01-01

The Bioenergy Knowledge Discovery Framework (BioenergyKDF) is a scalable, web-based collaborative environment for scientists working on bioenergy related research in which the connections between data, literature, and models can be explored and more clearly understood. The fully-operational and deployed system, built on multiple open source libraries and architectures, stores contributions from the community of practice and makes them easy to find, but that is just its base functionality. The BioenergyKDF provides a national spatiotemporal decision support capability that enables data sharing, analysis, modeling, and visualization as well as fosters the development and management of the U.S. bioenergy infrastructure, which ismore » an essential component of the national energy infrastructure. The BioenergyKDF is built on a flexible, customizable platform that can be extended to support the requirements of any user community especially those that work with spatiotemporal data. While there are several community data-sharing software platforms available, some developed and distributed by national governments, none of them have the full suite of capabilities available in BioenergyKDF. For example, this component-based platform and database independent architecture allows it to be quickly deployed to existing infrastructure and to connect to existing data repositories (spatial or otherwise). As new data, analysis, and features are added; the BioenergyKDF will help lead research and support decisions concerning bioenergy into the future, but will also enable the development and growth of additional communities of practice both inside and outside of the Department of Energy. These communities will be able to leverage the substantial investment the agency has made in the KDF platform to quickly stand up systems that are customized to their data and research needs.« less

Microscale Spatiotemporal Dynamics during Neocortical Propagation of Human Focal Seizures

PubMed Central

Wagner, Fabien B.; Eskandar, Emad N.; Cosgrove, G. Rees; Madsen, Joseph R.; Blum, Andrew S.; Potter, N. Stevenson; Hochberg, Leigh R.; Cash, Sydney S.; Truccolo, Wilson

2015-01-01

Some of the most clinically consequential aspects of focal epilepsy, e.g. loss of consciousness, arise from the generalization or propagation of seizures through local and large-scale neocortical networks. Yet, the dynamics of such neocortical propagation remain poorly understood. Here, we studied the microdynamics of focal seizure propagation in neocortical patches (4 × 4 mm) recorded via high-density microelectrode arrays (MEAs) implanted in people with pharmacologically resistant epilepsy. Our main findings are threefold: (1) A newly developed stage segmentation method, applied to local field potentials (LFPs) and multi-unit activity (MUA), revealed a succession of discrete seizure stages, each lasting several seconds. These different stages showed characteristic evolutions in overall activity and spatial patterns, which were relatively consistent across seizures within each of the 5 patients studied. Interestingly, segmented seizure stages based on LFPs or MUA showed a dissociation of their spatiotemporal dynamics, likely reflecting different contributions of non-local synaptic inputs and local network activity. (2) As previously reported, some of the seizures showed a peak in MUA that happened several seconds after local seizure onset and slowly propagated across the MEA. However, other seizures had a more complex structure characterized by, for example, several MUA peaks, more consistent with the succession of discrete stages than the slow propagation of a simple wavefront of increased MUA. In both cases, nevertheless, seizures characterized by spike-wave discharges (SWDs, ~ 2–3Hz) eventually evolved into patterns of phase-locked MUA and LFPs. (3) Individual SWDs or gamma oscillation cycles (25–60 Hz), characteristic of two different types of recorded seizures, tended to propagate with varying degrees of directionality, directions of propagation and speeds, depending on the identified seizure stage. However, no clear relationship was observed between the

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

NASA Astrophysics Data System (ADS)

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.

Tailoring the spatiotemporal structure of biphoton entanglement in type-I parametric down-conversion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caspani, L.; Brambilla, E.; Gatti, A.

2010-03-15

We investigate the spatiotemporal structure of the biphoton entangled state produced by parametric down-conversion (PDC) at the output face of the nonlinear crystal. We analyze the geometry of biphoton correlation for different gain regimes (from ultralow to high), different crystal lengths, and different tuning angles of the crystal. While for collinear or quasicollinear phase matching a X-shaped geometry, nonfactorizable in space and time, dominates, in the highly noncollinear conditions we observe a remarkable transition to a factorizable geometry. We show that the geometry of spatiotemporal correlation is a consequence of the angle-frequency relationship imposed by phase matching and that themore » fully spatiotemporal analysis provides a key to control the spatiotemporal properties of the PDC entangled state and in particular to access a biphoton localization in time and space in the femtosecond and micrometer range, respectively.« less

Energy prediction using spatiotemporal pattern networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun

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 bymore » 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.« less

Spatio-temporal interactions facilitate large carnivore sympatry across a resource gradient

PubMed Central

Karanth, K. Ullas; Srivathsa, Arjun; Puri, Mahi; Parameshwaran, Ravishankar; Kumar, N. Samba

2017-01-01

Species within a guild vary their use of time, space and resources, thereby enabling sympatry. As intra-guild competition intensifies, such behavioural adaptations may become prominent. We assessed mechanisms of facilitating sympatry among dhole (Cuon alpinus), leopard (Panthera pardus) and tiger (Panthera tigris) in tropical forests of India using camera-trap surveys. We examined population-level temporal, spatial and spatio-temporal segregation among them across four reserves representing a gradient of carnivore and prey densities. Temporal and spatial overlaps were higher at lower prey densities. Combined spatio-temporal overlap was minimal, possibly due to chance. We found fine-scale avoidance behaviours at one high-density reserve. Our results suggest that: (i) patterns of spatial, temporal and spatio-temporal segregation in sympatric carnivores do not necessarily mirror each other; (ii) carnivores are likely to adopt temporal, spatial, and spatio-temporal segregation as alternative mechanisms to facilitate sympatry; and (iii) carnivores show adaptability across a gradient of resource availability, a driver of inter-species competition. We discuss behavioural mechanisms that permit carnivores to co-occupy rather than dominate functional niches, and adaptations to varying intensities of competition that are likely to shape structure and dynamics of carnivore guilds. PMID:28179511

Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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

A High Performance Bayesian Computing Framework for Spatiotemporal Uncertainty Modeling

NASA Astrophysics Data System (ADS)

Cao, G.

2015-12-01

All types of spatiotemporal measurements are subject to uncertainty. With spatiotemporal data becomes increasingly involved in scientific research and decision making, it is important to appropriately model the impact of uncertainty. Quantitatively modeling spatiotemporal uncertainty, however, is a challenging problem considering the complex dependence and dataheterogeneities.State-space models provide a unifying and intuitive framework for dynamic systems modeling. In this paper, we aim to extend the conventional state-space models for uncertainty modeling in space-time contexts while accounting for spatiotemporal effects and data heterogeneities. Gaussian Markov Random Field (GMRF) models, also known as conditional autoregressive models, are arguably the most commonly used methods for modeling of spatially dependent data. GMRF models basically assume that a geo-referenced variable primarily depends on its neighborhood (Markov property), and the spatial dependence structure is described via a precision matrix. Recent study has shown that GMRFs are efficient approximation to the commonly used Gaussian fields (e.g., Kriging), and compared with Gaussian fields, GMRFs enjoy a series of appealing features, such as fast computation and easily accounting for heterogeneities in spatial data (e.g, point and areal). This paper represents each spatial dataset as a GMRF and integrates them into a state-space form to statistically model the temporal dynamics. Different types of spatial measurements (e.g., categorical, count or continuous), can be accounted for by according link functions. A fast alternative to MCMC framework, so-called Integrated Nested Laplace Approximation (INLA), was adopted for model inference.Preliminary case studies will be conducted to showcase the advantages of the described framework. In the first case, we apply the proposed method for modeling the water table elevation of Ogallala aquifer over the past decades. In the second case, we analyze the

Annotating spatio-temporal datasets for meaningful analysis in the Web

NASA Astrophysics Data System (ADS)

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.

Visual memory performance for color depends on spatiotemporal context.

PubMed

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.

Spatiotemporal coupling of the tongue in amyotrophic lateral sclerosis

PubMed Central

Kuruvilla, Mili S.; Green, Jordan R.; Yunusova, Yana; Hanford, Kathy

2013-01-01

Purpose The primary aim of the investigation was to identify deficits in spatiotemporal coupling between tongue regions in amyotrophic lateral sclerosis (ALS). The relations between disease-related changes in tongue movement patterns and speech intelligibility was also determined. Methods Eleven individuals with ALS with mild, moderate, and severe dysarthria were recorded using the x-ray microbeam during word productions. A coupling index based on sliding window covariance was used to determine disease-related changes in the coupling between the tongue regions across each word. Results The results indicate decreased spatiotemporal coupling and reduced tongue speed in the moderate-ALS subgroup. Spatiotemporal coupling of the mid-posterior tongue was significantly affected in the moderate-ALS group. Changes in the range of tongue coupling relations and speed of movement were highly correlated with speech intelligibility. Conclusions These results provide new insights into the loss of lingual motor control due to ALS and suggest that measures of tongue performance may provide useful indicators of bulbar disease severity and progression. PMID:22615476

Selecting salient frames for spatiotemporal video modeling and segmentation.

PubMed

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.

Harbour porpoise distribution can vary at small spatiotemporal scales in energetic habitats

NASA Astrophysics Data System (ADS)

Benjamins, Steven; van Geel, Nienke; Hastie, Gordon; Elliott, Jim; Wilson, Ben

2017-07-01

Marine habitat heterogeneity underpins species distribution and can be generated through interactions between physical and biological drivers at multiple spatiotemporal scales. Passive acoustic monitoring (PAM) is used worldwide to study potential impacts of marine industrial activities on cetaceans, but understanding of animals' site use at small spatiotemporal scales (<1 km, <1 day) remains limited. Small-scale variability in vocalising harbour porpoise (Phocoena phocoena) distribution within two Scottish marine renewable energy development (MRED) sites was investigated by deploying dense arrays of C-POD passive acoustic detectors at a wave energy test site (the European Marine Energy Centre [Billia Croo, Orkney]) and by a minor tidal-stream site (Scarba [Inner Hebrides]). Respective arrays consisted of 7 and 11 moorings containing two C-PODs each and were deployed for up to 55 days. Minimum inter-mooring distances varied between 300-600 m. All C-POD data were analysed at a temporal resolution of whole minutes, with each minute classified as 1 or 0 on the basis of presence/absence of porpoise click trains (Porpoise-Positive Minutes/PPMs). Porpoise detection rates were analysed using Generalised Additive Models (GAMs) with Generalised Estimation Equations (GEEs). Although there were many porpoise detections (wave test site: N=3,432; tidal-stream site: N=17,366), daily detection rates varied significantly within both arrays. Within the wave site array (<1 km diameter), average daily detection rates varied from 4.3 to 14.8 PPMs/day. Within the tidal-stream array (<2 km diameter), average daily detection rates varied from 10.3 to 49.7 PPMs/day. GAM-GEE model results for individual moorings within both arrays indicated linkages between porpoise presence and small-scale heterogeneity among different environmental covariates (e.g., tidal phase, time of day). Porpoise detection rates varied considerably but with coherent patterns between moorings only several hundred

Data Flow Analysis and Visualization for Spatiotemporal Statistical Data without Trajectory Information.

PubMed

Kim, Seokyeon; Jeong, Seongmin; Woo, Insoo; Jang, Yun; Maciejewski, Ross; Ebert, David S

2018-03-01

Geographic visualization research has focused on a variety of techniques to represent and explore spatiotemporal data. The goal of those techniques is to enable users to explore events and interactions over space and time in order to facilitate the discovery of patterns, anomalies and relationships within the data. However, it is difficult to extract and visualize data flow patterns over time for non-directional statistical data without trajectory information. In this work, we develop a novel flow analysis technique to extract, represent, and analyze flow maps of non-directional spatiotemporal data unaccompanied by trajectory information. We estimate a continuous distribution of these events over space and time, and extract flow fields for spatial and temporal changes utilizing a gravity model. Then, we visualize the spatiotemporal patterns in the data by employing flow visualization techniques. The user is presented with temporal trends of geo-referenced discrete events on a map. As such, overall spatiotemporal data flow patterns help users analyze geo-referenced temporal events, such as disease outbreaks, crime patterns, etc. To validate our model, we discard the trajectory information in an origin-destination dataset and apply our technique to the data and compare the derived trajectories and the original. Finally, we present spatiotemporal trend analysis for statistical datasets including twitter data, maritime search and rescue events, and syndromic surveillance.

Classification with spatio-temporal interpixel class dependency contexts

NASA Technical Reports Server (NTRS)

Jeon, Byeungwoo; Landgrebe, David A.

1992-01-01

A contextual classifier which can utilize both spatial and temporal interpixel dependency contexts is investigated. After spatial and temporal neighbors are defined, a general form of maximum a posterior spatiotemporal contextual classifier is derived. This contextual classifier is simplified under several assumptions. Joint prior probabilities of the classes of each pixel and its spatial neighbors are modeled by the Gibbs random field. The classification is performed in a recursive manner to allow a computationally efficient contextual classification. Experimental results with bitemporal TM data show significant improvement of classification accuracy over noncontextual pixelwise classifiers. This spatiotemporal contextual classifier should find use in many applications of remote sensing, especially when the classification accuracy is important.

Spatiotemporal causal modeling for the management of Dengue Fever

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Huang, Tailin; Lee, Chieh-Han

2015-04-01

Increasing climatic extremes have caused growing concerns about the health effects and disease outbreaks. The association between climate variation and the occurrence of epidemic diseases play an important role on a country's public health systems. Part of the impacts are direct casualties associated with the increasing frequency and intensity of typhoons, the proliferation of disease vectors and the short-term increase of clinic visits on gastro-intestinal discomforts, diarrhea, dermatosis, or psychological trauma. Other impacts come indirectly from the influence of disasters on the ecological and socio-economic systems, including the changes of air/water quality, living environment and employment condition. Previous risk assessment studies on dengue fever focus mostly on climatic and non-climatic factors and their association with vectors' reproducing pattern. The public-health implication may appear simple. Considering the seasonal changes and regional differences, however, the causality of the impacts is full of uncertainties. Without further investigation, the underlying dengue fever risk dynamics may not be assessed accurately. The objective of this study is to develop an epistemic framework for assessing dynamic dengue fever risk across space and time. The proposed framework integrates cross-departmental data, including public-health databases, precipitation data over time and various socio-economic data. We explore public-health issues induced by typhoon through literature review and spatiotemporal analytic techniques on public health databases. From those data, we identify relevant variables and possible causal relationships, and their spatiotemporal patterns derived from our proposed spatiotemporal techniques. Eventually, we create a spatiotemporal causal network and a framework for modeling dynamic dengue fever risk.

On the persistence of spatiotemporal oscillations generated by invasion

NASA Astrophysics Data System (ADS)

Kay, A. L.; Sherratt, J. A.

1999-10-01

Many systems in biology and chemistry are oscillatory, with a stable, spatially homogeneous steady state which consists of periodic temporal oscillations in the interacting species, and such systems have been extensively studied on infinite or semi-infinite spatial domains. We consider the effect of a finite domain, with zero-flux boundary conditions, on the behaviour of solutions to oscillatory reaction-diffusion equations after invasion. We begin by considering numerical simulations of various oscillatory predatory-prey systems. We conclude that when regular spatiotemporal oscillations are left in the wake of invasion, these die out, beginning with a decrease in the spatial frequency of the oscillations at one boundary, which then propagates across the domain. The long-time solution in this case is purely temporal oscillations, corresponding to the limit cycle of the kinetics. Contrastingly, when irregular spatiotemporal oscillations are left in the wake of invasion, they persist, even in very long time simulations. To study this phenomenon in more detail, we consider the {lambda}-{omega} class of reaction-diffusion systems. Numerical simulations show that these systems also exhibit die-out of regular spatiotemporal oscillations and persistence of irregular spatiotemporal oscillations. Exploiting the mathematical simplicity of the {lambda}-{omega} form, we derive analytically an approximation to the transition fronts in r and {theta}x which occur during the die-out of the regular oscillations. We then use this approximation to describe how the die-out occurs, and to derive a measure of its rate, as a function of parameter values. We discuss applications of our results to ecology, calcium signalling and chemistry.

Spatiotemporally and Sequentially-Controlled Drug Release from Polymer Gatekeeper-Hollow Silica Nanoparticles

NASA Astrophysics Data System (ADS)

Palanikumar, L.; Jeena, M. T.; Kim, Kibeom; Yong Oh, Jun; Kim, Chaekyu; Park, Myoung-Hwan; Ryu, Ja-Hyoung

2017-04-01

Combination chemotherapy has become the primary strategy against cancer multidrug resistance; however, accomplishing optimal pharmacokinetic delivery of multiple drugs is still challenging. Herein, we report a sequential combination drug delivery strategy exploiting a pH-triggerable and redox switch to release cargos from hollow silica nanoparticles in a spatiotemporal manner. This versatile system further enables a large loading efficiency for both hydrophobic and hydrophilic drugs inside the nanoparticles, followed by self-crosslinking with disulfide and diisopropylamine-functionalized polymers. In acidic tumour environments, the positive charge generated by the protonation of the diisopropylamine moiety facilitated the cellular uptake of the particles. Upon internalization, the acidic endosomal pH condition and intracellular glutathione regulated the sequential release of the drugs in a time-dependent manner, providing a promising therapeutic approach to overcoming drug resistance during cancer treatment.

Live-cell CRISPR imaging in plants reveals dynamic telomere movements.

PubMed

Dreissig, Steven; Schiml, Simon; Schindele, Patrick; Weiss, Oda; Rutten, Twan; Schubert, Veit; Gladilin, Evgeny; Mette, Michael F; Puchta, Holger; Houben, Andreas

2017-08-01

Elucidating the spatiotemporal organization of the genome inside the nucleus is imperative to our understanding of the regulation of genes and non-coding sequences during development and environmental changes. Emerging techniques of chromatin imaging promise to bridge the long-standing gap between sequencing studies, which reveal genomic information, and imaging studies that provide spatial and temporal information of defined genomic regions. Here, we demonstrate such an imaging technique based on two orthologues of the bacterial clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR associated protein 9 (Cas9). By fusing eGFP/mRuby2 to catalytically inactive versions of Streptococcus pyogenes and Staphylococcus aureus Cas9, we show robust visualization of telomere repeats in live leaf cells of Nicotiana benthamiana. By tracking the dynamics of telomeres visualized by CRISPR-dCas9, we reveal dynamic telomere movements of up to 2 μm over 30 min during interphase. Furthermore, we show that CRISPR-dCas9 can be combined with fluorescence-labelled proteins to visualize DNA-protein interactions in vivo. By simultaneously using two dCas9 orthologues, we pave the way for the imaging of multiple genomic loci in live plants cells. CRISPR imaging bears the potential to significantly improve our understanding of the dynamics of chromosomes in live plant cells. © 2017 The Authors The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

Caged Naloxone Reveals Opioid Signaling Deactivation Kinetics

PubMed Central

Banghart, Matthew R.; Shah, Ruchir C.; Lavis, Luke D.

2013-01-01

The spatiotemporal dynamics of opioid signaling in the brain remain poorly defined. Photoactivatable opioid ligands provide a means to quantitatively measure these dynamics and their underlying mechanisms in brain tissue. Although activation kinetics can be assessed using caged agonists, deactivation kinetics are obscured by slow clearance of agonist in tissue. To reveal deactivation kinetics of opioid signaling we developed a caged competitive antagonist that can be quickly photoreleased in sufficient concentrations to render agonist dissociation effectively irreversible. Carboxynitroveratryl-naloxone (CNV-NLX), a caged analog of the competitive opioid antagonist NLX, was readily synthesized from commercially available NLX in good yield and found to be devoid of antagonist activity at heterologously expressed opioid receptors. Photolysis in slices of rat locus coeruleus produced a rapid inhibition of the ionic currents evoked by multiple agonists of the μ-opioid receptor (MOR), but not of α-adrenergic receptors, which activate the same pool of ion channels. Using the high-affinity peptide agonist dermorphin, we established conditions under which light-driven deactivation rates are independent of agonist concentration and thus intrinsic to the agonist-receptor complex. Under these conditions, some MOR agonists yielded deactivation rates that are limited by G protein signaling, whereas others appeared limited by agonist dissociation. Therefore, the choice of agonist determines which feature of receptor signaling is unmasked by CNV-NLX photolysis. PMID:23960100

Mushroom biomass and diversity are driven by different spatio-temporal scales along Mediterranean elevation gradients

NASA Astrophysics Data System (ADS)

Alday, Josu G.; Martínez de Aragón, Juan; de-Miguel, Sergio; Bonet, José Antonio

2017-04-01

Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns.

Stochastic resonance based on modulation instability in spatiotemporal chaos.

PubMed

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.

Statistical Approaches for Spatiotemporal Prediction of Low Flows

NASA Astrophysics Data System (ADS)

Fangmann, A.; Haberlandt, U.

2017-12-01

An adequate assessment of regional climate change impacts on streamflow requires the integration of various sources of information and modeling approaches. This study proposes simple statistical tools for inclusion into model ensembles, which are fast and straightforward in their application, yet able to yield accurate streamflow predictions in time and space. Target variables for all approaches are annual low flow indices derived from a data set of 51 records of average daily discharge for northwestern Germany. The models require input of climatic data in the form of meteorological drought indices, derived from observed daily climatic variables, averaged over the streamflow gauges' catchments areas. Four different modeling approaches are analyzed. Basis for all pose multiple linear regression models that estimate low flows as a function of a set of meteorological indices and/or physiographic and climatic catchment descriptors. For the first method, individual regression models are fitted at each station, predicting annual low flow values from a set of annual meteorological indices, which are subsequently regionalized using a set of catchment characteristics. The second method combines temporal and spatial prediction within a single panel data regression model, allowing estimation of annual low flow values from input of both annual meteorological indices and catchment descriptors. The third and fourth methods represent non-stationary low flow frequency analyses and require fitting of regional distribution functions. Method three is subject to a spatiotemporal prediction of an index value, method four to estimation of L-moments that adapt the regional frequency distribution to the at-site conditions. The results show that method two outperforms successive prediction in time and space. Method three also shows a high performance in the near future period, but since it relies on a stationary distribution, its application for prediction of far future changes may be

Modulation of V1 Spike Response by Temporal Interval of Spatiotemporal Stimulus Sequence

PubMed Central

Kim, Taekjun; Kim, HyungGoo R.; Kim, Kayeon; Lee, Choongkil

2012-01-01

The spike activity of single neurons of the primary visual cortex (V1) becomes more selective and reliable in response to wide-field natural scenes compared to smaller stimuli confined to the classical receptive field (RF). However, it is largely unknown what aspects of natural scenes increase the selectivity of V1 neurons. One hypothesis is that modulation by surround interaction is highly sensitive to small changes in spatiotemporal aspects of RF surround. Such a fine-tuned modulation would enable single neurons to hold information about spatiotemporal sequences of oriented stimuli, which extends the role of V1 neurons as a simple spatiotemporal filter confined to the RF. In the current study, we examined the hypothesis in the V1 of awake behaving monkeys, by testing whether the spike response of single V1 neurons is modulated by temporal interval of spatiotemporal stimulus sequence encompassing inside and outside the RF. We used two identical Gabor stimuli that were sequentially presented with a variable stimulus onset asynchrony (SOA): the preceding one (S1) outside the RF and the following one (S2) in the RF. This stimulus configuration enabled us to examine the spatiotemporal selectivity of response modulation from a focal surround region. Although S1 alone did not evoke spike responses, visual response to S2 was modulated for SOA in the range of tens of milliseconds. These results suggest that V1 neurons participate in processing spatiotemporal sequences of oriented stimuli extending outside the RF. PMID:23091631

Spatiotemporal Processing in Crossmodal Interactions for Perception of the External World: A Review

PubMed Central

Hidaka, Souta; Teramoto, Wataru; Sugita, Yoichi

2015-01-01

Research regarding crossmodal interactions has garnered much interest in the last few decades. A variety of studies have demonstrated that multisensory information (vision, audition, tactile sensation, and so on) can perceptually interact with each other in the spatial and temporal domains. Findings regarding crossmodal interactions in the spatiotemporal domain (i.e., motion processing) have also been reported, with updates in the last few years. In this review, we summarize past and recent findings on spatiotemporal processing in crossmodal interactions regarding perception of the external world. A traditional view regarding crossmodal interactions holds that vision is superior to audition in spatial processing, but audition is dominant over vision in temporal processing. Similarly, vision is considered to have dominant effects over the other sensory modalities (i.e., visual capture) in spatiotemporal processing. However, recent findings demonstrate that sound could have a driving effect on visual motion perception. Moreover, studies regarding perceptual associative learning reported that, after association is established between a sound sequence without spatial information and visual motion information, the sound sequence could trigger visual motion perception. Other sensory information, such as motor action or smell, has also exhibited similar driving effects on visual motion perception. Additionally, recent brain imaging studies demonstrate that similar activation patterns could be observed in several brain areas, including the motion processing areas, between spatiotemporal information from different sensory modalities. Based on these findings, we suggest that multimodal information could mutually interact in spatiotemporal processing in the percept of the external world and that common perceptual and neural underlying mechanisms would exist for spatiotemporal processing. PMID:26733827

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

NASA Astrophysics Data System (ADS)

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.

Relaxation Dynamics of Spatiotemporal Chaos in the Nematic Liquid Crystal

NASA Astrophysics Data System (ADS)

Nugroho, Fahrudin; Ueki, Tatsuhiro; Hidaka, Yoshiki; Kai, Shoichi

2011-11-01

We are working on the electroconvection of nematic liquid crystals, in which a kind of spatiotemporal chaos called as a soft-mode turbulence (SMT) is observed. The SMT is caused by the nonlinear interaction between the convective modes and the Nambu--Goldstone (NG) modes. By applying an external magnetic field H, the NG mode is suppressed and an ordered pattern can be observed. By removing the suppression effect the ordered state relax to its original SMT pattern. We revealed two types of instability govern the relaxation process: the zigzag instability and the free rotation of wavevector q(r). This work is partially supported by Grant-in-Aid for Scientific Research (Nos. 20111003, 21340110, and 21540391) from the Ministry of Education, Culture, Sport, Science, and Technology of Japan and the Japan Society for the Promotion of Science (JSPS).

Eyetracking Reveals Multiple-Category Use in Induction

ERIC Educational Resources Information Center

Chen, Stephanie Y.; Ross, Brian H.; Murphy, Gregory L.

2016-01-01

Category information is used to predict properties of new category members. When categorization is uncertain, people often rely on only one, most likely category to make predictions. Yet studies of perception and action often conclude that people combine multiple sources of information near-optimally. We present a perception-action analog of…

Spatio-temporal distribution of soil nitrogen in Poyang lake ecological economic zone (South-China).

PubMed

Jiang, Yefeng; Rao, Lei; Sun, Kai; Han, Yi; Guo, Xi

2018-06-01

Revealing the spatio-temporal distribution of soil nitrogen (N) contributes to N management and prevention of N pollution. The objective of this work is to study the spatio-temporal distribution of soil N and their driving factors in the topsoil (0-20 cm) of farmland in Yugan county, China in 1982 and 2012. Data were collected from 200 sampling sites of the second national soil survey in Yugan in 1982 and 423 sampling sites of the soil testing and formula fertilization project in 2012. On average total N (TN) and available N (AN) significantly increased from 1.50 g kg -1 and 153.04 mg kg -1 in 1982 to 1.58 g kg -1 and 179.75 mg kg -1 in 2012, respectively. The distance of spatial autocorrelation for TN increased from 2.79 to 6.18 km and from 2.97 to 18.00 km for AN from 1982 to 2012. The nugget/sill ratio for TN (0.472 in 1982 and 0.581 in 2012) indicated that soil TN driving by natural characteristics in 1982 to human activities in 2012. The nugget/sill ratio for soil AN (0.471 in 1982 and 0.688 in 2012) indicated that soil AN is more influenced by human activities. The major factors driving the spatio-temporal distribution of soil N was N application rate. To promote the sustainable development of agriculture and eco-environment, we should improve the awareness of farmers on chemical fertilizers (particularly N) and the level of N fertilizer management, increase the use of manure and organic fertilizer and facilitate rational fertilization by farmers. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Spatiotemporal dynamics of HSV genome nuclear entry and compaction state transitions using bioorthogonal chemistry and super-resolution microscopy

PubMed Central

2017-01-01

We investigated the spatiotemporal dynamics of HSV genome transport during the initiation of infection using viruses containing bioorthogonal traceable precursors incorporated into their genomes (HSVEdC). In vitro assays revealed a structural alteration in the capsid induced upon HSVEdC binding to solid supports that allowed coupling to external capture agents and demonstrated that the vast majority of individual virions contained bioorthogonally-tagged genomes. Using HSVEdC in vivo we reveal novel aspects of the kinetics, localisation, mechanistic entry requirements and morphological transitions of infecting genomes. Uncoating and nuclear import was observed within 30 min, with genomes in a defined compaction state (ca. 3-fold volume increase from capsids). Free cytosolic uncoated genomes were infrequent (7–10% of the total uncoated genomes), likely a consequence of subpopulations of cells receiving high particle numbers. Uncoated nuclear genomes underwent temporal transitions in condensation state and while ICP4 efficiently associated with condensed foci of initial infecting genomes, this relationship switched away from residual longer lived condensed foci to increasingly decondensed genomes as infection progressed. Inhibition of transcription had no effect on nuclear entry but in the absence of transcription, genomes persisted as tightly condensed foci. Ongoing transcription, in the absence of protein synthesis, revealed a distinct spatial clustering of genomes, which we have termed genome congregation, not seen with non-transcribing genomes. Genomes expanded to more decondensed forms in the absence of DNA replication indicating additional transitional steps. During full progression of infection, genomes decondensed further, with a diffuse low intensity signal dissipated within replication compartments, but frequently with tight foci remaining peripherally, representing unreplicated genomes or condensed parental strands of replicated DNA. Uncoating and nuclear

Spatiotemporal data visualisation for homecare monitoring of elderly people.

PubMed

Juarez, Jose M; Ochotorena, Jose M; Campos, Manuel; Combi, Carlo

2015-10-01

Elderly people who live alone can be assisted by home monitoring systems that identify risk scenarios such as falls, fatigue symptoms or burglary. Given that these systems have to manage spatiotemporal data, human intervention is required to validate automatic alarms due to the high number of false positives and the need for context interpretation. The goal of this work was to provide tools to support human action, to identify such potential risk scenarios based on spatiotemporal data visualisation. We propose the MTA (multiple temporal axes) model, a visual representation of temporal information of the activity of a single person at different locations. The main goal of this model is to visualize the behaviour of a person in their home, facilitating the identification of health-risk scenarios and repetitive patterns. We evaluate the model's insight capacity compared with other models using a standard evaluation protocol. We also test its practical suitability of the MTA graphical model in a commercial home monitoring system. In particular, we implemented 8VISU, a visualization tool based on MTA. MTA proved to be more than 90% accurate in identify non-risk scenarios, independently of the length of the record visualised. When the spatial complexity was increased (e.g. number of rooms) the model provided good accuracy form up to 5 rooms. Therefore, user preferences and user performance seem to be balanced. Moreover, it also gave high sensitivity levels (over 90%) for 5-8 rooms. Fall is the most recurrent incident for elderly people. The MTA model outperformed the other models considered in identifying fall scenarios (66% of correctness) and was the second best for burglary and fatigue scenarios (36% of correctness). Our experiments also confirm the hypothesis that cyclic models are the most suitable for fatigue scenarios, the Spiral and MTA models obtaining most positive identifications. In home monitoring systems, spatiotemporal visualization is a useful tool for

Spatiotemporal patterns of fire-induced forest mortality in boreal regions and its potential drivers

NASA Astrophysics Data System (ADS)

Yang, J.; Tian, H.; Pan, S.; Hansen, M.; Wang, Y.

2017-12-01

Wildfire is the major natural disturbance in boreal forests, which have substantially affected various biological and biophysical processes. Although a few previous studies examined fire severity in boreal regions and reported a higher fire-induced forest mortality in boreal North America than in boreal Eurasia, it remains unclear how this mortality changes over time and how environmental factors affect the temporal dynamics of mortality at a large scale. By using a combination of multiple sources of satellite observations, we investigate the spatiotemporal patterns of fire-induced forest mortality in boreal regions, and examine the contributions of potential drivers. Our results show that forest composition is the key factor influencing the spatial variations of fire mortality across ecoregions. For the temporal variations, we find that the late-season burning was associated with higher fire intensity, which lead to greater forest mortality than the early-season burning. Forests burned in the warm and dry years had greater mortality than those burned in the cool and wet years. Our findings suggest that climate warming and drying not only stimulated boreal fire frequency, but also enhanced fire severity and forest mortality. Due to the significant effects of forest mortality on vegetation structure and ecosystem carbon dynamics, the spatiotemporal changes of fire-induced forest mortality should be explicitly considered to better understand fire impacts on regional and global climate change.

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

NASA Astrophysics Data System (ADS)

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.

Extreme events following bifurcation to spatiotemporal chaos in a spatially extended microcavity laser

NASA Astrophysics Data System (ADS)

Coulibaly, S.; Clerc, M. G.; Selmi, F.; Barbay, S.

2017-02-01

The occurrence of extreme events in a spatially extended microcavity laser has been recently reported [Selmi et al., Phys. Rev. Lett. 116, 013901 (2016), 10.1103/PhysRevLett.116.013901] to be correlated to emergence of spatiotemporal chaos. In this dissipative system, the role of spatial coupling through diffraction is essential to observe the onset of spatiotemporal complexity. We investigate further the formation mechanism of extreme events by comparing the statistical and dynamical analyses. Experimental measurements together with numerical simulations allow us to assign the quasiperiodicity mechanism as the route to spatiotemporal chaos in this system. Moreover, by investigating the fine structure of the maximum Lyapunov exponent, of the Lyapunov spectrum, and of the Kaplan-Yorke dimension of the chaotic attractor, we are able to deduce that intermittency plays a key role in the proportion of extreme events measured. We assign the observed mechanism of generation of extreme events to quasiperiodic extended spatiotemporal intermittency.

Spatio-temporal interactions facilitate large carnivore sympatry across a resource gradient.

PubMed

Karanth, K Ullas; Srivathsa, Arjun; Vasudev, Divya; Puri, Mahi; Parameshwaran, Ravishankar; Kumar, N Samba

2017-02-08

Species within a guild vary their use of time, space and resources, thereby enabling sympatry. As intra-guild competition intensifies, such behavioural adaptations may become prominent. We assessed mechanisms of facilitating sympatry among dhole ( Cuon alpinus ), leopard ( Panthera pardus ) and tiger ( Panthera tigris ) in tropical forests of India using camera-trap surveys. We examined population-level temporal, spatial and spatio-temporal segregation among them across four reserves representing a gradient of carnivore and prey densities. Temporal and spatial overlaps were higher at lower prey densities. Combined spatio-temporal overlap was minimal, possibly due to chance. We found fine-scale avoidance behaviours at one high-density reserve. Our results suggest that: (i) patterns of spatial, temporal and spatio-temporal segregation in sympatric carnivores do not necessarily mirror each other; (ii) carnivores are likely to adopt temporal, spatial, and spatio-temporal segregation as alternative mechanisms to facilitate sympatry; and (iii) carnivores show adaptability across a gradient of resource availability, a driver of inter-species competition. We discuss behavioural mechanisms that permit carnivores to co-occupy rather than dominate functional niches, and adaptations to varying intensities of competition that are likely to shape structure and dynamics of carnivore guilds. © 2017 The Author(s).

Climate-mediated spatiotemporal variability in terrestrial productivity across Europe

NASA Astrophysics Data System (ADS)

Wu, X.; Babst, F.; Ciais, P.; Frank, D.; Reichstein, M.; Wattenbach, M.; Zang, C.; Mahecha, M. D.

2014-06-01

Quantifying the interannual variability (IAV) of the terrestrial ecosystem productivity and its sensitivity to climate is crucial for improving carbon budget predictions. In this context it is necessary to disentangle the influence of climate from impacts of other mechanisms underlying the spatiotemporal patterns of IAV of the ecosystem productivity. In this study we investigated the spatiotemporal patterns of IAV of historical observations of European crop yields in tandem with a set of climate variables. We further evaluated if relevant remote-sensing retrievals of NDVI (normalized difference vegetation index) and FAPAR (fraction of absorbed photosynthetically active radiation) depict a similar behaviour. Our results reveal distinct spatial patterns in the IAV of the analysed proxies linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions in both crop yield and remote-sensing observations. Our results further indicate that variations in the water balance during the active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity-related variables in temperate Europe. Overall, we observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe during the 1975-2009 period. In the same regions, a simultaneous increase in the IAV of water availability was detected. These findings suggest intricate responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become potentially more sensitive to changes in water availability in the dry regions in Europe. The changing sensitivity of terrestrial productivity accompanied by the changing IAV of climate is expected to impact carbon stocks and the net carbon balance

Spatio-Temporal Progression of Cortical Activity Related to Continuous Overt and Covert Speech Production in a Reading Task.

PubMed

Brumberg, Jonathan S; Krusienski, Dean J; Chakrabarti, Shreya; Gunduz, Aysegul; Brunner, Peter; Ritaccio, Anthony L; Schalk, Gerwin

2016-01-01

How the human brain plans, executes, and monitors continuous and fluent speech has remained largely elusive. For example, previous research has defined the cortical locations most important for different aspects of speech function, but has not yet yielded a definition of the temporal progression of involvement of those locations as speech progresses either overtly or covertly. In this paper, we uncovered the spatio-temporal evolution of neuronal population-level activity related to continuous overt speech, and identified those locations that shared activity characteristics across overt and covert speech. Specifically, we asked subjects to repeat continuous sentences aloud or silently while we recorded electrical signals directly from the surface of the brain (electrocorticography (ECoG)). We then determined the relationship between cortical activity and speech output across different areas of cortex and at sub-second timescales. The results highlight a spatio-temporal progression of cortical involvement in the continuous speech process that initiates utterances in frontal-motor areas and ends with the monitoring of auditory feedback in superior temporal gyrus. Direct comparison of cortical activity related to overt versus covert conditions revealed a common network of brain regions involved in speech that may implement orthographic and phonological processing. Our results provide one of the first characterizations of the spatiotemporal electrophysiological representations of the continuous speech process, and also highlight the common neural substrate of overt and covert speech. These results thereby contribute to a refined understanding of speech functions in the human brain.

Spatio-Temporal Progression of Cortical Activity Related to Continuous Overt and Covert Speech Production in a Reading Task

PubMed Central

Brumberg, Jonathan S.; Krusienski, Dean J.; Chakrabarti, Shreya; Gunduz, Aysegul; Brunner, Peter; Ritaccio, Anthony L.; Schalk, Gerwin

2016-01-01

How the human brain plans, executes, and monitors continuous and fluent speech has remained largely elusive. For example, previous research has defined the cortical locations most important for different aspects of speech function, but has not yet yielded a definition of the temporal progression of involvement of those locations as speech progresses either overtly or covertly. In this paper, we uncovered the spatio-temporal evolution of neuronal population-level activity related to continuous overt speech, and identified those locations that shared activity characteristics across overt and covert speech. Specifically, we asked subjects to repeat continuous sentences aloud or silently while we recorded electrical signals directly from the surface of the brain (electrocorticography (ECoG)). We then determined the relationship between cortical activity and speech output across different areas of cortex and at sub-second timescales. The results highlight a spatio-temporal progression of cortical involvement in the continuous speech process that initiates utterances in frontal-motor areas and ends with the monitoring of auditory feedback in superior temporal gyrus. Direct comparison of cortical activity related to overt versus covert conditions revealed a common network of brain regions involved in speech that may implement orthographic and phonological processing. Our results provide one of the first characterizations of the spatiotemporal electrophysiological representations of the continuous speech process, and also highlight the common neural substrate of overt and covert speech. These results thereby contribute to a refined understanding of speech functions in the human brain. PMID:27875590

Spatiotemporal Trends in late-Holocene Fire Regimes in Arctic and Boreal Alaska

NASA Astrophysics Data System (ADS)

Hoecker, T. J.; Higuera, P. E.; Hu, F.; Kelly, R.

2015-12-01

Alaskan arctic and boreal ecosystems are of global importance owing to their sensitivity and feedbacks to directional climate change. Wildfires are a primary driver of boreal carbon balance, and altered fire regimes may significantly impact global climate through the release of stored carbon and changes to surface albedo. Paleoecological records provide a window to how these systems respond to change by revealing climatic and disturbance variability throughout the Holocene. These long-term records highlight the sensitivity of fire regimes to climate and vegetation change, including responses to the relatively warm Medieval Climate Anomaly (MCA), and the relatively cool Little Ice Age (LIA). Over millennial timescales, boreal forests and arctic tundra have been resilient to climate change, but continued directional climate change may result in novel vegetation compositions and fire regimes, with potentially significant implications for global climate. Here we present a spatiotemporal synthesis of 22 published sediment-charcoal records from three Alaskan ecoregions. We add to this network eight records collected in June 2015 from an additional ecoregion. Variability in fire return intervals (FRIs) was quantified within and among ecoregions and climatic periods spanning the past 2 millennia, based on a peak analysis representing local fire events. Preliminary results suggest that fire regimes were responsive to centennial-scale climatic shifts, including the MCA and LIA, but the degree of sensitivity varies by ecoregion. Over the past 2000 years, FRIs were shortest during the MCA, indicating the potential for climate warming to promote high rates of burning. FRIs in tundra regions of northwestern Alaska and in interior boreal forests were 20% shorter during the MCA than during the LIA, and 25% shorter in boreal forest in the south-central Brooks Range. Burning was likely promoted during the warmer, drier MCA through lower fuel moisture. Quantifying fire

Spatiotemporal dynamics in excitable homogeneous random networks composed of periodically self-sustained oscillation.

PubMed

Qian, Yu; Liu, Fei; Yang, Keli; Zhang, Ge; Yao, Chenggui; Ma, Jun

2017-09-19

The collective behaviors of networks are often dependent on the network connections and bifurcation parameters, also the local kinetics plays an important role in contributing the consensus of coupled oscillators. In this paper, we systematically investigate the influence of network structures and system parameters on the spatiotemporal dynamics in excitable homogeneous random networks (EHRNs) composed of periodically self-sustained oscillation (PSO). By using the dominant phase-advanced driving (DPAD) method, the one-dimensional (1D) Winfree loop is exposed as the oscillation source supporting the PSO, and the accurate wave propagation pathways from the oscillation source to the whole network are uncovered. Then, an order parameter is introduced to quantitatively study the influence of network structures and system parameters on the spatiotemporal dynamics of PSO in EHRNs. Distinct results induced by the network structures and the system parameters are observed. Importantly, the corresponding mechanisms are revealed. PSO influenced by the network structures are induced not only by the change of average path length (APL) of network, but also by the invasion of 1D Winfree loop from the outside linking nodes. Moreover, PSO influenced by the system parameters are determined by the excitation threshold and the minimum 1D Winfree loop. Finally, we confirmed that the excitation threshold and the minimum 1D Winfree loop determined PSO will degenerate as the system size is expanded.

Spatio-temporal epidemiology of the cholera outbreak in Papua New Guinea, 2009-2011.

PubMed

Horwood, Paul F; Karl, Stephan; Mueller, Ivo; Jonduo, Marinjho H; Pavlin, Boris I; Dagina, Rosheila; Ropa, Berry; Bieb, Sibauk; Rosewell, Alexander; Umezaki, Masahiro; Siba, Peter M; Greenhill, Andrew R

2014-08-20

Cholera continues to be a devastating disease in many developing countries where inadequate safe water supply and poor sanitation facilitate spread. From July 2009 until late 2011 Papua New Guinea experienced the first outbreak of cholera recorded in the country, resulting in >15,500 cases and >500 deaths. Using the national cholera database, we analysed the spatio-temporal distribution and clustering of the Papua New Guinea cholera outbreak. The Kulldorff space-time permutation scan statistic, contained in the software package SatScan v9.2 was used to describe the first 8 weeks of the outbreak in Morobe Province before cholera cases spread throughout other regions of the country. Data were aggregated at the provincial level to describe the spread of the disease to other affected provinces. Spatio-temporal and cluster analyses revealed that the outbreak was characterized by three distinct phases punctuated by explosive propagation of cases when the outbreak spread to a new region. The lack of road networks across most of Papua New Guinea is likely to have had a major influence on the slow spread of the disease during this outbreak. Identification of high risk areas and the likely mode of spread can guide government health authorities to formulate public health strategies to mitigate the spread of the disease through education campaigns, vaccination, increased surveillance in targeted areas and interventions to improve water, sanitation and hygiene.

Collapse of ultrashort spatiotemporal pulses described by the cubic generalized Kadomtsev-Petviashvili equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leblond, Herve; Kremer, David; Mihalache, Dumitru

2010-03-15

By using a reductive perturbation method, we derive from Maxwell-Bloch equations a cubic generalized Kadomtsev-Petviashvili equation for ultrashort spatiotemporal optical pulse propagation in cubic (Kerr-like) media without the use of the slowly varying envelope approximation. We calculate the collapse threshold for the propagation of few-cycle spatiotemporal pulses described by the generic cubic generalized Kadomtsev-Petviashvili equation by a direct numerical method and compare it to analytic results based on a rigorous virial theorem. Besides, typical evolution of the spectrum (integrated over the transverse spatial coordinate) is given and a strongly asymmetric spectral broadening of ultrashort spatiotemporal pulses during collapse is evidenced.

Neural feedback for instantaneous spatiotemporal modulation of afferent pathways in bi-directional brain-machine interfaces.

PubMed

Liu, Jianbo; Khalil, Hassan K; Oweiss, Karim G

2011-10-01

In bi-directional brain-machine interfaces (BMIs), precisely controlling the delivery of microstimulation, both in space and in time, is critical to continuously modulate the neural activity patterns that carry information about the state of the brain-actuated device to sensory areas in the brain. In this paper, we investigate the use of neural feedback to control the spatiotemporal firing patterns of neural ensembles in a model of the thalamocortical pathway. Control of pyramidal (PY) cells in the primary somatosensory cortex (S1) is achieved based on microstimulation of thalamic relay cells through multiple-input multiple-output (MIMO) feedback controllers. This closed loop feedback control mechanism is achieved by simultaneously varying the stimulation parameters across multiple stimulation electrodes in the thalamic circuit based on continuous monitoring of the difference between reference patterns and the evoked responses of the cortical PY cells. We demonstrate that it is feasible to achieve a desired level of performance by controlling the firing activity pattern of a few "key" neural elements in the network. Our results suggest that neural feedback could be an effective method to facilitate the delivery of information to the cortex to substitute lost sensory inputs in cortically controlled BMIs.

Climate-mediated spatiotemporal variability in the terrestrial productivity across Europe

NASA Astrophysics Data System (ADS)

Wu, X.; Mahecha, M. D.; Reichstein, M.; Ciais, P.; Wattenbach, M.; Babst, F.; Frank, D.; Zang, C.

2013-11-01

Quantifying the interannual variability (IAV) of the terrestrial productivity and its sensitivity to climate is crucial for improving carbon budget predictions. However, the influence of climate and other mechanisms underlying the spatiotemporal patterns of IAV of productivity are not well understood. In this study we investigated the spatiotemporal patterns of IAV of historical observations of crop yields, tree ring width, remote sensing retrievals of FAPAR and NDVI, and other variables relevant to the terrestrial productivity in Europe in tandem with a set of climate variables. Our results reveal distinct spatial patterns in the IAV of most variables linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions. Our results further indicate that variations in the water balance during active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity related variables in temperate Europe. We also observe a~temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe, which is likely attributable to the recently increased IAV of water availability in these regions. These findings suggest nonlinear responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become more sensitive and more vulnerable to changes in water availability in the dry regions in Europe. The changing climate sensitivity of terrestrial productivity accompanied by the changing IAV of climate could impact carbon stocks and the net carbon balance of European ecosystems.

Zero-inflated spatio-temporal models for disease mapping.

PubMed

Torabi, Mahmoud

2017-05-01

In this paper, our aim is to analyze geographical and temporal variability of disease incidence when spatio-temporal count data have excess zeros. To that end, we consider random effects in zero-inflated Poisson models to investigate geographical and temporal patterns of disease incidence. Spatio-temporal models that employ conditionally autoregressive smoothing across the spatial dimension and B-spline smoothing over the temporal dimension are proposed. The analysis of these complex models is computationally difficult from the frequentist perspective. On the other hand, the advent of the Markov chain Monte Carlo algorithm has made the Bayesian analysis of complex models computationally convenient. Recently developed data cloning method provides a frequentist approach to mixed models that is also computationally convenient. We propose to use data cloning, which yields to maximum likelihood estimation, to conduct frequentist analysis of zero-inflated spatio-temporal modeling of disease incidence. One of the advantages of the data cloning approach is that the prediction and corresponding standard errors (or prediction intervals) of smoothing disease incidence over space and time is easily obtained. We illustrate our approach using a real dataset of monthly children asthma visits to hospital in the province of Manitoba, Canada, during the period April 2006 to March 2010. Performance of our approach is also evaluated through a simulation study. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Visual search of cyclic spatio-temporal events

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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 distribution of Holocene populations in North America

PubMed Central

Chaput, Michelle A.; Kriesche, Björn; Betts, Matthew; Martindale, Andrew; Kulik, Rafal; Schmidt, Volker; Gajewski, Konrad

2015-01-01

As the Cordilleran and Laurentide Ice Sheets retreated, North America was colonized by human populations; however, the spatial patterns of subsequent population growth are unclear. Temporal frequency distributions of aggregated radiocarbon (14C) dates are used as a proxy of population size and can be used to track this expansion. The Canadian Archaeological Radiocarbon Database contains more than 35,000 14C dates and is used in this study to map the spatiotemporal demographic changes of Holocene populations in North America at a continental scale for the past 13,000 y. We use the kernel method, which converts the spatial distribution of 14C dates into estimates of population density at 500-y intervals. The resulting maps reveal temporally distinct, dynamic patterns associated with paleodemographic trends that correspond well to genetic, archaeological, and ethnohistoric evidence of human occupation. These results have implications for hypothesizing and testing migration routes into and across North America as well as the relative influence of North American populations on the evolution of the North American ecosystem. PMID:26351683

[Digital ischemia revealing multiple myeloma].

PubMed

Khammar, Z; Ouazzani, M; Bennani, B; Oubelkacem, N; Berrady, R

2018-02-01

Digital ulcers generally arise in a context of microangiopathy-related focal ischemia. In women, connective tissue diseases are the main etiology, while in men the cause is often diffuse arterial disease, e.g. Leo-Buerger disease, or emboligenic heart disease. A paraneoplastic origin of digital necrosis due to ischemia is rarely reported. A 75-year-old man presented with cyanosis of the fingertips and toes that had begun one month earlier. The physical examination found pulp ulcers on the fingers and toes of both hands and feet. Two weeks later, necrotic damage developed distally, with no other associated symptoms. Blood tests were suggestive of Kahler disease; immunodeficiency disorders tests were negative; the cyroglobulin test was positive. Multiple-drug chemotherapy was followed by clinical improvement. Distal necrotic damage is a frequent inaugural symptom in vascular disease. If the common causal mechanisms (iatrogenic, occupational, toxic, atheromatous, emboligenic heart disease, or systemic disease) have been ruled out, it is important to search for a blood disorder or cancer as the cause of distal necrotic damage. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Spatio-temporal distribution of energy radiation from low frequency tremor

NASA Astrophysics Data System (ADS)

Maeda, T.; Obara, K.

2007-12-01

Recent fine-scale hypocenter locations of low frequency tremors (LFTs) estimated by cross-correlation technique (Shelly et al. 2006; Maeda et al. 2006) and new finding of very low frequency earthquake (Ito et al. 2007) suggest that these slow events occur at the plate boundary associated with slow slip events (Obara and Hirose, 2006). However, the number of tremor detected by above technique is limited since continuous tremor waveforms are too complicated. Although an envelope correlation method (ECM) (Obara, 2002) enables us to locate epicenters of LFT without arrival time picks, however, ECM fails to locate LFTs precisely especially on the most active stage of tremor activity because of the low-correlation of envelope amplitude. To reveal total energy release of LFT, here we propose a new method for estimating the location of LFTs together with radiated energy from the tremor source by using envelope amplitude. The tremor amplitude observed at NIED Hi-net stations in western Shikoku simply decays in proportion to the reciprocal of the source-receiver distance after the correction of site- amplification factor even though the phases of the tremor are very complicated. So, we model the observed mean square envelope amplitude by time-dependent energy radiation with geometrical spreading factor. In the model, we do not have origin time of the tremor since we assume that the source of the tremor continuously radiates the energy. Travel-time differences between stations estimated by the ECM technique also incorporated in our locating algorithm together with the amplitude information. Three-component 1-hour Hi-net velocity continuous waveforms with a pass-band of 2-10 Hz are used for the inversion after the correction of site amplification factors at each station estimated by coda normalization method (Takahashi et al. 2005) applied to normal earthquakes in the region. The source location and energy are estimated by applying least square inversion to the 1-min window

Spatiotemporal Clustering Analysis of Malaria Infection in Pakistan.

PubMed

Umer, Muhammad Farooq; Zofeen, Shumaila; Majeed, Abdul; Hu, Wenbiao; Qi, Xin; Zhuang, Guihua

2018-06-07

Despite tremendous progress, malaria remains a serious public health problem in Pakistan. Very few studies have been done on spatiotemporal evaluation of malaria infection in Pakistan. The study aimed to detect the spatiotemporal pattern of malaria infection at the district level in Pakistan, and to identify the clusters of high-risk disease areas in the country. Annual data on malaria for two dominant species ( Plasmodium falciparum , Plasmodium vivax ) and mixed infections from 2011 to 2016 were obtained from the Directorate of Malaria Control Program, Pakistan. Population data were collected from the Pakistan Bureau of Statistics. A geographical information system was used to display the spatial distribution of malaria at the district level throughout Pakistan. Purely spatiotemporal clustering analysis was performed to identify the high-risk areas of malaria infection in Pakistan. A total of 1,593,409 positive cases were included in this study over a period of 6 years (2011⁻2016). The maximum number of P . vivax cases (474,478) were reported in Khyber Pakhtunkhwa (KPK). The highest burden of P . falciparum (145,445) was in Balochistan, while the highest counts of mixed Plasmodium cases were reported in Sindh (22,421) and Balochistan (22,229), respectively. In Balochistan, incidence of all three types of malaria was very high. Cluster analysis showed that primary clusters of P . vivax malaria were in the same districts in 2014, 2015 and 2016 (total 24 districts, 12 in Federally Administered Tribal Areas (FATA), 9 in KPK, 2 in Punjab and 1 in Balochistan); those of P . falciparum malaria were unchanged in 2012 and 2013 (total 18 districts, all in Balochistan), and mixed infections remained the same in 2014 and 2015 (total 7 districts, 6 in Balochistan and 1 in FATA). This study indicated that the transmission cycles of malaria infection vary in different spatiotemporal settings in Pakistan. Efforts in controlling P . vivax malaria in particular need to be

Spatiotemporal regulation of autophagy during Caenorhabditis elegans aging

PubMed Central

Chang, Jessica T; Kumsta, Caroline; Hellman, Andrew B; Adams, Linnea M; Hansen, Malene

2017-01-01

Autophagy has been linked to longevity in many species, but the underlying mechanisms are unclear. Using a GFP-tagged and a new tandem-tagged Atg8/LGG-1 reporter, we quantified autophagic vesicles and performed autophagic flux assays in multiple tissues of wild-type Caenorhabditis elegans and long-lived daf-2/insulin/IGF-1 and glp-1/Notch mutants throughout adulthood. Our data are consistent with an age-related decline in autophagic activity in the intestine, body-wall muscle, pharynx, and neurons of wild-type animals. In contrast, daf-2 and glp-1 mutants displayed unique age- and tissue-specific changes in autophagic activity, indicating that the two longevity paradigms have distinct effects on autophagy during aging. Although autophagy appeared active in the intestine of both long-lived mutants, inhibition of intestinal autophagy significantly abrogated lifespan extension only in glp-1 mutants. Collectively, our data suggest that autophagic activity normally decreases with age in C. elegans, whereas daf-2 and glp-1 long-lived mutants regulate autophagy in distinct spatiotemporal-specific manners to extend lifespan. DOI: http://dx.doi.org/10.7554/eLife.18459.001 PMID:28675140

Multiple adaptable mechanisms early in the primate visual pathway

PubMed Central

Dhruv, Neel T.; Tailby, Chris; Sokol, Sach H.; Lennie, Peter

2011-01-01

We describe experiments that isolate and characterize multiple adaptable mechanisms that influence responses of orientation-selective neurons in primary visual cortex (V1) of anesthetized macaque (Macaca fascicularis). The results suggest that three adaptable stages of machinery shape neural responses in V1: a broadly-tuned early stage and a spatio-temporally tuned later stage, both of which provide excitatory input, and a normalization pool that is also broadly tuned. The early stage and the normalization pool are revealed by adapting gratings that themselves fail to evoke a response from the neuron: either low temporal frequency gratings at the null orientation or gratings of any orientation drifting at high temporal frequencies. When effective, adapting stimuli that altered the sensitivity of these two mechanisms caused reductions of contrast gain and often brought about a paradoxical increase in response gain due to a relatively greater desensitization of the normalization pool. The tuned mechanism is desensitized only by stimuli well-matched to a neuron’s receptive field. We could thus infer desensitization of the tuned mechanism by comparing effects obtained with adapting gratings of preferred and null orientation modulated at low temporal frequencies. PMID:22016535

Bayesian spatiotemporal model of fMRI data using transfer functions.

PubMed

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.

Real-Time Spatio-Temporal Twice Whitening for MIMO Energy Detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Humble, Travis S; Mitra, Pramita; Barhen, Jacob

2010-01-01

While many techniques exist for local spectrum sensing of a primary user, each represents a computationally demanding task to secondary user receivers. In software-defined radio, computational complexity lengthens the time for a cognitive radio to recognize changes in the transmission environment. This complexity is even more significant for spatially multiplexed receivers, e.g., in SIMO and MIMO, where the spatio-temporal data sets grow in size with the number of antennae. Limits on power and space for the processor hardware further constrain SDR performance. In this report, we discuss improvements in spatio-temporal twice whitening (STTW) for real-time local spectrum sensing by demonstratingmore » a form of STTW well suited for MIMO environments. We implement STTW on the Coherent Logix hx3100 processor, a multicore processor intended for low-power, high-throughput software-defined signal processing. These results demonstrate how coupling the novel capabilities of emerging multicore processors with algorithmic advances can enable real-time, software-defined processing of large spatio-temporal data sets.« less

Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015.

PubMed

Larsen, David A; Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A

2017-01-01

Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009-2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted.

A spatiotemporal structure: common to subatomic systems, biological processes, and economic cycles

NASA Astrophysics Data System (ADS)

Naitoh, Ken

2012-03-01

A theoretical model derived based on a quasi-stability concept applied to momentum conservation (Naitoh, JJIAM, 2001, Artificial Life Robotics, 2008, 2010) has revealed the spatial structure of various systems. This model explains the reason why particles such as biological cells, nitrogenous bases, and liquid droplets have bimodal size ratios of about 2:3 and 1:1. This paper shows that the same theory holds true for several levels of parcels from baryons to stars in the cosmos: specifically, at the levels of nuclear force, van der Waals force, surface tension, and the force of gravity. A higher order of analysis clarifies other asymmetric ratios related to the halo structure seen in atoms and amino acids. We will also show that our minimum hypercycle theory for explaining the morphogenetic cycle (Naitoh, Artificial Life Robotics, 2008) reveals other temporal cycles such as those of economic systems and the circadian clock as well as the fundamental neural network pattern (topological pattern). Finally, a universal equation describing the spatiotemporal structure of several systems will be derived, which also leads to a general concept of quasi-stability.

Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015

PubMed Central

Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A.

2017-01-01

Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009–2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted. PMID:28319125

Spatiotemporal Characteristics for the Depth from Luminance Contrast

PubMed Central

Matsubara, Kazuya; Matsumiya, Kazumichi; Shioiri, Satoshi; Takahashi, Shuichi; Hyodo, Yasuhide; Ohashi, Isao

2011-01-01

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 conceptual platform for querying archaeological information systems

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Sartzetaki, Mary; Sarris, Apostolos

2015-04-01

Spatial and temporal distribution of archaeological sites has been shown to associate with several attributes including marine, water, mineral and food resources, climate conditions, geomorphological features, etc. In this study, archeological settlement attributes are evaluated under various associations in order to provide a specialized query platform in a geographic information system (GIS). Towards this end, a spatial database is designed to include a series of archaeological findings for a secluded geographic area of Crete in Greece. The key categories of the geodatabase include the archaeological type (palace, burial site, village, etc.), temporal information of the habitation/usage period (pre Minoan, Minoan, Byzantine, etc.), and the extracted geographical attributes of the sites (distance to sea, altitude, resources, etc.). Most of the related spatial attributes are extracted with readily available GIS tools. Additionally, a series of conceptual data attributes are estimated, including: Temporal relation of an era to a future one in terms of alteration of the archaeological type, topologic relations of various types and attributes, spatial proximity relations between various types. These complex spatiotemporal relational measures reveal new attributes towards better understanding of site selection for prehistoric and/or historic cultures, yet their potential combinations can become numerous. Therefore, after the quantification of the above mentioned attributes, they are classified as of their importance for archaeological site location modeling. Under this new classification scheme, the user may select a geographic area of interest and extract only the important attributes for a specific archaeological type. These extracted attributes may then be queried against the entire spatial database and provide a location map of possible new archaeological sites. This novel type of querying is robust since the user does not have to type a standard SQL query but

Spatiotemporal Heterogeneity Analysis of Hemorrhagic Fever with Renal Syndrome in China Using Geographically Weighted Regression Models

PubMed Central

Li, Shujuan; Ren, Hongyan; Hu, Wensheng; Lu, Liang; Xu, Xinliang; Zhuang, Dafang; Liu, Qiyong

2014-01-01

Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in China. The identification of the spatiotemporal pattern of HFRS will provide a foundation for the effective control of the disease. Based on the incidence of HFRS, as well as environmental factors, and social-economic factors of China from 2005–2012, this paper identified the spatiotemporal characteristics of HFRS distribution and the factors that impact this distribution. The results indicate that the spatial distribution of HFRS had a significant, positive spatial correlation. The spatiotemporal heterogeneity was affected by the temperature, precipitation, humidity, NDVI of January, NDVI of August for the previous year, land use, and elevation in 2005–2009. However, these factors did not explain the spatiotemporal heterogeneity of HFRS incidences in 2010–2012. Spatiotemporal heterogeneity of provincial HFRS incidences and its relation to environmental factors would provide valuable information for hygiene authorities to design and implement effective measures for the prevention and control of HFRS in China. PMID:25429681

Effects of Rhythmic Auditory Cueing in Gait Rehabilitation for Multiple Sclerosis: A Mini Systematic Review and Meta-Analysis

PubMed Central

Ghai, Shashank; Ghai, Ishan

2018-01-01

Rhythmic auditory cueing has been shown to enhance gait performance in several movement disorders. The “entrainment effect” generated by the stimulations can enhance auditory motor coupling and instigate plasticity. However, a consensus as to its influence over gait training among patients with multiple sclerosis is still warranted. A systematic review and meta-analysis was carried out to analyze the effects of rhythmic auditory cueing in studies gait performance in patients with multiple sclerosis. This systematic identification of published literature was performed according to PRISMA guidelines, from inception until Dec 2017, on online databases: Web of science, PEDro, EBSCO, MEDLINE, Cochrane, EMBASE, and PROQUEST. Studies were critically appraised using PEDro scale. Of 602 records, five studies (PEDro score: 5.7 ± 1.3) involving 188 participants (144 females/40 males) met our inclusion criteria. The meta-analysis revealed enhancements in spatiotemporal parameters of gait i.e., velocity (Hedge's g: 0.67), stride length (0.70), and cadence (1.0), and reduction in timed 25 feet walking test (−0.17). Underlying neurophysiological mechanisms, and clinical implications are discussed. This present review bridges the gaps in literature by suggesting application of rhythmic auditory cueing in conventional rehabilitation approaches to enhance gait performance in the multiple sclerosis community. PMID:29942278

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

NASA Astrophysics Data System (ADS)

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.

Spatiotemporal information during unsupervised learning enhances viewpoint invariant object recognition

PubMed Central

Tian, Moqian; Grill-Spector, Kalanit

2015-01-01

Recognizing objects is difficult because it requires both linking views of an object that can be different and distinguishing objects with similar appearance. Interestingly, people can learn to recognize objects across views in an unsupervised way, without feedback, just from the natural viewing statistics. However, there is intense debate regarding what information during unsupervised learning is used to link among object views. Specifically, researchers argue whether temporal proximity, motion, or spatiotemporal continuity among object views during unsupervised learning is beneficial. Here, we untangled the role of each of these factors in unsupervised learning of novel three-dimensional (3-D) objects. We found that after unsupervised training with 24 object views spanning a 180° view space, participants showed significant improvement in their ability to recognize 3-D objects across rotation. Surprisingly, there was no advantage to unsupervised learning with spatiotemporal continuity or motion information than training with temporal proximity. However, we discovered that when participants were trained with just a third of the views spanning the same view space, unsupervised learning via spatiotemporal continuity yielded significantly better recognition performance on novel views than learning via temporal proximity. These results suggest that while it is possible to obtain view-invariant recognition just from observing many views of an object presented in temporal proximity, spatiotemporal information enhances performance by producing representations with broader view tuning than learning via temporal association. Our findings have important implications for theories of object recognition and for the development of computational algorithms that learn from examples. PMID:26024454

Spatiotemporal control of opioid signaling and behavior

PubMed Central

Siuda, Edward R.; Copits, Bryan A.; Schmidt, Martin J.; Baird, Madison A.; Al-Hasani, Ream; Planer, William J.; Funderburk, Samuel C.; McCall, Jordan G.; Gereau, Robert W.; Bruchas, Michael R.

2015-01-01

Summary Optogenetics is now a widely accepted tool for spatiotemporal manipulation of neuronal activity. However, a majority of optogenetic approaches use binary on/off control schemes. Here we extend the optogenetic toolset by developing a neuromodulatory approach using a rationale-based design to generate a Gi-coupled, optically-sensitive, mu-opioid-like receptor, we term opto-MOR. We demonstrate that opto-MOR engages canonical mu-opioid signaling through inhibition of adenylyl cyclase, activation of MAPK and G protein-gated inward rectifying potassium (GIRK) channels, and internalizes with similar kinetics as the mu-opioid receptor. To assess in vivo utility we expressed a Cre-dependent viral opto-MOR in RMTg/VTA GABAergic neurons, which led to a real-time place preference. In contrast, expression of opto-MOR in GABAergic neurons of the ventral pallidum hedonic cold spot, led to real-time place aversion. This tool has generalizable application for spatiotemporal control of opioid signaling and, furthermore, can be used broadly for mimicking endogenous neuronal inhibition pathways. PMID:25937173

High-Throughput Analysis of Promoter Occupancy Reveals New Targets for Arx, a Gene Mutated in Mental Retardation and Interneuronopathies

PubMed Central

Quillé, Marie-Lise; Hirchaud, Edouard; Baron, Daniel; Benech, Caroline; Guihot, Jeanne; Placet, Morgane; Mignen, Olivier; Férec, Claude; Houlgatte, Rémi; Friocourt, Gaëlle

2011-01-01

Genetic investigations of X-linked intellectual disabilities have implicated the ARX (Aristaless-related homeobox) gene in a wide spectrum of disorders extending from phenotypes characterised by severe neuronal migration defects such as lissencephaly, to mild or moderate forms of mental retardation without apparent brain abnormalities but with associated features of dystonia and epilepsy. Analysis of Arx spatio-temporal localisation profile in mouse revealed expression in telencephalic structures, mainly restricted to populations of GABAergic neurons at all stages of development. Furthermore, studies of the effects of ARX loss of function in humans and animal models revealed varying defects, suggesting multiple roles of this gene during brain development. However, to date, little is known about how ARX functions as a transcription factor and the nature of its targets. To better understand its role, we combined chromatin immunoprecipitation and mRNA expression with microarray analysis and identified a total of 1006 gene promoters bound by Arx in transfected neuroblastoma (N2a) cells and in mouse embryonic brain. Approximately 24% of Arx-bound genes were found to show expression changes following Arx overexpression or knock-down. Several of the Arx target genes we identified are known to be important for a variety of functions in brain development and some of them suggest new functions for Arx. Overall, these results identified multiple new candidate targets for Arx and should help to better understand the pathophysiological mechanisms of intellectual disability and epilepsy associated with ARX mutations. PMID:21966449

Tectonic environments of South American porphyry copper magmatism through time revealed by spatiotemporal data mining

NASA Astrophysics Data System (ADS)

Butterworth, N.; Steinberg, D.; Müller, R. D.; Williams, S.; Merdith, A. S.; Hardy, S.

2016-12-01

Porphyry ore deposits are known to be associated with arc magmatism on the overriding plate at subduction zones. While general mechanisms for driving magmatism are well established, specific subduction-related parameters linking episodes of ore deposit formation to specific tectonic environments have only been qualitatively inferred and have not been formally tested. We develop a four-dimensional approach to reconstruct age-dated ore deposits, with the aim of isolating the tectonomagmatic parameters leading to the formation of copper deposits during subduction. We use a plate tectonic model with continuously closing plate boundaries, combined with reconstructions of the spatiotemporal distribution of the ocean floor, including subducted portions of the Nazca/Farallon plates. The models compute convergence rates and directions, as well as the age of the downgoing plate through time. To identify and quantify tectonic parameters that are robust predictors of Andean porphyry copper magmatism and ore deposit formation, we test two alternative supervised machine learning methods; the "random forest" (RF) ensemble and "support vector machines" (SVM). We find that a combination of rapid convergence rates ( 100 km/Myr), subduction obliquity of 15°, a subducting plate age between 25-70 Myr old, and a location far from the subducting trench boundary (>2000 km) represents favorable conditions for porphyry magmatism and related ore deposits to occur. These parameters are linked to the availability of oceanic sediments, the changing small-scale convection around the subduction zone, and the availability of the partial melt in the mantle wedge. When coupled, these parameters could influence the genesis and exhumation of porphyry copper deposits.

Spatiotemporal chaos of self-replicating spots in reaction-diffusion systems.

PubMed

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.

Coexistence of collapse and stable spatiotemporal solitons in multimode fibers

NASA Astrophysics Data System (ADS)

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.

Holocene forest dynamics in central and western Mediterranean: periodicity, spatio-temporal patterns and climate influence.

PubMed

Di Rita, Federico; Fletcher, William J; Aranbarri, Josu; Margaritelli, Giulia; Lirer, Fabrizio; Magri, Donatella

2018-06-12

It is well-known that the Holocene exhibits a millennial-scale climate variability. However, its periodicity, spatio-temporal patterns and underlying processes are not fully deciphered yet. Here we focus on the central and western Mediterranean. We show that recurrent forest declines from the Gulf of Gaeta (central Tyrrhenian Sea) reveal a 1860-yr periodicity, consistent with a ca. 1800-yr climate fluctuation induced by large-scale changes in climate modes, linked to solar activity and/or AMOC intensity. We show that recurrent forest declines and dry events are also recorded in several pollen and palaeohydrological proxy-records in the south-central Mediterranean. We found coeval events also in several palaeohydrological records from the south-western Mediterranean, which however show generally wet climate conditions, indicating a spatio-temporal hydrological pattern opposite to the south-central Mediterranean and suggesting that different expressions of climate modes occurred in the two regions at the same time. We propose that these opposite hydroclimate regimes point to a complex interplay of the prevailing or predominant phases of NAO-like circulation, East Atlantic pattern, and extension and location of the North African anticyclone. At a larger geographical scale, displacements of the ITCZ, modulated by solar activity and/or AMOC intensity, may have also indirectly influenced the observed pattern.

Method for detecting the signature of noise-induced structures in spatiotemporal data sets: an application to excitable media

NASA Astrophysics Data System (ADS)

Huett, Marc-Thorsten

2003-05-01

We formulate mathematical tools for analyzing spatiotemporal data sets. The tools are based on nearest-neighbor considerations similar to cellular automata. One of the analysis tools allows for reconstructing the noise intensity in a data set and is an appropriate method for detecting a variety of noise-induced phenomena in spatiotemporal data. The functioning of these methods is illustrated on sample data generated with the forest fire model and with networks of nonlinear oscillators. It is seen that these methods allow the characterization of spatiotemporal stochastic resonance (STSR) in experimental data. Application of these tools to biological spatiotemporal patterns is discussed. For one specific example, the slime mold Dictyostelium discoideum, it is seen, how transitions between different patterns are clearly marked by changes in the spatiotemporal observables.

Precipitation-productivity Relation in Grassland in Northern China: Investigations at Multiple Spatiotemporal Scales

NASA Astrophysics Data System (ADS)

Hu, Z.

2017-12-01

Climate change is predicted to cause dramatic variability in precipitation regime, not only in terms of change in annual precipitation amount, but also in precipitation seasonal distribution and precipitation event characteristics (high frenquency extrem precipitation, larger but fewer precipitation events), which combined to influence productivity of grassland in arid and semiarid regions. In this study, combining remote sensing products with in-situ measurements of aboveground net primary productivity (ANPP) and gross primary productivity (GPP) data from eddy covariance system in grassland of northern China, we quantified the effects of spatio-temporal vairation in precipitation on productivity from local sites to region scale. We found that, for an individual precipitation event, the duration of GPP-response to the individual precipitation event and the maximum absolute GPP response induced by the individual precipitation event increased linearly with the size of precipitation events. Comparison of the productivity-precipitation relationships between multi-sites determined that the predominant characteristics of precipitation events (PEC) that affected GPP differed remarkably between the water-limited temperate steppe and the temperature-limited alpine meadow. The number of heavy precipitation events (>10 mm d-1) was the most important PEC to impact GPP in the temperate steppe through affecting soil moisture at different soil profiles, while precipitation interval was the factor that affected GPP most in the alpine meadow via its effects on temperature. At the region scale, shape of ANPP-precipitation relationship varies with distinct spatial scales, and besides annual precipitation, precipitation seasonal distribution also has comparable impacts on spatial variation in ANPP. Temporal variability in ANPP was lower at both the dry and wet end, and peaked at a precipitation of 243.1±3.5mm, which is the transition region between typical steppe and desert steppe

How Question Types Reveal Student Thinking: An Experimental Comparison of Multiple-True-False and Free-Response Formats.

PubMed

Hubbard, Joanna K; Potts, Macy A; Couch, Brian A

2017-01-01

Assessments represent an important component of undergraduate courses because they affect how students interact with course content and gauge student achievement of course objectives. To make decisions on assessment design, instructors must understand the affordances and limitations of available question formats. Here, we use a crossover experimental design to identify differences in how multiple-true-false (MTF) and free-response (FR) exam questions reveal student thinking regarding specific conceptions. We report that correct response rates correlate across the two formats but that a higher percentage of students provide correct responses for MTF questions. We find that MTF questions reveal a high prevalence of students with mixed (correct and incorrect) conceptions, while FR questions reveal a high prevalence of students with partial (correct and unclear) conceptions. These results suggest that MTF question prompts can direct students to address specific conceptions but obscure nuances in student thinking and may overestimate the frequency of particular conceptions. Conversely, FR questions provide a more authentic portrait of student thinking but may face limitations in their ability to diagnose specific, particularly incorrect, conceptions. We further discuss an intrinsic tension between question structure and diagnostic capacity and how instructors might use multiple formats or hybrid formats to overcome these obstacles. © 2017 J. K. Hubbard et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Spatio-temporal Dynamics of Audiovisual Speech Processing

PubMed Central

Bernstein, Lynne E.; Auer, Edward T.; Wagner, Michael; Ponton, Curtis W.

2007-01-01

The cortical processing of auditory-alone, visual-alone, and audiovisual speech information is temporally and spatially distributed, and functional magnetic resonance imaging (fMRI) cannot adequately resolve its temporal dynamics. In order to investigate a hypothesized spatio-temporal organization for audiovisual speech processing circuits, event-related potentials (ERPs) were recorded using electroencephalography (EEG). Stimuli were congruent audiovisual /bα/, incongruent auditory /bα/ synchronized with visual /gα/, auditory-only /bα/, and visual-only /bα/ and /gα/. Current density reconstructions (CDRs) of the ERP data were computed across the latency interval of 50-250 milliseconds. The CDRs demonstrated complex spatio-temporal activation patterns that differed across stimulus conditions. The hypothesized circuit that was investigated here comprised initial integration of audiovisual speech by the middle superior temporal sulcus (STS), followed by recruitment of the intraparietal sulcus (IPS), followed by activation of Broca's area (Miller and d'Esposito, 2005). The importance of spatio-temporally sensitive measures in evaluating processing pathways was demonstrated. Results showed, strikingly, early (< 100 msec) and simultaneous activations in areas of the supramarginal and angular gyrus (SMG/AG), the IPS, the inferior frontal gyrus, and the dorsolateral prefrontal cortex. Also, emergent left hemisphere SMG/AG activation, not predicted based on the unisensory stimulus conditions was observed at approximately 160 to 220 msec. The STS was neither the earliest nor most prominent activation site, although it is frequently considered the sine qua non of audiovisual speech integration. As discussed here, the relatively late activity of the SMG/AG solely under audiovisual conditions is a possible candidate audiovisual speech integration response. PMID:17920933

Spatiotemporal Domain Decomposition for Massive Parallel Computation of Space-Time Kernel Density

NASA Astrophysics Data System (ADS)

Hohl, A.; Delmelle, E. M.; Tang, W.

2015-07-01

Accelerated processing capabilities are deemed critical when conducting analysis on spatiotemporal datasets of increasing size, diversity and availability. High-performance parallel computing offers the capacity to solve computationally demanding problems in a limited timeframe, but likewise poses the challenge of preventing processing inefficiency due to workload imbalance between computing resources. Therefore, when designing new algorithms capable of implementing parallel strategies, careful spatiotemporal domain decomposition is necessary to account for heterogeneity in the data. In this study, we perform octtree-based adaptive decomposition of the spatiotemporal domain for parallel computation of space-time kernel density. In order to avoid edge effects near subdomain boundaries, we establish spatiotemporal buffers to include adjacent data-points that are within the spatial and temporal kernel bandwidths. Then, we quantify computational intensity of each subdomain to balance workloads among processors. We illustrate the benefits of our methodology using a space-time epidemiological dataset of Dengue fever, an infectious vector-borne disease that poses a severe threat to communities in tropical climates. Our parallel implementation of kernel density reaches substantial speedup compared to sequential processing, and achieves high levels of workload balance among processors due to great accuracy in quantifying computational intensity. Our approach is portable of other space-time analytical tests.

In Australia: Multiple Intelligences in Multiple Settings.

ERIC Educational Resources Information Center

Vialle, Wilma

1997-01-01

In Australia, Gardner's multiple-intelligences theory has strongly influenced primary, preschool, and special education. A survey of 30 schools revealed that teachers use two basic approaches: teaching to, and teaching through, multiple intelligences. The first approach might develop children's music skills via playing an instrument. The second…

A Web Portal-Based Time-Aware KML Animation Tool for Exploring Spatiotemporal Dynamics of Hydrological Events

NASA Astrophysics Data System (ADS)

Bao, X.; Cai, X.; Liu, Y.

2009-12-01

Understanding spatiotemporal dynamics of hydrological events such as storms and droughts is highly valuable for decision making on disaster mitigation and recovery. Virtual Globe-based technologies such as Google Earth and Open Geospatial Consortium KML standards show great promises for collaborative exploration of such events using visual analytical approaches. However, currently there are two barriers for wider usage of such approaches. First, there lacks an easy way to use open source tools to convert legacy or existing data formats such as shapefiles, geotiff, or web services-based data sources to KML and to produce time-aware KML files. Second, an integrated web portal-based time-aware animation tool is currently not available. Thus users usually share their files in the portal but have no means to visually explore them without leaving the portal environment which the users are familiar with. We develop a web portal-based time-aware KML animation tool for viewing extreme hydrologic events. The tool is based on Google Earth JavaScript API and Java Portlet standard 2.0 JSR-286, and it is currently deployable in one of the most popular open source portal frameworks, namely Liferay. We have also developed an open source toolkit kml-soc-ncsa (http://code.google.com/p/kml-soc-ncsa/) to facilitate the conversion of multiple formats into KML and the creation of time-aware KML files. We illustrate our tool using some example cases, in which drought and storm events with both time and space dimension can be explored in this web-based KML animation portlet. The tool provides an easy-to-use web browser-based portal environment for multiple users to collaboratively share and explore their time-aware KML files as well as improving the understanding of the spatiotemporal dynamics of the hydrological events.

The influence of the interactions between anthropogenic activities and multiple ecological factors on land surface temperatures of urban forests

NASA Astrophysics Data System (ADS)

Ren, Y.

2017-12-01

Context Land surface temperatures (LSTs) spatio-temporal distribution pattern of urban forests are influenced by many ecological factors; the identification of interaction between these factors can improve simulations and predictions of spatial patterns of urban cold islands. This quantitative research requires an integrated method that combines multiple sources data with spatial statistical analysis. Objectives The purpose of this study was to clarify urban forest LST influence interaction between anthropogenic activities and multiple ecological factors using cluster analysis of hot and cold spots and Geogdetector model. We introduced the hypothesis that anthropogenic activity interacts with certain ecological factors, and their combination influences urban forests LST. We also assumed that spatio-temporal distributions of urban forest LST should be similar to those of ecological factors and can be represented quantitatively. Methods We used Jinjiang as a representative city in China as a case study. Population density was employed to represent anthropogenic activity. We built up a multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) on a unified urban scale to support urban forest LST influence interaction research. Through a combination of spatial statistical analysis results, multi-source spatial data, and Geogdetector model, the interaction mechanisms of urban forest LST were revealed. Results Although different ecological factors have different influences on forest LST, in two periods with different hot spots and cold spots, the patch area and dominant tree species were the main factors contributing to LST clustering in urban forests. The interaction between anthropogenic activity and multiple ecological factors increased LST in urban forest stands, linearly and nonlinearly. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots

World Spatiotemporal Analytics and Mapping Project (WSTAMP): Discovering, Exploring, and Mapping Spatiotemporal Patterns across the World s Largest Open Source Geographic Data Sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stewart, Robert N; Piburn, Jesse O; Sorokine, Alexandre

The application of spatiotemporal (ST) analytics to integrated data from major sources such as the World Bank, United Nations, and dozens of others holds tremendous potential for shedding new light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. 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, and changing attributes, as well as content that is textual, numeric, categorical, and hierarchical. Equally challenging is the development of analytical and visualization approaches that provide a serious exploration of thismore » integrated data while remaining accessible to practitioners with varied backgrounds. The WSTAMP project at 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 10,000+ attributes covering over 200 nation states spanning 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 discuss the status of this work and report on major findings. Acknowledgment Prepared by Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, Tennessee 37831-6285, managed by UT-Battelle, LLC for the U. S. Department of Energy under contract no. DEAC05-00OR22725. Copyright This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. Accordingly, the United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to

Spatiotemporal dynamics of Gaussian laser pulse in a multi ions plasma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jafari Milani, M. R., E-mail: mrj.milani@gmail.com

Spatiotemporal evolutions of Gaussian laser pulse propagating through a plasma with multiple charged ions are studied, taking into account the ponderomotive nonlinearity. Coupled differential equations for beam width and pulse length parameters are established and numerically solved using paraxial ray approximation. In one-dimensional geometry, effects of laser and plasma parameters such as laser intensity, plasma density, and temperature on the longitudinal pulse compression and the laser intensity distribution are analyzed for plasmas with singly and doubly charged ions. The results demonstrate that self-compression occurs in a laser intensity range with a turning point intensity in which the self-compression process hasmore » its strongest extent. The results also show that the multiply ionized ions have different effect on the pulse compression above and below turning point intensity. Finally, three-dimensional geometry is used to analyze the simultaneous evolution of both self-focusing and self-compression of Gaussian laser pulse in such plasmas.« less

Multi-gene phylogenetic analysis reveals the multiple origin and evolution of mangrove physiological traits through exaptation

NASA Astrophysics Data System (ADS)

Sahu, Sunil Kumar; Singh, Reena; Kathiresan, Kandasamy

2016-12-01

Mangroves are taxonomically diverse group of salt-tolerant, mainly arboreal, flowering plants that grow in tropical and sub-tropical regions and have adapted themselves to thrive in such obdurate surroundings. While evolution is often understood exclusively in terms of adaptation, innovation often begins when a feature adapted for one function is co-opted for a different purpose and the co-opted features are called exaptations. Thus, one of the fundamental issues is what features of mangroves have evolved through exaptation. We attempt to address these questions through molecular phylogenetic approach using chloroplast and nuclear markers. First, we determined if these mangroves specific traits have evolved multiple times in the phylogeny. Once the multiple origins were established, we then looked at related non-mangrove species for characters that could have been co-opted by mangrove species. We also assessed the efficacy of these molecular sequences in distinguishing mangroves at the species level. This study revealed the multiple origin of mangroves and shed light on the ancestral characters that might have led certain lineages of plants to adapt to estuarine conditions and also traces the evolutionary history of mangroves and hitherto unexplained theory that mangroves traits (aerial roots and viviparous propagules) evolved as a result of exaptation rather than adaptation to saline habitats.

Modeling spatio-temporal wildfire ignition point patterns

Treesearch

Amanda S. Hering; Cynthia L. Bell; Marc G. Genton

2009-01-01

We analyze and model the structure of spatio-temporal wildfire ignitions in the St. Johns River Water Management District in northeastern Florida. Previous studies, based on the K-function and an assumption of homogeneity, have shown that wildfire events occur in clusters. We revisit this analysis based on an inhomogeneous K-...

Retrieval of Spatio-temporal Distributions of Particle Parameters from Multiwavelength Lidar Measurements Using the Linear Estimation Technique and Comparison with AERONET

NASA Technical Reports Server (NTRS)

Veselovskii, I.; Whiteman, D. N.; Korenskiy, M.; Kolgotin, A.; Dubovik, O.; Perez-Ramirez, D.; Suvorina, A.

2013-01-01

The results of the application of the linear estimation technique to multiwavelength Raman lidar measurements performed during the summer of 2011 in Greenbelt, MD, USA, are presented. We demonstrate that multiwavelength lidars are capable not only of providing vertical profiles of particle properties but also of revealing the spatio-temporal evolution of aerosol features. The nighttime 3 Beta + 1 alpha lidar measurements on 21 and 22 July were inverted to spatio-temporal distributions of particle microphysical parameters, such as volume, number density, effective radius and the complex refractive index. The particle volume and number density show strong variation during the night, while the effective radius remains approximately constant. The real part of the refractive index demonstrates a slight decreasing tendency in a region of enhanced extinction coefficient. The linear estimation retrievals are stable and provide time series of particle parameters as a function of height at 4 min resolution. AERONET observations are compared with multiwavelength lidar retrievals showing good agreement.

Spatio-temporal response of maize yield to edaphic and meteorological conditions in a saline farmland

USDA-ARS?s Scientific Manuscript database

Spatio-temporal variability of crop production strongly depends on soil heterogeneity, meteorological conditions, and their interaction. Canopy reflectance can be used to describe crop status and yield spatial variability. The objectives of this work were to understand the spatio-temporal variabilit...

Close similarity between spatiotemporal frequency tunings of human cortical responses and involuntary manual following responses to visual motion.

PubMed

Amano, Kaoru; Kimura, Toshitaka; Nishida, Shin'ya; Takeda, Tsunehiro; Gomi, Hiroaki

2009-02-01

Human brain uses visual motion inputs not only for generating subjective sensation of motion but also for directly guiding involuntary actions. For instance, during arm reaching, a large-field visual motion is quickly and involuntarily transformed into a manual response in the direction of visual motion (manual following response, MFR). Previous attempts to correlate motion-evoked cortical activities, revealed by brain imaging techniques, with conscious motion perception have resulted only in partial success. In contrast, here we show a surprising degree of similarity between the MFR and the population neural activity measured by magnetoencephalography (MEG). We measured the MFR and MEG induced by the same motion onset of a large-field sinusoidal drifting grating with changing the spatiotemporal frequency of the grating. The initial transient phase of these two responses had very similar spatiotemporal tunings. Specifically, both the MEG and MFR amplitudes increased as the spatial frequency was decreased to, at most, 0.05 c/deg, or as the temporal frequency was increased to, at least, 10 Hz. We also found in peak latency a quantitative agreement (approximately 100-150 ms) and correlated changes against spatiotemporal frequency changes between MEG and MFR. In comparison with these two responses, conscious visual motion detection is known to be most sensitive (i.e., have the lowest detection threshold) at higher spatial frequencies and have longer and more variable response latencies. Our results suggest a close relationship between the properties of involuntary motor responses and motion-evoked cortical activity as reflected by the MEG.

Partial Fourier techniques in single-shot cross-term spatiotemporal encoded MRI.

PubMed

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.

Discovery of spatio-temporal patterns from location-based social networks

NASA Astrophysics Data System (ADS)

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.

Against Laplacian Reduction of Newtonian Mass to Spatiotemporal Quantities

NASA Astrophysics Data System (ADS)

Martens, Niels C. M.

2018-05-01

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.

Against Laplacian Reduction of Newtonian Mass to Spatiotemporal Quantities

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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

Spatiotemporal behavior and nonlinear dynamics in a phase conjugate resonator

NASA Technical Reports Server (NTRS)

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.

Spatiotemporal patterns of infant bronchiolitis in a Tennessee Medicaid population.

PubMed

Sloan, Chantel D; Gebretsadik, Tebeb; Wu, Pingsheng; Carroll, Kecia N; Mitchel, Edward F; Hartert, Tina V

2013-09-01

Respiratory syncytial virus (RSV) is a major cause of worldwide morbidity and mortality in infants, primarily through the induction of bronchiolitis. RSV epidemics are highly seasonal, occurring in the winter months in the northern hemisphere. Within the United States, RSV epidemic dynamics vary both spatially and temporally. This analysis employs a retrospective space–time scan statistic to locate spatiotemporal clustering of infant bronchiolitis in a very large Tennessee (TN) Medicaid cohort. We studied infants less than 6 months of age (N = 52,468 infants) who had an outpatient visit, emergency department visit, or hospitalization for bronchiolitis between 1995 and 2008. The scan statistic revealed distinctive and consistent patterns of deviation in epidemic timing. Eastern TN (Knoxville area) showed clustering in January and February, and Central TN (Nashville area) in November and December. This is likely due to local variation in geography-associated factors which should be taken into consideration in future modeling of RSV epidemics.

Spatiotemporal definition of neurite outgrowth, refinement and retraction in the developing mouse cochlea.

PubMed

Huang, Lin-Chien; Thorne, Peter R; Housley, Gary D; Montgomery, Johanna M

2007-08-01

The adult mammalian cochlea receives dual afferent innervation: the inner sensory hair cells are innervated exclusively by type I spiral ganglion neurons (SGN), whereas the sensory outer hair cells are innervated by type II SGN. We have characterized the spatiotemporal reorganization of the dual afferent innervation pattern as it is established in the developing mouse cochlea. This reorganization occurs during the first postnatal week just before the onset of hearing. Our data reveal three distinct phases in the development of the afferent innervation of the organ of Corti: (1) neurite growth and extension of both classes of afferents to all hair cells (E18-P0); (2) neurite refinement, with formation of the outer spiral bundles innervating outer hair cells (P0-P3); (3) neurite retraction and synaptic pruning to eliminate type I SGN innervation of outer hair cells, while retaining their innervation of inner hair cells (P3-P6). The characterization of this developmental innervation pattern was made possible by the finding that tetramethylrhodamine-conjugated dextran (TMRD) specifically labeled type I SGN. Peripherin and choline-acetyltransferase immunofluorescence confirmed the type II and efferent innervation patterns, respectively, and verified the specificity of the type I SGN neurites labeled by TMRD. These findings define the precise spatiotemporal neurite reorganization of the two afferent nerve fiber populations in the cochlea, which is crucial for auditory neurotransmission. This reorganization also establishes the cochlea as a model system for studying CNS synapse development, plasticity and elimination.

On the potentials of multiple climate variables in assessing the spatio-temporal characteristics of hydrological droughts over the Volta Basin.

PubMed

Ndehedehe, Christopher E; Awange, Joseph L; Corner, Robert J; Kuhn, Michael; Okwuashi, Onuwa

2016-07-01

Multiple drought episodes over the Volta basin in recent reports may lead to food insecurity and loss of revenue. However, drought studies over the Volta basin are rather generalised and largely undocumented due to sparse ground observations and unsuitable framework to determine their space-time occurrence. In this study, we examined the utility of standardised indicators (standardised precipitation index (SPI), standardised runoff index (SRI), standardised soil moisture index (SSI), and multivariate standardised drought index (MSDI)) and Gravity Recovery and Climate Experiment (GRACE) derived terrestrial water storage to assess hydrological drought characteristics over the basin. In order to determine the space-time patterns of hydrological drought in the basin, Independent Component Analysis (ICA), a higher order statistical technique was employed. The results show that SPI and SRI exhibit inconsistent behaviour in observed wet years presupposing a non-linear relationship that reflects the slow response of river discharge to precipitation especially after a previous extreme dry period. While the SPI and SSI show a linear relationship with a correlation of 0.63, the correlation between the MSDIs derived from combining precipitation/river discharge and precipitation/soil moisture indicates a significant value of 0.70 and shows an improved skill in hydrological drought monitoring over the Volta basin during the study period. The ICA-derived spatio-temporal hydrological drought patterns show Burkina Faso and the Lake Volta areas as predominantly drought zones. Further, the statistically significant negative correlations of pacific decadal oscillations (0.39 and 0.25) with temporal evolutions of drought in Burkina Faso and Ghana suggest the possible influence of low frequency large scale oscillations in the observed wet and dry regimes over the basin. Finally, our approach in drought assessment over the Volta basin contributes to a broad framework for hydrological

Spatiotemporal Variability of Meltwater Refreezing in Southwest Greenland Ice Sheet Firn

NASA Astrophysics Data System (ADS)

Rennermalm, A. K.; Hock, R.; Tedesco, M.; Corti, G.; Covi, F.; Miège, C.; Kingslake, J.; Leidman, S. Z.; Munsell, S.

2017-12-01

A substantial fraction of the summer meltwater formed on the surface of the Greenland ice sheet is retained in firn, while the remaining portion runs to the ocean through surface and subsurface channels. Refreezing of meltwater in firn can create impenetrable ice lenses, hence being a crucial process in the redistribution of surface runoff. To quantify the impact of refreezing on runoff and current and future Greenland surface mass balance, a three year National Science Foundation funded project titled "Refreezing in the firn of the Greenland ice sheet: Spatiotemporal variability and implications for ice sheet mass balance" started this past year. Here we present an overview of the project and some initial results from the first field season in May 2017 conducted in proximity of the DYE-2 site in the percolation zone of the Southwest Greenland ice sheet at elevations between 1963 and 2355 m a.s.l.. During this fieldwork two automatic weather stations were deployed, outfitted with surface energy balance sensors and 16 m long thermistor strings, over 300 km of ground penetrating radar data were collected, and five 20-26 m deep firn cores were extracted and analyzed for density and stratigraphy. Winter snow accumulation was measured along the radar tracks. Preliminary work on the firn-core data reveals increasing frequency and thickness of ice lenses at lower ice-sheet elevations, in agreement with other recent work in the area. Data collected within this project will facilitate advances in our understanding of the spatiotemporal variability of firn refreezing and its role in the hydrology and surface mass balance of the Greenland Ice Sheet.

NeuroMap: A Spline-Based Interactive Open-Source Software for Spatiotemporal Mapping of 2D and 3D MEA Data

PubMed Central

Abdoun, Oussama; Joucla, Sébastien; Mazzocco, Claire; Yvert, Blaise

2010-01-01

A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA) technology. Indeed, high-density MEAs provide large-scale coverage (several square millimeters) of whole neural structures combined with microscopic resolution (about 50 μm) of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid-deformation-based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware. PMID:21344013

NeuroMap: A Spline-Based Interactive Open-Source Software for Spatiotemporal Mapping of 2D and 3D MEA Data.

PubMed

Abdoun, Oussama; Joucla, Sébastien; Mazzocco, Claire; Yvert, Blaise

2011-01-01

A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA) technology. Indeed, high-density MEAs provide large-scale coverage (several square millimeters) of whole neural structures combined with microscopic resolution (about 50 μm) of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid-deformation-based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware.

Stable Isotope Analysis of Precipitation Samples Obtained via Crowdsourcing Reveals the Spatiotemporal Evolution of Superstorm Sandy

PubMed Central

Good, Stephen P.; Mallia, Derek V.; Lin, John C.; Bowen, Gabriel J.

2014-01-01

Extra-tropical cyclones, such as 2012 Superstorm Sandy, pose a significant climatic threat to the northeastern United Sates, yet prediction of hydrologic and thermodynamic processes within such systems is complicated by their interaction with mid-latitude water patterns as they move poleward. Fortunately, the evolution of these systems is also recorded in the stable isotope ratios of storm-associated precipitation and water vapor, and isotopic analysis provides constraints on difficult-to-observe cyclone dynamics. During Superstorm Sandy, a unique crowdsourced approach enabled 685 precipitation samples to be obtained for oxygen and hydrogen isotopic analysis, constituting the largest isotopic sampling of a synoptic-scale system to date. Isotopically, these waters span an enormous range of values (21‰ for O, 160‰ for H) and exhibit strong spatiotemporal structure. Low isotope ratios occurred predominantly in the west and south quadrants of the storm, indicating robust isotopic distillation that tracked the intensity of the storm's warm core. Elevated values of deuterium-excess (25‰) were found primarily in the New England region after Sandy made landfall. Isotope mass balance calculations and Lagrangian back-trajectory analysis suggest that these samples reflect the moistening of dry continental air entrained from a mid-latitude trough. These results demonstrate the power of rapid-response isotope monitoring to elucidate the structure and dynamics of water cycling within synoptic-scale systems and improve our understanding of storm evolution, hydroclimatological impacts, and paleo-storm proxies. PMID:24618882

Characterization of New Otic Enhancers of the Pou3f4 Gene Reveal Distinct Signaling Pathway Regulation and Spatio-Temporal Patterns

PubMed Central

Robert-Moreno, Àlex; Naranjo, Silvia; de la Calle-Mustienes, Elisa; Gómez-Skarmeta, José Luis; Alsina, Berta

2010-01-01

POU3F4 is a member of the POU-homedomain transcription factor family with a prominent role in inner ear development. Mutations in the human POU3F4 coding unit leads to X-linked deafness type 3 (DFN3), characterized by conductive hearing loss and progressive sensorineural deafness. Microdeletions found 1 Mb 5′ upstream of the coding region also displayed the same phenotype, suggesting that cis-regulatory elements might be present in that region. Indeed, we and others have recently identified several enhancers at the 1 Mb 5′ upstream interval of the pou3f4 locus. Here we characterize the spatio-temporal patterns of these regulatory elements in zebrafish transgenic lines. We show that the most distal enhancer (HCNR 81675) is activated earlier and drives GFP reporter expression initially to a broad ear domain to progressively restrict to the sensory patches. The proximal enhancer (HCNR 82478) is switched later during development and promotes expression, among in other tissues, in sensory patches from its onset. The third enhancer (HCNR 81728) is also active at later stages in the otic mesenchyme and in the otic epithelium. We also characterize the signaling pathways regulating these enhancers. While HCNR 81675 is regulated by very early signals of retinoic acid, HCNR 82478 is regulated by Fgf activity at a later stage and the HCNR 81728 enhancer is under the control of Hh signaling. Finally, we show that Sox2 and Pax2 transcription factors are bound to HCNR 81675 genomic region during otic development and specific mutations to these transcription factor binding sites abrogates HCNR 81675 enhancer activity. Altogether, our results suggest that pou3f4 expression in inner ear might be under the control of distinct regulatory elements that fine-tune the spatio-temporal activity of this gene and provides novel data on the signaling mechanisms controlling pou3f4 function. PMID:21209840

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

NASA Astrophysics Data System (ADS)

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 control of opioid signaling and behavior.

PubMed

Siuda, Edward R; Copits, Bryan A; Schmidt, Martin J; Baird, Madison A; Al-Hasani, Ream; Planer, William J; Funderburk, Samuel C; McCall, Jordan G; Gereau, Robert W; Bruchas, Michael R

2015-05-20

Optogenetics is now a widely accepted tool for spatiotemporal manipulation of neuronal activity. However, a majority of optogenetic approaches use binary on/off control schemes. Here, we extend the optogenetic toolset by developing a neuromodulatory approach using a rationale-based design to generate a Gi-coupled, optically sensitive, mu-opioid-like receptor, which we term opto-MOR. We demonstrate that opto-MOR engages canonical mu-opioid signaling through inhibition of adenylyl cyclase, activation of MAPK and G protein-gated inward rectifying potassium (GIRK) channels and internalizes with kinetics similar to that of the mu-opioid receptor. To assess in vivo utility, we expressed a Cre-dependent viral opto-MOR in RMTg/VTA GABAergic neurons, which led to a real-time place preference. In contrast, expression of opto-MOR in GABAergic neurons of the ventral pallidum hedonic cold spot led to real-time place aversion. This tool has generalizable application for spatiotemporal control of opioid signaling and, furthermore, can be used broadly for mimicking endogenous neuronal inhibition pathways. Copyright © 2015 Elsevier Inc. All rights reserved.

Multiscale recurrence analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

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.

Multiscale recurrence analysis of spatio-temporal data.

PubMed

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.

A spatiotemporal model of ecological and sociological ...

EPA Pesticide Factsheets

Background/Question/Methods Suffolk County, New York is a locus for West Nile virus (WNV) infection in the American northeast that includes the majority of Long Island to the east of New York City. The county has a robust system of light and gravid traps used for mosquito collection and disease monitoring. Since 2010, there have been 55 confirmed human cases of WNV in Suffolk County, resulting in 3 deaths. In order to identify predictors of WNV incidence in mosquitoes and predict future occurrence of WNV we developed a spatiotemporal Bayesian model, beginning with over 40 ecological, meteorological, and built-environment covariates. A mixed effects model including spatially and temporally correlated errors was fit to WNV surveillance data from 2008-2014 using the R package 'R-INLA' which allows for Bayesian modeling using the stochastic partial differential equation (SPDE) approach. The INLA SPDE allows for simultaneous fitting of temporal parameters and a spatial covariance matrix, while incorporating multiple likelihood functions and running in standard R statistical software on a typical home computer. Results/Conclusions We found that land cover classified as open water or woody wetlands had a negative association with WNV incidence in mosquitoes, and the count of septic systems was associated with an increase in WNV. Mean temperature at two weeks lag was associated with a strong positive impact, while mean precipitation at no lag and

Application of a novel hybrid method for spatiotemporal data imputation: A case study of the Minqin County groundwater level

NASA Astrophysics Data System (ADS)

Zhang, Zhongrong; Yang, Xuan; Li, Hao; Li, Weide; Yan, Haowen; Shi, Fei

2017-10-01

The techniques for data analyses have been widely developed in past years, however, missing data still represent a ubiquitous problem in many scientific fields. In particular, dealing with missing spatiotemporal data presents an enormous challenge. Nonetheless, in recent years, a considerable amount of research has focused on spatiotemporal problems, making spatiotemporal missing data imputation methods increasingly indispensable. In this paper, a novel spatiotemporal hybrid method is proposed to verify and imputed spatiotemporal missing values. This new method, termed SOM-FLSSVM, flexibly combines three advanced techniques: self-organizing feature map (SOM) clustering, the fruit fly optimization algorithm (FOA) and the least squares support vector machine (LSSVM). We employ a cross-validation (CV) procedure and FOA swarm intelligence optimization strategy that can search available parameters and determine the optimal imputation model. The spatiotemporal underground water data for Minqin County, China, were selected to test the reliability and imputation ability of SOM-FLSSVM. We carried out a validation experiment and compared three well-studied models with SOM-FLSSVM using a different missing data ratio from 0.1 to 0.8 in the same data set. The results demonstrate that the new hybrid method performs well in terms of both robustness and accuracy for spatiotemporal missing data.

Application of Deep Learning and Supervised Learning Methods to Recognize Nonlinear Hidden Pattern in Water Stress Levels from Spatiotemporal Datasets across Rural and Urban US Counties

NASA Astrophysics Data System (ADS)

Eisenhart, T.; Josset, L.; Rising, J. A.; Devineni, N.; Lall, U.

2017-12-01

In the wake of recent water crises, the need to understand and predict the risk of water stress in urban and rural areas has grown. This understanding has the potential to improve decision making in public resource management, policy making, risk management and investment decisions. Assuming an underlying relationship between urban and rural water stress and observable features, we apply Deep Learning and Supervised Learning models to uncover hidden nonlinear patterns from spatiotemporal datasets. Results of interest includes prediction accuracy on extreme categories (i.e. urban areas highly prone to water stress) and not solely the average risk for urban or rural area, which adds complexity to the tuning of model parameters. We first label urban water stressed counties using annual water quality violations and compile a comprehensive spatiotemporal dataset that captures the yearly evolution of climatic, demographic and economic factors of more than 3,000 US counties over the 1980-2010 period. As county-level data reporting is not done on a yearly basis, we test multiple imputation methods to get around the issue of missing data. Using Python libraries, TensorFlow and scikit-learn, we apply and compare the ability of, amongst other methods, Recurrent Neural Networks (testing both LSTM and GRU cells), Convolutional Neural Networks and Support Vector Machines to predict urban water stress. We evaluate the performance of those models over multiple time spans and combine methods to diminish the risk of overfitting and increase prediction power on test sets. This methodology seeks to identify hidden nonlinear patterns to assess the predominant data features that influence urban and rural water stress. Results from this application at the national scale will assess the performance of deep learning models to predict water stress risk areas across all US counties and will highlight a predominant Machine Learning method for modeling water stress risk using spatiotemporal

Effects of Pacing Site and Stimulation History on Alternans Dynamics and the Development of Complex Spatiotemporal Patterns in Cardiac Tissue

PubMed Central

Gizzi, Alessio; Cherry, Elizabeth M.; Gilmour, Robert F.; Luther, Stefan; Filippi, Simonetta; Fenton, Flavio H.

2013-01-01

Alternans of action potential duration has been associated with T wave alternans and the development of arrhythmias because it produces large gradients of repolarization. However, little is known about alternans dynamics in large mammalian hearts. Using optical mapping to record electrical activations simultaneously from the epicardium and endocardium of 9 canine right ventricles, we demonstrate novel arrhythmogenic complex spatiotemporal dynamics. (i) Alternans predominantly develops first on the endocardium. (ii) The postulated simple progression from normal rhythm to concordant to discordant alternans is not always observed; concordant alternans can develop from discordant alternans as the pacing period is decreased. (iii) In contrast to smaller tissue preparations, multiple stationary nodal lines may exist and need not be perpendicular to the pacing site or to each other. (iv) Alternans has fully three-dimensional dynamics and the epicardium and endocardium can show significantly different dynamics: multiple nodal surfaces can be transmural or intramural and can form concave/convex surfaces resulting in islands of discordant alternans. (v) The complex spatiotemporal patterns observed during alternans are very sensitive to both the site of stimulation and the stimulation history. Alternans in canine ventricles not only exhibit larger amplitudes and persist for longer cycle length regimes compared to those found in smaller mammalian hearts, but also show novel dynamics not previously described that enhance dispersion and show high sensitivity to initial conditions. This indicates some underlying predisposition to chaos and can help to guide the design of new drugs and devices controlling and preventing arrhythmic events. PMID:23637684

Velocity landscape correlation resolves multiple flowing protein populations from fluorescence image time series.

PubMed

Pandžić, Elvis; Abu-Arish, Asmahan; Whan, Renee M; Hanrahan, John W; Wiseman, Paul W

2018-02-16

Molecular, vesicular and organellar flows are of fundamental importance for the delivery of nutrients and essential components used in cellular functions such as motility and division. With recent advances in fluorescence/super-resolution microscopy modalities we can resolve the movements of these objects at higher spatio-temporal resolutions and with better sensitivity. Previously, spatio-temporal image correlation spectroscopy has been applied to map molecular flows by correlation analysis of fluorescence fluctuations in image series. However, an underlying assumption of this approach is that the sampled time windows contain one dominant flowing component. Although this was true for most of the cases analyzed earlier, in some situations two or more different flowing populations can be present in the same spatio-temporal window. We introduce an approach, termed velocity landscape correlation (VLC), which detects and extracts multiple flow components present in a sampled image region via an extension of the correlation analysis of fluorescence intensity fluctuations. First we demonstrate theoretically how this approach works, test the performance of the method with a range of computer simulated image series with varying flow dynamics. Finally we apply VLC to study variable fluxing of STIM1 proteins on microtubules connected to the plasma membrane of Cystic Fibrosis Bronchial Epithelial (CFBE) cells. Copyright © 2018 Elsevier Inc. All rights reserved.

Spatiotemporal coding of inputs for a system of globally coupled phase oscillators

NASA Astrophysics Data System (ADS)

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.

Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning.

PubMed

McGovern, Amy; Gagne, David J; Williams, John K; Brown, Rodger A; Basara, Jeffrey B

Severe weather, including tornadoes, thunderstorms, wind, and hail annually cause significant loss of life and property. We are developing spatiotemporal machine learning techniques that will enable meteorologists to improve the prediction of these events by improving their understanding of the fundamental causes of the phenomena and by building skillful empirical predictive models. In this paper, we present significant enhancements of our Spatiotemporal Relational Probability Trees that enable autonomous discovery of spatiotemporal relationships as well as learning with arbitrary shapes. We focus our evaluation on two real-world case studies using our technique: predicting tornadoes in Oklahoma and predicting aircraft turbulence in the United States. We also discuss how to evaluate success for a machine learning algorithm in the severe weather domain, which will enable new methods such as ours to transfer from research to operations, provide a set of lessons learned for embedded machine learning applications, and discuss how to field our technique.

Spatio-temporal pattern of viral meningitis in Michigan, 1993-2001

NASA Astrophysics Data System (ADS)

Greene, Sharon K.; Schmidt, Mark A.; Stobierski, Mary Grace; Wilson, Mark L.

2005-05-01

To characterize Michigan's high viral meningitis incidence rates, 8,803 cases from 1993-2001 were analyzed for standard epidemiological indices, geographic distribution, and spatio-temporal clusters. Blacks and infants were found to be high-risk groups. Annual seasonality and interannual variability in epidemic magnitude were apparent. Cases were concentrated in southern Michigan, and cumulative incidence was correlated with population density at the county level (r=0.45, p<0.001). Kulldorff's Scan test identified the occurrence of spatio-temporal clusters in Lower Michigan during July-October 1998 and 2001 (p=0.01). More extensive data on cases, laboratory isolates, sociodemographics, and environmental exposures should improve detection and enhance the effectiveness of a Space-Time Information System aimed at prevention.

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System

PubMed Central

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

Spatiotemporal Mapping of Interictal Spike Propagation: A Novel Methodology Applied to Pediatric Intracranial EEG Recordings

PubMed Central

Tomlinson, Samuel B.; Bermudez, Camilo; Conley, Chiara; Brown, Merritt W.; Porter, Brenda E.; Marsh, Eric D.

2016-01-01

Synchronized cortical activity is implicated in both normative cognitive functioning and many neurologic disorders. For epilepsy patients with intractable seizures, irregular synchronization within the epileptogenic zone (EZ) is believed to provide the network substrate through which seizures initiate and propagate. Mapping the EZ prior to epilepsy surgery is critical for detecting seizure networks in order to achieve postsurgical seizure control. However, automated techniques for characterizing epileptic networks have yet to gain traction in the clinical setting. Recent advances in signal processing and spike detection have made it possible to examine the spatiotemporal propagation of interictal spike discharges across the epileptic cortex. In this study, we present a novel methodology for detecting, extracting, and visualizing spike propagation and demonstrate its potential utility as a biomarker for the EZ. Eighteen presurgical intracranial EEG recordings were obtained from pediatric patients ultimately experiencing favorable (i.e., seizure-free, n = 9) or unfavorable (i.e., seizure-persistent, n = 9) surgical outcomes. Novel algorithms were applied to extract multichannel spike discharges and visualize their spatiotemporal propagation. Quantitative analysis of spike propagation was performed using trajectory clustering and spatial autocorrelation techniques. Comparison of interictal propagation patterns revealed an increase in trajectory organization (i.e., spatial autocorrelation) among Sz-Free patients compared with Sz-Persist patients. The pathophysiological basis and clinical implications of these findings are considered. PMID:28066315

Precursor of transition to turbulence: spatiotemporal wave front.

PubMed

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.

Spatiotemporal analysis of land use and land cover change in the Brazilian Amazon

PubMed Central

Li, Guiying; Moran, Emilio; Hetrick, Scott

2013-01-01

This paper provides a comparative analysis of land use and land cover (LULC) changes among three study areas with different biophysical environments in the Brazilian Amazon at multiple scales, from per-pixel, polygon, census sector, to study area. Landsat images acquired in the years of 1990/1991, 1999/2000, and 2008/2010 were used to examine LULC change trajectories with the post-classification comparison approach. A classification system composed of six classes – forest, savanna, other-vegetation (secondary succession and plantations), agro-pasture, impervious surface, and water, was designed for this study. A hierarchical-based classification method was used to classify Landsat images into thematic maps. This research shows different spatiotemporal change patterns, composition and rates among the three study areas and indicates the importance of analyzing LULC change at multiple scales. The LULC change analysis over time for entire study areas provides an overall picture of change trends, but detailed change trajectories and their spatial distributions can be better examined at a per-pixel scale. The LULC change at the polygon scale provides the information of the changes in patch sizes over time, while the LULC change at census sector scale gives new insights on how human-induced activities (e.g., urban expansion, roads, and land use history) affect LULC change patterns and rates. This research indicates the necessity to implement change detection at multiple scales for better understanding the mechanisms of LULC change patterns and rates. PMID:24127130

Noise tolerant spatiotemporal chaos computing.

PubMed

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.

Noise tolerant spatiotemporal chaos computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kia, Behnam; Kia, Sarvenaz; Ditto, William L.

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.

Sensor Web for Spatio-Temporal Monitoring of a Hydrological Environment

NASA Technical Reports Server (NTRS)

Delin, K. A.; Jackson, S. P.; Johnson, D. W.; Burleigh, S. C.; Woodrow, R. R.; McAuley, M.; Britton, J. T.; Dohm, J. M.; Ferre, T. P. A.; Ip, Felipe

2004-01-01

The Sensor Web is a macroinstrument concept that allows for the spatio-temporal understanding of an environment through coordinated efforts between multiple numbers and types of sensing platforms, including, in its most general form, both orbital and terrestrial and both fixed and mobile. Each of these platforms, or pods, communicates within its local neighborhood and thus distributes information to the instrument as a whole. The result of sharing and continual processing of this information among all the Sensor Web elements will result in an information flow and a global perception of and reactive capability to the environment. As illustrated, the Sensor Web concept also allows for the recursive notion of a web of webs with individual distributed instruments possibly playing the role of a single node point on a larger Sensor Web instrument. In particular, the fusion of inexpensive, yet sophisticated, commercial technology from both the computation and telecommunication revolutions has enabled the development of practical, fielded, and embedded in situ systems that have been the focus of the NASA/JPL Sensor Webs Project (http://sensorwebs.jpl.nasa.gov/). These Sensor Webs are complete systems consisting of not only the pod elements that wirelessly communicate among themselves, but also interfacing and archiving software that allows for easy use by the end-user. Previous successful deployments have included environments as diverse as coastal regions, Antarctica, and desert areas. The Sensor Web has broad implications for Earth and planetary science and will revolutionize the way experiments and missions are conceived and performed. As part of our current efforts to develop a macrointelligence within the system, we have deployed a Sensor Web at the Central Avra Valley Storage and Recovery Project (CAVSARP) facility located west of Tucson, AZ. This particular site was selected because it is ideal for studying spatio-temporal phenomena and for providing a test site for

Use of Visual and Proprioceptive Feedback to Improve Gait Speed and Spatiotemporal Symmetry Following Chronic Stroke: A Case Series

PubMed Central

Feasel, Jeff; Wentz, Erin; Brooks, Frederick P.; Whitton, Mary C.

2012-01-01

Background and Purpose Persistent deficits in gait speed and spatiotemporal symmetry are prevalent following stroke and can limit the achievement of community mobility goals. Rehabilitation can improve gait speed, but has shown limited ability to improve spatiotemporal symmetry. The incorporation of combined visual and proprioceptive feedback regarding spatiotemporal symmetry has the potential to be effective at improving gait. Case Description A 60-year-old man (18 months poststroke) and a 53-year-old woman (21 months poststroke) each participated in gait training to improve gait speed and spatiotemporal symmetry. Each patient performed 18 sessions (6 weeks) of combined treadmill-based gait training followed by overground practice. To assist with relearning spatiotemporal symmetry, treadmill-based training for both patients was augmented with continuous, real-time visual and proprioceptive feedback from an immersive virtual environment and a dual belt treadmill, respectively. Outcomes Both patients improved gait speed (patient 1: 0.35 m/s improvement; patient 2: 0.26 m/s improvement) and spatiotemporal symmetry. Patient 1, who trained with step-length symmetry feedback, improved his step-length symmetry ratio, but not his stance-time symmetry ratio. Patient 2, who trained with stance-time symmetry feedback, improved her stance-time symmetry ratio. She had no step-length asymmetry before training. Discussion Both patients made improvements in gait speed and spatiotemporal symmetry that exceeded those reported in the literature. Further work is needed to ascertain the role of combined visual and proprioceptive feedback for improving gait speed and spatiotemporal symmetry after chronic stroke. PMID:22228605

How Do Multiple-Star Systems Form? VLA Study Reveals "Smoking Gun"

NASA Astrophysics Data System (ADS)

2006-12-01

system, all the antennas could provide data for us. In addition, we improved the level of detail by using the Pie Town, NM, antenna of the Very Long Baseline Array, as part of an expanded system," Lim said. The implementation and improvement of the 43 GHz receiving system was a collaborative program among the German Max Planck Institute, the Mexican National Autonomous University, and the U.S. National Radio Astronomy Observatory. Two popular theoretical models for the formation of multiple-star systems are, first, that the two protostars and their surrounding dusty disks fragment from a larger parent disk, and, second, that the protostars form independently and then one captures the other into a mutual orbit. "Our new study shows that the disks of the two main protostars are aligned with each other, and also are aligned with the larger, surrounding disk. In addition, their orbital motion resembles the rotation of the larger disk. This is a 'smoking gun' supporting the fragmentation model," Lim said. However, the new study also revealed a third young star with a dust disk. "The disk of this one is misaligned with those of the other two, so it may be the result of either fragmentation or capture," Takakuwa said. The misalignment of the third disk could have come through gravitational interactions with the other two, larger, protostars, the scientists said. They plan further observations to try to resolve the question. "We have a very firm indication that two of these protostars and their dust disks formed from the same, larger disk-like cloud, then broke out from it in a fragmentation process. That strongly supports one theoretical model for how multiple-star systems are formed. The misalignment of the third protostar and its disk leaves open the possibility that it could have formed elsewhere and been captured, and we'll continue to work on reconstructing the history of this fascinating system," Lim summarized. The National Radio Astronomy Observatory is a facility of

Exploring the spatio-temporal neural basis of face learning

PubMed Central

Yang, Ying; Xu, Yang; Jew, Carol A.; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.

2017-01-01

Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150–250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150–250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces. PMID:28570739

Exploring the spatio-temporal neural basis of face learning.

PubMed

Yang, Ying; Xu, Yang; Jew, Carol A; Pyles, John A; Kass, Robert E; Tarr, Michael J

2017-06-01

Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150-250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150-250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces.

Spatio-Temporal Analysis of Forest Fire Risk and Danger Using LANDSAT Imagery.

PubMed

Saglam, Bülent; Bilgili, Ertugrul; Dincdurmaz, Bahar; Kadiogulari, Ali Ihsan; Kücük, Ömer

2008-06-20

Computing fire danger and fire risk on a spatio-temporal scale is of crucial importance in fire management planning, and in the simulation of fire growth and development across a landscape. However, due to the complex nature of forests, fire risk and danger potential maps are considered one of the most difficult thematic layers to build up. Remote sensing and digital terrain data have been introduced for efficient discrete classification of fire risk and fire danger potential. In this study, two time-series data of Landsat imagery were used for determining spatio-temporal change of fire risk and danger potential in Korudag forest planning unit in northwestern Turkey. The method comprised the following two steps: (1) creation of indices of the factors influencing fire risk and danger; (2) evaluation of spatio-temporal changes in fire risk and danger of given areas using remote sensing as a quick and inexpensive means and determining the pace of forest cover change. Fire risk and danger potential indices were based on species composition, stand crown closure, stand development stage, insolation, slope and, proximity of agricultural lands to forest and distance from settlement areas. Using the indices generated, fire risk and danger maps were produced for the years 1987 and 2000. Spatio-temporal analyses were then realized based on the maps produced. Results obtained from the study showed that the use of Landsat imagery provided a valuable characterization and mapping of vegetation structure and type with overall classification accuracy higher than 83%.

Spatiotemporal motion boundary detection and motion boundary velocity estimation for tracking moving objects with a moving camera: a level sets PDEs approach with concurrent camera motion compensation.

PubMed

Feghali, Rosario; Mitiche, Amar

2004-11-01

The purpose of this study is to investigate a method of tracking moving objects with a moving camera. This method estimates simultaneously the motion induced by camera movement. The problem is formulated as a Bayesian motion-based partitioning problem in the spatiotemporal domain of the image quence. An energy functional is derived from the Bayesian formulation. The Euler-Lagrange descent equations determine imultaneously an estimate of the image motion field induced by camera motion and an estimate of the spatiotemporal motion undary surface. The Euler-Lagrange equation corresponding to the surface is expressed as a level-set partial differential equation for topology independence and numerically stable implementation. The method can be initialized simply and can track multiple objects with nonsimultaneous motions. Velocities on motion boundaries can be estimated from geometrical properties of the motion boundary. Several examples of experimental verification are given using synthetic and real-image sequences.

Formulating qualitative features using interactive visualization for analysis of multivariate spatiotemporal data

NASA Astrophysics Data System (ADS)

Porter, M.; Hill, M. C.; Pierce, S. A.; Gil, Y.; Pennington, D. D.

2017-12-01

DiscoverWater is a web-based visualization tool developed to enable the visual representation of data, and thus, aid scientific and societal understanding of hydrologic systems. Open data sources are coalesced to, for example, illustrate the impacts on streamflow of irrigation withdrawals. Scientists and stakeholders are informed through synchronized time-series data plots that correlate multiple spatiotemporal datasets and an interactive time-evolving map that provides a spatial analytical context. Together, these components elucidate trends so that the user can try to envision the relations between groundwater-surface water interactions, the impacts of pumping on these interactions, and the interplay of climate. Aligning data in this manner has the capacity for interdisciplinary knowledge discovery and motivates dialogue about system processes that we seek to enhance through qualitative features informed through quantitative models. DiscoverWater and its connection is demonstrated using two field cases. First, it is used to visualize data sets from the High Plains aquifer, where reservoir- and groundwater-supported irrigation has affected the Arkansas River in western Kansas. Second, data and model results from Barton Springs segment of the Edwards aquifer in Texas reveal the effects of regional pumping on this important urbanizing aquifer system. Identifying what is interesting about the data and the modeled system in the two different case studies is a step towards moving typically static visualization capabilities to an adaptive framework. Additionally, the dashboard interface incorporates both quantitative and qualitative information about distinctive case studies in a machine-readable form, such that a catalog of qualitative models can capture subject matter expertise alongside associated datasets. As the catalog is expanded to include other case studies, the collection has potential to establish a standard framework able to inform intelligent system

Improved kinect-based spatiotemporal and kinematic treadmill gait assessment.

PubMed

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.

A LANGUAGE FOR MODULAR SPATIO-TEMPORAL SIMULATION (R824766)

EPA Science Inventory

Creating an effective environment for collaborative spatio-temporal model development will require computational systems that provide support for the user in three key areas: (1) Support for modular, hierarchical model construction and archiving/linking of simulation modules; (2)...

The role of spatiotemporal and spectral cues in segregating short sound events: evidence from auditory Ternus display.

PubMed

Wang, Qingcui; Bao, Ming; Chen, Lihan

2014-01-01

Previous studies using auditory sequences with rapid repetition of tones revealed that spatiotemporal cues and spectral cues are important cues used to fuse or segregate sound streams. However, the perceptual grouping was partially driven by the cognitive processing of the periodicity cues of the long sequence. Here, we investigate whether perceptual groupings (spatiotemporal grouping vs. frequency grouping) could also be applicable to short auditory sequences, where auditory perceptual organization is mainly subserved by lower levels of perceptual processing. To find the answer to that question, we conducted two experiments using an auditory Ternus display. The display was composed of three speakers (A, B and C), with each speaker consecutively emitting one sound consisting of two frames (AB and BC). Experiment 1 manipulated both spatial and temporal factors. We implemented three 'within-frame intervals' (WFIs, or intervals between A and B, and between B and C), seven 'inter-frame intervals' (IFIs, or intervals between AB and BC) and two different speaker layouts (inter-distance of speakers: near or far). Experiment 2 manipulated the differentiations of frequencies between two auditory frames, in addition to the spatiotemporal cues as in Experiment 1. Listeners were required to make two alternative forced choices (2AFC) to report the perception of a given Ternus display: element motion (auditory apparent motion from sound A to B to C) or group motion (auditory apparent motion from sound 'AB' to 'BC'). The results indicate that the perceptual grouping of short auditory sequences (materialized by the perceptual decisions of the auditory Ternus display) was modulated by temporal and spectral cues, with the latter contributing more to segregating auditory events. Spatial layout plays a less role in perceptual organization. These results could be accounted for by the 'peripheral channeling' theory.

Spatiotemporal alignment of in utero BOLD-MRI series.

PubMed

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 < 0.01) and volume overlap and distance between region boundaries measures were significantly improved (P < 0.01). The proposed approach to align MRI time series enables more accurate 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.

A semiparametric spatio-temporal model for solar irradiance data

DOE PAGES

Patrick, Joshua D.; Harvill, Jane L.; Hansen, Clifford W.

2016-03-01

Here, we evaluate semiparametric spatio-temporal models for global horizontal irradiance at high spatial and temporal resolution. These models represent the spatial domain as a lattice and are capable of predicting irradiance at lattice points, given data measured at other lattice points. Using data from a 1.2 MW PV plant located in Lanai, Hawaii, we show that a semiparametric model can be more accurate than simple interpolation between sensor locations. We investigate spatio-temporal models with separable and nonseparable covariance structures and find no evidence to support assuming a separable covariance structure. These results indicate a promising approach for modeling irradiance atmore » high spatial resolution consistent with available ground-based measurements. Moreover, this kind of modeling may find application in design, valuation, and operation of fleets of utility-scale photovoltaic power systems.« less

Spatiotemporal Dynamics of Scrub Typhus Transmission in Mainland China, 2006-2014

PubMed Central

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

2016-01-01

Background 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. Objective 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. Method 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. Results 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. Conclusions 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. PMID:27479297

Spatiotemporal Dynamics of Scrub Typhus Transmission in Mainland China, 2006-2014.

PubMed

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.

Spatiotemporal modelling and mapping of the bubonic plague epidemic in India.

PubMed

Yu, Hwa-Lung; Christakos, George

2006-03-17

This work studies the spatiotemporal evolution of bubonic plague in India during 1896-1906 using stochastic concepts and geographical information science techniques. In the past, most investigations focused on selected cities to conduct different kinds of studies, such as the ecology of rats. No detailed maps existed incorporating the space-time dependence structure and uncertainty sources of the epidemic system and providing a composite space-time picture of the disease propagation characteristics. Informative spatiotemporal maps were generated that represented mortality rates and geographical spread of the disease, and epidemic indicator plots were derived that offered meaningful characterizations of the spatiotemporal disease distribution. The bubonic plague in India exhibited strong seasonal and geographical features. During its entire duration, the plague continued to invade new geographical areas, while it followed a re-emergence pattern at many localities; its rate changed significantly during each year and the mortality distribution exhibited space-time heterogeneous patterns; prevalence usually occurred in the autumn and spring, whereas the plague stopped moving towards new locations during the summers. Modern stochastic modelling and geographical information science provide powerful means to study the spatiotemporal distribution of the bubonic plague epidemic under conditions of uncertainty and multi-sourced databases; to account for various forms of interdisciplinary knowledge; and to generate informative space-time maps of mortality rates and propagation patterns. To the best of our knowledge, this kind of plague maps and plots become available for the first time, thus providing novel perspectives concerning the distribution and space-time propagation of the deadly epidemic. Furthermore, systematic maps and indicator plots make possible the comparison of the spatial-temporal propagation patterns of different diseases.

Spatiotemporal modelling and mapping of the bubonic plague epidemic in India

PubMed Central

Yu, Hwa-Lung; Christakos, George

2006-01-01

Background This work studies the spatiotemporal evolution of bubonic plague in India during 1896–1906 using stochastic concepts and geographical information science techniques. In the past, most investigations focused on selected cities to conduct different kinds of studies, such as the ecology of rats. No detailed maps existed incorporating the space-time dependence structure and uncertainty sources of the epidemic system and providing a composite space-time picture of the disease propagation characteristics. Results Informative spatiotemporal maps were generated that represented mortality rates and geographical spread of the disease, and epidemic indicator plots were derived that offered meaningful characterizations of the spatiotemporal disease distribution. The bubonic plague in India exhibited strong seasonal and geographical features. During its entire duration, the plague continued to invade new geographical areas, while it followed a re-emergence pattern at many localities; its rate changed significantly during each year and the mortality distribution exhibited space-time heterogeneous patterns; prevalence usually occurred in the autumn and spring, whereas the plague stopped moving towards new locations during the summers. Conclusion Modern stochastic modelling and geographical information science provide powerful means to study the spatiotemporal distribution of the bubonic plague epidemic under conditions of uncertainty and multi-sourced databases; to account for various forms of interdisciplinary knowledge; and to generate informative space-time maps of mortality rates and propagation patterns. To the best of our knowledge, this kind of plague maps and plots become available for the first time, thus providing novel perspectives concerning the distribution and space-time propagation of the deadly epidemic. Furthermore, systematic maps and indicator plots make possible the comparison of the spatial-temporal propagation patterns of different diseases

Decoding-Accuracy-Based Sequential Dimensionality Reduction of Spatio-Temporal Neural Activities

NASA Astrophysics Data System (ADS)

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

Performance of a brain machine interface (BMI) critically depends on selection of input data because information embedded in the neural activities is highly redundant. In addition, properly selected input data with a reduced dimension leads to improvement of decoding generalization ability and decrease of computational efforts, both of which are significant advantages for the clinical applications. In the present paper, we propose an algorithm of sequential dimensionality reduction (SDR) that effectively extracts motor/sensory related spatio-temporal neural activities. The algorithm gradually reduces input data dimension by dropping neural data spatio-temporally so as not to undermine the decoding accuracy as far as possible. Support vector machine (SVM) was used as the decoder, and tone-induced neural activities in rat auditory cortices were decoded into the test tone frequencies. SDR reduced the input data dimension to a quarter and significantly improved the accuracy of decoding of novel data. Moreover, spatio-temporal neural activity patterns selected by SDR resulted in significantly higher accuracy than high spike rate patterns or conventionally used spatial patterns. These results suggest that the proposed algorithm can improve the generalization ability and decrease the computational effort of decoding.

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

NASA Technical Reports Server (NTRS)

Kuo, Kwo-Sen; Rilee, Michael Lee

2017-01-01

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

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

NASA Astrophysics Data System (ADS)

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

Spatio-temporal distribution and natural variation of metabolites in citrus fruits.

PubMed

Wang, Shouchuang; Tu, Hong; Wan, Jian; Chen, Wei; Liu, Xianqing; Luo, Jie; Xu, Juan; Zhang, Hongyan

2016-05-15

To study the natural variation and spatio-temporal accumulation of citrus metabolites, liquid chromatography tandem mass spectrometry (LC-MS) based metabolome analysis was performed on four fruit tissues (flavedo, albedo, segment membrane and juice sacs) and different Citrus species (lemon, pummelo and grapefruit, sweet orange and mandarin). Using a non-targeted metabolomics approach, more than 2000 metabolite signals were detected, from which more than 54 metabolites, including amino acids, flavonoids and limonoids, were identified/annotated. Differential accumulation patterns of both primary metabolites and secondary metabolites in various tissues and species were revealed by our study. Further investigation indicated that flavedo accumulates more flavonoids while juice sacs contain more amino acids. Besides this, cluster analysis based on the levels of metabolites detected in 47 individual Citrus accessions clearly grouped them into four distinct clusters: pummelos and grapefruits, lemons, sweet oranges and mandarins, while the cluster of pummelos and grapefruits lay distinctly apart from the other three species. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatio-temporal hierarchy in the dynamics of a minimalist protein model

NASA Astrophysics Data System (ADS)

Matsunaga, Yasuhiro; Baba, Akinori; Li, Chun-Biu; Straub, John E.; Toda, Mikito; Komatsuzaki, Tamiki; Berry, R. Stephen

2013-12-01

A method for time series analysis of molecular dynamics simulation of a protein is presented. In this approach, wavelet analysis and principal component analysis are combined to decompose the spatio-temporal protein dynamics into contributions from a hierarchy of different time and space scales. Unlike the conventional Fourier-based approaches, the time-localized wavelet basis captures the vibrational energy transfers among the collective motions of proteins. As an illustrative vehicle, we have applied our method to a coarse-grained minimalist protein model. During the folding and unfolding transitions of the protein, vibrational energy transfers between the fast and slow time scales were observed among the large-amplitude collective coordinates while the other small-amplitude motions are regarded as thermal noise. Analysis employing a Gaussian-based measure revealed that the time scales of the energy redistribution in the subspace spanned by such large-amplitude collective coordinates are slow compared to the other small-amplitude coordinates. Future prospects of the method are discussed in detail.

Adjoint sensitivity analysis of a tumor growth model and its application to spatiotemporal radiotherapy optimization.

PubMed

Fujarewicz, Krzysztof; Lakomiec, Krzysztof

2016-12-01

We investigate a spatial model of growth of a tumor and its sensitivity to radiotherapy. It is assumed that the radiation dose may vary in time and space, like in intensity modulated radiotherapy (IMRT). The change of the final state of the tumor depends on local differences in the radiation dose and varies with the time and the place of these local changes. This leads to the concept of a tumor's spatiotemporal sensitivity to radiation, which is a function of time and space. We show how adjoint sensitivity analysis may be applied to calculate the spatiotemporal sensitivity of the finite difference scheme resulting from the partial differential equation describing the tumor growth. We demonstrate results of this approach to the tumor proliferation, invasion and response to radiotherapy (PIRT) model and we compare the accuracy and the computational effort of the method to the simple forward finite difference sensitivity analysis. Furthermore, we use the spatiotemporal sensitivity during the gradient-based optimization of the spatiotemporal radiation protocol and present results for different parameters of the model.

Activity induces traveling waves, vortices and spatiotemporal chaos in a model actomyosin layer

NASA Astrophysics Data System (ADS)

Ramaswamy, Rajesh; Jülicher, Frank

2016-02-01

Inspired by the actomyosin cortex in biological cells, we investigate the spatiotemporal dynamics of a model describing a contractile active polar fluid sandwiched between two external media. The external media impose frictional forces at the interface with the active fluid. The fluid is driven by a spatially-homogeneous activity measuring the strength of the active stress that is generated by processes consuming a chemical fuel. We observe that as the activity is increased over two orders of magnitude the active polar fluid first shows spontaneous flow transition followed by transition to oscillatory dynamics with traveling waves and traveling vortices in the flow field. In the flow-tumbling regime, the active polar fluid also shows transition to spatiotemporal chaos at sufficiently large activities. These results demonstrate that level of activity alone can be used to tune the operating point of actomyosin layers with qualitatively different spatiotemporal dynamics.

Preschoolers' use of spatiotemporal history, appearance, and proper name in determining individual identity.

PubMed

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

NASA Astrophysics Data System (ADS)

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

Meteor tracking via local pattern clustering in spatio-temporal domain

NASA Astrophysics Data System (ADS)

Kukal, Jaromír.; Klimt, Martin; Švihlík, Jan; Fliegel, Karel

2016-09-01

Reliable meteor detection is one of the crucial disciplines in astronomy. A variety of imaging systems is used for meteor path reconstruction. The traditional approach is based on analysis of 2D image sequences obtained from a double station video observation system. Precise localization of meteor path is difficult due to atmospheric turbulence and other factors causing spatio-temporal fluctuations of the image background. The proposed technique performs non-linear preprocessing of image intensity using Box-Cox transform as recommended in our previous work. Both symmetric and asymmetric spatio-temporal differences are designed to be robust in the statistical sense. Resulting local patterns are processed by data whitening technique and obtained vectors are classified via cluster analysis and Self-Organized Map (SOM).

Spatio-Temporal Process Simulation of Dam-Break Flood Based on SPH

NASA Astrophysics Data System (ADS)

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.

Finding Spatio-Temporal Patterns in Large Sensor Datasets

ERIC Educational Resources Information Center

McGuire, Michael Patrick

2010-01-01

Spatial or temporal data mining tasks are performed in the context of the relevant space, defined by a spatial neighborhood, and the relevant time period, defined by a specific time interval. Furthermore, when mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. This dissertation is…

Spatiotemporal Interpolation Methods for Solar Event Trajectories

NASA Astrophysics Data System (ADS)

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.

Mapping and spatiotemporal analysis tool for hydrological data: Spellmap

USDA-ARS?s Scientific Manuscript database

Lack of data management and analyses tools is one of the major limitations to effectively evaluate and use large datasets of high-resolution atmospheric, surface, and subsurface observations. High spatial and temporal resolution datasets better represent the spatiotemporal variability of hydrologica...

Spatiotemporal Thinking in the Geosciences

NASA Astrophysics Data System (ADS)

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.

A spatiotemporally controllable chemical gradient generator via acoustically oscillating sharp-edge structures.

PubMed

Huang, Po-Hsun; Chan, Chung Yu; Li, Peng; Nama, Nitesh; Xie, Yuliang; Wei, Cheng-Hsin; Chen, Yuchao; Ahmed, Daniel; Huang, Tony Jun

2015-11-07

The ability to generate stable, spatiotemporally controllable concentration gradients is critical for resolving the dynamics of cellular response to a chemical microenvironment. Here we demonstrate an acoustofluidic gradient generator based on acoustically oscillating sharp-edge structures, which facilitates in a step-wise fashion the rapid mixing of fluids to generate tunable, dynamic chemical gradients. By controlling the driving voltage of a piezoelectric transducer, we demonstrated that the chemical gradient profiles can be conveniently altered (spatially controllable). By adjusting the actuation time of the piezoelectric transducer, moreover, we generated pulsatile chemical gradients (temporally controllable). With these two characteristics combined, we have developed a spatiotemporally controllable gradient generator. The applicability and biocompatibility of our acoustofluidic gradient generator are validated by demonstrating the migration of human dermal microvascular endothelial cells (HMVEC-d) in response to a generated vascular endothelial growth factor (VEGF) gradient, and by preserving the viability of HMVEC-d cells after long-term exposure to an acoustic field. Our device features advantages such as simple fabrication and operation, compact and biocompatible device, and generation of spatiotemporally tunable gradients.

A method to estimate spatiotemporal air quality in an urban traffic corridor.

PubMed

Singh, Nongthombam Premananda; Gokhale, Sharad

2015-12-15

Air quality exposure assessment using personal exposure sampling or direct measurement of spatiotemporal air pollutant concentrations has difficulty and limitations. Most statistical methods used for estimating spatiotemporal air quality do not account for the source characteristics (e.g. emissions). In this study, a prediction method, based on the lognormal probability distribution of hourly-average-spatial concentrations of carbon monoxide (CO) obtained by a CALINE4 model, has been developed and validated in an urban traffic corridor. The data on CO concentrations were collected at three locations and traffic and meteorology within the urban traffic corridor.(1) The method has been developed with the data of one location and validated at other two locations. The method estimated the CO concentrations reasonably well (correlation coefficient, r≥0.96). Later, the method has been applied to estimate the probability of occurrence [P(C≥Cstd] of the spatial CO concentrations in the corridor. The results have been promising and, therefore, may be useful to quantifying spatiotemporal air quality within an urban area. Copyright © 2015 Elsevier B.V. All rights reserved.

Assessing global vegetation activity using spatio-temporal Bayesian modelling

NASA Astrophysics Data System (ADS)

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

Do spatiotemporal parameters and gait variability differ across the lifespan of healthy adults? A systematic review.

PubMed

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 Change Modeling of Lulc: a Semantic Kriging Approach

NASA Astrophysics Data System (ADS)

Bhattacharjee, S.; Ghosh, S. K.

2015-07-01

Spatio-temporal land-use/ land-cover (LULC) change modeling is important to forecast the future LULC distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal change in LULC trend often exhibits non-linear behavior, due to various dynamic factors, such as, human intervention (e.g., urbanization), environmental factors, etc. Hence, proper forecasting of LULC distribution should involve the study and trend modeling of historical data. Existing literatures have reported that the meteorological attributes (e.g., NDVI, LST, MSI), are semantically related to the terrain. Being influenced by the terrestrial dynamics, the temporal changes of these attributes depend on the LULC properties. Hence, incorporating meteorological knowledge into the temporal prediction process may help in developing an accurate forecasting model. This work attempts to study the change in inter-annual LULC pattern and the distribution of different meteorological attributes of a region in Kolkata (a metropolitan city in India) during the years 2000-2010 and forecast the future spread of LULC using semantic kriging (SemK) approach. A new variant of time-series SemK is proposed, namely Rev-SemKts to capture the multivariate semantic associations between different attributes. From empirical analysis, it may be observed that the augmentation of semantic knowledge in spatio-temporal modeling of meteorological attributes facilitate more precise forecasting of LULC pattern.

[Spatiotemporal changes of wetlands in Hangzhou Bay Industrial Belt].

PubMed

Lu, Zhang-Wei; Wu, Ci-Fang; Yue, Wen-Ze; Liu, Yong; Ren, Li-Yan

2009-07-01

By using RS and GIS techniques, the spatiotemporal changes of wetlands in Hangzhou Bay Industrial Belt, one of the most developed zones in Zhejiang Province, from 1990 to 2005 were studied. There was a frequent conversion between the wetlands and other land use types and between the wetlands themselves, mainly manifested in the conversion between wetland and farmland, and from wetland to construction land and from tidal flat to aquiculture area. The comparative advantage of other land use types and the policy of cultivated land's requisition-compensation balance decided the inherent mechanisms of these spatiotemporal changes. Driven by the aquaculture's comparative advantage to traditional agriculture, large areas of inland farmland and of the tidal flat along the coast of Hangzhou Bay were reclaimed into aquiculture area, and the rapid expansion of construction land, limited land resources, and the implement of cultivated land's requisition-compensation balance policy induced the wetlands being occupied.

A general science-based framework for dynamical spatio-temporal models

USGS Publications Warehouse

Wikle, C.K.; Hooten, M.B.

2010-01-01

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic

Leaders and followers: quantifying consistency in spatio-temporal propagation patterns

NASA Astrophysics Data System (ADS)

Kreuz, Thomas; Satuvuori, Eero; Pofahl, Martin; Mulansky, Mario

2017-04-01

Repetitive spatio-temporal propagation patterns are encountered in fields as wide-ranging as climatology, social communication and network science. In neuroscience, perfectly consistent repetitions of the same global propagation pattern are called a synfire pattern. For any recording of sequences of discrete events (in neuroscience terminology: sets of spike trains) the questions arise how closely it resembles such a synfire pattern and which are the spike trains that lead/follow. Here we address these questions and introduce an algorithm built on two new indicators, termed SPIKE-order and spike train order, that define the synfire indicator value, which allows to sort multiple spike trains from leader to follower and to quantify the consistency of the temporal leader-follower relationships for both the original and the optimized sorting. We demonstrate our new approach using artificially generated datasets before we apply it to analyze the consistency of propagation patterns in two real datasets from neuroscience (giant depolarized potentials in mice slices) and climatology (El Niño sea surface temperature recordings). The new algorithm is distinguished by conceptual and practical simplicity, low computational cost, as well as flexibility and universality.

Distinct spatio-temporal profiles of beta-oscillations within visual and sensorimotor areas during action recognition as revealed by MEG.

PubMed

Pavlidou, Anastasia; Schnitzler, Alfons; Lange, Joachim

2014-05-01

The neural correlates of action recognition have been widely studied in visual and sensorimotor areas of the human brain. However, the role of neuronal oscillations involved during the process of action recognition remains unclear. Here, we were interested in how the plausibility of an action modulates neuronal oscillations in visual and sensorimotor areas. Subjects viewed point-light displays (PLDs) of biomechanically plausible and implausible versions of the same actions. Using magnetoencephalography (MEG), we examined dynamic changes of oscillatory activity during these action recognition processes. While both actions elicited oscillatory activity in visual and sensorimotor areas in several frequency bands, a significant difference was confined to the beta-band (∼20 Hz). An increase of power for plausible actions was observed in left temporal, parieto-occipital and sensorimotor areas of the brain, in the beta-band in successive order between 1650 and 2650 msec. These distinct spatio-temporal beta-band profiles suggest that the action recognition process is modulated by the degree of biomechanical plausibility of the action, and that spectral power in the beta-band may provide a functional interaction between visual and sensorimotor areas in humans. Copyright © 2014 Elsevier Ltd. All rights reserved.

Impaired heel to toe progression during gait is related to reduced ankle range of motion in people with Multiple Sclerosis.

PubMed

Psarakis, Michael; Greene, David; Moresi, Mark; Baker, Michael; Stubbs, Peter; Brodie, Matthew; Lord, Stephen; Hoang, Phu

2017-11-01

Gait impairment in people with Multiple Sclerosis results from neurological impairment, muscle weakness and reduced range of motion. Restrictions in passive ankle range of motion can result in abnormal heel-to-toe progression (weight transfer) and inefficient gait patterns in people with Multiple Sclerosis. The purpose of this study was to determine the associations between gait impairment, heel-to-toe progression and ankle range of motion in people with Multiple Sclerosis. Twelve participants with Multiple Sclerosis and twelve healthy age-matched participants were assessed. Spatiotemporal parameters of gait and individual footprint data were used to investigate group differences. A pressure sensitive walkway was used to divide each footprint into three phases (contact, mid-stance, propulsive) and calculate the heel-to-toe progression during the stance phase of gait. Compared to healthy controls, people with Multiple Sclerosis spent relatively less time in contact phase (7.8% vs 25.1%) and more time in the mid stance phase of gait (57.3% vs 33.7%). Inter-limb differences were observed in people with Multiple Sclerosis between the affected and non-affected sides for contact (7.8% vs 15.3%) and mid stance (57.3% and 47.1%) phases. Differences in heel-to-toe progression remained significant after adjusting for walking speed and were correlated with walking distance and ankle range of motion. Impaired heel-to-toe progression was related to poor ankle range of motion in people with Multiple Sclerosis. Heel-to-toe progression provided a sensitive measure for assessing gait impairments that were not detectable using standard spatiotemporal gait parameters. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatiotemporal throughfall patterns beneath an urban tree row

NASA Astrophysics Data System (ADS)

Bogeholz, P.; Van Stan, J. T., II; Hildebrandt, A.; Friesen, J.; Dibble, M.; Norman, Z.

2016-12-01

Much recent research has focused on throughfall patterns in natural forests as they can influence the heterogeneity of surface ecohydrological and biogeochemical processes. However, to the knowledge of the authors, no work has assessed how urban forest structures affect the spatiotemporal variability of throughfall water flux. Urbanization greatly alters not only a significant portion of the land surface, but canopy structure, with the most typical urban forest configuration being landscaped tree rows along streets, swales, parking lot medians, etc. This study examines throughfall spatiotemporal patterns for a landscaped tree row of Pinus elliottii (Engelm., slash pine) on Georgia Southern University's campus (southeastern, USA) using 150 individual observations per storm. Throughfall correlation lengths beneath this tree row were similar to, but appeared to be more stable across storm size than, observations in past studies on natural forests. Individual tree overlap and the planting interval also may more strongly drive throughfall patterns in tree rows. Meteorological influences beyond storm magnitude (intensity, intermittency, wind conditions, and atmospheric moisture demand) are also examined.

Spatiotemporal matrix image formation for programmable ultrasound scanners

NASA Astrophysics Data System (ADS)

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.

Weight Status in Persons with Multiple Sclerosis: Implications for Mobility Outcomes

PubMed Central

Pilutti, Lara A.; Dlugonski, Deirdre; Pula, John H.; Motl, Robert W.

2012-01-01

The accumulation of excess body weight may have important health and disease consequences for persons with multiple sclerosis (MS). This study examined the effect of weight status on mobility using a comprehensive set of mobility outcomes including ambulatory performance (timed 25-foot walk, T25FW; 6-minute walk, 6MW; oxygen cost of walking, Cw; spatiotemporal parameters of gait; self-reported walking impairment, Multiple Sclerosis Walking Scale-12 (MSWS-12); and free-living activity, accelerometry) in 168 ambulatory persons with MS. Mean (SD) BMI was 27.7 (5.1) kg/m2. Of the 168 participants, 31.0% were classified as normal weight (BMI = 18.5–24.9 kg/m2), 36.3% were classified as overweight (BMI = 25.0–29.9 kg/m2), and 32.7% were classified as obese, classes I and II (BMI = 30–39.9 kg/m2). There were no significant differences among BMI groups on T25FW and 6MW, Cw, spatiotemporal gait parameters, MSWS-12, or daily step and movement counts. The prevalence of overweight and obesity in this sample was almost 70%, but there was not a consistent nor significant impact of BMI on outcomes of mobility. The lack of an effect of weight status on mobility emphasizes the need to focus on and identify other factors which may be important targets of ambulatory performance in persons with MS. PMID:23050129

Weight status in persons with multiple sclerosis: implications for mobility outcomes.

PubMed

Pilutti, Lara A; Dlugonski, Deirdre; Pula, John H; Motl, Robert W

2012-01-01

The accumulation of excess body weight may have important health and disease consequences for persons with multiple sclerosis (MS). This study examined the effect of weight status on mobility using a comprehensive set of mobility outcomes including ambulatory performance (timed 25-foot walk, T25FW; 6-minute walk, 6MW; oxygen cost of walking, C(w); spatiotemporal parameters of gait; self-reported walking impairment, Multiple Sclerosis Walking Scale-12 (MSWS-12); and free-living activity, accelerometry) in 168 ambulatory persons with MS. Mean (SD) BMI was 27.7 (5.1) kg/m(2). Of the 168 participants, 31.0% were classified as normal weight (BMI = 18.5-24.9 kg/m(2)), 36.3% were classified as overweight (BMI = 25.0-29.9 kg/m(2)), and 32.7% were classified as obese, classes I and II (BMI = 30-39.9 kg/m(2)). There were no significant differences among BMI groups on T25FW and 6MW, C(w), spatiotemporal gait parameters, MSWS-12, or daily step and movement counts. The prevalence of overweight and obesity in this sample was almost 70%, but there was not a consistent nor significant impact of BMI on outcomes of mobility. The lack of an effect of weight status on mobility emphasizes the need to focus on and identify other factors which may be important targets of ambulatory performance in persons with MS.

Separability of spatiotemporal spectra of image sequences. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Eckert, Michael P.; Buchsbaum, Gershon; Watson, Andrew B.

1992-01-01

The spatiotemporal power spectrum was calculated of 14 image sequences in order to determine the degree to which the spectra are separable in space and time, and to assess the validity of the commonly used exponential correlation model found in the literature. The spectrum was expanded by a Singular Value Decomposition into a sum of separable terms and an index was defined of spatiotemporal separability as the fraction of the signal energy that can be represented by the first (largest) separable term. All spectra were found to be highly separable with an index of separability above 0.98. The power spectra of the sequences were well fit by a separable model. The power spectrum model corresponds to a product of exponential autocorrelation functions separable in space and time.

Kalman filter control of a model of spatiotemporal cortical dynamics

PubMed Central

Schiff, Steven J; Sauer, Tim

2007-01-01

Recent advances in Kalman filtering to estimate system state and parameters in nonlinear systems have offered the potential to apply such approaches to spatiotemporal nonlinear systems. We here adapt the nonlinear method of unscented Kalman filtering to observe the state and estimate parameters in a computational spatiotemporal excitable system that serves as a model for cerebral cortex. We demonstrate the ability to track spiral wave dynamics, and to use an observer system to calculate control signals delivered through applied electrical fields. We demonstrate how this strategy can control the frequency of such a system, or quench the wave patterns, while minimizing the energy required for such results. These findings are readily testable in experimental applications, and have the potential to be applied to the treatment of human disease. PMID:18310806

Spatiotemporal characterization of Sclerotinia crown rot epidemics in pyrethrum

USDA-ARS?s Scientific Manuscript database

Sclerotinia crown rot, caused by Sclerotinia minor and S. sclerotiorum is a disease of pyrethrum in Australia that may cause substantial decline in plant density. The spatiotemporal characteristics of the disease were quantified in 14 fields spread across three growing seasons. Fitting the binary ...

Spatiotemporal patterns, annual baseline and movement-related incidence of Streptococcus agalactiae infection in Danish dairy herds: 2000-2009.

PubMed

Mweu, Marshal M; Nielsen, Søren S; Halasa, Tariq; Toft, Nils

2014-02-01

Several decades after the inception of the five-point plan for the control of contagious mastitis pathogens, Streptococcus agalactiae (S. agalactiae) persists as a fundamental threat to the dairy industry in many countries. A better understanding of the relative importance of within- and between-herd sources of new herd infections coupled with the spatiotemporal distribution of the infection, may aid in effective targeting of control efforts. Thus, the objectives of this study were: (1) to describe the spatiotemporal patterns of infection with S. agalactiae in the population of Danish dairy herds from 2000 to 2009 and (2) to estimate the annual herd-level baseline and movement-related incidence risks of S. agalactiae infection over the 10-year period. The analysis involved registry data on bacteriological culture of all bulk tank milk samples collected as part of the mandatory Danish S. agalactiae surveillance scheme as well as live cattle movements into dairy herds during the specified 10-year period. The results indicated that the predicted risk of a herd becoming infected with S. agalactiae varied spatiotemporally; the risk being more homogeneous and higher in the period after 2005. Additionally, the annual baseline risks yielded significant yet distinctive patterns before and after 2005 - the risk of infection being higher in the latter phase. On the contrary, the annual movement-related risks revealed a non-significant pattern over the 10-year period. There was neither evidence for spatial clustering of cases relative to the population of herds at risk nor spatial dependency between herds. Nevertheless, the results signal a need to beef up within-herd biosecurity in order to reduce the risk of new herd infections. Copyright © 2013 Elsevier B.V. All rights reserved.

Spatio-temporal manipulation of small GTPase activity at subcellular level and on timescale of seconds in living cells.

PubMed

DeRose, Robert; Pohlmeyer, Christopher; Umeda, Nobuhiro; Ueno, Tasuku; Nagano, Tetsuo; Kuo, Scot; Inoue, Takanari

2012-03-09

Dynamic regulation of the Rho family of small guanosine triphosphatases (GTPases) with great spatiotemporal precision is essential for various cellular functions and events(1, 2). Their spatiotemporally dynamic nature has been revealed by visualization of their activity and localization in real time(3). In order to gain deeper understanding of their roles in diverse cellular functions at the molecular level, the next step should be perturbation of protein activities at a precise subcellular location and timing. To achieve this goal, we have developed a method for light-induced, spatio-temporally controlled activation of small GTPases by combining two techniques: (1) rapamycin-induced FKBP-FRB heterodimerization and (2) a photo-caging method of rapamycin. With the use of rapamycin-mediated FKBP-FRB heterodimerization, we have developed a method for rapidly inducible activation or inactivation of small GTPases including Rac(4), Cdc42(4), RhoA(4) and Ras(5), in which rapamycin induces translocation of FKBP-fused GTPases, or their activators, to the plasma membrane where FRB is anchored. For coupling with this heterodimerization system, we have also developed a photo-caging system of rapamycin analogs. A photo-caged compound is a small molecule whose activity is suppressed with a photocleavable protecting group known as a caging group. To suppress heterodimerization activity completely, we designed a caged rapamycin that is tethered to a macromolecule such that the resulting large complex cannot cross the plasma membrane, leading to virtually no background activity as a chemical dimerizer inside cells(6). Figure 1 illustrates a scheme of our system. With the combination of these two systems, we locally recruited a Rac activator to the plasma membrane on a timescale of seconds and achieved light-induced Rac activation at the subcellular level(6).

a New Process-Oriented and Spatiotemporal Data Model for GIS Data

NASA Astrophysics Data System (ADS)

Shen, Y.

2018-04-01

With the rapid development of wireless sensor and information technology, there is a trend of transition from "digital monitoring" to "intelligence monitoring" advancing process. The traditional model cannot completely match the dynamic data to accurately describe changes of geographical and environmental changes. In this paper, we try to build a process-oriented and real-time spatiotemporal data model to meet the demands. With various types of monitoring devices, detection methods and the utilization of new technologies, the model can simulate the possible waterlog area in a specific year by analyzing the given data. By testing and modifying the spatiotemporal model, we can come to a rational conclusion that our model can forecast the actual situation in certain extent.

Spatio-temporal distribution of soil-transmitted helminth infections in Brazil.

PubMed

Chammartin, Frédérique; Guimarães, Luiz H; Scholte, Ronaldo Gc; Bavia, Mara E; Utzinger, Jürg; Vounatsou, Penelope

2014-09-18

In Brazil, preventive chemotherapy targeting soil-transmitted helminthiasis is being scaled-up. Hence, spatially explicit estimates of infection risks providing information about the current situation are needed to guide interventions. Available high-resolution national model-based estimates either rely on analyses of data restricted to a given period of time, or on historical data collected over a longer period. While efforts have been made to take into account the spatial structure of the data in the modelling approach, little emphasis has been placed on the temporal dimension. We extracted georeferenced survey data on the prevalence of infection with soil-transmitted helminths (i.e. Ascaris lumbricoides, hookworm and Trichuris trichiura) in Brazil from the Global Neglected Tropical Diseases (GNTD) database. Selection of the most important predictors of infection risk was carried out using a Bayesian geostatistical approach and temporal models that address non-linearity and correlation of the explanatory variables. The spatial process was estimated through a predictive process approximation. Spatio-temporal models were built on the selected predictors with integrated nested Laplace approximation using stochastic partial differential equations. Our models revealed that, over the past 20 years, the risk of soil-transmitted helminth infection has decreased in Brazil, mainly because of the reduction of A. lumbricoides and hookworm infections. From 2010 onwards, we estimate that the infection prevalences with A. lumbricoides, hookworm and T. trichiura are 3.6%, 1.7% and 1.4%, respectively. We also provide a map highlighting municipalities in need of preventive chemotherapy, based on a predicted soil-transmitted helminth infection risk in excess of 20%. The need for treatments in the school-aged population at the municipality level was estimated at 1.8 million doses of anthelminthic tablets per year. The analysis of the spatio-temporal aspect of the risk of infection

Virtualized Traffic: reconstructing traffic flows from discrete spatiotemporal data.

PubMed

Sewall, Jason; van den Berg, Jur; Lin, Ming C; Manocha, Dinesh

2011-01-01

We present a novel concept, Virtualized Traffic, to reconstruct and visualize continuous traffic flows from discrete spatiotemporal data provided by traffic sensors or generated artificially to enhance a sense of immersion in a dynamic virtual world. Given the positions of each car at two recorded locations on a highway and the corresponding time instances, our approach can reconstruct the traffic flows (i.e., the dynamic motions of multiple cars over time) between the two locations along the highway for immersive visualization of virtual cities or other environments. Our algorithm is applicable to high-density traffic on highways with an arbitrary number of lanes and takes into account the geometric, kinematic, and dynamic constraints on the cars. Our method reconstructs the car motion that automatically minimizes the number of lane changes, respects safety distance to other cars, and computes the acceleration necessary to obtain a smooth traffic flow subject to the given constraints. Furthermore, our framework can process a continuous stream of input data in real time, enabling the users to view virtualized traffic events in a virtual world as they occur. We demonstrate our reconstruction technique with both synthetic and real-world input. © 2011 IEEE Published by the IEEE Computer Society

Propagating wave and irregular dynamics: Spatiotemporal patterns of cholinergic theta oscillations in neocortex, in vitro

PubMed Central

Bao, Weili; Wu, Jian-young

2010-01-01

Neocortical “theta” oscillation (5- 12 Hz) has been observed in animals and human subjects but little is known about how the oscillation is organized in the cortical intrinsic networks. Here we use voltage-sensitive dye and optical imaging to study a carbachol/bicuculline induced theta (~8 Hz) oscillation in rat neocortical slices. The imaging has large signal-to-noise ratio, allowing us to map the phase distribution over the neocortical tissue during the oscillation. The oscillation was organized as spontaneous epochs and each epoch was composed of a “first spike”, a “regular” period (with relatively stable frequency and amplitude) and an “irregular” period (with variable frequency and amplitude) of oscillations. During each cycle of the regular oscillation one wave of activation propagated horizontally (parallel to the cortical lamina) across the cortical section at a velocity of ~50 mm/sec. Vertically the activity was synchronized through all cortical layers. This pattern of one propagating wave associated with one oscillation cycle was seen during all the regular cycles. The oscillation frequency varied noticeably at two neighboring horizontal locations (330 μm apart), suggesting that the oscillation is locally organized and each local oscillator is about equal or less than 300 μm wide horizontally. During irregular oscillations the spatiotemporal patterns were complex and sometimes the vertical synchronization decomposed, suggesting a de-coupling among local oscillators. Our data suggested that neocortical theta oscillation is sustained by multiple local oscillators. The coupling regime among the oscillators may determine the spatiotemporal pattern and switching between propagating waves and irregular patterns. PMID:12612003

Tracking Local Spatiotemporal Microfracturing Processes and Stress Field Evolution Before and After Laboratory Fault Slip

NASA Astrophysics Data System (ADS)

Kwiatek, G.; Orlecka-Sikora, B.; Goebel, T.; Martínez-Garzón, P.; Dresen, G.; Bohnhoff, M.

2017-12-01

In this study we investigate details of spatial and temporal evolution of the stress field and damage at a pre-existing fault plane in laboratory stick-slip friction experiments performed on Westerly Granite sample. Specimen of 10 cm height and 4 cm diameter was deformed at a constant strain rate of 3×10-6 s-1 and confining pressure of 150 MPa. Here we analyze a series of 6 macroscopic slip events occurring on a rough fault during the course of experiment. Each macroscopic slip was associated with an intense femtoseismic acoustic emission (AE) activity recorded using a 16-channel transient recording system. To monitor the the spatiotemporal damage evolution, and unravel the micromechanical processes governing nucleation and propagation of slip events, we analyzed AE source characteristics (magnitude, seismic moment tensors, focal mechanisms), as well as the statistical properties (b-, c-, d- value) of femtoseismicity. In addition, the calculated AE focal mechanisms were used to reveal the spatiotemporal evolution of local stress field orientations and stress shape ratio coefficients over the fault plane, as well as additional parameters quantifying proximity to failure of individual fault patches. The calculated characteristics are used to comprehensively describe the complexity of the spatial and temporal evolution of the stress over the fault plane, and properties of the corresponding seismicity before and after the macroscopic slips. The observed faulting processes and characteristics are discussed in the context of global strain and stress changes, fault maturation, and earthquake stress drop.

Effects of climate change adaptation scenarios on perceived spatio-temporal characteristics of drought events

NASA Astrophysics Data System (ADS)

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

2012-04-01

Drought events develop in both space and time and they are therefore best described through summary joint spatio-temporal characteristics, like mean duration, mean affected area and total magnitude. This study 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 reproduce 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 under different emissions scenarios? (3) How would perceived drought characteristics evolve under 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-year multilevel and multiscale drought reanalysis over France (Vidal et al., 2010). Spatio-temporal characteristics of meteorological and agricultural drought events are computed using the Standardized Precipitation Index (SPI) and the Standardized Soil Wetness Index (SSWI), 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 reproduced 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 under all considered emissions scenarios, with stronger changes for agricultural droughts. Two theoretical adaptation scenarios are eventually built based on hypotheses of adaptation to evolving climate and hydrological normals. The two scenarios differ by the way the transient adaptation is performed for a given date in the future, with reference to the normals over either the previous 30-year window ("retrospective

Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach

PubMed Central

Yu, Zhaoyuan; Yuan, Linwang; Luo, Wen; Feng, Linyao; Lv, Guonian

2015-01-01

Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks. PMID:26729123

Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach.

PubMed

Yu, Zhaoyuan; Yuan, Linwang; Luo, Wen; Feng, Linyao; Lv, Guonian

2015-12-30

Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks.

Identifying food deserts and swamps based on relative healthy food access: a spatio-temporal Bayesian approach.

PubMed

Luan, Hui; Law, Jane; Quick, Matthew

2015-12-30

Obesity and other adverse health outcomes are influenced by individual- and neighbourhood-scale risk factors, including the food environment. At the small-area scale, past research has analysed spatial patterns of food environments for one time period, overlooking how food environments change over time. Further, past research has infrequently analysed relative healthy food access (RHFA), a measure that is more representative of food purchasing and consumption behaviours than absolute outlet density. This research applies a Bayesian hierarchical model to analyse the spatio-temporal patterns of RHFA in the Region of Waterloo, Canada, from 2011 to 2014 at the small-area level. RHFA is calculated as the proportion of healthy food outlets (healthy outlets/healthy + unhealthy outlets) within 4-km from each small-area. This model measures spatial autocorrelation of RHFA, temporal trend of RHFA for the study region, and spatio-temporal trends of RHFA for small-areas. For the study region, a significant decreasing trend in RHFA is observed (-0.024), suggesting that food swamps have become more prevalent during the study period. For small-areas, significant decreasing temporal trends in RHFA were observed for all small-areas. Specific small-areas located in south Waterloo, north Kitchener, and southeast Cambridge exhibited the steepest decreasing spatio-temporal trends and are classified as spatio-temporal food swamps. This research demonstrates a Bayesian spatio-temporal modelling approach to analyse RHFA at the small-area scale. Results suggest that food swamps are more prevalent than food deserts in the Region of Waterloo. Analysing spatio-temporal trends of RHFA improves understanding of local food environment, highlighting specific small-areas where policies should be targeted to increase RHFA and reduce risk factors of adverse health outcomes such as obesity.

Factors Related to Rape Reporting Behavior in Brazil: Examining the Role of Spatio-Temporal Factors.

PubMed

Melo, Silas Nogueira de; Beauregard, Eric; Andresen, Martin A

2016-07-01

The reporting of rape to police is an important component of this crime to have the criminal justice system involved and, potentially, punish offenders. However, for a number of reasons (fear of retribution, self-blame, etc.), most rapes are not reported to police. Most often, the research investigating this phenomenon considers incident and victim factors with little attention to the spatio-temporal factors of the rape. In this study, we consider incident, victim, and spatio-temporal factors relating to rape reporting in Campinas, Brazil. Our primary research question is whether or not the spatio-temporal factors play a significant role in the reporting of rape, over and above incident and victim factors. The subjects under study are women who were admitted to the Women's Integrated Healthcare Center at the State University of Campinas, Brazil, and surveyed by a psychologist or a social worker. Rape reporting to police was measured using a dichotomous variable. Logistic regression was used to predict the probability of rape reporting based on incident, victim, and spatio-temporal factors. Although we find that incident and victim factors matter for rape reporting, spatio-temporal factors (rape/home location and whether the rape was in a private or public place) play an important role in rape reporting, similar to the literature that considers these factors. This result has significant implications for sexual violence education. Only when we know why women decide not to report a rape may we begin to work on strategies to overcome these hurdles.

Spatiotemporal Coupling of the Tongue in Amyotrophic Lateral Sclerosis

ERIC Educational Resources Information Center

Kuruvilla, Mili S.; Green, Jordan R.; Yunusova, Yana; Hanford, Kathy

2012-01-01

Purpose: The primary aim of the investigation was to identify deficits in spatiotemporal coupling between tongue regions in amyotrophic lateral sclerosis (ALS). The relations between disease-related changes in tongue movement patterns and speech intelligibility were also determined. Methods: The authors recorded word productions from 11…

Spatiotemporal evolution of Calophaca (Fabaceae) reveals multiple dispersals in the Central Asian mountains and adjacent regions

Treesearch

Ming-Li Zhang; Zhi-Bin Wen; Peter W. Fritsch; Stewart C. Sanderson

2015-01-01

The Central Asian flora plays a significant role in Eurasia and the Northern Hemisphere. Calophaca, a member of this flora, includes eight currently recognized species, and is centered in Central Asia, with some taxa extending into adjacent areas. A phylogenetic analysis of the genus utilizing nuclear ribosomal ITS and plastid trnS-trnG and rbcL sequences was carried...

Spatiotemporal coupling of the tongue in amyotrophic lateral sclerosis.

PubMed

Kuruvilla, Mili S; Green, Jordan R; Yunusova, Yana; Hanford, Kathy

2012-12-01

The primary aim of the investigation was to identify deficits in spatiotemporal coupling between tongue regions in amyotrophic lateral sclerosis (ALS). The relations between disease-related changes in tongue movement patterns and speech intelligibility were also determined. Methods The authors recorded word productions from 11 individuals with ALS with mild, moderate, and severe dysarthria using an x-ray microbeam during word productions. A coupling index based on sliding window covariance was used to determine disease-related changes in the coupling between the tongue regions across each word. The results indicated decreased spatiotemporal coupling of mid-posterior tongue regions and reduced tongue speed in the ALS-moderate subgroup. Changes in the range of tongue coupling relations and speed of movement were highly correlated with speech intelligibility. These results provide new insights into the loss of lingual motor control due to ALS and suggest that measures of tongue performance may provide useful indicators of bulbar disease severity and progression.

Spatiotemporal regulation of ATP and Ca2+ dynamics in vertebrate rod and cone ribbon synapses

PubMed Central

Johnson, Jerry E.; Perkins, Guy A.; Giddabasappa, Anand; Chaney, Shawntay; Xiao, Weimin; White, Andrew D.; Brown, Joshua M.; Waggoner, Jenna; Ellisman, Mark H.

2007-01-01

Purpose In conventional neurons, Ca2+ enters presynaptic terminals during an action potential and its increased local concentration triggers transient exocytosis. In contrast, vertebrate photoreceptors are nonspiking neurons that maintain sustained depolarization and neurotransmitter release from ribbon synapses in darkness and produce light-dependent graded hyperpolarizing responses. Rods transmit single photon responses with high fidelity, whereas cones are less sensitive and exhibit faster response kinetics. These differences are likely due to variations in presynaptic Ca2+ dynamics. Metabolic coupling and cross-talk between mitochondria, endoplasmic reticulum (ER), plasma membrane Ca2+ ATPase (PMCA), and Na+-Ca2+ exchanger (NCX) coordinately control presynaptic ATP production and Ca2+ dynamics. The goal of our structural and functional studies was to determine the spatiotemporal regulation of ATP and Ca2+ dynamics in rod spherules and cone pedicles. Methods Central retina tissue from C57BL/6 mice was used. Laser scanning confocal microscopy (LSCM) experiments were conducted on fixed-frozen vertical sections. Primary antibodies were selected for their tissue/cellular specificity and ability to recognize single, multiple or all splice variants of selected isoforms. Electron microscopy (EM) and 3-D electron tomography (ET) studies used our standard procedures on thin- and thick-sectioned retinas, respectively. Calibrated fluo-3-Ca2+ imaging experiments of dark- and light-adapted rod and cone terminals in retinal slices were conducted. Results Confocal microscopy showed that mitochondria, ER, PMCA, and NCX1 exhibited distinct retinal lamination patterns and differential distribution in photoreceptor synapses. Antibodies for three distinct mitochondrial compartments differentially labeled retinal areas with high metabolic demand: rod and cone inner segments, previously undescribed cone juxtanuclear mitochondria and the two plexiform layers. Rod spherule membranes

Spatiotemporal regulation of ATP and Ca2+ dynamics in vertebrate rod and cone ribbon synapses.

PubMed

Johnson, Jerry E; Perkins, Guy A; Giddabasappa, Anand; Chaney, Shawntay; Xiao, Weimin; White, Andrew D; Brown, Joshua M; Waggoner, Jenna; Ellisman, Mark H; Fox, Donald A

2007-06-15

In conventional neurons, Ca2+ enters presynaptic terminals during an action potential and its increased local concentration triggers transient exocytosis. In contrast, vertebrate photoreceptors are nonspiking neurons that maintain sustained depolarization and neurotransmitter release from ribbon synapses in darkness and produce light-dependent graded hyperpolarizing responses. Rods transmit single photon responses with high fidelity, whereas cones are less sensitive and exhibit faster response kinetics. These differences are likely due to variations in presynaptic Ca2+ dynamics. Metabolic coupling and cross-talk between mitochondria, endoplasmic reticulum (ER), plasma membrane Ca2+ ATPase (PMCA), and Na+-Ca2+ exchanger (NCX) coordinately control presynaptic ATP production and Ca2+ dynamics. The goal of our structural and functional studies was to determine the spatiotemporal regulation of ATP and Ca2+ dynamics in rod spherules and cone pedicles. Central retina tissue from C57BL/6 mice was used. Laser scanning confocal microscopy (LSCM) experiments were conducted on fixed-frozen vertical sections. Primary antibodies were selected for their tissue/cellular specificity and ability to recognize single, multiple or all splice variants of selected isoforms. Electron microscopy (EM) and 3-D electron tomography (ET) studies used our standard procedures on thin- and thick-sectioned retinas, respectively. Calibrated fluo-3-Ca2+ imaging experiments of dark- and light-adapted rod and cone terminals in retinal slices were conducted. Confocal microscopy showed that mitochondria, ER, PMCA, and NCX1 exhibited distinct retinal lamination patterns and differential distribution in photoreceptor synapses. Antibodies for three distinct mitochondrial compartments differentially labeled retinal areas with high metabolic demand: rod and cone inner segments, previously undescribed cone juxtanuclear mitochondria and the two plexiform layers. Rod spherule membranes uniformly and intensely

Quantifying drivers of wild pig movement across multiple spatial and temporal scales

USGS Publications Warehouse

Kay, Shannon L.; Fischer, Justin W.; Monaghan, Andrew J.; Beasley, James C; Boughton, Raoul; Campbell, Tyler A; Cooper, Susan M; Ditchkoff, Stephen S.; Hartley, Stephen B.; Kilgo, John C; Wisely, Samantha M; Wyckoff, A Christy; Vercauteren, Kurt C.; Pipen, Kim M

2017-01-01

The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

An ensemble of regulatory elements controls Runx3 spatiotemporal expression in subsets of dorsal root ganglia proprioceptive neurons.

PubMed

Appel, Elena; Weissmann, Sarit; Salzberg, Yehuda; Orlovsky, Kira; Negreanu, Varda; Tsoory, Michael; Raanan, Calanit; Feldmesser, Ester; Bernstein, Yael; Wolstein, Orit; Levanon, Ditsa; Groner, Yoram

2016-12-01

The Runx3 transcription factor is essential for development and diversification of the dorsal root ganglia (DRGs) TrkC sensory neurons. In Runx3-deficient mice, developing TrkC neurons fail to extend central and peripheral afferents, leading to cell death and disruption of the stretch reflex circuit, resulting in severe limb ataxia. Despite its central role, the mechanisms underlying the spatiotemporal expression specificities of Runx3 in TrkC neurons were largely unknown. Here we first defined the genomic transcription unit encompassing regulatory elements (REs) that mediate the tissue-specific expression of Runx3. Using transgenic mice expressing BAC reporters spanning the Runx3 locus, we discovered three REs-dubbed R1, R2, and R3-that cross-talk with promoter-2 (P2) to drive TrkC neuron-specific Runx3 transcription. Deletion of single or multiple elements either in the BAC transgenics or by CRISPR/Cas9-mediated endogenous ablation established the REs' ability to promote and/or repress Runx3 expression in developing sensory neurons. Our analysis reveals that an intricate combinatorial interplay among the three REs governs Runx3 expression in distinct subtypes of TrkC neurons while concomitantly extinguishing its expression in non-TrkC neurons. These findings provide insights into the mechanism regulating cell type-specific expression and subtype diversification of TrkC neurons in developing DRGs. © 2016 Appel et al.; Published by Cold Spring Harbor Laboratory Press.

Imaging 2015 Mw 7.8 Gorkha Earthquake and Its Aftershock Sequence Combining Multiple Calibrated Global Seismic Arrays

NASA Astrophysics Data System (ADS)

LI, B.; Ghosh, A.

2016-12-01

The 2015 Mw 7.8 Gorkha earthquake provides a good opportunity to study the tectonics and earthquake hazards in the Himalayas, one of the most seismically active plate boundaries. Details of the seismicity patterns and associated structures in the Himalayas are poorly understood mainly due to limited instrumentation. Here, we apply a back-projection method to study the mainshock rupture and the following aftershock sequence using four large aperture global seismic arrays. All the arrays show eastward rupture propagation of about 130 km and reveal similar evolution of seismic energy radiation, with strong high-frequency energy burst about 50 km north of Kathmandu. Each single array, however, is typically limited by large azimuthal gap, low resolution, and artifacts due to unmodeled velocity structures. Therefore, we use a self-consistent empirical calibration method to combine four different arrays to image the Gorkha event. It greatly improves the resolution, can better track rupture and reveal details that cannot be resolved by any individual array. In addition, we also use the same arrays at teleseismic distances and apply a back-projection technique to detect and locate the aftershocks immediately following the Gorkha earthquake. We detect about 2.5 times the aftershocks recorded by the Advance National Seismic System comprehensive earthquake catalog during the 19 days following the mainshock. The aftershocks detected by the arrays show an east-west trend in general, with majority of the aftershocks located at the eastern part of the rupture patch and surrounding the rupture zone of the largest Mw 7.3 aftershock. Overall spatiotemporal aftershock pattern agrees well with global catalog, with our catalog showing more details relative to the standard global catalog. The improved aftershock catalog enables us to better study the aftershock dynamics, stress evolution in this region. Moreover, rapid and better imaging of aftershock distribution may aid rapid response

Determining Spatio-Temporal Cadastral Data Requirement for Infrastructure of Ladm for Turkey

NASA Astrophysics Data System (ADS)

Alkan, M.; Polat, Z. A.

2016-06-01

Nowadays, the nature of land title and cadastral (LTC) data in the Turkey is dynamic from a temporal perspective which depends on the LTC operations. Functional requirements with respect to the characteristics are investigated based upon interviews of professionals in public and private sectors. These are; Legal authorities, Land Registry and Cadastre offices, Highway departments, Foundations, Ministries of Budget, Transportation, Justice, Public Works and Settlement, Environment and Forestry, Agriculture and Rural Affairs, Culture and Internal Affairs, State Institute of Statistics (SIS), execution offices, tax offices, real estate offices, private sector, local governments and banks. On the other hand, spatio-temporal LTC data very important component for creating infrastructure of Land Administration Model (LADM). For this reason, spatio-temporal LTC data needs for LADM not only updated but also temporal. The investigations ended up with determine temporal analyses of LTC data, traditional LTC system and tracing temporal analyses in traditional LTC system. In the traditional system, the temporal analyses needed by all these users could not be performed in a rapid and reliable way. The reason for this is that the traditional LTC system is a manual archiving system. The aims and general contents of this paper: (1) define traditional LTC system of Turkey; (2) determining the need for spatio-temporal LTC data and analyses for core domain model for LADM. As a results of temporal and spatio-temporal analysis LTC data needs, new system design is important for the Turkish LADM model. Designing and realizing an efficient and functional Temporal Geographic Information Systems (TGIS) is inevitable for the Turkish LADM core infrastructure. Finally this paper outcome is creating infrastructure for design and develop LADM for Turkey.

Spatio-temporal characterization imaging of Ca2+ oscillations in rat hippocampal neurons

NASA Astrophysics Data System (ADS)

Zhang, Zhihong; Lu, Jinling; Zhou, Wei; Liu, Rengang; Zeng, Shaoqun; Luo, Qingming

2001-08-01

Ca2+ is the most common signal transduction element in cells and plays critical rolls in neuronal development and plasticity. Ca2+ signals encode information in their oscillation frequency or amplitude and response time to regular cellular function. In this study, in order to reveal the spatio-temporal characterization of Ca2+ oscillations in rat hippocampal neurons, two kinds of Ca2+ fluorescent probes, yellow cameleons 2.1 (YC2.1) and Fluo-3, were used to monitor the change of the intracellular free Ca2+ concentration (]Ca2+[i). Spontaneous Ca2+ oscillations and glutamate elicited Ca2+ oscillations were observed with multi-photon excitation laser scan microscope (MPELSM) and confocal laser scan microscope (CLSM). The observation showed that the spatio- temporal characterization of either spontaneous or glutamate provoked Ca2+ oscillations had difference between the neurites and somata in individual nerons, especially in some distal end of neurites. The result indicated that Ca2+ oscillations were most important signal transduction pattern in neuronal development and activation. The spatio-temporal characterization of difference of Ca2+ signals between the distal endo of neurites and the somata might be associated with the distribution of ionotropic receptor and metabotropic glutamate receptors, and Ca2+ response mechanism mediated by two kinds of glutamate receptor. Ca2+ signal elicited by glutamate in the distal end of neurites appeared more complex and generated faster than that in the somata. It was suggested that Ca2+ signal in glutamate stimulated hippacamal neurons first generated from the distal end of neurites and then transduted to the somata. The complicated Ca2+ signal characterization in the distal end of neurites might be associated with neuronal activitation, neurotransmitter releasing, and other functions of neurons.

Resolving the detailed spatiotemporal slip evolution of deep tremor in western Japan

NASA Astrophysics Data System (ADS)

Ohta, K.; Ide, S.

2017-12-01

A quantitative evaluation of the slip evolution of tremor is essential to understand the generation mechanism of slow earthquakes. The recent studies have revealed the most part of tremor signals can be expressed as the superposition of low frequency earthquakes (LFE). However, it is still challenging to explain the entire waveforms of tremor, because a conventional slip inversion analysis is not available for tremor due to insufficient knowledge of source locations and Green's functions. Here we investigate the detailed spatiotemporal behavior of deep tremor in western Japan through the development and application of a new slip inversion method. We introduce synthetic template waveforms, which are typical tremor waveforms obtained by stacking LFE seismograms at arranged points along the plate interface. Using these synthetic template waveforms as substitutes for Green's functions, we invert the continuous tremor waveforms using an iterative deconvolution approach with Bayesian constraints. We apply this method to two tremor burst episodes in western and central Shikoku, Japan. The estimated slip distribution from a 12-day tremor burst episode in western Shikoku is heterogeneous, with several patchy areas of slip along the plate interface where rapid moment releases with durations of <100 s regularly occur. We attribute these heterogeneous spatiotemporal slip patterns to heterogeneous material properties along the plate interface. For central Shikoku, where we focus on a tremor burst episode that occurred coincidentally with a very low frequency earthquake (VLF), we observe that the source size of the VLF is much larger than that estimated from tremor activity in western Shikoku. These differences in the size of the slip region may dictate the visibility of VLF signals in observed seismograms, which has implications for the mechanics of slow earthquakes and subduction zone processes.

Application of alternative spatiotemporal metrics of ambient air pollution exposure in a time-series epidemiological study in Atlanta

EPA Science Inventory

Exposure error in studies of ambient air pollution and health that use city-wide measures of exposure may be substantial for pollutants that exhibit spatiotemporal variability. Alternative spatiotemporal metrics of exposure for traffic-related and regional pollutants were applied...

The correlation between symptomatic fatigue to definite measures of gait in people with multiple sclerosis.

PubMed

Kalron, Alon

2016-02-01

There is a general consensus relating to the multidimensional aspects of fatigue in people with multiple sclerosis (PwMS), however, the exact impact of this symptom on gait is not fully understood. Our primary aim was to examine the relationship between definite parameters of gait with self-reported symptomatic fatigue in PwMS according to their level of neurological impairment. Spatio-temporal parameters of gait were studied using an electronic walkway. The Multiple Sclerosis Walking Scale (MSWS-12) questionnaire, a patient-rated measure of walking ability was collected. The Modified Fatigue Impact Scale (MFIS) questionnaire was used to determine the level of symptomatic fatigue. One hundred and one PwMS (61 women) were included in the study analysis. Subjects were divided into mild and moderate neurological impaired groups. Fatigue was correlated with 5 (out of 14) spatiotemporal parameters. However, correlation scores were all <0.35, thus considered as weak correlations. In the mild group, the double support period was the only variable positively correlated to fatigue (Spearman's rho=0.28, P=0.05). In the moderate group, step and stride length were solely negatively correlated to fatigue (Spearman's rho=0.32, P=0.03). In contrast to the definite gait parameters, the MSWS-12 self-questionnaire was moderately positively correlated to the level of fatigue. Scores for the total, mild and moderate groups were 0.54, 0.57 and 0.51; P<0.01, respectively. The present results indicate that modifications in spatio-temporal parameters of gait are not closely related to symptomatic fatigue in PwMS. On the contrary, the self-reported MSWS-12 questionnaire is predisposed to level of fatigue in PwMS. Copyright © 2015 Elsevier B.V. All rights reserved.

A spatiotemporal data model for incorporating time in geographic information systems (GEN-STGIS)

NASA Astrophysics Data System (ADS)

Narciso, Flor Eugenia

Temporal Geographic Information Systems (TGIS) is a new technology, which is being developed to work with Geographic Information Systems (GIS) that deal with geographic phenomena that change over time. The capabilities of TGIS depend on the underlying data model. However, a literature review of current spatiotemporal GIS data models has shown that they are not adequate for managing time when representing temporal data. In addition, the majority of these data models have been designed to support the requirements of specific-purpose applications. In an effort to resolve this problem, the related literature has been explored. A comparative investigation of the current spatiotemporal GIS data models has been made to identify their characteristics, advantages and disadvantages, similarities and differences, and to determine why they do not work adequately. A new object-oriented General-purpose Spatiotemporal GIS (GEN-STGIS) data model is proposed here. This model provides better representation, storage and management of data related to geographic phenomena that change over time and overcomes some of the problems detected in the reviewed data models. The proposed data model has four key benefits. First, it provides the capabilities of a standard vector-based GIS embedded in the 2-D Euclidean space. Second, it includes the two temporal dimensions, valid time and transaction time, supported by temporal databases. Third, it inherits, from the object oriented approach, the flexibility, modularity and ability to handle the complexities introduced by spatial and temporal dimensions. Fourth, it improves the geographic query capabilities of current TGIS with the introduction of the concept of bounding box while providing temporal and spatiotemporal query capabilities. The data model is then evaluated in order to assess its strengths and weaknesses as a spatiotemporal GIS data model, and to determine how well the model satisfies the requirements imposed by TGIS applications. The

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

PubMed

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

Spatiotemporal evolution of the chlorophyll a trend in the North Atlantic Ocean.

PubMed

Zhang, Min; Zhang, Yuanling; Shu, Qi; Zhao, Chang; Wang, Gang; Wu, Zhaohua; Qiao, Fangli

2018-01-15

Analyses of the chlorophyll a concentration (chla) from satellite ocean color products have suggested the decadal-scale variability of chla linked to the climate change. The decadal-scale variability in chla is both spatially and temporally non-uniform. We need to understand the spatiotemporal evolution of chla in decadal or multi-decadal timescales to better evaluate its linkage to climate variability. Here, the spatiotemporal evolution of the chla trend in the North Atlantic Ocean for the period 1997-2016 is analyzed using the multidimensional ensemble empirical mode decomposition method. We find that this variable trend signal of chla shows a dipole pattern between the subpolar gyre and along the Gulf Stream path, and propagation along the opposite direction of the North Atlantic Current. This propagation signal has an overlapping variability of approximately twenty years. Our findings suggest that the spatiotemporal evolution of chla during the two most recent decades is part of the multidecadal variations and possibly regulated by the changes of Atlantic Meridional Overturning Circulation, whereas the mechanisms of such evolution patterns still need to be explored. Copyright © 2017 Elsevier B.V. All rights reserved.

A data mining based approach to predict spatiotemporal changes in satellite images

NASA Astrophysics Data System (ADS)

Boulila, W.; Farah, I. R.; Ettabaa, K. Saheb; Solaiman, B.; Ghézala, H. Ben

2011-06-01

The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. Recently, data mining appears to be a promising research field leading to several interesting discoveries in various areas such as marketing, surveillance, fraud detection and scientific discovery. By integrating data mining and image interpretation techniques, accurate and relevant information (i.e. functional relation between observed parcels and a set of informational contents) can be automatically elicited. This study presents a new approach to predict spatiotemporal changes in satellite image databases. The proposed method exploits fuzzy sets and data mining concepts to build predictions and decisions for several remote sensing fields. It takes into account imperfections related to the spatiotemporal mining process in order to provide more accurate and reliable information about land cover changes in satellite images. The proposed approach is validated using SPOT images representing the Saint-Denis region, capital of Reunion Island. Results show good performances of the proposed framework in predicting change for the urban zone.

Bayesian inference for the spatio-temporal invasion of alien species.

PubMed

Cook, Alex; Marion, Glenn; Butler, Adam; Gibson, Gavin

2007-08-01

In this paper we develop a Bayesian approach to parameter estimation in a stochastic spatio-temporal model of the spread of invasive species across a landscape. To date, statistical techniques, such as logistic and autologistic regression, have outstripped stochastic spatio-temporal models in their ability to handle large numbers of covariates. Here we seek to address this problem by making use of a range of covariates describing the bio-geographical features of the landscape. Relative to regression techniques, stochastic spatio-temporal models are more transparent in their representation of biological processes. They also explicitly model temporal change, and therefore do not require the assumption that the species' distribution (or other spatial pattern) has already reached equilibrium as is often the case with standard statistical approaches. In order to illustrate the use of such techniques we apply them to the analysis of data detailing the spread of an invasive plant, Heracleum mantegazzianum, across Britain in the 20th Century using geo-referenced covariate information describing local temperature, elevation and habitat type. The use of Markov chain Monte Carlo sampling within a Bayesian framework facilitates statistical assessments of differences in the suitability of different habitat classes for H. mantegazzianum, and enables predictions of future spread to account for parametric uncertainty and system variability. Our results show that ignoring such covariate information may lead to biased estimates of key processes and implausible predictions of future distributions.

Spatiotemporal Distribution of Chinavia hilaris (Hemiptera: Pentatomidae) in Corn Farmscapes

PubMed Central

Cottrell, Ted E.; Tillman, P. Glynn

2015-01-01

The green stink bug, Chinavia hilaris (Say) (Hemiptera: Pentatomidae), is a pest of cotton in the southeastern United States but little is known concerning its spatiotemporal distribution in corn cropping systems. Therefore, the spatiotemporal distribution of C. hilaris in farmscapes, when corn was adjacent to cotton, peanut, or both, was examined weekly. The spatial patterns of C. hilaris counts were analyzed using Spatial Analysis by Distance Indices methodology. Interpolated maps of C. hilaris density were used to visualize abundance and distribution of C. hilaris in crops in corn–peanut–cotton farmscapes. This stink bug was detected in six of seven corn–cotton farmscapes, four of six corn–peanut farmscapes, and in both corn–peanut–cotton farmscapes. The frequency of C. hilaris in cotton (89.47%) was significantly higher than in peanut (7.02%) or corn (3.51%). This stink bug fed on noncrop hosts that grew in field borders adjacent to crops. The spatial distribution of C. hilaris in crops and the capture of C. hilaris adults and nymphs in pheromone-baited traps near noncrop hosts indicated that these hosts were sources of this stink bug dispersing into crops, primarily cotton. Significant aggregated spatial distributions were detected in cotton on some dates within corn–peanut–cotton farmscapes. Maps of local clustering indices depicted small patches of C. hilaris in cotton or cotton–sorghum at the peanut–cotton interface. Factors affecting the spatiotemporal dynamics of C. hilaris in corn farmscapes are discussed. PMID:25843581

Spatiotemporal patterns in reaction-diffusion system and in a vibrated granular bed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swinney, H.L.; Lee, K.J.; McCormick, W.D.

Experiments on a quasi-two-dimensional reaction-diffusion system reveal transitions from a uniform state to stationary hexagonal, striped, and rhombic spatial patterns. For other reactor conditions lamellae and self-replicating spot patterns are observed. These patterns form in continuously fed thin gel reactors that can be maintained indefinitely in well-defined nonequilibrium states. Reaction-diffusion models with two chemical species yield patterns similar to those observed in the experiments. Pattern formation is also being examined in vertically oscillated thin granular layers (typically 3-30 particle diameters deep). For small acceleration amplitudes, a granular layer is flat, but above a well-defined critical acceleration amplitude, spatial patterns spontaneouslymore » form. Disordered time-dependent granular patterns are observed as well as regular patterns of squares, stripes, and hexagons. A one-dimensional model consisting of a completely inelastic ball colliding with a sinusoidally oscillating platform provides a semi-quantitative description of most of the observed bifurcations between the different spatiotemporal regimes.« less

Spatiotemporal chaos involving wave instability.

PubMed

Berenstein, Igal; Carballido-Landeira, Jorge

2017-01-01

In this paper, we investigate pattern formation in a model of a reaction confined in a microemulsion, in a regime where both Turing and wave instability occur. In one-dimensional systems, the pattern corresponds to spatiotemporal intermittency where the behavior of the systems alternates in both time and space between stationary Turing patterns and traveling waves. In two-dimensional systems, the behavior initially may correspond to Turing patterns, which then turn into wave patterns. The resulting pattern also corresponds to a chaotic state, where the system alternates in both space and time between standing wave patterns and traveling waves, and the local dynamics may show vanishing amplitude of the variables.

Spatiotemporal chaos involving wave instability

NASA Astrophysics Data System (ADS)

Berenstein, Igal; Carballido-Landeira, Jorge

2017-01-01

In this paper, we investigate pattern formation in a model of a reaction confined in a microemulsion, in a regime where both Turing and wave instability occur. In one-dimensional systems, the pattern corresponds to spatiotemporal intermittency where the behavior of the systems alternates in both time and space between stationary Turing patterns and traveling waves. In two-dimensional systems, the behavior initially may correspond to Turing patterns, which then turn into wave patterns. The resulting pattern also corresponds to a chaotic state, where the system alternates in both space and time between standing wave patterns and traveling waves, and the local dynamics may show vanishing amplitude of the variables.

Spatiotemporal modeling of ecological and sociological ...

EPA Pesticide Factsheets

Suffolk County, New York, is a locus for West Nile virus (WNV) infection in the American northeast that includes the majority of Long Island to the east of New York City. The county has a system of light and gravid traps used for mosquito collection and disease monitoring. In order to identify predictors of WNV incidence in mosquitoes and predict future occurrence of WNV, we have developed a spatiotemporal Bayesian model, beginning with over 40 ecological, meteorological, and built-environment covariates. A mixed-effects model including spatially and temporally correlated errors was fit to WNV surveillance data from 2008 to 2014 using the R package “R-INLA,” which allows for Bayesian modeling using the stochastic partial differential equation (SPDE) approach. The integrated nested Laplace approximation (INLA) SPDE allows for simultaneous fitting of a temporal parameter and a spatial covariance, while incorporating a variety of likelihood functions and running in R statistical software on a home computer. We found that land cover classified as open water and woody wetlands had a negative association with WNV incidence in mosquitoes, and the count of septic systems was associated with an increase in WNV. Mean temperature at two-week lag was associated with a strong positive impact, while mean precipitation at no lag and one-week lag was associated with positive and negative impacts on WNV, respectively. Incorporation of spatiotemporal factors resulted in a mar

Estimation of multiple accelerated motions using chirp-Fourier transform and clustering.

PubMed

Alexiadis, Dimitrios S; Sergiadis, George D

2007-01-01

Motion estimation in the spatiotemporal domain has been extensively studied and many methodologies have been proposed, which, however, cannot handle both time-varying and multiple motions. Extending previously published ideas, we present an efficient method for estimating multiple, linearly time-varying motions. It is shown that the estimation of accelerated motions is equivalent to the parameter estimation of superpositioned chirp signals. From this viewpoint, one can exploit established signal processing tools such as the chirp-Fourier transform. It is shown that accelerated motion results in energy concentration along planes in the 4-D space: spatial frequencies-temporal frequency-chirp rate. Using fuzzy c-planes clustering, we estimate the plane/motion parameters. The effectiveness of our method is verified on both synthetic as well as real sequences and its advantages are highlighted.

Fast Spatio-Temporal Data Mining from Large Geophysical Datasets

NASA Technical Reports Server (NTRS)

Stolorz, P.; Mesrobian, E.; Muntz, R.; Santos, J. R.; Shek, E.; Yi, J.; Mechoso, C.; Farrara, J.

1995-01-01

Use of the UCLA CONQUEST (CONtent-based Querying in Space and Time) is reviewed for performance of automatic cyclone extraction and detection of spatio-temporal blocking conditions on MPP. CONQUEST is a data analysis environment for knowledge and data mining to aid in high-resolution modeling of climate modeling.

Compositing climate change vulnerability of a Mediterranean region using spatiotemporally dynamic proxies for ecological and socioeconomic impacts and stabilities.

PubMed

Demirkesen, Ali Can; Evrendilek, Fatih

2017-01-01

The study presents a new methodology to quantify spatiotemporal dynamics of climate change vulnerability at a regional scale adopting a new conceptual model of vulnerability as a function of climate change impacts, ecological stability, and socioeconomic stability. Spatiotemporal trends of equally weighted proxy variables for the three vulnerability components were generated to develop a composite climate change vulnerability index (CCVI) for a Mediterranean region of Turkey combining Landsat time series data, digital elevation model (DEM)-derived data, ordinary kriging, and geographical information system. Climate change impact was based on spatiotemporal trends of August land surface temperature (LST) between 1987 and 2016. Ecological stability was based on DEM, slope, aspect, and spatiotemporal trends of normalized difference vegetation index (NDVI), while socioeconomic stability was quantified as a function of spatiotemporal trends of land cover, population density, per capita gross domestic product, and illiteracy. The zones ranked on the five classes of no-to-extreme vulnerability were identified where highly and moderately vulnerable lands covered 0.02% (12 km 2 ) and 11.8% (6374 km 2 ) of the study region, respectively, mostly occurring in the interior central part. The adoption of this composite CCVI approach is expected to lead to spatiotemporally dynamic policy recommendations towards sustainability and tailor preventive and mitigative measures to locally specific characteristics of coupled ecological-socioeconomic systems.

Spatio-Temporal Patterning in Primary Motor Cortex at Movement Onset.

PubMed

Best, Matthew D; Suminski, Aaron J; Takahashi, Kazutaka; Brown, Kevin A; Hatsopoulos, Nicholas G

2017-02-01

Voluntary movement initiation involves the engagement of large populations of motor cortical neurons around movement onset. Despite knowledge of the temporal dynamics that lead to movement, the spatial structure of these dynamics across the cortical surface remains unknown. In data from 4 rhesus macaques, we show that the timing of attenuation of beta frequency local field potential oscillations, a correlate of locally activated cortex, forms a spatial gradient across primary motor cortex (MI). We show that these spatio-temporal dynamics are recapitulated in the engagement order of ensembles of MI neurons. We demonstrate that these patterns are unique to movement onset and suggest that movement initiation requires a precise spatio-temporal sequential activation of neurons in MI. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Measurement Error Correction for Predicted Spatiotemporal Air Pollution Exposures.

PubMed

Keller, Joshua P; Chang, Howard H; Strickland, Matthew J; Szpiro, Adam A

2017-05-01

Air pollution cohort studies are frequently analyzed in two stages, first modeling exposure then using predicted exposures to estimate health effects in a second regression model. The difference between predicted and unobserved true exposures introduces a form of measurement error in the second stage health model. Recent methods for spatial data correct for measurement error with a bootstrap and by requiring the study design ensure spatial compatibility, that is, monitor and subject locations are drawn from the same spatial distribution. These methods have not previously been applied to spatiotemporal exposure data. We analyzed the association between fine particulate matter (PM2.5) and birth weight in the US state of Georgia using records with estimated date of conception during 2002-2005 (n = 403,881). We predicted trimester-specific PM2.5 exposure using a complex spatiotemporal exposure model. To improve spatial compatibility, we restricted to mothers residing in counties with a PM2.5 monitor (n = 180,440). We accounted for additional measurement error via a nonparametric bootstrap. Third trimester PM2.5 exposure was associated with lower birth weight in the uncorrected (-2.4 g per 1 μg/m difference in exposure; 95% confidence interval [CI]: -3.9, -0.8) and bootstrap-corrected (-2.5 g, 95% CI: -4.2, -0.8) analyses. Results for the unrestricted analysis were attenuated (-0.66 g, 95% CI: -1.7, 0.35). This study presents a novel application of measurement error correction for spatiotemporal air pollution exposures. Our results demonstrate the importance of spatial compatibility between monitor and subject locations and provide evidence of the association between air pollution exposure and birth weight.

Spatiotemporal Patterns in a Predator-Prey Model with Cross-Diffusion Effect

NASA Astrophysics Data System (ADS)

Sambath, M.; Balachandran, K.; Guin, L. N.

The present research deals with the emergence of spatiotemporal patterns of a two-dimensional (2D) continuous predator-prey system with cross-diffusion effect. First, we work out the critical lines of Hopf and Turing bifurcations of the current model system in a 2D spatial domain by means of bifurcation theory. More specifically, the exact Turing region is specified in a two-parameter space. In effect, by choosing the cross-diffusion coefficient as one of the momentous parameter, we demonstrate that the model system undergoes a sequence of spatiotemporal patterns in a homogeneous environment through diffusion-driven instability. Our results via numerical simulation authenticate that cross-diffusion be able to create stationary patterns which enrich the findings of pattern formation in an ecosystem.

Exploring Spatiotemporal Trends in Commercial Fishing Effort of an Abalone Fishing Zone: A GIS-Based Hotspot Model

PubMed Central

Jalali, M. Ali; Ierodiaconou, Daniel; Gorfine, Harry; Monk, Jacquomo; Rattray, Alex

2015-01-01

Assessing patterns of fisheries activity at a scale related to resource exploitation has received particular attention in recent times. However, acquiring data about the distribution and spatiotemporal allocation of catch and fishing effort in small scale benthic fisheries remains challenging. Here, we used GIS-based spatio-statistical models to investigate the footprint of commercial diving events on blacklip abalone (Haliotis rubra) stocks along the south-west coast of Victoria, Australia from 2008 to 2011. Using abalone catch data matched with GPS location we found catch per unit of fishing effort (CPUE) was not uniformly spatially and temporally distributed across the study area. Spatial autocorrelation and hotspot analysis revealed significant spatiotemporal clusters of CPUE (with distance thresholds of 100’s of meters) among years, indicating the presence of CPUE hotspots focused on specific reefs. Cumulative hotspot maps indicated that certain reef complexes were consistently targeted across years but with varying intensity, however often a relatively small proportion of the full reef extent was targeted. Integrating CPUE with remotely-sensed light detection and ranging (LiDAR) derived bathymetry data using generalized additive mixed model corroborated that fishing pressure primarily coincided with shallow, rugose and complex components of reef structures. This study demonstrates that a geospatial approach is efficient in detecting patterns and trends in commercial fishing effort and its association with seafloor characteristics. PMID:25992800

Spatio-temporally resolved spectral measurements of laser-produced plasma and semiautomated spectral measurement-control and analysis software

NASA Astrophysics Data System (ADS)

Cao, S. Q.; Su, M. G.; Min, Q.; Sun, D. X.; O'Sullivan, G.; Dong, C. Z.

2018-02-01

A spatio-temporally resolved spectral measurement system of highly charged ions from laser-produced plasmas is presented. Corresponding semiautomated computer software for measurement control and spectral analysis has been written to achieve the best synchronicity possible among the instruments. This avoids the tedious comparative processes between experimental and theoretical results. To demonstrate the capabilities of this system, a series of spatio-temporally resolved experiments of laser-produced Al plasmas have been performed and applied to benchmark the software. The system is a useful tool for studying the spectral structures of highly charged ions and for evaluating the spatio-temporal evolution of laser-produced plasmas.

Network-constrained spatio-temporal clustering analysis of traffic collisions in Jianghan District of Wuhan, China

PubMed Central

Fan, Yaxin; Zhu, Xinyan; Guo, Wei; Guo, Tao

2018-01-01

The analysis of traffic collisions is essential for urban safety and the sustainable development of the urban environment. Reducing the road traffic injuries and the financial losses caused by collisions is the most important goal of traffic management. In addition, traffic collisions are a major cause of traffic congestion, which is a serious issue that affects everyone in the society. Therefore, traffic collision analysis is essential for all parties, including drivers, pedestrians, and traffic officers, to understand the road risks at a finer spatio-temporal scale. However, traffic collisions in the urban context are dynamic and complex. Thus, it is important to detect how the collision hotspots evolve over time through spatio-temporal clustering analysis. In addition, traffic collisions are not isolated events in space. The characteristics of the traffic collisions and their surrounding locations also present an influence of the clusters. This work tries to explore the spatio-temporal clustering patterns of traffic collisions by combining a set of network-constrained methods. These methods were tested using the traffic collision data in Jianghan District of Wuhan, China. The results demonstrated that these methods offer different perspectives of the spatio-temporal clustering patterns. The weighted network kernel density estimation provides an intuitive way to incorporate attribute information. The network cross K-function shows that there are varying clustering tendencies between traffic collisions and different types of POIs. The proposed network differential Local Moran’s I and network local indicators of mobility association provide straightforward and quantitative measures of the hotspot changes. This case study shows that these methods could help researchers, practitioners, and policy-makers to better understand the spatio-temporal clustering patterns of traffic collisions. PMID:29672551

Low-Energy Defibrillation Failure Correction is Possible Through Nonlinear Analysis of Spatiotemporal Arrhythmia Data

NASA Astrophysics Data System (ADS)

Simonotto, Jennifer; Furman, Michael; Beaver, Thomas; Spano, Mark; Kavanagh, Katherine; Iden, Jason; Hu, Gang; Ditto, William

2004-03-01

Explanted Porcine hearts were Langendorff-perfused, administered a voltage-sensitive fluorescent dye (Di-4-ANEPPS) and illuminated with a ND:Yag laser (532 nm); the change in fluorescence resulting from electrical activity on the heart surface was recorded with an 80 x 80 pixel CCD camera at 1000 frames per second. The heart was put into fibrillation with rapid ventricular pacing and shocks were administered close to the defibrillation threshold. Defibrillation failure data was analyzed using synchronization, space-time volume plots and recurrence quantification. Preliminary spatiotemporal synchronization results reveal a short window of time ( 1 second) after defibrillation failure in which the disordered electrical activity becomes ordered; this ordered period occurs 4-5 seconds after the defibrillation shock. Recurrence analysis of a single time series confirmed these results, thus opening the avenue for dynamic defibrillators that can detect an optimal window for cardioversion.

Analysis of the Spatiotemporal Characteristics of Hemorrhagic Fever with Renal Syndrome in Hubei Province, China

NASA Astrophysics Data System (ADS)

Fan, H.; Ge, L.; Song, L.; Zhao, Q.

2015-07-01

Hemorrhagic fever with renal syndrome(HFRS) is a worldwide fulminant infectious disease. Since the first HFRS cases in Hubei Province were reported in 1957, the disease has spread across the province and Hubei has become one of seriously affected areas in China. However, the epidemic characteristics of HFRS are still not entirely clear. Therefore, a systematic investigation of spatial and temporal distribution pattern of HFRS system is needed. In order to facilitate better prevention and control of HFRS in Hubei Province, in this paper, a GIS spatiotemporal analysis and modeling tool was developed to analyze the spatiotemporal dynamics of the HFRS epidemic, as well as providinga comprehensive examination the dynamic pattern of HFRS in Hubei over the past 30 years (1980-2009), to determine spatiotemporal change trends and the causes of HFRS. This paper describes the experiments and their results.

Implementation and evaluation of a hypercube-based method for spatiotemporal exploration and analysis

NASA Astrophysics Data System (ADS)

Marchand, Pierre; Brisebois, Alexandre; Bédard, Yvan; Edwards, Geoffrey

This paper presents the results obtained with a new type of spatiotemporal topological dimension implemented within a hypercube, i.e., within a multidimensional database (MDDB) structure formed by the conjunction of several thematic, spatial and temporal dimensions. Our goal is to support efficient SpatioTemporal Exploration and Analysis (STEA) in the context of Automatic Position Reporting System (APRS), the worldwide amateur radio system for position report transmission. Mobile APRS stations are equipped with GPS navigation systems to provide real-time positioning reports. Previous research about the multidimensional approach has proved good potential for spatiotemporal exploration and analysis despite a lack of explicit topological operators (spatial, temporal and spatiotemporal). Our project implemented such operators through a hierarchy of operators that are applied to pairs of instances of objects. At the top of the hierarchy, users can use simple operators such as "same place", "same time" or "same time, same place". As they drill down into the hierarchy, more detailed topological operators are made available such as "adjacent immediately after", "touch during" or more detailed operators. This hierarchy is structured according to four levels of granularity based on cognitive models, generalized relationships and formal models of topological relationships. In this paper, we also describe the generic approach which allows efficient STEA within the multidimensional approach. Finally, we demonstrate that such an implementation offers query run times which permit to maintain a "train-of-thought" during exploration and analysis operations as they are compatible with Newell's cognitive band (query runtime<10 s) (Newell, A., 1990. Unified theories of cognition. Harvard University Press, Cambridge MA, 549 p.).

Four-dimensional ultrasonography of the fetal heart using color Doppler spatiotemporal image correlation.

PubMed

Gonçalves, Luís F; Romero, Roberto; Espinoza, Jimmy; Lee, Wesley; Treadwell, Marjorie; Chintala, Kavitha; Brandl, Helmut; Chaiworapongsa, Tinnakorn

2004-04-01

To describe clinical and research applications of 4-dimensional imaging of the fetal heart using color Doppler spatiotemporal image correlation. Forty-four volume data sets were acquired by color Doppler spatiotemporal image correlation. Seven subjects were examined: 4 fetuses without abnormalities, 1 fetus with ventriculomegaly and a hypoplastic cerebellum but normal cardiac anatomy, and 2 fetuses with cardiac anomalies detected by fetal echocardiography (1 case of a ventricular septal defect associated with trisomy 21 and 1 case of a double-inlet right ventricle with a 46,XX karyotype). The median gestational age at the time of examination was 21 3/7 weeks (range, 19 5/7-34 0/7 weeks). Volume data sets were reviewed offline by multiplanar display and volume-rendering methods. Representative images and online video clips illustrating the diagnostic potential of this technology are presented. Color Doppler spatiotemporal image correlation allowed multiplanar visualization of ventricular septal defects, multiplanar display and volume rendering of tricuspid regurgitation, volume rendering of the outflow tracts by color and power Doppler ultrasonography (both in a normal case and in a case of a double-inlet right ventricle with a double-outlet right ventricle), and visualization of venous streams at the level of the foramen ovale. Color Doppler spatiotemporal image correlation has the potential to simplify visualization of the outflow tracts and improve the evaluation of the location and extent of ventricular septal defects. Other applications include 3-dimensional evaluation of regurgitation jets and venous streams at the level of the foramen ovale.

Optogenetically induced spatiotemporal gamma oscillations and neuronal spiking activity in primate motor cortex.

PubMed

Lu, Yao; Truccolo, Wilson; Wagner, Fabien B; Vargas-Irwin, Carlos E; Ozden, Ilker; Zimmermann, Jonas B; May, Travis; Agha, Naubahar S; Wang, Jing; Nurmikko, Arto V

2015-06-01

Transient gamma-band (40-80 Hz) spatiotemporal patterns are hypothesized to play important roles in cortical function. Here we report the direct observation of gamma oscillations as spatiotemporal waves induced by targeted optogenetic stimulation, recorded by intracortical multichannel extracellular techniques in macaque monkeys during their awake resting states. Microelectrode arrays integrating an optical fiber at their center were chronically implanted in primary motor (M1) and ventral premotor (PMv) cortices of two subjects. Targeted brain tissue was transduced with the red-shifted opsin C1V1(T/T). Constant (1-s square pulses) and ramp stimulation induced narrowband gamma oscillations during awake resting states. Recordings across 95 microelectrodes (4 × 4-mm array) enabled us to track the transient gamma spatiotemporal patterns manifested, e.g., as concentric expanding and spiral waves. Gamma oscillations were induced well beyond the light stimulation volume, via network interactions at distal electrode sites, depending on optical power. Despite stimulation-related modulation in spiking rates, neuronal spiking remained highly asynchronous during induced gamma oscillations. In one subject we examined stimulation effects during preparation and execution of a motor task and observed that movement execution largely attenuated optically induced gamma oscillations. Our findings demonstrate that, beyond previously reported induced gamma activity under periodic drive, a prolonged constant stimulus above a certain threshold may carry primate motor cortex network dynamics into gamma oscillations, likely via a Hopf bifurcation. More broadly, the experimental capability in combining microelectrode array recordings and optogenetic stimulation provides an important approach for probing spatiotemporal dynamics in primate cortical networks during various physiological and behavioral conditions.

Spontaneous and electrically modulated spatiotemporal dynamics of the neocortical slow oscillation and associated local fast activity.

PubMed

Greenberg, Anastasia; Dickson, Clayton T

2013-12-01

The neocortical slow oscillation (SO; ~1Hz) of non-REM sleep and anesthesia reflects synchronized network activity composed of alternating active and silent (ON/OFF) phases at the local network and cellular level. The SO itself shows self-organized spatiotemporal dynamics as it appears to originate at unique foci on each cycle and then propagates across the cortical surface. During sleep, this rhythm is relevant for neuroplastic processes mediating memory consolidation especially since its enhancement by slow, rhythmic electrical fields improves subsequent recall. However, the neurobiological mechanism by which spontaneous or enhanced SO activity might operate on memory traces is unknown. Here we show a series of original results, using cycle to cycle tracking across multiple neocortical sites in urethane anesthetized rats: The spontaneous spatiotemporal dynamics of the SO are complex, showing interfering propagation patterns in the anterior-to-posterior plane. These patterns compete for expression and tend to alternate following phase resets that take place during the silent OFF phase of the SO. Applying sinusoidal electrical field stimulation to the anterior pole of the cerebral cortex progressively entrained local field, gamma, and multi-unit activity at all sites, while disrupting the coordination of endogenous SO activity. Field stimulation also biased propagation in the anterior-to-posterior direction and more notably, enhanced the long-range gamma synchrony between cortical regions. These results are the first to show that changes to slow wave dynamics cause enhancements in high frequency cortico-cortical communication and provide mechanistic clues into how the SO is relevant for sleep-dependent memory consolidation. © 2013.