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Sample records for spatiotemporal pattern formation

  1. Spatiotemporal Wave Patterns: Information Dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Mikhail Rabinovich; Lev Tsimring

    2006-01-20

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

  2. Spatio-temporal pattern formation in predator-prey systems with fitness taxis

    DEFF Research Database (Denmark)

    Heilmann, Irene T.; Thygesen, Uffe Høgsbro; Sørensen, Mads Peter

    2018-01-01

    We pose a spatial predator–prey model in which the movement of animals is not purely diffusive, but also contains a drift term in the direction of higher specific growth rates. We refer to this as fitness taxis. We conduct a linear stability analysis of the resulting coupled reaction–advection–di......We pose a spatial predator–prey model in which the movement of animals is not purely diffusive, but also contains a drift term in the direction of higher specific growth rates. We refer to this as fitness taxis. We conduct a linear stability analysis of the resulting coupled reaction...... of diffusive motion, is ecologically plausible, and provides an alternative mechanism for formation of patterns in spatially explicit ecosystem models, with emphasis on non-stationary spatio-temporal dynamics....

  3. Regulation of Spatiotemporal Patterns by Biological Variability: General Principles and Applications to Dictyostelium discoideum.

    Directory of Open Access Journals (Sweden)

    Miriam Grace

    2015-11-01

    Full Text Available Spatiotemporal patterns often emerge from local interactions in a self-organizing fashion. In biology, the resulting patterns are also subject to the influence of the systematic differences between the system's constituents (biological variability. This regulation of spatiotemporal patterns by biological variability is the topic of our review. We discuss several examples of correlations between cell properties and the self-organized spatiotemporal patterns, together with their relevance for biology. Our guiding, illustrative example will be spiral waves of cAMP in a colony of Dictyostelium discoideum cells. Analogous processes take place in diverse situations (such as cardiac tissue, where spiral waves occur in potentially fatal ventricular fibrillation so a deeper understanding of this additional layer of self-organized pattern formation would be beneficial to a wide range of applications. One of the most striking differences between pattern-forming systems in physics or chemistry and those in biology is the potential importance of variability. In the former, system components are essentially identical with random fluctuations determining the details of the self-organization process and the resulting patterns. In biology, due to variability, the properties of potentially very few cells can have a driving influence on the resulting asymptotic collective state of the colony. Variability is one means of implementing a few-element control on the collective mode. Regulatory architectures, parameters of signaling cascades, and properties of structure formation processes can be "reverse-engineered" from observed spatiotemporal patterns, as different types of regulation and forms of interactions between the constituents can lead to markedly different correlations. The power of this biology-inspired view of pattern formation lies in building a bridge between two scales: the patterns as a collective state of a very large number of cells on the one hand

  4. Pattern formation and control of spatiotemporal chaos in a reaction diffusion prey–predator system supplying additional food

    International Nuclear Information System (INIS)

    Ghorai, Santu; Poria, Swarup

    2016-01-01

    Spatiotemporal dynamics of a predator–prey system in presence of spatial diffusion is investigated in presence of additional food exists for predators. Conditions for stability of Hopf as well as Turing patterns in a spatial domain are determined by making use of the linear stability analysis. Impact of additional food is clear from these conditions. Numerical simulation results are presented in order to validate the analytical findings. Finally numerical simulations are carried out around the steady state under zero flux boundary conditions. With the help of numerical simulations, the different types of spatial patterns (including stationary spatial pattern, oscillatory pattern, and spatiotemporal chaos) are identified in this diffusive predator–prey system in presence of additional food, depending on the quantity, quality of the additional food and the spatial domain and other parameters of the model. The key observation is that spatiotemporal chaos can be controlled supplying suitable additional food to predator. These investigations may be useful to understand complex spatiotemporal dynamics of population dynamical models in presence of additional food.

  5. Spatio-temporal databases complex motion pattern queries

    CERN Document Server

    Vieira, Marcos R

    2013-01-01

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

  6. Spatiotemporal patterns formed by deformed adhesive in peeling

    International Nuclear Information System (INIS)

    Yamazaki, Yoshihiro; Toda, Akihiko

    2007-01-01

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

  7. Spatiotemporal patterns and predictability of cyberattacks.

    Directory of Open Access Journals (Sweden)

    Yu-Zhong Chen

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

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

    Science.gov (United States)

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

    2016-06-01

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

  9. Spatio-temporal patterns in simple models of marine systems

    Science.gov (United States)

    Feudel, U.; Baurmann, M.; Gross, T.

    2009-04-01

    Spatio-temporal patterns in marine systems are a result of the interaction of population dynamics with physical transport processes. These physical transport processes can be either diffusion processes in marine sediments or in the water column. We study the dynamics of one population of bacteria and its nutrient in in a simplified model of a marine sediments, taking into account that the considered bacteria possess an active as well as an inactive state, where activation is processed by signal molecules. Furthermore the nutrients are transported actively by bioirrigation and passively by diffusion. It is shown that under certain conditions Turing patterns can occur which yield heterogeneous spatial patterns of the species. The influence of bioirrigation on Turing patterns leads to the emergence of ''hot spots``, i.e. localized regions of enhanced bacterial activity. All obtained patterns fit quite well to observed patterns in laboratory experiments. Spatio-temporal patterns appear in a predator-prey model, used to describe plankton dynamics. These patterns appear due to the simultaneous emergence of Turing patterns and oscillations in the species abundance in the neighborhood of a Turing-Hopf bifurcation. We observe a large variety of different patterns where i) stationary heterogeneous patterns (e.g. hot and cold spots) compete with spatio-temporal patterns ii) slowly moving patterns are embedded in an oscillatory background iii) moving fronts and spiral waves appear.

  10. A review and guidance for pattern selection in spatiotemporal system

    Science.gov (United States)

    Wang, Chunni; Ma, Jun

    2018-03-01

    Pattern estimation and selection in media can give important clues to understand the collective response to external stimulus by detecting the observable variables. Both reaction-diffusion systems (RDs) and neuronal networks can be treated as multi-agent systems from molecular level, intrinsic cooperation, competition. An external stimulus or attack can cause collapse of spatial order and distribution, while appropriate noise can enhance the consensus in the spatiotemporal systems. Pattern formation and synchronization stability can bridge isolated oscillators and the network by coupling these nodes with appropriate connection types. As a result, the dynamical behaviors can be detected and discussed by developing different spatial patterns and realizing network synchronization. Indeed, the collective response of network and multi-agent system depends on the local kinetics of nodes and cells. It is better to know the standard bifurcation analysis and stability control schemes before dealing with network problems. In this review, dynamics discussion and synchronization control on low-dimensional systems, pattern formation and synchronization stability on network, wave stability in RDs and neuronal network are summarized. Finally, possible guidance is presented when some physical effects such as polarization field and electromagnetic induction are considered.

  11. On the physical basis of pattern formation in nonlinear systems

    International Nuclear Information System (INIS)

    Sanduloviciu, M.; Lozneanu, E.; Popescu, S.

    2003-01-01

    Spatial, respectively spatiotemporal patterns appear in a gaseous conductor (plasma) when an external constraint produces a local gradient of electron kinetic energy. Under such conditions, collective quantum effects related to the spatial separation of the excitation and ionization cross-sections determine the appearance of adjacent opposite space charges. The state of the resulting space charge configuration depends on the self-enhancement process of positive ions production, which destabilizes the system. Thus, a spatial pattern in the form of a stable double layer appears after self-organization when the above gradient is smaller than that for which the double layer transits into a moving phase (spatiotemporal pattern). The proposed explanation, based on investigations performed on self-organization phenomena observed in gaseous conductors, suggests a new possibility to clarify the challenging problems concerning the actual physical basis of pattern formation in semiconductors

  12. An evaluation of space time cube representation of spatiotemporal patterns.

    Science.gov (United States)

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

    2009-01-01

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

  13. Size-dependent diffusion promotes the emergence of spatiotemporal patterns

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  14. Spatio-temporal patterns of coral recruitment at Vamizi Island ...

    African Journals Online (AJOL)

    Spatio-temporal patterns of coral recruitment at Vamizi Island, Quirimbas Archipelago, Mozambique. ... Spatial and temporal patterns of recruitment of reef corals were assessed for the first time in Mozambique ... AJOL African Journals Online.

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

    Science.gov (United States)

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

    2002-02-01

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

  16. Spongiosa Primary Development: A Biochemical Hypothesis by Turing Patterns Formations

    Directory of Open Access Journals (Sweden)

    Oscar Rodrigo López-Vaca

    2012-01-01

    Full Text Available We propose a biochemical model describing the formation of primary spongiosa architecture through a bioregulatory model by metalloproteinase 13 (MMP13 and vascular endothelial growth factor (VEGF. It is assumed that MMP13 regulates cartilage degradation and the VEGF allows vascularization and advances in the ossification front through the presence of osteoblasts. The coupling of this set of molecules is represented by reaction-diffusion equations with parameters in the Turing space, creating a stable spatiotemporal pattern that leads to the formation of the trabeculae present in the spongy tissue. Experimental evidence has shown that the MMP13 regulates VEGF formation, and it is assumed that VEGF negatively regulates MMP13 formation. Thus, the patterns obtained by ossification may represent the primary spongiosa formation during endochondral ossification. Moreover, for the numerical solution, we used the finite element method with the Newton-Raphson method to approximate partial differential nonlinear equations. Ossification patterns obtained may represent the primary spongiosa formation during endochondral ossification.

  17. The dynamics of visual experience, an EEG study of subjective pattern formation.

    Directory of Open Access Journals (Sweden)

    Mark A Elliott

    Full Text Available BACKGROUND: Since the origin of psychological science a number of studies have reported visual pattern formation in the absence of either physiological stimulation or direct visual-spatial references. Subjective patterns range from simple phosphenes to complex patterns but are highly specific and reported reliably across studies. METHODOLOGY/PRINCIPAL FINDINGS: Using independent-component analysis (ICA we report a reduction in amplitude variance consistent with subjective-pattern formation in ventral posterior areas of the electroencephalogram (EEG. The EEG exhibits significantly increased power at delta/theta and gamma-frequencies (point and circle patterns or a series of high-frequency harmonics of a delta oscillation (spiral patterns. CONCLUSIONS/SIGNIFICANCE: Subjective-pattern formation may be described in a way entirely consistent with identical pattern formation in fluids or granular flows. In this manner, we propose subjective-pattern structure to be represented within a spatio-temporal lattice of harmonic oscillations which bind topographically organized visual-neuronal assemblies by virtue of low frequency modulation.

  18. Spatiotemporal Patterns in a Ratio-Dependent Food Chain Model with Reaction-Diffusion

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2014-01-01

    Full Text Available Predator-prey models describe biological phenomena of pursuit-evasion interaction. And this interaction exists widely in the world for the necessary energy supplement of species. In this paper, we have investigated a ratio-dependent spatially extended food chain model. Based on the bifurcation analysis (Hopf and Turing, we give the spatial pattern formation via numerical simulation, that is, the evolution process of the system near the coexistence equilibrium point (u2*,v2*,w2*, and find that the model dynamics exhibits complex pattern replication. For fixed parameters, on increasing the control parameter c1, the sequence “holes → holes-stripe mixtures → stripes → spots-stripe mixtures → spots” pattern is observed. And in the case of pure Hopf instability, the model exhibits chaotic wave pattern replication. Furthermore, we consider the pattern formation in the case of which the top predator is extinct, that is, the evolution process of the system near the equilibrium point (u1*,v1*,0, and find that the model dynamics exhibits stripes-spots pattern replication. Our results show that reaction-diffusion model is an appropriate tool for investigating fundamental mechanism of complex spatiotemporal dynamics. It will be useful for studying the dynamic complexity of ecosystems.

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

    Science.gov (United States)

    Béjar, J.; Álvarez, S.; García, D.; Gómez, I.; Oliva, L.; Tejeda, A.; Vázquez-Salceda, J.

    2016-03-01

    Location-based social networks (LBSNs) such as Twitter or Instagram are a good source for user spatio-temporal behaviour. These networks collect data from users in such a way that they can be seen as a set of collective and distributed sensors of a geographical area. A low rate sampling of user's location information can be obtained during large intervals of time that can be used to discover complex patterns, including mobility profiles, points of interest or unusual events. These patterns can be used as the elements of a knowledge base for different applications in different domains such as mobility route planning, touristic recommendation systems or city planning. The aim of this paper is twofold, first to analyse the frequent spatio-temporal patterns that users share when living and visiting a city. This behaviour is studied by means of frequent itemsets algorithms in order to establish some associations among visits that can be interpreted as interesting routes or spatio-temporal connections. Second, to analyse how the spatio-temporal behaviour of a large number of users can be segmented in different profiles. These behavioural profiles are obtained by means of clustering algorithms that show the different patterns of behaviour of visitors and citizens. The data analysed were obtained from the public data feeds of Twitter and Instagram within an area surrounding the cities of Barcelona and Milan for a period of several months. The analysis of these data shows that these kinds of algorithms can be successfully applied to data from any city (or general area) to discover useful patterns that can be interpreted on terms of singular places and areas and their temporal relationships.

  20. Spatio-temporal flow maps for visualizing movement and contact patterns

    Directory of Open Access Journals (Sweden)

    Bing Ni

    2017-03-01

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

  1. Boundary-induced pattern formation from uniform temporal oscillation

    Science.gov (United States)

    Kohsokabe, Takahiro; Kaneko, Kunihiko

    2018-04-01

    Pattern dynamics triggered by fixing a boundary is investigated. By considering a reaction-diffusion equation that has a unique spatially uniform and limit cycle attractor under a periodic or Neumann boundary condition, and then by choosing a fixed boundary condition, we found three novel phases depending on the ratio of diffusion constants of activator to inhibitor: transformation of temporally periodic oscillation into a spatially periodic fixed pattern, travelling wave emitted from the boundary, and aperiodic spatiotemporal dynamics. The transformation into a fixed, periodic pattern is analyzed by crossing of local nullclines at each spatial point, shifted by diffusion terms, as is analyzed by using recursive equations, to obtain the spatial pattern as an attractor. The generality of the boundary-induced pattern formation as well as its relevance to biological morphogenesis is discussed.

  2. Pattern control and suppression of spatiotemporal chaos using geometrical resonance

    International Nuclear Information System (INIS)

    Gonzalez, J.A.; Bellorin, A.; Reyes, L.I.; Vasquez, C.; Guerrero, L.E.

    2004-01-01

    We generalize the concept of geometrical resonance to perturbed sine-Gordon, Nonlinear Schroedinger, phi (cursive,open) Greek 4 , and Complex Ginzburg-Landau equations. Using this theory we can control different dynamical patterns. For instance, we can stabilize breathers and oscillatory patterns of large amplitudes successfully avoiding chaos. On the other hand, this method can be used to suppress spatiotemporal chaos and turbulence in systems where these phenomena are already present. This method can be generalized to even more general spatiotemporal systems. A short report of some of our results has been published in [Europhys. Lett. 64 (2003) 743

  3. Spatiotemporal matrix image formation for programmable ultrasound scanners

    Science.gov (United States)

    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.

  4. A MapReduce-Based Parallel Frequent Pattern Growth Algorithm for Spatiotemporal Association Analysis of Mobile Trajectory Big Data

    Directory of Open Access Journals (Sweden)

    Dawen Xia

    2018-01-01

    Full Text Available Frequent pattern mining is an effective approach for spatiotemporal association analysis of mobile trajectory big data in data-driven intelligent transportation systems. While existing parallel algorithms have been successfully applied to frequent pattern mining of large-scale trajectory data, two major challenges are how to overcome the inherent defects of Hadoop to cope with taxi trajectory big data including massive small files and how to discover the implicitly spatiotemporal frequent patterns with MapReduce. To conquer these challenges, this paper presents a MapReduce-based Parallel Frequent Pattern growth (MR-PFP algorithm to analyze the spatiotemporal characteristics of taxi operating using large-scale taxi trajectories with massive small file processing strategies on a Hadoop platform. More specifically, we first implement three methods, that is, Hadoop Archives (HAR, CombineFileInputFormat (CFIF, and Sequence Files (SF, to overcome the existing defects of Hadoop and then propose two strategies based on their performance evaluations. Next, we incorporate SF into Frequent Pattern growth (FP-growth algorithm and then implement the optimized FP-growth algorithm on a MapReduce framework. Finally, we analyze the characteristics of taxi operating in both spatial and temporal dimensions by MR-PFP in parallel. The results demonstrate that MR-PFP is superior to existing Parallel FP-growth (PFP algorithm in efficiency and scalability.

  5. Spatiotemporal throughfall patterns beneath an urban tree row

    Science.gov (United States)

    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.

  6. A model for optimizing file access patterns using spatio-temporal parallelism

    Energy Technology Data Exchange (ETDEWEB)

    Boonthanome, Nouanesengsy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Patchett, John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Geveci, Berk [Kitware Inc., Clifton Park, NY (United States); Ahrens, James [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bauer, Andy [Kitware Inc., Clifton Park, NY (United States); Chaudhary, Aashish [Kitware Inc., Clifton Park, NY (United States); Miller, Ross G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shipman, Galen M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2013-01-01

    For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible file access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.

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

    International Nuclear Information System (INIS)

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

    2001-01-01

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

  8. Pattern formation in diffusive excitable systems under magnetic flow effects

    Science.gov (United States)

    Mvogo, Alain; Takembo, Clovis N.; Ekobena Fouda, H. P.; Kofané, Timoléon C.

    2017-07-01

    We study the spatiotemporal formation of patterns in a diffusive FitzHugh-Nagumo network where the effect of electromagnetic induction has been introduced in the standard mathematical model by using magnetic flux, and the modulation of magnetic flux on membrane potential is realized by using memristor coupling. We use the multi-scale expansion to show that the system equations can be reduced to a single differential-difference nonlinear equation. The linear stability analysis is performed and discussed with emphasis on the impact of magnetic flux. It is observed that the effect of memristor coupling importantly modifies the features of modulational instability. Our analytical results are supported by the numerical experiments, which reveal that the improved model can lead to nonlinear quasi-periodic spatiotemporal patterns with some features of synchronization. It is observed also the generation of pulses and rhythmics behaviors like breathing or swimming which are important in brain researches.

  9. Energy prediction using spatiotemporal pattern networks

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-11-01

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

  10. Mining Spatiotemporal Patterns of the Elder's Daily Movement

    Science.gov (United States)

    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.

  11. Nonmonotonic Behavior of Supermultiplet Pattern Formation in a Noisy Lotka-Volterra System

    International Nuclear Information System (INIS)

    Fiasconaro, A.; Valenti, D.; Spagnolo, B.

    2004-01-01

    The noise-induced pattern formation in a population dynamical model of three interacting species in the coexistence regime is investigated. A coupled map lattice of Lotka-Volterra equations in the presence of multiplicative noise is used to analyze the spatiotemporal evolution. The spatial correlation of the species concentration as a function of time and of the noise intensity is investigated. A nonmonotonic behavior of the area of the patterns as a function of both noise intensity and evolution time is found. (author)

  12. Exploring Spatiotemporal Patterns of Long-Distance Taxi Rides in Shanghai

    Directory of Open Access Journals (Sweden)

    Hangbin Wu

    2017-11-01

    Full Text Available Floating Car Data (FCD has been analyzed for various purposes in past years. However, limited research about the behaviors of taking long-distance taxi rides has been made available. In this paper, we used data from over 12,000 taxis during a six-month period in Shanghai to analyze the spatiotemporal patterns of long-distance taxi trips. We investigated these spatiotemporal patterns by comparing them with metro usage in Shanghai, in order to determine the extent and how the suburban trains divert the passenger flow from taxis. The results identified 12 pick-up and six drop-off hotspots in Shanghai. Overall, the pick-up locations were relatively more concentrated than the drop-off locations. Temporal patterns were also revealed. Passengers on long-distance taxi rides were observed to avoid the rush hours on the street as their first priority and tried to avoid the inconvenience of interchanges on the metro lines as their second priority.

  13. Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs.

    Science.gov (United States)

    Lee, Sungjun; Lim, Junseok; Park, Jonghun; Kim, Kwanho

    2016-01-23

    Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user's next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP) pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user's past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user's next places than the previous approaches considered in most cases.

  14. Spatio-Temporal Patterns in Colonies of Rod-Shaped Bacteria

    Science.gov (United States)

    Kitsunezaki, S.

    In incubation experiments of bacterial colonies of Proteus Mirabilis, macroscopic spatio-temporal patterns, such as turbulent and unidirectional spiral patterns, appear in colonies. Considering only kinetic propeties of rod-shaped bacteria, we propose a phenomenological model for the directional and positional distributions. As the average density increases, homogeneous states bifurcate sub-critically into nonuniform states exhibiting localized collective motion, and spiral patterns appear for sufficiently large density. These patterns result from interactions between the local bacteria densities and the order parameter representing collective motion. Our model can be described by reduced equations using a perturbative method for large density. The unidirectionality of sprial rotation is also discussed.

  15. Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs

    Directory of Open Access Journals (Sweden)

    Sungjun Lee

    2016-01-01

    Full Text Available Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user’s next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user’s past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user’s next places than the previous approaches considered in most cases.

  16. Spatiotemporal distribution patterns of forest fires in northern Mexico

    Science.gov (United States)

    Gustavo Pérez-Verdin; M. A. Márquez-Linares; A. Cortes-Ortiz; M. Salmerón-Macias

    2013-01-01

    Using the 2000-2011 CONAFOR databases, a spatiotemporal analysis of the occurrence of forest fires in Durango, one of the most affected States in Mexico, was conducted. The Moran's index was used to determine a spatial distribution pattern; also, an analysis of seasonal and temporal autocorrelation of the data collected was completed. The geographically weighted...

  17. Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics Approach

    Directory of Open Access Journals (Sweden)

    Junjun Yin

    2016-10-01

    Full Text Available Understanding human mobility patterns is of great importance for urban planning, traffic management, and even marketing campaign. However, the capability of capturing detailed human movements with fine-grained spatial and temporal granularity is still limited. In this study, we extracted high-resolution mobility data from a collection of over 1.3 billion geo-located Twitter messages. Regarding the concerns of infringement on individual privacy, such as the mobile phone call records with restricted access, the dataset is collected from publicly accessible Twitter data streams. In this paper, we employed a visual-analytics approach to studying multi-scale spatiotemporal Twitter user mobility patterns in the contiguous United States during the year 2014. Our approach included a scalable visual-analytics framework to deliver efficiency and scalability in filtering large volume of geo-located tweets, modeling and extracting Twitter user movements, generating space-time user trajectories, and summarizing multi-scale spatiotemporal user mobility patterns. We performed a set of statistical analysis to understand Twitter user mobility patterns across multi-level spatial scales and temporal ranges. In particular, Twitter user mobility patterns measured by the displacements and radius of gyrations of individuals revealed multi-scale or multi-modal Twitter user mobility patterns. By further studying such mobility patterns in different temporal ranges, we identified both consistency and seasonal fluctuations regarding the distance decay effects in the corresponding mobility patterns. At the same time, our approach provides a geo-visualization unit with an interactive 3D virtual globe web mapping interface for exploratory geo-visual analytics of the multi-level spatiotemporal Twitter user movements.

  18. Spatiotemporal chaos involving wave instability.

    Science.gov (United States)

    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.

  19. Spatio-temporal cerebral blood flow perfusion patterns in cortical spreading depression

    Science.gov (United States)

    Verisokin, Andrey Yu.; Verveyko, Darya V.; Postnov, Dmitry E.

    2017-04-01

    Cortical spreading depression (CSD) is an example of one of the most common abnormalities in biophysical brain functioning. Despite the fact that there are many mathematical models describing the cortical spreading depression (CSD), most of them do not take into consideration the role of redistribution of cerebral blood flow (CBF), that results in the formation of spatio-temporal patterns. The paper presents a mathematical model, which successfully explains the CBD role in the CSD process. Numerical study of this model has revealed the formation of stationary dissipative structures, visually analogous to Turing structures. However, the mechanism of their formation is not diffusion. We show these structures occur due to another type of spatial coupling, that is related to tissue perfusion rate. The proposed model predicts that at similar state of neurons the distribution of blood flow and oxygenation may by different. Currently, this effect is not taken into account when the Blood oxygen-level dependent (BOLD) contrast imaging used in functional magnetic resonance imaging (fMRI). Thus, the diagnosis on the BOLD signal can be ambiguous. We believe that our results can be used in the future for a more correct interpretation of the data obtained with fMRI, NIRS and other similar methods for research of the brain activity.

  20. Spatiotemporal Data Mining: A Computational Perspective

    Directory of Open Access Journals (Sweden)

    Shashi Shekhar

    2015-10-01

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

  1. Pattern selection and spatio-temporal transition to chaos in Ginzburg-Landau equation

    Energy Technology Data Exchange (ETDEWEB)

    Nozaki, K; Bekki, N

    1983-07-01

    It is shown that a modulationally unstable pattern is selected and propagates into an initially unstable motionless state in the 1-D generalized Ginzburg-Landau equation. A further spatio-temporal transition occurs with a sharp interface from the selected unstable pattern to a stabilized pattern or a chaotic state. The distinct transition makes a coherent structure to coexist with a chaotic state. 12 refs., 4 figs.

  2. Modeling how shark and dolphin skin patterns control transitional wall-turbulence vorticity patterns using spatiotemporal phase reset mechanisms.

    Science.gov (United States)

    Bandyopadhyay, Promode R; Hellum, Aren M

    2014-10-23

    Many slow-moving biological systems like seashells and zebrafish that do not contend with wall turbulence have somewhat organized pigmentation patterns flush with their outer surfaces that are formed by underlying autonomous reaction-diffusion (RD) mechanisms. In contrast, sharks and dolphins contend with wall turbulence, are fast swimmers, and have more organized skin patterns that are proud and sometimes vibrate. A nonlinear spatiotemporal analytical model is not available that explains the mechanism underlying control of flow with such proud patterns, despite the fact that shark and dolphin skins are major targets of reverse engineering mechanisms of drag and noise reduction. Comparable to RD, a minimal self-regulation model is given for wall turbulence regeneration in the transitional regime--laterally coupled, diffusively--which, although restricted to pre-breakdown durations and to a plane close and parallel to the wall, correctly reproduces many experimentally observed spatiotemporal organizations of vorticity in both laminar-to-turbulence transitioning and very low Reynolds number but turbulent regions. We further show that the onset of vorticity disorganization is delayed if the skin organization is treated as a spatiotemporal template of olivo-cerebellar phase reset mechanism. The model shows that the adaptation mechanisms of sharks and dolphins to their fluid environment have much in common.

  3. Formation mechanism of dot-line square superlattice pattern in dielectric barrier discharge

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Weibo; Dong, Lifang, E-mail: donglfhbu@163.com, E-mail: pyy1616@163.com; Wang, Yongjie; Zhang, Xinpu [College of Physics Science and Technology, Hebei University, Baoding 071002 (China); College of Quality and Technical Supervision, Hebei University, Baoding 071002 (China); Pan, Yuyang, E-mail: donglfhbu@163.com, E-mail: pyy1616@163.com [College of Quality and Technical Supervision, Hebei University, Baoding 071002 (China)

    2014-11-15

    We investigate the formation mechanism of the dot-line square superlattice pattern (DLSSP) in dielectric barrier discharge. The spatio-temporal structure studied by using the intensified-charge coupled device camera shows that the DLSSP is an interleaving of three different subpatterns in one half voltage cycle. The dot square lattice discharges first and, then, the two kinds of line square lattices, which form square grid structures discharge twice. When the gas pressure is varied, DLSSP can transform from square superlattice pattern (SSP). The spectral line profile method is used to compare the electron densities, which represent the amounts of surface charges qualitatively. It is found that the amount of surface charges accumulated by the first discharge of DLSSP is less than that of SSP, leading to a bigger discharge area of the following discharge (lines of DLSSP instead of halos of SSP). The spatial distribution of the electric field of the surface charges is simulated to explain the formation of DLSSP. This paper may provide a deeper understanding for the formation mechanism of complex superlattice patterns in DBD.

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

    Science.gov (United States)

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

    2011-01-01

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

  5. Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

    Directory of Open Access Journals (Sweden)

    Qiang Yu

    Full Text Available A new learning rule (Precise-Spike-Driven (PSD Synaptic Plasticity is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

  6. Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

    Science.gov (United States)

    Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

    2013-01-01

    A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

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

    Science.gov (United States)

    Khorram, Saeed; Ergil, Mustafa

    2018-03-01

    A measure of uncertainties, entropy has been employed in such different applications as coastal engineering probability inferences. Entropy sediment transport integration theories present novel visions in coastal analyses/modeling the application and development of which are still far-reaching. Effort has been made in the present paper to propose a method that needs an entropy-power index for spatio-temporal patterns analyses. Results have shown that the index is suitable for marine/hydrological ecosystem components analyses based on a beach area case study. The method makes use of six Makran Coastal monthly data (1970-2015) and studies variables such as spatio-temporal patterns, LSTR (long-shore sediment transport rate), wind speed, and wave height all of which are time-dependent and play considerable roles in terrestrial coastal investigations; the mentioned variables show meaningful spatio-temporal variability most of the time, but explanation of their combined performance is not easy. Accordingly, the use of an entropy-power index can show considerable signals that facilitate the evaluation of water resources and will provide an insight regarding hydrological parameters' interactions at scales as large as beach areas. Results have revealed that an STDDPI (entropy based spatio-temporal disorder dynamics power index) can simulate wave, long-shore sediment transport rate, and wind when granulometry, concentration, and flow conditions vary.

  8. Changing and Differentiated Urban Landscape in China: Spatiotemporal Patterns and Driving Forces.

    Science.gov (United States)

    Fang, Chuanglin; Li, Guangdong; Wang, Shaojian

    2016-03-01

    Urban landscape spatiotemporal change patterns and their driving mechanisms in China are poorly understood at the national level. Here we used remote sensing data, landscape metrics, and a spatial econometric model to characterize the spatiotemporal patterns of urban landscape change and investigate its driving forces in China between 1990 and 2005. The results showed that the urban landscape pattern has experienced drastic changes over the past 15 years. Total urban area has expanded approximately 1.61 times, with a 2.98% annual urban-growth rate. Compared to previous single-city studies, although urban areas are expanding rapidly, the overall fragmentation of the urban landscape is decreasing and is more irregular and complex at the national level. We also found a stair-stepping, urban-landscape changing pattern among eastern, central, and western counties. In addition, administrative level, urban size, and hierarchy have effects on the urban landscape pattern. We also found that a combination of landscape metrics can be used to supplement our understanding of the pattern of urbanization. The changes in these metrics are correlated with geographical indicators, socioeconomic factors, infrastructure variables, administrative level factors, policy factors, and historical factors. Our results indicate that the top priority should be strengthening the management of urban planning. A compact and congregate urban landscape may be a good choice of pattern for urban development in China.

  9. Pattern formations in chaotic spatio-temporal systems

    Indian Academy of Sciences (India)

    5Beijing–Hong Kong–Singapore Joint Center of Nonlinear and Complex Systems, ... For theoretical studies most previous work has focused on pattern .... Lyapunov exponents from arbitrary initial conditions, and the plots look rather.

  10. Spatiotemporal Propagation of the Cortical Atrophy: Population and Individual Patterns

    Directory of Open Access Journals (Sweden)

    Igor Koval

    2018-05-01

    Full Text Available Repeated failures in clinical trials for Alzheimer’s disease (AD have raised a strong interest for the prodromal phase of the disease. A better understanding of the brain alterations during this early phase is crucial to diagnose patients sooner, to estimate an accurate disease stage, and to give a reliable prognosis. According to recent evidence, structural alterations in the brain are likely to be sensitive markers of the disease progression. Neuronal loss translates in specific spatiotemporal patterns of cortical atrophy, starting in the enthorinal cortex and spreading over other cortical regions according to specific propagation pathways. We developed a digital model of the cortical atrophy in the left hemisphere from prodromal to diseased phases, which is built on the temporal alignment and combination of several short-term observation data to reconstruct the long-term history of the disease. The model not only provides a description of the spatiotemporal patterns of cortical atrophy at the group level but also shows the variability of these patterns at the individual level in terms of difference in propagation pathways, speed of propagation, and age at propagation onset. Longitudinal MRI datasets of patients with mild cognitive impairments who converted to AD are used to reconstruct the cortical atrophy propagation across all disease stages. Each observation is considered as a signal spatially distributed on a network, such as the cortical mesh, each cortex location being associated to a node. We consider how the temporal profile of the signal varies across the network nodes. We introduce a statistical mixed-effect model to describe the evolution of the cortex alterations. To ensure a spatiotemporal smooth propagation of the alterations, we introduce a constrain on the propagation signal in the model such that neighboring nodes have similar profiles of the signal changes. Our generative model enables the reconstruction of personalized

  11. Laser-induced hydrodynamic instability and pattern formation in metallic nanofilms

    Science.gov (United States)

    Sureshkumar, R.; Trice, J.; Favazza, C.; Kalyanaraman, R.

    2007-11-01

    Cost effective methodologies for the robust generation of nanoscale patterns in thin films and at interfaces are crucial in photonic, opto-electronic and solar energy harvesting applications. When ultrathin metal films are exposed to a series of short (ns) laser pulses, spontaneous pattern formation results with spatio-temporal scales that depend on the film height and thermo-physical properties of the film/substrate bilayer. Various self-organization mechanisms have been identified, including a dewetting instability due to a competition between surface tension and dispersion forces, and intrinsic and/or extrinsic thermocapillary effects. We will discuss these mechanisms as well as the evolution of surface perturbations which have been explored using experiments, linear stability analysis and nonlinear dynamical simulations (Trice et al. Phys. Rev. B, 75, 235439 (2007); Favazza et al. Appl. Phys. Lett., 91, 043105 (2007); 88, 153118 (2006)).

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

    Directory of Open Access Journals (Sweden)

    Zhiqu Liu

    2017-11-01

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

  13. Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors

    Science.gov (United States)

    Schöll, Eckehard

    2005-08-01

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

  14. Pattern formation and three-dimensional instability in rotating flows

    Science.gov (United States)

    Christensen, Erik A.; Aubry, Nadine; Sorensen, Jens N.

    1997-03-01

    A fluid flow enclosed in a cylindrical container where fluid motion is created by the rotation of one end wall as a centrifugal fan is studied. Direct numerical simulations and spatio-temporal analysis have been performed in the early transition scenario, which includes a steady-unsteady transition and a breakdown of axisymmetric to three-dimensional flow behavior. In the early unsteady regime of the flow, the central vortex undergoes a vertical beating motion, accompanied by axisymmetric spikes formation on the edge of the breakdown bubble. As traveling waves, the spikes move along the central vortex core toward the rotating end-wall. As the Reynolds number is increased further, the flow undergoes a three-dimensional instability. The influence of the latter on the previous patterns is studied.

  15. Characterizing the Spatio-Temporal Pattern of Land Surface Temperature through Time Series Clustering: Based on the Latent Pattern and Morphology

    Directory of Open Access Journals (Sweden)

    Huimin Liu

    2018-04-01

    Full Text Available Land Surface Temperature (LST is a critical component to understand the impact of urbanization on the urban thermal environment. Previous studies were inclined to apply only one snapshot to analyze the pattern and dynamics of LST without considering the non-stationarity in the temporal domain, or focus on the diurnal, seasonal, and annual pattern analysis of LST which has limited support for the understanding of how LST varies with the advancing of urbanization. This paper presents a workflow to extract the spatio-temporal pattern of LST through time series clustering by focusing on the LST of Wuhan, China, from 2002 to 2017 with a 3-year time interval with 8-day MODerate-resolution Imaging Spectroradiometer (MODIS satellite image products. The Latent pattern of LST (LLST generated by non-parametric Multi-Task Gaussian Process Modeling (MTGP and the Multi-Scale Shape Index (MSSI which characterizes the morphology of LLST are coupled for pattern recognition. Specifically, spatio-temporal patterns are discovered after the extraction of spatial patterns conducted by the incorporation of k -means and the Back-Propagation neural networks (BP-Net. The spatial patterns of the 6 years form a basic understanding about the corresponding temporal variances. For spatio-temporal pattern recognition, LLSTs and MSSIs of the 6 years are regarded as geo-referenced time series. Multiple algorithms including traditional k -means with Euclidean Distance (ED, shape-based k -means with the constrained Dynamic Time Warping ( c DTW distance measure, and the Dynamic Time Warping Barycenter Averaging (DBA centroid computation method ( k - c DBA and k -shape are applied. Ten external indexes are employed to evaluate the performance of the three algorithms and reveal k - c DBA as the optimal time series clustering algorithm for our study. The study area is divided into 17 geographical time series clusters which respectively illustrate heterogeneous temporal dynamics of LST

  16. Training spiking neural networks to associate spatio-temporal input-output spike patterns

    OpenAIRE

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

    2013-01-01

    In a previous work (Mohemmed et al., Method for training a spiking neuron to associate input–output spike trains) [1] we have proposed a supervised learning algorithm based on temporal coding to train a spiking neuron to associate input spatiotemporal spike patterns to desired output spike patterns. The algorithm is based on the conversion of spike trains into analogue signals and the application of the Widrow–Hoff learning rule. In this paper we present a mathematical formulation of the prop...

  17. Patterns of urban violent injury: a spatio-temporal analysis.

    Directory of Open Access Journals (Sweden)

    Michael Cusimano

    2010-01-01

    Full Text Available Injury related to violent acts is a problem in every society. Although some authors have examined the geography of violent crime, few have focused on the spatio-temporal patterns of violent injury and none have used an ambulance dataset to explore the spatial characteristics of injury. The purpose of this study was to describe the combined spatial and temporal characteristics of violent injury in a large urban centre.Using a geomatics framework and geographic information systems software, we studied 4,587 ambulance dispatches and 10,693 emergency room admissions for violent injury occurrences among adults (aged 18-64 in Toronto, Canada, during 2002 and 2004, using population-based datasets. We created kernel density and choropleth maps for 24-hour periods and four-hour daily time periods and compared location of ambulance dispatches and patient residences with local land use and socioeconomic characteristics. We used multivariate regressions to control for confounding factors. We found the locations of violent injury and the residence locations of those injured were both closely related to each other and clearly clustered in certain parts of the city characterised by high numbers of bars, social housing units, and homeless shelters, as well as lower household incomes. The night and early morning showed a distinctive peak in injuries and a shift in the location of injuries to a "nightlife" district. The locational pattern of patient residences remained unchanged during those times.Our results demonstrate that there is a distinctive spatio-temporal pattern in violent injury reflected in the ambulance data. People injured in this urban centre more commonly live in areas of social deprivation. During the day, locations of injury and locations of residences are similar. However, later at night, the injury location of highest density shifts to a "nightlife" district, whereas the residence locations of those most at risk of injury do not change.

  18. Phase defects and spatiotemporal disorder in traveling-wave convection patterns

    International Nuclear Information System (INIS)

    La Porta, A.; Surko, C.M.

    1997-01-01

    Spatiotemporal disorder is studied in traveling-wave convection in ethanol-water mixtures. Spectral measures of disorder, linear correlation functions, and mutual information are used to characterize the patterns, and are found to give a weak indication of the level of disorder. The calculation of the complex order parameter for experimental patterns is described. It is found that the ordering of the patterns is accompanied by a dramatic change in the topological structure of the order parameter. Specific arrangements of defects are found to be associated with the elements of traveling-wave patterns, and the net charge and total number of defects is introduced as a measure of disorder in the patterns. The coarsening of the patterns is marked by an accumulation of net charge and a dramatic decrease in the number of defects. The physical significance of the defects is discussed, and it is shown that the phase velocity of the waves is lower in the vicinity of the defects. The defect-defect correlation functions are calculated for the convection patterns. It is shown that the ordering of the patterns is closely related to the apparent defect-defect interactions. copyright 1997 The American Physical Society

  19. Real-time nonlinear feedback control of pattern formation in (bio)chemical reaction-diffusion processes: a model study.

    Science.gov (United States)

    Brandt-Pollmann, U; Lebiedz, D; Diehl, M; Sager, S; Schlöder, J

    2005-09-01

    Theoretical and experimental studies related to manipulation of pattern formation in self-organizing reaction-diffusion processes by appropriate control stimuli become increasingly important both in chemical engineering and cellular biochemistry. In a model study, we demonstrate here exemplarily the application of an efficient nonlinear model predictive control (NMPC) algorithm to real-time optimal feedback control of pattern formation in a bacterial chemotaxis system modeled by nonlinear partial differential equations. The corresponding drift-diffusion model type is representative for many (bio)chemical systems involving nonlinear reaction dynamics and nonlinear diffusion. We show how the computed optimal feedback control strategy exploits the system inherent physical property of wave propagation to achieve desired control aims. We discuss various applications of our approach to optimal control of spatiotemporal dynamics.

  20. Spatiotemporal chaos in coupled logistic maps

    International Nuclear Information System (INIS)

    Varella Guedes, Andre; Amorim Savi, Marcelo

    2010-01-01

    The objective of this work is to investigate the spatiotemporal dynamics of coupled logistic maps. These maps are prototypes of high-dimensional dynamical systems and have been used to describe the evolution and pattern formation in different systems. Here, the logistic map lattice is coupled by a power law and, therefore, each map is influenced by other maps in its neighborhood. The Kolmogorov-Sinai entropy density is employed to quantify the complexity of system behavior, permitting a general qualitative understanding of different aspects of system dynamics. Three kinds of boundary conditions are treated and the influence of initial conditions is also of concern. Non-homogeneous maps are investigated, showing interesting aspects of spatiotemporal dynamics. The idea is to analyze the spatial interaction between two qualitative different types of behavior from a grid that is split into two parts. Numerical simulations show what types of conditions present a greater tendency to develop chaotic, periodic and synchronized responses. It should be highlighted that non-homogeneous grids have situations where a chaotic pattern can emerge from two periodic responses and also situations where a periodic pattern can emerge from chaos.

  1. Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts

    International Nuclear Information System (INIS)

    Fonseca, Jimeno A.; Schlueter, Arno

    2015-01-01

    Highlights: • A model to describe spatiotemporal building energy demand patterns was developed. • The model integrates existing methods in urban and energy planning domains. • The model is useful to analyze energy efficiency strategies in neighborhoods. • Applicability in educational, urban and energy planning practices was found. - Abstract: We introduce an integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts. The model addresses the need for a comprehensive method to identify present and potential states of building energy consumption in the context of urban transformation. The focus lies on determining the spatiotemporal variability of energy services in both standing and future buildings in the residential, commercial and industrial sectors. This detailed characterization facilitates the assessment of potential energy efficiency measures at the neighborhood and city district scales. In a novel approach we integrated existing methods in urban and energy planning domains such as spatial analysis, dynamic building energy modeling and energy mapping to provide a comprehensive, multi-scale and multi-dimensional model of analysis. The model is part of a geographic information system (GIS), which serves as a platform for the allocation and future dissemination of spatiotemporal data. The model is validated against measured data and a peer model for a city district in Switzerland. In this context, we present practical applications in the analysis of energy efficiency measures in buildings and urban zoning. We furthermore discuss potential applications in educational, urban and energy planning practices

  2. Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago.

    Directory of Open Access Journals (Sweden)

    Xiaolu Zhou

    Full Text Available The growing number of bike sharing systems (BSS in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities.

  3. Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago.

    Science.gov (United States)

    Zhou, Xiaolu

    2015-01-01

    The growing number of bike sharing systems (BSS) in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities.

  4. Neural avalanches at the critical point between replay and non-replay of spatiotemporal patterns.

    Directory of Open Access Journals (Sweden)

    Silvia Scarpetta

    Full Text Available We model spontaneous cortical activity with a network of coupled spiking units, in which multiple spatio-temporal patterns are stored as dynamical attractors. We introduce an order parameter, which measures the overlap (similarity between the activity of the network and the stored patterns. We find that, depending on the excitability of the network, different working regimes are possible. For high excitability, the dynamical attractors are stable, and a collective activity that replays one of the stored patterns emerges spontaneously, while for low excitability, no replay is induced. Between these two regimes, there is a critical region in which the dynamical attractors are unstable, and intermittent short replays are induced by noise. At the critical spiking threshold, the order parameter goes from zero to one, and its fluctuations are maximized, as expected for a phase transition (and as observed in recent experimental results in the brain. Notably, in this critical region, the avalanche size and duration distributions follow power laws. Critical exponents are consistent with a scaling relationship observed recently in neural avalanches measurements. In conclusion, our simple model suggests that avalanche power laws in cortical spontaneous activity may be the effect of a network at the critical point between the replay and non-replay of spatio-temporal patterns.

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

    Science.gov (United States)

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

    2014-10-01

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

  6. Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

    Directory of Open Access Journals (Sweden)

    Jonathan Cannon

    2015-11-01

    Full Text Available Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

  7. Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

    Science.gov (United States)

    Cannon, Jonathan; Kopell, Nancy; Gardner, Timothy; Markowitz, Jeffrey

    2015-11-01

    Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

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

    Science.gov (United States)

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

    2017-12-01

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

  9. Analyzing Local Spatio-Temporal Patterns of Police Calls-for-Service Using Bayesian Integrated Nested Laplace Approximation

    Directory of Open Access Journals (Sweden)

    Hui Luan

    2016-09-01

    Full Text Available This research investigates spatio-temporal patterns of police calls-for-service in the Region of Waterloo, Canada, at a fine spatial and temporal resolution. Modeling was implemented via Bayesian Integrated Nested Laplace Approximation (INLA. Temporal patterns for two-hour time periods, spatial patterns at the small-area scale, and space-time interaction (i.e., unusual departures from overall spatial and temporal patterns were estimated. Temporally, calls-for-service were found to be lowest in the early morning (02:00–03:59 and highest in the evening (20:00–21:59, while high levels of calls-for-service were spatially located in central business areas and in areas characterized by major roadways, universities, and shopping centres. Space-time interaction was observed to be geographically dispersed during daytime hours but concentrated in central business areas during evening hours. Interpreted through the routine activity theory, results are discussed with respect to law enforcement resource demand and allocation, and the advantages of modeling spatio-temporal datasets with Bayesian INLA methods are highlighted.

  10. A simple spatiotemporal chaotic Lotka-Volterra model

    International Nuclear Information System (INIS)

    Sprott, J.C.; Wildenberg, J.C.; Azizi, Yousef

    2005-01-01

    A mathematically simple example of a high-dimensional (many-species) Lotka-Volterra model that exhibits spatiotemporal chaos in one spatial dimension is described. The model consists of a closed ring of identical agents, each competing for fixed finite resources with two of its four nearest neighbors. The model is prototypical of more complicated models in its quasiperiodic route to chaos (including attracting 3-tori), bifurcations, spontaneous symmetry breaking, and spatial pattern formation

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  12. Spatiotemporal Patterns of Urbanization in a Developed Region of Eastern Coastal China

    OpenAIRE

    Li, Jiadan; Deng, Jinsong; Wang, Ke; Li, Jun; Huang, Tao; Lin, Yi; Yu, Haiyan

    2014-01-01

    This study presents a practical methodology to monitor the spatiotemporal characteristics of urban expansion in response to rapid urbanization at the provincial scale by integrating remote sensing, urban built-up area boundaries, spatial metrics and spatial regression. Sixty-seven cities were investigated to examine the differences of urbanization intensity, urbanization patterns and urban land use efficiency in conjunction with the identification of socio-economic indicators and planning str...

  13. Nonlinear pattern formation in bone growth and architecture

    Directory of Open Access Journals (Sweden)

    Phil eSalmon

    2015-01-01

    Full Text Available The 3D morphology of bone arises through adaptation to its required engineering performance. Genetically and adaptively bone travels along a complex spatio-temporal trajectory to acquire optimal architecture. On a cellular, micro-anatomical scale, what mechanisms coordinate the activity of osteoblasts and osteoclasts to produce complex and efficient bone architectures? One mechanism is examined here – chaotic nonlinear pattern formation (NPF – which underlies in a unifying way natural structures as disparate as trabecular bone, swarms of birds flying, island formation, fluid turbulence and others. At the heart of NPF is the fact that simple rules operating between interacting elements, and Turing-like interaction between global and local signals, lead to complex and structured patterns. The study of group intelligence exhibited by swarming birds or shoaling fish has led to an embodiment of NPF called particle swarm optimization (PSO. This theoretical model could be applicable to the behavior of osteoblasts osteoclasts and osteocytes, seeing them operating socially in response simultaneously to both global and local signals (endocrine, cytokine, mechanical resulting in their clustered activity at formation and resorption sites. This represents problem-solving by social intelligence, and could potentially add further realism to in-silico simulation of bone modeling.What insights has NPF provided to bone biology? One example concerns the genetic disorder Juvenile Pagets Disease (JPD or Idiopathic Hyperphosphatasia, where the anomalous parallel trabecular architecture characteristic of this pathology is consistent with an NPF paradigm by analogy with known experimental NPF systems. Here coupling or feedback between osteoblasts and osteoclasts is the critical element.This NPF paradigm implies a profound link between bone regulation and its architecture: in bone the architecture is the regulation. The former is the emergent consequence of the

  14. Spatial and spatiotemporal pattern analysis of coconut lethal yellowing in Mozambique.

    Science.gov (United States)

    Bonnot, F; de Franqueville, H; Lourenço, E

    2010-04-01

    Coconut lethal yellowing (LY) is caused by a phytoplasma and is a major threat for coconut production throughout its growing area. Incidence of LY was monitored visually on every coconut tree in six fields in Mozambique for 34 months. Disease progress curves were plotted and average monthly disease incidence was estimated. Spatial patterns of disease incidence were analyzed at six assessment times. Aggregation was tested by the coefficient of spatial autocorrelation of the beta-binomial distribution of diseased trees in quadrats. The binary power law was used as an assessment of overdispersion across the six fields. Spatial autocorrelation between symptomatic trees was measured by the BB join count statistic based on the number of pairs of diseased trees separated by a specific distance and orientation, and tested using permutation methods. Aggregation of symptomatic trees was detected in every field in both cumulative and new cases. Spatiotemporal patterns were analyzed with two methods. The proximity of symptomatic trees at two assessment times was investigated using the spatiotemporal BB join count statistic based on the number of pairs of trees separated by a specific distance and orientation and exhibiting the first symptoms of LY at the two times. The semivariogram of times of appearance of LY was calculated to characterize how the lag between times of appearance of LY was related to the distance between symptomatic trees. Both statistics were tested using permutation methods. A tendency for new cases to appear in the proximity of previously diseased trees and a spatially structured pattern of times of appearance of LY within clusters of diseased trees were detected, suggesting secondary spread of the disease.

  15. Spatiotemporal Aeration and Lung Injury Patterns Are Influenced by the First Inflation Strategy at Birth.

    Science.gov (United States)

    Tingay, David G; Rajapaksa, Anushi; Zonneveld, C Elroy; Black, Don; Perkins, Elizabeth J; Adler, Andy; Grychtol, Bartłomiej; Lavizzari, Anna; Frerichs, Inéz; Zahra, Valerie A; Davis, Peter G

    2016-02-01

    Ineffective aeration during the first inflations at birth creates regional aeration and ventilation defects, initiating injurious pathways. This study aimed to compare a sustained first inflation at birth or dynamic end-expiratory supported recruitment during tidal inflations against ventilation without intentional recruitment on gas exchange, lung mechanics, spatiotemporal regional aeration and tidal ventilation, and regional lung injury in preterm lambs. Lambs (127 ± 2 d gestation), instrumented at birth, were ventilated for 60 minutes from birth with either lung-protective positive pressure ventilation (control) or as per control after either an initial 30 seconds of 40 cm H2O sustained inflation (SI) or an initial stepwise end-expiratory pressure recruitment maneuver during tidal inflations (duration 180 s; open lung ventilation [OLV]). At study completion, molecular markers of lung injury were analyzed. The initial use of an OLV maneuver, but not SI, at birth resulted in improved lung compliance, oxygenation, end-expiratory lung volume, and reduced ventilatory needs compared with control, persisting throughout the study. These changes were due to more uniform inter- and intrasubject gravity-dependent spatiotemporal patterns of aeration (measured using electrical impedance tomography). Spatial distribution of tidal ventilation was more stable after either recruitment maneuver. All strategies caused regional lung injury patterns that mirrored associated regional volume states. Irrespective of strategy, spatiotemporal volume loss was consistently associated with up-regulation of early growth response-1 expression. Our results show that mechanical and molecular consequences of lung aeration at birth are not simply related to rapidity of fluid clearance; they are also related to spatiotemporal pressure-volume interactions within the lung during inflation and deflation.

  16. Spatiotemporal patterns, annual baseline and movement-related incidence of Streptococcus agalactiae infection in Danish dairy herds: 2000–2009

    DEFF Research Database (Denmark)

    Mweu, Marshal M.; Nielsen, Søren S.; Hisham Beshara Halasa, Tariq

    2014-01-01

    -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...

  17. Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks.

    Science.gov (United States)

    Gardner, Brian; Sporea, Ioana; Grüning, André

    2015-12-01

    Information encoding in the nervous system is supported through the precise spike timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains an open question. Here we examine how multilayered networks of spiking neurons can learn to encode for input patterns using a fully temporal coding scheme. To this end, we introduce a new supervised learning rule, MultilayerSpiker, that can train spiking networks containing hidden layer neurons to perform transformations between spatiotemporal input and output spike patterns. The performance of the proposed learning rule is demonstrated in terms of the number of pattern mappings it can learn, the complexity of network structures it can be used on, and its classification accuracy when using multispike-based encodings. In particular, the learning rule displays robustness against input noise and can generalize well on an example data set. Our approach contributes to both a systematic understanding of how computations might take place in the nervous system and a learning rule that displays strong technical capability.

  18. A modified consumer inkjet for spatiotemporal control of gene expression.

    Directory of Open Access Journals (Sweden)

    Daniel J Cohen

    Full Text Available This paper presents a low-cost inkjet dosing system capable of continuous, two-dimensional spatiotemporal regulation of gene expression via delivery of diffusible regulators to a custom-mounted gel culture of E. coli. A consumer-grade, inkjet printer was adapted for chemical printing; E. coli cultures were grown on 750 microm thick agar embedded in micro-wells machined into commercial compact discs. Spatio-temporal regulation of the lac operon was demonstrated via the printing of patterns of lactose and glucose directly into the cultures; X-Gal blue patterns were used for visual feedback. We demonstrate how the bistable nature of the lac operon's feedback, when perturbed by patterning lactose (inducer and glucose (inhibitor, can lead to coordination of cell expression patterns across a field in ways that mimic motifs seen in developmental biology. Examples of this include sharp boundaries and the generation of traveling waves of mRNA expression. To our knowledge, this is the first demonstration of reaction-diffusion effects in the well-studied lac operon. A finite element reaction-diffusion model of the lac operon is also presented which predicts pattern formation with good fidelity.

  19. Spatiotemporal Modeling of Community Risk

    Science.gov (United States)

    2016-03-01

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

  20. Stability Switches, Hopf Bifurcations, and Spatio-temporal Patterns in a Delayed Neural Model with Bidirectional Coupling

    Science.gov (United States)

    Song, Yongli; Zhang, Tonghua; Tadé, Moses O.

    2009-12-01

    The dynamical behavior of a delayed neural network with bi-directional coupling is investigated by taking the delay as the bifurcating parameter. Some parameter regions are given for conditional/absolute stability and Hopf bifurcations by using the theory of functional differential equations. As the propagation time delay in the coupling varies, stability switches for the trivial solution are found. Conditions ensuring the stability and direction of the Hopf bifurcation are determined by applying the normal form theory and the center manifold theorem. We also discuss the spatio-temporal patterns of bifurcating periodic oscillations by using the symmetric bifurcation theory of delay differential equations combined with representation theory of Lie groups. In particular, we obtain that the spatio-temporal patterns of bifurcating periodic oscillations will alternate according to the change of the propagation time delay in the coupling, i.e., different ranges of delays correspond to different patterns of neural activities. Numerical simulations are given to illustrate the obtained results and show the existence of bursts in some interval of the time for large enough delay.

  1. Estimating Activity Patterns Using Spatio-temporal Data of Cellphone Networks

    Directory of Open Access Journals (Sweden)

    Zahedi Seyedmostafa

    2016-01-01

    Full Text Available The tendency towards using activity-based models to predict trip demand has increased dramatically over recent years, but these models have suffered insufficient data for calibration. This paper discusses ways to process the cellphone spatio-temporal data in a manner that makes it comprehensible for traffic interpretations and proposes methods on how to infer urban mobility and activity patterns from the aforementioned data. Movements of each subscriber is described by a sequence of stays and trips and each stay is labeled by an activity. The type of activities are estimated using features such as land use, duration of stay, frequency of visit, arrival time to that activity and its distance from home. Finally, the chains of trips are identified and different patterns that citizens follow to participate in activities are determined. The data comprises 144 million records of the location of 300,000 citizens of Shiraz at five-minute intervals.

  2. Non-linear pattern formation in bone growth and architecture.

    Science.gov (United States)

    Salmon, Phil

    2014-01-01

    The three-dimensional morphology of bone arises through adaptation to its required engineering performance. Genetically and adaptively bone travels along a complex spatiotemporal trajectory to acquire optimal architecture. On a cellular, micro-anatomical scale, what mechanisms coordinate the activity of osteoblasts and osteoclasts to produce complex and efficient bone architectures? One mechanism is examined here - chaotic non-linear pattern formation (NPF) - which underlies in a unifying way natural structures as disparate as trabecular bone, swarms of birds flying, island formation, fluid turbulence, and others. At the heart of NPF is the fact that simple rules operating between interacting elements, and Turing-like interaction between global and local signals, lead to complex and structured patterns. The study of "group intelligence" exhibited by swarming birds or shoaling fish has led to an embodiment of NPF called "particle swarm optimization" (PSO). This theoretical model could be applicable to the behavior of osteoblasts, osteoclasts, and osteocytes, seeing them operating "socially" in response simultaneously to both global and local signals (endocrine, cytokine, mechanical), resulting in their clustered activity at formation and resorption sites. This represents problem-solving by social intelligence, and could potentially add further realism to in silico computer simulation of bone modeling. What insights has NPF provided to bone biology? One example concerns the genetic disorder juvenile Pagets disease or idiopathic hyperphosphatasia, where the anomalous parallel trabecular architecture characteristic of this pathology is consistent with an NPF paradigm by analogy with known experimental NPF systems. Here, coupling or "feedback" between osteoblasts and osteoclasts is the critical element. This NPF paradigm implies a profound link between bone regulation and its architecture: in bone the architecture is the regulation. The former is the emergent

  3. Closing the gap between behavior and models in route choice: The role of spatiotemporal constraints and latent traits in choice set formation

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2012-01-01

    not account for individual-related spatiotemporal constraints. This paper reduces the gap by proposing a route choice model incorporating spatiotemporal constraints and latent traits. The proposed approach combines stochastic route generation with a latent variable semi-compensatory model representing......A considerable gap exists between the behavioral paradigm of choice set formation in route choice and its representation in route choice modeling. While travelers form their viable choice set by retaining routes that satisfy spatiotemporal constraints, existing route generation techniques do...

  4. Spatio-temporal transmission patterns of black-band disease in a coral community.

    Directory of Open Access Journals (Sweden)

    Assaf Zvuloni

    Full Text Available BACKGROUND: Transmission mechanisms of black-band disease (BBD in coral reefs are poorly understood, although this disease is considered to be one of the most widespread and destructive coral infectious diseases. The major objective of this study was to assess transmission mechanisms of BBD in the field based on the spatio-temporal patterns of the disease. METHODOLOGY/PRINCIPAL FINDINGS: 3,175 susceptible and infected corals were mapped over an area of 10x10 m in Eilat (northern Gulf of Aqaba, Red Sea and the distribution of the disease was examined monthly throughout almost two full disease cycles (June 2006-December 2007. Spatial and spatio-temporal analyses were applied to infer the transmission pattern of the disease and to calculate key epidemiological parameters such as (basic reproduction number. We show that the prevalence of the disease is strongly associated with high water temperature. When water temperatures rise and disease prevalence increases, infected corals exhibit aggregated distributions on small spatial scales of up to 1.9 m. Additionally, newly-infected corals clearly appear in proximity to existing infected corals and in a few cases in direct contact with them. We also present and test a model of water-borne infection, indicating that the likelihood of a susceptible coral becoming infected is defined by its spatial location and by the relative spatial distribution of nearby infected corals found in the site. CONCLUSIONS/SIGNIFICANCE: Our results provide evidence that local transmission, but not necessarily by direct contact, is likely to be an important factor in the spread of the disease over the tested spatial scale. In the absence of potential disease vectors with limited mobility (e.g., snails, fireworms in the studied site, water-borne infection is likely to be a significant transmission mechanism of BBD. Our suggested model of water-borne transmission supports this hypothesis. The spatio-temporal analysis also points

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

    Science.gov (United States)

    Yu, J.; Lee, K. S.

    2015-12-01

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

  6. Bridge damage detection using spatiotemporal patterns extracted from dense sensor network

    International Nuclear Information System (INIS)

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

    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. (paper)

  7. Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data

    Directory of Open Access Journals (Sweden)

    Xiping Yang

    2016-09-01

    Full Text Available Investigating human mobility patterns can help researchers and agencies understand the driving forces of human movement, with potential benefits for urban planning and traffic management. Recent advances in location-aware technologies have provided many new data sources (e.g., mobile phone and social media data for studying human space-time behavioral regularity. Although existing studies have utilized these new datasets to characterize human mobility patterns from various aspects, such as predicting human mobility and monitoring urban dynamics, few studies have focused on human convergence and divergence patterns within a city. This study aims to explore human spatial convergence and divergence and their evolutions over time using large-scale mobile phone location data. Using a dataset from Shenzhen, China, we developed a method to identify spatiotemporal patterns of human convergence and divergence. Eight distinct patterns were extracted, and the spatial distributions of these patterns are discussed in the context of urban functional regions. Thus, this study investigates urban human convergence and divergence patterns and their relationships with the urban functional environment, which is helpful for urban policy development, urban planning and traffic management.

  8. Spatiotemporal Patterns and Socioeconomic Dimensions of Shared Accommodations: the Case of Airbnb in LOS Angeles, California

    Science.gov (United States)

    Sarkar, A.; Koohikamali, M.; Pick, J. B.

    2017-10-01

    In recent years, disruptive innovation by peer-to-peer platforms in a variety of industries, notably transportation and hospitality have altered the way individuals consume everyday essential services. With growth in sharing economy platforms such as Uber for ridesharing and Airbnb for short-term accommodations, interest in examining spatiotemporal patterns of participation in the sharing economy by suppliers and consumers is increasing. This research is motivated by key questions: who are the sharing economy workers, where are they located, and does their location influence their participation in the sharing economy? This paper is the first systematic effort to analyze spatiotemporal patterns of participation by hosts in the shared accommodation-based economy. Using three different kinds of shared accommodations listed in a 3-year period in the popular short-term accommodation platform, Airbnb, we examine spatiotemporal dimensions of host participation in a major U.S. market, Los Angeles CA. The paper also develops a conceptual model by positing associations of demographic, socioeconomic, occupational, and social capital attributes of hosts, along with their attitudes toward trust and greener consumption with hosts' participation in a shared accommodation market. Results confirm host participation to be influenced by young dependency ratio, the potential of supplemental income, as well as the sustainability potential of collaborative consumption, along with finance, insurance, and real estate occupation, but not so much by trust for our overall study area. These results add new insights to limited prior knowledge about the sharing economy worker and have policy implications.

  9. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

    Science.gov (United States)

    Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

    2016-11-01

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

  10. A spatiotemporal analysis of hydrological patterns based on a wireless sensor network system

    Science.gov (United States)

    Plaza, F.; Slater, T. A.; Zhong, X.; Li, Y.; Liang, Y.; Liang, X.

    2017-12-01

    Understanding complicated spatiotemporal patterns of eco-hydrological variables at a small scale plays a profound role in improving predictability of high resolution distributed hydrological models. However, accurate and continuous monitoring of these complex patterns has become one of the main challenges in the environmental sciences. Wireless sensor networks (WSNs) have emerged as one of the most widespread potential solutions to achieve this. This study presents a spatiotemporal analysis of hydrological patterns (e.g., soil moisture, soil water potential, soil temperature and transpiration) based on observational data collected from a dense multi-hop wireless sensor network (WSN) in a steep-forested testbed located in Southwestern Pennsylvania, USA. At this WSN testbed with an approximate area of 3000 m2, environmental variables are collected from over 240 sensors that are connected to more than 100 heterogeneous motes. The sensors include the soil moisture of EC-5, soil temperature and soil water potential of MPS-1 and MPS-2, and sap flow sensors constructed in house. The motes consist of MICAz, IRIS and TelosB. In addition, several data loggers have been installed along the site to provide a comparative reference to the WSN measurements for the purpose of checking the WSN data quality. The edaphic properties monitored by the WSN sensors show strong agreement with the data logger measurements. Moreover, sap flow measurements, scaled to tree stand transpiration, are found to be reasonable. This study also investigates the feasibility and roles that these sensor measurements play in improving the performance of high-resolution distributed hydrological models. In particular, we explore this using a modified version of the Distributed Hydrological Soil Vegetation Model (DHSVM).

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

    Science.gov (United States)

    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.

  12. Comparison of Spatiotemporal Mapping Techniques for Enormous Etl and Exploitation Patterns

    Science.gov (United States)

    Deiotte, R.; La Valley, R.

    2017-10-01

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

  13. COMPARISON OF SPATIOTEMPORAL MAPPING TECHNIQUES FOR ENORMOUS ETL AND EXPLOITATION PATTERNS

    Directory of Open Access Journals (Sweden)

    R. Deiotte

    2017-10-01

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

  14. Clonal mobility and its implications for spatio-temporal patterns of plant communities: what do we need to know next?

    Czech Academy of Sciences Publication Activity Database

    Zobel, M.; Moora, M.; Herben, Tomáš

    2010-01-01

    Roč. 119, č. 5 (2010), s. 802-806 ISSN 0030-1299 Institutional research plan: CEZ:AV0Z60050516 Keywords : clonal mobility * spatio-temporal patterns * plant communities Subject RIV: EF - Botanics Impact factor: 3.393, year: 2010

  15. SPATIOTEMPORAL PATTERNS AND SOCIOECONOMIC DIMENSIONS OF SHARED ACCOMMODATIONS: THE CASE OF AIRBNB IN LOS ANGELES, CALIFORNIA

    Directory of Open Access Journals (Sweden)

    A. Sarkar

    2017-10-01

    Full Text Available In recent years, disruptive innovation by peer-to-peer platforms in a variety of industries, notably transportation and hospitality have altered the way individuals consume everyday essential services. With growth in sharing economy platforms such as Uber for ridesharing and Airbnb for short-term accommodations, interest in examining spatiotemporal patterns of participation in the sharing economy by suppliers and consumers is increasing. This research is motivated by key questions: who are the sharing economy workers, where are they located, and does their location influence their participation in the sharing economy? This paper is the first systematic effort to analyze spatiotemporal patterns of participation by hosts in the shared accommodation-based economy. Using three different kinds of shared accommodations listed in a 3-year period in the popular short-term accommodation platform, Airbnb, we examine spatiotemporal dimensions of host participation in a major U.S. market, Los Angeles CA. The paper also develops a conceptual model by positing associations of demographic, socioeconomic, occupational, and social capital attributes of hosts, along with their attitudes toward trust and greener consumption with hosts’ participation in a shared accommodation market. Results confirm host participation to be influenced by young dependency ratio, the potential of supplemental income, as well as the sustainability potential of collaborative consumption, along with finance, insurance, and real estate occupation, but not so much by trust for our overall study area. These results add new insights to limited prior knowledge about the sharing economy worker and have policy implications.

  16. Blood drop patterns: Formation and applications.

    Science.gov (United States)

    Chen, Ruoyang; Zhang, Liyuan; Zang, Duyang; Shen, Wei

    2016-05-01

    The drying of a drop of blood or plasma on a solid substrate leads to the formation of interesting and complex patterns. Inter- and intra-cellular and macromolecular interactions in the drying plasma or blood drop are responsible for the final morphologies of the dried patterns. Changes in these cellular and macromolecular components in blood caused by diseases have been suspected to cause changes in the dried drop patterns of plasma and whole blood, which could be used as simple diagnostic tools to identify the health of humans and livestock. However, complex physicochemical driving forces involved in the pattern formation are not fully understood. This review focuses on the scientific development in microscopic observations and pattern interpretation of dried plasma and whole blood samples, as well as the diagnostic applications of pattern analysis. Dried drop patterns of plasma consist of intricate visible cracks in the outer region and fine structures in the central region, which are mainly influenced by the presence and concentration of inorganic salts and proteins during drying. The shrinkage of macromolecular gel and its adhesion to the substrate surface have been thought to be responsible for the formation of the cracks. Dried drop patterns of whole blood have three characteristic zones; their formation as functions of drying time has been reported in the literature. Some research works have applied engineering treatment to the evaporation process of whole blood samples. The sensitivities of the resultant patterns to the relative humidity of the environment, the wettability of the substrates, and the size of the drop have been reported. These research works shed light on the mechanisms of spreading, evaporation, gelation, and crack formation of the blood drops on solid substrates, as well as on the potential applications of dried drop patterns of plasma and whole blood in diagnosis. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

  17. Spatio-temporal dynamics of the white-eye square superlattice pattern in dielectric barrier discharge

    International Nuclear Information System (INIS)

    Wei, Lingyan; Dong, Lifang; Feng, Jianyu; Liu, Weibo; Fan, Weili; Pan, Yuyang

    2016-01-01

    We report on the first investigation of the white-eye square superlattice pattern (WESSP) in a dielectric barrier discharge system. The evolution of patterns with increasing voltage is given. A phase diagram of WESSP as functions of gas pressure p and argon concentration φ is presented. The spatio-temporal dynamics of the WESSP is studied by using an intensified charge-coupled device camera and photomultipliers. Results show that the WESSP consists of four different transient sublattices, whose discharge sequence is small spots—spots on the line—halos—central spots in each half voltage cycle. The discharge moment and position of each sublattice are dependent upon the field of the wall charges produced by all sublattices discharged previously. (paper)

  18. Spatiotemporal exploratory models for broad-scale survey data.

    Science.gov (United States)

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

    2010-12-01

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

  19. Sponge budding is a spatiotemporal morphological patterning process: Insights from synchrotron radiation-based x-ray microtomography into the asexual reproduction of Tethya wilhelma

    Directory of Open Access Journals (Sweden)

    Nickel Michael

    2009-09-01

    Full Text Available Abstract Background Primary agametic-asexual reproduction mechanisms such as budding and fission are present in all non-bilaterian and many bilaterian animal taxa and are likely to be metazoan ground pattern characters. Cnidarians display highly organized and regulated budding processes. In contrast, budding in poriferans was thought to be less specific and related to the general ability of this group to reorganize their tissues. Here we test the hypothesis of morphological pattern formation during sponge budding. Results We investigated the budding process in Tethya wilhelma (Demospongiae by applying 3D morphometrics to high resolution synchrotron radiation-based x-ray microtomography (SR-μCT image data. We followed the morphogenesis of characteristic body structures and identified distinct morphological states which indeed reveal characteristic spatiotemporal morphological patterns in sponge bud development. We discovered the distribution of skeletal elements, canal system and sponge tissue to be based on a sequential series of distinct morphological states. Based on morphometric data we defined four typical bud stages. Once they have reached the final stage buds are released as fully functional juvenile sponges which are morphologically and functionally equivalent to adult specimens. Conclusion Our results demonstrate that budding in demosponges is considerably more highly organized and regulated than previously assumed. Morphological pattern formation in asexual reproduction with underlying genetic regulation seems to have evolved early in metazoans and was likely part of the developmental program of the last common ancestor of all Metazoa (LCAM.

  20. Sponge budding is a spatiotemporal morphological patterning process: Insights from synchrotron radiation-based x-ray microtomography into the asexual reproduction of Tethya wilhelma.

    Science.gov (United States)

    Hammel, Jörg U; Herzen, Julia; Beckmann, Felix; Nickel, Michael

    2009-09-08

    Primary agametic-asexual reproduction mechanisms such as budding and fission are present in all non-bilaterian and many bilaterian animal taxa and are likely to be metazoan ground pattern characters. Cnidarians display highly organized and regulated budding processes. In contrast, budding in poriferans was thought to be less specific and related to the general ability of this group to reorganize their tissues. Here we test the hypothesis of morphological pattern formation during sponge budding. We investigated the budding process in Tethya wilhelma (Demospongiae) by applying 3D morphometrics to high resolution synchrotron radiation-based x-ray microtomography (SR-muCT) image data. We followed the morphogenesis of characteristic body structures and identified distinct morphological states which indeed reveal characteristic spatiotemporal morphological patterns in sponge bud development. We discovered the distribution of skeletal elements, canal system and sponge tissue to be based on a sequential series of distinct morphological states. Based on morphometric data we defined four typical bud stages. Once they have reached the final stage buds are released as fully functional juvenile sponges which are morphologically and functionally equivalent to adult specimens. Our results demonstrate that budding in demosponges is considerably more highly organized and regulated than previously assumed. Morphological pattern formation in asexual reproduction with underlying genetic regulation seems to have evolved early in metazoans and was likely part of the developmental program of the last common ancestor of all Metazoa (LCAM).

  1. Patterning biomaterials for the spatiotemporal delivery of bioactive molecules

    Directory of Open Access Journals (Sweden)

    Silvia eMinardi

    2016-06-01

    Full Text Available The aim of tissue engineering is to promote the repair of functional tissues. For decades, the combined use of biomaterials, growth factors, and stem cells has been at the base of several regeneration strategies. Among these, biomimicry emerged as a robust strategy to efficiently address this clinical challenge. Biomimetic materials, able to recapitulate the composition and architecture of the extracellular matrix, are the materials of choice, for their biocompatibility and higher rate of efficacy. In addition, it has become increasingly clear that restoring the complex biochemical environment of the target tissue is crucial for its regeneration. Towards this aim, the combination of scaffolds and growth factors is required. The advent of nanotechnology significantly impacted the field of tissue engineering by providing new ways to reproduce the complex spatial and temporal biochemical patterns of tissues. This review will present the most recent approaches to finely control the spatiotemporal release of bioactive molecules for various tissue engineering applications.

  2. UNDERSTANDING THE SPATIO-TEMPORAL PATTERN OF FIRE DISTURBANCE IN THE EASTERN MONGOLIA USING MODIS PRODUCT

    OpenAIRE

    Wurihan; Zhang, H.; Zhang, Z.; Guo, X.; Zhao, J.; Duwala; Shan, Y.; Hongying

    2018-01-01

    Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1) The fire dis...

  3. Defects and spatiotemporal disorder in a pattern of falling liquid columns

    Science.gov (United States)

    Brunet, Philippe; Limat, Laurent

    2004-10-01

    Disordered regimes of a one-dimensional pattern of liquid columns hanging below an overflowing circular dish are investigated experimentally. The interaction of two basic dynamical modes (oscillations and drift) combined with the occurrence of defects (birth of new columns, disappearances by coalescences of two columns) leads to spatiotemporal chaos. When the flow rate is progressively increased, a continuous transition between transient and permanent chaos is pointed into evidence. We introduce the rate of defects as the sole relevant quantity to quantify this “turbulence” without ambiguity. Statistics on both transient and endlessly chaotic regimes enable to define a critical flow rate around which exponents are extracted. Comparisons are drawn with other interfacial pattern-forming systems, where transition towards chaos follows similar steps. Qualitatively, careful examinations of the global dynamics show that the contamination processes are nonlocal and involve the propagation of blocks of elementary laminar states (such as propagative domains or local oscillations), emitted near the defects, which turn out to be essential ingredients of this self-sustained disorder.

  4. Spatio-Temporal Data Exchange Standards

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Schmidt, Albrecht

    2003-01-01

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

  5. A Geographic Information Science (GISc) Approach to Characterizing Spatiotemporal Patterns of Terrorist Incidents in Iraq, 2004-2009

    Energy Technology Data Exchange (ETDEWEB)

    Medina, Richard M [ORNL; Siebeneck, Laura K. [University of Utah; Hepner, George F. [University of Utah

    2011-01-01

    As terrorism on all scales continues, it is necessary to improve understanding of terrorist and insurgent activities. This article takes a Geographic Information Systems (GIS) approach to advance the understanding of spatial, social, political, and cultural triggers that influence terrorism incidents. Spatial, temporal, and spatiotemporal patterns of terrorist attacks are examined to improve knowledge about terrorist systems of training, planning, and actions. The results of this study aim to provide a foundation for understanding attack patterns and tactics in emerging havens as well as inform the creation and implementation of various counterterrorism measures.

  6. Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

    Directory of Open Access Journals (Sweden)

    Pietro Quaglio

    2017-05-01

    Full Text Available Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs. STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons. In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST. We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE analysis.

  7. Pattern formations and oscillatory phenomena

    CERN Document Server

    Kinoshita, Shuichi

    2013-01-01

    Patterns and their formations appear throughout nature, and are studied to analyze different problems in science and make predictions across a wide range of disciplines including biology, physics, mathematics, chemistry, material science, and nanoscience. With the emergence of nanoscience and the ability for researchers and scientists to study living systems at the biological level, pattern formation research has become even more essential. This book is an accessible first of its kind guide for scientists, researchers, engineers, and students who require a general introduction to thi

  8. Spatiotemporal patterns, annual baseline and movement-related incidence of Streptococcus agalactiae infection in Danish dairy herds: 2000-2009.

    Science.gov (United States)

    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.

  9. Spatiotemporal network motif reveals the biological traits of developmental gene regulatory networks in Drosophila melanogaster

    Directory of Open Access Journals (Sweden)

    Kim Man-Sun

    2012-05-01

    Full Text Available Abstract Background Network motifs provided a “conceptual tool” for understanding the functional principles of biological networks, but such motifs have primarily been used to consider static network structures. Static networks, however, cannot be used to reveal time- and region-specific traits of biological systems. To overcome this limitation, we proposed the concept of a “spatiotemporal network motif,” a spatiotemporal sequence of network motifs of sub-networks which are active only at specific time points and body parts. Results On the basis of this concept, we analyzed the developmental gene regulatory network of the Drosophila melanogaster embryo. We identified spatiotemporal network motifs and investigated their distribution pattern in time and space. As a result, we found how key developmental processes are temporally and spatially regulated by the gene network. In particular, we found that nested feedback loops appeared frequently throughout the entire developmental process. From mathematical simulations, we found that mutual inhibition in the nested feedback loops contributes to the formation of spatial expression patterns. Conclusions Taken together, the proposed concept and the simulations can be used to unravel the design principle of developmental gene regulatory networks.

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

    OpenAIRE

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

    2012-01-01

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

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

    Science.gov (United States)

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

    2018-02-02

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

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

    Directory of Open Access Journals (Sweden)

    Xiaodong Cao

    2018-02-01

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

  13. Pattern formation in rotating Bénard convection

    Science.gov (United States)

    Fantz, M.; Friedrich, R.; Bestehorn, M.; Haken, H.

    1992-12-01

    Using an extension of the Swift-Hohenberg equation we study pattern formation in the Bénard experiment close to the onset of convection in the case of rotating cylindrical fluid containers. For small Taylor numbers we emphasize the existence of slowly rotating patterns and describe behaviour exhibiting defect motion. Finally, we study pattern formation close to the Küppers-Lortz instability. The instability is nucleated at defects and proceeds through front propagation into the bulk patterns.

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

    Directory of Open Access Journals (Sweden)

    Jinlei Zhang

    2018-02-01

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

  15. Spatiotemporal Dynamics of Dendritic Spines in the Living Brain

    Directory of Open Access Journals (Sweden)

    Chia-Chien eChen

    2014-05-01

    Full Text Available Dendritic spines are ubiquitous postsynaptic sites of most excitatory synapses in the mammalian brain, and thus may serve as structural indicators of functional synapses. Recent works have suggested that neuronal coding of memories may be associated with rapid alterations in spine formation and elimination. Technological advances have enabled researchers to study spine dynamics in vivo during development as well as under various physiological and pathological conditions. We believe that better understanding of the spatiotemporal patterns of spine dynamics will help elucidate the principles of experience-dependent circuit modification and information processing in the living brain.

  16. A theory of biological pattern formation

    OpenAIRE

    Gierer, Alfred; Meinhardt, H.

    2006-01-01

    The paper addresses the formation of striking patterns within originally near-homogenous tissue, the process prototypical for embryology, and represented in particularly puristic form by cut sections of hydra regenerating a complete animal with head and foot. Essential requirements are autocatalytic, self-enhancing activation, combined with inhibitory or depletion effects of wider range - “lateral inhibition”. Not only de-novo-pattern formation, but also well known, striking features of devel...

  17. Spatio-Temporal Diffusion Pattern and Hotspot Detection of Dengue in Chachoengsao Province, Thailand

    Directory of Open Access Journals (Sweden)

    Phaisarn Jeefoo

    2010-12-01

    Full Text Available In recent years, dengue has become a major international public health concern. In Thailand it is also an important concern as several dengue outbreaks were reported in last decade. This paper presents a GIS approach to analyze the spatial and temporal dynamics of dengue epidemics. The major objective of this study was to examine spatial diffusion patterns and hotspot identification for reported dengue cases. Geospatial diffusion pattern of the 2007 dengue outbreak was investigated. Map of daily cases was generated for the 153 days of the outbreak. Epidemiological data from Chachoengsao province, Thailand (reported dengue cases for the years 1999–2007 was used for this study. To analyze the dynamic space-time pattern of dengue outbreaks, all cases were positioned in space at a village level. After a general statistical analysis (by gender and age group, data was subsequently analyzed for temporal patterns and correlation with climatic data (especially rainfall, spatial patterns and cluster analysis, and spatio-temporal patterns of hotspots during epidemics. The results revealed spatial diffusion patterns during the years 1999–2007 representing spatially clustered patterns with significant differences by village. Villages on the urban fringe reported higher incidences. The space and time of the cases showed outbreak movement and spread patterns that could be related to entomologic and epidemiologic factors. The hotspots showed the spatial trend of dengue diffusion. This study presents useful information related to the dengue outbreak patterns in space and time and may help public health departments to plan strategies to control the spread of disease. The methodology is general for space-time analysis and can be applied for other infectious diseases as well.

  18. Rethinking pattern formation in reaction-diffusion systems

    Science.gov (United States)

    Halatek, J.; Frey, E.

    2018-05-01

    The present theoretical framework for the analysis of pattern formation in complex systems is mostly limited to the vicinity of fixed (global) equilibria. Here we present a new theoretical approach to characterize dynamical states arbitrarily far from (global) equilibrium. We show that reaction-diffusion systems that are driven by locally mass-conserving interactions can be understood in terms of local equilibria of diffusively coupled compartments. Diffusive coupling generically induces lateral redistribution of the globally conserved quantities, and the variable local amounts of these quantities determine the local equilibria in each compartment. We find that, even far from global equilibrium, the system is well characterized by its moving local equilibria. We apply this framework to in vitro Min protein pattern formation, a paradigmatic model for biological pattern formation. Within our framework we can predict and explain transitions between chemical turbulence and order arbitrarily far from global equilibrium. Our results reveal conceptually new principles of self-organized pattern formation that may well govern diverse dynamical systems.

  19. Spatio-Temporal Analysis of Urban Crime Pattern and its Implication for Abuja Municipal Area Council, Nigeria

    OpenAIRE

    Taiye Oluwafemi Adewuyi; Patrick Ali Eneji; Anthonia Silas Baduku; Emmanuel Ajayi Olofin

    2017-01-01

    This study examined the spatio-temporal analysis of urban crime pattern and its implication for Abuja Municipal Area Council of the Federal Capital Territory of Nigeria; it has the aim of using Geographical Information System to improve criminal justice system. The aim was achieved by establishing crime incident spots, types of crime committed, the time it occurred and factors responsible for prevailing crime. The methods for data collection involved Geoinformatics through the use of remote s...

  20. Span: spike pattern association neuron for learning spatio-temporal spike patterns.

    Science.gov (United States)

    Mohemmed, Ammar; Schliebs, Stefan; Matsuda, Satoshi; Kasabov, Nikola

    2012-08-01

    Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN - a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the precise timing of spikes. The idea of the proposed algorithm is to transform spike trains during the learning phase into analog signals so that common mathematical operations can be performed on them. Using this conversion, it is possible to apply the well-known Widrow-Hoff rule directly to the transformed spike trains in order to adjust the synaptic weights and to achieve a desired input/output spike behavior of the neuron. In the presented experimental analysis, the proposed learning algorithm is evaluated regarding its learning capabilities, its memory capacity, its robustness to noisy stimuli and its classification performance. Differences and similarities of SPAN regarding two related algorithms, ReSuMe and Chronotron, are discussed.

  1. Distinct spatiotemporal patterns for disease duration and stage in Parkinson's disease

    Energy Technology Data Exchange (ETDEWEB)

    Badoud, Simon [Geneva University Hospitals, Neurology Unit, Department of Clinical Neurosciences, Geneva (Switzerland); University of Fribourg, Neurophysiology Unit, Department of Medicine, Fribourg (Switzerland); University of Geneva, Faculty of Medicine, Geneva (Switzerland); Nicastro, Nicolas; Burkhard, Pierre R. [Geneva University Hospitals, Neurology Unit, Department of Clinical Neurosciences, Geneva (Switzerland); University of Geneva, Faculty of Medicine, Geneva (Switzerland); Garibotto, Valentina [University of Geneva, Faculty of Medicine, Geneva (Switzerland); Geneva University Hospitals, Nuclear Medicine and Molecular Imaging Unit, Department of Medical Imaging, Geneva (Switzerland); Haller, Sven [University of Geneva, Faculty of Medicine, Geneva (Switzerland); Centre de Diagnostique Radiologique de Carouge, Geneva (Switzerland); Uppsala University, Department of Surgical Sciences, Radiology, Uppsala (Sweden); University Hospital Freiburg, Department of Neuroradiology, Freiburg (Germany)

    2016-03-15

    To assess correlations between the degree of dopaminergic depletion measured using single-photon emission computed tomography (SPECT) and different clinical parameters of disease progression in Parkinson's disease (PD). This retrospective study included 970 consecutive patients undergoing {sup 123}I-ioflupane SPECT scans in our institution between 2003 and 2013, from which we selected a study population of 411 patients according to their clinical diagnosis: 301 patients with PD (69.4 ± 11.0 years, of age, 163 men) and 110 patients with nondegenerative conditions included as controls (72.7 ± 8.0 years of age, 55 men). Comprehensive and operator-independent data analysis included spatial normalization into standard space, estimation of the mean uptake values in the striatum (caudate nucleus + putamen) and voxel-wise correlation between SPECT signal intensity and disease stage as well as disease duration in order to investigate the spatiotemporal pattern of the dopaminergic nigrostriatal degeneration. To compensate for potential interactions between disease stage and disease duration, one parameter was used as nonexplanatory coregressor for the other. Increasing disease stage was associated with an exponential decrease in {sup 123}I-ioflupane uptake (R {sup 2} = 0.1501) particularly in the head of the ipsilateral caudate nucleus (p < 0.0001), whereas increasing disease duration was associated with a linear decrease in {sup 123}I-ioflupane uptake (p < 0.0001; R {sup 2} = 0.1532) particularly in the contralateral anterior putamen (p < 0.0001). We observed two distinct spatiotemporal patterns of posterior to anterior dopaminergic depletion associated with disease stage and disease duration in patients with PD. The developed operator-independent reference database of 411 {sup 123}I-ioflupane SPECT scans can be used for clinical and research applications. (orig.)

  2. Zebrafish: an exciting model for investigating the spatio-temporal pattern of enteric nervous system development.

    LENUS (Irish Health Repository)

    Doodnath, Reshma

    2012-02-01

    AIM: Recently, the zebrafish (Danio rerio) has been shown to be an excellent model for human paediatric research. Advantages over other models include its small size, externally visually accessible development and ease of experimental manipulation. The enteric nervous system (ENS) consists of neurons and enteric glia. Glial cells permit cell bodies and processes of neurons to be arranged and maintained in a proper spatial arrangement, and are essential in the maintenance of basic physiological functions of neurons. Glial fibrillary acidic protein (GFAP) is expressed in astrocytes, but also expressed outside of the central nervous system. The aim of this study was to investigate the spatio-temporal pattern of GFAP expression in developing zebrafish ENS from 24 h post-fertilization (hpf), using transgenic fish that express green fluorescent protein (GFP). METHODS: Zebrafish embryos were collected from transgenic GFP Tg(GFAP:GFP)(mi2001) adult zebrafish from 24 to 120 hpf, fixed and processed for whole mount immunohistochemistry. Antibodies to Phox2b were used to identify enteric neurons. Specimens were mounted on slides and imaging was performed using a fluorescent laser confocal microscope. RESULTS: GFAP:GFP labelling outside the spinal cord was identified in embryos from 48 hpf. The patterning was intracellular and consisted of elongated profiles that appeared to migrate away from the spinal cord into the periphery. At 72 and 96 hpf, GFAP:GFP was expressed dorsally and ventrally to the intestinal tract. At 120 hpf, GFAP:GFP was expressed throughout the intestinal wall, and clusters of enteric neurons were identified using Phox2b immunofluorescence along the pathway of GFAP:GFP positive processes, indicative of a migratory pathway of ENS precursors from the spinal cord into the intestine. CONCLUSION: The pattern of migration of GFAP:GFP expressing cells outside the spinal cord suggests an organized, early developing migratory pathway to the ENS. This shows for the

  3. Modelling spatiotemporal distribution patterns of earthworms in order to indicate hydrological soil processes

    Science.gov (United States)

    Palm, Juliane; Klaus, Julian; van Schaik, Loes; Zehe, Erwin; Schröder, Boris

    2010-05-01

    Soils provide central ecosystem functions in recycling nutrients, detoxifying harmful chemicals as well as regulating microclimate and local hydrological processes. The internal regulation of these functions and therefore the development of healthy and fertile soils mainly depend on the functional diversity of plants and animals. Soil organisms drive essential processes such as litter decomposition, nutrient cycling, water dynamics, and soil structure formation. Disturbances by different soil management practices (e.g., soil tillage, fertilization, pesticide application) affect the distribution and abundance of soil organisms and hence influence regulating processes. The strong relationship between environmental conditions and soil organisms gives us the opportunity to link spatiotemporal distribution patterns of indicator species with the potential provision of essential soil processes on different scales. Earthworms are key organisms for soil function and affect, among other things, water dynamics and solute transport in soils. Through their burrowing activity, earthworms increase the number of macropores by building semi-permanent burrow systems. In the unsaturated zone, earthworm burrows act as preferential flow pathways and affect water infiltration, surface-, subsurface- and matrix flow as well as the transport of water and solutes into deeper soil layers. Thereby different ecological earthworm types have different importance. Deep burrowing anecic earthworm species (e.g., Lumbricus terrestris) affect the vertical flow and thus increase the risk of potential contamination of ground water with agrochemicals. In contrast, horizontal burrowing endogeic (e.g., Aporrectodea caliginosa) and epigeic species (e.g., Lumbricus rubellus) increase water conductivity and the diffuse distribution of water and solutes in the upper soil layers. The question which processes are more relevant is pivotal for soil management and risk assessment. Thus, finding relevant

  4. Spatio-temporal patterns of soil erosion and suspended sediment dynamics in the Mekong River Basin.

    Science.gov (United States)

    Suif, Zuliziana; Fleifle, Amr; Yoshimura, Chihiro; Saavedra, Oliver

    2016-10-15

    Understanding of the distribution patterns of sediment erosion, concentration and transport in river basins is critically important as sediment plays a major role in river basin hydrophysical and ecological processes. In this study, we proposed an integrated framework for the assessment of sediment dynamics, including soil erosion (SE), suspended sediment load (SSL) and suspended sediment concentration (SSC), and applied this framework to the Mekong River Basin. The Revised Universal Soil Loss Equation (RUSLE) model was adopted with a geographic information system to assess SE and was coupled with a sediment accumulation and a routing scheme to simulate SSL. This framework also analyzed Landsat imagery captured between 1987 and 2000 together with ground observations to interpolate spatio-temporal patterns of SSC. The simulated SSL results from 1987 to 2000 showed the relative root mean square error of 41% and coefficient of determination (R(2)) of 0.89. The polynomial relationship of the near infrared exoatmospheric reflectance and the band 4 wavelength (760-900nm) to the observed SSC at 9 sites demonstrated the good agreement (overall relative RMSE=5.2%, R(2)=0.87). The result found that the severe SE occurs in the upper (China and Lao PDR) and lower (western part of Vietnam) regions. The SSC in the rainy season (June-November) showed increasing and decreasing trends longitudinally in the upper (China and Lao PDR) and lower regions (Cambodia), respectively, while the longitudinal profile of SSL showed a fluctuating trend along the river in the early rainy season. Overall, the results described the unique spatio-temporal patterns of SE, SSL and SSC in the Mekong River Basin. Thus, the proposed integrated framework is useful for elucidating complex process of sediment generation and transport in the land and river systems of large river basins. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Large-Scale Spatio-Temporal Patterns of Mediterranean Cephalopod Diversity.

    Directory of Open Access Journals (Sweden)

    Stefanie Keller

    Full Text Available Species diversity is widely recognized as an important trait of ecosystems' functioning and resilience. Understanding the causes of diversity patterns and their interaction with the environmental conditions is essential in order to effectively assess and preserve existing diversity. While diversity patterns of most recurrent groups such as fish are commonly studied, other important taxa such as cephalopods have received less attention. In this work we present spatio-temporal trends of cephalopod diversity across the entire Mediterranean Sea during the last 19 years, analysing data from the annual bottom trawl survey MEDITS conducted by 5 different Mediterranean countries using standardized gears and sampling protocols. The influence of local and regional environmental variability in different Mediterranean regions is analysed applying generalized additive models, using species richness and the Shannon Wiener index as diversity descriptors. While the western basin showed a high diversity, our analyses do not support a steady eastward decrease of diversity as proposed in some previous studies. Instead, high Shannon diversity was also found in the Adriatic and Aegean Seas, and high species richness in the eastern Ionian Sea. Overall diversity did not show any consistent trend over the last two decades. Except in the Adriatic Sea, diversity showed a hump-shaped trend with depth in all regions, being highest between 200-400 m depth. Our results indicate that high Chlorophyll a concentrations and warmer temperatures seem to enhance species diversity, and the influence of these parameters is stronger for richness than for Shannon diversity.

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

    International Nuclear Information System (INIS)

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

    1996-01-01

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

  7. A Fresh Look at Spatio-Temporal Remote Sensing Data: Data Formats, Processing Flow, and Visualization

    Science.gov (United States)

    Gens, R.

    2017-12-01

    With increasing number of experimental and operational satellites in orbit, remote sensing based mapping and monitoring of the dynamic Earth has entered into the realm of `big data'. Just the Landsat series of satellites provide a near continuous archive of 45 years of data. The availability of such spatio-temporal datasets has created opportunities for long-term monitoring diverse features and processes operating on the Earth's terrestrial and aquatic systems. Processes such as erosion, deposition, subsidence, uplift, evapotranspiration, urbanization, land-cover regime shifts can not only be monitored and change can be quantified using time-series data analysis. This unique opportunity comes with new challenges in management, analysis, and visualization of spatio-temporal datasets. Data need to be stored in a user-friendly format, and relevant metadata needs to be recorded, to allow maximum flexibility for data exchange and use. Specific data processing workflows need to be defined to support time-series analysis for specific applications. Value-added data products need to be generated keeping in mind the needs of the end-users, and using best practices in complex data visualization. This presentation systematically highlights the various steps for preparing spatio-temporal remote sensing data for time series analysis. It showcases a prototype workflow for remote sensing based change detection that can be generically applied while preserving the application-specific fidelity of the datasets. The prototype includes strategies for visualizing change over time. This has been exemplified using a time-series of optical and SAR images for visualizing the changing glacial, coastal, and wetland landscapes in parts of Alaska.

  8. Spatiotemporal representation of cardiac vectorcardiogram (VCG signals

    Directory of Open Access Journals (Sweden)

    Yang Hui

    2012-03-01

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

  9. Simple models for studying complex spatiotemporal patterns of animal behavior

    Science.gov (United States)

    Tyutyunov, Yuri V.; Titova, Lyudmila I.

    2017-06-01

    Minimal mathematical models able to explain complex patterns of animal behavior are essential parts of simulation systems describing large-scale spatiotemporal dynamics of trophic communities, particularly those with wide-ranging species, such as occur in pelagic environments. We present results obtained with three different modelling approaches: (i) an individual-based model of animal spatial behavior; (ii) a continuous taxis-diffusion-reaction system of partial-difference equations; (iii) a 'hybrid' approach combining the individual-based algorithm of organism movements with explicit description of decay and diffusion of the movement stimuli. Though the models are based on extremely simple rules, they all allow description of spatial movements of animals in a predator-prey system within a closed habitat, reproducing some typical patterns of the pursuit-evasion behavior observed in natural populations. In all three models, at each spatial position the animal movements are determined by local conditions only, so the pattern of collective behavior emerges due to self-organization. The movement velocities of animals are proportional to the density gradients of specific cues emitted by individuals of the antagonistic species (pheromones, exometabolites or mechanical waves of the media, e.g., sound). These cues play a role of taxis stimuli: prey attract predators, while predators repel prey. Depending on the nature and the properties of the movement stimulus we propose using either a simplified individual-based model, a continuous taxis pursuit-evasion system, or a little more detailed 'hybrid' approach that combines simulation of the individual movements with the continuous model describing diffusion and decay of the stimuli in an explicit way. These can be used to improve movement models for many species, including large marine predators.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-03-15

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

  11. Bifurcation Analysis and Spatiotemporal Patterns in Unidirectionally Delay-Coupled Vibratory Gyroscopes

    Science.gov (United States)

    Li, Li; Xu, Jian

    Time delay is inevitable in unidirectionally coupled drive-free vibratory gyroscope system. The effect of time delay on the gyroscope system is studied in this paper. To this end, amplitude death and Hopf bifurcation induced by small time delay are first investigated by analyzing the related characteristic equation. Then, the direction of Hopf bifurcations and stability of Hopf-bifurcating periodic oscillations are determined by calculating the normal form on the center manifold. Next, spatiotemporal patterns of these Hopf-bifurcating periodic oscillations are analyzed by using the symmetric bifurcation theory of delay differential equations. Finally, it is found that numerical simulations agree with the associated analytic results. These phenomena could be induced although time delay is very small. Therefore, it is shown that time delay is an important factor which influences the sensitivity and accuracy of the gyroscope system and cannot be neglected during the design and manufacture.

  12. Nonlinear waves and pattern dynamics

    CERN Document Server

    Pelinovsky, Efim; Mutabazi, Innocent

    2018-01-01

    This book addresses the fascinating phenomena associated with nonlinear waves and spatio-temporal patterns. These appear almost everywhere in nature from sand bed forms to brain patterns, and yet their understanding still presents fundamental scientific challenges. The reader will learn here, in particular, about the current state-of-the art and new results in: Nonlinear water waves: resonance, solitons, focusing, Bose-Einstein condensation, as well as and their relevance for the sea environment (sea-wind interaction, sand bed forms, fiber clustering) Pattern formation in non-equilibrium media: soap films, chimera patterns in oscillating media, viscoelastic Couette-Taylor flow, flow in the wake behind a heated cylinder, other pattern formation. The editors and authors dedicate this book to the memory of Alexander Ezersky, Professor of Fluid Mechanics at the University of Caen Normandie (France) from September 2007 to July 2016. Before 2007, he had served as a Senior Scientist at the Institute of Applied Physi...

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

    Directory of Open Access Journals (Sweden)

    Shaoying Lu

    2008-07-01

    Full Text Available 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.

  14. An Online Atlas for Exploring Spatio-Temporal Patterns of Cancer Mortality (1972-2011) and Incidence (1995-2008) in Taiwan.

    Science.gov (United States)

    Ku, Wen-Yuan; Liaw, Yung-Po; Huang, Jing-Yang; Nfor, Oswald Ndi; Hsu, Shu-Yi; Ko, Pei-Chieh; Lee, Wen-Chung; Chen, Chien-Jen

    2016-05-01

    Public health mapping and Geographical Information Systems (GIS) are already being used to locate the geographical spread of diseases. This study describes the construction of an easy-to-use online atlas of cancer mortality (1972-2011) and incidence (1995-2008) in Taiwan.Two sets of color maps were made based on "age-adjusted mortality by rate" and "age-adjusted mortality by rank." AJAX (Asynchronous JavaScript and XML), JSON (JavaScript Object Notation), and SVG (Scaling Vector Graphic) were used to create the online atlas. Spatio-temporal patterns of cancer mortality and incidence in Taiwan over the period from 1972 to 2011 and from 1995 to 2008.The constructed online atlas contains information on cancer mortality and incidence (http://taiwancancermap.csmu-liawyp.tw/). The common GIS functions include zoom and pan and identity tools. Users can easily customize the maps to explore the spatio-temporal trends of cancer mortality and incidence using different devices (such as personal computers, mobile phone, or pad). This study suggests an easy- to-use, low-cost, and independent platform for exploring cancer incidence and mortality. It is expected to serve as a reference tool for cancer prevention and risk assessment.This online atlas is a cheap and fast tool that integrates various cancer maps. Therefore, it can serve as a powerful tool that allows users to examine and compare spatio-temporal patterns of various maps. Furthermore, it is an-easy-to use tool for updating data and assessing risk factors of cancer in Taiwan.

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

    Science.gov (United States)

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

    2017-10-01

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

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

    Science.gov (United States)

    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.

  17. Programming Cells for Dynamic Assembly of Inorganic Nano-Objects with Spatiotemporal Control.

    Science.gov (United States)

    Wang, Xinyu; Pu, Jiahua; An, Bolin; Li, Yingfeng; Shang, Yuequn; Ning, Zhijun; Liu, Yi; Ba, Fang; Zhang, Jiaming; Zhong, Chao

    2018-04-01

    Programming living cells to organize inorganic nano-objects (NOs) in a spatiotemporally precise fashion would advance new techniques for creating ordered ensembles of NOs and new bio-abiotic hybrid materials with emerging functionalities. Bacterial cells often grow in cellular communities called biofilms. Here, a strategy is reported for programming dynamic biofilm formation for the synchronized assembly of discrete NOs or hetero-nanostructures on diverse interfaces in a dynamic, scalable, and hierarchical fashion. By engineering Escherichia coli to sense blue light and respond by producing biofilm curli fibers, biofilm formation is spatially controlled and the patterned NOs' assembly is simultaneously achieved. Diverse and complex fluorescent quantum dot patterns with a minimum patterning resolution of 100 µm are demonstrated. By temporally controlling the sequential addition of NOs into the culture, multilayered heterostructured thin films are fabricated through autonomous layer-by-layer assembly. It is demonstrated that biologically dynamic self-assembly can be used to advance a new repertoire of nanotechnologies and materials with increasing complexity that would be otherwise challenging to produce. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. The spatio-temporal Development of Copenhagen's bicycle infrastructure 1912-2013

    DEFF Research Database (Denmark)

    Carstensen, Trine Agervig; Olafsson, Anton Stahl; Bech, Nynne Marie

    2015-01-01

    Cycling plays an important role in low-carbon transitions. Around the globe, cities are constructing bicycle infrastructure. The city of Copenhagen has a bicycle-friendly infrastructure celebrated for its fine-meshed network. This study documents the spatio-temporal development of Copenhagen......’s bicycle infrastructure and explores how the development corresponds to other processes of urban transformation. The study builds on historical maps of bicycle infrastructure that are digitised into geographical information, which allows for a comprehensive analysis of the formation of the network....... In search for identifying drivers, the study analyses the city’s spatial growth pattern, migration pattern, development of road network and changes in the transport culture. Analyses reveal that the bicycle infrastructure expanded at a relatively constant pace during distinct periods of urban transformation...

  19. Are species photosynthetic characteristics good predictors of seedling post-hurricane demographic patterns and species spatiotemporal distribution in a hurricane impacted wet montane forest?

    Science.gov (United States)

    Luke, Denneko; McLaren, Kurt

    2018-05-01

    In situ measurements of leaf level photosynthetic response to light were collected from seedlings of ten tree species from a tropical montane wet forest, the John Crow Mountains, Jamaica. A model-based recursive partitioning ('mob') algorithm was then used to identify species associations based on their fitted photosynthetic response curves. Leaf area dark respiration (RD) and light saturated maximum photosynthetic (Amax) rates were also used as 'mob' partitioning variables, to identify species associations based on seedling demographic patterns (from June 2007 to May 2010) following a hurricane (Aug. 2007) and the spatiotemporal distribution patterns of stems in 2006 and 2012. RD and Amax rates ranged from 1.14 to 2.02 μmol (CO2) m-2s-1 and 2.97-5.87 μmol (CO2) m-2s-1, respectively, placing the ten species in the range of intermediate shade tolerance. Several parsimonious species 'mob' groups were formed based on 1) interspecific differences among species response curves, 2) variations in post-hurricane seedling demographic trends and 3) RD rates and species spatiotemporal distribution patterns at aspects that are more or less exposed to hurricanes. The composition of parsimonious groupings based on photosynthetic curves was not concordant with the groups based on demographic trends but was partially concordant with the RD - species spatiotemporal distribution groups. Our results indicated that the influence of photosynthetic characteristics on demographic traits and species distributions was not straightforward. Rather, there was a complex pattern of interaction between ecophysiological and demographic traits, which determined species successional status, post-hurricane response and ultimately, species distribution at our study site.

  20. Turing and Non-Turing patterns in diffusive plankton model

    Directory of Open Access Journals (Sweden)

    N. K. Thakur

    2015-03-01

    Full Text Available In this paper, we investigate a Rosenzweig-McAurthur model and its variant for phytoplankton, zooplankton and fish population dynamics with Holling type II and III functional responses. We present the theoretical analysis of processes of pattern formation that involves organism distribution and their interaction of spatially distributed population with local diffusion. The choice of parameter values is important to study the effect of diffusion, also it depends more on the nonlinearity of the system. With the help of numerical simulations, we observe the formation of spatiotemporal patterns both inside and outside the Turing space.

  1. Examining Spatiotemporal Urbanization Patterns in Kathmandu Valley, Nepal: Remote Sensing and Spatial Metrics Approaches

    Directory of Open Access Journals (Sweden)

    Rajesh Bahadur Thapa

    2009-09-01

    Full Text Available This paper examines the spatiotemporal pattern of urbanization in Kathmandu Valley using remote sensing and spatial metrics techniques. The study is based on 33-years of time series data compiled from satellite images. Along with new developments within the city fringes and rural villages in the valley, shifts in the natural environment and newly developed socioeconomic strains between residents are emerging. A highly dynamic spatial pattern of urbanization is observed in the valley. Urban built-up areas had a slow trend of growth in the 1960s and 1970s but have grown rapidly since the 1980s. The urbanization process has developed fragmented and heterogeneous land use combinations in the valley. However, the refill type of development process in the city core and immediate fringe areas has shown a decreasing trend in the neighborhood distances between land use patches, and an increasing trend towards physical connectedness, which indicates a higher probability of homogenous landscape development in the upcoming decades.

  2. Pattern formation by dewetting and evaporating sedimenting suspensions

    NARCIS (Netherlands)

    Habibi, M.; Moller, P.; Fall, A.; Rafaï, S.; Bonn, D.

    2012-01-01

    Pattern formation from drying droplets containing sedimenting particles and dewetting of thin films of such suspensions was studied. The dewetting causes the formation of finger-like patterns near the contact line which leave behind a deposit of branches. We find that the strikingly low speed of

  3. Quantum noise and spatio-temporal pattern formation in nonlinear optics

    DEFF Research Database (Denmark)

    Bache, Morten

    2002-01-01

    a nondegenerate parametric oscillation. We find that this model may completely stabilize the instabilities normally expected in SHG, but it may also give rise to entirely new phenomena, such as oscillating cavity solitons, intensity spirals and self-pulsing solutions. Especially the self-pulsing is important...... rise to spatially modulated structures, patterns. The two main parts of the thesis are the classical model and the quantum mechanical model, the latter being an extension of the former by including the inherent quantum fluctuations of light. From a theoretical point of view the classical dynamics...... are investigated with an experimental implementation in mind. Thus, we study the internally pumped optical parametric oscillator (IPOPO) as an experimentally more realistic model than the usual SHG model. In the IPOPO a competing process to SHG is taken into account, where the generated second harmonic drives...

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

    Science.gov (United States)

    Li, Xun

    2012-01-01

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

  5. Pattern formation in optical resonators

    International Nuclear Information System (INIS)

    Weiss, C O; Larionova, Ye

    2007-01-01

    We review pattern formation in optical resonators. The emphasis is on 'particle-like' structures such as vortices or spatial solitons. On the one hand, similarities impose themselves with other fields of physics (condensed matter, phase transitions, particle physics, fluds/super fluids). On the other hand the feedback is led by the resonator mirrors to bi- and multi-stability of the spatial field structure, which is the basic ingredient for optical information processing. The spatial dimension or the 'parallelism' is the strength of optics compared to electronics (and will have to be employed to fully use the advantages optics offers in information processing). But even in the 'serial' processing tasks of telecoms (e.g. information buffering) spatial resonator solitons can do better than the schemes proposed so far-including 'slow light'. Pattern formation in optical resonators will likely be the key to brain-like information processing like cognition, learning and association; to complement the precise but limited algorithmic capabilities of electronic processing. But even in the short term it will be useful for solving serial optical processing problems. The prospects for technical uses of pattern formation in resonators are one motivation for this research. The fundamental similarities with other fields of physics, on the other hand, inspire transfer of concepts between fields; something that has always proven fruitful for gaining deeper insights or for solving technical problems

  6. Unravelling spatio-temporal evapotranspiration patterns in topographically complex landscapes

    Science.gov (United States)

    Metzen, Daniel; Sheridan, Gary; Nyman, Petter; Lane, Patrick

    2016-04-01

    Vegetation co-evolves with soils and topography under a given long-term climatic forcing. Previous studies demonstrated a strong eco-hydrologic feedback between topography, vegetation and energy and water fluxes. Slope orientation (aspect and gradient) alter the magnitude of incoming solar radiation resulting in larger evaporative losses and less water availability on equator-facing slopes. Furthermore, non-local water inputs from upslope areas potentially contribute to available water at downslope positions. The combined effect of slope orientation and drainage position creates complex spatial patterns in biological productivity and pedogenesis, which in turn alter the local hydrology. In complex upland landscapes, topographic alteration of incoming radiation can cause substantial aridity index (ratio of potential evapotranspiration to precipitation) variations over small spatial extents. Most of the upland forests in south-east Australia are located in an aridity index (AI) range of 1-2, around the energy limited to water limited boundary, where forested systems are expected to be most sensitive to AI changes. In this research we aim to improve the fundamental understanding of spatio-temporal evolution of evapotranspiration (ET) patterns in complex terrain, accounting for local topographic effects on system properties (e.g. soil depth, sapwood area, leaf area) and variation in energy and water exchange processes due to slope orientation and drainage position. Six measurement plots were set-up in a mixed species eucalypt forest on a polar and equatorial-facing hillslope (AI ˜1.3 vs. 1.8) at varying drainage position (ridge, mid-slope, gully), while minimizing variations in other factors, e.g. geology and weather patterns. Sap flow, soil water content, incoming solar radiation and throughfall were continuously monitored at field sites spanning a wide range of soil depth (0.5 - >3m), maximum tree heights (17 - 51m) and LAI (1.2 - 4.6). Site-specific response curves

  7. Pattern formation in Pseudomonas aeruginosa biofilms

    DEFF Research Database (Denmark)

    Parsek, Matthew R.; Tolker-Nielsen, Tim

    2008-01-01

    Bacteria are capable of forming elaborate multicellular communities called biofilms. Pattern formation in biofilms depends on cell proliferation and cellular migration in response to the available nutrients and other external cues, as well as on self-generated intercellular signal molecules...... and the production of an extracellular matrix that serves as a structural 'scaffolding' for the biofilm cells. Pattern formation in biofilms allows cells to position themselves favorably within nutrient gradients and enables buildup and maintenance of physiologically distinct subpopulations, which facilitates...... survival of one or more subpopulations upon environmental insult, and therefore plays an important role in the innate tolerance displayed by biofilms toward adverse conditions....

  8. How pattern formation in ring networks of excitatory and inhibitoryspiking neurons depends on the input current regime

    Directory of Open Access Journals (Sweden)

    Birgit eKriener

    2014-01-01

    Full Text Available Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics,specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningfulproperties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily.When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supercritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- orfluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability.In particular, if neurons are mean-driven, the linearization has a very simple form and becomesindependent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance areimportant parameters in the determination of the critical weight.We demonstrate that interestingly even in ``intermediate'' regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical couplingstrength. We moreover analyze the effects of structural randomness by rewiring individualsynapses or redistributing weights, as well as coarse-graining on pattern

  9. A Comparative Study of Frequent and Maximal Periodic Pattern Mining Algorithms in Spatiotemporal Databases

    Science.gov (United States)

    Obulesu, O.; Rama Mohan Reddy, A., Dr; Mahendra, M.

    2017-08-01

    Detecting regular and efficient cyclic models is the demanding activity for data analysts due to unstructured, vigorous and enormous raw information produced from web. Many existing approaches generate large candidate patterns in the occurrence of huge and complex databases. In this work, two novel algorithms are proposed and a comparative examination is performed by considering scalability and performance parameters. The first algorithm is, EFPMA (Extended Regular Model Detection Algorithm) used to find frequent sequential patterns from the spatiotemporal dataset and the second one is, ETMA (Enhanced Tree-based Mining Algorithm) for detecting effective cyclic models with symbolic database representation. EFPMA is an algorithm grows models from both ends (prefixes and suffixes) of detected patterns, which results in faster pattern growth because of less levels of database projection compared to existing approaches such as Prefixspan and SPADE. ETMA uses distinct notions to store and manage transactions data horizontally such as segment, sequence and individual symbols. ETMA exploits a partition-and-conquer method to find maximal patterns by using symbolic notations. Using this algorithm, we can mine cyclic models in full-series sequential patterns including subsection series also. ETMA reduces the memory consumption and makes use of the efficient symbolic operation. Furthermore, ETMA only records time-series instances dynamically, in terms of character, series and section approaches respectively. The extent of the pattern and proving efficiency of the reducing and retrieval techniques from synthetic and actual datasets is a really open & challenging mining problem. These techniques are useful in data streams, traffic risk analysis, medical diagnosis, DNA sequence Mining, Earthquake prediction applications. Extensive investigational outcomes illustrates that the algorithms outperforms well towards efficiency and scalability than ECLAT, STNR and MAFIA approaches.

  10. Vascular pattern formation in plants.

    Science.gov (United States)

    Scarpella, Enrico; Helariutta, Ykä

    2010-01-01

    Reticulate tissue systems exist in most multicellular organisms, and the principles underlying the formation of cellular networks have fascinated philosophers, mathematicians, and biologists for centuries. In particular, the beautiful and varied arrangements of vascular tissues in plants have intrigued mankind since antiquity, yet the organizing signals have remained elusive. Plant vascular tissues form systems of interconnected cell files throughout the plant body. Vascular cells are aligned with one another along continuous lines, and vascular tissues differentiate at reproducible positions within organ environments. However, neither the precise path of vascular differentiation nor the exact geometry of vascular networks is fixed or immutable. Several recent advances converge to reconcile the seemingly conflicting predictability and plasticity of vascular tissue patterns. A control mechanism in which an apical-basal flow of signal establishes a basic coordinate system for body axis formation and vascular strand differentiation, and in which a superimposed level of radial organizing cues elaborates cell patterns, would generate a reproducible tissue configuration in the context of an underlying robust, self-organizing structure, and account for the simultaneous regularity and flexibility of vascular tissue patterns. Copyright 2010 Elsevier Inc. All rights reserved.

  11. Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons.

    Science.gov (United States)

    Oddo, Calogero M; Mazzoni, Alberto; Spanne, Anton; Enander, Jonas M D; Mogensen, Hannes; Bengtsson, Fredrik; Camboni, Domenico; Micera, Silvestro; Jörntell, Henrik

    2017-04-04

    Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an artificial fingertip equipped with an array of neuromorphic sensors. The artificial fingertip was used to transduce real-world haptic stimuli into spatiotemporal patterns of spikes. These spike patterns were delivered to the skin afferents of the second digit of rats via an array of stimulation electrodes. Combined with low-noise intra- and extracellular recordings from neocortical neurons in vivo, this approach provided a previously inaccessible high resolution analysis of the representation of tactile information in the neocortical neuronal circuitry. The results indicate high information content in individual neurons and reveal multiple novel neuronal tactile coding features such as heterogeneous and complementary spatiotemporal input selectivity also between neighboring neurons. Such neuronal heterogeneity and complementariness can potentially support a very high decoding capacity in a limited population of neurons. Our results also indicate a potential neuroprosthetic approach to communicate with the brain at a very high resolution and provide a potential novel solution for evaluating the degree or state of neurological disease in animal models.

  12. A hybrid spatiotemporal drought forecasting model for operational use

    Science.gov (United States)

    Vasiliades, L.; Loukas, A.

    2010-09-01

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

  13. Spatiotemporal patterns of childhood asthma hospitalization and utilization in Memphis Metropolitan Area from 2005 to 2015.

    Science.gov (United States)

    Oyana, Tonny J; Podila, Pradeep; Wesley, Jagila Minso; Lomnicki, Slawo; Cormier, Stephania

    2017-10-01

    To identify the key risk factors and explain the spatiotemporal patterns of childhood asthma in the Memphis metropolitan area (MMA) over an 11-year period (2005-2015). We hypothesize that in the MMA region this burden is more prevalent among urban children living south, downtown, and north of Memphis than in other areas. We used a large-scale longitudinal electronic health record database from an integrated healthcare system, Geographic information systems (GIS), and statistical and space-time models to study the spatiotemporal distributions of childhood asthma at census tract level. We found statistically significant spatiotemporal clusters of childhood asthma in the south, west, and north of Memphis city after adjusting for key covariates. The results further show a significant increase in temporal gradient in frequency of emergency department (ED) visits and inpatient hospitalizations from 2009 to 2013, and an upward trajectory from 4 per 1,000 children in 2005 to 16 per 1,000 children in 2015. The multivariate logistic regression identified age, race, insurance, admit source, encounter type, and frequency of visits as significant risk factors for childhood asthma (p asthma burden and healthcare utilization for African American (AA) patients living in a high-risk area than those living in a low-risk area in comparison to the white patients: AA vs. white [odds ratio (OR) = 3.03, 95% confidence interval (CI): 2.75-3.34]; and Hispanic vs. white (OR = 1.62, 95% CI: 1.21-2.17). These findings provide a strong basis for developing geographically tailored population health strategies at the neighborhood level for young children with chronic respiratory conditions.

  14. Spatio-temporal seasonal drought patterns in Europe from 1950 to 2015

    Science.gov (United States)

    Spinoni, Jonathan; Naumann, Gustavo; Vogt, Jürgen

    2016-04-01

    Drought is one of the natural disasters with severe impacts in Europe, not only in areas which frequently experience water scarcity such as the Mediterranean, but also in temperate or continental climates such as Central and Eastern Europe and even in cold regions such as Scandinavia and Iceland. In this study the spatio-temporal patterns of seasonal meteorological droughts in Europe between 1950 and 2015 are investigated using the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI). Since the focus is on the analysis of seasonal drought trends, indicators were calculated for 3 monthly accumulation periods. The input variables of precipitation and temperature were derived from E-OBS grids (v11-v12) at a spatial resolution of 0.25°x0.25°. Seasonal trends of drought frequency and severity were analyzed for moderate (SPI or SPEI 2.0) events during the periods 1950-2015 and 1981-2015. For the moderate events, results of the SPI analysis (precipitation driven) demonstrate a significant tendency towards less frequent and severe droughts in Northern Europe and Russia, especially in winter and spring; oppositely, an increasing trend is visible in Southern Europe, mainly in spring and summer. According to the SPEI analysis (precipitation and temperature driven) Northern Europe shows wetting patterns, while Southern and Eastern Europe show a more remarkable drying tendency, especially in summer and autumn for drought frequency and in every season for drought severity. The evolution towards drier conditions is more relevant from 1981 onwards, both in terms of frequency and severity. This is especially true for Central Europe in spring, for the Mediterranean in summer, and for Eastern Europe in autumn. Extreme events follow similar patterns, but in autumn no spatially coherent trend can be found.

  15. Square Turing patterns in reaction-diffusion systems with coupled layers

    Energy Technology Data Exchange (ETDEWEB)

    Li, Jing [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Wang, Hongli, E-mail: hlwang@pku.edu.cn, E-mail: qi@pku.edu.cn [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Center for Quantitative Biology, Peking University, Beijing 100871 (China); Ouyang, Qi, E-mail: hlwang@pku.edu.cn, E-mail: qi@pku.edu.cn [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Center for Quantitative Biology, Peking University, Beijing 100871 (China); The Peking-Tsinghua Center for Life Sciences, Beijing 100871 (China)

    2014-06-15

    Square Turing patterns are usually unstable in reaction-diffusion systems and are rarely observed in corresponding experiments and simulations. We report here an example of spontaneous formation of square Turing patterns with the Lengyel-Epstein model of two coupled layers. The squares are found to be a result of the resonance between two supercritical Turing modes with an appropriate ratio. Besides, the spatiotemporal resonance of Turing modes resembles to the mode-locking phenomenon. Analysis of the general amplitude equations for square patterns reveals that the fixed point corresponding to square Turing patterns is stationary when the parameters adopt appropriate values.

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

    NARCIS (Netherlands)

    Zijlstra, W; Hof, AL

    2003-01-01

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

  17. How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime.

    Science.gov (United States)

    Kriener, Birgit; Helias, Moritz; Rotter, Stefan; Diesmann, Markus; Einevoll, Gaute T

    2013-01-01

    Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningful properties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily. When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supracritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- or fluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability. In particular, if neurons are mean-driven, the linearization has a very simple form and becomes independent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance are important parameters in the determination of the critical weight. We demonstrate that interestingly even in "intermediate" regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical coupling strength. We moreover analyze the effects of structural randomness by rewiring individual synapses or redistributing weights, as well as coarse-graining on the formation of

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

    Directory of Open Access Journals (Sweden)

    B. Quan

    2017-09-01

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

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

    Science.gov (United States)

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

    2017-09-01

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

  20. Emergent pattern formation in an interstitial biofilm

    Science.gov (United States)

    Zachreson, Cameron; Wolff, Christian; Whitchurch, Cynthia B.; Toth, Milos

    2017-01-01

    Collective behavior of bacterial colonies plays critical roles in adaptability, survivability, biofilm expansion and infection. We employ an individual-based model of an interstitial biofilm to study emergent pattern formation based on the assumptions that rod-shaped bacteria furrow through a viscous environment and excrete extracellular polymeric substances which bias their rate of motion. Because the bacteria furrow through their environment, the substratum stiffness is a key control parameter behind the formation of distinct morphological patterns. By systematically varying this property (which we quantify with a stiffness coefficient γ ), we show that subtle changes in the substratum stiffness can give rise to a stable state characterized by a high degree of local order and long-range pattern formation. The ordered state exhibits characteristics typically associated with bacterial fitness advantages, even though it is induced by changes in environmental conditions rather than changes in biological parameters. Our findings are applicable to a broad range of biofilms and provide insights into the relationship between bacterial movement and their environment, and basic mechanisms behind self-organization of biophysical systems.

  1. Spatio-temporal modeling for residential burglary

    NARCIS (Netherlands)

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

    2017-01-01

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

  2. Globally Stable Microresonator Turing Pattern Formation for Coherent High-Power THz Radiation On-Chip

    Science.gov (United States)

    Huang, Shu-Wei; Yang, Jinghui; Yang, Shang-Hua; Yu, Mingbin; Kwong, Dim-Lee; Zelevinsky, T.; Jarrahi, Mona; Wong, Chee Wei

    2017-10-01

    In nonlinear microresonators driven by continuous-wave (cw) lasers, Turing patterns have been studied in the formalism of the Lugiato-Lefever equation with emphasis on their high coherence and exceptional robustness against perturbations. Destabilization of Turing patterns and the transition to spatiotemporal chaos, however, limit the available energy carried in the Turing rolls and prevent further harvest of their high coherence and robustness to noise. Here, we report a novel scheme to circumvent such destabilization, by incorporating the effect of local mode hybridizations, and we attain globally stable Turing pattern formation in chip-scale nonlinear oscillators with significantly enlarged parameter space, achieving a record-high power-conversion efficiency of 45% and an elevated peak-to-valley contrast of 100. The stationary Turing pattern is discretely tunable across 430 GHz on a THz carrier, with a fractional frequency sideband nonuniformity measured at 7.3 ×10-14 . We demonstrate the simultaneous microwave and optical coherence of the Turing rolls at different evolution stages through ultrafast optical correlation techniques. The free-running Turing-roll coherence, 9 kHz in 200 ms and 160 kHz in 20 minutes, is transferred onto a plasmonic photomixer for one of the highest-power THz coherent generations at room temperature, with 1.1% optical-to-THz power conversion. Its long-term stability can be further improved by more than 2 orders of magnitude, reaching an Allan deviation of 6 ×10-10 at 100 s, with a simple computer-aided slow feedback control. The demonstrated on-chip coherent high-power Turing-THz system is promising to find applications in astrophysics, medical imaging, and wireless communications.

  3. Spatiotemporal drought forecasting using nonlinear models

    Science.gov (United States)

    Vasiliades, Lampros; Loukas, Athanasios

    2010-05-01

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

  4. Automated Gait Analysis Through Hues and Areas (AGATHA): a method to characterize the spatiotemporal pattern of rat gait

    Science.gov (United States)

    Kloefkorn, Heidi E.; Pettengill, Travis R.; Turner, Sara M. F.; Streeter, Kristi A.; Gonzalez-Rothi, Elisa J.; Fuller, David D.; Allen, Kyle D.

    2016-01-01

    While rodent gait analysis can quantify the behavioral consequences of disease, significant methodological differences exist between analysis platforms and little validation has been performed to understand or mitigate these sources of variance. By providing the algorithms used to quantify gait, open-source gait analysis software can be validated and used to explore methodological differences. Our group is introducing, for the first time, a fully-automated, open-source method for the characterization of rodent spatiotemporal gait patterns, termed Automated Gait Analysis Through Hues and Areas (AGATHA). This study describes how AGATHA identifies gait events, validates AGATHA relative to manual digitization methods, and utilizes AGATHA to detect gait compensations in orthopaedic and spinal cord injury models. To validate AGATHA against manual digitization, results from videos of rodent gait, recorded at 1000 frames per second (fps), were compared. To assess one common source of variance (the effects of video frame rate), these 1000 fps videos were re-sampled to mimic several lower fps and compared again. While spatial variables were indistinguishable between AGATHA and manual digitization, low video frame rates resulted in temporal errors for both methods. At frame rates over 125 fps, AGATHA achieved a comparable accuracy and precision to manual digitization for all gait variables. Moreover, AGATHA detected unique gait changes in each injury model. These data demonstrate AGATHA is an accurate and precise platform for the analysis of rodent spatiotemporal gait patterns. PMID:27554674

  5. Simulation and spatiotemporal pattern of air temperature and precipitation in Eastern Central Asia using RegCM.

    Science.gov (United States)

    Meng, Xianyong; Long, Aihua; Wu, Yiping; Yin, Gang; Wang, Hao; Ji, Xiaonan

    2018-02-26

    Central Asia is a region that has a large land mass, yet meteorological stations in this area are relatively scarce. To address this data issues, in this study, we selected two reanalysis datasets (the ERA40 and NCEP/NCAR) and downscaled them to 40 × 40 km using RegCM. Then three gridded datasets (the CRU, APHRO, and WM) that were extrapolated from the observations of Central Asian meteorological stations to evaluate the performance of RegCM and analyze the spatiotemporal distribution of precipitation and air temperature. We found that since the 1960s, the air temperature in Xinjiang shows an increasing trend and the distribution of precipitation in the Tianshan area is quite complex. The precipitation is increasing in the south of the Tianshan Mountains (Southern Xinjiang, SX) and decreasing in the mountainous areas. The CRU and WM data indicate that precipitation in the north of the Tianshan Mountains (Northern Xinjiang, NX) is increasing, while the APHRO data show an opposite trend. The downscaled results from RegCM are generally consistent with the extrapolated gridded datasets in terms of the spatiotemporal patterns. We believe that our results can provide useful information in developing a regional climate model in Central Asia where meteorological stations are scarce.

  6. Spatiotemporal electromagnetic soliton and spatial ring formation in nonlinear metamaterials

    International Nuclear Information System (INIS)

    Zhang Jinggui; Wen Shuangchun; Xiang Yuanjiang; Wang Youwen; Luo Hailu

    2010-01-01

    We present a systematic investigation of ultrashort electromagnetic pulse propagation in metamaterials (MMs) with simultaneous cubic electric and magnetic nonlinearity. We predict that spatiotemporal electromagnetic solitons may exist in the positive-index region of a MM with focusing nonlinearity and anomalous group velocity dispersion (GVD), as well as in the negative-index region of the MM with defocusing nonlinearity and normal GVD. The experimental circumstances for generating and manipulating spatiotemporal electromagnetic solitons can be created by elaborating appropriate MMs. In addition, we find that, in the negative-index region of a MM, a spatial ring may be formed as the electromagnetic pulse propagates for focusing nonlinearity and anomalous GVD; while the phenomenon of temporal splitting of the electromagnetic pulse may appear for the same case except for the defocusing nonlinearity. Finally, we demonstrate that the nonlinear magnetization makes the sign of effective electric nonlinear effect switchable due to the combined action of electric and magnetic nonlinearity, exerting a significant influence on the propagation of electromagnetic pulses.

  7. Spatio-temporal pattern analysis for evaluation of the spread of human infections with avian influenza A(H7N9) virus in China, 2013-2014.

    Science.gov (United States)

    Dong, Wen; Yang, Kun; Xu, Quanli; Liu, Lin; Chen, Juan

    2017-10-24

    A large number (n = 460) of A(H7N9) human infections have been reported in China from March 2013 through December 2014, and H7N9 outbreaks in humans became an emerging issue for China health, which have caused numerous disease outbreaks in domestic poultry and wild bird populations, and threatened human health severely. The aims of this study were to investigate the directional trend of the epidemic and to identify the significant presence of spatial-temporal clustering of influenza A(H7N9) human cases between March 2013 and December 2014. Three distinct epidemic phases of A(H7N9) human infections were identified in this study. In each phase, standard deviational ellipse analysis was conducted to examine the directional trend of disease spreading, and retrospective space-time permutation scan statistic was then used to identify the spatio-temporal cluster patterns of H7N9 outbreaks in humans. The ever-changing location and the increasing size of the three identified standard deviational ellipses showed that the epidemic moved from east to southeast coast, and hence to some central regions, with a future epidemiological trend of continue dispersing to more central regions of China, and a few new human cases might also appear in parts of the western China. Furthermore, A(H7N9) human infections were clustering in space and time in the first two phases with five significant spatio-temporal clusters (p < 0.05), but there was no significant cluster identified in phase III. There was a new epidemiologic pattern that the decrease in significant spatio-temporal cluster of A(H7N9) human infections was accompanied with an obvious spatial expansion of the outbreaks during the study period, and identification of the spatio-temporal patterns of the epidemic can provide valuable insights for better understanding the spreading dynamics of the disease in China.

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

    Directory of Open Access Journals (Sweden)

    Shifen Cheng

    2018-06-01

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

  9. Patterns and Interfaces in Dissipative Dynamics

    CERN Document Server

    Pismen, L.M

    2006-01-01

    Spontaneous pattern formation in nonlinear dissipative systems far from equilibrium is a paradigmatic case of emergent behaviour associated with complex systems. It is encountered in a great variety of settings, both in nature and technology, and has numerous applications ranging from nonlinear optics through solid and fluid mechanics, physical chemistry and chemical engineering to biology. Nature creates its variety of forms through spontaneous pattern formation and self-assembly, and this strategy is likely to be imitated by future biomorphic technologies. This book is a first-hand account by one of the leading players in this field, which gives in-depth descriptions of analytical methods elucidating the complex evolution of nonlinear dissipative systems, and brings the reader to the forefront of current research. The introductory chapter on the theory of dynamical systems is written with a view to applications of its powerful methods to spatial and spatio-temporal patterns. It is followed by two chapters t...

  10. ANALYSIS OF SPATIO-TEMPORAL TRAFFIC PATTERNS BASED ON PEDESTRIAN TRAJECTORIES

    Directory of Open Access Journals (Sweden)

    S. Busch

    2016-06-01

    Full Text Available For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

  11. Analysis of Spatio-Temporal Traffic Patterns Based on Pedestrian Trajectories

    Science.gov (United States)

    Busch, S.; Schindler, T.; Klinger, T.; Brenner, C.

    2016-06-01

    For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

  12. Dynamic spatial pattern formation in the sea urchin embryo.

    Science.gov (United States)

    Riaz, Syed Shahed; Mackey, Michael C

    2014-02-01

    The spatiotemporal evolution of various proteins during the endo-mesodermal specification of the sea urchin embryo in the form of an expanding torus has been known experimentally for some time, and the regulatory network that controls this dynamic evolution of gene expression has been recently partially clarified. In this paper we construct a relatively simple mathematical model of this process that retains the basic features of the gene network and is able to reproduce the spatiotemporal patterns observed experimentally. We show here that a mathematical model based only on the gene-protein interactions so far reported in the literature predicts the origin of the behaviour to lie on a delayed negative feed-back loop due to the protein Blimp1 on the transcription of its corresponding mRNA. However though consistent with earlier results, this contradicts recent findings, where it has been established that the dynamical evolution of Wnt8 protein is independent of Blimp1. This leads us to offer a modified version of the original model based on observations in similar systems, and some more recent work in the sea urchin, assuming the existence of a mechanism involving inhibitory loop on wnt8 transcription. This hypothesis leads to a better match with the experimental results and suggests that the possibility of the existence of such an interaction in the sea urchin should be explored.

  13. Quantum properties of transverse pattern formation in second-harmonic generation

    DEFF Research Database (Denmark)

    Bache, Morten; Scotto, P.; Zambrini, R.

    2002-01-01

    these equations through extensive numerical simulations and analytically in the linearized limit. Our study, made below and above the threshold of pattern formation, is guided by a microscopic scheme of photon interaction underlying pattern formation in second-harmonic generation. Close to the threshold...

  14. Annotating spatio-temporal datasets for meaningful analysis in the Web

    Science.gov (United States)

    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.

  15. Violence in the prehistoric period of Japan: the spatio-temporal pattern of skeletal evidence for violence in the Jomon period.

    Science.gov (United States)

    Nakao, Hisashi; Tamura, Kohei; Arimatsu, Yui; Nakagawa, Tomomi; Matsumoto, Naoko; Matsugi, Takehiko

    2016-03-01

    Whether man is predisposed to lethal violence, ranging from homicide to warfare, and how that may have impacted human evolution, are among the most controversial topics of debate on human evolution. Although recent studies on the evolution of warfare have been based on various archaeological and ethnographic data, they have reported mixed results: it is unclear whether or not warfare among prehistoric hunter-gatherers was common enough to be a component of human nature and a selective pressure for the evolution of human behaviour. This paper reports the mortality attributable to violence, and the spatio-temporal pattern of violence thus shown among ancient hunter-gatherers using skeletal evidence in prehistoric Japan (the Jomon period: 13 000 cal BC-800 cal BC). Our results suggest that the mortality due to violence was low and spatio-temporally highly restricted in the Jomon period, which implies that violence including warfare in prehistoric Japan was not common. © 2016 The Author(s).

  16. Effective and efficient analysis of spatio-temporal data

    Science.gov (United States)

    Zhang, Zhongnan

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

  17. Robust dynamical pattern formation from a multifunctional minimal genetic circuit

    Directory of Open Access Journals (Sweden)

    Carrera Javier

    2010-04-01

    Full Text Available Abstract Background A practical problem during the analysis of natural networks is their complexity, thus the use of synthetic circuits would allow to unveil the natural mechanisms of operation. Autocatalytic gene regulatory networks play an important role in shaping the development of multicellular organisms, whereas oscillatory circuits are used to control gene expression under variable environments such as the light-dark cycle. Results We propose a new mechanism to generate developmental patterns and oscillations using a minimal number of genes. For this, we design a synthetic gene circuit with an antagonistic self-regulation to study the spatio-temporal control of protein expression. Here, we show that our minimal system can behave as a biological clock or memory, and it exhibites an inherent robustness due to a quorum sensing mechanism. We analyze this property by accounting for molecular noise in an heterogeneous population. We also show how the period of the oscillations is tunable by environmental signals, and we study the bifurcations of the system by constructing different phase diagrams. Conclusions As this minimal circuit is based on a single transcriptional unit, it provides a new mechanism based on post-translational interactions to generate targeted spatio-temporal behavior.

  18. The physics of pattern formation at liquid interfaces

    International Nuclear Information System (INIS)

    Maher, J.V.

    1991-06-01

    This report discusses the following physics of liquid interfaces: pattern formation; perturbing Saffman-Taylor flow with a small gap-gradient; scaling of radial patterns in a viscoelastic solution; dynamic surface tension at an interface between miscible liquids; and random systems

  19. Magnetic Assisted Colloidal Pattern Formation

    Science.gov (United States)

    Yang, Ye

    Pattern formation is a mysterious phenomenon occurring at all scales in nature. The beauty of the resulting structures and myriad of resulting properties occurring in naturally forming patterns have attracted great interest from scientists and engineers. One of the most convenient experimental models for studying pattern formation are colloidal particle suspensions, which can be used both to explore condensed matter phenomena and as a powerful fabrication technique for forming advanced materials. In my thesis, I have focused on the study of colloidal patterns, which can be conveniently tracked in an optical microscope yet can also be thermally equilibrated on experimentally relevant time scales, allowing for ground states and transitions between them to be studied with optical tracking algorithms. In particular, I have focused on systems that spontaneously organize due to particle-surface and particle-particle interactions, paying close attention to systems that can be dynamically adjusted with an externally applied magnetic or acoustic field. In the early stages of my doctoral studies, I developed a magnetic field manipulation technique to quantify the adhesion force between particles and surfaces. This manipulation technique is based on the magnetic dipolar interactions between colloidal particles and their "image dipoles" that appear within planar substrate. Since the particles interact with their own images, this system enables massively parallel surface force measurements (>100 measurements) in a single experiment, and allows statistical properties of particle-surface adhesion energies to be extracted as a function of loading rate. With this approach, I was able to probe sub-picoNewton surface interactions between colloidal particles and several substrates at the lowest force loading rates ever achieved. In the later stages of my doctoral studies, I focused on studying patterns formed from particle-particle interaction, which serve as an experimental model of

  20. SPATIO-TEMPORAL CHARACTERISTICS OF RESIDENT TRIP BASED ON POI AND OD DATA OF FLOAT CAR IN BEIJING

    OpenAIRE

    N. Mou; N. Mou; J. Li; L. Zhang; W. Liu; Y. Xu

    2017-01-01

    Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according t...

  1. Spatiotemporal patterns of population distribution as crucial element for risk management

    Science.gov (United States)

    Gokesch, Karin; Promper, Catrin; van Westen, Cees J.; Glade, Thomas

    2014-05-01

    The spatiotemporal distribution and presence of the population in a certain area is a crucial element within natural hazard risk management, especially in the case of rapid onset hazard events and emergency management. When fast onset hazards such as earthquakes, flash floods or industrial accidents occur, people may not have adequate time for evacuation and the emergency management requires a fast response and reaction. Therefore, information on detailed distribution of people affected by a certain hazard is important for a fast assessment of the situation including the number and the type of people (distinguishing between elderly or handicapped people, children, working population etc.) affected. This study thus aims at analyzing population distribution on an hourly basis for different days e.g. workday or holiday. The applied method combines the basic assessment of population distribution in a given area with specific location-related patterns of distribution-changes over time. The calculations are based on detailed information regarding the expected presence of certain groups of people, e.g. school children, working or elderly people, which all show different patterns of movement over certain time periods. The study area is the city of Waidhofen /Ybbs located in the Alpine foreland in the Southwest of Lower Austria. This city serves as a regional center providing basic infrastructure, shops and schools for the surrounding countryside. Therefore a lot of small and medium businesses are located in this area showing a rather high variation of population present at different times of the day. The available building footprint information was classified with respect to building type and occupancy type, which was used to estimate the expected residents within the buildings, based on the floorspace of the buildings and the average floorspace per person. Additional information on the distribution and the average duration of stay of the people in these buildings was

  2. Spatio-temporal dynamics of global H5N1 outbreaks match bird migration patterns

    Directory of Open Access Journals (Sweden)

    Yali Si

    2009-11-01

    Full Text Available The global spread of highly pathogenic avian influenza H5N1 in poultry, wild birds and humans, poses a significant pandemic threat and a serious public health risk. An efficient surveillance and disease control system relies on the understanding of the dispersion patterns and spreading mechanisms of the virus. A space-time cluster analysis of H5N1 outbreaks was used to identify spatio-temporal patterns at a global scale and over an extended period of time. Potential mechanisms explaining the spread of the H5N1 virus, and the role of wild birds, were analyzed. Between December 2003 and December 2006, three global epidemic phases of H5N1 influenza were identified. These H5N1 outbreaks showed a clear seasonal pattern, with a high density of outbreaks in winter and early spring (i.e., October to March. In phase I and II only the East Asia Australian flyway was affected. During phase III, the H5N1 viruses started to appear in four other flyways: the Central Asian flyway, the Black Sea Mediterranean flyway, the East Atlantic flyway and the East Africa West Asian flyway. Six disease cluster patterns along these flyways were found to be associated with the seasonal migration of wild birds. The spread of the H5N1 virus, as demonstrated by the space-time clusters, was associated with the patterns of migration of wild birds. Wild birds may therefore play an important role in the spread of H5N1 over long distances. Disease clusters were also detected at sites where wild birds are known to overwinter and at times when migratory birds were present. This leads to the suggestion that wild birds may also be involved in spreading the H5N1 virus over short distances.

  3. Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

    Science.gov (United States)

    Jung, Minju; Hwang, Jungsik; Tani, Jun

    2015-01-01

    It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

  4. Formation of self-organized anode patterns in arc discharge simulations

    International Nuclear Information System (INIS)

    Trelles, Juan Pablo

    2013-01-01

    Pattern formation and self-organization are phenomena commonly observed experimentally in diverse types of plasma systems, including atmospheric-pressure electric arc discharges. However, numerical simulations reproducing anode pattern formation in arc discharges have proven exceedingly elusive. Time-dependent three-dimensional thermodynamic non-equilibrium simulations reveal the spontaneous formation of self-organized patterns of anode attachment spots in the free-burning arc, a canonical thermal plasma flow established by a constant dc current between an axi-symmetric electrode configuration in the absence of external forcing. The number of spots, their size and distribution within the pattern depend on the applied total current and on the resolution of the spatial discretization, whereas the main properties of the plasma flow, such as maximum temperatures, velocity and voltage drop, depend only on the former. The sensibility of the solution to the spatial discretization stresses the computational requirements for comprehensive arc discharge simulations. The obtained anode patterns qualitatively agree with experimental observations and confirm that the spots originate at the fringes of the arc–anode attachment. The results imply that heavy-species–electron energy equilibration, in addition to thermal instability, has a dominant role in the formation of anode spots in arc discharges. (paper)

  5. Spatio-temporal pattern formation, fractals, and chaos in conceptual ecological models as applied to coupled plankton-fish dynamics

    International Nuclear Information System (INIS)

    Medvinskii, Aleksandr B; Tikhonova, Irina A; Tikhonov, D A; Ivanitskii, Genrikh R; Petrovskii, Sergei V; Li, B.-L.; Venturino, E; Malchow, H

    2002-01-01

    The current turn-of-the-century period witnesses the intensive use of the bioproducts of the World Ocean while at the same time calling for precautions to preserve its ecological stability. This requires that biophysical processes in aquatic systems be comprehensively explored and new methods for monitoring their dynamics be developed. While aquatic and terrestrial ecosystems have much in common in terms of their mathematical description, there are essential differences between them. For example, the mobility of oceanic plankton is mainly controlled by diffusion processes, whereas terrestrial organisms naturally enough obey totally different laws. This paper is focused on the processes underlying the dynamics of spatially inhomogeneous plankton communities. We demonstrate that conceptual reaction-diffusion mathematical models are an appropriate tool for investigating both complex spatio-temporal plankton dynamics and the fractal properties of planktivorous fish school walks. (reviews of topical problems)

  6. Pattern formation on Ge by low energy ion beam erosion

    International Nuclear Information System (INIS)

    Teichmann, Marc; Lorbeer, Jan; Frost, Frank; Rauschenbach, Bernd; Ziberi, Bashkim

    2013-01-01

    Modification of nanoscale surface topography is inherent to low-energy ion beam erosion processes and is one of the most important fields of nanotechnology. In this report a comprehensive study of surface smoothing and self-organized pattern formation on Ge(100) by using different noble gases ion beam erosion is presented. The investigations focus on low ion energies (⩽ 2000 eV) and include the entire range of ion incidence angles. It is found that for ions (Ne, Ar) with masses lower than the mass of the Ge target atoms, no pattern formation occurs and surface smoothing is observed for all angles of ion incidence. In contrast, for erosion with higher mass ions (Kr, Xe), ripple formation starts at incidence angles of about 65° depending on ion energy. At smaller incident angles surface smoothing occurs again. Investigations of the surface dynamics for specific ion incidence angles by changing the ion fluence over two orders of magnitude gives a clear evidence for coarsening and faceting of the surface pattern. Both observations indicate that gradient-dependent sputtering and reflection of primary ions play crucial role in the pattern evolution, just at the lowest accessible fluences. The results are discussed in relation to recently proposed redistributive or stress-induced models for pattern formation. In addition, it is argued that a large angular variation of the sputter yield and reflected primary ions can significantly contribute to pattern formation and evolution as nonlinear and non-local processes as supported by simulation of sputtering and ion reflection. (paper)

  7. Turing patterns induced by cross-diffusion in a predator-prey system in presence of habitat complexity

    International Nuclear Information System (INIS)

    Ghorai, Santu; Poria, Swarup

    2016-01-01

    In this paper, we have investigated the phenomena of Turing pattern formation in a predator-prey model with habitat complexity in presence of cross diffusion. Using the linear stability analysis, the conditions for the existence of stationary pattern and the existence of Hopf bifurcation are obtained. It is shown analytically that the presence of cross diffusion in the system supports the formation of Turing pattern. Two parameter bifurcation analysis are done analytically and corresponding bifurcation diagrams are presented numerically. A series of simulation results are plotted for different biologically meaningful parameter values. Effects of variation of habitat complexity and the predator mortality rate and birth rate of prey on pattern formation are also reported. It is shown that cross-diffusion can lead to a wide variety of spatial and spatiotemporal pattern formation. It is found that the model exhibits spot and stripe pattern, and coexistence of both spot and strip patterns under the zero flux boundary condition. It is observed that cross-diffusion, habitat complexity, birth rate of prey and predator’s mortality rate play a significant role in the pattern formation of a distributed population system of predator-prey type.

  8. Imaging collagen type I fibrillogenesis with high spatiotemporal resolution

    International Nuclear Information System (INIS)

    Stamov, Dimitar R; Stock, Erik; Franz, Clemens M; Jähnke, Torsten; Haschke, Heiko

    2015-01-01

    Fibrillar collagens, such as collagen type I, belong to the most abundant extracellular matrix proteins and they have received much attention over the last five decades due to their large interactome, complex hierarchical structure and high mechanical stability. Nevertheless, the collagen self-assembly process is still incompletely understood. Determining the real-time kinetics of collagen type I formation is therefore pivotal for better understanding of collagen type I structure and function, but visualising the dynamic self-assembly process of collagen I on the molecular scale requires imaging techniques offering high spatiotemporal resolution. Fast and high-speed scanning atomic force microscopes (AFM) provide the means to study such processes on the timescale of seconds under near-physiological conditions. In this study we have applied fast AFM tip scanning to study the assembly kinetics of fibrillar collagen type I nanomatrices with a temporal resolution reaching eight seconds for a frame size of 500 nm. By modifying the buffer composition and pH value, the kinetics of collagen fibrillogenesis can be adjusted for optimal analysis by fast AFM scanning. We furthermore show that amplitude-modulation imaging can be successfully applied to extract additional structural information from collagen samples even at high scan rates. Fast AFM scanning with controlled amplitude modulation therefore provides a versatile platform for studying dynamic collagen self-assembly processes at high resolution. - Highlights: • Continuous non-invasive time-lapse investigation of collagen I fibrillogenesis in situ. • Imaging of collagen I self-assembly with high spatiotemporal resolution. • Application of setpoint modulation to study the hierarchical structure of collagen I. • Observing real-time formation of the D-banding pattern in collagen I

  9. Imaging collagen type I fibrillogenesis with high spatiotemporal resolution

    Energy Technology Data Exchange (ETDEWEB)

    Stamov, Dimitar R, E-mail: stamov@jpk.com [JPK Instruments AG, Bouchéstrasse 12, 12435 Berlin (Germany); Stock, Erik [JPK Instruments AG, Bouchéstrasse 12, 12435 Berlin (Germany); Franz, Clemens M [DFG-Center for Functional Nanostructures (CFN), Karlsruhe Institute of Technology (KIT), Wolfgang-Gaede-Strasse 1a, 76131 Karlsruhe (Germany); Jähnke, Torsten; Haschke, Heiko [JPK Instruments AG, Bouchéstrasse 12, 12435 Berlin (Germany)

    2015-02-15

    Fibrillar collagens, such as collagen type I, belong to the most abundant extracellular matrix proteins and they have received much attention over the last five decades due to their large interactome, complex hierarchical structure and high mechanical stability. Nevertheless, the collagen self-assembly process is still incompletely understood. Determining the real-time kinetics of collagen type I formation is therefore pivotal for better understanding of collagen type I structure and function, but visualising the dynamic self-assembly process of collagen I on the molecular scale requires imaging techniques offering high spatiotemporal resolution. Fast and high-speed scanning atomic force microscopes (AFM) provide the means to study such processes on the timescale of seconds under near-physiological conditions. In this study we have applied fast AFM tip scanning to study the assembly kinetics of fibrillar collagen type I nanomatrices with a temporal resolution reaching eight seconds for a frame size of 500 nm. By modifying the buffer composition and pH value, the kinetics of collagen fibrillogenesis can be adjusted for optimal analysis by fast AFM scanning. We furthermore show that amplitude-modulation imaging can be successfully applied to extract additional structural information from collagen samples even at high scan rates. Fast AFM scanning with controlled amplitude modulation therefore provides a versatile platform for studying dynamic collagen self-assembly processes at high resolution. - Highlights: • Continuous non-invasive time-lapse investigation of collagen I fibrillogenesis in situ. • Imaging of collagen I self-assembly with high spatiotemporal resolution. • Application of setpoint modulation to study the hierarchical structure of collagen I. • Observing real-time formation of the D-banding pattern in collagen I.

  10. Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network

    Energy Technology Data Exchange (ETDEWEB)

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

    2018-02-01

    Non-intrusive load monitoring (NILM) of electrical demand for the purpose of identifying load components has thus far mostly been studied using univariate data, e.g., using only whole building electricity consumption time series to identify a certain type of end-use such as lighting load. However, using additional variables in the form of multivariate time series data may provide more information in terms of extracting distinguishable features in the context of energy disaggregation. In this work, a novel probabilistic graphical modeling approach, namely the spatiotemporal pattern network (STPN) is proposed for energy disaggregation using multivariate time-series data. The STPN framework is shown to be capable of handling diverse types of multivariate time-series to improve the energy disaggregation performance. The technique outperforms the state of the art factorial hidden Markov models (FHMM) and combinatorial optimization (CO) techniques in multiple real-life test cases. Furthermore, based on two homes' aggregate electric consumption data, a similarity metric is defined for the energy disaggregation of one home using a trained model based on the other home (i.e., out-of-sample case). The proposed similarity metric allows us to enhance scalability via learning supervised models for a few homes and deploying such models to many other similar but unmodeled homes with significantly high disaggregation accuracy.

  11. Pattern formation in superdiffusion Oregonator model

    Science.gov (United States)

    Feng, Fan; Yan, Jia; Liu, Fu-Cheng; He, Ya-Feng

    2016-10-01

    Pattern formations in an Oregonator model with superdiffusion are studied in two-dimensional (2D) numerical simulations. Stability analyses are performed by applying Fourier and Laplace transforms to the space fractional reaction-diffusion systems. Antispiral, stable turing patterns, and travelling patterns are observed by changing the diffusion index of the activator. Analyses of Floquet multipliers show that the limit cycle solution loses stability at the wave number of the primitive vector of the travelling hexagonal pattern. We also observed a transition between antispiral and spiral by changing the diffusion index of the inhibitor. Project supported by the National Natural Science Foundation of China (Grant Nos. 11205044 and 11405042), the Research Foundation of Education Bureau of Hebei Province, China (Grant Nos. Y2012009 and ZD2015025), the Program for Young Principal Investigators of Hebei Province, China, and the Midwest Universities Comprehensive Strength Promotion Project.

  12. Spatiotemporal complexity in coupled map lattices

    International Nuclear Information System (INIS)

    Kaneko, Kunihiko

    1986-01-01

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

  13. Understanding the Spatio-Temporal Pattern of Fire Disturbance in the Eastern Mongolia Using Modis Product

    Science.gov (United States)

    Wurihan; Zhang, H.; Zhang, Z.; Guo, X.; Zhao, J.; Duwala; Shan, Y.; Hongying

    2018-04-01

    Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1) The fire disturbance in eastern Mongolia has obvious high and low peak interleaving phenomenon in the year, and the seasonal change is obvious. (2) The distribution pattern of fire disturbance in eastern Mongolia is aggregated, which indicates that the fire disturbance is not random and it is caused by certain influence. (3) Fire disturbance is mainly distributed in the eastern province of Mongolia, the border between China and Mongolia and the northern forest area of Sukhbaatar province. (4) The fire disturbance in the eastern part of the study area is strong and the southwest is weaker. The spreading regularity of fire disturbances in eastern Mongolia is closer to the natural level of ecosystem.

  14. UNDERSTANDING THE SPATIO-TEMPORAL PATTERN OF FIRE DISTURBANCE IN THE EASTERN MONGOLIA USING MODIS PRODUCT

    Directory of Open Access Journals (Sweden)

    Wurihan

    2018-04-01

    Full Text Available Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1 The fire disturbance in eastern Mongolia has obvious high and low peak interleaving phenomenon in the year, and the seasonal change is obvious. (2 The distribution pattern of fire disturbance in eastern Mongolia is aggregated, which indicates that the fire disturbance is not random and it is caused by certain influence. (3 Fire disturbance is mainly distributed in the eastern province of Mongolia, the border between China and Mongolia and the northern forest area of Sukhbaatar province. (4 The fire disturbance in the eastern part of the study area is strong and the southwest is weaker. The spreading regularity of fire disturbances in eastern Mongolia is closer to the natural level of ecosystem.

  15. Nutrients and toxin producing phytoplankton control algal blooms - a spatio-temporal study in a noisy environment.

    Science.gov (United States)

    Sarkar, Ram Rup; Malchow, Horst

    2005-12-01

    A phytoplankton-zooplankton prey-predator model has been investigated for temporal, spatial and spatio-temporal dissipative pattern formation in a deterministic and noisy environment, respectively. The overall carrying capacity for the phytoplankton population depends on the nutrient level. The role of nutrient concentrations and toxin producing phytoplankton for controlling the algal blooms has been discussed. The local analysis yields a number of stationary and/or oscillatory regimes and their combinations. Correspondingly interesting is the spatio-temporal behaviour, modelled by stochastic reaction-diffusion equations. The present study also reveals the fact that the rate of toxin production by toxin producing phytoplankton (TPP) plays an important role for controlling oscillations in the plankton system. We also observe that different mortality functions of zooplankton due to TPP have significant influence in controlling oscillations, coexistence, survival or extinction of the zoo-plankton population. External noise can enhance the survival and spread of zooplankton that would go extinct in the deterministic system due to a high rate of toxin production.

  16. [The physics of pattern formation at liquid interfaces

    International Nuclear Information System (INIS)

    1990-01-01

    This paper discusses pattern formation at liquid interfaces and interfaces within disordered materials. The particular topics discussed are: a racetrack for competing viscous fingers; an experimental realization of periodic boundary conditions; what sets the length scale for patterns between miscible liquids; the fractal dimension of radial Hele-Shaw patterns; detailed analyses of low-contrast Saffman-Taylor flows; and the wetting/absorption properties of polystyrene spheres in binary liquid mixtures

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

    Directory of Open Access Journals (Sweden)

    Ram K Raghavan

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

  18. Vegetation pattern formation in a fog-dependent ecosystem.

    Science.gov (United States)

    Borthagaray, Ana I; Fuentes, Miguel A; Marquet, Pablo A

    2010-07-07

    Vegetation pattern formation is a striking characteristic of several water-limited ecosystems around the world. Typically, they have been described on runoff-based ecosystems emphasizing local interactions between water, biomass interception, growth and dispersal. Here, we show that this situation is by no means general, as banded patterns in vegetation can emerge in areas without rainfall and in plants without functional root (the Bromeliad Tillandsia landbeckii) and where fog is the principal source of moisture. We show that a simple model based on the advection of fog-water by wind and its interception by the vegetation can reproduce banded patterns which agree with empirical patterns observed in the Coastal Atacama Desert. Our model predicts how the parameters may affect the conditions to form the banded pattern, showing a transition from a uniform vegetated state, at high water input or terrain slope to a desert state throughout intermediate banded states. Moreover, the model predicts that the pattern wavelength is a decreasing non-linear function of fog-water input and slope, and an increasing function of plant loss and fog-water flow speed. Finally, we show that the vegetation density is increased by the formation of the regular pattern compared to the density expected by the spatially homogeneous model emphasizing the importance of self-organization in arid ecosystems. (c) 2010 Elsevier Ltd. All rights reserved.

  19. Tensor analysis methods for activity characterization in spatiotemporal data

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-03-01

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

  20. Routes to spatiotemporal chaos in Kerr optical frequency combs.

    Science.gov (United States)

    Coillet, Aurélien; Chembo, Yanne K

    2014-03-01

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

  1. Drought effects on US maize and soybean production: spatiotemporal patterns and historical changes

    Science.gov (United States)

    Zipper, Samuel C.; Qiu, Jiangxiao; Kucharik, Christopher J.

    2016-09-01

    Maximizing agricultural production on existing cropland is one pillar of meeting future global food security needs. To close crop yield gaps, it is critical to understand how climate extremes such as drought impact yield. Here, we use gridded, daily meteorological data and county-level annual yield data to quantify meteorological drought sensitivity of US maize and soybean production from 1958 to 2007. Meteorological drought negatively affects crop yield over most US crop-producing areas, and yield is most sensitive to short-term (1-3 month) droughts during critical development periods from July to August. While meteorological drought is associated with 13% of overall yield variability, substantial spatial variability in drought effects and sensitivity exists, with central and southeastern US becoming increasingly sensitive to drought over time. Our study illustrates fine-scale spatiotemporal patterns of drought effects, highlighting where variability in crop production is most strongly associated with drought, and suggests that management strategies that buffer against short-term water stress may be most effective at sustaining long-term crop productivity.

  2. Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.

    Science.gov (United States)

    Matsubara, Takashi

    2017-01-01

    Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning.

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

    Directory of Open Access Journals (Sweden)

    Christakos George

    2006-03-01

    Full Text Available Abstract 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

  4. Synchronization stability and pattern selection in a memristive neuronal network

    Science.gov (United States)

    Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

    2017-11-01

    Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

  5. Synchronization stability and pattern selection in a memristive neuronal network.

    Science.gov (United States)

    Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

    2017-11-01

    Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

  6. Visual representation of spatiotemporal structure

    Science.gov (United States)

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

    1998-07-01

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

  7. Mining User spatiotemporal Behavior in Geospatial Cyberinfrastructure --using GEOSS Clearinghouse as an example

    Science.gov (United States)

    XIA, J.; Yang, C.; Liu, K.; Huang, Q.; Li, Z.

    2013-12-01

    Big Data becomes increasingly important in almost all scientific domains, especially in geoscience where hundreds to millions of sensors are collecting data of the Earth continuously (Whitehouse News 2012). With the explosive growth of data, various Geospatial Cyberinfrastructure (GCI) (Yang et al. 2010) components are developed to manage geospatial resources and provide data access for the public. These GCIs are accessed by different users intensively on a daily basis. However, little research has been done to analyze the spatiotemporal patterns of user behavior, which could be critical to the management of Big Data and the operation of GCIs (Yang et al. 2011). For example, the spatiotemporal distribution of end users helps us better arrange and locate GCI computing facilities. A better indexing and caching mechanism could be developed based on the spatiotemporal pattern of user queries. In this paper, we use GEOSS Clearinghouse as an example to investigate spatiotemporal patterns of user behavior in GCIs. The investigation results show that user behaviors are heterogeneous but with patterns across space and time. Identified patterns include (1) the high access frequency regions; (2) local interests; (3) periodical accesses and rush hours; (4) spiking access. Based on identified patterns, this presentation reports several solutions to better support the operation of the GEOSS Clearinghouse and other GCIs. Keywords: Big Data, EarthCube, CyberGIS, Spatiotemporal Thinking and Computing, Data Mining, User Behavior Reference: Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P., & Uthurusamy, R. 1996. Advances in knowledge discovery and data mining. Whitehouse. 2012. Obama administration unveils 'BIG DATA' initiative: announces $200 million in new R&D investments. Whitehouse. Retrieved from http://www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_press_release_final_2.pdf [Accessed 14 June 2013] Yang, C., Wu, H., Huang, Q., Li, Z., & Li, J. 2011. Using spatial

  8. Pattern formation of a nonlocal, anisotropic interaction model

    KAUST Repository

    Burger, Martin

    2017-11-24

    We consider a class of interacting particle models with anisotropic, repulsive–attractive interaction forces whose orientations depend on an underlying tensor field. An example of this class of models is the so-called Kücken–Champod model describing the formation of fingerprint patterns. This class of models can be regarded as a generalization of a gradient flow of a nonlocal interaction potential which has a local repulsion and a long-range attraction structure. In contrast to isotropic interaction models the anisotropic forces in our class of models cannot be derived from a potential. The underlying tensor field introduces an anisotropy leading to complex patterns which do not occur in isotropic models. This anisotropy is characterized by one parameter in the model. We study the variation of this parameter, describing the transition between the isotropic and the anisotropic model, analytically and numerically. We analyze the equilibria of the corresponding mean-field partial differential equation and investigate pattern formation numerically in two dimensions by studying the dependence of the parameters in the model on the resulting patterns.

  9. Pattern formation of a nonlocal, anisotropic interaction model

    KAUST Repository

    Burger, Martin; Dü ring, Bertram; Kreusser, Lisa Maria; Markowich, Peter A.; Schö nlieb, Carola-Bibiane

    2017-01-01

    We consider a class of interacting particle models with anisotropic, repulsive–attractive interaction forces whose orientations depend on an underlying tensor field. An example of this class of models is the so-called Kücken–Champod model describing the formation of fingerprint patterns. This class of models can be regarded as a generalization of a gradient flow of a nonlocal interaction potential which has a local repulsion and a long-range attraction structure. In contrast to isotropic interaction models the anisotropic forces in our class of models cannot be derived from a potential. The underlying tensor field introduces an anisotropy leading to complex patterns which do not occur in isotropic models. This anisotropy is characterized by one parameter in the model. We study the variation of this parameter, describing the transition between the isotropic and the anisotropic model, analytically and numerically. We analyze the equilibria of the corresponding mean-field partial differential equation and investigate pattern formation numerically in two dimensions by studying the dependence of the parameters in the model on the resulting patterns.

  10. Pattern formation in reaction diffusion systems with finite geometry

    International Nuclear Information System (INIS)

    Borzi, C.; Wio, H.

    1990-04-01

    We analyze the one-component, one-dimensional, reaction-diffusion equation through a simple inverse method. We confine the system and fix the boundary conditions as to induce pattern formation. We analyze the stability of those patterns. Our goal is to get information about the reaction term out of the preknowledgment of the pattern. (author). 5 refs

  11. Nonlinear dynamics of pattern formation and pattern recognition in the rabbit olfactory bulb

    Science.gov (United States)

    Baird, Bill

    1986-10-01

    A mathematical model of the process of pattern recognition in the first olfactory sensory cortex of the rabbit is presented. It explains the formation and alteration of spatial patterns in neural activity observed experimentally during classical Pavlovian conditioning. On each inspiration of the animal, a surge of receptor input enters the olfactory bulb. EEG activity recorded at the surface of the bulb undergoes a transition from a low amplitude background state of temporal disorder to coherent oscillation. There is a distinctive spatial pattern of rms amplitude in this oscillation which changes reliably to a second pattern during each successful recognition by the animal of a conditioned stimulus odor. When a new odor is paired as conditioned stimulus, these patterns are replaced by new patterns that stabilize as the animal adapts to the new environment. I will argue that a unification of the theories of pattern formation and associative memory is required to account for these observations. This is achieved in a model of the bulb as a discrete excitable medium with spatially inhomogeneous coupling expressed by a connection matrix. The theory of multiple Hopf bifurcations is employed to find coupled equations for the amplitudes of competing unstable oscillatory modes. These may be created in the system by proper coupling and selectively evoked by specific classes of inputs. This allows a view of limit cycle attractors as “stored” fixed points of a gradient vector field and thereby recovers the more familiar dynamical systems picture of associative memory.

  12. Discrete simulations of spatio-temporal dynamics of small water bodies under varied stream flow discharges

    Science.gov (United States)

    Daya Sagar, B. S.

    2005-01-01

    Spatio-temporal patterns of small water bodies (SWBs) under the influence of temporally varied stream flow discharge are simulated in discrete space by employing geomorphologically realistic expansion and contraction transformations. Cascades of expansion-contraction are systematically performed by synchronizing them with stream flow discharge simulated via the logistic map. Templates with definite characteristic information are defined from stream flow discharge pattern as the basis to model the spatio-temporal organization of randomly situated surface water bodies of various sizes and shapes. These spatio-temporal patterns under varied parameters (λs) controlling stream flow discharge patterns are characterized by estimating their fractal dimensions. At various λs, nonlinear control parameters, we show the union of boundaries of water bodies that traverse the water body and non-water body spaces as geomorphic attractors. The computed fractal dimensions of these attractors are 1.58, 1.53, 1.78, 1.76, 1.84, and 1.90, respectively, at λs of 1, 2, 3, 3.46, 3.57, and 3.99. These values are in line with general visual observations.

  13. Discrete simulations of spatio-temporal dynamics of small water bodies under varied stream flow discharges

    Directory of Open Access Journals (Sweden)

    B. S. Daya Sagar

    2005-01-01

    Full Text Available Spatio-temporal patterns of small water bodies (SWBs under the influence of temporally varied stream flow discharge are simulated in discrete space by employing geomorphologically realistic expansion and contraction transformations. Cascades of expansion-contraction are systematically performed by synchronizing them with stream flow discharge simulated via the logistic map. Templates with definite characteristic information are defined from stream flow discharge pattern as the basis to model the spatio-temporal organization of randomly situated surface water bodies of various sizes and shapes. These spatio-temporal patterns under varied parameters (λs controlling stream flow discharge patterns are characterized by estimating their fractal dimensions. At various λs, nonlinear control parameters, we show the union of boundaries of water bodies that traverse the water body and non-water body spaces as geomorphic attractors. The computed fractal dimensions of these attractors are 1.58, 1.53, 1.78, 1.76, 1.84, and 1.90, respectively, at λs of 1, 2, 3, 3.46, 3.57, and 3.99. These values are in line with general visual observations.

  14. Understanding spatial and temporal patterning of astrocyte calcium transients via interactions between network transport and extracellular diffusion

    Science.gov (United States)

    Shtrahman, E.; Maruyama, D.; Olariu, E.; Fink, C. G.; Zochowski, M.

    2017-02-01

    Astrocytes form interconnected networks in the brain and communicate via calcium signaling. We investigate how modes of coupling between astrocytes influence the spatio-temporal patterns of calcium signaling within astrocyte networks and specifically how these network interactions promote coordination within this group of cells. To investigate these complex phenomena, we study reduced cultured networks of astrocytes and neurons. We image the spatial temporal patterns of astrocyte calcium activity and quantify how perturbing the coupling between astrocytes influences astrocyte activity patterns. To gain insight into the pattern formation observed in these cultured networks, we compare the experimentally observed calcium activity patterns to the patterns produced by a reduced computational model, where we represent astrocytes as simple units that integrate input through two mechanisms: gap junction coupling (network transport) and chemical release (extracellular diffusion). We examine the activity patterns in the simulated astrocyte network and their dependence upon these two coupling mechanisms. We find that gap junctions and extracellular chemical release interact in astrocyte networks to modulate the spatiotemporal patterns of their calcium dynamics. We show agreement between the computational and experimental findings, which suggests that the complex global patterns can be understood as a result of simple local coupling mechanisms.

  15. Pattern formation in three-dimensional reaction-diffusion systems

    Science.gov (United States)

    Callahan, T. K.; Knobloch, E.

    1999-08-01

    Existing group theoretic analysis of pattern formation in three dimensions [T.K. Callahan, E. Knobloch, Symmetry-breaking bifurcations on cubic lattices, Nonlinearity 10 (1997) 1179-1216] is used to make specific predictions about the formation of three-dimensional patterns in two models of the Turing instability, the Brusselator model and the Lengyel-Epstein model. Spatially periodic patterns having the periodicity of the simple cubic (SC), face-centered cubic (FCC) or body-centered cubic (BCC) lattices are considered. An efficient center manifold reduction is described and used to identify parameter regimes permitting stable lamellæ, SC, FCC, double-diamond, hexagonal prism, BCC and BCCI states. Both models possess a special wavenumber k* at which the normal form coefficients take on fixed model-independent ratios and both are described by identical bifurcation diagrams. This property is generic for two-species chemical reaction-diffusion models with a single activator and inhibitor.

  16. Understanding spatio-temporal mobility patterns for seniors, child/student and adult using smart card data

    Science.gov (United States)

    Huang, X.; Tan, J.

    2014-11-01

    Commutes in urban areas create interesting travel patterns that are often stored in regional transportation databases. These patterns can vary based on the day of the week, the time of the day, and commuter type. This study proposes methods to detect underlying spatio-temporal variability among three groups of commuters (senior citizens, child/students, and adults) using data mining and spatial analytics. Data from over 36 million individual trip records collected over one week (March 2012) on the Singapore bus and Mass Rapid Transit (MRT) system by the fare collection system were used. Analyses of such data are important for transportation and landuse designers and contribute to a better understanding of urban dynamics. Specifically, descriptive statistics, network analysis, and spatial analysis methods are presented. Descriptive variables were proposed such as density and duration to detect temporal features of people. A directed weighted graph G ≡ (N , L, W) was defined to analyze the global network properties of every pair of the transportation link in the city during an average workday for all three categories. Besides, spatial interpolation and spatial statistic tools were used to transform the discrete network nodes into structured human movement landscape to understand the role of transportation systems in urban areas. The travel behaviour of the three categories follows a certain degree of temporal and spatial universality but also displays unique patterns within their own specialties. Each category is characterized by their different peak hours, commute distances, and specific locations for travel on weekdays.

  17. Pattern formation during electropolishing

    International Nuclear Information System (INIS)

    Yuzhakov, V.V.; Chang, H.; Miller, A.E.

    1997-01-01

    Using atomic force microscopy, we find that the surface morphology of a dissolving aluminum anode in a commercial electropolishing electrolyte can exhibit both highly regular and randomly packed stripe and hexagonal patterns with amplitudes of about 5 nm and wavelengths of 100 nm. The driving instability of this pattern formation phenomenon is proposed to be the preferential adsorption of polar or polarizable organic molecules on surface ridges where the contorted double layer produces a higher electric potential gradient. The enhanced relative coverage shields the anode and induces a smaller dissolution rate at the ridges. The instability is balanced by surface diffusion of the adsorbate to yield a length scale of 4π(D s /k d ) 1/2 , where D s is the surface diffusivity and k d is the desorption coefficient of the adsorbate, which correlates well with the measured wavelength. A long-wavelength expansion of the double-layer field yields an interface evolution equation that reproduces all of the observed patterns. In particular, bifurcation analysis and numerical simulation yield a single voltage-dependent dimensionless parameter ξ that measures a balance between smoothing of adsorbate concentration by electric-field-dependent surface diffusion and fluctuation due to interfacial curvature and stretching. Randomly oriented stripes are favored at large ξ (low voltage), while random hills dominate at small ξ (high voltage) with perfectly periodic stripes and hexagonal hill patterns within a small window near ξ=1. These predictions are in qualitative and quantitative agreement with our measurements. copyright 1997 The American Physical Society

  18. Annual spatiotemporal migration schedules in three larger insectivorous birds

    DEFF Research Database (Denmark)

    Jacobsen, Lars Bo; Jensen, Niels Odder; Willemoes, Mikkel

    2017-01-01

    Background: Knowledge of spatiotemporal migration patterns is important for our understanding of migration ecology and ultimately conservation of migratory species. We studied the annual migration schedules of European nightjar, a large nocturnal insectivore and compared it with two other larger ...

  19. Bifurcation analysis and spatio-temporal patterns of nonlinear oscillations in a delayed neural network with unidirectional coupling

    International Nuclear Information System (INIS)

    Song Yongli; Tadé, Moses O; Zhang Tonghua

    2009-01-01

    In this paper, a delayed neural network with unidirectional coupling is considered which consists of two two-dimensional nonlinear differential equation systems with exponential decay where one system receives a delayed input from the other system. Some parameter regions are given for conditional/absolute stability and Hopf bifurcations by using the theory of functional differential equations. Conditions ensuring the stability and direction of the Hopf bifurcation are determined by applying the normal form theory and the centre manifold theorem. We also investigate the spatio-temporal patterns of bifurcating periodic oscillations by using the symmetric bifurcation theory of delay-differential equations combined with representation theory of Lie groups. Then the global continuation of phase-locked periodic solutions is investigated. Numerical simulations are given to illustrate the results obtained

  20. Pattern Transitions in Bacterial Oscillating System under Nanofluidic Confinement

    Science.gov (United States)

    Shen, Jie-Pan; Chou, Chia-Fu

    2011-03-01

    Successful binary fission in E. coli relies on remarkable oscillatory behavior of the MinCDE protein system to determine the exact division site. The most favorable models to explain this fascinating spatiotemporal regulation on dynamic MinDE pattern formation in cells are based on reaction-diffusion scenario. Although not fully understood, geometric factors caused by bacterial morphology play a crucial role in MinDE dynamics. In the present study, bacteria were cultured, confined and reshaped in various micro/nanofluidic devices, to mimic either curvature changes of cell peripherals. Fluorescence imaging was utilized to detail the mode transitions in multiple MinDE patterns. The understanding of the physics in multiple pattern formations is further complemented via in silico modeling. The study synergizes the join merits of in vivo, in vitro and in silico approaches, to grasp the insight of stochastic dynamics inherited from the noisy mesoscopic biophysics. We acknowledge support from the Foresight Project, Academia Sinica.

  1. Secondary Instabilities and Spatiotemporal Chaos in Parametric Surface Waves

    International Nuclear Information System (INIS)

    Zhang, W.; Vinals, J.

    1995-01-01

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

  2. Dewetting-mediated pattern formation inside the coffee ring

    Science.gov (United States)

    Li, Weibin; Lan, Ding; Wang, Yuren

    2017-04-01

    The rearrangement of particles in the final stage of droplet evaporation has been investigated by utilizing differential interference contrast microscopy and the formation mechanism of a network pattern inside a coffee ring has been revealed. A tailored substrate with a circular hydrophilic domain is prepared to obtain thin liquid film containing monolayer particles. Real-time bottom-view images show that the evolution of a dry patch could be divided into three stages: rupture initiation, dry patch expansion, and drying of the residual liquid. A growing number of dry patches will repeat these stages to form the network patterns inside the ringlike stain. It can be shown that the suction effect promotes the rupture of the liquid film and the formation of the dry patch. The particle-assembling process is totally controlled by the liquid film dewetting and dominated by the surface tension of the liquid film, which eventually determine the ultimate deposition patterns.

  3. Spatiotemporal Stochastic Resonance:Theory and Experiment

    Science.gov (United States)

    Peter, Jung

    1996-03-01

    The amplification of weak periodic signals in bistable or excitable systems via stochastic resonance has been studied intensively over the last years. We are going one step further and ask: Can noise enhance spatiotemporal patterns in excitable media and can this effect be observed in nature? To this end, we are looking at large, two dimensional arrays of coupled excitable elements. Due to the coupling, excitation can propagate through the array in form of nonlinear waves. We observe target waves, rotating spiral waves and other wave forms. If the coupling between the elements is below a critical threshold, any excitational pattern will die out in the absence of noise. Below this threshold, large scale rotating spiral waves - as they are observed above threshold - can be maintained by a proper level of the noise[1]. Furthermore, their geometric features, such as the curvature can be controlled by the homogeneous noise level[2]. If the noise level is too large, break up of spiral waves and collisions with spontaneously nucleated waves yields spiral turbulence. Driving our array with a spatiotemporal pattern, e.g. a rotating spiral wave, we show that for weak coupling the excitational response of the array shows stochastic resonance - an effect we have termed spatiotemporal stochastic resonance. In the last part of the talk I'll make contact with calcium waves, observed in astrocyte cultures and hippocampus slices[3]. A. Cornell-Bell and collaborators[3] have pointed out the role of calcium waves for long-range glial signaling. We demonstrate the similarity of calcium waves with nonlinear waves in noisy excitable media. The noise level in the tissue is characterized by spontaneous activity and can be controlled by applying neuro-transmitter substances[3]. Noise effects in our model are compared with the effect of neuro-transmitters on calcium waves. [1]P. Jung and G. Mayer-Kress, CHAOS 5, 458 (1995). [2]P. Jung and G. Mayer-Kress, Phys. Rev. Lett.62, 2682 (1995). [3

  4. Spatio-Temporal Rule Mining

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo; Pedersen, Torben Bach

    2005-01-01

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

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  6. Recapitulation of physiological spatiotemporal signals promotes in vitro formation of phenotypically stable human articular cartilage

    Science.gov (United States)

    Wei, Yiyong; Zhou, Bin; Bernhard, Jonathan; Robinson, Samuel; Burapachaisri, Aonnicha; Guo, X. Edward

    2017-01-01

    Standard isotropic culture fails to recapitulate the spatiotemporal gradients present during native development. Cartilage grown from human mesenchymal stem cells (hMSCs) is poorly organized and unstable in vivo. We report that human cartilage with physiologic organization and in vivo stability can be grown in vitro from self-assembling hMSCs by implementing spatiotemporal regulation during induction. Self-assembling hMSCs formed cartilage discs in Transwell inserts following isotropic chondrogenic induction with transforming growth factor β to set up a dual-compartment culture. Following a switch in the basal compartment to a hypertrophic regimen with thyroxine, the cartilage discs underwent progressive deep-zone hypertrophy and mineralization. Concurrent chondrogenic induction in the apical compartment enabled the maintenance of functional and hyaline cartilage. Cartilage homeostasis, chondrocyte maturation, and terminal differentiation markers were all up-regulated versus isotropic control groups. We assessed the in vivo stability of the cartilage formed under different induction regimens. Cartilage formed under spatiotemporal regulation in vitro resisted endochondral ossification, retained the expression of cartilage markers, and remained organized following s.c. implantation in immunocompromised mice. In contrast, the isotropic control groups underwent endochondral ossification. Cartilage formed from hMSCs remained stable and organized in vivo. Spatiotemporal regulation during induction in vitro recapitulated some aspects of native cartilage development, and potentiated the maturation of self-assembling hMSCs into stable and organized cartilage resembling the native articular cartilage. PMID:28228529

  7. An experimental design method leading to chemical Turing patterns.

    Science.gov (United States)

    Horváth, Judit; Szalai, István; De Kepper, Patrick

    2009-05-08

    Chemical reaction-diffusion patterns often serve as prototypes for pattern formation in living systems, but only two isothermal single-phase reaction systems have produced sustained stationary reaction-diffusion patterns so far. We designed an experimental method to search for additional systems on the basis of three steps: (i) generate spatial bistability by operating autoactivated reactions in open spatial reactors; (ii) use an independent negative-feedback species to produce spatiotemporal oscillations; and (iii) induce a space-scale separation of the activatory and inhibitory processes with a low-mobility complexing agent. We successfully applied this method to a hydrogen-ion autoactivated reaction, the thiourea-iodate-sulfite (TuIS) reaction, and noticeably produced stationary hexagonal arrays of spots and parallel stripes of pH patterns attributed to a Turing bifurcation. This method could be extended to biochemical reactions.

  8. Structure Formation of Ultrathin PEO Films at Solid Interfaces—Complex Pattern Formation by Dewetting and Crystallization

    Science.gov (United States)

    Braun, Hans-Georg; Meyer, Evelyn

    2013-01-01

    The direct contact of ultrathin polymer films with a solid substrate may result in thin film rupture caused by dewetting. With crystallisable polymers such as polyethyleneoxide (PEO), molecular self-assembly into partial ordered lamella structures is studied as an additional source of pattern formation. Morphological features in ultrathin PEO films (thickness dewetting patterns and diffusion limited growth pattern of ordered lamella growing within the dewetting areas. Besides structure formation of hydrophilic PEO molecules, n-alkylterminated (hydrophobic) PEO oligomers are investigated with respect to self-organization in ultrathin films. Morphological features characteristic for pure PEO are not changed by the presence of the n-alkylgroups. PMID:23385233

  9. Improved Discriminability of Spatiotemporal Neural Patterns in Rat Motor Cortical Areas as Directional Choice Learning Progresses

    Directory of Open Access Journals (Sweden)

    Hongwei eMao

    2015-03-01

    Full Text Available Animals learn to choose a proper action among alternatives to improve their odds of success in food foraging and other activities critical for survival. Through trial-and-error, they learn correct associations between their choices and external stimuli. While a neural network that underlies such learning process has been identified at a high level, it is still unclear how individual neurons and a neural ensemble adapt as learning progresses. In this study, we monitored the activity of single units in the rat medial and lateral agranular (AGm and AGl, respectively areas as rats learned to make a left or right side lever press in response to a left or right side light cue. We noticed that rat movement parameters during the performance of the directional choice task quickly became stereotyped during the first 2-3 days or sessions. But learning the directional choice problem took weeks to occur. Accompanying rats’ behavioral performance adaptation, we observed neural modulation by directional choice in recorded single units. Our analysis shows that ensemble mean firing rates in the cue-on period did not change significantly as learning progressed, and the ensemble mean rate difference between left and right side choices did not show a clear trend of change either. However, the spatiotemporal firing patterns of the neural ensemble exhibited improved discriminability between the two directional choices through learning. These results suggest a spatiotemporal neural coding scheme in a motor cortical neural ensemble that may be responsible for and contributing to learning the directional choice task.

  10. Wavenumber locking and pattern formation in spatially forced systems

    International Nuclear Information System (INIS)

    Manor, Rotem; Meron, Ehud; Hagberg, Aric

    2009-01-01

    We study wavenumber locking and pattern formation resulting from weak spatially periodic one-dimensional forcing of two-dimensional systems. We consider systems that produce stationary or traveling stripe patterns when unforced and apply forcing aligned with the stripes. Forcing at close to twice the pattern wavenumber selects, stabilizes, or creates resonant stripes locked at half the forcing wavenumber. If the mismatch between the forcing and pattern wavenumber is high we find that the pattern still locks but develops a wave vector component perpendicular to the forcing direction and forms rectangular and oblique patterns. When the unforced system supports traveling waves, resonant rectangular patterns remain stationary but oblique patterns travel in a direction orthogonal to the traveling waves.

  11. Active sensing via movement shapes spatiotemporal patterns of sensory feedback.

    Science.gov (United States)

    Stamper, Sarah A; Roth, Eatai; Cowan, Noah J; Fortune, Eric S

    2012-05-01

    Previous work has shown that animals alter their locomotor behavior to increase sensing volumes. However, an animal's own movement also determines the spatial and temporal dynamics of sensory feedback. Because each sensory modality has unique spatiotemporal properties, movement has differential and potentially independent effects on each sensory system. Here we show that weakly electric fish dramatically adjust their locomotor behavior in relation to changes of modality-specific information in a task in which increasing sensory volume is irrelevant. We varied sensory information during a refuge-tracking task by changing illumination (vision) and conductivity (electroreception). The gain between refuge movement stimuli and fish tracking responses was functionally identical across all sensory conditions. However, there was a significant increase in the tracking error in the dark (no visual cues). This was a result of spontaneous whole-body oscillations (0.1 to 1 Hz) produced by the fish. These movements were costly: in the dark, fish swam over three times further when tracking and produced more net positive mechanical work. The magnitudes of these oscillations increased as electrosensory salience was degraded via increases in conductivity. In addition, tail bending (1.5 to 2.35 Hz), which has been reported to enhance electrosensory perception, occurred only during trials in the dark. These data show that both categories of movements - whole-body oscillations and tail bends - actively shape the spatiotemporal dynamics of electrosensory feedback.

  12. Pattern Formation in Predator-Prey Model with Delay and Cross Diffusion

    Directory of Open Access Journals (Sweden)

    Xinze Lian

    2013-01-01

    Full Text Available We consider the effect of time delay and cross diffusion on the dynamics of a modified Leslie-Gower predator-prey model incorporating a prey refuge. Based on the stability analysis, we demonstrate that delayed feedback may generate Hopf and Turing instability under some conditions, resulting in spatial patterns. One of the most interesting findings is that the model exhibits complex pattern replication: the model dynamics exhibits a delay and diffusion controlled formation growth not only to spots, stripes, and holes, but also to spiral pattern self-replication. The results indicate that time delay and cross diffusion play important roles in pattern formation.

  13. A survey on pattern formation of autonomous mobile robots: asynchrony, obliviousness and visibility

    International Nuclear Information System (INIS)

    Yamauchi, Yukiko

    2013-01-01

    A robot system consists of autonomous mobile robots each of which repeats Look-Compute-Move cycles, where the robot observes the positions of other robots (Look phase), computes the track to the next location (Compute phase), and moves along the track (Move phase). In this survey, we focus on self-organization of mobile robots, especially their power of forming patterns. The formation power of a robot system is the class of patterns that the robots can form, and existing results show that the robot system's formation power is determined by their asynchrony, obliviousness, and visibility. We briefly survey existing results, with impossibilities and pattern formation algorithms. Finally, we present several open problems related to the pattern formation problem of mobile robots

  14. Identification of spatiotemporal nutrient patterns in a coastal bay via an integrated k-means clustering and gravity model.

    Science.gov (United States)

    Chang, Ni-Bin; Wimberly, Brent; Xuan, Zhemin

    2012-03-01

    This study presents an integrated k-means clustering and gravity model (IKCGM) for investigating the spatiotemporal patterns of nutrient and associated dissolved oxygen levels in Tampa Bay, Florida. By using a k-means clustering analysis to first partition the nutrient data into a user-specified number of subsets, it is possible to discover the spatiotemporal patterns of nutrient distribution in the bay and capture the inherent linkages of hydrodynamic and biogeochemical features. Such patterns may then be combined with a gravity model to link the nutrient source contribution from each coastal watershed to the generated clusters in the bay to aid in the source proportion analysis for environmental management. The clustering analysis was carried out based on 1 year (2008) water quality data composed of 55 sample stations throughout Tampa Bay collected by the Environmental Protection Commission of Hillsborough County. In addition, hydrological and river water quality data of the same year were acquired from the United States Geological Survey's National Water Information System to support the gravity modeling analysis. The results show that the k-means model with 8 clusters is the optimal choice, in which cluster 2 at Lower Tampa Bay had the minimum values of total nitrogen (TN) concentrations, chlorophyll a (Chl-a) concentrations, and ocean color values in every season as well as the minimum concentration of total phosphorus (TP) in three consecutive seasons in 2008. The datasets indicate that Lower Tampa Bay is an area with limited nutrient input throughout the year. Cluster 5, located in Middle Tampa Bay, displayed elevated TN concentrations, ocean color values, and Chl-a concentrations, suggesting that high values of colored dissolved organic matter are linked with some nutrient sources. The data presented by the gravity modeling analysis indicate that the Alafia River Basin is the major contributor of nutrients in terms of both TP and TN values in all seasons

  15. Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.

    Science.gov (United States)

    Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

    2017-01-01

    There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.

  16. Pattern formation induced by cross-diffusion in a predator–prey system

    International Nuclear Information System (INIS)

    Sun Guiquan; Jin Zhen; Liu Quanxing; Li Li

    2008-01-01

    This paper considers the Holling–Tanner model for predator–prey with self and cross-diffusion. From the Turing theory, it is believed that there is no Turing pattern formation for the equal self-diffusion coefficients. However, combined with cross-diffusion, it shows that the system will exhibit spotted pattern by both mathematical analysis and numerical simulations. Furthermore, asynchrony of the predator and the prey in the space. The obtained results show that cross-diffusion plays an important role on the pattern formation of the predator–prey system. (general)

  17. Structure Formation of Ultrathin PEO Films at Solid Interfaces—Complex Pattern Formation by Dewetting and Crystallization

    Directory of Open Access Journals (Sweden)

    Hans-Georg Braun

    2013-02-01

    Full Text Available The direct contact of ultrathin polymer films with a solid substrate may result in thin film rupture caused by dewetting. With crystallisable polymers such as polyethyleneoxide (PEO, molecular self-assembly into partial ordered lamella structures is studied as an additional source of pattern formation. Morphological features in ultrathin PEO films (thickness < 10 nm result from an interplay between dewetting patterns and diffusion limited growth pattern of ordered lamella growing within the dewetting areas. Besides structure formation of hydrophilic PEO molecules, n-alkylterminated (hydrophobic PEO oligomers are investigated with respect to self-organization in ultrathin films. Morphological features characteristic for pure PEO are not changed by the presence of the n-alkylgroups.

  18. Simulating discrete models of pattern formation by ion beam sputtering

    International Nuclear Information System (INIS)

    Hartmann, Alexander K; Kree, Reiner; Yasseri, Taha

    2009-01-01

    A class of simple, (2+1)-dimensional, discrete models is reviewed, which allow us to study the evolution of surface patterns on solid substrates during ion beam sputtering (IBS). The models are based on the same assumptions about the erosion process as the existing continuum theories. Several distinct physical mechanisms of surface diffusion are added, which allow us to study the interplay of erosion-driven and diffusion-driven pattern formation. We present results from our own work on evolution scenarios of ripple patterns, especially for longer timescales, where nonlinear effects become important. Furthermore we review kinetic phase diagrams, both with and without sample rotation, which depict the systematic dependence of surface patterns on the shape of energy depositing collision cascades after ion impact. Finally, we discuss some results from more recent work on surface diffusion with Ehrlich-Schwoebel barriers as the driving force for pattern formation during IBS and on Monte Carlo simulations of IBS with codeposition of surfactant atoms.

  19. Patterns of Dynamics : in Honour of Bernold Fiedler's 60th Birthday

    CERN Document Server

    Hell, Juliette; Sandstede, Björn; Scheel, Arnd

    2017-01-01

    Theoretical advances in dynamical-systems theory and their applications to pattern-forming processes in the sciences and engineering are discussed in this volume that resulted from the conference Patterns in Dynamics held in honor of Bernold Fiedler, in Berlin, July 25-29, 2016.The contributions build and develop mathematical techniques, and use mathematical approaches for prediction and control of complex systems. The underlying mathematical theories help extract structures from experimental observations and, conversely, shed light on the formation, dynamics, and control of spatio-temporal patterns in applications. Theoretical areas covered include geometric analysis, spatial dynamics, spectral theory, traveling-wave theory, and topological data analysis; also discussed are their applications to chemotaxis, self-organization at interfaces, neuroscience, and transport processes. .

  20. Self-Assembly, Pattern Formation and Growth Phenomena in Nano-Systems

    CERN Document Server

    Nepomnyashchy, Alexander A

    2006-01-01

    Nano-science and nano-technology are rapidly developing scientific and technological areas that deal with physical, chemical and biological processes that occur on nano-meter scale – one millionth of a millimeter. Self-organization and pattern formation play crucial role on nano-scales and promise new, effective routes to control various nano-scales processes. This book contains lecture notes written by the lecturers of the NATO Advanced Study Institute "Self-Assembly, Pattern Formation and Growth Phenomena in Nano-Systems" that took place in St Etienne de Tinee, France, in the fall 2004. They give examples of self-organization phenomena on micro- and nano-scale as well as examples of the interplay between phenomena on nano- and macro-scales leading to complex behavior in various physical, chemical and biological systems. They discuss such fascinating nano-scale self-organization phenomena as self-assembly of quantum dots in thin solid films, pattern formation in liquid crystals caused by light, self-organi...

  1. Master stability functions reveal diffusion-driven pattern formation in networks

    Science.gov (United States)

    Brechtel, Andreas; Gramlich, Philipp; Ritterskamp, Daniel; Drossel, Barbara; Gross, Thilo

    2018-03-01

    We study diffusion-driven pattern formation in networks of networks, a class of multilayer systems, where different layers have the same topology, but different internal dynamics. Agents are assumed to disperse within a layer by undergoing random walks, while they can be created or destroyed by reactions between or within a layer. We show that the stability of homogeneous steady states can be analyzed with a master stability function approach that reveals a deep analogy between pattern formation in networks and pattern formation in continuous space. For illustration, we consider a generalized model of ecological meta-food webs. This fairly complex model describes the dispersal of many different species across a region consisting of a network of individual habitats while subject to realistic, nonlinear predator-prey interactions. In this example, the method reveals the intricate dependence of the dynamics on the spatial structure. The ability of the proposed approach to deal with this fairly complex system highlights it as a promising tool for ecology and other applications.

  2. Spatiotemporal Coupling of the Tongue in Amyotrophic Lateral Sclerosis

    Science.gov (United States)

    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…

  3. Spatio-temporal patterns of the effects of precipitation variability and land use/cover changes on long-term changes in sediment yield in the Loess Plateau, China

    Science.gov (United States)

    Gao, Guangyao; Zhang, Jianjun; Liu, Yu; Ning, Zheng; Fu, Bojie; Sivapalan, Murugesu

    2017-09-01

    Within China's Loess Plateau there have been concerted revegetation efforts and engineering measures since the 1950s aimed at reducing soil erosion and land degradation. As a result, annual streamflow, sediment yield, and sediment concentration have all decreased considerably. Human-induced land use/cover change (LUCC) was the dominant factor, contributing over 70 % of the sediment load reduction, whereas the contribution of precipitation was less than 30 %. In this study, we use 50-year time series data (1961-2011), showing decreasing trends in the annual sediment loads of 15 catchments, to generate spatio-temporal patterns in the effects of LUCC and precipitation variability on sediment yield. The space-time variability of sediment yield was expressed notionally as a product of two factors representing (i) the effect of precipitation and (ii) the fraction of treated land surface area. Under minimal LUCC, the square root of annual sediment yield varied linearly with precipitation, with the precipitation-sediment load relationship showing coherent spatial patterns amongst the catchments. As the LUCC increased and took effect, the changes in sediment yield pattern depended more on engineering measures and vegetation restoration campaign, and the within-year rainfall patterns (especially storm events) also played an important role. The effect of LUCC is expressed in terms of a sediment coefficient, i.e., the ratio of annual sediment yield to annual precipitation. Sediment coefficients showed a steady decrease over the study period, following a linear decreasing function of the fraction of treated land surface area. In this way, the study has brought out the separate roles of precipitation variability and LUCC in controlling spatio-temporal patterns of sediment yield at catchment scale.

  4. Fluctuation-Induced Pattern Formation in a Surface Reaction

    DEFF Research Database (Denmark)

    Starke, Jens; Reichert, Christian; Eiswirth, Markus

    2006-01-01

    Spontaneous nucleation, pulse formation, and propagation failure have been observed experimentally in CO oxidation on Pt(110) at intermediate pressures ($\\approx 10^{-2}$mbar). This phenomenon can be reproduced with a stochastic model which includes temperature effects. Nucleation occurs randomly...... due to fluctuations in the reaction processes, whereas the subsequent damping out essentially follows the deterministic path. Conditions for the occurence of stochastic effects in the pattern formation during CO oxidation on Pt are discussed....

  5. Caudal regulates the spatiotemporal dynamics of pair-rule waves in Tribolium.

    Directory of Open Access Journals (Sweden)

    Ezzat El-Sherif

    2014-10-01

    Full Text Available In the short-germ beetle Tribolium castaneum, waves of pair-rule gene expression propagate from the posterior end of the embryo towards the anterior and eventually freeze into stable stripes, partitioning the anterior-posterior axis into segments. Similar waves in vertebrates are assumed to arise due to the modulation of a molecular clock by a posterior-to-anterior frequency gradient. However, neither a molecular candidate nor a functional role has been identified to date for such a frequency gradient, either in vertebrates or elsewhere. Here we provide evidence that the posterior gradient of Tc-caudal expression regulates the oscillation frequency of pair-rule gene expression in Tribolium. We show this by analyzing the spatiotemporal dynamics of Tc-even-skipped expression in strong and mild knockdown of Tc-caudal, and by correlating the extension, level and slope of the Tc-caudal expression gradient to the spatiotemporal dynamics of Tc-even-skipped expression in wild type as well as in different RNAi knockdowns of Tc-caudal regulators. Further, we show that besides its absolute importance for stripe generation in the static phase of the Tribolium blastoderm, a frequency gradient might serve as a buffer against noise during axis elongation phase in Tribolium as well as vertebrates. Our results highlight the role of frequency gradients in pattern formation.

  6. Pattern formation and self-organization in a simple precipitation system

    NARCIS (Netherlands)

    Volford, Andras; Izsak, F.; Ripzam, Matyas; Lagzi, Istvan

    Various types of pattern formation and self-organization phenomena can be observed in biological, chemical, and geochemical systems due to the interaction of reaction with diffusion. The appearance of static precipitation patterns was reported first by Liesegang in 1896. Traveling waves and

  7. The LLE, pattern formation and a novel coherent source

    Science.gov (United States)

    Castelli, Fabrizio; Brambilla, Massimo; Gatti, Alessandra; Prati, Franco; Lugiato, Luigi A.

    2017-04-01

    The LLE was introduced in order to provide a paradigmatic model for spontaneous spatial pattern formation in the field of nonlinear optics. In the first part of this paper we describe in details its historical evolution. We underline, first of all, that the multimode instability of optical bistability represents an important precursor of the LLE. Next, we illustrate how the original LLE was conceived in order to describe pattern formation in the planes transverse with respect to the longitudinal direction of propagation of light in the nonlinear medium contained in the optical cavity. We emphasize, in particular, the crucial role of the low transmission limit (also called mean field limit or uniform field limit in the literature) in determining the simplicity of the equation. In discussing transverse pattern formation in the LLE, we underline incidentally the presence of very important quantum aspects related to squeezing of quantum fluctuations and to quantum imaging. We consider not only the case of global patterns but also localized structures (cavity solitons and their control). Then we turn to the temporal/longitudinal version of the LLE, formulated by Haelterman et al. [H. Haelterman, S. Trillo, S. Wabnitz, Opt. Commun. 91, 401 (1992)], and to its equivalence with the transverse LLE in 1D, discussing especially the phenomenon of temporal cavity solitons, their experimental observation and their control. Finally for the first part we turn to the very recent topic of broadband frequency combs, observed in a versatile multiwavelength coherent source (driven Kerr microcavity), which is raising a lot of interest and of research activities because of its very favourable physical characteristics, which support quite promising applicative perspectives. Kerr microcavities realize in an ideal manner the basic assumptions of the LLE, and the spontaneous formation of travelling patterns along the microcavity is the crucial mechanism which creates the combs and governs

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

    Directory of Open Access Journals (Sweden)

    A. Bhushan

    2015-07-01

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

  9. Trickle-down boundary conditions in aeolian dune-field pattern formation

    Science.gov (United States)

    Ewing, R. C.; Kocurek, G.

    2015-12-01

    One the one hand, wind-blown dune-field patterns emerge within the overarching boundary conditions of climate, tectonics and eustasy implying the presence of these signals in the aeolian geomorphic and stratigraphic record. On the other hand, dune-field patterns are a poster-child of self-organization, in which autogenic processes give rise to patterned landscapes despite remarkable differences in the geologic setting (i.e., Earth, Mars and Titan). How important are climate, tectonics and eustasy in aeolian dune field pattern formation? Here we develop the hypothesis that, in terms of pattern development, dune fields evolve largely independent of the direct influence of 'system-scale' boundary conditions, such as climate, tectonics and eustasy. Rather, these boundary conditions set the stage for smaller-scale, faster-evolving 'event-scale' boundary conditions. This 'trickle-down' effect, in which system-scale boundary conditions indirectly influence the event scale boundary conditions provides the uniqueness and richness of dune-field patterned landscapes. The trickle-down effect means that the architecture of the stratigraphic record of dune-field pattern formation archives boundary conditions, which are spatially and temporally removed from the overarching geologic setting. In contrast, the presence of an aeolian stratigraphic record itself, reflects changes in system-scale boundary conditions that drive accumulation and preservation of aeolian strata.

  10. Spatio-Temporal Variability of Summer Precipitation in Mexico under the Influence of the MJO, with Emphasis on the Bimodal Pattern

    Science.gov (United States)

    Perdigón, J.; Romero-Centeno, R.; Barrett, B.; Ordoñez-Perez, P.

    2017-12-01

    In many regions of Mexico, precipitation occurs in a very well defined annual cycle with peaks in May-June and September-October and a relative minimum in the middle of the rainy season known as the midsummer drought (MSD). The MJO is the most important mode of intraseasonal variability in the tropics, and, although some studies have shown its evident influence on summer precipitation in Mexico, its role in modulating the bimodal pattern of the summer precipitation cycle is still an open question. The spatio-temporal variability of summer precipitation in Mexico is analyzed through composite analysis according to the phases of the MJO, using the very high resolution CHIRPS precipitation data base and gridded data from the CFSR reanalysis to analyzing the MJO influence on the atmospheric circulation over Mexico and its adjacent basins. In general, during MJO phases 8-2 (4-6) rainfall is above-normal (below-normal), although, in some cases, the summer rainfall patterns during the same phase present considerable differences. The atmospheric circulation shows low (high) troposphere southwesterly (northeasterly) wind anomalies in southern Mexico under wetter conditions compared with climatological patterns, while the inverse pattern is observed under drier conditions. Composite anomalies of several variables also agreed well with those rainfall anomalies. Finally, a MJO complete cycle that reinforces (weakens) the bimodal pattern of summer rainfall in Mexico was found.

  11. EXTRACTING SPATIOTEMPORAL OBJECTS FROM RASTER DATA TO REPRESENT PHYSICAL FEATURES AND ANALYZE RELATED PROCESSES

    Directory of Open Access Journals (Sweden)

    J. A. Zollweg

    2017-10-01

    Full Text Available Numerous ground-based, airborne, and orbiting platforms provide remotely-sensed data of remarkable spatial resolution at short time intervals. However, this spatiotemporal data is most valuable if it can be processed into information, thereby creating meaning. We live in a world of objects: cars, buildings, farms, etc. On a stormy day, we don’t see millions of cubes of atmosphere; we see a thunderstorm ‘object’. Temporally, we don’t see the properties of those individual cubes changing, we see the thunderstorm as a whole evolving and moving. There is a need to represent the bulky, raw spatiotemporal data from remote sensors as a small number of relevant spatiotemporal objects, thereby matching the human brain’s perception of the world. This presentation reveals an efficient algorithm and system to extract the objects/features from raster-formatted remotely-sensed data. The system makes use of the Python object-oriented programming language, SciPy/NumPy for matrix manipulation and scientific computation, and export/import to the GeoJSON standard geographic object data format. The example presented will show how thunderstorms can be identified and characterized in a spatiotemporal continuum using a Python program to process raster data from NOAA’s High-Resolution Rapid Refresh v2 (HRRRv2 data stream.

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

    Science.gov (United States)

    Zollweg, J. A.

    2017-10-01

    Numerous ground-based, airborne, and orbiting platforms provide remotely-sensed data of remarkable spatial resolution at short time intervals. However, this spatiotemporal data is most valuable if it can be processed into information, thereby creating meaning. We live in a world of objects: cars, buildings, farms, etc. On a stormy day, we don't see millions of cubes of atmosphere; we see a thunderstorm `object'. Temporally, we don't see the properties of those individual cubes changing, we see the thunderstorm as a whole evolving and moving. There is a need to represent the bulky, raw spatiotemporal data from remote sensors as a small number of relevant spatiotemporal objects, thereby matching the human brain's perception of the world. This presentation reveals an efficient algorithm and system to extract the objects/features from raster-formatted remotely-sensed data. The system makes use of the Python object-oriented programming language, SciPy/NumPy for matrix manipulation and scientific computation, and export/import to the GeoJSON standard geographic object data format. The example presented will show how thunderstorms can be identified and characterized in a spatiotemporal continuum using a Python program to process raster data from NOAA's High-Resolution Rapid Refresh v2 (HRRRv2) data stream.

  13. Numerical approaches to model perturbation fire in turing pattern formations

    Science.gov (United States)

    Campagna, R.; Brancaccio, M.; Cuomo, S.; Mazzoleni, S.; Russo, L.; Siettos, K.; Giannino, F.

    2017-11-01

    Turing patterns were observed in chemical, physical and biological systems described by coupled reaction-diffusion equations. Several models have been formulated proposing the water as the causal mechanism of vegetation pattern formation, but this isn't an exhaustive hypothesis in some natural environments. An alternative explanation has been related to the plant-soil negative feedback. In Marasco et al. [1] the authors explored the hypothesis that both mechanisms contribute in the formation of regular and irregular vegetation patterns. The mathematical model consists in three partial differential equations (PDEs) that take into account for a dynamic balance between biomass, water and toxic compounds. A numerical approach is mandatory also to investigate on the predictions of this kind of models. In this paper we start from the mathematical model described in [1], set the model parameters such that the biomass reaches a stable spatial pattern (spots) and present preliminary studies about the occurrence of perturbing events, such as wildfire, that can affect the regularity of the biomass configuration.

  14. Spatiotemporal patterns, triggers and anatomies of seismically detected rockfalls

    Directory of Open Access Journals (Sweden)

    M. Dietze

    2017-11-01

    Full Text Available Rockfalls are a ubiquitous geomorphic process and a natural hazard in steep landscapes across the globe. Seismic monitoring can provide precise information on the timing, location and event anatomy of rockfalls, which are parameters that are otherwise hard to constrain. By pairing data from 49 seismically detected rockfalls in the Lauterbrunnen Valley in the Swiss Alps with auxiliary meteorologic and seismic data of potential triggers during autumn 2014 and spring 2015, we are able to (i analyse the evolution of single rockfalls and their common properties, (ii identify spatial changes in activity hotspots (iii and explore temporal activity patterns on different scales ranging from months to minutes to quantify relevant trigger mechanisms. Seismic data allow for the classification of rockfall activity into two distinct phenomenological types. The signals can be used to discern multiple rock mass releases from the same spot, identify rockfalls that trigger further rockfalls and resolve modes of subsequent talus slope activity. In contrast to findings based on discontinuous methods with integration times of several months, rockfall in the monitored limestone cliff is not spatially uniform but shows a systematic downward shift of a rock mass release zone following an exponential law, most likely driven by a continuously lowering water table. Freeze–thaw transitions, approximated at first order from air temperature time series, account for only 5 out of the 49 rockfalls, whereas 19 rockfalls were triggered by rainfall events with a peak lag time of 1 h. Another 17 rockfalls were triggered by diurnal temperature changes and occurred during the coldest hours of the day and during the highest temperature change rates. This study is thus the first to show direct links between proposed rockfall triggers and the spatiotemporal distribution of rockfalls under natural conditions; it extends existing models by providing seismic observations of the

  15. Spatio-temporal patterns of the effects of precipitation variability and land use/cover changes on long-term changes in sediment yield in the Loess Plateau, China

    Directory of Open Access Journals (Sweden)

    G. Gao

    2017-09-01

    Full Text Available Within China's Loess Plateau there have been concerted revegetation efforts and engineering measures since the 1950s aimed at reducing soil erosion and land degradation. As a result, annual streamflow, sediment yield, and sediment concentration have all decreased considerably. Human-induced land use/cover change (LUCC was the dominant factor, contributing over 70 % of the sediment load reduction, whereas the contribution of precipitation was less than 30 %. In this study, we use 50-year time series data (1961–2011, showing decreasing trends in the annual sediment loads of 15 catchments, to generate spatio-temporal patterns in the effects of LUCC and precipitation variability on sediment yield. The space–time variability of sediment yield was expressed notionally as a product of two factors representing (i the effect of precipitation and (ii the fraction of treated land surface area. Under minimal LUCC, the square root of annual sediment yield varied linearly with precipitation, with the precipitation–sediment load relationship showing coherent spatial patterns amongst the catchments. As the LUCC increased and took effect, the changes in sediment yield pattern depended more on engineering measures and vegetation restoration campaign, and the within-year rainfall patterns (especially storm events also played an important role. The effect of LUCC is expressed in terms of a sediment coefficient, i.e., the ratio of annual sediment yield to annual precipitation. Sediment coefficients showed a steady decrease over the study period, following a linear decreasing function of the fraction of treated land surface area. In this way, the study has brought out the separate roles of precipitation variability and LUCC in controlling spatio-temporal patterns of sediment yield at catchment scale.

  16. Collective motion of cells mediates segregation and pattern formation in co-cultures.

    Directory of Open Access Journals (Sweden)

    Elod Méhes

    Full Text Available Pattern formation by segregation of cell types is an important process during embryonic development. We show that an experimentally yet unexplored mechanism based on collective motility of segregating cells enhances the effects of known pattern formation mechanisms such as differential adhesion, mechanochemical interactions or cell migration directed by morphogens. To study in vitro cell segregation we use time-lapse videomicroscopy and quantitative analysis of the main features of the motion of individual cells or groups. Our observations have been extensive, typically involving the investigation of the development of patterns containing up to 200,000 cells. By either comparing keratocyte types with different collective motility characteristics or increasing cells' directional persistence by the inhibition of Rac1 GTP-ase we demonstrate that enhanced collective cell motility results in faster cell segregation leading to the formation of more extensive patterns. The growth of the characteristic scale of patterns generally follows an algebraic scaling law with exponent values up to 0.74 in the presence of collective motion, compared to significantly smaller exponents in case of diffusive motion.

  17. Spatio-temporal patterns and source apportionment of pollution in Qiantang River (China) using neural-based modeling and multivariate statistical techniques

    Science.gov (United States)

    Su, Shiliang; Zhi, Junjun; Lou, Liping; Huang, Fang; Chen, Xia; Wu, Jiaping

    Characterizing the spatio-temporal patterns and apportioning the pollution sources of water bodies are important for the management and protection of water resources. The main objective of this study is to describe the dynamics of water quality and provide references for improving river pollution control practices. Comprehensive application of neural-based modeling and different multivariate methods was used to evaluate the spatio-temporal patterns and source apportionment of pollution in Qiantang River, China. Measurement data were obtained and pretreated for 13 variables from 41 monitoring sites for the period of 2001-2004. A self-organizing map classified the 41 monitoring sites into three groups (Group A, B and C), representing different pollution characteristics. Four significant parameters (dissolved oxygen, biochemical oxygen demand, total phosphorus and total lead) were identified by discriminant analysis for distinguishing variations of different years, with about 80% correct assignment for temporal variation. Rotated principal component analysis (PCA) identified four potential pollution sources for Group A (domestic sewage and agricultural pollution, industrial wastewater pollution, mineral weathering, vehicle exhaust and sand mining), five for Group B (heavy metal pollution, agricultural runoff, vehicle exhaust and sand mining, mineral weathering, chemical plants discharge) and another five for Group C (vehicle exhaust and sand mining, chemical plants discharge, soil weathering, biochemical pollution, mineral weathering). The identified potential pollution sources explained 75.6% of the total variances for Group A, 75.0% for Group B and 80.0% for Group C, respectively. Receptor-based source apportionment was applied to further estimate source contributions for each pollution variable in the three groups, which facilitated and supported the PCA results. These results could assist managers to develop optimal strategies and determine priorities for river

  18. Spatiotemporal expression profile of the Pumilio gene in the embryonic development of silkworm.

    Science.gov (United States)

    Chen, Liang; You, Zaizhi; Xia, Hengchuan; Tang, Qi; Zhou, Yang; Yao, Qin; Chen, Keping

    2014-01-01

    We previously identified a pumilio gene in silkworm (Bombyx mori L.), designated BmPUM, which was specifically expressed in the ovary and testis. To further characterize this gene's involvement in silkworm development, we have determined the spatiotemporal expression pattern of BmPUM during all embryonic stages. Real-time polymerase chain reaction (RT-PCR) analysis revealed that BmPUM was expressed in all stages of silkworm embryos and that its transcript levels displayed two distinct peaks. The first was observed at the germ-band formation stage (1 d after oviposition) and dropped to a low level at the gonad formation stage (5 d after oviposition). The second was detected at the stage of bristle follicle occurrence (6 d after oviposition), which was confirmed by Western blot analysis and immunohistochemistry. Nanos (Nos), functioning together with Pum in abdomen formation of Drosophila embryos, was also highly expressed at the beginning (0 h to 1 d after oviposition) of embryogenesis, but its transcript levels were very low after the stage of germ-band formation. These results suggest that BmPUM functions with Bombyx mori nanos (Bm-nanos) at the early stages of silkworm embryonic development, and may then play a role in gonad formation and the occurrence of bristle follicles. Our data thus provide a foundation to uncover the role of BmPUM during silkworm development.

  19. Modelling Global Pattern Formations for Collaborative Learning Environments

    DEFF Research Database (Denmark)

    Grappiolo, Corrado; Cheong, Yun-Gyung; Khaled, Rilla

    2012-01-01

    We present our research towards the design of a computational framework capable of modelling the formation and evolution of global patterns (i.e. group structures) in a population of social individuals. The framework is intended to be used in collaborative environments, e.g. social serious games...

  20. Pattern formation in two-dimensional square-shoulder systems

    International Nuclear Information System (INIS)

    Fornleitner, Julia; Kahl, Gerhard

    2010-01-01

    Using a highly efficient and reliable optimization tool that is based on ideas of genetic algorithms, we have systematically studied the pattern formation of the two-dimensional square-shoulder system. An overwhelming wealth of complex ordered equilibrium structures emerge from this investigation as we vary the shoulder width. With increasing pressure three structural archetypes could be identified: cluster lattices, where clusters of particles occupy the sites of distorted hexagonal lattices, lane formation, and compact particle arrangements with high coordination numbers. The internal complexity of these structures increases with increasing shoulder width.

  1. Pattern formation in two-dimensional square-shoulder systems

    Energy Technology Data Exchange (ETDEWEB)

    Fornleitner, Julia [Institut fuer Festkoerperforschung, Forschungsszentrum Juelich, D-52425 Juelich (Germany); Kahl, Gerhard, E-mail: fornleitner@cmt.tuwien.ac.a [Institut fuer Theoretische Physik and Centre for Computational Materials Science (CMS), Technische Universitaet Wien, Wiedner Hauptstrasse 8-10, A-1040 Wien (Austria)

    2010-03-17

    Using a highly efficient and reliable optimization tool that is based on ideas of genetic algorithms, we have systematically studied the pattern formation of the two-dimensional square-shoulder system. An overwhelming wealth of complex ordered equilibrium structures emerge from this investigation as we vary the shoulder width. With increasing pressure three structural archetypes could be identified: cluster lattices, where clusters of particles occupy the sites of distorted hexagonal lattices, lane formation, and compact particle arrangements with high coordination numbers. The internal complexity of these structures increases with increasing shoulder width.

  2. 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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    Lianfa Li

    2018-02-01

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

  4. Can Spatiotemporal Fluoride (18F-) Uptake be Used to Assess Bone Formation in the Tibia? A Longitudinal Study Using PET/CT.

    Science.gov (United States)

    Lundblad, Henrik; Karlsson-Thur, Charlotte; Maguire, Gerald Q; Jonsson, Cathrine; Noz, Marilyn E; Zeleznik, Michael P; Weidenhielm, Lars

    2017-05-01

    When a bone is broken for any reason, it is important for the orthopaedic surgeon to know how bone healing is progressing. There has been resurgence in the use of the fluoride ( 18 F - ) ion to evaluate various bone conditions. This has been made possible by availability of positron emission tomography (PET)/CT hybrid scanners together with cyclotrons. Absorbed on the bone surface from blood flow, 18 F - attaches to the osteoblasts in cancellous bone and acts as a pharmacokinetic agent, which reflects the local physiologic activity of bone. This is important because it shows bone formation indicating that the bone is healing or no bone formation indicating no healing. As 18 F - is extracted from blood in proportion to blood flow and bone formation, it thus enables determination of bone healing progress. The primary objective of this study was to determine whether videos showing the spatiotemporal uptake of 18 F - via PET bone scans could show problematic bone healing in patients with complex tibia conditions. A secondary objective was to determine if semiquantification of radionuclide uptake was consistent with bone healing. This study investigated measurements of tibia bone formation in patients with complex fractures, osteomyelitis, and osteotomies treated with a Taylor Spatial Frame TM (TSF) by comparing clinical healing progress with spatiotemporal fluoride ( 18 F - ) uptake and the semiquantitative standardized uptake value (SUV). This procedure included static and dynamic image acquisition. For intrapatient volumes acquired at different times, the CT and PET data were spatially registered to bring the ends of the bones that were supposed to heal into alignment. To qualitatively observe how and where bone formation was occurring, time-sequenced volumes were reconstructed and viewed as a video. To semiquantify the uptake, the mean and maximum SUVs (SUVmean, SUVmax) were calculated for the ends of the bones that were supposed to heal and for normal bone, using a

  5. What drives the formation of global oil trade patterns?

    International Nuclear Information System (INIS)

    Zhang, Hai-Ying; Ji, Qiang; Fan, Ying

    2015-01-01

    In this paper, the spatial characteristics of current global oil trade patterns are investigated by proposing a new indicator Moran-F. Meanwhile, the factors that influence the formation of oil trade patterns are identified by constructing four different kinds of spatial econometric models. The findings indicate that most oil exporters have an obvious export focus in North America and a relatively balanced export in Europe and the Asia-Pacific region. Besides supply and demand factors, technological progress and energy efficiency have also significantly influenced the oil trade. Moreover, there is a spillover effect of trade flow among different regions, but its impact is weak. In addition, oil importers in the same region have the potential to cooperate due to their similar import sources. Finally, promotion of oil importers' R&D investments can effectively reduce the demand for global oil trade. - Highlights: • A new spatial association Moran-F indicator that applies to trade flows is proposed. • Driving factors affecting the formation of oil trade patterns are identified. • Oil-exporting countries implement various export strategies in different regions. • Supply, demand and technological factors contribute to the oil trade patterns. • Spillover effect of each factor affecting oil trade flows does exist but is limited

  6. Spatiotemporal Patterns of Urbanization in a Developed Region of Eastern Coastal China

    Directory of Open Access Journals (Sweden)

    Jiadan Li

    2014-06-01

    Full Text Available This study presents a practical methodology to monitor the spatiotemporal characteristics of urban expansion in response to rapid urbanization at the provincial scale by integrating remote sensing, urban built-up area boundaries, spatial metrics and spatial regression. Sixty-seven cities were investigated to examine the differences of urbanization intensity, urbanization patterns and urban land use efficiency in conjunction with the identification of socio-economic indicators and planning strategies. Planning proposals to allocate the urbanization intensity among different-sized cities by considering sustainable urban development were also explored. The results showed that the urban area of Zhejiang Province expanded from 31,380 ha in 1980 to 415,184 ha in 2010, indicating that the area of the urban region expanded to more than 13-times the initial urban area. The urban built-up area boundaries became more complex and irregular in shape as the urban area expanded throughout the entire study period. Rapid urban population growth and economic development were identified as significant in stimulating the urban expansion process. However, different-sized cities exhibited marked differences in urban development. Small cities experienced the rapidest urbanization before 2000. Large cities, which are estimated to have the highest urban land use efficiency, had the most dramatic sprawl in urban area at the beginning of the 21st century. Promoting the development of large cities to mega-cities is recommended in Zhejiang Province to ensure sustainable urban development with consideration of land resource preservation.

  7. Selective metal pattern formation and its EMI shielding efficiency

    International Nuclear Information System (INIS)

    Lee, Ho-Chul; Kim, Jin-Young; Noh, Chang-Ho; Song, Ki Yong; Cho, Sung-Heon

    2006-01-01

    A novel method for selective metal pattern formation by using an enhanced life-time of photoexcited electron-hole pairs in bilayer thin film of amorphous titanium dioxide and hole-scavenger-containing poly(vinyl alcohol) was proposed. By UV-irradiation through photomask on the bilayer film, the photodefined image of photoelectrons could be easily and simply produced, consequently resulting in selective palladium (Pd) catalyst deposition by reduction. The successive electrolessplating on Pd catalysts and electroplating on electrolessplated pattern were possible. Furthermore, the electromagnetic interference shielding efficiencies of the metal mesh patterns with various characteristic length scales of line width and thickness were investigated

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-07-01

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

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

    International Nuclear Information System (INIS)

    Modis, K.

    2010-01-01

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

  10. Cellular automaton modeling of biological pattern formation characterization, examples, and analysis

    CERN Document Server

    Deutsch, Andreas

    2017-01-01

    This text explores the use of cellular automata in modeling pattern formation in biological systems. It describes several mathematical modeling approaches utilizing cellular automata that can be used to study the dynamics of interacting cell systems both in simulation and in practice. New in this edition are chapters covering cell migration, tissue development, and cancer dynamics, as well as updated references and new research topic suggestions that reflect the rapid development of the field. The book begins with an introduction to pattern-forming principles in biology and the various mathematical modeling techniques that can be used to analyze them. Cellular automaton models are then discussed in detail for different types of cellular processes and interactions, including random movement, cell migration, adhesive cell interaction, alignment and cellular swarming, growth processes, pigment cell pattern formation, tissue development, tumor growth and invasion, and Turing-type patterns and excitable media. In ...

  11. Spatiotemporal Data Organization and Application Research

    Science.gov (United States)

    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.

  12. Morphogenesis and pattern formation in biological systems experiments and models

    CERN Document Server

    Noji, Sumihare; Ueno, Naoto; Maini, Philip

    2003-01-01

    A central goal of current biology is to decode the mechanisms that underlie the processes of morphogenesis and pattern formation. Concerned with the analysis of those phenomena, this book covers a broad range of research fields, including developmental biology, molecular biology, plant morphogenesis, ecology, epidemiology, medicine, paleontology, evolutionary biology, mathematical biology, and computational biology. In Morphogenesis and Pattern Formation in Biological Systems: Experiments and Models, experimental and theoretical aspects of biology are integrated for the construction and investigation of models of complex processes. This collection of articles on the latest advances by leading researchers not only brings together work from a wide spectrum of disciplines, but also provides a stepping-stone to the creation of new areas of discovery.

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

    Science.gov (United States)

    Bittihn, Philip; Berg, Sebastian; Parlitz, Ulrich; Luther, Stefan

    2017-09-01

    Self-organized activation patterns in excitable media such as spiral waves and spatio-temporal chaos underlie dangerous cardiac arrhythmias. While the interaction of single spiral waves with different types of heterogeneity has been studied extensively, the effect of heterogeneity on fully developed spatio-temporal chaos remains poorly understood. We investigate how the complexity and stability properties of spatio-temporal chaos in the Bär-Eiswirth model of excitable media depend on the heterogeneity of the underlying medium. We employ different measures characterizing the chaoticity of the system and find that the spatial arrangement of multiple discrete lower excitability regions has a strong impact on the complexity of the dynamics. Varying the number, shape, and spatial arrangement of the heterogeneities, we observe strong emergent effects ranging from increases in chaoticity to the complete cessation of chaos, contrasting the expectation from the homogeneous behavior. The implications of our findings for the development and treatment of arrhythmias in the heterogeneous cardiac muscle are discussed.

  14. Probabilistic M/EEG source imaging from sparse spatio-temporal event structure

    DEFF Research Database (Denmark)

    Stahlhut, Carsten; Attias, Hagai T.; Wipf, David

    While MEG and EEG source imaging methods have to tackle a severely ill-posed problem their success can be stated as their ability to constrain the solutions using appropriate priors. In this paper we propose a hierarchical Bayesian model facilitating spatio-temporal patterns through the use of bo...

  15. Reliable Collaborative Filtering on Spatio-Temporal Privacy Data

    Directory of Open Access Journals (Sweden)

    Zhen Liu

    2017-01-01

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

  16. The formation of labyrinths, spots and stripe patterns in a biochemical approach to cardiovascular calcification

    International Nuclear Information System (INIS)

    Yochelis, A; Tintut, Y; Demer, L L; Garfinkel, A

    2008-01-01

    Calcification and mineralization are fundamental physiological processes, yet the mechanisms of calcification, in trabecular bone and in calcified lesions in atherosclerotic calcification, are unclear. Recently, it was shown in in vitro experiments that vascular-derived mesenchymal stem cells can display self-organized calcified patterns. These patterns were attributed to activator/inhibitor dynamics in the style of Turing, with bone morphogenetic protein 2 acting as an activator, and matrix GLA protein acting as an inhibitor. Motivated by this qualitative activator-inhibitor dynamics, we employ a prototype Gierer-Meinhardt model used in the context of activator-inhibitor-based biological pattern formation. Through a detailed analysis in one and two spatial dimensions, we explore the pattern formation mechanisms of steady state patterns, including their dependence on initial conditions. These patterns range from localized holes to labyrinths and localized peaks, or in other words, from dense to sparse activator distributions (respectively). We believe that an understanding of the wide spectrum of activator-inhibitor patterns discussed here is prerequisite to their biochemical control. The mechanisms of pattern formation suggest therapeutic strategies applicable to bone formation in atherosclerotic lesions in arteries (where it is pathological) and to the regeneration of trabecular bone (recapitulating normal physiological development)

  17. Schistosoma japonicum risk in Jiangsu province, People’s Republic of China: identification of a spatio-temporal risk pattern along the Yangtze River

    Directory of Open Access Journals (Sweden)

    Kun Yang

    2013-11-01

    Full Text Available The risk for Schistosoma japonicum infection in Jiangsu province, People’s Republic of China, was investigated by a mouse bioassay. Various investigations were conducted in the period 2009-2011 with the presentation here representing the summary of the results from 45-50 sites in the marshlands along the Yangtze River’s course through the province. Indices representing three aspects of the infection were collected to assess risk: (i the proportion of sentinel points where at least one mouse infection was recorded; (ii the proportion of infected mice at each of these sites; and (iii the average worm burdens. Directional distribution analysis and scan statistics were used to explore the spatio-temporal risk pattern. The spatial distribution was oriented along the Yangtze River and the directional distributions for the proportion of infected mice and mean worm burdens were similar for the positive sentinel sites. Four statistically significant clusters were detected in 2009, but only one in 2010 and 2011, respectively. Temporal windows for infection risk were seen in June and September. The study illustrates the utility of spatio-temporal analysis in assessing the risk for schistosomiasis. This approach should be useful with respect to surveillance and response that can be expected to be increasingly applied when moving from morbidity control to transmission control.

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

    Science.gov (United States)

    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.

  19. Stress-driven pattern formation in living and non-living matter

    DEFF Research Database (Denmark)

    Christensen, Amalie

    . On the smallest scale of nanometers, we study thin films of block copolymers, which have potential applications as self-organizing templates for microelectronics. By performing a thin-shell expansion of a well-known model for block copolymers, we develop an effective model for the impact of curvature on pattern......Spatial pattern formation is abundant in nature and occurs in both living and non-living matter. Familiar examples include sand ripples, river deltas, zebra fur and snail shells. In this thesis, we focus on patterns induced by mechanical stress, and develop continuum theories for three systems...

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

    Directory of Open Access Journals (Sweden)

    Paula Pereira

    2013-10-01

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

  1. Adaptive changes in spatiotemporal gait characteristics in women during pregnancy.

    Science.gov (United States)

    Błaszczyk, Janusz W; Opala-Berdzik, Agnieszka; Plewa, Michał

    2016-01-01

    Spatiotemporal gait cycle characteristics were assessed at early (P1), and late (P2) pregnancy, as well as at 2 months (PP1) and 6 months (PP2) postpartum. A substantial decrease in walking speed was observed throughout the pregnancy, with the slowest speed (1±0.2m/s) being during the third trimester. Walking at slower velocity resulted in complex adaptive adjustments to their spatiotemporal gait pattern, including a shorter step length and an increased duration of both their stance and double-support phases. Duration of the swing phase remained the least susceptible to changes. Habitual walking velocity (1.13±0.2m/s) and the optimal gait pattern were fully recovered 6 months after childbirth. Documented here adaptive changes in the preferred gait pattern seem to result mainly from the altered body anthropometry leading to temporary balance impairments. All the observed changes within stride cycle aimed to improve gait safety by focusing on its dynamic stability. The pregnant women preferred to walk at a slower velocity which allowed them to spend more time in double-support compared with their habitual pattern. Such changes provided pregnant women with a safer and more tentative ambulation that reduced the single-support period and, hence, the possibility of instability. As pregnancy progressed a significant increase in stance width and a decrease in step length was observed. Both factors allow also for gait stability improvement. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. Defects formation and spiral waves in a network of neurons in presence of electromagnetic induction.

    Science.gov (United States)

    Rostami, Zahra; Jafari, Sajad

    2018-04-01

    Complex anatomical and physiological structure of an excitable tissue (e.g., cardiac tissue) in the body can represent different electrical activities through normal or abnormal behavior. Abnormalities of the excitable tissue coming from different biological reasons can lead to formation of some defects. Such defects can cause some successive waves that may end up to some additional reorganizing beating behaviors like spiral waves or target waves. In this study, formation of defects and the resulting emitted waves in an excitable tissue are investigated. We have considered a square array network of neurons with nearest-neighbor connections to describe the excitable tissue. Fundamentally, electrophysiological properties of ion currents in the body are responsible for exhibition of electrical spatiotemporal patterns. More precisely, fluctuation of accumulated ions inside and outside of cell causes variable electrical and magnetic field. Considering undeniable mutual effects of electrical field and magnetic field, we have proposed the new Hindmarsh-Rose (HR) neuronal model for the local dynamics of each individual neuron in the network. In this new neuronal model, the influence of magnetic flow on membrane potential is defined. This improved model holds more bifurcation parameters. Moreover, the dynamical behavior of the tissue is investigated in different states of quiescent, spiking, bursting and even chaotic state. The resulting spatiotemporal patterns are represented and the time series of some sampled neurons are displayed, as well.

  3. Identifying food deserts and swamps based on relative healthy food access: a spatio-temporal Bayesian approach.

    Science.gov (United States)

    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.

  4. A Theoretical Model of Jigsaw-Puzzle Pattern Formation by Plant Leaf Epidermal Cells.

    Science.gov (United States)

    Higaki, Takumi; Kutsuna, Natsumaro; Akita, Kae; Takigawa-Imamura, Hisako; Yoshimura, Kenji; Miura, Takashi

    2016-04-01

    Plant leaf epidermal cells exhibit a jigsaw puzzle-like pattern that is generated by interdigitation of the cell wall during leaf development. The contribution of two ROP GTPases, ROP2 and ROP6, to the cytoskeletal dynamics that regulate epidermal cell wall interdigitation has already been examined; however, how interactions between these molecules result in pattern formation remains to be elucidated. Here, we propose a simple interface equation model that incorporates both the cell wall remodeling activity of ROP GTPases and the diffusible signaling molecules by which they are regulated. This model successfully reproduces pattern formation observed in vivo, and explains the counterintuitive experimental results of decreased cellulose production and increased thickness. Our model also reproduces the dynamics of three-way cell wall junctions. Therefore, this model provides a possible mechanism for cell wall interdigitation formation in vivo.

  5. Satellite-Derived Photic Depth on the Great Barrier Reef: Spatio-Temporal Patterns of Water Clarity

    Directory of Open Access Journals (Sweden)

    Scarla Weeks

    2012-11-01

    Full Text Available Detecting changes to the transparency of the water column is critical for understanding the responses of marine organisms, such as corals, to light availability. Long-term patterns in water transparency determine geographical and depth distributions, while acute reductions cause short-term stress, potentially mortality and may increase the organisms’ vulnerability to other environmental stressors. Here, we investigated the optimal, operational algorithm for light attenuation through the water column across the scale of the Great Barrier Reef (GBR, Australia. We implemented and tested a quasi-analytical algorithm to determine the photic depth in GBR waters and matched regional Secchi depth (ZSD data to MODIS-Aqua (2002–2010 and SeaWiFS (1997–2010 satellite data. The results of the in situ ZSD/satellite data matchup showed a simple bias offset between the in situ and satellite retrievals. Using a Type II linear regression of log-transformed satellite and in situ data, we estimated ZSD and implemented the validated ZSD algorithm to generate a decadal satellite time series (2002–2012 for the GBR. Water clarity varied significantly in space and time. Seasonal effects were distinct, with lower values during the austral summer, most likely due to river runoff and increased vertical mixing, and a decline in water clarity between 2008–2012, reflecting a prevailing La Niña weather pattern. The decline in water clarity was most pronounced in the inshore area, where a significant decrease in mean inner shelf ZSD of 2.1 m (from 8.3 m to 6.2 m occurred over the decade. Empirical Orthogonal Function Analysis determined the dominance of Mode 1 (51.3%, with the greatest variation in water clarity along the mid-shelf, reflecting the strong influence of oceanic intrusions on the spatio-temporal patterns of water clarity. The newly developed photic depth product has many potential applications for the GBR from water quality monitoring to analyses of

  6. Anomalous patterns of formation and distribution of the brachial ...

    African Journals Online (AJOL)

    block Background: Structural variations in the patterns of formation and distribution of the brachial plexus have drawn attentions both in anatomy and anaesthesia. Method: An observational study. Results: The brachial plexus was carefully inspected in both the right and left arms in 90 Nigerian cadavers, comprising of 74 ...

  7. Evaluation of urban sprawl and urban landscape pattern in a rapidly developing region.

    Science.gov (United States)

    Lv, Zhi-Qiang; Dai, Fu-Qiang; Sun, Cheng

    2012-10-01

    Urban sprawl is a worldwide phenomenon happening particularly in rapidly developing regions. A study on the spatiotemporal characteristics of urban sprawl and urban pattern is useful for the sustainable management of land management and urban land planning. The present research explores the spatiotemporal dynamics of urban sprawl in the context of a rapid urbanization process in a booming economic region of southern China from 1979 to 2005. Three urban sprawl types are distinguished by analyzing overlaid urban area maps of two adjacent study years which originated from the interpretation of remote sensed images and vector land use maps. Landscape metrics are used to analyze the spatiotemporal pattern of urban sprawl for each study period. Study results show that urban areas have expanded dramatically, and the spatiotemporal landscape pattern configured by the three sprawl types changed obviously. The different sprawl type patterns in five study periods have transformed significantly, with their proportions altered both in terms of quantity and of location. The present research proves that urban sprawl quantification and pattern analysis can provide a clear perspective of the urbanization process during a long time period. Particularly, the present study on urban sprawl and sprawl patterns can be used by land use and urban planners.

  8. Global stability and pattern formation in a nonlocal diffusive Lotka-Volterra competition model

    Science.gov (United States)

    Ni, Wenjie; Shi, Junping; Wang, Mingxin

    2018-06-01

    A diffusive Lotka-Volterra competition model with nonlocal intraspecific and interspecific competition between species is formulated and analyzed. The nonlocal competition strength is assumed to be determined by a diffusion kernel function to model the movement pattern of the biological species. It is shown that when there is no nonlocal intraspecific competition, the dynamics properties of nonlocal diffusive competition problem are similar to those of classical diffusive Lotka-Volterra competition model regardless of the strength of nonlocal interspecific competition. Global stability of nonnegative constant equilibria are proved using Lyapunov or upper-lower solution methods. On the other hand, strong nonlocal intraspecific competition increases the system spatiotemporal dynamic complexity. For the weak competition case, the nonlocal diffusive competition model may possess nonconstant positive equilibria for some suitably large nonlocal intraspecific competition coefficients.

  9. Formation of periodic and localized patterns in an oscillating granular layer.

    Energy Technology Data Exchange (ETDEWEB)

    Aranson, I.; Tsimring, L. S.; Materials Science Division; Bar Ilan Univ.; Univ. of California at San Diego

    1998-02-01

    A simple phenomenological model for pattern formation in a vertically vibrated layer of granular particles is proposed. This model exhibits a variety of stable cellular patterns including standing rolls and squares as well as localized excitations (oscillons and worms), similar to recent experimental observations (Umbanhowar et al., 1996). The model is an order parameter equation for the parametrically excited waves coupled to the mass conservation law. The structure and dynamics of the solutions resemble closely the properties of patterns observed in the experiments.

  10. Economic agglomerations and spatio-temporal cycles in a spatial growth model with capital transport cost

    Science.gov (United States)

    Juchem Neto, J. P.; Claeyssen, J. C. R.; Pôrto Júnior, S. S.

    2018-03-01

    In this paper we introduce capital transport cost in a unidimensional spatial Solow-Swan model of economic growth with capital-induced labor migration, considered in an unbounded domain. Proceeding with a stability analysis, we show that there is a critical value for the capital transport cost where the dynamic behavior of the economy changes, provided that the intensity of capital-induced labor migration is strong enough. On the one hand, if the capital transport cost is higher than this critical value, the spatially homogeneous equilibrium of coexistence of the model is stable, and the economy converges to this spatially homogeneous state in the long run; on the other hand, if transport cost is lower than this critical value, the equilibrium is unstable, and the economy may develop different spatio-temporal dynamics, including the formation of stable economic agglomerations and spatio-temporal economic cycles, depending on the other parameters in the model. Finally, numerical simulations support the results of the stability analysis, and illustrate the spatio-temporal dynamics generated by the model, suggesting that the economy as a whole benefits from the formation of economic agglomerations and cycles, with a higher capital transport cost reducing this gain.

  11. Multiscale recurrence analysis of spatio-temporal data

    Science.gov (United States)

    Riedl, M.; Marwan, N.; Kurths, J.

    2015-12-01

    The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

  12. Anode pattern formation in atmospheric pressure air glow discharges with water anode

    NARCIS (Netherlands)

    Verreycken, T.; Bruggeman, P.J.; Leys, C.

    2009-01-01

    Pattern formation in the anode layer at a water electrode in atmospheric pressure glow discharges in air is studied. With increasing current a sequence of different anode spot structures occurs from a constricted homogeneous spot in the case of small currents to a pattern consisting of small

  13. Spatiotemporal chaos from bursting dynamics

    International Nuclear Information System (INIS)

    Berenstein, Igal; De Decker, Yannick

    2015-01-01

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

  14. Pattern formation of nanoflowers during the vapor-liquid-solid growth of silicon nanowires

    International Nuclear Information System (INIS)

    Bae, Joonho; Thompson-Flagg, Rebecca; Ekerdt, John G.; Shih, C.-K.

    2008-01-01

    Pattern formation of nanoflowers during the vapor-liquid-solid growth of Si nanowires is reported. Using transmission electron microscopy, scanning electron microscopy, and energy dispersive spectrometer analysis, we show that the flower consists of an Au/SiO x core-shell structure. Moreover, the growth of flower starts at the interface between the gold catalyst and the silicon nanowire, presumably by enhanced oxidation at this interface. The pattern formation can be classified as dense branching morphology (DBM). It is the first observation of DBM in a spherical geometry and at the nanoscale. The analysis of the average branching distance of this pattern shows that the pattern is most likely formed during the growth process, not the cooling process, and that the curvature of the gold droplet plays a crucial role in the frequency of branching

  15. WORLD SPATIOTEMPORAL ANALYTICS AND MAPPING PROJECT (WSTAMP: DISCOVERING, EXPLORING, AND MAPPING SPATIOTEMPORAL PATTERNS ACROSS THE WORLD’S LARGEST OPEN SORUCE DATA SETS

    Directory of Open Access Journals (Sweden)

    R. Stewart

    2015-07-01

    Full Text Available 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.

  16. Spatio-Temporal Analysis of Urban Crime Pattern and its Implication for Abuja Municipal Area Council, Nigeria

    Directory of Open Access Journals (Sweden)

    Taiye Oluwafemi Adewuyi

    2017-12-01

    Full Text Available This study examined the spatio-temporal analysis of urban crime pattern and its implication for Abuja Municipal Area Council of the Federal Capital Territory of Nigeria; it has the aim of using Geographical Information System to improve criminal justice system. The aim was achieved by establishing crime incident spots, types of crime committed, the time it occurred and factors responsible for prevailing crime. The methods for data collection involved Geoinformatics through the use of remote sensing and Global Positioning Systems (GPS for spatial data. Questionnaires were administered for other attribute information required. The analysis carried out in a Geographic Information System (GIS environment especially for mapping and the establishment of spatial patterns.  The results indicated that the main types of crime committed were theft and house breaking (42.9%, followed by assault (12.4%, mischief (11.3%, forgery (10.5%, car snatching (9.05%, armed robbery (8.5%, trespass (5.2% and culpable homicide (0.2%. In terms of hot spots the districts recorded the following: Garki (27.62%, Maitama (25.7%, Utako (24.3%, Wuse (20.9% and Asokoro district (1.4% respectively with most of the crime committed during the day time. Many attributed the crimes to mainly high rate of unemployment and poverty (79.1%. Consequently to reduce the crime rate, the socio-economic situation of the city must be improved through properly constructed interventions scheme in areas known to quickly generate employment such as agriculture, small and medium scale enterprises, mining and tourism.

  17. Stability switches, oscillatory multistability, and spatio-temporal patterns of nonlinear oscillations in recurrently delay coupled neural networks.

    Science.gov (United States)

    Song, Yongli; Makarov, Valeri A; Velarde, Manuel G

    2009-08-01

    A model of time-delay recurrently coupled spatially segregated neural assemblies is here proposed. We show that it operates like some of the hierarchical architectures of the brain. Each assembly is a neural network with no delay in the local couplings between the units. The delay appears in the long range feedforward and feedback inter-assemblies communications. Bifurcation analysis of a simple four-units system in the autonomous case shows the richness of the dynamical behaviors in a biophysically plausible parameter region. We find oscillatory multistability, hysteresis, and stability switches of the rest state provoked by the time delay. Then we investigate the spatio-temporal patterns of bifurcating periodic solutions by using the symmetric local Hopf bifurcation theory of delay differential equations and derive the equation describing the flow on the center manifold that enables us determining the direction of Hopf bifurcations and stability of the bifurcating periodic orbits. We also discuss computational properties of the system due to the delay when an external drive of the network mimicks external sensory input.

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

    International Nuclear Information System (INIS)

    Yuan Guoyong; Yang Shiping; Wang Guangrui; Chen Shigang

    2008-01-01

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

  19. Combinatorial Study of Surface Pattern Formation in Thin Block Copolymer Films

    International Nuclear Information System (INIS)

    Smith, Archie P.; Douglas, Jack F.; Meredith, J. Carson; Amis, Eric J.; Karim, Alamgir

    2001-01-01

    Surface pattern formation in diblock copolymer films is investigated as a function of film thickness h and molecular mass M . Smooth films are observed for certain h ranges centered about multiples of the lamellar thickness L 0 , and we attribute this effect to an increase in the surface chain density with h in the outer brushlike copolymer layer. We also observe apparently stable labyrinthine surface patterns for other h ranges, and the average size of these patterns is found to scale as λ∼L -2.5 0 . Hole and island patterns occur for h ranges between those of the labyrinthine patterns and the smooth regions, and their size similarly decreases with L 0 and M

  20. Quantifying the Spatiotemporal Patterns of Urbanization along Urban-Rural Gradient with a Roadscape Transect Approach: A Case Study in Shanghai, China

    Directory of Open Access Journals (Sweden)

    Zhonghao Zhang

    2016-08-01

    Full Text Available Quantifying the landscape pattern change can effectively demonstrate the ecological progresses and the consequences of urbanization. Based on remotely sensed land cover data in 1994, 2000, 2006 and a gradient analysis with landscape metrics at landscape- and class- level, we attempted to characterize the individual and entire landscape patterns of Shanghai metropolitan during the rapid urbanization. We highlighted that a roadscape transect approach that combined the buffer zone method and the transect-based approach was introduced to describe the urban-rural patterns of agricultural, residential, green, industrial, and public facilities land along the railway route. Our results of landscape metrics showed significant spatiotemporal patterns and gradient variations along the transect. The urban growth pattern in two time spans conform to the hypothesis for diffusion–coalescence processes, implying that the railway is adaptive as a gradient element to analyze the landscape patterns with urbanization. As the natural landscape was replaced by urban landscape gradually, the desakota region expanded its extent widely. Suburb areas witnessed the continual transformation from the predominantly rural landscape to peri-urban landscape. Furthermore, the gap between urban and rural areas remained large especially in public service. More reasonable urban plans and land use policies should push to make more efforts to transition from the urban-rural separation to coordinated urban-rural development. This study is a meaningful trial in demonstrating a new form of urban–rural transects to study the landscape change of large cities. By combining gradient analysis with landscape metrics, we addressed the process of urbanization both spatially and temporally, and provided a more quantitative approach to urban studies.

  1. Tensor-based spatiotemporal saliency detection

    Science.gov (United States)

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

    2018-03-01

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

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

    Science.gov (United States)

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

    2017-10-18

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

  3. Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

    DEFF Research Database (Denmark)

    Frelat, Romain; Lindegren, Martin; Dencker, Tim Spaanheden

    2017-01-01

    it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered...... by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii...

  4. Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006

    Science.gov (United States)

    Xia, Jiangzhou; Liu, Shuguang; Liang, Shunlin; Chen, Yang; Xu, Wenfang; Yuan, Wenping

    2014-01-01

    Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

  5. Formation of banded vegetation patterns resulted from interactions between sediment deposition and vegetation growth.

    Science.gov (United States)

    Huang, Tousheng; Zhang, Huayong; Dai, Liming; Cong, Xuebing; Ma, Shengnan

    2018-03-01

    This research investigates the formation of banded vegetation patterns on hillslopes affected by interactions between sediment deposition and vegetation growth. The following two perspectives in the formation of these patterns are taken into consideration: (a) increased sediment deposition from plant interception, and (b) reduced plant biomass caused by sediment accumulation. A spatial model is proposed to describe how the interactions between sediment deposition and vegetation growth promote self-organization of banded vegetation patterns. Based on theoretical and numerical analyses of the proposed spatial model, vegetation bands can result from a Turing instability mechanism. The banded vegetation patterns obtained in this research resemble patterns reported in the literature. Moreover, measured by sediment dynamics, the variation of hillslope landform can be described. The model predicts how treads on hillslopes evolve with the banded patterns. Thus, we provide a quantitative interpretation for coevolution of vegetation patterns and landforms under effects of sediment redistribution. Copyright © 2018. Published by Elsevier Masson SAS.

  6. Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks

    Science.gov (United States)

    Pyle, Ryan; Rosenbaum, Robert

    2017-01-01

    Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

  7. Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks.

    Science.gov (United States)

    Pyle, Ryan; Rosenbaum, Robert

    2017-01-06

    Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

  8. From lag synchronization to pattern formation in one-dimensional open flow models

    International Nuclear Information System (INIS)

    Liu Zengrong; Luo Jigui

    2006-01-01

    In this paper, the relation between synchronization and pattern formation in one-dimensional discrete and continuous open flow models is investigated in detail. Firstly a sufficient condition for globally asymptotical stability of lag/anticipating synchronization among lattices of these models is proved by analytic method. Then, by analyzing and simulating lag/anticipating synchronization in discrete case, three kinds of pattern of wave (it is called wave pattern) travelling in the lattices are discovered. Finally, a proper definition for these kinds of pattern is proposed

  9. Spatiotemporal Analysis of Human Mobility in Manila Metropolitan Area with Person-Trip Data

    Directory of Open Access Journals (Sweden)

    Kai Liu

    2018-01-01

    Full Text Available The metropolitan area can be regarded as a multi-functional structure consisting of plural coordinated urban nucleuses. This study aims to clarify the characteristics of urban nucleuses and a spatiotemporal pattern of human mobility in the Manila metropolitan area. Hourly density of human mobility from 00:00 to 24:00 in the whole study area is quantitatively studied. Urban nucleuses with six types: central city, business city, commuter town, south suburb, north suburb, and subcenter city, are identified. Differences of human mobility owing to different human behaviors or properties are also analyzed in 10 typical areas with different urban functions. Results prove that pattern of human mobility in each area depends on its human social division, population composition, infrastructure condition, and functional structure. This study provides an effective thinking on handling geo-tagged big data supported by MATLAB programming and GIS technology. Moreover, spatiotemporal analysis of human mobility also possesses a meaningful academic value for transport geography.

  10. Parametric spatiotemporal oscillation in reaction-diffusion systems.

    Science.gov (United States)

    Ghosh, Shyamolina; Ray, Deb Shankar

    2016-03-01

    We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

  11. Wildlife in the Matrix: Spatio-Temporal Patterns of Herbivore Occurrence in Karnataka, India

    Science.gov (United States)

    Karanth, Krithi K.

    2016-01-01

    Wildlife reserves are becoming increasingly isolated from the surrounding human-dominated landscapes particularly in Asia. It is imperative to understand how species are distributed spatially and temporally in and outside reserves, and what factors influence their occurrence. This study surveyed 7500 km2 landscape surrounding five reserves in the Western Ghats to examine patterns of occurrence of five herbivores: elephant, gaur, sambar, chital, and pig. Species distributions are modeled spatio-temporally using an occupancy approach. Trained field teams conducted 3860 interview-based occupancy surveys in a 10-km buffer surrounding these five reserves in 2012. I found gaur and wild pig to be the least and most wide-ranging species, respectively. Elephant and chital exhibit seasonal differences in spatial distribution unlike the other three species. As predicted, distance to reserve, the reserve itself, and forest cover were associated with higher occupancy of all species, and higher densities of people negatively influenced occurrence of all species. Park management, species protection, and conflict mitigation efforts in this landscape need to incorporate temporal and spatial understanding of species distributions. All species are known crop raiders and conflict prone locations with resources (such as water and forage) have to be monitored and managed carefully. Wildlife reserves and adjacent areas are critical for long-term persistence and habitat use for all five herbivores and must be monitored to ensure wildlife can move freely. Such a large-scale approach to map and monitor species distributions can be adapted to other landscapes to identify and monitor critical habitats shared by people and wildlife.

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

    Directory of Open Access Journals (Sweden)

    M. Schulte

    2015-06-01

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

  13. Interfacial wave theory of pattern formation in solidification dendrites, fingers, cells and free boundaries

    CERN Document Server

    Xu, Jian-Jun

    2017-01-01

    This comprehensive work explores interfacial instability and pattern formation in dynamic systems away from the equilibrium state in solidification and crystal growth. Further, this significantly expanded 2nd edition introduces and reviews the progress made during the last two decades. In particular, it describes the most prominent pattern formation phenomena commonly observed in material processing and crystal growth in the framework of the previously established interfacial wave theory, including free dendritic growth from undercooled melt, cellular growth and eutectic growth in directional solidification, as well as viscous fingering in Hele-Shaw flow. It elucidates the key problems, systematically derives their mathematical solutions by pursuing a unified, asymptotic approach, and finally carefully examines these results by comparing them with the available experimental results. The asymptotic approach described here will be useful for the investigation of pattern formation phenomena occurring in a much b...

  14. McMaster Mesonet soil moisture dataset: description and spatio-temporal variability analysis

    Directory of Open Access Journals (Sweden)

    K. C. Kornelsen

    2013-04-01

    Full Text Available This paper introduces and describes the hourly, high-resolution soil moisture dataset continuously recorded by the McMaster Mesonet located in the Hamilton-Halton Watershed in Southern Ontario, Canada. The McMaster Mesonet consists of a network of time domain reflectometer (TDR probes collecting hourly soil moisture data at six depths between 10 cm and 100 cm at nine locations per site, spread across four sites in the 1250 km2 watershed. The sites for the soil moisture arrays are designed to further improve understanding of soil moisture dynamics in a seasonal climate and to capture soil moisture transitions in areas that have different topography, soil and land cover. The McMaster Mesonet soil moisture constitutes a unique database in Canada because of its high spatio-temporal resolution. In order to provide some insight into the dominant processes at the McMaster Mesonet sites, a spatio-temporal and temporal stability analysis were conducted to identify spatio-temporal patterns in the data and to suggest some physical interpretation of soil moisture variability. It was found that the seasonal climate of the Great Lakes Basin causes a transition in soil moisture patterns at seasonal timescales. During winter and early spring months, and at the meadow sites, soil moisture distribution is governed by topographic redistribution, whereas following efflorescence in the spring and summer, soil moisture spatial distribution at the forested site was also controlled by vegetation canopy. Analysis of short-term temporal stability revealed that the relative difference between sites was maintained unless there was significant rainfall (> 20 mm or wet conditions a priori. Following a disturbance in the spatial soil moisture distribution due to wetting, the relative soil moisture pattern re-emerged in 18 to 24 h. Access to the McMaster Mesonet data can be provided by visiting www.hydrology.mcmaster.ca/mesonet.

  15. Nonparametric evaluation of dynamic disease risk: a spatio-temporal kernel approach.

    Directory of Open Access Journals (Sweden)

    Zhijie Zhang

    Full Text Available Quantifying the distributions of disease risk in space and time jointly is a key element for understanding spatio-temporal phenomena while also having the potential to enhance our understanding of epidemiologic trajectories. However, most studies to date have neglected time dimension and focus instead on the "average" spatial pattern of disease risk, thereby masking time trajectories of disease risk. In this study we propose a new idea titled "spatio-temporal kernel density estimation (stKDE" that employs hybrid kernel (i.e., weight functions to evaluate the spatio-temporal disease risks. This approach not only can make full use of sample data but also "borrows" information in a particular manner from neighboring points both in space and time via appropriate choice of kernel functions. Monte Carlo simulations show that the proposed method performs substantially better than the traditional (i.e., frequency-based kernel density estimation (trKDE which has been used in applied settings while two illustrative examples demonstrate that the proposed approach can yield superior results compared to the popular trKDE approach. In addition, there exist various possibilities for improving and extending this method.

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

    Science.gov (United States)

    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.

  17. Estimating dew formation in rice, using seasonally averaged diel patterns of weather variables

    NARCIS (Netherlands)

    Luo, W.; Goudriaan, J.

    2004-01-01

    If dew formation cannot be measured it has to be estimated. Available simulation models for estimating dew formation require hourly weather data as input. However, such data are not available for places without an automatic weather station. In such cases the diel pattern of weather variables might

  18. Integrating GIS and ABM to Explore Spatiotemporal Dynamics

    Science.gov (United States)

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

    2013-12-01

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

  19. Spatiotemporal changes of built-up land and population distribution patterns in China during 1990-2010

    Science.gov (United States)

    Ren, Y. H.; Liu, Y. L.; Yu, L. J.

    2017-02-01

    With the population growth, built-up land is expanding constantly in China. The paper aims to analyse spatiotemporal pattern of built-up land and population, and their relationship in China mainland from 1990 to 2010. With population census data and built-up land data, it calculates population density of counties, built-up surface proportion and population density by built-up land, as measures of population and built-up land distribution. The result shows that, the total population and built-up area have increased by 17.5% and 33.9%, respectively, in China mainland from 1990 to 2010. Meanwhile, the population density of built-up land has decreased by 12.0%, indicating that built-up land growth has outpaced population growth overall. However, such changes are not evenly distributed in space and time. Change in the later decade is much more significant than that in the earlier decade. For built-up land, the increases don’t show obvious characteristics of spatial aggregation. Correspondingly, most increases in population density of counties and population density of built-up area are in the northwest area, divided by Aihui-Tengchong line, while most decreases are in the southeast area. These analyses help to explain the overall impact of political-economic environment and the policy changes on urbanization processes for China mainland.

  20. How memory of direct animal interactions can lead to territorial pattern formation.

    Science.gov (United States)

    Potts, Jonathan R; Lewis, Mark A

    2016-05-01

    Mechanistic home range analysis (MHRA) is a highly effective tool for understanding spacing patterns of animal populations. It has hitherto focused on populations where animals defend their territories by communicating indirectly, e.g. via scent marks. However, many animal populations defend their territories using direct interactions, such as ritualized aggression. To enable application of MHRA to such populations, we construct a model of direct territorial interactions, using linear stability analysis and energy methods to understand when territorial patterns may form. We show that spatial memory of past interactions is vital for pattern formation, as is memory of 'safe' places, where the animal has visited but not suffered recent territorial encounters. Additionally, the spatial range over which animals make decisions to move is key to understanding the size and shape of their resulting territories. Analysis using energy methods, on a simplified version of our system, shows that stability in the nonlinear system corresponds well to predictions of linear analysis. We also uncover a hysteresis in the process of territory formation, so that formation may depend crucially on initial space-use. Our analysis, in one dimension and two dimensions, provides mathematical groundwork required for extending MHRA to situations where territories are defended by direct encounters. © 2016 The Author(s).

  1. Pattern formation, logistics, and maximum path probability

    Science.gov (United States)

    Kirkaldy, J. S.

    1985-05-01

    The concept of pattern formation, which to current researchers is a synonym for self-organization, carries the connotation of deductive logic together with the process of spontaneous inference. Defining a pattern as an equivalence relation on a set of thermodynamic objects, we establish that a large class of irreversible pattern-forming systems, evolving along idealized quasisteady paths, approaches the stable steady state as a mapping upon the formal deductive imperatives of a propositional function calculus. In the preamble the classical reversible thermodynamics of composite systems is analyzed as an externally manipulated system of space partitioning and classification based on ideal enclosures and diaphragms. The diaphragms have discrete classification capabilities which are designated in relation to conserved quantities by descriptors such as impervious, diathermal, and adiabatic. Differentiability in the continuum thermodynamic calculus is invoked as equivalent to analyticity and consistency in the underlying class or sentential calculus. The seat of inference, however, rests with the thermodynamicist. In the transition to an irreversible pattern-forming system the defined nature of the composite reservoirs remains, but a given diaphragm is replaced by a pattern-forming system which by its nature is a spontaneously evolving volume partitioner and classifier of invariants. The seat of volition or inference for the classification system is thus transferred from the experimenter or theoretician to the diaphragm, and with it the full deductive facility. The equivalence relations or partitions associated with the emerging patterns may thus be associated with theorems of the natural pattern-forming calculus. The entropy function, together with its derivatives, is the vehicle which relates the logistics of reservoirs and diaphragms to the analog logistics of the continuum. Maximum path probability or second-order differentiability of the entropy in isolation are

  2. The Formation and Spatiotemporal Progress of the pH Wave Induced by the Temperature Gradient in the Thin-Layer H2O2-Na2S2O3-H2SO4-CuSO4 Dynamical System.

    Science.gov (United States)

    Jędrusiak, Mikołaj; Orlik, Marek

    2016-03-31

    The H2O2-S2O3(2-)-H(+)-Cu(2+) dynamical system exhibits sustained oscillations under flow conditions but reveals only a single initial peak of the indicator electrode potential and pH variation under batch isothermal conditions. Thus, in the latter case, there is no possibility of the coupling of the oscillations and diffusion which could lead to formation of sustained spatiotemporal patterns in this process. However, in the inhomogeneous temperature field, due to dependence of the local reaction kinetics on temperature, spatial inhomogeneities of pH distribution can develop which, in the presence of an appropriate indicator, thymol blue, manifest themselves as the color front traveling along the quasi-one-dimensional reactor. In this work, we describe the experimental conditions under which the above-mentioned phenomena can be observed and present their numerical model based on thermokinetic coupling and spatial coordinate introduced to earlier isothermal homogeneous kinetic mechanism.

  3. Gain-of-function screen for genes that affect Drosophila muscle pattern formation.

    Directory of Open Access Journals (Sweden)

    Nicole Staudt

    2005-10-01

    Full Text Available This article reports the production of an EP-element insertion library with more than 3,700 unique target sites within the Drosophila melanogaster genome and its use to systematically identify genes that affect embryonic muscle pattern formation. We designed a UAS/GAL4 system to drive GAL4-responsive expression of the EP-targeted genes in developing apodeme cells to which migrating myotubes finally attach and in an intrasegmental pattern of cells that serve myotubes as a migration substrate on their way towards the apodemes. The results suggest that misexpression of more than 1.5% of the Drosophila genes can interfere with proper myotube guidance and/or muscle attachment. In addition to factors already known to participate in these processes, we identified a number of enzymes that participate in the synthesis or modification of protein carbohydrate side chains and in Ubiquitin modifications and/or the Ubiquitin-dependent degradation of proteins, suggesting that these processes are relevant for muscle pattern formation.

  4. Collective Behavior of Chiral Active Matter: Pattern Formation and Enhanced Flocking

    Science.gov (United States)

    Liebchen, Benno; Levis, Demian

    2017-08-01

    We generalize the Vicsek model to describe the collective behavior of polar circle swimmers with local alignment interactions. While the phase transition leading to collective motion in 2D (flocking) occurs at the same interaction to noise ratio as for linear swimmers, as we show, circular motion enhances the polarization in the ordered phase (enhanced flocking) and induces secondary instabilities leading to structure formation. Slow rotations promote macroscopic droplets with late time sizes proportional to the system size (indicating phase separation) whereas fast rotations generate patterns consisting of phase synchronized microflocks with a controllable characteristic size proportional to the average single-particle swimming radius. Our results defy the viewpoint that monofrequent rotations form a vapid extension of the Vicsek model and establish a generic route to pattern formation in chiral active matter with possible applications for understanding and designing rotating microflocks.

  5. N-cadherin in adult rat cardiomyocytes in culture. II. Spatio-temporal appearance of proteins involved in cell-cell contact and communication. Formation of two distinct N-cadherin/catenin complexes.

    Science.gov (United States)

    Hertig, C M; Butz, S; Koch, S; Eppenberger-Eberhardt, M; Kemler, R; Eppenberger, H M

    1996-01-01

    The spatio-temporal appearance and distribution of proteins forming the intercalated disc were investigated in adult rat cardiomyocytes (ARC). The 'redifferentiation model' of ARC involves extensive remodelling of the plasma membrane and of the myofibrillar apparatus. It represents a valuable system to elucidate the formation of cell-cell contact between cardiomyocytes and to assess the mechanisms by which different proteins involved in the cell-cell adhesion process are sorted in a precise manner to the sites of function. Appearance of N-cadherin, the catenins and connexin43 within newly formed adherens and gap junctions was studied. Here first evidence is provided for a formation of two distinct and separable N-cadherin/catenin complexes in cardiomyocytes. Both complexes are composed of N-cadherin and alpha-catenin which bind to either beta-catenin or plakoglobin in a mutually exclusive manner. The two N-cadherin/catenin complexes are assumed to be functionally involved in the formation of cell-cell contacts in ARC; however, the differential appearance and localization of the two types of complexes may also point to a specific role during ARC differentiation. The newly synthesized beta-catenin containing complex is more abundant during the first stages in culture after ARC isolation, while the newly synthesized plakoglobin containing complex progressively accumulates during the morphological changes of ARC. ARC formed a tissue-like pattern in culture whereby the new cell-cell contacts could be dissolved through Ca2+ depletion. Presence of cAMP and replenishment of Ca2+ content in the culture medium not only allowed reformation of cell-cell contacts but also affected the relative protein ratio between the two N-cadherin/catenin complexes, increasing the relative amount of newly synthesized beta-catenin over plakoglobin at a particular stage of ARC differentiation. The clustered N-cadherin/catenin complexes at the plasma membrane appear to be a prerequisite for the

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

    Directory of Open Access Journals (Sweden)

    Verena Jürgens

    2013-05-01

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

  7. The effect of the signalling scheme on the robustness of pattern formation in development

    KAUST Repository

    Kang, H.-W.

    2012-03-21

    Pattern formation in development is a complex process which involves spatially distributed signals called morphogens that influence gene expression and thus the phenotypic identity of cells. Usually different cell types are spatially segregated, and the boundary between them may be determined by a threshold value of some state variable. The question arises as to how sensitive the location of such a boundary is to variations in properties, such as parameter values, that characterize the system. Here, we analyse both deterministic and stochastic reaction-diffusion models of pattern formation with a view towards understanding how the signalling scheme used for patterning affects the variability of boundary determination between cell types in a developing tissue.

  8. Selective formation of diamond-like carbon coating by surface catalyst patterning

    DEFF Research Database (Denmark)

    Palnichenko, A.V.; Mátéfi-Tempfli, M.; Mátéfi-Tempfli, Stefan

    2004-01-01

    The selective formation of diamond-like carbon coating by surface catalyst patterning was studied. DLC films was deposited using plasma enhanced chemical vapor deposition, filtered vacuum arc deposition, laser ablation, magnetron sputtering and ion-beam lithography methods. The DLC coatings were...

  9. Spiral and Rotor Patterns Produced by Fairy Ring Fungi

    Science.gov (United States)

    Karst, N.; Dralle, D.; Thompson, S. E.

    2015-12-01

    Soil fungi fill many essential ecological and biogeochemical roles, e.g. decomposing litter, redistributing nutrients, and promoting biodiversity. Fairy ring fungi offer a rare glimpse into the otherwise opaque spatiotemporal dynamics of soil fungal growth, because subsurface mycelial patterns can be inferred from observations at the soil's surface. These observations can be made directly when the fungi send up fruiting bodies (e.g., mushrooms and toadstools), or indirectly via the effect the fungi have on neighboring organisms. Grasses in particular often temporarily thrive on the nutrients liberated by the fungus, creating bands of rich, dark green turf at the edge of the fungal mat. To date, only annular (the "ring" in fairy ring) and arc patterns have been described in the literature. We report observations of novel spiral and rotor pattern formation in fairy ring fungi, as seen in publically available high-resolution aerial imagery of 22 sites across the continental United States. To explain these new behaviors, we first demonstrate that a well-known model describing fairy ring formation is equivalent to the Gray-Scott reaction-diffusion model, which is known to support a wide range of dynamical behaviors, including annular traveling waves, rotors, spirals, and stable spatial patterns including spots and stripes. Bifurcation analysis and numerical simulation are then used to define the region of parameter space that supports spiral and rotor formation. We find that this region is adjacent to one within which typical fairy rings develop. Model results suggest simple experimental procedures that could potentially induce traditional ring structures to exhibit rotor or spiral dynamics. Intriguingly, the Gray-Scott model predicts that these same procedures could be used to solicit even richer patterns, including spots and stripes, which have not yet been identified in the field.

  10. Pattern formation and chaos in synergetic systems

    Energy Technology Data Exchange (ETDEWEB)

    Haken, H

    1985-01-01

    A general approach to the reduction of the equations of systems composed of many subsystems of equations for, in general, few order parameters at instability points is sketched. As special case generalized Ginzburg-Landau equations are obtained. Recent results based on these equations, showing pattern formation in the convection instability and flames, are presented. Bifurcations from tori to other tori are treated, and some general conclusions are drawn. Analogies between fluid dynamics and lasers which led to the prediction of laser light chaos by Haken (1975) are pointed out. Finally the suspension of a class of discrete one-dimensional maps is discussed and explicitly presented for a typical case. 21 references.

  11. Emergence of spatiotemporal chaos arising from far-field breakup of spiral waves in the plankton ecological systems

    International Nuclear Information System (INIS)

    Quan-Xing, Liu; Gui-Quan, Sun; Zhen, Jin; Bai-Lian, Li

    2009-01-01

    It has been reported that the minimal spatially extended phytoplankton–zooplankton system exhibits both temporal regular/chaotic behaviour, and spatiotemporal chaos in a patchy environment. As a further investigation by means of computer simulations and theoretical analysis, in this paper we observe that the spiral waves may exist and the spatiotemporal chaos emerge when the parameters are within the mixed Turing–Hopf bifurcation region, which arises from the far-field breakup of the spiral waves over a large range of diffusion coefficients of phytoplankton and zooplankton. Moreover, the spatiotemporal chaos arising from the far-field breakup of spiral waves does not gradually invade the whole space of that region. Our results are confirmed by nonlinear bifurcation of wave trains. We also discuss ecological implications of these spatially structured patterns. (general)

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

    Directory of Open Access Journals (Sweden)

    Adriana Loureiro

    2018-01-01

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

  13. Spatiotemporal patterns of non-genetically modified crops in the era of expansion of genetically modified food.

    Science.gov (United States)

    Sun, Jing; Wu, Wenbin; Tang, Huajun; Liu, Jianguo

    2015-09-18

    Despite heated debates over the safety of genetically modified (GM) food, GM crops have been expanding rapidly. Much research has focused on the expansion of GM crops. However, the spatiotemporal dynamics of non-genetically modified (non-GM) crops are not clear, although they may have significant environmental and agronomic impacts and important policy implications. To understand the dynamics of non-GM crops and to inform the debates among relevant stakeholders, we conducted spatiotemporal analyses of China's major non-GM soybean production region, the Heilongjiang Province. Even though the total soybean planting area decreased from 2005 to 2010, surprisingly, there were hotspots of increase. The results also showed hotspots of loss as well as a large decline in the number and continuity of soybean plots. Since China is the largest non-GM soybean producer in the world, the decline of its major production region may signal the continual decline of global non-GM soybeans.

  14. Integument pattern formation involves genetic and epigenetic controls: feather arrays simulated by digital hormone models.

    Science.gov (United States)

    Jiang, Ting-Xin; Widelitz, Randall B; Shen, Wei-Min; Will, Peter; Wu, Da-Yu; Lin, Chih-Min; Jung, Han-Sung; Chuong, Cheng-Ming

    2004-01-01

    Pattern formation is a fundamental morphogenetic process. Models based on genetic and epigenetic control have been proposed but remain controversial. Here we use feather morphogenesis for further evaluation. Adhesion molecules and/or signaling molecules were first expressed homogenously in feather tracts (restrictive mode, appear earlier) or directly in bud or inter-bud regions ( de novo mode, appear later). They either activate or inhibit bud formation, but paradoxically colocalize in the bud. Using feather bud reconstitution, we showed that completely dissociated cells can reform periodic patterns without reference to previous positional codes. The patterning process has the characteristics of being self-organizing, dynamic and plastic. The final pattern is an equilibrium state reached by competition, and the number and size of buds can be altered based on cell number and activator/inhibitor ratio, respectively. We developed a Digital Hormone Model which consists of (1) competent cells without identity that move randomly in a space, (2) extracellular signaling hormones which diffuse by a reaction-diffusion mechanism and activate or inhibit cell adhesion, and (3) cells which respond with topological stochastic actions manifested as changes in cell adhesion. Based on probability, the results are cell clusters arranged in dots or stripes. Thus genetic control provides combinational molecular information which defines the properties of the cells but not the final pattern. Epigenetic control governs interactions among cells and their environment based on physical-chemical rules (such as those described in the Digital Hormone Model). Complex integument patterning is the sum of these two components of control and that is why integument patterns are usually similar but non-identical. These principles may be shared by other pattern formation processes such as barb ridge formation, fingerprints, pigmentation patterning, etc. The Digital Hormone Model can also be applied to

  15. Spatiotemporal optical solitons

    International Nuclear Information System (INIS)

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

    2005-01-01

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

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

    NARCIS (Netherlands)

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

    2012-01-01

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

  17. Effect of growth parameters on spatial pattern formation of cadmium hydroxide in agar gel

    International Nuclear Information System (INIS)

    Palaniandavar, N.; Gnanam, F.D.; Ramasamy, P.

    1986-01-01

    The interrelated effects of growth parameters on spatial pattern formation of cadmium hydroxide in agar gel medium have been investigated. The main parameters are concentration of electrolytes, pH of the medium, density of the gel, the concentration of parasitic electrolyte and the concentration of additives. The pattern formation is explained on the basis of electrical double layer theory coupled with diffusion. Using Shinohara's revised coagulation concept, the flocculation value is calculated. With suitable combinations of parameter values, dendritic growth and spherulitic growth of cadmium hydroxide crystals have been observed. (author)

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

    DEFF Research Database (Denmark)

    Møller, Jesper; Ghorbani, Mohammad

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

  19. The mechanism of Turing pattern formation in a positive feedback system with cross diffusion

    International Nuclear Information System (INIS)

    Yang, Xiyan; Liu, Tuoqi; Zhang, Jiajun; Zhou, Tianshou

    2014-01-01

    In this paper, we analyze a reaction–diffusion (R–D) system with a double negative feedback loop and find cases where self diffusion alone cannot lead to Turing pattern formation but cross diffusion can. Specifically, we first derive a set of sufficient conditions for Turing instability by performing linear stability analysis, then plot two bifurcation diagrams that specifically identify Turing regions in the parameter phase plane, and finally numerically demonstrate representative Turing patterns according to the theoretical predictions. Our analysis combined with previous studies actually implies an interesting fact that Turing patterns can be generated not only in a class of monostable R–D systems where cross diffusion is not necessary but also in a class of bistable R–D systems where cross diffusion is necessary. In addition, our model would be a good candidate for experimentally testing Turing pattern formation from the viewpoint of synthetic biology. (paper)

  20. Optimizing Cruising Routes for Taxi Drivers Using a Spatio-Temporal Trajectory Model

    Directory of Open Access Journals (Sweden)

    Liang Wu

    2017-11-01

    Full Text Available Much of the taxi route-planning literature has focused on driver strategies for finding passengers and determining the hot spot pick-up locations using historical global positioning system (GPS trajectories of taxis based on driver experience, distance from the passenger drop-off location to the next passenger pick-up location and the waiting times at recommended locations for the next passenger. The present work, however, considers the average taxi travel speed mined from historical taxi GPS trajectory data and the allocation of cruising routes to more than one taxi driver in a small-scale region to neighboring pick-up locations. A spatio-temporal trajectory model with load balancing allocations is presented to not only explore pick-up/drop-off information but also provide taxi drivers with cruising routes to the recommended pick-up locations. In simulation experiments, our study shows that taxi drivers using cruising routes recommended by our spatio-temporal trajectory model can significantly reduce the average waiting time and travel less distance to quickly find their next passengers, and the load balancing strategy significantly alleviates road loads. These objective measures can help us better understand spatio-temporal traffic patterns and guide taxi navigation.

  1. Amplitude death and spatiotemporal bifurcations in nonlocally delay-coupled oscillators

    International Nuclear Information System (INIS)

    Guo, Yuxiao; Niu, Ben

    2015-01-01

    Amplitude death and spatiotemporal oscillations are remarkable patterns in coupled systems. We consider a ring of n identical oscillators with distance-dependent couplings and time delay. The amplitude death region is the intersection of three stable regions. Employing the method of multiple scales and normal form theory, the stability and criticality of spatiotemporal oscillations are determined. Around the amplitude death boundary there exist one branch of synchronized oscillations, n − 3 branches of co-existing phase-locked oscillations, n branches of mirror-reflecting oscillations, n branches of standing-wave oscillations, one branch of quasiperiodic oscillations and two branches of co-existing synchronized oscillations. It is proved that amplitude death is robust to small inhomogeneity of couplings, and the stability of synchronized or phase-locked oscillations inherits that of the individual decoupled oscillator. For the arbitrary form of coupling functions, some general results are also obtained for the thermodynamic limit. Finally, two examples are given to support the main results. (paper)

  2. Seasonal Habitat Patterns of Japanese Common Squid (Todarodes Pacificus Inferred from Satellite-Based Species Distribution Models

    Directory of Open Access Journals (Sweden)

    Irene D. Alabia

    2016-11-01

    Full Text Available The understanding of the spatio-temporal distributions of the species habitat in the marine environment is central to effectual resource management and conservation. Here, we examined the potential habitat distributions of Japanese common squid (Todarodes pacificus in the Sea of Japan during a four-year period. The seasonal patterns of preferential habitat were inferred from species distribution models, built using squid occurrences detected from night-time visible images and remotely-sensed environmental factors. The predicted squid habitat (i.e., areas with high habitat suitability revealed strong seasonal variability, characterized by a reduction of potential habitat, confined off of the southern part of the basin during the winter–spring period (December–May. Apparent expansion of preferential habitat occurred during summer–autumn months (June–November, concurrent with the formation of highly suitable habitat patches in certain regions of the Sea of Japan. These habitat distribution patterns were in response to changes in oceanographic conditions and synchronous with seasonal migration of squid. Moreover, the most important variables regulating the spatio-temporal patterns of suitable habitat were sea surface temperature, depth, sea surface height anomaly, and eddy kinetic energy. These variables could affect the habitat distributions through their impacts on growth and survival of squid, local nutrient transport, and the availability of favorable spawning and feeding grounds.

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

    Science.gov (United States)

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

    2010-01-01

    This study aims to examine the impact of socio-ecologic factors on the transmission of Ross River virus (RRV) infection and to identify areas prone to social and ecologic-driven epidemics in Queensland, Australia. We used a Bayesian spatiotemporal conditional autoregressive model to quantify the relationship between monthly variation of RRV incidence and socio-ecologic factors and to determine spatiotemporal patterns. Our results show that the average increase in monthly RRV incidence was 2.4% (95% credible interval (CrI): 0.1–4.5%) and 2.0% (95% CrI: 1.6–2.3%) for a 1°C increase in monthly average maximum temperature and a 10 mm increase in monthly average rainfall, respectively. A significant spatiotemporal variation and interactive effect between temperature and rainfall on RRV incidence were found. No association between Socio-economic Index for Areas (SEIFA) and RRV was observed. The transmission of RRV in Queensland, Australia appeared to be primarily driven by ecologic variables rather than social factors. PMID:20810846

  4. Image sequence analysis using spatio-temporal texture

    International Nuclear Information System (INIS)

    Sengupta, S.K.; Clark, G.A.; Barnes, F.L.; Schaich, P.C.

    1994-01-01

    The authors have developed and coded an algorithm for motion pattern classification based on spatio-temporal texture. The algorithm has been implemented and tested for the detection of wakes in simulated data with a relatively low signal-to-noise ratio (0.7 dB). Using a open-quote hold one out close-quote method, a detection probability of 100% with a 0% false alarm rate has been achieved on the limited number of samples (47 in each category) tested. The actual detection can be displayed in the form of a movie that can effectively show the submarine tracks based on the detected wake locations

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

    Science.gov (United States)

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

    2017-12-01

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

  6. Spatio-temporal expression patterns of Wnt signaling pathway during the development of temporomandibular condylar cartilage.

    Science.gov (United States)

    Chen, Kan; Quan, Huixin; Chen, Gang; Xiao, Di

    2017-11-01

    There is a growing body of evidence supporting the involvement of the Wnt signaling pathway in various aspects of skeletal and joint development; however, it is unclear whether it is involved in the process of temporomandibular joint development. In order to clarify this issue, we examined the spatio-temporal distribution of mRNAs and proteins of the Wnt family during the formation of the mandibular condylar cartilage at the prenatal and postnatal stages. An in situ hybridization test revealed no mRNAs of β-catenin and Axin2 during early mesenchymal condensation; the ligands surveyed in this study (including Wnt-4, 5a, and 9a) were clearly detected at various ranges of expression, mainly in the condylar blastema and later distinct cartilaginous layers. Apart from β-catenin and Axin2, the Wnt family members surveyed in this study, including Lef-1, were found to be immunopositive during early chondrogenesis in the condylar cartilage at E14.5. After distinct chondrocyte layers were identified within the cartilage at E16.5, the expression of the Wnt signaling members was different and mainly restricted to proliferating cells and mineralized hypertrophic chondrocytes. In the adult mandibular condylar cartilage, the Wnt-4 mRNA, as well as the Wnt-4 and Wnt-9a proteins, was not observed. Our findings demonstrated that the Wnt signaling pathway was associated with the development of mandibular condylar cartilage. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Pattern formation in individual-based systems with time-varying parameters

    Science.gov (United States)

    Ashcroft, Peter; Galla, Tobias

    2013-12-01

    We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.

  8. Analysis of pattern formation in systems with competing range interactions

    International Nuclear Information System (INIS)

    Zhao, H J; Misko, V R; Peeters, F M

    2012-01-01

    We analyzed pattern formation and identified various morphologies in a system of particles interacting through a non-monotonic potential with a competing range interaction characterized by a repulsive core (r c ) and an attractive tail (r > r c ), using molecular-dynamics simulations. Depending on parameters, the interaction potential models the inter-particle interaction in various physical systems ranging from atoms, molecules and colloids to vortices in low κ type-II superconductors and in recently discovered ‘type-1.5’ superconductors. We constructed a ‘morphology diagram’ in the plane ‘critical radius r c -density n’ and proposed a new approach to characterizing the different types of patterns. Namely, we elaborated a set of quantitative criteria in order to identify the different pattern types, using the radial distribution function (RDF), the local density function and the occupation factor. (paper)

  9. Protein Tyrosine Phosphatase-PEST and β8 Integrin Regulate Spatiotemporal Patterns of RhoGDI1 Activation in Migrating Cells

    Science.gov (United States)

    Lee, Hye Shin; Cheerathodi, Mujeeburahiman; Chaki, Sankar P.; Reyes, Steve B.; Zheng, Yanhua; Lu, Zhimin; Paidassi, Helena; DerMardirossian, Celine; Lacy-Hulbert, Adam; Rivera, Gonzalo M.

    2015-01-01

    Directional cell motility is essential for normal development and physiology, although how motile cells spatiotemporally activate signaling events remains largely unknown. Here, we have characterized an adhesion and signaling unit comprised of protein tyrosine phosphatase (PTP)-PEST and the extracellular matrix (ECM) adhesion receptor β8 integrin that plays essential roles in directional cell motility. β8 integrin and PTP-PEST form protein complexes at the leading edge of migrating cells and balance patterns of Rac1 and Cdc42 signaling by controlling the subcellular localization and phosphorylation status of Rho GDP dissociation inhibitor 1 (RhoGDI1). Translocation of Src-phosphorylated RhoGDI1 to the cell's leading edge promotes local activation of Rac1 and Cdc42, whereas dephosphorylation of RhoGDI1 by integrin-bound PTP-PEST promotes RhoGDI1 release from the membrane and sequestration of inactive Rac1/Cdc42 in the cytoplasm. Collectively, these data reveal a finely tuned regulatory mechanism for controlling signaling events at the leading edge of directionally migrating cells. PMID:25666508

  10. Formation of quasistationary vortex and transient hole patterns through vortex merger

    International Nuclear Information System (INIS)

    Ganesh, R.; Lee, J.K.

    2002-01-01

    Collection of point-like intense vortices arranged symmetrically outside of a uniform circular vortex patch, both enclosed in a free-slip circular boundary, are numerically time evolved for up to 10-15 patch turnover times. These patterns are found to merge with the patch by successively inducing nonlinear dispersive modes (V-states) on the surface of the patch, draw off fingers of vorticity (filamentation), trap the irrotational regions as the fingers symmetrize under the shear flow of the patch and point-like vortices (wave breaking) followed by the vortex-hole capture. While the hole patterns are observed to break up over several turnover periods the vortex patterns appear to evolve into quasistationary patterns for some cases of an initial number of point-like vortices N pv . The bounded V-states, filamentation, and vortex (hole) pattern formation are discussed in some detail and their possible connection to recently observed vortex 'crystals' is pointed out

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

    Science.gov (United States)

    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.

  12. Integrated approaches to spatiotemporally directing angiogenesis in host and engineered tissues.

    Science.gov (United States)

    Kant, Rajeev J; Coulombe, Kareen L K

    2018-03-15

    The field of tissue engineering has turned towards biomimicry to solve the problem of tissue oxygenation and nutrient/waste exchange through the development of vasculature. Induction of angiogenesis and subsequent development of a vascular bed in engineered tissues is actively being pursued through combinations of physical and chemical cues, notably through the presentation of topographies and growth factors. Presenting angiogenic signals in a spatiotemporal fashion is beginning to generate improved vascular networks, which will allow for the creation of large and dense engineered tissues. This review provides a brief background on the cells, mechanisms, and molecules driving vascular development (including angiogenesis), followed by how biomaterials and growth factors can be used to direct vessel formation and maturation. Techniques to accomplish spatiotemporal control of vascularization include incorporation or encapsulation of growth factors, topographical engineering, and 3D bioprinting. The vascularization of engineered tissues and their application in angiogenic therapy in vivo is reviewed herein with an emphasis on the most densely vascularized tissue of the human body - the heart. Vascularization is vital to wound healing and tissue regeneration, and development of hierarchical networks enables efficient nutrient transfer. In tissue engineering, vascularization is necessary to support physiologically dense engineered tissues, and thus the field seeks to induce vascular formation using biomaterials and chemical signals to provide appropriate, pro-angiogenic signals for cells. This review critically examines the materials and techniques used to generate scaffolds with spatiotemporal cues to direct vascularization in engineered and host tissues in vitro and in vivo. Assessment of the field's progress is intended to inspire vascular applications across all forms of tissue engineering with a specific focus on highlighting the nuances of cardiac tissue

  13. Self-similar pattern formation and continuous mechanics of self-similar systems

    Directory of Open Access Journals (Sweden)

    A. V. Dyskin

    2007-01-01

    Full Text Available In many cases, the critical state of systems that reached the threshold is characterised by self-similar pattern formation. We produce an example of pattern formation of this kind – formation of self-similar distribution of interacting fractures. Their formation starts with the crack growth due to the action of stress fluctuations. It is shown that even when the fluctuations have zero average the cracks generated by them could grow far beyond the scale of stress fluctuations. Further development of the fracture system is controlled by crack interaction leading to the emergence of self-similar crack distributions. As a result, the medium with fractures becomes discontinuous at any scale. We develop a continuum fractal mechanics to model its physical behaviour. We introduce a continuous sequence of continua of increasing scales covering this range of scales. The continuum of each scale is specified by the representative averaging volume elements of the corresponding size. These elements determine the resolution of the continuum. Each continuum hides the cracks of scales smaller than the volume element size while larger fractures are modelled explicitly. Using the developed formalism we investigate the stability of self-similar crack distributions with respect to crack growth and show that while the self-similar distribution of isotropically oriented cracks is stable, the distribution of parallel cracks is not. For the isotropically oriented cracks scaling of permeability is determined. For permeable materials (rocks with self-similar crack distributions permeability scales as cube of crack radius. This property could be used for detecting this specific mechanism of formation of self-similar crack distributions.

  14. Spatiotemporal Pattern of PM2.5 Concentrations in Mainland China and Analysis of Its Influencing Factors using Geographically Weighted Regression

    Science.gov (United States)

    Luo, Jieqiong; Du, Peijun; Samat, Alim; Xia, Junshi; Che, Meiqin; Xue, Zhaohui

    2017-01-01

    Based on annual average PM2.5 gridded dataset, this study first analyzed the spatiotemporal pattern of PM2.5 across Mainland China during 1998-2012. Then facilitated with meteorological site data, land cover data, population and Gross Domestic Product (GDP) data, etc., the contributions of latent geographic factors, including socioeconomic factors (e.g., road, agriculture, population, industry) and natural geographical factors (e.g., topography, climate, vegetation) to PM2.5 were explored through Geographically Weighted Regression (GWR) model. The results revealed that PM2.5 concentrations increased while the spatial pattern remained stable, and the proportion of areas with PM2.5 concentrations greater than 35 μg/m3 significantly increased from 23.08% to 29.89%. Moreover, road, agriculture, population and vegetation showed the most significant impacts on PM2.5. Additionally, the Moran’s I for the residuals of GWR was 0.025 (not significant at a 0.01 level), indicating that the GWR model was properly specified. The local coefficient estimates of GDP in some cities were negative, suggesting the existence of the inverted-U shaped Environmental Kuznets Curve (EKC) for PM2.5 in Mainland China. The effects of each latent factor on PM2.5 in various regions were different. Therefore, regional measures and strategies for controlling PM2.5 should be formulated in terms of the local impacts of specific factors.

  15. Spatio-Temporal Pattern Mining on Trajectory Data Using Arm

    Science.gov (United States)

    Khoshahval, S.; Farnaghi, M.; Taleai, M.

    2017-09-01

    Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user's visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users' behaviour in a system and can be utilized in various location-based applications.

  16. Geographical distribution and spatio-temporal patterns of hospitalization due to dengue infection at a leading specialist hospital in Malaysia.

    Science.gov (United States)

    Low, Gary K K; Papapreponis, Panayoti; Isa, Ridzuan M; Gan, Seng Chiew; Chee, Hui Yee; Te, Kian Keong; Hatta, Nadia M

    2018-05-07

    Increasing numbers of dengue infection worldwide have led to a rise in deaths due to complications caused by this disease. We present here a cross-sectional study of dengue patients who attended the Emergency and Trauma Department of Ampang Hospital, one of Malaysia's leading specialist hospitals. The objective was to search for potential clustering of severe dengue, in space and/or time, among the annual admissions with the secondary objective to describe the spatio-temporal pattern of all dengue cases admitted to this hospital. The dengue status of the patients was confirmed serologically with the geographic location of the patients determined by residency, but not more specific than the street level. A total of 1165 dengue patients were included in the analysis using SaTScan software. The mean age of these patients was 27.8 years, with a standard deviation of 14.2 years and an age range from 1 to 77 years, among whom 54 (4.6%) were cases of severe dengue. A cluster of general dengue cases was identified occurring from October to December in the study year of 2015 but the inclusion of severe dengue in that cluster was not statistically significant (P=0.862). The standardized incidence ratio was 1.51. General presence of dengue cases was, however, detected to be concentrated at the end of the year, which should be useful for hospital planning and management if this pattern holds.

  17. Dynamic Assessment on the Landscape Patterns and Spatio-temporal Change in the mainstream of Tarim River

    Science.gov (United States)

    Zhang, Hui; Xue, Lianqing; Yang, Changbing; Chen, Xinfang; Zhang, Luochen; Wei, Guanghui

    2018-01-01

    The Tarim River (TR), as the longest inland river at an arid area in China, is a typical regions of vegetation variation research and plays a crucial role in the sustainable development of regional ecological environment. In this paper, the newest dataset of MODND1M NDVI, at a resolution of 500m, were applied to calculate vegetation index in growing season during the period 2000-2015. Using a vegetation coverage index, a trend line analysis, and the local spatial autocorrelation analysis, this paper investigated the landscape patterns and spatio-temporal variation of vegetation coverage at regional and pixel scales over mainstream of the Tarim River, Xinjiang. The results showed that (1) The bare land area on both sides of Tarim River appeared to have a fluctuated downward trend and there were two obvious valley values in 2005 and 2012. (2) Spatially, the vegetation coverage improved areas is mostly distributed in upstream and the degraded areas is mainly distributed in the left bank of midstream and the end of Tarim River during 2000-2005. (3) The local spatial auto-correlation analysis revealed that vegetation coverage was spatially positive autocorrelated and spatial concentrated. The high-high self-related areas are mainly distributed in upstream, where vegetation cover are relatively good, and the low-low self-related areas are mostly with lower vegetation cover in the lower reaches of Tarim River.

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

    DEFF Research Database (Denmark)

    Møller, Jesper; Ghorbani, Mohammad

    2012-01-01

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

  19. SPATIO-TEMPORAL PATTERN MINING ON TRAJECTORY DATA USING ARM

    Directory of Open Access Journals (Sweden)

    S. Khoshahval

    2017-09-01

    Full Text Available Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user’s visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users’ behaviour in a system and can be utilized in various location-based applications.

  20. The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World's Largest Open Source Data Sets

    Science.gov (United States)

    Piburn, J.; Stewart, R.; Myers, A.; Sorokine, A.; Axley, E.; Anderson, D.; Burdette, J.; Biddle, C.; Hohl, A.; Eberle, R.; Kaufman, J.; Morton, A.

    2017-10-01

    Spatiotemporal (ST) analytics applied to major data sources such as the World Bank and World Health Organization has shown tremendous value in shedding light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. WSTAMP engages this opportunity by situating analysts, data, and analytics together within a visually rich and computationally rigorous online analysis environment. Since introducing WSTAMP at the First International Workshop on Spatiotemporal Computing, several transformative advances have occurred. Collaboration with human computer interaction experts led to a complete interface redesign that deeply immerses the analyst within a ST context, significantly increases visual and textual content, provides navigational crosswalks for attribute discovery, substantially reduce mouse and keyboard actions, and supports user data uploads. Secondly, the database has been expanded to include over 16,000 attributes, 50 years of time, and 200+ nation states and redesigned to support non-annual, non-national, city, and interaction data. Finally, two new analytics are implemented for analyzing large portfolios of multi-attribute data and measuring the behavioral stability of regions along different dimensions. These advances required substantial new approaches in design, algorithmic innovations, and increased computational efficiency. We report on these advances and inform how others may freely access the tool.

  1. SPATIOTEMPORAL CONTRAST SENSITIVITY OF EARLY VISION

    NARCIS (Netherlands)

    Hateren, J.H. van

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

  2. Characteristics of juvenile survivors reveal spatio-temporal differences in early life stage survival of Baltic cod

    DEFF Research Database (Denmark)

    Huwer, Bastian; Hinrichsen, H.H.; Böttcher, U.

    2014-01-01

    with previous modeling studies on the survival chances of early-stage larvae and with general spatio-temporal patterns of larval prey availability suggests that differences in survival are related to food availability during the early larval stage. Results are discussed in relation to the recruitment process...

  3. Formation mechanisms and characteristics of transition patterns in oblique detonations

    Science.gov (United States)

    Miao, Shikun; Zhou, Jin; Liu, Shijie; Cai, Xiaodong

    2018-01-01

    The transition structures of wedge-induced oblique detonation waves (ODWs) in high-enthalpy supersonic combustible mixtures are studied with two-dimensional reactive Euler simulations based on the open-source program AMROC (Adaptive Mesh Refinement in Object-oriented C++). The formation mechanisms of different transition patterns are investigated through theoretical analysis and numerical simulations. Results show that transition patterns of ODWs depend on the pressure ratio Pd/Ps, (Pd, Ps are the pressure behind the ODW and the pressure behind the induced shock, respectively). When Pd/Ps > 1.3, an abrupt transition occurs, while when Pd/Ps 1.02Φ∗ (Φ∗ is the critical velocity ratio calculated with an empirical formula).

  4. Bifurcation and spatial pattern formation in spreading of disease with incubation period in a phytoplankton dynamics

    Directory of Open Access Journals (Sweden)

    Randhir Singh Baghel

    2012-02-01

    Full Text Available In this article, we propose a three dimensional mathematical model of phytoplankton dynamics with the help of reaction-diffusion equations that studies the bifurcation and pattern formation mechanism. We provide an analytical explanation for understanding phytoplankton dynamics with three population classes: susceptible, incubated, and infected. This model has a Holling type II response function for the population transformation from susceptible to incubated class in an aquatic ecosystem. Our main goal is to provide a qualitative analysis of Hopf bifurcation mechanisms, taking death rate of infected phytoplankton as bifurcation parameter, and to study further spatial patterns formation due to spatial diffusion. Here analytical findings are supported by the results of numerical experiments. It is observed that the coexistence of all classes of population depends on the rate of diffusion. Also we obtained the time evaluation pattern formation of the spatial system.

  5. Chemotactic preferences govern competition and pattern formation in simulated two-strain microbial communities.

    Science.gov (United States)

    Centler, Florian; Thullner, Martin

    2015-01-01

    Substrate competition is a common mode of microbial interaction in natural environments. While growth properties play an important and well-studied role in competition, we here focus on the influence of motility. In a simulated two-strain community populating a homogeneous two-dimensional environment, strains competed for a common substrate and only differed in their chemotactic preference, either responding more sensitively to a chemoattractant excreted by themselves or responding more sensitively to substrate. Starting from homogeneous distributions, three possible behaviors were observed depending on the competitors' chemotactic preferences: (i) distributions remained homogeneous, (ii) patterns formed but dissolved at a later time point, resulting in a shifted community composition, and (iii) patterns emerged and led to the extinction of one strain. When patterns formed, the more aggregating strain populated the core of microbial aggregates where starving conditions prevailed, while the less aggregating strain populated the more productive zones at the fringe or outside aggregates, leading to a competitive advantage of the less aggregating strain. The presence of a competitor was found to modulate a strain's behavior, either suppressing or promoting aggregate formation. This observation provides a potential mechanism by which an aggregated lifestyle might evolve even if it is initially disadvantageous. Adverse effects can be avoided as a competitor hinders aggregate formation by a strain which has just acquired this ability. The presented results highlight both, the importance of microbial motility for competition and pattern formation, and the importance of the temporal evolution, or history, of microbial communities when trying to explain an observed distribution.

  6. MEDICAL STUDENTS’ FEEDBACK ABOUT FORMATIVE ASSESSMENT PATTERN

    Directory of Open Access Journals (Sweden)

    Navajothi

    2016-03-01

    Full Text Available BACKGROUND Pharmacology is the toughest subject in the II MBBS syllabus. Students have to memorise a lot about the drugs’ name and classification. We are conducting internal assessment exams after completion of each system. Number of failures will be more than 60% in the internal assessments conducted during first six months of II MBBS course. AIM To assess the formative assessment pattern followed in our institution with the students’ feedback and modify the pattern according to the students’ feedback. SETTINGS & DESIGN Prospective Observational Study conducted at Department of Pharmacology, Government Sivagangai Medical College, Sivagangai, Tamil Nadu. MATERIALS AND METHODS Questionnaire was prepared and distributed to the 300 students of Government Sivagangai Medical College and feedback was collected. Data collected was analysed in Microsoft Excel 2007 version. RESULTS Received feedback from 274 students. Most (80% of the students wanted to attend the tests in all systems. Monthly assessment test was preferred by 47% of the students. Students who preferred to finish tests before holidays was 57%. Most (56% of the students preferred tests for 1 hour. Multiple choice question (MCQ type was preferred by 43%, which is not a routine question pattern. Only 7% preferred viva. Recall type of questions was preferred by 41% of the students. CONCLUSION In our institution, internal assessment is conducted as per the students’ mind setup. As the feedback has been the generally followed one, we will add MCQs in the forthcoming tests. Application type questions will be asked for more marks than Recall type of questions.

  7. Spatiotemporal Dynamics of Whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) in Commercial Watermelon Crops.

    Science.gov (United States)

    Lima, Carlos H O; Sarmento, Renato A; Galdino, Tarcísio V S; Pereira, Poliana S; Silva, Joedna; Souza, Danival J; Dos Santos, Gil R; Costa, Thiago L; Picanço, Marcelo C

    2018-04-16

    Spatiotemporal dynamics studies of crop pests enable the determination of the colonization pattern and dispersion of these insects in the landscape. Geostatistics is an efficient tool for these studies: to determine the spatial distribution pattern of the pest in the crops and to make maps that represent this situation. Analysis of these maps across the development of plants can be used as a tool in precision agriculture programs. Watermelon, Citrullus lanatus (Thunb.) Matsum. and Nakai (Cucurbitales: Cucurbitaceae), is the second most consumed fruit in the world, and the whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is one of the most important pests of this crop. Thus, the objective of this work was to determine the spatiotemporal distribution of B. tabaci in commercial watermelon crops using geostatistics. For 2 yr, we monitored adult whitefly densities in eight watermelon crops in a tropical climate region. The location of the samples and other crops in the landscape was georeferenced. Experimental data were submitted to geostatistical analysis. The colonization of B. tabaci had two patterns. In the first, the colonization started at the outermost parts of the crop. In the second, the insects occupied the whole area of the crop since the beginning of cultivation. The maximum distance between sites of watermelon crops in which spatial dependence of B. tabaci densities was observed was 19.69 m. The adult B. tabaci densities in the eight watermelon fields were positively correlated with rainfall and relative humidity, whereas wind speed negatively affected whiteflies population.

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

    OpenAIRE

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

    2013-01-01

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

  9. Influence of fast advective flows on pattern formation of Dictyostelium discoideum

    Science.gov (United States)

    Bae, Albert; Zykov, Vladimir; Bodenschatz, Eberhard

    2018-01-01

    We report experimental and numerical results on pattern formation of self-organizing Dictyostelium discoideum cells in a microfluidic setup under a constant buffer flow. The external flow advects the signaling molecule cyclic adenosine monophosphate (cAMP) downstream, while the chemotactic cells attached to the solid substrate are not transported with the flow. At high flow velocities, elongated cAMP waves are formed that cover the whole length of the channel and propagate both parallel and perpendicular to the flow direction. While the wave period and transverse propagation velocity are constant, parallel wave velocity and the wave width increase linearly with the imposed flow. We also observe that the acquired wave shape is highly dependent on the wave generation site and the strength of the imposed flow. We compared the wave shape and velocity with numerical simulations performed using a reaction-diffusion model and found excellent agreement. These results are expected to play an important role in understanding the process of pattern formation and aggregation of D. discoideum that may experience fluid flows in its natural habitat. PMID:29590179

  10. Class of nonsingular exact solutions for Laplacian pattern formation

    International Nuclear Information System (INIS)

    Mineev-Weinstein, M.B.; Dawson, S.P.

    1994-01-01

    We present a class of exact solutions for the so-called Laplacian growth equation describing the zero-surface-tension limit of a variety of two-dimensional pattern formation problems. These solutions are free of finite-time singularities (cusps) for quite general initial conditions. They reproduce various features of viscous fingering observed in experiments and numerical simulations with surface tension, such as existence of stagnation points, screening, tip splitting, and coarsening. In certain cases the asymptotic interface consists of N separated moving Saffman-Taylor fingers

  11. Universal stability curve for pattern formation in pulsed gas-solid fluidized beds of sandlike particles

    Science.gov (United States)

    de Martín, Lilian; Ottevanger, Coen; van Ommen, J. Ruud; Coppens, Marc-Olivier

    2018-03-01

    A granular layer can form regular patterns, such as squares, stripes, and hexagons, when it is fluidized with a pulsating gas flow. These structures are reminiscent of the well-known patterns found in granular layers excited through vibration, but, contrarily to them, they have been hardly explored since they were first discovered. In this work, we investigate experimentally the conditions leading to pattern formation in pulsed fluidized beds and the dimensionless numbers governing the phenomenon. We show that the onset to the instability is universal for Geldart B (sandlike) particles and governed by the hydrodynamical parameters Γ =ua/(utϕ ¯) and f /fn , where ua and f are the amplitude and frequency of the gas velocity, respectively, ut is the terminal velocity of the particles, ϕ ¯ is the average solids fraction, and fn is the natural frequency of the bed. These findings suggest that patterns emerge as a result of a parametric resonance between the kinematic waves originating from the oscillating gas flow and the bulk dynamics. Particle friction plays virtually no role in the onset to pattern formation, but it is fundamental for pattern selection and stabilization.

  12. Inherent-opening-controlled pattern formation in carbon nanotube arrays

    International Nuclear Information System (INIS)

    Huang Xiao; Zhou, Jijie J; Sansom, Elijah; Gharib, Morteza; Haur, Sow Chorng

    2007-01-01

    We have introduced inherent openings into densely packed carbon nanotube arrays to study self-organized pattern formation when the arrays undergo a wetting-dewetting treatment from nanotube tips. These inherent openings, made of circular or elongated hollows in nanotube mats, serve as dewetting centres, from where liquid recedes from. As the dewetting centres initiate dry zones and the dry zones expand, surrounding nanotubes are pulled away from the dewetting centres by liquid surface tension. Among short nanotubes, the self-organized patterns are consistent with the shape of the inherent openings, i.e. slender openings lead to elongated trench-like structures, and circular holes result in relatively round nest-like arrangements. Nanotubes in a relatively high mat are more connected, like in an elastic body, than those in a short mat. Small cracks often initialize themselves in a relatively high mat, along two or more adjacent round openings; each of the cracks evolves into a trench as liquid dries up. Self-organized pattern control with inherent openings needs to initiate the dewetting process above the nanotube tips. If there is no liquid on top, inherent openings barely enlarge themselves after the wetting-dewetting treatment

  13. Numerical and Experimental Study on the Formation and Dispersion Patterns of Multiple Explosively Formed Penetrators

    Directory of Open Access Journals (Sweden)

    Jian Feng Liu

    Full Text Available Abstract Three-dimensional numerical simulations and experiments were performed to examine the formation and spatial dispersion patterns of integral multiple explosively formed penetrators (MEFP warhead with seven hemispherical liners. Numerical results had successfully described the formation process and distribution pattern of MEFP. A group of penetrators consisting of a central penetrator surrounded by 6 penetrators is formed during the formation process of MEFP and moves in the direction of aiming position. The maximum divergence angle of the surrounding penetrator group was 7.8°, and the damage area could reach 0.16 m2 at 1.2 m. The laws of perforation dispersion patterns of MEFP were also obtained through a nonlinear fitting of the perforation information on the target at different standoffs. The terminal effects of the MEFP warhead were performed on three #45 steel targets with a dimension of 160cm ( 160cm ( 1.5cm at various standoffs (60, 80, and 120 cm. The simulation results were validated through penetration experiments at different standoffs. It has shown excellent agreement between simulation and experiment results.

  14. Spatio-Temporal Patterns and Climate Variables Controlling of Biomass Carbon Stock of Global Grassland Ecosystems from 1982 to 2006

    Directory of Open Access Journals (Sweden)

    Jiangzhou Xia

    2014-02-01

    Full Text Available Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production. The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

  15. The World Spatiotemporal Analytics and Mapping Project (WSTAMP: Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World’s Largest Open Source Data Sets

    Directory of Open Access Journals (Sweden)

    J. Piburn

    2017-10-01

    Full Text Available Spatiotemporal (ST analytics applied to major data sources such as the World Bank and World Health Organization has shown tremendous value in shedding light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. WSTAMP engages this opportunity by situating analysts, data, and analytics together within a visually rich and computationally rigorous online analysis environment. Since introducing WSTAMP at the First International Workshop on Spatiotemporal Computing, several transformative advances have occurred. Collaboration with human computer interaction experts led to a complete interface redesign that deeply immerses the analyst within a ST context, significantly increases visual and textual content, provides navigational crosswalks for attribute discovery, substantially reduce mouse and keyboard actions, and supports user data uploads. Secondly, the database has been expanded to include over 16,000 attributes, 50 years of time, and 200+ nation states and redesigned to support non-annual, non-national, city, and interaction data. Finally, two new analytics are implemented for analyzing large portfolios of multi-attribute data and measuring the behavioral stability of regions along different dimensions. These advances required substantial new approaches in design, algorithmic innovations, and increased computational efficiency. We report on these advances and inform how others may freely access the tool.

  16. [Study on formation process of honeycomb pattern in dielectric barrier discharge by optical emission spectrum].

    Science.gov (United States)

    Dong, Li-Fang; Zhu, Ping; Yang, Jing; Zhang, Yu

    2014-04-01

    The authors report on the first investigation of the variations in the plasma parameters in the formation process of the honeycomb pattern in a dielectric barrier discharge by optical emission spectrum in argon and air mixture. The discharge undergoes hexagonal lattice, concentric spot-ring pattern and honeycomb pattern with the applied voltage increasing. The molecular vibration temperature, electron excitation temperature and electronic density of the three kinds of patterns were investigated by the emission spectra of nitrogen band of second positive system (C3pi(u) --> B3 pi(g)), the relative intensity ratio method of spectral lines of Ar I 763.51 nm (2P(6) --> 1S(5)) and Ar I 772.42 nm (2P(2) -->1S(3)) and the broadening of spectral line 696.5 nm respectively. It was found that the molecular vibration temperature and electron excitation temperature of the honeycomb pattern are higher than those of the hexagonal lattice, but the electron density of the former is lower than that of the latter. The discharge powers of the patterns were also measured with the capacitance method. The discharge power of the honeycomb pattern is much higher than that of the hexagonal lattice. These results are of great importance to the formation mechanism of the patterns in dielectric barrier discharge.

  17. Spatio-temporal powder formation and trapping in RF silane plasmas using 2-D polarization-sensitive laser scattering

    International Nuclear Information System (INIS)

    Dorier, J.L.; Hollenstein, C.; Howling, A.A.

    1994-09-01

    Powder formation studies in deposition plasmas are motivated by the need to reduce contamination in the plasma and films. Models for the force acting upon particles in rf discharges suffer from a lack of quantitative experimental data for comparison in the case of silane-containing plasmas. In this work, a cross-section of the parallel-plate capacitor discharge is illuminated with a polarized beam-expanded laser and global spatio-temporal scattered light and extinction are recorded by CCD cameras. Spatially-regular periodic bright/dark zones due to constructive/destructive Mie interference are visible over large regions of the powder layers, which shows the uniform nature of particle growth in silane plasmas. For particles trapped in an argon plasma, as for steady-state conditions in silane, spatial size segregation is demonstrated by fringes which reverse according to the polarisation of scattered light. The method allow a self-consistent estimation of particle size and number density throughout the discharge volume from which strong particle Coulomb coupling (Γ>40) is suggested to influence powder dynamics. Correction must be made to the plasma emission profile for the extinction by powder. In conclusion, this global diagnostics improves understanding of particle growth and dynamics in silane rf discharges and provides experimental input for testing the validity of models. (author) 6 figs., 43 refs

  18. The timing and spatiotemporal patterning of Neanderthal disappearance.

    Science.gov (United States)

    Higham, Tom; Douka, Katerina; Wood, Rachel; Ramsey, Christopher Bronk; Brock, Fiona; Basell, Laura; Camps, Marta; Arrizabalaga, Alvaro; Baena, Javier; Barroso-Ruíz, Cecillio; Bergman, Christopher; Boitard, Coralie; Boscato, Paolo; Caparrós, Miguel; Conard, Nicholas J; Draily, Christelle; Froment, Alain; Galván, Bertila; Gambassini, Paolo; Garcia-Moreno, Alejandro; Grimaldi, Stefano; Haesaerts, Paul; Holt, Brigitte; Iriarte-Chiapusso, Maria-Jose; Jelinek, Arthur; Jordá Pardo, Jesús F; Maíllo-Fernández, José-Manuel; Marom, Anat; Maroto, Julià; Menéndez, Mario; Metz, Laure; Morin, Eugène; Moroni, Adriana; Negrino, Fabio; Panagopoulou, Eleni; Peresani, Marco; Pirson, Stéphane; de la Rasilla, Marco; Riel-Salvatore, Julien; Ronchitelli, Annamaria; Santamaria, David; Semal, Patrick; Slimak, Ludovic; Soler, Joaquim; Soler, Narcís; Villaluenga, Aritza; Pinhasi, Ron; Jacobi, Roger

    2014-08-21

    The timing of Neanderthal disappearance and the extent to which they overlapped with the earliest incoming anatomically modern humans (AMHs) in Eurasia are key questions in palaeoanthropology. Determining the spatiotemporal relationship between the two populations is crucial if we are to understand the processes, timing and reasons leading to the disappearance of Neanderthals and the likelihood of cultural and genetic exchange. Serious technical challenges, however, have hindered reliable dating of the period, as the radiocarbon method reaches its limit at ∼50,000 years ago. Here we apply improved accelerator mass spectrometry (14)C techniques to construct robust chronologies from 40 key Mousterian and Neanderthal archaeological sites, ranging from Russia to Spain. Bayesian age modelling was used to generate probability distribution functions to determine the latest appearance date. We show that the Mousterian ended by 41,030-39,260 calibrated years bp (at 95.4% probability) across Europe. We also demonstrate that succeeding 'transitional' archaeological industries, one of which has been linked with Neanderthals (Châtelperronian), end at a similar time. Our data indicate that the disappearance of Neanderthals occurred at different times in different regions. Comparing the data with results obtained from the earliest dated AMH sites in Europe, associated with the Uluzzian technocomplex, allows us to quantify the temporal overlap between the two human groups. The results reveal a significant overlap of 2,600-5,400 years (at 95.4% probability). This has important implications for models seeking to explain the cultural, technological and biological elements involved in the replacement of Neanderthals by AMHs. A mosaic of populations in Europe during the Middle to Upper Palaeolithic transition suggests that there was ample time for the transmission of cultural and symbolic behaviours, as well as possible genetic exchanges, between the two groups.

  19. Spatio-temporal models of mental processes from fMRI.

    Science.gov (United States)

    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.

  20. Spatio-Temporal Data Construction

    Directory of Open Access Journals (Sweden)

    Hai Ha Le

    2013-08-01

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

  1. Dynamics of weed populations : spatial pattern formation and implications for control

    NARCIS (Netherlands)

    Wallinga, J.

    1998-01-01

    Modelling studies were carried out to analyse spatio-temporal dynamics of annual weed populations and to identify the key factors that determine the long-term herbicide use of weed control programmes. Three different weed control programmes were studied.

    In the first weed

  2. Pattern selection near the onset of convection in binary mixtures in cylindrical cells

    International Nuclear Information System (INIS)

    Alonso, Arantxa; Mercader, Isabel; Batiste, Oriol

    2014-01-01

    We report numerical investigations of three-dimensional pattern formation of binary mixtures in a vertical cylindrical container heated from below. Negative separation ratio mixtures, for which the onset of convection occurs via a subcritical Hopf bifurcation, are considered. We focus on the dynamics in the neighbourhood of the initial oscillatory instability and analyze the spatio-temporal properties of the patterns for different values of the aspect ratio of the cell, 0.25≲Γ≲11 (Γ≡R/d, where R is the radius of the cell and d its height). Despite the oscillatory nature of the primary instability, for highly constrained geometries, Γ≲2.5, only pure thermal stationary modes are selected after long transients. As the aspect ratio of the cell increases, for intermediate aspect ratio cells such as Γ=3, multistability and coexistence of stationary and time-dependent patterns is observed. In highly extended cylinders, Γ≈11, the dynamics near the onset is completely different from the pure fluid case, and a startling diversity of confined patterns is observed. Many of these patterns are consistent with experimental observations. Remarkably, though, we have obtained persistent large amplitude highly localized states not reported previously. (paper)

  3. Pattern selection near the onset of convection in binary mixtures in cylindrical cells

    Energy Technology Data Exchange (ETDEWEB)

    Alonso, Arantxa; Mercader, Isabel; Batiste, Oriol, E-mail: arantxa@fa.upc.edu [Departament de Física Aplicada, Universitat Politècnica de Catalunya, Mòdul B4, 08034 Barcelona (Spain)

    2014-08-01

    We report numerical investigations of three-dimensional pattern formation of binary mixtures in a vertical cylindrical container heated from below. Negative separation ratio mixtures, for which the onset of convection occurs via a subcritical Hopf bifurcation, are considered. We focus on the dynamics in the neighbourhood of the initial oscillatory instability and analyze the spatio-temporal properties of the patterns for different values of the aspect ratio of the cell, 0.25≲Γ≲11 (Γ≡R/d, where R is the radius of the cell and d its height). Despite the oscillatory nature of the primary instability, for highly constrained geometries, Γ≲2.5, only pure thermal stationary modes are selected after long transients. As the aspect ratio of the cell increases, for intermediate aspect ratio cells such as Γ=3, multistability and coexistence of stationary and time-dependent patterns is observed. In highly extended cylinders, Γ≈11, the dynamics near the onset is completely different from the pure fluid case, and a startling diversity of confined patterns is observed. Many of these patterns are consistent with experimental observations. Remarkably, though, we have obtained persistent large amplitude highly localized states not reported previously. (paper)

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

    Science.gov (United States)

    Serinaldi, F.; Kilsby, C. G.

    2012-04-01

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

  5. Spatiotemporal patterns of non-point source nitrogen loss in an agricultural catchment

    Directory of Open Access Journals (Sweden)

    Jian-feng Xu

    2016-04-01

    Full Text Available Non-point source nitrogen loss poses a risk to sustainable aquatic ecosystems. However, non-point sources, as well as impaired river segments with high nitrogen concentrations, are difficult to monitor and regulate because of their diffusive nature, budget constraints, and resource deficiencies. For the purpose of catchment management, the Bayesian maximum entropy approach and spatial regression models have been used to explore the spatiotemporal patterns of non-point source nitrogen loss. In this study, a total of 18 sampling sites were selected along the river network in the Hujiashan Catchment. Over the time period of 2008–2012, water samples were collected 116 times at each site and analyzed for non-point source nitrogen loss. The morphometric variables and soil drainage of different land cover types were studied and considered potential factors affecting nitrogen loss. The results revealed that, compared with the approach using the Euclidean distance, the Bayesian maximum entropy approach using the river distance led to an appreciable 10.1% reduction in the estimation error, and more than 53.3% and 44.7% of the river network in the dry and wet seasons, respectively, had a probability of non-point source nitrogen impairment. The proportion of the impaired river segments exhibited an overall decreasing trend in the study catchment from 2008 to 2012, and the reduction in the wet seasons was greater than that in the dry seasons. High nitrogen concentrations were primarily found in the downstream reaches and river segments close to the residential lands. Croplands and residential lands were the dominant factors affecting non-point source nitrogen loss, and explained up to 70.7% of total nitrogen in the dry seasons and 54.7% in the wet seasons. A thorough understanding of the location of impaired river segments and the dominant factors affecting total nitrogen concentration would have considerable importance for catchment management.

  6. Spatio-temporal distribution patterns of the epibenthic community in the coastal waters of Suriname

    Science.gov (United States)

    Willems, Tomas; De Backer, Annelies; Wan Tong You, Kenneth; Vincx, Magda; Hostens, Kris

    2015-10-01

    This study aimed to characterize the spatio-temporal patterns of the epibenthic community in the coastal waters of Suriname. Data were collected on a (bi)monthly basis in 2012-2013 at 15 locations in the shallow (turbid-water zone (6-20 m depth), dominated by Atlantic seabob shrimp Xiphopenaeus kroyeri (Crustacea: Penaeoidea). Near the 30 m isobath, sediments were much coarser (median grain size on average 345±103 μm vs. 128±53 μm in the coastal assemblage) and water transparency was much higher (on average 7.6±3.5 m vs. 2.4±2.1 m in the coastal assemblage). In this zone, a diverse offshore assemblage was found, characterized by brittle stars (mainly Ophioderma brevispina and Ophiolepis elegans) and a variety of crabs, sea stars and hermit crabs. In between both zones, a transition assemblage was noted, with epibenthic species typically found in either the coastal or offshore assemblages, but mainly characterized by the absence of X. kroyeri. Although the epibenthic community was primarily structured in an on-offshore gradient related to depth, sediment grain size and sediment total organic carbon content, a longitudinal (west-east) gradient was apparent as well. The zones in the eastern part of the Suriname coastal shelf seemed to be more widely stretched along the on-offshore gradient. Although clear seasonal differences were noted in the environmental characteristics (e.g. dry vs. rainy season), this was not reflected in the epibenthic community structure. X. kroyeri reached very high densities (up to 1383 ind 1000 m-²) in the shallow coastal waters of Suriname. As X. kroyeri is increasingly exploited throughout its range, the current study provides the ecological context for its presence and abundance, which is crucial for an ecosystem approach and the sustainable management of this commercially important species and its habitat.

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

    Science.gov (United States)

    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

  8. The Voronoi spatio-temporal data structure

    Science.gov (United States)

    Mioc, Darka

    2002-04-01

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

  9. Analysis of spatiotemporal soil moisture patterns at the catchment scale using a wireless sensor network

    Science.gov (United States)

    Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry

    2010-05-01

    Soil water content plays a key role in partitioning water and energy fluxes and controlling the pattern of groundwater recharge. Despite the importance of soil water content, it is not yet measured in an operational way at larger scales. The aim of this paper is to present the potential of real-time monitoring for the analysis of soil moisture patterns at the catchment scale using the recently developed wireless sensor network SoilNet [1], [2]. SoilNet is designed to measure soil moisture, salinity and temperature in several depths (e.g. 5, 20 and 50 cm). Recently, a small forest catchment Wüstebach (~27 ha) has been instrumented with 150 sensor nodes and more than 1200 soil sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories). From August to November 2009, more than 6 million soil moisture measurements have been performed. We will present first results from a statistical and geostatistical analysis of the data. The observed spatial variability of soil moisture corresponds well with the 800-m scale variability described in [3]. The very low scattering of the standard deviation versus mean soil moisture plots indicates that sensor network data shows less artificial soil moisture variations than soil moisture data originated from measurement campaigns. The variograms showed more or less the same nugget effect, which indicates that the sum of the sub-scale variability and the measurement error is rather time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil water content, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to lateral and vertical water fluxes

  10. Stimulation of Changes, Collective Commitment and The Patterns of Group Formation in Community Development in South Sulawesi

    Science.gov (United States)

    Saleh, Syafiuddin

    2018-05-01

    This study aims to examine the pattern of group formation, related to the stimulation of change through the empowerment of farmers and poor fishermen The pattern of group formation is the basis for sustainable development. The research method used is qualitative descriptive method and relevant research type such as case study and triangulasi. The results of the study showed that (1) stimulation of changes made through development programs or community empowerment in the areas studied both among farm households and poor fishermen households for some programs received positive response from farmers and fishermen. However, the collective commitment to the breeding is relatively weak, since the group formed in each program is not done through good planning and concepts. (2) there are two patterns of group formation that are natural and formed formations initiated by outsiders. Groups that are naturally formed are more institutionalized and have characteristics such as intense and relatively routine interaction, strong mutual trust, and have a common form or mechanism shared for common purposes. The group can form the basis for sustainable development in improving the welfare of the poor.

  11. A Spatiotemporal Indexing Approach for Efficient Processing of Big Array-Based Climate Data with MapReduce

    Science.gov (United States)

    Li, Zhenlong; Hu, Fei; Schnase, John L.; Duffy, Daniel Q.; Lee, Tsengdar; Bowen, Michael K.; Yang, Chaowei

    2016-01-01

    Climate observations and model simulations are producing vast amounts of array-based spatiotemporal data. Efficient processing of these data is essential for assessing global challenges such as climate change, natural disasters, and diseases. This is challenging not only because of the large data volume, but also because of the intrinsic high-dimensional nature of geoscience data. To tackle this challenge, we propose a spatiotemporal indexing approach to efficiently manage and process big climate data with MapReduce in a highly scalable environment. Using this approach, big climate data are directly stored in a Hadoop Distributed File System in its original, native file format. A spatiotemporal index is built to bridge the logical array-based data model and the physical data layout, which enables fast data retrieval when performing spatiotemporal queries. Based on the index, a data-partitioning algorithm is applied to enable MapReduce to achieve high data locality, as well as balancing the workload. The proposed indexing approach is evaluated using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. The experimental results show that the index can significantly accelerate querying and processing (10 speedup compared to the baseline test using the same computing cluster), while keeping the index-to-data ratio small (0.0328). The applicability of the indexing approach is demonstrated by a climate anomaly detection deployed on a NASA Hadoop cluster. This approach is also able to support efficient processing of general array-based spatiotemporal data in various geoscience domains without special configuration on a Hadoop cluster.

  12. Spatio-temporal regulation of ADAR editing during development in porcine neural tissues

    DEFF Research Database (Denmark)

    Venø, Morten Trillingsgaard; Bramsen, Jesper Bertram; Bendixen, Christian

    2012-01-01

    Editing by ADAR enzymes is essential for mammalian life. Still, knowledge of the spatio-temporal editing patterns in mammals is limited. By use of 454 amplicon sequencing we examined the editing status of 12 regionally extracted mRNAs from porcine developing brain encompassing a total of 64...... putative ADAR editing sites. In total 24 brain tissues, dissected from up to five regions from embryonic gestation day 23, 42, 60, 80, 100 and 115, were examined for editing....

  13. Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China

    Directory of Open Access Journals (Sweden)

    Yanxia Wang

    2014-05-01

    Full Text Available Ischemic heart disease (IHD is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis measured the incidence rate (hospital admissions per 1,000 residents and the standardized rate (the observed cases standardized by the expected cases of IHD at the district level to determine the spatio-temporal distribution and identify patterns of change. The space-time scan statistics was used to identify spatio-temporal clusters of IHD hospital admissions at the district level. The other objective of this study was to forecast the IHD hospital admissions over the next three years (2013–2015 to predict the IHD incidence rates and the varying burdens of IHD-related medical services among the districts in Shenzhen. The results show that the highest hospital admissions, incidence rates, and standardized rates of IHD are in Futian. From 2003 to 2012, the IHD hospital admissions exhibited similar mean centers and directional distributions, with a slight increase in admissions toward the north in accordance with the movement of the total population. The incidence rates of IHD exhibited a gradual increase from 2003 to 2012 for all districts in Shenzhen, which may be the result of the rapid development of the economy and the increasing traffic pollution. In addition, some neighboring areas exhibited similar temporal change patterns, which were also detected by the spatio-temporal cluster analysis. Futian and Dapeng would have the highest and the lowest hospital admissions, respectively, although these districts have the highest incidence rates among all of the districts from 2013 to 2015 based on the prediction

  14. Rayleigh-Taylor instability and mushroom-pattern formation in a two-component Bose-Einstein condensate

    International Nuclear Information System (INIS)

    Sasaki, Kazuki; Suzuki, Naoya; Saito, Hiroki; Akamatsu, Daisuke

    2009-01-01

    The Rayleigh-Taylor instability at the interface in an immiscible two-component Bose-Einstein condensate is investigated using the mean field and Bogoliubov theories. Rayleigh-Taylor fingers are found to grow from the interface and mushroom patterns are formed. Quantized vortex rings and vortex lines are then generated around the mushrooms. The Rayleigh-Taylor instability and mushroom-pattern formation can be observed in a trapped system.

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

    Directory of Open Access Journals (Sweden)

    Lauren L Long

    2015-03-01

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

  16. Coarsening and pattern formation during true morphological phase separation in unstable thin films under gravity

    Science.gov (United States)

    Kumar, Avanish; Narayanam, Chaitanya; Khanna, Rajesh; Puri, Sanjay

    2017-12-01

    We address in detail the problem of true morphological phase separation (MPS) in three-dimensional or (2 +1 )-dimensional unstable thin liquid films (>100 nm) under the influence of gravity. The free-energy functionals of these films are asymmetric and show two points of common tangency, which facilitates the formation of two equilibrium phases. Three distinct patterns formed by relative preponderance of these phases are clearly identified in "true MPS". Asymmetricity induces two different pathways of pattern formation, viz., defect and direct pathway for true MPS. The pattern formation and phase-ordering dynamics have been studied using statistical measures such as structure factor, correlation function, and growth laws. In the late stage of coarsening, the system reaches into a scaling regime for both pathways, and the characteristic domain size follows the Lifshitz-Slyozov growth law [L (t ) ˜t1 /3] . However, for the defect pathway, there is a crossover of domain growth behavior from L (t ) ˜t1 /4→t1 /3 in the dynamical scaling regime. We also underline the analogies and differences behind the mechanisms of MPS and true MPS in thin liquid films and generic spinodal phase separation in binary mixtures.

  17. Heterogeneity induces spatiotemporal oscillations in reaction-diffusion systems

    Science.gov (United States)

    Krause, Andrew L.; Klika, Václav; Woolley, Thomas E.; Gaffney, Eamonn A.

    2018-05-01

    We report on an instability arising in activator-inhibitor reaction-diffusion (RD) systems with a simple spatial heterogeneity. This instability gives rise to periodic creation, translation, and destruction of spike solutions that are commonly formed due to Turing instabilities. While this behavior is oscillatory in nature, it occurs purely within the Turing space such that no region of the domain would give rise to a Hopf bifurcation for the homogeneous equilibrium. We use the shadow limit of the Gierer-Meinhardt system to show that the speed of spike movement can be predicted from well-known asymptotic theory, but that this theory is unable to explain the emergence of these spatiotemporal oscillations. Instead, we numerically explore this system and show that the oscillatory behavior is caused by the destabilization of a steady spike pattern due to the creation of a new spike arising from endogeneous activator production. We demonstrate that on the edge of this instability, the period of the oscillations goes to infinity, although it does not fit the profile of any well-known bifurcation of a limit cycle. We show that nearby stationary states are either Turing unstable or undergo saddle-node bifurcations near the onset of the oscillatory instability, suggesting that the periodic motion does not emerge from a local equilibrium. We demonstrate the robustness of this spatiotemporal oscillation by exploring small localized heterogeneity and showing that this behavior also occurs in the Schnakenberg RD model. Our results suggest that this phenomenon is ubiquitous in spatially heterogeneous RD systems, but that current tools, such as stability of spike solutions and shadow-limit asymptotics, do not elucidate understanding. This opens several avenues for further mathematical analysis and highlights difficulties in explaining how robust patterning emerges from Turing's mechanism in the presence of even small spatial heterogeneity.

  18. Spatio-temporal networks: reachability, centrality and robustness.

    Science.gov (United States)

    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.

  19. Pattern formation of frictional fingers in a gravitational potential

    Science.gov (United States)

    Eriksen, Jon Alm; Toussaint, Renaud; Mâløy, Knut Jørgen; Flekkøy, Eirik; Galland, Olivier; Sandnes, Bjørnar

    2018-01-01

    Aligned finger structures, with a characteristic width, emerge during the slow drainage of a liquid-granular mixture in a tilted Hele-Shaw cell. A transition from vertical to horizontal alignment of the finger structures is observed as the tilting angle and the granular density are varied. An analytical model is presented, demonstrating that the alignment properties are the result of the competition between fluctuating granular stresses and the hydrostatic pressure. The dynamics is reproduced in simulations. We also show how the system explains patterns observed in nature, created during the early stages of a dike formation.

  20. Initial spatio-temporal domain expansion of the Modelfest database

    Science.gov (United States)

    Carney, Thom; Mozaffari, Sahar; Sun, Sean; Johnson, Ryan; Shirvastava, Sharona; Shen, Priscilla; Ly, Emma

    2013-03-01

    The first Modelfest group publication appeared in the SPIE Human Vision and Electronic Imaging conference proceedings in 1999. "One of the group's goals is to develop a public database of test images with threshold data from multiple laboratories for designing and testing HVS (Human Vision Models)." After extended discussions the group selected a set of 45 static images thought to best meet that goal and collected psychophysical detection data which is available on the WEB and presented in the 2000 SPIE conference proceedings. Several groups have used these datasets to test spatial modeling ideas. Further discussions led to the preliminary stimulus specification for extending the database into the temporal domain which was published in the 2002 conference proceeding. After a hiatus of 12 years, some of us have collected spatio-temporal thresholds on an expanded stimulus set of 41 video clips; the original specification included 35 clips. The principal change involved adding one additional spatial pattern beyond the three originally specified. The stimuli consisted of 4 spatial patterns, Gaussian Blob, 4 c/d Gabor patch, 11.3 c/d Gabor patch and a 2D white noise patch. Across conditions the patterns were temporally modulated over a range of approximately 0-25 Hz as well as temporal edge and pulse modulation conditions. The display and data collection specifications were as specified by the Modelfest groups in the 2002 conference proceedings. To date seven subjects have participated in this phase of the data collection effort, one of which also participated in the first phase of Modelfest. Three of the spatio-temporal stimuli were identical to conditions in the original static dataset. Small differences in the thresholds were evident and may point to a stimulus limitation. The temporal CSF peaked between 4 and 8 Hz for the 0 c/d (Gaussian blob) and 4 c/d patterns. The 4 c/d and 11.3 c/d Gabor temporal CSF was low pass while the 0 c/d pattern was band pass. This

  1. Analyzing Spatiotemporal Anomalies through Interactive Visualization

    Directory of Open Access Journals (Sweden)

    Tao Zhang

    2014-06-01

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

  2. Generating spatiotemporal joint torque patterns from dynamical synchronization of distributed pattern generators

    Directory of Open Access Journals (Sweden)

    Alex Pitti

    2009-10-01

    Full Text Available Pattern generators found in the spinal cords are no more seen as simple rhythmic oscillators for motion control. Indeed, they achieve flexible and dynamical coordination in interaction with the body and the environment dynamics to rise motor synergies. Discovering the mechanisms underlying the control of motor synergies constitute an important research question not only for neuroscience but also for robotics: the motors coordination of high dimensional robotic systems is still a drawback and new control methods based on biological solutions may reduce their overall complexity. We propose to model the flexible combination of motor synergies in embodied systems via partial phase synchronization of distributed chaotic systems; for specific coupling strength, chaotic systems are able to phase synchronize their dynamics to the resonant frequencies of one external force. We take advantage of this property to explore and exploit the intrinsic dynamics of one specified embodied system. In two experiments with bipedal walkers, we show how motor synergies emerge when the controllers phase synchronize to the body’s dynamics, entraining it to its intrinsic behavioral patterns. This stage is characterized by directed information flow from the sensors to the motors exhibiting the optimal situation when the body dynamics drive the controllers (mutual entrainment. Based on our results, we discuss the relevance of our findings for modeling the modular control of distributed pattern generators exhibited in the spinal cords, and for exploring the motor synergies in robots.

  3. Unsupervised Learning of Spatiotemporal Features by Video Completion

    OpenAIRE

    Nallabolu, Adithya Reddy

    2017-01-01

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

  4. Influence of oxygen gas on characteristics of self-organized luminous pattern formation observed in an atmospheric dc glow discharge using a liquid electrode

    International Nuclear Information System (INIS)

    Shirai, Naoki; Uchida, Satoshi; Tochikubo, Fumiyoshi

    2014-01-01

    Self-organized luminous pattern formation is observed in the liquid surface of an atmospheric dc glow discharge using a liquid electrode with a miniature helium flow. The factors affecting pattern formation are the gap length, discharge current, helium mass flow rate and polarity. The pattern shape depends on the conductivity and temperature of the liquid electrode. A variety of patterns were observed by changing the conductivity and temperature of the liquid. We clarified that the self-organized pattern formation depends on the amount of electronegative gas, such as oxygen, in the gas in the electrode gap. When an oxygen gas flow was fed to the liquid surface from the outside in an obliquely downward direction, namely, the amount of oxygen gas on the liquid surface was increased locally, self-organized pattern formation was observed in the region with the increased amount of oxygen gas. When the amount of oxygen in the gas in the gap was changed by using a sheath flow system, the appearance of the pattern changed. The presence of oxygen gas strongly affected the self-organized pattern formation of the atmospheric dc discharge using a liquid anode. (paper)

  5. Influence of phase transition on pattern formation during catalytic reactions

    OpenAIRE

    Andrade, Roberto Fernandes Silva; Lima, D.; Cunha, F. B.

    2000-01-01

    p.434–445 We investigate the influence of the order of surface phase transitions on pattern formation during chemical reaction on mono-crystal catalysts. We use a model consisting of two partial differential equations, one of which describes the dynamics of the surface state with the help of a Ginzburg–Landau potential. Second- or first-order transitions are described by decreasing or increasing the relative value of the third-order coefficient of the potential. We concentrate on the stabi...

  6. Comparison of Spatiotemporal Fusion Models: A Review

    Directory of Open Access Journals (Sweden)

    Bin Chen

    2015-02-01

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

  7. Clastic patterned ground in Lomonosov crater, Mars: examining fracture controlled formation mechanisms

    Science.gov (United States)

    Barrett, Alexander M.; Balme, Matthew R.; Patel, Manish R.; Hagermann, Axel

    2017-10-01

    The area surrounding Lomonosov crater on Mars has a high density of seemingly organised boulder patterns. These form seemingly sorted polygons and stripes within kilometre scale blockfields, patches of boulder strewn ground which are common across the Martian high latitudes. Several hypotheses have been suggested to explain the formation of clastic patterned ground on Mars. It has been proposed that these structures could have formed through freeze-thaw sorting, or conversely by the interaction of boulders with underlying fracture polygons. In this investigation a series of sites were examined to evaluate whether boulder patterns appear to be controlled by the distribution of underlying fractures and test the fracture control hypotheses for their formation. It was decided to focus on this suite of mechanisms as they are characterised by a clear morphological relationship, namely the presence of an underlying fracture network which can easily be evaluated over a large area. It was found that in the majority of examples at these sites did not exhibit fracture control. Although fractures were present at many sites there were very few sites where the fracture network appeared to be controlling the boulder distribution. In general these were not the sites with the best examples of organization, suggesting that the fracture control mechanisms are not the dominant geomorphic process organising the boulders in this area.

  8. Assessing global vegetation activity using spatio-temporal Bayesian modelling

    Science.gov (United States)

    Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

    2016-04-01

    This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support

  9. Simultaneous spatio-temporal focusing for tissue manipulation

    Directory of Open Access Journals (Sweden)

    Squier J.

    2013-11-01

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

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

    Science.gov (United States)

    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 (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 metres apart and within hours. These patterns presumably have ecological relevance. These results indicate that, in energetically active and

  11. Spatiotemporal pattern of bacillary dysentery in China from 1990 to 2009: what is the driver behind?

    Directory of Open Access Journals (Sweden)

    Zhiwei Xu

    Full Text Available Little is known about the spatiotemporal pattern of bacillary dysentery (BD in China. This study assessed the geographic distribution and seasonality of BD in China over the past two decades.Data on monthly BD cases in 31 provinces of China from January 1990 to December 2009 obtained from Chinese Center for Disease Control and Prevention, and data on demographic and geographic factors, as well as climatic factors, were compiled. The spatial distributions of BD in the four periods across different provinces were mapped, and heat maps were created to present the seasonality of BD by geography. A cosinor function combined with Poisson regression was used to quantify the seasonal parameters of BD, and a regression analysis was conducted to identify the potential drivers of morbidity and seasonality of BD.Although most regions of China have experienced considerable declines in BD morbidity over the past two decades, Beijing and Ningxia still had high BD morbidity in 2009. BD morbidity decreased more slowly in North-west China than other regions. BD in China mainly peaked from July to September, with heterogeneity in peak time between regions. Relative humidity was associated with BD morbidity and peak time, and latitude was the major predictor of BD amplitude.The transmission of BD was heterogeneous in China. Improved sanitation and hygiene in North-west China, and better access to clean water and food in the big floating population in some metropolises could be the focus of future preventive interventions against BD. BD control efforts should put more emphasis on those dry areas in summer.

  12. Spatio-temporal Change Patterns of Tropical Forests from 2000 to 2014 Using MOD09A1 Dataset

    Science.gov (United States)

    Qin, Y.; Xiao, X.; Dong, J.

    2016-12-01

    Large-scale deforestation and forest degradation in the tropical region have resulted in extensive carbon emissions and biodiversity loss. However, restricted by the availability of good-quality observations, large uncertainty exists in mapping the spatial distribution of forests and their spatio-temporal changes. In this study, we proposed a pixel- and phenology-based algorithm to identify and map annual tropical forests from 2000 to 2014, using the 8-day, 500-m MOD09A1 (v005) product, under the support of Google cloud computing (Google Earth Engine). A temporal filter was applied to reduce the random noises and to identify the spatio-temporal changes of forests. We then built up a confusion matrix and assessed the accuracy of the annual forest maps based on the ground reference interpreted from high spatial resolution images in Google Earth. The resultant forest maps showed the consistent forest/non-forest, forest loss, and forest gain in the pan-tropical zone during 2000 - 2014. The proposed algorithm showed the potential for tropical forest mapping and the resultant forest maps are important for the estimation of carbon emission and biodiversity loss.

  13. Impact of mitochondrial Ca2+ cycling on pattern formation and stability.

    Science.gov (United States)

    Falcke, M; Hudson, J L; Camacho, P; Lechleiter, J D

    1999-07-01

    Energization of mitochondria significantly alters the pattern of Ca2+ wave activity mediated by activation of the inositol (1,4,5) trisphosphate (IP3) receptor (IP3R) in Xenopus oocytes. The number of pulsatile foci is reduced and spiral Ca2+ waves are no longer observed. Rather, target patterns of Ca2+ release predominate, and when fragmented, fail to form spirals. Ca2+ wave velocity, amplitude, decay time, and periodicity are also increased. We have simulated these experimental findings by supplementing an existing mathematical model with a differential equation for mitochondrial Ca2+ uptake and release. Our calculations show that mitochondrial Ca2+ efflux plays a critical role in pattern formation by prolonging the recovery time of IP3Rs from a refractory state. We also show that under conditions of high energization of mitochondria, the Ca2+ dynamics can become bistable with a second stable stationary state of high resting Ca2+ concentration.

  14. Multifunctional surfaces with biomimetic nanofibres and drug-eluting micro-patterns for infection control and bone tissue formation

    Directory of Open Access Journals (Sweden)

    XN Chen

    2012-09-01

    Full Text Available For long-term orthopaedic implants, the creation of a surface that is repulsive to bacteria while adhesive to tissue cells represents a promising strategy to control infection. To obtain such multifunctional surfaces, two possible approaches were explored to incorporate a model antibiotic, rifampicin (Rf, into the osteogenic polycaprolactone (PCL/chitosan (CHS biomimetic nanofibre meshes by (1 blending Rf into the electrospinning solutions and then electrospinning into nanofibres (i.e., Rf-incorporating fibres, or (2 depositing Rf-containing poly(D,L-lactic-co-glycolic acid (PLGA micro-patterns onto the PCL/chitosan nanofibre meshes via ink-jet printing (i.e., Rf-eluting micro-pattern/fibre. Rapid release of Rf from both meshes was measured even though a relatively slower release rate was obtained from the Rf-eluting micro-pattern ones. Antibacterial assay with Staphylococcus epidermidis showed that both mesh surfaces could effectively kill bacteria and prevent biofilm formation. However, only Rf-eluting micro-pattern meshes favoured the attachment, spreading and metabolic activity of preosteoblasts in the cell culture study. Furthermore, the Rf-eluting micro-pattern meshes could better support the osteogenic differentiation of preosteoblasts by up-regulating the gene expression of bone markers (type I collagen and alkaline phosphatase. Clearly, compared to Rf-incorporating nanofibre meshes, Rf-eluting micro-patterns could effectively prevent biofilm formation without sacrificing the osteogenic properties of PCL/chitosan nanofibre surfaces. This finding provides an innovative avenue to design multifunctional surfaces for enhancing bone tissue formation while controlling infection.

  15. Phase separation like dynamics during Myxococcus xanthus fruiting body formation

    Science.gov (United States)

    Liu, Guannan; Thutupalli, Shashi; Wigbers, Manon; Shaevitz, Joshua

    2015-03-01

    Collective motion exists in many living organisms as an advantageous strategy to help the entire group with predation, forage, and survival. However, the principles of self-organization underlying such collective motions remain unclear. During various developmental stages of the soil-dwelling bacterium, Myxococcus xanthus, different types of collective motions are observed. In particular, when starved, M. xanthus cells eventually aggregate together to form 3-dimensional structures (fruiting bodies), inside which cells sporulate in response to the stress. We study the fruiting body formation process as an out of equilibrium phase separation process. As local cell density increases, the dynamics of the aggregation M. xanthus cells switch from a spatio-temporally random process, resembling nucleation and growth, to an emergent pattern formation process similar to a spinodal decomposition. By employing high-resolution microscopy and a video analysis system, we are able to track the motion of single cells within motile collective groups, while separately tuning local cell density, cell velocity and reversal frequency, probing the multi-dimensional phase space of M. xanthus development.

  16. Spatiotemporal Patterns of the Use of Urban Green Spaces and External Factors Contributing to Their Use in Central Beijing

    Directory of Open Access Journals (Sweden)

    Fangzheng Li

    2017-02-01

    Full Text Available Urban green spaces encourage outdoor activity and social communication that contribute to the health of local residents. Examining the relationship between the use of urban green spaces and factors influencing their utilization can provide essential references for green space site selection in urban planning. In contrast to previous studies that focused on internal factors, this study highlights the external factors (traffic convenience, population density and commercial facilities contributing to the use of urban green spaces. We conducted a spatiotemporal analysis of the distribution of visitors in 208 selected green spaces in central Beijing. We examined the relationship between the spatial pattern of visitor distribution within urban green spaces and external factors, using the Gini coefficient, kernel density estimation, and geographical detectors. The results of the study were as follows. The spatial distribution of visitors within central Beijing’s green spaces was concentrated, forming different agglomerations. The three examined external factors are all associated with the use of green spaces. Among them, commercial facilities are the important external factor associated with the use of green spaces. For the selection of sites for urban green spaces, we recommend consideration of external factors in order to balance urban green space utilization.

  17. Spatio-temporal patterns in the north-western Mediterranean from MERIS derived chlorophyll a concentration

    Directory of Open Access Journals (Sweden)

    Ana Gordoa

    2008-12-01

    Full Text Available We address the major surface signatures of chlorophyll a in the Catalan Sea within the context of the dynamics of the north-western Mediterranean basin. Monthly composites from MERIS measurements and CHL products for Case 1 waters were analysed from June 2002 to June 2005. Composite images of variability were used to identify surface dynamics. The results showed that coastal and open sea waters were separated by a belt of low variability, a permanent oligotrophic belt that is noticeable with respect to the bloom conditions of the surrounding areas. The width of this Catalan Oligotrophic Belt (COB located along the continental slope, varied between 17 and 30 km and became blurred in the southernmost area. The chlorophyll a temporal pattern over the shelf showed an almost steady increase from September to March. A similar behaviour but with lower concentrations was observed in oceanic waters. Both temporal patterns showed a disruption during January and/or February that coincided with the well known deep water formation event in the Gulf of Lions. In 2004, the convection was weaker and the offshore temporal trend was not disrupted; however, the opposite was observed in 2005. The spatial chlorophyll a distribution of oceanic waters presented a clear north-south decreasing trend, while the coastal distribution did not show any latitudinal patterns but rather peaks in the areas enriched by river runoff. The observed seasonality was similar to the one published from SeaWiFS data and slightly different from the seasonality shown by CZCS data. Nevertheless, we did not discard the possibility that some of the observed seasonal differences could be a true temporal shift in chlorophyll a production.

  18. The role of irradiated tissue during pattern formation in the regenerating limb

    International Nuclear Information System (INIS)

    Maden, M.

    1979-01-01

    The amphibian limb regeneration blastema is used here to examine whether irradiated, non-dividing tissue can participate in the development of new patterns of morphogenesis. Irradiated blastemas were rotated 180 0 on normal stumps and normal blastemas rotated on irradiated stumps. In both cases supernumerary elements developed from the unirradiated tissue. The supernumeraries were defective but this did not seem to be due to a lack of tissue. Rather it suggested that this could be a realization of compartments in vertebrate development or simply reflect the limited regulative ability of the blastema. The results are also discussed in relation to a recent model of pattern formation. (author)

  19. Visualization and assessment of spatio-temporal covariance properties

    KAUST Repository

    Huang, Huang

    2017-11-23

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

  20. Dynamic decomposition of spatiotemporal neural signals.

    Directory of Open Access Journals (Sweden)

    Luca Ambrogioni

    2017-05-01

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

  1. Spatiotemporal Distribution of Gastrointestinal Tract Cancer through GIS over 2007-2012 in Kermanshah-Iran.

    Science.gov (United States)

    Reshadat, Sohyla; Saeidi, Shahram; Zangeneh, Ali Reza; Khademi, Nahid; Khasi, Keyvan; Ghasemi, SayedRamin; Gilan, Nader Rajabi

    2015-01-01

    Cancer is one of the common causes of disability and mortality in the world. The present study aimed to define the spatiotemporal distribution of gastrointestinal tract cancers using a geographic information system (GIS) over the time period of 2007-2012 in Kermanshah-Iran. The method of studying was descriptive-analytical as well as comparative with gastrointestinal tract cancer patients based in the City of Kermanshah over the time period covered. For data analysis, the GIS and SPSS 16.0 were applied. According to the pathological reports within the space of 5 years, 283 cases of gastrointestinal tract cancer (157 in males, 156 in females) were reported. The performed tests in terms of spatial distribution in the environment of GIS indicated that the disease demonstrated a clustered pattern in the City of Kermanshah. More to the point, some loci of this disease have emerged in the City of Kermanshah that in the first level, 6 neighborhoods with 29-59 cases of this disease per square kilometer and in the second level, 15-29 cases. Gastrointestinal tract cancer demonstrated an ascending trend within the space of 5 years of research and the spatiotemporal distribution of cancer featured a concentrated and clustered pattern in the City of Kermanshah.

  2. Parallel optical control of spatiotemporal neuronal spike activity using high-frequency digital light processingtechnology

    Directory of Open Access Journals (Sweden)

    Jason eJerome

    2011-08-01

    Full Text Available Neurons in the mammalian neocortex receive inputs from and communicate back to thousands of other neurons, creating complex spatiotemporal activity patterns. The experimental investigation of these parallel dynamic interactions has been limited due to the technical challenges of monitoring or manipulating neuronal activity at that level of complexity. Here we describe a new massively parallel photostimulation system that can be used to control action potential firing in in vitro brain slices with high spatial and temporal resolution while performing extracellular or intracellular electrophysiological measurements. The system uses Digital-Light-Processing (DLP technology to generate 2-dimensional (2D stimulus patterns with >780,000 independently controlled photostimulation sites that operate at high spatial (5.4 µm and temporal (>13kHz resolution. Light is projected through the quartz-glass bottom of the perfusion chamber providing access to a large area (2.76 x 2.07 mm2 of the slice preparation. This system has the unique capability to induce temporally precise action potential firing in large groups of neurons distributed over a wide area covering several cortical columns. Parallel photostimulation opens up new opportunities for the in vitro experimental investigation of spatiotemporal neuronal interactions at a broad range of anatomical scales.

  3. Incorporating NDVI in a gravity model setting to describe spatio-temporal patterns of Lyme borreliosis incidence

    Science.gov (United States)

    Barrios, J. M.; Verstraeten, W. W.; Farifteh, J.; Maes, P.; Aerts, J. M.; Coppin, P.

    2012-04-01

    Lyme borreliosis (LB) is the most common tick-borne disease in Europe and incidence growth has been reported in several European countries during the last decade. LB is caused by the bacterium Borrelia burgdorferi and the main vector of this pathogen in Europe is the tick Ixodes ricinus. LB incidence and spatial spread is greatly dependent on environmental conditions impacting habitat, demography and trophic interactions of ticks and the wide range of organisms ticks parasite. The landscape configuration is also a major determinant of tick habitat conditions and -very important- of the fashion and intensity of human interaction with vegetated areas, i.e. human exposure to the pathogen. Hence, spatial notions as distance and adjacency between urban and vegetated environments are related to human exposure to tick bites and, thus, to risk. This work tested the adequacy of a gravity model setting to model the observed spatio-temporal pattern of LB as a function of location and size of urban and vegetated areas and the seasonal and annual change in the vegetation dynamics as expressed by MODIS NDVI. Opting for this approach implies an analogy with Newton's law of universal gravitation in which the attraction forces between two bodies are directly proportional to the bodies mass and inversely proportional to distance. Similar implementations have proven useful in fields like trade modeling, health care service planning, disease mapping among other. In our implementation, the size of human settlements and vegetated systems and the distance separating these landscape elements are considered the 'bodies'; and the 'attraction' between them is an indicator of exposure to pathogen. A novel element of this implementation is the incorporation of NDVI to account for the seasonal and annual variation in risk. The importance of incorporating this indicator of vegetation activity resides in the fact that alterations of LB incidence pattern observed the last decade have been ascribed

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

    Science.gov (United States)

    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.

  5. Dying like rabbits: general determinants of spatio-temporal variability in survival.

    Science.gov (United States)

    Tablado, Zulima; Revilla, Eloy; Palomares, Francisco

    2012-01-01

    1. Identifying general patterns of how and why survival rates vary across space and time is necessary to truly understand population dynamics of a species. However, this is not an easy task given the complexity and interactions of processes involved, and the interpopulation differences in main survival determinants. 2. Here, using European rabbits (Oryctolagus cuniculus) as a model and information from local studies, we investigated whether we could make inferences about trends and drivers of survival of a species that are generalizable to large spatio-temporal scales. To do this, we first focused on overall survival and then examined cause-specific mortalities, mainly predation and diseases, which may lead to those patterns. 3. Our results show that within the large-scale variability in rabbit survival, there exist general patterns that are explained by the integration of factors previously known to be important at the local level (i.e. age, climate, diseases, predation or density dependence). We found that both inter- and intrastudy survival rates increased in magnitude and decreased in variability as rabbits grow old, although this tendency was less pronounced in populations with epidemic diseases. Some causes leading to these higher mortalities in young rabbits could be the stronger effect of rainfall at those ages, as well as, other death sources like malnutrition or infanticide. 4. Predation is also greater for newborns and juveniles, especially in population without diseases. Apart from the effect of diseases, predation patterns also depended on factors, such as, density, season, and type and density of predators. Finally, we observed that infectious diseases also showed general relationships with climate, breeding (i.e. new susceptible rabbits) and age, although the association type varied between myxomatosis and rabbit haemorrhagic disease. 5. In conclusion, large-scale patterns of spatio-temporal variability in rabbit survival emerge from the combination

  6. Individual Rules for Trail Pattern Formation in Argentine Ants (Linepithema humile)

    OpenAIRE

    Perna, Andrea; Granovskiy, Boris; Garnier, Simon; Nicolis, Stamatios C.; Labédan, Marjorie; Theraulaz, Guy; Fourcassié, Vincent; Sumpter, David J. T.

    2012-01-01

    We studied the formation of trail patterns by Argentine ants exploring an empty arena. Using a novel imaging and analysis technique we estimated pheromone concentrations at all spatial positions in the experimental arena and at different times. Then we derived the response function of individual ants to pheromone concentrations by looking at correlations between concentrations and changes in speed or direction of the ants. Ants were found to turn in response to local pheromone concentrations,...

  7. Spatio-temporal patterns of tree establishment are indicative of biotic interactions during early invasion of a montane meadow

    Science.gov (United States)

    J.M. Rice; C.B. Halpern; J.A. Antos; J.A. Jones

    2012-01-01

    Tree invasions of grasslands are occurring globally, with profound consequences for ecosystem structure and function. We explore the spatio-temporal dynamics of tree invasion of a montane meadow in the Cascade Mountains of Oregon, where meadow loss is a conservation concern. We examine the early stages of invasion, where extrinsic and intrinsic processes can be clearly...

  8. Density of founder cells affects spatial pattern formation and cooperation in Bacillus subtilis biofilms.

    Science.gov (United States)

    van Gestel, Jordi; Weissing, Franz J; Kuipers, Oscar P; Kovács, Akos T

    2014-10-01

    In nature, most bacteria live in surface-attached sedentary communities known as biofilms. Biofilms are often studied with respect to bacterial interactions. Many cells inhabiting biofilms are assumed to express 'cooperative traits', like the secretion of extracellular polysaccharides (EPS). These traits can enhance biofilm-related properties, such as stress resilience or colony expansion, while being costly to the cells that express them. In well-mixed populations cooperation is difficult to achieve, because non-cooperative individuals can reap the benefits of cooperation without having to pay the costs. The physical process of biofilm growth can, however, result in the spatial segregation of cooperative from non-cooperative individuals. This segregation can prevent non-cooperative cells from exploiting cooperative neighbors. Here we examine the interaction between spatial pattern formation and cooperation in Bacillus subtilis biofilms. We show, experimentally and by mathematical modeling, that the density of cells at the onset of biofilm growth affects pattern formation during biofilm growth. At low initial cell densities, co-cultured strains strongly segregate in space, whereas spatial segregation does not occur at high initial cell densities. As a consequence, EPS-producing cells have a competitive advantage over non-cooperative mutants when biofilms are initiated at a low density of founder cells, whereas EPS-deficient cells have an advantage at high cell densities. These results underline the importance of spatial pattern formation for competition among bacterial strains and the evolution of microbial cooperation.

  9. Spatiotemporal patterns of precipitation extremes in the Poyang Lake basin, China: Changing properties and causes

    Science.gov (United States)

    Xiao, M.

    2016-12-01

    Under the background of climate change, extensive attentions have been paid on the increased extreme precipitation from the public and government. To analyze the influences of large-scale climate indices on the precipitation extremes, the spatiotemporal patterns of precipitation extremes in the Poyang Lake basin have been investigated using the Bayesian hierarchical method. The seasonal maximum one-day precipitation amount (Rx1day) was used to represent the seasonal precipitation extremes. Results indicated that spring Rx1day was affected by El Niño/Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO), a positive ENSO event in the same year tends to decrease the spring Rx1day in the northern part of Poyang Lake Basin while increase the spring Rx1day in southeastern Poyang Lake Basin, a positive NAO events in the same year tends to increase the spring Rx1day in the southwest and northwest part of Poyang Lake basin while decrease the spring Rx1day in the eastern part of Poyang Lake basin; summer Rx1day was affected by Indian Ocean Dipole (IOD), positive IOD events in the same year tend to increase the summer Rx1day of northern Poyang Lake basin while decrease summer Rx1day of southern Poyang Lake basin; autumn Rx1day was affected by ENSO, positive ENSO events in the same year tend to mainly increase the autumn Rx1day in the west part of Poyang Lake basin; winter Rx1day was mainly affected by the NAO, positive NAO events in the same year tend to mainly increase the winter Rx1day of southern Poyang Lake basin, while positive NAO events in the previous year tend to mainly increase the winter Rx1day in the central and northeast part of Poyang Lake basin. It is considered that the region with the negative vertical velocity is dominated by more precipitation and vice versa. Furthermore, field patterns of 500 hPa vertical velocity anomalies related to each climate index have further corroborated the influences of climate indices on the seasonal Rx1day, and

  10. Motor patterns during walking on a slippery walkway

    NARCIS (Netherlands)

    Cappellini, Germana; Ivanenko, Yuri P; Dominici, Nadia; Poppele, Richard E; Lacquaniti, Francesco

    Friction and gravity represent two basic physical constraints of terrestrial locomotion that affect both motor patterns and the biomechanics of bipedal gait. To provide insights into the spatiotemporal organization of the motor output in connection with ground contact forces, we studied adaptation

  11. Delayed frost formation on hybrid nanostructured surfaces with patterned high wetting contrast

    Science.gov (United States)

    Hou, Youmin; Zhou, Peng; Yao, Shuhuai

    2014-11-01

    Engineering icephobic surfaces that can retard the frost formation and accumulation are important to vehicles, wind turbines, power lines, and HVAC systems. For condensation frosting, superhydrophobic surfaces promote self-removal of condensed droplets before freezing and consequently delay the frost growth. However, a small thermal fluctuation may lead to a Cassie-to-Wenzel transition, and thus dramatically enhance the frost formation and adhesion. In this work, we investigated the heterogeneous ice nucleation on hybrid nanostructured surfaces with patterned high wetting contrast. By judiciously introducing hydrophilic micro-patches into superhydrophobic nanostructured surface, we demonstrated that such a novel hybrid structure can efficiently defer the ice nucleation as compared to a superhydrophobic surface with nanostructures only. We observed efficient droplet jumping and higher coverage of droplets with diameter smaller than 10 μm, both of which suppress frost formation. The hybrid surface avoids the formation of liquid-bridges for Cassie-to-Wenzel transition, therefore eliminating the `bottom-up' droplet freezing from the cold substrate. These findings provide new insights to improve anti-frosting and anti-icing by using heterogeneous wettability in multiscale structures.

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

    Science.gov (United States)

    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.

  13. Spatiotemporal Analysis of AIDS Incidence Among Adults in Brazil.

    Science.gov (United States)

    da Silva Lizzi, Elisangela Aparecida; Nunes, Altacilio Aparecido; Martinez, Edson Zangiacomi

    2016-01-01

    AIDS is the fourth leading cause of death worldwide and, currently, the overall prevalence rate of HIV infection in Brazil is 0.5% among men and 0.3% among women. To evaluate the spatiotemporal trend of AIDS in Brazil from 2006 to 2012 and its relationship with human development index (HDI) and their components income, education and life expectancy. This ecological study evaluate the spatiotemporal trend of standardized incidence ratio of AIDS among adults in Brazil from 2006 to 2012 and its relationship with HDI by using a Bayesian analysis, considering the Brazilian Federal Units as units of analysis. The proposed statistical model allows obtaining a standardized incidence ratio (SIR, adjusted by gender and age). Among the men, our results show higher incidence rates in the States of the Southern regions as well as in the state of Amazonas (Northern Brazil). In females, we found other patterns for SIR, with higher incidence rates in the states of Rio de Janeiro (Southeast region), Rio Grande do Sul and Santa Catarina (both in Southern region). Among men it was observed as an expressive association between the SIR values and the overall HDI and income and education components, but it was observed to have an inverse association with the life expectancy component. Among women, it is noted that the SIR values are associated with the overall HDI and the education components only at the beginning of the studied period. AIDS remains a major public health problem in Brazil, mainly in the southern and southeastern regions of the country. Considering its association with HDI, it is noted that the disease still remains related to the pattern observed in the early years of the studied period, at least in the more developed regions of Brazil. This certainly happened because of the chronicity of the disease, thus affecting people with good socioeconomic status.

  14. Spatial and temporal expression patterns of auxin response transcription factors in the syncytium induced by the beet cyst nematode Heterodera schachtii in Arabidopsis.

    Science.gov (United States)

    Hewezi, Tarek; Piya, Sarbottam; Richard, Geoffrey; Rice, J Hollis

    2014-09-01

    Plant-parasitic cyst nematodes induce the formation of a multinucleated feeding site in the infected root, termed the syncytium. Recent studies point to key roles of the phytohormone auxin in the regulation of gene expression and establishment of the syncytium. Nevertheless, information about the spatiotemporal expression patterns of the transcription factors that mediate auxin transcriptional responses during syncytium formation is limited. Here, we provide a gene expression map of 22 auxin response factors (ARFs) during the initiation, formation and maintenance stages of the syncytium induced by the cyst nematode Heterodera schachtii in Arabidopsis. We observed distinct and overlapping expression patterns of ARFs throughout syncytium development phases. We identified a set of ARFs whose expression is predominantly located inside the developing syncytium, whereas others are expressed in the neighbouring cells, presumably to initiate specific transcriptional programmes required for their incorporation within the developing syncytium. Our analyses also point to a role of certain ARFs in determining the maximum size of the syncytium. In addition, several ARFs were found to be highly expressed in fully developed syncytia, suggesting a role in maintaining the functional phenotype of mature syncytia. The dynamic distribution and overlapping expression patterns of various ARFs seem to be essential characteristics of ARF activity during syncytium development. © 2014 BSPP AND JOHN WILEY & SONS LTD.

  15. Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex.

    Directory of Open Access Journals (Sweden)

    Laureline Logiaco

    2015-08-01

    Full Text Available The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70-200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys' behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators.

  16. Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex.

    Science.gov (United States)

    Logiaco, Laureline; Quilodran, René; Procyk, Emmanuel; Arleo, Angelo

    2015-08-01

    The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC) of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70-200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys' behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators.

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

    Energy Technology Data Exchange (ETDEWEB)

    Stewart, Robert N [ORNL; Piburn, Jesse O [ORNL; Sorokine, Alexandre [ORNL; Myers, Aaron T [ORNL; White, Devin A [ORNL

    2015-01-01

    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. 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 publish or

  18. Bifurcation of learning and structure formation in neuronal maps

    DEFF Research Database (Denmark)

    Marschler, Christian; Faust-Ellsässer, Carmen; Starke, Jens

    2014-01-01

    to map formation in the laminar nucleus of the barn owl's auditory system. Using equation-free methods, we perform a bifurcation analysis of spatio-temporal structure formation in the associated synaptic-weight matrix. This enables us to analyze learning as a bifurcation process and follow the unstable...... states as well. A simple time translation of the learning window function shifts the bifurcation point of structure formation and goes along with traveling waves in the map, without changing the animal's sound localization performance....

  19. Spatiotemporal Patterns of Urban Encroachment on Cropland and Its Impacts on Potential Agricultural Productivity in China

    Directory of Open Access Journals (Sweden)

    Hongyan Cai

    2013-11-01

    Full Text Available Rapid urbanization and population growth in China have raised great concerns regarding food security caused by the loss of limited cultivated land. In this study, we used remotely sensed data and an agricultural productivity estimation model to characterize the spatiotemporal patterns of the conversion of cropland into urban land and quantify its impacts on agricultural productivity potential during China’s rapid urbanization period, from 1990 to 2010. The results show that urban development has transformed approximately 4.18 Mha, or 2.26%, of the total cropland in China. From 1990 to 2000, approximately 1.50 Mha of cropland was developed, while roughly 1.8 times this amount (2.68 Mha was converted over the period of 2000 to 2010. Most of the conversion is located in the central and eastern coastal provinces and is mainly concentrated on the periphery of the major urban areas. The transformation has, consequently, caused a 71.45 Tg, or 2.65%, loss of potential light-temperature agricultural productivity (PLTAP; losses were 24.33 Tg in the first decade of the study and 47.11 Tg in the second. At the provincial scale, the largest percentages of PLTAP loss are mainly concentrated in the developed provinces on the eastern coast, such as Shanghai, Beijing, Zhejiang, Tianjin, and Jiangsu. Considering that these areas can accommodate more people and produce higher economic output on unit area of built-up land and, yet, scarce land that can be reclaimed, this study suggests that the dynamic balance of total farmland policy in China should be varied provincially according to the major function of the province. The policy adjustment will help maximize the utilization efficiency of land.

  20. The spatio-temporal dynamic pattern of rural domestic solid waste discharge of China and its challenges.

    Science.gov (United States)

    Tian, Guangjin; Kong, Lingqiang; Liu, Xiaojuan; Yuan, Wenping

    2018-04-01

    At present, construction of rural domestic waste treatment facilities is seriously lagging, and in many cases, treatment facilities do not yet exist in some villages of China. Serious rural waste pollution has not only impacted the quality of surface water and groundwater but also the atmosphere and the living environment of farmers of China. There are relatively few studies of rural domestic waste pollution, especially with respect to the spatio-temporal dynamic pattern of rural domestic waste discharge. Using survey data and income per capita, we calculated rural domestic waste discharge per capita per day. From this, we calculated provincial rural domestic waste discharge. According to our study, rural domestic waste discharge was 1.42 × 10 8 t/year in 2000. This number increased to 2.3 × 10 8 t/year in 2006 and to 2.47 × 10 8 t/year in 2010. Rural domestic waste increased dramatically while the actual rural population and the proportion of the rural population declined. When examining the eight regions, the rural domestic waste discharge of northeastern China, Qinghai-Tibet, middle China, and southwestern China had increased dramatically, while that of northern China, southern China, and eastern China increased relatively slowly. The economies of northern China, southern China, and eastern China are more developed; their rural domestic waste discharge has been high since 2000 and has continued to increase slowly. In northeastern China, Qinghai-Tibet, middle China, and southwestern China, rural domestic waste discharge was low in 2000; however, in the ten-year period from 2000 to 2010, their rural domestic waste discharge increased dramatically.

  1. Automated detection of qualitative spatio-temporal features in electrocardiac activation maps.

    Science.gov (United States)

    Ironi, Liliana; Tentoni, Stefania

    2007-02-01

    This paper describes a piece of work aiming at the realization of a tool for the automated interpretation of electrocardiac maps. Such maps can capture a number of electrical conduction pathologies, such as arrhytmia, that can be missed by the analysis of traditional electrocardiograms. But, their introduction into the clinical practice is still far away as their interpretation requires skills that belongs to very few experts. Then, an automated interpretation tool would bridge the gap between the established research outcome and clinical practice with a consequent great impact on health care. Qualitative spatial reasoning can play a crucial role in the identification of spatio-temporal patterns and salient features that characterize the heart electrical activity. We adopted the spatial aggregation (SA) conceptual framework and an interplay of numerical and qualitative information to extract features from epicardial maps, and to make them available for reasoning tasks. Our focus is on epicardial activation isochrone maps as they are a synthetic representation of spatio-temporal aspects of the propagation of the electrical excitation. We provide a computational SA-based methodology to extract, from 3D epicardial data gathered over time, (1) the excitation wavefront structure, and (2) the salient features that characterize wavefront propagation and visually correspond to specific geometric objects. The proposed methodology provides a robust and efficient way to identify salient pieces of information in activation time maps. The hierarchical structure of the abstracted geometric objects, crucial in capturing the prominent information, facilitates the definition of general rules necessary to infer the correlation between pathophysiological patterns and wavefront structure and propagation.

  2. Study of pattern formation at liquid interfaces: Progress report, November 1986-October 1987

    International Nuclear Information System (INIS)

    Maher, J.V.

    1987-10-01

    This paper summarizes the work done on the following topics at the University of Pittsburgh: the behavior of a tip-splitting, viscous-fingering system and the role of interfacial noise in pattern formation on planar interfaces; the search for instability on a quenched liquid interface; and binary liquid gels and polymer solutions

  3. Oscillations and patterns in a model of simultaneous CO and C2H2 oxidation and NO(x) reduction in a cross-flow reactor.

    Science.gov (United States)

    Hadač, Otto; Kohout, Martin; Havlica, Jaromír; Schreiber, Igor

    2015-03-07

    A model describing simultaneous catalytic oxidation of CO and C2H2 and reduction of NOx in a cross-flow tubular reactor is explored with the aim of relating spatiotemporal patterns to specific pathways in the mechanism. For that purpose, a detailed mechanism proposed for three-way catalytic converters is split into two subsystems, (i) simultaneous oxidation of CO and C2H2, and (ii) oxidation of CO combined with NOx reduction. The ability of these two subsystems to display mechanism-specific dynamical effects is studied initially by neglecting transport phenomena and applying stoichiometric network and bifurcation analyses. We obtain inlet temperature - inlet oxygen concentration bifurcation diagrams, where each region possessing specific dynamics - oscillatory, bistable and excitable - is associated with a dominant reaction pathway. Next, the spatiotemporal behaviour due to reaction kinetics combined with transport processes is studied. The observed spatiotemporal patterns include phase waves, travelling fronts, pulse waves and spatiotemporal chaos. Although these types of pattern occur generally when the kinetic scheme possesses autocatalysis, we find that some of their properties depend on the underlying dominant reaction pathway. The relation of patterns to specific reaction pathways is discussed.

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

    Science.gov (United States)

    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.

  5. Spatiotemporal Patterns of Urban Human Mobility

    Science.gov (United States)

    Hasan, Samiul; Schneider, Christian M.; Ukkusuri, Satish V.; González, Marta C.

    2013-04-01

    The modeling of human mobility is adopting new directions due to the increasing availability of big data sources from human activity. These sources enclose digital information about daily visited locations of a large number of individuals. Examples of these data include: mobile phone calls, credit card transactions, bank notes dispersal, check-ins in internet applications, among several others. In this study, we consider the data obtained from smart subway fare card transactions to characterize and model urban mobility patterns. We present a simple mobility model for predicting peoples' visited locations using the popularity of places in the city as an interaction parameter between different individuals. This ingredient is sufficient to reproduce several characteristics of the observed travel behavior such as: the number of trips between different locations in the city, the exploration of new places and the frequency of individual visits of a particular location. Moreover, we indicate the limitations of the proposed model and discuss open questions in the current state of the art statistical models of human mobility.

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

    Science.gov (United States)

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

    2014-07-21

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

  7. A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

    Directory of Open Access Journals (Sweden)

    Shengnan Ke

    2014-07-01

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

  8. A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

    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.

  10. Tree island pattern formation in the Florida Everglades

    Science.gov (United States)

    Carr, Joel; D'Odorico, P.; Engel, Victor C.; Redwine, Jed

    2016-01-01

    The Florida Everglades freshwater landscape exhibits a distribution of islands covered by woody vegetation and bordered by marshes and wet prairies. Known as “tree islands”, these ecogeomorphic features can be found in few other low gradient, nutrient limited freshwater wetlands. In the last few decades, however, a large percentage of tree islands have either shrank or disappeared in apparent response to altered water depths and other stressors associated with human impacts on the Everglades. Because the processes determining the formation and spatial organization of tree islands remain poorly understood, it is still unclear what controls the sensitivity of these landscapes to altered conditions. We hypothesize that positive feedbacks between woody plants and soil accretion are crucial to emergence and decline of tree islands. Likewise, positive feedbacks between phosphorus (P) accumulation and trees explain the P enrichment commonly observed in tree island soils. Here, we develop a spatially-explicit model of tree island formation and evolution, which accounts for these positive feedbacks (facilitation) as well as for long range competition and fire dynamics. It is found that tree island patterns form within a range of parameter values consistent with field data. Simulated impacts of reduced water levels, increased intensity of drought, and increased frequency of dry season/soil consuming fires on these feedback mechanisms result in the decline and disappearance of tree islands on the landscape.

  11. Formation of ring-patterned nanoclusters by laser–plume interaction

    International Nuclear Information System (INIS)

    Sivayoganathan, Mugunthan; Tan Bo; Venkatakrishnan, Krishnan

    2013-01-01

    This article reports for the first time a unique study performed to regulate the ring diameter of nanoclusters fabricated during femtosecond laser ablation of solids and a mechanism is proposed for the formation of those ring clusters. The ring nanoclusters are made out of nanoparticles with a range of 10–30 nm. Our experimental studies showed the synthesis of ring nanoclusters with random diameter distribution on metals, nonmetals, and semiconductors, such as titanium, aluminum, glasses, ceramics, graphite, and silicon. To regulate the ring size, the effects of laser parameters, such as wavelength, pulse duration, pulse energy, and repetition rate on the ring diameter are analyzed. The influence of ablated materials and the background gas on ring size is also elaborated in this article. The motion of plume species under the influence of ponderomotive force on free electrons possibly played a key role in the formation of the ring-patterned nanoclusters. This study could help to understand the fundamentals in laser ablative nanosynthesis as well as to produce nanostructures with organized ring diameter that controls the density and porosity of those 3D nanostructures.

  12. Ecological divergence and conservatism: spatiotemporal patterns of niche evolution in a genus of livebearing fishes (Poeciliidae: Xiphophorus).

    Science.gov (United States)

    Culumber, Zachary W; Tobler, Michael

    2016-02-19

    Ecological factors often have a strong impact on spatiotemporal patterns of biodiversity. The integration of spatial ecology and phylogenetics allows for rigorous tests of whether speciation is associated with niche conservatism (constraints on ecological divergence) or niche divergence. We address this question in a genus of livebearing fishes for which the role of sexual selection in speciation has long been studied, but in which the potential role of ecological divergence during speciation has not been tested. By combining reconstruction of ancestral climate tolerances and disparity indices, we show that the earliest evolutionary split in Xiphophorus was associated with significant divergence for temperature variables. Niche evolution and present day niches were most closely associated with each species' geographic distribution relative to a biogeographic barrier, the Trans-Mexican Volcanic Belt. Tests for similarity of the environmental backgrounds of closely related species suggested that the relative importance of niche conservatism and divergence during speciation varied among the primary clades of Xiphophorus. Closely related species in the two swordtail clades exhibited higher levels of niche overlap than expected given environmental background similarity indicative of niche conservatism. In contrast, almost all species of platyfish had significantly divergent niches compared to environmental backgrounds, which is indicative of niche divergence. The results suggest that the relative importance of niche conservatism and divergence differed among the clades of Xiphophorus and that traits associated with niche evolution may be more evolutionarily labile in the platyfishes. Our results ultimately suggest that the taxonomic scale of tests for conservatism and divergence could greatly influence inferences of their relative importance in the speciation process.

  13. Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

    Science.gov (United States)

    Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

    2017-04-01

    Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

  14. Inter-dependent tissue growth and Turing patterning in a model for long bone development

    International Nuclear Information System (INIS)

    Tanaka, Simon; Iber, Dagmar

    2013-01-01

    The development of long bones requires a sophisticated spatial organization of cellular signalling, proliferation, and differentiation programs. How such spatial organization emerges on the growing long bone domain is still unresolved. Based on the reported biochemical interactions we developed a regulatory model for the core signalling factors IHH, PTCH1, and PTHrP and included two cell types, proliferating/resting chondrocytes and (pre-)hypertrophic chondrocytes. We show that the reported IHH–PTCH1 interaction gives rise to a Schnakenberg-type Turing kinetics, and that inclusion of PTHrP is important to achieve robust patterning when coupling patterning and tissue dynamics. The model reproduces relevant spatiotemporal gene expression patterns, as well as a number of relevant mutant phenotypes. In summary, we propose that a ligand–receptor based Turing mechanism may control the emergence of patterns during long bone development, with PTHrP as an important mediator to confer patterning robustness when the sensitive Turing system is coupled to the dynamics of a growing and differentiating tissue. We have previously shown that ligand–receptor based Turing mechanisms can also result from BMP–receptor, SHH–receptor, and GDNF–receptor interactions, and that these reproduce the wildtype and mutant patterns during digit formation in limbs and branching morphogenesis in lung and kidneys. Receptor–ligand interactions may thus constitute a general mechanism to generate Turing patterns in nature. (paper)

  15. Inter-dependent tissue growth and Turing patterning in a model for long bone development

    Science.gov (United States)

    Tanaka, Simon; Iber, Dagmar

    2013-10-01

    The development of long bones requires a sophisticated spatial organization of cellular signalling, proliferation, and differentiation programs. How such spatial organization emerges on the growing long bone domain is still unresolved. Based on the reported biochemical interactions we developed a regulatory model for the core signalling factors IHH, PTCH1, and PTHrP and included two cell types, proliferating/resting chondrocytes and (pre-)hypertrophic chondrocytes. We show that the reported IHH-PTCH1 interaction gives rise to a Schnakenberg-type Turing kinetics, and that inclusion of PTHrP is important to achieve robust patterning when coupling patterning and tissue dynamics. The model reproduces relevant spatiotemporal gene expression patterns, as well as a number of relevant mutant phenotypes. In summary, we propose that a ligand-receptor based Turing mechanism may control the emergence of patterns during long bone development, with PTHrP as an important mediator to confer patterning robustness when the sensitive Turing system is coupled to the dynamics of a growing and differentiating tissue. We have previously shown that ligand-receptor based Turing mechanisms can also result from BMP-receptor, SHH-receptor, and GDNF-receptor interactions, and that these reproduce the wildtype and mutant patterns during digit formation in limbs and branching morphogenesis in lung and kidneys. Receptor-ligand interactions may thus constitute a general mechanism to generate Turing patterns in nature.

  16. Spatio-Temporal Characteristics of Resident Trip Based on Poi and OD Data of Float CAR in Beijing

    Science.gov (United States)

    Mou, N.; Li, J.; Zhang, L.; Liu, W.; Xu, Y.

    2017-09-01

    Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method - based on grid density, which is used to cluster the OD (origin and destination) data of taxi at different times. Then combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion - spatial aggregation - spatial relative dispersion" in one day.

  17. Analysis of surface soil moisture patterns in agricultural landscapes using Empirical Orthogonal Functions

    Directory of Open Access Journals (Sweden)

    W. Korres

    2010-05-01

    Full Text Available Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture. Nevertheless, its spatio-temporal patterns in agriculturally used landscapes that are affected by multiple natural (rainfall, soil, topography etc. and agronomic (fertilisation, soil management etc. factors are often not well known. The aim of this study is to determine the dominant factors governing the spatio-temporal patterns of surface soil moisture in a grassland and an arable test site that are located within the Rur catchment in Western Germany. Surface soil moisture (0–6 cm was measured in an approx. 50×50 m grid during 14 and 17 measurement campaigns (May 2007 to November 2008 in both test sites. To analyse the spatio-temporal patterns of surface soil moisture, an Empirical Orthogonal Function (EOF analysis was applied and the results were correlated with parameters derived from topography, soil, vegetation and land management to link the patterns to related factors and processes. For the grassland test site, the analysis resulted in one significant spatial structure (first EOF, which explained 57.5% of the spatial variability connected to soil properties and topography. The statistical weight of the first spatial EOF is stronger on wet days. The highest temporal variability can be found in locations with a high percentage of soil organic carbon (SOC. For the arable test site, the analysis resulted in two significant spatial structures, the first EOF, which explained 38.4% of the spatial variability, and showed a highly significant correlation to soil properties, namely soil texture and soil stone content. The second EOF, which explained 28.3% of the spatial variability, is linked to differences in land management. The soil moisture in the arable test site varied more strongly during dry and wet periods at locations with low porosity. The method applied is capable of identifying the dominant parameters controlling spatio-temporal patterns of

  18. Spatiotemporal Patterns of Ice Mass Variations and the Local Climatic Factors in the Riparian Zone of Central Valley, California

    Science.gov (United States)

    Inamdar, P.; Ambinakudige, S.

    2016-12-01

    Californian icefields are natural basins of fresh water. They provide irrigation water to the farms in the central valley. We analyzed the ice mass loss rates, air temperature and land surface temperature (LST) in Sacramento and San Joaquin basins in California. The digital elevation models from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to calculate ice mass loss rate between the years 2002 and 2015. Additionally, Landsat TIR data were used to extract the land surface temperature. Data from local weather stations were analyzed to understand the spatiotemporal trends in air temperature. The results showed an overall mass recession of -0.8 ± 0.7 m w.e.a-1. We also noticed an about 60% loss in areal extent of the glaciers in the study basins between 2000 and 2015. Local climatic factors, along with the global climate patterns might have influenced the negative trends in the ice mass loss. Overall, there was an increase in the air temperature by 0.07± 0.02 °C in the central valley between 2000 and 2015. Furthermore, LST increased by 0.34 ± 0.4 °C and 0.55± 0.1 °C in the Sacramento and San Joaquin basins. Our preliminary results show the decrease in area and mass of ice mass in the basins, and changing agricultural practices in the valley.

  19. SWARM-BOT: Pattern Formation in a Swarm of Self-Assembling Mobile Robots

    OpenAIRE

    El Kamel, A.; Mellouli, K.; Borne, P.; Sahin, E.; Labella, T.H.; Trianni, V.; Deneubourg, J.-L.; Rasse, P.; Floreano, D.; Gambardella, L.M.; Mondada, F.; Nolfi, S.; Dorigo, M.

    2002-01-01

    In this paper we introduce a new robotic system, called swarm-bot. The system consists of a swarm of mobile robots with the ability to connect to/disconnect from each other to self-assemble into different kinds of structures. First, we describe our vision and the goals of the project. Then we present preliminary results on the formation of patterns obtained from a grid-world simulation of the system.

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

    KAUST Repository

    Zhang, Bohai

    2014-01-01

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

  1. Spatial & Temporal Geophysical Monitoring of Microbial Growth and Biofilm Formation

    Science.gov (United States)

    Previous studies have examined the effect of biogenic gases and biomineralization on the acoustic properties of porous media. In this study, we investigated the spatiotemporal effect of microbial growth and biofilm formation on compressional waves and complex conductivity in sand...

  2. Spatiotemporal Simulation of Tourist Town Growth Based on the Cellular Automata Model: The Case of Sanpo Town in Hebei Province

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2013-01-01

    Full Text Available Spatiotemporal simulation of tourist town growth is important for research on land use/cover change under the influence of urbanization. Many scholars have shown great interest in the unique pattern of driving urban development with tourism development. Based on the cellular automata (CA model, we simulated and predicted the spatiotemporal growth of Sanpo town in Hebei Province, using the tourism urbanization growth model. Results showed that (1 average annual growth rate of the entire region was 1.5 Ha2 per year from 2005 to 2010, 4 Ha2 per year from 2010 to 2015, and 2.5 Ha2 per year from 2015 to 2020; (2 urban growth rate increased yearly, with regional differences, and had a high degree of correlation with the Euclidean distance of town center, traffic route, attractions, and other factors; (3 Gougezhuang, an important village center in the west of the town, demonstrated traffic advantages and increased growth rate since 2010; (4 Magezhuang village has the largest population in the region, so economic advantages have driven the development of rural urbanization. It showed that CA had high reliability in simulating the spatiotemporal evolution of tourist town, which assists the study of spatiotemporal growth under urbanization and rational protection of tourism resources.

  3. Continuous fine pattern formation by screen-offset printing using a silicone blanket

    Science.gov (United States)

    Nomura, Ken-ichi; Kusaka, Yasuyuki; Ushijima, Hirobumi; Nagase, Kazuro; Ikedo, Hiroaki; Mitsui, Ryosuke; Takahashi, Seiya; Nakajima, Shin-ichiro; Iwata, Shiro

    2014-09-01

    Screen-offset printing combines screen-printing on a silicone blanket with transference of the print from the blanket to a substrate. The blanket absorbs organic solvents in the ink, and therefore, the ink does not disperse through the material. This prevents blurring and allows fine patterns with widths of a few tens of micrometres to be produced. However, continuous printing deteriorates the pattern’s shape, which may be a result of decay in the absorption abilities of the blanket. Thus, we have developed a new technique for refreshing the blanket by substituting high-boiling-point solvents present on the blanket surface with low-boiling-point solvents. We analyse the efficacy of this technique, and demonstrate continuous fine pattern formation for 100 screen-offset printing processes.

  4. Continuous fine pattern formation by screen-offset printing using a silicone blanket

    International Nuclear Information System (INIS)

    Nomura, Ken-ichi; Kusaka, Yasuyuki; Ushijima, Hirobumi; Nagase, Kazuro; Ikedo, Hiroaki; Mitsui, Ryosuke; Takahashi, Seiya; Nakajima, Shin-ichiro; Iwata, Shiro

    2014-01-01

    Screen-offset printing combines screen-printing on a silicone blanket with transference of the print from the blanket to a substrate. The blanket absorbs organic solvents in the ink, and therefore, the ink does not disperse through the material. This prevents blurring and allows fine patterns with widths of a few tens of micrometres to be produced. However, continuous printing deteriorates the pattern’s shape, which may be a result of decay in the absorption abilities of the blanket. Thus, we have developed a new technique for refreshing the blanket by substituting high-boiling-point solvents present on the blanket surface with low-boiling-point solvents. We analyse the efficacy of this technique, and demonstrate continuous fine pattern formation for 100 screen-offset printing processes. (paper)

  5. Wave of chaos in a diffusive system: Generating realistic patterns of patchiness in plankton-fish dynamics

    International Nuclear Information System (INIS)

    Upadhyay, Ranjit Kumar; Kumari, Nitu; Rai, Vikas

    2009-01-01

    We show that wave of chaos (WOC) can generate two-dimensional time-independent spatial patterns which can be a potential candidate for understanding planktonic patchiness observed in marine environments. These spatio-temporal patterns were obtained in computer simulations of a minimal model of phytoplankton-zooplankton dynamics driven by forces of diffusion. We also attempt to figure out the average lifetimes of these non-linear non-equilibrium patterns. These spatial patterns serve as a realistic model for patchiness found in aquatic systems (e.g., marine and oceanic). Additionally, spatio-temporal chaos produced by bi-directional WOCs is robust to changes in key parameters of the system; e.g., intra-specific competition among individuals of phytoplankton and the rate of fish predation. The ideas contained in the present paper may find applications in diverse fields of human endeavor.

  6. Sponge budding is a spatiotemporal morphological patterning process: Insights from synchrotron radiation-based x-ray microtomography into the asexual reproduction of Tethya wilhelma

    OpenAIRE

    Hammel, J. U.; Herzen, J.; Beckmann, F.; Nickel, M.

    2009-01-01

    Abstract Background Primary agametic-asexual reproduction mechanisms such as budding and fission are present in all non-bilaterian and many bilaterian animal taxa and are likely to be metazoan ground pattern characters. Cnidarians display highly organized and regulated budding processes. In contrast, budding in poriferans was thought to be less specific and related to the general ability of this group to reorganize their tissues. Here we test the hypothesis of morphological pattern formation ...

  7. Antibiotic Resistance Pattern and Biofilm Formation Ability of Clinically Isolates of Salmonella enterica Serotype typhimurium

    Directory of Open Access Journals (Sweden)

    Hadi Ghasemmahdi

    2015-05-01

    Full Text Available Background: The emergence of antimicrobial-resistant bacteria with biofilm formation ability may be a major threat to public health and food safety and sanitation. Objectives: The aim of this study was to determine antibiotic resistance patterns and biofilm production characteristics of Salmonella typhimurium isolated from different species of birds. Materials and Methods: The antibiotic resistance patterns of 38 pre-identified isolates were screened by standard Kirby-Bauer disc-diffusion method performed on Mueller–Hinton agar to a panel of 17 antibiotics. The extent of biofilm formation was measured by Microtiter plate (MTP-based systems. Results: The highest antimicrobial resistance was detected against nalidixic acid (97%, followed by doxycycline (86%, colistin (84%, streptomycin (84% and tetracycline (84%. All isolates were sensitive to amikacin (100% and 97% and 95% of the isolates were sensitive to ceftazidime and ceftriaxone, respectively. Twenty one different antibiotic resistance patterns were observed among S. typhimurium isolates. According to the results of the microtitre plate biofilm assay, there was a wide variation in biofilm forming ability among S. typhimurium isolates. Most of the isolates (60.52% were not capable of producing biofilm, while 26.31%, 7.89%, and 5.26% isolates were weak, strong and moderate biofilm producers, respectively. Conclusions: It was concluded that nearly all S. typhimurium isolates revealed a high multiple antibiotic resistant with low biofilm forming capabilities which proposed low association between biofilm formation and antibiotic resistance of a major food important pathogen.

  8. Regulative feedback in pattern formation: towards a general relativistic theory of positional information.

    Science.gov (United States)

    Jaeger, Johannes; Irons, David; Monk, Nick

    2008-10-01

    Positional specification by morphogen gradients is traditionally viewed as a two-step process. A gradient is formed and then interpreted, providing a spatial metric independent of the target tissue, similar to the concept of space in classical mechanics. However, the formation and interpretation of gradients are coupled, dynamic processes. We introduce a conceptual framework for positional specification in which cellular activity feeds back on positional information encoded by gradients, analogous to the feedback between mass-energy distribution and the geometry of space-time in Einstein's general theory of relativity. We discuss how such general relativistic positional information (GRPI) can guide systems-level approaches to pattern formation.

  9. Patterned biofilm formation reveals a mechanism for structural heterogeneity in bacterial biofilms.

    Science.gov (United States)

    Gu, Huan; Hou, Shuyu; Yongyat, Chanokpon; De Tore, Suzanne; Ren, Dacheng

    2013-09-03

    Bacterial biofilms are ubiquitous and are the major cause of chronic infections in humans and persistent biofouling in industry. Despite the significance of bacterial biofilms, the mechanism of biofilm formation and associated drug tolerance is still not fully understood. A major challenge in biofilm research is the intrinsic heterogeneity in the biofilm structure, which leads to temporal and spatial variation in cell density and gene expression. To understand and control such structural heterogeneity, surfaces with patterned functional alkanthiols were used in this study to obtain Escherichia coli cell clusters with systematically varied cluster size and distance between clusters. The results from quantitative imaging analysis revealed an interesting phenomenon in which multicellular connections can be formed between cell clusters depending on the size of interacting clusters and the distance between them. In addition, significant differences in patterned biofilm formation were observed between wild-type E. coli RP437 and some of its isogenic mutants, indicating that certain cellular and genetic factors are involved in interactions among cell clusters. In particular, autoinducer-2-mediated quorum sensing was found to be important. Collectively, these results provide missing information that links cell-to-cell signaling and interaction among cell clusters to the structural organization of bacterial biofilms.

  10. Analysis of Relations between Spatiotemporal Movement Regulation and Performance of Discrete Actions Reveals Functionality in Skilled Climbing.

    Science.gov (United States)

    Orth, Dominic; Kerr, Graham; Davids, Keith; Seifert, Ludovic

    2017-01-01

    In this review of research on climbing expertise, we focus on different measures of climbing performance, including spatiotemporal measures related to fluency and activity states (i.e., discrete actions), adopted by climbers for achieving overall performance goals of getting to the end of a route efficiently and safely. Currently, a broad range of variables have been reported, however, many of these fail to capture how climbers adapt to a route whilst climbing. We argue that spatiotemporal measures should be considered concurrently with evaluation of activity states (such as reaching or exploring) in order gain a more comprehensive picture of how climbers successfully adapt to a route. Spatial and temporal movement measures taken at the hip are a traditional means of assessing efficiency of climbing behaviors. More recently, performatory and exploratory actions of the limbs have been used in combination with spatiotemporal indicators, highlighting the influence of limb states on climbing efficiency and skill transfer. However, only a few studies have attempted to combine spatiotemporal and activity state measures taken during route climbing. This review brings together existing approaches for observing climbing skill at performance outcome (i.e., spatiotemporal assessments) and process (i.e., limb activity states) levels of analysis. Skill level is associated with a spatially efficient route progression and lower levels of immobility. However, more difficult hold architecture designs require significantly greater mobility and more complex movement patterning to maintain performance. Different forms of functional, or goal-supportive, movement variability, including active recovery and hold exploration, have been implicated as important adaptations to physiological and environmental dynamics that emerge during the act of climbing. Indeed, recently it has also been shown that, when climbing on new routes, efficient exploration can improve the transfer of skill. This

  11. Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy.

    Science.gov (United States)

    Salis, Michele; Ager, Alan A; Alcasena, Fermin J; Arca, Bachisio; Finney, Mark A; Pellizzaro, Grazia; Spano, Donatella

    2015-01-01

    In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn probability, fire size, and flame length among time periods within the fire season, which starts in early June and ends in late September. Peak burn probability and flame length were observed in late July. We found that patterns of wildfire likelihood and intensity were mainly related to spatiotemporal variation in ignition locations, fuel moisture, and wind vectors. Our modeling approach allowed consideration of historical patterns of winds, ignition locations, and live and dead fuel moisture on fire exposure factors. The methodology proposed can be useful for analyzing potential wildfire risk and effects at landscape scale, evaluating historical changes and future trends in wildfire exposure, as well as for addressing and informing fuel management and risk mitigation issues.

  12. Mapping, Learning, Visualization, Classification, and Understanding of fMRI Data in the NeuCube Evolving Spatiotemporal Data Machine of Spiking Neural Networks.

    Science.gov (United States)

    Kasabov, Nikola K; Doborjeh, Maryam Gholami; Doborjeh, Zohreh Gholami

    2017-04-01

    This paper introduces a new methodology for dynamic learning, visualization, and classification of functional magnetic resonance imaging (fMRI) as spatiotemporal brain data. The method is based on an evolving spatiotemporal data machine of evolving spiking neural networks (SNNs) exemplified by the NeuCube architecture [1]. The method consists of several steps: mapping spatial coordinates of fMRI data into a 3-D SNN cube (SNNc) that represents a brain template; input data transformation into trains of spikes; deep, unsupervised learning in the 3-D SNNc of spatiotemporal patterns from data; supervised learning in an evolving SNN classifier; parameter optimization; and 3-D visualization and model interpretation. Two benchmark case study problems and data are used to illustrate the proposed methodology-fMRI data collected from subjects when reading affirmative or negative sentences and another one-on reading a sentence or seeing a picture. The learned connections in the SNNc represent dynamic spatiotemporal relationships derived from the fMRI data. They can reveal new information about the brain functions under different conditions. The proposed methodology allows for the first time to analyze dynamic functional and structural connectivity of a learned SNN model from fMRI data. This can be used for a better understanding of brain activities and also for online generation of appropriate neurofeedback to subjects for improved brain functions. For example, in this paper, tracing the 3-D SNN model connectivity enabled us for the first time to capture prominent brain functional pathways evoked in language comprehension. We found stronger spatiotemporal interaction between left dorsolateral prefrontal cortex and left temporal while reading a negated sentence. This observation is obviously distinguishable from the patterns generated by either reading affirmative sentences or seeing pictures. The proposed NeuCube-based methodology offers also a superior classification accuracy

  13. Spatio-temporal scaling of channels in braided streams.

    Science.gov (United States)

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

    2006-01-01

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

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

    Science.gov (United States)

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

    2017-09-01

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

  15. Formation factor of regular porous pattern in poly-α-methylstyrene film

    International Nuclear Information System (INIS)

    Yang Ruizhuang; Xu Jiajing; Gao Cong; Ma Shuang; Chen Sufen; Luo Xuan; Fang Yu; Li Bo

    2015-01-01

    Regular poly-α-methylstyrene (PAMS) porous film with macron-sized cells was prepared by casting the solution in the condition with high humidity. In this paper, the effects of the molecular weight of PAMS, PAMS concentration, humidity, temperature, volatile solvents and the thickness of liquid of solution on formation of regular porous pattern in PAMS film were discussed. The results show that these factors significantly affect the pore size and the pore distribution. The capillary force and Benard-Marangoni convection are main driving forces for the water droplet moving and making pores regular arrangement. (authors)

  16. How innate is locomotion in precocial animals? A study on the early development of spatio-temporal gait variables and gait symmetry in piglets.

    Science.gov (United States)

    Vanden Hole, Charlotte; Goyens, Jana; Prims, Sara; Fransen, Erik; Ayuso Hernando, Miriam; Van Cruchten, Steven; Aerts, Peter; Van Ginneken, Chris

    2017-08-01

    Locomotion is one of the most important ecological functions in animals. Precocial animals, such as pigs, are capable of independent locomotion shortly after birth. This raises the question whether coordinated movement patterns and the underlying muscular control in these animals is fully innate or whether there still exists a rapid maturation. We addressed this question by studying gait development in neonatal pigs through the analysis of spatio-temporal gait characteristics during locomotion at self-selected speed. To this end, we made video recordings of piglets walking along a corridor at several time points (from 0 h to 96 h). After digitization of the footfalls, we analysed self-selected speed and spatio-temporal characteristics (e.g. stride and step lengths, stride frequency and duty factor) to study dynamic similarity, intralimb coordination and interlimb coordination. To assess the variability of the gait pattern, left-right asymmetry was studied. To distinguish neuromotor maturation from effects caused by growth, both absolute and normalized data (according to the dynamic similarity concept) were included in the analysis. All normalized spatio-temporal variables reached stable values within 4 h of birth, with most of them showing little change after the age of 2 h. Most asymmetry indices showed stable values, hovering around 10%, within 8 h of birth. These results indicate that coordinated movement patterns are not entirely innate, but that a rapid neuromotor maturation, potentially also the result of the rearrangement or recombination of existing motor modules, takes place in these precocial animals. © 2017. Published by The Company of Biologists Ltd.

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

    Directory of Open Access Journals (Sweden)

    LI Yinchao

    2016-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Min Jiang

    2016-11-01

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

  19. Spiral wave classification using normalized compression distance: Towards atrial tissue spatiotemporal electrophysiological behavior characterization.

    Science.gov (United States)

    Alagoz, Celal; Guez, Allon; Cohen, Andrew; Bullinga, John R

    2015-08-01

    Analysis of electrical activation patterns such as re-entries during atrial fibrillation (Afib) is crucial in understanding arrhythmic mechanisms and assessment of diagnostic measures. Spiral waves are a phenomena that provide intuitive basis for re-entries occurring in cardiac tissue. Distinct spiral wave behaviors such as stable spiral waves, meandering spiral waves, and spiral wave break-up may have distinct electrogram manifestations on a mapping catheter. Hence, it is desirable to have an automated classification of spiral wave behavior based on catheter recordings for a qualitative characterization of spatiotemporal electrophysiological activity on atrial tissue. In this study, we propose a method for classification of spatiotemporal characteristics of simulated atrial activation patterns in terms of distinct spiral wave behaviors during Afib using two different techniques: normalized compressed distance (NCD) and normalized FFT (NFFTD). We use a phenomenological model for cardiac electrical propagation to produce various simulated spiral wave behaviors on a 2D grid and labeled them as stable, meandering, or breakup. By mimicking commonly used catheter types, a star shaped and a circular shaped both of which do the local readings from atrial wall, monopolar and bipolar intracardiac electrograms are simulated. Virtual catheters are positioned at different locations on the grid. The classification performance for different catheter locations, types and for monopolar or bipolar readings were also compared. We observed that the performance for each case differed slightly. However, we found that NCD performance is superior to NFFTD. Through the simulation study, we showed the theoretical validation of the proposed method. Our findings suggest that a qualitative wavefront activation pattern can be assessed during Afib without the need for highly invasive mapping techniques such as multisite simultaneous electrogram recordings.

  20. Hardware format pattern banks for the Associative memory boards in the ATLAS Fast Tracker Trigger System

    CERN Document Server

    Grewcoe, Clay James

    2014-01-01

    The aim of this project is to streamline and update the process of encoding the pattern bank to hardware format in the Associative memory board (AM) of the Fast Tracker (FTK) for the ATLAS detector. The encoding is also adapted to Gray code to eliminate possible misreadings in high frequency devices such as this one, ROOT files are used to store the pattern banks because of the compression utilized in ROOT.

  1. Competitive STDP Learning of Overlapping Spatial Patterns.

    Science.gov (United States)

    Krunglevicius, Dalius

    2015-08-01

    Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

  2. A stream cipher based on a spatiotemporal chaotic system

    International Nuclear Information System (INIS)

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

    2007-01-01

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

  3. Regulation of cell behavior and tissue patterning by bioelectrical signals: challenges and opportunities for biomedical engineering.

    Science.gov (United States)

    Levin, Michael; Stevenson, Claire G

    2012-01-01

    Achieving control over cell behavior and pattern formation requires molecular-level understanding of regulatory mechanisms. Alongside transcriptional networks and biochemical gradients, there functions an important system of cellular communication and control: transmembrane voltage gradients (V(mem)). Bioelectrical signals encoded in spatiotemporal changes of V(mem) control cell proliferation, migration, and differentiation. Moreover, endogenous bioelectrical gradients serve as instructive cues mediating anatomical polarity and other organ-level aspects of morphogenesis. In the past decade, significant advances in molecular physiology have enabled the development of new genetic and biophysical tools for the investigation and functional manipulation of bioelectric cues. Recent data implicate V(mem) as a crucial epigenetic regulator of patterning events in embryogenesis, regeneration, and cancer. We review new conceptual and methodological developments in this fascinating field. Bioelectricity offers a novel way of quantitatively understanding regulation of growth and form in vivo, and it reveals tractable, powerful control points that will enable truly transformative applications in bioengineering, regenerative medicine, and synthetic biology.

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

    Science.gov (United States)

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

    2009-06-22

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

  5. Monitoring the Spatiotemporal Activities of miRNAs in Small Animal Models Using Molecular Imaging Modalities

    Directory of Open Access Journals (Sweden)

    Patrick Baril

    2015-03-01

    Full Text Available MicroRNAs (miRNAs are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy.

  6. Monitoring the spatiotemporal activities of miRNAs in small animal models using molecular imaging modalities.

    Science.gov (United States)

    Baril, Patrick; Ezzine, Safia; Pichon, Chantal

    2015-03-04

    MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy.

  7. Optimization of Spatiotemporal Apertures in Channel Sounding

    DEFF Research Database (Denmark)

    Pedersen, Troels; Pedersen, Claus; Yin, Xuefeng

    2008-01-01

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

  8. Circuit Formation by Spatio-Temporal Control of Messenger RNA ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    The connections inside the brain need to be wired in a precise manner during development to ensure its proper function. This project will provide insight into circuit formation to help us understand how axon regeneration can improve clinical outcomes. Brain wiring, damage, and developmental defects Researchers have ...

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

    Science.gov (United States)

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

    2017-12-01

    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

  10. Formation of precise 2D Au particle arrays via thermally induced dewetting on pre-patterned substrates

    Directory of Open Access Journals (Sweden)

    Dong Wang

    2011-06-01

    Full Text Available The fabrication of precise 2D Au nanoparticle arrays over a large area is presented. The technique was based on pre-patterning of the substrate before the deposition of a thin Au film, and the creation of periodic particle arrays by subsequent dewetting induced by annealing. Two types of pre-patterned substrates were used: The first comprised an array of pyramidal pits and the second an array of circular holes. For the dewetting of Au films on the pyramidal pit substrate, the structural curvature-driven diffusion cooperates with capillarity-driven diffusion, resulting in the formation of precise 2D particle arrays for films within a structure dependent thickness-window. For the dewetting of Au films on the circular hole substrate, the periodic discontinuities in the films, induced by the deposition, can limit the diffusion paths and lead to the formation of one particle per individual separated region (holes or mesas between holes, and thus, result in the evolution of precise 2D particle arrays. The influence of the pre-patterned structures and the film thickness is analyzed and discussed. For both types of pre-patterned substrate, the Au film thickness had to be adjusted in a certain thickness-window in order to achieve the precise 2D particle arrays.

  11. Formation of precise 2D Au particle arrays via thermally induced dewetting on pre-patterned substrates

    Science.gov (United States)

    Ji, Ran

    2011-01-01

    Summary The fabrication of precise 2D Au nanoparticle arrays over a large area is presented. The technique was based on pre-patterning of the substrate before the deposition of a thin Au film, and the creation of periodic particle arrays by subsequent dewetting induced by annealing. Two types of pre-patterned substrates were used: The first comprised an array of pyramidal pits and the second an array of circular holes. For the dewetting of Au films on the pyramidal pit substrate, the structural curvature-driven diffusion cooperates with capillarity-driven diffusion, resulting in the formation of precise 2D particle arrays for films within a structure dependent thickness-window. For the dewetting of Au films on the circular hole substrate, the periodic discontinuities in the films, induced by the deposition, can limit the diffusion paths and lead to the formation of one particle per individual separated region (holes or mesas between holes), and thus, result in the evolution of precise 2D particle arrays. The influence of the pre-patterned structures and the film thickness is analyzed and discussed. For both types of pre-patterned substrate, the Au film thickness had to be adjusted in a certain thickness-window in order to achieve the precise 2D particle arrays. PMID:21977445

  12. Complex Pattern Formation from Current-Driven Dynamics of Single-Layer Epitaxial Islands on Crystalline Conducting Substrates

    Science.gov (United States)

    Kumar, Ashish; Dasgupta, Dwaipayan; Maroudas, Dimitrios

    We report a systematic study of complex pattern formation resulting from the driven dynamics of single-layer homoepitaxial islands on face-centered cubic (FCC) crystalline conducting substrate surfaces under the action of an externally applied electric field. The analysis is based on an experimentally validated nonlinear model of mass transport via island edge atomic diffusion, which also accounts for edge diffusional anisotropy. We analyze the morphological stability and simulate the field-driven evolution of rounded islands for an electric field oriented along the fast diffusion direction. For larger than critical island sizes on {110} and {100} FCC substrates, we show that multiple necking instabilities generate complex island patterns, including void-containing islands, mediated by sequences of breakup and coalescence events and distributed symmetrically with respect to the electric field direction. We analyze the dependence of the formed patterns on the original island size and on the duration of application of the external field. Starting from a single large rounded island, we characterize the evolution of the number of daughter islands and their average size and uniformity. The analysis reveals that the pattern formation kinetics follows a universal scaling relation. Division of Materials Sciences & Engineering, Office of Basic Energy Sciences, U.S. Department of Energy (Award No.: DE-FG02-07ER46407).

  13. Spatiotemporal Diffusive Evolution and Fractal Structure of Ground Motion

    Science.gov (United States)

    Suwada, Tsuyoshi

    2018-02-01

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

  14. Indeterminacy and Spatiotemporal Data

    DEFF Research Database (Denmark)

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

    2005-01-01

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

  15. Effects of Nordic walking and walking on spatiotemporal gait parameters and ground reaction force.

    Science.gov (United States)

    Park, Seung Kyu; Yang, Dae Jung; Kang, Yang Hun; Kim, Je Ho; Uhm, Yo Han; Lee, Yong Seon

    2015-09-01

    [Purpose] The purpose of this study was to investigate the effects of Nordic walking and walking on spatiotemporal gait parameters and ground reaction force. [Subjects] The subjects of this study were 30 young adult males, who were divided into a Nordic walking group of 15 subjects and a walking group of 15 subjects. [Methods] To analyze the spatiotemporal parameters and ground reaction force during walking in the two groups, the six-camera Vicon MX motion analysis system was used. The subjects were asked to walk 12 meters using the more comfortable walking method for them between Nordic walking and walking. After they walked 12 meters more than 10 times, their most natural walking patterns were chosen three times and analyzed. To determine the pole for Nordic walking, each subject's height was multiplied by 0.68. We then measured the spatiotemporal gait parameters and ground reaction force. [Results] Compared with the walking group, the Nordic walking group showed an increase in cadence, stride length, and step length, and a decrease in stride time, step time, and vertical ground reaction force. [Conclusion] The results of this study indicate that Nordic walking increases the stride and can be considered as helping patients with diseases affecting their gait. This demonstrates that Nordic walking is more effective in improving functional capabilities by promoting effective energy use and reducing the lower limb load, because the weight of the upper and lower limbs is dispersed during Nordic walking.

  16. SPATIO-TEMPORAL CHARACTERISTICS OF RESIDENT TRIP BASED ON POI AND OD DATA OF FLOAT CAR IN BEIJING

    Directory of Open Access Journals (Sweden)

    N. Mou

    2017-09-01

    Full Text Available Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.. In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method – based on grid density, which is used to cluster the OD (origin and destination data of taxi at different times. Then,combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion – spatial aggregation – spatial relative dispersion" in one day.

  17. Characterization of spatio-temporal patterns for various GRACE- and GLDAS-born estimates for changes of global terrestrial water storage

    Science.gov (United States)

    Yang, Tao; Wang, Chao; Yu, Zhongbo; Xu, Feng

    2013-10-01

    Since the launch in March 2002, the Gravity Recovery and Climate Experiment (GRACE) satellite mission has provided us with a new method to estimate terrestrial water storage (TWS) variations by measuring earth gravity change with unprecedented accuracy. Thus far, a number of standardized GRACE-born TWS products are published by different international research teams. However, no characterization of spatio-temporal patterns for different GRACE hydrology products from the global perspective could be found. It is still a big challenge for the science community to identify the reliable global measurement of TWS anomalies due to our limited knowledge on the true value. Hence, it is urgently necessary to evaluate the uncertainty for various global estimates of the GRACE-born TWS changes by a number of international research organizations. Toward this end, this article presents an in-depth analysis for various GRACE-born and GLDAS-based estimates for changes of global terrestrial water storage. The work characterizes the inter-annual and intra-annual variability, probability density variations, and spatial patterns among different GRACE-born TWS estimates over six major continents, and compares them with results from GLDAS simulations. The underlying causes of inconsistency between GRACE- and GLDAS-born TWS estimates are thoroughly analyzed with an aim to improve our current knowledge in monitoring global TWS change. With a comprehensive consideration of the advantages and disadvantages among GRACE- and GLDAS-born TWS anomalies, a summary is thereafter recommended as a rapid reference for scientists, end-users, and policy-makers in the practices of global TWS change research. To our best knowledge, this work is the first attempt to characterize difference and uncertainty among various GRACE-born terrestrial water storage changes over the major continents estimated by a number of international research organizations. The results can provide beneficial reference to usage of

  18. Spatio-temporal analysis of blood perfusion by imaging photoplethysmography

    Science.gov (United States)

    Zaunseder, Sebastian; Trumpp, Alexander; Ernst, Hannes; Förster, Michael; Malberg, Hagen

    2018-02-01

    Imaging photoplethysmography (iPPG) has attracted much attention over the last years. The vast majority of works focuses on methods to reliably extract the heart rate from videos. Only a few works addressed iPPGs ability to exploit spatio-temporal perfusion pattern to derive further diagnostic statements. This work directs at the spatio-temporal analysis of blood perfusion from videos. We present a novel algorithm that bases on the two-dimensional representation of the blood pulsation (perfusion map). The basic idea behind the proposed algorithm consists of a pairwise estimation of time delays between photoplethysmographic signals of spatially separated regions. The probabilistic approach yields a parameter denoted as perfusion speed. We compare the perfusion speed versus two parameters, which assess the strength of blood pulsation (perfusion strength and signal to noise ratio). Preliminary results using video data with different physiological stimuli (cold pressure test, cold face test) show that all measures are influenced by those stimuli (some of them with statistical certainty). The perfusion speed turned out to be more sensitive than the other measures in some cases. However, our results also show that the intraindividual stability and interindividual comparability of all used measures remain critical points. This work proves the general feasibility of employing the perfusion speed as novel iPPG quantity. Future studies will address open points like the handling of ballistocardiographic effects and will try to deepen the understanding of the predominant physiological mechanisms and their relation to the algorithmic performance.

  19. The physics of pattern formation at liquid interface: Progress report, June 1, 1988--May 31, 1989

    International Nuclear Information System (INIS)

    Maher, J.V.

    1989-06-01

    This paper describes pattern formation at liquid interfaces. Results shed light on questions which underlie the theory of solidification. Also reviewed are random system issues of wetting of curved surfaces and fluctuations in swollen polymeric gel

  20. A new method for discovering behavior patterns among animal movements

    Science.gov (United States)

    Wang, Y.; Luo, Ze; Takekawa, John Y.; Prosser, Diann J.; Xiong, Y.; Newman, S.; Xiao, X.; Batbayar, N.; Spragens, Kyle A.; Balachandran, S.; Yan, B.

    2016-01-01

    Advanced satellite tracking technologies enable biologists to track animal movements at fine spatial and temporal scales. The resultant data present opportunities and challenges for understanding animal behavioral mechanisms. In this paper, we develop a new method to elucidate animal movement patterns from tracking data. Here, we propose the notion of continuous behavior patterns as a concise representation of popular migration routes and underlying sequential behaviors during migration. Each stage in the pattern is characterized in terms of space (i.e., the places traversed during movements) and time (i.e. the time spent in those places); that is, the behavioral state corresponding to a stage is inferred according to the spatiotemporal and sequential context. Hence, the pattern may be interpreted predictably. We develop a candidate generation and refinement framework to derive all continuous behavior patterns from raw trajectories. In the framework, we first define the representative spots to denote the underlying potential behavioral states that are extracted from individual trajectories according to the similarity of relaxed continuous locations in certain distinct time intervals. We determine the common behaviors of multiple individuals according to the spatiotemporal proximity of representative spots and apply a projection-based extension approach to generate candidate sequential behavior sequences as candidate patterns. Finally, the candidate generation procedure is combined with a refinement procedure to derive continuous behavior patterns. We apply an ordered processing strategy to accelerate candidate refinement. The proposed patterns and discovery framework are evaluated through conceptual experiments on both real GPS-tracking and large synthetic datasets.