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
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
Spatiotemporal chaos involving wave instability.
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.
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
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
Spatio-temporal patterns in simple models of marine systems
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.
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
Control of Spiral Waves and Spatiotemporal Chaos by Exciting Travel Wave Trains
International Nuclear Information System (INIS)
Yuan Guoyong; Wang Guangrui; Chen Shigang
2005-01-01
Spiral waves and spatiotemporal chaos usually are harmful and need to be suppressed. In this paper, a method is proposed to control them. Travel wave trains can be generated by periodic excitations near left boundary, spiral waves and spatiotemporal chaos can be eliminated by the trains for some certain excitation periods. Obvious resonant behavior can be observed from the relation between the periods of the trains and excitation ones. The method is against noise.
Spatiotemporal chaos and two-dimensional dissipative rogue waves in Lugiato-Lefever model
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.
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)
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
Spatio-temporal scaling effects on longshore sediment transport pattern along the nearshore zone
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.
Nonlinear waves and pattern dynamics
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...
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.
Spatio-temporal databases complex motion pattern queries
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
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
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.
Estimating repetitive spatiotemporal patterns from resting-state brain activity data.
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.
Lateral Membrane Waves Constitute a Universal Dynamic Pattern of Motile Cells
Döbereiner, Hans-Günther; Dubin-Thaler, Benjamin J.; Hofman, Jake M.; Xenias, Harry S.; Sims, Tasha N.; Giannone, Grégory; Dustin, Michael L.; Wiggins, Chris H.; Sheetz, Michael P.
2006-07-01
We have monitored active movements of the cell circumference on specifically coated substrates for a variety of cells including mouse embryonic fibroblasts and T cells, as well as wing disk cells from fruit flies. Despite having different functions and being from multiple phyla, these cell types share a common spatiotemporal pattern in their normal membrane velocity; we show that protrusion and retraction events are organized in lateral waves along the cell membrane. These wave patterns indicate both spatial and temporal long-range periodic correlations of the actomyosin gel.
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.
Spatiotemporal Stochastic Resonance:Theory and Experiment
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
An evaluation of space time cube representation of spatiotemporal patterns.
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.
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...
A review and guidance for pattern selection in spatiotemporal system
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.
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.
Dynamical Properties of Transient Spatio-Temporal Patterns in Bacterial Colony of Proteus mirabilis
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.
Spatiotemporal synchronization of drift waves in a magnetron sputtering plasma
Czech Academy of Sciences Publication Activity Database
Martines, E.; Zuin, M.; Cavazzana, R.; Adámek, Jiří; Antoni, V.; Serianni, G.; Spolaore, M.; Vianello, N.
2014-01-01
Roč. 21, č. 10 (2014), s. 102309-102309 ISSN 1070-664X Institutional support: RVO:61389021 Keywords : Drift waves * Magnetron sputtering plasma * Spatiotemporal synchronization Subject RIV: BL - Plasma and Gas Discharge Physics Impact factor: 2.142, year: 2014 http://dx.doi.org/10.1063/1.4898693
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.
Spatiotemporal Visualization of Tsunami Waves Using Kml on Google Earth
Mohammadi, H.; Delavar, M. R.; Sharifi, M. A.; Pirooz, M. D.
2017-09-01
Disaster risk is a function of hazard and vulnerability. Risk is defined as the expected losses, including lives, personal injuries, property damages, and economic disruptions, due to a particular hazard for a given area and time period. Risk assessment is one of the key elements of a natural disaster management strategy as it allows for better disaster mitigation and preparation. It provides input for informed decision making, and increases risk awareness among decision makers and other stakeholders. Virtual globes such as Google Earth can be used as a visualization tool. Proper spatiotemporal graphical representations of the concerned risk significantly reduces the amount of effort to visualize the impact of the risk and improves the efficiency of the decision-making process to mitigate the impact of the risk. The spatiotemporal visualization of tsunami waves for disaster management process is an attractive topic in geosciences to assist investigation of areas at tsunami risk. In this paper, a method for coupling virtual globes with tsunami wave arrival time models is presented. In this process we have shown 2D+Time of tsunami waves for propagation and inundation of tsunami waves, both coastal line deformation, and the flooded areas. In addition, the worst case scenario of tsunami on Chabahar port derived from tsunami modelling is also presented using KML on google earth.
Discovery of spatio-temporal patterns from location-based social networks
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.
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 peopleâs 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
Nonlinear Waves on Stochastic Support: Calcium Waves in Astrocyte Syncytia
Jung, P.; Cornell-Bell, A. H.
Astrocyte-signaling has been observed in cell cultures and brain slices in the form of Calcium waves. Their functional relevance for neuronal communication, brain functions and diseases is, however, not understood. In this paper, the propagation of intercellular calcium waves is modeled in terms of waves in excitable media on a stochastic support. We utilize a novel method to decompose the spatiotemporal patterns into space-time clusters (wave fragments). Based on this cluster decomposition, a statistical description of wave patterns is developed.
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
Spatiotemporal throughfall patterns beneath an urban tree row
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.
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.
Spatiotemporal Patterns in a Ratio-Dependent Food Chain Model with Reaction-Diffusion
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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.
Precursor of transition to turbulence: spatiotemporal wave front.
Bhaumik, S; Sengupta, T K
2014-04-01
To understand transition to turbulence via 3D disturbance growth, we report here results obtained from the solution of Navier-Stokes equation (NSE) to reproduce experimental results obtained by minimizing background disturbances and imposing deterministic excitation inside the shear layer. A similar approach was adopted in Sengupta and Bhaumik [Phys. Rev. Lett. 107, 154501 (2011)], where a route of transition from receptivity to fully developed turbulent stage was explained for 2D flow in terms of the spatio-temporal wave-front (STWF). The STWF was identified as the unit process of 2D turbulence creation for low amplitude wall excitation. Theoretical prediction of STWF for boundary layer was established earlier in Sengupta, Rao, and Venkatasubbaiah [Phys. Rev. Lett. 96, 224504 (2006)] from the Orr-Sommerfeld equation as due to spatiotemporal instability. Here, the same unit process of the STWF during transition is shown to be present for 3D disturbance field from the solution of governing NSE.
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.
Spatiotemporal representation of cardiac vectorcardiogram (VCG signals
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Yang Hui
2012-03-01
Full Text Available Abstract Background Vectorcardiogram (VCG signals monitor both spatial and temporal cardiac electrical activities along three orthogonal planes of the body. However, the absence of spatiotemporal resolution in conventional VCG representations is a major impediment for medical interpretation and clinical usage of VCG. This is especially so because time-domain features of 12-lead ECG, instead of both spatial and temporal characteristics of VCG, are widely used for the automatic assessment of cardiac pathological patterns. Materials and methods We present a novel representation approach that captures critical spatiotemporal heart dynamics by displaying the real time motion of VCG cardiac vectors in a 3D space. Such a dynamic display can also be realized with only one lead ECG signal (e.g., ambulatory ECG through an alternative lag-reconstructed ECG representation from nonlinear dynamics principles. Furthermore, the trajectories are color coded with additional dynamical properties of space-time VCG signals, e.g., the curvature, speed, octant and phase angles to enhance the information visibility. Results In this investigation, spatiotemporal VCG signal representation is used to characterize various spatiotemporal pathological patterns for healthy control (HC, myocardial infarction (MI, atrial fibrillation (AF and bundle branch block (BBB. The proposed color coding scheme revealed that the spatial locations of the peak of T waves are in the Octant 6 for the majority (i.e., 74 out of 80 of healthy recordings in the PhysioNet PTB database. In contrast, the peak of T waves from 31.79% (117/368 of MI subjects are found to remain in Octant 6 and the rest (68.21% spread over all other octants. The spatiotemporal VCG signal representation is shown to capture the same important heart characteristics as the 12-lead ECG plots and more. Conclusions Spatiotemporal VCG signal representation is shown to facilitate the characterization of space-time cardiac
Mining Spatiotemporal Patterns of the Elder's Daily Movement
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.
Exploring Spatiotemporal Patterns of Long-Distance Taxi Rides in Shanghai
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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.
Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs.
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.
Spatio-Temporal Patterns in Colonies of Rod-Shaped Bacteria
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.
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.
Spatiotemporal distribution patterns of forest fires in northern Mexico
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...
Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics Approach
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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.
Routes to spatiotemporal chaos in Kerr optical frequency combs.
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.
Chaos induced by breakup of waves in a spatial epidemic model with nonlinear incidence rate
International Nuclear Information System (INIS)
Sun, Gui-Quan; Jin, Zhen; Liu, Quan-Xing; Li, Li
2008-01-01
Spatial epidemiology is the study of spatial variation in disease risk or incidence, including the spatial patterns of the population. The spread of diseases in human populations can exhibit large scale patterns, underlining the need for spatially explicit approaches. In this paper, the spatiotemporal complexity of a spatial epidemic model with nonlinear incidence rate, which includes the behavioral changes and crowding effect of the infective individuals, is investigated. Based on both theoretical analysis and computer simulations, we find out when, under the parameters which can guarantee a stable limit cycle in the non-spatial model, spiral and target waves can emerge. Moreover, two different kinds of breakup of waves are shown. Specifically, the breakup of spiral waves is from the core and the breakup of target waves is from the far-field, and both kinds of waves become irregular patterns at last. Our results reveal that the spatiotemporal chaos is induced by the breakup of waves. The results obtained confirm that diffusion can form spiral waves, target waves or spatial chaos of high population density, which enrich the findings of spatiotemporal dynamics in the epidemic model
Spatiotemporal Data Mining: A Computational Perspective
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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.
Attarzadeh, M. A.; Nouh, M.
2018-05-01
One-dimensional phononic materials with material fields traveling simultaneously in space and time have been shown to break elastodynamic reciprocity resulting in unique wave propagation features. In the present work, a comprehensive mathematical analysis is presented to characterize and fully predict the non-reciprocal wave dispersion in two-dimensional space. The analytical dispersion relations, in the presence of the spatiotemporal material variations, are validated numerically using finite 2D membranes with a prescribed number of cells. Using omnidirectional excitations at the membrane's center, wave propagations are shown to exhibit directional asymmetry that increases drastically in the direction of the material travel and vanishes in the direction perpendicular to it. The topological nature of the predicted dispersion in different propagation directions are evaluated using the computed Chern numbers. Finally, the degree of the 2D non-reciprocity is quantified using a non-reciprocity index (NRI) which confirms the theoretical dispersion predictions as well as the finite simulations. The presented framework can be extended to plate-type structures as well as 3D spatiotemporally modulated phononic crystals.
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.
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.
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.
Competition and Dispersal in Predator-Prey Waves
Savill, N.J.; Hogeweg, P.
1998-01-01
Dispersing predators and prey can exhibit complex spatio-temporal wave-like patterns if the interactions between them cause oscillatory dynamics. We study the effect of these predator- prey density waves on the competition between prey populations and between predator popu- lations with different
Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia
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
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.
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.
Wang, Pinya; Tang, Jianping; Sun, Xuguang; Liu, Jianyong; Juan, Fang
2018-03-01
Using the Weather Research and Forecasting (WRF) model, this paper analyzes the spatiotemporal features of heat waves in 20-year regional climate simulations over East Asia, and investigates the capability of WRF to reproduce observational heat waves in China. Within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX), the WRF model is driven by the ERA-Interim (ERAIN) reanalysis, and five continuous simulations are conducted from 1989 to 2008. Of these, four runs apply the interior spectral nudging (SN) technique with different wavenumbers, nudging variables and nudging coefficients. Model validations show that WRF can reasonably reproduce the spatiotemporal features of heat waves in China. Compared with the experiment without SN, the application of SN is effectie on improving the skill of the model in simulating both the spatial distributions and temporal variations of heat waves of different intensities. The WRF model shows advantages in reproducing the synoptic circulations with SN and therefore yields better representations for heat wave events. Besides, the SN method is able to preserve the variability of large-scale circulations quite well, which in turn adjusts the extreme temperature variability towards the observation. Among the four SN experiments, those with stronger nudging coefficients perform better in modulating both the spatial and temporal features of heat waves. In contrast, smaller nudging coefficients weaken the effects of SN on improving WRF's performances.
Simple models for studying complex spatiotemporal patterns of animal behavior
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.
Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium.
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.
Changing and Differentiated Urban Landscape in China: Spatiotemporal Patterns and Driving Forces.
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.
Spatiotemporal multiple coherence resonances and calcium waves in a coupled hepatocyte system
International Nuclear Information System (INIS)
Bao-Hua, Wang; Qi-Shao, Lu; Shu-Juan, Lü; Xiu-Feng, Lang
2009-01-01
Spatiotemporal multiple coherence resonances for calcium activities induced by weak Gaussian white noise in coupled hepatocytes are studied. It is shown that bi-resonances in hepatocytes are induced by the interplay and competition between noise and coupling of cells, in other words, the cell in network can be excited either by noise or by its neighbour via gap junction which can transfer calcium ions between cells. Furthermore, the intercellular annular calcium waves induced by noise are observed, in which the wave length decreases with noise intensity augmenting but increases monotonically with coupling strength increasing. And for a fixed noise level, there is an optimal coupling strength that makes the coherence resonance reach maximum. (general)
The influence of long-range links on spiral waves and their application for control
International Nuclear Information System (INIS)
Qian Yu
2012-01-01
The influence of long-range links on spiral waves in an excitable medium has been investigated. Spatiotemporal dynamics in an excitable small-world network transform remarkably when we increase the long-range connection probability P. Spiral waves with few perturbations, broken spiral waves, pseudo spiral turbulence, synchronous oscillations, and homogeneous rest state are discovered under different network structures. Tip number is selected to detect non-equilibrium phase transition between different spatiotemporal patterns. The Kuramoto order parameter is used to identify these patterns and explain the emergence of the rest state. Finally, we use long-range links to successfully control spiral waves and spiral turbulence. (interdisciplinary physics and related areas of science and technology)
Spatiotemporal Propagation of the Cortical Atrophy: Population and Individual Patterns
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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
Soil Moisture Retrieval and Spatiotemporal Pattern Analysis Using Sentinel-1 Data of Dahra, Senegal
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Zhiqu Liu
2017-11-01
Full Text Available The spatiotemporal pattern of soil moisture is of great significance for the understanding of the water exchange between the land surface and the atmosphere. The two-satellite constellation of the Sentinel-1 mission provides C-band synthetic aperture radar (SAR observations with high spatial and temporal resolutions, which are suitable for soil moisture monitoring. In this paper, we aim to assess the capability of pattern analysis based on the soil moisture retrieved from Sentinel-1 time-series data of Dahra in Senegal. The look-up table (LUT method is used in the retrieval with the backscattering coefficients that are simulated by the advanced integrated equation Model (AIEM for the soil layer and the Michigan microwave canopy scattering (MIMICS model for the vegetation layer. The temporal trend of Sentinel-1A soil moisture is evaluated by the ground measurements from the site at Dahra, with an unbiased root-mean-squared deviation (ubRMSD of 0.053 m3/m3, a mean average deviation (MAD of 0.034 m3/m3, and an R value of 0.62. The spatial variation is also compared with the existing microwave products at a coarse scale, which confirms the reliability of the Sentinel-1A soil moisture. The spatiotemporal patterns are analyzed by empirical orthogonal functions (EOF, and the geophysical factors that are affecting soil moisture are discussed. The first four EOFs of soil moisture explain 77.2% of the variance in total and the primary EOF explains 66.2%, which shows the dominant pattern at the study site. Soil texture and the normalized difference vegetation index are more closely correlated with the primary pattern than the topography and temperature in the study area. The investigation confirms the potential for soil moisture retrieval and spatiotemporal pattern analysis using Sentinel-1 images.
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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
Training spiking neural networks to associate spatio-temporal input-output spike patterns
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...
Patterns of urban violent injury: a spatio-temporal analysis.
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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.
A modified consumer inkjet for spatiotemporal control of gene expression.
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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.
Phase Defects as a Measure of Disorder in Traveling-Wave Convection
International Nuclear Information System (INIS)
La Porta, A.; Surko, C.M.
1996-01-01
Spatiotemporal disorder is studied in traveling-wave convection in an ethanol-water mixture. A technique for calculating the complex order parameter of the pattern is described, and the identification of phase defects is demonstrated. Point defects, domain boundaries, and standing wave patterns are shown to produce unique defect structures. The transition from a disordered state to a more ordered pattern is described in terms of the dynamics of defects and their statistics. copyright 1996 The American Physical Society
Bhaumik, Swagata; Sengupta, Tapan K.
2017-12-01
Here, we present the impulse response of the canonical zero pressure gradient boundary layer from the dynamical system approach. The fundamental physical mechanism of the impulse response is in creation of a spatio-temporal wave-front (STWF) by a localized, time-impulsive wall excitation of the boundary layer. The present research is undertaken to explain the unit process of diverse phenomena in geophysical fluid flows and basic hydrodynamics. Creation of a tsunami has been attributed to localized events in the ocean-bed caused by earthquakes, landslides, or volcanic eruptions, whose manifestation is in the run up to the coast by surface waves of massive amplitude but of very finite fetch. Similarly rogue waves have often been noted; a coherent account of the same is yet to appear, although some explanations have been proposed. Our studies in both two- and three-dimensional frameworks in Sengupta and Bhaumik ["Onset of turbulence from the receptivity stage of fluid flows," Phys. Rev. Lett. 107(15), 154501 (2011)] and Bhaumik and Sengupta ["Precursor of transition to turbulence: Spatiotemporal wave front," Phys. Rev. E 89(4), 043018 (2014)] have shown that the STWF provides the central role for causing transition to turbulence by reproducing carefully conducted transition experiments. Here, we furthermore relax the condition of time behavior and use a Dirac-delta wall excitation for the impulse response. The present approach is not based on any simplification of the governing Navier-Stokes equation (NSE), which is unlike solving a nonlinear shallow water equation and/or nonlinear Schrödinger equation. The full nonlinear Navier-Stokes equation (NSE) is solved here using high accuracy dispersion relation preserving numerical schemes and using appropriate formulation of the NSE which minimizes error. The adopted numerical methods and formulation have been extensively validated with respect to various external and internal 2D and 3D flow problems. We also present
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
Nonlinear pattern formation of Faraday waves
Binks, D.J.; Water, van de W.
1997-01-01
A cascade of surface wave patterns with increasing rotational symmetry ranging from simple square to tenfold quasiperiodic is observed for Faraday waves. The experiment concerns the excitation of subharmonic standing surface waves by oscillating vertical acceleration. Our observation agrees with the
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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.
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.
Neural avalanches at the critical point between replay and non-replay of spatiotemporal patterns.
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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.
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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.
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.
Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.
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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.
Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.
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.
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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.
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.
Standing and travelling waves in a spherical brain model: The Nunez model revisited
Visser, S.; Nicks, R.; Faugeras, O.; Coombes, S.
2017-06-01
The Nunez model for the generation of electroencephalogram (EEG) signals is naturally described as a neural field model on a sphere with space-dependent delays. For simplicity, dynamical realisations of this model either as a damped wave equation or an integro-differential equation, have typically been studied in idealised one dimensional or planar settings. Here we revisit the original Nunez model to specifically address the role of spherical topology on spatio-temporal pattern generation. We do this using a mixture of Turing instability analysis, symmetric bifurcation theory, centre manifold reduction and direct simulations with a bespoke numerical scheme. In particular we examine standing and travelling wave solutions using normal form computation of primary and secondary bifurcations from a steady state. Interestingly, we observe spatio-temporal patterns which have counterparts seen in the EEG patterns of both epileptic and schizophrenic brain conditions.
Spatiotemporal Patterns of Urbanization in a Developed Region of Eastern Coastal China
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...
Origin choice and petal loss in the flower garden of spiral wave tip trajectories
Gray, Richard A.; Wikswo, John P.; Otani, Niels F.
2009-01-01
Rotating spiral waves have been observed in numerous biological and physical systems. These spiral waves can be stationary, meander, or even degenerate into multiple unstable rotating waves. The spatiotemporal behavior of spiral waves has been extensively quantified by tracking spiral wave tip trajectories. However, the precise methodology of identifying the spiral wave tip and its influence on the specific patterns of behavior remains a largely unexplored topic of research. Here we use a two...
Probability of US Heat Waves Affected by a Subseasonal Planetary Wave Pattern
Teng, Haiyan; Branstator, Grant; Wang, Hailan; Meehl, Gerald A.; Washington, Warren M.
2013-01-01
Heat waves are thought to result from subseasonal atmospheric variability. Atmospheric phenomena driven by tropical convection, such as the Asian monsoon, have been considered potential sources of predictability on subseasonal timescales. Mid-latitude atmospheric dynamics have been considered too chaotic to allow significant prediction skill of lead times beyond the typical 10-day range of weather forecasts. Here we use a 12,000-year integration of an atmospheric general circulation model to identify a pattern of subseasonal atmospheric variability that can help improve forecast skill for heat waves in the United States. We find that heat waves tend to be preceded by 15-20 days by a pattern of anomalous atmospheric planetary waves with a wavenumber of 5. This circulation pattern can arise as a result of internal atmospheric dynamics and is not necessarily linked to tropical heating.We conclude that some mid-latitude circulation anomalies that increase the probability of heat waves are predictable beyond the typical weather forecast range.
Transition to turbulence via spatiotemporal intermittency in stimulated Raman backscattering
International Nuclear Information System (INIS)
Skoric, M.M.; Jovanovic, M.S.; Rajkovic, M.R.
1996-01-01
The spatiotemporal evolution of stimulated Raman backscattering in a bounded, uniform, weakly dissipative plasma is studied. The nonlinear model of a three-wave interaction involves a quadratic coupling of slowly varying complex amplitudes of the laser pump, the backscattered and the electron plasma wave. The corresponding set of coupled partial differential equations with nonlinear phase detuning that is taken into account is solved numerically in space time with fixed nonzero source boundary conditions. The study of the above open, convective, weakly confined system reveals a quasiperiodic transition to spatiotemporal chaos via spatiotemporal intermittency. In the analysis of transitions a dual scheme borrowed from fields of nonlinear dynamics and statistical physics is applied. An introduction of a nonlinear three-wave interaction to a growing family of paradigmatic equations which exhibit a route to turbulence via spatiotemporal intermittency is outlined in this work. copyright 1996 The American Physical Society
Spatial and spatiotemporal pattern analysis of coconut lethal yellowing in Mozambique.
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.
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.
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...
Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks.
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.
Origin choice and petal loss in the flower garden of spiral wave tip trajectories.
Gray, Richard A; Wikswo, John P; Otani, Niels F
2009-09-01
Rotating spiral waves have been observed in numerous biological and physical systems. These spiral waves can be stationary, meander, or even degenerate into multiple unstable rotating waves. The spatiotemporal behavior of spiral waves has been extensively quantified by tracking spiral wave tip trajectories. However, the precise methodology of identifying the spiral wave tip and its influence on the specific patterns of behavior remains a largely unexplored topic of research. Here we use a two-state variable FitzHugh-Nagumo model to simulate stationary and meandering spiral waves and examine the spatiotemporal representation of the system's state variables in both the real (i.e., physical) and state spaces. We show that mapping between these two spaces provides a method to demarcate the spiral wave tip as the center of rotation of the solution to the underlying nonlinear partial differential equations. This approach leads to the simplest tip trajectories by eliminating portions resulting from the rotational component of the spiral wave.
Writing magnetic patterns with surface acoustic waves
Energy Technology Data Exchange (ETDEWEB)
Li, Weiyang; Buford, Benjamin; Jander, Albrecht; Dhagat, Pallavi, E-mail: dhagat@eecs.oregonstate.edu [School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, Oregon 97331 (United States)
2014-05-07
A novel patterning technique that creates magnetization patterns in a continuous magnetostrictive film with surface acoustic waves is demonstrated. Patterns of 10 μm wide stripes of alternating magnetization and a 3 μm dot of reversed magnetization are written using standing and focusing acoustic waves, respectively. The magnetization pattern is size-tunable, erasable, and rewritable by changing the magnetic field and acoustic power. This versatility, along with its solid-state implementation (no moving parts) and electronic control, renders it as a promising technique for application in magnetic recording, magnonic signal processing, magnetic particle manipulation, and spatial magneto-optical modulation.
Spatiotemporal Modeling of Community Risk
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
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.
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.
Multiscale recurrence analysis of spatio-temporal data
Riedl, M.; Marwan, N.; Kurths, J.
2015-12-01
The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.
Spatio-temporal 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
Sporadic wind wave horse-shoe patterns
Directory of Open Access Journals (Sweden)
S. Yu. Annenkov
1999-01-01
Full Text Available The work considers three-dimensional crescent-shaped patterns often seen on water surface in natural basins and observed in wave tank experiments. The most common of these 'horse-shoe-like' patterns appear to be sporadic, i.e., emerging and disappearing spontaneously even under steady wind conditions. The paper suggests a qualitative model of these structures aimed at explaining their sporadic nature, physical mechanisms of their selection and their specific asymmetric form. First, the phenomenon of sporadic horse-shoe patterns is studied numerically using the novel algorithm of water waves simulation recently developed by the authors (Annenkov and Shrira, 1999. The simulations show that a steep gravity wave embedded into widespectrum primordial noise and subjected to small nonconservative effects typically follows the simple evolution scenario: most of the time the system can be considered as consisting of a basic wave and a single pair of oblique satellites, although the choice of this pair tends to be different at different instants. Despite the effective low-dimensionality of the multimodal system dynamics at relatively sho ' rt time spans, the role of small satellites is important: in particular, they enlarge the maxima of the developed satellites. The presence of Benjamin-Feir satellites appears to be of no qualitative importance at the timescales under consideration. The selection mechanism has been linked to the quartic resonant interactions among the oblique satellites lying in the domain of five-wave (McLean's class II instability of the basic wave: the satellites tend to push each other out of the resonance zone due to the frequency shifts caused by the quartic interactions. Since the instability domain is narrow (of order of cube of the basic wave steepness, eventually in a generic situation only a single pair survives and attains considerable amplitude. The specific front asymmetry is found to result from the interplay of quartic
Investigation of Spatiotemporal Pattern of Drought in North Korea Using Remote Sensing and GIS
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.
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)
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.
Harbour porpoise distribution can vary at small spatiotemporal scales in energetic habitats
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
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.
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.
Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks
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.
A spatiotemporal analysis of hydrological patterns based on a wireless sensor network system
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).
Stability of nonlinear waves and patterns and related topics
Ghazaryan, Anna; Lafortune, Stephane; Manukian, Vahagn
2018-04-01
Periodic and localized travelling waves such as wave trains, pulses, fronts and patterns of more complex structure often occur in natural and experimentally built systems. In mathematics, these objects are realized as solutions of nonlinear partial differential equations. The existence, dynamic properties and bifurcations of those solutions are of interest. In particular, their stability is important for applications, as the waves that are observable are usually stable. When the waves are unstable, further investigation is warranted of the way the instability is exhibited, i.e. the nature of the instability, and also coherent structures that appear as a result of an instability of travelling waves. A variety of analytical, numerical and hybrid techniques are used to study travelling waves and their properties. This article is part of the theme issue `Stability of nonlinear waves and patterns and related topics'.
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)
DEFF Research Database (Denmark)
Thomsen, Jon Juel; Blekhman, Iliya I.
2007-01-01
What are the effective properties of a generally nonlinear material or structure, whose local properties are modulated in both space and time? It has been suggested to use spatiotemporal modulation of structural properties to create materials and structures with adjustable effective properties......, and to call these dynamic materials or spatiotemporal composites. Also, according to theoretical predictions, structural nonlinearity enhances the possibilities of achieving specific effective properties. For example, with an elastic rod having cubical elastic nonlinearities, it seems possible to control......, and exemplified. Then simple approximate analytical expressions are derived for the effective wave speed and natural frequencies for one-dimensional wave propagation in a nonlinear elastic rod, where the spatiotemporal modulation is imposed as a high-frequency standing wave, supposed to be given. Finally the more...
Comparison of Spatiotemporal Mapping Techniques for Enormous Etl and Exploitation Patterns
Deiotte, R.; La Valley, R.
2017-10-01
The need to extract, transform, and exploit enormous volumes of spatiotemporal data has exploded with the rise of social media, advanced military sensors, wearables, automotive tracking, etc. However, current methods of spatiotemporal encoding and exploitation simultaneously limit the use of that information and increase computing complexity. Current spatiotemporal encoding methods from Niemeyer and Usher rely on a Z-order space filling curve, a relative of Peano's 1890 space filling curve, for spatial hashing and interleaving temporal hashes to generate a spatiotemporal encoding. However, there exist other space-filling curves, and that provide different manifold coverings that could promote better hashing techniques for spatial data and have the potential to map spatiotemporal data without interleaving. The concatenation of Niemeyer's and Usher's techniques provide a highly efficient space-time index. However, other methods have advantages and disadvantages regarding computational cost, efficiency, and utility. This paper explores the several methods using a range of sizes of data sets from 1K to 10M observations and provides a comparison of the methods.
COMPARISON OF SPATIOTEMPORAL MAPPING TECHNIQUES FOR ENORMOUS ETL AND EXPLOITATION PATTERNS
Directory of Open Access Journals (Sweden)
R. Deiotte
2017-10-01
Full Text Available The need to extract, transform, and exploit enormous volumes of spatiotemporal data has exploded with the rise of social media, advanced military sensors, wearables, automotive tracking, etc. However, current methods of spatiotemporal encoding and exploitation simultaneously limit the use of that information and increase computing complexity. Current spatiotemporal encoding methods from Niemeyer and Usher rely on a Z-order space filling curve, a relative of Peano’s 1890 space filling curve, for spatial hashing and interleaving temporal hashes to generate a spatiotemporal encoding. However, there exist other space-filling curves, and that provide different manifold coverings that could promote better hashing techniques for spatial data and have the potential to map spatiotemporal data without interleaving. The concatenation of Niemeyer’s and Usher’s techniques provide a highly efficient space-time index. However, other methods have advantages and disadvantages regarding computational cost, efficiency, and utility. This paper explores the several methods using a range of sizes of data sets from 1K to 10M observations and provides a comparison of the methods.
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
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.
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)
Spatiotemporal exploratory models for broad-scale survey data.
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).
Coherent patterning of matter waves with subwavelength localization
International Nuclear Information System (INIS)
Mompart, J.; Ahufinger, V.; Birkl, G.
2009-01-01
We propose the subwavelength localization via adiabatic passage (SLAP) technique to coherently achieve state-selective patterning of matter waves well beyond the diffraction limit. The SLAP technique consists in coupling two partially overlapping and spatially structured laser fields to three internal levels of the matter wave yielding state-selective localization at those positions where the adiabatic passage process does not occur. We show that by means of this technique matter wave localization down to the single nanometer scale can be achieved. We analyze in detail the potential implementation of the SLAP technique for nanolithography with an atomic beam of metastable Ne* and for coherent patterning of a two-component 87 Rb Bose-Einstein condensate.
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.
Cerebral functional connectivity and Mayer waves in mice: Phenomena and separability.
Bumstead, Jonathan R; Bauer, Adam Q; Wright, Patrick W; Culver, Joseph P
2017-02-01
Resting-state functional connectivity is a growing neuroimaging approach that analyses the spatiotemporal structure of spontaneous brain activity, often using low-frequency (Mayer waves. Despite how close in frequency these phenomena exist, there is little research on how vasomotion and Mayer waves are related to or affect resting-state functional connectivity. In this study, we analyze spontaneous hemodynamic fluctuations over the mouse cortex using optical intrinsic signal imaging. We found spontaneous occurrence of oscillatory hemodynamics ∼0.2 Hz consistent with the properties of Mayer waves reported in the literature. Across a group of mice (n = 19), there was a large variability in the magnitude of Mayer waves. However, regardless of the magnitude of Mayer waves, functional connectivity patterns could be recovered from hemodynamic signals when filtered to the lower frequency band, 0.01-0.08 Hz. Our results demonstrate that both Mayer waves and resting-state functional connectivity patterns can co-exist simultaneously, and that they can be separated by applying bandpass filters.
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...
Defects and spatiotemporal disorder in a pattern of falling liquid columns
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.
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.
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.
Mweu, Marshal M; Nielsen, Søren S; Halasa, Tariq; Toft, Nils
2014-02-01
Several decades after the inception of the five-point plan for the control of contagious mastitis pathogens, Streptococcus agalactiae (S. agalactiae) persists as a fundamental threat to the dairy industry in many countries. A better understanding of the relative importance of within- and between-herd sources of new herd infections coupled with the spatiotemporal distribution of the infection, may aid in effective targeting of control efforts. Thus, the objectives of this study were: (1) to describe the spatiotemporal patterns of infection with S. agalactiae in the population of Danish dairy herds from 2000 to 2009 and (2) to estimate the annual herd-level baseline and movement-related incidence risks of S. agalactiae infection over the 10-year period. The analysis involved registry data on bacteriological culture of all bulk tank milk samples collected as part of the mandatory Danish S. agalactiae surveillance scheme as well as live cattle movements into dairy herds during the specified 10-year period. The results indicated that the predicted risk of a herd becoming infected with S. agalactiae varied spatiotemporally; the risk being more homogeneous and higher in the period after 2005. Additionally, the annual baseline risks yielded significant yet distinctive patterns before and after 2005 - the risk of infection being higher in the latter phase. On the contrary, the annual movement-related risks revealed a non-significant pattern over the 10-year period. There was neither evidence for spatial clustering of cases relative to the population of herds at risk nor spatial dependency between herds. Nevertheless, the results signal a need to beef up within-herd biosecurity in order to reduce the risk of new herd infections. Copyright © 2013 Elsevier B.V. All rights reserved.
Spatio-temporal 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....
SPAN: spike pattern association neuron for learning spatio-temporal sequences
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...
Spatiotemporal behavior and nonlinear dynamics in a phase conjugate resonator
Liu, Siuying Raymond
1993-01-01
The work described can be divided into two parts. The first part is an investigation of the transient behavior and stability property of a phase conjugate resonator (PCR) below threshold. The second part is an experimental and theoretical study of the PCR's spatiotemporal dynamics above threshold. The time-dependent coupled wave equations for four-wave mixing (FWM) in a photorefractive crystal, with two distinct interaction regions caused by feedback from an ordinary mirror, was used to model the transient dynamics of a PCR below threshold. The conditions for self-oscillation were determined and the solutions were used to define the PCR's transfer function and analyze its stability. Experimental results for the buildup and decay times confirmed qualitatively the predicted behavior. Experiments were carried out above threshold to study the spatiotemporal dynamics of the PCR as a function of Pragg detuning and the resonator's Fresnel number. The existence of optical vortices in the wavefront were identified by optical interferometry. It was possible to describe the transverse dynamics and the spatiotemporal instabilities by modeling the three-dimensional-coupled wave equations in photorefractive FWM using a truncated modal expansion approach.
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.
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.
Variability patterns of Rossby wave source
Energy Technology Data Exchange (ETDEWEB)
Shimizu, Marilia Harumi; Albuquerque Cavalcanti, Iracema Fonseca de [National Institute for Space Research (INPE), Center for Weather Forecasting and Climate Studies (CPTEC), Sao Jose dos Campos (Brazil)
2011-08-15
Rossby waves (RW) propagation due to a local forcing is one of the mechanisms responsible for wave trains configurations known as teleconnections. The term teleconnection refers to anomalies patterns that are correlated in several regions of the world, causing large-scale changes in atmospheric waves patterns and temperature and precipitation regimes. The aim of teleconnections studies is to provide a better understanding of atmospheric variability and their mechanisms of action in order to identify patterns that can be tracked and predicted. The purpose of this study was to characterize seasonal and spatial variability of atmospheric RW sources. The RW source at 200 hPa was calculated for the four seasons with reanalysis data of zonal and meridional wind. In the Northern Hemisphere (NH), the RW sources were located on East Asia, North America, North Atlantic and Pacific. The main RW sources in the Southern Hemisphere (SH) were located over Intertropical, South Pacific, South Atlantic and South Indian Convergence Zones. Extratropical regions were also identified, mainly to the south of Australia. The vortex stretching term (S1) and the advection of absolute vorticity by the divergent wind (S2) were analyzed to discuss the physical mechanisms for RW generation. In the NH, the source at East Asia in DJF changed to a sink in JJA, related to the dominance of S1 term in DJF and S2 term in JJA. In the SH, the vortex stretching term had the dominant contribution for RW source located to the south of Australia. The main forcing for RW sources at east of Australia was the advection of absolute vorticity by divergent flow. Over South America, both terms contributed to the source in DJF. The main modes of RW source variability were discussed by using empirical orthogonal functions analysis. RW variability was characterized by wave trains configurations in both hemispheres over regions of jet streams and storm tracks, associated with favorable and unfavorable areas for RW
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.
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.
Characterization and modification of cavitation pattern in shock wave lithotripsy
Arora, Manish; Ohl, Claus Dieter; Liebler, Marko
2004-01-01
The temporal and spatial dynamics of cavitation bubble cloud growth and collapse in extracorporeal shock wave lithotripsy (ESWL) is studied experimentally. The first objective is obtaining reproducible cloud patterns experimentally and comparing them with FDTD-calculations. Second, we describe a method to modify the cavitation pattern by timing two consecutive pressure waves at variable delays. It is found that the spatial and temporal dynamics of the cavitation bubble can be varied in large ranges. The ability to control cavitation dynamics allows discussing strategies for improvement of medical and biological applications of shock waves such as cell membrane poration and stone fragmentation.
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...
Wave propagation in the Lorenz-96 model
van Kekem, Dirk L.; Sterk, Alef E.
2018-04-01
In this paper we study the spatiotemporal properties of waves in the Lorenz-96 model and their dependence on the dimension parameter n and the forcing parameter F. For F > 0 the first bifurcation is either a supercritical Hopf or a double-Hopf bifurcation and the periodic attractor born at these bifurcations represents a traveling wave. Its spatial wave number increases linearly with n, but its period tends to a finite limit as n → ∞. For F traveling wave also grows linearly with n. For F < 0 and even n, however, a Hopf bifurcation is preceded by either one or two pitchfork bifurcations, where the number of the latter bifurcations depends on whether n has remainder 2 or 0 upon division by 4. This bifurcation sequence leads to stationary waves and their spatiotemporal properties also depend on the remainder after dividing n by 4. Finally, we explain how the double-Hopf bifurcation can generate two or more stable waves with different spatiotemporal properties that coexist for the same parameter values n and F.
Span: spike pattern association neuron for learning spatio-temporal spike patterns.
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.
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.)
International Nuclear Information System (INIS)
Holmes, W R; Edelstein-Keshet, L; Carlsson, A E
2012-01-01
Patterns of waves, patches, and peaks of actin are observed experimentally in many living cells. Models of this phenomenon have been based on the interplay between filamentous actin (F-actin) and its nucleation promoting factors (NPFs) that activate the Arp2/3 complex. Here we present an alternative biologically-motivated model for F-actin-NPF interaction based on properties of GTPases acting as NPFs. GTPases (such as Cdc42, Rac) are known to promote actin nucleation, and to have active membrane-bound and inactive cytosolic forms. The model is a natural extension of a previous mathematical mini-model of small GTPases that generates static cell polarization. Like other modellers, we assume that F-actin negative feedback shapes the observed patterns by suppressing the trailing edge of NPF-generated wave-fronts, hence localizing the activity spatially. We find that our NPF-actin model generates a rich set of behaviours, spanning a transition from static polarization to single pulses, reflecting waves, wave trains, and oscillations localized at the cell edge. The model is developed with simplicity in mind to investigate the interaction between nucleation promoting factor kinetics and negative feedback. It explains distinct types of pattern initiation mechanisms, and identifies parameter regimes corresponding to distinct behaviours. We show that weak actin feedback yields static patterning, moderate feedback yields dynamical behaviour such as travelling waves, and strong feedback can lead to wave trains or total suppression of patterning. We use a recently introduced nonlinear bifurcation analysis to explore the parameter space of this model and predict its behaviour with simulations validating those results. (paper)
Defects formation and spiral waves in a network of neurons in presence of electromagnetic induction.
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.
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
Spatio-temporal patterns of soil erosion and suspended sediment dynamics in the Mekong River Basin.
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.
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.
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
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.
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.
Damage pattern and damage progression on breakwater roundheads under multidirectional waves
DEFF Research Database (Denmark)
Comola, F.; Andersen, Thomas Lykke; Martinelli, L.
2014-01-01
An experimental model test study is carried out to investigate damage pattern and progression on a rock armoured breakwater roundhead subjected to multidirectional waves. Concerning damage pattern, the most critical sector is observed to shift leeward with increasing wave period. Taking angles...... over the roundhead is developed. Thus the formula also considers the shifting of the critical sector due to increasing wave period which existing formulae do not include. Finally, analysing the damage produced by double peaked spectra, it is shown that the armour may be designed by the formula when...
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.
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.
Spatiotemporal and plantar pressure patterns of 1000 healthy individuals aged 3-101 years.
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.
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.
Stability of Nonlinear Wave Patterns to the Bipolar Vlasov-Poisson-Boltzmann System
Li, Hailiang; Wang, Yi; Yang, Tong; Zhong, Mingying
2018-04-01
The main purpose of the present paper is to investigate the nonlinear stability of viscous shock waves and rarefaction waves for the bipolar Vlasov-Poisson-Boltzmann (VPB) system. To this end, motivated by the micro-macro decomposition to the Boltzmann equation in Liu and Yu (Commun Math Phys 246:133-179, 2004) and Liu et al. (Physica D 188:178-192, 2004), we first set up a new micro-macro decomposition around the local Maxwellian related to the bipolar VPB system and give a unified framework to study the nonlinear stability of the basic wave patterns to the system. Then, as applications of this new decomposition, the time-asymptotic stability of the two typical nonlinear wave patterns, viscous shock waves and rarefaction waves are proved for the 1D bipolar VPB system. More precisely, it is first proved that the linear superposition of two Boltzmann shock profiles in the first and third characteristic fields is nonlinearly stable to the 1D bipolar VPB system up to some suitable shifts without the zero macroscopic mass conditions on the initial perturbations. Then the time-asymptotic stability of the rarefaction wave fan to compressible Euler equations is proved for the 1D bipolar VPB system. These two results are concerned with the nonlinear stability of wave patterns for Boltzmann equation coupled with additional (electric) forces, which together with spectral analysis made in Li et al. (Indiana Univ Math J 65(2):665-725, 2016) sheds light on understanding the complicated dynamic behaviors around the wave patterns in the transportation of charged particles under the binary collisions, mutual interactions, and the effect of the electrostatic potential forces.
Typology of nonlinear activity waves in a layered neural continuum.
Koch, Paul; Leisman, Gerry
2006-04-01
Neural tissue, a medium containing electro-chemical energy, can amplify small increments in cellular activity. The growing disturbance, measured as the fraction of active cells, manifests as propagating waves. In a layered geometry with a time delay in synaptic signals between the layers, the delay is instrumental in determining the amplified wavelengths. The growth of the waves is limited by the finite number of neural cells in a given region of the continuum. As wave growth saturates, the resulting activity patterns in space and time show a variety of forms, ranging from regular monochromatic waves to highly irregular mixtures of different spatial frequencies. The type of wave configuration is determined by a number of parameters, including alertness and synaptic conditioning as well as delay. For all cases studied, using numerical solution of the nonlinear Wilson-Cowan (1973) equations, there is an interval in delay in which the wave mixing occurs. As delay increases through this interval, during a series of consecutive waves propagating through a continuum region, the activity within that region changes from a single-frequency to a multiple-frequency pattern and back again. The diverse spatio-temporal patterns give a more concrete form to several metaphors advanced over the years to attempt an explanation of cognitive phenomena: Activity waves embody the "holographic memory" (Pribram, 1991); wave mixing provides a plausible cause of the competition called "neural Darwinism" (Edelman, 1988); finally the consecutive generation of growing neural waves can explain the discontinuousness of "psychological time" (Stroud, 1955).
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.
Topological horseshoes in travelling waves of discretized nonlinear wave equations
International Nuclear Information System (INIS)
Chen, Yi-Chiuan; Chen, Shyan-Shiou; Yuan, Juan-Ming
2014-01-01
Applying the concept of anti-integrable limit to coupled map lattices originated from space-time discretized nonlinear wave equations, we show that there exist topological horseshoes in the phase space formed by the initial states of travelling wave solutions. In particular, the coupled map lattices display spatio-temporal chaos on the horseshoes
Topological horseshoes in travelling waves of discretized nonlinear wave equations
Energy Technology Data Exchange (ETDEWEB)
Chen, Yi-Chiuan, E-mail: YCChen@math.sinica.edu.tw [Institute of Mathematics, Academia Sinica, Taipei 10617, Taiwan (China); Chen, Shyan-Shiou, E-mail: sschen@ntnu.edu.tw [Department of Mathematics, National Taiwan Normal University, Taipei 11677, Taiwan (China); Yuan, Juan-Ming, E-mail: jmyuan@pu.edu.tw [Department of Financial and Computational Mathematics, Providence University, Shalu, Taichung 43301, Taiwan (China)
2014-04-15
Applying the concept of anti-integrable limit to coupled map lattices originated from space-time discretized nonlinear wave equations, we show that there exist topological horseshoes in the phase space formed by the initial states of travelling wave solutions. In particular, the coupled map lattices display spatio-temporal chaos on the horseshoes.
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.
Synchronization stability and pattern selection in a memristive neuronal network
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.
Synchronization stability and pattern selection in a memristive neuronal network.
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.
Spatiotemporal Data Mining, Analysis, and Visualization of Human Activity Data
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…
Attractive target wave patterns in complex networks consisting of excitable nodes
International Nuclear Information System (INIS)
Zhang Li-Sheng; Mi Yuan-Yuan; Liao Xu-Hong; Qian Yu; Hu Gang
2014-01-01
This review describes the investigations of oscillatory complex networks consisting of excitable nodes, focusing on the target wave patterns or say the target wave attractors. A method of dominant phase advanced driving (DPAD) is introduced to reveal the dynamic structures in the networks supporting oscillations, such as the oscillation sources and the main excitation propagation paths from the sources to the whole networks. The target center nodes and their drivers are regarded as the key nodes which can completely determine the corresponding target wave patterns. Therefore, the center (say node A) and its driver (say node B) of a target wave can be used as a label, (A,B), of the given target pattern. The label can give a clue to conveniently retrieve, suppress, and control the target waves. Statistical investigations, both theoretically from the label analysis and numerically from direct simulations of network dynamics, show that there exist huge numbers of target wave attractors in excitable complex networks if the system size is large, and all these attractors can be labeled and easily controlled based on the information given by the labels. The possible applications of the physical ideas and the mathematical methods about multiplicity and labelability of attractors to memory problems of neural networks are briefly discussed. (topical review - statistical physics and complex systems)
Boundary-induced pattern formation from uniform temporal oscillation
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.
A cdk1 gradient guides surface contraction waves in oocytes.
Bischof, Johanna; Brand, Christoph A; Somogyi, Kálmán; Májer, Imre; Thome, Sarah; Mori, Masashi; Schwarz, Ulrich S; Lénárt, Péter
2017-10-11
Surface contraction waves (SCWs) in oocytes and embryos lead to large-scale shape changes coupled to cell cycle transitions and are spatially coordinated with the cell axis. Here, we show that SCWs in the starfish oocyte are generated by a traveling band of myosin II-driven cortical contractility. At the front of the band, contractility is activated by removal of cdk1 inhibition of the RhoA/RhoA kinase/myosin II signaling module, while at the rear, contractility is switched off by negative feedback originating downstream of RhoA kinase. The SCW's directionality and speed are controlled by a spatiotemporal gradient of cdk1-cyclinB. This gradient is formed by the release of cdk1-cyclinB from the asymmetrically located nucleus, and progressive degradation of cyclinB. By combining quantitative imaging, biochemical and mechanical perturbations with mathematical modeling, we demonstrate that the SCWs result from the spatiotemporal integration of two conserved regulatory modules, cdk1-cyclinB for cell cycle regulation and RhoA/Rok/NMYII for actomyosin contractility.Surface contraction waves (SCWs) are prominent shape changes coupled to cell cycle transitions in oocytes. Here the authors show that SCWs are patterned by the spatiotemporal integration of two conserved modules, cdk1-cyclinB for cell cycle regulation and RhoA/Rok/NMYII for actomyosin contractility.
Spin-wave interference patterns created by spin-torque nano-oscillators for memory and computation
International Nuclear Information System (INIS)
Macia, Ferran; Kent, Andrew D; Hoppensteadt, Frank C
2011-01-01
Magnetization dynamics in nanomagnets has attracted broad interest since it was predicted that a dc current flowing through a thin magnetic layer can create spin-wave excitations. These excitations are due to spin momentum transfer, a transfer of spin angular momentum between conduction electrons and the background magnetization, that enables new types of information processing. Here we show how arrays of spin-torque nano-oscillators can create propagating spin-wave interference patterns of use for memory and computation. Memristic transponders distributed on the thin film respond to threshold tunnel magnetoresistance values, thereby allowing spin-wave detection and creating new excitation patterns. We show how groups of transponders create resonant (reverberating) spin-wave interference patterns that may be used for polychronous wave computation and information storage.
Wave propagation in the Lorenz-96 model
Directory of Open Access Journals (Sweden)
D. L. van Kekem
2018-04-01
Full Text Available In this paper we study the spatiotemporal properties of waves in the Lorenz-96 model and their dependence on the dimension parameter n and the forcing parameter F. For F > 0 the first bifurcation is either a supercritical Hopf or a double-Hopf bifurcation and the periodic attractor born at these bifurcations represents a traveling wave. Its spatial wave number increases linearly with n, but its period tends to a finite limit as n → ∞. For F < 0 and odd n, the first bifurcation is again a supercritical Hopf bifurcation, but in this case the period of the traveling wave also grows linearly with n. For F < 0 and even n, however, a Hopf bifurcation is preceded by either one or two pitchfork bifurcations, where the number of the latter bifurcations depends on whether n has remainder 2 or 0 upon division by 4. This bifurcation sequence leads to stationary waves and their spatiotemporal properties also depend on the remainder after dividing n by 4. Finally, we explain how the double-Hopf bifurcation can generate two or more stable waves with different spatiotemporal properties that coexist for the same parameter values n and F.
Spatiotemporal variability of marine renewable energy resources in Norway
Varlas, George; Christakos, Konstantinos; Cheliotis, Ioannis; Papadopoulos, A.; Steeneveld, G.J.
2017-01-01
Marine Renewable Energy (MRE) resources such as wind and wave energy depend on the complex behaviour of weather and climatic conditions which determine the development of MRE technologies, energy grid, supply and prices. This study investigates the spatiotemporal variability of MRE resources along
Unravelling spatio-temporal evapotranspiration patterns in topographically complex landscapes
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
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.
Ding, Yang; Ming, Tingyu
2016-11-01
In undulatory locomotion, torque (bending moment) is required along the body to overcome the external forces from environments and bend the body. Previous observations on animals using less than two wavelengths on the body showed such torque has a single traveling wave pattern. Using resistive force theory model and considering the torque generated by external force in a resistive force dominated media, we found that as the wave number (number of wavelengths on the locomotor's body) increases from 0.5 to 1.8, the speed of the traveling wave of torque decreases. When the wave number increases to 2 and greater, the torque pattern transits from a single traveling wave to a two traveling waves and then a complex pattern that consists two wave-like patterns. By analyzing the force distribution and its contribution to the torque, we explain the speed decrease of the torque wave and the pattern transition. This research is partially supported by the Recruitment Program of Global Young Experts (China).
Xie, Fan; Ren, Yaqiong; Zhou, Yongsheng; Larose, Eric; Baillet, Laurent
2018-03-01
Diffuse acoustic or seismic waves are highly sensitive to detect changes of mechanical properties in heterogeneous geological materials. In particular, thanks to acoustoelasticity, we can quantify stress changes by tracking acoustic or seismic relative velocity changes in the material at test. In this paper, we report on a small-scale laboratory application of an innovative time-lapse tomography technique named Locadiff to image spatiotemporal mechanical changes on a granite sample under biaxial loading, using diffuse waves at ultrasonic frequencies (300 kHz to 900 kHz). We demonstrate the ability of the method to image reversible stress evolution and deformation process, together with the development of reversible and irreversible localized microdamage in the specimen at an early stage. Using full-field infrared thermography, we visualize stress-induced temperature changes and validate stress images obtained from diffuse ultrasound. We demonstrate that the inversion with a good resolution can be achieved with only a limited number of receivers distributed around a single source, all located at the free surface of the specimen. This small-scale experiment is a proof of concept for frictional earthquake-like failure (e.g., stick-slip) research at laboratory scale as well as large-scale seismic applications, potentially including active fault monitoring.
Baby booms and busts: waves in fertility patterns
Beets, G.C.N.
2009-01-01
Fertility curves sometimes resemble sea waves. During periods that the fertility age patterns change, according to whatever reason, 'this sea' may become very turbulent. Also other sea-like phenomena, for example tsunamis, are discernible in fertility behaviour. This article gives a short overview
Reconstruction of Interfering Waves from Three Dimensional Analysis of Their Interference Pattern
Directory of Open Access Journals (Sweden)
M. T. Tavassoli
1997-04-01
Full Text Available Optical interferometry is being used as an efficient tool to analyse smooth surfaces for more than a century. Although, due to introduction of novel computer assisted analyzing techniques and array detectors, like CCD, the speed and the precision of processing have been increased tremendously, but the main equation involved is not changed. The main equation is the intensity distribution in the interference pattern of a plane reference wave and the required wave. In the paper it is shown that by analysis of the interference pattern of two unknown waves in three dimension (which is possible for coherent waves it is possible to reconstruct each wave separately. This approach has several useful applications, namely, on can do without reference plane wave in the interferometric surface analysis and, it is possible to reconstruct an unknown wave by making it to interfere with itself. This is very useful in determining the profile of laser beams and erasing the effect of atmospheric disturbances on observing astronomical objects.
Stochastic resonance based on modulation instability in spatiotemporal chaos.
Han, Jing; Liu, Hongjun; Huang, Nan; Wang, Zhaolu
2017-04-03
A novel dynamic of stochastic resonance in spatiotemporal chaos is presented, which is based on modulation instability of perturbed partially coherent wave. The noise immunity of chaos can be reinforced through this effect and used to restore the coherent signal information buried in chaotic perturbation. A theoretical model with fluctuations term is derived from the complex Ginzburg-Landau equation via Wigner transform. It shows that through weakening the nonlinear threshold and triggering energy redistribution, the coherent component dominates the instability damped by incoherent component. The spatiotemporal output showing the properties of stochastic resonance may provide a potential application of signal encryption and restoration.
Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons.
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.
A hybrid spatiotemporal drought forecasting model for operational use
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.
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.
Spatio-temporal seasonal drought patterns in Europe from 1950 to 2015
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.
Visual search of cyclic spatio-temporal events
Gautier, Jacques; Davoine, Paule-Annick; Cunty, Claire
2018-05-01
The analysis of spatio-temporal events, and especially of relationships between their different dimensions (space-time-thematic attributes), can be done with geovisualization interfaces. But few geovisualization tools integrate the cyclic dimension of spatio-temporal event series (natural events or social events). Time Coil and Time Wave diagrams represent both the linear time and the cyclic time. By introducing a cyclic temporal scale, these diagrams may highlight the cyclic characteristics of spatio-temporal events. However, the settable cyclic temporal scales are limited to usual durations like days or months. Because of that, these diagrams cannot be used to visualize cyclic events, which reappear with an unusual period, and don't allow to make a visual search of cyclic events. Also, they don't give the possibility to identify the relationships between the cyclic behavior of the events and their spatial features, and more especially to identify localised cyclic events. The lack of possibilities to represent the cyclic time, outside of the temporal diagram of multi-view geovisualization interfaces, limits the analysis of relationships between the cyclic reappearance of events and their other dimensions. In this paper, we propose a method and a geovisualization tool, based on the extension of Time Coil and Time Wave, to provide a visual search of cyclic events, by allowing to set any possible duration to the diagram's cyclic temporal scale. We also propose a symbology approach to push the representation of the cyclic time into the map, in order to improve the analysis of relationships between space and the cyclic behavior of events.
Assessment of spatio-temporal gait parameters from trunk accelerations during human walking
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
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.
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.
Acharyya, Muktish
2017-07-01
The spin wave interference is studied in two dimensional Ising ferromagnet driven by two coherent spherical magnetic field waves by Monte Carlo simulation. The spin waves are found to propagate and interfere according to the classic rule of interference pattern generated by two point sources. The interference pattern of spin wave is observed in one boundary of the lattice. The interference pattern is detected and studied by spin flip statistics at high and low temperatures. The destructive interference is manifested as the large number of spin flips and vice versa.
Information processing in patterned magnetic nanostructures with edge spin waves.
Lara, Antonio; Robledo Moreno, Javier; Guslienko, Konstantin Y; Aliev, Farkhad G
2017-07-17
Low dissipation data processing with spins is one of the promising directions for future information and communication technologies. Despite a significant progress, the available magnonic devices are not broadband yet and have restricted capabilities to redirect spin waves. Here we propose a breakthrough approach to spin wave manipulation in patterned magnetic nanostructures with unmatched characteristics, which exploits a spin wave analogue to edge waves propagating along a water-wall boundary. Using theory, micromagnetic simulations and experiment we investigate spin waves propagating along the edges in magnetic structures, under an in-plane DC magnetic field inclined with respect to the edge. The proposed edge spin waves overcome important challenges faced by previous technologies such as the manipulation of the spin wave propagation direction, and they substantially improve the capability of transmitting information at frequencies exceeding 10 GHz. The concept of the edge spin waves allows to design a broad of logic devices such as splitters, interferometers, or edge spin wave transistors with unprecedented characteristics and a potentially strong impact on information technologies.
Spatio-temporal modeling for residential burglary
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
Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors
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.
Synchrony, waves and ripple in spatially coupled Kuramoto oscillators with Mexican hat connectivity.
Heitmann, Stewart; Ermentrout, G Bard
2015-06-01
Spatiotemporal waves of synchronized activity are known to arise in oscillatory neural networks with lateral inhibitory coupling. How such patterns respond to dynamic changes in coupling strength is largely unexplored. The present study uses analysis and simulation to investigate the evolution of wave patterns when the strength of lateral inhibition is varied dynamically. Neural synchronization was modeled by a spatial ring of Kuramoto oscillators with Mexican hat lateral coupling. Broad bands of coexisting stable wave solutions were observed at all levels of inhibition. The stability of these waves was formally analyzed in both the infinite ring and the finite ring. The broad range of multi-stability predicted hysteresis in transitions between neighboring wave solutions when inhibition is slowly varied. Numerical simulation confirmed the predicted transitions when inhibition was ramped down from a high initial value. However, non-wave solutions emerged from the uniform solution when inhibition was ramped upward from zero. These solutions correspond to spatially periodic deviations of phase that we call ripple states. Numerical continuation showed that stable ripple states emerge from synchrony via a supercritical pitchfork bifurcation. The normal form of this bifurcation was derived analytically, and its predictions compared against the numerical results. Ripple states were also found to bifurcate from wave solutions, but these were locally unstable. Simulation also confirmed the existence of hysteresis and ripple states in two spatial dimensions. Our findings show that spatial synchronization patterns can remain structurally stable despite substantial changes in network connectivity.
Spatiotemporal drought forecasting using nonlinear models
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
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
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.
Patterns of Dynamics : in Honour of Bernold Fiedler's 60th Birthday
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. .
Coexistence of collapse and stable spatiotemporal solitons in multimode fibers
Shtyrina, Olga V.; Fedoruk, Mikhail P.; Kivshar, Yuri S.; Turitsyn, Sergei K.
2018-01-01
We analyze spatiotemporal solitons in multimode optical fibers and demonstrate the existence of stable solitons, in a sharp contrast to earlier predictions of collapse of multidimensional solitons in three-dimensional media. We discuss the coexistence of blow-up solutions and collapse stabilization by a low-dimensional external potential in graded-index media, and also predict the existence of stable higher-order nonlinear waves such as dipole-mode spatiotemporal solitons. To support the main conclusions of our numerical studies we employ a variational approach and derive analytically the stability criterion for input powers for the collapse stabilization.
Near-field imaging of interference pattern of counterpropagating evanescent waves
DEFF Research Database (Denmark)
Bozhevolnyi, Sergey I.; Bozhevolnaya, Elena A.
1999-01-01
It is generally accepted that measurement of of the contrast of the intensity interference pattern formed by two counterpropagating evanescent waves can be used to characterize the resolving power of a collection near-field microscope. We argue that, if the light collected by a fiber probe propag...... be equal to the contrast of the interference pattern....
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.
Predicting spiral wave patterns from cell properties in a model of biological self-organization.
Geberth, Daniel; Hütt, Marc-Thorsten
2008-09-01
In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.
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
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.
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.
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.
Analysis of Spatio-Temporal Traffic Patterns Based on Pedestrian Trajectories
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.
Annotating spatio-temporal datasets for meaningful analysis in the Web
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.
Belkhatir, Zehor
2015-11-23
This paper discusses the estimation of distributed Cerebral Blood Flow (CBF) using spatiotemporal traveling wave model. We consider a damped wave partial differential equation that describes a physiological relationship between the blood mass density and the CBF. The spatiotemporal model is reduced to a finite dimensional system using a cubic b-spline continuous Galerkin method. A Kalman Filter with Unknown Inputs without Direct Feedthrough (KF-UI-WDF) is applied on the obtained reduced differential model to estimate the source term which is the CBF scaled by a factor. Numerical results showing the performances of the adopted estimator are provided.
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).
Effective and efficient analysis of spatio-temporal data
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
A computational role for bistability and traveling waves in motor cortex
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Stewart eHeitmann
2012-09-01
Full Text Available Adaptive changes in behavior require rapid changes in brain states yet the brain must also remain stable. We investigated two neural mechanisms for evoking rapid transitions between spatiotemporal synchronization patterns of beta oscillations (13--30Hz in motor cortex. Cortex was modeled as a sheet of neural oscillators that were spatially coupled using a center-surround connection topology. Manipulating the inhibitory surround was found to evoke reliable transitions between synchronous oscillation patterns and traveling waves. These transitions modulated the simulated local field potential in agreement with physiological observations in humans. Intermediate levels of surround inhibition were also found to produce bistable coupling topologies that supported both waves and synchrony. State-dependent perturbation between bistable states produced very rapid transitions but were less reliable. We surmise that motor cortex may thus employ state-dependent computation to achieve very rapid changes between bistable motor states when the demand for speed exceeds the demand for accuracy.
SPATIO-TEMPORAL CHARACTERISTICS OF RESIDENT TRIP BASED ON POI AND OD DATA OF FLOAT CAR IN BEIJING
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...
Relating Cortical Wave Dynamics to Learning and Remembering
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Eduardo Mercado III
2014-12-01
Full Text Available Electrical waves propagate across sensory and motor cortices in stereotypical patterns. These waves have been described as potentially facilitating sensory processing when they travel through sensory cortex, as guiding movement preparation and performance when they travel across motor cortex, and as possibly promoting synaptic plasticity and the consolidation of memory traces, especially during sleep. Here, an alternative theoretical framework is suggested that integrates Pavlovian hypotheses about learning and cortical function with concepts from contemporary proceduralist theories of memory. The proposed framework postulates that sensory-evoked cortical waves are gradually modified across repeated experiences such that the waves more effectively differentiate sensory events, and so that the waves are more likely to reverberate. It is argued that the qualities of cortical waves—their origins, form, intensity, speed, periodicity, extent, and trajectories —are a function of both the structural organization of neural circuits and ongoing reverberations resulting from previously experienced events. It is hypothesized that experience-dependent cortical plasticity, both in the short- and long-term, modulates the qualities of cortical waves, thereby enabling individuals to make progressively more precise distinctions between complex sensory events, and to reconstruct components of previously experienced events. Unlike most current neurobiological theories of learning and memory mechanisms, this hypothesis does not assume that synaptic plasticity, or any other form of neural plasticity, serves to store physical records of previously experienced events for later reactivation. Rather, the reorganization of cortical circuits may alter the potential for certain wave patterns to arise and persist. Understanding what factors determine the spatiotemporal dynamics of cortical waves, how structural changes affect their qualities, and how wave dynamics
Spatiotemporal patterns of population distribution as crucial element for risk management
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
Spatio-temporal dynamics of global H5N1 outbreaks match bird migration patterns
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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.
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.
Anatomical and spiral wave reentry in a simplified model for atrial electrophysiology.
Richter, Yvonne; Lind, Pedro G; Seemann, Gunnar; Maass, Philipp
2017-04-21
For modeling the propagation of action potentials in the human atria, various models have been developed in the past, which take into account in detail the influence of the numerous ionic currents flowing through the cell membrane. Aiming at a simplified description, the Bueno-Orovio-Cherry-Fenton (BOCF) model for electric wave propagation in the ventricle has been adapted recently to atrial physiology. Here, we study this adapted BOCF (aBOCF) model with respect to its capability to accurately generate spatio-temporal excitation patterns found in anatomical and spiral wave reentry. To this end, we compare results of the aBOCF model with the more detailed one proposed by Courtemanche, Ramirez and Nattel (CRN model). We find that characteristic features of the reentrant excitation patterns seen in the CRN model are well captured by the aBOCF model. This opens the possibility to study origins of atrial fibrillation based on a simplified but still reliable description. Copyright © 2017 Elsevier Ltd. All rights reserved.
Spatio-temporal cerebral blood flow perfusion patterns in cortical spreading depression
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.
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.
Airy Wave Packets Accelerating in Space-Time
Kondakci, H. Esat; Abouraddy, Ayman F.
2018-04-01
Although diffractive spreading is an unavoidable feature of all wave phenomena, certain waveforms can attain propagation invariance. A lesser-explored strategy for achieving optical self-similar propagation exploits the modification of the spatiotemporal field structure when observed in reference frames moving at relativistic speeds. For such an observer, it is predicted that the associated Lorentz boost can bring to a halt the axial dynamics of a wave packet of an arbitrary profile. This phenomenon is particularly striking in the case of a self-accelerating beam—such as an Airy beam—whose peak normally undergoes a transverse displacement upon free propagation. Here we synthesize an acceleration-free Airy wave packet that travels in a straight line by deforming its spatiotemporal spectrum to reproduce the impact of a Lorentz boost. The roles of the axial spatial coordinate and time are swapped, leading to "time diffraction" manifested in self-acceleration observed in the propagating Airy wave-packet frame.
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)
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.
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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.
Characterization and modification of cavitation pattern in shock wave lithotripsy
Arora, M.; Ohl, C.D.; Liebler, Marko
2004-01-01
The temporal and spatial dynamics of cavitation bubble cloud growth and collapse in extracorporeal shock wave lithotripsy (ESWL) is studied experimentally. The first objective is obtaining reproducible cloud patterns experimentally and comparing them with FDTD-calculations. Second, we describe a
Reentrant stability of Bose-Einstein-condensate standing-wave patterns
International Nuclear Information System (INIS)
Kalas, Ryan M.; Solenov, Dmitry; Timmermans, Eddy
2010-01-01
We describe standing-wave patterns induced by an attractive finite-ranged external potential inside a large Bose-Einstein Condensate (BEC). As the potential depth increases, the time-independent Gross-Pitaevskii equation develops pairs of solutions that have nodes in their wave function. We elucidate the nature of these states and study their dynamical stability. Although we study the problem in a two-dimensional BEC subject to a cylindrically symmetric square well potential of a radius that is comparable to the coherence length of the BEC, our analysis reveals general trends that are valid in two and three dimensions, independent of the symmetry of the localized potential well, and suggestive of the behavior in general short-range and large-range potentials. One set of nodal BEC wave functions resembles the single particle n-node bound-state wave function of the potential well, the other wave functions resemble the n-1-node bound-state wave function with a kink state pinned by the potential. The second state, though corresponding to the lower free energy value of the pair of n-node BEC states, is always unstable, whereas the first can be dynamically stable in intervals of the potential well depth, implying that the standing-wave BEC can evolve from being dynamically unstable to stable and back to unstable as the potential well is adiabatically deepened - a phenomenon that we refer to as 'reentrant dynamical stability'.
Bayesian spatio-temporal analysis and geospatial risk factors of human monocytic ehrlichiosis.
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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.
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.
Drought effects on US maize and soybean production: spatiotemporal patterns and historical changes
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.
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.
Spatiotemporal modelling and mapping of the bubonic plague epidemic in India
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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
Visual representation of spatiotemporal structure
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.
Prediction of ion-exchange column breakthrough curves by constant-pattern wave approach.
Lee, I-Hsien; Kuan, Yu-Chung; Chern, Jia-Ming
2008-03-21
The release of heavy metals from industrial wastewaters represents one of major threats to environment. Compared with chemical precipitation method, fixed-bed ion-exchange process can effectively remove heavy metals from wastewaters and generate no hazardous sludge. In order to design and operate fixed-bed ion-exchange processes successfully, it is very important to understand the column dynamics. In this study, the column experiments for Cu2+/H+, Zn2+/H+, and Cd2+/H+ systems using Amberlite IR-120 were performed to measure the breakthrough curves under varying operating conditions. The experimental results showed that total cation concentration in the mobile-phase played a key role on the breakthrough curves; a higher feed concentration resulted in an earlier breakthrough. Furthermore, the column dynamics was also predicted by self-sharpening and constant-pattern wave models. The self-sharpening wave model assuming local ion-exchange equilibrium could provide a simple and quick estimation for the breakthrough volume, but the predicted breakthrough curves did not match the experimental data very well. On the contrary, the constant-pattern wave model using a constant driving force model for finite ion-exchange rate provided a better fit to the experimental data. The obtained liquid-phase mass transfer coefficient was correlated to the flow velocity and other operating parameters; the breakthrough curves under varying operating conditions could thus be predicted by the constant-pattern wave model using the correlation.
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
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.
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.
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.
Dissipative neurodynamics in perception forms cortical patterns that are stabilized by vortices
Freeman, Walter J.; Vitiello, Giuseppe
2009-06-01
In the engagement of the brain with its environment, large-scale neural interactions in brain dynamics create a mesoscopic order parameter, which is evaluated by measuring brain waves (electrocorticogram, ECoG). Such large-scale interactions emerge from the background activity of the brain that is sustained by mutual excitation in cortical populations and manifest in spatiotemporal patterns of neural activity. Band pass filtering reveals beats in ECoG power that recur at theta rates (3-7 Hz) as null spikes in log10 power. The order parameter transiently approaches zero, and the microscopic activity is both disordered and symmetric. As the null spikes terminate, the order parameter resurges and imposes a mesoscopic spatial pattern of ECoG amplitude modulation that then governs the microscopic gamma activity and retrieves the memory of a stimulus. The brain waves reveal a spatial pattern of phase modulation in the form of a cone. The dissipative many-body model of brain dynamics describes these phase cones as vortices, which are initiated by the null spikes, and which stabilize the amplitude modulated patterns embedded in the turbulent neural noise from which they emerge.
Dissipative neurodynamics in perception forms cortical patterns that are stabilized by vortices
International Nuclear Information System (INIS)
Freeman, Walter J; Vitiello, Giuseppe
2009-01-01
In the engagement of the brain with its environment, large-scale neural interactions in brain dynamics create a mesoscopic order parameter, which is evaluated by measuring brain waves (electrocorticogram, ECoG). Such large-scale interactions emerge from the background activity of the brain that is sustained by mutual excitation in cortical populations and manifest in spatiotemporal patterns of neural activity. Band pass filtering reveals beats in ECoG power that recur at theta rates (3-7 Hz) as null spikes in log 10 power. The order parameter transiently approaches zero, and the microscopic activity is both disordered and symmetric. As the null spikes terminate, the order parameter resurges and imposes a mesoscopic spatial pattern of ECoG amplitude modulation that then governs the microscopic gamma activity and retrieves the memory of a stimulus. The brain waves reveal a spatial pattern of phase modulation in the form of a cone. The dissipative many-body model of brain dynamics describes these phase cones as vortices, which are initiated by the null spikes, and which stabilize the amplitude modulated patterns embedded in the turbulent neural noise from which they emerge.
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 ...
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
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....
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...
Stafford, Ben K; Sher, Alexander; Litke, Alan M; Feldheim, David A
2009-10-29
During development, retinal axons project coarsely within their visual targets before refining to form organized synaptic connections. Spontaneous retinal activity, in the form of acetylcholine-driven retinal waves, is proposed to be necessary for establishing these projection patterns. In particular, both axonal terminations of retinal ganglion cells (RGCs) and the size of receptive fields of target neurons are larger in mice that lack the beta2 subunit of the nicotinic acetylcholine receptor (beta2KO). Here, using a large-scale, high-density multielectrode array to record activity from hundreds of RGCs simultaneously, we present analysis of early postnatal retinal activity from both wild-type (WT) and beta2KO retinas. We find that beta2KO retinas have correlated patterns of activity, but many aspects of these patterns differ from those of WT retina. Quantitative analysis suggests that wave directionality, coupled with short-range correlated bursting patterns of RGCs, work together to refine retinofugal projections.
Matter wave interference pattern in the collision of bright solitons
International Nuclear Information System (INIS)
Kumar, V. Ramesh; Radha, R.; Panigrahi, Prasanta K.
2009-01-01
We investigate the dynamics of Bose-Einstein condensates in a quasi one-dimensional regime in a time-dependent trap and show analytically that it is possible to observe matter wave interference patterns in the intra-trap collision of two bright solitons by selectively tuning the trap frequency and scattering length.
Patterns induced by magnetic impurities in d-wave superconductors
International Nuclear Information System (INIS)
Zuo Xianjun; Gong Changde; Zhou Yuan
2010-01-01
We investigate the modulated patterns induced by magnetic impurities in d-wave superconductors (DSCs) near optimal doping based on the t-t ' -U-V model. Modulated checkerboard patterns with periodicity of eight or four lattice constants (8a or 4a) in the spin-, charge- and DSC orders are observed. Moreover, the checkerboard modulation in the spin order appear to be robust against parameter changes, which is consistent with neutron-scattering experiments. For the two-impurity case, a modulated stripe-like spin order with periodicity 8a is induced, which coexists with the DSC order. Further experiments of magnetic impurity substitution in DSCs are expected to check these results.
Patterns induced by magnetic impurities in d-wave superconductors
Zuo, Xian-Jun; Gong, Chang-De; Zhou, Yuan
2010-07-01
We investigate the modulated patterns induced by magnetic impurities in d-wave superconductors (DSCs) near optimal doping based on the t-t-U-V model. Modulated checkerboard patterns with periodicity of eight or four lattice constants (8 a or 4 a) in the spin-, charge- and DSC orders are observed. Moreover, the checkerboard modulation in the spin order appear to be robust against parameter changes, which is consistent with neutron-scattering experiments. For the two-impurity case, a modulated stripe-like spin order with periodicity 8 a is induced, which coexists with the DSC order. Further experiments of magnetic impurity substitution in DSCs are expected to check these results.
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.
Tagawa, Yoshiyuki; Yamamoto, Shota; Kameda, Masaharu
2014-11-01
We investigate the spatiotemporal evolution of a laser-induced shock wave in a liquid filled thin tube. In order to measure pressure distribution at shock front, we adopt the background-oriented schlieren (BOS) technique. This technique provides two- or three-dimensional pressure field in a small region with a simple setup. With an ultra high-speed video camera and a laser stroboscope, we successfully capture the spatial evolution of the shock every 0.2 μs. We find an angular variation of the pressure at the shock front. The maximum pressure is in the direction of the laser shot while the minimum value is in the perpendicular direction. We compare the temporal evolution of the pressure measured by BOS technique with those obtained by another method, i.e. pressure estimation from the shock front position. Overall trend from both methods show a good agreement. The pressure from the shock front position exists between the maximum and minimum values from BOS technique. It indicates that our quantification method can measure more detailed pressure field in two- or three-dimensions. Our results might be used for the efficient generation systems for the microjet, which can be applicable for needle free injection devices.
Spontaneous activity in the developing mammalian retina: Form and function
Butts, Daniel Allison
Spontaneous neuronal activity is present in the immature mammalian retina during the initial stages of visual system development, before the retina is responsive to light. This activity consists of bursts of action potentials fired by retinal ganglion cells, and propagates in a wavelike manner across the inner plexiform layer of the retina. Unlike waves in other neural systems, retinal waves have large variability in both their rate and direction of propagation, and individual waves only propagate across small regions of the retina. The unique properties of retinal activity arise from dynamic processes within the developing retina, and produce characteristic spatiotemporal properties. These spatiotemporal properties are of particular interest, since they are believed to play a role in visual system development. This dissertation addresses the complex spatiotemporal patterning of the retinal waves from two different perspectives. First, it proposes how the immature circuitry of the developing retina generates these patterns of activity. In order to reproduce the distinct spatiotemporal properties observed in experiments, a model of the immature retinal circuitry must meet certain requirements, which are satisfied by a coarse-grained model of the developing retina that we propose. Second, this dissertation addresses how the particular spatiotemporal patterning of the retinal waves provides information to the rest of the visual system and, as a result, can be used to guide visual system development. By measuring the properties of this information, we place constraints on the developmental mechanisms that use this activity, and show how the particular spatiotemporal properties of the retinal waves provide this information. Together, this dissertation demonstrates how the apparent complexity of retinal wave patterning can be understood both through the immature circuitry that generates it, and through the developmental mechanisms that may use it. The first three
Stress wave velocity patterns in the longitudinal-radial plane of trees for defect diagnosis
Guanghui Li; Xiang Weng; Xiaocheng Du; Xiping Wang; Hailin Feng
2016-01-01
Acoustic tomography for urban tree inspection typically uses stress wave data to reconstruct tomographic images for the trunk cross section using interpolation algorithm. This traditional technique does not take into account the stress wave velocity patterns along tree height. In this study, we proposed an analytical model for the wave velocity in the longitudinalâ...
Spatiotemporal dynamics of underwater conical shock wave focusing
Czech Academy of Sciences Publication Activity Database
Hoffer, Petr; Lukeš, Petr; Akiyama, H.; Hosseini, H.
2017-01-01
Roč. 27, č. 4 (2017), s. 685-690 ISSN 0938-1287 Grant - others:Rada Programu interní podpory projektů mezinárodní spolupráce AV ČR(CZ) M100431203 Program:M Institutional support: RVO:61389021 Keywords : Underwater shock wave focusing * multichannel * electrohydraulic discharge * conical shock wave reflection * medical application Subject RIV: BI - Acoustics OBOR OECD: Applied mechanics Impact factor: 1.107, year: 2016 https://link.springer.com/article/10.1007/s00193-016-0703-7
Active sensing via movement shapes spatiotemporal patterns of sensory feedback.
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.
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
International Nuclear Information System (INIS)
Dai Chaoqing; Wang Xiaogang; Zhang Jiefang
2011-01-01
Research highlights: → The similarity transformation of (n + 1)-dimensional inhomogeneous NLSE are found. → From transformation, analytical self-similar waves and rogue waves are obtained. → Dynamical behaviors of self-similar waves in DDF are discussed. → The propagation and control of spatiotemporal self-similar waves are presented. - Abstract: We develop a systematic way to find the similarity transformation and investigate nonautonomous optical similariton dynamics for (n + 1)-dimensional nonlinear Schroedinger equation in the inhomogeneous optical fibers. A condition between the parameters of the mediums, which hints a exact balance between the dispersion/diffraction, nonlinearity and the gain/loss, has been obtained. Under this condition the optical similariton transmission in the dispersion-decreasing fibers (DDF) can be exactly controlled by proper dispersion management. Moreover, novel propagation dynamics of bright and dark similaritons on the background waves and optical rogue waves (rogons) in DDF are investigated too.
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
Spatiotemporal Coupling of the Tongue in Amyotrophic Lateral Sclerosis
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…
Directory of Open Access Journals (Sweden)
P. Lionello
2008-06-01
Full Text Available This study analyzes the link between the SWH (Significant Wave Height distribution in the Mediterranean Sea during the second half of the 20th century and the Northern Hemisphere SLP (Sea Level Pressure teleconnection patterns.
The SWH distribution is computed using the WAM (WAve Model forced by the surface wind fields provided by the ERA-40 reanalysis for the period 1958–2001. The time series of mid-latitude teleconnection patterns are downloaded from the NOAA web site. This study shows that several mid-latitude patterns are linked to the SWH field in the Mediterranean, especially in its western part during the cold season: East Atlantic Pattern (EA, Scandinavian Pattern (SCA, North Atlantic Oscillation (NAO, East Atlantic/West Russia Pattern (EA/WR and East Pacific/ North Pacific Pattern (EP/NP. Though the East Atlantic pattern exerts the largest influence, it is not sufficient to characterize the dominant variability. NAO, though relevant, has an effect smaller than EA and comparable to other patterns. Some link results from possibly spurious structures. Patterns which have a very different global structure are associated to similar spatial features of the wave variability in the Mediterranean Sea. These two problems are, admittedly, shortcomings of this analysis, which shows the complexity of the response of the Mediterranean SWH to global scale SLP teleconnection patterns.
Modulation of propagation-invariant Localized Waves for FSO communication systems
Salem, Mohamed; Bagci, Hakan
2012-01-01
The novel concept of spatio-Temporal modulation of Nyquist pulses is introduced, and the resulting wave-packets are termed Nyquist Localized Waves (LWs). Ideal Nyquist LWs belong to the generic family of LW solutions and can propagate indefinitely in unbounded media without attenuation or chromatic dispersion. The possibility of modulating Nyquist LWs for free-space optical (FSO) communication systems is demonstrated using two different modulation techniques. The first technique is on-off keying (OOK) with alternate mark inversion (AMI) coding for 1-bit per symbol transmission, and the second one is 16-Ary quadrature amplitude modulation (16-QAM) for 4-bits per symbol transmission. Aspects related to the performance, detection and generation of the spatio-Temporally coupled wave-packets are discussed and future research directions are outlined. © 2012 Optical Society of America.
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.
Spatio-temporal evolution of magnetosonic wave in the laser plasma interaction
International Nuclear Information System (INIS)
Sharma, R. P.; Singh, Ram Kishor; Sharma, Swati; Tiwary, Prem Pyari; Modi, K. V.; Satsangi, V. R.
2015-01-01
This paper presents a theoretical model for the transient response of nonlinear coupling between magnetosonic wave and ion acoustic wave in the overdense plasma. Filamentation of magnetosonic wave has been considered to be responsible for magnetic turbulence during the laser plasma interaction. The ion acoustic wave gets excited due to the ponderomotive force exerted by magnetosonic wave and this ion acoustic wave in turn generates perturbation in the background density in the form of spatial density harmonics. Numerical simulation has been carried out for dimensionless coupled equations of magnetosonic wave and ion acoustic wave; and the results show quite complex localized structures that grow with time. The power spectrum has also been studied which shows that the spectral index follows an approximate scaling of the order of ∼k −2.4 at smaller scales. The data obtained from numerical simulation are used in semi analytical model to better understand the mechanism of nonlinear evolution of magnetosonic wave. The results indicate considerable randomness in the spatial structure of the magnetic field profile which gives sufficient indication of turbulence
Spatio-temporal evolution of magnetosonic wave in the laser plasma interaction
Energy Technology Data Exchange (ETDEWEB)
Sharma, R. P., E-mail: rpsharma@ces.iitd.ac.in; Singh, Ram Kishor, E-mail: ram007kishor@gmail.com; Sharma, Swati, E-mail: swati.sharma704@gmail.com [Centre for Energy Studies, Indian Institute of Technology Delhi, Delhi 110016 (India); Tiwary, Prem Pyari, E-mail: prempyari@gmail.com [Centre for Energy Studies, Indian Institute of Technology Delhi, Delhi 110016 (India); Department of Physics and Computer Science, Dayal Bagh Educational Institute(Deemed University), DayalBagh, Agra 282005 (India); Modi, K. V., E-mail: kvmodi.iitd@gmail.com [Centre for Energy Studies, Indian Institute of Technology Delhi, Delhi 110016 (India); Mechanical Engineering Department, Government Engineering College Valsad, Gujarat 396001 (India); Satsangi, V. R. [Department of Physics and Computer Science, Dayal Bagh Educational Institute(Deemed University), DayalBagh, Agra 282005 (India)
2015-05-15
This paper presents a theoretical model for the transient response of nonlinear coupling between magnetosonic wave and ion acoustic wave in the overdense plasma. Filamentation of magnetosonic wave has been considered to be responsible for magnetic turbulence during the laser plasma interaction. The ion acoustic wave gets excited due to the ponderomotive force exerted by magnetosonic wave and this ion acoustic wave in turn generates perturbation in the background density in the form of spatial density harmonics. Numerical simulation has been carried out for dimensionless coupled equations of magnetosonic wave and ion acoustic wave; and the results show quite complex localized structures that grow with time. The power spectrum has also been studied which shows that the spectral index follows an approximate scaling of the order of ∼k{sup −2.4} at smaller scales. The data obtained from numerical simulation are used in semi analytical model to better understand the mechanism of nonlinear evolution of magnetosonic wave. The results indicate considerable randomness in the spatial structure of the magnetic field profile which gives sufficient indication of turbulence.
Spatially Localized Chemical Patterns around an A + B → Oscillator Front.
Budroni, M A; Lemaigre, L; Escala, D M; Muñuzuri, A P; De Wit, A
2016-02-18
When two gels, each loaded with a different set of reactants A and B of an oscillatory reaction, are brought into contact, reaction-diffusion patterns such as waves or Turing patterns can develop in the reactive contact zone. The initial condition which separates the reactants at the beginning leads to a localization in space of the different dynamical regimes accessible to the chemical oscillator. We study here both numerically and experimentally the composite traveling structures resulting from the interaction between chemical fronts and localized waves in the case in which the reactants of such an A + B → oscillator system are those of the canonical Belousov-Zhabotinsky (BZ) oscillating reaction. A transition between different dynamics is obtained by varying the initial concentration of the organic substrate of the BZ reactants, which is one of the parameters controlling the local excitability. We show that the dynamical regime (excitable or oscillatory) characterizing the BZ oscillator in the initial contact area is the key feature which determines the spatiotemporal evolution of the system. The experimental results are in qualitative agreement with the theoretical predictions.
Acoustic tweezers: patterning cells and microparticles using standing surface acoustic waves (SSAW).
Shi, Jinjie; Ahmed, Daniel; Mao, Xiaole; Lin, Sz-Chin Steven; Lawit, Aitan; Huang, Tony Jun
2009-10-21
Here we present an active patterning technique named "acoustic tweezers" that utilizes standing surface acoustic wave (SSAW) to manipulate and pattern cells and microparticles. This technique is capable of patterning cells and microparticles regardless of shape, size, charge or polarity. Its power intensity, approximately 5x10(5) times lower than that of optical tweezers, compares favorably with those of other active patterning methods. Flow cytometry studies have revealed it to be non-invasive. The aforementioned advantages, along with this technique's simple design and ability to be miniaturized, render the "acoustic tweezers" technique a promising tool for various applications in biology, chemistry, engineering, and materials science.
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.
Laser Shock Wave-Assisted Patterning on NiTi Shape Memory Alloy Surfaces
Ilhom, Saidjafarzoda; Seyitliyev, Dovletgeldi; Kholikov, Khomidkohodza; Thomas, Zachary; Er, Ali O.; Li, Peizhen; Karaca, Haluk E.; San, Omer
2018-01-01
Shape memory alloys (SMAs) are a unique class of smart materials and they were employed in various applications in engineering, biomedical, and aerospace technologies. Here, we report an advanced, efficient, and low-cost direct imprinting method with low environmental impact to create thermally controllable surface patterns. Patterned microindents were generated on Ni50Ti50 (at. %) SMAs using an Nd:YAG laser with 1064 nm wavelength at 10 Hz. Laser pulses at selected fluences were focused on the NiTi surface and generated pressure pulses of up to a few GPa. Optical microscope images showed that surface patterns with tailorable sizes can be obtained. The depth of the patterns increases with laser power and irradiation time. Upon heating, the depth profile of SMA surfaces changed where the maximum depth recovery ratio of 30% was observed. Recovery ratio decreased and stabilized when the number of pulses and thus the well depth were further increased. A numerical simulation of pressure evolution in shape memory alloys showed a good agreement with the experimental results. The stress wave closely followed the rise time of the laser pulse to its peak value and initial decay. Rapid attenuation and dispersion of the stress wave were found in our simulation.
Laser Shock Wave-Assisted Patterning on NiTi Shape Memory Alloy Surfaces
Ilhom, Saidjafarzoda; Seyitliyev, Dovletgeldi; Kholikov, Khomidkohodza; Thomas, Zachary; Er, Ali O.; Li, Peizhen; Karaca, Haluk E.; San, Omer
2018-03-01
Shape memory alloys (SMAs) are a unique class of smart materials and they were employed in various applications in engineering, biomedical, and aerospace technologies. Here, we report an advanced, efficient, and low-cost direct imprinting method with low environmental impact to create thermally controllable surface patterns. Patterned microindents were generated on Ni50Ti50 (at. %) SMAs using an Nd:YAG laser with 1064 nm wavelength at 10 Hz. Laser pulses at selected fluences were focused on the NiTi surface and generated pressure pulses of up to a few GPa. Optical microscope images showed that surface patterns with tailorable sizes can be obtained. The depth of the patterns increases with laser power and irradiation time. Upon heating, the depth profile of SMA surfaces changed where the maximum depth recovery ratio of 30% was observed. Recovery ratio decreased and stabilized when the number of pulses and thus the well depth were further increased. A numerical simulation of pressure evolution in shape memory alloys showed a good agreement with the experimental results. The stress wave closely followed the rise time of the laser pulse to its peak value and initial decay. Rapid attenuation and dispersion of the stress wave were found in our simulation.
Local Dynamics of Baroclinic Waves in the Martian Atmosphere
Kavulich, Michael J.
2013-11-01
The paper investigates the processes that drive the spatiotemporal evolution of baroclinic transient waves in the Martian atmosphere by a simulation experiment with the Geophysical Fluid Dynamics Laboratory (GFDL) Mars general circulation model (GCM). The main diagnostic tool of the study is the (local) eddy kinetic energy equation. Results are shown for a prewinter season of the Northern Hemisphere, in which a deep baroclinic wave of zonal wavenumber 2 circles the planet at an eastward phase speed of about 70° Sol-1 (Sol is a Martian day). The regular structure of the wave gives the impression that the classical models of baroclinic instability, which describe the underlying process by a temporally unstable global wave (e.g., Eady model and Charney model), may have a direct relevance for the description of the Martian baroclinic waves. The results of the diagnostic calculations show, however, that while the Martian waves remain zonally global features at all times, there are large spatiotemporal changes in their amplitude. The most intense episodes of baroclinic energy conversion, which take place in the two great plain regions (Acidalia Planitia and Utopia Planitia), are strongly localized in both space and time. In addition, similar to the situation for terrestrial baroclinic waves, geopotential flux convergence plays an important role in the dynamics of the downstream-propagating unstable waves. © 2013 American Meteorological Society.
Local Dynamics of Baroclinic Waves in the Martian Atmosphere
Kavulich, Michael J.; Szunyogh, Istvan; Gyarmati, Gyorgyi; Wilson, R. John
2013-01-01
The paper investigates the processes that drive the spatiotemporal evolution of baroclinic transient waves in the Martian atmosphere by a simulation experiment with the Geophysical Fluid Dynamics Laboratory (GFDL) Mars general circulation model (GCM). The main diagnostic tool of the study is the (local) eddy kinetic energy equation. Results are shown for a prewinter season of the Northern Hemisphere, in which a deep baroclinic wave of zonal wavenumber 2 circles the planet at an eastward phase speed of about 70° Sol-1 (Sol is a Martian day). The regular structure of the wave gives the impression that the classical models of baroclinic instability, which describe the underlying process by a temporally unstable global wave (e.g., Eady model and Charney model), may have a direct relevance for the description of the Martian baroclinic waves. The results of the diagnostic calculations show, however, that while the Martian waves remain zonally global features at all times, there are large spatiotemporal changes in their amplitude. The most intense episodes of baroclinic energy conversion, which take place in the two great plain regions (Acidalia Planitia and Utopia Planitia), are strongly localized in both space and time. In addition, similar to the situation for terrestrial baroclinic waves, geopotential flux convergence plays an important role in the dynamics of the downstream-propagating unstable waves. © 2013 American Meteorological Society.
Tuan, P H; Wen, C P; Chiang, P Y; Yu, Y T; Liang, H C; Huang, K F; Chen, Y F
2015-04-01
The Chladni nodal line patterns and resonant frequencies for a thin plate excited by an electronically controlled mechanical oscillator are experimentally measured. Experimental results reveal that the resonant frequencies can be fairly obtained by means of probing the variation of the effective impedance of the exciter with and without the thin plate. The influence of the extra mass from the central exciter is confirmed to be insignificant in measuring the resonant frequencies of the present system. In the theoretical aspect, the inhomogeneous Helmholtz equation is exploited to derive the response function as a function of the driving wave number for reconstructing experimental Chladni patterns. The resonant wave numbers are theoretically identified with the maximum coupling efficiency as well as the maximum entropy principle. Substituting the theoretical resonant wave numbers into the derived response function, all experimental Chladni patterns can be excellently reconstructed. More importantly, the dispersion relationship for the flexural wave of the vibrating plate can be determined with the experimental resonant frequencies and the theoretical resonant wave numbers. The determined dispersion relationship is confirmed to agree very well with the formula of the Kirchhoff-Love plate theory.
Wave-processing of long-scale information by neuronal chains.
Directory of Open Access Journals (Sweden)
José Antonio Villacorta-Atienza
Full Text Available Investigation of mechanisms of information handling in neural assemblies involved in computational and cognitive tasks is a challenging problem. Synergetic cooperation of neurons in time domain, through synchronization of firing of multiple spatially distant neurons, has been widely spread as the main paradigm. Complementary, the brain may also employ information coding and processing in spatial dimension. Then, the result of computation depends also on the spatial distribution of long-scale information. The latter bi-dimensional alternative is notably less explored in the literature. Here, we propose and theoretically illustrate a concept of spatiotemporal representation and processing of long-scale information in laminar neural structures. We argue that relevant information may be hidden in self-sustained traveling waves of neuronal activity and then their nonlinear interaction yields efficient wave-processing of spatiotemporal information. Using as a testbed a chain of FitzHugh-Nagumo neurons, we show that the wave-processing can be achieved by incorporating into the single-neuron dynamics an additional voltage-gated membrane current. This local mechanism provides a chain of such neurons with new emergent network properties. In particular, nonlinear waves as a carrier of long-scale information exhibit a variety of functionally different regimes of interaction: from complete or asymmetric annihilation to transparent crossing. Thus neuronal chains can work as computational units performing different operations over spatiotemporal information. Exploiting complexity resonance these composite units can discard stimuli of too high or too low frequencies, while selectively compress those in the natural frequency range. We also show how neuronal chains can contextually interpret raw wave information. The same stimulus can be processed differently or identically according to the context set by a periodic wave train injected at the opposite end of the
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.
Spatiotemporal patterns, triggers and anatomies of seismically detected rockfalls
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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
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.
Eiichirou, Kawamori
2018-04-01
We report the observation of supercontinuum of Langmuir plasma waves, that exhibits broad power spectrum having significant spatio-temporal coherence grown from a monochromatic seed-wave, in one-dimensional particle-in-cell simulations. The Langmuir wave supercontinuum (LWSC) is formed when the seed wave excites side-band fields efficiently by the modulational instabilities. Its identification is achieved by the use of the tricoherence analysis, which detects four wave mixings (FWMs) of plasmons (plasma wave quanta), and evaluation of the first order coherence, which is a measure of temporal coherence, of the wave electric fields. The irreversible evolution to the coherent LWSC from the seed wave is realized by the wave-particle interactions causing stochastic electron motions in the phase space and the coherence of LWSC is maintained by the phase-preserving FWMs of plasmons. The LWSC corresponds to a quasi Bernstein-Greene-Kruskal mode.
Dynamics of baroclinic wave pattern in transition zones between different flow regimes
International Nuclear Information System (INIS)
Larcher, Thomas von; Egbers, Christoph
2005-01-01
Baroclinic waves, both steady and time-dependent, are studied experimentally in a differentially heated rotating cylindrical gap with a free surface, cooled from within. Water is used as working fluid. We focus especially on transition zones between different flow regimes, where complex flow pattern like mixed-mode states are found. The transition from steady wave regime to irregular flow is also of particular interest. The surface flow is observed with visualisation techniques. Velocity time series are measured with the optical laser-Doppler-velocimetry technique. Thermographic measurements are applied for temperature field visualisations
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
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
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
Spatiotemporal Patterns of Urbanization in a Developed Region of Eastern Coastal China
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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.
Beam pattern improvement by compensating array nonuniformities in a guided wave phased array
International Nuclear Information System (INIS)
Kwon, Hyu-Sang; Lee, Seung-Seok; Kim, Jin-Yeon
2013-01-01
This paper presents a simple data processing algorithm which can improve the performance of a uniform circular array based on guided wave transducers. The algorithm, being intended to be used with the delay-and-sum beamformer, effectively eliminates the effects of nonuniformities that can significantly degrade the beam pattern. Nonuniformities can arise intrinsically from the array geometry when the circular array is transformed to a linear array for beam steering and extrinsically from unequal conditions of transducers such as element-to-element variations of sensitivity and directivity. The effects of nonuniformities are compensated by appropriately imposing weight factors on the elements in the projected linear array. Different cases are simulated, where the improvements of the beam pattern, especially the level of the highest sidelobe, are clearly seen, and related issues are discussed. An experiment is performed which uses A0 mode Lamb waves in a steel plate, to demonstrate the usefulness of the proposed method. The discrepancy between theoretical and experimental beam patterns is explained by accounting for near-field effects. (paper)
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
Karve, Pranav M.; Fathi, Arash; Poursartip, Babak; Kallivokas, Loukas F.
2016-01-01
We discuss a methodology for computing the optimal spatio-temporal characteristics of surface wave sources necessary for delivering wave energy to a targeted subsurface formation. The wave stimulation is applied to the target formation to enhance
Spatiotemporal mapping of ground water pollution in a Greek lignite basin, using geostatistics
Energy Technology Data Exchange (ETDEWEB)
Modis, K. [National Technical Univ. of Athens, Athens (Greece)
2010-07-01
An issue of significant interest in the mining industry in Greece is the occurrence of chemical pollutants in ground water. Ammonium, nitrites and nitrates concentrations have been monitored through an extensive sampling network in the Ptolemais lignite opencast mining area in Greece. Due to intensive mining efforts in the area, the surface topology is continuously altered, affecting the life span of the water boreholes and resulting in messy spatiotemporal distribution of data. This paper discussed the spatiotemporal mapping of ground water pollution in the Ptolemais lignite basin, using geostatistics. More specifically, the spatiotemporal distribution of ground water contamination was examined by the application of the bayesian maximum entropy theory which allows merging spatial and temporal estimations in a single model. The paper provided a description of the site and discussed the materials and methods, including samples and statistics; variography; and spatiotemporal mapping. It was concluded that in the case of the Ptolemais mining area, results revealed an underlying average yearly variation pattern of pollutant concentrations. Inspection of the produced spatiotemporal maps demonstrated a continuous increase in the risk of ammonium contamination, while risk for the other two pollutants appeared in hot spots. 18 refs., 1 tab., 7 figs.
Spatiotemporal mapping of ground water pollution in a Greek lignite basin, using geostatistics
International Nuclear Information System (INIS)
Modis, K.
2010-01-01
An issue of significant interest in the mining industry in Greece is the occurrence of chemical pollutants in ground water. Ammonium, nitrites and nitrates concentrations have been monitored through an extensive sampling network in the Ptolemais lignite opencast mining area in Greece. Due to intensive mining efforts in the area, the surface topology is continuously altered, affecting the life span of the water boreholes and resulting in messy spatiotemporal distribution of data. This paper discussed the spatiotemporal mapping of ground water pollution in the Ptolemais lignite basin, using geostatistics. More specifically, the spatiotemporal distribution of ground water contamination was examined by the application of the bayesian maximum entropy theory which allows merging spatial and temporal estimations in a single model. The paper provided a description of the site and discussed the materials and methods, including samples and statistics; variography; and spatiotemporal mapping. It was concluded that in the case of the Ptolemais mining area, results revealed an underlying average yearly variation pattern of pollutant concentrations. Inspection of the produced spatiotemporal maps demonstrated a continuous increase in the risk of ammonium contamination, while risk for the other two pollutants appeared in hot spots. 18 refs., 1 tab., 7 figs.
International Nuclear Information System (INIS)
Borisenko, Konstantin B; Kirkland, Angus I
2014-01-01
We describe an algorithm to reconstruct the electron exit wave of a weak-phase object from single diffraction pattern. The algorithm uses analytic formulations describing the diffraction intensities through a representation of the object exit wave in a Gaussian basis. The reconstruction is achieved by solving an overdetermined system of non-linear equations using an easily parallelisable global multi-start search with Levenberg-Marquard optimisation and analytic derivatives
Izdebski, Krzysztof; Ward, Ronald R.; Yan, Yuling
2012-02-01
HSDI provides a whole new way to investigate visually intra-laryngeal behavior and posturing during phonation by providing detailed real-time information about laryngeal biomechanics that include observations about mucosal wave, wave motion directionality, glottic area wave form, asymmetry of vibrations within and across vocal folds and contact area of the glottis including posterior commissure closure. These observations are fundamental to our understanding and modeling of both normal and disordered phonation. In this preliminary report we focus on direct HSDI in vivo observations of not only the glottic region, but also on the entire supraglottic laryngeal posturing during fry, breathy/hiss and over-pressured phonation modes produced in a non-pathological settings. Analysis included spatio-temporal vibration patterns of vocal folds, multi-line kymograms, spectral PFFT analysis, and Nyquist spatio-temporal plots. The presented examples reveal that supraglottic contraction assists in prolonged closed phase of the vibratory cycle, and that prolonged closed phase is longest in fry and overpressure and shortest albeit complex in hiss. Hiss also allows for vocal fold vibration despite glottis separation. These findings need to be compared to pathologic phonation representing the three voice modes to derive at better differential diagnosis.
High Spatio-Temporal Resolution Bathymetry Estimation and Morphology
Bergsma, E. W. J.; Conley, D. C.; Davidson, M. A.; O'Hare, T. J.
2015-12-01
In recent years, bathymetry estimates using video images have become increasingly accurate. With the cBathy code (Holman et al., 2013) fully operational, bathymetry results with 0.5 metres accuracy have been regularly obtained at Duck, USA. cBathy is based on observations of the dominant frequencies and wavelengths of surface wave motions and estimates the depth (and hence allows inference of bathymetry profiles) based on linear wave theory. Despite the good performance at Duck, large discrepancies were found related to tidal elevation and camera height (Bergsma et al., 2014) and on the camera boundaries. A tide dependent floating pixel and camera boundary solution have been proposed to overcome these issues (Bergsma et al., under review). The video-data collection is set estimate depths hourly on a grid with resolution in the order of 10x25 meters. Here, the application of the cBathy at Porthtowan in the South-West of England is presented. Hourly depth estimates are combined and analysed over a period of 1.5 years (2013-2014). In this work the focus is on the sub-tidal region, where the best cBathy results are achieved. The morphology of the sub-tidal bar is tracked with high spatio-temporal resolution on short and longer time scales. Furthermore, the impact of the storm and reset (sudden and large changes in bathymetry) of the sub-tidal area is clearly captured with the depth estimations. This application shows that the high spatio-temporal resolution of cBathy makes it a powerful tool for coastal research and coastal zone management.
Dynamic patterns in a supported lipid bilayer driven by standing surface acoustic waves.
Hennig, Martin; Neumann, Jürgen; Wixforth, Achim; Rädler, Joachim O; Schneider, Matthias F
2009-11-07
In the past decades supported lipid bilayers (SLBs) have been an important tool in order to study the physical properties of biological membranes and cells. So far, controlled manipulation of SLBs is very limited. Here we present a new technology to create lateral patterns in lipid membranes controllable in both space and time. Surface acoustic waves (SAWs) are used to generate lateral standing waves on a piezoelectric substrate which create local "traps" in the lipid bilayer and lead to a lateral modulation in lipid concentration. We demonstrate that pattern formation is reversible and does not affect the integrity of the lipid bilayer as shown by extracting the diffusion constant of fluid membranes. The described method could possibly be used to design switchable interfaces for the lateral transport and organization of membrane bound macromolecules to create dynamic bioarrays and control biofilm formation.
Spatio-temporal statistical models with applications to atmospheric processes
International Nuclear Information System (INIS)
Wikle, C.K.
1996-01-01
This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model
Spatiotemporal Data Organization and Application Research
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.
Emergence of target waves in paced populations of cyclically competing species
Energy Technology Data Exchange (ETDEWEB)
Jiang Luoluo; Zhou Tao; Wang Binghong [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China); Perc, Matjaz [Department of Physics, Faculty of Natural Sciences and Mathematics, University of Maribor, Koroska cesta 160, SI-2000 Maribor (Slovenia); Huang Xin [Department of Physics, University of Science and Technology of China, Hefei 230026 (China)], E-mail: jiangluo@mail.ustc.edu.cn, E-mail: zhutou@ustc.edu, E-mail: matjaz.perc@uni-mb.si, E-mail: bhwang@ustc.edu.cn
2009-10-15
We investigate the emergence of target waves in a cyclic predator-prey model incorporating a periodic current of the three competing species in a small area situated at the center of a square lattice. The periodic current acts as a pacemaker, trying to impose its rhythm on the overall spatiotemporal evolution of the three species. We show that the pacemaker is able to nucleate target waves that eventually spread across the whole population, whereby three routes leading to this phenomenon can be distinguished depending on the mobility of the three species and the oscillation period of the localized current. First, target waves can emerge due to the synchronization between the periodic current and oscillations of the density of the three species on the spatial grid. The second route is similar to the first, the difference being that the synchronization sets in only intermittently. Finally, the third route toward target waves is realized when the frequency of the pacemaker is much higher than that characterizing the oscillations of the overall density of the three species. By considering the mobility and frequency of the current as variable parameters, we thus provide insights into the mechanisms of pattern formation resulting from the interplay between local and global dynamics in systems governed by cyclically competing species.
Evolution of wave patterns and temperature field in shock-tube flow
Kiverin, A. D.; Yakovenko, I. S.
2018-05-01
The paper is devoted to the numerical analysis of wave patterns behind a shock wave propagating in a tube filled with a gaseous mixture. It is shown that the flow inside the boundary layer behind the shock wave is unstable, and the way the instability develops fully corresponds to the solution obtained for the boundary layer over a flat plate. Vortical perturbations inside the boundary layer determine the nonuniformity of the temperature field. In turn, exactly these nonuniformities define the way the ignition kernels arise in the combustible mixture after the reflected shock interaction with the boundary layer. In particular, the temperature nonuniformity determines the spatial limitations of probable ignition kernel position relative to the end wall and side walls of the tube. In the case of low-intensity incident shocks the ignition could start not farther than the point of first interaction between the reflected shock wave and roller vortices formed in the process of boundary layer development. Proposed physical mechanisms are formulated in general terms and can be used for interpretation of the experimental data in any systems with a delayed exothermal reaction start. It is also shown that contact surface thickening occurs due to its interaction with Tollmien-Schlichting waves. This conclusion is of importance for understanding the features of ignition in shock tubes operating in the over-tailored regime.
Modulated amplitude waves in Bose-Einstein condensates
International Nuclear Information System (INIS)
Porter, Mason A.; Cvitanovic, Predrag
2004-01-01
We analyze spatiotemporal structures in the Gross-Pitaevskii equation to study the dynamics of quasi-one-dimensional Bose-Einstein condensates (BECs) with mean-field interactions. A coherent structure ansatz yields a parametrically forced nonlinear oscillator, to which we apply Lindstedt's method and multiple-scale perturbation theory to determine the dependence of the intensity of periodic orbits ('modulated amplitude waves') on their wave number. We explore BEC band structure in detail using Hamiltonian perturbation theory and supporting numerical simulations
International Nuclear Information System (INIS)
Cheong, Yong-Moo; Kim, Shin
2007-01-01
The presence of damage or defects in pipes or tubes is one of the major problems in nuclear power plants. However, in many cases, it is difficult to inspect all of them by the conventional ultrasonic methods, because of their geometrical complexity and inaccessibility. The magnetostrictive guided wave technique has several advantages for practical applications, such as a 100- percent volumetric coverage of a long segment of a structure, a reduced inspection time and its cost effectiveness, as well as its' relatively simple structure. One promising feature of the magnetostrictive sensor technique is that the wave patterns are relatively clear and simple compared to the conventional piezoelectric ultrasonic transducer. If we can characterize the evolution of the defect signals, it can be a promising tool for a structural health monitoring of pipes for a long period as well as the identification of flaws. An in-bore guided wave probe was developed for an application to small bore heat exchanger tubes. The magnetostrictive probe installed on the hollow cylindrical waveguide generates and detects torsional waves in the waveguide. This waveguide is expanded by the draw bar to create an intimate mechanical contact between the waveguide and the inside surface of the tube being tested. In this paper, we analyzed the wave patterns reflected from various artificial holes in a titanium tube, which is used in the condenser in a nuclear power plant. The torsional guided waves were generated and received by a coil and a DC magnetized nickel strip as well as an inbore guided wave probe. The wave patterns from various defects were compared with two different sensor techniques and a detectable limit of the defected was estimated
Micromagnetic computer simulations of spin waves in nanometre-scale patterned magnetic elements
International Nuclear Information System (INIS)
Kim, Sang-Koog
2010-01-01
Current needs for further advances in the nanotechnologies of information-storage and -processing devices have attracted a great deal of interest in spin (magnetization) dynamics in nanometre-scale patterned magnetic elements. For instance, the unique dynamic characteristics of non-uniform magnetic microstructures such as various types of domain walls, magnetic vortices and antivortices, as well as spin wave dynamics in laterally restricted thin-film geometries, have been at the centre of extensive and intensive researches. Understanding the fundamentals of their unique spin structure as well as their robust and novel dynamic properties allows us to implement new functionalities into existing or future devices. Although experimental tools and theoretical approaches are effective means of understanding the fundamentals of spin dynamics and of gaining new insights into them, the limitations of those same tools and approaches have left gaps of unresolved questions in the pertinent physics. As an alternative, however, micromagnetic modelling and numerical simulation has recently emerged as a powerful tool for the study of a variety of phenomena related to spin dynamics of nanometre-scale magnetic elements. In this review paper, I summarize the recent results of simulations of the excitation and propagation and other novel wave characteristics of spin waves, highlighting how the micromagnetic computer simulation approach contributes to an understanding of spin dynamics of nanomagnetism and considering some of the merits of numerical simulation studies. Many examples of micromagnetic modelling for numerical calculations, employing various dimensions and shapes of patterned magnetic elements, are given. The current limitations of continuum micromagnetic modelling and of simulations based on the Landau-Lifshitz-Gilbert equation of motion of magnetization are also discussed, along with further research directions for spin-wave studies.
Micromagnetic computer simulations of spin waves in nanometre-scale patterned magnetic elements
Kim, Sang-Koog
2010-07-01
Current needs for further advances in the nanotechnologies of information-storage and -processing devices have attracted a great deal of interest in spin (magnetization) dynamics in nanometre-scale patterned magnetic elements. For instance, the unique dynamic characteristics of non-uniform magnetic microstructures such as various types of domain walls, magnetic vortices and antivortices, as well as spin wave dynamics in laterally restricted thin-film geometries, have been at the centre of extensive and intensive researches. Understanding the fundamentals of their unique spin structure as well as their robust and novel dynamic properties allows us to implement new functionalities into existing or future devices. Although experimental tools and theoretical approaches are effective means of understanding the fundamentals of spin dynamics and of gaining new insights into them, the limitations of those same tools and approaches have left gaps of unresolved questions in the pertinent physics. As an alternative, however, micromagnetic modelling and numerical simulation has recently emerged as a powerful tool for the study of a variety of phenomena related to spin dynamics of nanometre-scale magnetic elements. In this review paper, I summarize the recent results of simulations of the excitation and propagation and other novel wave characteristics of spin waves, highlighting how the micromagnetic computer simulation approach contributes to an understanding of spin dynamics of nanomagnetism and considering some of the merits of numerical simulation studies. Many examples of micromagnetic modelling for numerical calculations, employing various dimensions and shapes of patterned magnetic elements, are given. The current limitations of continuum micromagnetic modelling and of simulations based on the Landau-Lifshitz-Gilbert equation of motion of magnetization are also discussed, along with further research directions for spin-wave studies.
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...
Pattern formation and three-dimensional instability in rotating flows
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.
Rocket photographs of fine structure and wave patterns in the solar temperature minimum
Bonnet, R. M.; Decaudin, M.; Foing, B.; Bruner, M.; Acton, L. W.; Brown, W. A.
1982-01-01
A new series of high resolution pictures of the sun has been obtained during the second flight of the Transition Region Camera which occurred on September 23, 1980. The qualitative analysis of the results indicates that a substantial portion of the solar surface at the temperature minimum radiates in non-magnetic regions and from features below 1 arcsec in size. Wave patterns are observed on the 160 nm temperature minimum pictures. They are absent on the Lyman alpha pictures. Their physical characteristics are compatible with those of gravitational and acoustic waves generated by exploding granules.
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.
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.
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.
Rogue waves, rational solutions, the patterns of their zeros and integral relations
International Nuclear Information System (INIS)
Ankiewicz, Adrian; Akhmediev, Nail; Clarkson, Peter A
2010-01-01
The focusing nonlinear Schroedinger equation, which describes generic nonlinear phenomena, including waves in the deep ocean and light pulses in optical fibres, supports a whole hierarchy of recently discovered rational solutions. We present recurrence relations for the hierarchy, the pattern of zeros for each solution and a set of integral relations which characterizes them. (fast track communication)
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.
Interference of Locally Forced Internal Waves in Non-Uniform Stratifications
Supekar, Rohit; Peacock, Thomas
2017-11-01
Several studies have investigated the effect of constructive or destructive interference on the transmission of internal waves propagating through non-uniform stratifications. Such studies have been performed for internal waves that are spatiotemporally harmonic. To understand the effect of localization, we perform a theoretical and experimental study of the transmission of two-dimensional internal waves that are generated by a spatiotemporally localized boundary forcing. This is done by considering an idealized problem and applying a weakly viscous semi-analytic linear model. Parametric studies using this model show that localization leads to the disappearance of transmission peaks and troughs that would otherwise be present for a harmonic forcing. Laboratory experiments that we perform provide a clear indication of this physical effect. Based on the group velocity and angle of propagation of the internal waves, a practical criteria that assesses when the transmission peaks or troughs are evident, is obtained. It is found that there is a significant difference in the predicted energy transfer due to a harmonic and non-harmonic forcing which has direct implications to various physical forcings such as a storm over the ocean.
Adaptive changes in spatiotemporal gait characteristics in women during pregnancy.
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.
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.
Dunlap, L.; Li, C.; Dickerson, R. R.; Krotkov, N. A.
2015-12-01
Weather systems, particularly mid-latitude wave cyclones, have been known to play an important role in the short-term variation of near-surface air pollution. Ground measurements and model simulations have demonstrated that stagnant air and minimal precipitation associated with high pressure systems are conducive to pollutant accumulation. With the passage of a cold front, built up pollution is transported downwind of the emission sources or washed out by precipitation. This concept is important to note when studying long-term changes in spatio-temporal pollution distribution, but has not been studied in detail from space. In this study, we focus on East Asia (especially the industrialized eastern China), where numerous large power plants and other point sources as well as area sources emit large amounts of SO2, an important gaseous pollutant and a precursor of aerosols. Using data from the Aura Ozone Monitoring Instrument (OMI) we show that such weather driven distribution can indeed be discerned from satellite data by utilizing probability distribution functions (PDFs) of SO2 column content. These PDFs are multimodal and give insight into the background pollution level at a given location and contribution from local and upwind emission sources. From these PDFs it is possible to determine the frequency for a given region to have SO2 loading that exceeds the background amount. By comparing OMI-observed long-term change in the frequency with meteorological data, we can gain insights into the effects of climate change (e.g., the weakening of Asian monsoon) on regional air quality. Such insight allows for better interpretation of satellite measurements as well as better prediction of future pollution distribution as a changing climate gives way to changing weather patterns.
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.
Nehmetallah, Georges; Banerjee, Partha; Khoury, Jed
2015-03-01
The nonlinearity inherent in four-wave mixing in photorefractive (PR) materials is used for adaptive filtering. Examples include script enhancement on a periodic pattern, scratch and defect cluster enhancement, periodic pattern dislocation enhancement, etc. through intensity filtering image manipulation. Organic PR materials have large space-bandwidth product, which makes them useful in adaptive filtering techniques in quality control systems. For instance, in the case of edge enhancement, phase conjugation via four-wave mixing suppresses the low spatial frequencies of the Fourier spectrum of an aperiodic image and consequently leads to image edge enhancement. In this work, we model, numerically verify, and simulate the performance of a four wave mixing setup used for edge, defect and pattern detection in periodic amplitude and phase structures. The results show that this technique successfully detects the slightest defects clearly even with no enhancement. This technique should facilitate improvements in applications such as image display sharpness utilizing edge enhancement, production line defect inspection of fabrics, textiles, e-beam lithography masks, surface inspection, and materials characterization.
Analysis of Wave Velocity Patterns in Black Cherry Trees and its Effect on Internal Decay Detection
Guanghui Li; Xiping Wang; Jan Wiedenbeck; Robert J. Ross
2013-01-01
In this study, we examined stress wave velocity patterns in the cross sections of black cherry trees, developed analytical models of stress wave velocity in sound healthy trees, and then tested the effectiveness of the models as a tool for tree decay diagnosis. Acoustic tomography data of the tree cross sections were collected from 12 black cherry trees at a production...
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
A spatio-temporal process data model for characterizing marine disasters
International Nuclear Information System (INIS)
Jiang, B; Gao, T; Zhang, X; Huang, X
2014-01-01
Marine disasters are a more prevalent problem in China than in many other countries. Based on the development of a status quo of China's marine disaster the space-time process model is used. The model uses the ocean's temperature field, salinity field, water density field, surface wind field, wave field and other four-dimensional spatio-temporal quantities. This paper studies that model in detail. This study aims at using the theory to provide support during marine disasters in an effort to prevent or decrease their frequency in the future
Spatiotemporal synchronization of drift waves in a magnetron sputtering plasma
Energy Technology Data Exchange (ETDEWEB)
Martines, E.; Zuin, M.; Cavazzana, R.; Antoni, V.; Serianni, G.; Spolaore, M.; Vianello, N. [Consorzio RFX, Padova (Italy); Adámek, J. [Institute of Plasma Physics AS CR, Prague (Czech Republic)
2014-10-15
A feedforward scheme is applied for drift waves control in a magnetized magnetron sputtering plasma. A system of driven electrodes collecting electron current in a limited region of the explored plasma is used to interact with unstable drift waves. Drift waves actually appear as electrostatic modes characterized by discrete wavelengths of the order of few centimeters and frequencies of about 100 kHz. The effect of external quasi-periodic, both in time and space, travelling perturbations is studied. Particular emphasis is given to the role played by the phase relation between the natural and the imposed fluctuations. It is observed that it is possible by means of localized electrodes, collecting currents which are negligible with respect to those flowing in the plasma, to transfer energy to one single mode and to reduce that associated to the others. Due to the weakness of the external action, only partial control has been achieved.
Spatiotemporal synchronization of drift waves in a magnetron sputtering plasma
International Nuclear Information System (INIS)
Martines, E.; Zuin, M.; Cavazzana, R.; Antoni, V.; Serianni, G.; Spolaore, M.; Vianello, N.; Adámek, J.
2014-01-01
A feedforward scheme is applied for drift waves control in a magnetized magnetron sputtering plasma. A system of driven electrodes collecting electron current in a limited region of the explored plasma is used to interact with unstable drift waves. Drift waves actually appear as electrostatic modes characterized by discrete wavelengths of the order of few centimeters and frequencies of about 100 kHz. The effect of external quasi-periodic, both in time and space, travelling perturbations is studied. Particular emphasis is given to the role played by the phase relation between the natural and the imposed fluctuations. It is observed that it is possible by means of localized electrodes, collecting currents which are negligible with respect to those flowing in the plasma, to transfer energy to one single mode and to reduce that associated to the others. Due to the weakness of the external action, only partial control has been achieved
Evaluation of urban sprawl and urban landscape pattern in a rapidly developing region.
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.
Ahrends, Antje; Burgess, Neil D; Milledge, Simon A H; Bulling, Mark T; Fisher, Brendan; Smart, James C R; Clarke, G Philip; Mhoro, Boniface E; Lewis, Simon L
2010-08-17
Tropical forest degradation emits carbon at a rate of approximately 0.5 Pgxy(-1), reduces biodiversity, and facilitates forest clearance. Understanding degradation drivers and patterns is therefore crucial to managing forests to mitigate climate change and reduce biodiversity loss. Putative patterns of degradation affecting forest stocks, carbon, and biodiversity have variously been described previously, but these have not been quantitatively assessed together or tested systematically. Economic theory predicts a systematic allocation of land to its highest use value in response to distance from centers of demand. We tested this theory to see if forest exploitation would expand through time and space as concentric waves, with each wave targeting lower value products. We used forest data along a transect from 10 to 220 km from Dar es Salaam (DES), Tanzania, collected at two points in time (1991 and 2005). Our predictions were confirmed: high-value logging expanded 9 kmxy(-1), and an inner wave of lower value charcoal production 2 kmxy(-1). This resource utilization is shown to reduce the public goods of carbon storage and species richness, which significantly increased with each kilometer from DES [carbon, 0.2 Mgxha(-1); 0.1 species per sample area (0.4 ha)]. Our study suggests that tropical forest degradation can be modeled and predicted, with its attendant loss of some public goods. In sub-Saharan Africa, an area experiencing the highest rate of urban migration worldwide, coupled with a high dependence on forest-based resources, predicting the spatiotemporal patterns of degradation can inform policies designed to extract resources without unsustainably reducing carbon storage and biodiversity.
Energy Technology Data Exchange (ETDEWEB)
Brandt, C; Grulke, O; Klinger, T, E-mail: christian.brandt@lpmi.uhp-nancy.f [Max-Planck-Institute for Plasma Physics, EURATOM Association, Wendelsteinstrasse 1, D-17491 Greifswald (Germany)
2010-05-15
Experiments in a cylindrical magnetized plasma on the control of drift waves by means of two different spatiotemporal open-loop control systems-an electrostatic and an electromagnetic exciter-are reported. The drift wave dynamics is controlled by a mode-selective signal created with azimuthal arrangements of eight electrodes and eight saddle coils, respectively. Nonlinear interaction between the control signals and drift waves is observed, leading to synchronization of coherent drift waves and suppression of broadband drift wave turbulence. The cross-phase between density and potential fluctuations reduces from {approx}{pi}/2 in turbulence to {approx}0 in controlled turbulence. Hence, the cross-field transport is reduced to the level of coherent drift waves. For both control systems the coupling to the drift wave can be ascribed to the drive of parallel currents, on the one hand via direct electric contact and, on the other hand, via electromagnetic induction.
Multiple scroll wave chimera states
Maistrenko, Volodymyr; Sudakov, Oleksandr; Osiv, Oleksiy; Maistrenko, Yuri
2017-06-01
We report the appearance of three-dimensional (3D) multiheaded chimera states that display cascades of self-organized spatiotemporal patterns of coexisting coherence and incoherence. We demonstrate that the number of incoherent chimera domains can grow additively under appropriate variations of the system parameters generating thereby head-adding cascades of the scroll wave chimeras. The phenomenon is derived for the Kuramoto model of N 3 identical phase oscillators placed in the unit 3D cube with periodic boundary conditions, parameters being the coupling radius r and phase lag α. To obtain the multiheaded chimeras, we perform the so-called `cloning procedure' as follows: choose a sample single-headed 3D chimera state, make appropriate scale transformation, and put some number of copies of them into the unit cube. After that, start numerical simulations with slightly perturbed initial conditions and continue them for a sufficiently long time to confirm or reject the state existence and stability. In this way it is found, that multiple scroll wave chimeras including those with incoherent rolls, Hopf links and trefoil knots admit this sort of multiheaded regeneration. On the other hand, multiple 3D chimeras without spiral rotations, like coherent and incoherent balls, tubes, crosses, and layers appear to be unstable and are destroyed rather fast even for arbitrarily small initial perturbations.
Wave energy patterns of counterpulsation: a novel approach with wave intensity analysis.
Lu, Pong-Jeu; Yang, Chi-Fu Jeffrey; Wu, Meng-Yu; Hung, Chun-Hao; Chan, Ming-Yao; Hsu, Tzu-Cheng
2011-11-01
In counterpulsation, diastolic augmentation increases coronary blood flow and systolic unloading reduces left ventricular afterload. We present a new approach with wave intensity analysis to revisit and explain counterpulsation principles. In an acute porcine model, a standard intra-aortic balloon pump was placed in descending aorta in 4 pigs. We measured pressure and velocity with probes in left anterior descending artery and aorta during and without intra-aortic balloon pump assistance. Wave intensities of aortic and left coronary waves were derived from pressure and flow measurements with synchronization correction. We identified predominating waves in counterpulsation. In the aorta, during diastolic augmentation, intra-aortic balloon inflation generated a backward compression wave, with a "pushing" effect toward the aortic root that translated to a forward compression wave into coronary circulation. During systolic unloading, intra-aortic balloon pump deflation generated a backward expansion wave that "sucked" blood from left coronary bed into the aorta. While this backward expansion wave translated to reduced left ventricular afterload, the "sucking" effect resulted in left coronary blood steal, as demonstrated by a forward expansion wave in left anterior descending coronary flow. The waves were sensitive to inflation and deflation timing, with just 25 ms delay from standard deflation timing leading to weaker forward expansion wave and less coronary regurgitation. Intra-aortic balloon pumps generate backward-traveling waves that predominantly drive aortic and coronary blood flow during counterpulsation. Wave intensity analysis of arterial circulations may provide a mechanism to explain diastolic augmentation and systolic unloading of intra-aortic balloon pump counterpulsation. Copyright © 2011 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.
Nonreciprocal Thermal Material by Spatiotemporal Modulation
Torrent, Daniel; Poncelet, Olivier; Batsale, Jean-Chirstophe
2018-03-01
The thermal properties of a material with a spatiotemporal modulation, in the form of a traveling wave, in both the thermal conductivity and the specific heat capacity are studied. It is found that these materials behave as materials with an internal convectionlike term that provides them with nonreciprocal properties, in the sense that the heat flux has different properties when it propagates in the same direction or in the opposite one to the modulation of the parameters. An effective medium description is presented which accurately describes the modulated material, and numerical simulations support this description and verify the nonreciprocal properties of the material. It is found that these materials are promising candidates for the design of thermal diodes and other advanced devices for the control of the heat flow at all scales.
Cavitation cluster dynamics in shock-wave lithotripsy: Part I
Arora, M.; Junge, L.; Junge, L.; Ohl, C.D.
2005-01-01
The spatiotemporal dynamics of cavitation bubble growth and collapse in shock-wave lithotripsy in a free field was studied experimentally. The lithotripter was equipped with two independently triggerable layers of piezoceramics. The front and back layers generated positive pressure amplitudes of 30
Karve, Pranav M.
2016-12-28
We discuss a methodology for computing the optimal spatio-temporal characteristics of surface wave sources necessary for delivering wave energy to a targeted subsurface formation. The wave stimulation is applied to the target formation to enhance the mobility of particles trapped in its pore space. We formulate the associated wave propagation problem for three-dimensional, heterogeneous, semi-infinite, elastic media. We use hybrid perfectly matched layers at the truncation boundaries of the computational domain to mimic the semi-infiniteness of the physical domain of interest. To recover the source parameters, we define an inverse source problem using the mathematical framework of constrained optimization and resolve it by employing a reduced-space approach. We report the results of our numerical experiments attesting to the methodology\\'s ability to specify the spatio-temporal description of sources that maximize wave energy delivery. Copyright © 2016 John Wiley & Sons, Ltd.
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
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.
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.
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.
Intelligent feature selection techniques for pattern classification of Lamb wave signals
International Nuclear Information System (INIS)
Hinders, Mark K.; Miller, Corey A.
2014-01-01
Lamb wave interaction with flaws is a complex, three-dimensional phenomenon, which often frustrates signal interpretation schemes based on mode arrival time shifts predicted by dispersion curves. As the flaw severity increases, scattering and mode conversion effects will often dominate the time-domain signals, obscuring available information about flaws because multiple modes may arrive on top of each other. Even for idealized flaw geometries the scattering and mode conversion behavior of Lamb waves is very complex. Here, multi-mode Lamb waves in a metal plate are propagated across a rectangular flat-bottom hole in a sequence of pitch-catch measurements corresponding to the double crosshole tomography geometry. The flaw is sequentially deepened, with the Lamb wave measurements repeated at each flaw depth. Lamb wave tomography reconstructions are used to identify which waveforms have interacted with the flaw and thereby carry information about its depth. Multiple features are extracted from each of the Lamb wave signals using wavelets, which are then fed to statistical pattern classification algorithms that identify flaw severity. In order to achieve the highest classification accuracy, an optimal feature space is required but it’s never known a priori which features are going to be best. For structural health monitoring we make use of the fact that physical flaws, such as corrosion, will only increase over time. This allows us to identify feature vectors which are topologically well-behaved by requiring that sequential classes “line up” in feature vector space. An intelligent feature selection routine is illustrated that identifies favorable class distributions in multi-dimensional feature spaces using computational homology theory. Betti numbers and formal classification accuracies are calculated for each feature space subset to establish a correlation between the topology of the class distribution and the corresponding classification accuracy
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.
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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.
Tensor-based spatiotemporal saliency detection
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.
Mapping child maltreatment risk: a 12-year spatio-temporal analysis of neighborhood influences.
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
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...
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.
Surface-Wave Pulse Routing around Sharp Right Angles
Gao, Z.; Xu, H.; Gao, F.; Zhang, Y.; Luo, Y.; Zhang, B.
2018-04-01
Surface-plasmon polaritons (SPPs), or localized electromagnetic surface waves propagating on a metal-dielectric interface, are deemed promising information carriers for future subwavelength terahertz and optical photonic circuitry. However, surface waves fundamentally suffer from scattering loss when encountering sharp corners in routing and interconnection of photonic signals. Previous approaches enabling scattering-free surface-wave guidance around sharp corners are limited to either volumetric waveguide environments or extremely narrow bandwidth, being unable to guide a surface-wave pulse (SPP wave packet) on an on-chip platform. Here, in a surface-wave band-gap crystal implemented on a single metal surface, we demonstrate in time-domain routing a surface-wave pulse around multiple sharp right angles without perceptible scattering. Our work not only offers a solution to on-chip surface-wave pulse routing along an arbitrary path, but it also provides spatiotemporal information on the interplay between surface-wave pulses and sharp corners, both of which are desirable in developing high-performance large-scale integrated photonic circuits.
A multimodal wave spectrum-based approach for statistical downscaling of local wave climate
Hegermiller, Christie; Antolinez, Jose A A; Rueda, Ana C.; Camus, Paula; Perez, Jorge; Erikson, Li; Barnard, Patrick; Mendez, Fernando J.
2017-01-01
Characterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g. the Pacific). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, we address these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into “wave families,” defined by spectral peaks and discrete generation regions, and relates atmospheric conditions in distant regions of the ocean basin to local wave conditions by incorporating travel times computed from effective energy flux across the ocean basin. When applied to locations with multimodal wave spectra, including Southern California and Trujillo, Peru, the new methodology improves the ability of the statistical model to project significant wave height, peak period, and direction for each wave family, retaining more information from the full wave spectrum. This work is the base of statistical downscaling by weather types, which has recently been applied to coastal flooding and morphodynamic applications.
Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks
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.
Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks.
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.
Cambazoglu, M. K.; Jacobs, G. A.; Howden, S. D.; Book, J. W.; Arnone, R.; Soto Ramos, I. M.; Vandermeulen, R. A.; Greer, A. T.; Miles, T. N.
2016-02-01
Internal waves enhance mixing in the upper ocean, transport nutrients and plankton over the water column and across the shelf from deeper waters to shallower coastal areas, and could also transport pollutants such as hydrocarbons onshore during an oil spill event. This study aims to characterize internal waves in the northern Gulf of Mexico (nGoM) and investigate the possible generation and dissipation mechanisms using a high-resolution (1-km) application of the Navy Coastal Ocean Model (NCOM). Three dimensional model products are used to detect the propagation patterns of internal waves. The vertical structure of internal waves is studied and the role of stratification is analyzed by looking at the temperature, salinity and velocity variations along the water column. The model predictions suggest the generation of internal waves on the continental shelf, therefore the role of ocean bottom topography interacting with tides and general circulation features such as the Loop Current Eddy front, on the internal wave generation will be discussed. The time periods of internal wave occurrences are identified from model predictions and compared to satellite ocean color imagery. Further data analysis, e.g. Fourier analysis, is implemented to determine internal wavelengths and frequencies and to determine if the response of internal waves are at tidal periods or at different frequencies. The atmospheric forcing provided to NCOM and meteorological data records are analyzed to define the interaction between wind forcing and internal wave generation. Wavelet analysis characterizes the ocean response to atmospheric events with periodic frequencies. Ocean color satellite imagery was used to visualize the location of the Mississippi river plume (and other oceanic features) and compared to the model predictions because the enhanced stratification from freshwater plumes which propagate across the Mississippi Bight can provide favorable conditions in coastal waters for internal wave
Ogawa, Kazuhisa; Kobayashi, Hirokazu; Tomita, Akihisa
2018-02-01
The quantum interference of entangled photons forms a key phenomenon underlying various quantum-optical technologies. It is known that the quantum interference patterns of entangled photon pairs can be reconstructed classically by the time-reversal method; however, the time-reversal method has been applied only to time-frequency-entangled two-photon systems in previous experiments. Here, we apply the time-reversal method to the position-wave-vector-entangled two-photon systems: the two-photon Young interferometer and the two-photon beam focusing system. We experimentally demonstrate that the time-reversed systems classically reconstruct the same interference patterns as the position-wave-vector-entangled two-photon systems.
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.
Wave refraction and longshore transport patterns along the southern Santa Catarina coast
Directory of Open Access Journals (Sweden)
Eduardo Siegle
2007-06-01
Full Text Available Based on the wave climate for the southern Brazilian coast, wave refraction has been modelled in order to obtain the refracted wave heights and directions along the southern Santa Catarina coast, providing the needed information for potential longshore drift estimates. According to its coastline orientation, different sectors of the coast present varying longshore drift patterns. Estimates have been made for the yearly-averaged wave climate as well as for each season, showing thereby the longshore drift patterns along the year. Based on the results of the potential longshore drift intensities and directions and on the shoreline outline in plan, it has been possible to identify a strongly drift-dominated coast in the south turning to a mixed drift and swash dominated coast towards the north of the studied area. Contrasting patterns of longshore drift between the southern and northern portion of the coastline indicate a sediment surplus in the central portion, making sediment available for cross-shore transport processes, either on- or offshore. Considering long-term aspects, the longshore drift patterns are in agreement with the coastal infilling process which has mainly been driven by persistent surplus from littoral sediment drift.Com base no clima de ondas para o sul da costa brasileira, a refração de ondas foi modelada para a obtenção de alturas e direção das ondas ao longo da costa sul de Santa Catarina. Essas informações permitem a estimativa da deriva litorânea potencial para a região. De acordo com a orientação da linha de costa, diferentes setores do litoral apresentam variados padrões de deriva. As estimativas foram realizadas com base nos dados médios anuais e para cada estação do ano, demonstrando assim a variabilidade dos padrões ao longo do ano. A configuração da linha de costa e os resultados das estimativas de intensidade e direção da deriva indicam o predomínio da deriva litorânea na porção sul da área e
Parametric spatiotemporal oscillation in reaction-diffusion systems.
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.
Migraine aura: retracting particle-like waves in weakly susceptible cortex.
Directory of Open Access Journals (Sweden)
Markus A Dahlem
Full Text Available Cortical spreading depression (SD has been suggested to underlie migraine aura. Despite a precise match in speed, the spatio-temporal patterns of SD observed in animal cortex and aura symptoms mapped to the cortical surface ordinarily differ in aspects of size and shape. We show that this mismatch is reconciled by utilizing that both pattern types bifurcate from an instability point of generic reaction-diffusion models. To classify these spatio-temporal pattern we suggest a susceptibility scale having the value sigma = 1 at the instability point. We predict that human cortex is only weakly susceptible to SD (sigma1, and potentially silent aura occurring below a second bifurcation point at sigma = 0 on the susceptible scale.
Wildlife in the Matrix: Spatio-Temporal Patterns of Herbivore Occurrence in Karnataka, India
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.
A Model of the Spatio-temporal Dynamics of Drosophila Eye Disc Development.
Fried, Patrick; Sánchez-Aragón, Máximo; Aguilar-Hidalgo, Daniel; Lehtinen, Birgitta; Casares, Fernando; Iber, Dagmar
2016-09-01
Patterning and growth are linked during early development and have to be tightly controlled to result in a functional tissue or organ. During the development of the Drosophila eye, this linkage is particularly clear: the growth of the eye primordium mainly results from proliferating cells ahead of the morphogenetic furrow (MF), a moving signaling wave that sweeps across the tissue from the posterior to the anterior side, that induces proliferating cells anterior to it to differentiate and become cell cycle quiescent in its wake. Therefore, final eye disc size depends on the proliferation rate of undifferentiated cells and on the speed with which the MF sweeps across the eye disc. We developed a spatio-temporal model of the growing eye disc based on the regulatory interactions controlled by the signals Decapentaplegic (Dpp), Hedgehog (Hh) and the transcription factor Homothorax (Hth) and explored how the signaling patterns affect the movement of the MF and impact on eye disc growth. We used published and new quantitative data to parameterize the model. In particular, two crucial parameter values, the degradation rate of Hth and the diffusion coefficient of Hh, were measured. The model is able to reproduce the linear movement of the MF and the termination of growth of the primordium. We further show that the model can explain several mutant phenotypes, but fails to reproduce the previously observed scaling of the Dpp gradient in the anterior compartment.
A Model of the Spatio-temporal Dynamics of Drosophila Eye Disc Development.
Directory of Open Access Journals (Sweden)
Patrick Fried
2016-09-01
Full Text Available Patterning and growth are linked during early development and have to be tightly controlled to result in a functional tissue or organ. During the development of the Drosophila eye, this linkage is particularly clear: the growth of the eye primordium mainly results from proliferating cells ahead of the morphogenetic furrow (MF, a moving signaling wave that sweeps across the tissue from the posterior to the anterior side, that induces proliferating cells anterior to it to differentiate and become cell cycle quiescent in its wake. Therefore, final eye disc size depends on the proliferation rate of undifferentiated cells and on the speed with which the MF sweeps across the eye disc. We developed a spatio-temporal model of the growing eye disc based on the regulatory interactions controlled by the signals Decapentaplegic (Dpp, Hedgehog (Hh and the transcription factor Homothorax (Hth and explored how the signaling patterns affect the movement of the MF and impact on eye disc growth. We used published and new quantitative data to parameterize the model. In particular, two crucial parameter values, the degradation rate of Hth and the diffusion coefficient of Hh, were measured. The model is able to reproduce the linear movement of the MF and the termination of growth of the primordium. We further show that the model can explain several mutant phenotypes, but fails to reproduce the previously observed scaling of the Dpp gradient in the anterior compartment.
Samsom, M.; Fraser, R.; Smout, A. J.; Verhagen, M. A.; Adachi, K.; Horowitz, M.; Dent, J.
1999-01-01
The organization of lumen-occlusive pressure waves is believed to be an important determinant of luminal flow. At present, little is known about the organization of small intestinal pressure waves in humans. The aim of the present study was to characterize the spatiotemporal organization of small
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.
Protopapa, M L; De Tomasi, F; Di Giulio, M; Perrone, M R; Scaglione, S
2002-01-01
The standing-wave electric field pattern that forms inside an optical coating as a consequence of laser irradiation is one of the factors influencing the coating laser-induced damage threshold. The influence of the standing-wave electric field profile on the damage resistance to ultraviolet radiation of hafnium dioxide (HfO sub 2) thin films was investigated in this work. To this end, HfO sub 2 thin films of different thicknesses deposited by the electron beam evaporation technique at the same deposition conditions were analyzed. Laser damage thresholds of the samples were measured at 308 nm (XeCl laser) by the photoacoustic beam deflection technique and microscopic inspections. The dependence of the laser damage threshold on the standing-wave electric field pattern was analyzed.
A perturbative analysis of modulated amplitude waves in Bose-Einstein condensates
International Nuclear Information System (INIS)
Porter, Mason A.; Cvitanovic, Predrag
2004-01-01
We apply Lindstedt's method and multiple scale perturbation theory to analyze spatio-temporal structures in nonlinear Schroedinger equations and thereby study the dynamics of quasi-one-dimensional Bose-Einstein condensates with mean-field interactions. We determine the dependence of the amplitude of modulated amplitude waves on their wave number. We also explore the band structure of Bose-Einstein condensates in detail using Hamiltonian perturbation theory and supporting numerical simulations
Characterizing the intra-urban spatiotemporal dynamics of High Heat Stress Zones (Hotspots)
Shreevastava, A.; Rao, P. S.; McGrath, G. S.
2017-12-01
In this study, we present an innovative framework to characterize the spatio-temporal dynamics of High Heat Stress Zones (Hot spots) created within an Urban area in the event of a Heat Wave. Heat waves are one of the leading causes of weather-related human mortality in many countries, and cities receive its worst brunt. The extreme heat stress within urban areas is often a synergistic combination of large-scale meteorological events, and the locally exacerbated impacts due to Urban Heat Islands (UHI). UHI is typically characterized as the difference between mean temperature of the urban and rural area. As a result, it fails to capture the significant variability that exists within the city itself. This variability arises from the diverse and complex spatial geometries of cities. Previous studies that have attempted to quantify the heat stress at an intra-urban scale are labor intensive, expensive, and difficult to emulate globally as they rely on availability of extensive data and their assimilation. The proposed study takes advantage of the well-established notion of fractal properties of cities to make the methods scalable to other cities where in-situ observational data might not be available. As an input, land surface temperatures are estimated using Landsat data. Using clustering analysis, we probe the emergence of thermal hotspots. The probability distributions (PD) of these hotspots are found to follow a power-law distribution in agreement with fractal characteristics of the city. PDs of several archetypical cities are then investigated to compare the effect of different spatial structures (e.g. monocentric v/s polycentric, sprawl v/s compact). Further, the temporal variability of the distributions on a diurnal as well as a seasonal scale is discussed. Finally, the spatiotemporal dynamics of the urban hotspots under a heat-wave (E.g. Delhi Heat wave, 2015) are compared against the non-heat wave scenarios. In summary, a technique that is globally adaptive and
Traveling waves in a spatially-distributed Wilson-Cowan model of cortex: From fronts to pulses
Harris, Jeremy D.; Ermentrout, Bard
2018-04-01
Wave propagation in excitable media has been studied in various biological, chemical, and physical systems. Waves are among the most common evoked and spontaneous organized activity seen in cortical networks. In this paper, we study traveling fronts and pulses in a spatially-extended version of the Wilson-Cowan equations, a neural firing rate model of sensory cortex having two population types: Excitatory and inhibitory. We are primarily interested in the case when the local or space-clamped dynamics has three fixed points: (1) a stable down state; (2) a saddle point with stable manifold that acts as a threshold for firing; (3) an up state having stability that depends on the time scale of the inhibition. In the case when the up state is stable, we look for wave fronts, which transition the media from a down to up state, and when the up state is unstable, we are interested in pulses, a transient increase in firing that returns to the down state. We explore the behavior of these waves as the time and space scales of the inhibitory population vary. Some interesting findings include bistability between a traveling front and pulse, fronts that join the down state to an oscillation or spatiotemporal pattern, and pulses which go through an oscillatory instability.
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.
Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data.
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.
Integrating GIS and ABM to Explore Spatiotemporal Dynamics
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.
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.
Construction of localized atomic wave packets
International Nuclear Information System (INIS)
Ranjani, S Sree; Kapoor, A K; Panigrahi, P K
2010-01-01
It is shown that highly localized solitons can be created in lower dimensional Bose-Einstein condensates (BECs), trapped in a regular harmonic trap, by temporally varying the trap frequency. A BEC confined in such a trap can be effectively used to construct a pulsed atomic laser emitting coherent atomic wave packets. In addition to having a complete control over the spatio-temporal dynamics of the solitons, we can separate the equation governing the Kohn mode (centre of mass motion). We investigate the effect of the temporal modulation of the trap frequency on the spatio-temporal dynamics of the bright solitons and also on the Kohn mode. The dynamics of the solitons and the variations in the Kohn mode with time are compared with those in a BEC confined in a trap with unmodulated trap frequency.
Influence of an octupole arrangement of electrodes on drift waves
International Nuclear Information System (INIS)
Block, D.; Piel, A.; Schroeder, Ch.; Klinger, T.
2001-01-01
In order to influence drift waves an octupole arrangement of electrodes is placed in direct vicinity of the plasma. By applying sinusoidal signals with proper phase shift to the electrodes synchronisation of drift waves is observed. The width of the synchronisation area is taken to quantify the interaction of the electrodes with the plasma. It turns out that the synchronisability strongly depends on the frequency, amplitude and phase shift and has to be interpreted as spatiotemporal effect. (orig.)
Intermode traces - fundamental interference phenomenon in quantum and wave physics
Kaplan, A.E.; Stifter, P.; Leeuwen, van K.A.H.; Lamb, W.E.; Schleich, W.P.
1998-01-01
Highly regular spatio-temporal or multi-dimensional patterns in the quantum mechanical probability or classical field intensity distributions can appear due to pair interference between individual eigen-modes of the system forming the so called intermode traces. These patterns are strongly
Afraimovich, E.
2009-04-01
using different methods of ionosphere radio sounding. The second type of the observed TEC disturbances is MS traveling wave packets (MS TWP) generated when the time derivative of TEC amount to its maximum. That ST-generated wave packets have been found for the first time. We have obtained the first data regarding the spatio-temporal characteristics and the statistics of MS TWP. There is no correlation between TWP amount and Dst-index value. We found that ST-generated wave packets have duration of about 1-2 hours and time shift of about 1.5-6 hours after the ST appearance at the altitude of 300 km. The TWP wave front extends almost along ST-line. The wavelength of ST-generated wave packets is about 100-300 km. The space image of MS TWP is characterized by pronounced anisotropy (the ratio between lengthwise and transversal scales exceeds 10) and high coherence over a long distance of about 2000 km. The work was supported by the SB RAS and FEB RAS collaboration project N 3.24, the RFBR-GFEN grant N 06-05-39026 and RFBR grant 07-05-00127.
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.
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.
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.
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)
Directory of Open Access Journals (Sweden)
Shilei Liu
2017-07-01
Full Text Available Acoustic standing waves have been widely used in trapping, patterning, and manipulating particles, whereas one barrier remains: the lack of understanding of force conditions on particles which mainly include acoustic radiation force (ARF and acoustic streaming (AS. In this paper, force conditions on micrometer size polystyrene microspheres in acoustic standing wave fields were investigated. The COMSOL® Mutiphysics particle tracing module was used to numerically simulate force conditions on various particles as a function of time. The velocity of particle movement was experimentally measured using particle imaging velocimetry (PIV. Through experimental and numerical simulation, the functions of ARF and AS in trapping and patterning were analyzed. It is shown that ARF is dominant in trapping and patterning large particles while the impact of AS increases rapidly with decreasing particle size. The combination of using both ARF and AS for medium size particles can obtain different patterns with only using ARF. Findings of the present study will aid the design of acoustic-driven microfluidic devices to increase the diversity of particle patterning.
Yang, Yanye; Ni, Zhengyang; Guo, Xiasheng; Luo, Linjiao; Tu, Juan; Zhang, Dong
2017-01-01
Acoustic standing waves have been widely used in trapping, patterning, and manipulating particles, whereas one barrier remains: the lack of understanding of force conditions on particles which mainly include acoustic radiation force (ARF) and acoustic streaming (AS). In this paper, force conditions on micrometer size polystyrene microspheres in acoustic standing wave fields were investigated. The COMSOL® Mutiphysics particle tracing module was used to numerically simulate force conditions on various particles as a function of time. The velocity of particle movement was experimentally measured using particle imaging velocimetry (PIV). Through experimental and numerical simulation, the functions of ARF and AS in trapping and patterning were analyzed. It is shown that ARF is dominant in trapping and patterning large particles while the impact of AS increases rapidly with decreasing particle size. The combination of using both ARF and AS for medium size particles can obtain different patterns with only using ARF. Findings of the present study will aid the design of acoustic-driven microfluidic devices to increase the diversity of particle patterning. PMID:28753955
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....
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
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)....
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.
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.
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.
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).
Orms, Natalie; Rehn, Dirk R; Dreuw, Andreas; Krylov, Anna I
2018-02-13
Density-based wave function analysis enables unambiguous comparisons of the electronic structure computed by different methods and removes ambiguity of orbital choices. We use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high- and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such as polyradicals. We show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of the bonding pattern.
Stochastic growth of localized plasma waves
International Nuclear Information System (INIS)
Robinson, P.A.; Cairns, Iver H.
2001-01-01
Localized bursty plasma waves are detected by spacecraft in many space plasmas. The large spatiotemporal scales involved imply that beam and other instabilities relax to marginal stability and that mean wave energies are low. Stochastic wave growth occurs when ambient fluctuations perturb the system, causing fluctuations about marginal stability. This yields regions where growth is enhanced and others where damping is increased; bursts are associated with enhanced growth and can occur even when the mean growth rate is negative. In stochastic growth, energy loss from the source is suppressed relative to secular growth, preserving it far longer than otherwise possible. Linear stochastic growth can operate at wave levels below thresholds of nonlinear wave-clumping mechanisms such as strong-turbulence modulational instability and is not subject to their coherence and wavelength limits. These mechanisms can be distinguished by statistics of the fields, whose strengths are lognormally distributed if stochastically growing and power-law distributed in strong turbulence. Recent applications of stochastic growth theory (SGT) are described, involving bursty plasma waves and unstable particle distributions in type III solar radio sources, the Earth's foreshock, magnetosheath, and polar cap regions. It is shown that when combined with wave-wave processes, SGT also accounts for associated radio emissions
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
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
The Spatiotemporal pattern and driving forces of the paddy in the Northeastern China
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.
Solitary waves and homoclinic orbits
International Nuclear Information System (INIS)
Balmforth, N.J.
1994-03-01
The notion that fluid motion often organizes itself into coherent structures has increasingly permeated modern fluid dynamics. Such localized objects appear in laminar flows and persist in turbulent states; from the water on windows on rainy days, to the circulations in planetary atmospheres. This review concerns solitary waves in fluids. More specifically, it centres around the mathematical description of solitary waves in a single spatial dimension. Moreover, it concentrates on strongly dissipative dynamics, rather than integrable systems like the KdV equation. One-dimensional solitary waves, or pulses and fronts as they are also called, are the simplest kinds of coherent structure (at least from a geometrical point of view). Nevertheless, their dynamics can be rich and complicated. In some circumstances this leads to the formation of spatio-temporal chaos in the systems giving birth to the solitary waves, and understanding that phenomenon is one of the major goals in the theory outlined in this review. Unfortunately, such a goal is far from achieved to date, and the author assess its current status and incompleteness
Directory of Open Access Journals (Sweden)
Jeonghun Nam
2017-01-01
Full Text Available We present continuous, sheathless microparticle patterning using conductive liquid (CL-based standing surface acoustic waves (SSAWs. Conventional metal electrodes patterned on a piezoelectric substrate were replaced with electrode channels filled with a CL. The device performance was evaluated with 5-μm fluorescent polystyrene particles at different flow rate and via phase shifting. In addition, our device was further applied to continuous concentration of malaria parasites at the sidewalls of the fluidic channel.
Demonstration of improved seismic source inversion method of tele-seismic body wave
Yagi, Y.; Okuwaki, R.
2017-12-01
Seismic rupture inversion of tele-seismic body wave has been widely applied to studies of large earthquakes. In general, tele-seismic body wave contains information of overall rupture process of large earthquake, while the tele-seismic body wave is inappropriate for analyzing a detailed rupture process of M6 7 class earthquake. Recently, the quality and quantity of tele-seismic data and the inversion method has been greatly improved. Improved data and method enable us to study a detailed rupture process of M6 7 class earthquake even if we use only tele-seismic body wave. In this study, we demonstrate the ability of the improved data and method through analyses of the 2016 Rieti, Italy earthquake (Mw 6.2) and the 2016 Kumamoto, Japan earthquake (Mw 7.0) that have been well investigated by using the InSAR data set and the field observations. We assumed the rupture occurring on a single fault plane model inferred from the moment tensor solutions and the aftershock distribution. We constructed spatiotemporal discretized slip-rate functions with patches arranged as closely as possible. We performed inversions using several fault models and found that the spatiotemporal location of large slip-rate area was robust. In the 2016 Kumamoto, Japan earthquake, the slip-rate distribution shows that the rupture propagated to southwest during the first 5 s. At 5 s after the origin time, the main rupture started to propagate toward northeast. First episode and second episode correspond to rupture propagation along the Hinagu fault and the Futagawa fault, respectively. In the 2016 Rieti, Italy earthquake, the slip-rate distribution shows that the rupture propagated to up-dip direction during the first 2 s, and then rupture propagated toward northwest. From both analyses, we propose that the spatiotemporal slip-rate distribution estimated by improved inversion method of tele-seismic body wave has enough information to study a detailed rupture process of M6 7 class earthquake.
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
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.
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.
Spatio-Temporal Pattern Mining on Trajectory Data Using Arm
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.
Spatio-temporal problems of locomotion control
International Nuclear Information System (INIS)
Smolyaninov, Vladimir V
2000-01-01
The problem of the spatio-temporal construction of legged movements involves structural freedoms due to the multi-link structure of the extremities, kinematic freedoms of the stepping cycle, and interextremity coordination freedoms, whose purposive organization is established by means of appropriate synergies, i.e. additional functional links the brain's control system forms. The main focus of attention in this work is on the kinematic and coordination synergies of the legged movements of humans and animals. The comparative historical analysis of experimental data and modelling metaphors concentrates on obtaining a unified description, whereas the ultimate mathematical metaphor reduces to space-time geometry, with base step synergies as its invariants. Thus, the concept of a synergetic organization for biomechanical movement freedoms is transformed to the geochronometry concept, actually a modification of Minkowskian geometry. To determine the spectrum of possible geochronometries, the consequences of a generalized 'postulate of a constant speed of light' are studied and different models of wave chronometers compared. (reviews of topical problems)
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.
Spatio-temporal light shaping for parallel nano-biophotonics
DEFF Research Database (Denmark)
Glückstad, Jesper; Palima, Darwin
followed separate tracks. Width-shaping, or spatial techniques, have mostly ignored light’s thickness (using continuous-wave lasers), while thickness-shaping, or temporal techniques, typically ignored the beam width. This disconnected spatial and temporal track also shows in our own research where we....... Another step is to vary light’s pulsewidth (thickness) as it propagates to get maximum compression (and highest energy density) at a chosen target plane. This temporal focusing can selectively look at a defined crosssection within a sample with only minimal disturbance from other regions. It can also do...... plane-byplane micromachining for faster laser processing compared to scanning a focused laser spot. Our previous work on spatial light shaping, together with the interplay between spatial and temporal modulation, invariably provides a strong position to pursue application-oriented spatiotemporal...
International Nuclear Information System (INIS)
Huang Yongxian; Tian Xiubo; Yang Shiqin; Fu Ricky; Paul, C.K.
2007-01-01
Plasma immersion ion implantation (PIII) has been developed as a low-cost and efficient surface modification technique of irregularly-shaped objects. The effect of six pulse waves with different rise-time patterns on the spatio-temporal evolution of plasma sheath,energy and dose of ion implantation has been simulated by particle-in-cell modeling. Statistical results may be obtained through assuming the Boltzmann distribution of electrons, and solving Poisson and Newton equations for tracing each ion in the plasma sheath. The results show that rise-time pattern has a critical influence on the evolution of plasma sheath. There exists maximum thickness difference of plasma sheath for different waveforms. The acceleration of ions is non-uniform due to the non-uniformity of electrical field strength. The maximum gradient of electrical field appears near the edge of plasma sheath. The results also show that optimization of dose and energy of incident ions may be achieved through modification of rise-time pattern. The numerical simulation of sheath expansion can be effectively used to provide a scientific basis for optimizing the PIII process. (authors)
Spike-like solitary waves in incompressible boundary layers driven by a travelling wave.
Feng, Peihua; Zhang, Jiazhong; Wang, Wei
2016-06-01
Nonlinear waves produced in an incompressible boundary layer driven by a travelling wave are investigated, with damping considered as well. As one of the typical nonlinear waves, the spike-like wave is governed by the driven-damped Benjamin-Ono equation. The wave field enters a completely irregular state beyond a critical time, increasing the amplitude of the driving wave continuously. On the other hand, the number of spikes of solitary waves increases through multiplication of the wave pattern. The wave energy grows in a sequence of sharp steps, and hysteresis loops are found in the system. The wave energy jumps to different levels with multiplication of the wave, which is described by winding number bifurcation of phase trajectories. Also, the phenomenon of multiplication and hysteresis steps is found when varying the speed of driving wave as well. Moreover, the nature of the change of wave pattern and its energy is the stability loss of the wave caused by saddle-node bifurcation.
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
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.
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....
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.
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.
SPATIOTEMPORAL CONTRAST SENSITIVITY OF EARLY VISION
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
Energy Technology Data Exchange (ETDEWEB)
Riecke, H.
1994-05-01
Goal is to contribute to understanding of localized spatial and spatio-temporal structures far from thermodynamic equilibrium. Here we report on our progress in the study of three classes of systems. (1) We have studied cellular flame structures arising in a circular burner. Using numerical computations we have found a number of traveling-wave structures in which different cells undergo different motion. Most strikingly, we have found a localized wave traveling through the array of steady cells. Results are interpreted using various asymptotic approaches. They are in qualitative agreement with recent experiments. (2) We have continued our investigation of localized waves in binary-mixture convection. Starting from the extended Ginzburg-Landau equations introduced earlier, we have derived equations of motion for interacting fronts connecting the conductive and the convective state. These equations reveal a repulsive interaction between the fronts which implies a new localization mechanism for waves. It is solely due to the long-wavelength mode specific to the extended Ginzburg-Landau equations. The stability properties of the resulting localized waves are in qualitative agreement with very recent experiments. (3) We have extended our investigation of domain structures to include their temporal evolution.
One-Dimensional Mass-Spring Chains Supporting Elastic Waves with Non-Conventional Topology
Directory of Open Access Journals (Sweden)
2016-04-01
Full Text Available There are two classes of phononic structures that can support elastic waves with non-conventional topology, namely intrinsic and extrinsic systems. The non-conventional topology of elastic wave results from breaking time reversal symmetry (T-symmetry of wave propagation. In extrinsic systems, energy is injected into the phononic structure to break T-symmetry. In intrinsic systems symmetry is broken through the medium microstructure that may lead to internal resonances. Mass-spring composite structures are introduced as metaphors for more complex phononic crystals with non-conventional topology. The elastic wave equation of motion of an intrinsic phononic structure composed of two coupled one-dimensional (1D harmonic chains can be factored into a Dirac-like equation, leading to antisymmetric modes that have spinor character and therefore non-conventional topology in wave number space. The topology of the elastic waves can be further modified by subjecting phononic structures to externally-induced spatio-temporal modulation of their elastic properties. Such modulations can be actuated through photo-elastic effects, magneto-elastic effects, piezo-electric effects or external mechanical effects. We also uncover an analogy between a combined intrinsic-extrinsic systems composed of a simple one-dimensional harmonic chain coupled to a rigid substrate subjected to a spatio-temporal modulation of the side spring stiffness and the Dirac equation in the presence of an electromagnetic field. The modulation is shown to be able to tune the spinor part of the elastic wave function and therefore its topology. This analogy between classical mechanics and quantum phenomena offers new modalities for developing more complex functions of phononic crystals and acoustic metamaterials.
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...
Tang, Ai-Hui; Wang, Shi-Qiang
2009-01-01
Spiral patterns have been found in various nonequilibrium systems. The Ca2+-induced Ca2+ release system in single cardiac cells is unique for highly discrete reaction elements, each giving rise to a Ca2+ spark upon excitation. We imaged the spiral Ca2+ waves in isolated cardiac cells and numerically studied the effect of system excitability on spiral patterns using a two-dimensional fire-diffuse-fire model. We found that under certain conditions, the system was able to display multiple stable patterns of spiral waves, each exhibiting different periods and distinct routines of spiral tips. Transition between these different patterns could be triggered by an internal fluctuation in the form of a single Ca2+ spark. PMID:19792039
Tang, Ai-Hui; Wang, Shi-Qiang
2009-09-01
Spiral patterns have been found in various nonequilibrium systems. The Ca(2+)-induced Ca(2+) release system in single cardiac cells is unique for highly discrete reaction elements, each giving rise to a Ca(2+) spark upon excitation. We imaged the spiral Ca(2+) waves in isolated cardiac cells and numerically studied the effect of system excitability on spiral patterns using a two-dimensional fire-diffuse-fire model. We found that under certain conditions, the system was able to display multiple stable patterns of spiral waves, each exhibiting different periods and distinct routines of spiral tips. Transition between these different patterns could be triggered by an internal fluctuation in the form of a single Ca(2+) spark.
Seemann, Gunnar; Panfilov, Alexander V.; Vandersickel, Nele
2017-01-01
Early Afterdepolarizations, EADs, are defined as the reversal of the action potential before completion of the repolarization phase, which can result in ectopic beats. However, the series of mechanisms of EADs leading to these ectopic beats and related cardiac arrhythmias are not well understood. Therefore, we aimed to investigate the influence of this single cell behavior on the whole heart level. For this study we used a modified version of the Ten Tusscher-Panfilov model of human ventricular cells (TP06) which we implemented in a 3D ventricle model including realistic fiber orientations. To increase the likelihood of EAD formation at the single cell level, we reduced the repolarization reserve (RR) by reducing the rapid delayed rectifier Potassium current and raising the L-type Calcium current. Varying these parameters defined a 2D parametric space where different excitation patterns could be classified. Depending on the initial conditions, by either exciting the ventricles with a spiral formation or burst pacing protocol, we found multiple different spatio-temporal excitation patterns. The spiral formation protocol resulted in the categorization of a stable spiral (S), a meandering spiral (MS), a spiral break-up regime (SB), spiral fibrillation type B (B), spiral fibrillation type A (A) and an oscillatory excitation type (O). The last three patterns are a 3D generalization of previously found patterns in 2D. First, the spiral fibrillation type B showed waves determined by a chaotic bi-excitable regime, i.e. mediated by both Sodium and Calcium waves at the same time and in same tissue settings. In the parameter region governed by the B pattern, single cells were able to repolarize completely and different (spiral) waves chaotically burst into each other without finishing a 360 degree rotation. Second, spiral fibrillation type A patterns consisted of multiple small rotating spirals. Single cells failed to repolarize to the resting membrane potential hence
Controlling nonlinear waves in excitable media
International Nuclear Information System (INIS)
Puebla, Hector; Martin, Roland; Alvarez-Ramirez, Jose; Aguilar-Lopez, Ricardo
2009-01-01
A new feedback control method is proposed to control the spatio-temporal dynamics in excitable media. Applying suitable external forcing to the system's slow variable, successful suppression and control of propagating pulses as well as spiral waves can be obtained. The proposed controller is composed by an observer to infer uncertain terms such as diffusive transport and kinetic rates, and an inverse-dynamics feedback function. Numerical simulations shown the effectiveness of the proposed feedback control approach.
Controlling nonlinear waves in excitable media
Energy Technology Data Exchange (ETDEWEB)
Puebla, Hector [Departamento de Energia, Universidad Autonoma Metropolitana, Av. San Pablo No. 180, Reynosa-Tamaulipas, Azcapotzalco 02200, DF, Mexico (Mexico)], E-mail: hpuebla@correo.azc.uam.mx; Martin, Roland [Laboratoire de Modelisation et d' Imagerie en Geosciences, CNRS UMR and INRIA Futurs Magique-3D, Universite de Pau (France); Alvarez-Ramirez, Jose [Division de Ciencias Basicas e Ingenieria, Universidad Autonoma Metropolitana-Iztapalapa (Mexico); Aguilar-Lopez, Ricardo [Departamento de Biotecnologia y Bioingenieria, CINVESTAV-IPN (Mexico)
2009-01-30
A new feedback control method is proposed to control the spatio-temporal dynamics in excitable media. Applying suitable external forcing to the system's slow variable, successful suppression and control of propagating pulses as well as spiral waves can be obtained. The proposed controller is composed by an observer to infer uncertain terms such as diffusive transport and kinetic rates, and an inverse-dynamics feedback function. Numerical simulations shown the effectiveness of the proposed feedback control approach.
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...
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.
Inositol trisphosphate receptor mediated spatiotemporal calcium signalling.
Miyazaki, S
1995-04-01
Spatiotemporal Ca2+ signalling in the cytoplasm is currently understood as an excitation phenomenon by analogy with electrical excitation in the plasma membrane. In many cell types, Ca2+ waves and Ca2+ oscillations are mediated by inositol 1,4,5-trisphosphate (IP3) receptor/Ca2+ channels in the endoplasmic reticulum membrane, with positive feedback between cytosolic Ca2+ and IP3-induced Ca2+ release creating a regenerative process. Remarkable advances have been made in the past year in the analysis of subcellular Ca2+ microdomains using confocal microscopy and of Ca2+ influx pathways that are functionally coupled to IP3-induced Ca2+ release. Ca2+ signals can be conveyed into the nucleus and mitochondria. Ca2+ entry from outside the cell allows repetitive Ca2+ release by providing Ca2+ to refill the endoplasmic reticulum stores, thus giving rise to frequency-encoded Ca2+ signals.
International Nuclear Information System (INIS)
Golubovskii, Yu B; Kozakov, R V; Wilke, C; Behnke, J; Nekutchaev, V O
2004-01-01
Time and space resolved measurements of the plasma potential in axial and radial directions in S- and P-striations in neon are performed. The measurements in different radial positions were carried out with high spatial resolution by means of simultaneous displacement of electrodes relative to the stationary probe. The plasma potential was found to be a superposition of the potentials of ionization wave and plasma oscillations relative to the electrodes. A method of decomposition of the measured spatio-temporal structure of the potential in components associated with the plasma oscillations and ionization wave propagation is proposed. A biorthogonal decomposition of the spatio-temporal structure of the potential is performed. A comparison of the decomposition results obtained by the two methods is made. The experiments revealed a two-dimensional structure of the potential field in an ionization wave. Qualitative discussions of the reasons for the occurrence of this two-dimensional structure are presented based on the analysis of the kinetic equation and the equation for the potential
A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates
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...
Directory of Open Access Journals (Sweden)
Daniel Geberth
2009-07-01
Full Text Available The slime mold Dictyostelium discoideum is one of the model systems of biological pattern formation. One of the most successful answers to the challenge of establishing a spiral wave pattern in a colony of homogeneously distributed D. discoideum cells has been the suggestion of a developmental path the cells follow (Lauzeral and coworkers. This is a well-defined change in properties each cell undergoes on a longer time scale than the typical dynamics of the cell. Here we show that this concept leads to an inhomogeneous and systematic spatial distribution of spiral waves, which can be predicted from the distribution of cells on the developmental path. We propose specific experiments for checking whether such systematics are also found in data and thus, indirectly, provide evidence of a developmental path.
Cong, Rui; Li, Jing; Guo, Song
2017-02-01
To examine the efficacy of qualitative shear wave elastography (SWE) in the classification and evaluation of solid breast masses, and to compare this method with conventional ultrasonograghy (US), quantitative SWE parameters and qualitative SWE classification proposed before. From April 2015 to March 2016, 314 consecutive females with 325 breast masses who decided to undergo core needle biopsy and/or surgical biopsy were enrolled. Conventional US and SWE were previously performed in all enrolled subjects. Each mass was classified by two different qualitative classifications. One was established in our study, herein named the Qual1. Qual1 could classify the SWE images into five color patterns by the visual evaluations: Color pattern 1 (homogeneous pattern); Color pattern 2 (comparative homogeneous pattern); Color pattern 3 (irregularly heterogeneous pattern); Color pattern 4 (intralesional echo pattern); and Color pattern 5 (the stiff rim sign pattern). The second qualitative classification was named Qual2 here, and included a four-color overlay pattern classification (Tozaki and Fukuma, Acta Radiologica, 2011). The Breast Imaging Reporting and Data System (BI-RADS) assessment and quantitative SWE parameters were recorded. Diagnostic performances of conventional US, SWE parameters, and combinations of US and SWE parameters were compared. With pathological results as the gold standard, of the 325 examined breast masses, 139 (42.77%) samples were malignant and 186 (57.23%) were benign. The Qual1 showed a higher Az value than the Qual2 and quantitative SWE parameters (all Pbreast mass diagnoses. Copyright © 2016. Published by Elsevier B.V.
Wave Pattern Peculiarities of Different Types of Explosions Conducted at Semipalatinsk Test Site
Sokolova, Inna
2014-05-01
The historical seismograms of the explosions conducted at the STS in 1949 - 1989 are of great interest for the researchers in the field of monitoring. Large number of air (86), surface (30) and underground nuclear explosions were conducted here in boreholes and tunnels (340). In addition to nuclear explosions, large chemical explosions were conducted at the Test Site. It is known that tectonic earthquakes occur on the Test Site territory and near it. Since 2005 the Institute of Geophysical Researches conducts works on digitizing the historical seismograms of nuclear explosions. Currently, the database contains more than 6000 digitized seismograms of nuclear explosions used for investigative monitoring tasks, major part of them (4000) are events from the STS region. Dynamic parameters of records of air, surface and underground nuclear explosions, as well as large chemical explosions with compact charge laying were investigated for seismic stations located on the territory of Kazakhstan using digitized records of the STS events. In addition, the comparison between salvo wave pattern and single explosions was conducted. The records of permanent and temporary seismic stations (epicentral distances range 100 - 800 km) were used for the investigations. Explosions spectra were analyzed, specific features of each class of events were found. The seismograms analysis shows that the wave pattern depends significantly on the explosion site and on the source type.
From retinal waves to activity-dependent retinogeniculate map development.
Markowitz, Jeffrey; Cao, Yongqiang; Grossberg, Stephen
2012-01-01
A neural model is described of how spontaneous retinal waves are formed in infant mammals, and how these waves organize activity-dependent development of a topographic map in the lateral geniculate nucleus, with connections from each eye segregated into separate anatomical layers. The model simulates the spontaneous behavior of starburst amacrine cells and retinal ganglion cells during the production of retinal waves during the first few weeks of mammalian postnatal development. It proposes how excitatory and inhibitory mechanisms within individual cells, such as Ca(2+)-activated K(+) channels, and cAMP currents and signaling cascades, can modulate the spatiotemporal dynamics of waves, notably by controlling the after-hyperpolarization currents of starburst amacrine cells. Given the critical role of the geniculate map in the development of visual cortex, these results provide a foundation for analyzing the temporal dynamics whereby the visual cortex itself develops.
H, V.; Karmakar, S.; Ghosh, S.
2015-12-01
Human induced global warming is unequivocal and observational studies shows that, this has led to increase in the intensity and frequency of hydro-climatic extremes, most importantly precipitation extreme, heat waves and drought; and also is expected to be increased in the future. The occurrence of these extremes have a devastating effects on nation's economy and on societal well-being. Previous studies on India provided the evidences of significant changes in the precipitation extreme from pre- to post-1950, with huge spatial heterogeneity; and projections of heat waves indicated that significant part of India will experience heat stress conditions in the future. Under these circumstance, it is necessary to develop a nation-wide social vulnerability map to scrutinize the adequacy of existing emergency management. Yet there has been no systematic past efforts on mapping social vulnerability to hydro-climatic extremes at nation-wide for India. Therefore, immediate efforts are required to quantify the social vulnerability, particularly developing country like India, where major transformations in demographic characteristics and development patterns are evident during past decades. In the present study, we perform a comprehensive spatio-temporal social vulnerability analysis by considering multiple sensitive indicators for three decades (1990-2010) which identifies the hot-spots, with higher vulnerability to hydro-climatic extremes. The population datasets are procured from Census of India and the meteorological datasets are obtained from India Meteorological Department (IMD). The study derives interesting results on decadal changes of spatial distribution of risk, considering social vulnerability and hazard to extremes.
Internal Waves and Wave Attractors in Enceladus' Subsurface Ocean
van Oers, A. M.; Maas, L. R.; Vermeersen, B. L. A.
2016-12-01
One of the most peculiar features on Saturn moon Enceladus is its so-called tiger stripe pattern at the geologically active South Polar Terrain (SPT), as first observed in detail by the Cassini spacecraft early 2005. It is generally assumed that the four almost parallel surface lines that constitute this pattern are faults in the icy surface overlying a confined salty water reservoir. In 2013, we formulated the original idea [Vermeersen et al., AGU Fall Meeting 2013, abstract #P53B-1848] that the tiger stripe pattern is formed and maintained by induced, tidally and rotationally driven, wave-attractor motions in the ocean underneath the icy surface of the tiger-stripe region. Such wave-attractor motions are observed in water tank experiments in laboratories on Earth and in numerical experiments [Maas et al., Nature, 338, 557-561, 1997; Drijfhout and Maas, J. Phys. Oceanogr., 37, 2740-2763, 2007; Hazewinkel et al., Phys. Fluids, 22, 107102, 2010]. Numerical simulations show the persistence of wave attractors for a range of ocean shapes and stratifications. The intensification of the wave field near the location of the surface reflections of wave attractors has been numerically and experimentally confirmed. We measured the forces a wave attractor exerts on a solid surface, near a reflection point. These reflection points would correspond to the location of the tiger stripes. Combining experiments and numerical simulations we conclude that (1) wave attractors can exist in Enceladus' subsurface sea, (2) their shape can be matched to the tiger stripes, (3) the wave attractors cause a localized force at the water-ice boundaries, (4) this force could have been large enough to contribute to fracturing the ice and (5) the wave attractors localize energy (and particles) and cause dissipation along its path, helping explain Enceladus' enigmatic heat output at the tiger stripes.
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.
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.
The timing and spatiotemporal patterning of Neanderthal disappearance.
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.
Williams, Gareth J; Smith, Jennifer E; Conklin, Eric J; Gove, Jamison M; Sala, Enric; Sandin, Stuart A
2013-01-01
Kingman Reef and Palmyra Atoll in the central Pacific are among the most remote coral reefs on the planet. Here we describe spatial patterns in their benthic communities across reef habitats and depths, and consider these in the context of oceanographic gradients. Benthic communities at both locations were dominated by calcifying organisms (54-86% cover), namely hard corals (20-74%) and crustose coralline algae (CCA) (10-36%). While turf algae were relatively common at both locations (8-22%), larger fleshy macroalgae were virtually absent at Kingman (wave energy, with hard coral cover decreasing and becoming more spatially clustered with increased wave energy, likely as a result of physical damage leading to patches of coral in localized shelter. In contrast, the cover of turf algae at Kingman was positively related to wave energy, reflecting their ability to rapidly colonize newly available space. No significant patterns with wave energy were observed on Palmyra's forereef, suggesting that a more detailed model is required to study biophysical coupling there. Kingman, Palmyra, and other remote oceanic reefs provide interesting case studies to explore biophysical influences on benthic ecology and dynamics.
Spatio-temporal models of mental processes from fMRI.
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.
Spatiotemporal Dynamics of Dendritic Spines in the Living Brain
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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.
Spatio-Temporal Data Construction
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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.
Analysis and modelling of spatio-temporal properties of daily rainfall over the Danube basin
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.
Spatiotemporal patterns of non-point source nitrogen loss in an agricultural catchment
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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.
Spatio-temporal distribution patterns of the epibenthic community in the coastal waters of Suriname
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.
Photo-induced travelling waves in condensed Langmuir monolayers
Energy Technology Data Exchange (ETDEWEB)
Tabe, Y [Yokoyama Nano-Structured Liquid Crystal Project, ERATO, Japan Science and Technology Corporation, 5-9-9 Tokodai, Tsukuba, Ibaraki 300-2635, Japan (Japan); Yamamoto, T [Yokoyama Nano-Structured Liquid Crystal Project, ERATO, Japan Science and Technology Corporation, 5-9-9 Tokodai, Tsukuba, Ibaraki 300-2635, Japan (Japan); Yokoyama, H [Yokoyama Nano-Structured Liquid Crystal Project, ERATO, Japan Science and Technology Corporation, 5-9-9 Tokodai, Tsukuba, Ibaraki 300-2635, Japan (Japan)
2003-06-01
We report the detailed properties of photo-induced travelling waves in liquid crystalline Langmuir monolayers composed of azobenzene derivatives. When the monolayer, in which the constituent rodlike molecules are coherently tilted from the layer normal, is weakly illuminated to undergo the trans-cis photo-isomerization, spatio-temporal periodic oscillations of the molecular azimuth begin over the entire excited area and propagate as a two-dimensional orientational wave. The wave formation takes place only when the film is formed at an asymmetric interface with broken up-down symmetry and when the chromophores are continuously excited near the long-wavelength edge of absorption to induce repeated photo-isomerizations between the trans and cis forms. Under proper illumination conditions, Langmuir monolayers composed of a wide variety of azobenzene derivatives have been confirmed to exhibit similar travelling waves with velocity proportional to the excitation power irrespective of the degree of amphiphilicity. The dynamics can be qualitatively explained by the modified reaction-diffusion model proposed by Reigada, Sagues and Mikhailov.
Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China
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
The Voronoi spatio-temporal data structure
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
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...
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
From retinal waves to activity-dependent retinogeniculate map development.
Directory of Open Access Journals (Sweden)
Jeffrey Markowitz
Full Text Available A neural model is described of how spontaneous retinal waves are formed in infant mammals, and how these waves organize activity-dependent development of a topographic map in the lateral geniculate nucleus, with connections from each eye segregated into separate anatomical layers. The model simulates the spontaneous behavior of starburst amacrine cells and retinal ganglion cells during the production of retinal waves during the first few weeks of mammalian postnatal development. It proposes how excitatory and inhibitory mechanisms within individual cells, such as Ca(2+-activated K(+ channels, and cAMP currents and signaling cascades, can modulate the spatiotemporal dynamics of waves, notably by controlling the after-hyperpolarization currents of starburst amacrine cells. Given the critical role of the geniculate map in the development of visual cortex, these results provide a foundation for analyzing the temporal dynamics whereby the visual cortex itself develops.
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....
Sub-wavelength patterning of organic monolayers via nonlinear processing with continuous-wave lasers
Energy Technology Data Exchange (ETDEWEB)
Mathieu, Mareike; Hartmann, Nils, E-mail: nils.hartmann@uni-due.de [Fakultaet fuer Chemie, Universitaet Duisburg-Essen, 45117 Essen (Germany); CeNIDE-Center for Nanointegration Duisburg-Essen, 47048 Duisburg (Germany); NETZ-NanoEnergieTechnikZentrum, 47048 Duisburg (Germany)
2010-12-15
In recent years, nonlinear processing with continuous-wave lasers has been demonstrated to be a facile means of rapid nanopatterning of organic monolayers down to the sub-100 nm range. In this study, we report on laser patterning of thiol-based organic monolayers with sub-wavelength resolution. Au-coated silicon substrates are functionalized with 1-hexadecanethiol. Irradiation with a focused beam of an Ar{sup +} laser operating at {lambda}=514 nm allows one to locally remove the monolayer. Subsequently, the patterns are transferred into the Au film via selective etching in a ferri-/ferrocyanide solution. Despite a 1/e{sup 2} spot diameter of about 2.8 {mu}m, structures with lateral dimensions down to 250 nm are fabricated. The underlying nonlinear dependence of the patterning process on laser intensity is traced back to the interplay between the laser-induced transient local temperature rise and the thermally activated desorption of the thiol molecules. A simple thermokinetic analysis of the data allows us to determine the effective kinetic parameters. These results complement our previous work on photothermal laser patterning of ultrathin organic coatings, such as silane-based organic monolayers, organo/silicon interfaces and supported membranes. A general introduction to nonlinear laser processing of organic monolayers is presented.
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
Modeling secondary accidents identified by traffic shock waves.
Junhua, Wang; Boya, Liu; Lanfang, Zhang; Ragland, David R
2016-02-01
The high potential for occurrence and the negative consequences of secondary accidents make them an issue of great concern affecting freeway safety. Using accident records from a three-year period together with California interstate freeway loop data, a dynamic method for more accurate classification based on the traffic shock wave detecting method was used to identify secondary accidents. Spatio-temporal gaps between the primary and secondary accident were proven be fit via a mixture of Weibull and normal distribution. A logistic regression model was developed to investigate major factors contributing to secondary accident occurrence. Traffic shock wave speed and volume at the occurrence of a primary accident were explicitly considered in the model, as a secondary accident is defined as an accident that occurs within the spatio-temporal impact scope of the primary accident. Results show that the shock waves originating in the wake of a primary accident have a more significant impact on the likelihood of a secondary accident occurrence than the effects of traffic volume. Primary accidents with long durations can significantly increase the possibility of secondary accidents. Unsafe speed and weather are other factors contributing to secondary crash occurrence. It is strongly suggested that when police or rescue personnel arrive at the scene of an accident, they should not suddenly block, decrease, or unblock the traffic flow, but instead endeavor to control traffic in a smooth and controlled manner. Also it is important to reduce accident processing time to reduce the risk of secondary accident. Copyright © 2015 Elsevier Ltd. All rights reserved.
Heterogeneity induces spatiotemporal oscillations in reaction-diffusion systems
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.
Spatio-temporal networks: reachability, centrality and robustness.
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.
Initial spatio-temporal domain expansion of the Modelfest database
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
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.
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.
Unsupervised Learning of Spatiotemporal Features by Video Completion
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...
Comparison of Spatiotemporal Fusion Models: A Review
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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.
Assessing global vegetation activity using spatio-temporal Bayesian modelling
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
Simultaneous spatio-temporal focusing for tissue manipulation
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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.
Arctic Climate and Atmospheric Planetary Waves
Cavalieri, D. J.; Haekkinen, S.; Zukor, Dorothy J. (Technical Monitor)
2001-01-01
Analysis of a fifty-year record (1946-1995) of monthly-averaged sea level pressure data provides a link between the phases of planetary-scale sea level pressure waves and Arctic Ocean and ice variability. Results of this analysis show: (1) a breakdown of the dominant wave 1 pattern in the late 1960's, (2) shifts in the mean phase of waves 1 and 2 since this breakdown, (3) an eastward shift in the phases of both waves 1 and 2 during the years of simulated cyclonic Arctic Ocean circulation relative to their phases during the years of anticyclonic circulation, (4) a strong decadal variability of wave phase associated with simulated Arctic Ocean circulation changes. Finally, the Arctic atmospheric circulation patterns that emerge when waves 1 and 2 are in their extreme eastern and western positions suggest an alternative approach for determining significant forcing patterns of sea ice and high-latitude variability.
Spatiotemporal pattern of bacillary dysentery in China from 1990 to 2009: what is the driver behind?
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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.
Spatio-temporal Change Patterns of Tropical Forests from 2000 to 2014 Using MOD09A1 Dataset
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.
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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.
Turing instability for a two-dimensional Logistic coupled map lattice
International Nuclear Information System (INIS)
Xu, L.; Zhang, G.; Han, B.; Zhang, L.; Li, M.F.; Han, Y.T.
2010-01-01
In this Letter, stability analysis is applied to a two-dimensional Logistic coupled map lattice with the periodic boundary conditions. The conditions of Turing instability are obtained, and various patterns can be exhibited by numerical simulations in the Turing instability region. For example, space-time periodic structures, periodic or quasiperiodic traveling wave solutions, stationary wave solutions, spiral waves, and spatiotemporal chaos, etc. have been observed. In particular, the different pattern structures have also been observed for same parameters and different initial values. That is, pattern structures also depend on the initial values. The similar patterns have also been seen in relevant references. However, the present Letter owes to pattern formation via diffusion-driven instabilities because the system is stable in the absence of diffusion.
Visualization and assessment of spatio-temporal covariance properties
Huang, Huang
2017-11-23
Spatio-temporal covariances are important for describing the spatio-temporal variability of underlying random fields in geostatistical data. For second-order stationary random fields, there exist subclasses of covariance functions that assume a simpler spatio-temporal dependence structure with separability and full symmetry. However, it is challenging to visualize and assess separability and full symmetry from spatio-temporal observations. In this work, we propose a functional data analysis approach that constructs test functions using the cross-covariances from time series observed at each pair of spatial locations. These test functions of temporal lags summarize the properties of separability or symmetry for the given spatial pairs. We use functional boxplots to visualize the functional median and the variability of the test functions, where the extent of departure from zero at all temporal lags indicates the degree of non-separability or asymmetry. We also develop a rank-based nonparametric testing procedure for assessing the significance of the non-separability or asymmetry. Essentially, the proposed methods only require the analysis of temporal covariance functions. Thus, a major advantage over existing approaches is that there is no need to estimate any covariance matrix for selected spatio-temporal lags. The performances of the proposed methods are examined by simulations with various commonly used spatio-temporal covariance models. To illustrate our methods in practical applications, we apply it to real datasets, including weather station data and climate model outputs.
Dynamic decomposition of spatiotemporal neural signals.
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Luca Ambrogioni
2017-05-01
Full Text Available Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals.
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.
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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.
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
Dying like rabbits: general determinants of spatio-temporal variability in survival.
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
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Luigia Riefolo
2018-02-01
Full Text Available This paper describes a set of experiments undertaken at Universitat Politècnica de Catalunya in the large wave flume of the Maritime Engineering Laboratory. The purpose of this study is to highlight the effects of wave grouping and long-wave short-wave combinations regimes on low frequency generations. An eigen-value decomposition has been performed to discriminate low frequencies. In particular, measured eigen modes, determined through the spectral analysis, have been compared with calculated modes by means of eigen analysis. The low frequencies detection appears to confirm the dependence on groupiness of the modal amplitudes generated in the wave flume. Some evidence of the influence of low frequency waves on runup and transport patterns are shown. In particular, the generation and evolution of secondary bedforms are consistent with energy transferred between the standing wave modes.
Space-time topology optimization for one-dimensional wave propagation
DEFF Research Database (Denmark)
Jensen, Jakob Søndergaard
2009-01-01
-dimensional transient wave propagation in an elastic rod with time dependent Young's modulus. By two simulation examples it is demonstrated how dynamic structures can display rich dynamic behavior such as wavenumber/frequency shifts and lack of energy conservation. The optimization method's potential for creating...... structures with novel dynamic behavior is illustrated by a simple example; it is shown that an elastic rod in which the optimized stiffness distribution is allowed to vary in time can be much more efficient in prohibiting wave propagation compared to a static bandgap structure. Optimized designs in form...... of spatio-temporal laminates and checkerboards are generated and discussed. The example lays the foundation for creating designs with more advanced functionalities in future work....
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...
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
Motor patterns during walking on a slippery walkway
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
International Nuclear Information System (INIS)
Wang, Xin; Chen, Yong; Cao, Jianli
2015-01-01
In this paper, we utilize generalized Darboux transformation to study higher-order rogue wave solutions of the three-wave resonant interaction equation, which describes the propagation and mixing of waves with different frequencies in weakly nonlinear dispersive media. A general Nth-order rogue wave solution with two characteristic velocities structural parameters and 3N independent parameters under a determined plane-wave background and a specific parameter condition is derived. As an application, we show that four fundamental rogue waves with fundamental, two kinds of line and quadrilateral patterns, or six fundamental rogue waves with fundamental, triangular, two kinds of quadrilateral and circular patterns can emerge in the second-order rogue waves. Moreover, several important wave characteristics including the maximum values, the corresponding coordinate positions of the humps, and the stability problem for some special higher-order rogue wave solutions such as the fundamental and quadrilateral cases are discussed. (paper)
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Barbara eKrahé
2014-10-01
Full Text Available A longitudinal study with N = 1,854 adolescents from Germany investigated patterns of change and gender differences in physical and relational aggression in relation to normative beliefs about aggression. Participants, whose mean age was 13 years at T1, completed self-report measures of physically and relationally aggressive behavior and indicated their normative approval about both forms of aggression at four data waves separated by 12-month intervals. Boys scored higher than did girls on both forms of aggression, but the gender difference was more pronounced for physical aggression. Physical aggression decreased and relational aggression increased over the four data waves in both gender groups. The normative acceptance of both forms of aggression decreased over time, with a greater decrease for the approval of physical aggression. In both gender groups, normative approval of relational aggression prospectively predicted relational aggression across all data waves, and the normative approval of physical aggression predicted physically aggressive behavior at the second and third data waves. A reciprocal reinforcement of aggressive norms and behavior was found for both forms of aggression. The findings are discussed as supporting a social information processing perspective on developmental patterns of change in physical and relational aggression in adolescence.
Krahé, Barbara; Busching, Robert
2014-01-01
In a longitudinal study with N = 1,854 adolescents from Germany, we investigated patterns of change and gender differences in physical and relational aggression in relation to normative beliefs about these two forms of aggression. Participants, whose mean age was 13 years at T1, completed self-report measures of physically and relationally aggressive behavior and indicated their normative approval of both forms of aggression at four data waves separated by 12-month intervals. Boys scored higher than did girls on both forms of aggression, but the gender difference was more pronounced for physical aggression. Physical aggression decreased and relational aggression increased over the four data waves in both gender groups. The normative acceptance of both forms of aggression decreased over time, with a greater decrease for the approval of physical aggression. In both gender groups, normative approval of relational aggression prospectively predicted relational aggression across all data waves, and the normative approval of physical aggression predicted physically aggressive behavior at the second and third data waves. A reciprocal reinforcement of aggressive norms and behavior was found for both forms of aggression. The findings are discussed as supporting a social information processing perspective on developmental patterns of change in physical and relational aggression in adolescence.
Parametric instability and wave turbulence driven by tidal excitation of internal waves
Le Reun, Thomas; Favier, Benjamin; Le Bars, Michael
2018-04-01
We investigate the stability of stratified fluid layers undergoing homogeneous and periodic tidal deformation. We first introduce a local model which allows to study velocity and buoyancy fluctuations in a Lagrangian domain periodically stretched and sheared by the tidal base flow. While keeping the key physical ingredients only, such a model is efficient to simulate planetary regimes where tidal amplitudes and dissipation are small. With this model, we prove that tidal flows are able to drive parametric subharmonic resonances of internal waves, in a way reminiscent of the elliptical instability in rotating fluids. The growth rates computed via Direct Numerical Simulations (DNS) are in very good agreement with WKB analysis and Floquet theory. We also investigate the turbulence driven by this instability mechanism. With spatio-temporal analysis, we show that it is a weak internal wave turbulence occurring at small Froude and buoyancy Reynolds numbers. When the gap between the excitation and the Brunt-V\\"ais\\"al\\"a frequencies is increased, the frequency spectrum of this wave turbulence displays a -2 power law reminiscent of the high-frequency branch of the Garett and Munk spectrum (Garrett & Munk 1979) which has been measured in the oceans. In addition, we find that the mixing efficiency is altered compared to what is computed in the context of DNS of stratified turbulence excited at small Froude and large buoyancy Reynolds numbers and is consistent with a superposition of waves.
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.
Stochastic growth of localized plasma waves
International Nuclear Information System (INIS)
Robinson, P.A.; Cairns, I.H.
2000-01-01
Full text: Localized bursty plasma waves occur in many natural systems, where they are detected by spacecraft. The large spatiotemporal scales involved imply that beam and other instabilities relax to marginal stability and that mean wave energies are low. Stochastic wave growth occurs when ambient fluctuations perturb the wave-driver interaction, causing fluctuations about marginal stability. This yields regions where growth is enhanced and others where damping is increased; observed bursts are associated with enhanced growth and can occur even when the mean growth rate is negative. In stochastic growth, energy loss from the source is suppressed relative to secular growth, preserving it for much longer times and distances than otherwise possible. Linear stochastic growth can operate at wave levels below thresholds of nonlinear wave-clumping mechanisms such as strong-turbulence modulational instability and is not subject to their coherence and wavelength limits. Growth mechanisms can be distinguished by statistics of the fields, whose strengths are lognormally distributed if stochastically growing, power-law distributed in strong turbulence, and uniformly distributed in log under secular growth. After delineating stochastic growth and strong-turbulence regimes, recent applications of stochastic growth theory (SGT) are described, involving bursty plasma waves and unstable particle distributions in type II and III solar radio sources, foreshock regions upstream of the bow shocks of Earth and planets, and Earth's magnetosheath, auroras, and polar-caps. It is shown that when combined with wave-wave processes, SGT accounts for type II and III solar radio emissions. SGT thus removes longstanding problems in understanding persistent unstable distributions, bursty fields, and radio emissions observed in space
The pattern of auditory brainstem response wave V maturation in cochlear-implanted children.
Thai-Van, Hung; Cozma, Sebastian; Boutitie, Florent; Disant, François; Truy, Eric; Collet, Lionel
2007-03-01
Maturation of acoustically evoked brainstem responses (ABR) in hearing children is not complete at birth but rather continues over the first two years of life. In particular, it has been established that the decrease in ABR wave V latency can be modeled as the sum of two decaying exponential functions with respective time-constants of 4 and 50 weeks [Eggermont, J.J., Salamy, A., 1988a. Maturational time-course for the ABR in preterm and full term infants. Hear Res 33, 35-47; Eggermont, J.J., Salamy, A., 1988b. Development of ABR parameters in a preterm and a term born population. Ear Hear 9, 283-9]. Here, we investigated the maturation of electrically evoked auditory brainstem responses (EABR) in 55 deaf children who recovered hearing after cochlear implantation, and proposed a predictive model of EABR maturation depending on the onset of deafness. The pattern of EABR maturation over the first 2 years of cochlear implant use was compared with the normal pattern of ABR maturation in hearing children. Changes in EABR wave V latency over the 2 years following cochlear implant connection were analyzed in two groups of children. The first group (n=41) consisted of children with early-onset of deafness (mostly congenital), and the second (n=14) of children who had become profoundly deaf after 1 year of age. The modeling of changes in EABR wave V latency with time was based on the mean values from each of the two groups, allowing comparison of the rates of EABR maturation between groups. Differences between EABRs elicited at the basal and apical ends of the implant electrode array were also tested. There was no influence of age at implantation on the rate of wave V latency change. The main factor for EABR changes was the time in sound. Indeed, significant maturation was observed over the first 2 years of implant use only in the group with early-onset deafness. In this group maturation of wave V progressed as in the ABR model of [Eggermont, J.J., Salamy, A., 1988a
Spatiotemporal Analysis of AIDS Incidence Among Adults in Brazil.
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.
Energy Technology Data Exchange (ETDEWEB)
Iwakami, Wakana; Nagakura, Hiroki [Yukawa Institute for Theoretical Physics, Kyoto University, Oiwake-cho, Kitashirakawa, Sakyo-ku, Kyoto 606-8502 (Japan); Yamada, Shoichi, E-mail: wakana@heap.phys.waseda.ac.jp [Advanced Research Institute for Science and Engineering, Waseda University, 3-4-1, Okubo, Shinjuku, Tokyo 169-8555 (Japan)
2014-05-10
In this study, we conduct three-dimensional hydrodynamic simulations systematically to investigate the flow patterns behind the accretion shock waves that are commonly formed in the post-bounce phase of core-collapse supernovae. Adding small perturbations to spherically symmetric, steady, shocked accretion flows, we compute the subsequent evolutions to find what flow pattern emerges as a consequence of hydrodynamical instabilities such as convection and standing accretion shock instability for different neutrino luminosities and mass accretion rates. Depending on these two controlling parameters, various flow patterns are indeed realized. We classify them into three basic patterns and two intermediate ones; the former includes sloshing motion (SL), spiral motion (SP), and multiple buoyant bubble formation (BB); the latter consists of spiral motion with buoyant-bubble formation (SPB) and spiral motion with pulsationally changing rotational velocities (SPP). Although the post-shock flow is highly chaotic, there is a clear trend in the pattern realization. The sloshing and spiral motions tend to be dominant for high accretion rates and low neutrino luminosities, and multiple buoyant bubbles prevail for low accretion rates and high neutrino luminosities. It is interesting that the dominant pattern is not always identical between the semi-nonlinear and nonlinear phases near the critical luminosity; the intermediate cases are realized in the latter case. Running several simulations with different random perturbations, we confirm that the realization of flow pattern is robust in most cases.
Energy-flux characterization of conical and space-time coupled wave packets
International Nuclear Information System (INIS)
Lotti, A.; Couairon, A.; Faccio, D.; Trapani, P. Di
2010-01-01
We introduce the concept of energy density flux as a characterization tool for the propagation of ultrashort laser pulses with spatiotemporal coupling. In contrast with calculations for the Poynting vector, those for energy density flux are derived in the local frame moving at the velocity of the envelope of the wave packet under examination and do not need knowledge of the magnetic field. We show that the energy flux defined from a paraxial propagation equation follows specific geometrical connections with the phase front of the optical wave packet, which demonstrates that the knowledge of the phase fronts amounts to the measurement of the energy flux. We perform a detailed numerical study of the energy density flux in the particular case of conical waves, with special attention paid to stationary-envelope conical waves (X or O waves). A full characterization of linear conical waves is given in terms of their energy flux. We extend the definition of this concept to the case of nonlinear propagation in Kerr media with nonlinear losses.
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.
Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex.
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.
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
Pulse wave imaging in normal, hypertensive and aneurysmal human aortas in vivo: a feasibility study
International Nuclear Information System (INIS)
Li, Ronny X; Luo, Jianwen; Shahmirzadi, Danial; Konofagou, Elisa E; Balaram, Sandhya K; Chaudhry, Farooq A
2013-01-01
Arterial stiffness is a well-established biomarker for cardiovascular risk, especially in the case of hypertension. The progressive stages of an abdominal aortic aneurysm (AAA) have also been associated with varying arterial stiffness. Pulse wave imaging (PWI) is a noninvasive, ultrasound imaging-based technique that uses the pulse wave-induced arterial wall motion to map the propagation of the pulse wave and measure the regional pulse wave velocity (PWV) as an index of arterial stiffness. In this study, the clinical feasibility of PWI was evaluated in normal, hypertensive, and aneurysmal human aortas. Radiofrequency-based speckle tracking was used to estimate the pulse wave-induced displacements in the abdominal aortic walls of normal (N = 15, mean age 32.5 ± 10.2 years), hypertensive (N = 13, mean age 60.8 ± 15.8 years), and aneurysmal (N = 5, mean age 71.6 ± 11.8 years) human subjects. Linear regression of the spatio-temporal variation of the displacement waveform in the anterior aortic wall over a single cardiac cycle yielded the slope as the PWV and the coefficient of determination r 2 as an approximate measure of the pulse wave propagation uniformity. The aortic PWV measurements in all normal, hypertensive, and AAA subjects were 6.03 ± 1.68, 6.69 ± 2.80, and 10.54 ± 6.52 m s −1 , respectively. There was no significant difference (p = 0.15) between the PWVs of the normal and hypertensive subjects while the PWVs of the AAA subjects were significantly higher (p 2 in the AAA subjects was significantly lower (p 2 ) obtained using PWI, in addition to the PWI images and spatio-temporal maps that provide qualitative visualization of the pulse wave, may potentially provide valuable information for the clinical characterization of aneurysms and other vascular pathologies that regionally alter the arterial wall mechanics. (paper)
Vermeersen, B. L. A.; Maas, L. R.; van Oers, S.; Rabitti, A.; Jara-Orue, H.
2014-12-01
One of the most peculiar features on Saturn moon Enceladus is its so-called tiger stripe pattern at the geologically active South Polar Terrain (SPT), as first observed in detail by the Cassini spacecraft early 2005. It is generally assumed that the four almost parallel surface lines that constitute this pattern are faults in the icy surface overlying a confined salty water reservoir. Indeed, later Cassini observations have shown that salty water jets originate from the tiger stripes [e.g., Hansen et al., Science, 311, 1422-1425, 2006; Postberg et al., Nature, 474, 620-622, 2011]. More recently, Porco et al. [Astron. J., 148:45, Sep. 2014] and Nimmo et al. [Astron. J., 148:46, Sep. 2014] have reported strong evidence that the geysers are not caused by frictional heating at the surface, but that geysers must originate deeper in Enceladus' interior. Tidal flexing models, like those of Hurford et al., Nature, 447, 292-294, 2007, give a good match for the brightness variations Cassini observes, but they seem to fail to reproduce the exact timing of plume brightening. Although jet activity is thus strongly connected to tidal forcing, another mechanism must be involved as well. Last year, we formulated the original idea [Vermeersen et al., AGU Fall Meeting 2013, abstract #P53B-1848] that the tiger stripe pattern is formed and maintained by induced, tidally and rotationally driven, wave-attractor motions in the ocean underneath the icy surface of the tiger-stripe region. Such wave-attractor motions are observed in water tank experiments in laboratories on Earth and in numerical experiments [Maas et al., Nature, 338, 557-561, 1997; Drijfhout and Maas, J. Phys. Oceanogr., 37, 2740-2763, 2007; Hazewinkel et al., Phys. Fluids, 22, 107102, 2010]. The latest observations by Porco et al. and Nimmo et al. seem to be in agreement with this tidal-induced wave attractor phenomenon, both with respect to tiger stripe pattern and with respect to timing of hotspot activity. However, in
Propagation Characteristics of Electromagnetic Waves Recorded by the Four CLUSTER Satellites
International Nuclear Information System (INIS)
Parrot, M.; Santolik, O.; Cornilleau-Wehrlin, N.; Maksimovic, M.; Harvey, Ch.
2001-01-01
This paper will describe the methods we use to determine the propagation characteristics of electromagnetic waves observed by the four CLUSTER satellites. The data is recorded aboard CLUSTER by the STAFF (Spatio-Temporal Analysis of Field Fluctuations) spectrum analyser. This instrument has several modes of operation, and can provide the spectral matrix of three magnetic and two electric components. This spectral matrix is processed by a dedicated software (PRASSADCO: Propagation Analysis of STAFF-SA Data with Coherency Tests) in order to determine the wave normal directions with respect to the DC magnetic field. PRASSADCO also provides a number of alternative methods to estimate wave polarisation and propagation parameters, such as the Poynting vector, and the refractive index. It is therefore possible to detect the source extension of various electromagnetic waves using the 4 satellites. Results of this data processing will be shown here for one event observed by one satellite. (author)
Belkhatir, Zehor; Mechhoud, Sarra; Laleg-Kirati, Taous-Meriem
2016-01-01
This paper deals with joint parameters and input estimation for coupled PDE-ODE system. The system consists of a damped wave equation and an infinite dimensional ODE. This model describes the spatiotemporal hemodynamic response in the brain
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.
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.
Control of transversal instabilities in reaction-diffusion systems
Totz, Sonja; Löber, Jakob; Totz, Jan Frederik; Engel, Harald
2018-05-01
In two-dimensional reaction-diffusion systems, local curvature perturbations on traveling waves are typically damped out and vanish. However, if the inhibitor diffuses much faster than the activator, transversal instabilities can arise, leading from flat to folded, spatio-temporally modulated waves and to spreading spiral turbulence. Here, we propose a scheme to induce or inhibit these instabilities via a spatio-temporal feedback loop. In a piecewise-linear version of the FitzHugh–Nagumo model, transversal instabilities and spiral turbulence in the uncontrolled system are shown to be suppressed in the presence of control, thereby stabilizing plane wave propagation. Conversely, in numerical simulations with the modified Oregonator model for the photosensitive Belousov–Zhabotinsky reaction, which does not exhibit transversal instabilities on its own, we demonstrate the feasibility of inducing transversal instabilities and study the emerging wave patterns in a well-controlled manner.
Automated detection of qualitative spatio-temporal features in electrocardiac activation maps.
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.
A new qualitative pattern classification of shear wave elastograghy for solid breast mass evaluation
Energy Technology Data Exchange (ETDEWEB)
Cong, Rui, E-mail: congrui2684@163.com; Li, Jing, E-mail: lijing@sj-hospital.org; Guo, Song, E-mail: 21751735@qq.com
2017-02-15
Highlights: • Qualitative SWE classification proposed here was significantly better than quantitative SWE parameters. • Qualitative classification proposed here was better than the classification proposed before. • Qualitative classification proposed here could obtain higher specificity without a loss of sensitivity. - Abstract: Objectives: To examine the efficacy of qualitative shear wave elastography (SWE) in the classification and evaluation of solid breast masses, and to compare this method with conventional ultrasonograghy (US), quantitative SWE parameters and qualitative SWE classification proposed before. Methods: From April 2015 to March 2016, 314 consecutive females with 325 breast masses who decided to undergo core needle biopsy and/or surgical biopsy were enrolled. Conventional US and SWE were previously performed in all enrolled subjects. Each mass was classified by two different qualitative classifications. One was established in our study, herein named the Qual1. Qual1 could classify the SWE images into five color patterns by the visual evaluations: Color pattern 1 (homogeneous pattern); Color pattern 2 (comparative homogeneous pattern); Color pattern 3 (irregularly heterogeneous pattern); Color pattern 4 (intralesional echo pattern); and Color pattern 5 (the stiff rim sign pattern). The second qualitative classification was named Qual2 here, and included a four-color overlay pattern classification (Tozaki and Fukuma, Acta Radiologica, 2011). The Breast Imaging Reporting and Data System (BI-RADS) assessment and quantitative SWE parameters were recorded. Diagnostic performances of conventional US, SWE parameters, and combinations of US and SWE parameters were compared. Results: With pathological results as the gold standard, of the 325 examined breast masses, 139 (42.77%) samples were malignant and 186 (57.23%) were benign. The Qual1 showed a higher Az value than the Qual2 and quantitative SWE parameters (all P < 0.05). When applying Qual1
A new qualitative pattern classification of shear wave elastograghy for solid breast mass evaluation
International Nuclear Information System (INIS)
Cong, Rui; Li, Jing; Guo, Song
2017-01-01
Highlights: • Qualitative SWE classification proposed here was significantly better than quantitative SWE parameters. • Qualitative classification proposed here was better than the classification proposed before. • Qualitative classification proposed here could obtain higher specificity without a loss of sensitivity. - Abstract: Objectives: To examine the efficacy of qualitative shear wave elastography (SWE) in the classification and evaluation of solid breast masses, and to compare this method with conventional ultrasonograghy (US), quantitative SWE parameters and qualitative SWE classification proposed before. Methods: From April 2015 to March 2016, 314 consecutive females with 325 breast masses who decided to undergo core needle biopsy and/or surgical biopsy were enrolled. Conventional US and SWE were previously performed in all enrolled subjects. Each mass was classified by two different qualitative classifications. One was established in our study, herein named the Qual1. Qual1 could classify the SWE images into five color patterns by the visual evaluations: Color pattern 1 (homogeneous pattern); Color pattern 2 (comparative homogeneous pattern); Color pattern 3 (irregularly heterogeneous pattern); Color pattern 4 (intralesional echo pattern); and Color pattern 5 (the stiff rim sign pattern). The second qualitative classification was named Qual2 here, and included a four-color overlay pattern classification (Tozaki and Fukuma, Acta Radiologica, 2011). The Breast Imaging Reporting and Data System (BI-RADS) assessment and quantitative SWE parameters were recorded. Diagnostic performances of conventional US, SWE parameters, and combinations of US and SWE parameters were compared. Results: With pathological results as the gold standard, of the 325 examined breast masses, 139 (42.77%) samples were malignant and 186 (57.23%) were benign. The Qual1 showed a higher Az value than the Qual2 and quantitative SWE parameters (all P < 0.05). When applying Qual1
Spatiotemporal Patterns of Urban Human Mobility
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.
International Nuclear Information System (INIS)
Pollino, Maurizio; La Porta, Luigi; Caiaffa, Emanuela
2015-01-01
GIS technologies are able to provide a useful tool for estimating the energy resource from the sea waves, assessing whether this energy flux is exploitable and evaluating the social and environmental impacts in deep water and/or in the seaboard. The DDS-WebGIS 'Energy Waves' represents a tool for displaying and sharing geo spatial data and maps, as well as a valuable support for new installations planning, forecasting system and existing infrastructure management. [it
A hybrid spatio-temporal data indexing method for trajectory databases.
Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting
2014-07-21
In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.
A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases
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.
A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases
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
Modeling waves forced by a drop bouncing on a vibrating bath
Turton, Sam; Rosales, Ruben; Bush, John
2017-11-01
We study the wavefield generated by a droplet bouncing on a bath of silicon oil undergoing vertical oscillations. Such droplets may bounce indefinitely below the Faraday threshold, and in certain parameter regimes destabilize into a walking state in which they are propelled by their own wavefield. While previous theoretical models have rationalize the behavior of single droplets, difficulties have arisen in rationalizing the behavior of multi-droplet systems. We here present a refined wave model that allows us to do so. In particular, we give a detailed account of the spatio-temporal decay of the waves, in addition to the couping between the wave amplitude and modulations in the droplet's vertical dynamics. Our analytic model is compared with the results of direct numerical simulations and experiments. We gratefully acknowledge the financial support of the NSF.
Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015.
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.
Guo, Feng; Zhou, Weijie; Li, Peng; Mao, Zhangming; Yennawar, Neela H; French, Jarrod B; Huang, Tony Jun
2015-06-01
Advances in modern X-ray sources and detector technology have made it possible for crystallographers to collect usable data on crystals of only a few micrometers or less in size. Despite these developments, sample handling techniques have significantly lagged behind and often prevent the full realization of current beamline capabilities. In order to address this shortcoming, a surface acoustic wave-based method for manipulating and patterning crystals is developed. This method, which does not damage the fragile protein crystals, can precisely manipulate and pattern micrometer and submicrometer-sized crystals for data collection and screening. The technique is robust, inexpensive, and easy to implement. This method not only promises to significantly increase efficiency and throughput of both conventional and serial crystallography experiments, but will also make it possible to collect data on samples that were previously intractable. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
The greenscape shapes surfing of resource waves in a large migratory herbivore.
Aikens, Ellen O; Kauffman, Matthew J; Merkle, Jerod A; Dwinnell, Samantha P H; Fralick, Gary L; Monteith, Kevin L
2017-06-01
The Green Wave Hypothesis posits that herbivore migration manifests in response to waves of spring green-up (i.e. green-wave surfing). Nonetheless, empirical support for the Green Wave Hypothesis is mixed, and a framework for understanding variation in surfing is lacking. In a population of migratory mule deer (Odocoileus hemionus), 31% surfed plant phenology in spring as well as a theoretically perfect surfer, and 98% surfed better than random. Green-wave surfing varied among individuals and was unrelated to age or energetic state. Instead, the greenscape, which we define as the order, rate and duration of green-up along migratory routes, was the primary factor influencing surfing. Our results indicate that migratory routes are more than a link between seasonal ranges, and they provide an important, but often overlooked, foraging habitat. In addition, the spatiotemporal configuration of forage resources that propagate along migratory routes shape animal movement and presumably, energy gains during migration. © 2017 John Wiley & Sons Ltd/CNRS.
Surfing a spike wave down the ventral stream.
VanRullen, Rufin; Thorpe, Simon J
2002-10-01
Numerous theories of neural processing, often motivated by experimental observations, have explored the computational properties of neural codes based on the absolute or relative timing of spikes in spike trains. Spiking neuron models and theories however, as well as their experimental counterparts, have generally been limited to the simulation or observation of isolated neurons, isolated spike trains, or reduced neural populations. Such theories would therefore seem inappropriate to capture the properties of a neural code relying on temporal spike patterns distributed across large neuronal populations. Here we report a range of computer simulations and theoretical considerations that were designed to explore the possibilities of one such code and its relevance for visual processing. In a unified framework where the relation between stimulus saliency and spike relative timing plays the central role, we describe how the ventral stream of the visual system could process natural input scenes and extract meaningful information, both rapidly and reliably. The first wave of spikes generated in the retina in response to a visual stimulation carries information explicitly in its spatio-temporal structure: the most salient information is represented by the first spikes over the population. This spike wave, propagating through a hierarchy of visual areas, is regenerated at each processing stage, where its temporal structure can be modified by (i). the selectivity of the cortical neurons, (ii). lateral interactions and (iii). top-down attentional influences from higher order cortical areas. The resulting model could account for the remarkable efficiency and rapidity of processing observed in the primate visual system.
Yoon, Jung Hyun; Ko, Kyung Hee; Jung, Hae Kyoung; Lee, Jong Tae
2013-12-01
To determine the correlation of qualitative shear wave elastography (SWE) pattern classification to quantitative SWE measurements and whether it is representative of quantitative SWE values with similar performances. From October 2012 to January 2013, 267 breast masses of 236 women (mean age: 45.12 ± 10.54 years, range: 21-88 years) who had undergone ultrasonography (US), SWE, and subsequent biopsy were included. US BI-RADS final assessment and qualitative and quantitative SWE measurements were recorded. Correlation between pattern classification and mean elasticity, maximum elasticity, elasticity ratio and standard deviation were evaluated. Diagnostic performances of grayscale US, SWE parameters, and US combined to SWE values were calculated and compared. Of the 267 breast masses, 208 (77.9%) were benign and 59 (22.1%) were malignant. Pattern classifications significantly correlated with all quantitative SWE measurements, showing highest correlation with maximum elasticity, r = 0.721 (P0.05). Pattern classification shows high correlation to maximum stiffness and may be representative of quantitative SWE values. When combined to grayscale US, SWE improves specificity of US. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Suppression of Spiral Waves by Voltage Clamp Techniques in a Conductance-Based Cardiac Tissue Model
International Nuclear Information System (INIS)
Lian-Chun, Yu; Guo-Yong, Zhang; Yong, Chen; Jun, Ma
2008-01-01
A new control method is proposed to control the spatio-temporal dynamics in excitable media, which is described by the Morris–Lecar cells model. It is confirmed that successful suppression of spiral waves can be obtained by spatially clamping the membrane voltage of the excitable cells. The low voltage clamping induces breakup of spiral waves and the fragments are soon absorbed by low voltage obstacles, whereas the high voltage clamping generates travel waves that annihilate spiral waves through collision with them. However, each method has its shortcomings. Furthermore, a two-step method that combines both low and high voltage clamp techniques is then presented as a possible way of out this predicament. (cross-disciplinary physics and related areas of science and technology)
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.
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.
Internal wave patterns in enclosed density-stratified and rotating fluids
Manders, A.M.A.
2003-01-01
Stratified fluids support internal waves, which propagate obliquely through the fluid. The angle with respectto the stratification direction is contrained: it is purely determined by the wave frequency and the strength of the density stratification (internal gravity waves) or the rotation rate
The convection patterns in microemulsions
International Nuclear Information System (INIS)
Korneta, W.; Lopez Quintela, M.A.; Fernandez Novoa, A.
1991-07-01
The Rayleigh-Benard convection in the microemulsion consisting of water (7.5%), cyclohexan (oil-61.7%) and diethylenglycolmonobutylether (surfactant-30.8%) is studied from the onset of convection to the phase separation. The five classes of convection patterns are observed and recorded on the video: localized travelling waves, travelling waves, travelling waves and localized steady rolls, steady rolls and steady polygons. The Fourier transforms and histograms of these patterns are presented. The origin of any pattern is discussed. The intermittent behaviour close to the phase separation was observed. Possible applications of the obtained results are suggested. (author). 6 refs, 4 figs
Spatio-Temporal Characteristics of Resident Trip Based on Poi and OD Data of Float CAR in Beijing
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.
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
Directory of Open Access Journals (Sweden)
Susanne H Landis
Full Text Available Extreme climate events such as heat waves are expected to increase in frequency under global change. As one indirect effect, they can alter magnitude and direction of species interactions, for example those between hosts and parasites. We simulated a summer heat wave to investigate how a changing environment affects the interaction between the broad-nosed pipefish (Syngnathus typhle as a host and its digenean trematode parasite (Cryptocotyle lingua. In a fully reciprocal laboratory infection experiment, pipefish from three different coastal locations were exposed to sympatric and allopatric trematode cercariae. In order to examine whether an extreme climatic event disrupts patterns of locally adapted host-parasite combinations we measured the parasite's transmission success as well as the host's adaptive and innate immune defence under control and heat wave conditions. Independent of temperature, sympatric cercariae were always more successful than allopatric ones, indicating that parasites are locally adapted to their hosts. Hosts suffered from heat stress as suggested by fewer cells of the adaptive immune system (lymphocytes compared to the same groups that were kept at 18°C. However, the proportion of the innate immune cells (monocytes was higher in the 18°C water. Contrary to our expectations, no interaction between host immune defence, parasite infectivity and temperature stress were found, nor did the pattern of local adaptation change due to increased water temperature. Thus, in this host-parasite interaction, the sympatric parasite keeps ahead of the coevolutionary dynamics across sites, even under increasing temperatures as expected under marine global warming.
Mimickers of generalized spike and wave discharges.
Azzam, Raed; Bhatt, Amar B
2014-06-01
Overinterpretation of benign EEG variants is a common problem that can lead to the misdiagnosis of epilepsy. We review four normal patterns that mimic generalized spike and wave discharges: phantom spike-and-wave, hyperventilation hypersynchrony, hypnagogic/ hypnopompic hypersynchrony, and mitten patterns.
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.
International Nuclear Information System (INIS)
Jiang, Shixiao W; Lu, Haihao; Zhou, Douglas; Cai, David
2016-01-01
Characterizing dispersive wave turbulence in the long time dynamics is central to understanding of many natural phenomena, e.g., in atmosphere ocean dynamics, nonlinear optics, and plasma physics. Using the β -Fermi–Pasta–Ulam nonlinear system as a prototypical example, we show that in thermal equilibrium and non-equilibrium steady state the turbulent state even in the strongly nonlinear regime possesses an effective linear stochastic structure in renormalized normal variables. In this framework, we can well characterize the spatiotemporal dynamics, which are dominated by long-wavelength renormalized waves. We further demonstrate that the energy flux is nearly saturated by the long-wavelength renormalized waves in non-equilibrium steady state. The scenario of such effective linear stochastic dynamics can be extended to study turbulent states in other nonlinear wave systems. (paper)
Full-Scale Approximations of Spatio-Temporal Covariance Models for Large Datasets
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.
Asiri, Sharefa M.; Laleg-Kirati, Taous-Meriem
2017-01-01
In this paper, a method based on modulating functions is proposed to estimate the Cerebral Blood Flow (CBF). The problem is written in an input estimation problem for a damped wave equation which is used to model the spatiotemporal variations