Spatial Spreading Research Articles

Spreading of perturbations in myosin group kinetics along actin filaments

Global changes in the state of spatially distributed systems can often be traced back to perturbations that arise locally. Whether such local perturbations grow into global changes depends on the system geometry and the spatial spreading of these perturbations. Here, we investigate how different spreading behaviors of local perturbations determine their global impact in 1-dimensional systems of different size. Specifically, we assessed sliding arrest events in in vitro motility assays where myosins propel actin, and simulated the underlying mechanochemistry of myosins that bind along the actin filament. We observed spontaneous sliding arrest events that occurred more frequently for shorter actin filaments. This observation could be explained by spontaneous local arrest of myosin kinetics that stabilizes once it spreads throughout an entire actin filament. When we introduced intermediate concentrations of the actin cross-linker filamin, longer actin was arrested more frequently. This observation was reproduced by simulations where filamin binding induces persistent local arrest of myosin kinetics, which subsequently spreads throughout the actin filament. A spin chain model with nearest-neighbor coupling reproduced key features of our experiments and simulations, thus extending to other linear systems with nearest-neighbor coupling the following conclusions: 1) perturbations that are persistent only once they spread throughout the system are more effective in smaller systems, and 2) perturbations that are persistent upon their establishment are more effective in larger systems. Beyond these general conclusions, our work also provides a theoretical model of collective myosin kinetics with a finite range of mechanical coupling along the actin filament.

Can chemotaxis speed up or slow down the spatial spreading in parabolic-elliptic Keller-Segel systems with logistic source?

The current paper is concerned with the spatial spreading speed and minimal wave speed of the following Keller-Segel chemoattraction system, [Formula: see text]where [Formula: see text], a, b, [Formula: see text], and [Formula: see text] are positive constants. Assume [Formula: see text] . Then if in addition [Formula: see text] holds, it is proved that [Formula: see text] is the spreading speed of the solutions of (0.1) with nonnegative continuous initial function [Formula: see text] with nonempty compact support, that is, [Formula: see text]and [Formula: see text]where [Formula: see text] is the unique global classical solution of (0.1) with [Formula: see text]. It is also proved that, if [Formula: see text] and [Formula: see text] holds, then [Formula: see text] is the minimal speed of the traveling wave solutions of (0.1) connecting (0,0) and [Formula: see text], that is, for any [Formula: see text], (0.1) has a traveling wave solution connecting (0,0) and [Formula: see text] with speed c, and (0.1) has no such traveling wave solutions with speed less than [Formula: see text]. Note that [Formula: see text] is the spatial spreading speed as well as the minimal wave speed of the following Fisher-KPP equation, [Formula: see text]Hence, if [Formula: see text] and [Formula: see text], or [Formula: see text] and [Formula: see text], then the chemotaxis neither speeds up nor slows down the spatial spreading in (0.1).

Suppression of epidemic spreading process on multiplex networks via active immunization.

Spatial epidemic spreading, a fundamental dynamical process upon complex networks, attracts huge research interest during the past few decades. To suppress the spreading of epidemic, a couple of effective methods have been proposed, including node vaccination. Under such a scenario, nodes are immunized passively and fail to reveal the mechanisms of active activity. Here, we suggest one novel model of an observer node, which can identify infection through interacting with infected neighbors and inform the other neighbors for vaccination, on multiplex networks, consisting of epidemic spreading layer and information spreading layer. In detail, the epidemic spreading layer supports susceptible-infected-recovered process, while observer nodes will be selected according to several algorithms derived from percolation theory. Numerical simulation results show that the algorithm based on large degree performs better than random placement, while the algorithm based on nodes' degree in the information spreading layer performs the best (i.e., the best suppression efficacy is guaranteed when placing observer nodes based on nodes' degree in the information spreading layer). With the help of state probability transition equation, the above phenomena can be validated accurately. Our work thus may shed new light into understanding control of empirical epidemic control.

Inviscid diffusion of vorticity in low-temperature superfluid helium

We numerically study the spatial spreading of quantized vortex lines in low temperature liquid helium. The vortex lines, initially concentrated in a small region, diffuse into the surrounding vortex-free helium, a situation which is typical of many experiments. We find that this spreading, which occurs in the absence of viscosity, emerges from the interactions between the vortex lines, and can be interpreted as a diffusion process with effective coefficient equal to approximately 0.5$\kappa$ where $\kappa$ is the quantum of circulation.

Rough infection fronts in a random medium

We study extended infection fronts advancing over a spatially uniform susceptible population by solving numerically a diffusive Kermack McKendrick SIR model with a dichotomous spatially random transmission rate, in two dimensions. We find a non-trivial dynamic critical behavior in the mean velocity, in the shape, and in the rough geometry of the displacement field of the infective front as the disorder approaches a threshold value for spatial spreading of the infection.

Mechanistic and experimental models of cell migration reveal the importance of cell-to-cell pushing in cell invasion

Moving fronts of cells are essential for development, repair and disease progression. Therefore, understanding and quantifying the details of the mechanisms that drive the movement of cell fronts is of wide interest. Quantitatively identifying the role of intercellular interactions, and in particular the role of cell pushing, remains an open question. In this work, we report a combined experimental-modelling approach showing that intercellular interactions contribute significantly to the spatial spreading of a population of cells. We use a novel experimental data set with PC-3 prostate cancer cells that have been pretreated with Mitomycin-C to suppress proliferation. This allows us to experimentally separate the effects of cell migration from cell proliferation, thereby enabling us to focus on the migration process in detail as the population of cells recolonizes an initially-vacant region in a series of two-dimensional experiments. We quantitatively model the experiments using a stochastic modelling framework, based on Langevin dynamics, which explicitly incorporates random motility and various intercellular forces including: (i) long range attraction (adhesion); and (ii) finite size effects that drive short range repulsion (pushing). Quantitatively comparing the ability of this model to describe the experimentally observed population-level behaviour provides us with quantitative insight into the roles of random motility and intercellular interactions. To quantify the mechanisms at play, we calibrate the stochastic model to match experimental cell density profiles to obtain estimates of cell diffusivity, D, and the amplitude of intercellular forces, f0. Our analysis shows that taking a standard modelling approach which ignores intercellular forces provides a poor match to the experimental data whereas incorporating intercellular forces, including short-range pushing and longer range attraction, leads to a faithful representation of the experimental observations. These results demonstrate a significant role of cell pushing during cell front movement and invasion.

A probabilistic risk modelling chain for analysis of regional flood events

A probabilistic flood risk modelling chain is proposed for flood risk analysis with consideration of spatial spreading and temporal clustering of the flood events. The proposed method consists of (1) a continuous simulation of long-term climatic and hydrologic fields, (2) Monte-Carlo simulations of a 1D river and inundation model and (3) a probabilistic loss model. In the first stage, three multisite multivariate weather generators were tested and a K-nearest neighbor weather generator (KNN-CAD v4) was found most suitable to reproduce hydrological extremes. The methodology was then applied to identify variations in risk between spatially coherent and simplified event sets generated from 5000 years of synthetic data across four river basins in Uttarakhand, India. The results showed that preserving the spatial coherency of regional events lead to a spreading of the T-year local event distributions on both sides of a uniform regional T-year return period. The specificity of the exposure and the correlations between local events translated into minimal (4%) differences in losses at high return periods (> 50 year) but larger difference (20%) at low return periods (5 to 10-year). The redistribution of loss frequencies led to negligible differences in the Annual Average Losses between the different event sets. In this application, a simplified event set structure with uniform but appropriate T-year return periods proved to capture reasonably well the averaged risk metrics regionally. This study illustrates the complexity of estimating regional flood risk accumulation and exemplifies how a probabilistic risk model chain with continuous simulation can provide a more detailed picture of flood risks.

Agronegócio do dendê e campesinato no Pará

A expansão capitalista do dendê pelo nordeste do Pará, no início do século XXI, está intrinsecamente conectada com os rumos políticos do governo de Luís Inácio Lula da Silva, em 2003, quando se intensifica o investimento na produção dos agrocombustíveis no Brasil. Articulam-se neste cenário o discurso de preservação e desenvolvimento regional, aliados a inclusão social dos camponeses na cadeia produtiva do dendê. Contraditoriamente à perspectiva de geração de renda e por conseguinte, melhoria de vida dos povos do campo expresso no PNPB, visualizou-se a ampliação das disputas entre terra de negócio versus terra de trabalho. Desse modo, busca-se nesse artigo discutir a espacialização do agronegócio do dendê no nordeste paraense bem como as ações empreendidas pelos camponeses como estratégia de resistência a esse processo. O texto foi construído a partir das reflexões suscitadas na pesquisa de campo realizada entre os anos de 2012 e 2017 na região. Mais especificamente, apresentaremos uma abordagem geo-histórica do dendê na Amazônia e suas relações contraditórias com as famílias camponesas que vivem em suas proximidades.

Social network analysis for better understanding of influenza.

The objective of this study is to improve the understanding of spatial spreading of complicated cases of influenza that required hospitalizations, by creating heatmaps and social networks. They will allow to identify critical hubs and routes of spreading of Influenza, in specific geographic locations, in order to contain infections and prevent complications, that require hospitalizations. Data were downloaded from the Healthcare Cost and Utilization Project (HCUP) - SID, New York State database. Patients hospitalized with flu complications, between 2003 and 2012 were included in the research (30,380 cases). A novel approach was designed, by constructing heatmaps for specific geographic regions in New York state and power law networks, in order to analyze distribution of hospitalized flu cases. Heatmaps revealed that distributions of patients follow urban areas and big roads, indicating that flu spreads along routes, that people use to travel. A scale-free network, created from correlations among zip codes, discovered that, the highest populated zip codes didn't have the largest number of patients with flu complications. Among the top five most affected zip codes, four were in Bronx. Demographics of top affected zip codes were presented in results. Normalized numbers of cases per population revealed that, none of zip codes from Bronx were in the top 20. All zip codes with the highest node degrees were in New York City area. Heatmaps identified geographic distribution of hospitalized flu patients and network analysis identified hubs of the infection. Our results will enable better estimation of resources for prevention and treatment of hospitalized patients with complications of Influenza. Analyses of geographic distribution of hospitalized patients with Influenza and demographic characteristics of populations, help us to make better planning and management of resources for Influenza patients, that require hospitalization. Obtained results could potentially help to save many lives and improve the health of the population.

Accounting for heterogeneous invasion rates reveals management impacts on the spatial expansion of an invasive species

AbstractSuccess of large‐scale control programs for established invasive species is challenging to evaluate because of spatial variability in expansion rates, management techniques, and the strength of management intensity. For a well‐established invasive species in the spreading phase of invasion, a useful metric of impact is the magnitude by which control slows the rate of spatial spread. The prevention of spatial spreading likely results in substantial benefits in terms of ecosystem or economic damage that is prevented by an expanding invasive species. To understand how local management actions could impact the spatial spread of an established invasive species, we analyzed distribution and management data for feral swine across contiguous United States using occupancy analysis. We quantified changes in the rate of spatial expansion of feral swine and its relationship to local management actions. We found that after 4 yr of enhanced control, invasion probability decreased by 8% on average relative to pre‐program rates. This decrease was as high as 15% on average in states with low‐density populations of feral swine. The amount of decrease in invasion rate was attributed to removal intensity in neighboring counties and depended on the extent of neighboring counties with feral swine (spatial heterogeneity in local invasion pressure). Although we did not find a significant overall increase in the probability of elimination, increased elimination probability tended to occur in regions with low invasion pressure. Accounting for spatial heterogeneity in invasion pressure was important for quantifying management impacts (i.e., the relationship between management intensity and spatial spreading processes) because management impacts changed depending on the strength of invasion pressure from neighboring counties. Predicting reduction in spatial spread of an invasive species is an important first step in valuation of overall damage reduction for invasive species control programs by providing estimates of where a species may be, and thus which natural and agricultural resources would be affected, if the control program had not been operating. For minimizing losses from spatial expansion of an invasive species, our framework can be used for adaptive resource prioritization to areas where spatial expansion and underlying damage potential are concurrently highest.

Semiclassical quench dynamics of Bose gases in optical lattices

We analyze the time evolution of the Bose-Hubbard model after a sudden quantum quench to a weakly interacting regime. Specifically, motivated by a recent experiment at Kyoto University, we numerically simulate redistribution of the kinetic and onsite-interaction energies at an early time, which was observed in non-equilibrium dynamics of ultracold Bose gases in a cubic optical lattice starting with a singly-occupied Mott-insulator state. In order to compute the short-time dynamics corresponding to the experimental situation, we apply the truncated-Wigner approximation (TWA) to the Bose-Hubbard model on a cubic lattice. We show that our semiclassical approach quantitatively reproduces the fast redistribution dynamics. We further analyze spatial spreading of density-density correlations at equal time in the Bose-Hubbard model on a square lattice with a large filling factor. When the system is initially prepared in a coherent state, we find that a propagation velocity of the correlation wave packet in the correlation function strongly depends on the final interaction strength, and it is bounded by twice the maximum group velocity of the elementary excitations. In contrast, when the system is initially in a Mott-insulator state, the propagation velocity of the wave packet is approximately independent of the final interaction strength.

Mining spatiotemporal association patterns from complex geographic phenomena

ABSTRACTSpatiotemporal association pattern mining can discover interesting interdependent relationships among various types of geospatial data. However, existing mining methods for spatiotemporal association patterns usually model geographic phenomena as simple spatiotemporal point events. Therefore, they cannot be applied to complex geographic phenomena, which continuously change their properties, shapes or locations, such as storms and air pollution. The most salient feature of such complex geographic phenomena is the geographic dynamic. To fully reveal dynamic characteristics of complex geographic phenomena and discover their associated factors, this research proposes a novel complex event-based spatiotemporal association pattern mining framework. First, a complex geographic event was hierarchically modeled and represented by a new data structure named directed spatiotemporal routes. Then, sequence mining technique was applied to discover the spatiotemporal spread pattern of the complex geographic events. An adaptive spatiotemporal episode pattern mining algorithm was proposed to discover the candidate driving factors for the occurrence of complex geographic events. Finally, the proposed approach was evaluated by analyzing the air pollution in the region of Beijing-Tianjin-Hebei. The experimental results showed that the proposed approach can well address the geographic dynamic of complex geographic phenomena, such as the spatial spreading pattern and spatiotemporal interaction with candidate driving factors.

Periodic and Spatial Spreading of Alkanes and Alcanivorax Bacteria in Deep Waters of the Mariana Trench.

In subduction zones, serpentinization and biological processes may release alkanes to the deep waters, which would probably result in the rapid spread of Alcanivorax However, the timing and area of the alkane distribution and associated enrichment of alkane-degrading microbes in the dark world of the deep ocean have not been explored. In this study, we report the richness (up to 17.8%) of alkane-degrading bacteria, represented by Alcanivorax jadensis, in deep water samples obtained at 3,000 to 6,000 m in the Mariana Trench in two cruises. The relative abundance of A. jadensis correlated with copy numbers of functional almA and alkB genes, which are involved in alkane degradation. In these water samples, we detected a high flux of alkanes, which probably resulted in the prevalence of A. jadensis in the deep waters. Contigs of A. jadensis were binned from the metagenomes for examination of alkane degradation pathways and deep sea-specific pathways, which revealed a lack of nitrate and nitrite dissimilatory reduction in our A. jadensis strains. Comparing the results for the two cruises conducted close to each other, we suggest periodic release of alkanes that may spread widely but periodically in the trench. Distribution of alkane-degrading bacteria in the world's oceans suggests the periodic and remarkable contributions of Alcanivorax to the deep sea organic carbon and nitrogen sources.IMPORTANCE In the oligotrophic environment of the Mariana Trench, alkanes as carbohydrates are important for the ecosystem, but their spatial and periodic spreading in deep waters has never been reported. Alkane-degrading bacteria such as Alcanivorax spp. are biological signals of the alkane distribution. In the present study, Alcanivorax was abundant in some waters, at depths of up to 6,000 m, in the Mariana Trench. Genomic, transcriptomic, and chemical analyses provide evidence for the presence and activities of Alcanivorax jadensis in deep sea zones. The periodic spreading of alkanes, probably from the subductive plates, might have fundamentally modified the local microbial communities, as well as perhaps the deep sea microenvironment.

Data on THMs concentration and spatial trend in water distribution network (a preliminary study in center of Iran)

The Trihalomethanes (THMs) formed due to a reaction between water disinfection chlorine and some natural organic matters, as chlorinated by products. The aim of this study was determination of THMs values and spatial trend in Yazd city water distribution network, in center of Iran. Sampling of tap water was done in two autumn and winter seasons. The THMs value were measured by using a gas chromatograph-mass spectrometer (GC/MS), Agilent Company 6890 N. The spatial analysis of THMs values was carried out using ArcGIS 10.1 to show the spatial spreading. The Kriging method was used to draw distribution maps. Using the Kriging method to illustrate the difference or precision of forecasts is relatively easy compared to the other interpolation methods. Also, the acceptable level of % RMSE (Root mean square error) was calculated for Kriging method (% RMSE > 40). Thus, this protocol as integrated between data and geraphic could easily used for reporting of THMs level in studies of water distribution network.Finally, the maximum THMs value were obtained lower than USEPA and WHO guidelines for drinking water (THMs < 40 ppb).

Effect of Crystal Structure on Hole Carrier Generation in Wide-gap P-type Tin-Niobate

AbstractSn2Nb2O7 and SnNb2O6 are promising candidates for wide-gap p-type conducting oxides with high mobility, because their valence-band maximum are composed of Sn 5s orbital with large spatial spreading and isotropic nature. Though hole carriers were generated by Sn4+ substitutional defects on Nb5+ site (Sn’Nb) in the substructure of Nb2O6 octahedra in both tin niobates, the generation efficiency of hole carriers in SnNb2O6 was larger than that of Sn2Nb2O7. From the variation in bond length of Nb-O in the Nb2O6 octahedra calculated by Rietveld analysis, the difference in carrier generation efficiency of two tin niobates was examined. The bond length of Nb-O in p-type Sn2Nb2O7 with large amounts of Sn’Nb was smaller than that of n-type Sn2Nb2O7 with small amounts of Sn’Nb. The holes generated by Sn’Nb were considered to be captured by the negative charge of oxygen anions consisting of the Nb2O6 octahedra, resulting in low carrier generation efficiency. In SnNb2O6 showing higher efficiency, Nb-O was 8.6 % larger than that of p-type Sn2Nb2O7. It is considered that the large Nb-O bond length provide the preferred environment for the generation of positive holes, resulting in the higher carrier generation efficiency.

Spatial dynamics of transmission and persistence of African swine fever in wild boar populations: insight for control

Spatial dynamics of transmission and persistence of African swine fever in wild boar populations: insight for control

COASTAL FLOODING-INDUCED DEBRIS MOTION

Extreme coastal events such as the 2004 Indian Ocean Tsunami, the 2011 Tohoku Tsunami as well as the 2005 Katrina and 2012 Sandy hurricanes demonstrated that, hydrodynamic loading aside, debris loading represents a major factor in the extreme loading conditions experienced by inland infrastructure. While extreme hydrodynamic loading due to coastal flooding events has been the object of intense research over the past decade, few studies dealing with debris impact due to coastal flooding have been conducted. Post-tsunami forensic engineering field investigations conducted by the authors (Nistor et al. 2005; Shibayama et al., 2006; Nistor et al. 2010) or other researchers (Chock et al. 2012, Sato et al. 2014;) revealed that debris loading and debris damming have a significant effect on the structural integrity of buildings and infrastructure in general, especially in high-density urban areas. Current design guidelines (FEMA P-55, 2011; FEMA P-646, 2012) and the new ASCE-7 Chapter 6 - Tsunami Effects and Loads suggest conservative estimations of the debris spatial spreading based on limited sets of field data to assess debris impact potential (Chock et al., 2012; Naito et al., 2014). The primary objective of this study was to investigate the spatial and temporal displacement of floating debris due to rapid coastal flooding in a built-in port environment using two novel different measuring techniques: (1) high-accuracy video debris detection and tracking system and (2) a real-time locating “smart” sensor-tracking system. Results are compared with prescriptions of the ASCE7 Chapter 6 pertaining to debris motion.

Epidemiological spreading of mortgage default

PurposeThis paper aims to introduce mathematical models to capture the spreading of epidemics to explain the expansion of mortgage default events in the USA.Design/methodology/approachThe authors use the state of infectiousness and death to represent the subsequent steps of payment elinquency and default, respectively. As the local economic structure influences regional unemployment, which is a strong driver of mortgage default, the authors model interdependencies of regional mortgage default rates through employment conditions and vicinity.FindingsBased on a large sample between 2000 and 2014 of loan-level data, the estimation of key parameters of the model is proposed. The model’s forecast accuracy shows an above-average performance compared to well-known approaches such as linear regression or logit models.Originality/valueThe key findings may be useful in understanding the dynamics of mortgage defaults and its spatial spreading.

Modeling the spreading and interaction between wild and transgenic mosquitoes with a random dispersal.

Due to recent advances in genetic manipulation, transgenic mosquitoes may be a viable alternative to reduce some diseases. Feasibility conditions are obtained by simulating and analyzing mathematical models that describe the behavior of wild and transgenic populations living in the same geographic area. In this paper, we present a reaction–diffusion model in which the reaction term is a nonlinear function that describes the interaction between wild and transgenic mosquitoes, considering the zygosity, and the diffusive term that represents a nonuniform spatial spreading characterized by a random diffusion parameter. The resulting nonlinear system of partial differential equations is numerically solved using the sequential operator splitting technique, combining the finite element method and Runge-Kutta method. This scheme is numerically implemented considering uncertainty in the diffusion parameters of the model. Several scenarios simulating spatial release strategies of transgenic mosquitoes are analyzed, demonstrating an intrinsic association between the transgene frequency in the total population and the strategy adopted.

Major Baltic Inflow Statistics – Revised

Major Baltic inflow events (MBI) transport large amounts of saline water into the Baltic. They are the solely source for deep water ventilation in the central Baltic basins, and control to a large extent the environmental conditions below the permanent halocline. Available series of MBI frequency and intensity depict strong decrease of MBI frequency after the 1980ies, followed by long lasting stagnation periods in the central Baltic basins. However, the expected decrease in mean salinity of the Baltic was not observed. Also the frequency of large volume changes of the Baltic has not changed, and recent model studies predict a slight increase of MBI frequency with warming climate. Using long term data series of sea level, river discharge, and salinity from the Belt Sea and the Sound a continuous series of barotropic inflows was reconstructed for the period from 1887 till present. A comparison with the MBI series of Fischer and Matthaus (1996) revealed significant differences in the period since the 1980ies. The reasons for the deviations are mainly the lack of appropriate data between 1976 and 1991, and the change in observation methods afterwards, which caused a bias in the inflow statistics. In contrast to earlier investigations the revised MBI series depicts no significant long term trend in MBI frequency and intensity, contradicting the hypothesis that climate change caused a decreasing MBI frequency. There exists a decadal variability of MBI with a main period of 25 to 30 years. Periods with reduced MBI frequency were identified. The revised MBI series was proved with observations of dissolved oxygen and salinity in the bottom layer of the Bornholm basin. Until today climate change has no obvious impact on the MBI related oxygen supply to the central Baltic Sea. The increased eutrophication during the last century is most probably the main driver for temporal and spatial spreading of suboxic and anoxic conditions in the deep layer of the Baltic Sea.