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Journal articles on the topic 'Spatial spreading'

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Published: 7 June 2025

Last updated: 16 July 2025

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Lion, S., and S. Gandon. "Spatial evolutionary epidemiology of spreading epidemics." Proceedings of the Royal Society B: Biological Sciences 283, no. 1841 (2016): 20161170. http://dx.doi.org/10.1098/rspb.2016.1170.

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Most spatial models of host–parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation.

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Wong, David W. S., and Yun Li. "Spreading of COVID-19: Density matters." PLOS ONE 15, no. 12 (2020): e0242398. http://dx.doi.org/10.1371/journal.pone.0242398.

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Physical distancing has been argued as one of the effective means to combat the spread of COVID-19 before a vaccine or therapeutic drug becomes available. How far people can be spatially separated is partly behavioral but partly constrained by population density. Most models developed to predict the spread of COVID-19 in the U.S. do not include population density explicitly. This study shows that population density is an effective predictor of cumulative infection cases in the U.S. at the county level. Daily cumulative cases by counties are converted into 7-day moving averages. Treating the weekly averages as the dependent variable and the county population density levels as the explanatory variable, both in logarithmic scale, this study assesses how population density has shaped the distributions of infection cases across the U.S. from early March to late May, 2020. Additional variables reflecting the percentages of African Americans, Hispanic-Latina, and older adults in logarithmic scale are also included. Spatial regression models with a spatial error specification are also used to account for the spatial spillover effect. Population density alone accounts for 57% of the variation (R-squared) in the aspatial models and up to 76% in the spatial models. Adding the three population subgroup percentage variables raised the R-squared of the aspatial models to 72% and the spatial model to 84%. The influences of the three population subgroups were substantial, but changed over time, while the contributions of population density have been quite stable after the first several weeks, ascertaining the importance of population density in shaping the spread of infection in individual counties, and in their neighboring counties. Thus, population density and sizes of vulnerable population subgroups should be explicitly included in transmission models that predict the impacts of COVID-19, particularly at the sub-county level.

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HUI, ZI, XU CAI, JEAN-MARC GRENECHE, and QIUPING A. WANG. "IMPACTS OF SPATIAL STRUCTURE ON EPIDEMIC SPREADING." International Journal of Modern Physics C 23, no. 12 (2012): 1250082. http://dx.doi.org/10.1142/s0129183112500829.

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The epidemic spreading on spatial-driven network is studied with the spatial susceptible-infected-susceptible (SIS) model. The network is constructed by random addition of nodes on the plan. The probability for a previous node to be connected to the new one is inversely proportional to their spatial distance to the power α. The spreading rate between two nodes is inversely proportional to their spatial distance. The effective spreading time increases with the increasing of α. The proportional coefficient is found to have a α-dependent threshold with a maximum situated in the interval 1.5 < α < 2.

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Wayland, Richard, David Bromley, Douglas Pickett, and Anthony Passamante. "Measuring spatial spreading in recurrent time series." Physica D: Nonlinear Phenomena 79, no. 2-4 (1994): 320–34. http://dx.doi.org/10.1016/s0167-2789(05)80012-0.

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Savva, Nikos, and Serafim Kalliadasis. "Influence of spatial heterogeneities on spreading dynamics." Journal of Physics: Conference Series 216 (March 1, 2010): 012017. http://dx.doi.org/10.1088/1742-6596/216/1/012017.

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Sapaty, P. S., and R. Finkelstein. "Fighting global viruses under spatial grasp technology." Mathematical machines and systems 4 (2020): 113–24. http://dx.doi.org/10.34121/1028-9763-2020-4-113-124.

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This has been inspired by the current world fight with COVID-19, in an attempt to participate in it with patented and developed networking technology, also based on spreading powerful viruses in large physi-cal and virtual spaces. The Spatial Grasp Technology (SGT) with basic Spatial Grasp Language (SGL) is using parallel self-spreading, self-replicating, and self-matching semantic level code creating powerful distributed infrastructures for solving complex problems. The paper shows how to find virus sources in distributed networks, first, by tracing them via infected predecessors if such were fixed, and then, more complexly, by moving through nodes with lower or close infection time, also taking into account possi-ble failures in real networks. If to outline a number of infected nodes staying far away from each other and on different sides of the infected network, the probable source may also be on intersection of short-est path trees starting in them, as shown in SGL. But analyzing complexity, dynamics, and unpredicta-bility of spread of Covid-19, we understood the insufficiency of discrete networks for simulating its world coverage. By using the SGT capability to directly operate in continuous physical spaces too, we showed how to describe the global malicious virus in a massive way, with the infection spreading via many and so far unclear channels. The paper also shows how to model the planned distribution of the antivirus vaccine and its global impact on the virus, symbolically presented as spatial fight of benign (vaccine) with malicious (Covid) viruses. The latest version of SGT can be implemented and integrated with any existing networked systems in a global manner, with installment of communicating SGL in-terpreters in millions to billions copies and converting the world into a global simulation and control engine.

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Indrajani, Indrajani. "Rancang Bangun Basis Data Spasial Pemantauan Penyebaran Klinik 24 Jam di Dki Jakarta." ComTech: Computer, Mathematics and Engineering Applications 4, no. 2 (2013): 1368. http://dx.doi.org/10.21512/comtech.v4i2.2674.

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The purpose of this research is for designing and building spatial database to monitor the spreading of 24 hours clinic in DKI Jakarta. It includes spatial and attributive information for clinics. The benefit of this research is integrating tabular database with spatial database, giving information about the spreading of clinicspatially, and locating new clinics easily in DKI Jakarta. The research method used is data collection such as examine the documents and observation, followed by database analysis and design by Life Cycle (DBLC). The result obtained from this research is a spatial model of database that monitors the spreading of 24-hour clinics in DKI Jakarta. Implementing the new spatial database in monitoring the spread of clinic 24 hours can help the government to increase and develop health service for people in DKI Jakarta.

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Cramer, L. P., and T. J. Mitchison. "Myosin is involved in postmitotic cell spreading." Journal of Cell Biology 131, no. 1 (1995): 179–89. http://dx.doi.org/10.1083/jcb.131.1.179.

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We have investigated a role for myosin in postmitotic Potoroo tridactylis kidney (PtK2) cell spreading by inhibitor studies, time-lapse video microscopy, and immunofluorescence. We have also determined the spatial organization and polarity of actin filaments in postmitotic spreading cells. We show that butanedione monoxime (BDM), a known inhibitor of muscle myosin II, inhibits nonmuscle myosin II and myosin V adenosine triphosphatases. BDM reversibly inhibits PtK2 postmitotic cell spreading. Listeria motility is not affected by this drug. Electron microscopy studies show that some actin filaments in spreading edges are part of actin bundles that are also found in long, thin, structures that are connected to spreading edges and substrate (retraction fibers), and that 90% of this actin is oriented with barbed ends in the direction of spreading. The remaining actin in spreading edges has a more random orientation and spatial arrangement. Myosin II is associated with actin polymer in spreading cell edges, but not retraction fibers. Myosin II is excluded from lamellipodia that protrude from the cell edge at the end of spreading. We suggest that spreading involves myosin, possibly myosin II.

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Richardson, Thomas O., and Thomas E. Gorochowski. "Beyond contact-based transmission networks: the role of spatial coincidence." Journal of The Royal Society Interface 12, no. 111 (2015): 20150705. http://dx.doi.org/10.1098/rsif.2015.0705.

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Animal societies rely on interactions between group members to effectively communicate and coordinate their actions. To date, the transmission properties of interaction networks formed by direct physical contacts have been extensively studied for many animal societies and in all cases found to inhibit spreading. Such direct interactions do not, however, represent the only viable pathways. When spreading agents can persist in the environment, indirect transmission via ‘same-place, different-time’ spatial coincidences becomes possible. Previous studies have neglected these indirect pathways and their role in transmission. Here, we use rock ant colonies, a model social species whose flat nest geometry, coupled with individually tagged workers, allowed us to build temporally and spatially explicit interaction networks in which edges represent either direct physical contacts or indirect spatial coincidences. We show how the addition of indirect pathways allows the network to enhance or inhibit the spreading of different types of agent. This dual-functionality arises from an interplay between the interaction-strength distribution generated by the ants' movement and environmental decay characteristics of the spreading agent. These findings offer a general mechanism for understanding how interaction patterns might be tuned in animal societies to control the simultaneous transmission of harmful and beneficial agents.

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Vaknin, Dana, Michael M. Danziger, and Shlomo Havlin. "Spreading of localized attacks in spatial multiplex networks." New Journal of Physics 19, no. 7 (2017): 073037. http://dx.doi.org/10.1088/1367-2630/aa7b09.

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Zimeras, Stelios, and Yiannis G. Matsinos. "Modeling Uncertainty Based on Spatial Models in Spreading Diseases." International Journal of Reliable and Quality E-Healthcare 8, no. 4 (2019): 55–66. http://dx.doi.org/10.4018/ijrqeh.2019100103.

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Lately, spatial models have become a powerful, necessary statistical tool to estimate parameters where data are represented by regions of interests using the window method . Estimation processes based on the high dimensionality of the data have become difficult to implement especially in cases where variability in the spatial models is the main task to investigate. Variability between spatial models considering hierarchical levels of scale, most of the time, involves errors leading to uncertainty in spatial regions. Solving the problem with uncertainty via the estimation of errors in spatial models, complex models could be simplified in easiest ones and important decisions for the quality of data could be taken.

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Franzheva, Olena D. "Analysis of quasi-periodic space-time non-separable processes to support decision-making in medical monitoring systems." Herald of Advanced Information Technology 4, no. 3 (2021): 225–31. http://dx.doi.org/10.15276/hait.03.2021.2.

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In many decisionsupport systemsthere are processedchaotic spatial-time processes which are non-separable and quasi-periodic. Some examples of such systemsareepidemic spreading, population development, fire spreading, radio wave signals, image processing, information encryption, radio vision, etc. Processes in these systems have periodic character, e.g. seasonal fluctuations(epidemic spreading, population development), harmonic fluctuations (pattern recognition, image processing),etc. In simulation block the existing systems use separable process models which are presented as multiplication of spatialand temporal parts and are linearized. This significantly reduces the quality of spatial-time non-separable processes. The quality model building of chaotic spa-tial-time non-separable processwhich is processed by decisionsupport systemis necessary for getting of learning set. Itis really complicated especially if the random process is formed. The implementation ensemble of chaotic spatial-time non-separable process requires high costs what causes reduction of the system efficiency. Moreover, in many cases the implementation ensemble of spatial-time processes is impossible to get. In this workthemathematical model of a quasi-periodic spatial-time non-separable process has been developed. Based on it the formation method of this process has been developed and investigated. The epidemic spreading pro-cessed was presented as an example

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SUN, GUI-QUAN, ZHEN JIN, and LI LI. "EMERGENT TURING PATTERN IN EPIDEMIC SPREADING USING CELLULAR AUTOMATON." International Journal of Modern Physics B 25, no. 32 (2011): 4605–13. http://dx.doi.org/10.1142/s0217979211059401.

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Spatial epidemiology is the study of spatial variation in disease risk or incidence, including the spatial patterns of the population. Thus, an epidemic model with spatial structure based on the cellular automata method, which is different from deterministic and probabilistic CA models, is investigated. The construction of the cellular automata is based on the work of Bussemaker et al. [Phys. Rev. Lett.78, 5018–5021 (1997)]. For the appropriately chosen parameters, Turing pattern formation can emerge from a randomly perturbed uniform state, which is shown by numerical simulations. The results obtained confirm that diffusion can form the disease being in high density and the population being more stable.

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Hu, Chich-Ping. "The COVID-19 Epidemic Spreading Effects." Sustainability 14, no. 15 (2022): 9750. http://dx.doi.org/10.3390/su14159750.

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Cities are hotbeds for the outbreak and spread of infectious diseases. In the process of urban development, frequent interpersonal interactions are conducive to the spread of viruses. After the outbreak of COVID-19 in Wuhan, China in 2019, it quickly spread to Europe, North America, and Asia. This paper collects data on the number of COVID-19-infected cases per 100,000 people in Taiwan from 1 January to 4 May 2022 and the researcher uses the spatial regression model to analyze the spatial effect of the COVID-19 epidemic. The results of the study find that the hot zones of COVID-19-infected cases per 100,000 people are distributed in Taipei City, New Taipei City, Keelung City, Yilan County, and Taoyuan City, and the cold zones are distributed in Changhua County, Yunlin County, Chiayi County, Chiayi City, Tainan City, and Kaohsiung City. There are three types of urban development indicators: density, urbanization, and transportation system and means of transport, all of which can significantly affect the spatial spread of COVID-19. There is a negative correlation between the area of the “urban planning” district, the “road area” per person, the current status of the urban planning district population “density”, and the number of infected cases of “COVID19”. There is a negative correlation between “urban planning”, “road area”, “urbanization”, and “density” of neighboring cities and “COVID19” in a certain city.

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Lin, T. S., L. Kondic, U. Thiele, and L. J. Cummings. "Modelling spreading dynamics of nematic liquid crystals in three spatial dimensions." Journal of Fluid Mechanics 729 (July 16, 2013): 214–30. http://dx.doi.org/10.1017/jfm.2013.297.

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AbstractWe study spreading dynamics of nematic liquid crystal droplets within the framework of the long-wave approximation. A fourth-order nonlinear parabolic partial differential equation governing the free surface evolution is derived. The influence of elastic distortion energy and of imposed anchoring variations at the substrate are explored through linear stability analysis and scaling arguments, which yield useful insight and predictions for the behaviour of spreading droplets. This behaviour is captured by fully nonlinear time-dependent simulations of three-dimensional droplets spreading in the presence of anchoring variations that model simple defects in the nematic orientation at the substrate.

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Xu, Mingyue, Dingding Han, Kaidi Zhao, and Qingqing Yao. "Time-Varying Spatial Memory Model and Its Impact on Virus Spreading." Complexity 2021 (October 4, 2021): 1–15. http://dx.doi.org/10.1155/2021/6687168.

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The models of time-varying network have a profound impact on the study of virus spreading on the networks. On the basis of an activity-driven memory evolution model, a time-varying spatial memory model (TSM) is proposed. In the TSM model, the cumulative number of connections between nodes is recorded, and the spatiality of nodes is considered at the same time. Therefore, the active nodes tend to connect the nodes with high intimacy and close proximity. Then, the TSM model is applied to epidemic spreading, and the epidemic spreading on different models is compared. To verify the universality of the TSM model, this model is also applied to rumor spreading, and it is proved that it can also play a good inhibiting effect. We find that, in the TSM network, the introduction of spatiality and memory can slow down the propagation speed and narrow the propagation scope of disease or rumor, and memory is more important. We then explore the impact of different prevention and control methods on pandemic spreading to provide reference for COVID-19 management control and find when the activity of node is restricted, the spreading will be controlled. As floating population has been acknowledged as a key parameter that affects the situation of COVID-19 after work resumption, the factor of population mobility is introduced to calculate the interregional population interaction rate, and the time-varying interregional epidemic model is established. Finally, our results of infectious disease parameters based on daily cases are in good agreement with the real data, and the effectiveness of different control measures is evaluated.

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Zhou, Fei, and Jérôme Dyment. "Temporal and spatial variation of seafloor spreading at ultraslow spreading ridges: Contribution of marine magnetics." Earth and Planetary Science Letters 602 (January 2023): 117957. http://dx.doi.org/10.1016/j.epsl.2022.117957.

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Mahajan, Rahul B., and Gregory J. Hakim. "Spatial Growth of Perturbations in a Turbulent Baroclinic Jet." Journal of the Atmospheric Sciences 68, no. 11 (2011): 2731–41. http://dx.doi.org/10.1175/jas-d-11-038.1.

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Abstract The spatial spreading of infinitesimal disturbances superposed on a turbulent baroclinic jet is explored. This configuration is representative of analysis errors in an idealized midlatitude storm track and the insight gained may be helpful to understand the spreading of forecast errors in numerical weather prediction models. This problem is explored through numerical experiments of a turbulent baroclinic jet that is perturbed with spatially localized disturbances. Solutions from a quasigeostrophic model for the disturbance fields are compared with those for a passive tracer to determine whether disturbances propagate faster than the basic-state flow. Results show that the disturbance spreading rate is sensitive to the structure of the initial disturbance. Disturbances that are localized in potential vorticity (PV) have far-field winds that allow the disturbance to travel downstream faster than disturbances that are initially localized in geopotential, which have no far-field wind. Near the jet, the spread of the disturbance field is observed to exceed the tracer field for PV-localized disturbances, but not for the geopotential-localized disturbances. Spreading rates faster than the flow for geopotential-localized disturbances are found to occur only for disturbances located off the jet axis. These results are compared with those for zonal and time-independent jets to qualitatively assess the effects of transience and nonlinearity. This comparison suggests that the average properties of localized perturbations to the turbulent jet can be decomposed into a superposition of dynamics associated with a time-independent parallel flow plus a “diffusion” process.

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Hyun, J., P. Ercius, and DA Muller. "Beam Spreading and Spatial Resolution in Thick Organic Specimens." Microscopy and Microanalysis 12, S02 (2006): 1582–83. http://dx.doi.org/10.1017/s1431927606069200.

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Yasuda, Ryohei, and Hideji Murakoshi. "The mechanisms underlying the spatial spreading of signaling activity." Current Opinion in Neurobiology 21, no. 2 (2011): 313–21. http://dx.doi.org/10.1016/j.conb.2011.02.008.

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Hyun, Jerome K., Peter Ercius, and David A. Muller. "Beam spreading and spatial resolution in thick organic specimens." Ultramicroscopy 109, no. 1 (2008): 1–7. http://dx.doi.org/10.1016/j.ultramic.2008.07.003.

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Hui, Zi. "The Spatial SIS model of epidemic spreading on networks." Journal of Physics: Conference Series 1113 (November 2018): 012006. http://dx.doi.org/10.1088/1742-6596/1113/1/012006.

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Kawai, Reiichiro. "Anomalous spreading and misidentification of spatial random walk models." Applied Mathematical Modelling 40, no. 9-10 (2016): 5283–91. http://dx.doi.org/10.1016/j.apm.2015.12.028.

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White, R. L., and D. Van Compernolle. "Current Spreading and Speech-Processing Strategies for Cochlear Prostheses." Annals of Otology, Rhinology & Laryngology 96, no. 1_suppl (1987): 22–24. http://dx.doi.org/10.1177/00034894870960s109.

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It is well known that current spreading in the cochlea causes a blurring at the excitable neural tissue of spatial details when the electrode array is stimulated. This paper describes techniques for compensating for current spreading by computing the pseudoinverse of the spreading function and applying a stimulation pattern to the electrode array, which produces the desired current pattern at the neural tissue. Specific examples are given assuming several current spreading functions, and the limits of applicability of the techniques in the domain of severe current spreading are explored.

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Melnikova, Ekaterina. "Nonlinear dynamics of an epidemic spreading." Izvestiya VUZ. Applied Nonlinear Dynamics 6, no. 2 (1998): 110–16. http://dx.doi.org/10.18500/0869-6632-1998-6-2-110-116.

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А spatiotemporal model of an epidemic spreading in the human society is introduced. It is based on a reaction-diffusion equation with local and nonlocal modes of growth. The system behavior on the phase surface and limitation of the wave velocity are analysed. The immunization and density of population as the function of spatial coordinate are taken into account.

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Amar, Patrick. "Pandæsim: An Epidemic Spreading Stochastic Simulator." Biology 9, no. 9 (2020): 299. http://dx.doi.org/10.3390/biology9090299.

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Many methods have been used to model epidemic spreading. They include ordinary differential equation systems for globally homogeneous environments and partial differential equation systems to take into account spatial localisation and inhomogeneity. Stochastic differential equations systems have been used to model the inherent stochasticity of epidemic spreading processes. In our case study, we wanted to model the numbers of individuals in different states of the disease, and their locations in the country. Among the many existing methods we used our own variant of the well known Gillespie stochastic algorithm, along with the sub-volumes method to take into account the spatial localisation. Our algorithm allows us to easily switch from stochastic discrete simulation to continuous deterministic resolution using mean values. We applied our approaches on the study of the Covid-19 epidemic in France. The stochastic discrete version of Pandæsim showed very good correlations between the simulation results and the statistics gathered from hospitals, both on day by day and on global numbers, including the effects of the lockdown. Moreover, we have highlighted interesting differences in behaviour between the continuous and discrete methods that may arise in some particular conditions.

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Wollschläger, Daniel, Antonio M. Rodriguez, and Donald D. Hoffman. "Flank Transparency: The Effects of Gaps, Line Spacing, and Apparent Motion." Perception 31, no. 9 (2002): 1073–92. http://dx.doi.org/10.1068/p3410.

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We analyze the properties of a dynamic color-spreading display created by adding narrow colored flanks to rigidly moving black lines where these lines fall in the interior of a stationary virtual disk. This recently introduced display (Wollschläger et al, 2001 Perception30 1423–1426) induces the perception of a colored transparent disk bounded by strong illusory contours. It provides a link between the classical neon-color-spreading effect and edge-induced color spreading as discussed by Pinna et al (2001 Vision Research41 2669–2676). We performed three experiments to quantitatively study (i) the enhancing influence of apparent motion; (ii) the degrading effect of small spatial discontinuities (gaps) between lines and flanks; and (iii) the spatial extent of the color spreading. We interpret the results as due to varying degrees of objecthood of the dynamically specified disk: increased objecthood leads to increased surface visibility in both contour and color.

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Shukla, A. K., S. K. Behera, R. Tripathi, et al. "Evaluation of spatial spreading of phyto-available sulphur and micronutrients in cultivated coastal soils." PLOS ONE 16, no. 10 (2021): e0258166. http://dx.doi.org/10.1371/journal.pone.0258166.

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Understanding the spatial spreading patterns of plant-available sulphur (S) (AS) and plant-available micronutrients (available zinc (AZn), available iron (AFe), available copper (ACu), available manganese (AMn) and available boron (AB)) in soils, especially in coastal agricultural soils subjected to various natural and anthropogenic activities, is vital for sustainable crop production by adopting site-specific nutrient management (SSNM) strategies. We studied the spatial distribution patterns of AS, AZn, AFe, ACu, AMn, and AB in cultivated soils of coastal districts of India using geostatistical approaches. Altogether 39,097 soil samples from surface (0 to 15 cm depth) layers were gathered from farm lands of 68 coastal districts. The analysis of soil samples was carried out for soil pH, electrical conductivity (EC), soil organic carbon (SOC) and AS, AZn, AFe, ACu, AMn, and AB. Soil pH, EC and SOC varied from 3.70 to 9.90, 0.01 to 7.45 dS m-1 and 0.02 to 3.74%, respectively. The concentrations of AS, AZn, AFe, ACu, AMn, and AB varied widely in the study area with their corresponding mean values were 37.4±29.4, 1.50±1.53, 27.9±35.1, 2.14±1.74, 16.9±18.4 and 1.34±1.52 mg kg-1, respectively. The coefficient of variation values of analyzed soil parameters varied from 14.6 to 126%. The concentrations of AS, AZn, AFe, ACu, AMn, and AB were negatively and significantly correlated with soil pH and positively and significantly correlated with SOC. The geostatistical analysis indicated stable, Gaussian and exponential best-fit semivariogram models with moderate to strong spatial dependence for available nutrients. The generated spatial spreading maps revealed different distribution patterns for AS, AZn, AFe, ACu, AMn, and AB. There were variations in spatial spreading patterns of AS, AZn, AFe, ACu, AMn, and AB in east- and west-coastal area. About 62, 35, 12, 0.4, 23 and 45% of the study area had deficiency of AS, AZn, AFe, ACu, AMn, and AB, respectively. The spatial spreading maps will be highly useful for SSNM in the cultivated coastal soils of the country. This study could also be used as a base for assessing spatial spreading patterns of soil parameters in cultivated coastal areas of other parts of the world.

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Ibrahim, Najihah, Fadratul Hafinaz Hassan, Nor Muzlifah Mahyuddin, and Noorhazlinda Abd Ra. "Cellular Automaton based Fire Spreading Simulation in Closed Area: Clogging Region Detection." International Journal of Engineering & Technology 7, no. 4.44 (2018): 37. http://dx.doi.org/10.14419/ijet.v7i4.44.26859.

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Fire spreading is one of the visualization techniques used for re-enacting or envisions the fire incidents for conducting the post-incidents’ responses and analysing the incidents for post-mortem purposes. There are several current researches on the fire spreading incidents that involve the construction of fire spreading simulation which has focusing on the fire development, smoke control, the prediction of temperature distribution during the fire spreading, emergency response’s plans and post-fire damage assessment. However, there are more features need to be explored in the fire spreading simulation and also the pedestrians movement of the affected incident’s area for the future space design development, arrangement and structural improvement that are impactful towards human safety and also useful for the justification and prediction on the pedestrian survival rate during any panic situations. Hence, this research has focusing on the features of realistic scaling of the spatial layout and implementing the Cellular Automata (CA) approach for imitating the near-realistic pedestrian self-organizing movement and fire spreading characteristics at the microstructure level for designing the heat map of the affected area to show the clogging region in the spatial layout while constructing a reliable prediction on the pedestrian survival rate. This clogging region mapping will be useful for finding the existing issues that lead towards high casualties. Based on the experiments and observations, the heat map of the affected area showed the heavy congestions happened specifically near to the ingress/ egress points and narrow pathways that had affected the pedestrian flow rate and caused the 75% of the 352 pedestrians in the spatial layout to burn and die during the fire simulation by unintentionally taking an extra of 43.85 seconds more than the total fire spreading time (13.42 seconds) to evacuate from the closed area building.

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Zheng, Yanqiao, Xiaobing Zhao, Xiaoqi Zhang, Xinyue Ye, and Qiwen Dai. "Mining the Hidden Link Structure from Distribution Flows for a Spatial Social Network." Complexity 2019 (May 2, 2019): 1–17. http://dx.doi.org/10.1155/2019/6902027.

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This study aims at developing a non-(semi-)parametric method to extract the hidden network structure from the {0,1}-valued distribution flow data with missing observations on the links between nodes. Such an input data type widely exists in the studies of information propagation process, such as the rumor spreading through social media. In that case, a social network does exist as the media of the spreading process, but its link structure is completely unobservable; therefore, it is important to make inference of the structure (links) of the hidden network. Unlike the previous studies on this topic which only consider abstract networks, we believe that apart from the link structure, different social-economic features and different geographic locations of nodes can also play critical roles in shaping the spreading process, which has to be taken into account. To uncover the hidden link structure and its dependence on the external social-economic features of the node set, a multidimensional spatial social network model is constructed in this study with the spatial dimension large enough to account for all influential social-economic factors. Based on the spatial network, we propose a nonparametric mean-field equation to govern the rumor spreading process and apply the likelihood estimator to make inference of the unknown link structure from the observed rumor distribution flows. Our method turns out easily extendible to cover the class of block networks that are useful in most real applications. The method is tested through simulated data and demonstrated on a data set of rumor spreading on Twitter.

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Xu, Zhi Jing, Zheng Hu Zu, Tao Zheng, Qing Xu, Wen Dou Zhang, and Jin Jie Liu. "Air-Transportation Networks and the Spatial Spreading of Infectious Diseases." Applied Mechanics and Materials 513-517 (February 2014): 4020–24. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.4020.

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Many studies suggest that air-transportation networks contribute a lot to the spatiotemporal dynamics of infectious diseases. The mobility of individuals over the networks has greatly speeded up the spreading processes of the epidemics and pushed the population in non-epidemic areas into the risk of infection. To figure out the underlying interactions between the air-transportation networks and the transmission of the epidemics, we have (i) analyzed the air-routes and the statistical data on the passenger throughput of the civil aviation of China and (ii) carried out a computer simulation based on the assumption that a novel influenza outbreaks in Southeast Asia. The results show that the topology of the air-transportations networks has a typical structure of heterogeneities. We also find that the epidemics will soon strike China after the initial outbreaks and rapidly spread throughout the whole networks without air-travel restrictions even the reproductive number () is small.

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Zheng, Jie, Xiaofei Wu, Fangxin Fang, et al. "Numerical study of COVID-19 spatial–temporal spreading in London." Physics of Fluids 33, no. 4 (2021): 046605. http://dx.doi.org/10.1063/5.0048472.

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Kasai, Tetsuko. "Attention-spreading Based on Hierarchical Spatial Representations for Connected Objects." Journal of Cognitive Neuroscience 22, no. 1 (2010): 12–22. http://dx.doi.org/10.1162/jocn.2008.21158.

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Attention selects objects or groups as the most fundamental unit, and this may be achieved through a process in which attention automatically spreads throughout their entire region. Previously, we found that a lateralized potential relative to an attended hemifield at occipito-temporal electrode sites reflects attention-spreading in response to connected bilateral stimuli [Kasai, T., & Kondo, M. Electrophysiological correlates of attention-spreading in visual grouping. NeuroReport, 18, 93–98, 2007]. The present study examined the nature of object representations by manipulating the extent of grouping through connectedness, while controlling the symmetrical structure of bilateral stimuli. The electrophysiological results of two experiments consistently indicated that attention was guided twice in association with perceptual grouping in the early phase (N1, 150–200 msec poststimulus) and with the unity of an object in the later phase (N2pc, 310/330–390 msec). This suggests that there are two processes in object-based spatial selection, and these are discussed with regard to their cognitive mechanisms and object representations.

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Infascelli, Roberta, Raffaele Pelorosso, and Lorenzo Boccia. "Spatial assessment of animal manure spreading and groundwater nitrate pollution." Geospatial health 4, no. 1 (2009): 27. http://dx.doi.org/10.4081/gh.2009.208.

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Balcan, D., V. Colizza, B. Goncalves, H. Hu, J. J. Ramasco, and A. Vespignani. "Multiscale mobility networks and the spatial spreading of infectious diseases." Proceedings of the National Academy of Sciences 106, no. 51 (2009): 21484–89. http://dx.doi.org/10.1073/pnas.0906910106.

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Maidana, Norberto Aníbal, and Hyun Mo Yang. "Spatial spreading of West Nile Virus described by traveling waves." Journal of Theoretical Biology 258, no. 3 (2009): 403–17. http://dx.doi.org/10.1016/j.jtbi.2008.12.032.

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Li, Bingtuan, William F. Fagan, and Kimberly I. Meyer. "Success, failure, and spreading speeds for invasions on spatial gradients." Journal of Mathematical Biology 70, no. 1-2 (2014): 265–87. http://dx.doi.org/10.1007/s00285-014-0766-y.

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Wang, Lin, Xiang Li, Yi-Qing Zhang, Yan Zhang, and Kan Zhang. "Evolution of Scaling Emergence in Large-Scale Spatial Epidemic Spreading." PLoS ONE 6, no. 7 (2011): e21197. http://dx.doi.org/10.1371/journal.pone.0021197.

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Kita, Ashley, Yumiko Sakurai, David R. Myers, et al. "Platelet Sensing of Microenviornmental Geometry Guides Adhesion and Spreading: A Quantitative Study At the Single-Cell Level." Blood 118, no. 21 (2011): 2192. http://dx.doi.org/10.1182/blood.v118.21.2192.2192.

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Abstract Abstract 2192 To activate clot formation and maintain hemostasis, platelets adhere and spread onto sites of vascular injury. Although well-characterized biochemically, the role of physical and spatial cues in the microenvironment affect platelet adhesion and spreading remains unclear. No published data systemically characterizes and quantifies, at the single platelet level, how the microenvironmental geometry influences platelet spreading, and what the physical limitations and constraints are. In this study, we applied protein microcontact printing techniques to quantitatively investigate the extent of spatial regulation, if any, during platelet spreading. This concept of physical and microenvironmental control of platelet function is important to our understanding of platelet physiology and clot formation. Indeed, as fibrin formation takes place on the surface of activated platelets, investigation into the spatial regulation of platelet spreading will provide valuable insight into how clot formation itself is regulated and may have implications in bleeding and thrombotic disorders. To enable submicron resolution of single platelet adhesion and spreading, microfabricated features were created on silicon chips using deep UV photolithography. Micropatterns of Type I collagen-FITC or fibrinogen-Alexa 488 on glass coverslips were created using microcontact printing.1 Platelets were then incubated on the protein micropattern for 1 to 2 hours and monitored using confocal microscopy. We observed that after adhesion, platelets generally spread only onto micropatterned collagen or fibrinogen surfaces and follow the microenvironmental geometry with high fidelity (Figure 1A & 1B). That is, platelets “respect” and follow the micropattern protein boundaries. By using micropatterns of different thicknesses, we determined that platelets are able to spread onto and conform to protein micropatterns as thin as 1 mm with a maximum aspect ratio of 5.6. The ability of platelets to adjust their aspect ratio and maximize the area they spread on protein reflects an ability to sense interfaces and spread accordingly. Interestingly and somewhat paradoxically, platelets were also able to span and spread over non-patterned regions of up to 5 mm, a length consistent with that of maximally extended filopodia (Figure 1C). Time-lapse videomicroscopy further revealed that that platelet filopodia are sensitive to spatial cues and involved in probing the geometry of their microenvironment to guide spreading.Figure 1.Platelet sensing of the protein micropattern. (A) Spreading of platelets (red) stained with a fluorescent membrane dye is confined to collagen-FITC (green). (B) Platelets on thin protein stripes assume an aspect ratio that allows them to spread primarily on the protein-coated region. (C) At protein separations less than 5 mm, platelets span gaps in protein to spread on both surfaces. Scale bars = 10 mm.Figure 1. Platelet sensing of the protein micropattern. (A) Spreading of platelets (red) stained with a fluorescent membrane dye is confined to collagen-FITC (green). (B) Platelets on thin protein stripes assume an aspect ratio that allows them to spread primarily on the protein-coated region. (C) At protein separations less than 5 mm, platelets span gaps in protein to spread on both surfaces. Scale bars = 10 mm. Conclusions: We observed that the fidelity of platelet spreading decreases with feature sizes below 5 μm, likely due to the mass effect of the platelet itself. However, as platelets extend filopodia, they “bridge” and spread over non-protein patterned areas of up to 5 μm in distance. Taken together, our data quantifies the extent of spatial regulation during platelet spreading and has important implications in our understanding of clot formation. Biochemically, hemostasis is tightly controlled via multiple feedback mechanisms. Our observations suggest that this platelet adhesion and spreading is also highly spatially controlled, thereby potentially providing another mechanism by which hemostatic plug formation occurs only at sites of vascular injury. The capability of platelets to span <5 μm distances may imply that spatial guidance is less important for micron-scale, subclinical sites of vascular injury. Ongoing efforts focus on 1) investigating on how flow affects these phenomena and 2) how the microenvironmental geometry affects biological processes within the platelet such as actin and tubulin rearrangement, calcium signaling, and phosphatidyl serine exposure. Disclosures: No relevant conflicts of interest to declare.

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Sun, Shengtao, Jibing Gong, Jijun He, and Siwei Peng. "A spreading activation algorithm of spatial big data retrieval based on the spatial ontology model." Cluster Computing 18, no. 2 (2015): 563–75. http://dx.doi.org/10.1007/s10586-014-0417-5.

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Schweikert, Jochen, and Markus Höchstötter. "Epidemiological spreading of mortgage default." International Journal of Housing Markets and Analysis 12, no. 1 (2019): 74–93. http://dx.doi.org/10.1108/ijhma-05-2017-0047.

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Purpose This 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/approach The 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. Findings Based 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/value The key findings may be useful in understanding the dynamics of mortgage defaults and its spatial spreading.

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Matem, Rima, S. A. Aljunid, M. N. Junita, C. B. M. Rashidi, and Israa Shihab Ahmed. "Influence of Code Size Variation on the Performance of 2D Hybrid ZCC/MD in OCDMA System." MATEC Web of Conferences 150 (2018): 06018. http://dx.doi.org/10.1051/matecconf/201815006018.

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Several two dimensional OCDMA have been developed in order to overcome many problems in optical network, enhancing cardinality, suppress Multiple Access Interference (MAI) and mitigate Phase Induced Intensity Noise (PIIN). This paper propose a new 2D hybrid ZCC/MD code combining between 1D ZCC spectral encoding where M is its code length and 1D MD spatial spreading where N is its code length. The spatial spreading (N) code length offers a good cardinality so it represents the main effect to enhance the performance of the system compared to the spectral (M) code length according to the numerical results.

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O'Dea, Reuben, Jonathan J. Crofts, and Marcus Kaiser. "Spreading dynamics on spatially constrained complex brain networks." Journal of The Royal Society Interface 10, no. 81 (2013): 20130016. http://dx.doi.org/10.1098/rsif.2013.0016.

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The study of dynamical systems defined on complex networks provides a natural framework with which to investigate myriad features of neural dynamics and has been widely undertaken. Typically, however, networks employed in theoretical studies bear little relation to the spatial embedding or connectivity of the neural networks that they attempt to replicate. Here, we employ detailed neuroimaging data to define a network whose spatial embedding represents accurately the folded structure of the cortical surface of a rat brain and investigate the propagation of activity over this network under simple spreading and connectivity rules. By comparison with standard network models with the same coarse statistics, we show that the cortical geometry influences profoundly the speed of propagation of activation through the network. Our conclusions are of high relevance to the theoretical modelling of epileptic seizure events and indicate that such studies which omit physiological network structure risk simplifying the dynamics in a potentially significant way.

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Mufida, Ananda Azmi, and Mohamad Anis Fahmi. "Pemetaan Kasus Stunting di Kabupaten Lamongan Tahun 2023." Ficco Public Health Journal 01, no. 02 (2024): 42–48. https://doi.org/10.5281/zenodo.14561145.

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Background: Stunting is a condition in toddlers who experience growth failure due to chronic malnutrition that causes children to be shorter than their group. The results of the Indonesia Nutrition Status Survey (SSGI) in 2022 show that the prevalence of stunting in Lamongan Regency is 27.5%. and is still above the WHO standard of ≤20%. The purpose of this study is to find out if there is a spatial autocorrelation of stunting incidence in Lamongan Regency in 2023. Methods: The methods used are Moran Index, Moran's Scatterplot, Local Indicator of Spatial Association (LISA). Results: The value of the Moran Index of stunting incidence was 0.1851, indicating a positive spatial autocorrelation or forming a grouping pattern. Population Density with Stunting Incidence of -0.1966 indicates a negative spatial autocorrelation or random pattern of spreading. The availability of clean water with a stunting incidence is -0.3497 which indicates a negative spatial autocorrelation or a random spreading pattern. Conclusions: There is a positive Spatial Autocorrelation or forming a clustered pattern in stunting events in Lamongan Regency in 2023, There is a negative spatial autocorrelation of random distribution patterns between population density and stunting events in Lamongan Regency in 2023, There is a negative spatial autocorrelation of random distribution patterns between the availability of clean water and stunting events in Lamongan Regency in 2023.

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Xu, Feng, and Oliver E. Jensen. "Drop spreading with random viscosity." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 472, no. 2194 (2016): 20160270. http://dx.doi.org/10.1098/rspa.2016.0270.

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We examine theoretically the spreading of a viscous liquid drop over a thin film of uniform thickness, assuming the liquid’s viscosity is regulated by the concentration of a solute that is carried passively by the spreading flow. The solute is assumed to be initially heterogeneous, having a spatial distribution with prescribed statistical features. To examine how this variability influences the drop’s motion, we investigate spreading in a planar geometry using lubrication theory, combining numerical simulations with asymptotic analysis. We assume diffusion is sufficient to suppress solute concentration gradients across but not along the film. The solute field beneath the bulk of the drop is stretched by the spreading flow, such that the initial solute concentration immediately behind the drop’s effective contact lines has a long-lived influence on the spreading rate. Over long periods, solute swept up from the precursor film accumulates in a short region behind the contact line, allowing patches of elevated viscosity within the precursor film to hinder spreading. A low-order model provides explicit predictions of the variances in spreading rate and drop location, which are validated against simulations.

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Guan, Xiangyang, and Cynthia Chen. "General methodology for inferring failure-spreading dynamics in networks." Proceedings of the National Academy of Sciences 115, no. 35 (2018): E8125—E8134. http://dx.doi.org/10.1073/pnas.1722313115.

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A generic modeling framework to infer the failure-spreading process based on failure times of individual nodes is proposed and tested in four simulation studies: one for cascading failures in interdependent power and transportation networks, one for influenza epidemics, one benchmark test case for congestion cascade in a transportation network, and one benchmark test case for cascading power outages. Four general failure-spreading mechanisms—external, temporal, spatial, and functional—are quantified to capture what drives the spreading of failures. With the failure time of each node given, the proposed methodology demonstrates remarkable capability of inferring the underlying general failure-spreading mechanisms and accurately reconstructing the failure-spreading process in all four simulation studies. The analysis of the two benchmark test cases also reveals the robustness of the proposed methodology: It is shown that a failure-spreading process embedded by specific failure-spreading mechanisms such as flow redistribution can be captured with low uncertainty by our model. The proposed methodology thereby presents a promising channel for providing a generally applicable framework for modeling, understanding, and controlling failure spreading in a variety of systems.

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Kumar, Surender, Veer, and Ripudaman Singh. "GIS-Based Review for Monitoring the Spatial Distribution of Covid-19: A Case Study of Haryana." International Journal for Research in Applied Science and Engineering Technology 10, no. 2 (2022): 1093–99. http://dx.doi.org/10.22214/ijraset.2022.

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Abstract: Worldwide COVID-19 cases were noticed from its first variant to new variant very fast which is becoming threatening to human health, social function, production and supply of goods, and international relations. In Haryana, cases are increasing rapidly. GIS techniques contribute to controlling the epidemic by mapping of visualizing epidemic data, spatial visualization of protected and risk zones, spatial tracking of spreading, and route networking to fulfill demanded supply. These types of big spatial data can support taking decisions, formulating measurements, and effectiveness to control and prevent COVID-19. In the study area, total cases, daily reported cases, active cases, recovered cases, and fatalities were mapped. Based on daily reported cases, a high to less affected zone map was prepared by using the IDW technique. Results showed that the NCR region was highly affected and the rest of the part was less affected. Mapping of spreading epidemics on spatial distribution and variability of corona can provide the most useful insights to the authorities for decision making. Keywords: COVID-19, GIS, Spatial Distribution, IDW, Haryana

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Kumar, Surender, Vikas Veer, and Ripudaman Singh. "GIS-Based Review for Monitoring the Spatial Distribution of Covid-19: A Case Study of Haryana." International Journal for Research in Applied Science and Engineering Technology 10, no. 2 (2022): 1093–99. http://dx.doi.org/10.22214/ijraset.2022.40405.

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Murtadha, Amir, Noer Fadhly, and Muhammad Rusdi. "Urban Spatial Patterns in Banda Aceh City Using the Shannon's Entrophy Model." Aceh International Journal of Science and Technology 12, no. 2 (2023): 231–38. http://dx.doi.org/10.13170/aijst.12.2.30551.

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The rapid development of the city of Banda Aceh occurred in general in the suburbs. The impact is the occurrence of propagation which is a complex urban phenomenon and difficult to measure. Policy makers need a simple method to control and evaluate urban spread. This study integrates the Shannon's Entropy model with remote sensing and GIS to analyze spreading patterns in each sub-district in Banda Aceh City based on two aspects of distance, namely the distance to the city center and the road network to describe urban spreading patterns. The application of the Shannon's Entropy method in Banda Aceh City in 2010-2020 can be seen in the Relative Entropy Matrix which shows that the linear propagation pattern (Quadrant C) is more dominant in Banda Raya District, Baiturrahman District, Kuta Raja District, Kuta Alam District, Lueng District Bata, and the District of Syiah Kuala. Whereas the spreading pattern of Meuraxa District and Jaya Baru District is in quadrant B, namely the elongated (Radial) type of propagation pattern, but in 2020 Jaya Baru District there has been a change in the propagation pattern, namely the linear propagation pattern. In the Ulee Kareng sub-district, there was a pattern of propagation changes in 2020 which was in quadrant D, namely the leapfrog development pattern from the previous year, namely 2010 and 2015 in quadrant C with a linear propagation pattern. The spreading pattern of Banda Aceh City tends to lead to the East. This is mostly caused by the shape of the land which is very suitable to be used as a built-up area

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Cheng, Yingying, Liang’an Huo, Liang Ma, and Hongyuan Guo. "Dynamical behaviors and spatial diffusion in a psychologically realistic rumor spreading model." International Journal of Modern Physics C 31, no. 02 (2020): 2050034. http://dx.doi.org/10.1142/s0129183120500345.

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The spread of rumors has caused serious social and economic problems, especially during emergencies. Reducing the harm caused by rumors requires understanding the dynamical mechanism by which they propagate. To include the influence of time-dependent psychological factors, this paper proposes an improved rumor spreading model and derives mean-field equations describing the dynamics of rumor spreading. The psychological factors considered are the attenuation of individual interest, the cumulative effect of memory, and changes in sensory intensity with time. We also obtain the threshold condition of rumor spreading. Numerical simulations are used to verify our theoretical results. It is proved that the extremum of the cumulative effect of memory and the rumor attraction rate are positively correlated with the peak number of rumor spreaders, and negatively with the time required to reach the final rumor size. Time grows geometrically, while sensory intensity grows arithmetically. The initial approval rate of the memory accumulation effect and the stifling mechanism have little effect on the final rumor size. Finally, it is found that increasing the attenuation of interest coefficient reduces the time needed for the rumor to reach its final size.

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