129,495 research outputs found
Spatial Patterns Associating Low Birth Weight with Environmental and Behavioral Factors
Low birth weight (LBW) is a significant public health problem in the world. It was estimated globally by the World Health Organization (WHO) that prevalence of LBW was 15% of all births. In Murung Raya district LBW cases remain high. This paper aimed to identify and discuss the relationship between environmental risk factors with LBW in Murung Raya.A spatial analysis was conducted with 150 women as the total participantswho were recruited through the incidence data in 2013-2014. The questionnaires, medical records, and geographic data were measured by Stata software, ArcGis, SatScan, and Geoda. The study results indicated there was significant correlation between health behavior and environmental variables with the strength of external neighborhood effect across LBW risk factors. More intense clustering of high values (hot spots) was found through the spatial analysis showing that most of the cases were located near the defined buffer zone. This research demonstrates that the spatial pattern analysis provided greater statistical power to detect an effect that was not apparent in the previous epidemiology studies
Spatial Patterns of Headquarters
This study of the spatial concentration of the headquarters of exchange-listed companies suggests that the relevancy of the "efficiency parameter" of agglomeration theory still holds in explaining the location of headquarters, especially when the production function is reinterpreted as a productivity function. The sample of 5189 headquarters exceeds previous studies of Fortune 500 firms. Across industries, a high degree of clustering is found: 40% of the nation's headquarters were found in twenty counties. Cluster analysis suggests grouping patterns for headquarters; discriminant analysis confirms the uniqueness of these spatial clustering patterns across 229 urban counties. For certain industries, the clustering occurs within small areas. The headquarters of these spatially-correlated groups of firms money and media, gas and electric, business services, and machining technology were mapped at the county and zipcode level for counties within major metropolitan areas. The spatial density patterns take on traditional urban forms: core, ring and wedge.
Spatial patterns of competing random walkers
We review recent results obtained from simple individual-based models of
biological competition in which birth and death rates of an organism depend on
the presence of other competing organisms close to it. In addition the
individuals perform random walks of different types (Gaussian diffusion and
L\'{e}vy flights). We focus on how competition and random motions affect each
other, from which spatial instabilities and extinctions arise. Under suitable
conditions, competitive interactions lead to clustering of individuals and
periodic pattern formation. Random motion has a homogenizing effect and then
delays this clustering instability. When individuals from species differing in
their random walk characteristics are allowed to compete together, the ones
with a tendency to form narrower clusters get a competitive advantage over the
others. Mean-field deterministic equations are analyzed and compared with the
outcome of the individual-based simulations.Comment: 38 pages, including 6 figure
Formation of regular spatial patterns in ratio-dependent predator-prey model driven by spatial colored-noise
Results are reported concerning the formation of spatial patterns in the
two-species ratio-dependent predator-prey model driven by spatial
colored-noise. The results show that there is a critical value with respect to
the intensity of spatial noise for this system when the parameters are in the
Turing space, above which the regular spatial patterns appear in two
dimensions, but under which there are not regular spatial patterns produced. In
particular, we investigate in two-dimensional space the formation of regular
spatial patterns with the spatial noise added in the side and the center of the
simulation domain, respectively.Comment: 4 pages and 3 figure
Spatial Patterns of Pulmonary Tuberculosis Analysing Rainfall Patterns in Visual Formation
Management sustainability related tuberculosis patient treatment was limited. Tuberculosis analysis was still in the form of data aggregation. This is cross sectional survey using geographical information system, analyzed by descriptive methods, the sample included 162 pulmonary tuberrculosis patient in 2014. The variables were pulmonary tuberrculosis patients and isohyet data. Mycrobacterium tuberculosis will be survive and multiply during rainy season. Rainfall data was an increasing pattern from first quarter to fourth quarter in 2014, however data in 2011, 2012 and 2013, which each quarter was largely experiencing sustained increase and decline. Pulmonary tuberrculosis patients were most prevalent in 2014. It was increase in the rainy season. The most high rainfall intensity (> 2400 mm) in east of Lendah and western of Kokap areas, while the lowest intensity (< 1500 mm) in east of Nanggulan, in the south of Panjatan and Galur areas. It was mostly located in areas with high rainfall intensity (2200 - 2400 mm) which spreads and stretches in Sentolo, Wates, and Panjatan areas. Pulmonary tuberrculosis occurred over the rainy season. Spatial pattern distribution of pulmonary tuberrculosis patients in high rainfall intensity spreads and stretches from east to west areas. Active case monitoring program should be performed by tuberculosis program that concerned in areas of high rainfall intensity
Complex Networks Unveiling Spatial Patterns in Turbulence
Numerical and experimental turbulence simulations are nowadays reaching the
size of the so-called big data, thus requiring refined investigative tools for
appropriate statistical analyses and data mining. We present a new approach
based on the complex network theory, offering a powerful framework to explore
complex systems with a huge number of interacting elements. Although interest
on complex networks has been increasing in the last years, few recent studies
have been applied to turbulence. We propose an investigation starting from a
two-point correlation for the kinetic energy of a forced isotropic field
numerically solved. Among all the metrics analyzed, the degree centrality is
the most significant, suggesting the formation of spatial patterns which
coherently move with similar vorticity over the large eddy turnover time scale.
Pattern size can be quantified through a newly-introduced parameter (i.e.,
average physical distance) and varies from small to intermediate scales. The
network analysis allows a systematic identification of different spatial
regions, providing new insights into the spatial characterization of turbulent
flows. Based on present findings, the application to highly inhomogeneous flows
seems promising and deserves additional future investigation.Comment: 12 pages, 7 figures, 3 table
Spatial patterns of desynchronization bursts in networks
We adapt a previous model and analysis method (the {\it master stability
function}), extensively used for studying the stability of the synchronous
state of networks of identical chaotic oscillators, to the case of oscillators
that are similar but not exactly identical. We find that bubbling induced
desynchronization bursts occur for some parameter values. These bursts have
spatial patterns, which can be predicted from the network connectivity matrix
and the unstable periodic orbits embedded in the attractor. We test the
analysis of bursts by comparison with numerical experiments. In the case that
no bursting occurs, we discuss the deviations from the exactly synchronous
state caused by the mismatch between oscillators
Spatial Patterns Induced Purely by Dichotomous Disorder
We study conditions under which spatially extended systems with coupling a la
Swift-Hohenberg exhibit spatial patterns induced purely by the presence of
quenched dichotomous disorder. Complementing the theoretical results based on a
generalized mean-field approximation, we also present numerical simulations of
particular dynamical systems that exhibit the proposed phenomenology
Spatial patterns in intermunicipal Danish commuting
Intermunicipal variations in in-commuting are mainly explained by variations in number of workplaces, urbanization degree and wealth, whereas variations in out- commuting are mainly determined by variations in workforce size, number of workplaces, living patterns and unemployment. This is quite satisfactory according to existing theory. However, of these explanatory factors only the number of workplaces influences the net in-commuting. But by using spatial lag structures it is shown that unemployment in neighbourhood municipalities influences net in-commuting. Finally, evidence of impact of local spatial industrial patterns on the commuting behaviour is provided, and the nature and reasons for these spatial patterns are discussed.
Bistability and regular spatial patterns in arid ecosystems.
A variety of patterns observed in ecosystems can be explained by resource–concentration mechanisms. A resource–concentration mechanism occurs when organisms increase the lateral flow of a resource toward them, leading to a local concentration of this resource and to its depletion from areas farther away. In resource–concentration systems, it has been proposed that certain spatial patterns could indicate proximity to discontinuous transitions where an ecosystem abruptly shifts from one stable state to another. Here, we test this hypothesis using a model of vegetation dynamics in arid ecosystems. In this model, a resource– concentration mechanism drives a positive feedback between vegetation and soil water availability. We derived the conditions leading to bistability and pattern formation. Our analysis revealed that bistability and regular pattern formation are linked in our model. This means that, when regular vegetation patterns occur, they indicate that the system is along a discontinuous transition to desertification. Yet, in real systems, only observing regular vegetation patterns without identifying the pattern-driving mechanism might not be enough to conclude that an ecosystem is along a discontinuous transition because similar patterns can emerge from different ecological mechanisms
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