Spatial Dynamics of Chickenpox Outbreaks in Rapidly Developing Regions:Implications for Global Public Health

Objective The occurrence of chickenpox in rapidly developing areas poses substantial seasonal risk to children.However,certain factors influencing local chickenpox outbreaks have not been studied.Here,we examined the relationship between spatial clustering,heterogeneity of chickenpox outbreaks,and socioeconomic factors in Southern China.Methods We assessed chickenpox outbreak data from Southern China between 2006 and 2021,comprising both relatively fast-growing parts and slower sub-regions,and provides a representative sample of many developing regions.We analyzed the spatial clustering attributes associated with chickenpox outbreaks using Moran’s I and local indicators of spatial association and quantified their socioeconomic determinants using Geodetector q statistics.Results There were significant spatial heterogeneity in the risk of chickenpox outbreaks,with strong correlations between chickenpox risk and various factors,particularly demographics and living environment.Furthermore,interactive effects among specific are factors,such as population density and per capita residential building area,percentage of households with toilets,percentage of rental housing,exhibited q statistics of 0.28,0.25,and 0.24,respectively.Conclusion This study provides valuable insights into the spatial dynamics of chickenpox outbreaks in rapidly developing regions,revealing the socioeconomic factors affecting disease transmission.These implications extend the formulation of effective public health strategies and interventions to prevent and control chickenpox outbreaks in similar global contexts.

The integration of climate change,spatial dynamics,and habitat fragmentation:A conceptual overview

A growing number of studies have looked at how climate change alters the effects of habitat fragmentation and degradation on both single and multiple species;some raise concern that biodiversity loss and its effects will be exacerbated.The published literature on spatial dynamics(such as dispersal and metapopulation dynamics),habitat fragmentation and climate change requires synthesis and a conceptual framework to simplify thinking.We propose a framework that integrates how climate change affects spatial population dynamics and the effects of habitat fragmentation in terms of:(i)habitat quality,quantity and distribution;(ii)habitat connectivity;and(iii)the dynamics of habitat itself.We use the framework to categorize existing autecological studies and investigate how each is affected by anthropogenic climate change.It is clear that a changing climate produces changes in the geographic distribution of climatic conditions,and the amount and quality of habitat.The most thorough published studies show how such changes impact metapopulation persistence,source-sink dynamics,changes in species’geographic range and community composition.Climate-related changes in movement behavior and quantity,quality and distribution of habitat have also produced empirical changes in habitat connectivity for some species.An underexplored area is how habitat dynamics that are driven by climatic processes will affect species that live in dynamic habitats.We end our discussion by suggesting ways to improve current attempts to integrate climate change,spatial population dynamics and habitat fragmentation effects,and suggest distinct areas of study that might provide opportunities for more fully integrative work.

Spatial dynamics of Chinese Muntjac related to past and future climate fluctuations

Climate fluctuations in the past and in the future are likely to result in population expansions,shifts,or the contraction of the ecological niche of many species,and potentially leading to the changes in their geographical distributions.Prediction of suitable habitats has been developed as a useful tool for the assessment of habitat suitability and resource conservation to protect wildlife.Here,we model the ancestral demographic history of the extant modern Chinese Muntjac Muntiacus reevesi populations using approximate Bayesian computation(ABC)and used the maximum entropy model to simulate the past and predict the future spatial dynamics of the species under climate oscillations.Our results indicated that the suitable habitats for the M.reevesi shifted to the Southeast and contracted during the Last Glacial Maximum,whereas they covered a broader more northern position in the Middle Holocene.The ABC analyses revealed that the modern M.reevesi populations diverged in the Middle Holocene coinciding with the significant contraction of the highly suitable habitat areas.Furthermore,our predictions suggest that the potentially suitable environment distribution for the species will expand under all future climate scenarios.These results indicated that the M.reevesi diverged in the recent time after the glacial period and simultaneously as its habitat's expanded in the Middle Holocene.Furthermore,the past and future climate fluctuation triggered the change of Chinese muntjac spatial distribution,which has great influence on the Chinese muntjac's population demographic history.

Geostatistical Analysis of Spatial Distribution and Dynamics of Dead Heart of Sugarcane Seedlings Caused by Borer

Dead heart of sugarcane is an important symptom caused by borer attack. In the present study, the spatial distribution and dynamics of dead heart of sugarcane in the field were investigated based on geostatistical analysis, and semivariograms were computed in four separate directions(0°, 45°, 90° and 135°) and fitted with various theoretical models to determine the best fitted one. The Ordinary Kriging was used to interpolate spatial data. The results revealed that the density of dead hearts of sugarcane increased in a single-peak pattern, and the degree of spatial aggregation and random variation both decreased with the increase in the density of dead heart. In addition, dead heart of sugarcane caused by borer exhibited spatial aggregation.With the increase in the density of dead heart, the degree of spatial aggregation decreased, while the correlation increased. Kriging interpolation indicated that the correlation between the spatial patches was weak in early seedling stage, and became strong in middle and late seedling stage.

Spatial spillover effects of official development assistance on environmental pressure in sub-Saharan African(SSA)countries

Impoverished sub-Saharan Africa(SSA)is under increasing environmental pressure from global environmental changes.It is now generally accepted in academic circles that economic development in SSA countries can cause environmental pressure in other countries.However,there is research gap on the impact of economic assistance on environmental pressure in SSA countries and whether economic assistance causes spatial spillovers of environ-mental pressure between SSA countries.To better understand the impact of economic assistance on environmental pressures in SSA,a dynamic spatial Dubin panel model was developed.It helped us explore the spatial spillover effects of economic assistance on environmental pressures in recipient countries based on the panel data from 34 SSA countries.The results show that economic assistance had a positive stimulating effect on environmen-tal pressures of recipient countries,which means that the degree of human disturbance to the environment has deepened.Due to the regional correlation effect,neighboring countries were saddled with environmental pres-sures from the target country.Moreover,environmental pressures have time inertia,which can easily produce a snowball effect.The decomposition of effects shows that the impact of economic assistance on environmental pressures is relatively minor.Environmental pressures have spillover effects,so to deal with diffuse risks,joint regional prevention and control policies should be developed.

A novel algorithm for evaluating cement azimuthal density based on perturbation theory in horizontal well

Cement density monitoring plays a vital role in evaluating the quality of cementing projects,which is of great significance to the development of oil and gas.However,the presence of inhomogeneous cement distribution and casing eccentricity in horizontal wells often complicates the accurate evaluation of cement azimuthal density.In this regard,this paper proposes an algorithm to calculate the cement azimuthal density in horizontal wells using a multi-detector gamma-ray detection system.The spatial dynamic response functions are simulated to obtain the influence of cement density on gamma-ray counts by the perturbation theory,and the contribution of cement density in six sectors to the gamma-ray recorded by different detectors is obtained by integrating the spatial dynamic response functions.Combined with the relationship between gamma-ray counts and cement density,a multi-parameter calculation equation system is established,and the regularized Newton iteration method is employed to invert casing eccentricity and cement azimuthal density.This approach ensures the stability of the inversion process while simultaneously achieving an accuracy of 0.05 g/cm^(3) for the cement azimuthal density.This accuracy level is ten times higher compared to density accuracy calculated using calibration equations.Overall,this algorithm enhances the accuracy of cement azimuthal density evaluation,provides valuable technical support for the monitoring of cement azimuthal density in the oil and gas industry.

Synergistic dance of digital economy and green finance on carbon emissions:Insights from China

China has recently implemented a dual-carbon strategy to combat climate change and other environmental issues and is committed to modernizing it sustainably.This paper supports these goals and explores how the digital economy and green finance intersect and impact carbon emissions.Using panel data from 30 Chinese provinces over the period 2011-2021,this paper finds that the digital economy and green finance can together reduce carbon emissions,and conducts several robustness tests supporting this conclusion.A heterogeneity analysis shows that these synergistic effects are more important in regions with low levels of social consumption Meanwhile,in the spatial dimension,the synergistic effect of the local digital economy and green finance adversely impacts the level of carbon emissions in surrounding areas.The findings of this paper provide insights for policymakers in guiding capital flow and implementing carbon-reduction policies while fostering the growth of China’s digital economy and environmental sustainability.

Unveiling the impact and mechanism of digital technology on agricultural economic resilience

Enhancing the economic resilience of agriculture is essential for promoting sustainable and high-quality agricultural development.The emergence of digital technology has created new opportunities in this field.However,existing research predominantly focuses on traditional agricultural factors and technologies.Therefore,the impact of digital technology on agricultural economic resilience within the broader context of the“production-operation-industry”system in agriculture has not been comprehensively explored.To bridge this gap,this study analyzes panel data from 30 Chinese provinces from 2011 to 2020.It employs the static Van Dorn’s law and a dynamic spatial panel model to examine how digital technology empowers agricultural resilience.The findings indicate a continuous strengthening of digital technology development in China,albeit with significant polarization and spatial imbalances.Moreover,the resilience of the agricultural economy undergoes notable fluctuations,initially narrowing and subsequently displaying an upward trend.Digital technology clearly plays a pivotal role in empowering resilience through agricultural scale operation,industrial transformation,and technological progress.Its impact,particularly on the promotion of resilience in the eastern region and non-grain-producing areas and on high-level agricultural economies,also shows regional and technological variations.

Dynamics of Soil Erosion in Xingguo County, China, Determined Using Remote Sensing and GIS

The spatial and temporal dynamics of soil erosion in Xingguo County, Jiangxi Province, China were studied using multi-period remote sensing images and GIS. The results indicated that the soil erosion status of the region has been improving, particularly since the 1980s, with the erosion rate showing an evident decline over the past 30 years. The improvement showed not only in the decline of eroded soil area, but also with the reduction in the extent of erosion. The extent of erosion mainly changed by one level, and the change primarily occurred with the severely or moderately eroded soil types. However, in general, soil erosion was still an overriding problem in the region with some areas becoming more serious, especially those with large quantities of granite.

The spatial-temporal dynamic characteristics of the marsh in the Sanjiang Plain

Using the methods of combining landscape ecology with GIS spatial analysis, this paper analyses the dynamics of the marsh landscape structure of the Sanjiang Plain in the past 20 years, furthermore, taking Fujin County, located in the north of the plain, as an example, analyzes the conversion between marsh and other land use types. It is shown that the marsh in the Sanjiang Plain decreased greatly in the past 20 years, but the trend has begun to reverse. The marsh area decreased by 51.33% from 1980 to 1996, whereas it decreased by 4.19% from 1996 to 2000. The fragmentation of the marsh increased; the number of the patches increased by 326 from 1986 to 1996, whereas it only increased by 18 patches from 1996 to 2000. It is obvious that the speed of patches number diminished and the marsh fragmentation decreased, which shows that the reclamation of the marsh converted from the fragmentation to the brim in a large area of the marsh. The reclaimed marsh has mainly converted to paddy field and dry land. Large-scale reclamation in the Sanjiang Plain influences its natural environment directly: the climate of the region turns from cold and wet to warm and dry, which makes the marsh both in the low-temperature northern part and in the deeply stagnant eastern part suitable for further agricultural development.

Effect of conformity on evolution of cooperation in a coordination game

Individual decision-making processes are not solely driven by self-interest maximization but are also influenced by the pressure to conform to the group.In primary games like the prisoner's dilemma,the presence of conformity pressure may facilitate the constructive development of cooperative behavior.In this study,we investigate how conformity influences the growth of cooperation in complicated coordination games.Our findings reveal that,even in the presence of stringent game rules,conformity can promote cooperation.In fact,a certain level of conformity pressure can even eliminate the“defection basin”of deer hunting games played on regular networks.Additionally,we demonstrate that the effect of conformity on cooperative behavior is contingent upon the degree of conformity pressure,with different levels of conformity pressure producing opposite effects.These findings provide novel insights into the promotion of cooperative evolution.For instance,if increasing the reward for cooperation has proven ineffective,manipulating the proportion of initial strategy choices may be a more promising approach.

F-structure model of overlying strata for dynamic disaster prevention in coal mine

The rupture and movement scope of overlying strata upon the longwall mining face increased sharply as the exploitation scale and degree growing recently,and the spatial structure formed by fractured strata became much more complex.The overlying strata above the working face and adjacent gobs would affect each other and move cooperatively because small pillar can hardly separate the connection of overlying strata between two workfaces,which leads to mining seismicity in the gob and induces rockburst disaster that named spatial structure instability rockburst in this paper.Based on the key stratum theory,the F-structure model was established to describe the overlying strata characteristic and rockburst mechanism of workface with one side of gob and the other side un-mined solid coal seam.The results show that F-structure in the gob will re-active and loss stability under the influence of neighboring mining,and fracture and shear slipping in the process of instability is the mechanism of the seismicity in the gob.The F-structure was divided into two categories that short-arm F and long-arm F structure based on the state of strata above the gob.We studied the underground pressure rules of different F-structure and instability mechanism,thus provide the guide for prevention and control of the F-structure spatial instability rockburst.The micro-seismic system is used for on-site monitoring and researching the distribution rules of seismic events,the results confrmed the existence and correct of F-spatial structure.At last specialized methods for prevention seismicity and rockburst induced by F-structure instability are proposed and applied in Huating Coal Mine.

A Nonparametric Approach to Foreground Detection in Dynamic Backgrounds

Foreground detection is a fundamental step in visual surveillance.However,accurate foreground detection is still a challenging task especially in dynamic backgrounds.In this paper,we present a nonparametric approach to foreground detection in dynamic backgrounds.It uses a history of recently pixel values to estimate background model.Besides,the adaptive threshold and spatial coherence are introduced to enhance robustness against false detections.Experimental results indicate that our approach achieves better performance in dynamic backgrounds compared with several approaches.

Obtaining vehicle parameters from bridge dynamic response:a combined semi-analytical and particle filtering approach

Dynamic load imposed on the bridge by mov- ing vehicle depends on several bridge-vehicle parameters with various uncertainties. In the present paper, particle filter technique based on conditional probability has been used to identify vehicle mass, suspension stiffness, and damping including tyre parameters from simulated bridge accelerations at different locations. A closed-form expres- sion is derived to generate independent response samples for the idealized bridge-vehicle coupled system consider- ing spatially non-homogeneous pavement unevenness. Thereafter, it is interfaced with the iterative process of particle filtering algorithm. The generated response sam- ples are contaminated by adding artificial noise in order to reflect field condition. The mean acceleration time history is utilized in particle filtering technique. The vehicle- imposed dynamic load is reconstructed with the identified parameters and compared with the simulated results. The present identification technique is examined in the presence of different levels of artificial noise with bridge response simulated at different locations. The effect of vehicle velocity, bridge surface roughness, and choice of prior probability density parameters on the efficiency of the method is discussed.

Industrial carbon emissions and influencing factors in the Yangtze River Delta urban agglomeration

This paper calculates the industrial carbon emissions of the Yangtze River Delta urban agglomeration over the period 2006-2013. An empirical analysis is conducted to find out the influencing factors of industrial carbon emissions of the Yangtze River Delta urban agglomeration, using a spatial Durbin panel model. The results show that cities with larger industrial carbon emissions often enjoy low annual growth rates, while the cities with smaller ones enjoy higher annual growth rate; There exists a comparatively strong positive correlation in space in per capita carbon emission; urbanization, and total population. GDP per capita and international trade are the main influencing factors of industrial carbon emissions; There are spatial spillover effects on international trade and urbanization of neighboring cities, which have a significant impact on local industrial carbon emissions.

Spatial hints of forest ecotone indicating forest succession, a case of larch forests in Baihuashan Reserve, north China

In cold or alpine areas of northern China,birch forests and larch forests are the two primary forest types.These forests are also characteristic of a south branch of boreal forests in Asia.Some ecologists argue that larch forests can replace birch forests,but this still remains a question due to fragmentary or short observations.The ecotone between a larch forest patch and a birch forest patch is the arena in which the two species interplay and compete with each other,and studies of these areas are meaningful to understanding forest succession.In the alpine area of the Baihuashan Reserve,northern China,we sampled a larch-birch forest ecotone with eight plots in four transects and then analyzed population structures of larches and birches.The results show that the edges of the larch forest patch are composed of many larch saplings or young trees,but the edges of the birch forest patch are mainly composed of old birches.Across the ecotone,the larches,on average,are taller than the birches.These facts suggest that larch saplings can permeate into birch forest patches,probably by seed dispersal,germination,success-ful competition and growth,but birch saplings cannot permeate into larch forest patches.Therefore,on the ecotone,larch forest patches can steadily expand by unceasing permeation into birch forest patches,whereas birch forest patches progressively recede due to ultimate death of the old and poor recruitment of the young.Larch forest patches replace birch forest patches in a stepwise manner,causing succession from birch forests to larch forests.This study not only confirms that larch forests can naturally replace birch forests,but also introduces a simple and reliable method,employing spatial hints,to study forest succession.Additionally,the findings are of benefit to cultivation or development of larch forests in cold or alpine areas of the North Temperate Zone,which can be a huge carbon sink.

A spatial epidemic model with a moving boundary

We present a new mathematical model to investigate the spatial spread of an infectious disease.The model consists of a nonlinear PDE system with an unknown velocity field,defined on an epidemic domain that changes with time.The moving boundary of the domain represents the wavefront of the epidemic.We conduct an equilibrium analysis to the simplified models represented by ODE systems.We also perform a numerical study on the original PDE system for a range of scenarios,including one under a realistic epidemic setting.

Dynamic Shortest Path Monitoring in Spatial Networks

With the increasing availability of real-time traffic information, dynamic spatial networks are pervasive nowa- days and path planning in dynamic spatial networks becomes an important issue. In this light, we propose and investigate a novel problem of dynamically monitoring shortest paths in spatial networks （DSPM query）. When a traveler aims to a des- tination, his/her shortest path to the destination may change due to two reasons： 1） the travel costs of some edges have been updated and 2） the traveler deviates from the pre-planned path. Our target is to accelerate the shortest path computing in dynamic spatial networks, and we believe that this study may be useful in many mobile applications, such as route planning and recommendation, car navigation and tracking, and location-based services in general. This problem is challenging due to two reasons： 1） how to maintain and reuse the existing computation results to accelerate the following computations, and 2） how to prune the search space effectively. To overcome these challenges, filter-and-refinement paradigm is adopted. We maintain an expansion tree and define a pair of upper and lower bounds to prune the search space. A series of optimization techniques are developed to accelerate the shortest path computing. The performance of the developed methods is studied in extensive experiments based on real spatial data.

Regional inequality, spatial spillover effects, and the factors influencing city-level energy-related carbon emissions in China

Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.

Large-diameter trees and deadwood correspond with belowground ectomycorrhizal fungal richness

Background: Large-diameter trees have an outsized influence on aboveground forest dynamics, composition, and structure. Although their influence on aboveground processes is well studied, their role in shaping belowground fungal communities is largely unknown. We sought to test if (i) fungal community spatial structure matched aboveground forest structure;(ii) fungal functional guilds exhibited differential associations to aboveground trees, snags, and deadwood;and (iii) that large-diameter trees and snags have a larger influence on fungal community richness than smaller-diameter trees. We used MiSeq sequencing of fungal communities collected from soils in a spatially intensive survey in a portion of Cedar Breaks National Monument, Utah, USA. We used random forest models to explore the spatial structure of fungal communities as they relate to explicitly mapped trees and deadwood distributed across 1.15 ha of a 15.32-ha mapped subalpine forest. Results: We found 6,177 fungal amplicon sequence variants across 117 sequenced samples. Tree diameter, dead-wood presence, and tree species identity explained more than twice as much variation (38.7% vs. 10.4%) for ectomy-corrhizal composition and diversity than for the total or saprotrophic fungal communities. Species identity and dis-tance to the nearest large-diameter tree (≥ 40.2 cm) were better predictors of fungal richness than were the identity and distance to the nearest tree. Soil nutrients, topography, and tree species differentially influenced the composition and diversity of each fungal guild. Locally rare tree species had an outsized influence on fungal community richness. Conclusions: These results highlight that fungal guilds are differentially associated with the location, size, and species of aboveground trees. Large-diameter trees are implicated as drivers of belowground fungal diversity, particularly for ectomycorrhizal fungi.