Identifying power outage hotspots to support risk management planning.

Secure and reliable power systems are vital for modern societies and economies. While there is a focus in the literature on predicting power outages caused by severe weather events, relatively little literature exists on identifying hot spots, locations where outages occur repeatedly and at a higher rate than expected. Reliably identifying hotspots can provide critical input for risk management efforts by power utilities, helping them to focus scarce resources on the most problematic portions of their system. In this article, we show how existing work on Moran's I spatial statistic can be adapted to identify power outage hotspots based on the types and quantities of data available to utilities in practice. The local Moran's I statistic was calculated on a grid cell level and a set of criteria were used to filter out which grid cells are considered hotspots. The hotspot identification approach utilized in this article is an easy method for utilities to use in practice, and it provides the type of information needed to directly support utility decisions about prioritizing areas of a power system to inspect and potentially reinforce.

GIS-based assessment of spatial and temporal disparities of urban health index in Shenzhen, China.

Purpose: To explore the inter-regional health index at the city level to contribute to the reduction of health inequalities. Methods: Employed the health determinant model to select indicators for the urban health index of Shenzhen City. Utilized principal component analysis, the weights of these indicators are determined to construct the said health index. Subsequently, the global Moran's index and local Moran's index are utilized to investigate the geographical spatial distribution of the urban health index across various administrative districts within Shenzhen. Results: The level of urban health index in Shenzhen exhibits spatial clustering and demonstrates a positive spatial correlation (2017, Moran's I = 0.237; 2019, Moran's I = 0.226; 2021, Moran's I = 0.217). However, it is noted that this clustering displays a relatively low probability (90% confidence interval). Over the period from 2017 to 2019, this spatial clustering gradually diminishes, suggesting a narrowing of health inequality within economically developed urban areas. Conclusion: Our study reveals the urban health index in a relatively high-income (Shenzhen) in a developing country. Certain spatially correlated areas in Shenzhen present opportunities for the government to address health disparities through regional connectivity.

Exploring the temporal-spatial characteristics and determinants of high-quality development of city clusters in China.

The complexity, severity, and uncertainty of the international situation have prompted the development of city clusters to focus more on resilience and the building of infrastructures and safeguards. Chinese-style modernization proposes a new realization path for the high-quality development (HQD) of city clusters, based on which an evaluation system for HQD indicators of city clusters is constructed. We also measured the HQD levels of 19 city clusters from 2011 to 2021 and analyzed their spatial differentiation characteristics, agglomeration evolution characteristics, and influencing factors by using kernel density, standard deviation ellipse, Moran's index, geographic detector, and geographically weighted regression. The study revealed that (1) the overall level of HQD of China's city clusters shows a trend of continuous growth, and there is obvious polarization in the high quality of city clusters in different regions. (2) The spatial distribution of HQD in city clusters decreased in the "East, Center and West" direction, but the spatial patterns of "Southeast highlighting" and "Northwest rising" became more obvious. (3) The HQD of city clusters shows obvious spatial agglomeration characteristics and overall presents a spatial pattern of "hot in the east and cold in the west", with the scope of the cold spot area gradually shrinking, and the hot spot area tends to spread outward, with mature city clusters at the core. (4) The influencing factors of HQD in Chinese city clusters are diverse, with financial levels, digital economics, human capital and green innovations having decreasing influence on HQD in city clusters but showing an obvious two-factor enhancement trend, with financial levels being able to effectively stimulate the driving potential of other factors. Financial levels can effectively stimulate the driving potential of other factors. (5) The coefficients of the driving factors affecting the HQD of city clusters vary significantly spatially, with human capital, financial levels and green innovations showing a north‒south hierarchical banded distribution of "high in the south and low in the north", and digital economy shows an east-west hierarchical belt distribution of "high west and low east". Based on the above conclusions, the realization path of accelerating the HQD of China's city clusters is proposed by optimizing the functional division of labor of the city clusters, giving full play to the comparative advantages of the hinterland city clusters, and relying on the high level of the city clusters for opening up.

Urbanization alters the relative importance of local and landscape factors affecting plant communities in the Tokyo megacity.

Plant communities are impacted by local factors (related to environmental filtering) and landscape factors (related to dispersal limitation). While many studies have shown that the relative importance of these factors in understanding plant community dynamics due to urbanization, little is known about how they are altered by urbanization-a significant threat to biodiversity. This study evaluates the relative importance of local environmental (local factors), landscape, and spatial (landscape factors) variables that influence plant communities in 34 urban green spaces comprising two different habitats (forests and grasslands) along the urban-rural gradients in the Tokyo megacity, Japan. To continuously assess the relative importance of each factor along the urban-rural gradients, we extracted 1000 landscapes within a certain range that contained several sites. Subsequently, the relative importance of each factor and urbanization rate (proportion of artificial built-up area) were estimated for each landscape. Our study found that the relative importance of both local and landscape factors decreased, while that of local factor for native species in forest habitats and that of landscape factors for native species in grassland habitats increased. Collectively, these findings suggest that city size and habitat characteristics must be considered when predicting changes in plant communities caused by urbanization.

Unveiling spatial patterns of West Nile virus emergence in northern Greece, 2010-2023.

The Region of Central Macedonia (RCM) in Northern Greece recorded the highest number of human West Nile virus (WNV) infections in Greece, despite considerable local mosquito control actions. We examined spatial patterns and associations of mosquito levels, infected mosquito levels, and WNV human cases (WNVhc) across the municipalities of this region over the period 2010-2023 and linked it with climatic characteristics. We combined novel entomological and available epidemiological and climate data for the RCM, aggregated at the municipality level and used Local and Global Moran's I index to assess spatial associations of mosquito levels, infected mosquito levels, and WNVhc. We identified areas with strong interdependencies between adjacent municipalities in the Western part of the region. Furthermore, we employed a Generalized Linear Mixed Model to first, identify the factors driving the observed levels of mosquitoes, infected mosquitoes and WNVhc and second, estimate the influence of climatic features on the observed levels. This modeling approach indicates a strong dependence of the mosquito levels on the temperatures in winter and spring and the total precipitation in early spring, while virus circulation relies on the temperatures of late spring and summer. Our findings highlight the significant influence of climatic factors on mosquito populations (∼60 % explained variance) and the incidence of WNV human cases (∼40 % explained variance), while the unexplained ∼40 % of the variance suggests that targeted interventions and enhanced surveillance in identified hot-spots can enhance public health response.

The spatial-temporal distribution of hepatitis B virus infection in China,2006-2018.

OBJECTIVES: Hepatitis B is a liver disease caused by Hepatitis B virus (HBV) infection and is highly prevalent in China. To better understand the epidemiological characteristics of hepatitis B in China and develop effective disease control strategies, we employed temporal and spatial statistical methods. METHODS: We obtained HBV incidence data from the Public Health Science Data Center of the Chinese Center for Disease Control and Prevention for the years 2006 to 2018. Using Geographic Information System (GIS) and SaTScan scanning technology, we conducted spatial autocorrelation analysis and spatiotemporal scan analysis to create a map and visualize the distribution of hepatitis B incidence. RESULTS: While hepatitis B incidence rebounded in 2011 and 2017, the overall incidence in China decreased.In the trend analysis by item, the incidence varies from high to low. The global spatial autocorrelation analysis revealed a clustered distribution, and the Moran index analysis of spatial autocorrelation within local regions identified five provinces as H-H clusters (hot spots), while one province was an L-L cluster (cold spot). Spatial scan analysis identified 11 significant spatial clusters. CONCLUSIONS: We found significant clustering in the spatial distribution of hepatitis B incidence and positive spatial correlation of hepatitis B incidence in China. We also identified high-risk times and regional clusters of hepatitis B incidence.

Characterization of the Spatial Distribution of the Pepper Weevil, Anthonomus eugenii Cano (Col.: Curculionidae), in Pepper Fields in South Florida.

The pepper weevil, Anthonomus eugenii Cano, is an economically important pest of cultivated peppers (Capsicum annuum) in tropical and subtropical regions of the world. This study aimed to ascertain the spatial distribution of pepper weevil infestation across various fields in Miami Dade County, South Florida. The spatio-temporal dynamics of pepper weevil were evaluated using 144 sample points within each of seven pepper fields. The data were analyzed using three different geospatial techniques, spatial analysis by distance indices (SADIE), Moran's I, and Geary's C, to determine the spatial distribution of pepper weevil. The SADIE analysis revealed a significant aggregation distribution in 18 out of 30 sampling dates across all fields. The results from Geary's C and Moran's I indices indicated a positive spatial autocorrelation (spatial clustering/aggregation) of pepper weevil regardless of field or pepper types. Overall, the findings from this study depict an aggregated spatial distribution pattern of pepper weevil populations, characterized by a tendency for aggregation that transitions to a more uniform distribution as the season progresses.

Tail-dependence of masting synchrony results in continent-wide seed scarcity.

Spatial synchrony may be tail-dependent, meaning it is stronger for peaks rather than troughs, or vice versa. High interannual variation in seed production in perennial plants, called masting, can be synchronized at subcontinental scales, triggering extensive resource pulses or famines. We used data from 99 populations of European beech (Fagus sylvatica) to examine whether masting synchrony differs between mast peaks and years of seed scarcity. Our results revealed that seed scarcity occurs simultaneously across the majority of the species range, extending to populations separated by distances up to 1800 km. Mast peaks were spatially synchronized at distances up to 1000 km and synchrony was geographically concentrated in northeastern Europe. Extensive synchrony in the masting lower tail means that famines caused by beech seed scarcity are amplified by their extensive spatial synchrony, with diverse consequences for food web functioning and climate change biology.

Investigating the impact of urban growth on land use using spatial autocorrelation methods in Konya/Türkiye.

Land use land cover (LULC) change, global environmental change, and sustainable change are frequently discussed topics in research at the moment. It is important to determine the historical LULC change process for effective environmental planning and the most appropriate use of land resources. This study analysed the spatial autocorrelation of the land use structure in Konya between 1990 and 2018. For this, Global and Local Moran's I indices based on land use data from 122 neighbourhoods and hot spot analysis (Getis-Ord Gi*) methods were applied to measure the spatial correlation of changes and to determine statistically significant hot and cold spatial clusters. According to the research results, the growth of urban areas has largely destroyed the most productive agricultural lands in the region. This change showed high spatial clustering both on an area and a proportional basis in the northern and southern parts of the city. On the other hand, the growth in the industrial area suppressed the pasture areas the most in the north-eastern region of the city, and this region showed high spatial clustering on both spatial and proportional scales.

Muller's ratchet in a near-critical regime: Tournament versus fitness proportional selection.

Muller's ratchet, in its prototype version, models a haploid, asexual population whose size N is constant over the generations. Slightly deleterious mutations are acquired along the lineages at a constant rate, and individuals carrying less mutations have a selective advantage. The classical variant considers fitness proportional selection, but other fitness schemes are conceivable as well. Inspired by the work of Etheridge et al. (2009) we propose a parameter scaling which fits well to the "near-critical" regime that was in the focus of Etheridge et al. (2009) (and in which the mutation-selection ratio diverges logarithmically as N→∞). Using a Moran model, we investigate the"rule of thumb" given in Etheridge et al. (2009) for the click rate of the "classical ratchet" by putting it into the context of new results on the long-time evolution of the size of the best class of the ratchet with (binary) tournament selection. This variant of Muller's ratchet was introduced in González Casanova et al. (2023), and was analysed there in a subcritical parameter regime. Other than that of the classical ratchet, the size of the best class of the tournament ratchet follows an autonomous dynamics up to the time of its extinction. It turns out that, under a suitable correspondence of the model parameters, this dynamics coincides with the so called Poisson profile approximation of the dynamics of the best class of the classical ratchet.

The Impact of Sunshine Duration on Myopia in Central China: Insights from Populational and Spatial Analysis in Hubei.

Purpose: This study aimed to analyze myopia distribution in Hubei and the impact of regional Sunshine Duration on myopia in children and adolescents. Patients and Methods: The Cross-sectional study included students (kindergarten to grade 12) through multistage cluster stratified sampling in 17 cities (103 areas) of Hubei, China, who underwent ophthalmic examinations from September 2021 to November 2021. The association of sunshine duration with the prevalence and distribution of myopia was analyzed. Using Moran's index to quantify the distribution relationship, a spatial analysis was constructed. Results: A total of 435,996 students (53.33% male; mean age, 12.16±3.74 years) were included in the study. A negative association was identified between myopia prevalence and sunshine duration in the region, especially in population of primary students (r=-0.316, p<0.001). Each 1-unit increment in the sunshine duration was associated with a decreased risk of myopia prevalence (OR=0.996; 95% CI, 0.995-0.998; P <0.001). Regression showed a linear relationship between sunshine duration and myopia rates of primary school students [Prevalence%= (-0.1331*sunshine duration+47.73)%, p = 0.02]. Sunshine duration influenced the distribution of myopia rates among primary (Moran's I=-0.206, p<0.001) and junior high school (Moran's I=-0.183, p=0.002). Local spatial analysis showed that areas with low sunshine duration had high myopia prevalence concentration. Conclusion: This study revealed sunshine duration associations with myopia prevalence at the regional and population levels. The results may emphasize the significance of promptly implementing myopia control in regions with poor sunshine. The effect of sunshine on myopia is pronounced in the early years of education, especially in primary students.

Synchrony in adult survival is remarkably strong among common temperate songbirds across France.

Synchronous variation in demographic parameters across species increases the risk of simultaneous local extinction, which lowers the probability of subsequent recolonization. Synchrony therefore tends to destabilize meta-populations and meta-communities. Quantifying interspecific synchrony in demographic parameters, like abundance, survival, or reproduction, is thus a way to indirectly assess the stability of meta-populations and meta-communities. Moreover, it is particularly informative to identify environmental drivers of interspecific synchrony because those drivers are important across species. Using a Bayesian hierarchical multisite multispecies mark-recapture model, we investigated temporal interspecific synchrony in annual adult apparent survival for 16 common songbird species across France for the period 2001-2016. Annual adult survival was largely synchronous among species (73%, 95% credible interval [47%-94%] of the variation among years was common to all species), despite species differing in ecological niche and life history. This result was robust to different model formulations, uneven species sample sizes, and removing the long-term trend in survival. Synchrony was also shared across migratory strategies, which suggests that environmental forcing during the 4-month temperate breeding season has a large-scale, interspecific impact on songbird survival. However, the strong interspecific synchrony was not easily explained by a set of candidate weather variables we defined a priori. Spring weather variables explained only 1.4% [0.01%-5.5%] of synchrony, while the contribution of large-scale winter weather indices may have been stronger but uncertain, accounting for 12% [0.3%-37%] of synchrony. Future research could jointly model interspecific variation and covariation in breeding success, age-dependent survival, and age-dependent dispersal to understand when interspecific synchrony in abundance emerges and destabilizes meta-communities.

The mutation process on the ancestral line under selection.

We consider the Moran model of population genetics with two types, mutation, and selection, and investigate the line of descent of a randomly-sampled individual from a contemporary population. We trace this ancestral line back into the distant past, far beyond the most recent common ancestor of the population (thus connecting population genetics to phylogeny), and analyse the mutation process along this line. To this end, we use the pruned lookdown ancestral selection graph (Lenz et al., 2015), which consists of a set of potential ancestors of the sampled individual at any given time. Relative to the neutral case (that is, without selection), we obtain a general bias towards the beneficial type, an increase in the beneficial mutation rate, and a decrease in the deleterious mutation rate. This sheds new light on previous analytical results. We discuss our findings in the light of a well-known observation at the interface of phylogeny and population genetics, namely, the difference in the mutation rates (or, more precisely, mutation fluxes) estimated via phylogenetic methods relative to those observed in pedigree studies.

Application of a novel remote sensing ecological index (RSEI) based on geographically weighted principal component analysis for assessing the land surface ecological quality.

In evaluating the integrated remote sensing-based ecological index (RSEIPCA), principal component analysis (PCA) has been extensively utilized. However, the conventional PCA-based RSEI (RSEIPCA) cannot accurately evaluate component indicators' spatially shifting relative significance. This study presented a novel RSEI evaluation strategy based on geographically weighted principal component analysis (RSEIGWPCA) to address this deficiency. Second, compared to the classic RSEIPCA, RSEIGWPCA was tested at English Bazar and surrounding areas using two-fold validation. In this regard, the Jaccard test from a different setting and correlation analysis were utilized to examine the geographical distribution of RSEI derived by PCA and GWPCA. The validation output revealed better effectiveness of GWPCA over PCA in assessing the RSEI. The findings revealed that (i) in RSEI assessment, the spatial heterogeneity of the dataset helped to formulate individual weights by GWPCA that was not performed by PCA; and (ii) the areas having higher RSEI were primarily located around the Chatra wetland of this study area, and the areas with lower RSEI were located mainly in the industrial part. It has been concluded that RSEIGWPCA is a helpful approach in the RSEI evaluating for the regional and local scale like English bazaar city and its neighbourhood.

A spatial autocorrelation analysis of road traffic crash by severity using Moran's I spatial statistics: A comparative study of Addis Ababa and Berlin cities.

Methodological advancements in road safety research reveal an increasing inclination toward integrating spatial approaches in hot spot identification, spatial pattern analysis, and developing spatially lagged models. Previous studies on hot spot identification and spatial pattern analysis have overlooked crash severities and the spatial autocorrelation of crashes by severity, missing valuable insights into crash patterns and underlying factors. This study investigates the spatial autocorrelation of crash severity by taking two capital cities, Addis Ababa and Berlin, as a case study and compares patterns in low and high-income countries. The study used three-year crash data from each city. It employed the average nearest neighbor distance (ANND) method to determine the significance of spatial clustering of crash data by severity, Global Moran's I to examine the statistical significance of spatial autocorrelation, and Local Moran's I to identify significant cluster locations with High-High (HH) and Low-Low (LL) crash severity values. The ANND analysis reveals a significant clustering of crashes by severity in both cities, except in Berlin's fatal crashes. However, different Global Moran's I results were obtained for the two cities, with a strong and statistically significant value for Addis Ababa compared to Berlin. The Local Moran's I result indicates that the central business district and residential areas have LL values, while the city's outskirts exhibit HH values in Addis Ababa. With some persistent HH value locations, Berlin's HH and LL grid clusters are intermingled on the city's periphery. Socio-economic factors, road user behavior and roadway factors contribute to the difference in the result. Nevertheless, it is interesting to note the similarity of significant HH value locations on the outskirts of both cities. Finally, the results are consistent with previous studies and indicate the need for further investigation in other locations.

Can the digitalization level of agriculture improve its ecological efficiency under carbon constraints: Evidence from China.

The interplay between digitalization and economic development constitutes a pivotal global issue, yet empirical research on agricultural ecological efficiency in developing countries remains limited. This study initially establishes a measurement system and a comprehensive index for the level of agricultural digitalization. Subsequently, it delineates the relationship between agricultural digitalization level and agroecological efficiency using the spatial Durbin model, and ultimately explores the enhancing effect of agricultural digitalization level on agroecological efficiency using China as a case study. Research reveals that the agricultural ecological efficiency across the 31 mainland Chinese provinces demonstrates a generally linear upward trajectory, embodying both agglomeration and heterogeneity. The level of agricultural digitization exerts a significant, positive direct impact and facilitates a spatial spillover effect on agricultural ecological efficiency. Other control variables, such as financial support for agriculture and local economic development, impart a positive direct impact on regional agricultural ecological efficiency, while rural household operating income propels a positive spatial spillover effect on adjacent areas. The findings furnish guidance for developing countries to adeptly execute digital rural construction, aiming to enhance agricultural ecological efficiency amidst carbon constraints.

Geospatial methodology for determining the regional prevalence of hospital-reported childhood intussusception in patients from India.

Both developed and developing countries carry a large burden of pediatric intussusception. Sentinel site surveillance-based studies have highlighted the difference in the regional incidence of intussusception. The objectives of this manuscript were to geospatially map the locations of hospital-confirmed childhood intussusception cases reported from sentinel hospitals, identify clustering and dispersion, and reveal the potential causes of the underlying pattern. Geospatial analysis revealed positive clustering patterns, i.e., a Moran's I of 0.071 at a statistically significant (p value < 0.0010) Z score of 16.14 for the intussusception cases across India (cases mapped n = 2221), with 14 hotspots in two states (Kerala = 6 and Tamil Nadu = 8) at the 95% CI. Granular analysis indicated that 67% of the reported cases resided < 50 km from the sentinel hospitals, and the average travel distance to the sentinel hospital from the patient residence was calculated as 47 km (CI 95% min 1 km-max 378 km). Easy access and facility referral preferences were identified as the main causes of the existing clustering pattern of the disease. We recommend designing community-based surveillance studies to improve the understanding of the prevalence and regional epidemiological burden of the disease.

The expected sample allele frequencies from populations of changing size via orthogonal polynomials.

In this article, discrete and stochastic changes in (effective) population size are incorporated into the spectral representation of a biallelic diffusion process for drift and small mutation rates. A forward algorithm inspired by Hidden-Markov-Model (HMM) literature is used to compute exact sample allele frequency spectra for three demographic scenarios: single changes in (effective) population size, boom-bust dynamics, and stochastic fluctuations in (effective) population size. An approach for fully agnostic demographic inference from these sample allele spectra is explored, and sufficient statistics for stepwise changes in population size are found. Further, convergence behaviours of the polymorphic sample spectra for population size changes on different time scales are examined and discussed within the context of inference of the effective population size. Joint visual assessment of the sample spectra and the temporal coefficients of the spectral decomposition of the forward diffusion process is found to be important in determining departure from equilibrium. Stochastic changes in (effective) population size are shown to shape sample spectra particularly strongly.

Impact of Resistance on Therapeutic Design: A Moran Model of Cancer Growth.

Resistance of cancers to treatments, such as chemotherapy, largely arise due to cell mutations. These mutations allow cells to resist apoptosis and inevitably lead to recurrence and often progression to more aggressive cancer forms. Sustained-low dose therapies are being considered as an alternative over maximum tolerated dose treatments, whereby a smaller drug dosage is given over a longer period of time. However, understanding the impact that the presence of treatment-resistant clones may have on these new treatment modalities is crucial to validating them as a therapeutic avenue. In this study, a Moran process is used to capture stochastic mutations arising in cancer cells, inferring treatment resistance. The model is used to predict the probability of cancer recurrence given varying treatment modalities. The simulations predict that sustained-low dose therapies would be virtually ineffective for a cancer with a non-negligible probability of developing a sub-clone with resistance tendencies. Furthermore, calibrating the model to in vivo measurements for breast cancer treatment with Herceptin, the model suggests that standard treatment regimens are ineffective in this mouse model. Using a simple Moran model, it is possible to explore the likelihood of treatment success given a non-negligible probability of treatment resistant mutations and suggest more robust therapeutic schedules.

The ancestral selection graph for a Λ-asymmetric Moran model.

Motivated by the question of the impact of selective advantage in populations with skewed reproduction mechanisms, we study a Moran model with selection. We assume that there are two types of individuals, where the reproductive success of one type is larger than the other. The higher reproductive success may stem from either more frequent reproduction, or from larger numbers of offspring, and is encoded in a measure Λ for each of the two types. Λ-reproduction here means that a whole fraction of the population is replaced at a reproductive event. Our approach consists of constructing a Λ-asymmetric Moran model in which individuals of the two populations compete, rather than considering a Moran model for each population. Provided the measure are ordered stochastically, we can couple them. This allows us to construct the central object of this paper, the Λ-asymmetric ancestral selection graph, leading to a pathwise duality of the forward in time Λ-asymmetric Moran model with its ancestral process. We apply the ancestral selection graph in order to obtain scaling limits of the forward and backward processes, and note that the frequency process converges to the solution of an SDE with discontinuous paths. Finally, we derive a Griffiths representation for the generator of the SDE and use it to find a semi-explicit formula for the probability of fixation of the less beneficial of the two types.