Cluster Region Research Articles

Экономическая динамика и эколого-экономическая устойчивость арктических регионов России

This paper explores the environmental and economic resilience of the regions within the Arctic zone of the Russian Federation (AZRF). We define a region's environmental and economic resilience as its capacity to withstand external shocks, independently restore the balance between its economy and environment, and transform while maintaining or improving the balance between its environmental and economic systems. The study's relevance stems from the rapid industrialization of the Russian Arctic in recent years and the constraints on investment in environmental technologies, green production, and management. The study discusses an analysis of macroeconomic, environmental, and economic indicators of the Russian Arctic regions, examining their interrelations during the pandemic crisis and under the pressure of Western sanctions. From 2018 to 2022, the anthropogenic impact on the environment in the Russian Arctic gradually declined, although the situation varied for individual indicators depending on trends in the regional sectors. Regions were identified that lead in environmental and economic resilience as well as those showing increased anthropogenic impact despite declining industrial production. A multidimensional classification of regions in the Russian Arctic was developed based on indicators characterizing the state of the environmental and economic spheres. Clusters of regions with high, low, and limited levels of environmental and economic resilience were identified. The study revealed that the macroeconomic situation in these regions is more dynamic than their environmental and economic conditions. Macroeconomic indicators in the Arctic regions demonstrate different trends during periods of external shocks. Overall, the Russian Arctic economy was sensitive to the 2020 crisis; the 2022 sanctions had a negative impact on economies focused on Western markets, and in 2023, macroeconomic dynamics slowed down across all regions of the Russian Arctic. Further research is necessary to understand the factors influencing the environmental and economic resilience of the Russian Arctic regions under current conditions.

Assessing heatwave resilience in municipalities around Lake Balaton: A comparative analysis

Changing climate patterns represent a major challenge for Hungarian municipalities, particularly with regard to the increasing severity and frequency of heatwaves. As a result of the COVID-19 lockdowns, thousands of people moved to communities around Lake Balaton; therefore, cities and villages should place more emphasis on their long-term sustainability and climate resilience. This article addresses the literature gap in assessing the heatwave resilience of Hungarian settlements, focusing on the municipalities of the Lake Balaton Resort Area. Our main objective was to uncover spatial and temporal patterns in the 180 settlements involved in the analysis by using an indicator-based comparative method. The set of indicators included nine sensitivity and six adaptive capacity measures referring to the base years 2015 and 2022. Our results show heterogeneous spatial patterns across the analysed categories; however, several regional clusters can be identified: 1) in general, settlements from the northern part of the study area had above-average adaptive capacity, while the southern and south-western municipalities had significantly lower values, 2) only one micro-regional cluster can be defined in terms of sensitivity values in the northern part of the study area; 3) below average resilience values were found in the south-western and southern areas; 4) finally, neither sensitivity nor adaptive capacity nor overall resilience scores had changed significantly over time at the regional level. The applied methodology can easily be adopted in other Hungarian or even Central and Eastern European cities; consequently, new results can contribute to a better understanding of inter- and intra-regional patterns of heatwave resilience at the local level.

Very High-energy Gamma-Ray Episodic Activity of Radio Galaxy NGC 1275 in 2022–2023 Measured with MACE

The radio galaxy NGC 1275, located at the central region of Perseus cluster, is a well-known very high-energy (VHE) gamma-ray emitter. The Major Atmospheric Cherenkov Experiment Telescope has detected two distinct episodes of VHE (E > 80 GeV) gamma-ray emission from NGC 1275 during 2022 December and 2023 January. The second outburst, observed on 2023 January 10, was the more intense of the two, with flux reaching 58% of the Crab Nebula flux above 80 GeV. The differential energy spectrum measured between 80 GeV and 1.5ṪeV can be described by a power law with a spectral index of Γ = −2.90 ± 0.16stat for both flaring events. The broadband spectral energy distribution derived from these flares, along with quasisimultaneous low-energy counterparts, suggests that the observed gamma-ray emission can be explained using a homogeneous single-zone synchrotron self-Compton model. The physical parameters derived from this model for both flaring states are similar. The intermediate state observed between two flaring episodes is explained by a lower Doppler factor or magnetic field, which subsequently returned to its previous value during the high-activity state observed on 2023 January 10.

Seasonal assessment of surface water and sediments pollution in Rachiine River, Northern Lebanon, using multivariate statistical analysis

Urbanization has caused severe negative impacts on intra-urban river water worldwide. In this study, the WHO drinking water standards (2024) were used as reference to assess the physicochemical properties, heavy metals (HMs) content and microbial load in water and sediment samples collected from 25 locations along Rachiine River, located in Northern Lebanon, during wet and dry periods. Multivariate statistical analysis was applied to evaluate the seasonal variations in water and sediment quality, and determine the pollution sources. The microbial load assessment indicated high pollution levels by Escherichia coli, fecal enterococci, total coliform and fecal coliform, which generally increased as the river progressed downstream. Cluster analysis (CA) provided three major clusters in the study region, representing the northern, central, and southern sectors of the river. Principal components analysis (PCA) of water samples generated four principal components (PCs) accounting for 64.3, 11.4, 7.6 and 4.1 % of the total variance, whereas PCA of sediment samples explained 59.1, 16.9 and 11.1 % of the data set variance. These PCs revealed that the quality of water and sediments is significantly impacted by point and diffuse sources, including geological and anthropogenic factors. These findings call for urgent management strategies to limit future deterioration of the aquatic bodies.

Filamentary Hierarchies and Superbubbles: Galactic Multiscale Magnetohydrodynamic Simulations of Giant Molecular Cloud to Star Cluster Formation

There is now abundant observational evidence that star formation is a highly dynamical process that connects filament hierarchies and supernova feedback from galaxy-scale kiloparsec filaments and superbubbles to giant molecular clouds (GMCs) on 100 pc scales and star clusters (1 pc). Here we present galactic multiscale MHD simulations that track the formation of structure from galactic down to subparsec scales in a magnetized, Milky Way–like galaxy undergoing supernova-driven feedback processes. We do this by adopting a novel zoom-in technique that follows the evolution of typical 3 kpc subregions without cutting out the surrounding galactic environment, allowing us to reach 0.28 pc resolution in the individual zoom-in regions. We find a wide range of morphologies and hierarchical structures, including superbubbles, turbulence, and kiloparsec atomic gas filaments hosting multiple GMC condensations that are often associated with superbubble compression, down to smaller-scale filamentary GMCs and star cluster regions within them. Gas accretion and compression ultimately drive filaments over a critical, scale-dependent line mass leading to gravitational instabilities that produce GMCs and clusters. In quieter regions, galactic shear can produce filamentary GMCs within flattened, rotating disklike structures on 100 pc scales. Strikingly, our simulations demonstrate the formation of helical magnetic fields associated with the formation of these disklike structures.

Exploring the impact of biological sex on intrinsic connectivity networks in PTSD: A data-driven approach

IntroductionSex as a biological variable (SABV) may help to account for the differential development and expression of post-traumatic stress disorder (PTSD) symptoms among trauma-exposed males and females. Here, we investigate the impact of SABV on PTSD-related neural alterations in resting-state functional connectivity (rsFC) within three core intrinsic connectivity networks (ICNs): the salience network (SN), central executive network (CEN), and default mode network (DMN). MethodsUsing an independent component analysis (ICA), we compared rsFC of the SN, CEN, and DMN between males and females, with and without PTSD (n = 47 females with PTSD, n = 34 males with PTSD, n = 36 healthy control females, n = 20 healthy control males) via full factorial ANCOVAs. Additionally, linear regression analyses were conducted with clinical variables (i.e., PTSD and depression symptoms, childhood trauma scores) in order to determine intrinsic network connectivity characteristics specific to SABV. Furthermore, we utilized machine learning classification models to predict the biological sex and PTSD diagnosis of individual participants based on intrinsic network activity patterns. ResultsOur findings revealed differential network connectivity patterns based on SABV and PTSD diagnosis. Males with PTSD exhibited increased intra-SN (i.e., SN-anterior insula) rsFC and increased DMN-right superior parietal lobule/precuneus/superior occipital gyrus rsFC as compared to females with PTSD. There were also differential network connectivity patterns for comparisons between the PTSD and healthy control groups for males and females, separately. We did not observe significant correlations between clinical measures of interest and brain region clusters which displayed significant between group differences as a function of biological sex, thus further reinforcing that SABV analyses are likely not confounded by these variables. Furthermore, machine learning classification models accurately predicted biological sex and PTSD diagnosis among novel/unseen participants based on ICN activation patterns. ConclusionThis study reveals groundbreaking insights surrounding the impact of SABV on PTSD-related ICN alterations using data-driven methods. Our discoveries contribute to further defining neurobiological markers of PTSD among females and males and may offer guidance for differential sex-related treatment needs.

Evaluation of the Smart Logistics Based on the SLDI Model: Evidence from China

Smart logistics (SL) reflects the digital transformation of the logistics industry, which is key for economic development. Most evaluations are based on the application of technology in SL, and few studies have evaluated SL from a comprehensive perspective. The paper builds the SL development index (SLDI) model from five dimensions based on the driving force, pressure, state, impact, and response (DPSIR) model and identifies the indicator weight by the entropy weight technique. The paper employs the ETDK method, a combined quantitative approach that incorporates entropy weight (E), the technique for order preference by similarity to an ideal solution (TOPSIS) (T), the Dagum Gini coefficient (D), and Kernel density estimation (K), to calculate the closeness degree, analyze spatial-temporal differentiation, and explain the distribution characteristics using data from China spanning 2013 to 2021. The findings show that (1) The SL evaluation is multidimensional and cannot be evaluated only based on technical indicators. A comprehensive evaluation indicator system is necessary. (2) A combined quantitative approach can measure SL development from multiple perspectives and get a clearer picture of the characteristics and regional differences of SL. (3) Influenced by economic development, infrastructure, regional clusters, location, talent, etc., the overall SL development is improving yearly, but SL development in different regions is unbalanced and has different distribution characteristics. The SLDI model developed in this paper will provide a more scientific and reasonable tool for comprehensively evaluating SL. The findings are helpful in proposing suggestions and optimization approaches for subsequent research on SL evaluation and development.

An atlas of gas motions in the TNG-Cluster simulation: From cluster cores to the outskirts

Galaxy clusters are unique laboratories for studying astrophysical processes and their impact on halo gas kinematics. Despite their importance, the full complexity of gas motion within and around these clusters remains poorly known. This paper is part of a series presenting the first results from the new TNG-Cluster simulation, a suite comprising 352 high-mass galaxy clusters including the full cosmological context, mergers and accretion, baryonic processes and feedback, and magnetic fields. Studying the dynamics and coherence of gas flows, we find that gas motions in galaxy cluster cores and intermediate regions are largely balanced between inflows and outflows, exhibiting a Gaussian distribution centered at zero velocity. In the outskirts, even the net velocity distribution becomes asymmetric, featuring a double peak where the second peak reflects cosmic accretion. Across all cluster regions, the resulting net flow distribution reveals complex gas dynamics. These are strongly correlated with halo properties: at a given total cluster mass, unrelaxed, late-forming halos with fewer massive black holes and lower accretion rates exhibit a more dynamic behavior. Our analysis shows no clear relationship between line-of-sight and radial gas velocities, suggesting that line-of-sight velocity alone is insufficient to distinguish between inflowing and outflowing gas. Additional properties, such as temperature, can help break this degeneracy. A velocity structure function (VSF) analysis indicates more coherent gas motion in the outskirts and more disturbed kinematics toward halo centers. In all cluster regions, the VSF shows a slope close to the theoretical models of Kolmogorov (∼1/3), except within 50 kpc of the cluster centers, where the slope is significantly steeper. The outcome of TNG-Cluster broadly aligns with observations of the VSF of multiphase gas across different scales in galaxy clusters, ranging from ∼1 kpc to megaparsec scales.

Spatial distribution of teenage pregnancy and its associated factors in Ethiopia: spatial and multilevel analysis of EDHS 2019

BackgroundOne of the reasons for the high rates of maternal and child morbidity and mortality in Sub-Saharan Africa is the rising proportion of teenage pregnancy. Preventing teenage pregnancy is critical to meeting sustainable development goal number three which aims to reduce the global maternal mortality ratio to less than 70 per 100,000 live births. To support the achievement of this goal, this study aimed to assess the spatial variation and factors associated with teenage pregnancy in Ethiopia using the recent nationally representative data.MethodsA secondary data analysis of the 2019 Ethiopian mini Demographic and Health Survey was conducted with a total weighted sample of 2211 (unweighted 2100) teenagers. The Bernoulli model was fitted using SaTScan version 9.6 to identify hotspot areas and the geospatial pattern and prediction of teenage pregnancy were mapped using ArcGIS version 10.7. A multilevel logistic regression model was fitted to identify factors associated with teenage pregnancy among teenagers. Adjusted OR with 95% CI was calculated and variables having a p-value less than 0.05 were statistically significant factors of teenage pregnancy.ResultThe prevalence of teenage pregnancy among adolescents aged 15–19 years in Ethiopia was 12.89% (95% CI: 11.56%, 14.36%). The SaTScan analysis identified a primary cluster in the Gambella region of Ethiopia (log-likelihood ratio = 14.02, p < 0.001). A high prevalence of teenage pregnancy was observed in Somalia, Afar, Gambella, and the southern part of the Oromia regions of Ethiopia. Age, educational status- primary and secondary, religion- protestant, having television, contraceptive knowledge, household head-female, and region- Small peripheral were significant determinants of teenage pregnancy.ConclusionThe spatial distribution of teenage pregnancy in Ethiopia was nonrandom. Age, educational status, religion, having television, contraceptive knowledge, sex of household head, and region were significant determinants of teenage pregnancy. Therefore, concerned government bodies and other stakeholders should organize periodic educational campaigns and youth-friendly reproductive health services. Collaboration between healthcare professionals, and religious and community leaders could also form a strategic partnership that makes interventions more comprehensive, culturally sensitive, and effective in reducing teenage pregnancy.

Long-range transcription factor binding sites clustered regions may mediate transcriptional regulation through phase-separation interactions in early human embryo

In mammals, during the post-fertilization pre-implantation phase, the expression of cell type-specific genes is crucial for normal embryonic development, which is regulated by cis-regulatory elements (CREs). TFs control gene expression by interacting with CREs. Research shows that transcription factor binding sites (TFBSs) reflect the general characteristics of the regulatory genome. Here, we identified TFBSs from chromatin accessibility data in five stages of early human embryonic development, and quantified transcription factor binding sites-clustered regions (TFCRs) and their complexity (TC). Assigning TC values to TFCRs has made it possible to assess the functionality of these regulatory elements in a more quantitative way. Our findings reveal a robust correlation between TFCR complexity and gene expression starting from the 8Cell stage, which is when the zygotic genome is activated in humans. Furthermore, we have defined long-range TFCRs (LR-TFCRs) and conjecture that LR-TFCRs may regulate gene expression through phase-separation mechanisms during the early stages of human embryonic development.

Isolation of Virulent Leptospira Serogroup Australis Field Strains from Symptomatic Dogs for Canine Leptospiral Vaccine Development.

Leptospirosis is a widespread zoonosis caused by spirochaetes belonging to the pathogenic species of Leptospira, which are classified into more than 25 serogroups and 250 serovars. Vaccination can prevent the disease in dogs but offers incomplete efficacy because of a lack of cross-protection between serogroups. The aim of this study was to validate a robust recruitment and sampling process, with the objectives of isolating and typing circulating Leptospira pathogenic strains and then selecting those of proven virulence and pathogenicity for vaccine development. Blood and urine samples from dogs with clinical syndromes compatible with acute leptospirosis were sterilely collected and transported to a reference laboratory for a micro-agglutination test (MAT), PCR, and bacterial isolation. Isolated strains underwent molecular typing using RNA16S, variable-number tandem repeat (VNTR), and pulsed-field gel electrophoresis (PFGE). Subtyping was performed using core genome multilocus sequence typing (CgMLST). Among 64 included dogs, 41 had MAT and/or PCR results compatible with Leptospira infection, and 14 Leptospira strains were isolated. Based on molecular typing, 11 isolates were classified as L. interrogans serogroup Australis, serovar Bratislava, and 3 as serogroup Icterohaemorrhagiae, serovar Icterohaemorrhagiae. CgMLST subtyping revealed a diversity of clonal groups (CGs) distributed in several regional clusters. Besides validating a robust recruitment and sampling process, this study outlines the value of combining PCR and serological testing when suspecting leptospirosis and the usefulness of implementing molecular typing methods to identify circulating field strains. It also confirms the epidemiological importance of the Australis serogroup and allows for the collection of different highly pathogenic strains for vaccine development.

The constitutional codification of academic freedom over time and space

Abstract This article explores the global spread of domestic codifications of academic freedom norms by mapping constitutional provisions over time and space. Drawing on the new Academic Freedom in Constitutions dataset, the study evaluates several hypotheses that may explain the norm’s geographically diverse, yet comparatively limited, adoption in 52 per cent of constitutions today. The descriptive analysis of constitutional adoption patterns suggests that the as yet large pockets of absence are a result of the fact that academic freedom was not included as a fundamental right from the early days of constitution-making, combined with its close link to higher education development, thus locking many countries into a path dependency of early constitutions exclusive of academic freedom norms. The availability of relevant models in nearby countries, together with higher education expansion, are key facilitators of academic freedom adoption at the critical time of a constitutional reform process. Diverse countries in different regions acted as norm entrepreneurs, often motivated to domestically protect academic freedom, thus leading to the emergence of regional and other clusters of academic freedom reference types. A sizeable proportion of insincere adopters further suggests that, in some regions, academic freedom serves as a legitimizing international norm.

Analysis of Spatiotemporal Changes in Energy Consumption Carbon Emissions at District and County Levels Based on Nighttime Light Data—A Case Study of Jiangsu Province in China

Approximately 86% of the total carbon emissions are generated by energy consumption, and the study of the variation of energy consumption carbon emissions (ECCE) is of vital significance to regional sustainable development and energy conservation. Currently, carbon emissions accounting mainly focuses on large and medium-scale statistics, but at smaller scales (district and county level), it still remains unclear. Due to the high correlation between nighttime light (NTL) data and ECCE, this study combines “energy inventory statistics” with NTL data to estimate ECCE at smaller scales. First, we obtained city-level statistics on ECCE and corrected the NTL data by applying the VANUI index to the original NTL data from NPP-VIIRS. Second, an analysis was conducted on the correlation between the two variables, and a model was created to fit the relationship between them. Under the assumption that ECCE will be consistent within a given region, we utilized the model to estimate ECCE in districts and counties, eventually obtaining correct results at the county-level. We estimated the ECCE in each district and county of Jiangsu Province from 2013 to 2022 using the above-proposed approach, and we examined the variations in these emissions both spatially and temporally across the districts and counties. The results revealed a significant degree of correlation between the two variables, with the R2 of the fitting models exceeding 0.8. Furthermore, ECCE in Jiangsu Province fluctuated upward during this period, with clear regional clustering characteristics. The study’s conclusions provide information about how carbon emissions from small-scale energy use are estimated. They also serve as a foundation for the creation of regional energy conservation and emission reduction policies, as well as a small-scale assessment of the present state.

Hydrometeorology-wildfire relationship analysis based on a wildfire bivariate probabilistic framework in different ecoregions of the continental United States

Wildfires are a natural part of the ecosystem in the U.S.. It is vital to classify wildfires using a comprehensive approach that simultaneously considers wildfire activity (the number of wildfires) and burned area. On this basis, the influence of hydrometeorological variables on wildfires can be further analyzed. Therefore, this study first classified wildfire types using a wildfire bivariate probability framework. Then, by considering six hydrometeorological variables, the dominant hydrometeorological variables for different wildfire types in 17 ecoregions of the United States were quantified. In addition, based on the results of this hydrometeorology-wildfire relationship analysis, we obtained new clusters that simultaneously considered wildfire characteristics and the impact of hydrometeorology on wildfires. In particular, the results were as follows: (1) Through the probability of wildfire bivariate statistical characteristics, wildfires could be classified into five types in this paper: WT-1 (mega-wildfire), WT-2 (joint wildfire-1), WT-3 (joint extremes), WT-4 (joint wildfire-2), and WT-5 (super frequent wildfires); (2) The dominant hydrometeorological variables under different wildfire types were discussed in 17 ecoregions of the United States; and (3) In the four new cluster regions, intensifying droughts are a concern in clusters 1 and 4, while there are multiple concerns in cluster 3, namely, stronger winds, higher temperatures, and more drought.

A TOPSIS analysis of regional competitiveness at European level

PurposeThe measurement of regional competitiveness is becoming essential for policymakers to address territorial disparities, while considering the issue of correlations among indicators. Therefore, the purpose of this paper is to measure regional competitiveness using the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) by considering different distance measures and two levels of analysis to provide a comparative and comprehensive measurement of regional competitiveness in Europe.Design/methodology/approachThe authors apply TOPSIS based on three different distance measures (the Manhattan, the Euclidean and the Mahalanobis distance measures) to the regions of the EU Regional Competitiveness Index (RCI) 2019, which is taken as the frame of reference.FindingsThe authors replicate the RCI by using TOPSIS with a less preferred choice of distance measure, indicating TOPSIS as a valuable method for policymakers in the analysis of regional competitiveness. The authors argue in favour of the Mahalanobis distance measure as the best of the three, as it considers correlations among macro-economic indicators.Originality/valueThis study aims to make three contributions. Firstly, by replicating the RCI by means of TOPSIS with a less preferred choice of distance measure, the paper provides a benchmark for future research on regional competitiveness. Secondly, by suggesting the use of TOPSIS with the use of the Mahalanobis distance measure, the authors show how to measure regional competitiveness by taking into account correlations among pillars. Thirdly, the authors argue in favour of considering clusters of regions when measuring regional competitiveness.

RESEARCH ON DIGITAL ECONOMY AND GREEN TOTAL FACTOR PRODUCTIVITY GROWTH OF CHINA’S INDUSTRY AND SPATIAL EFFECTS

This paper evaluates the impact and role of digital economy on industrial green total factor productivity based on the perspective of China’s industrial green transformation and provides a realistic basis and decision-making reference for industrial green transformation. This paper constructs the industrial green total factor productivity and digital economy development index of 30 provinces from 2013 to 2019, and empirically tests the spatial-temporal evolution relationship between them and the impact of digital economy on industrial green development by using time-fixed effect and spatial Durbin model. The results show that the digital economy and industrial green total factor productivity digital economy are unevenly developed, basically showing a distribution trend of high in the east and low in the west, and the two have a significant positive spatial correlation in the years observed. The results of local spatial autocorrelation analysis show that there is a high clustering of digital economy and total factor productivity in the eastern coastal region and low clustering in the western region. The regional heterogeneity analysis shows that the development of digital economy is beneficial to optimize the distortion of capital and labor allocation and thus improve industrial green total factor productivity, but the indirect effect of digital economy on industrial green total factor productivity is not significant and the direct effect plays a dominant role.

Context‐driven implementation strategies: Exploring three approaches to implement a lean capability framework within a global production company

AbstractThis paper explores global implementation of capability building projects as part of an corporate lean programme. The aim is to identify the core parameters in global implementation of complex knowledge in various contexts within the corporation. The empirical research investigates the global implementation of a lean capability project in three regional clusters within a large pharmaceutical multinational production company. The findings indicate that contextual situations in regional clusters, for example, maturity levels, national culture, and previous experiences, influence the design of the implementation approaches embedding knowledge management principles in various ways. Three types of implementation approaches (horizontal, parallel, and delegated) are identified, which highlights the strategically different pathways to realise new frameworks for knowledge management. This study shows how adjustments to contextual situations influence the implementation process and identifies various hallenges with various approaches that may hinder the execution of lean strategy. This paper puts forward five identified implementation parameters that could guide future research and knowledge management practitioners in opex, HR, and learning and development functions.

Intersectional equity in Brazil's remote rural municipalities: the road to efficiency and effectiveness in local health systems.

The Brazilian remote rurality has been classified more reliably only recently, according to demographic density, proportion of urban population, and accessibility to urban centers. It comprises 5.8% of the municipalities, in nearly half of the states, with a population of 3,524,597 (1.85%). Remote rural localities (RRL) have reduced political/economic power, facing greater distances and barriers. Most health strategies are developed with the urban space in mind. We aim to understand how RRL are positioned concerning efficiency/effectiveness in health, compared to other urban-rural typologies of Brazilian localities, focusing on Primary Health Care (PHC), and its organizational models. We evaluated the efficiency and effectiveness of the organizational models using the health production model, from 2010-2019, gradually deepening the immersion into the RRL reality. We analyzed the human and financial resources dimensions, emphasizing teams, the results of PHC actions, and health levels. We used the fixed effects model and data envelopment analysis, cross-sectioned by intersectional inequities. We compared the Brazilian states with and without RRL, Brazilian municipalities according to rural-urban typologies, and RRL clusters. Brazilian RRL states show superior resource/health efficiency through services utilization according to health needs. The remote rural typology demonstrated greater efficiency and effectiveness in health than the other typologies in the RRL states. The organizational models with the Family Health Strategy (FHS) teams and the Community Health Worker (CHW) visits played a key role, together with local per capita health expenditures and intergovernmental transfers. Thus, financial resources and health professionals are essential to achieve efficient/effective results in health services. Among the RRL, the Amazon region clusters stand out, denoting the importance of riverine and fluvial health teams, the proportion of diagnostic/treatment units in addition to the proportion of illiteracy and adolescent mothers along with the inequity of reaching high levels of schooling between gender/ethnicity. Hopefully, these elements might contribute to gains in efficiency and effectiveness, prioritizing the allocation of financial/human resources, mobile FHS teams, availability of local diagnosis/treatment, and basic sanitation. Finally, one should aim for equity of gender/ethnicity in income and education and, above all, of place, perceived in its entirety.

Water and socioeconomic inequalities: spatial analysis of water consumption in Brazil

ABSTRACT To achieve equitable water access, it is necessary to understand and quantify the heterogeneity of water consumption. Thus, this study assessed the spatial dependence of water consumption for Brazil and an urban center. Two spatial autocorrelation tests were applied: the Global Moran’s Index (I) and the Local Indicator of Spatial Association (LISA). It was found that, both at the national and municipal scales, water consumption is not uniformly distributed in space, indicating the formation of clusters of regions with High-High, High-Low, Low-High, and Low-Low aggregation patterns. In this way, water and socioeconomic inequalities in Brazil are highlighted, emphasizing the gap between the Center-South and the North-Northeast regions. Additionally, water and socioeconomic disparities within the city of Fortaleza are also observed, resulting from its urbanization process. Finally, the spatial autocorrelation between water consumption and per capita income is strongly evident at both the national and municipal levels.

Framework for Regional to Global Extension of Optical Water Types for Remote Sensing of Optically Complex Transitional Water Bodies

Water quality indicator algorithms often separate marine and freshwater systems, introducing artificial boundaries and artifacts in the freshwater to ocean continuum. Building upon the Ocean Colour- (OC) and Lakes Climate Change Initiative (CCI) projects, we propose an improved tool to assess the interactions across river–sea transition zones. Fuzzy clustering methods are used to generate optical water types (OWT) representing spectrally distinct water reflectance classes, occurring within a given region and period (here 2016–2021), which are then utilized to assign membership values to every OWT class for each pixel and seamlessly blend optimal in-water algorithms across the region. This allows a more flexible representation of water provinces across transition zones than classic hard clustering techniques. Improvements deal with expanded sensor spectral band-sets, such as Sentinel-3 OLCI, and increased spatial resolution with Sentinel-2 MSI high-resolution data. Regional clustering was found to be necessary to capture site-specific characteristics, and a method was developed to compare and merge regional cluster sets into a pan-regional representative OWT set. Fuzzy clustering OWT timeseries data allow unique insights into optical regime changes within a lagoon, estuary, or delta system, and can be used as a basis to improve WQ algorithm performance.