Search Results (855)

Green total factor productivity (GTFP), as an important indicator considering both economic development and environmental protection, has prompted countries around the world to actively explore ways to improve it in the context of the global transition to a green economy. The Low-Carbon City Policy (LCCP) implemented by the Chinese government, along with the National Big Data Comprehensive Pilot Zone Policy (NBDCPZ), which serve as key carriers of green regulation and digital innovation, respectively, play an important role in improving green total factor productivity (GTFP) and achieving high-quality economic development. This study aims to deeply explore whether there is a collaborative enabling effect of the Low-Carbon City Policy (LCCP) and the National Big Data Comprehensive Pilot Zone Policy (NBDCPZ) on green total factor productivity (GTFP) and to reveal the internal mechanism by which they improve GTFP through green technological innovation and industrial agglomeration. Specifically, based on the panel data of 269 prefecture-level cities in China from 2006 to 2022, a “dual-pilot” policy is constructed through LCCP and NBDCPZ, and a multi-period difference-in-differences model (DID) is used to evaluate the collaborative effect of the “dual-pilot” policy on GTFP. The results show that the “dual-pilot” policy has a significant collaborative effect on green total factor productivity (GTFP), and its enabling effect is more obvious than that of the “single-pilot” policy. These conclusions still hold after a series of endogeneity and robustness tests. Mechanism analysis shows that the “dual-pilot” policy can also improve green total factor productivity (GTFP) through green technological innovation and industrial agglomeration. Heterogeneity analysis reveals that the collaborative enabling effect of the “dual-pilot” policy is influenced by geographical location and population density. Specifically, the “dual-pilot” policy significantly promotes green total factor productivity (GTFP) in coastal cities and those with high population density. These research results provide a scientific basis for formulating green development policies in China and other countries, as well as a direction for subsequent research on the collaborative enabling effect of multiple policies. Full article

Background/Objectives: Comprehensive knowledge of body composition and bone status across the lifespan is critical for clinical evaluation and public health initiatives. This study aimed to develop age- and sex-specific reference curves for body composition and bone status in a physically active Greek population aged 18–80 using dual-energy X-ray absorptiometry (DXA). A secondary objective was to examine age- and sex-related trends in fat distribution, lean mass (LM), and bone status. Methods: A cross-sectional analysis was conducted on 637 participants (275 men and 362 women). Physical activity was assessed through structured interviews evaluating type, frequency, and intensity, categorized using established guidelines from organizations such as the American Heart Association and World Health Organization. Anthropometric data and DXA scans were utilized to measure parameters including fat mass (FM), LM, and BMD. Participants were stratified into age categories, and percentile curves were generated using generalized additive models for location, scale, and shape (GAMLSS). Results: Among women, body mass increased by 20.9% and body fat percentage rose by 38.3% from the youngest to the oldest age group, accompanied by a 5.7% reduction in bone mineral density (BMD) and an 11.5% decline in bone mineral content (BMC). Men exhibited a 49.1% increase in body fat percentage, with LM remaining stable across age groups. In men, BMD decreased by 1.7%, while BMC showed minimal variation. Notable sex differences were observed in fat redistribution, with android fat (AF) increasing significantly in older individuals, particularly among women, highlighting distinct age-related patterns. Conclusions: This study provides essential reference data on body composition and bone status, emphasizing the need for tailored interventions to address sex- and age-related changes, particularly in fat distribution and bone density, to support improved health outcomes in aging populations. Full article

While striped catfish (Pangasianodon hypophthalmus) is an economically important aquaculture species, its genomic resources remain limited. To date, linkage maps, QTL (quantitative trait loci) analyses, and the identification of candidate genes associated with disease resistance traits are very limited. Therefore, the present study aimed to construct a high-density linkage map and identify candidate genes for this species. Our analysis was conducted on a pedigree population consisting of 560 individuals (490 offspring and 70 parents for 40 families), whose genomes were analyzed using a genotyping-by-sequencing platform. After stringent filtering, 9882 high-quality SNPs were retained for linkage analysis. Linkage analysis placed 8786 markers onto 30 linkage groups (LGs), with an average density of 0.43 SNPs per cM. Recombination rates varied across the 30 linkage groups (LGs), averaging of 3.6 cM/Mb in males, 6.7 cM/Mb in females, and 5.1 cM/Mb when sex-averaged. Using the linkage map, our QTL analysis identified three significant QTLs for disease resistance to Edwardsiella ictaluri, the causative agent of Bacillary Necrosis of Pangasius (BNP). The QTLs were located on LG1, LG9 and LG29, and their peak markers explained 17.03% of the phenotypic variance. An LD-based interval of approximately ±25 kb surrounding the QTL peak was identified as the putative candidate region. However, subsequent genome-wide association analysis did not identify significant SNP effects within these regions, suggesting that the QTLs may represent polygenic or small-effect loci that are detectable only in linkage-based analyses. In summary, this study presents the first high-density SNP-based linkage map for striped catfish and reports significant QTL and associated candidate genes related to disease resistance and growth traits. These findings provide valuable insights into the genetic architecture of economically important traits in P. hypophthalmus. Nevertheless, further validation in independent populations is required before incorporating these markers into selective breeding programs. Full article

Population models offer insights into both theoretical and practical aspects of insect population dynamics. Among the models, stage-structured matrix models are used to describe the population dynamics of insects because the development of insects is by nature stage-structured. Field populations of the pine caterpillar, Dendrolimus spectabilis (Lepidoptera: Lasiocampidae) were monitored in a pine stand located in Dorak-ri, Cheongsan-myeon, Wando-gun, Jeollanam-do, from May 1998 to March 1999, and the pest density was measured as the number of larvae, pupae, or eggs at one-month intervals, excluding the winter season. Life tables and matrix models were constructed based on field observations, and the most vulnerable life stage was identified through sensitivity analysis. The density of the pine caterpillar (number per 1000 cm² branch) was 7.9 on 8 May 1998, and subsequently decreased to 0.5 on 14 March 1999, showing a decreasing trend of caterpillar density. The population growth rate was 0.74, a decreasing trend. The most vulnerable stages were (1) the larvae immediately after hatching and (2) again during overwintering, probably due to indirect mortality caused by humid conditions and activities of natural enemies during winter. Given the significant damage caused by mature larvae in the spring and that the density of the caterpillar after overwintering typically remains stable, forest management requires that the pest density be monitored soon after overwintering to allow decisions about control measures to be taken. Our results showed that a matrix model is useful to describe the population dynamics of the pine caterpillar and to construct suitable management strategies. Full article

In densely populated and traffic-congested major cities, medical emergency rescue incidents occur frequently, making the use of drones for emergency medical supplies delivery a new emergency distribution method. However, establishing drone transportation networks in urban areas requires balancing spatiotemporal fluctuations in emergency needs, meeting hospitals’ mandatory constraints on response time, and addressing factors like airspace restrictions and weather impacts. By analyzing the spatiotemporal distribution characteristics of medical emergency logistics in large cities, this study constructs a drone base station location optimization model integrating dynamic and static factors. The model combines multi-source data including emergency needs, geographic information, and airspace limitations. It employs kernel density estimation to identify hotspot areas, uses DBSCAN clustering to detect long-term stable demand hotspots, and applies LSTM methods to predict short-term and sudden demand fluctuations. The model optimizes coverage rate, response time, and cost budget control for drone transportation networks through a multi-objective genetic algorithm. Using Guangzhou as a case study, the results demonstrate that through “dynamic-static” collaborative deployment and multi-model drone coordination, the network achieves 96.18% demand coverage with an average response time of 673.38 s, significantly outperforming traditional vehicle transportation. Sensitivity analysis and robustness testing further validate the model’s effectiveness in handling demand fluctuations, weather changes, and airspace restrictions. This research provides theoretical support and decision-making basis for scientific planning of urban medical emergency drone transportation networks, offering practical significance for enhancing urban emergency rescue capabilities. Full article

In Kampinoski National Park (KNP), located in central Poland near the Warsaw agglomeration, the ASF epidemic lasted five years (2017–2021). The virus likely entered the park via wild boar migrating along a natural ecological corridor or through unintentional transmission by residents and tourists. Between 2014 and 2021, intensive monitoring and wild boar population reduction were implemented. The wild boar population, estimated at 11 individuals/km² in 2013, began to be reduced from 2014 onward, when ASF was first detected in Poland. In 2018, at the peak of the epidemic, the density of wild boar dropped to about 0.51 individuals/km²—the lowest in the park’s history. Between 2017 and 2021, 408 ASF cases were recorded, mainly in dead wild boar, although age and sex structure analysis suggests that the actual mortality rate could have been up to about 50% higher. The early intervention—culling—which was controversial from the National Park’s perspective, appears to have played a key role in controlling the situation and likely in limiting the epidemic. At the same time, the limited organizational resources of KNP highlighted the need for proactive management and close institutional cooperation in protected areas subject to high anthropogenic pressure. Full article

Characterized by zero-carbon, congestion-free, and high-capacity features, the utilization of metro systems for collaborative passenger-and-freight transport (the metro-based underground logistics system, M-ULS) has been recognized as a favorable alternative to facilitate automated freight transport in future megacities. This article constructs a three-echelon M-ULS network and establishes a multi-objective bilevel programming model, considering the interests of both government investment departments and transport enterprises. The overall goal of the study is to establish a transportation network with the lowest construction cost, lowest operating cost, and highest facility utilization rate, taking into account factors such as population density, transportation conditions, land resources, logistics demand, and metro station location, under given cost parameters and demand conditions. The upper-level model takes government investment as the main body and aims to minimize the total cost, establishing an optimization model for location selection allocation paths with capacity constraints; the lower-level model aims to minimize the generalized cost for freight enterprises by simulating the competition between traditional transportation and the M-ULS mode. In addition, a bi-level programming model solving framework was established, and a multi-stage precise heuristic hybrid algorithm based on adaptive immune clone selection algorithm (AICSA) and improved plant growth simulation algorithm (IPGSA) is designed for the upper-level model. Finally, taking the central urban area of Beijing as an example, four network scales are set up for numerical simulation research to verify the reliability and superiority of the model and algorithm. By analyzing and setting key indicators, an optimal network configuration scheme is proposed, providing a feasible path for cities to improve logistics efficiency and reduce the impact of logistics externalities under limited land resources, further strengthening the strategic role of subway logistics systems in urban sustainable development. Full article

Cordulegaster heros is an endemic species for Central and Southeastern Europe and one of the species protected under the European Union’s Habitats Directive. To adequately protect this species and its habitats, it is of crucial importance to have detailed information on its distribution, habitat requirements and potential threats to its survival. The main aims of this study were to record Cordulegaster heros geographical and altitudinal distribution and habitat requirements (stream width, fine substrate content and habitat shading), along with the importance of protected area network in its conservation and threats to its habitats in Croatia. To achieve those aims, we investigated 201 perennial and intermittent streams across three biogeographical regions (Continental, Alpine, Mediterranean). Additionally, in a small-scale study conducted in streams located within a protected area, we assessed the species’ relationship with water quality. According to the current results, Cordulegaster heros was confirmed to reproduce in 44 perennial streams in the Continental and Alpine regions, with a significantly higher number of sites and species’ abundance recorded in the Continental region. As the species was not recorded in the Mediterranean region, its occurrence there remains unverified. The species occurred at an altitudinal range between 150 and 665 m a.s.l., with 77% of the sites being between 150 and 350 m a.s.l. It was mostly documented in streams with widths up to 250 cm, fine sediment content up to 30%, and high habitat shading (>75%). A small-scale assessment of its relationship with water parameters within a protected area revealed a significant correlation with higher concentration of oxygen and lower conductivity, confirming its requirements for clean and well-oxygenated habitats. Approximately 57% of the sites where this species was recorded are within the protected area network. However, because most known occurrences are concentrated within only one area, the Continental region, along with the rather low population densities and anthropogenic threats (e.g., deforestation, hydro-morphological alterations) present at 43% of those streams, further monitoring activities are necessary. The presented results provide a basis for further monitoring of Cordulegaster heros and its habitats in Croatia. Full article

Helianthus annuus L. is one of the major oilseed crops worldwide, and its production is seriously affected by a highly destructive necrotrophic pathogen, Sclerotinia sclerotiorum (S. sclerotiorum). The use of resistant cultivars is the best control measure via molecular breeding; however, the gene action underlying resistance to this stress is not well-established. Here, we conducted QTL analysis for S. sclerotiorum resistance in a recombinant inbred line (RIL) population that were developed from parents with resistant (C6) and susceptible (B728) to the disease. A high-density genetic linkage map with 6059 single nucleotide polymorphism (SNP) markers and a total length of 2763 cM was developed. The lesion length (LL) and the lesion area (LA) in the field, under climate chamber conditions or greenhouse conditions, were assessed following standardized inoculation protocols. A total of 16 major QTL for LL and 12 for LA were detected across three experimental environments, explaining 1.58–32.86% of the phenotypic variation. Of these, a major-effect QTL, qSCL2.4 on chromosome 2, could explain 30.22% of phenotypic variance with alleles from parent C6 which had more increased resistance to S. sclerotiorum. Fine-mapping in the BC₁F₃ population narrowed the locus to a 226.7 kb interval. HaWRKY48, which encodes a WRKY transcription factor located in this region, was prioritized as the prime candidate gene. Polymorphism analysis of HaWRKY48 in 138 sunflower accessions revealed eight SNPs defining six haplotypes. Resistance was associated with Hap3 and susceptibility to Hap1/Hap6. These findings advance our understanding of the genetic mechanisms governing sunflower resistance to S. sclerotiorum and provide valuable genetic markers for molecular breeding of resistant cultivars. Full article

Energy transition has become a priority in public policy; however, knowledge of its progress in peripheral, border regions of Eastern Poland—particularly in rural and urban—rural communes—remains sketchy. Research gaps concern both the scale and intensity of investments co-financed from European Union (EU) funds, as well as the effect of their locations in relation to the state border and their position in reference to Functional Urban Areas (FUAs) on the level and character of the discussed investment activity. The primary aim of this study was to assess how the location of a border region and its relation to FUAs diversifies the investment activity and level of investment co-financed from EU funds aimed at developing the low-carbon economy in rural and urban–rural communes of the Eastern Macroregion. The analysis was conducted in two complementary dimensions: (i) a comparative nationwide assessment, covering all macroregions of Poland, within the two most recent, completed EU financial frameworks; i.e., the years 2007–2013 and 2014–2020 and (ii) an in-depth analysis of the Eastern Macroregion, with particular attention to rural and urban–rural communes, their affiliation with Functional Urban Areas (FUAs), and the typology defined by the Delimitation of Rural Areas (DRA). The aim of the conducted analyses was to respond to the research hypothesis assuming that “in the Eastern Macroregion the spatial conditions, i.e., the border location and the location in relation to functional urban areas (within an FUA vs. outside an FUA) significantly diversify the investment activity of rural and urban–rural communes aimed at the low-carbon economy co-financed from EU funds”. Empirical studies were conducted based on data from the Ministry of Development Funds and Regional Policy and Statistics Poland, which were processed applying methods of descriptive statistics and statistical inference and also using correspondence analysis. The analyses confirmed that in Eastern Poland the process of energy transition moved from the pilot phase to the common implementation of low-carbon measures, to a considerable extent thanks to the activity of rural and urban–rural communes. The results indicate that spatial factors, particularly location in relation to Functional Urban Areas and population density, significantly diversify intensity of investments in rural and urban–rural communes in the spatial context, whereas no such relationship was found for the investment level per capita. Full article

Bangladesh is at the forefront of climate change impacts because of its geographical location, high population density, and constrained socio-economic infrastructure. Our objective is to explore the impacts of climate change on human security components and conflict constellation, and identify adaptation actors through the lens of experts in Bangladesh. We conducted 12 semi-structured qualitative interviews with lead experts using the Problem-centred Interview (PCI) methodology and inductively applied content analysis to analyse the data, complemented with descriptive statistics. Experts see a shift in baseline risk due to the increase in frequency and severity of natural hazards. It exacerbates existing vulnerabilities by declining agricultural productivity, undermining water security and increasing migration. Food, economic, and water security are predominantly impacted, where women and the poor suffer disproportionately. Impacts on urban areas, energy and community security are under-researched. Experts agreed that climate change is a “threat multiplier” and could aggravate political insecurity, leading to conflicts. Individuals and households are primary adaptation actors, followed by governmental and non-governmental organisations. This research contributes to the broader understanding of the complex nexus of climate change impacts, human security, and conflict constellation, complements climate models and provides policy-relevant insights for inclusive, long-term adaptation grounded in local realities in Bangladesh. Full article

Analyzing the spatial patterns of vitality in historic urban areas and their influencing elements is essential for improving the vitality of historic and cultural cities and fostering sustainable urban development. This research investigated the historic urban area of Kaifeng City. Employing Baidu Huiyan population location data, it assessed the spatial distribution of vitality on weekdays and weekends. A built environment indicator system was developed using multi-source data, and the CatBoost-SHAP model was applied to examine the nonlinear relationship between the built environment and the vitality of a historic urban area, along with the interactions among different factors. The study systematically explored the spatiotemporal dynamics of vitality and the influence mechanisms of the built environment. The results showed the following: (1) The vitality of Kaifeng’s historic urban area demonstrated significant spatiotemporal heterogeneity, exhibiting an “inner-hot, outer-cold” spatial pattern. Overall vitality levels were higher on weekends than on weekdays, with a progressive decline from morning to night. (2) Built environment factors dynamically influenced vitality across time periods. The impacts of POIM and BD shifted markedly, indicating temporal variations in vitality-driving mechanisms. (3) Synergistic interactions among built environment factors exerted nonlinear effects on urban vitality. Within reasonable threshold ranges, BSD, POID, and BD promoted vitality but exhibited diminishing marginal returns under high-density conditions. Notably, BSD played a core moderating role in multi-factor interactions. These findings reveal the complex and dynamic relationship between the built environment and historic urban vitality. They indicate that spatial governance should prioritize the synergistic integration of transportation, functions, ecology, and culture to achieve dual improvements in urban vitality and environmental quality, thereby providing important theoretical support and practical guidance for planning and spatial optimization in historic urban areas. Full article

Wolong Town, Pingquan City, is located in a typical low-mountainous area of northern China, where groundwater is a crucial drinking water resource, thus, investigating groundwater’s hydrochemical characteristics and assessing nitrate-related health risks are vital for protecting, developing, and utilizing water resources. In this study, 66 groundwater samples were collected and analyzed for physicochemical parameters and major ion concentrations. Results showed that the groundwater in Wolong Town was weakly alkaline (average pH = 7.6), and classified as fresh water with TDS ranging from 90.0 to 900 mg/L. The dominant hydrochemical type was identified as HCO₃⁻-Ca²⁺. Hydrochemical evolution was jointly regulated by natural water-rock interaction, anthropogenic nitrogen input, and environmental redox differentiation. Among these, water-rock interaction was the primary driver, where the hydrochemical composition was mainly shaped by the dissolution of halite, calcite, dolomite, and gypsum, coupled with cation exchange. Nitrate was the primary groundwater pollutant, with concentrations varying from 0.94 to 259 mg/L; elevation, soil type, and population density were key drivers influencing nitrate distribution. Health risk assessment indicated that nitrate posed significantly higher non-carcinogenic risks to infants and children than to adults, and long-term consumption of groundwater with excessive nitrate might induce adverse health effects. This study enhances understanding of shallow groundwater’s hydrochemical evolution and nitrate contamination-related health risks, thereby providing theoretical support for the sustainable development, utilization, and quality protection of groundwater resources in semi-arid low-mountainous areas. Full article

This study draws on the experience of selected European micro-regions in Germany, Poland, and Romania, representing different stages of a just transition, to identify applicable strategies for the Ukrainian context. The research aims to assess the spatial and economic preconditions for transformation, compare them across regions, and propose adaptation pathways. Methodologically, it combines spatial–economic analysis, comparative assessment, and critical evaluation of EU strategic approaches. The results reveal substantial disparities: European coal regions generally benefit from high population density, diversified economies dominated by the tertiary sector, strong research and education infrastructure, and cross-border advantages. In contrast, Ukrainian micro-regions are marked by demographic decline, low population density, rural settlement patterns, and complex security conditions. Based on these findings, the study recommends a localized transformation model emphasizing targeted investments, the strategic use of cross-border location, and the repurposing of existing specialized logistics and production infrastructure for new economic activities. The proposed approach contributes to the discourse on just transition by aligning regional development strategies with local structural capacities and constraints. The results obtained may be applicable in other European countries. Full article

Rapid urbanization in China has reshaped retail spatial structures, creating challenges of accessibility and service equity. This study employs a Geographic Information Systems (GIS)-based analytical framework to examine the spatial distribution and driving mechanisms of retail outlets in Taiyuan, a resource-based transition city in central China. Using 2023 Point of Interest (POI) data and a 2 km × 2 km grid system, kernel density estimation (KDE), Average Nearest Neighbor (ANN) Analysis, Location Quotient (LQ), and spatial autocorrelation were applied to identify clustering patterns and functional specialization. The GeoDetector (Word version, downloaded 2025) model further quantified the explanatory power of twelve natural, social, economic, and transportation variables. Results reveal a polycentric retail structure, with high-density clusters in Yingze and Xiaodian districts and under-supply in Jiancaoping and Jinyuan. Population density, nighttime light (NTL) intensity, and school distribution emerged as the strongest drivers, while topography constrained expansion. By integrating GIS-based spatial statistics with GeoDetector, the study demonstrates a transferable framework for analyzing urban retail spatial patterns. The findings extend retail geography to transition cities and provide practical guidance for optimizing retail allocation, enhancing service equity, and supporting spatial decision-making for sustainable urban development. Full article