Search Results (7,307)

Background: Oestradiol has been implicated as a factor in substrate utilisation in male and mouse studies but the effect of acute changes during the menstrual cycle is yet to be fully understood. Objective: To determine the role of oestradiol in respiratory exchange ratio (RER) during exercise at various intensities. Methods: This systematic review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. From inception to November 2023, four online databases (Cochrane, SPORTDiscus, MEDline and Web of Science) were searched for relevant articles. Studies that reported a resting oestradiol measurement in naturally menstruating women with exercise at a percentage of maximal aerobic capacity (%V˙O_2max) were included. Mean and standard deviation for oestradiol, RER and exercise intensity were extracted and study quality assessed using a modified Downs and Black checklist. Risk of bias was assessed using I₂ measure of heterogeneity and Egger’s regression test, assessment of bias from methodological quality was identified by sensitivity analysis. Eligible datasets were extracted for pairwise comparisons within a meta-analysis and correlation between change in oestradiol and change in RER. Data were also pooled to produce a mean and standard deviation for RER for menstrual stage and for low and high oestradiol groups. Results: Twenty-four articles were identified, over 50% were identified as high quality. Sixteen articles included datasets eligible for meta-analysis. Eleven articles utilised a submaximal constant-load exercise intensity, finding a standardised mean difference of − 0.09 ([CI: −0.35–0.17], p = 0.5) suggesting no effect of menstrual phase on constant-load exercise RER. In six articles using incremental exercise tests to exhaustion, a standardised mean difference of 0.60 ([CI 0.00–1.19], p = 0.05) was identified towards a higher maximal RER attained in follicular compared to luteal phase. There was no correlation (R = −0.26, p = 0.2) between change in oestradiol and change in RER between phases. All 24 articles, totalling 650 participants, were included in pooled analysis. When grouped by menstrual cycle phase or when grouped by oestradiol levels, RER was higher in the follicular phase than the luteal phase at low and high constant load exercise intensities. Discussion: Findings from the pooled-analysis and meta-analysis suggest that there may be menstrual cycle phase differences in RER that are intensity dependent. These differences may be related to sex hormone levels, but this was not supported by evidence of correlation between differences in RER and differences in oestradiol. At present, it remains best practice to assess performance in the same menstrual cycle phase if seeking to assess change from baseline. Full article

Data have become a virtual factor of production, and when integrated with the traditional factors of labor, capital, and land form digital labor, digital capital, and digital land, thereby generating a multiplier effect that contributes to the comprehensive revitalization of rural areas. This paper utilizes panel data from 30 provinces (autonomous regions and municipalities) in China from 2013 to 2023 and employs a double machine learning model to empirically test the impact mechanism of rural digitalization on the integration of rural industries. The results indicate that digital villages significantly promote the integrated development of rural industries through three direct pathways—digital industry development, digital information infrastructure, and digital service levels—with this conclusion remaining valid after a series of robustness tests. A mechanism analysis shows that digital villages facilitate the integration of rural industries through three indirect pathways—alleviating urban–rural factor mismatches, adjusting the agricultural–industrial structure, and promoting agricultural technological advancement—with this conclusion still valid after various robustness tests. The heterogeneity results show that there is significant variability in how digital villages promote the development of integrated rural industries, with the effects being more pronounced in major grain-producing and eastern regions compared to non-major grain-producing and central-western regions. Based on this, this paper proposes policy recommendations focused on accelerating digital village construction, formulating differentiated strategies, and alleviating factor mismatches, aiming to provide references for achieving rural revitalization. We mainly propose countermeasures and suggestions from three aspects: digital dividend, differentiation strategy, and element mismatch. Our main purpose in writing this article is to make up for the shortcomings of existing theories, enrich the theoretical system of digital rural construction, contribute Chinese solutions for digital rural construction around the world, and improve the word’s level of digital rural construction. Full article

Whether and how new infrastructure (NI) promotes urban–rural integration (URI) remains crucial for addressing unbalanced urban–rural development. This study analyzes panel data from 31 provincial-level administrative regions in China (2013–2022) to construct an evaluation index system for URI, encompassing economic, social, ecological, spatial, and demographic dimensions. Using the entropy method, the study quantifies the development level of NI and investigates its differential effects on URI. The empirical findings demonstrate that NI exhibits a significant positive effect on URI, with the strongest impact manifested in economic and spatial dimensions. The influence on social, ecological, and demographic aspects, while positive, is comparatively modest. Regional disparities and innovation investment levels contribute to the heterogeneous impact of NI. Moreover, the study reveals that industrial structure advancement serves as the transmission mechanism through which NI drives URI. The promotional effect becomes more pronounced after crossing both the double threshold of industrial structure upgrading and the single threshold of industrial structure rationalization. Based on these findings, the following policy recommendations are proposed to optimize the new infrastructure investment structure, promote deep integration with industrial structural adjustments, and implement new infrastructure construction in accordance with local conditions. Full article

Background: Currently, there is a need for approaches to understand and manage the multidimensional autism spectrum and quantify its heterogeneity. The diagnosis is based on behaviors observed in two key dimensions, social communication and repetitive, restricted behaviors, alongside the identification of required support levels. However, it is now recognized that additional modifiers, such as language abilities, IQ, and comorbidities, are essential for a more comprehensive assessment of the complex clinical presentations and clinical trajectories in autistic individuals. Different approaches have been used to identify autism subgroups based on the genetic and clinical heterogeneity, recognizing the importance of autistic behaviors and the assessment of modifiers. While valuable, these methods are limited in their ability to evaluate a specific individual in relation to a normative reference sample of autistic individuals. A quantitative score based on axes of phenotypic variability could be useful to compare individuals, evaluate the homogeneity of subgroups, and follow trajectories of an individual or a specific group. Here we propose an approach by (i) combining measures of phenotype variability that contribute to clinical presentation and could impact different trajectories in autistic persons and (ii) using it with normative modeling to assess the clinical heterogeneity of a specific individual. Methods: Using phenotypic data available in a comprehensive reference sample, the Simons Simplex Collection (n = 2744 individuals), we performed principal component analysis (PCA) to find components of phenotypic variability. Features that contribute to clinical heterogeneity and could impact trajectories in autistic people were assessed by the Autism Diagnostic Interview-Revised (ADI-R), Vineland Adaptive Behavior Scales (VABS) and the Child Behavior Checklist (CBCL). Cognitive assessment was estimated by the Total Intelligence Quotient (IQ). Results: Three PCs embedded 72% of the normative sample variance. PCA-projected dimensions supported normative modeling where a multivariate normal distribution was used to calculate percentiles. A Multidimensional General Functionality Score (MGFS) to evaluate new prospective single subjects was developed based on percentiles. Conclusions: Our approach proposes a basis for comparing individuals, or one individual at two or more times and evaluating homogeneity in phenotypic clinical presentation and possibly guides research sample selection for clinical trials. Full article

Rural infrastructure is an important foundation for achieving sustainable rural development. To effectively formulate policies for rural infrastructure, it is crucial to evaluate the benefits of rural infrastructure investment (RII) using a systematic method. This study aims to conduct a systematic analysis of the income-increasing effect of RII from a multidimensional perspective, and provide a reference for developing countries to adjust and improve rural infrastructure policies. For this purpose, this study has utilized 15 years of data in China to analyze the income-increasing effect of RII from three dimensions: structure, spatiality, and heterogeneity. The results indicate that (1) in terms of structure, both living infrastructure investment (LII) and production infrastructure investment (PII) promote wage income. PII has an increasing effect on non-wage income, but the increasing effect of LII on non-wage income is not evident. Meanwhile, the income-increasing effect of RII for high-income groups is larger than that for low-income groups. (2) In terms of spatiality, RII has a spatial spillover effect, which increases villagers’ income in neighboring areas. From the perspective of spatial effect decomposition, the indirect effect of RII even exceeds the direct effect. (3) In terms of heterogeneity, the increase in the level of job-related migration inhibits the income-increasing effect of LII but promotes the income-increasing effect of PII; the improvement of the education level promotes the income-increasing effect of LII but inhibits the income-increasing effect of PII. Full article

This paper uses Low-Carbon Pilot City (LCCP) as a quasi-natural experiment, 282 prefecture-level cities in China from 2007 to 2021, and models such as DID, SDM-DID, and DML to examine the impact of LCCP on urban shrinkage. Research shows that, first, LCCPs have effectively inhibited urban shrinkage, with pilot cities reducing urban shrinkage by 1.8% compared with non-pilot cities. Second, the LCCP may inhibit the city’s ability to shrink by reducing resource allocation efficiency, promoting technological innovation, and optimizing the living environment. Third, the urban shrinkage effect of the LCCP is heterogeneous depending on the economic region and whether the city is resource-based. Full article

Land use and land cover (LULC) studies, particularly those focused on mapping forest species using Sentinel-2 (S2A) data, face challenges in delineating and identifying areas of heterogeneous forest components with spectral similarity at the canopy level. In this context, the main objective of this study was to compare and analyze the feasibility of two classification algorithms, K-Nearest Neighbor (KNN) and Random Forest (RF), with S2A data for mapping forest cover in the southern regions of Portugal, using tools with a free, open-source, accessible, and easy-to-use interface. Sentinel-2A data from summer 2019 provided 26 independent variables at 10 m spatial resolution for the analysis. Nine object-based LULC categories were distinguished, including five forest species (Quercus suber, Quercus rotundifolia, Eucalyptus spp., Pinus pinaster, and Pinus pinea), and four non-forest classes. Orfeo ToolBox (OTB) proved to be a reliable and powerful tool for the classification process. The best results were achieved using the RF algorithm in all regions, where it reached the highest accuracy values in Alentejo Central region (OA = 92.16% and K = 0.91). The use of open-source tools has enabled high-resolution mapping of forest species in the Mediterranean, democratizing access to research and monitoring. Full article

Farmer’s incentive is a core issue in achieving sustainable agricultural development. In many developing countries, smallholder farming is predominant in agricultural production, potentially limiting improvements in agricultural sustainability. Promoting agricultural cooperatives is a widely adopted strategy to help resource-poor farmers obtain higher agricultural revenue. In China, these organizations have expanded rapidly since the early 21st century, reaching 2.22 million by September 2023 and providing services to nearly half of farming households. However, their effectiveness and impact on enhancing agricultural revenue remain subjects of ongoing debate. To provide more empirical evidence on this topic, this paper constructs an agricultural cooperatives database based on the national commercial registration enterprise dataset and matches it with the National Fixed Point Rural Survey (NFP). The findings reveal that the development of agricultural cooperatives in China significantly helps farmers enhance their production revenue, leading to an increase in household income. Furthermore, the paper identifies strong heterogeneity in the positive effects of cooperative development at both the village and household levels. In the mechanism analysis, it is shown that agricultural cooperatives in China facilitate increased investment in capital, intermediate inputs, and technology, optimizing the allocation of production factors in agricultural processes, thereby improving land productivity and ultimately increasing agricultural revenue. Full article

Using panel data of Chinese cities from 2006 to 2020, this study constructs the carbon emission performance index from the perspective of the dual differences in the four stages of growth, maturity, decline and regeneration of eastern, central, western and resource-based cities (RBCs). This study employs the Dagum Gini coefficient and kernel density estimation to explore σ convergence and β convergence for understanding the dual differences, dynamic evolutionary trend and convergence. Results indicate that during the sample period, the carbon emission performance index of RBCs shows a fluctuating upward trend with regional and typological imbalance influenced by geographical location and division of labour. The carbon emission performance index of RBCs of different regions and types (Growing, Mature, Declining and Regenerative) shows a fluctuating downward trend. However, the carbon emission performance index gap between the 116 RBCs in China is gradually expanding, further corroborating the influence of “excellent but outliers”. The overall level of carbon emission performance index of RBCs exhibits σ convergence, absolute β convergence and conditional β convergence phenomena. Notably, growing and regenerative RBCs demonstrate a clear “catching-up” trend compared to mature and declining RBCs. Furthermore, the inclusion of control variables reveals varying degrees of increased convergence speed. Environmental regulation intensity (ERI), gross domestic product (GDP), energy consumption structure (ECS), technology development level (T), industrial structure (IS) and foreign direct investment demonstrate significant regional and type heterogeneity in the changes in the carbon emission performance index of RBCs. Finally, based on the analysis results, implications are proposed to enhance the carbon emission performance of RBCs of different types, as well as at the national and regional levels. Full article

Incorporating sewage sludge (SS) into soils presents a cost-effective and environmentally friendly option compared to conventional farming practices. However, SS could be perceived as a double-edged sword, as it may contain a broad spectrum of contaminants, such as heavy metals (HMs), microplastics (MPs), Pharmaceuticals in the Environment (PIE), and personal care products (PSPs), raising concerns for soil health, water resources, food safety, and human health. Council Directive 86/278/EEC, which regulates SS application in agriculture, specifies limits for six HMs but has not undergone substantive revisions since its inception in 1986, until the release of the updated working document SWD-2023-{final 158}. This study critically examines the legislative landscape across the European Union (EU) Member States (MSs), identifying heterogeneity in implementation, regulatory gaps, and the absence of thresholds for emerging contaminants. The results reveal significant disparities in the permissible concentrations of HMs across MSs and in comparison to international guidelines established by the Food and Agriculture Organization (FAO) and the World Health Organization (WHO). Furthermore, the absence of regulatory measures for MPs, PIE, and other common soil pollutants underscores critical deficiencies in the current framework. These inconsistencies contribute to varying levels of soil health across the EU and highlight the need for a harmonized approach. The findings of this study highlight the imperative for a comprehensive overhaul of the EU legislative framework governing SS application. As evidenced, the establishment of harmonized contaminant thresholds, rigorous monitoring protocols, and regulatory provisions for emergent pollutants is essential for addressing the identified regulatory gaps, enhancing legislative coherence, and promoting sustainable agricultural practices aligned with the EU’s environmental and public health objectives. Full article

Household food waste contributes to 60% of the total global food waste. Based on an online questionnaire survey on household food waste in China, this paper explores the association between food safety preference and household food waste. This demonstrates that (1) the excessive concern about food safety significantly increased the proportion of household food waste, the weight of food wasted, and the food waste ratio. The robustness tests supported this finding. (2) heterogeneity analysis showed that the impact of the safety preference on the likelihood of household food waste varied by the gender of respondents, household size, and urban–rural type. The effect of safety preference on the weight of food wasted in the household varied by the gender and education level, household size, income level, urban–rural type, and located region. Thus, the study provides evidence for reducing household food waste in Chinese households through the popularization of food safety knowledge, which has certain implications for reducing food waste and achieving sustainable food consumption in other developing countries. Full article

Rapid urbanization facilitates socioeconomic development but also exacerbates land use/cover change (LUCC), significantly impacting ecological environments. Timely, objective, and quantitative assessments of ecological quality changes resulting from LUCC are essential for safeguarding the natural environment and managing land resources. However, limited research has explored the potential interrelationships between the spatio-temporal heterogeneity of LUCC and ecological quality during urbanization. This study focuses on the Xiong’an New Area, a region experiencing rapid urbanization, utilizing the remote sensing-based ecological index (RSEI) to monitor ecological quality dynamics from 2017 to 2023. To address the computational challenges associated with large-scale regions, a streamlined RSEI construction method was developed using Landsat imagery and implemented via Google Earth Engine (GEE). A geographically weighted regression (GWR) analysis, integrated with Sentinel-2 land use data, was employed to examine the influence of LUCC on ecological quality. The findings reveal the following: (1) Ecological quality in the Xiong’an New Area has exhibited an overall positive trajectory, with improvements elevating the ecological status to above moderate levels. (2) Urban expansion resulted in a 17% reduction in farmland, primarily converted into construction land, which expanded by approximately 12%. (3) Ecological protection policies have facilitated the conversion of farmland into wetlands and urban green areas, which emerged as the principal contributors to ecological quality enhancement. (4) A positive correlation was observed between changes in ecological land and ecological quality, while a negative correlation was identified between shifts in the construction land and farmland and ecological quality. This research provides valuable scientific insights into ecological conservation and land use management, thereby establishing a foundation for the development of rational land resource planning and sustainable ecological development strategies in the Xiong’an New Area. Full article

The discrepancy between the physical accessibility and perceived accessibility of public service facilities in coastal towns and villages of Fujian, China, was investigated in this study. Through a spatial distribution analysis of education and medical service facilities in Liushui Town and Xingchen Town, the equity and coverage levels of various facilities were evaluated based on the residents’ physical travel costs and perceptions. The results show pronounced spatial heterogeneity between the physical and perceived accessibility across different regions. Our findings suggest that, while certain areas boast a lot of physical access to facilities, the residents’ perceived access is significantly influenced by factors such as the terrain, transportation conditions, and the types of available travel tools. The findings of this study provide a scientific basis for optimizing the allocation of rural public service facilities, aiming to bridge the foundational service gap between urban and rural areas and promote the equitable development of rural living environments. Full article

Identifying priority conservation areas (PCAs) for national parks is critical for improving the cost-effectiveness and viability of conservation efforts, given the multiplicity of conservation values, the complexity of human activities, and the limited financial resources available. Assessing conservation costs is central to systematic conservation planning (SCP). To compensate for the limitations of the alternative cost method in small-scale case studies and accurately reflect the cost differences due to specific land use, tenure, and management strategies, conservation costs are quantified and spatialized in this study using monetization methods. Taking Shennongjia National Park (SNP) as an example, we considered the core conservation values of species, ecosystems, and geological heritage, using the Zonation 5 model to identify PCAs under three different targets: 17%, 30%, and 50%. The results indicated that, as the conservation targets increased, PCAs expanded from the central and southern high-altitude areas to the northwest and northeast. Conservation gaps are primarily concentrated in the western part of Songluo and the northern parts of Hongping and Songba. Conservation costs exhibit clear spatial heterogeneity, increasing gradually from the central high mountains towards the surrounding areas. Among these, ecological compensation cost was the primary factor driving the sharp increase in total costs, while opportunity cost remained consistently low with minimal fluctuations. Compared to the alternative method, our study clarified the spatial distribution and types of costs in the process of national park construction, providing a quantitative basis and scientific guidance for future fiscal investment directions, methods, and responsible entities. At the administrative division level, we revealed the main cost challenges faced by townships in balancing resource conservation with community development, leading to more targeted, timely, and actionable community governance strategies. These findings further illustrate the significant advantages of using monetary costs in optimizing the boundaries of individual national parks and enhancing funding allocation efficiency, while promoting effective unified management of natural resource assets within spatial planning. Full article

A comprehensive understanding of the pattern of genetic variation among populations and adaptations to environmental heterogeneity is very important for conservation and genetic improvement. Forest tree species are ideal resources for understanding population genetic differentiation and detecting signatures of selection due to their adaptations to heterogeneous landscapes. Ulmus lamellosa is a tree species that is endemic to northern China. In this study, using restriction-site-associated DNA sequencing (RAD-seq) data, 12,179 single-nucleotide polymorphisms were identified across 51 individuals from seven populations. There was a high level of genetic diversity and population differentiation in U. lamellosa. Population genetic structure analyses revealed a significant genetic structure related to the configuration of the mountains. Additionally, we found that the isolation-by-distance pattern explained the genetic differentiation best, and environmental heterogeneity also played a role in shaping the landscape genetics of this species inhabiting mountain ecosystems. The F_ST-based outlier and genotype–environment association approaches were used to explore the genomic signatures of selection and local adaptation and detected 317 candidate outlier loci. Precipitation seasonality (coefficient of variation), precipitation in the driest month, and enhanced vegetation index were important determinants of adaptive genetic variation. This study provides abundant genetic resources for U. lamellosa and insights into the genetic variation patterns among populations. Full article