The impact of green finance on carbon productivity: The mediating effects of the quantity and quality of green innovation.

While China's economy is developing rapidly, the problem of carbon emissions is indeed more prominent. The development of green finance is conducive to supporting environmental improvement and enhancing carbon productivity. Most of the existing literature examines the relationship between green innovation and carbon productivity from the perspectives of industrial structure, technological innovation, and economic growth. However, the mechanism by which green finance (GF) affects carbon productivity and whether there is heterogeneity remains unclear. Therefore, this study utilizes panel data from 277 cities from 2010 to 2020 and employs a mediation effect model to investigate the relationship between GF and carbon productivity. The results of the study found that GF has a positive U-shaped association with carbon productivity. The quantity and the quality of green innovation have a mediating effect on the above relationship. It may be due to the fact that GF promotes the green transformation and sustainable development of the economic structure by supporting green industry and technological innovation, which provides strong support to enhance carbon productivity. In non-resource cities, the impact of GF on carbon productivity is more obvious through improving the quality of green innovation, probably because non-resource cities have the advantages of a diversified industrial structure, stronger innovation capacity, and easier access to policy support and market mechanism support than resource cities. The quantity and the quality of green innovation in the eastern, central, and western regions all play a mediating role. The findings provide policymakers with recommendations for utilizing GF in a two-carbon environment to achieve sustainable low-carbon development.

Spatiotemporal analysis of the food-related carbon emissions of China: Regional heterogeneity and the urban‒rural divide.

As the world's largest carbon emitter of food systems, China's goal of carbon neutrality cannot be achieved without addressing the issue of food GHGs. Given the knowledge gap in subnational spatiotemporal research on China's food carbon emissions, especially drivers of regional heterogeneity and the urban‒rural divide, this study uses the household metabolism approach, the gray correlation, and logarithmic mean Divisia index decomposition to assess food-related carbon emissions (FCEs) in China, conducts urban‒rural comparisons and quantifies emission drivers across 31 provinces/regions from 1990 to 2022. The data are sourced from authentic and credible government departments. The results indicate a notable increase in FCEs in most provinces for urban regions following periods of slight decline (1990-2001), sharp increase (2001-2016), and slow growth (2016-2022). In contrast, there has been a more pronounced increase in most provinces for rural regions following a phase of slow growth (1990-2002), a marked decline (2002-2012), and a sharp rise (2012-2022). Among others, per capita carbon emissions from plant-based foods decreased from 345.79 kg in 1990 to 262.70 kg in 2022, whereas emissions from animal-based foods increased from 90.78 kg to 284.39 kg over the same period, suggesting that dietary changes have been a major contributor. Clustering based on the gray correlation further confirms the large interprovincial heterogeneity and significant urban‒rural divide. Regardless of cluster and stage, affluence consistently and significantly drives the growth of FCEs in urban/rural areas, whereas food consumption intensity consistently and significantly contributes to this reduction. The Engel coefficient reduces carbon emissions by a large amount, and the carbon emission factor increases urban/rural FCEs, albeit by a small amount. Consumption willingness reduces FCEs in urban areas but increases FCEs in rural areas in most stages. These findings can aid policy-makers in designing emission reduction policies tailored to the local context.

Impact of urban-rural development and its industrial elements on regional economic growth: An analysis based on provincial panel data in China.

Urban-rural development is an important driving force for regional economic growth. The existing researches have studied this issue from various perspectives, but they ignore the impact of big data on the economy. In the post pandemic era, big data, as an emerging production factor, has a significant indicative effect in promoting urban-rural economic recovery and fostering new business forms. Therefore, fully considering the factor of big data can help reveal its impact mechanism on urban-rural economic growth in the post-epidemic period. Based on the data of 30 provinces and cities in China, this paper introduced big data on the basis of traditional models and constructed a multi-dimensional factor indicator system. At the same time, the panel regression model was established by using unit root test, Hausman test and precision test. Through benchmark regression and heterogeneity analysis, the impact of urban-rural development factors on economic growth was discussed. The results showed that the panel model passed all tests, and its regression error was stable below 5 %. Transportation, technology, and the three major industries can all promote positive economic growth, with a significance of 1 %. The three industries' contribution to economic growth ranks the third, second and first industries in order. In addition, the good ecological environment contributes to the benign economic growth during the study period. A 1 % increase in forest cover would drive economic growth by 0.215 %. But the impact of public's attention on the overall economy was an indirect effect manifested through its physical industries.The regional heterogeneity indicated that each element had different effects on economic development in eastern, central and western regions. Based on its results, this paper proposed suggestions for each region. In addition, this study found that the Internet attention reflected by big data did not directly drive economic growth, but affected economic growth through indirect channels such as information flow and resource allocation of real industries. This study provided data support for the existing theoretical review, and provided policy reference for the rational planning and industrial layout of China's regional economy.

The genomics and physiology of abiotic stressors associated with global elevational gradients in Arabidopsis thaliana.

Phenotypic and genomic diversity in Arabidopsis thaliana may be associated with adaptation along its wide elevational range, but it is unclear whether elevational clines are consistent among different mountain ranges. We took a multi-regional view of selection associated with elevation. In a diverse panel of ecotypes, we measured plant traits under alpine stressors (low CO2 partial pressure, high light, and night freezing) and conducted genome-wide association studies. We found evidence of contrasting locally adaptive regional clines. Western Mediterranean ecotypes showed low water use efficiency (WUE)/early flowering at low elevations to high WUE/late flowering at high elevations. Central Asian ecotypes showed the opposite pattern. We mapped different candidate genes for each region, and some quantitative trait loci (QTL) showed elevational and climatic clines likely maintained by selection. Consistent with regional heterogeneity, trait and QTL clines were evident at regional scales (c. 2000 km) but disappeared globally. Antioxidants and pigmentation rarely showed elevational clines. High elevation east African ecotypes might have higher antioxidant activity under night freezing. Physiological and genomic elevational clines in different regions can be unique, underlining the complexity of local adaptation in widely distributed species, while hindering global trait-environment or genome-environment associations. To tackle the mechanisms of range-wide local adaptation, regional approaches are thus warranted.

La diversidad fenotípica y genómica en Arabidopsis thaliana puede estar asociada con la adaptación a lo largo de su amplio rango de elevación, pero no está claro si la variación asociada a la elevación es consistente entre diferentes cadenas montañosas. Investigamos la selección asociada con la elevación tomando una visión multiregional. En un panel diverso de ecotipos, medimos fenotipos bajo condiciones estresantes alpinas (baja presión parcial de CO2, mucha luz y congelación nocturna) y realizamos estudios de asociación con el genoma. Encontramos evidencia de clinas de elevación regionales contrastantes. Los ecotipos del Mediterráneo occidental mostraron una eficiencia de uso de agua baja/floración temprana en elevaciones bajas y una eficiencia de uso de agua alta/floración tardía en elevaciones altas. Los ecotipos de Asia Central mostraron el patrón opuesto. Mapeamos diferentes genes candidatos para cada región, y algunos locus mostraron variación en elevación probablemente mantenida por selección. De acuerdo con heterogeneidad regional, las clinas de fenotipo y de frecuencia alélica fueron evidentes a escalas regionales (~2000 km) pero desaparecieron a nivel global. Los antioxidantes y la pigmentación rara vez mostraron clinas, aunque los ecotipos de alta elevación del este de África podrían tener una mayor actividad antioxidante bajo congelación nocturna. Las clinas de elevación fisiológicas y genómicas en diferentes regiones pueden ser únicas, lo que subraya la complejidad de la adaptación local en especies ampliamente distribuidas, al tiempo que obstaculiza las asociaciones globales fenotipo­ambiente o genoma­ambiente. Por lo tanto, para abordar los mecanismos de adaptación local a gran escala, se necesitan enfoques regionales.

Global insights on the impact of digital infrastructure on carbon emissions: A multidimensional analysis.

With the swift expansion of global digital infrastructure, understanding its impact on carbon emissions is essential for addressing global warming. This study develops a digital infrastructure indicator system. We use panel data from 83 countries spanning 2005 to 2021 to thoroughly examine the effects and underlying mechanisms of digital infrastructure on carbon emissions. Our findings indicate that digital infrastructure contributes to an increase in carbon emissions worldwide. Mechanism tests suggest that this increase is facilitated by capital agglomeration and fossil energy consumption. However, the impact of digital infrastructure on carbon emissions shows regional variations. In the Arab region, digital infrastructure development seems to reduce carbon emissions, a trend also observed, albeit potentially, in the CIS, Africa, and the Americas. In contrast, Europe and the Asia-Pacific experience a significant surge in carbon emissions due to digital infrastructure. Population density and the proportion of renewable energy emerge as critical threshold variables. Beyond a certain population density, the impact on carbon emissions intensifies, whereas an increase in renewable energy share beyond a specific point mitigates this effect. Robustness tests confirm that digital infrastructure elevates both per capita carbon emissions and carbon intensity, with digital markets and technologies notably amplifying carbon emissions.

The impact of residential environment on stroke onset and its spatial heterogeneity: A multiscale exploration in Shanghai.

BACKGROUND: Stroke is a worldwide concern due to its high disability and mortality rates, especially in many countries entering ageing societies. This study aims to understand the spatial heterogeneity of stroke onset and residential environment influence scopes from multiscale. METHODS: The 2013 to 2022 spatiotemporal distribution pattern of stroke onset was obtained via out-patient data from a hospital in Shanghai. Then nine residential environmental factors were selected to estimate the association of stroke onset by multiscale geographically weighted regression (MGWR), in three scenarios. RESULTS: Accessibility to pubs/bars (PUB) and building density (BD) were the top two residential environmental factors both for the entire sample and by gender. Stress-related environmental factors have a greater impact on the onset of stroke in men but are limited in scope. The population of elderly people have relevance to environmental variables heterogeneity. The indicators relating to unhealthy food and alcohol suggest that habit-inducing environmental factors have a limited impact on stroke onset, but rather that pre-existing habits play a greater role. CONCLUSIONS: MGWR analyses individual components across multiple bandwidths, revealing geographical disparities in the impact of elements that would otherwise be undetected on a global scale. Environmental factors have a limited impact on the onset of stroke. When society is faced with both heavy ageing and fiscal constraints, some of the blue-green space budgets can be scaled back to invest in more secure facilities.

How does urbanization impact China's carbon emissions: A regional heterogeneity perspective.

In the context of China's green development and "dual carbon" goal, urbanization, as a way to achieve Chinese modernization, has a particularly important effect on green and low-carbon economic development. Firstly, this paper empirically analyzed the influence of urbanization on per capita carbon emissions using Chinese city data and a panel fixed-effects model. Then, the impact mechanisms of urbanization on carbon emissions were examined from both the demand and supply sides. Finally, we analyzed the differences in the transmission mechanisms of urbanization affecting carbon emissions in the eastern, central, and western regions. The results show that (1) urbanization increases per capita carbon emissions. However, this effect shows inter-regional differences, with more significant promotion effects in the eastern and central regions; (2) on the demand side, the residents' consumption intensity can drive carbon emissions, while the rise of human capital agglomeration suppresses carbon emissions; on the supply side, industrial structure can drive carbon emissions, while the increase of green technological innovation suppresses carbon emissions; (3) the consumption effect and the industry effect play a major role in the eastern and central regions, while the intermediary effect is not obvious in the western region. This study can provide important insights for synergizing urbanization and achieving carbon reduction commitments.

Study on factors influencing carbon dioxide emissions and carbon peak heterogenous pathways in Chinese provinces.

Implementing a Carbon Peak Action Plan at the regional level requires comprehensive consideration of the developmental heterogeneity among different provinces, which is an effective pathway for China to realize the goal of carbon peak by 2030. However, there is currently no clear provincial roadmap for carbon peak, and existing studies on carbon peak pathways inadequately address provincial heterogeneity. Therefore, this paper employs the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to decompose assess 8 factors influencing carbon emissions of 30 provinces. According to scenario analysis, the paper explores the differentiated pathways for provincial carbon peaks based on policy expectation indicators (including population, economy, and urbanization rate) and comprises policy control indicators (including the energy structure, energy efficiency, industrial structure, transportation structure, and innovation input). The results indicate that population, per capita GDP, urbanization rate, and innovation input are the primary factors for influencing (negatively) the growth of carbon emissions. In contrast, the optimization and upgrading of the industrial structure, energy intensity, energy structure, and transportation structure have mitigating effects on carbon emissions, especially for the first two factors. The forecasting results reveal that robust regulations of the energy and industry can effectively accelerate carbon peak at a reduced magnitude. If developed at BAU, China cannot achieve carbon peak by 2030, continuing an upward trend. However, by maximizing the adjustment strength of energy and industrial transformation within the scope of provincial capabilities, China could achieve carbon peak as early as 2025, with a peak of 12.069 billion tons. In this scenario, 24 provinces could achieve carbon peak before 2030. Overall, this study suggests the feasibility of differentiated pathway to achieve carbon peaks in China, exploring the carbon peak potential and paths of 30 provinces, and identifying provinces where carbon peak is more challenging. It also provides a reference for the design of carbon peak roadmaps at both provincial and national levels and offers targeted recommendations for the implementation of differentiated policy strategies for the government.

The Impact of digital finance on rural energy poverty-empirical evidence from rural China.

It is of critical importance to address energy poverty in rural areas if inclusive prosperity is to be achieved. Digital finance offers new opportunities to alleviate energy poverty in these regions. However, previous studies have mainly focused on the impact of digital finance on poverty, neglecting research on its impact in rural areas and on specific forms of poverty. This study aims to fill this gap by investigating the impact of digital finance on rural energy poverty. The period 2011-2021 was selected as the observation period, with 31 provinces serving as the study objects. The fixed effects model was employed to investigate the impact of digital finance on rural energy poverty, while exploring the mediating effect. The results indicate that digital finance alleviates the level of rural energy poverty, and this conclusion remains valid following a series of robustness tests. Furthermore, digital finance can indirectly alleviate rural energy poverty through technological innovation and agricultural entrepreneurship activities. Further research indicates that the impact of digital finance on rural energy poverty is more pronounced in regions with abundant human capital, robust government intervention, and minimal urban-rural disparities. This study extends the theoretical support for digital finance to indirectly support rural energy to alleviate poverty. Likewise, this finding provides a new perspective for the government and relevant departments to improve the welfare of residents and alleviate rural energy poverty.

An evaluation of the regional heterogeneity of museums' operational efficiency and productivity changes across Chinese provinces.

Museums are critical in safeguarding cultural heritage and cultivating community educational opportunities. This research aims to evaluate operational efficiency (OE), the impact of technological change on total factor productivity change (TFPC), and the regional heterogeneity of museum performance in three regions and 31 provinces across China. To this end, the study employed DEA-SBM and the Malmquist Productivity Index to gauge OE, TFPC, and determinants of TFPC (efficiency change or emerging technologies change) across 31 provinces for 2012-2021. Results reveal that the average OE of the Chinese Museum is 0.8394. It shows a 16.06 % growth potential in the operational efficiency of Chinese Museums. Further, the OE of Chinese Museums declined over the study period from 0.8965 in 2012 to 0.8088 in 2021. Beijing, Fujian, and Hunan are ranked top with a Museum's OE Score of 1. The average MI score of Chinese Museums is 0.9744, and technology change is the main determinant of Decline in productivity change as EC = 0.9992 is greater than TC = 0.9846. The MI of Liaoning, Shanghai, Ningxia, Jiangxi, Chongqing, Sichuan, Guangdong, and Tianjin is over 1, indicating growth in total factor productivity over the study period. The eastern region of China shows higher operational efficiency and total factor productivity scores of museums than the central and western regions. The results of the Kruskal-Wallis test proved that a statistically significant difference exists among different regions of China for the OE, MI, EC, and TC of museums.

Structural effects of provincial digital economy on carbon emissions within China: A multi-region input-output based structural decomposition analysis.

The digital economy, serving as a new engine to boost China's economic growth, inevitably affects carbon emissions given both its green features and its potential demands for energy inputs. To investigate the province-level impacts of the digital economy on carbon emissions, this study splits the digital industry from the multi-regional input-output table, and adopts a downscale structural decomposition analysis to reveal the technological, structural, and scale effects of the digital economy on carbon emissions. The results show that: (1) the expansion of digital economy increased 186.3 Mt of carbon emissions at the aggregate level during the investigated period (2012-2017) and that, therefore, the direct structural effects of the digital economy played a leading role in emission reduction (-156 Mt); (2) in terms of heterogeneity, most provinces presented a U distribution with the structural mitigation effect at the bottom and highly-developed provinces generated significant negative spillover effects; (3) from a regional coordination perspective, digital production achieved greater carbon emission reductions in the eastern and western areas of the country, while the northeastern and central regions gained environmental benefits via digital applications. The main conclusions thus enhance existent understanding of China's digital economy and low-carbon development, and the paper also proffers corresponding policy recommendations, e.g., accelerating the convergence of digital economy and traditional industries to promote carbon emissions reduction.

Construction of China's food security evaluation index system and spatiotemporal evolution.

Food security is a vital material foundation for a nation's development and has been a topic of significant concern on the international stage in recent years. With a population exceeding 1.4 billion, China is not only a major producer but also a substantial consumer of food. Ensuring food security in China is not only a top priority for its socio-economic development but also a driving force in maintaining the stability of the global food supply chain and reducing the number of hungry people worldwide. However, a lack of comprehensive research into the Chinese food security system remains. This study addresses this gap by constructing a comprehensive evaluation framework encompassing four dimensions: food supply, accessibility, production stability, and sustainability. Utilizing the Moran's Index and generating LISA (Local Indicators of Spatial Association) maps, we analyze the spatial correlations of food security. The Dagum Gini coefficient and kernel density estimation are applied to assess heterogeneity and spatial disparities. Furthermore, this research employs the Exponential Smoothing (ETS) model to forecast food security trends. The findings reveal that the overall composite food security score exhibited fluctuations, initially increasing and reaching its peak of 0.407 in 2003, followed by a subsequent sharp decline after 2019. Spatially, food security exhibits correlations, with the Huang-Huai-Hai Plain and Northeast regions consistently showing high-high clustering. In contrast, the Western and Southern regions exhibit low-low clustering at specific periods. The Dagum Gini coefficient indicates that overall food security disparities are relatively small. However, these disparities have gradually expanded in recent years, with inter-group differences becoming predominant after 2005. As indicated by the kernel density estimation, the dynamic distribution of food security initially widens and then narrows, suggesting a shift from dispersed to concentrated data distribution. This phenomenon is accompanied by polarization and convergence trends, particularly evident after 2015. According to the ETS model, the study forecasts a substantial risk of declining food security in China over the next decade, largely influenced by the ongoing pandemic. In conclusion, this research provides a comprehensive assessment of the changing status of food security in China. It offers early warnings through predictive analysis, addressing the existing research gaps in the field of food security.

Enhancing environmental sustainability in transferred farmlands through rural e-commerce: insights from China.

The issue of farmers neglecting environmental concerns in transferred farmlands poses a serious challenge, contradicting the long-term ecological goals of establishing resource-efficient and environment-friendly agriculture. Amidst the pivotal trend of moderately scaled agricultural operations, rural e-commerce holds promise as a catalyst and driving force for enhancing long-term environmental governance of transferred lands. The effectiveness and mechanisms of this potential, however, remain to be empirically examined. This study gathers panel data on environmental positive and negative externalities from six provinces in China, spanning the period from 2013 to 2022, encompassing 6372 farmers. A quasi-natural experiment of farmers' e-commerce participation is designed using difference-in-differences methodology (DID), propensity score matching (PSM), and moderating models. The primary findings are as follows: E-commerce participation increases farmers' positive environmental inputs on transferred lands, such as water-saving irrigation, adoption of social services, and preservation of traditional varieties. Simultaneously, it decreases negative environmental inputs, such as the consumption of fertilizers, pesticides, and agricultural films. The environmental sustainability effects of e-commerce vary across the eastern, central, and western regions of China. E-commerce has a more pronounced impact on agricultural social services and chemical pollutants in the eastern and central regions, while its influence is more significant on water-saving irrigation and variety preservation in the western region. Land transfer forms and supply order contracts do not directly promote farmers' environmentally friendly cultivation practices. Instead, they catalyze the environmental effects of e-commerce through a significant positive interaction term. These conclusions hold after matching for e-commerce participation propensity, while passing sensitivity tests, parallel trend tests, and placebo tests. Consequently, rural e-commerce, without compromising farmers' income, enhances the proactiveness of farmers in environmental conservation, transforms agricultural management practices, and effectively reduces rural non-point source pollution. Policy recommendations include reducing institutional barriers to rural e-commerce participation at the national level, encouraging the establishment of region-specific agricultural environmental sustainability goals, and leveraging the rural e-commerce industry chain to establish a nationwide environmental credit database and incentive mechanism.

Household size and transport carbon emissions in China: Direct, heterogeneity and mediating effects.

Shrinking household sizes presents a significant sustainable challenge by reducing the sharing of means of transportation and increasing individual resource consumption and carbon emissions. Research from the historical literature reveals that larger households generally exhibit lower per capita energy consumption and carbon emissions. However, it remains uncertain how widely these trends extend and their implications for carbon emissions within the expanding transportation industry. This paper employs inter-provincial data from China spanning 2003-2021 to investigate the effects, regional heterogeneity, and mechanisms by which household size influences carbon emissions from the transport sector. The findings show that the expansion of household size in China significantly reduces carbon emissions from transport by 0.2805 %. Households with 2 to 4 members are more effective in achieving transport carbon emission reductions, with an average reduction level of 0.1853 %. Moreover, in terms of geographic factors, reducing transport carbon emissions is more effective in low-density areas than in high-density areas. At the income and carbon emissions level, household size significantly reduces transport carbon emissions in high-income and low-emission regions, and to a lesser extent in low-income and high-emission regions. Additionally, the study revealed that transport consumption expenditure and energy consumption indirectly strengthen the effect of household size on reducing transport carbon emissions. Future sustainable development strategies should focus on regulating household size and promoting moderate household size to decrease personal resource consumption and transportation carbon emissions, and to achieve the objective of sustainable development.

The economic effect of financial compensation in China's healthcare system: comprehensive insights regarding supply and demand factors.

OBJECTIVES: We aim to analyse the effects of government subsidies on residents' health and healthcare expenditure from the perspectives of supply and demand. DATA AND METHODS: According to the regional division adopted in the data query system of the National Bureau of Statistics, this study divides 31 provinces and cities into three regions: eastern, central, and western. The data used are from public databases, such as the "China Statistical Yearbook," "China Health Statistical Yearbook," and "Government Final Account Report". In this study, mathematical model derivation is used to construct a fixed effects model, and an empirical study based on cross-sectional data and general linear regression is conducted. To prevent endogeneity issues, this study introduces instrumental variables and uses 2SLS regression to further analyse the output results. RESULTS: For every 1% increase in supplementary funding on the supply side, the perinatal mortality rate decreases by 1.765%, while for every 1% increase in financial compensation on the demand side, per capita outpatient expenses increase by 0.225% and per capita hospitalization expenses increase by 0.196%. Regarding medical resources, for every 1% increase in the number of beds per 1,000 people, per capita hospitalization expenses decrease by 0.099%. In the central and eastern regions, where economic levels are higher, supply-side government funding is more effective than demand-side funding. In contrast, demand-side funding is more effective in the western region. CONCLUSIONS: The roles of multiple influencing factors and significant regional heterogeneity are clarified. Increasing financial compensation to providers positively impacts perinatal mortality but leads to higher per capita outpatient and hospital expenditures. Finally, this study provides targeted policy recommendations and solid theoretical support for policymakers.

A comparison of brain retraction mechanisms using finite element analysis and the effects of regionally heterogeneous material properties.

Finite element (FE) simulations of the brain undergoing neurosurgical procedures present us with the great opportunity to better investigate, understand, and optimize surgical techniques and equipment. FE models provide access to data such as the stress levels within the brain that would otherwise be inaccessible with the current medical technology. Brain retraction is often a dangerous but necessary part of neurosurgery, and current research focuses on minimizing trauma during the procedure. In this work, we present a simulation-based comparison of different types of retraction mechanisms. We focus on traditional spatulas and tubular retractors. Our results show that tubular retractors result in lower average predicted stresses, especially in the subcortical structures and corpus callosum. Additionally, we show that changing the location of retraction can greatly affect the predicted stress results. As the model predictions highly depend on the material model and parameters used for simulations, we also investigate the importance of using region-specific hyperelastic and viscoelastic material parameters when modelling a three-dimensional human brain during retraction. Our investigations demonstrate how FE simulations in neurosurgical techniques can provide insight to surgeons and medical device manufacturers. They emphasize how further work into this direction could greatly improve the management and prevention of injury during surgery. Additionally, we show the importance of modelling the human brain with region-dependent parameters in order to provide useful predictions for neurosurgical procedures.

Ecological niches and assembly dynamics of diverse microbial consortia in the gastrointestine of goat kids.

Goats are globally invaluable ruminants that balance food security and environmental impacts, and their commensal microbiome residing in the gastrointestinal tract (GIT) is associated with animal health and productivity. However, the reference genomes and functional repertoires of GIT microbes in goat kids have not been fully elucidated. Herein, we performed a comprehensive landscape survey of the GIT microbiome of goat kids using metagenomic sequencing and binning, spanning a dense sampling regime covering three gastrointestinal compartments spatially and five developmental ages temporally. We recovered 1002 high-quality metagenome-assembled genomes (termed the goat kid GIT microbial catalog [GKGMC]), 618 of which were novel. They encode more than 2.3 million nonredundant proteins, and represent a variety of carbohydrate-degrading enzymes and metabolic gene clusters. The GKGMC-enriched microbial taxa, particularly Sodaliphilus, expanded the microbial tree of life in goat kids. Using this GKGMC, we first deciphered the prevalence of fiber-degrading bacteria for carbohydrate decomposition in the rumen and colon, while the ileal microbiota specialized in the uptake and conversion of simple sugars. Moreover, GIT microorganisms were rapidly assembled after birth, and their carbohydrate metabolic adaptation occurred in three phases of progression. Finally, phytobiotics modified the metabolic cascades of the ileal microbiome, underpinned by the enrichment of Sharpea azabuensis and Olsenella spp. implicated in lactate formation and utilization. This GKGMC reference provides novel insights into the early-life microbial developmental dynamics in distinct compartments, and offers expanded resources for GIT microbiota-related research in goat kids.

Research on the impact and mechanism of digital capabilities and digital finance on household wealth in the context of aging.

China has entered a period of synchronous development between digitalization and aging. Based on the data from the China Household Finance Survey (CHFS), the partial least squares structural equation model (PLS-SEM) and multi-group analysis were used to analyze the impact mechanism of digital capabilities and digital finance on the wealth of elderly households. The results indicate that digital capabilities and digital finance can improve the wealth level of households headed by the elderly through direct and indirect paths. The indirect effects of digital capabilities and digital finance on elderly household wealth are all exerted through the node of business and property income, and entrepreneurship/investment are mediating variables. Moreover, digital capabilities have a greater impact on the wealth of elderly households in the central and western China regions, while digital finance has a greater impact in the eastern China regions. In addition, there is no significant difference in the effect of digital capabilities on business and property income across regions, while digital finance has a larger effect in the eastern region. The above conclusions can provide theoretical and practical support for realizing active aging and common prosperity in different countries and regions.

Testing for stationary of housing prices in China: An examination using efficient unit root tests.

Changes in housing prices affect all aspects of production and life, and have always been a hot spot of social concern. This paper uses the sequence panel selection method (SPSM) to study the time series properties of housing prices in 100 cities in China from June 2010 to December 2022. It is found that there are large differences in the stationary of housing prices in first/second/third-tier cities. Using the SPSM test method, it is found that housing prices in first-tier cities are all non-stationary series, the samples of second- and third-tier cities can be significantly divided into stable housing prices and non-stable housing prices. After further using the Fourier function to approximate the structural mutation of the data, more second-tier cities show stable housing prices, while less third-tier cities show stable housing prices. These findings provide an important decision-making basis for the government to implement regulatory policies according to local conditions based on the differential characteristics of changes in housing prices.

Influence mechanism of green finance on regional emission reduction.

The implementation of green finance is crucial in achieving a reduction in regional emissions. As such, understanding how green finance affects regional emission reduction is essential. Using provincial panel data from 2008 to 2019, we employed the fixed effects model to examine the impact of green finance on regional emission reduction. The empirical results reveal the following: (1) Green finance has a negative effect on sulfur dioxide intensity, and the development of green finance can significantly reduce the emission of regional pollutants. (2) Among the different instruments of green finance, green credit and green investment exhibit more substantial emission reduction effects than green securities and green insurance. (3) The mechanism by which green finance affects regional emission reduction is mainly through the advanced industrial structure and green technology innovation. (4) The development of green finance shows geographical discrepancies: The eastern region of China is more effective in reducing emissions than the central and western regions. To fully maximize the role of green finance in emission reduction, this paper offers pertinent suggestions for strengthening the green financial system, improving the advanced industrial process, increasing investment in green energy technology, and formulating specific development tactics that consider the prominent characteristics of distinct regions.