Search Results (14,878)

In the context of global climate change and industrial low-carbon transition, whether environmental taxes can simultaneously promote environmental and economic benefits by stimulating corporate green investment remains a central issue in academic research. Existing studies have reached mixed conclusions regarding the effects of environmental taxes, emphasizing either the “innovation compensation” effect or the “crowding-out” effect. However, this binary perspective overlooks the internal boundary conditions under which environmental taxes operate, particularly the roles of market competition and firm-level resource endowments. In particular, limited attention has been paid to how competitive market environments shape firms’ responses to environmental regulation. To address this gap, this study develops an integrated analytical framework that combines external market competition with internal firm endowments. Using China’s 2018 Environmental Protection Tax Law as a quasi-natural experiment and a panel dataset of Chinese listed firms from 2009 to 2024, this study employs a Difference-in-Differences (DID) approach to examine the impact of environmental taxation on corporate green investment. The results show that: (1) the environmental protection tax significantly promotes corporate green investment, with substantial heterogeneity across firm size, ownership structure, and regional institutional environments; (2) market competition serves as an important external moderating mechanism, as intensified competition strengthens firms’ incentives to pursue technological differentiation through green investment, thereby generating an “escape-competition effect”; and (3) from an internal perspective, the effectiveness of environmental taxation is also shaped by firm endowments. High investment activity provides the necessary resource buffer to support strategic pivots, whereas rapid revenue growth and high financial slack (excessive cash ratio) generate strategic inertia, thereby attenuating firms’ responsiveness to the tax shock. This study not only provides empirical evidence from China on the mechanisms through which environmental taxes influence corporate green transformation, but also offers important policy implications for improving environmental tax systems in other countries. Full article

Maternal hemorrhage (MH) remains a leading preventable cause of maternal health, yet global disparities on its burden remain poorly quantified. Using the Global Burden of Disease 2021 data, we analyzed global, regional, and national trends in age-standardized maternal mortality ratio (ASR_MMR) attributed to MH from 1990 to 2021. We applied Joinpoint regression, age–period–cohort modeling, inequality indices and frontier analysis. This descriptive–analytical ecological study is based on modeled secondary data. Globally, the proportion of ASR_MMR attributed to MH declined from 33.31% in 1990 to 24.52% in 2021 (relative reduction: 24.24%). ASR_MMR attributed to MH consistently declined, with an estimated annual percentage change (EAPC) of −3.17 (95% UI: −3.42, −2.91). In 2021, Central and West Africa countries reported ASR_MMR attributed to MH exceeding 300 per 100,000 live births, while the Caribbean experienced a temporary increase. ASR_MMR attributed to MH was strongly inversely correlated with the socio-demographic index (SDI). Absolute inequality (slope index of inequality) narrowed by 49.4%, while relative inequality (concentration index) increased by approximately 27.5%. Countries with the largest negative deviations from the frontier included Somalia, the Central African Republic, Chad, Nigeria, and Afghanistan. While substantial global progress has been made, socioeconomic inequities continue to drive persistent disparities in MMR attributed to MH. Policies must not only address average reductions but also the widening relative gap between advantaged and disadvantaged populations. Full article

From the Red Shirt heartlands of the North and Northeast to the conservative South and the fragmented middle-class electorate of Bangkok, Thailand’s regional divisions reflect a deeply contested relationship with centralized power. How these divisions shape citizens’ relative trust in local versus central government remains an open empirical question. Drawing on three waves of the Asian Barometer Survey conducted between 2014 and 2022 (pooled N = 3600), this study examines whether territorial location produces differential trust in local relative to central government. The findings are mixed. Regional differences are observable in baseline models, but their explanatory power diminishes once individual-level evaluations of political institutions and economic conditions are taken into account. Rural residents exhibit a smaller trust gap, indicating a weaker relative preference for local over central government, consistent with central welfare transfers sustaining support for the central tier. At the contextual level, higher regional poverty rates are associated with a compression of the trust gap between levels of government. Once poverty is introduced, the overall temporal increase observed by 2022 is no longer statistically significant. Structural economic geography explains much of the aggregate shift. Regional dynamics, however, are not uniform. The Northeast diverges sharply in the final wave, and the pattern holds across model specifications. The shift points to accumulated political alienation rooted in repeated episodes of electoral disenfranchisement. The findings carry direct implications for decentralization policy and territorial development strategy. Where regional trust gaps are driven by fiscal constraints on local government and accumulated political alienation, administrative redesign alone cannot restore citizen confidence in sub-national governance. Full article

Background and Objectives: To evaluate two-year functional, anatomical, and patient-reported outcomes after bilateral implantation of a diffractive implantable phakic contact lens (IPCL) for presbyopia correction in myopic patients within a high–solar-radiation Atlantic island environment. Methods: This retrospective observational study included 11 presbyopic myopic patients aged 40–50 years (22 eyes) who underwent bilateral diffractive IPCL implantation and completed a 2-year follow-up. Monocular defocus curves were recorded from +3.0 to −5.0 D and converted to logMAR. Functional visual range and area under the defocus curve (AUC) were calculated. Anatomical stability was assessed by central vault, pupil diameter, and crystalline lens rise measurements. Safety evaluation included slit-lamp examination for crystalline lens transparency and corneal integrity. Patient-reported outcomes were measured using the Quality of Vision (QoV) and Catquest-9SF questionnaires. Environmental parameters during implantation and follow-up were characterized using regional meteorological data. Results: Mean visual acuity remained ≤0.14 logMAR up to −2.5 D of defocus, with functional vision (≤0.2 logMAR) extending to approximately −3.0 D in about half of the eyes. Median vault at 2 years was 546 µm (IQR 361.5–667.3 µm). No cases of clinically significant cataract or corneal compromise were observed. QoV scores were low (1.41 ± 0.43) and Catquest-9SF scores high (3.70 ± 0.18), with no strong correlations between subjective and anatomical metrics. Visual performance remained stable within a consistent high-solar-radiation and atmospheric light-scattering environment. Conclusions: Diffractive IPCL implantation was associated with stable anatomical positioning, sustained functional visual performance across distances, and favorable patient-reported outcomes at 2 years. Within a consistent real-world environmental context, these findings provide a descriptive framework for understanding diffractive IPCL performance, while larger prospective studies are warranted. Full article

China’s inland regions are vital for territorial spatial planning and sustainable development due to their abundant resources. However, the dynamic coordination between natural resource utilization (NRU) and ecological resilience (ER) remains poorly understood. Using panel data from 20 inland provinces in China (2009–2023), this study constructs NRU and ER evaluation systems, with ER assessed through the Pressure–State–Response (PSR) framework. Indicator weights are determined using an AHP–entropy method. Kernel density, panel vector autoregression (P-VAR), and coupling coordination models are applied to examine spatiotemporal evolution patterns, coordination levels, and interaction mechanisms between NRU and ER. The results show that: (1) The NRU index rises overall, peaking around 2020 (0.706), while the intensity of resource development continues to decline. Regional disparities widen, resulting in a spatial pattern of development intensity that was higher in the west and lower in the east. (2) The ER index continues to rise, accelerating at certain stages, and reaches a peak (0.723) between 2018 and 2020. Geographically, the eastern region led the way, with values decreasing in a stepwise manner, and regional disparities showed relatively gradual changes. (3) The degree of coordination between the two continues to improve, evolving from a “low level of dispersion” to a “medium-to-high level of concentration.” This has resulted in a pattern where the eastern region leads, followed by the central and southwestern regions in succession. Specifically, the EC index rose from 0.429 to 0.615, and the CC index rose from 0.384 to 0.533. Eastern and Central China have already reached a medium level of coordination, while Northwest and Southwest China remain primarily at a basic level of coordination. (4) Significant bidirectional dynamic interactions exist between the NRU and ER, with asymmetric pathways. By region, the NE, EC, and NC exhibit greater fluctuations and higher system sensitivity, while the CC experiences more concentrated short-term shocks; the SW and NW exhibit relatively smoother responses and converge more rapidly. Policy implications highlight the need for region-specific coordination strategies, better alignment between resource development and ecological protection, and enhanced cross-regional governance to support sustainable inland development. Full article

Amid rapid urbanisation and the associated environmental challenges, such as increased flood risk, the urban heat island effect, and ecosystem degradation, Blue–Green Infrastructure (BGI) has emerged as a vital sustainable development strategy. Some countries have successfully implemented BGI projects, shaped by their unique geographical conditions, socioeconomic contexts, and governance structures. Although the BGI concept is highly relevant worldwide, strategies for integrating BGI into urban environments vary significantly across regions and countries due to their distinct urban structures and spatial planning systems. This study provides a comparative study of BGI implementation into spatial planning systems of Ljubljana (Slovenia) and Kraków (Poland), as Central European cities, and Shanghai and Guangzhou, as Chinese cities. Through a systematic analysis of semi-structured interviews with key stakeholders, the study evaluates how different enablers, i.e., (1) guidelines, strategies, and actions, (2) land-use strategy for BGI, and (3) potential of factors for BGI implementation, including planning scale, financial, technical, and spatial, facilitate BGI implementation. This comparative study reveals contrasting yet complementary BGI paradigms, most notably related to top-down versus bottom-up implementation and different prioritisation of BGI functions. These varying paradigms are shaped by specific urban challenges, governance, and spatial planning systems. Full article

Rural sustainable development is a core component of the global Sustainable Development Goals, and building digital villages and enhancing the resilience of rural economies are key pathways for underdeveloped regions to achieve rural sustainable development. The coordination and synergy between these two areas are central to rural revitalization. Taking 122 counties in Hunan Province as research units and using 2013–2023 spatial panel data, this study employs an improved coupling coordination model, spatial autocorrelation analysis and geographically weighted regression to explore their spatiotemporal evolution, clustering patterns and driving factors. The results show that both systems improved steadily: digital villages expanded from core areas, while economic resilience developed more balancedly. The coupling coordination evolved from near-disorder to a pattern characterized by regional equilibrium. The coupling coordination degree displayed significant positive spatial autocorrelation, forming an “High-High (H-H)” cluster in the Changsha-Zhuzhou-Xiangtan-Dongting Lake Plain and an “Low-Low (L-L)” cluster in western Hunan. Driving factors showed marked spatial heterogeneity. These findings provide empirical support for differentiated digital village policies in Hunan. Full article

Amid the ongoing acceleration of climate change over recent decades, extreme precipitation events have become more frequent and intense on a global scale, triggering severe natural hazards and considerable socioeconomic damage. Nevertheless, how extreme precipitation has evolved at the national level over long time spans, and what role atmosphere–ocean teleconnections play in driving regional differences, remains insufficiently explored. This study addresses that knowledge gap by conducting a comprehensive assessment of eight ETCCDI-based extreme precipitation indices (PRCPTOT, CWD, R20, R95p, R99p, RX1day, RX5day, and SDII) across six climatic sub-regions of China (Northeast, North, East, Central South, Northwest, and Southwest) over 1960–2020, drawing on daily records from 695 quality-controlled meteorological stations. Key atmospheric and oceanic circulation drivers were further diagnosed and their joint influence was quantified via multiple wavelet coherence (MWC). The analysis shows that five of the eight indices (CWD, R95p, R99p, RX1day, and RX5day) underwent statistically significant fluctuating changes (p < 0.05) throughout the 61-year record. Seven indices, all except CWD, demonstrated upward tendencies, with mutation points clustering after 2010, most notably between 2011 and 2016. Wavelet power spectra indicates elevated energy concentrations at multiple time scales, although only CWD exhibited a statistically significant periodicity of approximately 8–10 a (p < 0.05 against red noise). In terms of spatial patterns, index magnitudes generally increased along a northwest-to-southeast gradient. Stations registering significant upward shifts were concentrated in East and Central South China, whereas significant downward shifts appeared mainly in North China and the northern portion of East China. An altitude-dependent pattern was also detected: CWD rose with elevation, while the remaining indices declined sharply below 1288 m, fluctuated in the 1288–2090 m band, and dropped again above 2090 m. Wavelet coherence analysis uncovered significant resonance between extreme precipitation and four circulation indices—SCSMMI, WPSHI, PNA, and NAO. MWC further identified three driver combinations—ENSO-PNA, SCSMMI-WPSHI, and ENSO-NAO-EASMI—as the most influential, acting both individually and synergistically. These results furnish an empirical basis for forecasting, preventing, and managing precipitation-related disasters across China under future climate scenarios. Full article

Foot-and-mouth disease (FMD) is a highly transmissible viral infection of livestock that threatens food security and causes substantial economic losses in endemic regions. Despite its economic impact, the role of environmental viral load and wildlife reservoirs in sustaining FMD transmission remains poorly quantified. The aim of this study is to assess the extent to which community viral load sustains FMD persistence and to identify key transmission drivers in a coupled livestock–wildlife–environment system. A Susceptible–Exposed–Infected (SEI) model with a free-living virus compartment was analyzed via the basic reproduction number ($R_0$) and solved numerically using a Nonstandard Finite Difference Method. Sensitivity analysis identified wild host population size, transmission rates, host recruitment, environmental viral decay, and viral load thresholds as major determinants of $R_0$. Results indicate that higher transmission rates accelerate susceptible depletion and increase exposed and infected classes, with wildlife dominating environmental viral contributions. Community viral load is central to sustaining outbreaks and informs targeted control strategies. Full article

Reducing carbon emissions while improving air quality is a central challenge for rapidly urbanizing regions. Focusing on 31 prefecture-level cities in the Middle Reaches of the Yangtze River Urban Agglomeration, this study examines carbon–pollution synergy (CPS), spatial dynamics, and the driving factors of CO₂ and representative air pollutants from 2013 to 2023. Spatial autocorrelation analysis, a revised four-factor Logarithmic Mean Divisia Index (LMDI) decomposition, and a factor-based CPS assessment were used to identify spatial clustering, compare driver heterogeneity, and evaluate coordination between CO₂ and primary pollutants. To improve methodological consistency, the LMDI decomposition and CPS assessment focus on the primary pollutants SO₂, CO, and NO₂, whereas PM_2.5 and O₃ are retained in the spatial analysis and discussion because they are strongly affected by secondary formation, atmospheric transport, and meteorological conditions. The results show that CO₂ and the selected pollutants exhibit significant but pollutant-specific spatial clustering. High CO₂ values remain concentrated in the core cities of Wuhan, Changsha, and Nanchang, PM_2.5 shows a persistent north–south gradient, and SO₂ hotspots shift from traditional industrial cores toward peripheral areas receiving industrial relocation. The revised LMDI results show that economic development is the most stable positive driver of CO₂ and the primary pollutants, whereas the energy-consumption factor generally suppresses emissions. The recalculated population-scale factor fluctuates around 1, indicating a comparatively limited and stage-dependent contribution once the other factors are controlled for. CPS analysis further indicates that coordinated reduction is most robust under the energy-consumption factor and, for conventional combustion-related pollutants, also under the energy-structure factor. Overall, the region has a clear basis for CPS governance, but effective implementation requires pollutant-specific and region-specific control strategies rather than a uniform co-mitigation pathway. Full article

Prestressed centrifugal concrete hollow square piles often require on-site splicing, and the structural reliability of the pile connection largely governs the performance of the assembled pile. To address the limitations of conventional welded and mechanical joints, a section steel plug-in composite joint combining central grouted steel tube anchorage and peripheral end-plate welding was developed and experimentally evaluated. Flexural and shear tests were conducted on 12 full-scale specimens, including pile shaft specimens and joint specimens with cross-sectional side lengths of 400, 500, and 600 mm. The flexural and shear behavior of the jointed specimens was assessed in terms of bearing capacity, load–deflection response, crack development, and failure mode by comparison with the corresponding pile shafts. Under flexural loading, the pile shaft specimens mainly failed by fracture of prestressing steel bars at midspan, whereas the joint specimens failed near the loading point by prestressing steel fracture, indicating that the critical failure region shifted away from the joint core. The flexural capacities of the joint specimens reached about 92–97% of those of the corresponding pile shafts. Under shear loading, both pile shaft and joint specimens mainly exhibited diagonal compression failure in the flexural–shear region, while no obvious damage was observed in the joint core region. The shear capacities of the joint specimens were about 103–130% of those of the corresponding pile shafts. These results indicate that the proposed section steel plug-in composite joint can effectively maintain flexural resistance while enhancing shear performance. The central steel tube, hardened grout, anchorage reinforcement, and peripheral welds jointly contributed to the integrity and force transfer capacity of the connection, showing favorable potential for engineering application in prestressed centrifugal concrete hollow square pile splicing. Full article

To investigate the underlying mechanisms of talent mobility in higher-education institutions influenced by factors such as the development environment, macroeconomic policies, and evaluation mechanisms, this paper proposes a nonlinear stochastic differential equation (SDE) dynamical model that incorporates time delays and multiplicative noise. We analyze the dynamic processes of talent mobility under varying conditions regarding the number of nodes, policy implementation cycles, and noise intensity. First, we employ central manifold theory and stochastic averaging methods to reduce the system to a one-dimensional averaged $It\widehat{o}$ equation. Subsequently, with $\tau$ as a parameter, we conduct an in-depth study of the system’s stochastic bifurcation behavior using the corresponding Fok–Planck–Kolmogorov equations. Finally, we validate the theoretical conclusions through numerical simulations. The results indicate that the number of nodes, policy delay, and noise intensity all have significant effects on system stability; an increasing delay induces random P-bifurcation in the system, and when $N\le 3$ and $N>3$, the system exhibits distinctly different steady-state behaviors. We also found that excessively high noise intensity disrupts system stability, whereas moderate noise intensity has a positive effect on stability. This study not only provides theoretical insights into the dynamic evolution mechanisms of talent mobility in regional universities but also offers valuable guidance for universities in formulating talent recruitment and evaluation policies. The methodology employed in this study opens up a promising avenue for analyzing complex dynamic problems in the field of sociology. Full article

Efficient electricity distribution in rural areas is strongly affected by seasonal agricultural energy demand, particularly in irrigation-intensive regions where electricity consumption increases substantially during summer periods. Conventional transformer operation strategies in such rural grids often fail to adapt to seasonal load variability, leading to unnecessary idle operation, increased technical losses, and reduced infrastructure efficiency. Existing approaches generally rely on static assumptions or simulated data, limiting their ability to represent real irrigation-driven seasonal load asymmetry. To address this issue, this study proposes a data-driven multi-objective seasonal transformer scheduling framework using a bio-inspired Artificial Immune System (AIS) algorithm. The model was developed using two years of empirical hourly SCADA load data and transformer operation records obtained from a real 380/154 kV TEİAŞ transmission substation in Central Anatolia, Türkiye. Hourly SCADA measurements were used for seasonal load characterization and objective-function evaluation, while transformer scheduling decisions were defined at the seasonal operational level. The proposed AIS-based scheduling strategy reduced annual technical energy losses by approximately 5.4 GWh, decreased operational costs by 10.81 million TL (≈360,000 USD), and lowered carbon emissions by about 2270 metric tons of CO₂ compared with conventional static transformer operation. The study presents a proof-of-concept framework integrating empirical SCADA measurements with AIS-assisted seasonal transformer scheduling for practical utility-scale operational planning in irrigation-dominated rural electricity networks. Full article

Ongoing global climate change and intensified human activities have increased the frequency and intensity of droughts, posing a serious threat to global ecosystems and agricultural sustainability. However, the seasonally differentiated effects of droughts on cropland phenology and productivity, especially in Northeast China, remain insufficiently understood, limiting the assessment of agro-ecosystem vulnerability and the development of effective adaptation strategies. In this study, the standardized precipitation evapotranspiration index (SPEI) was used to assess the frequency and severity of extreme drought in Northeast China based on run theory. Cropland phenology parameters and productivity were derived from time-series MODIS normalized difference vegetation index (NDVI), and gross primary productivity (GPP) products, which were smoothed using a Savitzky–Golay (S–G) filter. Correlation analyses were conducted to examine regional associations between SPEI-defined drought conditions and cropland phenology and productivity. Results show that: (1) Drought events occurred frequently in the central and southern parts of Northeast China, particularly in the Songnen Plain (5.22 events per decade) and the Liaohe Plain (4.89 events per decade); (2) the Songnen Plain showed significant increases (Sen’s slope > 0, p < 0.05) across all drought metrics over 2001–2020, which coincided with LOS shortening (−0.18 d a⁻¹) and GPP decline (−9.12 g C m⁻² a⁻¹); in contrast, the Sanjiang Plain exhibited slight declines (Sen’s slope, p > 0.05) in drought metrics, resulting in LOS lengthening (0.06 d a⁻¹) and GPP increases (7.84 g C m⁻² a⁻¹); and (3) drought impacts were strongly season-dependent, with autumn droughts showing a stronger association with reductions in crop productivity in local areas of Northeast China. These findings highlight the need to account for crop responses to drought events, which is essential for developing measures to cope with drought and protecting regional food security. Full article

To better capture ecological quality under aerosol pollution stress, an AOD-integrated Remote Sensing Ecological Index (ARSEI) was developed for the Shenyang Metropolitan Area (2000–2025). Using Google Earth Engine, multi-source MODIS products were compiled to generate an annual growing-season ARSEI through PCA, combining PC1 and PC2 by variance-weighted contributions. Long-term trends were assessed with Theil–Sen slope estimation and the Mann–Kendall test, future persistence with the Hurst index, and drivers with an optimal parameter geographical detector. ARSEI closely matched conventional RSEI in multi-year pixel means (R² = 0.98, p < 0.001) but identified larger “poor” (+0.4%) and “moderate” (+3.4%) areas from 2000 to 2025, indicating higher sensitivity to pollution-related stress. Ecological quality improved overall, with high grades in eastern mountainous forests and low grades in the central built-up core and surrounding croplands. Improvement was dominant (31.08% significant, 38.27% slight), while degradation was limited (4.27% significant, 13.92% slight) and concentrated in peri-urban expansion belts. Elevation was the strongest natural control, whereas land use and population were the leading socioeconomic drivers with increasing influence over time. Finally, we delineated differentiated management zones based on current status and projected trajectories to support targeted regional governance. Full article