Search Results (1,992)

Based on the panel data of daily meteorological stations and winter wheat yield in Henan Province from 2000 to 2023, this study comprehensively used the Mann–Kendall trend test, wavelet coherence analysis (WTC), and other methods to reveal the temporal and spatial evolution of extreme precipitation and its multi-scale stress mechanism on grain yield. The results showed the following: (1) Extreme precipitation showed the characteristics of ‘frequent fluctuation-gentle trend-strong spatial heterogeneity’, and the maximum daily precipitation in spring (RX1DAY) showed a significant uplift. The increase in rainstorm events (R95p/R99p) in the southern region during the summer is particularly prominent; at the same time, the number of consecutive drought days (CDDs > 15 d) in the middle of autumn was significantly prolonged. It was also found that 2010 is a significant mutation node. Since then, the synergistic effect of ‘increasing drought days–increasing rainstorm frequency’ has begun to appear, and the short-period coherence of super-strong precipitation (R99p) has risen to more than 0.8. (2) The spatial pattern of winter wheat in Henan is characterized by the three-level differentiation of ‘stable core area, sensitive transition zone and shrinking suburban area’, and the stability of winter wheat has improved but there are still local risks. (3) There is a multi-scale stress mechanism of extreme precipitation on winter wheat yield. The long-period (4–8 years) drought and flood events drive the system risk through a 1–2-year lag effect (short-period (0.5–2 years) medium rainstorm intensity directly impacted the production system). This study proposes a ‘sub-scale governance’ strategy, using a 1–2-year lag window to establish a rainstorm warning mechanism, and optimizing drainage facilities for high-risk areas of floods in the south to improve the climate resilience of the agricultural system against the background of climate change. Full article

The interface between high-performance thermoelectric materials and electrodes critically governs the conversion efficiency and long-term reliability of thermoelectric generators under high-temperature operation. Here, we propose Al_xCoCrFeNi high-entropy alloys (HEA) as barrier layers to bond Cu-W electrodes with p-type skutterudite (p-SKD) thermoelectric materials. The HEA/p-SKD interface exhibited excellent chemical bonding with a stable and controllable reaction layer, forming a dense, defect-free (Fe,Ni,Co,Cr)Sb phase (thickness of ~2.5 μm) at the skutterudites side. The interfacial resistivity achieved a low value of 0.26 μΩ·cm² and remained at 7.15 μΩ·cm² after aging at 773 K for 16 days. Moreover, the interface demonstrated remarkable mechanical stability, with an initial shear strength of 88 MPa. After long-term aging for 16 days at 773 K, the shear strength retained 74 MPa (only 16% degradation), ranking among the highest reported for thermoelectric materials/metal joints. Remarkably, the joint maintained a shear strength of 29 MPa even after 100 continuous thermal cycles (623–773 K), highlighting its outstanding thermo-mechanical stability. These results validate the Al_xCoCrFeNi high-entropy alloys as an ideal interfacial material for thermoelectric generators, enabling simultaneous optimization of electrical and mechanical performance in harsh environments. Full article

Drought stress is a major environmental constraint that significantly reduces wheat productivity worldwide. In this study, seventeen wheat genotypes were evaluated under well-watered and drought-stressed conditions across two consecutive years (2023–2024) in a controlled greenhouse experiment. Twenty morphological and agronomic traits were recorded, and their responses to prolonged water limitation were assessed using multivariate statistical methods, including three-way ANOVA, principal component analysis (PCA), and cluster analysis. Drought stress significantly decreased all traits except the harvest index (HI), with the most severe reductions observed in traits related to secondary spikes (e.g., grain weight reduced by 95%). The ANOVA results confirmed significant genotype × treatment (G × T) interactions for key agronomic traits, with the strongest effect observed for total grain weight (F = 7064.30, p < 0.001). A PCA reduced the 20 original variables to five principal components, explaining 87.2% of the total variance. These components reflected distinct trait groups associated with productivity, spike architecture, and development in phenology. Cluster analysis based on PCA scores grouped genotypes into three clusters with contrasting drought response profiles. A yield-based evaluation confirmed the cluster structure, distinguishing genotypes with a stable performance (average yield loss ~58%) from highly sensitive ones (~70% loss). Overall, the findings demonstrate that drought tolerance in wheat is governed by complex trait interactions. Integrating a trait-based multivariate analysis with a yield stability assessment enables the identification of genotypes with superior adaptation to water-limited environments, providing an excellent genotype background for future breeding efforts. Full article

Reactions of the angular 4,4′-oxybis[N-(pyridin-3-ylmethyl)benzamide] (L) with dicarboxylic acids and transition metal salts afforded non-entangled {[Cd(L)(1,3-BDC)(H₂O)]∙2H₂O}_n (1,3-BDC = 1,3-benzenedicarboxylic acid), 1; {[Cd(L)(1,4-HBDC)(1,4-BDC)_0.5]∙2H₂O}_n (1,4-BDC = 1,4-benzenedicarboxylic acid), 2; {[Cu₂(L)₂(1,3-BDC)₂]∙1.5H₂O}_n, 3; {[Ni(L)(1,3-BDC)(H₂O)]∙2H₂O}_n, 4; {[Zn(L)(1,3-BDC)]∙4H₂O}_n, 5; {[Zn(L)(1,4-BDC)]∙2H₂O}_n, 6; and [Cd₃(L)₂(1,4-BDC)₃]_n, 7, which have been structurally characterized by using single-crystal X-ray diffraction. Complexes 1–5 and 7 are 2D layers, giving (6⁴·8·10)(6)-2,4L3, (4²·8²·10²)(4²·8⁴)₂(4)₂, (4·5·6)(4·5⁵·6³·7)-3,5L66, (6⁴·8·10)(6)-2,4L3, interdigitated (8⁴·12²)(8)₂-2,4L2 and (3⁶·4⁶·5³)-hxl topologies, respectively, and 6 is a 1D chain with the (4³·6²·8)(4)-2,4C3 topology. The factors that govern the structures of 1–7 are discussed and the thermal properties of 1–7 and the luminescent properties of complexes 1, 2, 5 and 6 are investigated. The stabilities of complexes 1 and 5 toward the detection of Fe³⁺ ions are also evaluated. Full article

Although organizational resilience is well established, refining the systematic quantitative evaluation of health systems resilience (HSR) remains an ongoing opportunity for advancement. Research either focuses on individual HSR indicators, such as social welfare policy, public expenditure, health insurance, healthcare quality, and technology, or broadly examines socio-economic factors, highlighting the need for a more comprehensive methodological approach. This study employed the Slacks-Based Measure (SBM) within Data Envelopment Analysis (DEA) to analyze efficiency by maximizing outputs. It systematically examined key HSR factors across countries, providing insights for improved policymaking and resource allocation. Taking a five-year (2016–2020) dataset that covered 55 to 56 countries and evaluating 17 indicators across governance, health systems, and economic aspects, the paper presents that all sixteen top-ranked countries with a perfect efficiency score of 1 belonged to the high-income group, with ten in Europe, highlighting regional HSR differences. This paper concludes that adequate economic resources form the foundation of HSR and ensure stability and sustained progress. A properly supported healthcare workforce is essential for significantly enhancing health systems and delivering quality care. Last, effective governance and the equitable allocation of resources are crucial for fostering sustainable development and strengthening HSR. Full article

This research examines the compounding risks of global environmental change, including climate change, environmental law, biodiversity loss, and pollution, which threaten the stability of economic systems worldwide. While digital technology and global governance regulation are increasingly being proposed as solutions, their synergistic potential in advancing economic sustainability has been less explored. How can these technologies mitigate environmental risks while promoting sustainable and equitable development, aligning with the Sustainable Development Goals? We analyze policy global environmental data from the World Bank and the United Nations, as well as literature reviews on digital interventions, artificial intelligence, and smart databases. Global environmental change presents economic stability and rule of law threats, and innovative governance responses are needed. This study evaluates the potential for digital technology to be leveraged to enhance climate resilience and regulatory systems and address key implementation, equity, and policy coherence deficits. Policy recommendations for aligning economic development trajectories with planetary boundaries emphasize that proactive digital governance integration is indispensable for decoupling growth from environmental degradation. However, fragmented governance and unequal access to technologies undermine scalability. Successful experiences demonstrate that integrated policies, combining incentives, data transparency, and multilateral coordination, deliver maximum economic and environmental co-benefits, matching digital innovation with good governance. We provide policymakers with an action plan to leverage technology as a multiplier of sustainability, prioritizing inclusive governance structures to address implementation gaps and inform legislation. Full article

This study presents the scientific and methodological foundation of Spain’s first national framework for the ethical management of community cat populations: the Action Plan for the Management of Community Cat Colonies (PACF), launched in 2025 under the mandate of Law 7/2023. This pioneering legislation introduces a standardized, nationwide obligation for trap–neuter–return (TNR)-based management of free-roaming cats, defined as animals living freely, territorially attached, and with limited socialization toward humans. The PACF aims to support municipalities in implementing this mandate through evidence-based strategies that integrate animal welfare, biodiversity protection, and public health objectives. Using standardized data submitted by 1128 municipalities (13.9% of Spain’s total), we estimated a baseline population of 1.81 million community cats distributed across 125,000 colonies. These data were stratified by municipal population size and applied to national census figures to generate a model-ready demographic structure. We then implemented a stochastic simulation using Vortex software to project long-term population dynamics over a 25-year horizon. The model integrated eight demographic–environmental scenarios defined by a combination of urban–rural classification and ecological reproductive potential based on photoperiod and winter temperature. Parameters included reproductive output, mortality, sterilization coverage, abandonment and adoption rates, stochastic catastrophic events, and territorial carrying capacity. Under current sterilization rates (~20%), our projections indicate that Spain’s community cat population could surpass 5 million individuals by 2050, saturating ecological and social thresholds within a decade. In contrast, a differentiated sterilization strategy aligned with territorial reproductive intensity (50% in most areas, 60–70% in high-pressure zones) achieves population stabilization by 2030 at approximately 1.5 million cats, followed by a gradual long-term decline. This scenario prioritizes feasibility while substantially reducing reproductive output, particularly in rural and high-intensity contexts. The PACF combines stratified demographic modeling with spatial sensitivity, offering a flexible framework adaptable to local conditions. It incorporates One Health principles and introduces tools for adaptive management, including digital monitoring platforms and standardized welfare protocols. While ecological impacts were not directly assessed, the proposed demographic stabilization is designed to mitigate population-driven risks to biodiversity and public health without relying on lethal control. By integrating legal mandates, stratified modeling, and realistic intervention goals, this study outlines a replicable and scalable framework for coordinated action across administrative levels. It exemplifies how national policy can be operationalized through data-driven, territorially sensitive planning tools. The findings support the strategic deployment of TNR-based programs across diverse municipal contexts, providing a model for other countries seeking to align animal welfare policy with ecological planning under a multi-level governance perspective. Full article

This study examines the energy behavior of a strengthening system consisting of a Fiber Reinforced Polymer (FRP) plate bonded to a rigid substrate and subjected to tensile loading, where the adhesive interface is governed by a bilinear bond–slip law with a vertical descending branch. The investigation focuses on the interaction between the elastic energy stored in the FRP and the adhesive interface, as well as the characteristic lengths that control the debonding process. Analytical expressions for the strain energy stored in both the FRP plate and the adhesive interface are derived, enabling the identification and evaluation of two critical characteristic lengths as the bond stress at the loaded end approaches its maximum value $l_c$, at which the elastic energies of the FRP and the adhesive interface converge, signaling energy saturation; and $l_{max}$, where the adhesive interface attains its peak energy absorption. Upon reaching the energy saturation state, the system undergoes failure through the sudden and complete debonding of the FRP from the substrate. The onset of unstable debonding is rigorously analyzed in terms of the first and second derivatives of the total potential energy with respect to the bond length. It is further demonstrated that abrupt debonding may also occur in cases where the length exceeds $l_c$ when the bond stress reaches its maximum, and the bond–slip law is characterized by a vertical branch. The findings provide significant insights into the energy balance and stability criteria governing the debonding failure mode in FRP-strengthened structures, highlighting the pivotal role of characteristic lengths in predicting both structural performance and failure mechanisms. Full article

The numerical simulation of unsteady, high-Reynolds-number incompressible flows governed by the Navier–Stokes (NS) equations presents significant challenges in computational fluid dynamics, primarily concerning numerical stability and computational efficiency. Standard Galerkin finite element methods often suffer from non-physical oscillations in convection-dominated regimes, while the multiscale nature of these flows demands prohibitively high computational resources for uniformly refined meshes. This paper proposes an improved Galerkin framework that synergistically integrates a Variational Multiscale Stabilization (VMS) method with an adaptive mesh refinement (AMR) strategy to overcome these dual challenges. Based on the Ritz–Galerkin formulation with the stable Taylor–Hood ($P_2-P_1$) element, a VMS term is introduced, derived from a generalized $\theta$-scheme. This explicitly constructs a subgrid-scale model to effectively suppress numerical oscillations without introducing excessive artificial diffusion. To enhance computational efficiency, a novel a posteriori error estimator is developed based on dual residuals. This estimator provides the robust and accurate localization of numerical errors by dynamically weighting the momentum and continuity residuals within each element, as well as the flux jumps across element boundaries. This error indicator guides an AMR algorithm that combines longest-edge bisection with local Delaunay re-triangulation, ensuring optimal mesh adaptation to complex flow features such as boundary layers and vortices. Furthermore, the stability of the Taylor–Hood element, essential for stable velocity–pressure coupling, is preserved within this integrated framework. Numerical experiments are presented to verify the effectiveness of the proposed method, demonstrating its ability to achieve stable, high-fidelity solutions on adaptively refined grids with a substantial reduction in computational cost. Full article

To investigate temporal deformation mechanisms of hydraulic asphalt concrete slope flow under evolving temperatures, this study developed a novel temperature-controlled slope flow intelligent test apparatus. Using this apparatus, slope flow tests were conducted at four temperature levels: 20 °C, 35 °C, 50 °C, and 70 °C. By applying nonlinear dynamics theory, the temporal evolution of slope flow deformation and its nonlinear mechanical characteristics under varying temperatures were thoroughly analyzed. Results indicate that the thermal stability of hydraulic asphalt concrete is synergistically governed by the phase-transition behavior between asphalt binder and aggregates. Temporal evolution of slope flow exhibits a distinct three-stage pattern as follows: rapid growth (0~12 h), where sharp temperature rise disrupts the primary skeleton of coarse aggregates; decelerated growth (12~24 h), where an embryonic secondary skeleton forms and progressively resists deformation; stabilization (>24 h), where reorganization of coarse aggregates is completed, establishing structural equilibrium. The thermal stability temperature influence factor (δ) shows a nonlinear concave growth trend with increasing test temperature. Dynamically, this process transitions sequentially through critical stability, nonlinear stability, period-doubling oscillatory stability, and unsteady states. Full article

Burnout syndrome is a growing concern in higher education, affecting the psychological well-being and performance of university professors. This systematic review presents a narrative synthesis of findings from quantitative studies on sociodemographic and psychosocial determinants of academic burnout. Following PRISMA 2020 guidelines, sixty peer-reviewed articles published between Jan 2019 and May 2024 were selected from Scopus and Web of Science. Inclusion criteria required validated psychometric instruments and exclusive focus on university faculty. Methodological quality was assessed using the Newcastle-Ottawa Scale and CASP checklist. Data from approximately 43,639 academic staff were analyzed. Key risk factors identified include excessive workload, lack of institutional support, and workplace conflict. In contrast, collegial support, participative leadership, and job satisfaction functioned as protective elements. Variables such as age, gender, academic rank, and employment stability significantly influenced burnout vulnerability. While general patterns were observed across studies, differences in design and sampling require caution in generalization. The evidence supports the implementation of integrated strategies encompassing mental health programs, workload regulation, participatory governance, and culturally responsive approaches. These findings inform the development of institutional policies aimed at preventing burnout and fostering academic well-being. Future research should adopt longitudinal and cross-cultural designs to further explore burnout trajectories and support educational reform. Full article

Surface and sub-surface atomic configurations are critical for catalysis as they host the active sites governing electrochemical processes. This study employs density functional theory (DFT) calculations and Monte Carlo simulations combined with the cluster-expansion approach to investigate atom distribution and Pt segregation in Pt-Fe alloys across varying Pt/Fe ratios. Our simulations reveal a strong tendency for Pt atoms to segregate to the surface layer while Fe atoms enrich the sub-surface region. Crucially, the calculations predict the stability of a periodic Pt₂Fe alloy surface model, characterized by specific defect structures, at low platinum content and low annealing temperatures. Electronic structure analysis indicates that forming this Pt₂Fe surface alloy lowers the d-band center of Pt atoms, weakening CO adsorption and thereby enhancing resistance to CO poisoning. Although defect-induced strains can modulate the d-band center, crystal orbital Hamilton population (COHP) analysis confirms that such strains generally strengthen Pt-CO interactions. Therefore, the theoretical design of Pt₂Fe alloy surfaces and controlling defect density are predicted to be effective strategies for enhancing catalyst resistance to CO poisoning. This work highlights the advantages of periodic Pt₂Fe surface models for anti-CO poisoning and provides computational guidance for designing efficient Pt-based electrocatalysts. Full article

Promoting sustainable development requires a clear understanding of how short-term fluctuations in anthropogenic emissions affect urban environmental quality. This is especially relevant for cities experiencing rapid industrial changes or emergency policy interventions. Among key environmental concerns, variations in ambient pollutants like ozone (O₃) are closely tied to both public health and long-term sustainability goals. However, traditional chemical transport models often face challenges in accurately estimating emission changes and providing timely assessments. In contrast, statistical approaches such as the difference-in-differences (DID) model utilize observational data to improve evaluation accuracy and efficiency. This study leverages the synthetic difference-in-differences (SDID) approach, which integrates the strengths of both DID and the synthetic control method (SCM), to provide a more reliable and accurate analysis of the impacts of interventions on city-level air quality. Using Shanghai’s 2022 lockdown as a case study, we compare the deweathered ozone (O₃) concentration in Shanghai to a counterfactual constructed from a weighted average of cities in the Yangtze River Delta (YRD) that did not undergo lockdown. The quasi-natural experiment reveals an average increase of 4.4 μg/m³ (95% CI: 0.24–8.56) in Shanghai’s maximum daily 8 h O₃ concentration attributable to the lockdown. The SDID method reduces reliance on the parallel trends assumption and improves the estimate stability through unit- and time-specific weights. Multiple robustness checks confirm the reliability of these findings, underscoring the efficacy of the SDID approach in quantitatively evaluating the causal impact of emission perturbations on air quality. This study provides credible causal evidence of the environmental impact of short-term policy interventions, highlighting the utility of SDID in informing adaptive air quality management. The findings support the development of timely, evidence-based strategies for sustainable urban governance and environmental policy design. Full article

Class D β-lactamases (DBLs) represent a major threat to antibiotic efficacy by hydrolyzing β-lactam drugs, including last-resort carbapenems, thereby driving antimicrobial resistance in Gram-negative bacteria. The enzymes share a structurally conserved two-domain α/β architecture with seven active-site motifs and three flexible extended loops (the P-loop, Ω-loop, and newly designated B-loop) that surround the active site. While each of these loops is known to influence enzyme function, their coordinated roles have not been fully elucidated. To investigate the significance of their interplay, we compared the sequences and crystal structures of 40 DBLs from clinically relevant Gram-negative pathogens and performed molecular dynamics simulations on selected representatives. Combined structural and dynamical analyses revealed a strong correlation between B-loop architecture and carbapenemase activity in the pathogens Klebsiella and Acinetobacter, particularly regarding loop length and spatial organization. These findings emphasize the B-loop’s critical contribution, in concert with the P- and Ω-loops, in tuning active site versatility, substrate recognition, catalytic activity, and structural stability. A deeper understanding of how these motifs and loops govern DBL function may inform the development of novel antibiotics and inhibitors targeting this class of enzymes. Full article

A modular strategy for the molecular design of silicone-based antifoaming agents was developed by precisely controlling the architecture of poly (methylhydrosiloxane) (PMHS). Sixteen PMHS variants were synthesized by systematically varying the siloxane chain length (L1–L4), backbone composition (D₃T₁ vs. D₃₀T₁), and terminal group chemistry (H- vs. M-type). These structural modifications resulted in a broad range of Si-H functionalities, which were quantitatively analyzed and correlated with defoaming performance. The PMHS matrices were integrated with high-viscosity PDMS, a nonionic surfactant, and covalently grafted fumed silica—which was chemically matched to each PMHS backbone—to construct formulation-specific defoaming systems with enhanced interfacial compatibility and colloidal stability. Comprehensive physicochemical characterization via FT-IR, ¹H NMR, GPC, TGA, and surface tension analysis revealed a nonmonotonic relationship between Si-H content and defoaming efficiency. Formulations containing 0.1–0.3 wt% Si-H achieved peak performance, with suppression efficiencies up to 96.6% and surface tensions as low as 18.9 mN/m. Deviations from this optimal range impaired performance due to interfacial over-reactivity or reduced mobility. Furthermore, thermal stability and molecular weight distribution were found to be governed by repeat unit architecture and terminal group selection. Compared with conventional EO/PO-modified commercial defoamers, the PMHS-based systems exhibited markedly improved suppression durability and formulation stability in high-viscosity environments. These results establish a predictive structure–property framework for tailoring antifoaming agents and highlight PMHS-based formulations as advanced foam suppressors with improved functionality. This study provides actionable design criteria for high-performance silicone materials with strong potential for application in thermally and mechanically demanding environments such as coating, bioprocessing, and polymer manufacturing. Full article