Search Results (1,041)

Short-term wind power prediction is pivotal for maintaining the stability of power grids characterized by high renewable energy penetration. However, wind power time series exhibit complex characteristics, including local turbulence-induced fluctuations and long-term temporal dependencies, which challenge traditional forecasting models. Furthermore, the performance of hybrid deep learning models is often compromised by the difficulty of tuning hyperparameters over non-convex optimization surfaces. To address these challenges, this study proposes a novel framework: CPO—BiTCN—BiGRU—Attention. Adopting a physically motivated “Filter–Memorize–Focus” strategy, the model first employs a Bidirectional Temporal Convolutional Network (BiTCN) with dilated causal convolutions to extract multi-scale local features and denoise raw data. Subsequently, a Bidirectional Gated Recurrent Unit (BiGRU) captures global temporal evolution, while an attention mechanism dynamically weights critical time steps corresponding to ramp events. To mitigate hyperparameter uncertainty, the Crowned Porcupine Optimization (CPO) algorithm is introduced to adaptively tune the network structure, balancing global exploration and local exploitation more effectively than traditional swarm algorithms. Experimental results obtained from real-world wind farm data in Xinjiang, China, demonstrate that the proposed model consistently outperforms State-of-the-Art benchmark models. Compared with the best competing methods, the proposed framework reduces MAE and MAPE by approximately 30–45%, while maintaining competitive RMSE performance, indicating improved average forecasting accuracy and robustness under varying operating conditions. The results confirm that the proposed architecture effectively decouples local noise from global trends, providing a robust and practical solution for short-term wind power forecasting in grid dispatching applications. Full article

This study examines the evolution, heterogeneity, and short-term prospects of export performance in seven Central and Eastern European (CEE) economies—Croatia, Czech Republic, Hungary, Poland, Romania, Bulgaria, and Slovakia—over the period 1995–2024. Using annual World Bank data, exports are modeled as a share of GDP to ensure cross-country comparability and to capture differences in trade dependence. The analysis combines descriptive and inferential statistics with Augmented Dickey–Fuller tests, non-parametric comparisons, Granger causality analysis, and country-specific ARIMA models to investigate export dynamics, the role of foreign direct investment (FDI), and future export trajectories. The results reveal a common long-term upward trend in export intensity across all countries, driven by European integration and structural transformation, but with pronounced cross-country differences in export dependence and volatility. Highly open economies such as Slovakia, Hungary, and the Czech Republic exhibit strong export performance alongside greater exposure to external shocks, while larger domestic markets such as Poland and Romania display lower export intensity and greater stabilization. Granger causality tests indicate that FDI contributes to export growth in several economies, often with multi-year lags, highlighting the importance of absorptive capacity and institutional quality in translating investment inflows into export competitiveness. ARIMA-based forecasts for 2025–2027 suggest continued export expansion and relative stabilization despite recent global disruptions. This study’s primary contribution lies in integrating comparative export analysis, causality testing, and short-term forecasting within a unified econometric framework, offering policy-relevant insights into export-led growth and economic convergence in post-transition European economies. Full article

Urban vitality is a critical metric for measuring the quality of sustainable development and overall competitiveness, serving as the core kinetic energy for urban survival and growth. As a key link for land–sea resource coordination and internal–external economic circulation, the urban vitality of China’s coastal regions is of great significance for promoting regional coordinated development. Focusing on 130 cities in China’s coastal regions, this study constructs an evaluation system encompassing five dimensions: economy, society, culture, environment, and population. Utilizing the AHP–entropy combined weighting method, the urban vitality index (UVI) for 2023 is calculated based on a scientific measurement of each dimension’s vitality level. Additionally, spatial autocorrelation and the multiscale geographically weighted regression (MGWR) model are employed to examine the spatial evolution patterns and multidimensional driving mechanisms in depth. The results indicate the following: (1) Coastal regions exhibit significant spatial heterogeneity in vitality, characterized by a distinct south–north gradient (high in the south and low in the north). Geographically, the distribution of overall vitality is highly uneven: high-value clusters are concentrated in southern coastal urban agglomerations—notably the Pearl River Delta and the Yangtze River Delta—whereas northern coastal areas, with the exception of the Shandong Peninsula, generally demonstrate relatively low vitality levels. Administrative rank has a significant effect on vitality agglomeration; the average vitality of provincial capitals and above is approximately four times that of other cities. (2) Environmental vitality performs best but shows significant spatial polarization. High-value areas for economic and population vitality are concentrated in the Yangtze River Delta, Pearl River Delta, and Shandong Peninsula urban agglomerations, while social and cultural vitality only stand out in megacities such as Shenzhen, Guangzhou, and Shanghai. (3) Urban vitality exhibits strong spatial correlation and path dependence. Coastal urban vitality shows a significant positive spatial autocorrelation, with H-H (high–high) clusters primarily concentrated in the Yangtze River Delta and Pearl River Delta, indicating a high degree of spatial aggregation and regional synergy in urban vitality. Conversely, L-L (low–low) “depressed cities” are distributed in contiguous blocks in the north and peripheral areas, indicating that regional collaborative driving forces need to be further strengthened. (4) Multifactor driving mechanisms show obvious spatial heterogeneity and scale effects. The MGWR model results reveal that the medical insurance coverage rate, human capital level, and annual average PM 2.5 concentration are the dominant factors driving coastal urban vitality. Their influence intensity shows significant north–south differences across geographical locations, and the contribution of nonspatial factors is overall higher than that of traditional built environment factors. These findings provide a scientific reference for formulating precise and differentiated regional vitality enhancement strategies, optimizing coastal resource allocation, and promoting high-quality land–sea coordinated development. Full article

The mechanical response of the iron–hydrogen (Fe-H) system under triaxial tensile loading is systematically investigated using molecular dynamics simulations. The study focuses on how hydrogen concentration affects the stress state and void evolution and further explores its coupled effects with temperature. The results indicate that when the hydrogen concentration is less than or equal to 1%, hydrogen atoms impede dislocation motion, thereby retarding void growth by promoting dislocation entanglement and the formation of loop structures. Moreover, the evolution of void volume exhibits a typical three-stage characteristic: an initial slow growth phase, a rapid growth phase, and a decelerated growth phase after coalescence. In addition, the evolution of void surface area in the model essentially results from competition between two mechanisms: the decrease caused by void collapse and coalescence and the increase caused by void expansion. Cluster configuration analysis reveals that void formation around the clusters serves as a critical turning point for their structural stability, and the subsequent evolution of the voids leads to a substantial reduction in local structural stability. The analysis of the coupling effect between temperature and hydrogen concentration reveals that under high-temperature conditions, temperature plays a key role in determining the strength, while the strengthening effect of low hydrogen concentrations can be neglected. Additionally, at low temperatures, hydrogen concentration has a negligible effect on structure, but under elevated temperatures, increased hydrogen concentration markedly intensifies the degree of structural disorder. Full article

Metropolitan governance in the U.S. has taken shape over generations and is still evolving. The U.S. territory is literally covered by a myriad of institutions responsible for influencing the country’s physical destiny, cultural identity, and digital representations. Due to their growing complexity, metropolitan areas require adequate institutional mechanisms capable of steering the physical, socio-economic, ecological, and digital transformations within their jurisdictional boundaries. The research question at the core of this article is the following: Where does knowledge concerning land management for metropolitan governance in the U.S.A. come from? This paper aims to review metropolitan governance’s evolution, state of the art, and current challenges in the U.S. at the beginning of the 21st century. The methods consisted mostly of reviews of specialized literature as well as an analysis of two metropolitan archetypal case studies on opposite ends of the country: the sprawling Southwest (Phoenix, Arizona) and the shrinking Northeast Rust Belt (the Albany Capital Region of upstate New York). It is argued that although the Councils of Government (COGs) and metropolitan planning organizations (MPOs) are invaluable in producing land cover and land use change atlases and toolkits of their territories, fragmented units of government within metropolises intensify economic and fiscal disparities and can potentially undermine regional competitiveness and efficiency. The article’s key findings revolve around the current and most pressing challenges and strategies with the potential to move metropolitan governance institutions toward greater regional cooperation and planning. Full article

Pursuit–evasion involves coupled, antagonistic decision-making and is prone to local-optimal behaviors when solved online under nonlinear dynamics and constraints. This study investigates a dual-AUV pursuit–evasion problem in ocean-current environments by integrating game theory with model predictive control (MPC). We formulated a game-theoretic MPC scheme that optimizes pursuit and evasion actions over a finite receding horizon, producing Nash-like responses. To solve the resulting nonconvex and multi-modal optimization problems reliably, we developed an Enhanced Adaptive Quantum Particle Swarm Optimization (EA-QPSO) method that incorporates chaos-based initialization and adaptive diversity-aware exploration with stagnation-escape perturbations. EA-QPSO is benchmarked against representative solvers, including fmincon, Differential Evolution (DE), and the Marine Predator Algorithm (MPA). Extensive 2D and 3D simulations demonstrate that EA-QPSO mitigates local-optimum trapping and yields more effective closed-loop behaviors, achieving longer escaping trajectories and more persistent pursuit until capture under the game formulation. In 3D scenarios, EA-QPSO better preserves high-speed motion while coordinating agile angular-rate adjustments, outperforming competing methods that exhibit premature deceleration or degraded maneuvering. These results validate the proposed framework for computing reliable competitive strategies in constrained underwater pursuit–evasion games. Full article

Nutritional immunity is a major facet of host defense, wherein the host immune system strategically limits pathogen access to critical nutrients, including iron, zinc, vitamins, lipids, and amino acids, to repress microbial proliferation and virulence. This review provides a comprehensive synthesis of the molecular mechanisms that power nutrient immunity, including metal homeostasis, nutrient competition, transporter modulation, hormonal regulation, and direct antimicrobial actions. We examine nutrient-specific strategies employed by the host, such as iron-withholding mechanisms, vitamin deprivation, and copper-mediated toxicity. We also explore how diverse pathogens, including extracellular, intracellular, and eukaryotic pathogens, adapt to these hostile nutritional landscapes through siderophore diversification, regulatory integration, and metabolic rewiring. Comparative genomic analyses reveal convergent evolution in nutrient acquisition systems, illuminating the dynamic arms race between host restriction and microbial evasion. We examine the immunological mechanisms that regulate nutritional immunity. Further, we discuss the translational potential of nutritional immunity, cutting across nutrient-based therapies, host-directed interventions, and emerging diagnostic biomarkers. Finally, we suggest future directions that synergize nutritional immunity with microbiome ecology, global malnutrition, and personalized medicine. By elucidating the interconnection between metabolism and immunity, this review highlights the therapeutic promise of starving or toxifying the pathogen to save the host. Full article

In the context of strategies for the promotion of a sustainable wine industry, the utilization of production regulations under the European Geographical Indications system is seldom contemplated. Furthermore, when such texts are considered, the focus is typically on rules for viticulture or winemaking, rather than on articles governing the boundaries of a PDO or PGI. The present study examines the manner in which regulatory innovation, when viewed from a strictly geographical perspective, can promote the sustainable growth of the sparkling wine districts of Franciacorta and Oltrepò Pavese, which are located in the Italian Lombardy region. Through a comparative analysis of Franciacorta and Oltrepò Pavese, we explore how regulatory frameworks, land-use constraints, and production capacities interact to shape environmental, social, and economic sustainability. Franciacorta’s premium positioning and global reputation are constrained by its limited geographic area, making expansion environmentally and socially challenging. In contrast, Oltrepò Pavese has substantial production potential, particularly for Pinot Noir-based classic-method sparkling wines but suffers from a fragmented identity and weak market recognition. Benchmarking the Prosecco PDO evolution, we propose a sustainability-oriented growth model integrating multiple territories under harmonized rules, termed “Grande Franciacorta”. This framework would enable controlled growth, reduce land pressure in high-density areas, enhance regional competitiveness, and support long-term ecological stewardship. This study outlines managerial implications for producers, emphasizing multi-tier product architectures, dynamic capabilities, and coordinated governance mechanisms. Policy recommendations highlight the need for regulatory frameworks that embed sustainability criteria, optimize land use, and consolidate regional reputation to ensure the long-term viability of high-quality sparkling wine production. Full article

Large-scale wind farms operate under highly unsteady atmospheric inflows, where transient turbulence, dynamic wake interactions, and inflow-wake coupling reduce energy production and exacerbate turbine loads. Over the past five years, advances in high-fidelity computational fluid dynamics (CFDs), large eddy simulation (LES), machine learning (ML)-based wake modeling, and multi-objective optimization have reshaped wind farm layout optimization under dynamic inflow conditions. This review synthesizes recent progress in five key areas: dynamic inflow and high-fidelity wake modeling (including LES-driven transient wake evolution and turbulence-resolved inflow generation), data-driven wake prediction, multi-objective layout optimization (considering the annual energy production (AEP), fatigue load constraints, and the levelized cost of energy (LCOE)), blockage modeling for complex terrain and yaw misalignment, and real-time optimization addressing inflow, turbine performance, and modeling uncertainties. Coupling transient wake models with surrogate-assisted multi-objective optimization enables a computationally efficient and physically consistent layout design. Key open challenges (dynamic wake controllability, real-time optimization under uncertainty, and integration with next-generation farm-level control systems) and future directions for enhancing large-scale wind farm resilience and cost-competitiveness are also identified. However, despite significant progress, existing models still face fundamental limitations, such as oversimplified treatment of complex turbulence structures, poor generalization under extreme or atypical conditions, and inadequate capture of long-timescale dynamic responses, which constrain their reliability in practical optimization settings. Full article

Traditional villages, as carriers of agricultural civilization and ecological wisdom, represent important sites for fostering new-quality productive forces. In the context of rapid urbanization, they function as key spaces for rural development while also confronting vulnerabilities such as spatial functional imbalance and ecological degradation. Within the production–living–ecology (PLE) spaces, dependence on labor-intensive and capital-intensive agricultural models often results in resource misallocation and systemic dysfunction. New-quality productive forces, driven by innovation and green transition, provide a fresh perspective for sustainable rural spatial restructuring. However, their micro-scale mechanisms within traditional villages remain underexplored. This study focuses on 22 nationally recognized traditional villages in Foshan, China. Based on land-use and socioeconomic data from 1993, 2003, 2013, and 2023, we applied land-use transition matrices, a coupling coordination degree model, and geographical detector analysis to examine the evolution of PLE spatial patterns and their driving mechanisms. The findings show that (1) spatially, the share of living space increased significantly, while ecological and agricultural production spaces continued to shrink, reflecting heightened competition among the three; (2) the overall coupling coordination degree exhibited a declining trend, indicating weakened synergy among PLE functions; (3) key drivers of system coordination include per capita disposable income of rural residents, agricultural labor productivity, regional technological innovation capacity, and forest coverage, underscoring the synergistic role of socioeconomic and ecological factors in new countryside development. This study elucidates the micro-spatial pathways through which new rural construction and conservation mechanisms operate, providing a reference for context-sensitive conservation and high-quality development of traditional villages in rapidly industrializing regions. The analytical framework can also be extended to other rural areas undergoing transition. Full article

Electroencephalography-based motor imagery (EEG-MI) classification is a cornerstone of Brain–Computer Interface (BCI) systems, enabling the identification of motor intentions by decoding neural patterns within EEG signals. However, conventional methods, predominantly reliant on convolutional neural networks (CNNs), are proficient at extracting local temporal features but struggle to capture long-range dependencies and global contextual information. To address this limitation, we propose a Triple-path Heterogeneous Feature Collaboration Network (TPHFC-Net), which synergistically integrates three distinct temporal modeling pathways: a multi-scale Temporal Convolutional Network (TCN) to capture fine-grained local dynamics, a Transformer branch to model global dependencies via multi-head self-attention, and a Long Short-Term Memory (LSTM) network to track sequential state evolution. These heterogeneous features are subsequently fused adaptively by a dynamic gating mechanism. In addition, the model’s robustness and discriminative power are further augmented by a lightweight front-end denoising diffusion model for enhanced noisy feature representation and a back-end prototype attention mechanism to bolster the inter-class separability of non-stationary EEG features. Extensive experiments on the BCI Competition IV-2a and IV-2b datasets validate the superiority of the proposed model, achieving mean classification accuracies of 82.45% and 89.49%, respectively, on the subject-dependent MI task and significantly outperforming existing mainstream baselines. Full article

The corrosion behavior of P110 tubing in a supercritical CO₂/oil/water environment (20 MPa, 90 °C) was investigated over a test duration of 168 h by means of weight loss testing and corrosion scale analysis. The results reveal a significant transition at 50% water cut, where the uniform corrosion rate surged by approximately two orders of magnitude, while the localized corrosion rate exhibited a distinct convex trend, peaking at this threshold due to inhomogeneous wetting dynamics. The corrosion scales were identified as Calcium-substituted Iron Carbonate solid solutions (Fe_xCa_1−xCO₃). Based on the competitive crystallization between corrosion-derived Fe²⁺ and bulk Ca²⁺, a mechanism for scale morphological evolution is proposed. This model explains the structural transition of the scale from a heterogeneous multi-layered film at a low water cut (30%) to a kinetic-controlled single layer at the critical water cut (50%), and finally, to a diffusion-controlled tri-layer gradient structure under fully water-wetted conditions (100%). Full article

In the era of globalization, Chinese firms increasingly leverage sequential cross-border mergers and acquisitions to navigate complex international environments. Understanding the sustained impact of this strategy requires a holistic view beyond isolated transactions. Adopting an open systems perspective, this study examines how sequential cross-border M&As influence the evolution of firms’ innovation boundaries as a dynamic system property. Combining grounded theory with textual analysis of Chinese M&A cases, this study develops an integrated systemic process framework and empirically tests it using data from Chinese listed firms (2002–2021) via fixed-effects models. Results reveal that sequential cross-border M&As act as external inputs that trigger internal system reconfiguration, significantly expanding innovation boundaries. This expansion process is mediated by dynamic capabilities, which constitute the firm’s core adaptive mechanism, and is moderated by resource slack that functions as critical system redundancy. These findings contribute to systems science by elucidating how firms, conceptualized as complex adaptive systems, transition from isolated deal-making to sustained capability building through iterative feedback loops in global competition. Full article

As the “brain” of the information industry and modern manufacturing, chips have emerged as a focal point in global competition over critical technologies. Based on global chip trade data from 2010 to 2023, this study employs social network analysis to investigate the structural evolution of the chip trade network and applies the quadratic assignment procedure (QAP) to examine the driving mechanisms of network reconstruction. The findings are as follows: First, the global chip trade network exhibits a loosely connected core-periphery structure, characterized by clustering and polarization, with a pronounced short-term deglobalization trend. Second, China, the United States, Germany, France, South Korea, and Singapore have long dominated central positions in competitive dynamics, while developing economies such as Mexico, Malaysia, and the Philippines have significantly risen in prominence in recent years. Third, the network takes on a core–subcore–periphery configuration with clearly delineated trade communities, reflecting a community-based, multi-centric, and hierarchical pattern. Fourth, political relations serve as a key driver of network restructuring, with their promotional effect on chip trade being negatively moderated by technological distance yet positively moderated by economic-complexity distance. Full article

Electrocatalytic hydrogenation (ECH) represents an environmentally friendly pathway for converting 5-hydroxymethylfurfural (HMF) into the high-value chemical 2,5-bis(hydroxymethyl)furan (BHMF). However, its selectivity and Faradaic efficiency are often constrained by competitive hydrogen evolution at the cathode and insufficient supply of active hydrogen at the surface. To address this challenge, this study developed an Ir-decorated copper oxide nanowire catalyst (denoted as CuIr) featuring a hydrogen-rich adsorption (H_ads) surface. The incorporation of Ir significantly enhances the catalyst’s water dissociation capacity, creating abundant H_ads sources that selectively accelerate HMF hydrogenation while suppressing side reactions. Under a mild applied potential of −0.45 V vs. RHE and a current density of approximately −20 mA cm⁻², the optimal CuIr₄₀ catalyst achieved near-complete conversion of HMF (99%), a BHMF yield of 99%, and a high Faradaic efficiency of 97% within 120 min of electrolysis. Mechanistic studies reveal that this catalytic leap stems from the synergistic functional interaction between Cu and Ir sites in substrate activation and hydrogen supply. This work presents a novel strategy for designing efficient electrocatalysts for biomass hydrogenation by regulating surface H_ads concentration. Full article