Search Results (25,885)

The decoupling properties and low-inertia characteristics of large-scale wind power have heightened concerns regarding power grid frequency stability, particularly as modern power systems impose stringent frequency regulation requirements on wind integration, leading to an increased complexity of frequency response characteristics under fault conditions. To address this challenge in high-wind-penetration grids, this paper proposes a post-fault frequency dynamics analysis method capable of concurrently accommodating multi-wind-speed scenarios through three key innovations: the linearization of traditional AC system components (including network equations, composite load models, and generator prime mover-governor systems) to establish nodal power increment equations; the development of wind turbine frequency regulation models under diverse wind conditions using small-signal analysis, incorporating regional operational disparities and refined by information entropy-based reliability quantification for adaptive parameter adjustment; and the derivation of the system state equation for post-fault frequency response using wide-area measurement system (WAMS) data, yielding an analytical model that captures region-specific regulation characteristic disparities for physically faithful frequency analysis. Validation via tailored IEEE 39-node simulations convincingly demonstrates the method’s effectiveness and superiority in handling fault-induced transients and wind variability. Full article

Feature selection in high-dimensional datasets presents significant computational challenges, particularly in domains with large feature spaces and limited sample sizes. This paper introduces FL-SBA, a novel metaheuristic algorithm integrating fractional calculus enhancements with Laguerre operators into the Secretary Bird Optimization Algorithm framework for binary feature selection. The methodology incorporates fractional opposition-based learning utilizing Laguerre operators for enhanced population initialization with non-local memory characteristics, and a Laguerre-based binary transformation function replacing conventional sigmoid mechanisms through orthogonal polynomial approximation. Fractional calculus integration introduces memory effects that enable historical search information retention, while Laguerre polynomials provide superior approximation properties and computational stability. Comprehensive experimental validation across ten high-dimensional gene expression datasets compared FL-SBA against standard SBA and five contemporary methods including BinCOA, BAOA, BJSO, BGWO, and BMVO. Results demonstrate FL-SBA’s superior performance, achieving 96.06% average classification accuracy compared to 94.41% for standard SBA and 82.91% for BinCOA. The algorithm simultaneously maintained exceptional dimensionality reduction efficiency, selecting 29 features compared to 40 for competing methods, representing 27% improvement while achieving higher accuracy. Statistical analysis reveals consistently lower fitness values (0.04924 averages) and stable performance with minimal standard deviation. The integration addresses fundamental limitations in integer-based computations while enhancing convergence behavior. These findings suggest FL-SBA represents significant advancement in metaheuristic-based feature selection, offering theoretical innovation and practical performance improvements for high-dimensional optimization challenges. Full article

Innovative reasoning frameworks have been proposed to enhance the reasoning capabilities of AI agents, improving their performance in various tasks. However, most existing research has focused on enhancing designing frameworks for LLMs, with limited attention on leveraging in-context learning to boost their reasoning power. This paper proposes a novel approach, Demo-ToT, which enhances the Tree-of-Thought (ToT) reasoning framework by dynamically retrieving relevant demonstrations to improve reasoning accuracy. Various demonstration retrieval strategies, including vector similarity, sparse retrieval, and string similarity, were explored to identify the most effective methods for optimizing LLM performance. Experiments conducted across multiple benchmarks and language models of varying sizes demonstrated that Demo-ToT substantially enhanced the reasoning ability of smaller LLMs, achieving performance comparable to or even surpassing that of much larger models such as GPT-4. Full article

For the state estimation problem of multi-sensor linear systems with noise cross-correlated, where process noise correlates with measurement noise and measurement noises are mutually correlated, researchers have long attempted to design a sequential fusion Kalman filter that is strictly equivalent to the centralized fusion Kalman filter. To the best of our knowledge, this problem has remained unsolved. To this end, this paper designs a truly globally optimal sequential fusion filter suitable for such systems. First, an innovative method is proposed to indirectly decorrelate process noise from all measurement noise, addressing the challenge of their direct decorrelation. Then, the measurement equations are equivalently rewritten based on the Gram–Schmidt orthogonalization principle so that mutual independence among the noises is achieved. Next, a sequential fusion Kalman filter is established based on the rewritten measurement equation. Finally, the equivalence between filters is rigorously proven theoretically. To demonstrate the effectiveness of the proposed algorithms, the problem of tracking a target moving with constant velocity is considered. Full article

The aim of this paper is to analyze the transfer performance of a spacecraft equipped with a TANDEM electric propulsion system in a classical interplanetary mission scenario targeting Mars, Venus, or a near-Earth asteroid. The TANDEM concept is a coaxial, two-channel Hall-effect thruster recently proposed under ESA’s Technology Development Element program. This innovative propulsion system, currently undergoing experimental characterization, is designed to operate at power levels between $3\mathrm{kW}$ and $25\mathrm{kW}$, delivering a maximum thrust of approximately $1\mathrm{N}$. Its architecture allows operation using a single channel (internal or external) or both channels simultaneously to achieve maximum thrust. This inherent flexibility enables the definition of advanced control strategies for future missions employing such a propulsion system. In the context of a heliocentric mission scenario, this paper adopts a simplified thrust model based on actual thruster characteristics and a semi-analytical model for spacecraft mass breakdown. Transfer performance is evaluated within an optimization framework in terms of time of flight and the corresponding propellant mass consumption as functions of the main spacecraft design parameters. Full article

Controlling low-frequency noise and achieving multi-band sound insulation remain significant challenges and have long been hot topics in industrial research. This study introduces a novel multifunctional device based on the principles of acoustic metamaterials, which not only offers high-performance sound insulation but also converts low-frequency acoustic energy into electrical energy. Through an innovative design featuring multiple local resonance design, the proposed device effectively mitigates the impact of pre-tension on the membrane, while enabling efficient multi-band sound insulation that can be finely tuned by adjusting structural parameters. Experimental results demonstrate that the device achieves a maximum sound insulation of 40 dB and an average sound insulation exceeding 25 dB within the 1000 Hz frequency range. Moreover, by utilizing its local resonance property, a triboelectric nanogenerator (TENG) is specifically designed for low-frequency acoustic–electric conversion, maintaining high performance low-frequency sound insulation while simultaneously powering small scale electronic devices. This work provides a promising approach for multi-band sound insulation and low-frequency acoustic–electric conversion, offering broad potential for industrial applications. Full article

Rapid industrialization and urbanization have driven China’s economic growth but also worsened air pollution, posing serious challenges to sustainable development and public health. Balancing economic growth and environmental protection has become essential for achieving the UN Sustainable Development Goal of “Climate Action.” The National Ecological Civilization Construction Demonstration Zone policy, a major institutional innovation for green transition, aims to integrate ecological protection, industrial upgrading, and spatial governance to achieve both economic and environmental goals. Using county-level panel data from 2010 to 2022, this study applies a difference-in-differences (DID) approach, treating the phased establishment of NECCDZs as an exogenous policy shock. It further explores the mediating effects of green innovation capability and land use efficiency. The results show that the NECCDZ policy significantly reduces PM2.5 concentrations in pilot regions, and the findings remain robust under multiple tests. Improvements in green innovation and land use efficiency are identified as key transmission mechanisms, while policy effects vary across city hierarchies, industrial base types, and regions. Overall, the NECCDZ policy demonstrates the effectiveness of institutionalized ecological governance and offers policy insights for developing countries seeking coordinated progress in economic growth and environmental sustainability. Full article

The built environment contributes approximately 25% of the UK’s total greenhouse gas emissions, positioning it as a critical sector in the national net-zero strategy. This review investigates the enabling role of the domestic smart metering infrastructure combined with other IoT systems in accelerating the decarbonisation of residential buildings. Drawing from experience gained from governmental and commercially funded R&D projects, the article demonstrates how smart metering data can be leveraged to assess building energy performance, underpin cost-effective carbon reduction solutions, and enable energy flexibility services for maintaining grid stability. Unlike controlled laboratory studies, this review article focuses on real-world applications where data from publicly available infrastructure is accessed and utilised, enhancing scalability and policy relevance. The integration of smart meter data with complementary IoT data—such as indoor temperature, weather conditions, and occupancy—substantially improves built environment digital energy analytics. This capability was previously unattainable due to the absence of a nationwide digital energy infrastructure. The insights presented in this work highlight the untapped potential of the UK’s multibillion-pound investment in smart metering, offering a scalable pathway for low-carbon innovation for the built environment, thus supporting the broader transition to a net-zero future. Full article

Objectives: This research paper proposes an innovative framework for developing adaptive and dedicated rehabilitation strategies based on the perceptions of specialists in sports rehabilitation (RT), sports training (AR) and with mixed expertise (RT+AR) regarding advanced resistance training methods, including Effort-Based Training (EBT-3/7), Cluster Training (CT), Rest-Pause Training (RPT) and Post-Activation Potentiation (PAP). The aim of this paper was to develop a tailored strategy for rehabilitation programs, grounded in a targeted selection of training methods, short-term periodization and exercises structured around key training variables such as frequency, intensity and volume. Methods: In order to reach this objective, a quantitative research method is proposed, aiming to identify the experts’ opinion on the way of managing and integrating Unilateral Resistance Training Exercise (URTE). Data processing and analysis were conducted by means of specific tests supplied by the SPSS Statistics for Windows (version 20.0, IBM Corp., Armonk, NY, USA)Results: The findings indicate that EBT-3/7 is perceived as the most effective method for rehabilitation with minimal injury risk, whereas CT and PAP are associated with performance benefits but higher perceived injury risk. RT+AR specialists reported more frequent use of these methods and higher perceived effectiveness. Additionally, they demonstrated superior operational and dynamic capabilities compared to single-domain specialists. Conclusions: According to specialists’ opinions, URTE is effective for post-injury rehabilitation, with combined rehabilitation and training expertise enhancing utilization, perceived effectiveness and implementation of personalized, performance-oriented strategies. Full article

This study examines how supply chain structure diversification drives high-quality enterprise development in the digital economy. Using panel data from Chinese listed non-financial firms (2009–2023), we find that diversification of both suppliers and customers significantly improves firms’ total factor productivity (TFP), and the results remain robust after controlling for endogeneity. Mechanism analyses show that diversification enhances innovation capability, sustainability performance, and risk resilience, while digital supply chains strengthen these effects by improving information flow and coordination. Heterogeneity tests reveal that the impact is greater for firms with higher operational efficiency, cultural synergy, and information transparency. Overall, the findings highlight that diversified and digitally integrated supply chains are essential for innovation-driven, resilient, and sustainable enterprise growth. Full article

Developing highly efficient and stable electrocatalysts from inexpensive and earth-abundant elements represents a significant advancement in overall water splitting (OWS). This study focuses on the synthesis and evaluation of palladium-modified cobalt–phosphorus (PdCoP) and cobalt–iron–phosphorus (PdCoFeP) coatings for use as electrocatalysts in hydrogen evolution (HER), oxygen evolution (OER) and overall water splitting (OWS) in alkaline media. A facile electroless plating method is adopted to deposit the CoP and CoFeP coatings onto a copper surface (Cu sheet), with sodium hypophosphite (NaH₂PO₂) acting as the reducing agent. Pd crystallites were incorporated on CoP and CoFeP coatings using the galvanic displacement method. This study details morphological characterization (using SEM, EDX, and XRD), as well as electrochemical activity testing, for both HER and OER using linear sweep voltammetry (LSV) at different temperatures. The stability of the catalysts for HER was evaluated using chronoamperometry (CA) and chronopotentiometry (CP). The results show that the Pd-modified CoFeP and CoP catalysts exhibited lower overpotentials of 207 and 227 mV, respectively, for HER and 396 mV for OER at a current density of 10 mA cm⁻² compared to the unmodified CoFeP and CoP catalysts. The innovation achieved in this study lies in combining a facile, low-cost deposition method (electroless plating followed by galvanic displacement) with a novel, highly effective ternary composition (PdCoFeP) that exploits synergistic electronic and morphological effects to achieve superior bifunctional performance for alkaline OWS, achieving a low cell voltage of 1.69 V at a current density of 10 mA cm⁻². Overall, this research demonstrates that these synthesized materials are promising candidates for sustainable and economical hydrogen production. Full article

In situ process monitoring systems (IPMSs) are rapidly gaining importance in quality assurance of laser powder bed fusion (L-PBF) parts, yet standardized methods for their objective evaluation are lacking. This study introduces a novel, system-independent assessment method for IPMSs based on a specially designed Energy Step Cube (ESC) test specimen. The ESC enables systematic variation in volumetric energy density (VED) by adjusting laser scan speed, without disclosing complete process parameters. Two industrially relevant IPMSs—PrintRite3D by Divergent and Trumpf’s integrated system—were evaluated using the ESC approach with AlSi10Mg as the test material. System performance was assessed based on sensitivity to VED changes and correlation with actual porosity, determined by metallographic analysis. Results revealed significant differences in sensitivity and effective observation windows between the systems. PrintRite3D demonstrated higher sensitivity to small VED changes, while the Trumpf system showed a broader stable observation range. The study highlights the challenges in establishing relationships between IPMS signals and resulting part properties, currently restricting their standalone use for quality assurance. This work establishes a foundation for standardized IPMS evaluation in additive manufacturing, offering valuable insights for technology advancement and enabling objective comparisons between various IPMSs, thereby promoting innovation in this field. Full article

Innovation is central to the Zero Hunger agenda, yet its distributional links to agricultural performance and policy in Eastern Europe remain unclear. This study investigates whether national innovation performance, proxied by the Global Innovation Index, is associated with agriculture’s macroeconomic weight and with public budget orientation in Bulgaria, Czechia, Hungary, Poland, Romania, and Slovakia across the past decade and a half. Using panel quantile regression with country fixed effects and bootstrapped standard errors, we estimate effects at the lower, median, and upper parts of the outcome distributions for three indicators: agriculture value added share of gross domestic product, the agriculture orientation index for government expenditures, and the agriculture share of government expenditure. Results show a robust negative association between innovation and the agricultural share of gross domestic product that strengthens toward the upper quantiles, consistent with structural transformation that reallocates value added toward higher-productivity sectors. For the orientation index, innovation is unrelated at the lower and median parts but becomes positive in mid–upper regimes, fading again at the extreme upper tail. No systematic relationship emerges for the budget share. Land endowment is positively associated with agricultural weight, while population size is negatively associated. We conclude that economy-wide innovation aligns with structural change, whereas shifting agricultural budget shares requires targeted, sector-specific policy instruments. Full article

In this paper, virtual synchronous generator (VSG) technology is innovatively introduced into the distributor-unified power flow controller (D-UPFC) control to simulate the power generation characteristics of the synchronous generator. Concepts such as inertia and damping in the synchronous generator are introduced into power electronic equipment to provide voltage and frequency support for the system. The VSG control system, which specifically includes the virtual governor, the virtual excitation regulator, and the construction of the VSG model, is designed first. Then, the overall control combining the VSG and the series converter in D-UPFC is discussed. Finally, based on the influence of moment of inertia and damping coefficient on the response parameters, a VSG parameter adaptive control strategy based on refined fuzzy control was proposed. The simulation shows that this strategy can effectively reduce the active overshot and frequency deviation in the dynamic process of the system, eliminate secondary oscillations, and improve the dynamic response capability. Full article

With the acceleration of urbanization, environmental degradation is increasingly restricting the improvement of residents’ quality of life, and promoting the transformation of old communities has become a key path for sustainable urban development. However, existing buildings generally face challenges, such as the deterioration of the performance of the envelope structure and the rising energy consumption of the air conditioning system, which pose a serious test for the realization of green renovation. Inspired by the application of bionics in the field of architecture, this study innovatively designed five types of bionic envelope structures for outdoor air conditioning units, namely scales, honeycombs, spider webs, leaves, and bird nests, based on the aerodynamic characteristics of biological prototypes. The ventilation performance of these structures was evaluated at three scales—namely, single building, townhouse, and community—under natural ventilation conditions, using a CFD simulation system. The study shows the following: (1) the spider web structure has the best comprehensive performance among all types of enclosures, which can significantly improve the uniformity of the flow field and effectively eliminate the low-speed stagnation area on the windward side; (2) the structure reorganizes the flow structure of the near-wall area through the cutting and diversion of the porous grid, reduces the wake range, and weakens the negative pressure intensity, making the pressure distribution around the building more balanced; (3) in the height range of 1.5–27 m, the spider web structure performs particularly well at the townhouse and community scales, with an average wind speed increase of 1.1–1.4%; and (4) the design takes into account both the safety of the enclosure and the comfort of the pedestrian area, achieving a synergistic optimization of function and performance. This study provides new ideas for the micro-renewal of buildings, based on bionic principles, and has theoretical and practical value for improving the wind environment quality of old communities and promoting low-carbon urban development. Full article