Search Results (6,085)

Rapid growth in photovoltaic (PV) development has intensified competition between renewable energy expansion and land resources, highlighting the importance of integrating PV growth with spatial planning toward carbon neutrality. This study addresses the lack of township-level evidence by integrating spatio-temporal analysis, the Optimal Parameter Geodetector (OPGD), and the Patch-generating Land Use Simulation (PLUS) model to investigate the evolution, driving mechanisms, and future spatial patterns of PV development. Taking Xintai City as a case study, this research examines PV development from 2010 to 2022 and simulates future spatial patterns under natural development (ND) and carbon neutrality (CN) scenarios. Results show that PV development entered a rapid expansion stage after 2015, characterized by leapfrog growth and increasing spatial agglomeration. The centroid of PV patches shifted eastward, whereas the centroid of PV area migrated westward, indicating differentiated spatial evolution between the number and scale of PV facilities. PV development was jointly shaped by climatic conditions, socioeconomic factors, and land availability, with interactions among multiple factors substantially enhancing spatial heterogeneity. Scenario simulations revealed that PV development continued under both scenarios, while the CN scenario promoted more concentrated expansion in coal subsidence areas and inefficient industrial and mining lands, thereby helping alleviate potential conflicts with cultivated land protection. These findings highlight the importance of prioritizing low-conflict land resources and strengthening spatial coordination between renewable energy development and land management to support sustainable low-carbon development in resource-based cities. Full article

Non-intrusive load monitoring (NILM) provides a cost-effective way to obtain appliance-level electricity information from aggregate smart-meter measurements and is therefore important for energy management, demand-side response, and sustainable operation in smart buildings. However, accurate appliance-level power disaggregation remains challenging because residential load signals usually involve overlapping appliance signatures, sparse activations, heterogeneous temporal patterns, and transient switching events. To address these challenges, this paper proposes a State-Event-Guided Multi-Scale Gated Network (SEMG-Net) for NILM. The proposed framework integrates a residual temporal encoder, multi-scale dilated convolutional blocks, and a state-event-guided gating mechanism within a unified multi-task learning architecture. The shared encoder extracts hierarchical temporal representations from aggregate mains windows, while task-specific branches jointly estimate appliance power, on/off state, and switching event type. The predicted state probability, three-class event probability distribution, and shared temporal representation are jointly used to construct a continuous gate that modulates the raw power estimate, thereby directly incorporating behavioral predictions into final power estimation. Experimental results on public datasets show that SEMG-Net achieves competitive overall performance, with clear advantages in power estimation, energy consistency, and state identification, particularly for appliances with complex operating stages or transient switching behavior. The ablation results further demonstrate the benefits of multi-scale feature extraction and auxiliary supervision, as well as the effectiveness of the proposed state-event-guided power modulation mechanism. Full article

The global energy sector is undergoing rapid and, in many respects, irreversible transformation driven by the convergence of digital disruption, sustainability mandates, and shifting investor expectations. Technologies such as artificial intelligence (AI), blockchain, and digital twin systems are fundamentally reshaping energy operations and strategic decision-making, while ESG governance quality and renewable energy adoption have emerged as two of the most consequential determinants of corporate financial competitiveness and equity valuation. Despite growing practitioner and regulatory interest in these dynamics, limited empirical evidence exists on how ESG governance, renewable adoption, and digital disruption jointly influence financial performance and environmental outcomes across multiple sectors simultaneously. This study addresses that gap using panel data from 26 large-cap US-listed firms across five sectors over 2015–2022 (N = 208 firm-year observations for Revenue/Market Cap/ROA models; N = 91 for the CO₂ model). A multi-method econometric framework is employed, comprising Fixed Effects and Random Effects panel regression with Hausman specification testing, Difference in Differences quasi-experimental analysis, and sequential OLS path analysis with HC3 robust standard errors. Three of four hypotheses are supported. ESG governance quality generates a significant market capitalisation premium of approximately 10–14% per unit Bloomberg ESG Score improvement, after controlling for firm size and R&D intensity; no significant revenue channel effect is found once firm size is properly accounted for. Renewable energy adoption shows a marginal association with market capitalisation at the 10% significance level (FE β = 0.019, p = 0.086; RE β = 0.016, p = 0.077), suggesting capital markets may price clean energy adoption as a forward-looking signal. ESG governance quality drives within-firm CO₂ emission reduction substantially more powerfully than renewable energy quantity alone, with the Fixed Effects estimator identifying a governance-led eco-efficiency mechanism. Firm profitability functions as a cross-model financial capacity moderator, enabling simultaneous ESG investment and environmental improvement. The findings carry direct implications for corporate managers, institutional investors, and policymakers aligned with SDG 7, SDG 9, and SDG 13. Full article

This study investigates how quality tourism supply contributes to destination competitiveness through the sequential mediating roles of local resource integration and perceived authenticity within a sustainability-oriented tourism framework. Building upon the Resource-Based View and destination competitiveness theory, the study proposes and empirically tests a sequential mediation model in which local resource integration and perceived authenticity explain the mechanisms through which quality tourism supply contributes to destination competitiveness. Data were collected through a survey of 430 tourism stakeholders, including representatives of hotels, restaurants, tourism boards, travel agencies, rural tourism enterprises, and local producers. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) implemented in SmartPLS 4. The findings indicate that quality tourism supply positively influences local resource integration and destination competitiveness, while local resource integration significantly enhances perceived authenticity. Perceived authenticity, in turn, positively affects destination competitiveness. The results also confirm significant individual and sequential mediation effects, demonstrating that tourism quality generates stronger competitive advantages when destinations effectively integrate local resources and foster authentic tourism experiences. The proposed model demonstrated substantial explanatory power, explaining 45.9% of the variance in local resource integration (R² = 0.459), 50.7% of the variance in perceived authenticity (R² = 0.507), and 63.1% of the variance in destination competitiveness (R² = 0.631). The study contributes to the destination competitiveness literature by introducing local resource integration as a strategic mediating construct and by integrating quality, authenticity, and competitiveness within a unified analytical framework. The findings provide theoretical contributions to destination competitiveness research and practical implications for destination managers and policymakers seeking to promote sustainable and competitive tourism development through place-based and community-oriented approaches. Full article

Weeds create a significant challenge in agricultural production by competing with crops for essential resources such as nutrients, sunlight, and water. This competition leads to reduced crop yields and quality, resulting in substantial economic losses. Consequently, there is a critical need for effective weed control strategies to mitigate the impact of unwanted plant growth and ensure sustainable agricultural practices. In precision agriculture, enabling autonomous navigation between crop rows during tasks such as weeding and harvesting presents a significant research challenge, particularly when leveraging cost-effective technological solutions. Effective robot navigation requires adaptive traffic management strategies and robust object recognition capabilities to distinguish between cultivated and uncultivated areas. In fact, the integration of computer vision techniques into these systems is essential for optimizing trafficability in cropping fields and enhancing robots’ dynamics for better working efficiency in agricultural environments. This review addresses the challenge of enhancing inter-row navigation in field crops and delivering reliable guidance for autonomous agricultural robots. A PRISMA-based systematic review methodology was adopted to identify, screen, and analyze 38 relevant studies selected from the Scopus and Web of Science databases. The selected studies are classified according to their target platform (Unmanned Ground Vehicles and Unmanned Aerial Vehicles) and grouped into three methodological categories: conventional computer vision, deep learning architectures, and hybrid approaches. The findings provide practical guidance for selecting appropriate vision-based crop row detection technologies according to the application requirements and highlight key research directions toward more robust, cost-effective, and adaptable autonomous navigation systems. This article presents an outline of artificial-intelligence-based row detection methods used in agricultural fields and a classification of related semantic segmentation approaches. Unlike previous surveys, it provides an overview of the technological progress in agricultural robots and navigation based on systems vision for crop row detection, with a focus on comparisons balancing technical performance with economic and practical constraints. Full article

Entrepreneurship Education (EE) is acknowledged for developing entrepreneurial skills, ideas, and knowledge to support individuals and foster independence, thereby promoting economic growth and national sustainability. Digitised EE has been proposed as a means to strengthen entrepreneurial effectiveness and economic transformation. This literature review classifies studies on digitised EE, emphasises how it supports entrepreneurial effectiveness, and suggests guidelines for digitised EE performance in Tertiary Institutions (TIs). A search strategy was used to identify publications in databases such as Scopus, ScienceDirect, DOAJ, WOS, IEEE, and Cochrane. The publication range spanned from 2012 to 2024. A total of 912 publications were identified in the database, of which 43 met the inclusion criteria. Digitised EE requires considerable study to determine its impact on reducing unemployment, economic development through TIs, and the Sustainable Development Goals (SDGs). A descriptive research design was adopted; the themes selected were acknowledged in the research and discussed based on data extracted from the included criteria. Additionally, most of the included criteria are recent publications, with journals the most frequently identified and quantitative methods the most commonly applied. The lack of improved EE deprives the realisation of entrepreneurial effectiveness, which is attributed to Artificial Intelligence (AI), entrepreneurial knowledge, competitiveness, and strategic decisions. It is imperative to research digitised EE practices for entrepreneurial effectiveness and efficiency in the education sector for a country’s growth. Recommendations for related studies are provided in the review. Full article

Tropical cyclones reduce port capacity and leave heterogeneous congestion. Yet empirical measurements of port resilience are rarely connected to operational strategy evaluation on the same observed event baseline. This study develops a dual-layer framework that measures event-level operational resilience under prevailing practice and estimates modelled marginal improvements from three operational levers. Aggregate baseline measures calibrate multi-server queues for 28 ports without event-period tuning, and discrete-event simulation replays 178 port-event trajectories. The calibrated representation places heterogeneous ports on a common queueing scale. Measured states are benchmarked against a dynamic four-hour business-as-usual (BAU) baseline that retains normal temporal variation. During exposure, median service-capacity loss reaches 0.627, and sustained operational-capacity restoration is confirmed after a median 44 h. Service-focused recovery (SES), coordinated recovery (CRS), and two-stage proactive–reactive response (TPRS) are compared after matching costs within each event. CRS gives the largest mean reduction in cumulative queue burden under the base-case cost coefficients and ranks first in 113 of 128 cost-sensitivity scenarios. SES leads when capacity coordination becomes sufficiently expensive, while TPRS becomes more competitive under prolonged, high-loss exposure. The framework supports strategy assessment according to event state, operational feasibility, and implementation cost. Full article

Mediterranean agriculture is increasingly constrained by severe and recurrent water scarcity. Rising temperatures, declining precipitation, and more frequent droughts are driving higher crop water demand and reducing rainfall reliability. Combined with growing competition for limited freshwater resources, these climatic pressures pose a major challenge to the long-term sustainability and productivity of farming systems in the region. In this context, urban treated wastewater (UTWW) is increasingly recognized as a strategic alternative resource. Regulation (EU) 2020/741 establishes minimum quality requirements for agricultural water reuse based on the fit-for-purpose principle. The Italian regulatory framework requires regional authorities to plan water reuse by mapping reclamation facilities, water demand, and distribution networks. From this perspective, to support the planning process, this study describes the application of a Geographic Information System (GIS)-based methodology to assess the potential for UTWW reuse in Sicily by integrating national datasets (regularly updated) and comparing reclaimed water supply with irrigation demand from both qualitative and quantitative perspectives. UTWW supply was estimated by integrating data from the Italian National Institute of Statistics (ISTAT) Census of Water for Civil Use and the European Environment Agency (EEA) dataset, while irrigation demand was derived by combining Copernicus crop data, ISTAT irrigated-to-total UAA ratios and crop-specific irrigation demand (Seasonal Specific Volumes) derived from the SIGRIAN database. Two scenarios were analyzed for grasslands, vineyards, olive groves, and orchards. Scenario 1 included only wastewater treatment plants (WWTPs) located inside irrigation areas, whereas Scenario 2 also included selected WWTPs located outside irrigation areas where orographic and distance constraints allowed potentially feasible connections. Under Regulation (EU) 2020/741, potential compatibility with the required water quality classes was identified at the screening level for all crop categories considered, which require classes B, C or D. From a quantitative perspective, Scenario 1 identified 19 WWTPs serving 11 out of 38 irrigation areas with an aggregated uncapped demand coverage of 53%; only two areas reached full local demand satisfaction. Scenario 2 added 23 external WWTPs, increased potentially served areas to 20, and raised the aggregate uncapped coverage to 73%. When surplus volumes were capped within each irrigation area, effective demand satisfaction was 12% and 22% in Scenarios 1 and 2, respectively, highlighting the importance of storage, conveyance and inter-area transfer. The results indicate that treated wastewater reuse could contribute to agricultural water security and climate-resilient water management in Mediterranean regions. The framework supports the first-order identification of candidate reuse areas, but site-specific assessments of effluent quality, risk management, costs, and seasonal storage remain necessary before implementation. Full article

The Golden Triangle circuit (Delhi–Agra–Jaipur) is India’s most iconic tourism product, yet it faces mounting pressure from overtourism, environmental degradation, and economic leakage to non-regional operators. We argue that strategic management of visitor satisfaction can play a key role in transforming this high-volume circuit into a sustainable destination that delivers long-term economic growth. Drawing on expectancy disconfirmation theory (EDT), SERVQUAL (service quality), perceived value theory, social exchange theory (SET), destination competitiveness models, and systematic classification of destination attributes, this study evaluates destination attributes and visitor satisfaction. This study assesses the importance of visitor satisfaction with the Golden Triangle and proposes a comprehensive framework for its measurement and application with destination-specific attributes. It uses a qualitative methodology that incorporates an extensive review of information available through various sources and triangulates findings with autoethnography. It identifies key attributes driving tourist satisfaction in the Golden Triangle and assesses the overall current state of the circuit. Furthermore, it identifies major challenges (harassment, congestion, and leakage) and proposes actionable improvements through smart technology, community-based tourism, and real-time feedback. A comprehensive evaluation of visitor satisfaction with various destination attributes of the Golden Triangle reveals that it performs well, as the outcome shows high overall satisfaction. This study also highlights that overall visitor satisfaction is an indirect economic lever that impacts local economic activity by creating jobs and earning foreign currency. The Golden Triangle can possibly serve as a replicable model for other heritage circuits in the Global South with similar characteristics. Full article

The study presents a sustainable, metal-free tanning system based on 2-chloro-4,6-dimethoxy-1,3,5-triazine (CDMT) and N-methylmorpholine (NMM), which stabilizes collagen through a zero-length crosslinking mechanism. Reactive triazine intermediates, generated in situ, selectively activate collagen carboxyl groups, forming active esters that subsequently react with amine functionalities to form amide bonds. Unlike conventional tanning systems, no metals or toxic chemicals are incorporated into the tanned leather. Optimization of reagent concentration, temperature, and dosing strategy revealed that the gradual formation of reactive intermediates is essential to balance reaction kinetics and diffusion throughout collagen. Under pickle-free conditions, hydrothermal stability was achieved with only 2.5–3.4 wt% CDMT/NMM, yielding shrinkage temperatures of 81–85 °C that surpass most reported chrome-free tanning systems. The resulting leather displayed a bright white appearance, excellent dyeability, and outstanding physical-mechanical performance, including superior tear resistance and competitive tensile strength. These properties are consistent with the formation of a homogeneous collagen network reinforced by direct covalent amide crosslinks while maintaining fiber flexibility. Furthermore, avoiding pickling significantly reduces chemical consumption and improves wastewater biodegradability, enhancing the environmental sustainability of the process. Overall, CDMT/NMM emerges as a scalable, environmentally friendly tanning technology that combines mechanistically controlled collagen crosslinking with excellent leather performance. Full article

This study investigates the impact of real effective exchange rate (REER) volatility on foreign direct investment (FDI) inflows in three major Central and Eastern European (CEE) economies—Hungary, Poland, and Romania—using quarterly data spanning from 2007-Q1 to 2024-Q4. The exchange rate volatility is modeled using a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) framework, and country-specific relationships are estimated through Autoregressive Distributed Lag (ARDL) bounds testing and Toda–Yamamoto causality analysis. Our research indicates that a uniform relationship does not exist across the region. In Hungary, the utilization of directional FDI data excluding Special Purpose Entities (SPEs), in conjunction with structural breaks and quarterly seasonal controls, reveals a statistically significant nonlinear (inverted U-shaped) relationship between long-run exchange rate volatility and FDI inflows. In addition, domestic financial development exerts a substantial buffering effect on the transmission of volatility in Hungary by bypassing SPE flows that previously obscured this effect. In Poland and Romania, a stronger currency consistently discourages investment by reducing cost competitiveness. Romania shows a distinct pattern: volatility initially attracts FDI, and while deeper financial markets meaningfully dampen this effect, the net relationship remains positive, unlike Hungary, where sufficiently deep credit markets fully reverse it. These results suggest that policymakers should look beyond short-term exchange rate stabilization and instead prioritize structural reforms, competitive exchange rate levels, transparent FDI reporting standards, and deeper domestic financial markets to sustain FDI inflows. Full article

This review paper systematically investigates the surface modification technology of wooden table tennis blades, with a particular focus on the inherent conflict between coating-induced protection and the preservation of acoustic performance—a critical yet underexplored aspect of blade design. While protective coatings are essential for enhancing durability against moisture, wear, and impact, they inevitably alter the blade’s vibrational characteristics and acoustic feedback, compromising the tactile–auditory perception that elite players rely upon. The current literature predominantly treats protection and acoustics as separate design objectives, lacking an integrated framework to resolve their inherent trade-off. To address this gap, this review establishes a material–structure–function integrated design paradigm that elucidates the synergistic optimization of coating protection and acoustic response. We systematically analyze the regulatory mechanisms of key coating parameters—specifically elastic modulus, density, and damping coefficient—on blade vibration modes and impact sound characteristics, demonstrating that conventional singular optimization inevitably leads to undesirable frequency shifts and diminished tactile feedback. Our synthesis of materials science, acoustic analysis, and biomechanics reveals that the key to synergy lies in constructing a mechanical impedance-matching transition system through material selection and thickness gradient design. Notably, we show that a multi-layer gradient coating architecture, guided by finite element simulation, can enhance protective performance by 40% while restricting acoustic deviation to within 5%, validating a rational “design–simulation–verification” closed-loop methodology. Furthermore, this review identifies critical research frontiers, including smart adaptive coatings and sustainable bio-based materials, and proposes a multi-objective optimization framework to bridge the gap between laboratory innovation and manufacturable, high-performance sporting equipment. This work provides a foundational theoretical roadmap for the next-generation design of competition-grade table tennis blades, balancing durability with the nuanced sensory demands of elite athletes. Full article

Digital transformation is crucial to the sustainable development of industries in locked-in specialized peripheral regions. Taking Longyan in Fujian Province as a case study, this study draws on county-level panel data covering the period 2008–2022 and employs the entropy weight method, kernel density estimation, location quotient analysis, Necessary Condition Analysis (NCA), and panel-data qualitative comparative analysis (PD-QCA) to identify the constraints and multiple pathways through which digital transformation drives industrial upgrading in peripheral regions. The findings are threefold. First, industrial upgrading in Longyan has continued to advance, while disparities in industrial development across counties and districts have generally tended to converge. Second, industrial upgrading in Longyan has primarily involved the extension of existing industrial foundations into knowledge-intensive fields, including energy conservation and environmental protection, advanced equipment, and new materials. Third, digital infrastructure, digital transformation environment, core enterprises’ digital technology application, digital technology innovation, intra-regional innovation collaboration, and cross-regional innovation collaboration combine to form five pathways to industrial upgrading. The findings demonstrate that digital transformation can enable peripheral regions to achieve knowledge recombination, functional upgrading, and the reconstruction of development paths on the basis of their existing industrial foundations. Full article

The use of fruit by-products in animal feed can reduce costs and competition between human and animal feed. This study evaluated the effect of dietary inclusion of yellow passion fruit (Passiflora edulis f. flavicarpa) seed meal (PSM) on growth performance, in vitro fermentation, and feed costs in beef steers. A total of 36 steers (Bos indicus; initial BW 416 ± 30 kg) were randomly assigned to three treatments: a control diet (CON) and diets containing 5 or 10% PSM for 45 days. Feed intake and average daily gain (ADG) were measured. An in vitro fermentation assay evaluated gas production and pH changes. Steers fed with 5% and 10% PSM showed numerically higher group-level fresh matter intake (1.10% and 9.34%, respectively), and significantly greater ADG over the entire trial (p = 0.00015) compared to CON. In addition, diets containing 10% PSM produced the highest cumulative gas (17.00 ± 1.00 mL vs. 10.00 ± 1.00 mL for CON and 10.33 ± 2.52 mL for 5% PSM; p = 0.003), indicating high fermentability. Feed cost was reduced by 57% and 46% when using diets containing 5% and 10% PSM, respectively. In conclusion, this study reveals that dietary inclusion of up to 10% PSM improves feed intake and growth performance in steers while reducing feed costs, supporting its value as a sustainable feed ingredient for beef cattle. Full article

Widening participation spans the whole student lifecycle, from access through to success within higher education and progression beyond it, yet policy and evaluation have concentrated on the access stage alone. Far less is known about how students admitted through widened access routes come to understand the legitimacy of their place, and the terms of their belonging, once inside an elite university. Reporting twenty-one (n = 21) walking interviews with students who entered the University of Cambridge through its Foundation Year, a one-year pre-degree programme for applicants whose educational opportunities have been constrained by structural disadvantage, this article examines a tension at the heart of meritocracy. Belonging is approached throughout as a relational and processual accomplishment practised in situ rather than as a psychological state to be measured, and the article asks on what terms it is made available along a visibly marked route. Participants recognized that admissions standards are shaped by unequal opportunity, though the recognition appeared not to weaken their commitment to meritocratic judgement, and they endeavored to suffuse their belonging with proof of deservingness. Such a pattern sits uneasily with Bourdieusian accounts of symbolic domination grounded in misrecognition, and points towards a compliance sustained through lucid perception of meritocracy and its ideological demands. Analysis of the walks suggests that the route organizes this tension by marking students publicly as different, by tying belonging to a competitive progression threshold, by collapsing heterogeneous experiences into a single administrative category, and by locating institutional judgement in everyday encounters with teaching staff. Belonging emerges less as a settled outcome of admission than as a conditional status that must be repeatedly earned. Widening access may therefore secure entry without securing the later stages of participation, so long as the legitimacy of membership continues to be organized through meritocratic evaluation that students simultaneously critique and reproduce. Full article