Search Results (201)

Against the backdrop of China’s dual-carbon goals and the global green transition, low-carbon production in the manufacturing sector is crucial to achieving high-quality development. Based on the dual mechanisms of the free-riding effect and technology spillovers, this paper develops a Moran stochastic evolutionary game model of manufacturing firms’ low-carbon production strategies under government regulation. We analyze the dynamic evolution and stability of low-carbon versus conventional production strategies under strong- and weak-selection conditions. The results show that under strong selection, a low free-riding payoff promotes the diffusion of the low-carbon strategy and the formation of a stable equilibrium; a moderate free-riding payoff makes population size the key factor shaping evolutionary outcomes; and a high free-riding payoff leads the system to degenerate into a steady state dominated by conventional production. Under weak selection, government subsidies and fines increase the fixation probability and stability of the low-carbon strategy, whereas excessive free-riding payoffs undermine the persistence of the transition. Numerical simulations validate the theoretical analysis and indicate that government regulation, technology spillovers, and population structure jointly shape the long-term evolution of low-carbon behavior, providing a theoretical basis and decision-making reference for optimizing policy mechanisms and promoting the low-carbon transition of the manufacturing sector. Full article

The increasing deployment of renewable energy introduces significant dynamic challenges to green methanol synthesis systems due to its inherent intermittency and variability. However, loop-level dynamic stability and controllability under multi-scenario transient conditions remain insufficiently explored. To address this gap, a steady-state and dynamic model of a renewable-driven methanol synthesis loop was developed in UniSim Design and evaluated under various realistic transient scenarios. Baseline simulations reveal recurring dynamic amplification within the synthesis loop, with pressure deviations exceeding 600 kPa during load increase and persistent oscillatory behavior under fluctuating conditions. To mitigate these instability mechanisms, a control-oriented refinement strategy incorporating first-order feed filtering, load-dependent temperature setpoint scheduling, and gain scheduling of key control loops was implemented. Within the simulation framework, the optimized strategy reduces maximum transient deviations of pressure and temperature by approximately 50–70% and mitigates startup pressure overshoots by over 60%. Under wind–solar-driven operation, pressure integral absolute error (IAE) decreases by up to 42%, and system trajectories become more bounded and better damped. These results provide quantitative insight into renewable-induced instability mechanisms and highlight the potential of control-oriented strategies to enhance dynamic operability in flexible power-to-methanol systems. Full article

Ball balancers are nonlinear, electromechanical, multivariable, open-loop unstable systems widely used in research laboratories, aerospace, military, and automotive industries to evaluate control mechanism effectiveness. The inherent difficulty in precisely managing ball position, combined with actuator saturation and system sensitivity to disturbances, makes trajectory tracking a persistent challenge. Conventional controllers often exhibit oscillatory responses with steady-state errors exceeding acceptable limits. Sliding mode control (SMC) offers robustness against model uncertainties; however, chattering finite-frequency, finite-amplitude oscillations near the sliding surface caused by switching imperfections, time delays, and actuator dynamics remain a significant limitation. This study addresses chattering through explicit vibration model compensation integrated into the SMC design for a 2-DOF ball balancer system using a visual servoing approach. A double-loop control architecture is implemented, where the inner loop handles servo angular position control and the outer loop manages ball position tracking through visual servoing feedback. The sliding mode controller is designed with a power rate reaching law, synthesizing two control laws: one with explicit vibration model compensation incorporating damping and stiffness terms, and one without. Experimental validation confirmed that SMC with compensation achieved significantly reduced steady-state error (0.034 mm vs. 0.386 mm) and lower overshoot (3.95% vs. 13.81%) compared to the uncompensated variant, with chattering amplitude reduced by approximately 72%. Full article

For decades, Saudi Arabia has relied heavily on oil revenues to support its economic growth. While this strategy brought substantial benefits, oil prices and global demand remain volatile, and oil itself is a non-renewable resource. These realities raise important concerns about long-term economic sustainability. In response, the country has pursued economic diversification to reduce risk and build a more resilient growth model. This study examines how the roles of the oil and non-oil sectors in driving GDP growth evolved between 1970 and 2024. To capture differences across economic conditions, the study applies both four and ten quantile regression models. These approaches allow us to observe how sectoral contributions change across low, moderate, and high growth periods. The results show that oil sector growth remains positive and significant across the distribution of GDP growth, with a stronger effect during periods of higher growth. At the same time, the non-oil sector is gaining importance, not only in stronger growth conditions, but is also cushioning the economy in periods of low growth. This signals gradual structural progress toward a more balanced and sustainable economy. The two-state Markov-switching model further identifies two persistent growth regimes: one more oil-dependent and another relatively more diversified. However, oil continues to play a meaningful role in both regimes. Overall, the findings suggest a gradual, steady transition rather than a sharp structural break. For long-term sustainability, Saudi Arabia needs to continue strengthening the productivity, resilience, and competitiveness of its non-oil sectors through its oil revenues accrued during periods of high growth. The implications of this study would be beneficial for all resource-rich economies aiming at economic diversification. Full article

Accurately characterizing the relationship between nighttime human activity intensity and population distribution is essential for understanding urban development. This study proposes an integrated analytical framework that combines multilevel coupling quantification, regional trend detection, and interpretable machine learning to examine the Nighttime Lights and Population Coupling Coordination Degree (NPCCD) across China from 2012 to 2022. Based on this framework, NPCCD is evaluated from grid to regional level, and the characteristics of effective, persistent, and newly added coupled regions are identified. Twelve socioeconomic indicators are further constructed as explanatory variables to model NPCCD using machine learning algorithms, and Shapley Additive Explanations (SHAP) is applied to interpret the outputs. The results show that 49.07% of China’s overall NPCCD experienced steady improvement during the study period. Significant regional disparities were observed: in the eastern and central regions, more than 60% of grids fell into the improving category, whereas nearly half of the grids in the western and northeastern regions remained unchanged. Newly emerging coupling areas exhibited an average NPCCD of 0.03, markedly lower than the 0.07 observed in persistent effective areas, reflecting a mismatch between infrastructure development and population growth. Population density, human capital, industrial upgrading, and fiscal decentralization jointly explained 58.4% of the model’s variance and were identified as the major driving forces, each showing pronounced nonlinear and interaction effects. This study provides a quantitative framework for evaluating the coordination between nighttime lights and population distribution and offers insights for sustainable and balanced regional development. Full article

This study investigates how firms in high-emission sectors progress along the low-carbon transition by analysing the joint dynamics of Management Quality (MQ) and Carbon Performance (CP) using probabilistic modelling and explainable machine-learning methods. Digitalisation is conceptualised as the increasing use of data-driven and algorithmic tools in corporate governance, sustainability monitoring, and regulatory oversight, enabling a more granular assessment of corporate transition pathways across multiple time horizons. Using annual Transition Pathway Initiative data for 175 firms over the period 2018–2025, we apply discrete-time Markov chains to capture state persistence and directional mobility in MQ and CP, while Hidden Markov Models uncover latent performance regimes shaping firms’ transition trajectories across three decarbonisation horizons (2028, 2035, and 2050). To enhance interpretability and policy relevance, CatBoost-based feature importance analysis identifies governance, emissions-related, and sector-specific drivers of transitions between states. The results indicate a steady and highly persistent improvement in Management Quality, reflecting cumulative consolidation of governance structures, while Carbon Performance evolves more slowly and heterogeneously, with only moderate convergence emerging toward the 2050 horizon. Latent-regime estimates reveal a gradual shift from volatile, low-performance pathways toward more stable transition regimes over time. From a policy perspective, the findings suggest that governance improvements alone are insufficient to ensure timely emission reductions, highlighting the need for digitally enabled, sector-specific regulatory incentives and enforcement mechanisms targeting realised Carbon Performance. Full article

Plastic waste poses a major environmental issue because it persists in nature for long durations and recycling facilities are not readily available. The conversion of waste materials into hydrogen creates two beneficial effects that help decrease pollution levels and establish hydrogen as a clean energy source for sustainable low-carbon systems. In this study, an integrated process for plastic-to-hydrogen conversion was developed using Aspen HYSYS v14. The system uses pyrolysis, steam reforming, and the water–gas shift (WGS) reaction, through pseudo-components of polyethylene, polypropylene and polystyrene to model decomposition processes. Following optimization, the hydrogen fraction in the syngas rose from 0.664 to 0.733. At this stage, the process produced roughly 651 kg of hydrogen per hour in steady operation. In addition, char and pyrolysis oil were produced as co-products that can be valorized in circular economy applications The implementation of heat integration achieved an 8% reduction in utility demand that proves that internal energy recovery stands as a vital element for sustainable design. The techno-economic analysis showed that the project would achieve a 39% internal rate of return and payback period of 5.95 years, thus proving its financial stability. The research demonstrates how modern process modeling techniques enable the creation of clean technology systems that address plastic pollution problems while producing low-carbon hydrogen. Full article

This bibliometric study provides a comprehensive mapping of the scientific landscape on education financing in Europe, highlighting its main trends, conceptual foundations, and influential contributions. Based on 168 publications indexed in the Web of Science and analyzed using VOSviewer, the research traces the chronological evolution of the field, explores keyword co-occurrence networks, and identifies the most impactful studies. Findings indicate a steady growth of academic interest after 2005, with a notable peak from 2014 to 2019, stimulated by major European policy frameworks such as Europe 2020 and Horizon 2020. Keyword analysis reveals dominant themes—including higher education, performance-based funding, human capital, digitalization, and governance—while areas such as pre-university education, digital equity, and large-scale comparative assessments remain insufficiently explored. Highly cited publications focus on the diversification of funding sources, the tensions generated by neoliberal approaches in higher education, and the persistent challenges of financing inclusive education. In addition, country-level analysis highlights an uneven geographic distribution of research output, with scientific production concentrated in a limited number of European countries, alongside contributions from non-European partners reflecting international collaboration patterns. Overall, results show that European research on education financing is fragmented and often shaped by political and institutional priorities. By identifying major research directions and uncovering existing gaps, this study offers a valuable foundation for future investigations aimed at strengthening equity, sustainability, and innovation in the financing of education systems. Full article

Reliable state-of-charge (SoC) estimation is crucial for safe and efficient battery management. However, it is challenging in practice. Terminal-voltage sensitivity becomes weak in open-circuit-voltage (OCV) plateau regions. Model uncertainty also persists at practical sampling periods. To tackle this issue, this paper proposes a discrete-time, model-based SoC estimation framework. This framework combines a dual-polarization equivalent-circuit model with a tuning-light sliding-mode observer. It is specifically designed for digitally sampled battery management systems. The modeling stage includes: (i) a discrete-time DP representation suitable for embedded use, (ii) a shape-preserving PCHIP reconstruction of the OCV–SoC curve and its derivative, and (iii) an effective-slope regularization mechanism that maintains non-vanishing output sensitivity even in flat OCV regions. On top of this structure, a boundary-layer SMO is developed with output-error shaping, model-driven gain scaling, and simple bias-compensation terms based on integral correction and leaky Coulomb counting. A discrete-time Lyapunov analysis is conducted directly on the surface dynamics. This analysis shows finite-time reaching to the boundary layer and a practical limit on the steady-state error that depends on the sampling period, disturbance level, and boundary-layer width. Numerical tests on a DP model identified from experimental data indicate that the proposed method achieves SoC accuracy similar to a switching-gain adaptive SMO. The results confirm the benefits of a model-centric design. The discrete-time formulation and convergence proof, which do not depend on high sampling rates, provide robustness advantages over traditional sliding-mode methods. The proposed method also performs better than a tuned EKF in plateau regions, requiring much less tuning effort. Full article

Thiocyanate (SCN⁻), a persistent inorganic contaminant widely present in industrial wastewater, poses severe risks to plant growth and photosynthesis. Hydrogen sulfide (H₂S) is an emerging gaseous signaling molecule involved in the regulation of plant stress responses; however, its role in modulating Rubisco energy metabolism and activation under SCN⁻ stress remains unclear. Here, we investigated the effects of exogenous H₂S on magnesium homeostasis, ATP/NADPH metabolism, Rubisco activation, and photosynthetic performance in rice seedlings exposed to SCN⁻ stress via physiological, biochemical, and transcriptional approaches. We found that exogenous H₂S significantly increased Mg²⁺ accumulation, enhanced H⁺-ATPase and Mg²⁺-ATPase activities, and promoted Rubisco activase (RCA) abundance and activity. These changes were accompanied by reduced steady-state ATP and NADPH contents, indicating that increased energy consumption was driven by accelerated Calvin cycle turnover. At the transcriptional level, H₂S regulated key genes involved in ATP hydrolysis, Mg²⁺ transport, Rubisco activation, and chlorophyll biosynthesis. Consequently, the chlorophyll content, stomatal conductance, and transpiration rate improved under SCN⁻ stress. Collectively, our results demonstrate that exogenous H₂S enhances photosynthetic efficiency and Rubisco carboxylation capacity by coordinating Rubisco energy metabolism and activation. Full article

Taking cities along the Beijing-Hangzhou Grand Canal as the research subject, this study constructs urbanization and ecological environment indices to examine changes in urbanization and ecological environment in these cities from 2008 to 2024. First, an urbanization index and an ecological environment index were constructed for cities along the Beijing-Hangzhou Grand Canal. The spatiotemporal trends of these indices were analyzed. Subsequently, a coupling coordination model was developed to examine how coupling coordination levels evolve. Finally, a GM(GM (1,1) model was used to forecast future trends in coupling coordination levels. The conclusions are as follows: (1) Urbanization along the canal advanced rapidly and consistently. In contrast, the ecological environment followed a slow recovery and eventual steady improvement. Although the coupling coordination status historically improved from “barely coordinated imbalance” to “primary coordination,” the ecological subsystem consistently lagged behind. (2) Spatially, coordination levels show clear “core-periphery” and “south-high, north-low” disparities. High-coordination clusters are centered in the Yangtze River Delta urban agglomeration, while low-coordination zones are concentrated in western Shandong and southeastern Hebei, with these spatial clustering effects growing stronger over time. (3) Projections from the GM (1,1) model suggest that, under a natural evolution scenario, the entire canal region will reach an “intermediate coordination” phase by 2030. However, significant internal disparities are expected to persist. Full article

Low-voltage mini-grids play a crucial role in expanding electricity access for rural and remote communities. However, they continue to face technical and operational barriers that hinder their performance and reliability. This study reviewed the evolution of research on technical challenges in low-voltage mini-grids from 2005 to 2025. Using the PRISMA approach, data were extracted from the Scopus database, yielding 155 publications for bibliometric analysis. Bibliometrix in R Studio was used to examine publication trends, geographical contributions, and thematic evolution, while qualitative synthesis identified key engineering and operational constraints. The findings revealed a steady increase in research outputs since 2020, driven by global policy commitments, including Sustainable Development Goal 7 and the Paris Agreement. Persistent technical barriers include voltage and frequency instability, inadequate power quality monitoring, inefficient integration of energy storage, poor control coordination, and limited system design optimisation. African nations contribute less to global research despite being most affected by energy poverty, highlighting capacity and funding gaps. The study highlights the need for integrated solutions combining smart control, hybrid storage, and grid-interconnection technologies to enhance resilience and reliability. For policymakers and practitioners, the findings advocate for investment in research, capacity building, and locally tailored technical standards designed for resource-constrained contexts. This review provides a comprehensive evidence base to guide future research and policy directions aimed at achieving sustainable, technically robust, and financially viable mini-grid systems for universal energy access. Full article

Background/Objectives: Understanding changes in dental service utilization is vital for planning effective oral health strategies in aging societies. In this study, we aimed to elucidate nationwide trends in major dental procedures in Japan from fiscal year (FY) 2016 to FY2023, and to assess the age, period, and cohort effects underlying these trends. Methods: Using open data from Japan’s National Database of Health Insurance Claims, five procedure types were analyzed: cavity filling, dental calculus removal, tooth extraction, dental crown procedures, and denture procedures. Descriptive analyses were performed to examine the annual and age-specific changes in the number of procedures per 1000 population. Age–period–cohort (APC) analyses were conducted using Poisson regression with spline functions, applying 10-year age groups. Results: From FY2016 to FY2023, restorative and prosthetic procedures, including cavity fillings, crowns, and dentures, demonstrated a steady decline, whereas preventive procedures, such as dental calculus removal increased, particularly among younger age groups. The APC analysis revealed distinct age-, period-, and cohort-related patterns in dental service utilization. Age effects indicated relatively higher rates of prosthetic procedures among older adults, whereas cohort effects suggested generational improvements in oral health. Period effects showed a downward shift beginning in FY2020, temporally aligned with the coronavirus disease pandemic. Conclusions: The combined descriptive and APC analyses indicate evolving patterns in dental service utilization in Japan, characterized by increased preventive care among younger generations and persistent age-related differences in prosthetic service use. These findings provide population-based evidence relevant for planning sustainable oral healthcare systems in aging societies. Full article

For listed companies, board diversity is often associated with improved decision-making, sustainability and financial performance. However, prior studies have neglected the interplay between board diversity and executive remuneration, especially in developing countries, over extended time horizons, and at the level of individual executives. This study addressed this gap by examining the evolution of board diversity and executive remuneration in South African listed companies from 2002 to 2017. Specifically, it investigated trends in board diversity and the determinants of executive remuneration, with particular attention to gender and ethnic pay gaps. Descriptive and regression analyses were conducted on a dataset comprising 8835 executive-level observations. Findings reveal a steady increase in female and non-white executive representation, possibly to align with societal expectations and remain legitimate. However, persistent gender and ethnic pay gaps were also noted, which might indicate that white and/or male executives are more entrenched and able to extract additional remuneration in line with the managerial power theory. The study contributes to the literature by documenting long-term trends in diversity and remuneration, providing empirical evidence on the influence of demographic attributes on remuneration outcomes, and offering insights for regulators, investors and non-executive directors seeking to advance equity and effective governance. Full article

This review examines the status, challenges, and future trajectories of global mussel aquaculture within the blue food system. Despite steady production growth, mussels’ relative contribution to total bivalve output has significantly declined over recent decades due to disproportionate expansion of oyster, clam, and scallop sectors. A major geographical production shift has occurred, with Asia, spearheaded by China, emerging as the dominant region, supplanting traditional European producers while the Americas rapidly ascend. China’s overwhelming dominance in overall bivalve production starkly contrasts with its underdeveloped mussel sector, where growth lags behind other bivalves despite substantial absolute increases, reflecting a fundamental restructuring of species composition. The industry faces interconnected sustainability constraints: persistent vulnerabilities in spat supply stemming from environmental variability, hatchery limitations, and disease transmission risks; escalating environmental stressors including climate change impacts, harmful algal blooms, pollution, and pathogens; structural flaws in value chains characterized by fragmented production, market volatility, and underutilized byproducts; and governance challenges related to spatial access and licensing inefficiencies. This review advocates for a comprehensive strategy to boost the mussel aquaculture. These encompass advancing hatchery technology and genetic breeding programs, implementing ecosystem-based management such as multi-trophic systems and AI-enhanced environmental monitoring, restructuring value chains through producer cooperation and high value product diversification, and establishing science-based spatial planning frameworks with streamlined governance. Addressing these challenges holistically is critical to position mussel farming as a resilient pillar of sustainable blue food production capable of reconciling ecological integrity with economic viability and social equity. Full article