Search Results (31,536)

This study investigates the environmental dimension of sustainable development across fifteen post-Soviet republics in 2022. While sustainability is generally understood as a triadic construct—economic, social, and environmental—this paper isolates the ecological pillar to highlight cross-country differences shaped by industrial legacies, institutional capacity, and governance models. A composite Environmental Performance Index (EPI) is developed using the Mazziotta–Pareto Index (MPI), which captures both average performance and internal consistency across three SDG-related domains: SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), and SDG 15 (Life on Land). The study adds to existing literature as it includes a non-compensatory composite index and cluster analysis, and in policy terms, it provides a benchmarking system for facilitating ecological transition in the post-Soviet context. The results reveal strong divergence across the region: Baltic countries and Moldova achieve higher scores, reflecting policy convergence with the European Union and stronger environmental institutions, while Central Asian republics lag due to resource dependence, water scarcity, and weaker governance. Geographic cluster analysis corroborates these differences, showing clear spatial patterns of environmental convergence and divergence. Correlation analysis further demonstrates that environmental sustainability is positively associated with GDP per capita, HDI, and life expectancy, while negatively linked with inequality and fertility rates. These findings stress the need for context-sensitive and evidence-based policies, intra-regional cooperation, and integrated governance mechanisms to advance ecological transition in line with the 2030 Agenda for Sustainable Development. Full article

Achieving environmentally sustainable growth is a core challenge for developing economies, yet the welfare consequences of green development policies for vulnerable populations remain understudied. This article investigates the distributional impacts of one of the world’s largest development interventions: China’s energy transition. By integrating provincial-level energy metrics with a decade-long household panel survey (CFPS), we employ a fixed-effects model to provide a holistic assessment of the policy’s effects on household well-being. The analysis reveals a stark trade-off: a 10% increase in clean energy adoption generates significant non-monetary well-being gains, equivalent to a 190,000 CNY annual income rise, primarily through improved environmental quality and cleaner cooking fuel access. However, these benefits are partially offset by rising energy costs. Our heterogeneity analysis reveals a clear regressive burden: the transition significantly increases energy expenditures for rural and low-income households, while having a negligible or even cost-reducing effect on their urban and high-income counterparts. Our findings demonstrate that while the energy transition promotes aggregate welfare, its benefits are unevenly distributed, potentially exacerbating energy poverty and inequality. This underscores a critical development challenge: green growth is not automatically inclusive. We argue that for the energy transition to be truly pro-poor, it must be accompanied by robust social protection mechanisms, such as targeted subsidies, to shield the most vulnerable from the adverse economic shocks of the policy. Full article

In response to escalating global concerns about waste generation throughout the product life cycle, the Circular Economy (CE) has emerged as a central alternative to the dominant linear economic model. The integration of CE principles into supply chain management is manifested in Circular Supply Chain Management (CSCM), offering a novel perspective on supply chain sustainability. Despite the growing research interest in developing CSCM to enhance supply chain sustainability, assessment approaches of this concept are notably absent in the literature. This study addresses this gap by focusing on the assessment and performance measurement of circular practices in the context of supply chains. At first, the research presents a bibliometric analysis to delve into the performance and science mapping of CSCM assessment, providing a comprehensive view of the scientific landscape. Subsequently, a content analysis is then used to identify current assessment approaches, focusing on frameworks, methodologies, barriers, enablers, and CE strategies. The study proposes a conceptual model based on the SCOR framework, including core categories such as enablers (business model, technology, collaboration, design) and results (material, water, energy flows) represented by the Rs strategies. This model contributes to bridging theoretical gaps and guiding practitioners and policymakers in the design, evaluation, and implementation of circular supply chains. Full article

Few studies have explored the holistic public health risk assessment associated with toxic elements (TEs) and their bioaccessibility in integrated urban environmental media including soils, vegetables, atmospheric particles, dust, etc. Urban industrial complex areas like Qingshan-Chemical District (QCD) in the Chinese Wuhan city, located within the Yangtze River Economic Belt, face increasing environmental exposure risks due to industrial activities. This study innovatively assessed the hierarchical risks of toxic metals in 4 environmental media (air PM, dust, soil, vegetables) from the QCD based on field sampling and chemical analysis, and developed an improved fuzzy health risk assessment model based on toxic metals’ in vitro bioaccessibilities of different exposure pathways and triangular fuzzy numbers for handling parameter uncertainties. The study found that the highest health risks were associated with ingestion, particularly from consuming homegrown vegetables. Carcinogenic risks for arsenic (As), lead (Pb), and cadmium (Cd) via ingestion exceeded the admissible threshold of 1.00 × 10⁻⁶, with As showing the highest risk ([1.92 × 10⁻³, 2.37 × 10⁻³]), followed by Cd ([2.98 × 10⁻⁵, 3.67 × 10⁻⁵]) and Pb ([7.92 × 10⁻⁷, 1.48 × 10⁻⁶]). Inhalation risks from soil, dust, and air particulates were below the threshold, indicating lower respiratory concerns. Dermal exposure, especially from soil and dust, posed elevated carcinogenic risks for As ([7.47 × 10⁻⁶, 8.06 × 10⁻⁶]). With the screened priority risk control toxic metals and pathways, the targeted measures including relocating vegetable planting areas, promoting cultivation of low-enrichment crops, building vegetation buffer zones around the industrial park, etc., were proposed. Full article

The integration of solar generation into national energy balances is associated with a wide range of technical, economic, and organizational challenges, the solution of which requires the adoption of innovative strategies for energy system management. The inherent variability of electricity production, driven by fluctuating climatic conditions, complicates system balancing processes and necessitates the reservation of capacities from conventional energy sources to ensure reliability. Under modern market conditions, the pricing of generated electricity is commonly based on day-ahead forecasts of day energy yield, which significantly affects the economic performance of solar power plants. Consequently, achieving high accuracy in day-ahead electricity production forecasting is a critical and highly relevant task. To address this challenge, a physico-statistical model has been developed, in which the analytical approximation of daily electricity generation is represented as a function of a random variable—cloud cover—modeled by a β-distribution. Analytical expressions were derived for calculating the mathematical expectation and variance of daily electricity generation as functions of the β-distribution parameters of cloudiness. The analytical approximation of daily generation deviates from the exact value, obtained through hourly integration, by an average of 3.9%. The relative forecasting error of electricity production, when using the mathematical expectation of cloudiness compared to the analytical approximation of daily generation, reaches 15.2%. The proposed forecasting method, based on a β-parametric cloudiness model, enhances the accuracy of day-ahead production forecasts, improves the economic efficiency of solar power plants, and contributes to strengthening the stability and reliability of power systems with a substantial share of solar generation. Full article

The randomness and volatility of wind power increase peak regulation pressure, leading to wind curtailment despite the deep peak regulation efforts of thermal power units. By integrating conventional power source dispatch and high-energy-consuming load configuration, a two-layer optimization model is developed to maximize wind curtailment absorption and minimize thermal power deep peak regulation costs. The model first analyzes the fused magnesium load’s operating characteristics and its dispatch-participation model, then combines with the thermal power deep peak regulation model for hierarchical joint peak regulation. Applying the method to an actual regional system via CPLEX shows that it reduces wind curtailment, optimizes thermal power deep peak regulation, and improves power generation economic efficiency. Full article

In modern robotics, actuators are crucial for achieving effective movement and ensuring robustness. Although different applications demand specific actuator qualities, an actuator with built-in compliance and high torque density is generally preferred. Recently, harmonic gearboxes have become widely used in robotics for actuation due to their zero-backlash, lightweight design, flexibility, and high torque density. However, the intricate and precise machining required for these gearboxes makes them economically unviable in some cases. This work presents the RM-Act, a novel Radial Modular Actuator that employs synchronous belts as a harmonic speed reducer. The RM-Act retains the advantages of the harmonic principle, making it a promising candidate for robotic actuation. This paper describes the novel actuation principle and its validation through a prototype, along with a model identification to define its characteristics. The actuator demonstrates a nominal torque density of 10.08 N·m/kg, indicating its potential for efficient robotic applications. Full article

Greater Casablanca, one of Africa’s largest metropolitan regions, is undergoing significant spatial and demographic transformation. Yet, the underlying patterns of these dynamics remain poorly understood. This study investigates population dynamics and spatial inequalities in Greater Casablanca between 2014 and 2024. The analysis combines geospatial data, regression modeling, and clustering techniques to explore the interplay between demographic change, housing affordability, public-transport accessibility, and economic activity, providing a data-driven perspective on how these factors shape spatial inequalities and the region’s urban development trajectory. The results reveal a clear core–periphery divide. The central prefecture has lost population despite continued land consumption, while peripheral communes have experienced rapid demographic and economic expansion. This growth is strongly associated with affordable housing and high rates of new-firm formation, but it occurs where transport access remains weakest. Cluster analysis identifies four socio-spatial types, ranging from a shrinking but well-served core to fast-growing, poorly connected peripheries. The study underscores the need for integrated policy interventions to improve transport connectivity, implement inclusive housing strategies, and manage economic decentralization in ways that foster balanced and sustainable metropolitan development. By situating Greater Casablanca’s trajectory within global urbanization debates, this research extends core–periphery and shrinking-city frameworks to a North African context and provides evidence-based insights to support progress towards Sustainable Development Goal 11. Full article

This article examines the global efforts to govern and regulate Artificial Intelligence (AI) in response to its rapid development and growing influence across many parts of society. It explores how governance takes place at multiple levels, including international bodies, national governments, industries, companies, and communities. The study draws on a wide range of official documents, policy reports, and international agreements to build a timeline of key regulatory and standardization milestones. It also analyzes the challenges of coordinating across different legal systems, economic priorities, and cultural views. The findings show that while some progress has been made through soft-law frameworks and regional partnerships, deep divisions remain. These include unclear responsibilities, uneven enforcement, and risks of regulatory gaps. The article argues that effective AI governance requires stronger international cooperation, fair and inclusive participation, and awareness of power imbalances that shape policy decisions. Competing global and commercial interests can create obstacles to building systems that prioritize the public good. The conclusion highlights that future governance models must be flexible enough to adapt to fast-changing technologies, yet consistent enough to protect rights and promote trust. Addressing these tensions is critical for building a more just and accountable future of AI. Full article

Background: The rising prevalence of neurodegenerative conditions such as dementia underscores the impact of population aging. Consequently, long-term care needs have increased and are often met by family members through informal caregiving, thereby supporting formal care systems by reducing associated costs. These caregivers face physical and mental health challenges, raising concerns about their psychological well-being and prompting interest in both clinical and psychosocial research. Ryff’s eudaimonic model offers a robust framework for the assessment of psychological well-being; yet, in Romania, data on this population segment remain limited. Objective: This study aimed to compare the psychological well-being of Romanian dementia family caregivers with a reference population from the Romanian adaptation of the 54-item Ryff Psychological Well-Being Scale, and to explore how sociodemographic characteristics relate to relevant differences across well-being dimensions. Methods: A cross-sectional study was conducted among 70 Romanian family caregivers recruited from a single clinical hospital in Bucharest, Romania. Caregivers completed the 54-item Ryff Scale (Romanian adaptation), and scores were compared to reference values using one-sample t-tests with bootstrap confidence intervals. The most relevant dimension (purpose in life) was dichotomized and further examined in relation to sociodemographic and caregiving variables using Chi-squared and Fisher’s exact tests. Results: Caregivers reported significantly lower scores compared to the reference population in purpose in life (p < 0.001, d = −1.01), personal growth (p < 0.001, d = −0.91), and positive relations (p = 0.01, d = −0.30). The most pronounced deficit was observed in purpose in life, with 85.7% of caregivers scoring below the reference mean. This dimension was further examined in relation to caregiver characteristics. Retirement status showed a statistically significant association with Purpose in Life, with retired caregivers more likely to report lower scores (χ² (1) = 4.04, p = 0.04), supported by the likelihood ratio test (p = 0.01) and a linear trend (p = 0.05). Additional marginal associations were found for household income (p = 0.14) and whether the patient slept in a separate room (p = 0.15), suggesting possible links between caregiver well-being and economic or environmental conditions. Conclusions: The study findings highlight notable psychological vulnerabilities among Romanian dementia caregivers, particularly in purpose in life and personal growth. Associations with structural and contextual factors such as retirement status, income, and caregiving environment suggest that caregiver well-being is shaped by broader socioeconomic conditions. While the magnitude of these deficits may be underestimated due to elevated stress levels in the reference group, the findings underscore the need for targeted clinical, social, and policy-level interventions aimed at strengthening existential meaning and personal development in culturally specific settings. Full article

Promoting the green transformation of traditional diesel-powered ships is crucial for achieving carbon peaking and carbon neutrality goals. This study focuses on diesel-engine ships operating in the inland river areas of Anhui Province, China. It proposes two electrification retrofit schemes based mainly on lithium iron phosphate (LIP) batteries: full electrification and diesel-engine redundancy. The economic and environmental impacts of these schemes are analyzed and compared with those of conventional diesel-powered ships. A cost prediction algorithm based on model prediction is proposed, supported by a mathematical model for cost analysis. Results indicate that for electric tankers to become economically viable, battery costs must decrease through yearly improvements in energy density and reduced degradation rates. Additionally, government support is essential, such as raising carbon prices and providing subsidies—either an annual operational subsidy of CNY 80,000 or an initial construction subsidy of CNY 500,000. The study concludes that continued advances in battery technology, together with policy and financial support, will accelerate the large-scale electrification of ships. Full article

In situ leaching represents an efficient and safe method for uranium mining, where a suboptimal well flow rate distribution leads to solution imbalances between wells, forming stagnant zones that increase operational costs. This study examines a real technological block from the Budenovskoye deposit, applying reactive transport modeling to optimize well flow rates and reduce operational time and reagent consumption. A reactive transport model was developed based on mass conservation and Darcy’s laws coupled with chemical kinetics describing sulfuric acid interactions with uranium minerals ($U{O}_2$ and $U{O}_3$). The model simulated a technological block with 4 production and 18 injection wells arranged in hexagonal cells over 511–542 days to achieve 90% uranium recovery. Six approaches for well flow rate redistribution were compared, based on different weighting factor calculation methods: advanced traditional, linear distance, squared distance, quadrilateral area, and two streamline-based approaches utilizing the minimum and average time of flight. The squared distance method achieved the highest efficiency, reducing operational costs by 5.7% through improved flow redistribution. The streamline-based methods performed comparably and offer potential advantages for heterogeneous conditions by automatically identifying hydraulic connections. The reactive transport modeling approach successfully demonstrated that multi-criteria optimization methods can improve ISL efficiency by 3.9%–5.7% while reducing operational costs. Full article

Background: Euthanasia and physician-assisted suicide (EPAS) are highly contentious topics with significant medical, legal, and cultural implications. Previous research suggests that various sociodemographic, health, and psychosocial factors determine attitudes toward EPAS. This study set out to identify psychosocial predictors of support for EPAS. We hypothesized that perceived control, self-efficacy, and social support would each predict support for EPAS after controlling for sociodemographic and health-related variables. Methods: For this study, we recruited 446 Jewish Israeli adults who were 82.32 years of age on average (SD = 5.99; range 65–101 years). Participants completed a battery of questionnaires including a series of vignettes featuring hypothetical family members with a terminal illness (i.e., cancer, dementia, Parkinson’s disease). We performed a three-step hierarchical regression equation, controlling for demographic factors (age, gender, education, relationship status, economic status, and religiosity) as well as perceived and relative physical health. Results: As hypothesized, both self-efficacy and (the absence of) social support predicted support for EPAS; perceived control did not. Religiosity was the strongest predictor of opposition to EPAS. Fully 31% of variance in support for EPAS was predicted by this regression model. Conclusion: Support for EPAS does not appear to reflect a pervasive need for control over all aspects of life (i.e., perceived control) but a more specific need for personal autonomy (i.e., self-efficacy). Longitudinal research is required over multiple points of data collection to ascertain how change in social support affects support for EPAS in late life. Policy makers should embrace these findings when formulating end-of-life care policies, ensuring that both social support and personal autonomy are prioritized in the care of older adults. Full article

Seafood plays a key role in a healthy diet due to its high content of essential nutrients. However, its global trade and complex supply chains expose it to frequent mislabeling and food fraud. This study investigates Italian consumers’ willingness to pay (WTP) for traceable seafood products, exploring how blockchain technology (BT) can enhance transparency and economic sustainability in the fish supply chain. An online questionnaire, administered in 2022 and 2024, gathered responses from a diverse demographic, focusing on four representative seafood species: farmed sea bass, striped venus clams, giant red shrimp, and albacore tuna. Results indicate that most respondents—primarily with higher education levels—value traceability and are willing to pay a premium for certified, traceable seafood. The study models the economic feasibility of implementing BT at both national and regional levels and finds that the consumer’s WTP exceeds the additional costs incurred by adopting BT. These findings support the viability of traceability systems in improving food safety and sustainability, while reinforcing consumer trust. The results also underscore the importance of providing clear information at the point of purchase, particularly regarding species, origin, and production methods—factors critical to informed seafood choices and advancing more sustainable consumer behavior in Italy. Full article

In response to the challenges faced by high-energy-consuming enterprises in utilizing renewable energy and implementing low-carbon operations, this paper proposes a multi-objective optimization strategy based on source–storage–load collaborative scheduling. The strategy establishes a refined model of aluminum electrolysis load, thoroughly considering the coupling relationship between temperature, production output, and power consumption. Additionally, it develops a dynamic coupling model between multi-functional crane loads and aluminum electrolysis production to reveal the influence mechanism of auxiliary equipment on the main production process. Based on this foundation, this paper constructs a multi-objective optimization model that targets the minimization of operating costs, the minimization of carbon emissions, and the maximization of the renewable energy consumption rate. An improved heuristic intelligent optimization algorithm is employed to solve the model. The simulation results demonstrate that, under a renewable energy penetration of 67.8%, the proposed multi-objective optimization strategy achieves a maximum reduction in carbon emissions of 1677.35 t and an increase in renewable energy consumption rate of 12.11%, compared to the conventional single-objective economic optimization approach, while ensuring the stability of aluminum electrolysis production. Furthermore, when the renewable energy penetration is increased to 76.2%, the maximum reduction in carbon emissions reaches 8260.97 t, and the renewable energy consumption rate is improved by 18.86%. Full article