Search Results (1,815)

The growing interest in no- and low-alcohol (NoLo) wines reflects evolving consumer preferences toward moderation, health, and mindful drinking. This study investigates consumer perception and acceptance of NoLo wines within a traditional wine context (Trentino-Alto Adige, Italy), based on a survey of 344 people. Respondents were primarily between 18 and 34 years old. Descriptive results indicated low familiarity and purchase frequency but positive attitudes, especially among women and health-oriented consumers. Nonparametric tests revealed that gender significantly affected familiarity, social acceptance, and willingness to recommend NoLo wines, with women respondents showing higher engagement and acceptance. Age showed a weaker but still significant effect on familiarity, while consumers who regularly consumed NoLo beverages exhibited greater social acceptance and willingness to recommend. In addition, logit and probit models suggested that preference for mid-to-low alcohol levels and prior experience with alcohol-free drinks positively influenced purchase frequency. In contrast, traditional wine consumption habits and expenditure had no significant effects. These findings suggest that while NoLo wine adoption in a premium wine region such as Trentino-Alto Adige is in an emerging phase, it is underpinned by evolving young consumer motivations toward moderation, well-being, and social inclusivity, offering clear opportunities for targeted market development and product innovation. Full article

With the rapid growth of residential electric vehicles, synchronized charging during peak periods can induce severe load ramping and exceed distribution network capacity limits. To mitigate these issues, governments have promoted a unified build-and-operate community model that enables centralized coordination of community charging and ensures real-time responsiveness to grid dispatch signals. Targeting this emerging operational paradigm, a dual-dimensional compensation mechanism for real-time electric vehicle (EV) demand response is proposed. The mechanism integrates two types of compensation: power regulation compensation, which rewards users for providing controllable power flexibility, and state-of-charge (SoC) loss compensation, which offsets energy deficits resulting from demand response actions. This dual-layer design enhances user willingness and long-term engagement in community-level coordination. Based on the proposed mechanism, a bi-level optimization framework is developed to realize efficient real-time regulation: the upper level maximizes the active response capacity under budget constraints, while the lower level minimizes the aggregator’s total compensation cost subject to user response behavior. Simulation results demonstrate that, compared with conventional fair-share curtailment and single-compensation approaches, the proposed mechanism effectively increases active user participation and reduces incentive expenditures. The study highlights the mechanism’s potential for practical deployment in unified build-and-operate communities and discusses limitations and future research directions. Full article

The continuous tightening of European regulatory requirements, particularly under the General Safety Regulation (GSR), has considerably increased the scope and cost of proving ground testing required for the validation of Advanced Driver Assistance Systems (ADASs) and Automated Driving Systems (ADSs). This study presents a methodology for constructing complex proving ground test scenarios aimed at supporting early-stage functional validation and cost-efficient preparation for type approval. The method is based on the systematic analysis of proving ground–relevant ADAS regulations and the classification of test case variations according to sensing, actuation, and execution complexity. By filtering and combining representative test cases, minimum and maximum complexity scenarios were developed and evaluated on the ZalaZONE proving ground in Hungary. The results demonstrate that the proposed approach can substantially reduce test duration, facility occupancy, and overall validation costs, while maintaining the representativeness and credibility of results. Beyond cost savings, the methodology offers a scalable and practical framework for physical validation, supporting manufacturers in achieving regulatory compliance with reduced time and expenditure. Full article

Combined application of organic (M) and chemical fertilizer (C) is a significant measure to enhance soil fertility and ensure food security. In 2023 and 2024, we established six treatments: T1 (no fertilization), T2 (100% C), T3 (75% C + 25% M), T4 (50% C + 50% M), T5 (25% C +75% M), and T6 (100% M), with three replicates for each treatment. The total amount of nitrogen applied to the soil for T2–T6 was the same, and the organic fertilizer was compost sourced from cow dung. The aims of this study were to explore the effects of organic fertilizer combined with chemical fertilizer on soil fertility, and apparent nutrient balance, to investigate its possible economic benefits. We also analyzed the influence of the combined application of organic and chemical fertilizers on the degree of coupling and coordination (D) between soil fertility and economic benefits. The total phosphorus, total potassium, available phosphorus, available potassium, and organic matter in the soil all showed an increasing trend with an increase in the proportion of organic fertilizer applied. T2 reduced the soil pH by 7.41–8.94% compared with T1, while applying organic fertilizers (T3–T6) increased the soil pH by 0.72–8.62% compared with T2. T4 is conducive to the balance of income and expenditure of nitrogen, phosphorus, and potassium elements. The corn yield, net income, and input–output ratio all showed an initial increase followed by a decrease with an increase in the proportion of organic fertilizer applied, and their values all reached the maximum under T4. Based on the CRITIC-TOPSIS method and the coupling coordination degree model, it was determined that the fertilization strategy with the highest comprehensive score and D under the conditions of this experiment was 50% C +50% M (T4), which not only improved soil fertility but also achieved the highest economic benefit. The research results were of great significance for promoting sustainable agricultural development. Full article

Intangible cultural heritage (ICH) is deeply embedded in everyday social life, yet its officially recognized spatial distribution reflects both the independent influences of cultural traditions, development trajectories, and governance practices, and the complex interactions among them. Focusing on 494 national-level ICH items across ten categories in Jiangsu(J), Zhejiang(Z), and Shanghai(H), this study adopts a social-geographical perspective to examine both the spatio-temporal evolution and the driving mechanisms of ICH recognition in one of China’s most developed regions. After rigorous verification of point-based ICH locations, we combine kernel density estimation and the average nearest neighbor index to trace changes across five batches of national designation, and then employ the univariate and interaction detectors of the Geodetector model to assess the effects of 28 natural, socioeconomic, and cultural-institutional variables. The results show, first, that ICH exhibits significant clustering along river corridors and historical cultural belts, with a persistent high-density core in the Shanghai–southern Jiangsu–northern Zhejiang zone and a clear shift over time from highly concentrated to more dispersed and territorially balanced recognition. Second, human-environment factors—especially factors such as urban and rural income and consumption; residents’ education and cultural expenditures; and public education and cultural facilities—have far greater explanatory power than natural conditions, while different ICH categories embed distinctively in urban and rural socio-economic contexts. Third, bivariate interactions reveal that natural and macroeconomic “background” variables are strongly amplified when combined with demographic and cultural factors, whereas interactions among strong human variables show bivariate enhancement with diminishing marginal returns. In summary, these findings enrich international debates on the geography of ICH by clarifying how recognition processes align with regional development and social equity agendas, and they provide a quantitative basis for category-sensitive, place-based strategies that coordinate income policies, public cultural services, and the joint safeguarding of tangible and intangible heritage in both urban renewal and rural revitalization planning. Full article

With the large-scale integration of new energy and power electronic devices into power systems, frequency stability has become an increasingly critical concern. To maintain frequency stability while mitigating the high capital expenditure of energy storage systems (ESSs), this paper develops a control framework centered on edge energy management terminals (EEMTs). The design is based on a demonstration project in which distributed energy resources (DERs) and flexible loads collaboratively provide frequency regulation. A monitoring station is implemented to make fast frequency response (FFR) resources dispatchable, detectable, measurable, and tradable. Furthermore, a control strategy tailored for building- and factory-level applications is proposed. This strategy enables real-time optimal scheduling of DERs and flexible loads through coordinated communication between EEMTs and net load units (NLUs). Two field tests further demonstrate the effectiveness and advantages of the proposed approach. In addition, this paper proposes a coordinated scheme in which wind farms and NLUs jointly participate in frequency regulation, aiming to mitigate the response delay of NLUs and the secondary frequency drop observed in wind farms. The feasibility and benefits of this scheme are validated through experimental tests. Full article

This study aims to investigate the impact of green finance on corporate sector investments and their associated environmental outcomes. The authors collected cross-sectional survey data with a sample of four hundred firms selected from the five green-relevant industries in an emerging economy. The results indicate that, over the last three years, seventy percent of firms have accessed at least one green instrument. Overall, the firms under study indicate that PKR 3.4 million is being allocated to green finance, and PKR 2.7 million is spent on CAPEX. However, each million PKR is associated with a ten percent capital expenditure, which exhibits the highest adoption of the renewable energy sector, while the manufacturing sector has the lowest adoption. Regression results depict that Greenhouse gas reduction is only achievable if expenditure on R&D is ensured for environmental gains. This study indicates a declining incremental impact when green finance exceeds PKR 5.00 million, suggesting that firms’ limitations in utilizing the additional amount may be a factor. Financially constrained firms achieve stronger environmental goals, confirming that strict criteria to finance projects show more responsibility and discipline in executing projects. However, small- and medium-sized firms are confronted with barriers, such as lack of information and transaction costs. The findings of this study highlight the need for a multi-layered regulatory framework, innovation-driven incentives, and fintech integration to fully realize the potential of green finance. The outcome enables financial institutions, sustainability practitioners, and regulators to connect financial markets, national climate, and development goals. Full article

China’s higher education system is the largest globally but faces significant spatial imbalance issues. While studies have examined the spatial distribution of universities, long-term dynamic analysis, quantitative exploration of influencing factors, and investigation of spatial heterogeneity are lacking. This study investigates the spatiotemporal evolution of China’s regular higher education institutions (HEIs) from 1952 to 2023 by using ArcGIS spatial analysis and integrating the Geographical Detector and Multi-scale Geographically Weighted Regression (MGWR) models. Findings reveal that (1) the spatial distribution of China’s HEIs has become increasingly clustered, transitioning from a “point-like” to a “network-like” and finally to a “surface-like” pattern, with its center shifting southwestward—this evolution reflects the gradual formation of a spatially sustainable layout that adapts to regional development needs. (2) Multiple interacting factors influence distribution—including the number of full-time faculty, regional GDP, national universities’ presence during the Republic of China era, and fiscal expenditure on education—with significant variations in their explanatory power. Regional population size also exerts a notable influence. (3) The impact of these factors exhibits significant spatial heterogeneity, with pronounced local imbalances. Thus, multi-scale processes operating at different geographical levels have shaped HEIs’ spatial pattern and addressing this heterogeneity is a key prerequisite for achieving sustainable and equitable development of higher education. These findings provide critical insights for optimizing higher education resource allocation, promoting balanced regional development, and advancing the construction of a high-quality education system in China. Full article

Background/Objectives: Adherence to the Mediterranean Diet (MD) is shaped by its multidimensional nature, encompassing nutritional, cultural, and environmental dimensions. However, systematic reviews indicate a notable decline in MD adherence across Mediterranean countries over the past decade. This study aimed to objectively assess the affordability of the MD under Turkish conditions using nationally representative data for a typical four-person household. Methods: A Turkish Mediterranean Diet Food Basket (MDFB) was developed for a reference household and its affordability evaluated through a four-step analytical framework: (i) construction of the MD food basket, (ii) collection of price data and estimation of average monthly cost, (iii) verification of nutritional adequacy, and (iv) assessment of affordability by comparing the basket cost with household income indicators Results: Based on the regional equivalised median income in the TR62 region (21,331 TRY/month), the monthly cost of the MDFB (TRY 20,930) represented 98% of household income. Using the national median income for couples with children (27,918 TRY/month), this share decreased to 75%. Both estimates substantially exceed the national average share of food expenditure (18.1%). Among the lowest-income households, the MDFB cost corresponded to 214% of income, indicating economic inaccessibility. For middle- and high-income groups, the ratios were 91.9% and 37.3%, respectively. Conclusions: Despite its recognized health benefits, the MD remains economically unattainable for most households in Türkiye, underscoring persistent socioeconomic disparities in diet quality and accessibility. Full article

Background: Vitamin D (VD) insufficiency is present in chronic pancreatitis (CP), leading to increased cardiovascular risk, bone complications, impaired quality of life, and increased mortality. This study aimed to determine the prevalence of VD deficiency in patients with CP and to assess its relationship to CP progression and associated cardiovascular complications. Methods: Seventy patients were enrolled and evaluated for pancreatic exocrine insufficiency by fecal elastase-1, CP severity by M-ANNHEIM classification, cardiovascular risk by 10-year risk mortality scores (SCORE and FRS), and for arterial stiffness using pulse wave velocity (PWV) at a. carotis and a. femoralis. Determination of 25-hydroxyvitamin D was performed by an LC-MS/MS method. Resting energy expenditure was calculated using the Harris–Benedict formula. Results: Mean VD levels were 37.86 ± 24.36 nmol/L (range 3.854–99.874 nmol/L); only five patients were in sufficiency status. VD levels correlated significantly with body mass index (BMI) and resting energy expenditure. In patients with severe structural changes, we observed lower VD levels regardless of etiology (p < 0.01). VD levels were lower in patients with pancreatic exocrine insufficiency (PEI), p < 0.05. Patients with mild CP by M-ANNHEIM had lower levels of VD compared to moderate and advanced CP, p < 0.05. At a cut-off of VD 11.95 nmol/L, we verified pancreatic lithiasis with 89.4% sensitivity, 83.3% specificity, and AUC of 0.826 ± 0.113 (95% CI, 0.61–1). VD status worsened with the increase in the 10-year risk mortality by both SCORE and FRS and PWV, p < 0.05. Conclusions: Most of our patients with CP were VD insufficient. Monitoring of nutritional status in patients with CP is mandatory to prevent the development of malnutrition complications and the associated morbidity and mortality. Full article

The beginning of the 21st century is associated with a significant technological leap on a global scale, which has had a substantial impact on production and economic processes at the national and regional levels. This radical technological change in the economy is linked to the emergence and development of artificial intelligence and effective knowledge management, which are the main drivers of economic growth. The use of AI today can be traced in many different areas of applied science—medicine, physics, mathematics, and engineering design, including modeling, planning, and management of territorial systems. The accumulation of large databases and other information necessary for AI to function is directly related to the spatial aspects of economic development, which is also based on local potential (a place-based approach). At the same time, local knowledge resources and innovation potential are not fully utilized in the context of technology diffusion and AI implementation in individual countries and regions. In this regard, this study aims to analyze the role of regional innovation systems, with a focus on AI development, and to track their impact across individual European regions, using NUTS2 spatial-level data to ensure objectivity. The authors consider AI innovation a modern tool for decision-making in the implementation of regional policy, with a specific impact on cohesion between EU regions. The results of the study show a direct link between the localization of regional innovation systems, R & D expenditure, AI implementation, and the economic development of European regions. Important factors influencing this process are the degree of Internet coverage, the capacity to generate innovation, the degree of AI implementation in the individual economic sectors of the countries, the growth of the ICT sector in relation to the overall development of GDP and the economy, and the result of the smart specialisation of regional innovation systems. Full article

This study investigates the relationship between labour productivity, wages, and social welfare expenditure (SWE) in South Africa, with implications for fiscal sustainability and budget deficits. A theoretical model linking government expenditure, taxation, and labour market dynamics is developed and empirically tested using data from 1994 to 2022. Results from state and private labour market regressions reveal significant evidence of wage–productivity decoupling in the state labour market, where wages are influenced more by institutional factors than productivity growth. Conversely, private sector wages show a positive association with productivity, inflation, and working capital balances. The budget deficit model demonstrates strong alignment with empirical trends, though it underestimates the impact of economic shocks such as COVID-19. Findings suggest that increases in productivity alone will not reduce social welfare dependency in South Africa, given structural inequality, weak labour absorption, and low skills development. Policy implications highlight the need for targeted investment, industrial expansion, and education reform to mitigate rising welfare expenditure and ensure fiscal sustainability. Full article

Overweight and obesity are major public health concerns among children and adolescents worldwide. The most prevalent form is exogenous–constitutional obesity, which is driven by a sedentary lifestyle and an unhealthy diet in which caloric intake exceeds energy expenditure. Beyond their association with chronic disease, these factors are closely linked to deficits in cognitive development and executive functions essential for learning (including working memory, sustained attention, planning, behavioral self-regulation, and cognitive flexibility). Oxidative stress (OS), characterized by the accumulation of reactive oxygen species (ROS) in cells and extracellular fluids, is a significant potential mediator in childhood obesity and an important contributor to its comorbidities. The antioxidant defense system (AOD)’s activity largely depends on levels of trace element cofactors, which determine the body’s resistance to adverse environmental factors (the “maladaptation phenomenon”). OS and trace element deficiencies contribute to the development of morphological changes in the brain, thus serving as a critical connecting link between childhood obesity and cognitive impairment. Non-pharmacological interventions are the most accessible and effective approach for prevention and treatment. Bioactive compounds derived from food and natural plants, classified as antioxidants and phytopreparations, may represent a promising complementary approach. These compounds are most effective when used in combination with sustained lifestyle modifications in children. Research in this area can help define future directions for study and develop targeted intervention strategies in the pediatric population. The aim of this review is to examine the relationship between OS, antioxidant cofactor micronutrients, and cognitive outcomes in childhood obesity and to explore mechanisms, evidence, and therapeutic opportunities. Full article

Comprehending the spatial–temporal transformation of urban resilience (UR) is fundamental for promoting sustainable urban growth in the Chinese context. In this study, a multi-dimensional index framework is developed to cover economic, social, ecological, and infrastructural aspects of resilience, assessing urban resilience across 282 prefecture-level cities between 2005 and 2022. By integrating the Time-Varying Entropy Method (TEM) with the Two-Stage Nested Theil Index (TNTI), we quantify the intensity and origins of spatial disparities in UR. Furthermore, spatial econometric models are employed to examine β convergence across regional and temporal dimensions. Additionally, the research adopts an Optimal Parameter-based Geographical Detector (OPGD) approach to explore and quantify the major determinants affecting urban resilience. The results reveal that (1) UR has significantly improved nationwide, with higher levels concentrated in eastern and southern China; (2) intra-provincial disparities are the dominant source of spatial differences, and continue to expand; (3) UR shows robust β-convergence nationally and regionally, although σ-convergence is limited to specific periods; (4) savings deposits per capita, ratio of employees, per capita fiscal expenditure and market size are identified as the core factors driving UR. The findings offer new insights into urban spatial governance under multi-dimensional constraints and challenges and serve as empirical guidance for narrowing resilience gaps and promoting balanced regional development. Full article

This study presents a methodology for optimizing repair intervals of mining equipment by integrating economic efficiency and reliability criteria. A review of existing maintenance strategies revealed their limitations, and a mathematical model was developed that incorporates both projected financial expenditures and the probability of equipment failures, enabling more accurate prediction of the optimal repair timing. This study introduces a novel integration of the Weibull reliability distribution with a cost-convolution optimization model, explicitly capturing the trade-off between economic efficiency and failure risk. Unlike traditional fixed-schedule approaches, the proposed model provides analytically optimized repair intervals derived from observed degradation trends. Statistical analysis demonstrates that unplanned repairs are, on average, 56% more costly than scheduled ones, highlighting the need to revise current preventive maintenance practices. The cost comparison is based on 34 restoration records collected from publicly available supplier price lists and field maintenance logs, converted into a unified currency. Based on operational data and reliability parameter estimation, the optimal repair interval was determined to be 5129 machine hours, which minimizes both the probability of failure and total maintenance-related financial losses, while reducing unplanned downtime. Unlike traditional fixed-schedule approaches, the proposed model allows adaptive adjustment of maintenance intervals according to the actual degradation characteristics of the equipment. The practical significance of the research lies in its ability to help mining enterprises reduce expenditures on corrective repairs, extend the service life of machinery, and improve overall operational efficiency. The findings contribute to advancing maintenance optimization in the mining industry, supporting more sustainable and cost-effective equipment management. Full article