Search Results (6,400)

Existing studies on the abrasive cutting process have primarily focused on the influence of cutting conditions on key parameters such as temperature, cut-off wheel wear, and machined surface quality. However, the choice of working conditions is often made based on the experience of qualified personnel or using data from reference sources. The literature also provides optimal values for the cutting mode elements, but these are only valid for specific methods and cutting conditions. This article proposes a new multi-objective optimization approach for determining the conditions for the implementation of the abrasive cutting process that leads to Pareto-optimal solutions for improving economic efficiency, evaluated by production rate and manufacturing net cost parameters. To demonstrate this approach, the elastic abrasive cutting process of structural steels C45 and 42Cr4 has been selected. Theoretical–experimental models for production rate and manufacturing net cost have been developed, reflecting the complex influence of the conditions of the elastic abrasive cutting process (compression force of the cut-off wheel on the workpiece and rotational frequency of the workpiece). Multi-objective compromise optimization based on a genetic algorithm has been conducted by applying two methods—the determination of a compromise optimal area for the conditions of the elastic abrasive cutting process and the generalized utility function method. Optimal conditions for the implementation of the elastic abrasive cutting process have been determined, ensuring the best combination of high production rate and low manufacturing net cost. Full article

Potato (Solanum tuberosum L.) is one of the most important food crops in the world, ranking fourth after rice, maize, and wheat. Potatoes are exposed to biotic and abiotic environmental factors, which lead to economic losses and increase the possibility of food security threats in many countries. Traditional potato breeding faces several challenges, primarily due to its genetic complexity and the time-consuming nature of the process. Therefore, gene editing—CRISPR-Cas technology—allows for more precise and rapid changes to the potato genome, which can speed up the breeding process and lead to more effective varieties. In this review, we consider CRISPR-Cas technology as a potential tool for plant breeding strategies to ensure global food security. This review summarizes in detail current and potential technological breakthroughs that open new opportunities for the use of CRISPR-Cas technology for potato breeding, as well as for increasing resistance to abiotic and biotic stresses, and improving potato tuber quality. In addition, the review discusses the challenges and future perspectives of the CRISPR-Cas system in the prospects of the development of potato production and the regulation of gene-edited crops in different countries around the world. Full article

Pork is a major global source of animal protein, and improving both its production efficiency and meat quality is a central goal in modern animal agriculture and food systems. This study investigated post-inflection-point growth patterns in two genetically distinct pig breeds—the lean-type Yorkshire pig (YP) and the fatty-type Qingyu pig (QYP)—with the aim of elucidating breed-specific characteristics that influence pork quality and yield. Comprehensive evaluations of carcass traits, meat quality attributes, nutritional composition, and gene expression profiles were conducted. After the growth inflection point, carcass traits exhibited greater variability than meat quality traits in both breeds, though with distinct patterns. YPs displayed superior muscle development, with the longissimus muscle area (LMA) increasing rapidly before plateauing at ~130 kg, whereas QYPs maintained more gradual but sustained muscle growth. In contrast, intramuscular fat (IMF)—a key determinant of meat flavor and texture—accumulated faster in YPs post inflection but plateaued earlier in QYPs. Correlation and clustering analyses revealed more synchronized regulation of meat quality traits in QYPs, while YPs showed greater trait variability. Gene expression patterns aligned with these phenotypic trends, highlighting distinct regulatory mechanisms for muscle and fat development in each breed. In addition, based on the growth curves, we calculated the peak age at which the growth rate declined in lean-type and fat-type pigs, which was approximately 200 days for YPs and around 270 days for QYPs. This suggests that these ages may represent the optimal slaughter times for the respective breeds, balancing both economic efficiency and meat quality. These findings provide valuable insights for enhancing pork quality through precision management and offer theoretical guidance for developing breed-specific feeding strategies, slaughter timing, and value-added pork production tailored to consumer preferences in the modern food market. Full article

Smart cities are technologically advanced urban environments where interconnected systems and data-driven technologies enhance public service delivery and quality of life. These cities rely on information and communication technologies, the Internet of Things, big data, cloud computing, and other Industry 4.0 tools to support efficient city management and foster citizen engagement. Often referred to as digital cities, they integrate intelligent infrastructures and real-time data analytics to improve mobility, security, and sustainability. Ubiquitous sensors, paired with Artificial Intelligence, enable cities to monitor infrastructure, respond to residents’ needs, and optimize urban conditions dynamically. Given the increasing significance of Industry 4.0 in urban development, this study adopts a bibliometric approach to systematically review the application of these technologies within smart cities. Utilizing major academic databases such as Scopus and Web of Science the research aims to identify the primary Industry 4.0 technologies implemented in smart cities, assess their impact on infrastructure, economic systems, and urban communities, and explore the challenges and benefits associated with their integration. The bibliometric analysis included publications from 2016 to 2023, since the emergence of urban researchers’ interest in the technologies of the new industrial revolution. The task is to contribute to a deeper understanding of how smart cities evolve through the adoption of advanced technological frameworks. Research indicates that IoT and AI are the most commonly used tools in urban spaces, particularly in smart mobility and smart environments. Full article

This study examines the role of human capital, technological investment, and institutional quality in promoting economic complexity in South Africa, with implications for sustainable development and the strategic role of Small and Medium Enterprises. Motivated by the growing importance of productive sophistication for long-term development in emerging economies (notably SDG 8 and SDG 9), the study examines both long-run and short-run dynamics using the Autoregressive Distributed Lag approach, with robustness checks via Fully Modified Least Squares, Dynamic Least Squares, and Canonical Cointegration Regression. Structural Vector Autoregression is employed to assess the persistence of shocks, while the Toda–Yamamoto causality test evaluates causality. The results reveal that institutional quality significantly enhances economic complexity in the long run, while technological investment exhibits a negative long-run impact, potentially indicating absorptive capacity constraints within industries. Though human capital and income per capita do not influence complexity in the long run, they have short-term effects, with income per capita having the most immediate influence. Variance decomposition shows that shocks to technological investment are essential for economic complexity, and are the most persistent, followed by human capital and institutional quality. These findings show the need for institutional reforms that lower entry barriers for SMEs in industries, targeted innovation policies that support upgrading, and human capital strategies aligned with driven industrial transformation. The study offers insights for policymakers striving to influence structural drivers to advance sustainable industrial development and achieve the SDGs. Full article

China’s economy is shifting from an era of rapid expansion to one focused on high-quality development, making it imperative to tackle environmental degradation linked to energy use. Understanding how New Quality Productive Forces (NQPF) interact with energy efficiency, along with the mechanisms driving this relationship, is essential for economic transformation and long-term sustainability. This study establishes an evaluation framework for NQPF, integrating technological, green, and digital dimensions. We apply fixed-effects models, the spatial Durbin model (SDM), a moderation model, and a threshold model to analyze the influence of NQPF on Green Total Factor Energy Efficiency (GTFEE) and its spatial implications. This underscores the necessity of distinguishing it from traditional productivity frameworks and adopting a new analytical perspective. Furthermore, by considering dimensions such as input, application, innovation capability, and market efficiency, we reveal the moderating role and heterogeneous effects of artificial intelligence (AI). The findings are as follows: The development of NQPF significantly enhances GTFEE, and the conclusion remains robust after tail reduction and endogeneity tests. NQPF has a positive spatial spillover effect on GTFEE; that is, while improving the local GTFEE, it also improves neighboring regions GTFEE. The advancement of AI significantly strengthens the positive impact of NQPF on GTFEE. AI exhibits a significant U-shaped threshold effect: as AI levels increase, its moderating effect transitions from suppression to facilitation, with marginal benefits gradually increasing over time. Full article

Achieving sustainable development goals remains a core issue in global development. In response, China has proposed the development of new quality productive forces (NQPFs) through innovative thinking, emphasizing that fostering NQPFs is both an intrinsic requirement and a pivotal focus for advancing high-quality development. Concurrently, the intelligent transformation of the manufacturing sector serves as a critical direction for China’s economic restructuring and upgrading. This paper places “new quality productive forces” and “intelligent transformation of manufacturing” within the same analytical framework. Starting from the logical chain of “new quality productive forces—three major mechanisms—intelligent transformation of manufacturing,” it concretizes the value implications of new quality productive forces into a systematic conceptual framework driven by the synergistic interaction of three major mechanisms: the mechanism of revolutionary technological breakthroughs, the mechanism of innovative allocation of production factors, and the mechanism of deep industrial transformation and upgrading. This study constructs a “3322” evaluation index system for NQPFs, based on three formative processes, three driving forces, two supporting systems, and two-dimensional characteristics. Simultaneously, it builds an evaluation index system for the intelligent transformation of manufacturing, encompassing intelligent technology, intelligent applications, and intelligent benefits. Using national time-series data from 2012 to 2023, this study assesses the development levels of both NQPFs and the intelligent transformation of manufacturing during this period. The study further analyzes the impact of NQPFs on the intelligent transformation of the manufacturing sector. The research results indicate the following: (1) NQPFs drive the intelligent transformation of the manufacturing industry through the three mechanisms of innovative allocation of production factors, revolutionary breakthroughs in technology, and deep transformation and upgrading of industries. (2) The development of NQPFs exhibits a slow upward trend; however, the outbreak of the pandemic and Sino-US trade frictions have caused significant disruptions to the development of new-type productive forces. (3) The level of intelligent manufacturing continues to improve; however, from 2020 to 2023, due to the impact of the COVID-19 pandemic and Sino-US trade conflicts, the level of intelligent benefits has slightly declined. (4) NQPFs exert a powerful driving force on the intelligent transformation of manufacturing, exerting a significant positive impact on intelligent technology, intelligent applications, and intelligent efficiency levels. Full article

Natural fiber-based biocomposites are rapidly gaining traction in sustainable manufacturing. However, their supply chain (SC) designs at the feedstock pre-processing stage often lack robust multicriteria decision-making evaluations, which can impact downstream processes and final product quality. This case study proposes a sustainability-driven multicriteria decision-making framework for selecting pre-processing equipment configurations within a hemp-based biocomposite SC. Using a cradle-to-gate system boundary, four alternative configurations combining balers (square vs. round) and hammer mills (full-screen vs. half-screen) are evaluated. The analytical network process (ANP) model is used to evaluate alternative SC configurations while capturing the interdependencies among environmental, economic, social, and technical sustainability criteria. These criteria are further refined with the inclusion of sub-criteria, resulting in a list of 11 key performance indicators (KPIs). To evaluate ranking robustness, a non-linear programming (NLP)-based sensitivity model is developed, which minimizes the weight perturbations required to trigger rank reversals, using an IPOPT solver. The results indicated that the Half-Round setup provides the most balanced sustainability performance, while Full-Square performs best in economic and environmental terms but ranks lower socially and technically. Also, the ranking was most sensitive to the weight of the system reliability and product quality criteria, with up to a 100% shift being required to change the top choice under the ANP model, indicating strong robustness. Overall, the proposed framework enables decision-makers to incorporate uncertainty, interdependencies, and sustainability-related KPIs into the early-stage SC design of bio-based composite materials. Full article

Biochar, a carbon-rich material derived from biomass, presents a sustainable solution to several pressing challenges in U.S. agriculture, including soil degradation, carbon emissions, and waste management. Despite global advancements, the U.S. biochar market remains underexplored in terms of economic viability, adoption potential, and sector-specific applications. This narrative review synthesizes two decades of literature to examine biochar’s applications, production methods, and market dynamics, with a focus on its economic and environmental role within the United States. The review identifies biochar’s multifunctional benefits: enhancing soil fertility and crop productivity, sequestering carbon, reducing greenhouse gas emissions, and improving water quality. Recent empirical studies also highlight biochar’s economic feasibility across global contexts, with yield increases of up to 294% and net returns exceeding USD 5000 per hectare in optimized systems. Economically, the global biochar market grew from USD 156.4 million in 2021 to USD 610.3 million in 2023, with U.S. production reaching ~50,000 metric tons annually and a market value of USD 203.4 million in 2022. Forecasts project U.S. market growth at a CAGR of 11.3%, reaching USD 478.5 million by 2030. California leads domestic adoption due to favorable policy and biomass availability. However, barriers such as inconsistent quality standards, limited awareness, high costs, and policy gaps constrain growth. This study goes beyond the existing literature by integrating market analysis, SWOT assessment, cost–benefit findings, and production technologies to highlight strategies for scaling biochar adoption. It concludes that with supportive legislation, investment in research, and enhanced supply chain transparency, biochar could become a pivotal tool for sustainable development in the U.S. agricultural and environmental sectors. Full article

In today’s dynamic and highly uncertain environment, organizations, particularly in the aviation sector, face increasing challenges that demand resilient, flexible, and data-driven change management decisions. Responding to the growing need for structured approaches to managing complex uncertainties—geopolitical tensions, economic volatility, social shifts, rapid technological advancements, environmental pressures and regulatory changes—this research proposes a theoretical change management model for aviation service providers, such as airports. Integrating three analytical approaches, the model offers a robust, multi-method approach for supporting sustainable transformation under uncertainty. Normative analysis using Bayesian decision theory identifies influential external environmental factors, capturing probabilistic relationships, and revealing causal links under uncertainty. Prescriptive planning through scenario theory explores alternative future pathways and helps to identify possible predictions, offer descriptive evaluation employing fuzzy comprehensive evaluation, and assess decision quality under vagueness and complexity. The proposed four-stage model—observation, analysis, evaluation, and response—offers a methodology for continuous external environment monitoring, scenario development, and data-driven, proactive change management decision-making, including the impact assessment of change and development. The proposed model contributes to the theoretical advancement of the change management research area under uncertainty and offers practical guidance for aviation organizations (airports) facing a volatile external environment. This framework strengthens aviation organizations’ ability to anticipate, evaluate, and adapt to multifaceted external changes, supporting operational flexibility and adaptability and contributing to the sustainable development of aviation services. Supporting aviation organizations with tools to proactively manage systemic uncertainty, this research directly supports the integration of sustainability principles, such as resilience and adaptability, for long-term value creation through change management decision-making. Full article

This study synthesizes the rapidly expanding evidence on how digital technologies reshape international trade, with a particular focus on small and medium-sized enterprises (SMEs). Guided by two research questions—(RQ1) How do digital tools influence the volume and composition of cross-border trade? and (RQ2) How do these effects vary by countries’ development level and firm size?—we conducted a PRISMA-compliant systematic literature review covering 2010–2024. Searches across eight major databases yielded 1857 records; after duplicate removal, title/abstract screening, full-text assessment, and Mixed Methods Appraisal Tool (MMAT 2018) quality checks, 86 peer-reviewed English-language studies were retained. Findings reveal three dominant technology clusters: (1) e-commerce platforms and cloud services, (2) IoT-enabled supply chain solutions, and (3) emerging AI analytics. E-commerce and cloud adoption consistently raise export intensity—doubling it for digitally mature SMEs—while AI applications are the fastest-growing research strand, particularly in East Asia and Northern Europe. However, benefits are uneven: firms in low-infrastructure settings face higher fixed digital costs, and cybersecurity and regulatory fragmentation remain pervasive obstacles. By integrating trade economics with development and SME internationalization studies, this review offers the first holistic framework that links national digital infrastructure and policy support to firm-level export performance. It shows that the trade-enhancing effects of digitalization are contingent on robust broadband penetration, affordable cloud access, and harmonized data-governance regimes. Policymakers should, therefore, prioritize inclusive digital-readiness programs, while business leaders should invest in complementary capabilities—data analytics, cyber-risk management, and cross-border e-logistics—to fully capture digital trade gains. This balanced perspective advances theory and practice on building resilient, equitable digital trade ecosystems. Full article

Improving the green innovation quality (GIQ) of center cities is crucial to achieve sustainable urban agglomeration development. Utilizing data on green patent citations and economic indicators across cities in the Yangtze River Delta urban agglomeration (YRD) from 2003 to 2022, this research examines the influence of center cities’ GIQ on the economic performance of peripheral municipalities. The results show the following: (1) Center cities’ GIQ exerts a significant suppressive effect on peripheral cities’ economic growth overall. Heterogeneity analysis uncovers a distance-dependent duality. GIQ stimulates growth in proximate cities (within 300 km) but suppresses it beyond this threshold. This spatial siphoning effect is notably amplified in national-level center cities. (2) Mechanisms suggest that GIQ accelerates the outflow of skilled labor in peripheral cities through factor agglomeration and industry transfer mechanisms. Concurrently, it impedes the gradient diffusion of urban services, collectively hindering peripheral development. (3) Increased government green attention (GGA) and industry–university–research cooperation (IURC) in centers can mitigate these negative impacts. This paper contributes to the theoretical discourse on center cities’ spatial externalities within agglomerations and offers empirical support and policy insights for the exertion of spillover effects of high-quality green innovation from center cities and the sustainable development of urban agglomeration. Full article

‘Mushy halibut syndrome’ (MHS) is associated with inferior fillet quality in Greenland halibut and is reported to occur in commercial catches across the North Atlantic. MHS constitutes a quality issue in fisheries and leads to economic losses and food wastage. Despite the known challenges associated with MHS, quantitative data on product properties are lacking, and yet they are crucial to assess actual losses and value-adding processing potential. As part of a larger effort to document and characterize MHS in Greenland halibut, we investigated how thaw drip loss (TDL), cooked drip loss (CDL), cooked yield, and tissue compressibility and elasticity differ between normal and ‘mushy’ halibut fillets. The fillets were sorted into three categories: normal, intermediate MHS, and severe MHS. The mean TDL and CDL increased more than three-fold in both MHS categories compared to normal fillets, while cooked yield decreased by approximately 20%. Fillets severely affected by MHS demonstrated high tissue compressibility (56%) and poor elasticity (46%), while the elasticity of the fillets belonging to the intermediate MHS category did not differ significantly from that of normal ones. These findings provide new insights into the product attributes of fillets affected by MHS, which are important for developing utilization and valorization strategies. Full article

Acid mine drainage (AMD) remains a critical environmental challenge in South Africa due to its severe impact on water quality, ecosystems and public health. Numerous studies on AMD management, treatment and resource recovery have been conducted over the past 20 years. This study presents a comprehensive review of research activities on AMD in South Africa from 1998 to 2025, highlighting key trends, emerging challenges and future directions. The study reveals a significant focus on passive and active treatment methods, environmental remediation and the recovery of valuable resources, such as iron, rare earth elements (REEs) and gypsum. A bibliometric analysis was conducted to identify the most influential studies and thematic research areas over the years. Bibliometric tools (Biblioshiny and VOSviewer) were used to analyse the data that was extracted from the PubMed database. The findings indicate that research production has increased significantly over time, with substantial contributions from top academics and institutions. Advanced treatment technologies, the use of artificial intelligence and circular economy strategies for resource recovery are among the new research prospects identified in this study. Despite substantial progress, persistent challenges, such as scalability, economic viability and policy implementation, remain. Furthermore, few technologies have moved beyond pilot-scale implementation, underscoring the need for greater investment in field-scale research and technology transfer. This study recommends stronger industry–academic collaboration, the development of standardised treatment protocols and enhanced government policy support to facilitate sustainable AMD management. The study emphasises the necessity of data-driven approaches, sustainable technology and interdisciplinary cooperation to address AMD’s socioeconomic and environmental effects in the ensuing decades. Full article

In recent decades, the rapid expansion of the food processing industry has led to significant losses and waste, with the fruit and vegetable sector among the most affected. According to the Food and Agriculture Organization of the United Nations (FAO), losses in this category can reach up to 60%. Vegetable waste includes edible parts discarded during processing, packaging, distribution, and consumption, often comprising by-products rich in bioactive compounds such as polyphenols, carotenoids, dietary fibers, vitamins, and enzymes. The underutilization of these resources constitutes both an economic drawback and an environmental and ethical concern. Current recovery practices, including their use in animal feed or bioenergy production, contribute to a circular economy but are often limited by high operational costs. In this context, fermentation has emerged as a promising, sustainable approach for converting vegetable by-products into value-added food ingredients. This process improves digestibility, reduces undesirable compounds, and introduces probiotics beneficial to human health. The present review examines how fermentation can improve the nutritional, sensory, and functional properties of plant-based foods. By presenting several case studies, it illustrates how fermentation can effectively valorize vegetable processing by-products, supporting the development of novel, health-promoting food products with improved technological qualities. Full article