Search Results (7,398)

Growing global challenges have made it imperative to evaluate economic activities not only in terms of economic growth but also from the perspectives of environmental and social well-being. Within this context, Women’s Production and Business Cooperatives have emerged as critical collective initiatives that support local development. In this study, “Women’s Production and Business Cooperatives” refer to cooperatives established and predominantly managed by women to collectively engage in the production and commercialization of goods and services, generate income and employment opportunities for their members, and promote women’s economic and social empowerment. Hereafter, these organizations are referred to as “women’s cooperatives.” However, studies that comprehensively examine the sustainability practices of women’s cooperatives through the framework of Elkington’s Triple Bottom Line (economic, social, and environmental sustainability) remain limited. From the perspective of Stakeholder Theory, cooperatives are regarded as organizations that extend beyond the pursuit of economic profit by creating value for both internal and external stakeholders, including women, local communities, the environment, consumers, and public institutions. Accordingly, this study aims to provide an in-depth examination of the sustainability practices adopted by women’s cooperatives within these three dimensions, as well as to identify the challenges they encounter. This study adopted a qualitative research design, utilizing in-depth interviews with seven presidents and managers representing women’s cooperatives. The findings suggest that zero-waste practices, the adoption of circular economy principles, and the transition toward green agriculture constitute the primary sustainability initiatives, whereas high technology and packaging costs, together with insufficient institutional collaboration, represent the major challenges to the environmental sustainability. Within the economic sustainability dimension, the findings indicate that the participating cooperatives have increasingly shifted toward industrial production standards, value-added by-products, and business-to-business (B2B) marketing strategies. Nevertheless, rising input and logistics costs, together with unfair competition, continue to pose significant challenges. As relates to social sustainability, the findings highlight intergenerational transmission of cultural heritage, psychosocial recovery, efforts to challenge social prejudice, inter-cooperative solidarity, and the allocation of resources for social benefit, including scholarship support. Overall, the findings reveal that these cooperatives make meaningful contributions to multidimensional sustainability and stakeholder well-being, thereby providing valuable empirical insights into the sustainability literature. Full article

The implementation of collaborative robots (cobots) in Industry 5.0 requires a synergistic connection between technical safety and integrated management systems (IMSs). This article introduces three newly defined interaction concepts that map technological evolution: HCDI, an approximation for Industry 4.0; HCD_XI, designed for anthropocentric Industry 5.0; and aICD_XI, which anticipates the emerging cognitive era of artificial intelligence. The principal contribution is an original four-phase engineering algorithm for cobot implementation linked to thirteen ISO standards, including ISO 9001, ISO 45001, ISO 14001, ISO/IEC 27001, and ISO/IEC 42001. The algorithm applies the multicriteria SCATI method for process prioritization and the probabilistic reliability performance index (RPI) based on conditional probabilities as an operational reliability acceptance gate, distinct from ISO/TS 15066 functional safety requirements. IMS synergies are visualized by the Synergy HOUSE architectural model. The methodology was validated in an optical quality-inspection cell consisting of MiR100 + UR5e + Robotiq + Smart Vision ADMIN 4.0. Evaluated via Monte Carlo simulation, the pre-operational index reached RPI = 0.9801. Deployment of the node demonstrated a 60.0% increase in productivity, a 64.5% decrease in the defect rate, a statistically significant 32.0% reduction in cognitive workload, and a 50.0% reduction in total energy consumption (ISO 50001), enabled by the transition to lights-out operation. At the same time, the energy paradox of edge cooling for AI was described. The results confirm the robustness of the algorithm for systematic and sustainable enterprise transformation. Full article

Extensive small-ruminant grazing sustains food production on the Mediterranean land with few alternative uses, yet supervision is intermittent and welfare oversight weak. Digital monitoring is expected to close that gap, but detection alone does not produce intervention. In remote rangelands the link is unreliable, so an inference may reach the farmer late, degraded or not at all, and an alert arriving after the animal has moved is not a weaker alert but a different decision. This study develops a human-in-the-loop decision framework in which the delivery state of the link becomes a decision variable rather than a transport detail, coupling technology, farmer behaviour and governance. Constructed through design science research and structured analysis of an EU-funded project’s specifications and evaluation plans, it comprises a seven-layer architecture, a decision-episode schema, a connectivity-aware alert lifecycle, a decision-provenance matrix, and an evidence-maturity classification constraining what may be claimed. Five decision classes from a Cretan sheep and goat pilot instantiate it. After applying it, specification inconsistencies invisible to component-level review surfaced, among which is an alert payload lacking the coordinates, confidence and severity that its own indicators require. The framework is an instantiated specification, not a validated intervention: no detection, delivery, acknowledgement, usability or sustainability outcome is measured. Full article

Alginate is a biodegradable and renewable natural polysaccharide that has been extensively investigated for the design of macromolecular delivery systems. This review presents an overview of alginate-based microparticles regarding the relationship between molecular structure, gelation behavior, and functional performance. The impacts of main structural parameters (mannuronic to guluronic acid (M/G) ratio, molecular weight, and block distribution) are discussed comprehensively. Particular attention is given to Ca²⁺-mediated ionic gelation, including egg-box junction zone formation and the development of three-dimensional hydrogel networks. Different production strategies such as external and internal gelation, emulsification, and microfluidic approaches are evaluated in terms of their impact on particle morphology and network homogeneity. In addition, the effects of formulation and process parameters on encapsulation efficiency, mechanical stability, and mass transfer behavior are analyzed. Furthermore, release mechanisms are discussed in relation to network structure and polymer-solute interactions. The environmental significance of alginate-based systems is also emphasized as sustainable alternatives to synthetic polymeric carriers. Full article

The transition towards a circular economy is widely expected to reduce dependence on primary resources, yet higher levels of circularity do not necessarily translate into proportional reductions in absolute material use. This study investigates the relationship between circular material use and dematerialization across the EU-27 over the period 2010–2024, with particular attention to whether this relationship remains constant at different levels of circularity. Using Eurostat data, the empirical analysis combines descriptive statistics with linear panel regression models and nonlinear threshold regression. Domestic material consumption (DMC) and raw material consumption (RMC) are employed as complementary indicators of material use. The results indicate that higher circular material use is associated with lower material consumption after controlling for country-specific heterogeneity and common time effects. However, this relationship is not constant across different levels of circularity. The threshold analysis identifies a significant nonlinear relationship for RMC, showing that the negative association between circularity and material use is substantially stronger at lower levels of circularity and weakens as circularity increases. A robustness analysis using DMC reveals a similar regime-dependent pattern, although the statistical evidence for threshold nonlinearity is weaker. These findings do not provide evidence of a circular economy rebound effect in the strict sense but instead suggest diminishing marginal dematerialization effects as circularity advances. Overall, the results indicate that increasing circularity remains an important component of sustainable resource management but is unlikely to achieve substantial reductions in absolute material use without complementary structural changes. Circular economy policies should therefore combine material recirculation with measures promoting resource-efficient design, product longevity, reuse, and reductions in overall material demand. Full article

Pharmaceutical pollutants have emerged as a critical class of aquatic micropollutants due to their continuous release, persistence, and potential impacts on ecosystems and human health. Conventional wastewater treatment systems are often insufficient to achieve complete removal, necessitating the development of advanced oxidation processes (AOPs), such as Fenton and Fenton-like systems. These processes rely on the generation of reactive oxygen species (ROS), including hydroxyl radicals (•OH), superoxide species, singlet oxygen, and, in some heterogeneous systems, high-valent iron-oxo intermediates, which collectively enable the degradation of structurally diverse and recalcitrant pharmaceutical compounds. Recent advances have highlighted the pivotal role of nanomaterials as catalysts in enhancing Fenton-based processes. Nanostructured catalysts, including iron-based nanoparticles (NPs), metal oxides, carbon-based materials, and bimetallic composites, offer high surface area, tunable redox properties, and improved electron transfer, leading to enhanced catalytic efficiency and mineralization rates. Importantly, the integration of green synthesis approaches using plant extracts, microorganisms, and biopolymers provides environmentally benign routes for nanomaterial fabrication while introducing functional surface groups that improve catalytic performance. Mechanistically, pharmaceutical degradation in Fenton systems involves complex pathways driven by multiple ROS species, including •OH, superoxide radicals, and singlet oxygen, leading to the formation of intermediate products and eventual mineralization. However, challenges such as NP aggregation, metal leaching, incomplete mineralization, and potential toxicity of intermediates remain critical considerations. This review critically evaluates the occurrence of pharmaceutical pollutants, the fundamentals of Fenton and Fenton-like processes, and the design and application of green-synthesized nanomaterials as efficient catalysts. It further explores degradation mechanisms, operational parameters, and sustainability considerations, highlighting future directions for scalable, environmentally responsible water treatment technologies. Full article

Biochar is no longer considered merely a substitute for conventional fillers in asphalt materials; rather, it represents a multifunctional modifier that aligns with the goals of sustainable road design and urban mobility in smart cities. Its application now extends to the rheological modification of asphalt binders, mitigation of asphalt fume emissions, improvement in aging resistance and interfacial adhesion, and assessment of carbon sequestration potential. Biochar can improve the high-temperature stability, rutting and aging resistance, and asphalt–aggregate adhesion of asphalt materials in a suitable dosage, and at the same time reduce emissions of volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), hydrogen sulfide (H₂S), and other fumes. However, the above effects are highly dependent on the biochar feedstock, production process, physicochemical properties, particle size, dosage and degree of dispersion. An excess amount or uneven distribution will reduce the crack resistance and fatigue life at low temperatures; phase separation may also occur and VOC emissions will increase. Therefore, the main problem in this area has shifted from whether biochar is effective to when it can be applied for particular pavement performance goals, what pollutant control targets are aimed for, and over what life-cycle periods. This review integrates evidence obtained at the binder, mastic, and mixture scales and critically evaluates the influence of biochar on pavement performance, fume emissions, aging, interfacial adhesion, and environmental safety. It also argues that empirical dosage selection should be replaced by coordinated optimization of biochar structure, material performance, emission mitigation, and life-cycle impacts. Verification of the low-carbon benefits and environmental safety of biochar-modified asphalt will ultimately require standardized assessment frameworks and consistently defined system boundaries. Ultimately, this work provides a foundation for integrating biochar-modified asphalt into eco-friendly and resilient road infrastructures, aligning with the goals of smart urban mobility and sustainable transportation. Full article

Microalgae facade systems have emerged as an innovative approach in sustainable architecture, offering benefits in energy efficiency, carbon reduction, and biomass production. However, research remains fragmented across biotechnology, environmental engineering, and architectural design, with limited synthesis of its intellectual structure and thematic evolution. This study presents a bibliometric and thematic analysis of microalgae facade research in buildings from 2016 to 2025 using a combined Web of Science and Scopus dataset of 59 publications. The analysis examines publication trends, influential authors, journals, collaboration networks, and key research themes, while science mapping identifies conceptual clusters and their evolution. A sustainability-oriented perspective further links these themes to the environmental, economic, and social dimensions of sustainability and the United Nations Sustainable Development Goals (SDGs). The findings show that research has primarily focused on photobioreactor technologies, energy performance, and biomass production, whereas architectural integration and real-world building applications remain underexplored. Although interdisciplinary collaboration has increased in recent years, the field is still at an early stage of development. This study provides a systematic overview of the current intellectual landscape, identifies research gaps, and offers directions for advancing microalgae facade technologies toward sustainable and net-zero built environments. Full article

Spent coffee grounds (SCGs), a ubiquitous and renewable agricultural waste, have emerged as a promising biosorbent for environmental remediation. This review provides a comprehensive overview of the application of SCG-derived materials in wastewater treatment and gas purification. We systematically summarize their physicochemical characteristics, adsorption performance towards diverse contaminants, and underlying mechanisms. Specifically, modification strategies of raw SCGs are discussed in detail, including chemical modifications (e.g., degreasing/alkali/acid/organic solvent/metal oxide treatment), thermochemical conversions (e.g., pyrolysis, hydrothermal carbonization, and activation), and the fabrication of composites with natural or synthetic materials such as chitosan, clay minerals, and agricultural/industrial wastes. These approaches effectively optimize pore structure, enrich surface functionalities, and enhance selectivity and adsorption capacity. Particular attention is devoted to SCG-derived activated carbon and composites for capturing gaseous pollutants (e.g., CO₂, H₂S, PH₃, and VOCs). Techno-economic analysis of SCG-derived materials production is discussed to evaluate their commercial viability and overall sustainability. Finally, critical research gaps are identified, and future perspectives are proposed, emphasizing the elucidation of adsorption mechanisms, rational material design, and rigorous techno-economic and life-cycle assessments. This review underscores the potential of SCG-based materials as low-cost, high-performance alternatives to conventional adsorbents, aligning with the principles of a circular economy and environmental sustainability. Full article

Green consumption is a crucial pathway for promoting ecological environmental improvement and fostering sustainable economic and social development. Although policies have been continuously implemented and residents’ environmental awareness is gradually increasing, there remains a significant gap in the transformation from cognition to behavior. Promoting green consumption is a systematic project that requires deep coordination among three key actors: the government, enterprises, and residents. However, existing studies have mostly focused on interactions between the government and enterprises, paying insufficient attention to the long-term strategic interactions among all three parties when residents are incorporated into the game system. To address this gap, this study develops a tripartite evolutionary game model that includes the government, enterprises, and residents to analyze the intrinsic driving forces behind the development of green consumption, thereby extending the research perspective to multi-agent dynamic strategic interaction. Through mathematical derivation of the replicator dynamic equations and the Jacobian matrix for each party, this study finds that the system has a unique evolutionarily stable equilibrium point, namely a tripartite synergistic state characterized by active government intervention, green production by enterprises, and green consumption by residents. Sensitivity analysis examines the impact of changes in key parameters on the evolutionary trajectory of the system, providing parameter-level evidence for differentiated policy design. Simulation results indicate that efforts should be directed toward building a collaborative governance system based on government guidance, enterprise responsibility, and resident participation, so as to promote the transformation of green consumption governance from single-dimensional management to pluralistic co-governance. Full article

In the contemporary world, artificial intelligence (AI) is driving profound changes across global institutional, technological, and social processes. However, countries’ readiness for its integration varies substantially by economic development, regional characteristics, and digital maturity. Accordingly, this article aims to assess the alignment between the AI publication footprint, based on Scopus publication data, and national AI readiness, measured by the IMF AI Preparedness Index, across 173 countries, classified by geographic region and income level. The application of analysis of variance (ANOVA), the Kruskal–Wallis test and post hoc comparisons, correlation, regression, and cluster analysis enabled the identification of multidimensional relationships between scientific activity and the four key dimensions of digital maturity: digital infrastructure, human capital/labor market, innovation/economic integration, and regulation/ethics. The results revealed a strong overall global correlation between AI publication footprint and national AI readiness (r = 0.68, R² = 0.46), with the highest level of alignment observed in high-income countries’ readiness (r = 0.67, R² = 0.45), and regions such as the Americas (r = 0.72, R² = 0.51) and Europe (r = 0.57, R² = 0.33). At the same time, lower-income countries demonstrate weak or statistically insignificant relationships, indicating persistent structural barriers. Cluster analysis identified four types of countries, ranging from those with high levels of digital maturity to those with lower levels of national AI readiness. These findings highlight diverse national development trajectories and the need for differentiated policy approaches. However, the AI Publication Footprint is based on absolute cumulative Scopus publication counts and should be interpreted as a proxy for AI knowledge-production capacity rather than a normalized measure of research intensity or actual AI adoption. Given the cross-sectional and primarily bivariate design, the results indicate associations rather than causal effects and do not directly capture educational outcomes. The findings may have implications for education and sustainability by suggesting that disparities in infrastructure, human capital, innovation capacity, and responsible governance may shape the conditions for inclusive and sustainable AI-enabled education; these implications require direct empirical testing. Accordingly, the study emphasizes the need for adaptive policy frameworks that account for regional and economic disparities. Full article

Serving large language models (LLMs) on cloud spot and preemptible instances reduces costs by 60 to 90 percent compared to on-demand pricing, but unpredictable instance preemptions cause request failures, KV-cache state loss, and degraded user experience. We present MorphCloud-LLM, an elastic LLM serving system designed to achieve the reliability properties of on-demand serving at spot-instance pricing. MorphCloud-LLM integrates three synergistic components: (1) an asynchronous incremental KV-cache checkpointing engine that streams only delta state to disaggregated persistent storage with less than 3% throughput overhead, enabling sub-second KV-cache delta streaming and reconstruction for KV-cache sizes up to 32 GB on replacement instances (total end-to-end migration latency: 1390 ms); (2) a gradient-boosted preemption prediction model trained on spot market telemetry that achieves 89% recall at a 30-s prediction horizon, providing sufficient lead time for proactive migration before forced eviction; and (3) a speculative decoding continuity engine that offloads draft model token generation to on-demand fallback nodes during migration windows, bounding the user-visible interruption to a sub-second buffering pause. MorphCloud-LLM is deployed and evaluated on AWS and GCP using LLaMA-70B and Mixtral-8x7B across 521 trace-injected preemption events, achieving up to 76% cost reduction under active-serving accounting (69.8% for LLaMA-70B; 67% including warm standby fallback capacity) with only 2.1% p99 latency overhead and zero dropped requests. Extensive ablation studies confirm the contribution of each component to overall system resilience. Note that preemption events are reproduced via a trace-driven simulation framework built on empirical AWS and GCP spot interruption traces rather than fully uncontrolled live production preemptions. Production generalizability under uncontrolled preemption—including simultaneous multi-node failures, network congestion, storage contention, and replacement-instance scarcity remains subject to future validation in sustained live deployments. Full article

Open government data is a key institutional arrangement in market-oriented data factor reforms. Using the staggered rollout of city-level government data platforms in China as a quasi-natural experiment and panel data of listed manufacturing firms (2011–2024), we employ a staggered difference-in-differences design to examine the effect of open government data on firms’ resource allocation efficiency. We find that government data platforms significantly reduce resource misallocation, a result robust to propensity score matching, exclusion of concurrent policy shocks, and double machine learning. Channel-level tests do not find statistically significant transmission through government transparency, firm digital innovation, or fiscal subsidy reallocation. Directional identification shows that the effect operates primarily as a corrective force on capital-overallocated firms by curbing inefficient investment, rather than as a relief effect on constrained firms, and is more pronounced in high-digital-intensity industries, smaller cities, and regions with lower digital development. By reducing the wasteful use of capital, labour, and energy and improving the information environment in factor markets, open government data offers a low-cost, institutionalized instrument for reconciling productivity growth with sustainable resource use, with direct relevance to the United Nations (UN) Sustainable Development Goals (SDGs). Full article

Methane is an abundant carbon resource with significant potential for the sustainable production of hydrogen, syngas, light hydrocarbons, oxygenates, and carbon nanomaterials. However, its efficient utilization remains challenging because of the high stability of the C–H bond, requiring energy-intensive thermocatalytic processes that often suffer from limited selectivity, carbon deposition, and high CO₂ emissions. Plasma-assisted technologies have emerged as a promising alternative by activating methane through energetic electrons and reactive species under non-equilibrium conditions. Although considerable progress has been achieved, existing reviews have primarily focused on individual plasma sources, reaction pathways, or catalyst systems, with limited attention to the coupled interactions among plasma characteristics, radical chemistry, reactor engineering, and product selectivity. This review provides a comprehensive and critical analysis of plasma-assisted methane valorisation by integrating the fundamental mechanisms of electron-impact activation, radical generation, and plasma kinetics with reactor design and process performance. The major plasma reactor technologies, including dielectric barrier discharge, gliding arc, microwave, and plasma jet systems, are critically compared in terms of methane conversion pathways, energy efficiency, operating conditions, reactor configuration, and product distribution. Finally, current challenges and emerging opportunities, including plasma catalysis, advanced reactor architectures, operando diagnostics, and reactor scale-up, are discussed to provide future perspectives for the industrial implementation of plasma-assisted methane valorisation. Full article

Yam bean (Pachyrhizus spp.) is a promising, yet underutilized, leguminous crop with considerable potential for biopesticide development. However, baseline data on seed yield, the heritability of pod traits, and antibacterial effects against Ralstonia solanacearum (RS) are lacking, limiting informed selection for seed production and biopesticide use. This study evaluated the morpho-agronomic traits of nine Amazonian yam bean progenies and screened their seed extracts for in vitro antibacterial activity against RS. We conducted the experiment on a Spodosol, using a trellis system in a randomized complete block design with four replications and four plants per plot. Seed yield varied from 0.56 to 0.98 t ha⁻¹, with progenies P14, P20, and P23 exhibiting the highest numerical yields. Broad-sense heritability (H²) was high for pod length (0.77), pod width (0.81), and 100-seed mass (0.85), suggesting considerable potential for genetic improvement of these traits. In vitro antibacterial assays revealed concentration-dependent biphasic activity: 0.5% (w/v) extracts initially stimulated bacterial growth at 6 and 12 h but suppressed multiplication by 88–90% at 24 h, whereas 5% (w/v) extracts promoted growth throughout the 24 h period. These findings establish baseline seed yield data for yam bean grown in Amazonian Spodosols and highlight the genetic variability available for breeding programs in the region. Progenies P14, P20, and P23 warrant further investigation as sources of natural compounds for sustainable plant protection, underscoring the need for optimized formulations and extended exposure periods. Full article