Search Results (7,172)

As digital technologies continue to evolve, intelligent manufacturing technology represented by industrial robots has been increasingly integrated into various stages of enterprise production and operational activities. This trend has created new opportunities for enterprises to advance green transformation and enhance the level of sustainable green innovation. Based on data from Chinese A-share listed firms, this study empirically examines the effect of industrial robot application on sustainable green innovation of enterprises. The study finds that industrial robot application significantly enhances sustainable green innovation of enterprises. The underlying mechanisms mainly operate through the optimization of human capital structure and government-specific subsidies. Meanwhile, industrial robot application exhibits significant peer spillover effect, which can generate demonstration and pressure transmission effects among enterprises within the same industry and region, thereby promoting the coordinated improvement of sustainable green innovation. Heterogeneity analysis further reveals that the promoting effect of industrial robot application on sustainable green innovation is more pronounced in non-state-owned enterprises, labor-intensive enterprises, enterprises whose executives have an environmental background, and enterprises in regions with stricter environmental regulation. Furthermore, the establishment of regional environmental courts can strengthen the positive effect of industrial robot application on sustainable green innovation of enterprises. The results of the extended analysis further demonstrate that the contribution of industrial robot application to sustainable green innovation mainly stems from its ‘’leverage effect’’ on overall corporate innovation activities, rather than from the ‘’crowding-out effect’’ caused by compressing other technological innovation activities. This study not only enriches the literature on the environmental effects of industrial robot application but also provides new insights into how enterprises can leverage intelligent technologies such as industrial robots to achieve green transformation. Full article

Background: Personalized nutrition, also referred to as precision nutrition, is an emerging approach that integrates genetic, metabolic, phenotypic, behavioral, and environmental characteristics to develop individualized dietary strategies. Obesity, metabolic syndrome (MetS), and metabolic dysfunction-associated steatotic liver disease (MASLD) represent interconnected disorders with substantial inter-individual variability in disease development, metabolic risk, and response to dietary interventions. Although body mass index (BMI) remains widely used for obesity classification, it does not adequately capture differences in body composition, fat distribution, or metabolic health. Consequently, individuals with normal-weight obesity (NWO), characterized by excessive body fat accumulation despite a normal BMI, may remain unidentified despite increased cardiometabolic risk.This narrative review critically evaluates the current evidence on the potential role of personalized nutrition in the prevention and management of obesity, MetS, MASLD, and related cardiometabolic abnormalities. Particular attention is given to five major domains: nutrigenetics, gut microbiota, metabolic phenotyping, body composition assessment, and digital health technologies, with emphasis on their current clinical applicability and limitations. Methods: A structured narrative review was performed using PubMed, Scopus, and Web of Science to identify English-language studies (2003–2026) on personalized nutrition in obesity, normal-weight obesity, metabolic syndrome, and MASLD. Eligible studies were selected according to predefined inclusion and exclusion criteria, and 31 publications were included in the qualitative synthesis. Results: Current evidence suggests that personalized nutrition strategies may contribute to improvements in body weight regulation, insulin sensitivity, lipid metabolism, and liver-related outcomes; however, the magnitude and consistency of these effects remain variable. The integration of genetic, metabolic, microbiome, and phenotypic information may improve individual risk stratification and help identify high-risk groups, including individuals with NWO who may not be recognized through BMI-based assessment alone. Emerging approaches involving multi-omics technologies, microbiome profiling, wearable devices, continuous glucose monitoring, and artificial intelligence-based tools provide promising opportunities for individualized dietary interventions. Nevertheless, limitations related to methodological heterogeneity, insufficient standardization, limited external validation, and the scarcity of long-term pragmatic clinical trials currently restrict their routine implementation. Conclusions: Personalized nutrition represents a promising but still evolving approach for addressing obesity and its metabolic complications, including MetS and MASLD. While the integration of biological, phenotypic, and digital information may support more targeted dietary recommendations, current evidence does not yet fully establish the clinical effectiveness and cost-effectiveness of these approaches in routine care. Future large-scale, longitudinal, and well-designed randomized controlled trials are required to determine which personalized nutrition strategies provide clinically meaningful benefits and for which patient populations. Full article

Cloud-native software-delivery pipelines increasingly rely on Policy-as-Code (PaC) to automate security, compliance, and governance enforcement. Although Policy-as-Code is widely adopted within Continuous Integration (CI) pipelines and Kubernetes admission-control frameworks, governance requirements are often implemented independently, potentially increasing maintenance effort and creating opportunities for policy drift. Despite the growing adoption of Policy-as-Code, comparatively little empirical evidence exists regarding the reuse of a shared policy-definition layer across complementary enforcement stages within the software-delivery lifecycle. This paper presents and empirically evaluates a reusable multi-stage Policy-as-Code enforcement model based on a shared policy-definition layer implemented using the Open Policy Agent (OPA) framework and its Rego policy language. Rather than proposing a new Policy-as-Code technology, the study investigates whether a shared policy-definition layer can support consistent policy enforcement across Continuous Integration validation and Kubernetes admission control. The model was evaluated using Conftest and OPA Gatekeeper through a structured experimental study comprising 29 Kubernetes manifests, 37 experimental scenarios, eight Kubernetes resource types, and 261 policy assertions covering representative cloud-native workload-governance requirements. Within the evaluated dataset, all intentionally introduced insecure configurations were correctly identified without observed false positives or false negatives. The shared policy-definition layer was successfully reused across both validation stages, while Kubernetes admission control mitigated all evaluated CI bypass scenarios by providing an independent deployment-time enforcement boundary. The results demonstrate that a shared policy-definition layer can support consistent policy enforcement across complementary enforcement stages while enabling policy reuse without requiring duplicate policy implementations within the evaluated environment. More broadly, the study contributes empirical evidence supporting policy reuse as a governance strategy for cloud-native software delivery and provides a reproducible foundation for future investigations involving larger datasets, broader governance-policy portfolios, alternative Policy-as-Code ecosystems, and production-scale deployments. Full article

Global restoration frameworks, such as the Bonn Challenge and Forest Landscape Restoration, have endorsed multistakeholder engagement in agroforestry as key to reversing land degradation at scale. This paper follows shifts in how stakeholders have been organised, coordinated and steered since 2010 when Rwanda’s National Forestry Policy came into force, a year ahead of Rwanda’s pledge to the Bonn Challenge. The specific focus is on Bugesera District, representing a national policy shift from focusing on restoration in highland areas only. Bugesera is a lowland area facing complex socio-ecological and livelihood challenges including high rates of deforestation, recurrent drought and rapid population fluctuations. This paper analyses these changes by investigating which stakeholders were involved, how they were engaged (modes of participation) and why they participated (drivers of participation). Conceptually, this follows stakeholder mapping, Reed’s theory of participation and multi-level governance theory. Through thematic analysis, we triangulated data from 15 policy-related documents with semi-structured interviews with representatives from 24 organisations. Our findings show that both before and after 2010, stakeholder engagement has remained top-down. However, since 2010 this has been qualified by an asymmetrical form of collaboration that increasingly takes the form of top-down deliberation. Changes were observed in participation patterns, engagement approaches, and governance arrangements, driven by contextual conditions, power relations, process design, and spatial–temporal dynamics. Within a centrally coordinated government system, shaped by the post-genocide political context and culturally embedded structures such as Umuganda and Ubudehe, multistakeholder restoration initiatives have largely remained state-led, with structured approaches to coordination and implementation that have varied in the extent of local stakeholder engagement. Trust emerged as an important factor influencing stakeholder interactions. Despite more diverse and expanded institutional arrangements over time, variations in levels of participation and influence among stakeholders persist, with differences in how engagement and decision-making power are distributed. We conclude that effective stakeholder engagement is contingent on existing governance structures, the political will to engage with a diversity of actors at different levels, contextual conditions including spatial-temporal dynamics, and opportunities provided by global and regional restoration frameworks. Full article

Institutional artificial intelligence (AI) decision-support systems progressively evaluate cases, determine eligibility, and allocate resources; yet, predicted efficacy alone does not guarantee equity, contestability, or responsible utilization. Current research frequently considers fairness measures, explainability, human oversight, and organizational governance as rather distinct issues. This paper presents a traceable bias-auditing framework that amalgamates prediction, explanation, selective human review, and structured recording into a cohesive operational decision pathway. Through design science research, the artifact was exhibited in a controlled proof-of-concept utilizing 8000 synthetic institutional situations and historically biased data labels. The foundational classifier was a logistic regression model. Selective escalation is initiated by the proximity of boundaries, tension in explanation patterns, and the rules governing review priorities. Three situations were evaluated: baseline prediction, prediction with explanation alone, and comprehensive architecture with review and audit recording. Explanations enhanced reviewability but did not significantly alter fairness outcomes. The proposed architecture improved F1 from 0.781 to 0.795, reduced the demographic parity gap from 0.070 to 0.010, decreased the equal opportunity gap from 0.116 to 0.036, and improved audit completeness from 0.33 to 1.00, while escalating only 4.8% of cases for human review. The results indicate that explanations attain institutional significance solely when linked to procedural regulations and enduring records. The evaluation was simulation-based; thus, the results should be interpreted as proof-of-concept evidence rather than direct field validation. Full article

The growing availability of large-scale online data has created new opportunities for analysing public discourse on climate change, although the reconstruction of structured social representations within digital environments remains methodologically challenging. This study proposes a computational framework for adapting the Hierarchical Evocation Method (HEM), grounded in Social Representation Theory, to large-scale social media discourse. Using a continuously updated Reddit dataset on climate change, the approach combines theory-informed lexical anchoring with data-driven semantic expansion to construct a renewable energy subcorpus comprising 91,817 comments published between 2018 and 2026. Representational structures are reconstructed through user-level lexical diffusion, positional salience, rhetorical foregrounding, and co-occurrence analysis, enabling the identification of central, peripheral, and contrastive components within online discourse. The results reveal a relatively stabilised representational core centred on climate transition, fossil dependency, renewable infrastructures, and socio-economic transformation, while peripheral zones display greater contextual variability and evaluative fragmentation. Longitudinal analyses further suggest a progressive consolidation of renewable energy discourse despite high user turnover and sustained growth in participation. The framework additionally highlights the relevance of affective and interactional dimensions, particularly through the widespread use of ironic and sceptical emoji configurations. Methodologically, the study provides a transparent and reproducible computational pipeline that extends classical evocation-based approaches to large-scale, dynamic corpora. More broadly, the findings contribute to sustainability communication research by showing how renewable energy is collectively framed and negotiated within English Reddit-based digital discussions. Full article

Youth in northern Ghana experience high rates of unintended pregnancy due to limited access to and use of sexual and reproductive healthcare (SRH) services. Peer-led interventions are effective in increasing the youth uptake of SRH services, but limited peer-led interventions have been developed for Ghana. This study explores youth (ages 15–24 years) and clinical provider perspectives on youth SRH to inform the co-design of a peer-led SRH counseling program in northern Ghana. We conducted a qualitative study using semi-structured interviews with 22 SRH providers and 27 youth. We then conducted an inductive thematic analysis and mapped themes onto the COM-B (Capability-Opportunity-Motivation-Behavior) model. Results revealed that youth capability to make informed and confident SRH decisions is constrained by a fragmented information environment. Although access to SRH services is increasing in the region, logistical and privacy barriers limit adolescents’ opportunities to engage in care. Religious and cultural norms stigmatize youth SRH care, though support for contraceptive use is growing among more educated sectors. Youth motivation to use SRH services is driven by a desire for autonomy but undermined by concerns about contraceptive side effects and anticipated stigma. This study supports the co-development of a contextually grounded peer counseling SRH intervention in northern Ghana. Full article

Precise site-specific ligand design remains a major challenge in structure-based drug discovery. Most existing approaches screen ligands against binding pockets identified from static protein structures obtained by X-ray crystallography, NMR spectroscopy, cryo-electron microscopy, or AlphaFold predictions. However, protein function is governed by a structure–dynamics–function relationship, and ligand screening that does not account for binding competition across the protein surface or the receptor’s dynamic, substrate-dependent conformational states remains incomplete. Substrate-specific conformations are underexplored and may offer new opportunities for selective ligand design, although systematic workflows to identify and exploit such states remain limited. Previously, we showed that collagen alters matrix metalloprotease-1 (MMP1) dynamics and that R405 is a collagen-specific allosteric residue exhibiting strong dynamic correlations with the catalytic site. Here, we present a computational framework for substrate-specific allosteric ligand design using collagen-bound MMP1 as a model system. We characterized the conformational dynamics of free and collagen-bound MMP1 by all-atom molecular dynamics simulations, clustered the resulting conformational ensembles, and identified conformations unique to the collagen-bound state. These conformations were used as structural templates for machine-learning-based generation of approximately 150,000 candidate ligands, which were subsequently docked against both the R405-centered region and all detectable binding pockets on the MMP1 surface. Several candidate ligands were predicted to dock preferentially at the R405 region by at least 0.3 kcal/mol compared with competing surface pockets. Together, these results establish a generalizable computational workflow for identifying candidate ligands predicted to preferentially dock to substrate-specific allosteric conformations and provide a foundation for future experimental validation of selective allosteric modulation. Full article

Background/Objectives: The Bologna Process and the European Higher Education Area consolidated the transition of nursing education in Spain from diploma-level training to a university degree framework. Although previous research has examined newly graduated nurses’ transition to practice, less attention has been paid to how key informants involved in educational reform interpret its long-term professional implications, including their potential relevance for nurses’ well-being. This study explored key informants’ perspectives on the implications of the Bologna Process and the Nursing White Paper on nursing education and professional development in Spain. Methods: An exploratory qualitative study was conducted using in-depth semi-structured interviews with six key informants involved in nursing educational reform in Spain. Interviews were conducted between June and November 2025, audio-recorded, transcribed verbatim, and analyzed using reflexive thematic analysis. Results: Three main themes were identified: (1) academic professionalization and the generation of professional expectations; (2) structural misalignment between university-based professionalization and clinical practice; and (3) Reality Shock, professional identity and nurses’ well-being. Conclusions: From the perspective of key informants, Reality Shock may be understood not only as an individual transition difficulty, but also as a possible expression of structural misalignment between academic professionalization and healthcare organizations. These findings suggest that strengthening nurses’ well-being may require organizational strategies that translate educational reform into professional recognition, autonomy, leadership opportunities, and coherent career development. Full article

Large-scale fishing bans are increasingly implemented to restore aquatic ecosystems, yet their effects on lower trophic levels remain poorly understood. As one of the world’s largest estuarine systems, the Yangtze River Estuary has been subjected to a ten-year fishing ban since 2021, providing a unique opportunity to potentially examine the response of plankton community to reduced fishing pressure along a steep salinity–nutrient gradient. This study relies on one-off environmental and plankton field surveys conducted in autumn 2024 (a sampling instead of multi-year time-series monitoring), we applied redundancy analysis, Mantel tests, and threshold indicator taxa analysis to tentatively clarify the roles of nutrients and salinity in structuring post-ban plankton communities. Species richness may have increased substantially compared with pre-ban levels, but community evenness declined and the dominance of Skeletonema costatum could have intensified, revealing a possible non-equilibrium recovery pattern. Zooplankton density increased substantially, which may not be fully consistent with the expectation under a simple top-down release scenario. Threshold analysis showed that S. costatum exhibited bidirectional responses to dissolved inorganic nitrogen and phosphate, with its positive response thresholds matching ambient nutrient concentrations in the inner estuary; this discrepancy is only a plausible inference since we lack direct measurements of fish predation and zooplankton grazing rates to verify causal trophic interactions. Our findings suggest that bottom-up forces driven by persistent eutrophication remain the dominant control on plankton community structure three years after the ban. From a watershed management perspective, our observational results provide a tentative implication that substantial reductions in nutrient loading might be required to mitigate unbalanced plankton community recovery; otherwise, the structural integrity of plankton assemblages could lag far behind the recovery of species richness under the current eutrophic background. Full article

This study examines the effectiveness of government support mechanisms in fostering venture capital (VC) ecosystems in emerging economies, with a particular focus on Kazakhstan. While venture capital is widely recognized as a key driver of innovation, entrepreneurship, and economic diversification, many developing countries face persistent structural barriers, including underdeveloped financial markets, limited private investment, and regulatory inefficiencies. To address these challenges, this research adopts a multi-source qualitative design, combining a systematic literature review with semi-structured interviews conducted with venture capital experts and practitioners. The analysis evaluates key policy instruments—such as co-investment schemes, tax incentives, startup accelerators, and regulatory reforms—and assesses their role in shaping VC activity. The findings indicate that although Kazakhstan has made significant progress in establishing institutional support for venture capital, critical constraints remain, including bureaucratic complexity, investor risk aversion, and limited exit opportunities. The study contributes to the literature by integrating global best practices with context-specific evidence, offering policy-relevant insights into how governments can more effectively design and implement interventions to strengthen venture capital ecosystems in developing economies. Full article

The integration of artificial intelligence (AI) into higher education assessment has prompted growing interest in how students perceive and prefer AI involvement in scoring and feedback. While prior research has largely focused on technical performance and accuracy, this study aims to fill a gap in the literature by examining students’ preferences and perceptions regarding AI scoring and feedback, with particular attention to context, assignment stakes, and post-evaluation reflections. Ninety-three undergraduate students completed a survey consisting of Likert-type items, scenario-based questions, and an activity in which they generated AI-based scoring and feedback using ChatGPT. Results showed that students preferred structured, moderately detailed AI feedback, particularly for grammar and organization, but generally favoured human evaluation, especially for subjective tasks. While AI was seen as useful in lower-stakes contexts, concerns remained about its ability to assess more complex aspects of writing. Participants expressed a strong preference for hybrid approaches in which AI augments rather than replaces human judgment, along with a need for transparency and opportunities for human review. Collectively, these findings highlight that undergraduate students’ preferences are highly context-sensitive and role-specific, underscoring the importance of student-centred implementation strategies of AI in higher education. Full article

Background: Outpatient Parenteral Antimicrobial Therapy (OPAT) has long been established as a safe and cost-effective alternative to inpatient care in Western healthcare systems. In contrast, its implementation across Asia has historically been fragmented and unstructured. A landmark multinational survey in 2017 identified OPAT in Asia as a “missed opportunity,” citing the lack of systematic oversight, standardized protocols, and outcome monitoring systems. Methods: This narrative review examines the evolution of OPAT in Asia over the past decade, synthesizing evidence from regional studies, national policies, and implementation models. Results: The findings demonstrate a clear shift from ad hoc infusion practices toward structured, multidisciplinary OPAT programs in several healthcare systems. These systems increasingly integrate antimicrobial stewardship principles, dedicated care teams, and reimbursement mechanisms. In parallel, innovative models, including hospital-at-home services and elastomeric pump–based continuous infusion, have expanded treatment feasibility while enabling the use of narrower-spectrum antibiotics. Despite these advances, substantial heterogeneity persists. Key barriers include the absence of unified national guidelines, limited monitoring infrastructure, workforce constraints, and regulatory restrictions in certain settings. Resource-limited regions continue to face challenges related to financing, laboratory capacity, and digital health integration. Conclusions: Overall, OPAT in Asia is transitioning from an underrecognized and inconsistently delivered service to an increasingly structured component of infectious disease care. Future priorities include standardized governance, integration with antimicrobial stewardship programs, sustainable reimbursement, digital outcome monitoring, and region-specific evidence on antimicrobial stability and safety. Full article

Osteochondral defects, involving both articular cartilage and subchondral bone, can lead to joint degeneration and osteoarthritis. Recent advances in 3D-printed biphasic scaffolds offer promising opportunities to recreate physiological microenvironments for tissue regeneration. In tissue engineering, these scaffolds can be mechanically stimulated to promote targeted cartilage and bone formation. While computational models have been widely used to study mechanically induced cellular responses in monophasic scaffolds, time-dependent modelling of biphasic osteochondral systems remains relatively scarce. In this study, a fluid–structure interaction (FSI) framework coupled with a mechanoregulatory algorithm was developed to predict mechanically induced early-stage mesenchymal stem cell (MSC) differentiation in biphasic open-porous osteochondral scaffolds comprising chondral and bone layers designed for direct ink writing (DIW). In a second model, an interfacial barrier layer representing the native osteochondral interface was integrated. Dynamic compressive loading (1 Hz, $2.5\%$ strain) was applied. The simulations predicted region-specific differentiation patterns in both the chondral and subchondral bone regions. In the scaffold without a barrier layer, approximately $68.9\%$ of MSCs in the chondral layer and $93.4\%$ of MSCs in the bone layer underwent chondrogenic and osteogenic differentiation, respectively. Incorporation of the barrier layer caused only minor changes, reducing predicted cartilage and bone differentiation by approximately $1.5\%$ and $3.9\%$, respectively. Overall, this study highlights the capability of computational modelling to predict mechanobiological responses in complex osteochondral systems and support scaffold design and effective mechanical stimulation protocols. Full article

South Africa has implemented an extensive social grant system to improve the wellbeing of vulnerable households. However, evidence remains limited regarding the pathways through which social grants are associated with household food insecurity and whether these relationships vary across geographical contexts of South Africa. Understanding these mechanisms is essential for designing more effective and spatially targeted social protection policies. This study examined the relationship between social grant receipt and household food insecurity, hypothesizing that household income serves as the principal pathway linking social grants to food insecurity. This study used nationally representative data from the 2024 General Household Survey. A latent food insecurity index was constructed using a two-parameter logistic Item Response Theory model, and a moderated-mediation structural equation model was employed to decompose the association between social grant receipt and food insecurity into direct and indirect components while accounting for geographic heterogeneity. The results indicate that social grants are strongly targeted toward households with higher levels of food insecurity and lower incomes, confirming that grant recipients are among the most vulnerable households in South Africa. Household income was negatively associated with food insecurity and mediated 55.4% of the total association between social grant receipt and household food insecurity. This underscores income as the main transmission pathway. High geographic heterogeneity was observed. The indirect income-mediated association was strongest in commercial farming areas, followed by urban and rural areas administered by local leaders. The direct association was significant in urban and rural areas administered by local leaders. These results show that the effectiveness of income transfers depends on the household’s demographic and socioeconomic conditions. The findings suggest that although social grants play an important role in reducing household vulnerability, cash support alone is insufficient to address household food insecurity among disadvantaged households in South Africa. Therefore, strengthening income support provided through social grants should be complemented by location-specific interventions that expand employment opportunities, improve market access, promote productive asset accumulation, and strengthen local food systems, particularly in rural areas where constraints continue to limit household food security. Full article