Search Results (333)

Commercial computer-aided design (CAD) software is often expensive. This paper examines the use of product manufacturing information (PMI) web visualization to address the challenges faced by production site personnel and external partners collaborating on product development. These individuals need to be able to view or query PMI in model-based definition models without having to install professional CAD software. A detailed analysis of the relationships between PMI entity attributes in standard for the exchange of product model data (STEP) AP242 files was conducted. An algorithm for the automatic parsing and mapping of PMI semantics to a web browser is presented. Using linear sizes as an example, this paper introduces a prototype system with the following features: PMI web visualization; automatic linkage of PMI to associated geometry; browser-native rendering without the need for dedicated applications; and integration of graphical presentation and semantic representation. The effectiveness and feasibility of the prototype system are validated through case studies. However, the system has limitations when handling large assemblies with compound tolerances, curved dimension placements, and overlapping annotations, which presents areas for future research. Full article

Extended Reality (XR) technologies—including Virtual Reality, Augmented Reality, and Mixed Reality—are increasingly applied in the food industry to simulate sensory environments, support education, and influence consumer behavior, while robotics addresses labor shortages, hygiene, and efficiency in production. This review uniquely synthesizes their convergence through digital twin frameworks, combining XR’s immersive simulations with robotics’ precision and scalability. A systematic literature review and keyword co-occurrence analysis of over 800 titles revealed research clusters around consumer behavior, nutrition education, sensory experience, and system design. In parallel, robotics has expanded beyond traditional pick-and-place tasks into areas such as precision cleaning, chaotic mixing, and digital gastronomy. The integration of XR and robotics offers synergies including risk-free training, predictive task validation, and enhanced human–robot interaction but faces hurdles such as high hardware costs, motion sickness, and usability constraints. Future research should prioritize interoperability, ergonomic design, and cross-disciplinary collaboration to ensure that XR–robotics systems evolve not merely as tools, but as a paradigm shift in redefining the human–food–environment relationship. Full article

Grass–legume mixtures are increasingly recognized for their potential to enhance soil health and forage productivity through belowground biotic interactions. In this study, we evaluated the effects of Vicia faba L. (faba bean 4060)–Avena sativa L. (oat ‘Baylor II’) mixtures on biomass, soil properties, and bacterial community dynamics. Results showed that mixtures significantly reduced the fresh weight of faba bean (6.2 kg/m²) compared to monoculture (8.8 kg/m², p < 0.001), while oat biomass increased under mixtures (3.2 kg m⁻² vs. 2.8 kg m⁻², p < 0.01). Available phosphorus (AP) and available potassium (AK) significantly decreased in the rhizosphere of both mixtures, whereas alkali-hydrolyzable nitrogen (AN) significantly increased, particularly in oat. Mixtures significantly enhanced bacterial richness, evenness, and Shannon diversity in faba bean (p < 0.01) but had no significant effect on oat diversity metrics. NMDS indicated distinct shifts in bacterial community structures under mixtures. Acidobacteriota and Vicinamibacteraceae were enriched in faba bean mixtures, whereas Actinobacteriota decreased in both forages under mixtures. Source Tracker analysis suggested substantial microbial exchange between species, with over 40% of the bacterial community in mixed roots originating from the partner monoculture. Although microbial community stability tended to decline under mixtures, differences were not significant. Niche breadth was significantly expanded in faba bean mixtures. Community assembly processes remained predominantly stochastic; however, mixtures slightly shifted the balance toward deterministic processes. Structural equation model revealed that soil physicochemical properties had a significant negative effect on diversity (β = −0.371, p = 0.007), and diversity had a significant negative effect on freshweight (β = −0.770, p < 0.001), suggesting that bacterial diversity may play a mediating role in the relationship between soil properties and plant fresh weight (β = 0.285, p = 0.011). These findings demonstrate that mixture-induced changes in soil nutrient status and microbial community characteristics collaboratively mediate plant performance through altered community assembly and diversity–function relationships. Full article

We examined the effects of emotional intelligence (EI) and the Big Five on students’ performance in collaborative problem solving (CPS). 162 secondary-school students completed the Mayer-Salovey-Caruso Emotional Intelligence Test and the Big Five Inventory. Divided into 54 triads (64.8% female), they then collaboratively solved a complex social problem. Based on video-recordings of the CPS sessions, we assessed four CPS processes: the team’s socio-cognitive exchange, socio-emotional interaction, task management, and relationship management. The CPS product (solution) of each team was judged by two independent raters. Using structural equation modelling (1) with team-level EI abilities as predictors, we found a small indirect effect (via CPS processes) of both understanding and managing emotions on the CPS product, and a medium-size direct effect of understanding emotions on the same criterion; (2) with team-level traits as predictors, a medium-size positive effect of neuroticism on task management, a small negative effect of extraversion on relationship management, and a small positive effect of openness on the CPS product. A model including both EI and personality confirmed their independent contributions to CPS performance, with EI abilities contributing both directly and indirectly to the CPS product, and the contribution of personality narrowed down to neuroticism positively affecting task management. Full article

As digitalization reshapes industrial ecosystems, small and medium-sized enterprises (SMEs) in resource-based economies face growing pressure to adapt. This study examines the digital maturity of supplier firms within Chile’s Antofagasta mining cluster, a region that plays a central role in national productivity. A structured survey was conducted with 83 companies, using a ten-dimensional model to assess key areas such as data management, processes, personnel, and technology use. Results show that the average maturity level is 2.5 on a five-point scale, placing most firms at an early stage of digital transformation. While data-related capabilities scored relatively high, critical gaps persist in automation, robotics, and cybersecurity. Company size was moderately correlated with digital maturity, but no consistent relationship was observed with revenue growth. Although most firms acknowledge the relevance of digital technologies, few have formal plans or strategies in place. These findings reveal a structural lag that limits the potential of SMEs to engage fully with Industry 4.0, underscoring the need for tailored support policies and collaborative development initiatives in the mining sector. Full article

During the cloud-based product form design process, traditional collaborative-filtering recommendation methods fail to effectively calculate similarity metrics or generate relevant knowledge recommendations for newly joined designers, due to their lack of historical knowledge scores, resulting in inefficient knowledge acquisition. Since designers show a clear tendency of professional trust in the knowledge adoption process, they are more inclined to accept knowledge resources recommended by people with similar professional backgrounds to theirs or by authorities in their fields. Therefore, this paper proposes a knowledge recommendation method for product form design integrating crowd-intelligence context similarity and trust relationships in cloud environments. The method first constructs an ontology model and a product form design knowledge ontology, containing task context, designer’s context, and computational context to facilitate the acquisition, storage, processing, and invocation of contextual information and knowledge. Second, the neighboring set of target designers is determined by calculating the multidimensional contextual similarity and trust relationship between designers. Finally, the missing knowledge score of the target designer is predicted by the knowledge evaluation of the neighboring designers, and the recommendation list is generated. The method’s effectiveness and feasibility are confirmed through a case study of coffee machine product form design. Full article

Understanding the intricate relationship between sensory perception and physicochemical properties of cacao-based products is crucial for advancing quality control and driving product innovation. However, effectively integrating these heterogeneous data sources poses a significant challenge, particularly when sensory evaluations are derived from low-quality, subjective, and often inconsistent annotations provided by multiple experts. We propose a comprehensive framework that leverages a correlated chained Gaussian processes model for learning from crowds, termed MAR-CCGP, specifically designed for a customized Casa Luker database that integrates sensory and physicochemical data on cacao-based products. By formulating sensory evaluations as regression tasks, our approach enables the estimation of continuous perceptual scores from physicochemical inputs, while concurrently inferring the latent, input-dependent reliability of each annotator. To address the inherent noise, subjectivity, and non-stationarity in expert-generated sensory data, we introduce a three-stage methodology: (i) construction of an integrated database that unifies physicochemical parameters with corresponding sensory descriptors; (ii) application of a MAR-CCGP model to infer the underlying ground truth from noisy, crowd-sourced, and non-stationary sensory annotations; and (iii) development of a novel localized expert trustworthiness approach, also based on MAR-CCGP, which dynamically adjusts for variations in annotator consistency across the input space. Our approach provides a robust, interpretable, and scalable solution for learning from heterogeneous and noisy sensory data, establishing a principled foundation for advancing data-driven sensory analysis and product optimization in the food science domain. We validate the effectiveness of our method through a series of experiments on both semi-synthetic data and a novel real-world dataset developed in collaboration with Casa Luker, which integrates sensory evaluations with detailed physicochemical profiles of cacao-based products. Compared to state-of-the-art learning-from-crowds baselines, our framework consistently achieves superior predictive performance and more precise annotator reliability estimation, demonstrating its efficacy in multi-annotator regression settings. Of note, our unique combination of a novel database, robust noisy-data regression, and input-dependent trust scoring sets MAR-CCGP apart from existing approaches. Full article

Integrated multidisciplinary care is recognised as essential for people living with motor neurone disease (PlwMND) and their families. The values underpinning integrated care, such as person-centredness, respect, empowerment, and co-production, are central to delivering meaningful and comprehensive support. Trust is an essential yet often overlooked element of effective person- and family-centred integrated care, particularly for PlwMND. While specialist multidisciplinary MND clinics represent the benchmark for evidence-based care, many PlwMND and their families depend significantly on local and community-based support services to maintain quality of life. Trust directly influences their engagement with these services and the continuity of care provided. Trust enables understanding of personal priorities and how they change as the disease progresses, ultimately allowing for person-centred care to happen. Trust is necessary to enable service co-production, which is a strong value of integrated care. Research highlights seven key domains of support essential to PlwMND and their carers: practical, social, informational, psychological, physical, emotional, and spiritual. Effective integrated care requires strong relationships built upon trust, shared decision-making, respect for individuality, and clear communication. Furthermore, due to the rapidly progressive nature of MND, care priorities and perceived symptom burdens may shift significantly over short periods, making flexible, temporally sensitive approaches critical. A dynamic, inclusive model of decision-making that fosters autonomy within and regular co-review of needs is recommended. This perspective paper examines how person- and family-centred integrated care is currently being delivered, what is working well, and how these practices can be further strengthened to enhance the care experiences of PlwMND, their families, and the health and social care providers involved. This paper builds on both theoretical knowledge and clinical experience to offer our perspective on the critical role of trust in co-producing integrated care for PlwMND. It brings together the voices of clinicians and researchers, alongside those with lived experience of MND. We propose a diagram of care that embeds the core values of integrated, person-centred care within the specific context of MND. Our aim is to enhance collaborative practices, strengthen cross-sector partnerships, and ultimately improve the care experiences for professionals, PlwMND, and their families. Full article

Optimizing agricultural structure serves as a crucial pathway to promote sustainable rural economic development. This study focuses on a representative village in the mountainous region of North China, where agricultural production is constrained by perennial low-temperature conditions, resulting in widespread adoption of single-cropping systems. There exists an urgent need to enhance both economic returns and risk resilience of limited arable land through refined cultivation planning. However, traditional planting strategies face difficulties in synergistically optimizing long-term benefits from multi-crop combinations, while remaining vulnerable to climate fluctuations, market volatility, and complex inter-crop relationships. These limitations lead to constrained land productivity and inadequate economic resilience. To address these challenges, we propose an integrated decision-making approach combining stochastic programming, robust optimization, and data-driven modeling. The methodology unfolds in three phases: First, we construct a stochastic programming model targeting seven-year total profit maximization, which quantitatively analyzes relationships between decision variables (crop planting areas) and stochastic variables (climate/market factors), with optimal planting solutions derived through robust optimization algorithms. Second, to address natural uncertainties, we develop an integer programming model for ideal scenarios, obtaining deterministic optimization solutions via genetic algorithms. Furthermore, this study conducts correlation analyses between expected sales volumes and cost/unit price for three crop categories (staples, vegetables, and edible fungi), establishing both linear and nonlinear regression models to quantify how crop complementarity–substitution effects influence profitability. Experimental results demonstrate that the optimized strategy significantly improves land-use efficiency, achieving a 16.93% increase in projected total revenue. Moreover, the multi-scenario collaborative optimization enhances production system resilience, effectively mitigating market and environmental risks. Our proposal provides a replicable decision-making framework for sustainable intensification of agriculture in cold-region rural areas. Full article

Corrosion has a significant impact on the economic and environmental sustainability of metal-based infrastructure and products. This position paper explores the intrinsic relationship between corrosion protection and sustainability, examining the economic costs, environmental impacts and technological strategies involved. While corrosion results in resource waste, energy loss, and increased CO₂ emissions, effective corrosion management can extend the service life of metallic components, thus preserving resources and minimizing environmental burden. The approaches such as Total Cost of Ownership (TCO) and Life Cycle Analysis (LCA) can provide a framework for selecting the most cost-efficient and environmentally friendly corrosion protection method in view of the required lifetime. The paper emphasises the crucial role of material selection, design optimization, recyclability and environmentally friendly coatings. Regulatory pressures and new trends such as machine learning are also discussed. Achieving sustainability goals requires greater awareness, education, interdisciplinary collaboration, and continued innovation in corrosion protection strategies. Full article

This study analyzes the relationship between ergonomic and psychosocial risk factors and labor productivity using a bibliometric approach through a general analysis and one that includes inclusion criteria such as English language, open access, and primary research publications to identify only those articles that explicitly address the relationship between ergonomic and psychosocial risk factors and labor productivity. It is recognized that both physical and psychosocial conditions of the work environment directly influence workers’ health and organizational performance. For this purpose, a bibliometric review was conducted in academic databases, including Scopus, Web of Science, ScienceDirect, and Taylor & Francis, resulting in the selection of 4794 relevant articles for general analysis. Additionally, 116 relevant articles were selected based on the inclusion criteria. Tools and methodologies, such as Rayyan, Excel, VOSviewer 1.6.20, and PRISMA, were used to classify the studies and identify trends, collaboration networks, and geographical distribution. The results reveal a sustained growth in scientific production, with clusters on occupational safety and health, work environment factors, and the characteristics of the population, approach, and methodologies used in the studies. Likewise, Procedia Manufacturing, International Journal of Occupational Safety and Ergonomics, and Ergonomics stand out as the main sources of publication, while countries such as Sweden, Poland, and the United States lead the scientific production in this field. In addition, the network of co-occurrence of keywords evidences a comprehensive approach that articulates physical or ergonomic and psychosocial risk factors with organizational performance, while the network of authors shows consolidated collaborations and studies focused on analyzing the relationship between physical demands and musculoskeletal disorders from advanced ergonomic approaches. Full article

Introduction: Breakfast has emerged as a critical factor in preventing cardiovascular diseases, driven not only by its nutritional content but also by its alignment with circadian rhythms. However, gaps remain in the literature regarding its clinical impact and thematic evolution. Objective: To characterize the global scientific output on the relationship between breakfast quality and cardiovascular health through a systematic bibliometric analysis. Methodology: The PRISMA 2020 protocol was applied to select 1436 original articles indexed in Scopus and Web of Science (1957–2025). Bibliometric tools, including R (v4.4.2) and VOSviewer (v1.6.19) were used to map productivity, impact, collaboration networks, and emerging thematic areas. Results: Scientific output has grown exponentially since 2000. The most influential journals are the American Journal of Clinical Nutrition, Nutrients, and Diabetes Care. The United States, United Kingdom, and Japan lead in publication volume and citations, with increasing participation from Latin American countries. Thematic trends have shifted from traditional clinical markers to innovative approaches such as chrononutrition, digital health, and personalized nutrition. However, methodological gaps persist, including a predominance of observational studies and an underrepresentation of vulnerable populations. Conclusions: Breakfast is a dietary practice with profound implications for cardiometabolic health. This study provides a comprehensive overview of scientific literature, highlighting both advancements and challenges. Strengthening international collaboration networks, standardizing definitions of a healthy breakfast, and promoting evidence-based interventions in school, clinical, and community settings are recommended. Full article

Background/Objective: Fentanyl plays a pivotal role in the opioid epidemic, defined by four waves of overdose deaths. To analyse fentanyl research trends, examining its links to mental health, pharmaceutical development, healthcare, diseases, and pathophysiology within the broader social and health context of the time. Methods: To understand the evolution of scientific publications on fentanyl and its relationship to the opioid crisis, a search using Web of Science Core Collection and PubMed was conducted. A total of 53,670 documents were retrieved related to opioid scientific production, among which 1423 articles (3%) focused specifically on fentanyl. The 21,546 MeSH terms identified in these documents were analysed by publication year and specific fields: Psychiatry and Psychology, Chemicals and Drugs, Healthcare, Diseases, and Phenomena and Processes. R-statistical/FactoMineR libraries were used for the correspondence analysis. Results: In the first overdose death wave, research focused on improving therapies and reducing side effects. The second wave emphasised detoxification methods with naltrexone, methadone, and behavioural therapies. The third wave addressed psychological treatments and HIV-syringe-sharing prevention. The fourth wave prioritised less addictive analogues and understanding consumer profiles to combat the epidemic. Conclusions: Fentanyl research has evolved alongside real-world challenges, reinforcing the connection between patients’ needs, healthcare professionals’ roles, illicit users, policymakers, and the research community’s contributions to addressing both therapeutic use and its broader societal impact. These findings highlight the necessity for an interdisciplinary approach to scientific research integrating prevention, treatment, education, legal reform, and social support, emphasising the need for public health policies and collaborative research to mitigate its impact. Full article

China’s national strategies emphasize both achieving carbon peaking and neutrality (“dual carbon” objectives) and fostering high-quality economic development. This dual focus highlights the critical importance of the Green and Low-Carbon Transition (GLCT) of the economy and the development of New Quality Productive Forces (NQPF). Firms are central actors in this transformation, prompting the core research question: How does corporate engagement in GLCT contribute to the formation of NQPF? We investigate this relationship using panel data comprising 33,768 firm-year observations for A-share listed companies across diverse industries in China from 2012 to 2022. Corporate GLCT is measured via textual analysis of annual reports, while an NQPF index, incorporating both tangible and intangible dimensions, is constructed using the entropy method. Our empirical analysis relies primarily on fixed-effects regressions, supplemented by various robustness checks and alternative econometric specifications. The results demonstrate a significantly positive relationship: corporate GLCT robustly promotes the development of NQPF, with dynamic lag structures suggesting delayed productivity realization. Mechanism analysis reveals that this effect operates through three primary channels: improved access to financing, stimulated collaborative innovation and enhanced resource-allocation efficiency. Heterogeneity analysis indicates that the positive impact of GLCT on NQPF is more pronounced for state-owned enterprises (SOEs), firms operating in high-emission sectors, those in energy-efficient or environmentally friendly industries, technology-intensive sectors, non-heavily polluting industries and companies situated in China’s eastern regions. Overall, our findings suggest that corporate GLCT enhances NQPF by improving resource-utilization efficiency and fostering innovation, with these effects amplified by specific regional advantages and firm characteristics. This study offers implications for corporate strategy, highlighting how aligning GLCT initiatives with core business objectives can drive NQPF, and provides evidence relevant for policymakers aiming to optimize environmental governance and foster sustainable economic pathways. Full article

Background: Youth tobacco use remains a significant public health concern, particularly in urban communities disproportionately burdened by health disparities. In Baltimore City, where tobacco-related harms are elevated, understanding the relationship between tobacco use—including e-cigarettes—and mental health among high school students is essential for guiding equitable prevention and cessation strategies. The CEASE (Communities Engaged and Advocating for a Smoke-free Environment) program, in collaboration with the American Lung Association’s Not On Tobacco (N-O-T) initiative, developed an online school-based survey to inform community-responsive interventions. Aims: This study aimed to examine the associations between cigarette use, including conventional cigarette use, and self-rated mental health among high school students in Baltimore City. Methods: High school students in Baltimore City completed an anonymous online survey that assessed demographic characteristics, tobacco knowledge and use, mental health, and related behaviors. Self-rated mental health was dichotomized as poor versus fair/good. Tobacco use categories included current use of e-cigarettes and conventional cigarettes. Logistic regression models were used to examine associations between tobacco use and self-rated mental health, adjusting for age, gender, race, and parental education. Odds ratios (ORs) with 95% confidence intervals (CIs) were reported. Results: No statistically significant associations were found between self-rated mental health and e-cigarette use and conventional tobacco use after adjusting for covariates. Conclusions: The absence of a significant association may reflect unique aspects of the social context in Baltimore City, where youth may not use tobacco products as a coping mechanism for mental health challenges. Alternatively, it may be due to limitations in measurement, particularly the use of a single-item mental health assessment. These findings should be considered preliminary. Future research using more comprehensive mental health measures and larger samples is warranted to further explore these complex relationships. Full article