Search Results (82,180)

As global supply chains face increasing pressure to reconcile economic efficiency, environmental responsibility, and ethical transparency, emerging digital technologies offer unprecedented opportunities for sustainable transformation. This article examines this dynamic in the context of the Moroccan industrial sector, with particular reference to blockchain and digital twin technologies. The study employs a rigorous mixed-methods design, combining an in-depth qualitative exploration with 30 industry professionals and a Partial Least Squares Structural Equation Modeling (PLS-SEM) model based on survey data from 125 Moroccan manufacturing firms. The findings highlight the synergistic contribution of blockchain and digital twins in enabling circular, low-carbon, and resilient supply chains. Blockchain adoption strengthens environmental impact traceability, data reliability, and responsible governance, while digital twin systems enhance eco-efficiency through real-time modeling and predictive flow simulation. Circular integration emerges as a critical enabler, significantly amplifying the positive effects of both technologies by aligning physical and informational flows within closed-loop processes. With its strong empirical grounding and contextual relevance to an emerging economy, this research provides actionable insights for policymakers, industrial managers, and supply chain practitioners committed to accelerating the sustainable transformation of production systems. It also offers a renewed understanding of how digitalization and circularity jointly support environmental performance within industrial ecosystems. Full article

Generalized aquifers are widely used in various fields, such as groundwater use, mine water prevention and control, and geothermal energy. This paper presents a transformer-model-based automatic aquifer generalization method using borehole logs in scenarios with scarce experimental parameters. Relying only on basic borehole data, the method used an agent-assisted approach to extract and clean key lithological and coordinate information, which was then fused using a dual embedding mechanism. The model leveraged multi-head self-attention to calculate attention weights between the target stratum and its adjacent strata, capturing the potential contextual correlations in aquifer potential across strata. The resulting deep feature vectors from the transformer’s encoder were fed into a classification head to predict aquifer potential labels. Evaluation results demonstrated a model accuracy of 0.86, significantly outperforming the random classification baseline in precision, recall, the F1-score, and the kappa coefficient. Full article

As universities increasingly work towards the adoption of their third mission—fostering entrepreneurship and innovation—the concept of the Entrepreneurial University (EntUni) emphasizes the need to cultivate a defined set of entrepreneurial competencies in students, such as opportunity recognition, risk-taking, perseverance, self-efficacy, and adaptability. The purpose of this study is to identify which entrepreneurial competencies are most critical for student readiness within the context of an Entrepreneurial University. However, limited consensus remains on which competencies are most essential. This study identifies the entrepreneurial competencies most critical for students within an Entrepreneurial University context through a mixed-methods approach. A student survey assesses self-perceived competencies; a stakeholder survey captures the perspectives of faculty, industry experts, and entrepreneurs; and qualitative interviews with industry professionals explore best practices for competency development. Findings reveal six core competencies that EntUnis should help students cultivate: proactiveness, perseverance, grit, risk propensity, self-efficacy, and entrepreneurial intention. Industry experts further highlight the importance of teamwork, ethical and sustainable thinking, and ambiguity tolerance—competencies often underdeveloped in academic environments. The study also identifies a disconnect between entrepreneurial education and practical application, with many students demonstrating high entrepreneurial intention but limited participation in start-up activities. These insights offer actionable implications for educators, policymakers, and university administrators. Overall, the study highlights the importance of experiential learning, academia-industry collaboration, and structured competency-building to enhance entrepreneurial readiness. By addressing these gaps, EntUnis can better equip students to drive innovation, economic growth, and societal impact. Full article

This study investigates the different mechanisms through which environmental disclosure and green accounting practices influence investment attractiveness in an emerging market context. Drawing on legitimacy theory and the resource-based view, we examine whether these environmental accountability mechanisms create value directly or through enhanced sustainability performance. Using survey data from 290 non-financial firms listed on the Saudi Stock Exchange, we employ partial least squares structural equation modeling to test a mediated-moderation model within the Saudi Vision 2030 framework. The results reveal differentiated value-creation pathways: environmental disclosure affects investment attractiveness indirectly through sustainable economic outcomes (full mediation; indirect effect β = 0.121, p < 0.001), while green accounting demonstrates both direct (β = 0.237, p < 0.001) and indirect effects (β = 0.091, p < 0.01), indicating partial mediation. Both practices are positively associated with sustainable economic outcomes (β_ED = 0.290, β_GA = 0.219, p < 0.001), which in turn are positively related to investment attractiveness (β = 0.416, p < 0.001). Unexpectedly, Vision 2030 alignment shows no significant moderating effect (β = 0.042, p = 0.498), suggesting that the sustainability–investment relationship is not significantly conditioned by perceived alignment with the national strategic framework in this sample. The model explains 25.7% of the variance in investment attractiveness and 20.0% of that in sustainable economic outcomes, indicating moderate explanatory power. These findings contribute to the environmental accounting literature by suggesting that internal management-oriented practices may be more closely associated with investment attractiveness than disclosure transparency alone. Overall, the results indicate that green accounting systems are associated with investment attractiveness, while environmental disclosure appears to require observable sustainability performance to be reflected in investment perceptions, offering measured implications for corporate strategy and regulatory policy in sustainability transitions. Full article

The rapid and reliable geometric documentation of historic built heritage is a key requirement for a wide range of conservation, analysis, and risk assessment activities. In recent years, portable and wearable Simultaneous Localization and Mapping (SLAM)-based systems have emerged as efficient tools for fast 3D data acquisition, offering significant advantages in terms of operational speed, accessibility, and flexibility. This paper presents an experimental performance assessment of three portable SLAM-based mobile mapping systems applied to the 3D documentation of historic religious buildings. Two historic parish churches in the Lunigiana region (Italy) are used as case studies to evaluate the systems under real-world conditions. The analysis focuses on key performance indicators relevant to metric documentation, including georeferencing accuracy, 3D model accuracy, point cloud density and resolution, and model completeness. The results highlight the capabilities and limitations of the tested systems, showing that all instruments can efficiently capture the primary geometries of complex historic buildings, while differences emerge in terms of accuracy, data consistency, and readability of architectural details. Although the work is framed within a broader research project addressing seismic vulnerability of historic structures, this contribution specifically focuses on the experimental evaluation of SLAM-based surveying performance. The results demonstrate that portable SLAM systems provide reliable geometric datasets suitable for preliminary documentation tasks and for supporting further multidisciplinary analyses, representing a valuable resource for the rapid 3D documentation of historic built heritage. Full article

The adoption of green pest control technologies (GPCTs) has emerged as a critical factor in the pursuit of sustainable agricultural practices, particularly in improving farm efficiency and mitigating environmental impacts. This study investigates the effect of GPCT adoption on the technical efficiency of apple farmers in Shandong Province, China, using survey data collected in 2022. Applying advanced econometric techniques, including stochastic frontier analysis (SFA) to measure technical efficiency and endogenous switching regression model (ESR) to address endogeneity and selection bias, the findings indicate that GPCT adoption significantly enhances farmers’ technical efficiency. Specifically, under the counterfactual scenario of adoption, non-adopters’ technical efficiency would increase by 18.2% (from 0.669 to 0.851), whereas adopters would experience a 3.9% efficiency gain attributable to adoption (from the counterfactual 0.700 to the observed 0.739). The analysis further reveals that lower-income farmers benefit disproportionately from GPCT adoption, suggesting that the technology offers greater potential to enhance the productivity of resource-constrained farmers. These results underscore the importance of targeted policy interventions, such as subsidies and agricultural extension programs, to foster the widespread adoption of GPCTs, particularly among lower-income groups. This study contributes to the literature by providing empirical evidence of the dual benefits of GPCT adoption: improving farm efficiency while promoting environmental sustainability, with important implications for policy formulation in developing economies. Full article

It is important to understand the ecological information of Metapenaeopsis dalei to better conserve and manage the stocks in Asia. In this study, we employed research vessels to collect the field data including biomass and number of M. dalei in each survey stations along with environmental data including depth, water temperature, and salinity from November 2018 to September 2019 in the region of 26.50–35.00° N and 120.00–127.00° E in the southern Yellow and East China Seas of China. We found that the annual mean catch per unit effort of weight and number (CPUE_w and CPUE_n) was 15,235.89 g∙h⁻¹ and 17,319.13 ind∙h⁻¹, respectively. Metapenaeopsis dalei was found in 10–130 m. The greatest biomass occurred at 10–20 m in spring, 30–40 m in summer, 10–100 m in autumn, and 10–40 m in winter. The greatest abundance occurred at sea bottom temperature (SBT) 14–15 °C in spring, 19 °C in summer, 15–20 °C in autumn, and 10–12 °C in winter. The greatest abundance occurred at sea bottom salinity (SBS) 32–33 in spring, 32 in summer, 32–35 in autumn, and 31–32 in winter. We found the lowest SBT of M. dalei at 10–11 °C in spring and summer. The juveniles were found at SBT 21 °C and SBS 34 in autumn. The total CPUE_w and CPUE_n rankings were winter > spring > autumn > summer, and the mean average individual weight (AIW) ranking was summer > spring > winter > autumn. Fishing grounds of Haizhou Bay–Lvsi and Zhoushan–Yushan may be the spawning grounds for M. dalei. These findings can benefit fishery management action and planning in the future. Full article

A key challenge in precision agriculture is acquiring reliable spatial soil information under varying sampling densities, from sparse surveys to intensive monitoring. The individual predictive soil mapping (iPSM) method performs well in data-scarce conditions but neglects spatial proximity, limiting its predictive accuracy where spatial autocorrelation exists. To overcome this, we developed an enhanced framework, iPSM-Spatial Distance (iPSM-SD), which systematically integrates spatial proximity through multiplicative (MUL) and additive (ADD) strategies. The framework was validated using two contrasting cases: sparse soil organic carbon density data from Yunnan Province (n = 118) and dense soil organic matter data from Bayi Farm (n = 2511). Results show that the additive model (iPSM-ADD) significantly outperformed the original iPSM and benchmark models, including random forest, regression kriging, geographically weighted regression, and multiple linear regression, under sufficient sampling, achieving an R² of 0.86 and reducing RMSE by 46.6% at Bayi Farm. It also maintained robust accuracy under sparse sampling conditions. The iPSM-SD framework thus provides a unified and adaptive tool for digital soil mapping across a wide range of data availability, supporting scalable soil management decisions from regional assessment to field-scale variable-rate applications in precision agriculture. Full article

Accurately assessing collapse risks of high-elevation, concealed rock mass blocks within the steep cliffs of Bijiashan, Three Gorges Reservoir Area, is challenging. This study employed a multidimensional approach—integrating airborne Light Detection and Ranging (LiDAR), the transient electromagnetic method (TEM), close-range photogrammetry, horizontal drilling, and borehole optical imaging—to characterize the rock mass structure of the WD1 cliff belt and delineate 52 individual blocks. Stability analysis incorporated stereographic projection for macro-scale assessment and employed mechanical models specific to three primary failure modes (toppling, sliding, falling). Finite element strength reduction quantified the stress–strain response of a representative block under natural and rainstorm conditions. Particle Flow Code (PFC) simulated dynamic instability of the exceptionally large block W1-37. Results indicate the WD1 rock mass is highly fractured, with base sections prone to weakness. Toppling failure dominates (90.4%). Under rainstorm conditions, the average Factor of Safety (FOS) decreased by 14.7%, and 73.1% of the blocks that were stable under natural conditions were destabilized—specifically transitioning to marginally stable or substable states—often triggering chain-reaction instability characterized by “crack propagation—base buckling”. W1-37 exhibited staged failure under rainstorm: “strain localization at fissure tips—penetration of basal cracks—overturning of the upper rock mass”. Its frontal rock reached a peak sliding velocity of 15.17 m/s, indicative of base-breaking toppling. The integrated “multi-technology survey—multi-method evaluation—multi-scale simulation” framework provides a quantitative basis for risk assessment of rock mass disasters in the Three Gorges Reservoir Area and offers a technical paradigm for similar high-steep canyon regions. Full article

This study examined Croatian consumer attitudes towards fresh pork from the Black Slavonian pig, focusing on the following sustainability dimensions: environmental, social, economic sustainability, and animal welfare. A survey of 410 consumers was conducted in June 2021, using an online questionnaire assessing consumption habits, breed knowledge, and socio-demographic characteristics. Factor analysis identified four key dimensions: attention to animal welfare, support for local production and biodiversity, origin and information, and price and intrinsic quality. Cluster analysis revealed three distinct consumer segments: conscious consumers (32.4%), value-oriented consumers (37.3%), and uninvolved meat consumers (30.2%). Multinomial logistic regression showed that age, region, family economic status, and place of purchase significantly predicted cluster membership (Nagelkerke R² = 0.251, classification accuracy = 52.9%), while gender, education level, and household composition did not. Conscious consumers were characterised by older age, higher income, and a preference for direct purchasing channels, while value-oriented consumers favoured supermarkets and mid-range pricing. These findings highlight the need for improved consumer education, transparent labelling, targeted marketing strategies, and enhanced policy support to promote sustainable indigenous pig breed production and conservation. Full article

Amid increasing job complexity and evolving career demands, understanding how employees can proactively sustain their employability has become a critical concern for organizations. Although prior research highlights the importance of job crafting for employability, the motivational mechanisms through which this relationship unfolds—and the contextual conditions under which it is strengthened or weakened—remain insufficiently understood. Drawing on self-determination theory and role theory, this study examines how job crafting influences sustainable employability through the mediating role of self-determination and the moderating role of role ambiguity. Using a two-wave, time-lagged survey design, data were collected from 989 employees across diverse industries in Türkiye. Job crafting and role ambiguity were measured at Time 1, while self-determination and sustainable employability were assessed one month later. The proposed relationships were tested using confirmatory factor analysis and conditional process analysis. The results show that job crafting is positively associated with both self-determination and sustainable employability. Self-determination partially mediates the relationship between job crafting and sustainable employability, indicating that proactive job redesign enhances employability by fostering autonomous motivation. Moreover, role ambiguity weakens the positive effects of job crafting on both self-determination and sustainable employability, highlighting the importance of role clarity as a boundary condition. This study advances the job crafting and sustainable employability literature by identifying self-determination as a key motivational mechanism and by demonstrating how role ambiguity constrains the benefits of proactive work behavior. By integrating self-determination theory with role theory, the findings offer nuanced insights into how employee agency and contextual clarity jointly support sustainable employability in dynamic work environments. Full article

Construction projects are inherently exposed to high levels of uncertainty due to technical complexity, multiple stakeholders, and dynamic operating environments. However, empirical evidence on the systematic implementation of risk management practices in developing construction contexts remains limited. Unlike studies that assess the effectiveness or outcomes of risk management, this study addresses the gap by examining perception-based evidence of its implementation at the project and organizational levels in Jordanian construction projects. The study focuses on planning, control and monitoring, perceived advantages, and implementation barriers. A quantitative, survey-based research design was employed using purposive sampling. The statistical population consisted of engineers, project managers, and contractors working in the Jordanian construction sector. Out of 280 distributed questionnaires, 232 valid responses were received (response rate: 82.9%). Data were analyzed using descriptive statistics and one-sample t-tests, with the neutral midpoint of the five-point Likert scale (3.00) used as the reference value. The reliability of the instrument was confirmed by Cronbach’s alpha coefficients ranging from 0.814 to 0.868. The findings indicate generally positive perceptions of risk management implementation, with mean values ranging from 3.84 to 4.13. Risk management planning achieved the highest mean score (4.13), whereas control and monitoring practices were comparatively weaker (3.84). Although 82.3% of respondents reported applying risk management techniques, experience levels remain low to moderate. Key barriers include the lack of structured programs, limited knowledge, and insufficient experience. The results highlight the need for institutionalized risk management frameworks and targeted professional training to enhance systematic implementation. Full article

In this digital era, many companies are integrating new solutions involving Artificial Intelligence (AI)-based automation systems to optimize processes, reach higher efficiency, and help them with decision-making. While implementing these changes, various challenges may arise, including resistance to AI integration from employees. This study examines how employees’ perceived benefits, concerns, and trust regarding AI-driven algorithmic decision-making influence their comfort with AI-driven algorithmic decision-making in the workplace. This study employed a quantitative method by surveying employees in the Gulf Cooperation Council (GCC) and Lebanon with a final sample size of 388 participants. The results demonstrate that employees are more likely to feel comfortable with AI-driven algorithmic decision-making in the workplace if they believe AI will increase efficiency, promote fairness, and decrease errors. Unexpectedly, employee concerns were positively associated with comfort, suggesting an adaptive response to AI adoption. Lastly, comfort with AI-driven algorithmic decision-making is positively correlated with greater levels of trust in AI systems. These findings provide actionable guidance to organizations, underscoring the need to communicate clearly about AI’s role, address employees’ concerns through transparency and human oversight, and invest in training and reskilling initiatives that build trust and foster responsible, employee-centered adoption of AI. Full article

Background: Men who have sex with men (MSM) using HIV pre-exposure prophylaxis (PrEP) experience a high burden of human papillomavirus (HPV) infection and related diseases, yet data on HPV vaccination among this group in Brazil remain limited. Aims: The aims of this study were to estimate the prevalence of complete HPV vaccination and to identify factors associated with vaccination completion among MSM using PrEP in Brazil. Methods: We conducted a cross-sectional online survey between May and September 2025 among MSM aged ≥18 years, residing in Brazil and currently using oral PrEP. Participants were recruited through virtual snowball sampling and targeted advertisements on social media and a gay geosocial networking application. Data were collected using a structured, self-administered questionnaire hosted on REDCap^®. Complete HPV vaccination was defined as self-reported receipt of all doses recommended according to the participant’s age and clinical condition. Sociodemographic characteristics, relationship patterns, sexual behaviors, lubricant use during sexual activity, and history of sexually transmitted infections (STIs) were assessed. Adjusted prevalence ratios (aPRs) and 95% confidence intervals (95% CIs) were estimated using Poisson regression with robust (sandwich) variance. Results: A total of 872 MSM using PrEP were included, of whom 59.4% reported complete HPV vaccination. In adjusted analyses, complete vaccination was more frequent among participants reporting both steady and casual partners (aPR = 1.90; 95% CI: 1.36–2.65) or only casual partners (aPR = 1.72; 95% CI: 1.24–2.39), those reporting lubricant use during sexual activity (aPR = 1.41; 95% CI: 1.23–1.61), and those with a diagnosis of chlamydia and/or gonorrhea in the previous 12 months (aPR = 1.22; 95% CI: 1.08–1.36). Conclusions: Although HPV vaccination coverage among MSM using PrEP in Brazil is higher than that reported for MSM in general, it remains incomplete in a population with regular contact with specialized health services. Integrating systematic assessment and delivery of HPV vaccination into PrEP care may help increase vaccination completion and reduce missed opportunities for prevention. Full article

Antimicrobial resistant (AMR) infections are a persistent public health issue causing excess death and economic impacts globally. Because AMR in clinical settings is often acquired from nonpathogenic bacteria that surround us, environmental surveillance must be better characterized. It has been well established that metals can co-select for bacterial AMR. Furthermore, recent studies have shown that compromised microbial community diversity may lead to community invasion by antibiotic resistance genes (ARGs). Widespread legacy mining has led to acid mine drainage and metal contamination of waterways and sediments throughout the western United States, potentially compromising microbial community diversity while simultaneously selecting for AMR bacteria. Our study objectives were to survey metal contaminated sediments from the Bonita Peak Mining District (BPMD) in southwestern Colorado, USA, compared to sites downstream in Durango, CO for bacterial and ARG diversity. Sediment bacteria were characterized using 16S rRNA Ilumina and metagenomic sequencing. We found that overall, bacterial diversity was lower in metal-contaminated, acidic sites (p = 0.04). Metagenomic sequencing revealed 31 different ARGs, with those encoding for efflux pumps (mex and spe gene families) substantially more prevalent in the BPMD sites, elucidating a specific AMR marker fingerprint from the high metal concentration sediments. Raising awareness and providing antimicrobial tracking techniques to resource limited communities could help provide information needed for better antibiotic use recommendations and environmental monitoring. Full article