Search Results (8,136)

The study examines the relationship between Corporate Social Responsibility (CSR) adoption and firms’ future CSR investment, with a particular focus on the mechanisms and conditions that shape this relationship, drawing on the business case perspective and the resource-based view. A quantitative research design was employed using survey data collected from 568 business executives in Greece. Structural Equation Modeling (SEM) was applied to test the proposed relationships. The findings indicate that CSR adoption has a significant positive impact on future CSR investment, confirming that CSR engagement evolves into a sustained strategic commitment. Perceived benefits are found to play significant mediating roles, suggesting that firms increase future CSR investment when they recognize the value generated by CSR. In contrast, institutional barriers negatively moderate this relationship, weakening the effect of CSR adoption. The study demonstrates that the continuation of CSR investment is driven by internal reinforcement mechanisms and external conditions rather than purely by financial constraints. It offers empirical evidence that CSR adoption initiates a self-reinforcing process supported by perceived value decisions. The findings provide practical insights, emphasizing the importance of strengthening institutional frameworks and enhancing the perceived benefits of CSR to foster long-term investment in sustainable business practices. Full article

Engineering education plays a critical role in preparing future engineers to address sustainability challenges, which can be taught through diverse pedagogical approaches. This paper explores how active learning approaches, project-based learning and design-based learning can foster a holistic understanding of sustainability through an interdisciplinary engineering project, which aimed to design a solar-powered robotic system developed for environmental (ENVIBOT) monitoring of air, water, and soil quality. First, the study presents a technical description of the design. Subsequently, semi-structured reflective questions were used to capture students’ perceptions of sustainability, problem solving, interdisciplinary collaboration, and professional responsibility. As such, this study adopted a qualitative case study approach in which thematic analysis of the reflections revealed that participation in an interdisciplinary project enabled students to move beyond a narrow environmental interpretation of sustainability. The findings suggest that combining design projects with a standalone sustainability course may further strengthen students’ awareness. Students also demonstrated increased awareness of systems thinking, real-world constraints, and the societal role of engineers in promoting sustainable solutions. Projects such as the ENVIBOT can not only serve as effective pedagogical tools to enhance students’ understanding of sustainability concepts, but can also act as platforms for developing technical competence, maturity and professional responsibility. These findings highlight the potential of integrating sustainability more effectively into engineering curricula and practice alike. Full article

Environmental Impact Assessment (EIA) is a key instrument for integrating environmental considerations into development planning; however, its effectiveness remains a subject of ongoing debate. This study evaluated the quality of ecological information across all stages of the EIA process, including baseline studies, impact assessment, mitigation measures, and monitoring programs. A total of 121 Environmental Impact Statements (EISs) from land development projects in central Thailand (2019–2024) were analyzed using structured content analysis. The results indicated that baseline ecological studies were generally comprehensive, particularly in species identification and habitat characterization. However, impact assessments remained largely descriptive, with limited use of quantitative and spatial analytical methods. Ecological mitigation measures were often generic, weakly linked to identified impacts, and particularly unclear in land development projects, indicating limited alignment with the mitigation hierarchy. Monitoring programs were even less frequently included and rarely functioned as a mechanism for evaluating mitigation effectiveness or supporting adaptive management. To address these gaps, this study proposes an integrated DPSIR–EIA–Ecosystem Services framework that strengthens linkages across EIA stages and enhances the analytical and decision-support capacity of ecological assessment for sustainable environmental governance. Full article

This work deals with questions of enhancing the scalability and security of linear chain Bitcoin by introducing a D-BTC (Domino Bitcoin) protocol, supported by a simply connected two-dimensional structure. The paper seeks to answer the question: can the linear topology of Bitcoin be replaced by a richer geometric structure that simultaneously (i) enlarges the number of valid positions where parallel mining can occur, and (ii) strengthens the asymptotic decay of the double-spend reversal probability? In the D-BTC protocol, the blocks, called B-dominoes (Bitcoin dominoes) are organized as a finite connected region subset of ${\mathbb{Z}}^2$ without holes, also called a lattice. Simple connectivity plays a central role in D-BTC and to mine a (valid) B-domino, a miner has to compute four PoW (Proof of Work), corresponding to cardinal directions, allowing them to add it to the frontier of the lattice, under the constraint that the new lattice is simply connected. We introduce a new deterministic consensus based on maximization of the lattice surface. By using a simple version of the isoperimetric inequality, we see that the frontier size grows as $\Omega \left(\sqrt{n}\right)$, where n is the lattice size. Following the Nakamoto’s heuristic, and under the honest majority assumption, a double-spending attack is successful with probability decaying exponentially in $k^2$, where k is the minimum Manhattan distance of the concerned B-domino from the lattice frontier. Additionally, we set up implementations and experiments to demonstrate the practical viability of the protocol with authentic gossip-based message propagation and complete Merkle tree verification. Full article

Text-to-motion generation aims to synthesize realistic human motion sequences that accurately reflect natural language descriptions. While recent approaches have improved motion quality, achieving strong semantic alignment between text and motion, especially for fine-grained articulations, remains a significant challenge. In this work, we propose a latent-guided text-to-motion generation framework that strengthens the interaction between textual representations and motion latent sequences. The proposed method integrates a structured motion latent space with a text-conditioned variational generation module, enhanced by a cross-modal attention mechanism. This design enables the model to effectively capture both global motion dynamics and detailed semantic information from text. Extensive experiments on the Motion-X dataset demonstrate that the proposed approach achieves strong semantic alignment, as reflected by improved R-precision and competitive matching performance. In addition, the model improves multi-modality, indicating its ability to generate diverse motion patterns under the same textual condition. Qualitative results further show that the generated motions preserve core action semantics and exhibit coherent temporal dynamics across different motion categories. Overall, the proposed framework provides an effective solution for improving text–motion alignment in high-dimensional motion spaces, highlighting the importance of latent-guided modeling for realistic and semantically consistent motion generation. Full article

Background: Hemophilia care has undergone a major therapeutic transformation with the introduction of extended half-life products, non-replacement therapies, and gene therapy. However, the benefits of these advances are not equally distributed worldwide, and their impact on long-term musculoskeletal outcomes remains uncertain. Objective: To analyze global disparities in hemophilia care and research production in the context of recent therapeutic advances, with particular attention to musculoskeletal management, physiotherapy, and scalable strategies for resource-limited settings. Methods: A narrative review with a structured literature search was conducted. Two conceptual blocks were explored: global disparities and access to care in hemophilia, and recent therapeutic advances, including non-replacement therapies, extended half-life products, and gene therapy. Retrieved records were screened using Rayyan, and a structured workflow diagram was used to summarize the literature identification and selection process. A descriptive analysis was also performed to identify representative authors, institutions, and geographic patterns in hemophilia research. Results: The evidence shows substantial global disparities in diagnosis, access to treatment, healthcare infrastructure, and research production. Scientific output remains concentrated in high-income countries, while low- and middle-income regions are underrepresented. Advanced therapies consistently reduce bleeding rates and treatment burden, but concerns remain regarding access, affordability, durability, breakthrough bleeding, and long-term structural joint outcomes. Musculoskeletal complications, including subclinical bleeding and hemophilic arthropathy, remain clinically relevant despite improved hematologic control. Conclusions: The current paradigm shift in hemophilia care is not uniformly experienced worldwide. Addressing global disparities requires not only expanding access to advanced therapies, but also strengthening research capacity, implementing multidisciplinary care models, and integrating scalable interventions such as physiotherapy, patient education, and simplified diagnostic tools. Accessible musculoskeletal assessment strategies may help improve early detection, functional outcomes, and equity of care in resource-limited settings. Full article

Cultural heritage is a critical pillar of identity, social cohesion and continuity within ethnocultural communities. However, the preservation of cultural heritage across Southern Africa is largely constrained by fragmented colonial policy implementation, and limited community engagement. This study critically examines the application of the Evidence-Based Policy and Practice (EBPP) model as a decolonizing framework for sustainable management of cultural heritage. The study conducts a structured scoping review of literature to explore the integration of EBPP with the principles of Collective Benefit, Authority to Control, Responsibility, Ethics (CARE), and the principles of Findable, Accessible, Interoperable, Reusable (FAIR) to support inclusive and ethical governance. The findings of the study reveal that sustainable management of cultural heritage is dependent upon community-led governance, alignment between research, policy, and practice, and strengthening of intellectual property protections. The study identifies persistent gaps in the operationalization of indigenous knowledge policies and highlighted the need for participatory approaches to ensure the long-term sustainability of cultural heritage. The study argues that the integration of EBPP, alongside the principles of CARE and FAIR, significantly enhances accountability, fosters data sovereignty, and supports the decolonization of knowledge systems. Thus, the study makes a significant contribution to the growing global discourse on sustainable development by positioning cultural heritage as a dynamic resource for social transformation. Full article

Photovoltaic (PV) power forecasting plays a central role in power system operation, electricity markets, and the integration of high shares of renewable energy. Over the past decade, forecasting approaches have evolved from classical statistical time-series models to advanced machine learning and deep learning architectures. This review analyses 119 studies published between 2016 and 2026, providing a structured assessment of PV forecasting methodologies, including model types, data requirements, validation strategies, and performance evaluation practices. Beyond summarizing existing approaches, the paper identifies three major methodological gaps in the literature: (i) fragmentation of evaluation metrics, which limits cross-study comparability; (ii) insufficient reporting of data preprocessing procedures and temporal leakage prevention; and (iii) limited integration of forecasting accuracy with economic and operational performance metrics. A systematic comparison of representative studies is conducted to highlight dominant modelling trends and persistent limitations. Beyond a descriptive summary, this review highlights significant limitations in methodological reporting across the 119 studies analysed, particularly regarding temporal leakage prevention in Deep Learning-based forecasting. To address these issues, we introduce a reproducibility checklist and propose a strategic roadmap aimed at strengthening the link between statistical accuracy (e.g., RMSE/MAE) and operational relevance in electricity markets. Full article

This study aims to improve wagon unloading processes in a real industrial context characterized by operational variability, process constraints, and strict performance requirements. Traditional decision-making approaches in such contexts often rely on single performance indicators, which may lead to suboptimal and less sustainable decisions. In line with Industry 5.0 principles, which emphasize human-centricity, resilience, and sustainability, this paper proposes a multi-criteria decision framework to support more balanced and adaptive operational decisions. A real-world case study based on anonymized industrial data is used to evaluate different arrival-track operational configurations. The proposed model considers several indicators, including unloading time, throughput, tonnage, process variability, operational losses, and a proxy of operator exposure. To strengthen the human-centric dimension, an Operational Handling Exposure Proxy (OHEP) was introduced to capture manoeuvre-related operator exposure during wagon handling and batch repositioning. A weighted scoring system was then used to identify the most balanced configuration by considering trade-offs between performance, stability, losses and operator exposure. The results show that the arrival-track operational configuration influences loss structure, process stability and overall decision ranking more than direct throughput alone. Track 2 provides the best overall trade-off under the baseline MCDM weighting scheme, while Track 3 may become preferable when wagon-loss minimization is prioritized. The findings highlight the importance of integrating variability and human-centered indicators into industrial decision-making processes. In future work, the proposed framework could be extended using data-driven methods and machine learning to support predictive and adaptive optimization in Industry 5.0 environments. This study contributes to the literature by integrating real-world industrial analysis, multi-criteria decision-making, and sustainability-oriented optimization into a single decision support framework. Full article

This study integrated Item Response Theory (IRT) models with ordinal survey instruments to establish a baseline psychometric framework and identify multidimensional factors associated with academic achievement among first-semester leveling students (N = 1558 pre-test; N = 1676 post-test) at the Escuela Politécnica Nacional, Ecuador. A dual-component methodology was employed in this study. Initially, an 80-item ordinal survey was utilized to assess eight latent constructs, yielding substantial validation metrics through Confirmatory Factor Analysis (CFA). Secondly, structured diagnostic assessments in core STEM and language subjects were calibrated using three-parameter logistic (3PL) IRT models via Expected A Posteriori (EAP) estimation. Results demonstrated high internal consistency ($r = 0.93$ between IRT and raw scores), with mean IRT-scaled ability $\overline{\theta } = 10.45$ ($SD = 3.51$) on a 1–20 scale. Estimated item parameters yielded a mean discrimination of $\overline{\mathrm{a}} = 1.92$ and a centered mean difficulty of $\overline{b} = 0.05$. The Orlando–Thissen $S-X^2$ goodness-of-fit test, applied at a significance threshold of $p < 0.01$, identified 19 items (23.75%) whose observed response patterns deviated significantly from model predictions, with the majority concentrated in the physics and chemistry content domains. Factor scores and performance outcomes were statistically contrasted against 24 categorical demographic variables, revealing differential performance patterns across student subgroups. This research provides validated psychometric instruments, reproducible IRT-LMS integration protocols, and empirical evidence supporting targeted interventions to strengthen university transition. Full article

Background/Objectives: Nurses’ engagement in research is essential to strengthen evidence-based practice, knowledge translation, and quality of care. However, individual, organisational, and cultural barriers may limit nurses’ participation in research activities. This study aimed to cross-culturally adapt and psychometrically test the Italian version of the Barriers to Nurses’ Participation in Research Questionnaire within the Italian cultural and healthcare organisational context, and to explore perceived obstacles to research engagement among nurses in Italy. Methods: A cross-sectional methodological study was conducted. The instrument was translated, back-translated, reviewed by the original instrument developer and an expert panel, and evaluated for content validity by 12 clinical research professionals. Data were collected online between September and October 2024 from 196 nurses working across Italian healthcare settings, including hospitals, university hospitals, IRCCS, primary care, and private hospitals. Exploratory Structural Equation Modelling was used to examine the factor structure. Results: A total of 196 nurses were enrolled in the study. A two-factor structure was identified, comprising Research Resources and Personal Relevance of Research, which explained 35.37% and 25.14% of the variance, respectively. Both factors demonstrated good reliability. The most prominent barrier was the lack of incentive or reward for nurses to engage in research, whereas the least relevant barrier was the perception that research was not interesting or valuable. Greater barriers were reported by younger nurses, those with fewer years of experience, and those without specific research training. Lack of time to conduct research emerged as a pervasive obstacle across the sample. Conclusions: The Italian version of the Barriers to Nurses’ Participation in Research Questionnaire provides preliminary evidence of validity and reliability for assessing perceived barriers to research participation among Italian nurses. Owing to the structural modifications introduced during adaptation, the instrument should be interpreted as a culturally adapted and modified Italian version rather than as a direct replication of the original structure. Its use may support organisational diagnosis, research mentorship, training planning, and future research-capacity-building initiatives, although further validation in larger and more heterogeneous samples is warranted. Full article

The growing availability of genomic resources is changing how genetic diversity is studied in Vitis vinifera L. At the same time, it has become increasingly clear that a single reference genome cannot fully represent the complexity of a species characterised by high heterozygosity, clonal propagation and a long history of diversification. Recent grapevine pangenomes, super-pangenomes and graph-based resources have revealed forms of variation that are often overlooked in conventional reference-based analyses, including structural variants and gene presence–absence variation. Rather than providing another inventory of available datasets, this review examines how continued reliance on a single reference genome may influence the interpretation of grapevine diversity and what can be gained from a broader pangenomic perspective. Drawing on recent studies in grapevine and other crops, we discuss how these approaches are beginning to improve the representation of genetic diversity, uncover biologically relevant variation and strengthen links between genomic information and adaptive traits. We also examine the challenges that still limit their practical use, particularly the integration of genomic resources with functional studies and breeding programmes. In the end, the value of pangenomics will probably depend not only on generating additional genomic resources, but also on how effectively these can be translated into tools that support grapevine conservation, climate adaptation and varietal improvement. Full article

Transportation hub cities serve as pivotal nodes within integrated transport systems. This study reveals the corridor-oriented characteristics of comprehensive transportation system, confirms the progress of its transportation hub city development, and identifies future improvement directions based on diagnostic evaluation, taking Gansu Province, China as the research subject. To address hierarchical differentiation and structural constraints in the development of integrated transportation hubs, this study develops an evaluation framework integrating the entropy-weighted TOPSIS method, a coupling coordination model, and indicator-based diagnostic analysis. This framework was applied to 14 prefecture-level cities and autonomous prefectures in Gansu, classifying them into four hub tiers according to the comprehensive evaluation index. The results reveal a pronounced hierarchical and corridor-oriented spatial structure: Lanzhou is identified as the only Tier 1 core hub, five cities are classified as Tier 2 backbone hubs, seven cities and prefectures as Tier 3 general hubs, and Pingliang as Tier 4 terminal hub. Lanzhou exhibits the highest development level, with a comprehensive evaluation index of 0.9640, which is substantially higher than the provincial mean of 0.3867, but its radiation-driving capacity still needs to be strengthened. In terms of subsystem coordination, Lanzhou reaches the primary coordination stage with a coupling coordination degree of 0.532, while Jiuquan, Jiayuguan, and Tianshui are classified into the near-coordination stage with D values of 0.353, 0.351, and 0.321, respectively; the remaining ten units are classified as uncoordinated relatively. Based on the combined perspectives of development level and subsystem coordination, the study identifies future development directions for hub operational organization, multimodal transport integration, feeder connectivity, and industry-logistics coupling. The findings reveal the corridor-oriented characteristics and development progress of Gansu’s transportation hub system, highlight the analytical value of distinguishing hub development level from subsystem coordination, and provide empirical evidence for understanding hierarchical and functional differentiation in corridor-oriented inland regions. Full article

Against the backdrop of China’s strategic goals of achieving carbon peaking and carbon neutrality, a key question is whether renewable electricity generation (REG) is associated with lower carbon emission intensity (CEI). To address this issue, this study employs panel data from 30 Chinese provinces from 2005 to 2024 and combines the Tapio decoupling model, Moran’s I test, and the spatial Durbin model (SDM), with the ordinary least squares (OLS) used as a benchmark to analyze the decoupling evolution, spatial spillover associations, and potential transmission channels between REG and CEI. The findings show that: (1) the relationship between REG and CEI evolves from weak decoupling to strong decoupling, suggesting a potentially nonlinear relationship; (2) CEI exhibits significant spatial autocorrelation and regional clustering; (3) REG is significantly associated with lower CEI, with both local and spatial spillover associations; (4) the local mitigation association is stronger in eastern and higher-CEI provinces, while spillover effects are more pronounced in western, northeastern, and resource-based provinces; and (5) the REG-CEI association may operate through energy structure (ES) optimization and energy intensity (EI) reduction, while environmental regulation (ER) may strengthen this association. The endogeneity tests provide supplementary evidence consistent with these findings, although they should not be interpreted as definitive causal proof. Overall, this study contributes to the sustainability literature by showing that the REG-CEI relationship is not merely a static local association, but a dynamic and spatially differentiated pattern shaped by regional coordination and energy-system adjustment. These findings provide evidence relevant to sustainability-oriented energy policy by suggesting that renewable electricity development should be assessed not only by generation scale, but also by its association with carbon-intensity reduction, spatial coordination, and energy-system efficiency Full article

Developing critical thinking is a central aim of contemporary higher education, yet conventional instructional approaches often underuse authentic, real-world materials that stimulate higher-order reasoning and reflective judgment. The study examines the effectiveness of case-based socio-legal pedagogy in fostering critical thinking within contexts of legal pluralism and social complexity. A quasi-experimental mixed-methods pre–post design was conducted with 62 undergraduate students enrolled in a course on Islamic law and society. Over a four-week intervention, students engaged with six socio-legal cases drawn from Muslim women’s legal experiences in Israel, focusing on divorce, maintenance (nafaka), and child custody. Quantitative data were collected using a validated Critical Thinking Rubric assessing argumentation, evaluation of multiple perspectives, and legal reasoning. Results showed significant improvement in overall critical thinking, with gains across all measured dimensions. Qualitative analysis of written assignments and student reflections revealed greater recognition of legal ambiguity, more structured and evidence-based argumentation, and deeper engagement with competing normative and social frameworks. Overall, the findings highlight the pedagogical value of integrating socio-legal complexity into case-based learning as an adaptable model for strengthening critical thinking across disciplines involving interpretive, contested, and context-dependent knowledge in higher education and other fields requiring careful judgment under conditions of uncertainty and change. Full article