Search Results (2,153)

The digitization of Human Resource (HR) processes is currently regarded as a vital step towards enhancing efficiency, transparency, and employee satisfaction within organizations. This research paper analyzes the circumstances under which the digitization process in human resource management within innovative business entrepreneurship will affect corporate sustainable development. The present study assesses employee satisfaction with the innovative digital HR tools used and identifies the perceived benefits and barriers in assessing the impact of digitization on the functioning of HR processes. The primary objective of the research paper is to estimate the impact of the digitization of personnel management processes, from the perspective of employees, on their satisfaction with the innovative digital personnel tools used, and to determine the extent to which innovative digitization tools would affect the sustainable development of the corporation. The estimation is based on the data assessment approach regarding the questionnaire survey conducted within the framework of the VEGA project output. The primary method employed for hypothesis verification is the chi-square test, accompanied by graphical representation. The findings of this study suggest that corporations must strategically allocate resources to invest in digital tools and cultivate digital competencies within their workforce if they are to reap the full benefits of digitization and innovation processes. The ability to adapt to and leverage innovative, cutting-edge digital technologies will be a key determinant in terms of reinforcing sustainable development in business. Full article

This study analyses the development of digital and artistic competence among pre-service language teachers within the framework of a teaching innovation project (2018–2024) at the University of Oviedo. It not only explores student teachers’ perceptions of the proposal’s pedagogical usefulness but also seeks to determine whether statistically significant differences exist between participating master and undergraduate students. The research adopts a mixed-methods approach: the qualitative component is based on the European DigCompEdu framework, while the quantitative component employed an ad hoc questionnaire analysed using SPSS (v.22), including descriptive analysis, Levene’s test to assess equality of variances and Student’s t-test to identify potential significant differences according to the master–undergraduate variable. The results indicate, on the one hand, that this initiative successfully strengthens five of the six areas defined in the European framework, and on the other, that there is an overall high level of satisfaction, reflected in the high scores obtained in the competences examined in this study: artistic, digital and pedagogical. These findings underscore the value of integrating innovative, video-based strategies into teacher education programmes to support the development of key competences required for 21st-century teaching. Full article

Active learning has increasingly been adopted as an evidence-aligned approach to improving learning quality in university physics—a domain characterized by high conceptual abstraction, persistent misconceptions, and substantial variability in student performance. Evidence from physics education research indicates that active-learning designs can outperform lecture-dominant instruction in conceptual learning and student engagement; however, reported effects vary substantially across instructional settings and implementation models. Here, empirical studies and review-level syntheses are integrated to delineate (i) the instructional components that most reliably underpin successful active learning, (ii) the mechanisms through which these components influence learning processes and outcomes, and (iii) the boundary conditions that moderate effectiveness across higher-education contexts. The synthesis is further situated within sustainability-oriented higher education by linking physics active-learning designs to competence development relevant to quality education, climate literacy, and collaborative problem solving. Evidence spanning flipped classroom implementations, peer instruction, collaborative problem solving, inquiry- and project-based approaches, and technology-enhanced formats is organized into a component–mechanism–outcome framework structured along cognitive, affective, and behavioral pathways. Two deliverables are advanced: an integrative mechanism model connecting instructional components to mediating processes, learning outcomes, and sustainability-aligned competencies, and an operational toolbox that translates the evidence into actionable design heuristics, measurement options, and scaling considerations. By redirecting attention from “which strategy works” to “which components work, how, and under what conditions,” the review aims to support instructors, departments, and institutions seeking scalable, evidence-aligned active learning in university physics. Full article

This article maps and prioritises the foundational developmental needs of children and adolescents: social development, cognitive growth, emotional regulation, identity formation, and moral reasoning. Early and excessive digital engagement is then examined for its potential to impact these milestones, with consequences that reverberate through wellbeing, relationships, and lifelong resilience. Arguments which frame digital engagement as an individual right with potential benefits, downplay developmental risks. Drawing on developmental rights and agency frameworks, the current review disputes the prevailing assumption that digital participation should take precedence over healthy developmental trajectories. Instead, the debate is reframed around children’s evolving capacities. It is proposed that digital entitlements are nested within age-appropriate limits and supports. Protecting the best interests of the child requires recognising the risk of addictive technology use. The rights of the child must also ensure cultivation of emotional competence and self-reliance. Overemphasis on digital expression risks elevating performative self-presentation before moral reasoning, critical thinking, and offline social skills have matured, particularly within environments shaped by algorithmic amplification, transient relationships, peer harassment, and the desire for validation. To address these risks, we advocate for a multi-layered public health response: consistent, developmentally attuned messaging; empowered parents and educators; whole-school strategies; and policy reforms that prioritise safety, accountability, and developmental alignment. By situating digital engagement within a developmental framework, this article proposes key principles on which to base the discussion of safeguarding youth wellbeing in the digital era. Full article

Background: Combinatorial optimization problems (COPs) are central to Logistics and Supply Chain decision making, yet their NP-hardness prevents exact optimal solutions in reasonable time. Methods: This work addresses that limitation by developing a novel ternary network flow linear programming (LP) model of the assignment problem (AP) polytope. The model is very large scale (with $\mathsf{\Theta }\left(m^9\right)$ variables and $\mathsf{\Theta }\left(m^8\right)$ constraints, where m is the number of assignments). Although not intended to compete with conventional two-dimensional formulations of the AP with respect to solution procedures, it enables hard COPs to be solved exactly as “strict” (integrality requirements-free) LPs through simple transformations of their cost functions. Illustrations are given for the quadratic assignment problem (QAP) and the traveling salesman problem (TSP). Results: Because the proposed LP model is polynomial-sized and there exist polynomial-time algorithms for solving LPs, it affirms “$P=NP$.” A separable substructure of the model shows promise for practical-scale instances due to its suitability for large-scale optimization techniques such as Dantzig–Wolfe Decomposition, Column Generation, and Lagrangian Relaxation. The formulation also has greater robustness relative to standard network flow models. Conclusions: Overall, the approach provides a systematic, modeling-barrier-free framework for representing NP-complete problems as polynomial-sized LPs, with clear theoretical interest and practical potential for medium to large-scale Logistics and other COP-intensive applications. Full article

Green AI contributes to digital sustainability in higher education by encouraging computationally efficient technologies and responsible digital practices. Despite growing interest in sustainable AI, empirical evidence remains limited on how Gen Z students develop socially responsible intentions toward the use of sustainability-aligned AI, particularly within a single host-country higher-education context. This study examines these intentions among students enrolled in Saudi Arabia, using a culturally diverse sample of Saudi and international students while treating national origin as a demographic characteristic rather than a basis for cross-national comparison. The research also addresses emerging concerns related to AI hallucinations and ethical governance in educational settings. An integrated framework is employed that combines the instrumental appraisal logic of UTAUT with responsibility-oriented constructs. The model includes Sustainable Performance Value (SPV), Responsible Use Ease (RUE), Ethical Social Norms (ESN), Institutional Ethical Support (IES), Responsible AI Competence (RAC), AI Hallucination Awareness (AHA), and Green Digital Responsibility (GDR) as predictors of Socially Responsible Intentions (SRI). Data were collected through an anonymous survey of 1159 higher-education students residing and studying within the Saudi higher-education system. The study design reflects one institutional context rather than a multi-country comparison. The findings show strong explanatory and predictive capability (R² = 0.64; Q² = 0.43). SPV, RAC, AHA, and GDR are the strongest predictors of SRI, while RUE shows a moderate association and IES provides contextual support; ESN is not significant. The results highlight the importance of values, competence, and risk awareness in shaping the responsible use of AI. Implications focus on governance and curriculum strategies that support sustainability-aligned engagement with AI in higher education. Full article

The scheduling of Earth observation satellites presents a formidable multi-objective optimization challenge, characterized by inherent trade-offs among task completion rate, execution timeliness, and the temporal uniformity of revisits. To address this, we introduce the Multi-Satellite Observation Task Scheduling (MSOTS) framework, a novel end-to-end approach based on Multi-Agent Reinforcement Learning (MARL). This framework formulates the scheduling process as a Markov game, employing the Multi-Agent Proximal Policy Optimization (MAPPO) algorithm within a Centralized Training, Decentralized Execution (CTDE) paradigm to effectively navigate these competing objectives. Furthermore, to ensure a balanced evaluation, we propose a Composite Multi-Objective Performance Score grounded in a weighted harmonic mean. Comprehensive empirical evaluations conducted on large-scale, simulated orbital scenarios demonstrate that MSOTS significantly outperforms both traditional heuristics and existing deep reinforcement learning methods in comprehensive performance and robust efficiency. This research provides a highly effective and intelligent approach to modern satellite task scheduling. Full article

Higher education institutions are expected to cultivate graduates capable of addressing sustainability challenges through innovation, collaboration, and digital competence. However, many business programs struggle to integrate experiential authenticity, intelligent technologies, and collaborative learning into coherent instructional models, limiting students’ intrinsic motivation and sustainability-oriented competence development. This study aims to examine how experiential learning, artificial intelligence-assisted collaborative learning, and team-based learning operate within the Conceive–Design–Implement–Operate instructional framework to influence learning interest and learning satisfaction in a sustainability-oriented business course. Survey data from 217 undergraduate students were analyzed using confirmatory factor analysis, structural equation modeling, and moderated regression analysis. The results indicate that both experiential and AI-supported collaborative learning positively enhance students’ learning interest, which partially mediates their effects on learning satisfaction. Team-based learning strengthens the experiential pathway but does not significantly moderate the AI-assisted pathway. These findings clarify differentiated motivational mechanisms within structured instructional systems and provide theoretical support for designing digitally enhanced sustainability education. Full article

Strengthening key competencies in veterinary preclinical education, such as anatomical identification, spatial–visual reasoning, and anatomical–surgical understanding, is essential for effective preclinical learning. In this context, veterinary preclinical education is undergoing a transformation process in which traditional theoretical–practical approaches show limitations in responding to current educational demands, making it necessary to adopt innovative strategies based on active learning and simulation. This study presents a simulation-based educational approach designed to support competency development within preclinical veterinary education. Using a reproducible and low-cost workflow applied to a real canine cranial case of extra-genital transmissible venereal tumor (TVCT) with frontal bone invasion, used exclusively as a teaching scenario. Fourteen veterinary medicine students from the same institution participated in two instructional conditions: Group A received traditional theoretical instruction (including cadaveric specimens) without the use of 3D-printed models, while Group B participated in simulation-based training supported by virtual planning and a 3D-printed cranial model. Learning outcomes are assessed through structured observation and descriptive analysis. A Likert-type survey was also used to assess satisfaction and engagement among students who participated in the model-supported training, as well as to map competencies across cognitive, visual-spatial, and anatomical-surgical reasoning domains, with evaluation conducted by veterinarians with clinical and teaching experience. Descriptive observations indicated that students participating in the simulation-based training engaged in three-dimensional anatomical exploration of cranial anatomy and case-based anatomical-surgical discussion. In addition, survey responses from Group B indicated high levels of engagement and interest, as well as high perceived usefulness of the model-supported training experience. These findings suggest that simulation-based educational frameworks may offer a safe, transferable, and pedagogically valuable strategy for competency development within preclinical veterinary education. Full article

This article examines the governance of Global Value Chains (GVCs) through the lens of economic competence based on a systematic literature review of 32 selected studies. The findings show that economic competence functions as a governance-contingent construct whose effects vary across hierarchical, captive, relational, and modular governance structures. Rather than directly determining upgrading outcomes, competence dimensions operate through governance repositioning and shifts in dependence asymmetries within value chains. The review identifies recurring mechanisms—such as substitutability reduction, coordination cost mitigation, and institutional alignment—that explain how competence and governance interact. The analysis further demonstrates that economic competence is multidimensional, encompassing innovation-oriented, market-oriented, decision-making, relational, and systemic components. These dimensions operate differently depending on coordination complexity and power distribution within the chain. By advancing a contingency-based framework, the study refines GVC governance theory through a micro-foundational explanation of upgrading dynamics. From a managerial perspective, the framework offers a structured tool for aligning competence development strategies with specific governance configurations, supporting informed capability investments and improved strategic positioning. Overall, the study contributes by systematically integrating competence theory with governance typologies and power asymmetries, providing a coherent analytical model for future empirical research. Full article

Ultra-endurance running presents significant physiological demands, with adequate nutritional intake being critical for optimal preparation, performance, and recovery. However, athletes of this sport often consume an insufficient diet. Semi-structured interviews were conducted virtually with ten recreational ultra-endurance runners (age mean ± standard deviation 46 ± 12 years; eight male, two female), all with experience competing in ultra-endurance events, to explore their ultra-endurance experience, dietary intake, nutrition knowledge, and gastrointestinal symptom management. Interviews were transcribed verbatim and thematically analysed in accordance with the COM-B model and the Theoretical Domains Framework. Themes were defined under each of the three COM-B model components: Capability: (1) knowledge and skills, (2) the intention–behaviour challenge; Opportunity: (1) facilitators and barriers to optimal nutrition, (2) information sourcing and learning; and Motivation: (1) drivers of nutrition behaviours, (2) risk perceptions’ influence on fuelling strategies. Participants demonstrated strong psychological capability, that is, awareness of nutrition’s importance, yet limited behavioural regulation to translate this knowledge into practice. Nutrition strategies were largely self-directed, relying on peers and social media over professional support. Fear of gastrointestinal symptoms and time pressures further shaped dietary decisions. These findings emphasise the importance of evidence-based nutrition guidance to support performance and recovery while minimising gastrointestinal symptom risk. For practitioners and self-coached athletes, recommendations should reflect the practical realities and competing demands of ultra-endurance runners’ daily lives and be feasible within real-world settings. Full article

This paper examines the relation between transversal skills, economic education, and financial literacy in modern education. A systematic literature review was conducted in accordance with the PRISMA 2022 methodology, resulting in the selection and analysis of 49 peer-reviewed articles from Scopus and Web of Science. The paper explores theoretical considerations, pedagogical strategies, and the possibility of integrating these fields into educational practice. It identifies three specific points of research interest: firstly, to identify trends in the integration of transversal competencies into economic education; secondly, to assess how transversal skills impact the development of financial literacy; and thirdly, to create recommendations for educational programs and teaching methods. The results highlight that transversal skills—particularly critical thinking, collaboration, being digitally literate, and problem-solving—play an indispensable role in both learning economics and building financial literacy. While students of economic education gain insight into issues such as resource management, market mechanisms, and labor economics, financial literacy provides them with knowledge on personal finance issues, sustainability, and informed decision-making. An original aspect of the research is the attempt to merge transversal skills with economic education and financial literacy within a single framework. The results also indicate future directions of educational reform and point to ways to enhance students’ financial well-being and entrepreneurial capacity. Full article

This article investigates the phenomenon of numismatic forgery legitimisation and its impact on the fields of numismatics, archaeology, history and law. Forgery legitimisation is a broad phenomenon that encompasses both physical forgery and the presentation of fake artifacts as genuine in research literature, auction catalogues, and other contexts. Using the qualitative case-study methodology, the authors propose an analytical framework for suspected forgery legitimisation that incorporates a novel classification of forms and types of forgery, as well as socio-legal mens rea elements. The framework also accounts for factors contributing to the legitimisation of forgeries, including lack of competence, low competition in coin catalogue publication, tradition, closed numismatic communities, and insufficient academic and legal attention. Using this framework, the authors examine two cases of legitimisation of fake coins in medieval Polish–Lithuanian numismatics. The analysis shows how repetition across sources can legitimise fake artifacts, complicating later correction and corrupting heritage research, history and museum science, as well as market integrity. The proposed analytical framework can be useful for investigating other dubious artifacts and for developing analysis methods for forgery legitimisation cases. Full article

The Particle swarm optimization (PSO) algorithm has strong universality and fast convergence speed, but when solving complex multimodal optimization problems, it is prone to fall into local optimum due to insufficient population diversity. To address this issue, this paper proposes a dual-population hybrid particle swarm optimization algorithm based on Hooke’s law competition mechanism (HLCM-DHPSO). This algorithm integrates the differential evolution algorithm into the PSO framework, and the two subpopulation sizes dynamically compete for computing resources according to the adaptive mechanism of Hooke’s law. When the algorithm stagnates, HLCM-DHPSO can automatically trace back to historical archives and adjust the inertia weight based on excellent experience data. Meanwhile, HLCM-DHPSO adaptively adjusts the acceleration coefficient through the Sine function to enhance the algorithm’s ability to escape from local optimum. To verify the effectiveness of the HLCM-DHPSO algorithm, it is compared with eight advanced optimization algorithms on the CEC2017 benchmark test set. The experimental results show that HLCM-DHPSO significantly outperforms the comparison algorithms in terms of solution performance, especially in handling high-dimensional and multi-peak complex functions, demonstrating superior global search and optimization capabilities. Full article

Maintenance of skeletal muscle mass is essential for mobility, metabolic homeostasis, and clinical outcomes across a wide spectrum of physiological and pathological conditions. While muscle atrophy and hypertrophy have traditionally been interpreted through upstream anabolic–catabolic signaling and proteolytic pathways, accumulating evidence indicates that ribosome biogenesis and translational control represent rate-limiting determinants of muscle plasticity. However, this regulatory layer remains insufficiently integrated into current models of muscle adaptation and disease. In this review, we synthesize recent advances in ribosomal RNA transcription, ribosomal protein dynamics, and translational regulation in skeletal muscle, with particular emphasis on signaling networks governed by mTORC1, c-Myc, AMPK, and FOXO. We highlight ribosome biogenesis as a central hub linking mechanical loading, nutrient availability, inflammatory stress, and metabolic status to protein synthesis capacity. Evidence from human and animal studies demonstrates that impaired ribosome production and translational efficiency precede and predict muscle atrophy in disuse, aging, cancer cachexia, and chronic disease, whereas ribosome expansion is a prerequisite for sustained hypertrophy. Beyond quantitative regulation, we discuss the emerging concept of ribosome heterogeneity as a qualitative layer of translational control that may enable selective mRNA translation during muscle growth, stress adaptation, and degeneration. We further examine ribosome–mitochondria crosstalk as a critical but underexplored mechanism coordinating anabolic capacity with cellular energetics. Finally, we outline therapeutic implications, highlighting exercise, nutritional strategies, and indirect pharmacological interventions that preserve ribosomal competence, and propose ribosome-based biomarkers as promising tools for precision management of muscle-wasting disorders. Collectively, this review positions ribosome biology as a translationally relevant framework bridging molecular mechanisms with therapeutic perspectives in skeletal muscle atrophy and hypertrophy. Full article