Search Results (2,432)

Background: Public health in Greece has undergone substantial changes since the COVID-19 pandemic, while challenges related to governance, workforce distribution, regional inequalities and service organization remain. This study aimed to map the current public health landscape in Greece by examining its institutional frameworks, stakeholder roles, policy implementation and public health data systems. Methods: A structured situation analysis combining a review of peer-reviewed and gray literature, policy analysis, and stakeholder mapping was conducted. PubMed, EMBASE, and CINAHL were searched for English- and Greek-language publications issued between 2005 and 2026, supplemented by reports, legislation, and policy documents from the Greek Ministry of Health, the World Health Organization, the Organisation for Economic Co-operation and Development, the European Commission, and other relevant institutions. Results: Public health responsibilities were distributed across multiple national, regional, and local institutions, creating challenges concerning coordination and accountability. Regional and socioeconomic inequalities continued to affect access to services, while workforce shortages and skill-mix imbalances constrained public health capacity. Public health information was dispersed across different institutions and data systems, with limitations concerning standardization, accessibility, and interoperability. Recent legislation, prevention programs, and digital-health initiatives indicated increased policy attention to prevention and population health, although publicly available evidence regarding their implementation and outcomes remained limited. Conclusions: Strengthening public health in Greece requires clearer institutional responsibilities, improved coordination across governance levels, sustainable workforce planning and interoperable data systems that support routine monitoring of program coverage, equity, and population-level outcomes. Full article

Sustainable energy systems increasingly rely on digital auxiliary processes that convert telemetry, forecasts, diagnostic evidence, and operating rules into reviewable information for authorized human decision-makers. This targeted review develops a transparent and traceable conceptual evidence-to-review framework for photovoltaic, wind, storage, fuel-cell, and converter-coupled systems. The coded review pool comprised 100 sources, including 75 analytical and 25 contextual sources; 10 additional references supported methodological, technical, and case-specific context and were not included in thematic coding. A six-stage thematic analysis, supported by a revision-stage coding audit, identified five analytical layers: data-quality control, forecasting and uncertainty, explanation diagnostics, constrained evidence briefing, and accountable human review. These layers were translated into an eight-stage advisory architecture that separates evidence preparation, validation, briefing, and review from the authorized control plane. No direct large-language-model-to-controller or model-to-asset path is permitted. An illustrative Jeju scenario traces one evidence record through the architecture and shows how safety conditions, evidence admissibility, and procedural authority lead to CHECK, HOLD, or ESCALATE outcomes. The review concludes that trustworthy digital support requires traceable evidence, deterministic safety and rule boundaries, and accountable human authorization. Full article

As artificial intelligence and digital human technologies become increasingly integrated into livestream commerce, AI anchors are becoming important marketing agents. Yet prior research has focused primarily on their visual characteristics, leaving dynamic vocal cues largely unexplored. Drawing on social response theory and perceived authenticity research, this study examines the nonlinear association between AI anchor pitch variability and consumer engagement, together with a proposed psychological pathway and boundary condition. Study 1 analyzes 4322 product-presentation segments nested within 330 AI-anchored livestreams and 85 independent accounts on Douyin. Negative binomial models, formal boundary-slope tests, and additional specifications using account and livestream-session fixed effects, a correlated-random-effects decomposition, and viewer-minutes exposure provide robust evidence of an inverted U-shaped association between pitch variability and real-time danmaku engagement. Evidence concerning appearance-realism moderation is conditional and specification-sensitive across alternative pitch operationalizations, exposure definitions, and within-account specifications. Study 2 uses a preregistered multi-stimulus mixed design with four AI anchors, four products, and three between-participants pitch-variability conditions. Correctly scaled planned contrasts show that moderate pitch variability produced greater perceived authenticity and engagement intentions than the average of the two endpoint conditions. A 2-1-1 multilevel analysis yielded an indirect-effect pattern consistent with the proposed role of perceived authenticity. Models allowing treatment effects to vary across the 16 included anchor-product combinations showed a positive average moderate-pitch advantage, although its magnitude varied across stimuli. These findings extend livestream-commerce research from human streamers to AI-mediated communication while indicating that appearance-realism moderation, stimulus-level generalization, and causal mediation require further replication. Full article

This mixed-methods study examines the associations among fintech advancement, green finance, and financial inclusion in Jordan, an emerging economy. It draws on a distinctive three-part dataset: survey data from 21 commercial banks (N = 21), a national household survey, and semi-structured interviews with stakeholders. The quantitative results indicate that the positive association between fintech adoption and the provision of green finance is statistically consistent with full mediation by banks’ absorptive capacity, particularly their digital maturity and data analytics capabilities. Proactive regulatory support significantly moderates this mediated relationship. Market demand, by contrast, has no statistically significant moderating effect. At the household level, the combined use of digital and green financial products is associated with higher formal account ownership and with the use of a greater number of financial products. The interviews support these results, pointing to institutional capacity and regulatory clarity as essential enabling factors. Given the cross-sectional bank-level data (N = 21) and the exploratory scope of the mediation analysis, causal interpretations should be avoided. Future longitudinal research is needed to examine temporal dynamics. Even so, these findings offer policymakers an initial empirical framework: channeling fintech toward sustainable development will likely require targeted interventions to build institutional digital capacity and establish clear regulatory frameworks, rather than depending solely on market forces. Full article

The MENRO: Monitoring and Management System is a digital solution developed to modernize the manual operations of the Municipal Environment and Natural Resources Office (MENRO). The system provides a secure and user-friendly platform designed to streamline document handling, automate monitoring tasks, and ensure accurate environmental data management. This project specifically aims to: (1) develop a user-friendly interface that enables seamless document and record management, allowing administrators to effortlessly add, edit, update, and store essential information, and (2) design a system that is capable of automatically generating comprehensive lists of apprehension receipts, including violations and penalties issued to establishments under MENRO’s jurisdiction. These functions address long-standing inefficiencies in manual monitoring, recordkeeping, and compliance tracking. The system was evaluated using the ISO/IEC 25010:2011 software quality standards, focusing on functional suitability, performance efficiency, reliability, usability, compatibility, maintainability, portability, and security. Results show high usability and strong security features, ensuring that the platform meets operational needs while safeguarding sensitive environmental and legal records. By integrating real-time data access, automated reporting, and digitized forms used in environmental compliance checks, the system enhances MENRO’s capability to uphold environmental governance with greater transparency, accuracy, and accountability. Full article

Although stablecoins occupy a segment of digital-asset markets in which price stability is central by design, their temporary departures from reference values may reveal important information about latent risk and market stress. In this paper, we examine whether bubble and crash signals extracted from traditional cryptocurrencies and stablecoins improve volatility, Value-at-Risk, and Expected Shortfall forecasting and, in connection with these forecasting gains, contribute to the assessment of cross-asset contagions. The analysis applies the Bubble Crash–GARCH models, in which extreme price phases are identified through the Phillips, Shi, and Yu real-time monitoring procedure and incorporated into the conditional mean of returns through event-based dummy variables. For stablecoins, extreme episodes are not inferred from price dynamics in isolation but from deviations between the observed price and the asset-specific reference value. The empirical investigation focuses on Bitcoin, Ethereum, Tether’s USD-pegged (USDT), and Tether Gold and evaluates asset-specific bubble–crash effects and bidirectional contagion channels between traditional cryptocurrencies and stablecoins, using Bitcoin and Tether as the leading representatives of the two market segments. The findings indicate that accounting for bubble and crash episodes leads to more accurate volatility forecasts than standard GARCH benchmarks. For Value-at-Risk and Expected Shortfall, the bubble–crash specifications can improve tail risk forecasting at several tail probability levels through more accurate coverage, lower quantile loss, and stronger ESR backtesting performance. The results also reveal different degrees of price exuberance across the two asset categories: while extreme price dynamics are more evident among traditional cryptocurrencies, deviations from fundamentals are rare for stablecoins. Among stablecoins, USDT exhibits limited but detectable exuberance, whereas Tether Gold does not display extreme price episodes. However, when such deviations occur, as in the case of USDT, they generate significant contagion effects on major cryptocurrencies. Notably, extreme episodes originating in USDT have a stronger impacts on Bitcoin and Ethereum than the reverse spillovers from traditional cryptocurrencies to USDT. Overall, the evidence suggests that stablecoins are not merely passive instruments within the digital-asset ecosystem. Even temporary deviations from their reference values contain valuable information for risk forecasting and contagion monitoring. Full article

Architecture has often represented itself through permanence, stability, and formal autonomy while materially existing through irreversible exchanges, dissipation, aging, maintenance, and transformation. Situated within a cumulative research program on architectural conception, thermodynamics, constructal law, environmental transfer, digital design, and spatial morphogenesis, this article isolates a more specific question: how can irreversibility and constructal law become generative principles within architectural design rather than corrective considerations applied after form has been established? The study develops a situated theoretical-methodological framework in which the building is approached as a finite open configuration traversed by thermal, material, environmental, and occupational flows. Drawing on the second law of thermodynamics, exergy degradation, finite-time processes, boundary-layer reasoning, and constructal access, the framework organizes design through the definition of the finite domain, the identification of gradients, the localization of resistance and irreversible loss, the spatial and temporal staging of differences, the organization of access, and the evaluation of geometry through dynamic persistence. The framework is applied to an unbuilt amphibious dwelling as a research-by-design case study, examining its implications for site interpretation, flood accommodation, sectional organization, envelope depth, material differentiation, circulation, and maintenance. The application is not presented as a complete numerical performance validation, but as an architectural translation of the method that establishes the basis for subsequent computational, structural, material, and life-cycle testing. The article contributes a focused account of architecture as the organization of irreversible processes under finite constraints and proposes a design methodology through which gradients, resistances, transfers, and temporal transformations may participate directly in the generation of form. Full article

Background: Corporate energy transition can create efficiency, financing, and valuation benefits, but it also exposes firms to implementation, information, and transition risks. This study examines whether digital transformation helps firms convert energy-transition strategies into financial value. Unlike prior studies that mainly treated digitalization or sustainability as broad direct predictors, this study examines an implementation-based, multidimensional digital capability as a boundary condition across three distinct energy-transition strategies and both accounting- and market-based financial outcomes. Methods: Using an unbalanced panel of 30 firms associated with Indonesia’s LQ45 Low Carbon Leaders Index (120 firm years, 2020–2025), we construct a 30-item implementation-based Digital Transformation Index and estimate two-way fixed-effects models with firm-level wild-cluster-bootstrap inference, conditional marginal effects, false-discovery-rate adjustment, and prespecified robustness checks. Results: Clean energy use is positively associated with return on assets, return on equity, and Tobin’s Q. Low-carbon operational efficiency is most clearly associated with return on assets, whereas renewable energy use is primarily reflected in Tobin’s Q. Digital transformation is positively associated with all three outcomes and selectively strengthens the financial effects of the three transition strategies. Conclusions: Digital transformation is not a universal performance amplifier. It functions as a strategy- and outcome-specific value-conversion and risk-management capability that improves the monitoring, coordination, financing, verification, and communication of energy-transition investments. Full article

Construction materials move in large volumes, over varying distances and through fragmented logistics chains. Yet EN 15804 Module A4, which covers transport to the building site, is still often calculated with static assumptions rather than verified transport data. This creates a gap between declared and project-specific cradle-to-site emissions, especially when circular strategies shift flows from factory-to-site towards site-to-site, site-to-processing and processing-to-site logistics. This paper focuses on dynamic A4 assessment, using macro-level analysis to identify the material flows, spatial patterns, transport modes and digital data needed for traceable logistics-based carbon accounting. The framework connects construction material-flow analysis with Digital Product Passports, ISO 14083 logistics data, GS1 Digital Link, GS1 EPCIS and digital-twin concepts. Building-permit data are used as spatial indicators of material sinks and transport-demand hotspots. The analysis uses Slovenian road, rail and maritime freight statistics, operational railway data for construction-related material categories, CDW data and building-permit data for 2020–2024. Results show that domestic road transport accounts for 93–95% of transported construction-material tonnage, while the smaller international freight volume generates nearly half of total ton-kilometers. Macro-level analysis is essential for locating material demand, potential transport hotspots and 5R strategies: refuse, reduce, reuse, repurpose and recycle. This study defines key information needs for product identification, transported mass, transport legs, distance, mode, energy pathway, load factor, empty running, logistics events and traceability. The results support policymakers, standardization bodies, contractors, logistics providers, manufacturers, researchers and software developers. Full article

Construction projects generate substantial material waste and embodied carbon losses, yet no integrating framework currently transforms routine project documentation into stage-specific decision signals during building delivery. This paper proposes Construction Material Flow Intelligence (CMFI), a project-level decision-support framework that applies mass-balance principles within a four-layer processing architecture to convert standard procurement records, delivery logs, installation data, and waste records into six performance indicators and structured operational signals. CMFI operates at the project-stage-material scale and produces three classes of output: procurement-adjustment signals, waste reduction triggers, and storage optimisation recommendations. An illustrative application to a five-storey commercial building across five material categories and three construction stages demonstrates that CMFI generates seven decision signals and identifies approximately 27.2 tCO₂e of avoidable embodied carbon loss from routine project documentation, without bespoke sensing infrastructure. Component sensitivity analysis confirms that waste classification, stage-based tracking, and embodied carbon integration are each load-bearing elements of the framework. CMFI addresses the gap between aggregate material flow analysis and project-level operational management by shifting construction material monitoring from retrospective waste reporting to stage-resolved sustainability intelligence. Limitations include the use of illustrative rather than empirical data, single-period stage accounting, and uncalibrated trigger thresholds; empirical validation and digital implementation are identified as priority future directions. Full article

This article explores the topic of digital sovereignty from the vantage point of the theory of politics, maintaining that AI disrupts the traditional Westphalian principle of state sovereignty. Drawing on the normative frame of Roberts and the comparative analyses of Larsen and Kurbalija, it illustrates the three competing philosophical models of digital self-determination: the liberal market model (United States), the techno-legal rights model (European Union), and the cyber-sovereignty model (China), and evaluates the normative presumption. It furthermore assesses these models in light of emerging legislative patterns in Vietnam, arguing that true digital sovereignty requires more than technical infrastructure but a philosophically cohesive conception of collective self-determination in an increasingly interconnected world. The article concludes with an outline for a relational account of digital sovereignty incorporating autonomy/interdependence. Full article

The increasing digitalization of higher education has created the need for ICT-assisted instructional frameworks capable of supporting both technical competency development and pervasive skills acquisition. This study presents a data-driven framework for informing ICT-assisted instruction based on the assessment of accountancy students’ perceived importance and readiness regarding pervasive skills. An online survey was conducted among students enrolled in the Accountancy program at Romblon State University using a researcher-developed instrument covering personal attributes, intellectual and professional skills, interpersonal and communication skills, and professional ethics and moral values. Descriptive statistics and paired-samples t-tests were employed to identify readiness gaps across the four competency domains. Results indicate statistically significant differences between perceived importance and readiness, with communication-related competencies exhibiting the largest readiness gaps. These findings provide empirical requirements for designing human-centered ICT-assisted instructional systems that integrate digital collaboration platforms, simulations, adaptive learning technologies, and analytics-driven learning activities. The proposed framework supports evidence-based instructional configuration by aligning technology-enhanced learning environments with learner competency needs, thereby contributing to the development of more responsive educational information systems for accounting education. Full article

Artificial Intelligence (AI) is now part of accounting systems, changing the way that accounting data is handled and the quality of the financial reporting. The impact of the qualifications of accountants and the adoption of AI has been studied separately in previous studies and the mediating variable of AI between the two variables, accounting education and information quality, has not been studied yet. This research aims to explore the relationship between the academic qualifications of accountants, AI in accounting systems, and accounting information quality between the two major variables explored in this study. The study design adopted for this study is quantitative research which involved 353 respondents in Saudi Arabia. The proposed measurement and structure models were tested using a software program known as SmartPLS which is partial least squares structural equation modeling (PLS-SEM), including mediation analysis. The results indicate that the academic qualification of an accountant does not directly significantly affect the quality of accounting information but it has an indirect significant effect via AI. Moreover, AI has strong positive effects on the quality of accounting information and acts as an important mediator between the academic qualification of the accountants and quality of accounting information. This research’s results have shown that the use of the AI capabilities in an accountant’s education and professional training is important in improving the quality of financial reporting. It also adds to the socio-technical systems literature by highlighting AI’s potential to link human capital and accounting information quality in the evolving digital accounting environment. Full article

Co-Creative Robotics combines computational creativity, robotic embodiment, and human–robot collaboration to support or generate creative behavior in physical and social environments. As these systems become more autonomous, data-intensive, and interactive, cybersecurity and privacy can no longer be treated as external safeguards added after creative functionality has been designed. This PRISMA-informed review investigates whether principles of cybersecurity-by-design and privacy-by-design can be integrated into Co-Creative Robotics without constraining creativity, autonomy, and user agency. The database search covered ACM Digital Library, Google Scholar, IEEE Xplore, Scopus, SpringerLink, and Web of Science, and was complemented by two focused backward and forward snowballing iterations. From 623 database records, the final synthesis includes 27 primary studies. The results show that direct literature combining cybersecurity, privacy, and Co-Creative Robotics remains limited, but evidence from creative HRI, social-robot privacy, cyber-physical security, privacy-preserving interaction design, security modeling, and robot ethics supports a conditional answer. Integration is feasible when security and privacy mechanisms are adaptive, explainable, participatory, context-sensitive, and lifecycle-aware. However, the evidence on transparency-oriented privacy mechanisms is mixed: improvements in awareness or acceptance do not consistently translate into reduced disclosure or greater perceived safety. Rigid controls may constrain creative exploration, whereas well-designed controls can support trust, accountable autonomy, safe embodiment, privacy-aware interaction, provenance, and agency-preserving creativity. The review proposes a conceptual lifecycle-oriented research agenda for secure and privacy-aware Co-Creative Robotics. Full article

Digital infrastructure (DI) and agricultural socialized services (ASSs) are key drivers of agricultural value chain efficiency (AVCE), yet their causal effects remain confounded by endogeneity bias. This study constructs an integrated SFA-Tobit-DML framework using 31-province Chinese panel data (2011–2023). SFA estimates provincial technical efficiency; Tobit provides associational benchmarks; and Double Machine Learning (DML) with K = 5 cross-fitting identifies causal average treatment effects (ATEs). The DML results validate the Tobit benchmark for DI (LassoCV ATE: 0.810, 95% CI [0.656, 0.963]; Tobit: 0.826), while revealing Tobit overestimates ASSs by approximately 37% (LassoCV: 0.850 [0.599, 1.101]; Tobit: 1.347). Bootstrap mediation tests confirm that agricultural R&D investment mediates 61.58% and 47.45% of DI and ASS effects. Heterogeneity analysis shows that urbanization amplifies DI marginal returns (ATE: 1.401 in low-urban vs. 0.711 in high-urban regions), while government intervention exhibits conditional crowding-out effects. These findings imply that policies should shift from uniform investment toward regionally differentiated strategies that account for local absorptive capacity. Full article