Search Results (584)

The integration of artificial intelligence (AI) in education offers novel opportunities to enhance critical thinking while also posing challenges to independent cognitive development. In particular, Human-Centered Artificial Intelligence (HCAI) in education aims to enhance human experience by providing a supportive and collaborative learning environment. Rather than replacing the educator, HCAI serves as a tool that empowers both students and teachers, fostering critical thinking and autonomy in learning. This study investigates the potential for AI to become a collaborative partner that assists learning and enriches academic engagement. The research was conducted during the 2024–2025 winter semester within the Pedagogical and Teaching Sufficiency Program offered by the Audio and Visual Arts Department, Ionian University, Corfu, Greece. The research employs a hybrid ethnographic methodology that blends digital interactions—where students use AI tools to create artistic representations—with physical classroom engagement. Data was collected through student projects, reflective journals, and questionnaires, revealing that structured dialog with AI not only facilitates deeper critical inquiry and analytical reasoning but also induces a state of flow, characterized by intense focus and heightened creativity. The findings highlight a dialectic between individual agency and collaborative co-agency, demonstrating that while automated AI responses may diminish active cognitive engagement, meaningful interactions can transform AI into an intellectual partner that enriches the learning experience. These insights suggest promising directions for future pedagogical strategies that balance digital innovation with traditional teaching methods, ultimately enhancing the overall quality of education. Furthermore, the study underscores the importance of integrating reflective practices and adaptive frameworks to support evolving student needs, ensuring a sustainable model. Full article

Background and aim: Advanced Therapy Medicinal Products (ATMPs) are innovative drugs based on genes, tissues, or cells that target rare and severe diseases. ATMPs have shown promising clinical outcomes but are associated with high costs, raising questions about cost-effectiveness. Hence, this systematic review aims to analyze the cost-effectiveness and cost-utility profiles of the European Medicines Agency-authorized ATMPs for treating rare diseases. Methods: A systematic review was conducted following PRISMA guidelines. Studies were identified by searching PubMed, Embase, Web of Science, and ProQuest scientific databases. Economic evaluations reporting incremental cost-effectiveness/utility ratios (ICERs/ICURs) for ATMPs were included. Costs were standardized to 2023 Euros, and a cost-effectiveness plane was constructed to evaluate the results against willingness-to-pay (WTP) thresholds of EUR 50,000, EUR 100,000, and EUR 150,000 per QALY, as part of a sensitivity analysis. Results: A total of 61 studies met the inclusion criteria. ATMPs for rare blood diseases, such as tisagenlecleucel and axicabtagene ciloleucel, were found to be cost-effective in a majority of studies, with incremental QALYs ranging from 1.5 to 10 per patient over lifetime horizon. Tisagenlecleucel demonstrated a positive cost-effectiveness profile in the treatment of acute lymphoblastic leukemia (58%), while axicabtagene ciloleucel showed a positive profile in the treatment of diffuse large B-cell lymphoma (85%). Onasemnogene abeparvovec for spinal muscular atrophy (SMA) showed uncertain cost-effectiveness results, and voretigene neparvovec for retinal diseases was not cost-effective in 40% of studies, with incremental QALYs around 1.3 and high costs exceeding the WTP threshold set. Conclusions: ATMPs in treating rare diseases show promising economic potential, but cost-effectiveness varies across indications. Policymakers must balance innovation with system sustainability, using refined models and the long-term impact on patient outcomes. Full article

Amid intensifying global ESG regulations and the expanding influence of green finance, China’s digital economy policies have emerged as key institutional instruments for promoting corporate sustainability. Leveraging the implementation of the National Big Data Comprehensive Pilot Zone as a quasi-natural experiment, this study utilizes panel data of Chinese listed firms from 2009 to 2023 and applies multi-period Difference-in-Differences (DID) and Spatial DID models to rigorously identify the policy’s effects on corporate ESG performance. Empirical results indicate that the impact of digital economy policy is not exerted through a direct linear pathway but operates via three institutional mechanisms, enhanced information transparency, eased financing constraints, and expanded fiscal support, collectively constructing a logic of “institutional embedding–governance restructuring.” Moreover, disruptive technological innovation significantly amplifies the effects of the transparency and fiscal mechanisms, but exhibits no statistically significant moderating effect on the financing constraint pathway, suggesting a misalignment between innovation heterogeneity and financial responsiveness. Further heterogeneity analysis confirms that the policy effect is concentrated among firms characterized by robust governance structures, high levels of property rights marketization, and greater digital maturity. This study contributes to the literature by developing an integrated moderated mediation framework rooted in institutional theory, agency theory, and dynamic capabilities theory. The findings advance the theoretical understanding of ESG policy transmission by unpacking the micro-foundations of institutional response under digital policy regimes, while offering actionable insights into the strategic alignment of digital transformation and sustainability-oriented governance. Full article

This research examines the shifting geography of small firm innovation in the U.S. by tracking the location of small business innovation research (SBIR) and small business technology transfer (STTR) awardees between 2010 and 2024. The SBIR and STTR are “seed fund” awards coordinated by the Small Business Administration (SBA) and funded through 11 U.S. federal agencies. Of particular interest is whether the number of individual SBA awards, awarded firms, and/or funding amounts are (1) becoming increasingly concentrated within regional innovation hubs and (2) exhibiting a shift toward or away from urban centers and other walkable, transit-accessible urban neighborhoods, particularly since 2020 and the COVID-19 pandemic. While the rise of remote work and pandemic-related fears may have reduced the desirability of urban spaces for both living and working, there remain significant benefits to spatial agglomeration that may be especially crucial for startups and other small firms in the knowledge- or information-intensive industries. The results suggest that innovative activity of smaller firms has indeed trended toward more centralized, denser, and walkable urban areas in recent years while also remaining fairly concentrated within major metropolitan innovation hubs. The pandemic appears to have resulted in a measurable, though potentially short-lived, cessation of these trends. Full article

A critical gap exists between coastal communities’ need for accessible flood risk assessment tools and the availability of sophisticated modeling, which remains limited by technical barriers and computational demands. This study introduces three key innovations through Coastal Defense Pro: (1) the first operational web-based AI ensemble for coastal flood risk assessment integrating real-time multi-agency data, (2) an automated regional calibration system that corrects systematic model biases through machine learning, and (3) browser-accessible implementation of research-grade modeling previously requiring specialized computational resources. The system combines Bayesian neural networks with optional LSTM and attention-based models, implementing automatic regional calibration and multi-source elevation consensus through a modular Python architecture. Real-time API integration achieves >99% system uptime with sub-3-second response times via intelligent caching. Validation against Hurricane Isabel (2003) demonstrates correction from 197% overprediction (6.92 m predicted vs. 2.33 m observed) to accurate prediction through automated identification of a Chesapeake Bay-specific reduction factor of 0.337. Comprehensive validation against 15 major storms (1992–2024) shows substantial improvement over standard methods (RMSE = 0.436 m vs. 2.267 m; R² = 0.934 vs. −0.786). Economic assessment using NACCS fragility curves demonstrates 12.7-year payback periods for flood protection investments. The open-source Streamlit implementation democratizes access to research-grade risk assessment, transforming months-long specialist analyses into immediate browser-based tools without compromising scientific rigor. Full article

Unmanned Aerial Vehicle Remote Sensing (UAV-RS) has emerged as a transformative technology in high-resolution Earth observation, with widespread applications in precision agriculture, ecological monitoring, and disaster response. However, a systematic understanding of its scientific evolution and structural bottlenecks remains lacking. This study collected 4985 peer-reviewed articles from the Web of Science Core Collection and conducted a comprehensive scientometric analysis using CiteSpace v.6.2.R4, Origin 2022, and Excel. We examined publication trends, country/institutional collaboration networks, keyword co-occurrence clusters, and emerging research fronts. Results reveal an exponential growth in UAV-RS research since 2015, dominated by application-driven studies. Hotspots include vegetation indices, structure from motion modeling, and deep learning integration. However, foundational challenges—such as platform endurance, sensor coordination, and data standardization—remain underexplored. The global collaboration network exhibits a “strong hubs, weak bridges” pattern, limiting transnational knowledge integration. This review highlights the imbalance between surface-level innovation and deep technological maturity and calls for a paradigm shift from fragmented application responses to integrated systems development. Our findings provide strategic insights for researchers, policymakers, and funding agencies to guide the next stage of UAV-RS evolution. Full article

In the age of artificial intelligence (AI), architectural practice faces a paradox of immense potential and creeping standardization. As humans are increasingly relying on AI-generated outputs, architecture risks becoming a spectacle of repetition—a shuffling of data that neither truly innovates nor progresses vertically in creative depth. This paper explores the critical role of data in AI systems, scrutinizing the training datasets that form the basis of AI’s generative capabilities and the implications for architectural practice. We argue that when architects approach AI passively, without actively engaging their own creative and critical faculties, they risk becoming passive users locked in an endless loop of horizontal expansion without meaningful vertical growth. By examining the epistemology of architecture in the AI age, this paper calls for a paradigm where AI serves as a tool for vertical and horizontal growth, contingent on human creativity and agency. Only by mastering this dynamic relationship can architects avoid the trap of passive, standardized design and unlock the true potential of AI. Full article

ESG serves as a key metric for measuring corporate sustainability, but divergence among rating agencies has led to uncertainty in such an assessment. This investigation identifies ESG rating divergence as a critical catalyst for corporate digital transformation, establishing empirical analysis through a robust positive correlation between the heterogeneity in sustainability assessments and organizational digitalization intensity. Comprehensive robustness examinations and endogeneity controls substantiate the persistent significance of this relationship. Mechanistically, such divergence drives technological adaptation by restructuring the R&D team composition and elevating capital allocation toward innovative initiatives. Contextual heterogeneity manifests through amplified effects in firms with elevated analyst scrutiny and stringent internal governance, whereas pollution-intensive enterprises exhibit significant effect suppression. These findings collectively advance theoretical frameworks concerning ESG evaluation economics and digital transformation drivers, while furnishing actionable implementation blueprints for corporate digitization strategists. Full article

American citizens are significantly more likely to experience property crime victimization than violent crime victimization. During a staffing crisis, police prioritize limited resources in combating serious crime; however, property crimes remain impactful to the community. Therefore, agencies need to consider innovative ways to control property crime, such as “super-cocooning” strategies that alert residents to recent offenses. These strategies intend to empower the community to implement guardianship and crime prevention measures. For these strategies to be effective, they require public buy-in and support. The present study implements a preregistered information provision survey experiment (N = 2412), similar to the strategy of super-cocooning, to assess whether the public is more likely to support such strategies to combat property crime. Although the sample held overall high support of this strategy, exposure to a super-cocooning door hanger prime produced no significant changes in perceived effectiveness. However, there was observed racial heterogeneity in the treatments: non-White respondents assigned to the treatment relative to White respondents experienced significantly increased support of super-cocooning strategies. Implications for light-footprint crime control strategies, particularly during a staffing crisis, are discussed. Full article

Wildfires are becoming an increasingly severe threat to European forests, driven by climate change, land use changes, and socio-economic factors. Integrated solutions for wildfire prevention, early detection, emergency management, and ecological restoration are urgently needed to enhance forest resilience. The Horizon 2020 SILVANUS project developed a comprehensive multi-sectoral platform combining technological innovation, stakeholder engagement, and sustainable forest management strategies. This report analyses the Slovak Republic’s participation in SILVANUS, applying a seven-criterion fit–gap framework (governance, legal, interoperability, staff capacity, ecological suitability, financial feasibility, and stakeholder acceptance) to evaluate the platform’s alignment with national conditions. Notable contributions include stakeholder-supported functional requirements for wildfire prevention, climate-sensitive forest models for long-term adaptation planning, IoT- and UAV-based early fire detection technologies, and decision support systems (DSS) for emergency response and forest-restoration activities. The Slovak pilot sites, particularly in the Podpoľanie region, served as important testbeds for the validation of these tools under real-world conditions. All SILVANUS modules scored ≥12/14 in the fit–gap assessment; early deployment reduced high-risk fuel polygons by 23%, increased stand-level structural diversity by 12%, and raised the national Sustainable Forest Management index by four points. Integrating SILVANUS outcomes into national forestry practices would enable better wildfire risk assessment, improved resilience planning, and more effective public engagement in wildfire management. Opportunities for adoption include capacity-building initiatives, technological deployments in fire-prone areas, and the incorporation of DSS outputs into strategic forest planning. Potential challenges, such as technological investment costs, inter-agency coordination, and public acceptance, are also discussed. Overall, the Slovak Republic’s engagement with SILVANUS demonstrates the value of participatory, technology-driven approaches to sustainable wildfire management and offers a replicable model for other European regions facing similar challenges. Full article

Urban environmental issues are fundamental to ecological civilization development, with key stakeholders such as governments, enterprises, social organizations, and community residents playing crucial roles in the governance process. From a network governance perspective, this study innovatively applied social network analysis (SNA) to policy co-occurrence networks, analyzing over 2300 policy documents related to China’s urban environmental governance from 2017 to 2023 to investigate evolutionary trends. The key findings indicate the following. (1) The comparative analysis across two periods reveals that China’s urban environmental governance network structure has stabilized, with both network density and centralization indices showing an upward trend. (2) The degree of centrality and betweenness centrality shows that government agencies remain the core entities within the network, while the role and influence of business enterprises have steadily increased. (3) The participation of social organizations in governance continues to increase, but community public participation in governance is insufficient. Therefore, China’s ecological environment governance network has formed a network structure with the government as the leader, enterprises as the key role, and social organizations providing effective support. Full article

Land use change plays a pivotal role in understanding surface processes and environmental dynamics, exerting considerable influence on regional ecosystem management. Traditional monitoring approaches, which often rely on manual sampling and single spectral features, exhibit limitations in efficiency and accuracy. This study proposes an innovative technical framework that integrates automated sample generation, multi-feature optimization, and classification model refinement to enhance the accuracy of land use classification and enable detailed spatiotemporal analysis in the Ebinur Lake Basin. By integrating Landsat data with multi-temporal European Space Agency (ESA) products, we acquired 14,000 pixels of 2021 land use samples, with multi-temporal spectral features enabling robust sample transfer to 12028 pixels in 2011 and 10,997 pixels in 2001. Multi-temporal composite data were reorganized and reconstructed to form annual and monthly feature spaces that integrate spectral bands, indices, terrain, and texture information. Feature selection based on the Gini coefficient and Out-Of-Bag Error (OOBE) reduced the original 48 features to 23. In addition, an object-oriented Gradient Boosting Decision Tree (GBDT) model was employed to perform accurate land use classification. A systematic evaluation confirmed the effectiveness of the proposed framework, achieving an overall accuracy of 93.17% and a Kappa coefficient of 92.03%, while significantly reducing noise in the classification maps. Based on land use classification results from three different periods, the spatial distribution and pattern changes of major land use types in the region over the past two decades were investigated through analyses of ellipses, centroid shifts, area changes, and transition matrices. This automated framework effectively enhances automation, offering technical support for accurate large-area land use classification. Full article

This study explores the use of artificial intelligence (AI) in religious leadership in Germany, focusing on the interplay between technological innovation, theological principles, and human interaction. Drawing on qualitative methods, 23 Christian leaders and experts were interviewed to examine their perceptions, assessments, and potential applications of AI and related technologies in their work, alongside ethical and theological considerations. The findings reveal a prevailing ambivalence towards AI: while it is generally accepted as a tool for administrative tasks, its use in pastoral contexts encounters resistance due to ethical concerns and theological tensions. Despite predominantly neutral to positive attitudes, many leaders lack proactive engagement in exploring AI’s transformative potential—pointing to a marked lack of agency. Digital competence among leaders emerges as a significant factor influencing the openness to AI adoption. This study identifies key barriers to the integration of AI into religious practice and underscores the need for strategic education and planning. It advocates for a balanced approach to leveraging AI in ways that align with religious values while embracing innovation in a digitalizing society. Full article

This article proposes recognizing innovation as the European Union’s “fifth freedom”, alongside the free movement of goods, services, capital, and people, with the aim of embedding it into renewable energy legislation. Focusing on renewable energy storage—a critical but overlooked component of decarbonization—it identifies structural barriers in EU cleantech innovation, including regulatory fragmentation, slow financing, and weak industrial coordination. To address these, this article introduces the Risk–Resilience–Reward (RRR) framework, a strategic tool for more anticipatory policymaking. It outlines how the proposed Clean Energy Delivery Agency and Clean Energy Deployment Fund could operationalize the RRR framework to accelerate storage deployment and strengthen EU competitiveness. Embedding purpose-led principles in energy policy, this article positions storage as the “unsung hero of decarbonization” and offers takeaways for advancing a just, sustainable EU economy. Full article

Background: Locally acting gastrointestinal (GI) drugs present challenges for generic drug development because traditional bioequivalence measures, which rely on systemic drug levels, do not reflect local efficacy. This review examines regulatory guidelines for establishing therapeutic equivalence for such drugs, using rifaximin—a minimally absorbed, gut-localized antibiotic—as a case study. Methods: We reviewed bioequivalence guidelines from the United States Food and Drug Administration (FDA) and European Medicines Agency (EMA), along with the literature on rifaximin’s biopharmaceutical and clinical properties, to identify strategies and challenges for establishing equivalence for locally acting GI drugs. Results: Rifaximin exemplifies the limitations of standard bioequivalence methods: as a Biopharmaceutics Classification System (BCS) class IV drug with minimal absorption and low solubility, in vitro dissolution may not predict local drug availability. Clinical endpoint trials (e.g., traveler’s diarrhea, hepatic encephalopathy, IBS-D) are resource-intensive and insensitive to formulation differences. Pharmacokinetic (PK) studies in healthy volunteers show low, variable plasma levels, which may inaccurately discriminate between formulations. The EMA requires evidence of non-saturable absorption to accept PK data, a difficult-to-establish but potentially irrelevant criterion. Differences between FDA and EMA approaches highlight a lack of harmonization, complicating global generic development. Conclusions: A tailored, multifaceted approach is needed to demonstrate bioequivalence for GI-localized drugs like rifaximin. This case underscores the need for more sensitive surrogate methods (e.g. advanced in vitro or pharmacodynamic models) and flexible regulatory criteria. Harmonization across international guidelines and innovative bioequivalence study designs are key to facilitating the approval of safe and effective generic alternatives in this drug class. Full article