Search Results (1,941)

As municipalities increasingly adopt artificial intelligence (AI) and generative AI (GenAI) to automate self-service technologies (SSTs), concerns related to fairness, transparency, accountability, and citizen trust have become central to sustainable public-sector governance. While existing studies emphasize either AI adoption or high-level ethical principles, limited empirical research explains how governance mechanisms translate into user-level outcomes in municipal services, particularly in the context of emerging GenAI capabilities. This study addresses this gap by examining how governance antecedents and system design attributes shape user satisfaction, trust, and perceived fairness in AI-enabled municipal SSTs in the United Arab Emirates (UAE). A mixed-methods research design was employed, combining a comparative analysis of international and UAE AI governance frameworks with semi-structured interviews (n = 16) and a survey of municipal employees and service users (n = 272). Qualitative findings reveal persistent concerns regarding data privacy, fairness, explainability, and the absence of standardized municipal-level accountability instruments. Quantitative analysis shows that perceived helpfulness significantly increases user satisfaction, while perceived fairness strongly predicts continued usage intentions. In contrast, system responsiveness exhibits a negative association with satisfaction, highlighting an expectation–performance gap in automated service delivery. Based on these findings, the study proposes a governance–implementation–outcomes model that operationalizes ethical AI principles into measurable governance and service-design mechanisms. Unlike prior adoption-focused or purely normative frameworks, this model empirically links governance instrumentation to citizen-centered outcomes, offering practical guidance for inclusive and sustainable AI and GenAI deployment in municipal self-service systems. The findings contribute to debates on sustainable digital governance by demonstrating how ethically governed AI systems can reinforce public trust, service equity, and long-term institutional resilience. Full article

The discovery and development of new drugs is a lengthy, complex, and costly process, often requiring 10–20 years to progress from initial concept to market approval, with clinical trials representing the most resource-intensive stage. In recent years, Artificial Intelligence (AI) has emerged as a transformative technology capable of reshaping the entire pharmaceutical research and development (R&D) pipeline. The purpose of this narrative review is to examine the role of AI in drug discovery and development, highlighting its contributions, challenges, and future implications for pharmaceutical sciences and global public health. A comprehensive review of the scientific literature was conducted, focusing on published studies, reviews, and reports addressing the application of AI across the stages of drug discovery, preclinical development, clinical trials, and post-marketing surveillance. Key themes were identified, including AI-driven target identification, molecular screening, de novo drug design, predictive toxicity modelling, and clinical monitoring. The reviewed evidence indicates that AI has significantly accelerated drug discovery and development by reducing timeframes, costs, and failure rates. AI-based approaches have enhanced the efficiency of target identification, optimized lead compound selection, improved safety predictions, and supported adaptive clinical trial designs. Collectively, these advances position AI as a catalyst for innovation, particularly in promoting accessible, efficient, and sustainable healthcare solutions. However, substantial challenges remain, including reliance on high-quality and representative biomedical data, limited algorithmic transparency, high implementation costs, regulatory uncertainty, and ethical and legal concerns related to data privacy, bias, and equitable access. In conclusion, AI represents a paradigm shift in pharmaceutical research and drug development, offering unprecedented opportunities to improve efficiency and innovation. Addressing its technical, ethical, and regulatory limitations will be essential to fully realize its potential as a sustainable and globally impactful tool for therapeutic innovation. Full article

The broader aim of this research is to examine how Learning Analytics (LA) can become ethically sound, pedagogically actionable, and realistically adopted in educational practice. To address this overarching challenge, the study investigates three interrelated research questions: ethics by design, learning impact, and adoption conditions. Methodologically, the research follows an exploratory sequential multi-method design. First, a meta-synthesis of 53 studies is conducted to identify key ethical challenges in LA and to derive an ethics-by-design framework. Second, a quasi-experimental study examines the impact of interface-based LA guidance (strong versus minimal) on students’ self-regulated learning skills and academic performance. Third, a mixed-methods adoption study, combining surveys, focus groups, and ethnographic observations, investigates the factors that encourage or hinder teachers’ adoption of LA in K–12 education. The findings indicate that strong LA-based guidance leads to statistically significant improvements in students’ self-regulated learning skills and academic performance compared to minimal guidance. Furthermore, the adoption analysis reveals that performance expectancy, social influence, human-centred design, and positive emotions facilitate LA adoption, whereas effort expectancy, limited facilitating conditions, ethical concerns, and cultural resistance inhibit it. Overall, the study demonstrates that ethics by design, effective pedagogical guidance, and adoption conditions are mutually reinforcing dimensions. It argues that LA can support intelligent, responsive, and human-centred learning environments when ethical safeguards, instructional design, and stakeholder involvement are systematically aligned. Full article

Growing interest in food sustainability education aims to increase awareness of food distribution systems, environmental degradation, and the connectivity of sustainable and ethical food practices. However, recent scholarship has questioned whether such pedagogical efforts are meaningfully internalized by students or lead to sustained behavioral change. Prior studies document persistent gaps in students’ understanding of sustainability impacts and the limited effectiveness of existing instructional approaches in promoting transformative engagement. To address these concerns, the Food Ethics, Sustainability and Alternatives (FESA) course was implemented with 21 undergraduate and graduate students at Montclair State University (Montclair, NJ, USA). Course outcomes were evaluated using a mixed-methods design integrating qualitative analysis with quantitative measures informed by the Theory of Planned Behavior, to identify influences on students’ attitudes, and a Transtheoretical Model (TTM) panel survey to address progression from awareness to action, administered pre- and post-semester. Qualitative findings revealed five central themes: increased self-awareness of food system contexts, heightened attention to animal ethics, the importance of structured classroom dialogue, greater recognition of food waste, and increased openness to alternative food sources. TTM results indicated significant reductions in contemplation and preparation stages, suggesting greater readiness for change, though no significant gains were observed in action or maintenance scores. Overall, the findings suggest that while food sustainability education can positively shape student attitudes, the conversion of attitudinal shifts into sustained behavioral change remains limited by external constraints, including time pressures, economic factors, culturally embedded dietary practices, structural tensions within contemporary food systems, and perceptions of limited individual efficacy. Full article

Chimeric antigen receptor (CAR)-T-cell therapy is a revolutionary approach in immunotherapy that has shown remarkable success in the treatment of blood cancers. Many preclinical studies are currently underway worldwide to extend the CAR-T-cell therapy benefits to a broad spectrum of cancers, using rodent models. Alternative in vivo platforms are essential for overcoming the drawbacks associated with rodent models, including immunodeficiency in humanized models, ethical concerns, extended time requirements, and cost. In this work, we used the chicken chorioallantoic membrane (CAM) assay to evaluate the in vivo efficacy of cluster-of-differentiation 19 (CD19)-targeting CAR-T cells expressing a second-generation CAR construct against human lymphoma derived from the Raji cell line. Our results confirm the efficacy of selected CAR-T cells on tumor growth, metastasis, and angiogenesis. Further, the chicken embryo has an intrinsic active immune system. Therefore, the dialog between CAR-T cells and endogenous immune cells, as well as their participation in the tumor challenge, has also been studied. In conclusion, our study demonstrates that the chicken CAM assay provides a relevant in vivo, 3Rs (Replacement, Reduction and Refinement)-compliant new approach methodology (NAM), which is well-suited for the current needs of preclinical research on CAR-T-cell therapy. Full article

The limitations of conventional diabetes management are increasingly evident. As a result, both type 1 and 2 diabetes in pediatric populations have become major global health concerns. As new technologies emerge, particularly artificial intelligence (AI), they offer new opportunities to improve diagnostic accuracy, treatment outcomes, and patient self-management. A PRISMA-based systematic review was conducted using PubMed, Web of Science, and BIREME. The research covered studies published up to February 2025, where twenty-two studies met the inclusion criteria. These studies examined machine learning algorithms, continuous glucose monitoring (CGM), closed-loop insulin delivery systems, telemedicine platforms, and digital educational interventions. AI-driven interventions were consistently associated with reductions in HbA1c and extended time in range. Furthermore, they reported earlier detection of complications, personalized insulin dosing, and greater patient autonomy. Predictive models, including digital twins and self-learning neural networks, significantly improved diagnostic accuracy and early risk stratification. Digital health platforms enhanced treatment adherence. Nonetheless, the barriers included unequal access to technology and limited long-term clinical validation. Artificial intelligence is progressively reshaping pediatric diabetes care toward a predictive, preventive, personalized, and participatory paradigm. Broader implementation will require rigorous multiethnic validation and robust ethical frameworks to ensure equitable deployment. Full article

Higher education continues to encounter the challenge of redesigning writing pedagogy beyond the rapid adoption of emerging technologies. This challenge is particularly evident in English writing courses, which play a role in developing students’ writing and research skills in universities across the United Arab Emirates (UAE). While generative artificial intelligence (GenAI) tools offer practical affordances for writing instruction, their growing use has also raised concerns about academic integrity, authenticity, and critical engagement. Although early discourse has focused on the risks and potential of GenAI, there remains a clear dearth of frameworks to guide instructors in designing meaningful and engaging writing assignments. This paper introduces Ai-RACE, an adaptable pedagogical framework for designing purposeful and innovative writing tasks. Grounded in classroom-based insights, principles of writing pedagogy, constructivist and multimodal learning theories, Ai-RACE conceptualises assignment design around five interconnected components: AI integration, Relevance, Authenticity, the 4Cs, and Engagement. Employing a design-focused qualitative approach, the study uses instructional practices and student reflections to examine the implementation of Ai-RACE in writing contexts. Although situated within a specific institutional context, the study offers transferable guidelines for designing writing assignments across international higher education settings. By positioning Ai-RACE as a design heuristic, the study demonstrates its potential in supporting engagement, critical thinking, writing skills and ethical use of AI, and highlights the importance of rethinking writing pedagogy and the professional development in AI- influenced contexts. Full article

This article presents a conceptual framework linking responsible leadership competencies to organizational processes relevant for sustainability transformation. A leader’s personal impact is conceptualized as indirect through organizational governance, prioritization, collaboration, and innovation. The article provides a conceptual mapping approach that systematically connects individual leadership competencies with strategic organizational impact areas. The framework builds on the Competency Assessment for Responsible Leadership (CARL) and the Positive Impact Organization (PIO) concept to relate leadership capabilities to organizational transformation requirements. Five responsible leadership competencies—ethics and values, self-awareness, stakeholder relations, change and innovation, and systems thinking—are mapped to five organizational impact areas: governance alignment, sustainability culture, external stakeholder validation, purpose-driven product and service innovation, and transformative sustainability. The article identifies how specific leadership competencies align with distinct organizational leverage points, clarifying the mechanisms through which leaders shape structures, decision processes, cultural norms, and innovation pathways associated with sustainability transformation. By specifying these relationships, the framework distinguishes leadership impact at the organizational level and provides a structured basis for analyzing how leadership competencies contribute to an organization’s capacity for societal and environmental contribution. The framework is applicable to research on responsible leadership and business sustainability and informs leadership development and management education concerned with sustainability-oriented organizational change. Full article

Every act of design tells a story about who belongs, who is seen, and who is heard. This paper looks at how participatory design-based research (PDR), practiced with relational care and reflexivity, can help shift interactions among marginalized youth from urban Indigenous and newcomer immigrant communities in Canada from othering toward understanding. Moving beyond surface-level celebrations of multiculturalism, the study frames design as a relational and ethical practice, one that surfaces assumptions, holds space for difference, and creates openings for intercultural dialogue. The study draws on a series of design circles (d.circles) in which youth co-created visual communication artefacts reflecting their lived experiences. These artefacts became catalysts for dialogue, enabling participants to challenge stereotypes, articulate concerns, and develop shared perspectives. Reflexivity was integral to the process, guiding both participants and the facilitator to consider power, positionality, and relational accountability throughout. Findings show that participatory design, grounded in Indigenous relational principles and participatory action research, can unsettle dominant narratives, foster mutual recognition, and support youth-led meaning-making. This work contributes to emerging conversations that position design thinking as a practice of ethical engagement rather than a tool for problem-solving alone. The learnings from this study show how critically practiced PDR can cultivate more inclusive and socially responsive pathways for intercultural understanding to take shape. Full article

Background/Objectives: Neonatal Intensive Care Units (NICUs) constitute a highly complex clinical environment characterized by patient fragility and frequent ethically sensitive decisions. To date, systematic studies investigating how Italian NICUs address these challenges and what forms of ethics support are effectively available are lacking. The aim of this study is therefore to assess how ethical issues are managed in Italian NICUs, with particular attention to the availability, use, and perceived usefulness of clinical ethics support in everyday practice. Methods: A 25-item questionnaire was developed by adapting an existing tool for investigating clinical ethics activities to the neonatal context. Following expert review by the GIBCE (Gruppo Interdisciplinare di Bioetica Clinica e Consulenza Etica in ambito sanitario), the final instrument covered four areas (general data, experience with ethical dilemmas, tools and procedures, opinions and training needs). A manual web search identified all Italian NICUs and their clinical directors, who were asked to disseminate the survey among staff. Participation was voluntary and anonymous. Data collection was conducted via Google Forms and analyzed through qualitative thematic analysis. Results: A total of 217 questionnaires were collected. The most frequent ethical dilemmas concern quality of life with anticipated multiple or severe disabilities (72.4%) and decisions to withdraw or withhold life-sustaining treatments (64.5%). Major challenges include fear of medico-legal repercussions (57.6%) and communication divergences between physicians and nurses (49.8%). More than half of respondents (52.1%) reported no formal training in clinical ethics, and 68.7% had never developed a Shared Care Plan (Shared Document for healthcare ethics planning) as defined by the Italian Law 219/2017. Conclusions: Findings highlight marked fragmentation in ethical practices across Italian NICUs. On this basis, establishing structured and accessible CEC services could help promote consistency, reinforce shared ethical standards, and support transparent and equitable decision-making in critical neonatal care. Full article

Objective—Partial do-not-resuscitate (DNR) orders, directives specifying limited resuscitative efforts, are intended to align medical interventions with patient preferences. However, their complexity may introduce ambiguity, inconsistent care, and ethical challenges. Design—A retrospective review was conducted of inpatient partial code order entries over a three-year period at a single institution with a pediatric oncology and immunology cohort. Partial DNR orders were identified and categorized based on included or excluded interventions (chest compressions, defibrillation, intubation, mechanical ventilation, medications). Data was analyzed to assess the frequency, variation, and internal consistency of documented preferences as well as alignment with institutional definitions and clinical feasibility. Results—Partial DNR orders represented a small (n = 15, 7%) but notable proportion of total code status entries. Wide variability was observed in the combinations of permitted and withheld interventions, with orders containing internally conflicting instructions. Documentation of inconsistencies and unclear terminology were common, raising concerns about interpretability during emergent situations. Conclusions—Partial DNR orders demonstrate heterogeneity and potential for miscommunication. These findings suggest that while partial codes may reflect nuanced patient preferences, they pose operational and ethical risks that could compromise care clarity. Clinical implications are reviewed. These findings will guide institutional deliberations regarding whether to refine, restrict, or eliminate partial code order options to enhance patient safety and decision-making transparency. Full article

Blue economy aims to bring prosperity to coastal communities whilst also protecting natural ocean resources for future generations. But how can this vision be put into practice, especially in communities in which dependence on natural resources is high, and food and livelihood security are key concerns? This paper examines two cases of community-led nature-based enterprise in Kenya in a search for solutions to this challenge: fisheries reform through market access and gear sustainability; mangrove forest conservation and community development using carbon credit revenues. I use a ‘diverse economies framework’ for the first time in blue economy contexts to delve into the heterogeneous relations at work and in search of insights that can be applied in multiple contexts. Analysed through key informant interviews and field observation, the cases reveal a complex assemblage of institutions, knowledges, technologies, and practices within which enterprises operate. Whilst the enterprises featured are still relatively new and developing, they suggest a direction of travel for a community-led sustainable blue economy that both supports and benefits from nature recovery. The insights gained from this diverse economies analysis lead us to appreciate a sustainable blue economy as a rediscovered and reinvigorated relationship of reciprocity between society and nature—one that nurtures place-based nature-based livelihoods and nature recovery together, and which embodies a set of values and ethics shared by government, communities, and business. Full article

This paper is concerned with the sexual rights of homeless adolescents. After a brief presentation of the ethical foundation of these rights in the capabilities approach and noting the relevance of the concept of relational autonomy, an ethical analysis of a specific problem is performed, namely the risky sexual behavior of homeless adolescents. It is argued that although these young people have moral agency it is not fully developed and thus they cannot be held to the same standards of responsibility as are adults. Thus, we can see the importance of interventions that empower homeless youth to protect their own sexual health through risk-avoidance or harm reduction strategies. Full article

Industry 5.0 challenges higher education to adopt human-centred and sustainable uses of artificial intelligence, yet many current deployments still treat generative AI as a stand-alone tool, neurophysiological sensing as largely laboratory-bound, and governance as an external add-on rather than a design constraint. This article introduces Nested Learning as a neuro-adaptive ecosystem design in which generative-AI agents, IoT infrastructures and multimodal deep learning orchestrate instructional support while preserving student agency and a “pedagogy of hope”. We report an exploratory two-phase mixed-methods study as an initial empirical illustration. First, a neuro-experimental calibration with 18 undergraduate students used mobile EEG while they interacted with ChatGPT in problem-solving tasks structured as challenge–support–reflection micro-cycles. Second, a field implementation at a university in Madrid involved 380 participants (300 students and 80 lecturers), embedding the Nested Learning ecosystem into regular courses. Data sources included EEG (P300) signals, interaction logs, self-report measures of engagement, self-regulated learning and cognitive safety (with strong internal consistency; $\alpha /\omega \ge 0.82$), and open-ended responses capturing emotional experience and ethical concerns. In Phase 1, P300 dynamics aligned with key instructional micro-events, providing feasibility evidence that low-cost neuro-adaptive pipelines can be sensitive to pedagogical flow in ecologically relevant tasks. In Phase 2, participants reported high levels of perceived nested support and cognitive safety, and observed associations between perceived Nested Learning, perceived neuro-adaptive adjustments, engagement and self-regulation were moderate to strong ($r=0.41$–$0.63$, $p<0.001$). Qualitative data converged on themes of clarity, adaptive support and non-punitive error culture, alongside recurring concerns about privacy and cognitive sovereignty. We argue that, under robust ethical, data-protection and sustainability-by-design constraints, Nested Learning can strengthen academic resilience, learner autonomy and human-centred uses of AI in higher education. Full article

The role of cardiac implantable electronic devices (CIEDs), including implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy (CRT) devices, in patients supported with left ventricular assist devices (LVADs) remains controversial. Although ICDs clearly reduce the risk of sudden cardiac death (SCD) and improve outcomes in advanced heart failure (HF), their benefit in patients with continuous-flow mechanical circulatory support is less certain. Initial small studies involving LVAD patients, particularly those with older pulsatile devices, suggested that ICDs confer a survival benefit during LVAD support. However, more recent evidence has been inconsistent. Some studies show modest protection against arrhythmic death, whereas others show no improvement in overall mortality. Similarly, CRT does not appear to offer significant additional hemodynamic benefits after LVAD implantation, and current evidence does not strongly support its routine continuation. Device-related complications—including lead failure, infection, electromagnetic interference, and inappropriate shocks—are major clinical concerns that can offset potential benefits. Accordingly, current guidelines recommend maintaining pre-existing ICD or CRT devices in LVAD patients but do not endorse the routine implantation of new devices after LVAD placement. The existing evidence highlights the need for a nuanced and individualized approach to CIED therapy in patients with LVAD. Future research should focus on randomized trials, registry-based analyses, and the exploration of novel technologies such as leadless pacing, subcutaneous ICDs, and advanced programming algorithms. Patient-centered outcomes, particularly quality of life and ethical considerations—such as ICD deactivation in end-of-life scenarios—must be considered in decision-making in this evolving field. Full article