Search Results (5,995)

The rapid digitalization of cities is reshaping urban planning practices; however, significant gaps persist between technological investments and institutional governance capacity, particularly in transition economies. This study investigates how digital tools can be systematically embedded within planning processes to improve decision-making quality, coordination, and administrative efficiency. Drawing on urban governance theory and an empirical implementation study conducted in Yerevan, Armenia (population 1.1 million) between 2019 and 2023, the paper develops and operationalizes a multi-layer governance framework that aligns digital instruments—including geospatial information systems, performance dashboards, and decision-support platforms—with strategic, tactical, and operational levels of city management. The framework is evaluated through institutional analysis of municipal policy documents, planning databases, and semi-structured interviews with planning officials. The results reveal substantial governance barriers, including data fragmentation, organizational silos, and limited digital capacity. Framework-based implementation produced measurable improvements: planning decision cycles shortened by 43%, GIS utilization increased from 18% to 68% of eligible projects, inter-agency data sharing rose sixfold, and annual cost savings of approximately $1.2 million were achieved through reduced duplication and faster approvals. By combining conceptual design with empirical validation, the study advances digital urban governance research and offers a transferable, evidence-based model for implementing resilient and efficient data-driven planning systems in resource-constrained contexts. Full article

Community pharmacies in the United States (US) face an increasingly unsustainable future due to declining third-party reimbursement (remuneration) and ongoing cash flow challenges following the elimination of retroactive direct and indirect remuneration (DIR) fees. These pressures have contributed to widespread pharmacy closures, the emergence of pharmacy deserts, and reduced access to care for millions of patients. Despite these challenges, community pharmacy remains the most common employment setting for pharmacy school graduates in the US. However, currently required community pharmacy Advanced Pharmacy Practice Experience (APPE) student rotations may offer limited exposure to business, management, and entrepreneurial activities, potentially leaving students underprepared for practice in this setting. US colleges and schools of pharmacy are uniquely positioned to address this gap by partnering with their community pharmacy APPE rotation sites to intentionally integrate business- and practice-focused knowledge, skills, and attitudes (KSAs) into the APPE. Equipping students with these KSAs may enhance early career readiness while also supporting the financial sustainability of US community pharmacies through the development of innovative, revenue-generating services. These efforts further align with the 2025 Accreditation Council for Pharmacy Education (ACPE) Standards and may help advance the profession. Future research should examine optimal community pharmacy APPE structures, models, and assessment strategies to maximize student preparedness and long-term community pharmacy sustainability. Full article

In the 21st century, rapid urban development during global urbanization has led to high-density environments. These settings have become a significant cause of stress-related health problems for residents. Healing street design plays an important role in helping address mental health challenges caused by this process. Current research often focuses on healing elements and methods from only a single field. As a result, it lacks the integration of multidisciplinary and multi-stakeholder perspectives. To address this gap, this paper formed a Delphi expert panel with multidisciplinary scholars, urban managers, and practicing designers. The panel developed a quantitative evaluation model. This model covers four core dimensions: Safety (0.3210), Attractiveness (0.1080), Friendliness (0.2155), and Comfort (0.3553). It also includes eleven healing elements, such as Pedestrian Right-of-Way (0.4131), Night Lighting (0.3209), Visual Landscape (0.759), Street Furniture (0.4000), and Street Scale (0.3274). Using this model, the healing potential of Jingliu Road in Zhengzhou was assessed. The analysis identified the overall healing potential, core healing dimensions, and shortcomings of the street. This finding provides a clear direction for future healing-oriented street design. This paper builds a healing system for pedestrian spaces in high-density urban streets in China. It thus offers an evidence-based scientific tool for environmental design. Healing environments have expanded from less accessible spaces, such as squares and parks, to interactive and accessible streets. This transition enhances urban spaces’ capacity to address residents’ mental health concerns and promotes public health. Additionally, this paper offers specific recommendations for planners and policymakers to prioritize healing elements in urban renewal projects. Full article

The rapid increase in companion animal ownership has intensified the demand for innovative tools that support animal health and overall welfare. In recent years, artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has emerged as a promising approach in veterinary medicine. However, its application beyond clinical diagnostics, especially in behaviour and personality assessment, remains fragmented and insufficiently integrated into routine practice. This systematic review aims to synthesise current knowledge on AI-based applications in companion animal care, with a focus on behavioural monitoring, personality prediction, and welfare-related challenges. Following PRISMA guidelines, a structured literature search was conducted in the Scopus and PubMed databases from 2020 to 2025. In addition, grey literature sources were searched to capture relevant non-peer-reviewed data. A total of 115 studies met the inclusion criteria and were included in the analysis. Eligibility criteria included studies applying AI methods (machine learning or deep learning) to companion animals (dogs, cats, and exotic pets), while studies on humans, farm animals, or without AI methods were excluded. Due to the heterogeneity of included studies, no formal risk of bias assessment was performed, and results were synthesised narratively. The findings indicate that AI applications are most advanced in diagnostic imaging and clinical decision support, where data availability and methodological maturity are highest. In contrast, AI-based approaches for behaviour and personality prediction remain limited, particularly in cats and exotic companion animals, largely due to small, heterogeneous datasets, potential bias, and a lack of external validation. Emerging technologies such as wearable sensors, computer vision, and multimodal data integration demonstrate substantial potential for continuous behavioural monitoring and early detection of welfare-related issues in real household environments. Nevertheless, significant challenges persist, including data heterogeneity, limited model explainability, ethical considerations, and the absence of regulatory frameworks specifically addressing AI-based veterinary applications. Overall, this review highlights a substantial gap between the technical potential of AI and its current readiness for widespread application in companion animal behaviour and welfare assessment. Future research should prioritise large-scale and standardised data collection, cross-species validation, and interdisciplinary collaboration to ensure that AI-driven tools effectively support veterinary decision-making, animal welfare, and the well-being of owners. Full article

Initial teacher education is increasingly expected to prepare pre-service teachers for ongoing professional development and teacher research, yet it remains unclear how systematically these competences are embedded in programmes and how prepared pre-service teachers feel. We used a mixed-methods design, combining a content analysis of 47 teacher education programmes at the University of Ljubljana with two cross-sectional surveys involving 443 pre-service (303 enrolled in first-cycle programmes and 140 in second-cycle programmes) and 138 in-service teachers. Programme documents frequently referenced professional development and research; however, research was more often stated as a competence outcome than as an explicit programme goal. In the surveys, pre-service teachers rated teaching competences highly, whereas perceived current competence was lower for professional development and lowest for teacher research, particularly for active research engagement. Across all items, pre-service teachers reported substantial gaps between current and required competence. Perceived current competence increased with study stage, while required competence varied less by stage. Required competence ratings were largely aligned between pre-service and in-service teachers, although pre-service teachers assigned higher ratings to selected research engagement items. The findings indicate a misalignment between curricular emphasis and perceived preparedness, and support stronger integration of practice-embedded professional learning and inquiry across coursework. Full article

The rapid evolution of the Open Radio Access Network (O-RAN) architecture and the exponential growth in specification complexity create significant barriers for researchers translating 5G standards into practical implementations. Existing evaluation frameworks for large language models, such as ORAN-Bench-13K, focus predominantly on the theoretical comprehension of regulatory documents while neglecting the critical aspect of software execution. This disparity results in a profound semantic gap, defined here as the structural and conceptual misalignment between abstract normative requirements and their concrete realization in the source code of open platforms like srsRAN. To bridge this divide and enable advanced cognitive reasoning, this paper presents a Hybrid Retrieval-Augmented Generation (RAG) framework designed to unify two heterogeneous knowledge domains: the O-RAN/3GPP specification corpus and the srsRAN C++ codebase. The proposed architecture leverages a hierarchical Parent–Child Chunking strategy to preserve the structural integrity of complex code and normative protocols. Additionally, it introduces a probabilistic Semantic Query Routing mechanism that dynamically selects the relevant context domain based on query intent. This routing actively mitigates semantic interference—a phenomenon where merging conflicting cross-domain terminology introduces informational noise, which our baseline tests showed degrades response accuracy by 4.7%. Empirical evaluation demonstrates that the hybrid approach successfully overcomes this, achieving an overall accuracy of 76.70% and outperforming the standard RAG baseline of 72.00%. Furthermore, system performance analysis reveals that effective context filtering reduces the average response generation latency to 3.47 s, compared to 3.73 s for traditional RAG methods, rendering the framework highly suitable for real-time telecommunications engineering tasks. Full article

As the development of the ocean extends to the deep and open seas, the application of multi-hull floating systems is becoming increasingly widespread, covering offshore oil and gas transfer and material replenishment operations. In multi-body floating systems, the hydrodynamic interactions between adjacent floating bodies significantly affect the overall motion response and load distribution. However, there is currently a lack of systematic experimental research on systems involving three or more units under the combined action of wind, waves, and currents. This study presents a 1:50 scale model experiment on a five-body offshore replenishment station, comprising a central transfer platform and four surrounding vessels. Absolute six-degree-of-freedom motions and relative displacements between the transfer platform and neighboring vessels were measured. The results indicate distinct differences among the units. The peripheral vessels have greater horizontal and yaw motions, while the central units are more restricted. The relative motions are substantially increased for beam and oblique wave conditions, implying increased interaction effects in the gaps between neighboring bodies. Moreover, the combined oblique environmental loading and asymmetric mooring stiffness result in increased global drift and yaw motions. These findings provide benchmark data for numerical validation and practical guidance for the design and operation of multi-body floating systems. Full article

Objective: The objective of this study was to map and critically synthesize empirical evidence on ML/AI applications across surface mining unit operations, and to characterize models, validation practices, and evidence gaps. Eligibility criteria: Our eligibility criteria comprised peer-reviewed studies (2020–2025) applying ML/AI to surface mining activities, training/validating models on empirical datasets, and reporting quantitative performance metrics. Information sources: Scopus, ScienceDirect, Dimensions, and Web of Science were our information sources, last searched December 2025 and supplemented by website and citation snowballing. Risk of bias: Risk of bias was assessed using an adapted domain-based approach based on PROBAST, used to interpret findings without excluding studies. Synthesis method: Our research employed a narrative synthesis (no meta-analysis due to heterogeneity in datasets, algorithms, contexts, and metrics), grouped by application domain. Results: From 5317 records, 57 studies were included, concentrated in blasting (43), followed by load and haul (6), post-dismantling management (4), extraction (2), and overall exploitation (2). Studies predominantly reported statistical metrics (e.g., R², RMSE, and MAE), with limited operational performance indicators; validation was frequently site-specific. Dataset sizes were not reported consistently across studies. Limitations: This study’s limitations were database coverage, restricted timeframe, and incomplete reporting (e.g., software/tooling). Conclusions: ML/AI shows strong potential, especially in blasting, but scalable deployment is constrained by site specificity, inconsistent reporting, and heterogeneous validation; standardized reporting and operational indicators are priorities. Registration: The systematic review protocol was registered in OSF with DOI 10.17605/OSF.IO/5UMKB. Funding: EU Erasmus+ STRIM project (1010832727). Full article

Consumer food waste is a major global challenge to sustainable development, generating massive carbon and water footprints, exacerbating food insecurity, and undermining the United Nations Sustainable Development Goals. While extensive research has documented individual and contextual drivers of consumer food waste, critical gaps remain in understanding how core marketing tools shape wasteful behavior, particularly the unintended post-purchase consequences of ubiquitous price promotions. Addressing this gap, we unpack the psychological mechanism underlying the classic social dilemma of promotions: short-term individual economic savings from discounts conflict with long-term collective ecological welfare. Across four rigorous studies, including a real-world field experiment in a university canteen, we establish a causal effect of price promotions on increased consumer food waste behavior. We further demonstrate that this effect is mediated by enhanced perceived resources: price promotions generate subjective feelings of windfall gains and resource abundance, which in turn increase consumers’ willingness to discard edible food. We identify two practical actionable boundary conditions that attenuate this pro-waste effect: the impact of price promotions on food waste is eliminated when consumers focus on money spent (rather than money saved) from the transaction, and when they perceive their spending as exceeding their psychological budget. Our findings advance the literature on price promotions and sustainable consumption by documenting a previously unrecognized hidden cost of promotional marketing, unpacking the micro-psychological foundations of the social dilemma in food waste decisions, and providing evidence-based, actionable implications for policymakers, food retailers, and food service operators to curb promotion-induced food waste. Full article

Mountain Social–Ecological Systems (MtSES) are global assets, providing essential ecosystem services to nearly half of humanity, yet they are disproportionately vulnerable to global change, experiencing “polytraps” of depopulation, poverty, and environmental degradation. Despite the inherent human dimension in sustainability, the social pillar remains conceptually chaotic, forming a highly fragmented “publication labyrinth”, and is often neglected in favor of more easily quantifiable environmental and economic metrics. These oversights leave mountain communities in a precarious state, underscoring an urgent need for robust, context-specific assessment tools. This paper addresses this critical gap by employing a two-step methodology: first, a literature review identifies prevailing social sustainability issues in mountain contexts; second, a comparative analysis evaluates prominent frameworks and indicator-based tools against these themes, using Ostrom’s multi-tier Social–Ecological Systems (SES) framework as the theoretical lens. Our findings reveal a persistent environmental bias in MtSES research and highlight the necessity for frameworks that integrate local knowledge, address power imbalances, and support bottom-up governance. A tool is proposed with indicators specifically for mountainous contexts. This study contributes to theory by offering a structured approach to unpack the elusive “social” in SES and to practice by providing a model and tool for developing actionable, context-sensitive social sustainability assessments, thereby fostering resilience and equitable development in vulnerable mountain regions. Ultimately, by operationalizing these social dimensions, this research provides a direct roadmap for achieving key United Nations Sustainable Development Goals in marginalized high-altitude contexts, particularly focusing on No Poverty (SDG 1), Good Health and Well-being (SDG 3), Reduced Inequalities (SDG 10), Sustainable Communities (SDG 11), and Peace, Justice, and Strong Institutions (SDG 16). Full article

Background: Artificial intelligence (AI) is poised to fundamentally reshape healthcare delivery, offering unprecedented advancements in diagnostics, treatment personalization, and operational efficiency. However, a growing body of international research reveals a critical “optimism–knowledge gap”: healthcare professionals are enthusiastic about AI’s potential but possess limited technical knowledge and practical experience. This gap compromises the safe and effective implementation of AI tools. The Italian healthcare context presents a unique and amplifying challenge, as it is defined by the stringent “human-in-the-loop” oversight mandated by the Garante per la protezione dei dati personali (Italy’s Data Protection Authority). This legal framework makes clinician competence not just a goal, but a prerequisite for regulatory compliance. Objective: This study aimed to provide an exploratory quantitative assessment of AI awareness, practical application, and understanding of its limitations among a sample of clinicians in Italy. It specifically sought to compare the preparedness of hospital-based clinicians and general practitioners (GPs) and to identify the workforce’s perceived educational needs within this unique legal environment. Methods: A descriptive, cross-sectional survey was conducted from February to August 2025. Using a non-probability convenience sampling method via professional networks, the survey yielded 362 total responses. Data were analyzed descriptively and inferentially using Chi-square (${\chi }^2$) tests to compare cohort responses on familiarity, practical exposure, knowledge of limitations, and interest in further training. Results: A universal and high demand for education was found, with 89.9% of all respondents being “Moderately” or “Very” interested in learning more about AI. This optimism coexists with dangerously low practical exposure. The gap was most profound among GPs, 44.1% of whom have “Never” used an AI tool—a rate significantly higher than hospital clinicians (34.9%; ${\chi }^2=3.14$, p = 0.045). Furthermore, 32.6% of GPs admitted that they “understand some benefits but not the limitations.” Conclusions: Italian clinicians mirror the global optimism–knowledge gap. These findings underscore the urgent need for structured, continuous education in AI literacy to address ethical and regulatory imperatives within the Italian healthcare system. Full article

Objective: Nutrition is a key determinant of women’s health across all life stages. Clinical practice remains heterogeneous because of lack of evidence and non-homogeneous guidelines. Despite growing research on micronutrient supplementation, skeptical opinions persist around universal versus individualized approaches, optimal dosages, and life-stage-specific recommendations. Material and methods: This is a modified Delphi process conducted under the supervision of the Italian Association of University Gynecologists and Obstetricians (AGUI). Thirteen Italian experts in gynecology and obstetrics completed two rounds of anonymous online surveys (September–November 2025). The questionnaire, developed through a scoping review, covered six domains: pre-/periconception, pregnancy, postpartum, routine supplementation in non-pregnant women, nutrition in gynecological conditions, and menopause. Consensus was defined as ≥75% agreement on a 10-point Likert scale. Quantitative data were summarized descriptively, and qualitative comments contextualized findings. Results: Experts strongly supported personalized nutritional strategies across all life stages. Consensus was reached on individualized micronutrient supplementation in the preconception period and on the prescription of active folates for women undergoing assisted reproduction. In pregnancy, agreement emerged for universal DHA supplementation (200–300 mg/day); however, universal vitamin D supplementation lacked consensus except in gestational diabetes. In the postpartum period, iron supplementation for non-breastfeeding women reached consensus, while micronutrient recommendations for breastfeeding women remained uncertain. Strong agreement supported personalized dietary approaches for PCOS, endometriosis, and gestational diabetes, including inositol use, while evidence for interventions in severe premenstrual syndrome remained insufficiently supported. In menopause, consensus was reached for macronutrient adjustments and universal calcium and vitamin D supplementation. Conclusions: This Delphi consensus highlights shared expert perspectives on nutritional care in women and identifies key evidence gaps, particularly regarding vitamin D in physiological pregnancy, postpartum micronutrient needs during breastfeeding, and nutritional strategies for premenstrual disorders. Unified life-course guidelines and future research on standardized nutritional assessments are necessary for nutritional approach management. Full article

Edible coatings (ECs) derived from natural biopolymers represent an effective preservation strategy for fruits and vegetables and a promising postharvest approach aligned with the increasing demand for sustainable agricultural practices. These Generally Recognized As Safe (GRAS)-based coatings, which are mainly polysaccharide-, protein-, and lipid-based, can extend shelf-life with minimal impact on texture, flavor, and nutritional value, reducing reliance on synthetic packaging and helping mitigate food loss and waste. Beyond acting as a physical barrier, ECs can significantly influence fruit and vegetable metabolism by modulating biochemical and molecular processes. This review focuses on these effects by summarizing evidence from conventional analytical methods, including targeted metabolite analyses, as well as omics-based approaches, primarily transcriptomics and metabolomics, which remain poorly explored in the current EC research literature. Furthermore, integrated metabolomic and transcriptomic analyses are examined, as they offer a more comprehensive understanding of the molecular mechanisms underlying quality attributes, stress responses, and preservation outcomes. Collectively, this work offers detailed insights into coating-induced changes in metabolite profiles and gene expression in coated fruits and vegetables, including formulations derived from agri-food by-products and coatings enriched with bioactive compounds with antioxidant, antimicrobial, and antifungal properties. Overall, by addressing a current gap in the literature, it provides an integrative and innovative framework for interpreting coating performance at both applied and molecular levels, with potential relevance for the agri-food industry and for future research aimed at developing more sustainable, effective, and commodity-tailored postharvest technologies. Full article

In the digital economy era, digital marketing has become a key strategy for firms seeking competitive advantage. However, its reliance on data has heightened exposure to cybersecurity risks. While existing research highlights the importance of digital transformation, less is known about how cybersecurity governance influences firms’ digital marketing activities. Drawing on signalling theory and the resource-based view, this study uses panel data from Chinese A-share listed firms during 2012–2023 to examine the impact of cybersecurity governance on digital marketing and its underlying mechanisms. The results show that effective cybersecurity governance significantly enhances firms’ digital marketing engagement. Mechanism analyses identify three channels. First, by preventing data breaches and negative incidents, firms enhance corporate reputation. Second, by creating a secure operating environment, cybersecurity governance strengthens risk-taking capacity and encourages marketing innovation. Third, by improving information disclosure and stakeholder communication, it alleviates information asymmetry. Heterogeneity analyses indicate that the positive effect is more pronounced for non-state-owned enterprises, firms in eastern regions, and high-tech firms. This study fills a gap in the literature by linking cybersecurity governance path to digital marketing and contributes to research on its economic consequences. The findings also offer practical implications for strengthening internal governance to support external market activities. Full article

Sn-based perovskites offer lower lead content but face a major challenge: Sn²⁺ oxidizes readily, which has led most research groups to use gloveboxes and chemical additives during processing. Here, we investigate whether precursor molarity alone can mitigate this oxidation problem in ambient air. MAPb_0.75Sn_0.25I₃ solar cells with mesoporous N–i–P architecture were prepared from 1.0 M and 0.9 M solutions by spin-coating with ethyl acetate antisolvent, under standard lab conditions (28–34 °C, 30–45% RH). The characterization included SEM, XRD, XPS, profilometry, and J–V measurements. The 0.9 M concentration produced thinner films (275 nm vs. 474 nm), better Sn²⁺/Sn⁴⁺ ratios (16.5%/83.5% vs. 77.6%/22.4% by XPS), lower band gaps (1.51–1.52 vs. 1.55–1.56 eV), and larger grains. Device efficiency increased from 1.61 ± 0.68% (1.0 M) to 4.53 ± 0.91% (0.9 M), with the best cell reaching 5.91%—about 85% of our MAPbI₃ control (6.96%). After one month of storage, 0.9 M cells retained 61% efficiency compared to 37% for 1.0 M devices. These findings demonstrate that a simple reduction in precursor molarity can substantially suppress Sn⁴⁺ formation during ambient fabrication, providing a practical route for laboratories without controlled atmospheres. Full article