Search Results (704)

Proximity-based urban models, including the widely discussed 15 min city, aim to bring everyday destinations within a short walk, cycle, or shared-mobility trip, with promising benefits for well-being, public health, local economies, and low-carbon mobility. While the appeal of proximity is widely shared, far less is known about how to deliver and govern such neighbourhoods so that these benefits are realised, durable, and embraced by residents across the full range of their mobility needs. Implementation, public acceptance, and governance therefore remain comparatively under-examined. This article contributes an enabling governance approach for proximity-based, accessible neighbourhoods, centred on co-creation and on a rich, attractive menu of mobility options. Through a cross-disciplinary synthesis organised by the CalmMobility paradigm, a governance-posture lens that emphasises co-creation, sequencing, and readiness, it integrates evidence on proximity, accessibility, active travel, shared mobility, well-being, and low-carbon outcomes. The article argues that proximity and shared mobility widen the range of convenient and attractive options for everyday trips, and that this supports health, quality of life, and lower emissions. It also argues that these benefits are more likely to last under calm, co-created governance, which builds good options first and respects the freedom of residents to choose among all modes, including the car. To put the paradigm to work, the study introduces the Governance Compass and applies it to Paris, Barcelona, and Melbourne. The Compass was applied through a qualitative document analysis carried out by one analyst. It is offered as an exploratory tool that aims to make the reasoning open to inspection, not as a validated measuring instrument. Results are reported as ordinal bands, from Absent to Exemplary, and a 0 to 100 index is kept only as an illustration. The three cases show different patterns. In Paris and in the early Barcelona work, the documents set ambitious proximity goals but say much less about how change is paced, how residents shape it, and how choice is preserved, and these dimensions fall in the lower bands. In Melbourne, whose programme is still a pilot, the pattern is the reverse. The process dimensions are stronger there, but proximity itself is less developed. These bands describe the documents examined, not a fixed ranking of the three cities. Positioned as a constructive complement to the proximity-city agenda rather than a critique of it, the article closes with a cross-disciplinary research agenda spanning planning, transport, public health, and policy. Full article

Smart cities have emerged as a strategic approach to enhancing urban sustainability through the integration of digital technologies, intelligent infrastructure, and data-driven governance. However, limited research has comprehensively examined how technological, institutional, governance, and contextual factors interact to influence sustainability outcomes in industrial-city settings, particularly in Saudi Arabia. This study develops an integrated conceptual framework for sustainable smart industrial cities through a qualitative research design based on a systematic screening and synthesis of the literature, complemented by a contextual analysis of the Dammam Metropolitan Area (DMA) as an illustrative urban-industrial case under Saudi Vision 2030. A total of 86 articles, reports, and website materials were identified and screened, of which 49 sources met the inclusion criteria and were synthesized to develop the proposed framework. The analysis examined five interrelated components: smart-city applications, institutional governance, implementation conditions, contextual barriers and opportunities, and sustainability outcomes across three dimensions: environmental, social, and economic. The findings suggest that the effectiveness of smart-city applications depends not only on technological innovation but also on institutional governance, digital readiness, stakeholder participation, integrated planning, and supportive regulatory environments. The study further identifies fragmented governance, limited institutional coordination, cybersecurity risks, and high infrastructure costs as key implementation barriers, while highlighting opportunities associated with Saudi Vision 2030, digital-transformation initiatives, and circular-economy principles. The principal contribution of the study is the development of an integrated conceptual framework that explains the interactions among these five components and provides a theoretical foundation for future empirical validation, as well as conceptually informed guidance for policy development and planning in Saudi Arabia and comparable industrial-city contexts. Full article

Background/Objectives: Artificial intelligence (AI), including large language models, chatbots, machine-learning systems, and hybrid tools, is increasingly used to support patient-facing eye-care communication. This systematic review evaluated the accuracy and effectiveness of AI-powered systems used for patient counseling, education, communication, referral/follow-up, and management support in optometry and related eye-care settings. Methods: A systematic review was conducted according to a predefined protocol and PRISMA 2020 reporting principles. Searches covered studies published from January 2020 to 31 May 2026 in PubMed, Embase, Web of Science, Cochrane Library, and IEEE Xplore. Eligible studies were original primary studies evaluating AI-supported tools for patient-facing counseling, education, question answering, treatment or medication guidance, triage, referral, follow-up, screening linked to management, or clinical decision support. Methodological quality was appraised using relevant JBI critical appraisal tools. Results: Thirty-nine studies were included in the qualitative synthesis. JBI appraisal indicated heterogeneous study designs and reporting quality, with common limitations related to simulated prompts or AI-output evaluations, variable comparators, and inconsistent outcome reporting. Evidence was dominated by patient-facing large language models and chatbot-based tools used for patient education, question answering, readability improvement, glaucoma and myopia counseling, diabetic retinopathy referral/follow-up, cataract education, oculoplastic and retinal-condition questions, and multilingual educational support. Study designs, AI models, prompting approaches, comparators, clinical topics, and outcome definitions varied widely, supporting narrative synthesis rather than quantitative pooling. Conclusions: AI-powered systems show potential as supervised adjunctive tools for eye-care counseling, education, and management-related communication. However, evidence remains heterogeneous and dependent on simulated prompts, AI-generated outputs, and model-based evaluations. Future research should prioritize standardized evaluation, real-patient validation, safety monitoring, readability control, and patient-centered outcomes before routine implementation in optometry and broader eye-care practice across diverse clinical settings. Full article

Despite growing interest in artificial intelligence (AI) applications in the construction industry, the literature still lacks a consolidated understanding of how AI functions across the full spectrum of construction supply chain processes. Existing studies are dispersed across different technologies, project stages, and application contexts, making it difficult to identify the intellectual structure of this field, the main areas of AI application, and the barriers that continue to constrain practical implementation. To address this gap, this study conducts a systematic review of AI applications in construction supply chains by combining scientometric analysis with qualitative content synthesis. A total of 212 journal articles retrieved from Scopus were analyzed using VOSviewer-based scientometric analysis and qualitative content synthesis. The scientometric analysis maps annual publication trends, keyword co-occurrence patterns, co-cited sources, influential documents, and collaboration networks. The qualitative synthesis further examines how AI supports construction supply chain management across three broad themes: procurement and production optimization, logistics and material management, and collaborative decision-making for resilience and sustainability. The findings show that AI has been primarily applied to demand forecasting, resource optimization, logistics coordination, contract and document processing, computer vision-based monitoring, and multi-agent decision support. However, its practical diffusion remains constrained by fragmented and low-quality data, limited empirical validation, high implementation costs, algorithmic opacity, cybersecurity risks, and unresolved governance and liability issues. Based on these findings, this study proposes a data-centric and phased research agenda that emphasizes benchmark datasets, human–AI collaboration, lifecycle economic evaluation, explainable AI, and multi-stakeholder governance. The study contributes to the literature by integrating fragmented AI-related research into a structured knowledge map and by clarifying future pathways for developing intelligent, transparent, and resilient construction supply chains. Full article

Background: Triple-Negative Breast Cancer (TNBC) remains the most aggressive oncological challenge within the African continent, characterized by high molecular heterogeneity, early onset in African women, and the absence of hormonal receptors. Multi-drug resistance (MDR), driven by ATP-binding cassette (ABC) efflux pumps and supported by the persistence of cancer stem cells (CSCs) within the tumor microenvironment, significantly compromises clinical outcomes and traditional treatment efficacy. Objective: This systematic review evaluates the ethnobotanical relevance, phytochemical diversity, and toxicity of some medicinal plants from the African pharmacopoeia specifically utilized or investigated for their activity against the TNBC phenotype. Methods: Following PRISMA guidelines, a systematic search was executed across PubMed, ScienceDirect, Scopus, Web of Science, and AJOL. The study focuses on original research published between 2011 and 2026 utilizing TNBC-specific models (such as MDA-MB-231, BT-20, HCC1937, or 4T1) and analyses the growth habits, parts used, and traditional administration modes of the selected African plant species, distributed across Western, Central, Southern, and Eastern Africa. Following a rigorous multi-reviewer screening process, a final set of 52 primary articles representing 30 distinct genera and 22 botanical families was selected for qualitative and quantitative synthesis. Results: This review identifies plant species actively used or studied in Africa for their anti-TNBC potential, with the most representative botanical families being Asteraceae (13%), Fabaceae (7%), and Annonaceae (7%). These species are traditionally administered through various methods, including decoction, infusion, and mastication, utilizing diverse plant parts such as leaves, stem and root barks. Significant cytotoxic activities against TNBC cell lines (notably MDA-MB-231) were recorded, with IC₅₀ values as low as 5.10 ± 0.28 µg/mL for Catharanthus roseus and 13.56 µg/mL for Nauclea pobeguinii. Furthermore, species such as Vernonia amygdalina and Curcuma longa demonstrated a capacity to enhance the effectiveness of conventional chemotherapy like Doxorubicin, suggesting a strong potential for chemosensitization and therapeutic synergy in managing resistant breast cancer phenotypes. Conclusions: Standardized African phytomedicines represent a promising frontier in overcoming TNBC chemoresistance. However, the lack of clinical trials and end-to-end drug development infrastructure on the continent remains a significant barrier. Transitioning to nano-formulated delivery systems and establishing regional drug discovery hubs under the ethical framework of the Nagoya Protocol are essential steps toward developing precise and equitable oncology treatments from Africa’s rich biodiversity. Full article

Background: The neutrophil-to-lymphocyte ratio (NLR) has been the focus of extensive research in recent years as an inexpensive inflammatory biomarker with prognostic value in oncology, but its relationship with tumor grade across solid malignancies remains uncertain. Methods: This systematic review evaluated original clinical studies reporting the association between peripheral blood NLR and histological tumor grade in solid tumors. PubMed and Web of Science were searched using Boolean strategies, and eligible full-text studies were synthesized qualitatively because of heterogeneity in tumor type, grading system, NLR threshold, and statistical reporting. Results: The qualitative synthesis included 13 retrospective primary studies comprising 5394 patients. Eight studies reported statistically significant associations between higher NLR and higher tumor grade or poorer differentiation, most consistently in bladder cancer and in single studies of prostate cancer, soft tissue sarcoma, renal cell carcinoma, pancreatic cancer, breast cancer, and colorectal cancer with synchronous liver metastases. Four studies reported no statistically significant grade-related association, mainly in heterogeneous breast cancer and ovarian cancer cohorts, whereas a small colorectal adenocarcinoma cohort study showed a non-significant positive trend. Conclusions: The available evidence suggests a possible relationship between systemic inflammation and tumor grade in selected malignancies, but the evidence remains preliminary, tumor-specific, retrospective, and vulnerable to confounding. NLR should not be interpreted as a surrogate for histological grade. Full article

Background/Objectives: Colitis involves both local intestinal damage and systemic dysfunction, driven by oxidative stress and immune imbalance. Histamine, acting through its receptors, influences these processes, yet its therapeutic relevance in colitis remains unclear. This review systematically examines histamine-mediated signaling in colitic inflammation and evaluates preclinical and clinical data on antihistamines to assess their potential as a mechanism-based treatment. Methods: A structured literature search was conducted using PubMed and Google Scholar to identify studies addressing histamine signaling and the use of antihistamines in colitis, using keywords such as “colitis,” “histamine,” “histamine receptors,” and “antihistamines.” Relevant experimental and clinical studies were screened and critically analyzed to provide an integrated overview of mechanistic and therapeutic insights. This review was designed as a mechanistic narrative synthesis based on a structured search and qualitative appraisal rather than a formal systematic review with quantitative risk-of-bias grading. Results: Findings from preclinical investigations consistently indicate that pharmacological manipulation of histamine signaling—especially through H3 and H4 receptor subtypes—reduces inflammatory activity and modulates oxidative balance in animal models of colitis. Conversely, clinical evidence concerning H1 and H2 receptor antagonists remains scarce and discordant, lacking sufficient support for a definitive causal relationship or unambiguous therapeutic efficacy. Importantly, no clinical studies to date have assessed the effects of selective H3 or H4 receptor blockers in individuals with colitis, revealing a substantial disconnect between bench research and bedside application. Existing human trials have mainly concentrated on mucosal endpoints, with little attention paid to systemic manifestations or oxidative stress-related parameters. Conclusions: Histamine-dependent signaling constitutes a mechanistically credible target in colitis, connecting immune activation, impairment of the epithelial barrier, and oxidative injury. Although experimental data are encouraging, clinical corroboration remains absent. Antihistamines may hold greater promise for alleviating systemic oxidative stress than for directly ameliorating intestinal inflammation. Rigorously designed clinical trials that incorporate both gastrointestinal and systemic outcome measures are necessary to elucidate their therapeutic position. Full article

The digital transformation of Morocco’s construction sector requires new approaches to address increasing project complexity and evolving regulatory demands. This exploratory qualitative study investigates the integration of building information modeling (BIM) and artificial intelligence (AI) through eight semi-structured interviews with field engineers, design engineers, sector experts, and researchers. The interview data were analyzed using thematic analysis in NVivo, supported by systematic coding, lexical similarity analysis, and cross-matrix synthesis. The findings reveal that BIM implementation in Morocco remains predominantly at Level 1, despite unanimous recognition of its high perceived usefulness. This gap between perceived usefulness and actual adoption is primarily explained by economic, institutional, legal, and capacity-related barriers rather than technological limitations. Participants also reported successful BIM-based clash detection experiences, highlighting measurable returns on investment through reduced design conflicts, rework, and project coordination efforts. Furthermore, AI was consistently perceived as an augmentation technology that enhances professional expertise and decision-making rather than replacing human roles. Based on these findings, the study recommends establishing a national BIM mandate, developing a national BIM competence center, strengthening regulatory and legal frameworks, and promoting context-specific research and development to accelerate Morocco’s digital transition while adapting BIM and AI implementation to local technical, institutional, and climatic conditions. Future research should validate these findings through pilot implementation projects. Full article

Background: Continuous chelation with etidronic acid (1-Hydroxyethylidene-1,1-diphosphonic acid, HEDP) has been proposed as a less aggressive alternative to sequential irrigation with ethylenediaminetetraacetic acid (EDTA) in endodontics. This systematic review and meta-analysis aimed to compare the effects of these two protocols on the mechanical properties and structure of root dentin. Methods: PubMed, Scopus, and Cochrane Central databases were searched up to June 2026 for in vitro studies comparing continuous chelation (NaOCl + HEDP mixture) with sequential irrigation (NaOCl and EDTA) on root dentin of permanent teeth. Studies on coronal dentin and those not using NaOCl + HEDP as a mixture were excluded. Risk of bias was assessed using the QUIN tool. Meta-analyses were performed for fracture resistance using a random-effects model. This review was registered in PROSPERO (CRD420250630663). Results: Twenty studies with a total of 572 specimens were included. Six studies had a low risk of bias and thirteen had a medium risk. The qualitative synthesis showed that HEDP generally resulted in similar or lower levels of erosion, microhardness reduction, demineralization, and collagen degradation compared to EDTA. The meta-analysis revealed no significant difference in fracture resistance (5 studies; SMD = 0.28; 95% CI: −0.37 to 0.92; p = 0.40); however, substantial heterogeneity was observed (I² = 66.7%). Conclusions: The evidence was limited by substantial heterogeneity and mainly medium risk of bias. Within the limitations, in vitro evidence suggests that continuous chelation with HEDP is comparable to EDTA in terms of root dentin mechanical properties and composition, supporting its use as a chelating agent in endodontic practice. This research received no external funding. Full article

This study synthesised reviews to identify methodological indicators that are instrumental in informing claims regarding digital storytelling (DST) outcomes and effectiveness across fields. An umbrella review methodology was employed, following the PRISMA-ScR reporting framework, with the Population–Concept–Context (PCC) framework guiding research question formulation. Four databases were searched, yielding 1656 records. Following independent screening by two reviewers, 19 reviews met the inclusion criteria. Critical appraisal was conducted using the JBI checklist, and content and thematic synthesis were subsequently performed using MAXQDA 26. Findings related to publication indicators revealed a gradual increase in DST reviews between 2016 and 2025, with qualitative systematic reviews being the most prevalent type. In terms of geographic distribution, most reviews were conducted by researchers based in Türkiye, with notable gaps in South American and African contexts. Analysis on contextual indicators demonstrated that the majority of reviews adopted a configurative review orientation regarding micro-level practices across health-related, general education, and language education fields. Drawing on participants from both formal and non-formal settings, these reviews primarily reported outcomes across eight domains. Regarding methodological indicators, the analysis revealed a lack of uniformity and considerable variation in the use and reporting of quality assessment, theoretical and pedagogical frameworks, technological tools, and measurement instruments. Key recommendations include prioritising meta-analytic and mixed-method reviews, encouraging research in underrepresented regions, examining DST at meso- and macro-levels, and systematically integrating and reporting key methodological indicators in future reviews. Full article

Membrane-based processes have emerged as efficient alternatives to conventional separation methods because they enable protein fractionation under mild processing conditions while preserving protein functionality and bioactivity. Furthermore, whey, traditionally regarded as a by-product of cheese manufacture, is now recognized as a valuable source of proteins and bioactive compounds that can be recovered and valorized through membrane processing. Despite this, the literature on protein fractionation processes based on membrane technologies remains limited across different membrane technologies and operational scales. This systematic review evaluates microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO) in the context of milk protein fractionation, with a focus on industrial relevance, process limitations, and the resulting high-value protein fractions. Unlike previous narrative reviews, the study integrates comparative performance metrics, including pressure, protein recovery, purity, process limitations, and resulting products. Following the PRISMA guidelines for the selection and assessment of eligibility for a systematic review, 55 studies were included in the final qualitative synthesis. The analysis shows that UF consistently achieves high protein recovery (>90%) and represents the dominant industrial technology for the production of whey protein concentrates and isolates, although its efficiency is limited by concentration polarization and flow rate drop at elevated volumetric concentration factors. Consequently, future research should prioritize integrated performance reporting, quantitative measurement, and integration of sustainability indicators to enable more robust industrial application of membrane-based dairy technologies. Moreover, more reporting bases on standardized industrial performance indicators and commercial case studies are needed to support the wider adoption and optimization of membrane technologies in dairy processing. Full article

This article develops a systems-thinking framework to analyze and govern interconnections among the Sustainable Development Goals (SDGs). Contemporary policy challenges, including food insecurity, climate change, water and energy security, inequality, urbanization, and conflict, are treated as complex systems characterized by feedback loops, delays, cross-sector dependencies, and unintended consequences. Drawing on a structured literature review, qualitative case analysis, and framework synthesis, the article translates core systems concepts into an operational workflow for coherent policy decision-making. The framework combines causal-loop analysis, leverage-point identification, cross-sector coordination, adaptive monitoring, and iterative learning. Two illustrative policy arenas, Zero Hunger and Climate Action, demonstrate how a systems lens can reveal reinforcing and balancing feedback loops, clarify synergies and trade-offs among SDGs, and support more coherent interventions. The article contributes to systems research by connecting conceptual tools from systems thinking with practical governance mechanisms for SDG implementation. It also identifies institutional, methodological, political economy, and financing barriers that limit adoption and proposes strategies for embedding systems analysis into policy design, budgeting, evaluation, and adaptive governance. Full article

Selective harvesting requires tree-level decisions that balance operational productivity, stand development, and sustainable forest management, yet current AI and sensing studies often remain fragmented across remote sensing, machine perception, optimization, and forestry domains. This review synthesizes research on AI-assisted selective harvesting and smart forest management, with emphasis on multimodal sensing, decision support, and harvester-oriented deployment. A PRISMA-informed scoping review was conducted using Scopus, Web of Science Core Collection, IEEE Xplore, ScienceDirect, and SpringerLink, resulting in 82 studies retained for qualitative synthesis. The reviewed literature was organized into eight thematic groups covering smart forestry, harvesting operations, RGB-based perception, LiDAR and point-cloud processing, multimodal fusion, edge deployment, decision-support systems, and forecasting-oriented digital forestry. The analysis shows that RGB imaging provides semantic tree recognition, LiDAR enables spatial localization and structural assessment, and decision-support methods can translate tree-level observations into transparent cut/keep recommendations. However, integrated harvester-mounted systems remain underdeveloped, particularly regarding real-time RGB–LiDAR fusion, operator-facing recommendations, and forecasting integration. This review proposes a reference architecture for human-in-the-loop AI-assisted selective harvesting and identifies future research priorities for field validation and smart forest-management integration. Full article

Climate change poses significant environmental and socio-economic challenges for Small Island Developing States (SIDS), including Timor-Leste. This systematic review aimed to synthesise evidence on climate change impacts, vulnerabilities, adaptation pathways, and research gaps in Timor-Leste. Following PRISMA 2020 guidelines, literature searches were conducted in Web of Science, Scopus, and Google Scholar through May 2025. Eligible sources included peer-reviewed studies, technical reports, policy documents, and institutional publications. Source quality was assessed based on relevance, methodological consistency, credibility, and thematic contribution, and evidence was synthesised using a qualitative meta-synthesis approach. A total of 79 peer-reviewed studies and 8 international reports met the eligibility criteria, resulting in a final corpus of 87 documents. The evidence indicates a warming trend of 0.16 °C/decade and a sea-level rise of 5.5 mm/year with significant implications for agriculture, food security, water resources, and coastal systems. Approximately 70% of the population depends on climate-sensitive livelihoods, increasing exposure to climate-related risks. Evidence remains limited by data scarcity and methodological heterogeneity. Overall, Timor-Leste faces substantial climate vulnerability, highlighting the need for strengthened adaptation planning, improved climate information systems, and targeted policy interventions. Full article

Background: Supply chains are becoming increasingly complex, interconnected, and stakeholder-intensive, making effective problem formulation as important as identifying optimal solutions. Although problem structuring methods (PSMs) have been widely applied in logistics and supply chain management (LSCM), the literature remains fragmented, providing limited guidance on selecting appropriate methodologies for different problem contexts. Methods: Following the PRISMA guidelines, this review analyzes 187 journal articles published between 1997 and 2026. Bibliometric analysis and qualitative synthesis were combined to examine the evolution of the field, compare the characteristics and applications of different PSMs, and identify emerging methodological trends. Results: PSM research has grown substantially since 2015, with System Dynamics, Cognitive Mapping, and Scenario Planning emerging as the dominant methodologies. The review also identifies a clear shift toward mixed-methodology approaches that integrate PSMs with optimization, simulation, and multi-criteria decision-making techniques. Stakeholder complexity, uncertainty, and system dynamics were identified as the primary factors influencing methodology selection. Conclusions: This study advances theory and practice by developing an integrated decision-support framework and methodological guidance for selecting appropriate PSMs in complex logistics and supply chain environments. The proposed framework provides a practical roadmap for diagnosing ill-structured problems and choosing suitable problem structuring approaches across diverse supply chain contexts. Full article