Search Results (13,436)

Leftover spaces, often associated with neglected urban corners, bear physical and conceptual similarities to ignored parts of designed wholes. This study proposes an analytical approach to develop resilient intervention strategies by analyzing the production of leftover spaces through users’ emotional experiences. An experimental pilot study was conducted along Söğütlüçeşme Street in Kadıköy, Istanbul, where all corner points were typologically classified based on morphological characteristics. To measure the impact of these configurations on spatial emotional characters, a survey was implemented using Plutchik’s wheel of emotions. Following a quantitative analysis of emotion frequencies and intensities, findings were visualized via radar charts and spatialized using QGIS 3.40 to generate an emotional map. The resulting emotional maps were further used to identify spatial vulnerabilities and resilience priorities across the study area. By making the gaps between point-based emotional clusters continuous through the IDW interpolation method, the emotional topography of the study area was modeled, thereby presenting an analytical framework that identifies emotional thresholds, spatial vulnerabilities, and resilience priorities. Results indicate that as the physical boundaries of corner voids expand, influenced by angling and massing decisions, public diversity increases, creating a positive emotional atmosphere. Conversely, compressed voids demonstrate a higher potential for producing leftover spaces. This study reveals that mapping user emotions as a data layer is critical for constructing more inclusive and resilient urban environments. Full article

Education systems face increasing pressure to adopt evidence-informed innovations that respond to learner diversity. In early childhood, understanding neuroplasticity is foundational for developing inclusive pedagogies, yet translating basic neuroscience into teacher professional development remains complex. This study presents a descriptive and exploratory bibliometric analysis characterizing the intersection of neuroplasticity, neuropedagogy, and early childhood to map how research evidence is organized. A corpus of 2937 documents spanning from 1975 to early 2026 was analyzed to identify publication trends, global collaboration networks, and thematic structures. Results indicate exponential growth in the field, with the United States leading in volume but European and South American nations demonstrating higher international collaboration rates. Thematic mapping reveals a structural separation between applied human studies and mechanistic basic science. This translational distance, combined with the documented prevalence of neuromyths among educators, presents a significant barrier to evidence-informed inclusive education. These findings provide researchers and policymakers with a diagnostic map of the field, outlining specific implications for the content, design, implementation, and evaluation of future teacher professional development to responsibly advance educational equity and inclusion. Full article

Anxiety disorders pose an increasing challenge to the mental health of individuals, particularly in regions with limited healthcare access. This study investigated the potential of integrating a brain–computer interface for processing electroencephalography (EEG) data with deep learning models to accurately classify anxious and non-anxious states. In the first phase, a convolutional neural network (CNN) was developed and validated on the public GAMEEMO dataset, achieving a classification accuracy of 95.72%. In the second phase, we conducted a separate experimental validation with seven participants (aged 18–60 years) using a within-subjects design. The protocol comprised a custom Stroop test to elicit acute cognitive stress and anxiety-related arousal, followed by a guided 4–7–8 breathing exercise to induce relaxation. EEG data from this experiment were used to classify anxious versus non-anxious states with the same CNN architecture after domain adaptation. On this self-collected dataset, the CNN achieved an accuracy of 86.58%. These results demonstrate proof-of-concept transferability while highlighting the performance gap between controlled benchmark data and real-world, small-sample recordings. The deep learning model can subsequently be coupled with neurofeedback techniques to manage anxiety levels. Overall, the findings support the potential of the developed automated system for detecting stress-induced anxious states, with possible future integration into neurofeedback-based management systems. Full article

Urban historic districts often present archaeological sites and historic buildings in a fragmented way, posing significant challenges for public understanding and enhancing heritage value. Solely physical conservation fails to fully communicate their cultural significance, while excessive commercialization often results in the erosion of cultural authenticity and the displacement of local communities. Drawing from cultural capital theory in sociology and cultural economics, this study redefines historical districts as sustainable urban cultural capital, comprising habituated, objectified, and institutionalized components. A Value Chain Model of Cultural Capital (VCMCC) is developed, consisting of three stages: cultural resource excavation, cultural asset cultivation, and cultural capital management. This model aims to empower heritage adaptive reuse and foster synergy between cultural heritage and economic development. Utilizing an embedded single-case design with longitudinal ethnography, the research focuses on the Western Han Archaeological Sites Historical District (WHAS HD) in Hanzhong, China. It involves multiple rounds of mixed-data collection from 2023 to 2025, on which design-based research is performed. This study operationalizes VCMCC through a series of spatially and socially grounded strategies. In the cultural resource excavation stage, superior resources are identified through a systematic review of historical archives, archaeological reports, and local gazetteers, along with surveys of architectural remains and spatial mapping. In the cultural asset cultivation stage, these resources are transformed into experiential and communicable cultural assets via a “one courtyard, one strategy” approach for activating courtyard functions, developing dual-theme heritage routes, and deploying digital interpretation tools. In the cultural capital management stage, a multi-stakeholder community committee is established, and binding institutional safeguards are integrated to ensure sustainable heritage adaptive reuse. Concurrently, a baseline indicator system covering three dimensions, cultural, social, and economic benefits, is developed to provide benchmarks for future post-intervention benefit evaluation and verification. The proposed and implemented VCMCC model translates cultural capital theory from an abstract explanatory framework into an actionable pathway for heritage adaptive reuse, offering theoretical and methodological guidance for the adaptive reuse of similar small and medium-sized historic districts. Full article

Background/Objectives: Standardised institutional patient satisfaction surveys are the primary quality-monitoring tool in Romanian public hospitals, but their ability to capture the full range of patient experiences remains uncertain. This study quantifies the discrepancy between institutional patient satisfaction scores and an independent, unmediated national feedback instrument, the Patient Feedback Mechanism (MFP), at Targoviste County Emergency Hospital (SJUT) over a six-year period (2019–2024), and examines item-level MFP results across eight dimensions of the patient experience, including dimensions not captured by the institutional indicators routinely reported by SMCSP. Methods: A sequential design combined six years of institutional satisfaction data (2019–2024) from SJUT (N = 32,176 questionnaires) with item-level MFP results for the same period, covering eight questions on medical services, cleanliness, out-of-pocket medication costs, staff involvement, communication, recommendation intent, self-reported health outcome, and willingness to report requests for money from staff. Hypotheses were tested using two-proportion z-tests with Wilson confidence intervals, Mann–Kendall trend analysis, and Cohen’s h for effect sizes. Results: Institutional satisfaction remained consistently high (96.88–97.45%), while MFP satisfaction with medical services ranged from 70.7% to 88.9% across the same years, yielding gaps of 7.9 to 26.7 percentage points, significant in every year (p < 0.001; Cohen’s h ranging from 0.32 to 0.82). The gap did not follow a monotonic trend (Mann–Kendall p = 0.469); instead, it widened to a peak in 2021 and narrowed progressively through 2024. A parallel comparison between the Quality and Patient Safety Management Service (SMCSP) overall impression item (exceeding 99%) and the MFP recommendation item (69.9–76.3%) showed even larger gaps, of 23.3 to 29.6 percentage points. The MFP item on willingness to report requests for money from staff, which is not part of SMCSP’s reported institutional indicators, remained in a narrow 4.0–5.5% range between 2019 and 2023 with no significant trend (Mann–Kendall p = 0.82); a higher 2024 value (6.9%) coincides with a national redesign of this item and is not directly comparable to earlier years. Conclusions: Institutional surveys and an independent national feedback instrument offer structurally distinct perspectives on hospital performance, reflecting differences in administration rather than equivalent estimates of patient satisfaction. The discrepancy between sources is significant and persistent, though not monotonic, widening sharply during 2021 before narrowing. One item with no institutional equivalent documents a measurable, non-trivial proportion of patients willing to report informal payment requests every year, although the available data do not establish whether this proportion is rising over time. Systematic use of existing MFP data, already collected nationally, can complement institutional surveys at minimal additional cost, provided the two instruments are interpreted as structurally different rather than as alternative estimates of the same quantity. Full article

Sustainability transitions confront firms with the following informational paradox: the regulatory pressure to innovate green has intensified, yet the knowledge required to do so is dispersed across agencies, sectors, and jurisdictions that rarely speak to one another. Treating data as a strategic factor of production, this paper asks whether and how opening public data—the systematic release of government-held datasets—reconfigures the conditions under which firms generate green innovation. We model the green-innovation ecosystem as a Complex Adaptive System (CAS) in which heterogeneous, bounded-rational agents co-evolve with a data-mediated selection environment. Within this frame, public data openness (PDO) is not marginal input but an exogenous shock to the fitness landscape that propagates through three coupling channels—supply–demand alignment, recalibration of government intervention, and amplification of green credit. Formal derivations link each channel to a testable proposition, and a multi-period Difference-in-Differences (DIDs) design built on the staggered roll-out of Chinese municipal open-data platforms identifies the causal effects, with Callaway–Sant’Anna estimators and double/debiased machine learning (DDML) addressing recent econometric critiques. The evidence supports each proposition and reveals the following distinctive heterogeneity signature consistent with absorptive-capacity heterogeneity: the policy is most consequential where agents and ecosystems are best able to convert data into knowledge. Reframing PDO as a systemic enabler clarifies why uniform rollouts yield uneven returns and motivates a tiered design that scales with the absorptive capacity of recipient firms and regions. Full article

Farmers’ investment decisions can shape their capacity to implement practices consistent with sustainable development objectives. The article identifies the declarative structure of investment decisions on Polish dairy farms based on a survey and diverse theoretical frameworks (resource-based view, institutional approach, real options theory, behavioural theory, and the theory of planned behaviour). The purpose is to identify the determinants of the extent and structure of declared agricultural investments. The authors determined the relationships between declared investments and groups of variables and identified investment axes and interdependencies. Investment decision predictions are founded on logistic regression, an SEM model for relationship structuring, and residual correlation analysis for mapping relationships and evaluating the correlation demasking effect, according to which raw correlations between investment axes may hide underlying residual associations between them. We found that declared farmland investments were associated with milk production volume and appeared to be linked to long-term farm development objectives. The respondents became less keen on investing in livestock production as they aged, whereas older farmers showed a greater propensity to undertake energy-related investments. These results suggest that farmers’ declared investment intentions may be consistent with conditions conducive to achieving sustainable development objectives through their potential association with farm viability, resource-use efficiency, and rural economic development. Our findings may have potential policy relevance by informing the design of public measures aimed at strengthening farms’ adaptive capacity in the context of sustainability transitions. Full article

Climate change is reshaping agricultural systems by altering temperature and rainfall regimes, increasing the frequency of extreme events, and intensifying risks to crop productivity, water use, and farm decision-making. As climate–agriculture research expands rapidly, it becomes increasingly difficult to identify consolidated knowledge domains, emerging priorities, and evidence gaps. This study maps the structure and evolution of this literature using 219,261 Scopus-indexed documents selected from 290,560 records published between 1990 and 2025. A text-mining workflow combined BERTopic-based semantic modeling with supervised thematic classification into 18 macro-themes, while annual shares, z-scores, and document-level primary–secondary co-framing were used to assess temporal salience and cross-theme coupling. The results show sustained growth in research output, with 53.67% of publications produced between 2016 and 2025, and strong geographical concentration in the United States and China, which together account for 41.98% of the corpus. Hydrology and water management, crop production, impact assessment, and atmospheric processes remain central pillars, while socio-economic vulnerability, food security, sustainability, biotechnology, and greenhouse gas mitigation have gained prominence. The resulting evidence map provides a reproducible overview of the climate–agriculture knowledge landscape and can support research prioritization and policy design for climate-resilient agrifood systems. Full article

Commercially mature products obtained by fractionation or extraction of phototrophic microalgal biomass remain concentrated in four categories: whole-cell Spirulina/Chlorella, C-phycocyanin, astaxanthin, and DHA-rich oils. Little diversification of these fractionated, mid-tier products has followed the decline in upstream costs. Whole-cell feed and live-culture markets, agricultural biostimulants, and fermentation-derived ingredients are commercially active but lie outside this phototrophic downstream-processing scope. Reported open-pond biomass production costs have fallen from ~US$10 kg⁻¹ in the 1990s to sub-US$1 kg⁻¹ nth-plant projections, yet no substantial product diversification has occurred. This review brings together three complementary lines of evidence: a bibliometric analysis of 1995–2025 publications showing that downstream fractionation, biorefinery, and integrated process design account for only 9.3% of food-core microalgal research; institutional surveys documenting the same four dominant categories across Europe, China, and global markets; and a meta-analysis of 53 whole-biomass cost rows from 16 techno-economic assessments. These sources indicate consistently that downstream processing is a necessary, though not sole, constraint on commercial diversification. A four-tier unit-operation roadmap is proposed-cell disruption at commodity energy cost, fractionation with functional ingredient preservation, decolorization and desalting at food-ingredient unit cost, and standardized transferable workflows-each linked to a quantitative threshold and to the product categories it would unlock. Closing the microalgal processing technology gap now depends less on demonstrating feasibility than on meeting these thresholds. Full article

Neighbourhood-scale sustainable urban mobility assessment requires analytical tools that evaluate walking, cycling, and public transport together rather than as separate modes. Existing studies often rely on single-mode indicators or aggregated urban-scale measures, which limit their ability to reveal micro-scale spatial inequalities and multimodal performance imbalances. This study addresses this gap by developing an integrated Geographic Information Systems (GIS)–Analytic Hierarchy Process (AHP)–correlation–clustering framework for six sample areas in Kayseri, Türkiye. The framework evaluates three main criteria—walkability, bikeability, and public transport accessibility—through ten sub-criteria. In addition, seven land-use and urban design variables are used to examine built environment relationships. A 100 × 100 m grid-based spatial database was created; criteria weights were determined using AHP; mobility scores were examined through correlation analysis; and spatial mobility typologies were identified using K-means clustering. The findings indicate that development density and land-use diversity support walkability. However, similar density patterns do not automatically improve cycling performance or public transport integration. The clustering results reveal persistent modal imbalances, even in areas with medium-to-high overall performance. The study demonstrates that density alone is insufficient for multimodal sustainability and offers an adaptable decision-support framework for context-sensitive neighbourhood planning. Full article

Background: Measles remains a significant public health challenge in Ethiopia, and the country has not achieved measles elimination despite the commitments outlined in the Immunization Agenda 2030. This study assessed inequalities in MCV2 vaccination among children aged 24–35 months in Ethiopia. Methods: This study used nationally representative data from the 2022/23 National Health Equity Survey, which employed a two-stage stratified cluster sampling design across all regions and city administrations. A total of 1987 mothers/caregivers of eligible children were interviewed. Descriptive statistics, bivariable analyses, and multivariable logistic regression were conducted using Stata 17 software, and determinants of MCV2 uptake were identified. Wealth-related inequality was assessed using concentration index analysis. Statistical significance was set at p < 0.05. Results: Overall MCV2 coverage was 60.4%. The multivariable analysis identified a significant inequality in second-dose measles vaccination (MCV2) in Ethiopia. Children born in health facilities had higher odds of vaccination (AOR = 1.88; 95% CI: 1.49–2.38), and maternal age of 25–34 years was associated with increased uptake compared to younger mothers (AOR = 2.03; 95% CI: 1.18–3.48). Postnatal care utilization and vitamin A supplementation strongly improved vaccination coverage, with children receiving vitamin A showing markedly higher odds of MCV2 uptake (AOR = 16.74; 95% CI: 9.61–29.14). Female children were more likely to be vaccinated than males (AOR = 1.50; 95% CI: 1.01–2.24), and higher maternal education (college or above) significantly increased uptake (AOR = 2.78; 95% CI: 1.02–7.73). Wealth status also influenced coverage. Conclusion: Improving MCV2 coverage in Ethiopia requires strengthening of maternal and child health services and promotion of integrated care, including PNC, vitamin A supplementation, and routine immunization. Early and consistent contact with the health system, along with addressing gaps in health education and supporting younger mothers, is essential. Persistent inequalities by place of birth, household wealth, and region highlight the need for targeted interventions. Strengthening equitable immunization services remains critical to achieving national and global measles elimination goals. Full article

Background: Gestational diabetes mellitus (GDM) affects between 1% and 14% of pregnancies worldwide. Major risk factors include advanced maternal age, excess adiposity, family history of type 2 diabetes, and unhealthy dietary habits. In Mexico, evidence on the association between dietary patterns and GDM remains scarce, particularly in socioeconomically vulnerable populations with limited access to specialized nutrition services. This study aimed to evaluate the association between dietary patterns and the presence of GDM in pregnant women attending the outpatient obstetrics clinic of a teaching public hospital in Guadalajara, México. Methods: We conducted a case–control study including 169 pregnant women: 71 with GDM confirmed by the ADA one-step 75 g oral glucose tolerance test OGTT criteria and 98 without GDM based on a negative OGTT, recruited consecutively from the same clinic during the same period. Dietary intake was assessed using a culturally adapted and validated Food Frequency Questionnaire. Dietary patterns were identified through Principal Component Analysis, and associations were examined using logistic regression adjusted for maternal age, pregestational BMI, and family history of type 2 diabetes. Results: Women with GDM had higher maternal age, greater pregestational BMI, and more frequent family history of type 2 diabetes compared with controls. Three dietary patterns were identified: Western, Healthy, and Dairy/Refined. High adherence to the Western pattern was inversely associated with GDM (aOR = 0.36; 95% CI: 0.16–0.78; p = 0.010); however, this finding most likely reflects post-diagnosis dietary modifications rather than a protective effect, while maternal age remained the strongest risk factor (OR = 1.09; 95% CI: 1.03–1.16; p = 0.002). The Healthy pattern (aOR = 1.25; 95% CI: 0.55–2.82; p = 0.593) and the Dairy/Refined pattern (aOR = 0.80; 95% CI: 0.39–1.66; p = 0.554) were not significantly associated with GDM in the adjusted model. Conclusions: GDM was associated with older maternal age, higher pregestational BMI, and family history of T2DM. The inverse association with the Western pattern may reflect post-diagnosis dietary changes rather than a protective effect. Due to the retrospective design, causal inference is not possible, highlighting the need for longitudinal studies. Full article

The integration of collaborative robots into industrial environments requires rigorous safety validation under the Power and Force Limiting (PFL) regime. This review article systematically maps the technological and normative development of certified Pressure and Force Measurement Devices (PFMDs) and experimental biofidelic instruments for Physical Human–Robot Interaction (pHRI) between the years 2011 and 2026. A quantitative screening of 68 studies revealed a publication peak in impact metrology in 2021. This peak occurred with a five-year latency after the release of the ISO/TS 15066 technical specification. Although global interest in collaborative robotics steadily grows, the publication trend indicates a gradual shift in scientific focus from reactive testing toward proactive prevention. A methodological deconstruction of four Research Questions (RQs) identifies persistent limitations in safety evaluation. The findings demonstrate that the internal structure of conventional sensors induces nonlinear shock filtering and parasitic oscillations (RQ1). Furthermore, the rigid fixation of test stands generates unrealistic pressure spikes. This physical limitation forces a transition to flexible and pendulum-based configurations (RQ2). Commercial flat films physically fail due to sensor saturation and introduced stiffness. Such failures accelerate the development of conformable electronic skins (e-skins) and multimodal test manikins (RQ3). To ensure interlaboratory reproducibility within the current ISO 10218-2:2025 standard, the text defines imperative metrological parameters. These parameters strictly include frequency response, calibration protocols, and volumetric mapping of inertial masses (RQ4). Furthermore, the analysed publications were systematically stratified into distinct technological categories, strictly reflecting their primary engineering domains, ranging from empirical metrological evaluation and sensor hardware design to advanced numerical modeling. Finally, the vision for future research anticipates a definitive shift toward proactive anti-collision technologies, encompassing Artificial Intelligence (AI), machine vision, and Augmented Reality/Virtual Reality/Mixed reality (AR/VR/MR). Future methodologies must also consider demographic anisotropies and the cognitive fatigue of the human operator. Full article

Decommissioned airfields are increasingly recognized as strategic sites for ecological regeneration, climate adaptation, and the creation of new public spaces. However, research on their transformation has predominantly focused on the environmental performance of Nature-based Solutions (NBS), often overlooking the role of inherited spatial morphology in structuring regeneration processes and outcomes. This paper proposes an AI-assisted, morphology-based proto-ontological framework for analyzing and designing post-airfield architecture. The framework was developed through the inductive and comparative analysis of a corpus of 32 urban post-airfield regeneration projects, from which recurrent inherited morphologies, transformation actions, spatial devices, and NBS were identified and structured into a relational sequence. The framework was then applied to two contrasting case studies: Maurice Rose Airfield Park (Frankfurt) and Xuhui Runway Park (Shanghai); these were selected for their different transformation logics. The results show that similar airfield morphologies can generate markedly different climatic, ecological, social, and memory-related outcomes depending on how they are transformed and linked to NBS. The study demonstrates that inherited airfield morphologies are not passive remnants but operative spatial structures, and that NBS should be understood as spatially embedded and form-generating design components. The proposed proto-ontology offers a transferable analytical model and a basis for future computational and generative design applications. Full article

The Internet of Vehicles (IoV) is reshaping intelligent transportation through pervasive connectivity, real-time data exchange, cooperative perception, and vehicle–edge–cloud services, while also expanding cybersecurity and privacy risks across heterogeneous cyber–physical environments. This paper presents a PRISMA 2020-informed systematic review of IoV security and privacy protection research. A cross-layer and lifecycle-oriented analytical framework is developed by integrating a four-layer IoV architecture—sensing layer, network access layer, coordinative computing layer, and application layer—with a five-stage data lifecycle covering data collection, transmission, storage, usage, and disposal. Based on this framework, the paper examines representative threat surfaces, vehicle-to-everything (V2X) communication security, public key infrastructure (PKI) based authentication, trust management, privacy-preserving data sharing, intrusion detection, active defense, and AI-assisted security analytics. Privacy-preserving mechanisms, including differential privacy, federated learning, blockchain, homomorphic encryption, and secure multi-party computation, are further compared in terms of deployment layer, lifecycle stage, real-time suitability, and representative performance evidence. In addition, the review discusses the engineering relevance of UNECE WP.29 R155/R156, ISO/SAE 21434, and related national standards, with emphasis on compliance evidence, over-the-air (OTA) governance, supply-chain coordination, and lifecycle cybersecurity management. The review shows that no single protection mechanism can simultaneously satisfy the requirements of real-time performance, scalability, privacy preservation, trustworthiness, and regulatory compliance in dynamic IoV environments. Future research should emphasize lightweight and adaptive protection, cross-layer trust coordination, privacy–utility co-optimization, trustworthy AI-assisted security operations, and evidence-based lifecycle governance. This review provides a structured reference for researchers and a practical basis for secure and privacy-aware IoV system design. Full article