Search Results (6,112)

Conventional diagnosis of chronic kidney disease (CKD) relies predominantly on invasive blood-based examinations, limiting the scalability of kidney health screening in resource-constrained environments. This study presents embedded engineering framework for non-invasive, breath-based CKD staging framework supported by machine learning and implemented on a low-cost embedded platform. To account for physiological sex differences in baseline creatinine production, estimated glomerular filtration rate (eGFR) values and breath ammonia concentrations were derived from two independent clinical cohorts using sex-specific MDRD equations (incorporating the standard male formula and the $0.742$ female correction factor, respectively) and creatinine–BUN conversion models, with male- and female-parameterized algorithms developed in parallel. The resulting feature space was analyzed using four unsupervised clustering approaches to stratify subjects into five clinically meaningful kidney function stages. Stage-specific ammonia thresholds were implemented within an Arduino Nano-based prototype equipped with an MQ-137 gas sensor and OLED display, enabling real-time point-of-care classification. Dataset-level classification accuracy reached 82% for the male algorithm and 92% for the female algorithm. Hospital-based validation on 29 patients (22 male, 7 female) yielded a real-world testing accuracy of 90.5% ($20/22$) for male patients and 71.4% ($5/7$) for female patients, a discrepancy largely attributable to the small female sample size. Because the current evaluation lacks healthy control subjects and is constrained by sample size, these empirical results serve primarily to demonstrate hardware-software functional integration and real-world deployment feasibility rather than definitive clinical efficacy. Despite these preliminary, sample-limited clinical datasets, results suggest this approach holds promise as an accessible, non-invasive screening complement to conventional diagnostic pathways, particularly in low-resource healthcare settings. Full article

High shrinkage-related defect rates in aluminum die casting reduce effective production capacity. They also create energy-intensive re-melting loops, which weaken production planning reliability and environmental performance. This study examines how Green Lean Six Sigma can stabilize a resource-constrained Small and Medium-Sized Enterprise (SME) die-casting process and translate quality improvement into measurable capacity recovery and Scope 2 electricity-related carbon savings. Based on a 10-month case study, the Define–Measure–Analyze–Improve–Control (DMAIC) framework was integrated with factorial ANOVA, the Response Surface Methodology (RSM), one-way analysis of variance (ANOVA) and statistical process control (SPC). These methods supported process parameter identification, operating-window development and shop-floor process stabilization. The analysis identified the filling speed and mold temperature as significant shrinkage drivers, developed a mold temperature control map, and determined the standardized filling speed at 800 mm/s. The intervention reduced the shrinkage defect rate from 7.19% to 1.46%, reduced the overall scrap rate from 7.60% to 2.71%, and improved the overall sigma level from 2.93 to 3.42. This yield improvement generated a 4.89 percentage-point yield-equivalent capacity gain, avoided 4401 kWh of re-melting electricity, reduced Scope 2 emissions by 2.36 t CO₂e, and generated gross annualized savings of RMB 249,214 (USD 35,783). Considering a one-time implementation cost of RMB 31,445 (USD 4515), the first-year net saving was RMB 217,769 (USD 31,268). The findings show that accessible statistical process control methods can provide SMEs with a resource-efficient pathway to improve process stability, capacity utilization and electricity-related environmental performance before investing in advanced digital technologies. Full article

Data movement constrains edge convolutional neural network (CNN) accelerators. We present Weight and Activation Compression for Tensor Traffic (WACT), a lossless framework for 8-bit signed integer (INT8) weights and consumer-facing activations. WACT calibrates a mode, tile geometry, and Rice parameter per invocation-aware tensor identity, freezes the policy, and uses a complete metadata- and alignment-inclusive comparison with strict uncompressed (RAW) fallback. Across five image-classification CNNs with one cold weight load and 320 activation passes per model, WACT reduced measured downstream occupied packet bytes by 44.48% (1.801×) over 78,339 events, with zero decoded-INT8 mismatches. A minimal aligned-RAW sensitivity changed this saving by 0.0293 percentage points. On MobileNetV2, FULL_WACT exceeded the best recalibrated single mode and a matched zero-value-compression-style baseline by at least 5.402 and 8.587 percentage points, respectively. A separate labeled 50,000-image validation measured FP32 and INT8 quantize–dequantize (QDQ) Top-1 accuracies of 72.148% and 71.392%, respectively; the latter used scales frozen from the canonical 32-image calibration subset, denoted S0. Explicitly bounded aggregate cold-start SCALE-Sim modeled-access projections were 11.00–17.70%. The complete WACT policy was evaluated in software, whereas the implemented hardware was limited to the single-tile Rice-mode encoder and decoder paths. The routed 28 nm CMOS blocks had standard-cell areas of 0.010942 and 0.010571 mm², passed post-layout SDF loopback, and consumed 4.939 mW of codec-logic power. The measured downstream-byte reduction therefore provides an energy-saving opportunity whose realization depends on codec overhead and the cost of memory movement in the target hierarchy. Full article

Electronic waste (e-waste) is among the fastest-growing global waste streams, with 62 million tonnes generated in 2022 and only 22.3% formally recycled, while generation is projected to reach 82 million tonnes by 2030. Fragmented record-keeping, weak chain-of-custody controls, and limited transparency enable illegal dumping, fraudulent recycling claims, and loss of recoverable materials. This paper presents a narrative literature review of blockchain and distributed ledger technologies applied to electronics and e-waste management. Following a structured search and relevance screening of major scientific databases, publisher platforms and grey literature (last search was run on 15 July 2026), 110 sources published between 2017 and 2026 were thematically synthesized across four domains: technological developments, sustainability and circular-economy implications, traceability and compliance mechanisms, and e-waste management applications. Blockchain delivers value primarily through an auditable chain-of-custody built on three pillars: standardized item and batch identities, standardized lifecycle event schemas, and licensed-actor attestations supported by off-chain evidence anchored on-chain. Recurring design patterns include permissioned consortium networks, hybrid storage, and role-based access control. Persistent barriers include data-input integrity, scalability, governance, and cost. Blockchain immutability protects stored records but cannot correct falsified inputs, making trusted data capture and governance the decisive factors for reliability. Adoption should be evaluated against measurable indicators, such as traceability completeness, audit-time reduction, fraud rates, and verified material recovery, rather than assumed benefits. Full article

Urban greening studies have traditionally emphasized vegetation quantity, while the perceptual implications of horticultural composition and spatial configuration remain less clearly understood. This study investigated how horticultural configurations were associated with multidimensional landscape perception across 10 urban parks in Chengdu, China. A total of 500 standardized landscape images, comprising 50 images per park, were assessed by 150 participants across 17 perceptual dimensions. Vegetation composition, spatial configuration, and conventional greenness indicators were quantified from the images and park-level spatial data. Principal component analysis and PERMANOVA were used to characterize structural gradients among parks, while exploratory factor analysis was used to identify integrated perceptual domains. XGBoost models with five-fold cross-validation were subsequently developed to predict individual perceptual outcomes, and SHapley Additive exPlanations (SHAP) were applied to interpret feature contributions and nonlinear response patterns. Multi-objective optimization was further used to explore hypothetical configuration scenarios involving trade-offs among perceptual objectives. The first two structural principal components explained 65.60% of the variation in horticultural composition and spatial organization, and park configurations differed significantly (PERMANOVA: F = 166.66, p = 0.001). Horticultural typologies differed across 15 of the 17 perceptual dimensions (all p < 0.001), with the largest differentiation observed for nature (ε² = 0.270), species richness (ε² = 0.259), openness (ε² = 0.251), being away (ε² = 0.245), serenity (ε² = 0.236), and enclosure (ε² = 0.234). The XGBoost models showed consistently strong predictive performance, with test-set R² values of 0.692–0.812 and cross-validated R² values of 0.756–0.796. SHAP analyses indicated differentiated and nonlinear associations: vegetation continuity and enclosure were primarily related to restorative immersion, open configurations to spatial accessibility, and ornamental and compositional complexity to affective richness. The optimization results further identified continuous trade-offs among restorative immersion, spatial openness, and affective richness, rather than a single universally optimal configuration. These findings show that landscape perception is associated with the spatial organization and composition of horticultural elements through multidimensional and nonlinear pathways. The study therefore extends vegetation-quantity assessments by providing a configuration-based analytical framework for exploring perceptually balanced urban horticultural environments. Full article

This paper presents the SCORPiò-NIDI project as a case study for the implementation of collaborative digital workflows aimed at enhancing the value and accessibility of archaeological heritage through 3D modelling. The study outlines a replicable pipeline that integrates rigorous CAD-based scientific modelling, functional animation, high-quality rendering, and web-based dissemination, aligned with FAIR principles and international standards for cultural heritage visualisation. The 3D models of the scorpion and ballista are conceived not merely as visual assets but as epistemic and narrative instruments, enabling scientific analysis, effective communication, and immersive, interactive engagement through collaborative platforms such as ATON and WordPress. Full article

This review examines the clinical and practical implications of embedding molecular profiles directly into the 2023 FIGO staging system for endometrial carcinoma, in the context of the 2025 ESGO/ESTRO/ESP guidelines. The primary purpose is to navigate a central conflict in modern oncology: how to deliver increasingly personalized care while maintaining a globally accessible, equitable, and standardized cancer classification system. The 2023 FIGO update represents a paradigm shift from the traditional dualistic model (Type I versus Type II) by allowing molecular findings to redefine stage itself. While this integration offers clear benefits, it introduces significant challenges. First, the system depends on advanced molecular testing, creating a “rich-poor” divide where patients in resource-limited settings are systematically overtreated because testing is unavailable. Second, stage becomes unstable, changing with sequential histologic and molecular re-review, which causes confusion for patients and clinicians. Third, the system lumps prognostically distinct histotypes (Serous, Clear Cell, Carcinosarcoma, and Grade 3 Endometrioid) into a single aggressive stage, obscuring meaningful differences in survival. Fourth, it relies on subjective parameters such as “substantial” lymphovascular space invasion, for which no standardized definition exists, leading to high inter-observer variability. After analyzing these controversies, the review proposes a pragmatic solution: decouple anatomical staging from molecular risk stratification. Staging should remain a purely anatomical, universally applicable descriptor of tumor extent, while molecular and histologic data are used separately within a dynamic risk assessment model, as suggested by the European guidelines. This dual-track approach preserves global comparability, reduces inequity, and maintains diagnostic stability, while still enabling personalized treatment where advanced diagnostics are available. Full article

Molecularly imprinted polymers (MIPs) have emerged as promising recognition materials for antibiotic sensing owing to their high stability, low cost, and tunable selectivity. However, enhanced recognition capability does not necessarily translate into high-performance sensing. A critical yet often overlooked bottleneck lies in the inherently indirect nature of this conversion: molecular binding occurs within an insulating polymer matrix that is spatially and functionally decoupled from the underlying signal transducer, particularly in complex environmental matrices. To address this limitation, this review proposes a unified framework centered on recognition–structure–signal interplay. Within this framework, sensing performance depends not on the simple addition of independently optimized components, but on the synergistic integration of recognition fidelity, structural accessibility, and signal transduction efficiency. Recent advances in electrochemical, optical, photoelectrochemical, and electrochemiluminescent MIP sensors are critically examined through this lens, with emphasis on platform-specific failure modes-including inaccessible recognition sites, insufficient site-transducer integration, weak binding-induced signal modulation, signal amplification-dominated responses, and matrix-induced decoupling. Machine learning is further critically assessed as an emerging data-driven tool for MIP design, signal decoding, experimental optimization, and sensor-level performance prediction, while its broader applicability remains constrained by limited datasets, insufficient external validation, and poor cross-platform transferability. Despite major progress in sensitivity, unresolved challenges persist, including weak intrinsic conversion efficiency, structural trade-offs, limited reliability in real-world samples, a lack of standardized validation protocols, and poor scalability of laboratory fabrication. This review concludes that next-generation MIP-based antibiotic sensors require a paradigm shift from affinity-oriented imprinting and signal amplification toward co-localized recognition-transduction interfaces, matrix-tolerant architectures, interpretable data-driven design, and manufacturable field-deployable systems. Full article

Background: Point-of-care ultrasound (POCUS) use continues to expand across specialties caring for pediatric patients in the perioperative period, offering noninvasive, diagnostic information that complements clinical assessment in real time. Although many POCUS applications were developed and validated in adults, pediatric POCUS requires unique considerations. This review examines the current evidence of diagnostic POCUS within pediatric perioperative care. Methods: A structured search of PubMed was performed for literature published through December 2025, using terms related to point-of-care ultrasound, perioperative care, cardiac, lung, gastric, and airway ultrasound, as well as focused assessment with sonography in trauma (FAST). Priority was given to systematic reviews, meta-analyses, randomized controlled trials, clinical practice guidelines, and landmark observational studies, while supplemented by recent high-quality publications. Findings: POCUS in each of the following areas is discussed: cardiac, pulmonary, airway, gastric, and FAST. Topics for each of the areas include a general overview, considerations for devices and probe selection to optimize imaging, specific uses and applications of the imaging, and potential limitations. Conclusions: POCUS is a valuable tool to complement comprehensive clinical evaluation of children in the perioperative period. Widespread adoption will require additional pediatric normative data, standardized protocols, and structured training for providers. Future research should continue to validate POCUS algorithms and clarify the role of artificial intelligence in enhancing image interpretation and accessibility. Full article

Coupling-coordination degree (CCD) indices are often interpreted as evidence that urban systems are developing in a mutually supportive manner. The standard formula, however, combines similarity between subsystem scores with their average level. This article evaluates those two components against the following external outcome: municipal environmental services. A city panel for China in 2002–2024 combines broadband and mobile adoption, urban road provision, licensed internet data-center records, and seven indicators of water, gas, drainage, sewage, waste, and urban greening. The preferred sample contains 6094 observations for 275 cities in 28 provinces. We estimate city fixed-effect models with province-by-year fixed effects and report province-clustered, two-way-clustered, and 9999-repetition wild-cluster-bootstrap inference. In the baseline rank-based construction, a one-standard-deviation increase in relative digital-transport alignment is associated with a 0.046-standard-deviation increase in the environmental-service index (wild-bootstrap p = 0.042), whereas the portfolio-level coefficient is 0.191 (p < 0.001). The alignment estimate is concentrated in water and gas access and is not robust to complete-component outcomes, PCA or entropy weighting, logarithmic standardization, road density, or lags beyond one year. Portfolio level remains positive across these tests, although lead and reverse-direction estimates preclude causal interpretation. The findings show why infrastructure scale, relative configuration, and realized service outcomes should be monitored separately. For SDGs 9 and 11, city governments should target documented service bottlenecks and operating capacity rather than maximize a composite coordination score. Full article

Liver fibrosis staging plays a key role in the prognosis and management of chronic liver disease. Liver biopsy remains the reference standard for fibrosis assessment but is limited by its invasiveness and risk of complications, while magnetic resonance elastography, though also considered a gold standard, is constrained by cost and limited availability. Ultrasound-based elastography techniques—vibration-controlled transient elastography (VCTE), point shear wave elastography (pSWE), and two-dimensional shear wave elastography (2D SWE)—have emerged as accessible non-invasive alternatives. This narrative review aimed to summarize the principles, diagnostic performance, advantages, and limitations of these three techniques across a range of etiologies. A comprehensive literature search was conducted across Scopus, PubMed, Embase, CINAHL, the Cochrane Library, Informit, and the JBI Database of Systematic Reviews and Implementation Reports, covering January 2015 to February 2026. Search terms included “vibration-controlled transient elastography”, “point shear wave elastography”, “two-dimensional shear wave elastography”, “liver stiffness measurement”, “non-invasive assessment” and “chronic liver disease”. International guidelines, systematic reviews and meta-analyses, large observational cohort studies, and narrative reviews were included in the synthesis. VCTE, pSWE, and 2D SWE all demonstrated good diagnostic performance for detecting advanced fibrosis and cirrhosis across multiple etiologies. VCTE was the most extensively validated technique, with standardized cut-offs endorsed by major international guidelines. pSWE and 2D SWE showed comparable diagnostic accuracy and can be integrated into conventional ultrasound systems, enabling simultaneous structural and stiffness assessment, although validated cut-off values for these two techniques are not yet established in current guidelines, and absolute stiffness values are not directly interchangeable across techniques, manufacturers, or software versions. Obesity, inflammation, steatosis and recent food intake were identified as factors affecting measurement accuracy across all three techniques. Ultrasound-based elastography techniques offer effective, non-invasive alternatives to liver biopsy for fibrosis assessment. VCTE remains the most validated option despite cost and availability constraints, while pSWE and 2D SWE offer comparable accuracy with practical integration advantages. Future research should focus on standardizing cut-off values, addressing confounding factors, and combining elastography with biomarkers and AI-driven models. Full article

Temporary sidewalk disruptions caused by construction, maintenance, or other obstructions can significantly affect pedestrian mobility, particularly for those with mobility impairments. Although accessibility standards and universal design principles exist, temporary pedestrian detours do not always provide safe, continuous, and accessible routes, creating barriers to independent mobility. This study examines how municipalities plan, approve, and monitor sidewalk detours, focusing on accessibility. A qualitative descriptive approach was used, combining a review of guidance documents and grey literature with semi-structured interviews with seven professionals from five municipalities and one transportation organization in Québec, Canada (April–August 2024). Thematic analysis allowed the identification of four main themes concerning the detour design process, the criteria used, accessibility-related challenges, and the use of geospatial technology. The findings show that pedestrian safety and continuity of movement are central concerns, while accessibility is considered unevenly across organizations. Organizations in larger cities described more detailed accessibility-related criteria, such as width, slope, surface condition, curb ramps, and corridor delineation, but even this level of detail did not translate into consistent application. They indicated that applying these criteria is sometimes hindered by existing infrastructure, limited space, time constraints, variable guidance application, and a lack of decision-support tools. These findings provide an empirical basis for understanding current detour design practice and for developing geospatial decision-support tools for accessible detour planning. Full article

Gender equality has become a fundamental indicator of constitutional democracy, effective governance, and the protection of human rights. This study examines the effectiveness of legal and institutional mechanisms for promoting gender equality through a comparative analysis of selected European jurisdictions and recent legal reforms in Uzbekistan. Comparative legal, doctrinal, systemic, statistical, and socio-legal methods were employed, complemented by original empirical evidence from an anonymous sociological survey. The findings demonstrate that the effectiveness of gender-equality reforms depends on the interaction between the scope and enforceability of legal guarantees, institutional capacity and accountability, socio-economic conditions affecting equality of opportunity and outcomes, and the accessibility and effectiveness of protection against discrimination, harassment, and gender-based violence. Although Uzbekistan has introduced significant legislative reforms, substantive gender equality remains constrained by persistent gender stereotypes, unequal career opportunities, and limited public awareness of available legal protections. The study proposes an integrated legal-institutional framework that combines comparative legal analysis with empirical socio-legal evidence to assess the implementation of gender equality reforms in transitional legal systems. It concludes that strengthening institutional accountability, introducing systematic gender monitoring and audits, enhancing transparency in labor relations, and ensuring effective enforcement of existing legal guarantees are essential for translating formal legal equality into substantive equality in accordance with international human rights standards. Full article

Higher education institutions operate complex digital environments that combine administrative services, research infrastructures, learning platforms, identity systems, and heterogeneous departmental IT. In the European Union, the NIS2 Directive increases the need for structured cybersecurity governance, while ISO/IEC 27001:2022 provides a mature information security management system standard that can support implementation. This paper proposes a design science artefact for aligning NIS2 obligations with ISO/IEC 27001:2022 clauses and Annex A controls in the context of higher education institutions. The framework organizes cybersecurity governance, asset and service scoping, risk management, incident handling, business continuity, supplier and cloud dependencies, access control, awareness, monitoring, and continual improvement into a staged maturity model. The artefact is instantiated for a Romanian public university context and assessed through internal traceability analysis, including mappings between NIS2 Articles 20, 21, and 23, Romanian NIS2 transposition requirements, and ISO/IEC 27001:2022 control areas. The institutional illustration identifies candidate assessment domains and evidence requirements but does not assign maturity levels because the internal records required by the scoring protocol were unavailable; it therefore does not constitute an audit, verified institutional measurement, or empirical validation. The contribution is therefore a structured and reusable compliance design artefact, together with a transparent mapping method that can support future expert validation, institutional pilots, and audit-oriented refinement. Full article

Destinations increasingly shift from promotional branding toward holistic and inclusive identity strategies, where cultural heritage operates as both an anchor of local distinctiveness and a catalyst for creative place-making. This study presents a mixed-methods Triple Bottom Line (TBL) assessment of four Greek cultural heritage institutions, a regional theatre, a municipal gallery, a university-affiliated foundation, and a regional film festival, to examine how governance structures, resource availability, and organisational capacity shape environmental, social, and economic sustainability performance. Through document analysis and semi-structured interviews, the research identifies eleven recurring thematic variables across the TBL dimensions and systematically compares their implementation across distinct governance models. Findings show that social sustainability, particularly accessibility, education, and community engagement, constitutes a structurally universal baseline across all institutions, regardless of governance type or resource level. In contrast, environmental and economic performance diverge sharply according to governance model, building ownership, and access to capital. As cultural institutions function as experiential landmarks within cultural and creative tourism, their inclusive practices enhance community wellbeing while co-producing destination identity as socially responsible and culturally authentic. The study concludes with targeted policy recommendations on reporting standards, capacity building, and structural constraints, offering transferable insights for creative place-making and sustainable destination branding in Greece and other Mediterranean contexts. Full article