Search Results (103,824)

Large-scale administrative hospital discharge data is a key resource for secondary health systems research, yet reuse is constrained by barriers of access, quality, interoperability, and semantic comparability. This paper presents and validates a reproducible, declarative, loss-aware harmonization framework for public discharge data that avoids full migration to a comprehensive common data model. The framework comprises a lightweight 14-field canonical model, versioned JSON crosswalks, a shared execution engine, a resilient file reader, schema validation, idempotency tests, value-domain checks, and an information-loss map. It was evaluated on public record-level discharge data from five jurisdictions on three continents (Korea, Brazil, Mexico, Chile, and New York State), comprising 561,966,231 harmonized records from 2001 to 2025. Validation demonstrated conformance to the declared source profiles for 82 of 99 files and full canonical conformance for 39, idempotency across all 99 files, 99.99% conformance with permitted value domains under an explicitly stated aggregation, and detection of source-level defects such as truncated files, malformed rows, and completeness anomalies. A marker-condition query for ischemic stroke (ICD-10 I63) showed that a single case definition executes consistently on the four sources retaining raw ICD-10 codes. The results show that, for heterogeneous administrative data, the key value lies not in scale alone but in the auditability of transformations, explicit loss documentation, and reproducibility of the harmonization process. Full article

Climate change is increasing the frequency of heat stress events in dairy farming, adversely affecting milk production, milk composition, cow behavior, and animal health. However, many previous studies relied on distant weather-station data and low-frequency milk recording systems, limiting the assessment of short-term and delayed heat stress responses. Therefore, the aim of this study was to combine dense longitudinal data from automatic milking systems (AMS) with continuously recorded on-farm meteorological measurements to investigate the immediate and lagged effects of heat stress on Holstein dairy cows. The study included 386,587 AMS visit records from 790 cows on three commercial dairy farms in Germany, corresponding to up to 127,310 cow-day records collected between August 2022 and August 2025. Temperature–humidity index (THI) values were calculated based on dense on-farm temperature and relative humidity records and were evaluated for multiple lag periods prior to AMS recordings. Linear mixed models were applied to infer the effects of THI on production, physiological, behavioral, and milking process traits. Increasing THI was associated with reduced daily milk yield, altered milk fat and protein percentages, decreased AMS visit frequency, prolonged milking intervals, and increased milk temperature. For contemporaneous THI, an increase from THI 50 to THI 70 corresponded to model-estimated declines of −0.86 kg in daily milk yield, −0.20% in milk fat content and −0.06% in milk protein content, −0.12 daily AMS visits, and +1.14 °C in milk temperature. The strongest associations were generally observed for prompt and short-term lagged THI windows. In contrast, longer lag periods were associated with weaker and less distinct trait responses. Rather than merely confirming the established decline in milk yield under heat stress, the integrated and temporally resolved analysis revealed trait-specific response patterns across production, behavioral, physiological, health-related, and milking-process traits. In particular, milk temperature and voluntary AMS attendance showed pronounced associations with contemporaneous and short-term THI, demonstrating the value of combining AMS-derived phenotypes with high-resolution on-farm climate data for heat stress monitoring. Full article

Career decision-making difficulties (CDDs) among female undergraduates are associated with both individual psychological processes and culturally embedded social contexts. This study examined the associations among career anxiety, career decision-making self-efficacy (CDSE), perceived frequency of parental career support, and CDD among female undergraduates from four purposively selected non-elite universities in Jiangsu Province, China. Guided by Social Cognitive Career Theory (SCCT), this explanatory sequential mixed-methods study combined quantitative and qualitative approaches. Quantitative data from 407 participants were analyzed using SPSS 27.0, AMOS 26.0, and PROCESS macro 4.1, including confirmatory factor analysis and conditional process analysis with 5000 bootstrap samples, followed by thematic analysis of semi-structured interviews with 12 participants using NVivo 12. Career anxiety was positively associated with CDD and negatively associated with CDSE, with CDSE partially accounting for the association between anxiety and decision difficulties. The anxiety–CDD association was stronger among students reporting higher frequencies of parental career support behaviors. Qualitative findings suggested that perceived support quality, autonomy support, and contextual fit shaped how parental involvement was experienced. These findings suggest that parental career support should be understood not only in terms of behavioral frequency but also in relation to how involvement is experienced under conditions of heightened career anxiety. Longitudinal, dyadic, and culturally diverse research is needed. Full article

Urban streets are critical public spaces that support residents’ daily psychological recovery, and their landscape quality is directly related to pedestrians’ physical and mental well-being. In the rapid urbanization process, numerous urban streets have exhibited problems such as excessive building density, cluttered visual interfaces, a lack of natural elements, and an absence of regional characteristics, leading to a continuous decline in the psychological restorative capacity of street spaces and failure to meet residents’ demands for a healthy urban environment. Existing research mostly employs qualitative assessment methods to evaluate walking experiences and psychological restoration levels of street environments, lacking high-precision, pixel-level quantification of street landscape elements and rarely incorporating regional cultural elements into the analytical framework of restorative environments. This study takes Foshan, a famous historical and cultural city in China, as the research object, and selects five typical streets in the main urban area, including comprehensive streets, living streets, landscape streets, commercial streets, and historical–cultural streets, to construct a technical route of “data collection–element quantification–model construction–effect analysis.” Leveraging the pre-trained Mask2Former semantic segmentation model and pedestrian-perspective street-view images (SVIs), combined with field research, the study quantifies 22 street landscape elements across five dimensions: environment, transportation, social interaction, facilities, and culture. Through PCA principal component analysis and K-means clustering, 20 typical photos were objectively sampled, and public psychological evaluations were conducted using the Perceived Restorativeness Scale (PRS). A stepwise multiple linear regression model was then employed to construct an exploratory explanatory model for street psychological restoration, identifying key influencing factors and their effect intensities. The results indicate the following: (1) Environmental and cultural elements are the core characteristics associated with pedestrians’ psychological restoration, whereas transportation, social, and facility elements are correlated only with certain restoration dimensions and show no significant association with the overall psychological restoration level. (2) Among the 22 element indicators, the Green View Index showed the strongest positive association with psychological restoration (β = 0.681, p < 0.001); historical memory markers and the Blue View Index also exhibited significant positive associations. (3) By integrating the elements associated with pedestrians’ psychological restoration and their association strengths, an exploratory explanatory model of the psychological restoration benefits of urban street landscapes was constructed, with an adjusted coefficient of determination of 69.8%, accounting for 69.8% of the variation in street psychological restoration levels. The findings establish an exploratory analytical framework and furnish empirical evidence for healthy city planning and street renewal in similar historical and cultural cities. Full article

The development of sustainable coatings that combine reprocessability with active functionalities remains a central challenge for the composites sector. In this work, a healable, electrically conductive coating was formulated using epoxidized castor oil (ECO) as a bio-based matrix, dibutyl phosphate (DBP) as a transesterification catalyst, and short recycled carbon fibres (RCFs, 2 mm in length) as a conductive filler at loadings of 10 and 20 phr. Formulations were UV-cured via cationic photopolymerization and characterized across the full liquid-to-solid processing chain. FT-IR and photo-DSC showed that increasing RCF content progressively reduced curing rate and conversion, an effect attributed to light scattering/absorption by the fibres and restricted chain mobility, although gel content remained above 98% in all cases. DMTA showed that RCF did significantly affect the glass transition temperature but markedly increased the rubbery storage modulus and apparent crosslink density, consistent with a physical reinforcement mechanism. Stress relaxation tests confirmed the dynamic bond exchange behaviour in all formulations, with the apparent activation energy decreasing from 112 kJ/mol for the neat resin to 33–34 kJ/mol upon RCF incorporation. This significant reduction suggests that the presence of RCF facilitates the bond-exchange process, potentially through interfacial interactions between the polymer network and the fibre surface. However, the specific molecular mechanism responsible for this effect cannot be established from the present data. Electrical conductivity peaked at 10 phr RCF (3.6 × 10⁻³ S/m), enabling measurable Joule heating, while the 20 phr formulation showed reduced conductivity linked to voids and lower conversion. Thermally triggered healing at 120 °C for 6 h restored mechanical integrity, which is higher than reference values, demonstrating the coating’s capacity for repeated repair through its dynamic covalent network. Full article

Against the backdrop of high-density Asian cities shifting from production- to consumption-oriented spaces, commercial pedestrian streets are key to urban public life and vitality. This study selects six major commercial pedestrian streets in Chongqing and employs natural language processing (NLP) and importance–performance analysis (IPA) methods to construct a four-dimensional evaluation framework (spatial, commercial, cultural, location/facility). It analyzes public perception and experience based on user-generated content (UGC). Findings show that: (1) Significant differences across dimensions form three development types: cultural identity, functional hub, and distinctive growth, reflecting structural bottlenecks in transitioning from single- to multi-functional spaces. (2) IPA identifies “business formats,” “cultural activities,” and “consumption experience” as priorities for improvement, while “commercial atmosphere” and “transportation conditions” are current strengths to maintain. (3) Sentiment analysis reveals that negative perceptions focus on basic functions and sense of place, whereas positive sentiments relate to cultural expression and spatial esthetics, highlighting the role of cultural soft power and visual design in street appeal. This study reveals public perception patterns via big data analysis, offering empirical support for the refined renewal, cultural preservation, and sustainable management of commercial pedestrian streets in high-density Asian cities. Full article

Through-going structures are widely distributed in rock masses of underground engineering, and their dip angles act as the core factor affecting the stress field and mechanical response of surrounding rock. To reveal the mechanical mechanism of rock masses containing through-going structures with different dip angles, this study adopts a combined method of theoretical derivation, indoor model testing and numerical simulation. Firstly, a plane strain mechanical model is established to classify Tectonically-induced Stress, Residual Gravitational Stress and engineering-induced stress, and the theoretical formulas for stress components, stress residual coefficient and stress deflection angle are derived. Secondly, rock-like specimens with through-going structures of various dip angles are prepared and biaxial compression tests are carried out to monitor mechanical parameters such as surrounding rock strain and peak strength. Finally, a large-scale numerical model is built by FLAC2D (version 7.0) software to simulate the whole process of stress equilibrium and excavation unloading of rock mass under a normal stress of 20 MPa. Then the data of principal stress, stress components, stress residual coefficient and deflection angle under different dip angles are extracted. The results show that the dip angle of through-going structure exerts a prominent regulatory effect on the rock mass stress field. With the increase of the dip angle, the Tectonically-induced Stress decreases continuously while the Residual Gravitational Stress rises gradually. The variation trend of stress deflection angle is highly consistent with structural dip angle, and the influence of Residual Gravitational Stress on deflection angle is limited. Due to the differences in loading modes and model sizes between indoor tests and numerical simulations, the evolution laws of stress residual coefficient show opposite trends, but both results verify the dominant effect of structural dip angle. Combined with theoretical, experimental and numerical results, the proposed theoretical system can effectively describe the stress evolution law of rock masses with through-going structures, which provides theoretical reference and technical support for the stability analysis of surrounding rock in similar underground engineering. Full article

With the advancement of healthy city development and community renewal practices, the influence of perceived community environmental quality on residents’ psychological well-being has attracted increasing attention. Previous research has shown that the built environment is closely related to residents’ well-being; however, most studies have focused on objective spatial elements or facility provision and have paid insufficient attention to the mechanisms through which subjective environmental perceptions operate in the process by which the environment affects psychological well-being. From the perspective of Homo Urbanicus theory, this study takes 36 communities in Yangpu District, Shanghai, as cases and uses data from 882 valid questionnaires. Structural equation modeling is employed to examine the relationships among perceived community environmental quality, perceived environmental restorativeness, and residents’ psychological well-being, and to further explore age-related patterns among young-old, middle-old, and oldest-old groups. The results show that perceived community environmental quality has a significant positive effect on residents’ psychological well-being and produces a significant indirect effect through perceived environmental restorativeness. Exploratory age-stratified analyses further suggested different pathway patterns among the young-old, middle-old, and oldest-old groups. On this basis, the study further proposes a four-quadrant model of spatial contact opportunities and a five-category accessibility classification and accordingly develops community environment optimization strategies for older adults of different ages. The findings provide a theoretical basis and practical reference for healthy-community development and age-friendly community renewal. Full article

Background: Medication non-adherence is a major driver of poor therapeutic outcomes, and computer vision methods that observe facial movements offer a non-contact route to verifying oral medication intake. Objective: To map and synthesize the existing literature on computer vision techniques applicable to the monitoring of medication intake, focusing on face tracking methods, oral movement detection and deglutition recognition, and to assess their potential in supporting automatic medication adherence verification systems. Eligibility criteria: Peer-reviewed articles, conference papers, patents, theses and preprints published from 2016 onward, written in English or Portuguese, applying facial landmark tracking or face analysis to ingestion-related movements (mouth opening, hand-to-mouth motion, pill placement, mastication or deglutition); studies confined to object/pill detection without facial analysis, or to general food intake without transferability to medication, were excluded. Sources of evidence: A systematic screening of 362 initial records was conducted across six main electronic databases and repositories: Google Scholar, PubMed, ScienceDirect, arXiv, IEEE Xplore, and Espacenet. Charting methods: Data were charted with a standardized, pilot-tested extraction form capturing bibliographic attributes, dataset type, experimental environment, face tracking approach, tools/models, and target movements; extraction was performed by a single reviewer. Following the screening process, a final selection of 34 relevant studies was included for detailed analysis and mapping. Results: Among the 34 included studies, 14 employ facial landmarks, 11 utilize temporal deep learning models, 6 apply facial action models and 3 rely on hybrid multimodal approaches that combine video analysis, object detection and temporal modeling. Tasks such as detecting mouth opening or tracking pill-to-mouth movement show promising results, while accurately detecting deglutition remains a technical challenge due to high sensitivity and individual variability. Limitations: The majority of the literature relies on private or institutional datasets (31 studies) and operates in controlled laboratory environments (22 studies); only 2 studies evaluated their methods via independent external datasets, which limits the generalization of current solutions to real-world telemonitoring scenarios. Conclusions: The literature indicates the existence of solid technical foundations for developing automated medication intake verification systems. To advance the field toward practical deployment, future research must address the need for more diverse datasets, real-world validation and more robust, adaptable modeling frameworks. Full article

Insulator types and materials vary substantially across power system inspection scenarios, while damage defects occur infrequently; consequently, defect images that match a target insulator type and operating environment are often difficult to obtain. Existing open-source insulator image datasets provide limited coverage of equipment types, scene backgrounds, and defect morphologies. Their direct use for detector training may therefore cause domain mismatch and poor generalization. To address these limitations, this study proposes a scene-domain-adaptive sample expansion method for few-shot damaged-insulator detection. The method adapts a general-purpose pretrained diffusion model to the insulator inspection domain and incorporates three-dimensional (3D) structural constraints to generate targeted samples of damaged insulators. First, low-rank adaptation (LoRA) is used for scene-domain adaptation, enabling the generation model to learn the characteristic geometry, appearance, and material properties of insulators. Second, a 3D model of the target insulator is constructed, and physical damage simulation and edge extraction are applied to obtain geometric guidance maps containing shed boundaries and fracture contours. These maps constrain the locations and shapes of the generated defects. Finally, the geometric guidance is injected into the diffusion process to synthesize damaged-insulator images, which are combined with limited real samples to train detectors for damaged-insulator instances, which were evaluated exclusively on real validation images. Experimental results show that adding a moderate number of generated samples enriches the scarce defect features in the real dataset and improves detector performance. In the mixture-ratio experiment using YOLOv8, mAP@0.5 increased by 8.2 percentage points. Additional experiments with multiple detectors yielded performance gains of varying magnitudes, demonstrating that the generated samples provide an effective supplement to limited, real-world data. The proposed method alleviates the scarcity of insulator defect samples and offers a practical data-augmentation strategy for intelligent inspection of power equipment. Full article

This paper presents a data-driven run-to-run (R2R) controller for manufacturing processes subject to process drift. The proposed approach combines the exponentially weighted moving average (EWMA) method with the K-nearest neighbors (KNN) algorithm to determine process recipe adjustments. Control actions are derived entirely from historical process output data. In the hybrid controller, the EWMA estimator recursively updates the accumulated process drift using historical process errors and generates the corresponding recipe compensation. The KNN-based controller, in turn, identifies the K nearest neighbors in the historical feature database based on the current process error and determines the compensation action from the associated error–compensation relationships. The proposed controller was evaluated through simulations of a chemical mechanical planarization (CMP) process, with removal rate as the control objective. Under linear process drift with random white-noise disturbances, the proposed controller maintained the removal rate close to the target value, with a maximum overshoot of 4.40%, and satisfied the settling criterion from the beginning of the control process. Its performance was superior to that of the conventional EWMA controller and the standalone KNN controller. The EWMA controller exhibited several oscillations during the initial runs, with a maximum overshoot of 15.17%. Although the KNN controller satisfied the settling criterion from the beginning of the control process and produced a relatively small maximum overshoot of 3.10%, it did not consistently maintain the removal rate near the target value. Under nonlinear process drift with random disturbances, the proposed controller also maintained the process output near the target value with satisfactory stability, provided that the process drift remained within a bounded range. The controller also has a simple and intuitive implementation, which may facilitate practical industrial application. Full article

This study investigates the impact of critical raw material mining and processing on surface water quality within a representative catchment area, using the Luda Yana River Basin in Southern Bulgaria as a case study. Water quality was evaluated using the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI), based on data collected from five monitoring stations. The analysis focused on key heavy metals, including Cu, Zn, Pb, Cd, Fe, Mn, Ni, and As, reflecting the influence of both active and historical mining activities in the region. Index values were calculated for the period 2008–2024 and revealed considerable temporal variability and pronounced spatial differences in water quality along the river course. This study provides one of the first long-term integrated assessments of heavy-metal-related water quality in a mining-impacted river basin in Bulgaria using the CCME WQI framework and offers new evidence on the cumulative effects of historical and ongoing mining activities on surface waters. The calculated CCME WQI values ranged from very low levels indicating poor conditions to moderate values corresponding to marginal and, occasionally, fair conditions. Overall, the predominant water quality categories were “poor” and “marginal.” The results demonstrate that the waters of the studied river basin remain below the thresholds for “fair” physicochemical status as defined by the European Water Framework Directive (2000/60/EC) and the corresponding Bulgarian legislation, including Regulation No. H-4/2012 on surface water characterization and the 2010 Ordinance on environmental quality standards for priority substances and certain pollutants. The findings highlight the persistent anthropogenic pressure exerted on the river system and emphasize the need for improved water management strategies. The study further underlines the importance of integrating environmental protection measures into the exploitation of critical raw materials in order to balance economic development with the sustainable management of water resources. Full article

The design of regular microreliefs requires process and tool variables that satisfy surface-coverage, lubricant-retention, and residual-depth requirements. This theoretical and computational study formulates the task as a two-objective inverse problem for rigid-ball burnishing of external cylinders and compliant-roller burnishing of internal tubes. The analytical chain maps force or imposed displacement and relative curvature to indentation, elastic recovery, periodic cavity overlap, relative dimple area $F_n$, and specific oil capacity q. A full-factorial grid generates a discrete catalog of process settings and provides the initial seeds for continuous refinement by the non-dominated sorting genetic algorithm II (NSGA-II). Under a common budget of 648 forward evaluations, the two-phase method achieved $95.9\%$ of the median target-centered hypervolume of pure NSGA-II and produced a higher hypervolume than Latin hypercube sampling (LHS) in eight of ten paired runs. A comparison calibrated at the 200 N data point yielded a held-out axial-width error of $-6.5\%$ at 400 N, consistent with the predicted force–width trend under the stated comparison conditions. Morris screening identified imposed displacement as the most influential variable for both objectives, with crown-base thickness also strongly influencing q. The resulting candidates are illustrative model-based solutions that satisfy the stated constraints and lie within the reference machine-coordinate envelope; process-specific calibration and experimental assessment are required before quantitative implementation. Full article

Adapting psychological interventions from High-Income Countries (HICs) to Low- and Middle-Income Countries (LMICs) is often needed because developing new treatments requires significant resources. Contextual adaptation improves acceptability, practicality, and effectiveness in diverse settings. However, few studies clearly describe the frameworks guiding these adaptations. Our review examined the literature on conceptual and procedural frameworks for culturally adapting psychological interventions aimed at youth depression and anxiety and identified common challenges. We searched several databases for studies that had culturally adapted psychological treatments in LMICs. We used the Reporting Cultural Adaptation in Psychological Trials (RECAPT) framework to gather data and guide the thematic analysis. We reviewed 25 studies; most (n = 23) reported formative work but lacked detailed, step-by-step descriptions of the adaptation processes. When frameworks were described, processes were often unclear, making it difficult to determine what constitutes adaptation and how to implement it. The review underscores the need for more structured, detailed reporting of adaptation frameworks. Clearer documentation is vital for better understanding and successful implementation. Based on these findings, we suggest ways to improve reporting practices for the cultural adaptation of psychological interventions. We recommend (1) explicit reporting of step-by-step adaptation processes using established frameworks and (2) systematic documentation of cultural and contextual modifications based on identified conceptual and process frameworks using reporting guidelines such as RECAPT. Full article

Chronic kidney disease (CKD) is sustained by a network of sterile inflammation, oxidative and metabolic stress, uremic toxin retention, gut barrier dysfunction, and maladaptive immune activation. These processes contribute to kidney fibrosis, cardiovascular injury, wasting, and excess mortality, but inflammatory biomarkers do not by themselves establish therapeutic causality. This narrative review integrates mechanistic and therapeutic evidence using an explicit three-layer translational hierarchy. Renin–angiotensin system inhibitors, sodium–glucose cotransporter-2 inhibitors, finerenone, and glucagon-like peptide-1 receptor agonists improve cardiorenal outcomes and have plausible anti-inflammatory actions, although inflammatory mediation remains unproven. Interleukin-1 blockade provides cardiovascular proof of principle and small dialysis feasibility data. Interleukin-6 ligand inhibition produces marked human target engagement; however, headline results from the completed phase 3 ZEUS trial showed no reduction in three-point major adverse cardiovascular events with ziltivekimab despite biomarker suppression, while serious infections were more frequent. POSIBIL6ESKD continues to test clazakizumab in inflamed dialysis patients. Direct NLRP3 inhibition has entered early human CKD development, whereas senescence-directed and microbiota-based approaches remain less mature. Future progress requires inflammatory endotyping, repeated biomarker assessment, mechanistically aligned outcomes, and rigorous infection surveillance. ZEUS underscores that pathway suppression must deliver clinical benefit beyond contemporary standard therapy. Full article