Search Results (1,816)

This paper introduces a comparative analysis of urban housing conflicts across eight major Canadian cities, Toronto, Vancouver, Québec, Ottawa, Calgary, Edmonton, St. John’s, and Halifax, over a 20-year period. Using Large Language Models (LLMs), we implement a structured workflow to extract, classify, and organize more than one thousand conflict instances from diverse textual sources, including municipal reports, media archives, and non-governmental organization publications. The methodological contribution lies in demonstrating how an LLM-assisted pipeline, combining schema-based extraction, prompt perturbation, and a two-phase calibration procedure, can generate structured, multi-city conflict datasets while addressing challenges such as output homogenization and sensitivity to prompt design. The findings highlight both shared national tendencies and city-specific configurations with post-2020 conflicts intensifying. Overall, the study proposes a transparent workflow for applying LLMs to conflict-related text analysis and offers an exploratory overview of the spatial, temporal, and semantic regularities of housing conflicts in Canadian cities. Full article

Effective perioperative hemostasis in pediatric cardiac surgery depends not only on accurate diagnostics and targeted transfusion strategies but also on a clear and consistent definition of postoperative bleeding. Despite the clinical importance of bleeding in neonates and children undergoing cardiopulmonary bypass, bleeding remains variably defined across institutions, registries, and clinical trials. This heterogeneity complicates bedside decision-making, limits benchmarking, and weakens the interpretation of interventional studies. In this review, we examine postoperative bleeding definitions as a foundational component of hemostatic management in pediatric cardiac surgery. We summarize commonly used adult bleeding definitions and highlight their variability and limited applicability to neonatal and infant physiology. We review current pediatric approaches, including chest tube output-based thresholds and multidimensional severity scales that incorporate clinical impact and physiologic consequences, while avoiding reliance on transfusion or procedural interventions alone. We discuss the limitations of intervention-driven criteria, the challenges of quantifying blood loss, and the influence of developmental hemostasis and surgical complexity. We also explore structural barriers within electronic medical records that impede standardized data capture and consider harmonization efforts in ECMO populations as a potential model. By outlining the consequences of definitional heterogeneity and proposing principles for standardization, this manuscript aims to support more consistent hemostatic care, meaningful benchmarking, and stronger multicenter research in pediatric cardiac surgery. We recommend that future multistakeholder consensus efforts develop a multidimensional, developmentally calibrated bleeding definition that integrates quantitative blood loss, physiologic impact, and clinical consequences while clearly separating bleeding severity from the interventions used to treat it. Full article

Multivariate calibration methods have proven to be helpful in interpreting complex spectral data, particularly in the simultaneous analysis of pharmaceutical mixtures. In this study, three chemometric-assisted spectrophotometric methods were developed and validated for the simultaneous assessment of flunixin meglumine (FM) and florfenicol (FF), namely, multivariate curve resolution–alternating least squares (MCR-ALS), artificial neural networks (ANNs), and partial least squares (PLS). These methods were successfully utilized to address the significant spectral overlap between FM and FF in their combined dose form, enabling simultaneous quantification without prior chromatographic separation. Statistical analysis was conducted to compare the performance of the proposed methods to that of a published HPLC method, and the results showed no significant variation in trueness or precision. The proposed methods were validated according to ICH guidelines, showing high sensitivity, low LOD and LOQ, and excellent precision (%RSD < 2.0%). Furthermore, they were evaluated for environmental sustainability using the analytical greenness (AGREE) metric and the complex modified green analytical procedure index (Complex MoGAPI), which provided a greenness score of 0.7 and a total sustainability score of 80. These results demonstrate the applicability of the proposed chemometric methods as straightforward, effective, and ecologically beneficial substitutes for regular quality control analysis. Full article

Background/Objectives: The Global Lung Initiative (GLI) 2022 race-neutral spirometry reference equations were introduced to improve interpretability across populations; however, their performance in Middle Eastern adolescents remains insufficiently validated. This study evaluated the applicability of GLI-2022 among healthy Jordanian adolescents. Methods: Healthy adolescents were recruited from secondary schools across multiple Jordanian cities (July–November 2025). Spirometry was performed according to ATS/ERS standards using a single device and standardized procedures. GLI-2022 predicted values and z-scores were derived for forced expiratory volume in one second (FEV₁), forced vital capacity (FVC), and FEV₁/FVC. Calibration was assessed using mean (SD) z-scores and the proportion below the lower limit of normal (LLN; z < −1.645). Agreement between measured and predicted values was examined using Bland–Altman methods. LLN-based pattern classifications were compared with those obtained using the local reference equation and GLI-2012. Results: A total of 921 adolescents (482 males, 439 females; mean age 15.7–16.0 years) were included. GLI-2022 produced positive mean z-scores for FEV1 (0.51–0.73) and FVC (0.51–0.69), with low proportions below LLN for both indices (<2% in each sex), indicating underestimation of predicted lung volumes. Exact binomial testing confirmed that the observed proportions below LLN for FEV1 and FVC were significantly lower than the expected 5% in both sexes (all p < 0.001). The FEV1/FVC ratio showed smaller deviations (mean z 0.07–0.19), with 4.1% of females and 5.8% of males below LLN, and these proportions did not differ significantly from 5% (female p = 0.444; male p = 0.402). Mean observed-minus-predicted biases for FEV1 were +0.185 L in females and +0.306 L in males, and for FVC were +0.224 L and +0.351 L, respectively; FEV1/FVC bias was −0.15 percentage points in females and +0.60 percentage points in males. LLN-based pattern classification showed 98.7% overall agreement with the local equation and 99.7% with GLI-2012; concordance for obstructive and possible restrictive patterns was 93.5% and 100.0%, respectively. Conclusions: In healthy Jordanian adolescents, GLI-2022 appears to underestimate predicted FEV₁ and FVC, yielding upward-shifted z-scores and fewer volume indices below LLN, while the ratio is less affected. Although LLN-based pattern classification was largely preserved, population-specific validation remains necessary before routine clinical adoption of GLI-2022 in Jordanian adolescents; extrapolation to other Middle Eastern adolescent populations should await additional regional validation. Full article

Science universities strive to offer efficient lab training to their students and at the same time secure their safety and minimize the damages to the lab equipment. Thus, the development of distance learning tools for students to be trained virtually and safely in using the various lab instruments and performing experiments is necessary. Since the students are evaluated for their performance at the on-site labs, the assessment at the virtual labs is also needed and consequently, an embedded assessment mechanism for the evaluation of the user’s performance in the virtual lab is a necessary feature. For the assessment mechanism to be reliable and devoid of the designer’s bias, though, it may need calibration with Machine Learning. Hellenic Open University has developed its own virtual biology laboratory, Onlabs, which simulates its on-site one for its students to be trained and evaluated at. Considering the evaluation of the user’s performance in Onlabs, it is made with respect to particular experiments and is based on an embedded scoring algorithm. The latter is two-fold, measuring the extent to which the necessary steps have been made and the extent to which those steps were made in the correct order. Within the context of the experimental procedure of microscoping, the scoring algorithm has been recalibrated with the use of various Machine Learning techniques. In this paper, we propose the design of a Reinforcement Learning variant and recalibration of the scoring measure concerning the steps order. The results suggest that under specific parameters and Reinforcement Learning methods, a more efficient scoring mechanism may be achieved. Full article

This article concerns the issue of contactless estimation of the complex electrical permittivity of masonry materials by means of a microwave technique in the frequency domain. The main aim of the study was to develop a method enabling the determination of the real part of relative permittivity and the electrical conductivity of ceramic building materials using microwave reflection measurements, as well as to assess the applicability of the proposed approach for moisture diagnostics in porous media. The research was performed using a reflection-mode measuring setup comprising a vector network analyser and a broadband horn antenna, while measurements were carried out in the frequency range from 1 to 6 GHz on samples of solid ceramic brick with six gravimetric moisture levels. A one-dimensional model of electromagnetic wave propagation in the material was developed, considering complex permittivity, impedance transformation, and a calibration procedure compensating for the influence of the antenna and free-space propagation. Based on the fitting of the magnitude and phase characteristics of the reflection coefficient, the electrical parameters of the tested samples were estimated. The results obtained showed an increase in both permittivity and conductivity with increasing moisture content and revealed very good agreement with the reference values determined using the time-domain method. It can be concluded that the frequency-domain microwave approach may be effectively applied for contactless and non-destructive diagnostics and estimation of the dielectric properties and moisture content in ceramic materials. Full article

Background: Venous catheter placement is the most common invasive procedure performed in hospitals. Despite their widespread use and importance in healthcare, these devices can cause complications such as catheter-associated bloodstream infections (CABSIs). Although several studies have investigated potential risk factors, including sociodemographic, medical history, and clinical variables, the results remain inconsistent and inconclusive. Objectives: The aim of this study was to identify independent risk factors for CABSIs and to develop and validate a predictive model for CABSIs in patients with midline catheters, centrally inserted central catheters (CICCs), and peripherally inserted central catheters (PICCs). Methods: We conducted an observational cohort follow-up study including hospitalized patients with a CICC, PICC, or midline catheter between January 2016 and March 2022. Devices were randomly assigned to derivation (n = 6036) and validation (n = 1549) cohorts. Candidate predictors with p < 0.25 in univariate analysis entered a multivariable logistic regression model, and final variables were selected by backward stepwise regression. Performance in the validation cohort was assessed by calibration and discrimination using the Hosmer–Lemeshow test and AUC. Results: The prevalence of CABSIs in the derivation cohort was 1.8%. Independent risk factors for CABSIs included tracheostomy, a history of bacteremia within 3 months before catheter placement, the presence of a synchronous central catheter, active oncohematological disease, and having received total parenteral nutrition (TPN). The presence of these five variables increased the probability of CABSIs to 42.1%. The final model demonstrated good predictive performance with an area under the curve (AUC) of 0.73 in the derivation cohort and 0.77 in the validation cohort. Decision curve analysis showed that the predictive model offered a greater net clinical benefit than the “treat-all” or “treat-none” strategies among threshold probabilities between 0.5% and 5%. Conclusions: The model can help identify high-risk patients, guide risk-based clinical decisions, reduce unnecessary catheter use, and support infection prevention and antimicrobial stewardship. Full article

Aircraft flyover measurements are used to record the acoustic pressure signals generated by large civil aircraft as they fly over a large-scale microphone array deployed on the ground, thereby obtaining the spatial distribution of aircraft airframe noise and providing technical support for aircraft noise reduction. Aircraft flyover measurements have been widely applied in the research and development of numerous large civil aircraft in Europe and North America since the 1990s. In recent years, aircraft flyover measurements have also been extensively adopted in China, particularly with the rapid development of COMAC C919 large civil aircraft. Computer vision techniques have also been applied to microphone position calibration and aircraft trajectory determination in measurements, which has effectively improved measurement efficiency and accuracy. This paper presents an integrated procedure for aircraft flyover measurements of large civil aircraft in China, including microphone array design, installation, and calibration, noise acquisition system setup and data acquisition, aircraft trajectory determination, and data processing. Full article

Fibrin gel, a protein-based polymer naturally generated during coagulation, has garnered attention in the biomedical field for applications such as fibrin glue, due to its specific physical and biological properties. Despite it, low mechanical strength and rapid degradation limited its utilization for biomedical applications. This study presents a reproducible protocol for the synthesis of pure fibrin hydrogels, aimed at achieving predictable structural properties through the precise calibration of fibrinogen and thrombin concentrations. By examining the mechanical and morphological characteristics, as well as the relationship between reagent concentrations and structural integrity, this research assesses impacts on swelling behavior, water absorption, and overall stability. Through a comprehensive analytical approach, we identified an optimal formulation, specifically 2.25 mg/mL fibrinogen and 1.375 U/mL thrombin, that effectively balances structural integrity with high cytocompatibility. The results demonstrate that this calibrated approach ensures high procedural reproducibility and a well-defined hydrogel architecture without the need for exogenous chemical cross-linkers. This work provides a robust methodological framework to overcome the common lack of reproducibility in fibrin-based hydrogel studies, positioning these materials as highly reliable candidates for advanced 3D in vitro models and biomedical applications. Full article

An edge-based and curve-based rule-driven nose detection framework is designed to improve the reliability of face detection. The designed framework combines quadratic curve fitting with a calibrated scoring mechanism that fuses geometric, photometric, and structural information into a unified model. These stages jointly enforce symmetry consistency, reliable tip position, and clear wing boundaries. Candidate face regions are first refined by skin filtering and ellipse validation, from which a mid-lower facial ROI is framed for nasal candidate extraction. We further incorporate eye/mouth hints (EyeMap/MouthMap) to restrict the region of interest (ROI) to the region below the eyes, above the mouth, and between the two eyes. When a mouth is detected, this ROI refinement supersedes the chrominance-red (Cr) channel trimming; otherwise, we fall back to the Cr channel horizontal projection to detect dominant mouth peaks and trim the lower-lip band, thereby suppressing lip interference. A multi-threshold Canny procedure with histogram projection is employed to collect multiple nose rectangles by selecting various vertical and horizontal peaks under three adaptive threshold scales. Within each rectangle, edge contours are quadratically fitted and categorized into U-shape (nasal base), N-shape (nostril rim), and C-shape (nasal wings), enabling rule-based selection of the base, wings, and nostrils. The fused features are then processed by a calibrated geometric–photometric–structural scoring module that uses YCbCr contrasts and red/black penalties to suppress lip and eye confounders. Experiments with diverse faces and lighting conditions show accurate and stable nose localization, with notably reliable wing fitting and nasal base detection, improving the accuracy of face detection. Full article

Since 2007, the porosity–to–cement relationship has been widely used as a unified parameter to predict mechanical strength, durability, expansion, and stiffness of stabilized soils. In this formulation, the volumetric binder content is adjusted by an internal exponent x, typically ranging between 0 and 1, to balance the relative contributions of porosity and cementation. Traditionally, the parameters of this relationship have been obtained using manual regression procedures. This study proposes an automated calibration methodology for the porosity–binder index, where the parameters A, B, and x are determined through an iterative optimization framework based on minimization of the sum of absolute errors (SAE) combined with a Monte Carlo search algorithm. The methodology is applied to a cement-stabilized clay blended with ground glass (GG), recycled gypsum (GY), and limestone residues (CLW). The predictive capability of the calibrated model is evaluated using unconfined compressive strength (q_u) and initial shear stiffness (Go) datasets. Two calibration strategies are considered: Calibration Process No. 1, based on CLW mixtures and q_u values only, and Calibration Process No. 2, incorporating all mixtures (CLW, GG, and GY) and both q_u and Go responses. The results indicate that Calibration Process No. 2 provides a more robust and physically consistent parameter set, yielding coefficients of determination of 0.9318 and 0.9412 for q_u and Go, respectively. The proposed algorithm-driven calibration framework improves predictive capability and provides a systematic approach for determining the parameters of the porosity–binder relationship. Full article

Reliable short-term air traffic forecasts are important for operational planning in national airspace systems. This study develops a transparent forecasting framework for Türkiye’s monthly aircraft movements using publicly available data from the General Directorate of State Airports Authority (DHMİ) for 2018–2025. Because DHMİ releases may follow cumulative within-year reporting, month-specific increments are reconstructed through within-year differencing and checked through simple audit procedures. The empirical analysis compares seasonal naïve, ETS, and a constrained SARIMA family under leakage-free evaluation, combining a strict 2025 holdout with expanding-window rolling-origin validation. Forecast performance is assessed using standard accuracy metrics and complemented by Diebold–Mariano comparisons, which are interpreted cautiously, given the short holdout length. To examine instability around the pandemic period, this study also reports structural-break and stability diagnostics as supportive evidence rather than definitive identification. Uncertainty is evaluated through backtested 80% and 95% prediction intervals, comparing nominal SARIMA intervals, parametric bootstrap, split conformal prediction, and adaptive conformal inference (ACI). The results show that SARIMA provides the strongest point-forecast performance among the benchmarked models, while adaptive conformal calibration offers a useful balance between empirical coverage and interval width under changing conditions. Overall, this study provides a reproducible and operationally interpretable baseline for national air traffic forecasting in Türkiye and a clear benchmark for future multivariate extensions. Full article

Bioeconomy policy requires timely, economy-wide evidence; however, two persistent measurement constraints remain: official input–output (IO) tables are published with time lags, novel start-up and novel prospective or hybrid bio-based activities are rarely identified as separate sectors in national accounts. This study develops an applied framework that combines IO nowcasting with an accounting-consistent sector-embedding procedure under limited data availability. Using Ireland’s national IO system and an existing bioeconomy IO framework as the accounting backbone, we update the 2015 table to 2022 through calibration to macroeconomic control totals, providing a timely structural baseline. We then introduce a transparent method for constructing new bioeconomy sectors based on dominant input shares, import intensity, and output allocation, while preserving national accounting identities. The approach is demonstrated for aquaculture systems, anaerobic digestion scenarios, and plant-based protein value chains. Demand-driven Leontief multipliers reveal heterogeneity in domestic propagation effects across activities and development stages. The framework offers a resource-efficient and replicable tool for evaluating bioeconomy strategies under real-world data constraints. The paper finds that the bioeconomy is structurally heterogeneous rather than a single uniform sector. Aquaculture is strongly transport- and service-linked, anaerobic digestion is more manufacturing-oriented, and plant-based protein production combines agricultural and industrial inputs while showing relatively high import dependence. Full article

This paper presents a practical implementation of relative primary radiation thermometry (RPRT) together with MultiFixRadSoft, an open-source software package developed in accordance with the Mise-en-Pratique for the kelvin (MeP-K) for realization of the thermodynamic temperature scale and uncertainty evaluation under the new definition of the kelvin. The software enables realization of temperature scales using ITS-90 metal fixed points as well as metal–carbon and metal–carbide–carbon eutectic high-temperature fixed points (HTFPs) for both radiation thermometers and radiometers. It incorporates automated routines for melting plateau analysis, including determination of the point of inflection, liquidus point, and melting range, together with correction modules for size-of-source effect, detector nonlinearity, emissivity, and temperature drop. Validation is demonstrated through experimental realization using six fixed points (Cu, Fe–C, Co–C, Pd–C, Ru–C, and WC–C) and a linear radiation thermometer. The software also supports ITS-90 extrapolation procedures and flexible calibration schemes (n = 1 to n ≥ 3), with automated Sakuma–Hattori fitting and full uncertainty propagation compliant with MeP-K requirements. The results show excellent agreement with manual analyses and published data, confirming the correctness of the implemented algorithms. By integrating data processing, scale realization, and uncertainty analysis within a unified and transparent framework, MultiFixRadSoft provides a robust and accessible tool for traceable radiometric thermometry, supporting emerging NMIs and industrial laboratories while promoting the wider adoption of primary thermodynamic temperature realization methods. Full article

Pneumatic transmission lines play a critical role in the dynamic performance of soft robotic actuation systems, yet their behaviour is difficult to capture using conventional integer-order (IO) models. In long, slender pipelines, compressibility, viscothermal losses, and wave propagation give rise to distributed damping and non-exponential relaxation dynamics that are not well represented by finite-dimensional models. This paper presents a control-oriented, experimentally validated fractional-order (FO) modelling framework for pneumatic pipeline dynamics under closed-end boundary conditions. Models are calibrated using measured step-response data from a 13.2 m pipeline, with all parameters—including the fractional order—identified through a unified optimisation procedure. In addition to global fitting accuracy, model performance is evaluated using control-relevant metrics, including effective delay, initial slope and early transient behaviour, and early-time error. The results show that FO models provide a more compact and structurally consistent representation of long-memory dynamics while improving the accuracy of control-relevant features compared to their IO counterparts. These findings demonstrate that fractional dynamics offer a physically meaningful and practically useful framework for modelling pneumatic transmission lines, with direct implications for high-performance control design in soft robotic systems. Full article