Search Results (24,504)

This work presents an extensive experimental and numerical analysis, aimed at investigating the impact of shelf-like fences applied on the suction side of a turbine nozzle guide vane. The cascade is constituted of vanes characterized by long chord and low aspect ratio, which are typical features of some LPT first stages directly downstream of an HPT, hence presenting high channel diffusion, especially near the tip. In particular, the present study complements existing literature by highlighting how blade fences positioned on the suction side can reduce the penetration of the large passage vortex. This is particularly effective in applications where flow turning is limited, the blades are lightly loaded at the front, and the horseshoe vortex is weak. The benefits of the present fence design in terms of losses and flow uniformity at the cascade exit plane have been demonstrated by means of a detailed experimental campaign carried out on a large-scale linear cascade in the low-speed wind tunnel installed in the Aerodynamics and Turbomachinery Laboratory of the University of Genova. Measurements mainly focused on the characterization of the flow field upstream and downstream of straight and fenced vane cascades using a five-hole pressure probe, to evaluate the impact of the device in reducing secondary flows. Furthermore, experiments were also adopted to validate both low-fidelity (RANS) and high-fidelity (LES) simulations and revealed the capability of both simulation approaches to accurately predict losses and flow deviation. Moreover, the accuracy in high-fidelity simulations has enabled an in-depth investigation of how fences act mitigating the effects of the passage vortex along the blade channel. By comparing the flow fields of the configurations with and without fences, it is possible to highlight the mitigation of secondary flows within the channel. Full article

Infrared thermography non-destructive testing technology has been widely used in the defect detection of composite structures due to its advantages, including non-contact operation, rapidity, low cost, and high precision. In this study, a laser-line scanning system combined with an infrared thermography was developed, along with a corresponding dynamic sequence image reconstruction method, enabling rapid localization of surface damages. Then, high-precision quantitative characterization of defect morphology in reconstructed images was achieved by integrating an edge gradient detection algorithm. The reconstruction method was validated through finite element simulations and experimental studies. The results demonstrated that the laser-line scanning thermography effectively enables both rapid localization of surface damages and precise quantitative characterization of their morphology. Experimental measurements of ceramic materials indicate that the relative error in detecting crack width is about 6% when the crack is perpendicular to the scanning direction, and the relative error gradually increases when the angle between the crack and the scanning direction decreases. Additionally, an alumina ceramic plate with micrometer-width cracks is inspected by the continuous laser-line scanning thermography. The morphology detection results are completely consistent with the actual morphology. However, limited by the spatial resolution of the thermal imager in the experiment, the quantitative identification of the crack width cannot be carried out. Finally, the proposed method is also effective for detecting surface damage of wrinkles in ceramic matrix composites. It can localize damage and quantify its geometric features with an average relative error of less than 3%, providing a new approach for health monitoring of large-scale ceramic matrix composite structures. Full article

Seasonally dry tropical forests (SDTFs) are shaped by strong climatic and edaphic constraints, including pronounced rainfall seasonality, extended dry periods, and shallow karst soils with limited water retention. Understanding how tree species respond to these pressures is crucial for predicting ecosystem resilience under climate change. In the Yucatán Peninsula, we characterized sixteen tree species along a spatial and seasonal precipitation gradient, quantifying wood density, predawn and midday water potential, saturated and relative water content, and specific leaf area. Across sites, diameter classes, and seasons, we measured ≈4 individuals per species (n = 319), ensuring replication despite natural heterogeneity. Using a principal component analysis (PCA) based on individual-level data collected during the dry season, we identified five functional groups spanning a continuum from conservative hard-wood species, with high hydraulic safety and access to deep water sources, to acquisitive light-wood species that rely on stem water storage and drought avoidance. Intermediate-density species diverged into subgroups that employed contrasting strategies such as anisohydric tolerance, high leaf area efficiency, or strict stomatal regulation to maintain performance during the dry season. Functional traits were strongly associated with precipitation regimes, with wood density emerging as a key predictor of water storage capacity and specific leaf area responding plastically to spatial and seasonal variability. These findings refine functional group classifications in heterogeneous karst landscapes and highlight the value of trait-based approaches for predicting drought resilience and informing restoration strategies under climate change. Full article

Background/Objectives: Laboratory tests are a cornerstone of modern medicine, and their interpretation depends on reference intervals (RIs) that define expected values in healthy populations. Standard RIs are obtained in cohort studies that are costly and time-consuming and typically do not account for demographic factors such as age, sex, and ethnicity that strongly influence biomarker distributions. This study establishes a data-driven approach for deriving RIs directly from routinely collected laboratory results. Methods: Multidimensional joint distributions of lipid biomarkers were estimated from large-scale real-world laboratory data from the Puerto Rican population using a Gaussian Mixture Model (GMM). GMM and additional statistical analyses were used to enable separation of healthy and pathological subpopulations and exclude the influence of comorbidities all without the use of diagnostic codes. Selective mortality patterns were examined to explain counterintuitive age trends in lipid values while comorbidity implication networks were constructed to characterize interdependencies between conditions. Results: The approach yielded sex- and age-stratified RIs for lipid panel biomarkers estimated from the inferred distributions (total cholesterol, LDL, HDL, triglycerides). Apparent improvements in biomarker profiles after midlife were explained by selective survival. Comorbidities exerted pronounced effects on the 95% ranges, with their broader influence captured through network analysis. Beyond fixed limits, the method yields full distributions, allowing each individual result to be mapped to a percentile and interpreted as a continuous measure of risk. Conclusions: Population-specific and sex- and age-segmented RIs can be derived from real-world laboratory data without recruiting healthy cohorts. Incorporating selective mortality effects and comorbidity networks provides additional insight into population health dynamics. Full article

Rapid urbanization and frequent extreme events have made urban flooding a growing threat to residents. This issue is acute in old urban districts, where extremely limited land resources, outdated standards and poor infrastructure have led to inadequate drainage and uneven pipe settlement, heightening flood risk. This study applies InfoWorks ICM Ultimate (version 21.0.284) to simulate flooding in a typical old urban district for six return periods. A risk assessment was carried out, flood causes were analyzed, and mitigation strategies were evaluated to reduce inundation and cost. Results show that all combined schemes outperform single-measure solutions. Among them, the green roof combined with pipe optimization scheme eliminated high-risk and medium-risk areas, while reducing low-risk areas by over 78.23%. It also lowered the ponding depth at key waterlogging points by 70%, significantly improving the flood risk profile. The permeable pavement combined with pipe optimization scheme achieved similar results, reducing low-risk areas by 77.42% and completely eliminating ponding at key locations, although at a 50.8% higher cost. This study underscores the unique contribution of cost-considered gray-green infrastructure retrofitting in old urban areas characterized by land scarcity and aging pipeline networks. It provides a quantitative basis and optimization strategies for refined modeling and multi-strategy management of urban waterlogging in such regions, offering valuable references for other cities facing similar challenges. The findings hold significant implications for urban flood control planning and hydrological research, serving as an important resource for urban planners engaged in flood risk management and researchers in urban hydrology and stormwater management. Full article

This article presents a principled framework for selecting and tuning classical computer vision algorithms in the context of optical displacement sensing. By isolating key factors that affect algorithm behavior—such as feed window size and motion step size—the study seeks to move beyond intuition-based practices and provide rigorous, repeatable performance evaluations. Computer vision-based optical odometry sensors offer non-contact, high-precision measurement capabilities essential for modern metrology and robotics applications. This paper presents a systematic comparative analysis of three classical tracking algorithms—phase correlation, template matching, and optical flow—for 2D surface displacement measurement using synthetic image sequences with subpixel-accurate ground truth. A virtual camera system generates controlled test conditions using a multi-circle trajectory pattern, enabling systematic evaluation of tracking performance using 400 × 400 and 200 × 200 pixel feed windows. The systematic characterization enables informed algorithm selection based on specific application requirements rather than empirical trial-and-error approaches. Full article

Recent advances in cardiovascular imaging have revolutionized the assessment and management of abdominal aortic aneurysm (AAA) through the integration of sophisticated haemodynamic biomarkers. This comprehensive review evaluates the clinical utility and mechanistic significance of multiple biomarkers in AAA pathogenesis, progression, and treatment outcomes. Advanced cardiac imaging modalities, including four-dimensional magnetic resonance imaging (4D MRI), computational fluid dynamics (CFD), and specialized echocardiography, enable precise quantification of critical haemodynamic parameters. Wall shear stress (WSS) emerges as a fundamental biomarker, with values below 0.4 Pa indicating pathological conditions and increased risk for aneurysm progression. Time-averaged wall shear stress (TAWSS), typically maintaining values above 1.5 Pa in healthy arterial segments, provides crucial information about sustained haemodynamic forces affecting the vessel wall. The oscillatory shear index (OSI), ranging from 0 (unidirectional flow) to 0.5 (purely oscillatory flow), quantifies directional changes in WSS during cardiac cycles. In AAA, elevated OSI values between 0.3 and 0.4 correlate with disturbed flow patterns and accelerated disease progression. The relative residence time (RRT), combining TAWSS and OSI, identifies regions prone to thrombosis, with values exceeding 2–3 Pa⁻¹ indicating increased risk. The endothelial cell activation potential (ECAP), calculated as OSI/TAWSS, serves as an integrated metric for endothelial dysfunction risk, with values above 0.2–0.3 Pa⁻¹ suggesting increased inflammatory activity. Additional biomarkers include the volumetric perivascular characterization index (VPCI), which assesses vessel wall inflammation through perivascular tissue analysis, and pulse wave velocity (PWV), measuring arterial stiffness. Central aortic systolic pressure and the aortic augmentation index provide essential information about cardiovascular load and arterial compliance. Novel parameters such as particle residence time, flow stagnation, and recirculation zones offer detailed insights into local haemodynamics and potential complications. Implementation challenges include the need for specialized equipment, standardized protocols, and expertise in data interpretation. However, the potential for improved patient outcomes through more precise risk stratification and personalized treatment planning justifies continued development and validation of these advanced assessment tools. Full article

Within the modernizing energy infrastructure of today, the integration of renewable energy sources and direct current (DC)-powered technologies calls for the re-examination of traditional alternative current (AC) networks. Low-voltage DC (LVDC) grids offer an attractive way forward in reducing conversion losses and simplifying local power management. However, ensuring reliable operation depends on a thorough understanding of DC distortions—phenomena generated by power converters, source instability, and varying loads. Two complementary traceable measurement chains are presented in this article with the purpose of measuring the steady-state DC component and the amplitude and frequency of the distortions around the DC bus with low uncertainties. One chain is optimized for laboratory environments, with high effectiveness in a controlled setup, and the other one is designed as a flexible and easily transportable solution, ensuring efficient and accurate assessments of DC distortions for field applications. In addition to our hardware solutions fully characterized by the uncertainty budget, we present the measurement method used for assessing DC distortions after evaluating the limitations of conventional AC techniques. Both arrangements are set to measure voltages of up to 1000 V, currents of up to 30 A, and frequency components of up to 150–500 kHz, with an uncertainty varying from 0.01% to less than 1%. This level of accuracy in the measurements will allow us to draw reliable conclusions regarding the dynamic behavior of future LVDC grids. Full article

Malay songket motifs are a vital component of Malaysia’s intangible cultural heritage, characterized by intricate visual designs and deep cultural symbolism. However, the practical digital preservation and retrieval of these motifs present challenges, particularly due to the rotational variations typical in textile imagery. This study introduces a novel Content-Based Image Retrieval (CBIR) model that integrates Principal Component Analysis (PCA) for feature extraction and Quadratic Geometric Distance (QGD) for measuring similarity. To evaluate the model’s performance, a curated dataset comprising 413 original images and 4956 synthetically rotated songket motif images was utilized. The retrieval system featured metadata-driven preprocessing, dimensionality reduction, and multi-angle similarity assessment to address the issue of rotational invariance comprehensively. Quantitative evaluations using precision, recall, and F-measure metrics demonstrated that the proposed PCAQGD + Rotation technique achieved a mean F-measure of 59.72%, surpassing four benchmark retrieval methods. These findings confirm the model’s capability to accurately retrieve relevant motifs across varying orientations, thus supporting cultural heritage preservation efforts. The integration of PCA and QGD techniques effectively narrows the semantic gap between machine perception and human interpretation of motif designs. Future research should focus on expanding motif datasets and incorporating deep learning approaches to enhance retrieval precision, scalability, and applicability within larger national heritage repositories. Full article

Evidence has suggested that post-exercise heart rate recovery (PHRR) is a useful tool in evaluating cardiac autonomic function. Altered cardiac autonomic function is characterized by heightened sympathetic activation and the abnormal reactivation of the parasympathetic nervous system and is associated with delayed HRR. Although grape seed extract (GSE) supplementation has been shown to increase nitric oxide production and modify sympathetic output, there is limited evidence on its potential beneficial effects on PHRR. We investigated the effect of GSE supplementation on PHRR during sympathetic overactivation induced by muscle metaboreflex activation (MMA) in young individuals. Participants were randomly assigned, via a double-blind, cross-over design, to either receive GSE (300 mg, two capsules) or PL (300 mg, two capsules), with a washout period of at least 72 h. between trials. A submaximal exercise test was performed using a cycle ergometer combined with an isometric handgrip exercise using a handgrip dynamometer and blood flow occlusion by placing a cuff over the brachial artery of the dominant arm. PHRR was measured at 5 s. intervals throughout the experiment. The PHRR was evaluated between GSE and PL at every min. for 300 s. PHRR kinetics significantly improved following GSE supplementation (74.3 ± 7.5 s) compared with the PL condition (86.2 ± 10.4 s). Our results suggest that GSE is effective in improving HRR kinetics during heightened sympathetic activity induced by MMA in young individuals (p = 0.034; ES = 0.4). Thus, regular treatment with GSE may provide a nonpharmacological intervention to reduce sympathetic hyperactivity in conditions where excessive sympathetic activity is consistently present. Full article

Background/Objectives: Behavioral variant frontotemporal dementia (bvFTD), the most prevalent clinical subtype within the frontotemporal lobar degeneration spectrum disorders, is characterized by early and prominent changes that significantly disrupt everyday functioning. This study aims to identify the key correlates of functional status in bvFTD by investigating the relative contributions of cognitive deficits, behavioral disturbances, personality changes, and brain perfusion abnormalities. Additionally, it seeks to develop a theoretical framework to elucidate how these factors may interconnect and shape unique functional profiles. Methods: A total of 26 individuals diagnosed with bvFTD were recruited from the 2nd Neurology Clinic of “AHEPA” University Hospital in Thessaloniki, Greece, and underwent a comprehensive neuropsychological assessment to evaluate their cognitive functions. Behavioral disturbances, personality traits, and functional status were rated using informant-based measures. Regional cerebral blood flow was assessed using Single Photon Emission Computed Tomography (SPECT) imaging to evaluate brain perfusion patterns. Penalized Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was performed to identify the most robust correlates of functional impairment, followed by path analyses using structural equation modeling to explore how these factors may interrelate and contribute to functional disability. Results: The severity of negative behavioral symptoms (e.g., apathy), conscientiousness levels, and performance on neuropsychological measures of semantic verbal fluency, visual attention, visuomotor speed, and global cognition were identified as the strongest correlates of performance in activities of daily living. Neuroimaging analysis revealed hypoperfusion in the right prefrontal (Brodmann area 8) and inferior parietal (Brodmann area 40) cortices as statistically significant neural correlates of functional impairment in bvFTD. Path analyses indicated that reduced brain perfusion was associated with attentional and processing speed deficits, which were further linked to more severe negative behavioral symptoms. These behavioral disturbances were subsequently correlated with declines in global cognition and conscientiousness, which were ultimately associated with poorer daily functioning. Conclusions: Hypoperfusion in key prefrontal and parietal regions, along with the subsequent cognitive and neuropsychiatric manifestations, appears to be associated with the pronounced functional limitations observed in individuals with bvFTD, even in early stages. Understanding the key determinants of the disease can inform the development of more targeted, personalized treatment strategies aimed at mitigating functional deterioration and enhancing the quality of life for affected individuals. Full article

This study investigates the enhancement of polyvinylidene fluoride (PVDF) membranes with polyethylene glycol (PEG) to improve their efficacy in treating tofu wastewater through the ultrafiltration (UF) process. PVDF membranes with varying PEG concentrations of 0, 0.5, 1, and 1.5% in the dope solution were produced, characterized via FTIR, mechanical strength, porosity, and contact angle measurements, and evaluated in wastewater treatment at varying pressures of 3, 4, and 5 bar in the UF process. The incorporation of PEG increased the membrane’s porosity from 28.2% for M-0 to 43.5% for M-1.5. The contact angle decreased from 65.3° for M-0 to 53.3° for M-1.5, indicating an increase in hydrophilicity. Elongation increased from 36.0% for M-0 to 113.5% for M-1.5; however, the tensile strength decreased from 11.8 MPa for M-0 to 5.4 MPa for M-1.5. Although PEG-modified membranes demonstrated enhanced flux, with values of 6.3 L∙m⁻²∙h⁻¹ for M-0 and 15.7 L∙m⁻²∙h⁻¹ for M-1.5 at a pressure of 5 bar, pure PVDF membranes (M-0) showed greater rejection rates for chemical oxygen demand (COD), total dissolve solid (TDS), total suspended solid (TSS), and turbidity at 3 bar, achieving values of 66.3%, 41.6%, 99.6%, and 99.1%, respectively. Following ultrafiltration, the pH and TDS levels conformed to Indonesian government guidelines; however, the COD levels were non-compliant, indicating the need for additional treatment. The findings suggest that PVDF/PEG ultrafiltration membranes are suitable for pre-treatment; however, nanofiltrationor reverse osmosis may be necessary to meet the stringent regulatory standards for tofu wastewater treatment. The modified M-1.5 membrane is recommended as the primary ultrafiltration membrane for tofu wastewater treatment due to its superior flux, prior to nanofiltration or reverse osmosis, to comply with the stringent regulatory standards established by the Government of the Republic of Indonesia. Full article

Wireless power transfer (WPT) has emerged as a compelling solution for delivering electrical energy without physical connectors, particularly in applications requiring reliability, mobility, or encapsulation. This work presents the modeling, simulation, construction, and experimental validation of an optimized dual-frequency WPT system using magnetically coupled resonant coils. Unlike conventional single-frequency systems, the proposed architecture introduces two independently controlled excitation frequencies applied to distinct transistors, enabling improved resonance behavior and enhanced power delivery across a range of coupling conditions. The design process integrates numerical circuit simulations in PSpice and three-dimensional electromagnetic analysis in ANSYS Maxwell 3D, allowing accurate evaluation of coupling coefficient variation, mutual inductance, and magnetic flux distribution as functions of coil geometry and alignment. A sixth-degree polynomial model was derived to characterize the coupling coefficient as a function of coil separation, supporting predictive tuning. Experimental measurements were carried out using a physical prototype driven by both sinusoidal and rectangular control signals under varying load conditions. Results confirm the simulation findings, showing that specific signal periods (e.g., 8 µs, 18 µs, 20 µs, 22 µs) yield optimal induced voltage values, with strong sensitivity to the coupling coefficient. Moreover, the presence of a real load influenced system performance, underscoring the need for adaptive control strategies. The proposed approach demonstrates that dual-frequency excitation can significantly enhance system robustness and efficiency, paving the way for future implementations of self-adaptive WPT systems in embedded, mobile, or biomedical environments. Full article

Multiple myeloma (MM) is one of the most common hematological malignancies and remains incurable. However, the survival of multiple myeloma patients has significantly increased due to the implementation of novel therapies along with autologous stem cell transplantation, changing the natural history of the disease. Consequently, there is an unmet need for more sensitive response assessment techniques capable of quantifying minimal tumor burden to identify patients at higher risk of early relapse. Multiparameter flow cytometry (MFC) is an essential tool for diagnosing and monitoring patients with various hematological conditions and has recently gained prominence in identifying, characterizing, and monitoring malignant plasma cells. The implementation of Next-Generation Flow (NGF) by EuroFlow aims to overcome the pitfalls of conventional MFC, including lack of standardization and lower sensitivity, by offering standardized and optimized protocols for evaluating response depth. Both MFC and NGF have wide-ranging applications in MM for diagnosis and measurable residual disease (MRD) monitoring. Plasma cell identification and clonality evaluation through MFC and NGF assist in diagnostic workup and are routinely used to assess therapeutic response through MRD analysis. Additionally, flow cytometry is applied for circulating tumor plasma cell (CTPC) enumeration, which has demonstrated significant prognostic value. Immune composition studies through MFC may provide better understanding of disease biology. Furthermore, MFC provides additional information about other bone marrow cell populations, assessing cellularity, immunophenotypic characteristics of plasma cells, and possible hemodilution. This review explores the applications of MFC and NGF in MM, highlighting their roles in diagnosis, response assessment, and prognosis. Beyond their established use in MRD monitoring, flow cytometry-derived immunophenotypic profiles show strong potential as cost-effective prognostic tools. We advocate for future studies to validate and integrate these markers into risk stratification models, complementing cytogenetic analyses and guiding individualized treatment strategies. Full article

The present study presents a comparative evaluation of two analytical deconvolution models applied to Optically Stimulated Luminescence (OSL) decay curves of zirconia-reinforced lithium silicate (ZLS), a glass-ceramic material with potential applications in accidental dosimetry. ZLS samples were subjected to beta irradiation and measured under Continuous Wave OSL (CW-OSL) protocols. A comparative analysis is conducted between two deconvolution approaches—the General Order Kinetics (GOK) model and a master analytical equation based on the Lambert W function. The results imply that both models yield a linear dose-response behavior of the fast OSL component; however, the Lambert W approach offers simpler fitting with fewer parameters. The abovementioned findings demonstrate the methodological robustness of the Lambert W formalism and also confirm that ZLS is a promising dosimetric material, aligning with the goals of protocol development in material characterization. Full article