Search Results (134)

Coastal erosion, exacerbated by climate change, poses a critical global threat to both the environment and human livelihoods. Acquiring accurate, high-resolution topo-bathymetric data is vital for understanding these dynamic environments, without underestimating the hydrodynamic and meteo-oceanographic conditions. However, traditional methods often present significant challenges in achieving comprehensive, high-resolution topo-bathymetric coverage efficiently in shallow coastal zones, leading to a notable ”white ribbon” data gap. This study introduces a novel, integrated methodology combining unmanned aerial vehicles (UAVs) for terrestrial surveys, unmanned surface vehicles (USVs) for bathymetry, and the Global Navigation Satellite System (GNSS) for ground control and intertidal gap-filling. Through this technologically rigorous approach, a seamless Bathymetry-Topography Digital Surface Model for the Guardamar del Segura dune system (Spain) was successfully elaborated using a DJI Mini 2 UAV, Leica Zeno FLX100 GNSS, and Apache 3 USV. The method demonstrated a substantial time reduction of at least 50–75% for comparable high-resolution coverage, efficiently completing the 86.4 ha field campaign in approximately 4 h. This integrated approach offers an accessible and highly efficient solution for generating detailed coastal elevation models crucial for coastal management and research. Full article

Silicon carbide (SiC) half-bridge power modules are widely utilized in new energy power generation, electric vehicles, and industrial power supplies. To address the research gap in collaborative validation between electro-thermal coupling models and process reliability, this paper proposes a closed-loop methodology of “design-simulation-process-validation”. This approach integrates in-depth electro-thermal simulation (LTspice XVII/COMSOL Multiphysics 6.3) with micro/nano-packaging processes (sintering/bonding). Firstly, a multifunctional double-pulse test board was designed for the dynamic characterization of SiC devices. LTspice simulations revealed the switching characteristics under an 800 V operating condition. Subsequently, a thermal simulation model was constructed in COMSOL to quantify the module junction temperature gradient (25 °C → 80 °C). Key process parameters affecting reliability were then quantified, including conductive adhesive sintering (S820-F680, 39.3 W/m·K), high-temperature baking at 175 °C, and aluminum wire bonding (15 mil wire diameter and 500 mW ultrasonic power/500 g bonding force). Finally, a double-pulse dynamic test platform was established to capture switching transient characteristics. Experimental results demonstrated the following: (1) The packaged module successfully passed the 800 V high-voltage validation. Measured drain current (4.62 A) exhibited an error of <0.65% compared to the simulated value (4.65 A). (2) The simulated junction temperature (80 °C) was significantly below the safety threshold (175 °C). (3) Microscopic examination using a Leica IVesta 3 microscope (55× magnification) confirmed the absence of voids at the sintering and bonding interfaces. (4) Frequency-dependent dynamic characterization revealed a 6 nH parasitic inductance via Ansys Q3D 2025 R1 simulation, with experimental validation at 8.3 nH through double-pulse testing. Thermal evaluations up to 200 kHz indicated 109 °C peak temperature (below 175 °C datasheet limit) and low switching losses. This work provides a critical process benchmark for the micro/nano-manufacturing of high-density SiC modules. Full article

This study presents a comprehensive comparison of static and SLAM (Simultaneous Localization and Mapping) laser scanners of both new and old generation in a controlled indoor environment of a standard commercial building with long, linear corridors and recesses. The aim was to assess both global and local accuracy, as well as noise characteristics, of each scanner. Methods: A highly accurate static scanner was used to generate a reference point cloud. Five devices were evaluated: two static scanners (Leica RTC 360 and Trimble X7) and three SLAM scanners (GeoSLAM ZEB Horizon RT, Emesent Hovermap ST-X, and FARO Orbis). Accuracy analysis included systematic and random error assessment, axis-specific displacement evaluation, and profile-based local accuracy measurements. Additionally, noise was quantified before and after data smoothing. Static scanners yielded superior accuracies, with the Leica RTC 360 achieving the best performance (absolute accuracy of 1.2 mm). Among SLAM systems, the Emesent Hovermap ST-X and FARO Orbis—both newer-generation devices—demonstrated significant improvements over the older-generation GeoSLAM ZEB Horizon RT. After smoothing, the noise levels of these new-generation SLAM scanners (approx. 2.1–2.2 mm) approached those of static systems. The findings underline the ongoing technological progress in SLAM systems, with the new-generation SLAM scanners becoming increasingly viable alternatives to static scanners, especially when speed, ease of use, and reduced occlusions are prioritized. This makes them well-suited for rapid indoor mapping applications, provided that the slightly lower accuracy is acceptable for the intended use. Full article

Background Veno-venous extracorporeal membrane oxygenation (VV-ECMO) supports critically ill patients with respiratory failure. However, ECMO may induce systemic inflammation, hemolysis, and hemodilution, potentially resulting in endothelial activation and damage. Therefore, this study explored the longitudinal changes in circulating markers of inflammation, hemolysis, and endothelial activation and damage in patients with COVID-19 on VV-ECMO. Methods Plasma was obtained before, within 48 h as well as on day 4, week 1, and week 2 of ECMO support and after decannulation. Circulating markers were measured using Luminex, ELISA, and spectrophotometry. Human pulmonary endothelial cells were exposed to patient plasma, and in vitro endothelial permeability was assessed using electric cell-substrate impedance sensing. Results From April 2020 to January 2022, plasma was collected from 14 patients (71.4% male; age 54 (45–61) years). IL-6 levels decreased (1.238 vs. 0.614 ng/mL, p = 0.039) while ICAM-1 increased (667 vs. 884 ng/mL, p = 0.003) over time when compared to pre-ECMO. Angiopoietin-1 decreased after ECMO initiation (7.57 vs. 3.58 ng/mL, p = 0.030), whereas angiopoietin-2 increased (5.20 vs. 10.19 ng/mL, p = 0.017), particularly in non-survivors of ECMO. Cell-free hemoglobin decreased directly after VV-ECMO initiation but remained stable thereafter (55.29 vs. 9.19 mg/dL, p = 0.017). Moreover, the plasma obtained at several time points during the ECMO run induced in vitro pulmonary endothelial hyperpermeability. Conclusions This exploratory study shows that patients on VV-ECMO support due to COVID-ARDS exhibit progressive endothelial activation and damage but not inflammation and hemolysis. Larger prospective studies are necessary to elucidate pathophysiological pathways leading to endothelial activation and damage, thereby reducing organ failure in these critically ill patients. Full article

To address the inefficiencies and limited spatial resolution of traditional single-point monitoring techniques, this study proposes a multi-scale analysis method that integrates the Multi-Scale Model-to-Model Cloud Comparison (M3C2) algorithm with least-squares plane fitting. This approach employs the M3C2 algorithm for qualitative full-field deformation detection and utilizes least-squares plane fitting for quantitative feature extraction. When applied to the approach span of a cross-river bridge in Hubei Province, China, this method leverages dense point clouds (greater than 500 points per square meter) acquired using a Leica RTC360 scanner. Data preprocessing incorporates curvature-adaptive cascade denoising, achieving over 98% noise removal while retaining more than 95% of structural features, along with octree-based simplification. By extracting multi-level slice features from bridge decks and piers, this method enables the simultaneous analysis of global trends and local deformations. The results revealed significant deformation, with an average settlement of 8.2 mm in the left deck area. The bridge deck exhibited a deformation trend characterized by left and higher right in the vertical direction, while the bridge piers displayed noticeable tilting, particularly with the maximum offset of the rear pier columns reaching 182.2 mm, which exceeded the deformation of the front pier. The bridge deck’s micro-settlement error was ±1.2 mm, and the pier inclination error was ±2.8 mm, meeting the Chinese Highway Bridge Maintenance Code (JTG H11-2004) and the American Association of State Highway and Transportation Officials (AASHTO) standards, and the multi-scale algorithm achieved engineering-level accuracy. Utilizing point cloud densities >500 pt/m², the M3C2 algorithm achieved a spatial resolution of 0.5 mm, enabling sub-millimeter full-field analysis for complex scenarios. This method significantly enhances bridge safety monitoring precision, enhances the precision of intelligent systems monitoring, and supports the development of targeted systems as pile foundation reinforcement efforts and as improvements to foundations. Full article

Background/Objectives: Fluid dynamic models of the cerebral vasculature are being developed to evaluate intracranial vascular pathology. Fluid–structure interaction modeling provides an opportunity for more accurate simulation of vascular pathology by modelling the vessel wall itself in conjunction with the fluid forces. Accuracy of these models is heavily dependent on the parameters used. Of those studied, elastin has been considered a key component used in aortic and common carotid artery modeling. We studied elastin thickness to determine if there was significant variation between cerebral artery territories to suggest its importance in cerebral blood vessel biomechanical response and provide reference data for modeling intracranial elastin. Elastin thickness was compared to vessel location, thickness, diameter, and laterality within human intracranial arteries. Methods: Tissue was taken from five human cadaveric heads preserved in formaldehyde from each intracranial vessel distribution bilaterally and stained with Van Gieson stain for elastin. A total of 160 normal cerebral vascular artery specimens were obtained from 17 different cerebrovascular regions. Two reviewers measured elastin thickness for each sample at five different locations per sample using Aperio ImageScope (Leica Biosystems, Deer Park, IL, USA). Statistical analysis of the samples was performed using mixed-models repeated measures regression methods. Results: There was a significant difference between anterior circulation (6.01 µm) and posterior circulation (4.4 µm) vessel elastin thickness (p-value < 0.05). Additionally, two predictive models of elastin thickness were presented, utilizing a combination of anterior versus posterior circulation, vessel diameter, and vessel wall thickness, which demonstrated significance for prediction with anterior versus posterior combined with vessel diameter and wall thickness. Conclusions: Elastin thicknesses are significantly different between anterior and posterior circulation vessels, which may explain the differences seen in aneurysm rupture risk for anterior versus posterior circulation aneurysms. Additionally, we propose two potential models for predicting elastin thickness based on vessel location, vessel diameter, and vessel wall thickness, all of which can be obtained using preoperative imaging techniques. These findings suggest that elastin plays an important role in cerebral vascular wall integrity, and this data will further enable fluid–structure interaction modeling parameters to be more precise in an effort to provide predictive modeling for cerebrovascular pathology. Full article

The aim of this study was to investigate the effect of dose, temperature and mechanical stress on the return and rate of return deformation. The structure of the polymers under study begins to change under the influence of electron and ion beams, as well as temperature and mechanical stress, which leads to a change in such mechanical properties as return deformation and rate of return deformation. The authors proposed formulas for models that accurately explain the experimental data. In addition, using an optical microscope DM 6000M (Leica, Wetzlar, Germany), photographs of the surface morphology of unirradiated and irradiated materials before and after tensile testing were obtained. The results can be used to improve the properties of packaging materials in the food industry. Full article

Extracorporeal membrane oxygenation (ECMO) can be a life-saving intervention, but it is associated with high complication rates. ECMO induces systemic inflammation and endothelial hyperpermeability, thereby causing tissue edema, microcirculatory perfusion disturbances, and organ failure. This study investigated whether the inhibition of vascular endothelial protein tyrosine phosphatase (VE-PTP), a regulator of endothelial permeability, reduces extracorporeal circulation (ECC)-induced microvascular dysfunction. Rats were subjected to ECC after treatment with Razuprotafib (n = 11) or a placebo (n = 11), or they underwent a sham procedure (n = 8). Razuprotafib had no effect on the ECC-induced impairment of capillary perfusion, as assessed with intravital microscopy, nor did it influence the increased wet-to-dry weight ratio in kidneys, a marker of edema associated with ECC. Interestingly, Razuprotafib suppressed the ECC-induced increase in TNFα, whereas angiopoietin-2 even further increased, following the discontinuation of ECC. Circulating interleukin-6, ICAM-1, angiopoietin-1, and soluble Tie2 and tissue VE-PTP, Tie1, and Tie2 mRNA expression were not affected by Razuprotafib. Furthermore, Razuprotafib improved the PaO₂/FiO₂ ratio and reduced histopathological pulmonary interstitial inflammation following ECC compared to the placebo. To conclude, treatment with Razuprotafib did not improve ECC-induced microcirculatory perfusion disturbances nor renal edema. Full article

This study expands on prior research by generalising the machine tool integrated inverse multilateration methodology to evaluate ambient thermal effects on medium- and large-sized machine tools in industrial environments. This method integrates an absolute distance measurement device into the machine tool spindle, enabling an automated and robust multilateration scheme without requiring controlled environments, expensive thermal instruments, or specialised artifacts. Tests were conducted using a LEICA AT960™ laser tracker and wide-angle retro-reflectors (both from Hexagon Manufacturing Intelligence, Stockholm, Sweden) across two machine architectures, THERA™ (gantry type) and ZERO™ (bed type), building on earlier work with the ARION G™ (bridge type), all of them MTs manufactured by Zayer (Vitoria, Spain). Sequential experiments in varying ambient conditions demonstrated the reliability of the machine tool integrated inverse multilateration approach over extended periods, showing strong correlations between the measured errors and temperature variations. The results were validated using a first-order mathematical model and finite element method simulations, confirming thermal error evolution as a function of ambient temperature changes. This method’s adaptability to diverse machine architectures and industrial conditions highlights its potential for characterising and mitigating thermal errors in large machine tools. This work underscores the method’s effectiveness and utility for advancing thermal error analysis in practical manufacturing settings. Full article

Background: Nosocomial lower respiratory tract infections (nLRTIs) are associated with unfavorable clinical outcomes and significant healthcare costs. nLRTIs include hospital-acquired pneumonia (HAP), ventilator-associated pneumonia (VAP), and other ICU-acquired pneumonia phenotypes. While risk factors for mortality in these infections are critical to guide preventive strategies, it remains unclear whether they vary based on their requirement of invasive mechanical ventilation (IMV) at any point during the hospitalization. Objectives: This study aims to identify risk factors associated with short- and long-term mortality in patients with nLRTIs, considering differences between those requiring IMV and those who do not. Methods: This multinational prospective cohort study included ICU-admitted patients diagnosed with nLRTI from 28 hospitals across 13 countries in Europe and South America between May 2016 and August 2019. Patients were selected based on predefined inclusion and exclusion criteria, and clinical data were collected from medical records. A random forest classifier determined the most optimal clustering strategy when comparing pneumonia site acquisition [ward or intensive care unit (ICU)] versus intensive mechanical ventilation (IMV) necessity at any point during hospitalization to enhance the accuracy and generalizability of the regression models. Results: A total of 1060 patients were included. The random forest classifier identified that the most efficient clustering strategy was based on ventilation necessity. In total, 76.4% of patients [810/1060] received IMV at some point during the hospitalization. Diabetes mellitus was identified to be associated with 28-day mortality in the non-IMV group (OR [IQR]: 2.96 [1.28–6.80], p = 0.01). The 90-day mortality-associated factor was MDRP infection (1.98 [1.13–3.44], p = 0.01). For ventilated patients, chronic liver disease was associated with 28-day mortality (2.38 [1.06–5.31] p = 0.03), with no variable showing statistical and clinical significance at 90 days. Conclusions: The risk factors associated with 28-day mortality differ from those linked to 90-day mortality. Additionally, these factors vary between patients receiving invasive mechanical ventilation and those in the non-invasive ventilation group. This underscores the necessity of tailoring therapeutic objectives and preventive strategies with a personalized approach. Full article

This article focuses on modern methods of documentation and visualization for a historic object. Digital photogrammetry and terrestrial laser scanning (TLS), which are essential tools for documenting cultural heritage in view of their rapid development in recent years, were used, compared, and analyzed. Furthermore, the use of available 3D computer graphics technologies for visualization is described and an optimal procedure for converting the object into VR and AR is proposed and implemented. The technologies presented in this article were tested within the context of a project on the reconstruction of the shrine of the Prophet Nahum in the city of Alqosh in northern Iraq, taking the shrine as a case study. Funded by ARCH Int. and provided by GemaArt Int., the restoration project started in 2018 and was completed in 2021. The ongoing documentation was prepared by the CTU and it used the materials for research purposes. Accurate documentation using photogrammetry, drones, and TLS was key to the restoration. Leica BLK360, Faro Focus S150, and GeoSlam laser scanners were used, as well as photogrammetric methods. In particular, the documentation process involved the creation of 3D textured models from the photogrammetry, which were compared to the TLS data to ensure accuracy. These models were necessary to track changes during the reconstruction phases and to calculate the volumes of rubble removed and materials added. Our data analysis revealed significant differences between the construction logs and the analysis of the accurate 3D models; the results showed an underestimation of the displaced material statements by 13.4% for removed material and 4.6% for added material. The use of heat maps and volumetric analyses helped to identify areas of significant change that guided the reconstruction and documented significant changes to the building for the investor. These findings are important for use in the construction industry with respect to historic sites as well as for further research focused on visualization using VR (virtual reality) and AR (augmented reality). The conversion of existing 3D models into VR and AR is rapidly evolving and significant progress was made during this project. The Unreal Engine (UE) game engine was used. Despite the significantly improved performance of the new UE 5 version, the data for conversion to VR and AR needs to be decimated to reduce the amount—in our case, this was by up to 90%. The quality appearance of the objects is then ensured by textures. An important outcome of this part of the research was the debugged workflow developed to optimize the 3D models for VR, which was essential for creating a virtual museum that shows the restoration process. Full article

Shield tunnels are increasingly monitored using 3D laser scanning technology to generate high-resolution point cloud data, which serve as a critical foundation for precise deformation analysis. This study introduces an advanced methodology for analyzing tunnel cross-section displacements, leveraging point cloud data captured by the Self-Mobile Intelligent Laser Scanning System (SILSS), a Mobile Laser Scanning (MLS) platform capable of rapid and detailed 3D mapping of shield tunnels. The preprocessing pipeline includes the precise extraction of cross-sectional linings through local point density outlier removal techniques to enhance data accuracy. A custom segmentation algorithm partitions the tunnel cross-section linings into individual shield rings, enabling detailed and time-resolved displacement tracking. Aligned point clouds from different times were processed using the Iterative Closest Point (ICP) algorithm to achieve high-accuracy displacement analysis. Key displacement metrics, including average shield ring point cloud displacement and centerline shift, were computed to quantify displacement. Additionally, ovality analysis was employed to detect shield ring shape changes, providing critical insights into structural deformations. The findings are visualized in 3D, highlighting significant displacement areas in the tunnel cross-section. An analysis of the corresponding data obtained from the Leica Pegasus Two Ultimate scanner system shows that the data collected by SILSS are accurate. This methodology offers a robust tool for continuous tunnel monitoring, supporting the development of safer and more resilient underground infrastructure systems. Full article

The proposed work presents a Sliding Mode Controller (SMC) for trajectory tracking of a TurtleBot3 Burger mobile robot based on sliding mode. Trajectory tracking is performed in congested environments; therefore, an obstacle avoidance strategy is presented to prevent the robot from colliding with obstacles. A clear and detailed methodology is developed for the design of the SMC controller with a PID sliding surface for trajectory tracking that can be extrapolated to position control and posture control. The discontinuous part of the SMC is used to ensure that the robot tends to the desired reference whenever an obstacle appears. The stability analysis of the proposed controller is presented, and the experimental results are shown, demonstrating the good performance of the controller. Full article

An innovative cascade control strategy is presented in this work, based on sliding mode control (SMC) for trajectory tracking of the formation of mobile robots. The proposed strategy was compared with five alternative control approaches: PID control, inverse dynamics, and other SMC-based structures. The objective was to evaluate the most effective control technique by analyzing the integral of squared error (ISE) index. Additionally, robustness tests were carried out by varying the parameters of the dynamic model of the mobile robot and analyzing the response of the controllers to perturbations in the modeling. The results show that the PD-SMCV controller provides the best performance in trajectory tracking and robustness against disturbances, demonstrating significant superiority over the evaluated methods for maintaining a stable mobile robot formation under dynamic conditions. Full article

In this paper, four control strategies are developed and evaluated for the trajectory-tracking of a two-degree-of-freedom SCARA-type robotic manipulator: (i) a proportional-derivative controller (PD), (ii) a proportional-derivative controller with friction compensation (PD + G), (iii) an inverse-dynamics controller and (iv) a sliding-mode controller with a dynamic model (SMCD). These controllers are implemented in a dynamic model of a manipulator robot, and their performance is assessed based on trajectory-tracking accuracy and robustness against disturbances. Robustness tests are conducted by varying the parameters of the dynamic model of the robot. The performance of each controller is analyzed using the Integral Squared Error (ISE) and the Integral of Time-weighted Squared Error (ITSE) indexes to compare their effectiveness. This study offers a comprehensive evaluation of each control strategy, demonstrating that the SMCD achieves the optimal balance between accuracy and disturbance robustness. Full article