Search Results (272)

A monocular deflectometric system comprises a camera and a screen that collaboratively facilitate the reconstruction of a specular surface under test (SUT). This paper presents a methodology for solving the slope distribution of the SUT utilizing pose estimation derived from reflections, based on vision ray calibration (VRC). Initially recorded by the camera, an assisted flat mirror in different postures reflects the patterns displayed by a screen maintained in a constant posture. The system undergoes a calibration based on the VRC to ascertain the vision ray distribution of the camera and the spatial relationship between the camera and the screen. Subsequently, the camera records the reflected patterns by the SUT, which remains in a constant posture while the screen is adjusted to multiple postures. Utilizing the VRC, the vision ray distribution among several postures of the screen and the SUT is calibrated. Following this, an iterative integrated calibration is performed, employing the calibration results from the preceding separate calibrations as initial parameters. The integrated calibration amalgamates the cost functions from the separate calibrations with the intersection of lines in Plücker space. Ultimately, the results from the integrated calibration yield the slope distribution of the SUT, enabling an integral reconstruction. In both the numeric simulations and actual measurements, the integrated calibration significantly enhances the accuracy of the reconstructions when compared to the reconstructions with the separate calibrations. Full article

Background: The ROSA Knee System (Zimmer Biomet, Warsaw, IN, USA) is a robotic system aiming to increase bone resections and component alignment accuracy during TKA. While much is known about its performance in the coronal plane, its accuracy in the sagittal plane remains debated. The present investigation evaluated the system’s accuracy in achieving planned mechanical axis alignment and specific knee angles in both planes. Methods: A retrospective analysis was performed on 55 consecutive patients who underwent robotic-assisted TKA using the ROSA Knee System. Data on the medial proximal tibial angle (MPTA), lateral distal femoral angle (LDFA), hip–knee–ankle angle (HKA), tibial slope (TS), and distal femoral flexion (DFF) were collected pre- and post-operatively using the ROSA software. Planned and achieved angles were compared, with deviations greater than 2° and 3° defined as outliers. Results: The mean differences between planned and achieved angles for LDFA and MPTA were 0.5° ± 1.00° and 0.3° ± 1.3°, respectively, with less than 10% outliers. The hip–knee angle recorded only a minimal deviation from planned values. In contrast, the TS angle showed a statistically significant difference between planned and achieved values, while no significant difference was found for the DFF angle. The surgeon’s experience did not impact alignment accuracy. Conclusions: The ROSA Knee System demonstrates high accuracy in achieving planned alignment in the coronal plane during robotic-assisted TKA, with minimal outliers and reliable predictions for both femoral and tibial angles. However, the ROSA Knee System showed less accuracy in the sagittal plane, particularly for the tibial slope, which did not adversely affect the implant’s stability. Full article

Under the background of global climate change, shallow landslide clusters induced by extreme rainfall are occurring with increasing frequency, causing severe casualties and economic losses. To address this challenge, this study proposes an integrated approach to support both emergency response and long-term mitigation for rainfall-induced shallow landslides. The workflow includes (1) rapid landslide detection based on time-series image fusion and threshold segmentation on the Google Earth Engine (GEE) platform; (2) numerical simulation of landslide runout using the R.avaflow model; (3) landslide susceptibility assessment based on event-driven inventories and machine learning; and (4) delineation of high-risk slopes by integrating simulation outputs, susceptibility results, and exposed elements. Applied to Qugaona Township in Zhouqu County, Bailong River Basin, the framework identified 747 landslides. The R.avaflow simulations captured the spatial extent and depositional features of landslides, assisting post-disaster operations. The Gradient Boosting-based susceptibility model achieved an accuracy of 0.870, with 8.0% of the area classified as highly susceptible. In Cangan Village, high-risk slopes were delineated, with 31.08%, 17.85%, and 22.42% of slopes potentially affecting buildings, farmland, and roads, respectively. The study recommends engineering interventions for these areas. Compared with traditional methods, this approach demonstrates greater applicability and provides a more comprehensive basis for managing rainfall-induced landslide hazards. Full article

Background/Objectives: The clinically validated multiplex Oncuria bladder cancer (BC) assay quickly and noninvasively identifies disease risk and tracks treatment success by simultaneously profiling 10 protein biomarkers in voided urine samples. Oncuria uses paramagnetic bead-based fluorescence multiplex technology (xMAP^®; Luminex, Austin, TX, USA) to simultaneously measure 10 protein analytes in urine [angiogenin, apolipoprotein E, carbonic anhydrase IX (CA9), interleukin-8, matrix metalloproteinase-9 and -10, alpha-1 anti-trypsin, plasminogen activator inhibitor-1, syndecan-1, and vascular endothelial growth factor]. Methods: In a pilot study (N = 36 subjects; 18 with BC), Oncuria performed essentially identically across three different common analyzers (the laser/flow-based FlexMap 3D and 200 systems, and the LED/image-based MagPix system; Luminex). The current study compared Oncuria performance across instrumentation platforms using a larger study population (N = 181 subjects; 51 with BC). Results: All three analyzers assessed all 10 analytes in identical samples with excellent concordance. The percent coefficient of variation (%CV) in protein concentrations across systems was ≤2.3% for 9/10 analytes, with only CA9 having %CVs > 2.3%. In pairwise correlation plot comparisons between instruments for all 10 biomarkers, R² values were 0.999 for 15/30 comparisons and R² ≥ 0.995 for 27/30 comparisons; CA9 showed the greatest variability (R² = 0.948–0.970). Standard curve slopes were statistically indistinguishable for all 10 biomarkers across analyzers. Conclusions: The Oncuria BC assay generates comprehensive urinary protein signatures useful for assisting BC diagnosis, predicting treatment response, and tracking disease progression and recurrence. The equivalent performance of the multiplex BC assay using three popular analyzers rationalizes test adoption by CLIA (Clinical Laboratory Improvement Amendments) clinical and research laboratories. Full article

The accessibility of nature trails for people with motor disabilities and impairments stands as a significant challenge for inclusive tourism. In the present study, we would like to present a review of research, approaches, and solutions to enable people with motor impairments to enjoy nature trails independently or with assistance. The study is conducted from the perspective of public bodies that aim to reduce the accessibility barriers for People with Disabilities (PwDs) by adapting and improving the conditions of the trails and by providing clear and comprehensive information about the difficulties that hikers may encounter on a trail while using a specific aid. The paper initially presents the wide variety of aids for outdoor mobility, including both those to be used independently (i.e., self-propelled wheelchairs that can be equipped with additional small wheels, off-road wheels and/or auxiliary drives) and those that require assistance (e.g., single-wheeled wheelchairs). Then, we shift focus onto the difficulty classification of trails for PwDs, analysing papers and guidelines that tried to define objective evaluation criteria such as the slope, the trail surface, and the length of the sloping sections. Starting from these studies, the paper proposes a synthesis of the different classifications that consider, for the first time, all the aids available on the market, thus filling the gaps of the single studies. In the last sections, we present some national and international guidelines with tailored and practical solutions to improve the accessibility of nature trails and some studies about the inclusive planning that directly involves PwDs, as well as on the need for a better training of tourism service providers. The present work aims to stimulate a debate on the barriers and opportunities related to the accessibility of hiking trails, contributing to making nature a truly accessible experience for all. Full article

This case study is the second of three which we have been conducting on different industrial waste landfills. We are planning a fourth study comparing the three landfills. Phytostabilization, including assisted phytostabilization, is a measure of reducing the negative impact of industrial waste landfills on the environment. It is particularly important in the case of old unprotected and often abandoned landfills. Most studies investigate how phytostability depends on the plant species but do not consider its dependence on the specific location at the landfill where the plants are growing. We assumed that the habitat conditions within the landfill had been modified unequally over the years. The most heterogeneous habitat conditions were found on the slopes of the landfill. The aims of the study were to assess the impact of the location on the landfill, i.e., the site of growth; the impact of the plant species or organ; and the combined and simultaneous impact of the location and species/organ on the phytostabilization of cadmium, lead, zinc, and copper. All bioaccumulation factor (BCF) values calculated for each metal and each location (base, middle, and top) differed statistically significantly from one another. In the case of lead, zinc, and copper the highest BCFs, irrespective of species, were obtained for plants growing at the top of the landfill, whereas the highest value for cadmium was recorded at the base. Additionally, all interactions analyzed between location and species/organ were statistically significant. Variations in the BCF values, including the variation influenced by the interaction between location and species/organ, followed four distinct patterns along the slope of the landfill from the base, to the middle, and to the top. Full article

Background: Flow cytometric detection of minimal residual disease (MRD) in chronic lymphocytic leukemia (CLL) is complex, time-consuming, and subject to inter-operator variability. Deep neural networks (DNNs) offer potential for standardization and efficiency improvement, but require rigorous validation and monitoring for safe clinical implementation. Methods: We evaluated a DNN-assisted human-in-the-loop approach for CLL MRD detection. Initial validation included method comparison against manual analysis (n = 240), precision studies, and analytical sensitivity verification. Post-implementation monitoring comprised four components: daily electronic quality control, input data drift detection, error analysis, and attribute acceptance sampling. Laboratory efficiency was assessed through a timing study of 161 cases analyzed by five technologists. Results: Method comparison demonstrated 97.5% concordance with manual analysis for qualitative classification (sensitivity 100%, specificity 95%) and excellent correlation for quantitative assessment (r = 0.99, Deming slope = 0.99). Precision studies confirmed high repeatability and within-laboratory precision across multiple operators. Analytical sensitivity was verified at 0.002% MRD. Post-implementation monitoring identified 2.97% of cases (26/874) with input data drift, primarily high-burden CLL and non-CLL neoplasms. Error analysis showed the DNN alone achieved 97% sensitivity compared to human-in-the-loop-reviewed results, with 13 missed cases (1.5%) showing atypical immunophenotypes. Attribute acceptance sampling confirmed 98.8% of reported negative cases were true negatives. The DNN-assisted workflow reduced average analysis time by 60.3% compared to manual analysis (4.2 ± 2.3 vs. 10.5 ± 5.8 min). Conclusions: The implementation of a DNN-assisted approach for CLL MRD detection in a clinical laboratory provides diagnostic performance equivalent to expert manual analysis while substantially reducing analysis time. Comprehensive performance monitoring ensures ongoing safety and effectiveness in routine clinical practice. This approach provides a model for responsible AI integration in clinical laboratories, balancing automation benefits with expert oversight. Full article

This article proposes an innovative energy management strategy for hybrid multi-source dump trucks operating under real slope conditions in mining areas. Although previous studies have addressed the energy management issues of hybrid vehicles, few studies have taken into account complex environmental factors such as slopes under actual working conditions. The article overcomes this limitation by integrating a radial basis function (RBF) neural network to directly and accurately predict future vehicle demand power, thereby optimizing the DP-MPC strategy and improving energy efficiency. The results indicate that, compared with the traditional MPC strategy, the proposed strategy reduces fuel consumption by 3.34% and engine start-stop events by 76.2%. Additionally, when compared with another strategy that uses historical data to predict future speed and slope, calculates the vehicle’s future power demand, and incorporates it into the DP-MPC algorithm, the proposed strategy achieves comparable fuel consumption while also reducing engine start-stop events by 69.7%. Notably, the average calculation time for each step is 43.85 ms, which is substantially less than the sampling time of 1 s. To further confirm the real-time performance of the strategy, a hardware-in-the-loop (HIL) test is conducted. Full article

Crystalline–amorphous core–shell-like heterostructures have attracted considerable attention in electrocatalysis due to their unique electronic and structural properties; however, tuning the surface composition of the amorphous shell remains a major challenge. In this work, we report a simple, low-cost, one-pot hydrazine-assisted chemical deposition method for synthesizing a series of Co-doped Ni@Ni(OH)₂ catalysts with a crystalline Ni core and an amorphous Ni(OH)₂ shell. Among the prepared catalysts, the sample containing 10 wt.% cobalt (denoted as b-Co-doped Ni@Ni(OH)₂) exhibited the highest electrocatalytic activity toward both the oxygen evolution reaction (OER) and the urea oxidation reaction (UOR). In 1.0 M KOH, the b-Co-doped Ni@Ni(OH)₂ catalyst achieved a 40 mV lower overpotential at 50 mA·cm⁻² compared to undoped Ni@Ni(OH)₂ for the OER. For the UOR in 0.33 M urea/1.0 M KOH, it delivered approximately twice the anodic current density relative to the undoped sample, along with improved reaction kinetics as evidenced by a Tafel slope of 70.7 mV·dec⁻¹. This performance enhancement is attributed to the optimized core–shell-like architecture, cobalt doping-induced electronic modulation, increased electrochemically active surface area, and improved charge transfer efficiency. Overall, this study demonstrates a promising and scalable strategy for designing advanced Ni-based bifunctional catalysts for sustainable energy conversion and wastewater treatment applications. Full article

Addressing the global energy demand requires the development of sustainable and highly efficient technologies for clean energy generation. One of the primary challenges in the oxygen evolution reaction (OER) is overcoming sluggish reaction kinetics, which requires the design of electrocatalysts with greater activity and long-term stability. In this study, a precipitation method was employed to synthesize polyethylene glycol (PEG) assisted tungsten oxide (WO₃) as an effective and stable electrocatalyst for OER. PEG was incorporated at varying concentrations (1%, 3%, and 5%) to modulate the structural and electrochemical characteristics of WO₃. Among the resulting composites, the sample with 3% PEG (PEG-WO₃-2) exhibited the most favorable catalytic behavior, achieving a low overpotential of 407.7 mV at a current density of 10 mA cm⁻² and a Tafel slope of 76.2 mV dec⁻¹ in 1 M KOH electrolyte. Furthermore, long-term electrochemical stability was evaluated over 5000 consecutive cycles, revealing minimal degradation in catalytic activity. The heightened performance is attributed to the optimized composition, improved electron transport properties, and the presence of a higher density of active sites, all of which contribute to the superior catalytic activity of the PEG-WO₃-2 electrocatalyst. Full article

Background: This study examined the relationship between hearing device price and sound quality. Method: A novel consumer-centric metric of sound quality (“SoundScore”) was used to assess hearing devices’ audio performance. Each hearing device is tested with two fittings. The “Initial Fit” is designed to approximate the most likely fitting for an individual with a mild-to-moderate sloping sensorineural hearing loss. The “Tuned Fit” includes adjusting parameters optimized to hit prescriptive fitting targets (NAL NL2) on an acoustic manikin. Each fitting is evaluated across five dimensions. Both fittings are combined using a weighted average to create a single number from 0 to 5 representative of a device’s overall audio performance. Seventy-one hearing devices were tested. Results: A strong positive correlation was found between hearing device price and SoundScore. The average SoundScore increased dramatically as the price approached USD 1000, with marginal improvements beyond this point. SoundScore was consistently poor for devices under USD 500, highly variable between USD 500–1000, and consistently good over USD 1000. Conclusions: There is a strong but nonlinear relationship between hearing device price and sound quality. This information can aid consumers in making informed decisions while also assisting hearing healthcare professionals in providing comprehensive guidance to their patients. Full article

Accurate prognostic stratification in patients with chronic heart failure and reduced ejection fraction (HFrEF) remains a significant clinical challenge. Many different parameters, including left ventricular (LV) and right ventricular (RV) function and cardiopulmonary exercise testing (CPET) parameters, are available in the literature. LV ejection fraction (LVEF) is the most used parameter in clinical practice. This study aimed to analyze CPET and echocardiographic data in patients under evaluation for heart transplantation (HTx) to identify the parameter that best correlates with cardiac events. Methods and Results. Echocardiography and CPET were performed in patients with HFrEF under evaluation for HTx. The population comprised 170 patients (mean age: 55 ± 9 years; 88% male; non-ischemic etiology: 63%). LVEF was 30.4 ± 7.6%, peak oxygen uptake (Vo_2peak) was 17.08 ± 4.6 mL/Kg/min; minute ventilation (VE)/carbon dioxide production (Vco₂) slope was 34.8 ± 8.7. During a follow-up of 4 ± 1 years, 37 hospitalizations, 4 deaths, 14 HTx, and 5 LV assist device implantation occurred. Patients who experienced major events had a lower Vo_2peak (p < 0.005), higher VE/Vco₂ slope (p < 0.005), greater LV end-systolic diameter (p < 0.005), and RV end-diastolic diameter (p < 0.005) than patients without events. Conversely, LVEF did not differ between these two groups. VE/Vco₂ slope and RV dimensions significantly correlated with hard cardiac events (p = 0.019 and p = 0.008, respectively). Conclusions. In patients with HFrEF, parameters quantifying the system reserve (i.e., Vo_2peak and VE/Vco₂ slope) and those demonstrating advanced biventricular remodeling may help stratify the risk of cardiac events. Conversely, LVEF showed a limited prognostic value in this setting. Full article

Winch-assisted harvesting has expanded considerably in recent years as it enables ground-based machines to work safely on steep slopes. To analyze operator exposure to whole-body and hand–arm vibration (WBV, HAV) and noise exposure (LA_eq, LC_peak) during winch-assisted harvesting (TW) and harvesting without winch assistance (NTW), a field study using a Ponsse Scorpion King harvester and an Ecoforst T-winch traction winch was conducted. Vibrations were measured at three locations inside the cabin (seat, seat base/floor, control lever), while noise exposure was recorded both inside and outside the cabin. WBV exposure during work time operations was highest in the Y-direction, both on the seat (0.49–0.87 m/s²) and on the floor (0.41–0.84 m/s²). The WBV and HAV exposure levels were highest while driving on the forest and skid road. Exposure during the main productive time was significantly influenced by the harvesting system, diameter at breast height (DBH), and tree species. Noise exposure was higher, while WBV and HAV exposures on the seat, floor and control lever were lower during non-work time than during work time. The daily vibration exposure on the seat exceeded the EU action value, while LC_peak noise exposure surpassed the limit value of 140 dB(C) on all measured days. Noise and vibration exposure were constantly higher during TW than NTW harvesting but differences were small. Compared to other studies, the results show that harvesting on steep terrain increases noise and vibration exposure, while non-work time has the opposite effect on vibration and noise exposure. Full article

Safety zones protect firefighters from bodily injury and death caused by exposure to dangerous heat levels. These zones are defined by maintaining a safe distance from combustible fuels, a safe separation distance (SSD) derived from flame height. This study aimed to determine safety zones, integrating an existing automated identification-of-safety-zone model with vegetation height derived from a freely available high-resolution global canopy height dataset for Manavgat Forest Management Directorate (FMD) in Türkiye. Flame height, terrain slope, size of a safety zone, and distance to the closest road were also used as input in this model. The results indicated that vegetation height from high-resolution global canopy height offered promising results for determining potential safety zones (SZs) associated with SSD. Integrating the global canopy height dataset into the existing model could assist in determining the safety zone in the absence of lidar. Thus, this spatial model would provide a framework for decision-makers to develop fire prevention and suppression strategies for higher fire risk areas, especially before and during a fire. Full article

The development of efficient and sustainable electrocatalysts for optimizing methanol oxidation reactions (MORs) in direct methanol fuel cells (DMFCs) is crucial for the innovation of clean electrode energy technologies. This study highlights the synthesis and characterization of magnesium ferrite (MgFe₂O₄) and magnesium-based metal–organic framework (Mg-MOF) composites, utilizing cost-effective and scalable methods such as co-precipitation and ultrasound-assisted synthesis. The composite material, prepared in a 1:1 ratio, demonstrated enhanced catalytic performance due to the synergistic integration of MgFe₂O₄ and Mg-MOF. Comprehensive structural and morphological analyses, including X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), the Brunauer–Emmett–Teller (BET) technique, and X-ray photoelectron spectroscopy (XPS), confirmed the successful formation of the composite. Also, the modification of magnetic properties, particularly the values of coercive force (Hc), led to a significant enhancement in electrical and catalytic performance. The material exhibited mesoporous characteristics and an improved surface area. Electrochemical evaluations revealed superior MOR activity for the composite electrode, achieving a current density of 31.5 mA∙cm⁻² at 1 M methanol with an onset potential of 0.34 V versus Ag/AgCl, measured at a scan rate of 100 mV/s. Remarkably, the composite electrode showed a 75% improvement in current density compared to its components. Additionally, the composite exhibited a low overpotential of 350 mV and favorable Tafel slopes of 22.54 and 4.27 mV∙dec⁻¹ at high and low potentials, respectively, confirming rapid methanol oxidation kinetics on this electrode. It also demonstrated excellent stability, retaining 97.4% of its current density after 1 h. Electrochemical impedance spectroscopy (EIS) further revealed a reduced charge transfer resistance of 9.26 Ω, indicating enhanced conductivity and catalytic efficiency. These findings underscore the potential of MgFe₂O₄/Mg-MOF composites as cost-effective and high-performance anode materials for DMFCs, paving the way for sustainable energy solutions. Full article