Search Results (1,183)

Background: COVID-19-associated coagulopathy (CAC) is a complex condition, with high rates of thrombosis, high levels of inflammation markers and hypercoagulation (increased levels of fibrinogen and D-Dimer), as well as extensive microthrombosis in the lungs and other organs of the deceased. It resembles, without being identical, other coagulation disorders such as sepsis-DIC (SIC/DIC), hemophagocyte syndrome (HPS) and thrombotic microangiopathy (TMA). Platelets (PLTs), key regulators of thrombosis, inflammation and immunity, are considered an important risk mediator in COVID-19 pathogenesis. Platelet index MPV/PLT ratio is reported in the literature as more specific in the prognosis of platelet-related systemic thrombogenicity. Studies of MPV/PLT ratio with regards to the severity of COVID-19 disease are limited, and there are no references regarding this ratio to the outcome of COVID-19 disease at specific time points of hospitalization. The aim of this study is to evaluate the relationship of COVID-19 mortality with the red cell distribution width–coefficient of variation (RDW-CV), platelets and MPV/PLT ratio parameters. Methods: Values of these parameters in 511 COVID-19 hospitalized patients were recorded (a) on admission, (b) as mean values of the 1st and 2nd week of hospitalization, (c) over the total duration of hospitalization, (d) as nadir and zenith values, and (e) at discharge. Results: As for mortality (survivors vs. deceased), statistical analysis with ROC curves showed that regarding the values of the parameters on admission, only the RDW-CV baseline was of prognostic value. Platelet parameters, absolute number and MPV/PLT ratio had predictive potential for the disease outcome only as 2nd week values. On the contrary, with regards to disease severity (mild/moderate versus severe/critical), only the MPV/PLT ratio on admission can be used for prognosis, and to a moderate degree. On multivariable logistic regression analysis, only the RDW-CV mean hospitalization value (RDW-CV mean) was an independent and prognostic variable for mortality. Regarding disease severity, the MPV/PLT ratio on admission and RDW-CV mean were independent and prognostic variables. Conclusions: RDW-CV, platelets and MPV/PLT ratio hematological parameters could be of predictive value for mortality and severity in COVID-19 disease, depending on the hospitalization timeline. Full article

In this study, the process of electrolytic–plasma nitrocarburizing (EPNC) of 20-grade steel was investigated using various electrolytes and temperature regimes. At the first stage, optical spectral analysis of plasma emission during EPNC was carried out with spectral registration in the range of 275–850 nm, which allowed the identification of active components (Hα, CN, Fe I, O I lines, etc.) and the calculation of electron density. Additionally, the EPNC process was recorded using a high-speed camera (1500 frames per second), which made it possible to visually evaluate the dynamics of arc and glow discharges under varying electrolyte compositions. At the next stage, the influence of temperature regimes (650 °C, 750 °C, and 850 °C) on the formation of the hardened layer was studied. Using SEM and EDS methods, the morphology, phase zones, and the distribution of chemical elements were determined. Microhardness measurements along the depth and friction tests were carried out. It was found that a temperature of 750 °C provides the best balance between the uniformity of chemical composition, high microhardness (~800 HV), and a minimal coefficient of friction (~0.48). The obtained results confirm the potential of the selected EPNC regime for improving the performance characteristics of 20-grade steel. Full article

This research presents a comprehensive methodology for calibrating Discrete Element Method (DEM) parameters governing rice grain interactions with biodegradable Polylactic Acid (PLA) components in agricultural bucket elevator systems. Rice grains, a critical global food staple requiring efficient post-harvest handling, were modeled as three-sphere clusters to accurately represent their physical dimensions (6.5 mm length), while the Hertz–Mindlin contact model provided the theoretical framework for particle interactions. The calibration process employed a multi-phase experimental design integrating Plackett–Burmann screening, steepest ascent method, and Face Central Composite Design to systematically identify and optimize critical micro-mechanical parameters for agricultural material handling. Statistical analysis revealed the coefficient of static friction between rice and PLA as the dominant factor, contributing 96.49% to system performance—significantly higher than previously recognized in conventional agricultural processing designs. Response Surface Methodology generated predictive models achieving over 90% correlation with experimental results from 3D-printed PLA shear box tests. Validation through comparative velocity profile analysis during bucket elevator discharge operations confirmed excellent agreement between simulated and experimental behavior despite a 20% discharge velocity variance that warrants further investigation into agricultural material-specific phenomena. The established parameter set enables accurate virtual prototyping of sustainable agricultural handling equipment, offering post-harvest processing engineers a powerful tool for optimizing bulk material handling systems with reduced environmental impact. This integrated approach bridges fundamental agricultural material properties with sustainable engineering design principles, providing a scalable framework applicable across multiple agricultural processing operations using biodegradable components. Full article

To address the high cost of cobalt in rare-earth hydrogen storage alloys, this study developed cost-effective low-cobalt and cobalt-free AB₅-type alloys. The results demonstrate that all synthesized alloys displayed a single-phase LaNi₅ structure possessing a homogeneous elemental distribution. Low-cobalt (La, Ce) (Ni, Co, Mn, Al)₅ alloy 4SC and cobalt-free (La, Ce) (Ni, Mn, Al)₅ alloy 7D exhibited similarly excellent electrochemical performance, including high discharge capacity, long cycle life, and superior high-rate discharge (HRD) capability. In addition, the kinetic test results show that the exchange current densities of these two alloys were quite similar, measuring 302.97 mA g⁻¹ and 317.70 mA g⁻¹, respectively. However, the hydrogen diffusion coefficient of 7D was significantly higher than that of 4SC, reaching 9.45 × 10⁻¹⁰ cm² s⁻¹, while that of 4SC was only 5.88 × 10⁻¹⁰ cm²/s. This work establishes a theoretical foundation for industrial-scale and cost-effective AB₅-type hydrogen storage alloys, offering significant commercial potential. Full article

Decentralized sanitation in rural areas urgently requires accessible and nature-based solutions to achieve Sustainable Development Goal 6 (clean water and sanitation for all). However, monitoring studies of such ecotechnologies in disperse communities remain limited. This study evaluated the performance of an evapotranspiration tank (TEvap), designed with community participation, for the treatment of domestic sewage in a rural Quilombola household in the Brazilian Cerrado. The system (total area of 8.1 m², with about 1.0 m² per inhabitant) was monitored for 218 days, covering the rainy season and the plants’ establishment phase. After 51 days, the TEvap reached operational equilibrium, maintaining a zero-discharge regime, and after 218 days, 92.3% of the total system inlet volumes (i.e., 37.47 in 40.58 m³) were removed through evapotranspiration and uptake by cultivated plants (Musa spp.). Statistical analyses revealed correlations that were moderate to strong, and weak between the blackwater level and relative humidity (Pearson correlation coefficient, r = 0.75), temperature (r = −0.66), and per capita blackwater contribution (r = 0.28), highlighting the influence of climatic conditions on system efficiency. These results confirm the TEvap as a promising, low-maintenance, and climate-resilient technology for decentralized domestic sewage treatment in vulnerable rural communities, with the potential to support sanitation policy goals and promote public health. Full article

Accurate estimation of long-term average (LTA) discharge is fundamental for water resource assessment, infrastructure planning, and hydrological modeling, yet it remains a significant challenge, particularly in data-scarce or ungauged basins. This study introduces an advanced machine learning framework to estimate long-term average discharge using globally available hydrological station metadata from the Global Runoff Data Centre (GRDC). The methodology involved comprehensive data preprocessing, extensive feature engineering, log-transformation of the target variable, and the development of multiple predictive models, including a custom deep neural network with specialized pathways and gradient boosting machines (XGBoost, LightGBM, CatBoost). Hyperparameters were optimized using Bayesian techniques, and a weighted Meta Ensemble model, which combines predictions from the best individual models, was implemented. Performance was rigorously evaluated using R², RMSE, and MAE on an independent test set. The Meta Ensemble model demonstrated superior performance, achieving a Coefficient of Determination (R²) of 0.954 on the test data, significantly surpassing baseline and individual advanced models. Model interpretability analysis using SHAP (Shapley Additive explanations) confirmed that catchment area and geographical attributes are the most dominant predictors. The resulting model provides a robust, accurate, and scalable data-driven solution for estimating long-term average discharge, enhancing water resource assessment capabilities and offering a powerful tool for large-scale hydrological analysis. Full article

The remote sensing inversion of the Suspended Sediment Concentration (SSC) at the Yellow River estuary is crucial for regional sediment management and the advancement of monitoring techniques for highly turbid waters. Traditional in situ methods and low-resolution imagery are no longer sufficient for high-accuracy studies. Using SSC data from the Longmen Hydrological Station (2019–2020) and Sentinel-2 imagery, multiple models were compared, and the random forest regression model was selected for its superior performance. A non-parametric regression model was developed based on optimal band combinations to estimate the SSC in high-sediment rivers. Results show that the model achieved a high coefficient of determination (R² = 0.94) and met accuracy requirements considering the maximum SSC, MAPE, and RMSE. The B4, B7, B8A, and B9 bands are highly sensitive to high-concentration sediment rivers. SSC exhibited significant seasonal and spatial variation, peaking above 30,000 mg/L in summer (July–September) and dropping below 1000 mg/L in winter, with a positive correlation with discharge. Spatially, the SSC was higher in the gorge section than in the main channel during the flood season and higher near the banks than in the river center during the dry season. Overall, the random forest model outperformed traditional methods in SSC prediction for sediment-laden rivers. Full article

Controlled iron extraction from iron-based sludge (Fe-Sludge) drainage and its use as a Fenton’s reagent is investigated in the current study for eliminating organics from launderette discharge stream. The influences of the iron dosage, hydrogen peroxide concentration, and pH are assessed as treatment factors for their direct impact on the oxidation of organic compounds. Additionally, optimal oxidation conditions are determined using the response surface methodology (RSM) technique, and the ranges of treatment variables are analyzed. The optimum values of a pH of 2.0, Fe sludge concentration of 99 mg/L, and H₂O₂ content of 402 mg/L resulted in optimal organics removal of up to 98%, expressed as Chemical Oxygen Demand (COD) removal. The oxidation efficacy attained from the design is confirmed and the model validation is assessed, and the suggestive model is accepted since it possesses a correlation coefficient of 97.7%. The thermodynamic and kinetic models are also investigated, and the reaction showed that the temperature increases resulted in the oxidation efficiency being reduced. The oxidation efficiency expressed as COD reduction is clearly characterized by first-order reaction kinetics. The thermodynamic characteristics indicated that the oxidation reaction was exothermic and not spontaneous. Full article

Thermal mass flow sensors (TMFS) are used to detect the flow rates of gases. TMFS elements are available in different technologies and, depending on the one used, the material choice of substrate, heater, and temperature sensors can limit their performance. In this work, a sensor element based on the Ensinger Microsystems Technology (EMST) is presented that uses PEEK as the substrate, nickel-chromium as the heater, and nickel as the temperature sensor material. The fabrication process of the element is described, the completion to a flow sensor with a control and readout circuit based on discharge time measurement with picosecond resolution is presented, and measurement results are shown, which are compared to sensors with a commercially available element based on thin film technology on ceramic and an element built with discrete components, all using the same electronics. It is shown that the operation of all sensor elements with the proposed readout circuit was successful, flow-dependent signals were achieved, and the performance of TMFS in EMST improved. Its heater shows better results compared to the commercial element due to material choice with a smaller temperature coefficient of resistance. In its current state, the TMFS in EMST is suitable to detect flow rates > 20 SLPM. The performance needs to be improved further, since the temperature sensors still differ too much from another. Full article

This paper analyzes the influence of the number of ignition coils and spark discharge energy on the Coefficient of Variation of Indicated Mean Effective Pressure (COV_IMEP) of an SI internal combustion piston engine. A modern electronically controlled induction ignition system is used during the test. Two fuels are used in the experiment. The reference fuel is gasoline and the tested fuel is ammonia. For the traditional fuel, using an additional ignition coil does not improve COV_IMEP. This parameter for gasoline has an almost constant value for different ignition system charging times. The situation is different for ammonia. This fuel requires high ignition energy. The use of one ignition coil demands a long charging time. For short charging times, unrepeatability of the engine cycles is unacceptable. The use of an additional ignition coil allowed to the charging coil timing to be shortened and the unrepeatable engine cycles to be reduced. This paper determined the maximum charging time of the used ignition coil, above which the spark parameters are worse. In addition, the influence of charging time and number of ignition coils on total spark energy, spark discharge duration, maximum spark power, and voltage during spark discharge for ammonia is presented. The data presented in this paper are developed based on measurements of current and voltage in the secondary winding of the ignition coil. A self-developed electronic device enabling the change in spark energy is used to control the ignition system. This paper also presents the construction of modern ignition systems, describes the functions of selected components, and briefly discusses their diagnostics. Full article

To investigate the relationship between the seeding performance of a novel pre-cut sugarcane planter designed by South China Agricultural University and operational settings, field seeding tests was conducted with the following protocol: First, the John Deere M1654 tractor’s forward velocity was calibrated, and the planter’s safe loading capacity was determined. Subsequently, eight experimental treatments (A–H) were designed to quantify the relationships between the three performance indicators: seeding density N, the seeding efficiency E and seeding uniformity (coefficient of variation, CV), and three key operational parameters: forward speed of planter v, the discharging sprocket rotational speed n, and the hopper outlet size w. Mathematical models (R20.979) between three key operational parameters with two performance indicators (N, E) was developed through analysis of variance (ANOVA) and regression analysis. The seeding rate per meter was confirmed to follow a Poisson distribution based on Kolmogorov–Smirnov (K–S) tests. When the CV was below 40%, the mean relative error remained within 3%. These findings provide a theoretical foundation for seeding performance prediction under field conditions. Full article

The role of weirs in flow regulation in water resources infrastructure and flood control is well known. In the meantime, the study of full-width plate weirs (FWPW), due to their wide application and lacking findings, is of great importance. In this study, experimental models were conducted at Babol Noshirvani University of Technology to investigate flow passing through FWPWs with five different heights (p = 0.07, 0.09, 0.11, and 0.15 m) under eight discharge conditions (Q = 1.4 to 6.3 L/s). The experiments were carried out in a flume measuring 4 m in length, 0.6 m in width, and 0.2 m in height. The discharges were measured with a calibrated flowmeter, and the water depths upstream of the weir (h) and the tailwater depths (h₁) were measured with a point gauge with an accuracy of 0.1 mm. For each test, the discharge coefficient (C_d), relative residual energy (E₁/E₀), and relative energy dissipation ((E₀ − E₁)/E₀) were computed. The proposed equation for calculating discharge achieved good accuracy with RMSE = 0.0002, MAE=0.0002, and R² = 0.997. Results show a reducing trend of C_d by increasing h/P, which is compatible with previous results. It was observed that at a constant discharge, relative residual energy reduces by an average of 47% by increasing weir height, and at a constant P, increasing flow discharge increases it a little. A novel accurate equation for relative energy dissipation in FWPW was proposed based on h/P that provided specific constant coefficients for each p value. Full article

Partial discharge (PD) in insulators will not only lead to the gradual degradation of insulation performance but even cause power system failure in serious cases. Because there is strong noise interference in the field, it is difficult to accurately locate the position of the PD source. Therefore, this paper proposes a three-dimensional spatial localization method of the PD source with a four-element ultra-high-frequency (UHF) array based on improved wavelet packet dynamic threshold denoising and the $G_{xx}-\beta$ generalized cross-correlation algorithm. Firstly, considering the field noise interference, the PD signal is decomposed into sub-signals with different frequency bands by the wavelet packet, and the corresponding wavelet packet coefficients are extracted. By using the improved threshold function to process the wavelet packet coefficients, the PD signal with low distortion rate and high signal-to-noise ratio (SNR) is reconstructed. Secondly, in order to solve the problem that the amplitude of the first wave of the PD signal is small and the SNR is low, an improved weighting function, $G_{xx}-\beta$, is proposed, which is based on the self-power spectral density of the signal and is adjusted by introducing an exponential factor to improve the accuracy of the first wave arrival time and time difference calculation. Finally, the influence of different sensor array shapes and PD source positions on the localization results is analyzed, and a reasonable arrangement scheme is found. In order to verify the performance of the proposed method, simulation and experimental analysis are carried out. The results show that the improved wavelet packet denoising algorithm can effectively realize the separation of PD signal and noise and improve the SNR of the localization signal with low distortion rate. The improved $G_{xx}-\beta$ weighting function significantly improves the estimation accuracy of the time difference between UHF sensors. With the sensor array designed in this paper, the relative localization error is 3.46%, and the absolute error is within 6 cm, which meets the requirements of engineering applications. Full article

Suyukou Gully, located on the eastern slope of the Helan Mountains in northwest China, is a typical debris-flow-prone catchment characterized by a steep terrain, fractured bedrock, and abundant loose colluvial material. The area is subject to intense short-duration convective rainfall events, which often trigger destructive debris flows that threaten the Suyukou Scenic Area. To investigate the dynamics and risks associated with such events, this study employed the FLO-2D two-dimensional numerical model to simulate debris flow propagation, deposition, and hazard distribution under four rainfall return periods (10-, 20-, 50-, and 100-year scenarios). The modeling framework integrated high-resolution digital elevation data (original 5 m DEM resampled to 20 m grid), land-use classification, rainfall design intensities derived from regional storm atlases, and detailed field-based sediment characterization. Rheological and hydraulic parameters, including Manning’s roughness coefficient, yield stress, dynamic viscosity, and volume concentration, were calibrated using post-event geomorphic surveys and empirical formulations. The model was validated against field-observed deposition limits and flow depths, achieving a spatial accuracy within 350 m. Results show that the debris flow mobility and hazard intensity increased significantly with rainfall magnitude. Under the 100-year scenario, the peak discharge reached 1195.88 m³/s, with a maximum flow depth of 20.15 m and velocities exceeding 8.85 m·s⁻¹, while the runout distance surpassed 5.1 km. Hazard zoning based on the depth–velocity (H × V) product indicated that over 76% of the affected area falls within the high-hazard zone. A vulnerability assessment incorporated exposure factors such as tourism infrastructure and population density, and a matrix-based risk classification revealed that 2.4% of the area is classified as high-risk, while 74.3% lies within the moderate-risk category. This study also proposed mitigation strategies, including structural measures (e.g., check dams and channel straightening) and non-structural approaches (e.g., early warning systems and land-use regulation). Overall, the research demonstrates the effectiveness of physically based modeling combined with field observations and a GIS analysis in understanding debris flow hazards and supports informed risk management and disaster preparedness in mountainous tourist regions. Full article

In this investigation, a comprehensive validation framework for an integrated electrochemical-thermal model that addresses critical thermal management challenges in lithium-ion batteries (LIBs) is presented. The two-dimensional numerical model combines the Newman–Tiedemann–Gu–Kim (NTGK) electrochemical-thermal battery framework with the enthalpy-porosity approach for phase change material (PCM) battery thermal management systems (BTMSs). Rigorous validation against benchmarks demonstrates the model’s exceptional predictive capability across a wide range of operating conditions. Simulated temperature distribution and voltage capacity profiles at multiple discharge rates show excellent agreement with the experimental data, accurately capturing the underlying electrochemical-thermal mechanisms. Incorporating Capric acid (with a phase transition range of 302–305 K) as the PCM, the thermal management model demonstrates significantly improved accuracy over existing models in the literature. Notable error reductions include a 78.3% decrease in the Mean Squared Error (0.477 vs. 2.202), a 53.4% reduction in the Root Mean Squared Error (0.619 vs. 1.483), and a 55.5% drop in the Mean Absolute Percentage Error. Statistical analysis further confirms the model’s robustness, with a high coefficient of determination (R² = 0.968858) and well-distributed residuals. Liquid fraction evolution analysis highlights the PCM’s ability to absorb thermal energy effectively during high-discharge operations, enhancing thermal regulation. This validated model provides a reliable foundation for the design of next-generation BTMS, aiming to improve the safety, performance, and lifespan of LIBs in advanced energy storage applications where thermal stability is critical. Full article