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The meta-analysis is to evaluate the predictive value of the blood urea nitrogen / creatinine ratio (BCR) for long-term outcomes in patients with heart failure (HF). PubMed, EMBASE, the Cochrane library, and Web of Science were searched for relevant studies from inception to October 2023. STATA SE 14.0 software was used for statistical analysis. A total of 2036 reports were identified with 14 studies meeting pre-designed inclusion criteria. Three long-term outcomes were investigated. In patients with HF, the increase of BCR level indicated a greater risk of all-cause mortality (HR = 1.67, 95% CI 1.38–2.00; I2 = 90.8%, P = 0.000). The acute HF (AHF) subgroup demonstrated a higher risk of all-cause mortality (HR = 1.79, 95% CI 1.15–2.79; I2 = 93.9%, P = 0.000) as did the non-AHF subgroup (HR = 1.51, 95% CI 1.34–1.71; I2 = 37.1%, P = 0.122). The subgroup (≤ 70 years old) demonstrated a lower risk of all-cause mortality in patients with HF (HR = 1.62, 95% CI 1.35–1.94; I2 = 68.3%, P = 0.004) as did the subgroup (> 70 years old) (HR = 1.67, 95% CI 1.19–2.34; I2 = 88.3%, P = 0.000). In addition, this study did not support the predictive value of BCR in CVD mortality (HR = 1.48, 95% CI 0.91–2.43; I2 = 63%, P = 0.100) and HF hospitalization (HR = 1.28, 95% CI 0.73–2.24; I2 = 77.5%, P = 0.035). Sensitivity analysis showed that all the results were robust. In summary, the results showed that the blood urea nitrogen / creatinine ratio (BCR) had a significant predictive value for all-cause mortality in patients with heart failure and was a fairly promising predictor obviously. Moreover, more studies are needed to further determine the predictive value of BCR in other long-term outcomes such as CVD mortality, HF hospitalization or aborted cardiac arrest. [ABSTRACT FROM AUTHOR]

Small-radius wheels are gradually introduced on special rail vehicles, such as double-decker coaches and piggyback wagons. It allows for a low-floor design and further increases the loading capacity of vehicles. From the perspective of vehicle dynamics, small-radius wheels have lower unsprung mass than the nominal wheels with a radius of 460 mm, and it could mitigate the wheel-rail dynamic interaction. Also, the contact patch size is reduced due to the increased curvature of the rolling contact circle, and they are more sensitive to changes in the track geometry than nominal wheels, especially in turnouts with discontinuous rail profiles. To investigate the dynamic response of small-radius wheels in a turnout, the Manchester Benchmark passenger coach with variable radius wheels and a left-hand turnout with a radius of 245 m are introduced in this work. The influence of wheel radii on the running performance, including the wheel-rail interaction and wheel damage behaviour, is investigated by numerical simulations. In addition, a sensitivity study is executed to evaluate the influence of unsprung mass and wheel flange friction on the performance of a vehicle whose wheel radius is 275 mm, and the potential remedy to mitigate high wheel wear is proposed. [ABSTRACT FROM AUTHOR]

In addition to the discontinuity of the rail profile of a normal turnout, the unique S-shaped curve of a crossover significantly affects the negotiation performance of a train. For heavy-haul freight trains, the in-train forces generated during the braking process may further deteriorate the running safety. Investigating the dynamic behaviour of the train passing through the crossover under braking forces, therefore, can provide a reasonable basis for ensuring train safety. This paper analyses the dynamic response and wheel wear of a three-vehicle train negotiating a single crossover under variable conditions, including variable braking forces, wheel-rail friction coefficient, and crossover layout forms. The results show that the three factors have considerable influences on train safety. If one of the three factors keeps an ideal level, the safe probability of empty wagons can be significantly improved. Considering that there are still some crossovers with tight curves in the existing railway system, avoiding large braking or lubricating the wheel flange in the crossover is still an effective solution to improve the vehicle's performance. In addition, for a new single crossover, a 600-m-radius curve is a good option for balancing permissible train speeds and construction costs of the crossover. [ABSTRACT FROM AUTHOR]

The friction draft gear with hysteresis characteristics is one of the typical nonlinear elements in longitudinal train dynamics (LTD). Due to the nonlinear hysteresis of friction damping, the discontinuity between loading and unloading envelopes becomes a mathematical integration issue when adopting look-up table methods to establish draft gear models. It might cause integration divergence and wrong results if ignored. To solve this discontinuity, three different transitional strategies (velocity-dependent, intermediate slope, and smoothing approximation) are applied to building draft gear models, and the one-dimensional (1D) longitudinal train model adopting the 'Zhai' integration method is used. To ensure accurate results, the international benchmark cases of LTD are studied, and three draft gear models with different transitional strategies are compared in this paper. The results show that these three models can successfully work with 'Zhai' method in the LTD simulation to achieve the force agreement with benchmark cases. Compared to the other two models, the velocity-dependent model doesn't exhibit good buffer deflection agreement and requires a smaller step size to achieve convergent results. Therefore, it is recommended that adopting the intermediate slope method or smoothing approximation approach avoids discontinuity problems of modelling draft gears in LTD. [ABSTRACT FROM AUTHOR]

• The angular domain synchronous averaging (ADSA) method for wheel flat detection is proposed. • Simulation and experiment study on the effectiveness of the ADSA method. • This method can remove the interfering signals due to special track geometries or track defects. • This method can identify the position and the number of wheel flats. Wheel flats (WFs) can generate periodic impact forces and aggravate the wheel-rail interaction. Therefore, the early detection of WFs is significant for railway operators to lower the maintenance cost. In this work, the angular domain synchronous averaging (ADSA) method is employed to detect WFs on railway vehicles since it can handle the non-stationary vibration process of rotating machines by processing the vibration data in the angular domain. Furthermore, the short-time irregular impulses, such as those caused by crossings and rail joints, can be attenuated by using synchronous averaging technology. The periodic impact caused by WFs can be easily observed in the polar coordinate using the ADSA method, which is verified by one multibody system (MBS) simulation and one field experiment. Besides, the sensitivity of this method to various flat dimensions and multiple flats is also studied in the MBS simulation. [ABSTRACT FROM AUTHOR]

Aiming at preventing frequently occurred coupler jack-knifing in slave control locomotives of 20,000-tonne heavy-haul trains, a theoretical and experimental research on enhancing the coupler stability has been carried out. Field tests are conducted to ascertain the load characteristics of the slave control locomotive, and the coupler stability mechanism of the locomotive is studied. A dynamic simulation model considering the locomotive, adjacent wagons, and attached coupling devices is established and validated. Based on the model, countermeasures for improving the coupler stability are studied. The field test results indicate that: 1) the slave control locomotives suffer from sustained compressive forces less than 1500kN at the braking stage of cycle braking, while the maximum short-term impact force at the release stage exceeds 2000kN; 2) The coupler jack-knifing mostly occurs at the braking stage, and the yaw angles of the middle couplers are larger than the front and rear couplers. According to the theoretical analysis and dynamic simulation results, the coupler stability can be improved by increasing the stiffness of secondary lateral bump stops and reducing its clearance. Moreover, the proposed countermeasure of setting up lateral bump stop to locomotive couplers is proved to be effective to prevent the coupler jack-knifing. [ABSTRACT FROM AUTHOR]

The aim of local path planning for unmanned surface vehicles (USVs) is to avoid unknown dynamic or static obstacles. However, current relative studies have not fully considered the impact of ocean environmental factors which significantly increase the control difficulty and collision risk of USVs. Therefore, this work studies two ocean environmental factors, namely, wave and current, given that they both have a significant impact on USVs. Furthermore, we redesign a kinematic model of an USV and the evaluation function of a classical and practical local path planning method based on the dynamic window approach (DWA). As shown by the results of the simulations, the path length was impacted mainly by the intensity of the environmental load and slightly by the direction of the environmental load, but the navigation time was significantly influenced by both. Taking the situation in still water as a benchmark in terms of the intensity and direction of the environmental factors, the maximum change rates of the path length were 8.6% and 0.6%, respectively, but the maximum change rates of the navigating time were 17.9% and 25.6%, separately. In addition, the average calculation time of each cycle was only 0.0418 s, and the longest time did not exceed the simulation time corresponding to a single cycle of 0.1 s. This method has proven to be a good candidate for real-time local path planning of USVs since it systematically considers the impact of waves and currents on the navigation of USVs, and thus ensures that USVs can adjust to the planned path in time and avoid obstacles when navigating in the real ocean environment. [ABSTRACT FROM AUTHOR]

Failures of rotating mechanical components (e.g., turbine, gear, wheelset) often cause serious shocks to the mechanical system, and real-time detection of these shocks is of importance in maintenance decision-making for the equipment. The service conditions (e.g., rotating speed, load) of rotating machinery are often complex, and therefore the self-adaptability and generalizability of shock detection methods under variable operating conditions is an issue worthy of in-depth study. In this paper, a novel hybrid method combining a threshold-based method for feature extraction and a machine-learning-based method for pattern recognition is developed. This method consists of two steps. First, an adaptive feature called activated time-domain image (ATDI) is proposed, where two adaptive activation functions are proposed to activate the time-domain vibration signals after being preprocessed. The resulting ATDI feature image is highly adaptive and changes adaptively depending on the operating conditions. Then, a hybrid method combining ATDI and deep neural network (ATDI-DNN) is developed, where a circshift-based data augmentation method is introduced for enriching the ATDI feature images. Finally, the proposed ATDI-DNN method is used for wheel flat detection of a railway vehicle under variable operating conditions. Experiments demonstrate that the ATDI-DNN model trained with samples from one speed level can be directly applied to other speed levels, and its superiority is demonstrated by comparative methods. The proposed method can be extended to shock detection of other similar rotating machinery. [ABSTRACT FROM AUTHOR]