Trend and Attribution Analysis of Runoff Changes in the Weihe River Basin in the Last 50 Years

In recent years, the Weihe River basin has experienced dramatic changes and a sharp decrease in runoff, which has constrained the sustainable development of the local society, economy, and ecology. Quantitative attribution analysis of runoff changes in the Weihe River basin can help to illustrate reasons for dramatic runoff changes and to understand its complex hydrological response. In this paper, the trends of hydrological elements in the Weihe River basin from 1970 to 2019 were systematically analyzed using the M–K analysis method, and the effects of meteorological elements and underlying surface changes on runoff were quantitatively analyzed using the Budyko theoretical framework. The results show that potential evapotranspiration and precipitation in the Weihe River basin have no significant change in 1970–2019; runoff depth has an abrupt change around 1990 and then decrease significantly. The study period is divided into the base period (1970–1989), PΙ (1990–2009), and PII (2010–2019). Compared with the base period, the elasticity coefficients (absolute values) of each element show an increasing trend in PΙ and PII. The sensitivity of runoff to these coefficients is increasing. The sensitivity of the precipitation is the highest (2.72~3.17), followed by that of the underlying surface parameter (−2.01~−2.35); the sensitivity of the potential evapotranspiration is the weakest (−1.72~−2.17). In the PΙ period, the runoff depth decreased significantly due to the combination effects of precipitation and underlying surface with the values of 6.18 mm and 13.92 mm, respectively. In the PII period, rainfall turned to an increasing trend, contributing to the increase in runoff by 11.80 mm; the further increase in underlying surface parameters was the main reason for the decrease in runoff by 22.19 mm. The significant increase in runoff by 8.54 mm because of the increased rainfall, compared with the PΙ periods. Overall, the increasing underlying surface parameter makes the largest contribution to the runoff changes while the precipitation change is also an important factor.

Optimization of running-in surface morphology parameters based on the AutoML model

Running-in is an important and relatively complicated process. The surface morphology prior to running-in affects the surface morphology following the running-in process, which in turn influences the friction and wear characteristics of the workpiece. Therefore, the establishment of a model for running-in surface morphology prediction is important to investigate the process and optimize the surface design. Black-box models based on machine learning have robust complex object simulation performance. In this paper, five common machine learning methods are applied to establish running-in modeling performance based on surface morphology parameters. The support vector machine has the best model performance. The change law of the surface morphology parameters is obtained based on model testing, and the surface morphology optimization is explored. When better oil storage capacity is required, the recommendation is to increase the Sq, Sdq and Sk surface parameter values while setting medium Sdc and Sdr surface parameter values. When a lower coefficient of friction (COF) is required, Sdc and Sdr should be decreased, and Sq and Sdq should be increased. When better support performance is required, Sdc, Sdq, and Sdr should be increased. This article provides a solution to establish a link between surface design and functional performance in the steady wear stage, further filling the gap in quality monitoring of lifecycles.

A comparison of head movements tests in force plate and accelerometer based posturography in patients with balance problems due to vestibular dysfunction

This study compares HS posturography on inertial sensors (MediPost) with force platform posturography in patients with unilateral vestibular dysfunction. The study group included 38 patients (age 50.6; SD 11.6) with unilateral vestibular weakness (UV) and 65 healthy volunteers (48.7; SD 11.5). HS tests were performed simultaneously on the force plate and with MediPost sensor attached at L4. Four conditions applied: eyes open/closed, firm/foam. The tests were performed twice, with the head moving at the frequency of 0.3 Hz (HS 0.3) and 0.6 Hz (HS 0.6). Mean sway velocity was significantly lower for MediPost than force plate in 4th condition both in UV and healthy group. For HS 0.3 the differences between devices were marginal; the highest sensitivity (87%) and specificity (95%) were in 4th condition. For HS 0.6 MediPost revealed lower sensitivity than force plate although the surface parameter improved results. MediPost IMU device and force platform posturography revealed a similar ability to differentiate between patients with balance problems in course of vestibular pathology and healthy participants, despite the differences observed between measuring methods. In some tests surface parameter may be more appropriate than sway velocity in improving MediPost sensitivity.