The regional features of precipitation variation trends over Sichuan in China by the ESMD method

Based on a precipitation time series from 49 meteorological stations in Sichuan Province during the period from 1961 to 2011, the multi-scale characteristics of precipitation variability are analyzed using the extreme-point symmetric mode decomposition method (ESMD). Regional differences in variation trends and change-points were also preliminarily discussed. The results indicated that in the last 50+ years, the overall precipitation in Sichuan Province has exhibited a significant non-linear downward trend, and its changes have clearly exhibited an inter-annual scale (quasi-3 and quasi-8-year) and interdecadal scale (quasi-13-year). The variance contribution rates of each component demonstrated that the inter-annual change had a strong influence on the overall precipitation change in Sichuan Province, and the reconstructed inter-annual variation trend could describe the fluctuation state of the original precipitation during the study period. The reconstructed interdecadal variability revealed that the climate mode in Sichuan Province had divided into three distinct variation periods with 1973 and 1998 as the boundaries. Furthermore, there were regional differences in the non-linear changes and change-points of precipitation. In addition, in order to study the relations between the changing more or less of rising or decrease and meteorological station’s geographical position (latitude, longitude and elevation) i.e., the Cokriging interpolation technique is applied directly to precipitation variation trend components through ESMD decomposition. At the same time, the results also suggested that the ESMD method can effectively reveal variations in long-term precipitation sequences at different time scales and can be used for the complex diagnosis of non-linear and non-stationary signal changes.

Research on Low-Speed Driving Model of Ultrasonic Motor Based on Beat Traveling Wave Theory

This paper proposes a driving method, the superimposed pulse driving method, that can make an ultrasonic motor run at a low speed. Although this method solves the periodic oscillation of speed in a traditional low-speed driving motor, it still has a small periodic fluctuation, which affects the stability of the speed. To reduce the fluctuation rate of the motor speed, the structure model and driving model of the motor are established, based on the theory of a beat traveling wave, and the motion characteristics of the particle point are analyzed in this paper. The simulation curve of the motor speed is obtained according to the stator and rotor contact model and the transfer model. The research shows that the driving method introduced in this paper causes the stator surface to generate a traveling beat wave, and the driving end of the stator generates an intermittent reciprocating vibration and drives the rotor rotation, which is the mechanism of low-speed operation when the driving method is used to drive the motor, as well as the reason for the periodic fluctuation of the motor speed. To improve the speed stability, this paper controlled the output performance of the motor by changing the two control variables—prepressure and frequency difference—and concluded that the variation trend of the average speed and speed volatility were consistent with the variation trend of the motor’s average speed determinant and the speed volatility determinant, respectively, which is verified by the velocity measurement experiment and the vibration measurement experiment. These insights lay the theoretical foundation for the velocity adjustment and stability optimization and, finally, the application of the new driving method is prospected.

Comparative analysis and forecasting of isentropic efficiency of gas turbine compressor with ARIMA, VAR, NARNN and ANFIS approaches

It is extremely important to monitor the status of gas turbine to ensure its safe and reliable operation. In this work, the variation trend of isentropic efficiency of compressor is analysed based on the measured data of F-class heavy-duty gas turbine in practical industrial application. The actual measured data of F-class heavy-duty gas turbine includes the data under start-stop and unstable working conditions, which cannot be directly used for calculation and analysis. To solve this problem, the data selection rules are designed and determined according to the operating conditions of gas turbine to select the data under effective working state. The isentropic efficiency of compressor is calculated based on the selected data. Then the forecasting effects of four forecasting methods on the variation trend of isentropic efficiency of compressor are studied. Four indexes, namely, symmetric mean absolute percentage error (SMAPE), mean absolute percentage error (MAPE), root mean square error (RMSE), and similarity (SIM) values are utilized to evaluate the forecasting accuracy. The research results indicate that the Adaptive Neuro-Fuzzy Inference System (ANFIS) method has better forecasting effect than Autoregressive Integrated Moving Average (ARIMA), Vector Autoregression (VAR) and Nonlinear Autoregression Neural Network (NARNN) for this F-class heavy-duty gas turbine. Through the ANFIS method, the SIM up to 96.77%, the SMAPE and MAPE are less than 0.1, and the RMSE is only 0.1157. Therefore, the ANFIS method is suitable for forecasting the isentropic efficiency of this F-class heavy-duty gas turbine compressor.

Lightning Behaviour during the COVID-19 Pandemic

Background COVID-19 has drastically dampened human activities since early 2020. Studies have shown that this has resulted in changes in air temperature and humidity. Since lightning activities are dependent on air temperature and humidity, this study is conducted to evaluate the correlation between the intensity of lightning activities with the atmospheric changes, and investigates the changes, in lightning activities due to atmospheric changes during the COVID-19 pandemic. Methods The hypothesis was tested through a t-test and Pearson’s correlation study. The variation trend of lightning strikes count (LSC) in Europe and Oceania during the five months COVID-19 lockdown period (March – July) compared to the same period in the previous five years from 2015 to 2019 is investigated. Results Statistical analysis shows the LSC in Europe and Oceania during the lockdown period dropped significantly by more than 50% and 44% respectively compared to the same period in previous five years. Furthermore, LSC was found to be positively correlated with air temperature and relative humidity in Europe. However, in Oceania, LSC seems to be only positively correlated with air temperature but negatively correlated with relative humidity. Conclusions This study seems to suggest that lightning activities have significantly changed during this pandemic due to reduction in human activities.

Mechanical and Electronic Properties of DNTF Crystals under Different Pressure

In the present study, the effects of pressure on the structure, elastic properties and electronic structure of DNTF compounds are studied using the first principles method. It is found that pressure has a great influence on lattice constants. When the pressure reaches 80 GPa, the structure of DNTF changes suddenly. The variation trend of C11, C22 and C33 values is consistent with that of pressure. In addition, pressure can improve the compressibility and shear resistance of the DNTF compound. The pressure can reduce the bandgap and further increases the charge density, causing DNTF to decompose and explode.

Transformations in Plasma Metabolic Profiles of Patients with Major Depression During Treatment: A Pilot Metabolomics Study

Background Major depression disorder (MDD) is a mental disease that seriously endangers human physical and mental health. The purpose of present study is to detect the differences of plasma metabolic profiles between MDD patients and healthy controls. Moreover, the hospitalization process of MDD patients was followed to explore the reversal of metabolic abnormalities in MDD patients by conventional treatment in the form of self-control.Methods Ultra-Performance Liquid Chromatography- Mass Spectrometry (UPLC-MS) was used to detect the metabolic profiles in 47 plasma samples from 12 controls and 12 MDD patients. Multivariate statistical analysis and K-means clustering were operated to search for significantly different metabolites (SDMs) between pair-comparison groups and specific metabolites (SMs) with ideal variation trend in relative content. Finally, the metabolites were integrated into Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to preliminarily explore the potential mechanism of MDD disrupting the metabolic process.Results There were significant differences in plasma metabolic profiles between healthy controls and MDD patients. A total of 14 SDMs between untreated MDD patients and healthy controls were classified into the top ten KEGG pathways enrichment, among which the relative contents of 4 SMs, 9-HPODE, imidazoleacetic acid, thromboxane B2 (TXB2), and arachidonic acid (AA) showed a regular variation trend after MDD patients’ treatment. A new metabolite-pathway network containing 4 SMs and 8 pathways was accessed after further integration analysis. The sample size calculation showed that a verification set of 84-135 subjects (containing healthy controls and MDD paients) was desired to confirm the results of this study.Conclusion The results indicate that the transition in metabolic pathways during the occurrence and treatment process of MDD is mainly dominated by transformations in lipid metabolism and its relevant signaling pathway system. Additionally, histidine metabolism is also engaged. Subsequent large-scale validation study is acquired to evaluate whether the selected metabolites have the potential to diagnose and access the therapeutic effect of MDD, and to explore the probable mechanism of MDD in combination with other technologies.

Lightning Behaviour during the COVID-19 Pandemic

Background COVID-19 has drastically dampened human activities since early 2020. Studies have shown that this has resulted in changes in air temperature and humidity. Since lightning activities are dependent on air temperature and humidity, this study is conducted to evaluate the correlation between the intensity of lightning activities with the atmospheric changes, and investigates the changes, in lightning activities due to atmospheric changes during the COVID-19 pandemic. Methods The hypothesis was tested through a t-test and Pearson’s correlation study. The variation trend of lightning strikes count (LSC) in Europe and Oceania during the five months COVID-19 lockdown period (March – July) compared to the same period in the previous five years from 2015 to 2019 is investigated. Results Statistical analysis shows the LSC in Europe and Oceania during the lockdown period dropped significantly by more than 50% and 44% respectively compared to the same period in previous five years. Furthermore, LSC was found to be positively correlated with air temperature and relative humidity in Europe. However, in Oceania, LSC seems to be only positively correlated with air temperature but negatively correlated with relative humidity. Conclusions This study seems to suggest that lightning activities have significantly changed during this pandemic due to reduction in human activities.

Research on Bonding Performance of Anchorage Caisson Foundation with Different Contact Surfaces and Grouting Bed

In view of the first domestic offshore suspension bridge with caisson foundation, this paper mainly studies the bonding properties between underwater pre-filled aggregate grouting bed and anchorage caisson foundation. Through the test, the cohesive force of adding ordinary concrete between the anchorage caisson foundation and the grouting bed, the cohesive force of adding paper base asphalt felt between the anchorage caisson foundation and the grouting bed, and the cohesive force of adding geotextile between the anchorage caisson foundation and the grouting bed are measured, respectively. When the contact surface is concrete and geotextile, the fracture form of the specimen was analyzed by numerical simulation, and the AE variation trend of the two specimens have been studied. The results of this article can provide references for other projects.

The Trend of the Distribution of Ectopic Pregnancy Sites and the Clinical Characteristics of Cesarean Scar Pregnancy

Objective: To investigate the distribution and its variation trend of the ectopic site and the clinical characteristics of cesarean scar pregnancy, to provide clues for further clinical practice. Methods: 3915 patients are brought into our study. To calculate the distribution of the implantation of ectopic pregnancy. Then analyze with trend χ2 test and calculate the quantity of each type of ectopic pregnancy during the year 2012-2015 and the year 2016-2019 to analyze the variation trend. Results: 1. The proportion of each site of ectopic pregnancy is as following: tubal pregnancy (84.70%), ovarian pregnancy (1.56%), cesarean scar pregnancy (8.63%), abdominal pregnancy (0.61%), cornual pregnancy (2.68%), cervical pregnancy (0.49%), heterotopic pregnancy (0.43%). 2. Through trend χ2 test, the ratio of cesarean scar pregnancy to ectopic pregnancy showed an increasing trend(P=0.005). From the year 2012-2015 to the year 2016-2019, the ratio of cesarean scar pregnancy to ectopic pregnancy increased from 5.74% to 11.81%(P<0.001). 3.72.78%(246/338) cesarean scar pregnancy patients had cesarean delivery once, 25.15%(85/338) had cesarean delivery twice, and 2.07%(7/338) had cesarean delivery three times. 80.18%(271/338) had aborted before. The most common clinical manifestations are amenorrhea (98.52%), abdominal pain (25.74%) and vaginal bleeding (67.76%), the most common sign is hysterauxesis (46.75%). Conclusion: As the increasing of the ratio of cesarean scar pregnancy to ectopic pregnancy, the cesarean delivery rate should be decreased to decrease the morbidity of cesarean scar pregnancy.