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By taking the spring mass damping system of the single degree of freedom excited by the eccentric rotor as the object， Sommerfeld effect of the non-ideal vibration system driven by the AC motor as the prime motor was studied. The electromagnetic torque formula of the AC motor was introduced to establish the dynamic model of the vibration system driven by the AC motor. Based on the small parameter averaging method， the approximate solution of the vibration system response was obtained. According to the solution， the torque balance equation of the motor in steady-state motion was derived. Numerical analysis illustrated that the angular velocity of the motor and the frequency of power will jump in the resonance region， and the relationship between the amplitude of the system and the frequency of power has hard non-linear characteristics. The mechanism of these phenomena was explained by the stability judgment conditions， and the correctness of the theoretical method was verified by the numerical time domain simulation. Finally， the key structural parameters were discussed quantitatively and qualitatively. [ABSTRACT FROM AUTHOR]

To comprehensively understand the repetitive jump ability, this paper explores the research progress of repetitive jump ability abroad by reviewing related foreign literature, including the influencing factors, testing methods, and training strategy. The results show that: (1) in terms of influencing factors, physiological factors include anaerobic capacity, thermal environment, age and gender; biomechanical factors include inter-limb coordination, vertical stiffness, peak force, flight and ground contact times, lower-extremity joint angles, and muscle activation degree; training factors include lower-limb explosive force, relative strength and reaction strength. (2) in terms of testing methods, the differences and connections between various methods focus on movement pattern, duration, interval and jump frequency; the power index has high reliability and validity, but the jump height and fatigue index in some methods lack of test with reliability and validity. The testing methods are commonly applied to sports primarily involving in jump and to sports that emphasizes on conducting repeated explosive lower-limb movements. These methods can used to evaluate lower-limb explosive power endurance and anaerobic capacity. (3) Regarding training strategy, acute training includes squat exercises and cold therapy recovery; long-term training includes specific practical training, plyometrics, combination training of plyometrics and resistance, and repeated-sprint training. The future research should be focus on followings: (1) exploring the influence of aerobic capacity on interval jump performance, as well as the changes in biomechanical parameters of upper-limb swing motion and their impacts on jump performance during repetitive jump; (2) optimizing and developing testing methods and indicators that are consistent with the characteristics about the sports; (3) further enriching acute and long-term training strategy. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Donghua University (Natural Science Edition) is the property of Journal of Donghua University (Natural Science) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ｃｏｎｓｉｄｅｒｉｎｇ ｔｈｅ ｊｕｍｐｉｎｇ ｂｅｈａｖｉｏｒｓ ａｎｄ ｌｅｖｅｒａｇｅ ｅｆｆｅｃｔｓ ｉｎ ｔｈｅ ｓｔｏｃｋ ｍａｒｋｅｔ, ａ ｎｅｗ ｍｕｌｔｉｆｒａｃｔａｌ ｖｏｌａｔｉｌｉｔｙ ｍｏｄｅｌ ｗａｓ ｃｏｎｓｔｒｕｃｔｅｄ ｂａｓｅｄ ｏｎ ｔｈｅ ＨＡＲ ｍｏｄｅｌ. Ｔａｋｉｎｇ ５ ｍｉｎ ｈｉｇｈ- ｆｒｅｑｕｅｎｃｙ ｄａｔａ ｏｆ Ｓｈａｎｇｈａｉ ｃｏｍｐｏｓｉｔｅ ｉｎｄｅｘ ａｎｄ Ｓｈｅｎｚｈｅｎ ｃｏｍｐｏｎｅｎｔ ｉｎｄｅｘ ａｓ ｔｈｅ ｒｅｓｅａｒｃｈ ｓａｍｐｌｅｓ ａｎｄ ｕｓｉｎｇ ｔｈｅ ｔｅｓｔ ｍｅｔｈｏｄ ｏｆ “ｍｏｄｅｌ ｃｏｎｆｉｄｅｎｃｅ ｓｅｔ”(ＭＣＳ), ｔｈｅ ｐｒｅｄｉｃｔｉｏｎ ａｂｉｌｉｔｙ ｏｆ ｅａｃｈ ｖｏｌａｔｉｌｉｔｙ ｍｏｄｅｌ ｔｏ Ｃｈｉｎａ’ｓ ｓｔｏｃｋ ｍａｒｋｅｔ ｉｎ ｔｈｅ ｔｗｏ ｓｕｂ-ｓａｍｐｌｅｓ ｏｆ ｈｉｇｈ ｖｏｌａｔｉｌｉｔｙ ａｎｄ ｌｏｗ ｖｏｌａｔｉｌｉｔｙ ｗａｓ ｅｍｐｉｒｉｃａｌｌｙ ｃｏｍｐａｒｅｄ. Ｔｈｅ ｒｅｓｕｌｔｓ ｓｈｏｗｅｄ ｔｈａｔ ｔｈｅ ｐｒｏｐｏｓｅｄ ｍｕｌｔｉｆｒａｃｔａｌ ｖｏｌａｔｉｌｉｔｙ ｍｅａｓｕｒｅ ｉｎｄｅｘ ａｎｄ ｉｔｓ ｍｅａｓｕｒｅｍｅｎｔ ｍｏｄｅｌ ｈａｖｅ ａ ｇｏｏｄ ｐｒｅｄｉｃｔｉｖｅ ｆｕｎｃｔｉｏｎ, ｅｓｐｅｃｉａｌｌｙ ｉｎ ｔｈｅ ｐｅｒｉｏｄ ｏｆ ｈｉｇｈ(ｅｘｔｒｅｍｅ) ｖｏｌａｔｉｌｉｔｙ. Ｔｈｅ ｒｅｓｕｌｔｓ ａｒｅ ｅｘｐｅｃｔｅｄ ｔｏ ｐｒｏｖｉｄｅ ｎｅｗ ｉｄｅａｓ ａｎｄ ｍｅｔｈｏｄｓ ｆｏｒ ｔｈｅ ｍａｎａｇｅｍｅｎｔ ａｎｄ ｃｏｎｔｒｏｌ ｏｆ ｆｉｎａｎｃｉａｌ ｒｉｓｋｓ, ｉｎ ｐａｒｔｉｃｕｌａｒ ｅｘｔｒｅｍｅ ｒｉｓｋｓ. [ABSTRACT FROM AUTHOR]

Most HAR-RV-JUMP models of high frequency volatility only include the endogenous variables related to high frequency volatility, but ignore the impact of external information, which may lead to errors and bias in estimation and prediction. This paper introduces the impact of the external information into the existing HAR-RV-JUMP models by constructing a high-frequency volatility model with signed jump variation. These new models take into account not only the common influence of endogenous factors and external information, but also the asymmetric effect of multi-information on high frequency volatility. Then, high-frequency trading data of CSI 300 Index and CSI 500 Index is collected to make estimates and prediction, and rolling time window prediction method and SPA test are used to evaluate the forecasting capacity of HAR-V-RV-JUMP model. The result shows HAR-V-RV-JUMP models boast higher prediction accuracy in high frequency volatility than HAR-RV-JUMP models. However, the result also shows the performance of HAR-V-RV-JUMP models is better in predicting high frequency volatility during the stable period. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Based on realized GARCH model with skew t distribution, we proposed a tail risk estimation method which incorporates both high frequency and low frequency information. Realized GARCH models with RV, RRV and BPV constitute the competing models. The empirical analysis using high-frequency data of Shanghai composite index shows that the realized GARCH model estimates VaR and ES more accurately than the EGARCH model, and that incorporating realized measures robust to microstructure noise and jump contributes to improve the estimation accuracy of VaR and ES. Moreover, the performance of the realized GARCH model is robust during the pre- and post-crisis period. [ABSTRACT FROM AUTHOR]

The generalized double exponential distribution is proposed by combining the asymmetric and biased double exponential distributions, which could fully disclose the features of bias, asymmetry, and steep-peak and heavy tails in financial markets. By referencing to the KDJ model, the generalized double exponential jump diffusion model (GDED-KDJ) is proposed and analyzed. Taking into account the heteroskedasticity and volatility jump, and the double jump diffusion model proposed by Eraker, we further extend the GDED-KDJ to the generalized double exponential double-jump diffusion model, i.e., GDED-SVIJ model. Then, we analyze the features of the new model, such as the general, biased, asymmetric and steep-peak and heavy tails, which also present its superiority. Also, we study the conditions likelihood function and MCMC iterative algorithm of the new model. At last, by the empirical study about three metal futures in SHEF, the feasibility and superiority of the new model are showed and proved. [ABSTRACT FROM AUTHOR]

Based on hydrologic data of long time series about Xiaohuangguayuan hydrometric station of Longchuan River, the multi-time-scale and jump characteristics of precipitation and sediment discharge time series of Longchuan River were studied utilizing wavelet transform. Results show that the annual precipitation of Xiaohuangguayuan station has quasi-prime periods of 2 a and 4 a; the annual sediment discharge has quasi-prime periods of 2 a, 4 a, and 9.5 a. The sediment discharge of Longchuan River distributes unevenly within a year, the amount from July to October accounts for 96.7%, particularly in June and August it takes almost 55.7%. The cause of the changes within a year and high-frequency tremble is due to the changing time of precipitation. The river sediment stems from midstream and downstream of Longchuan River (the percentage is 94.2% of the total watershed), and the total load sediment of Xiaohuangguayuan station offers 1.69% of that of Pingshan station. [ABSTRACT FROM AUTHOR]

The phenomenon of jump is one of the importantly external forms of hydrological variabi-lity under environmental changes, representing the adaption of hydrological nonlinear systems to the influence of external disturbances. Presently, the related studies mainly focus on the methods for identifying the jump positions and jump times in hydrological time series. In contrast, few studies have focused on the quantitative description and classification of jump degree in hydrological time series, which make it difficult to understand the environmental changes and evaluate its potential impacts. Here, we proposed a theatrically reliable and easy-to-apply method for the classification of jump degree in hydrological time series, using the correlation coefficient as a basic index. The statistical tests verified the accuracy, reasonability, and applicability of this method. The relationship between the correlation coefficient and the jump degree of series were described using mathematical equation by derivation. After that, several thresholds of correlation coefficients under different statistical significance levels were chosen, based on which the jump degree could be classified into five levels: no, weak, moderate, strong and very strong. Finally, our method was applied to five diffe-rent observed hydrological time series, with diverse geographic and hydrological conditions in China. The results of the classification of jump degrees in those series were closely accorded with their physically hydrological mechanisms, indicating the practicability of our method.