In this paper, we investigate the new agegraphic dark energy model in the framework of Brans-Dicke theory, which is a natural extension of the Einstein＇s general relativity. In this framework the form of the new ageg...In this paper, we investigate the new agegraphic dark energy model in the framework of Brans-Dicke theory, which is a natural extension of the Einstein＇s general relativity. In this framework the form of the new agegraphic dark energy density takes as pq = 3n^2Ф（t）η^-2, where η is the conformal age of the universe and Ф（t） is the Brans-Dicke scalar field representing the inverse of the time-variable Newton＇s constant. We derive the equation of state of the new agegraphic dark energy and the deceleration parameter of the universe in the Brans-Dicke theory. It is very interesting to find that in the Brans-Dicke theory the agegraphic dark energy realizes quintom-like behavior, i.e., its equation of state crosses the phantom divide ω= -1 during the evolution. We also compare the situation of the agegraphic dark energy model in the Brans-Dicke theory with that in the Einstein＇s theory. In addition, we discuss the new agegraphic dark energy model with interaction in the framework of the Brans-Dicke theory.展开更多
The mass spectrum of the S-wave mesons is considered in the frame work of relativistic harmonic model （RHM）. The full Hamiltonian used in the investigation has the Lorentz scalar plus a vector harmonic-oscillator po...The mass spectrum of the S-wave mesons is considered in the frame work of relativistic harmonic model （RHM）. The full Hamiltonian used in the investigation has the Lorentz scalar plus a vector harmonic-oscillator potential, the confined-one-gluon-exchange potential （COGEP） and the instanton-induced quark-antiquak interaction （Ⅲ）. A good description of the mass spectrum is obtained. The respective role of Ⅲ and COGEP in the S-wave meson spectrum is discussed.展开更多
The solubility of red palm oil （RPO） in supercritical carbon dioxide （scCO2） was determined using a dynamic method at 8.5-25 MPa and, 313.15-333.15 K and at a fixed scCO2 flow rate of 2.9 g. mn -1 using a full fac...The solubility of red palm oil （RPO） in supercritical carbon dioxide （scCO2） was determined using a dynamic method at 8.5-25 MPa and, 313.15-333.15 K and at a fixed scCO2 flow rate of 2.9 g. mn -1 using a full factorial design. The solubility was determined under low pressures and temperatures as a preliminary study for RPO par- ticle formation using scCO2. The solubility of RPO was 0.5-11.3 mg. （g CO2） -1 and was significantly affected by the pressure and temperature. RPO solubility increased with pressure and decreased with temperature. The Adachi-Lu model showed the best-fit for RPO solubility data with an average relative deviation of 14% with a high coefficient of determination, R2 of 0.9667, whereas the Peng-Robinson equation of state thermodynamic model recorded deviations of 17%-30%.展开更多
This study was conducted to establish a Support Vector Machines(SVM)-Markov Chain prediction model for prediction of mining water inflow. According to the raw data sequence, the Support Vector Machines(SVM) model was ...This study was conducted to establish a Support Vector Machines(SVM)-Markov Chain prediction model for prediction of mining water inflow. According to the raw data sequence, the Support Vector Machines(SVM) model was built, and then revised by means of a Markov state change probability matrix. Through dividing the state and analyzing absolute errors and relative errors and other indexes of the measured value and the fitted value of SVM, the prediction results were improved. Finally,the model was used to calculate relative errors. Through predicting and analyzing mining water inflow, the prediction results of the model were satisfactory. The results of this study enlarge the application scope of the Support Vector Machines(SVM) prediction model and provide a new method for scientific forecasting water inflow in coal mining.展开更多
In order to study dynamic laws of surface movements over coal mines due to mining activities,a dynamic prediction model of surface movements was established,based on the theory of support vector machines(SVM) and time...In order to study dynamic laws of surface movements over coal mines due to mining activities,a dynamic prediction model of surface movements was established,based on the theory of support vector machines(SVM) and times-series analysis.An engineering application was used to verify the correctness of the model.Measurements from observation stations were analyzed and processed to obtain equal-time interval surface movement data and subjected to tests of stationary,zero means and normality.Then the data were used to train the SVM model.A time series model was established to predict mining subsidence by rational choices of embedding dimensions and SVM parameters.MAPE and WIA were used as indicators to evaluate the accuracy of the model and for generalization performance.In the end,the model was used to predict future surface movements.Data from observation stations in Huaibei coal mining area were used as an example.The results show that the maximum absolute error of subsidence is 9 mm,the maximum relative error 1.5%,the maximum absolute error of displacement 7 mm and the maximum relative error 1.8%.The accuracy and reliability of the model meet the requirements of on-site engineering.The results of the study provide a new approach to investigate the dynamics of surface movements.展开更多
A two-mode entangled state was generated experimentally through mixing two squeezed lights from two optical parametric amplifiers on a 50/50 beam splitter.The entangled beams were measured by means of two pairs of bal...A two-mode entangled state was generated experimentally through mixing two squeezed lights from two optical parametric amplifiers on a 50/50 beam splitter.The entangled beams were measured by means of two pairs of balanced homodyne detection systems respectively.The relative phases between the local beams and the detected beams can be locked by using the optical phase modulation technique.The covariance matrix of the two-mode entangled state was obtained when the relative phase of the local beam and the detected beam in one homodyne detection system is locked and the other is scanned.This method provides a way by which one can extract the covariance matrix of any selected quadrature components of two-mode Gaussian state.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No.10705041
文摘In this paper, we investigate the new agegraphic dark energy model in the framework of Brans-Dicke theory, which is a natural extension of the Einstein＇s general relativity. In this framework the form of the new agegraphic dark energy density takes as pq = 3n^2Ф（t）η^-2, where η is the conformal age of the universe and Ф（t） is the Brans-Dicke scalar field representing the inverse of the time-variable Newton＇s constant. We derive the equation of state of the new agegraphic dark energy and the deceleration parameter of the universe in the Brans-Dicke theory. It is very interesting to find that in the Brans-Dicke theory the agegraphic dark energy realizes quintom-like behavior, i.e., its equation of state crosses the phantom divide ω= -1 during the evolution. We also compare the situation of the agegraphic dark energy model in the Brans-Dicke theory with that in the Einstein＇s theory. In addition, we discuss the new agegraphic dark energy model with interaction in the framework of the Brans-Dicke theory.
基金the DST for funding the project (Sanction No.SR/S2/HEP-14/2006)
文摘The mass spectrum of the S-wave mesons is considered in the frame work of relativistic harmonic model （RHM）. The full Hamiltonian used in the investigation has the Lorentz scalar plus a vector harmonic-oscillator potential, the confined-one-gluon-exchange potential （COGEP） and the instanton-induced quark-antiquak interaction （Ⅲ）. A good description of the mass spectrum is obtained. The respective role of Ⅲ and COGEP in the S-wave meson spectrum is discussed.
基金supported by Geran Putra IPS(Vote No.:9469400),University Putra Malaysia
文摘The solubility of red palm oil （RPO） in supercritical carbon dioxide （scCO2） was determined using a dynamic method at 8.5-25 MPa and, 313.15-333.15 K and at a fixed scCO2 flow rate of 2.9 g. mn -1 using a full factorial design. The solubility was determined under low pressures and temperatures as a preliminary study for RPO par- ticle formation using scCO2. The solubility of RPO was 0.5-11.3 mg. （g CO2） -1 and was significantly affected by the pressure and temperature. RPO solubility increased with pressure and decreased with temperature. The Adachi-Lu model showed the best-fit for RPO solubility data with an average relative deviation of 14% with a high coefficient of determination, R2 of 0.9667, whereas the Peng-Robinson equation of state thermodynamic model recorded deviations of 17%-30%.
文摘This study was conducted to establish a Support Vector Machines(SVM)-Markov Chain prediction model for prediction of mining water inflow. According to the raw data sequence, the Support Vector Machines(SVM) model was built, and then revised by means of a Markov state change probability matrix. Through dividing the state and analyzing absolute errors and relative errors and other indexes of the measured value and the fitted value of SVM, the prediction results were improved. Finally,the model was used to calculate relative errors. Through predicting and analyzing mining water inflow, the prediction results of the model were satisfactory. The results of this study enlarge the application scope of the Support Vector Machines(SVM) prediction model and provide a new method for scientific forecasting water inflow in coal mining.
基金supported by the Research and Innovation Program for College and University Graduate Students in Jiangsu Province (No.CX10B-141Z)the National Natural Science Foundation of China (No. 41071273)
文摘In order to study dynamic laws of surface movements over coal mines due to mining activities,a dynamic prediction model of surface movements was established,based on the theory of support vector machines(SVM) and times-series analysis.An engineering application was used to verify the correctness of the model.Measurements from observation stations were analyzed and processed to obtain equal-time interval surface movement data and subjected to tests of stationary,zero means and normality.Then the data were used to train the SVM model.A time series model was established to predict mining subsidence by rational choices of embedding dimensions and SVM parameters.MAPE and WIA were used as indicators to evaluate the accuracy of the model and for generalization performance.In the end,the model was used to predict future surface movements.Data from observation stations in Huaibei coal mining area were used as an example.The results show that the maximum absolute error of subsidence is 9 mm,the maximum relative error 1.5%,the maximum absolute error of displacement 7 mm and the maximum relative error 1.8%.The accuracy and reliability of the model meet the requirements of on-site engineering.The results of the study provide a new approach to investigate the dynamics of surface movements.
基金supported by the National Basic Research Program of China(Grant No.2011CB921601)the National Natural Science Foundation of China(Grant No.11234008)+1 种基金the NSFC Project for Excellent Research Team(Grant Nos.61121064 and 11234008)Doctoral Program Foundation of the Ministry of Education China(Grant No.20111401130001)
文摘A two-mode entangled state was generated experimentally through mixing two squeezed lights from two optical parametric amplifiers on a 50/50 beam splitter.The entangled beams were measured by means of two pairs of balanced homodyne detection systems respectively.The relative phases between the local beams and the detected beams can be locked by using the optical phase modulation technique.The covariance matrix of the two-mode entangled state was obtained when the relative phase of the local beam and the detected beam in one homodyne detection system is locked and the other is scanned.This method provides a way by which one can extract the covariance matrix of any selected quadrature components of two-mode Gaussian state.
