In the current study, twenty lambs, aged 4 months, half male and half female, were classified into four groups, with five in each group. The experimental three groups of lambs were given intravenous (IV), intramuscular (IM) and subcutaneous (SC) administrations of recombinant ovine interferon-τ (roIFN-τ). The fourth group (normal control) of lambs was given normal saline injections in the same way. After administrations, blood samples were collected from the tested animals at different time points post injection, and the serum titers of roIFN-τ were measured using cytopathic effect (CPE) inhibition bioassay. The results of calculating pharmacokinetic (PK) parameters using DAS software showed that the PK characteristics of roIFN-τ through IV injection conformed to the two-compartment open model, whose half-life of distribution phases (T1/2α) was 0.33±0.034 h and the elimination half-life(T1/2β) was 5.01±0.24 h. However, the PK features of IM injection and SC injection of roIFN-τ conformed to the one compartment open model, whose Tmax were 3.11±0.26 h and 4.83±0.43 h, respectively, together with an elimination half life(T1/2β) of 9.11±0.76 h and 7. 43±0.58 h, and an absorption half-life (T1/2k(a)) of 1.13±0.31 h and 1.85±0.40 h, respectively. The bioavailability of roIFN-τ after IM administration reaches 73.57%, which is greater than that of SC administration (53.43%). These results indicate that the drug administration effect can be preferably obtained following a single dose IM administration of the roIFN-τ aqueous preparation. This study will facilitate the clinical application of roIFN-τ as a potential antiviral agent in future work.
A speaker recognition system based on joint factor analysis (JFA) is proposed to improve whispering speakers’ recognition rate under channel mismatch. The system estimated separately the eigenvoice and the eigenchannel before calculating the corresponding speaker and the channel factors. Finally, a channel-free speaker model was built to describe accurately a speaker using model compensation. The test results from the whispered speech databases obtained under eight different channels showed that the correct recognition rate of a recognition system based on JFA was higher than that of the Gaussian Mixture Model-Universal Background Model. In particular, the recognition rate in cellphone channel tests increased significantly.
The active distribution network (ADN) represents the future development of distribution networks, whether the islanding phenomenon occurs or not determines the control strategy adopted by the ADN. The best wavelet packet has a better time-frequency characteristic than traditional wavelet analysis in the different signal processing, because it can extract better and more information from the signal effectively. Based on wavelet packet energy and the neural network, the islanding phenomenon of the ADN can be detected. Firstly, the wavelet packet is used to decompose current and voltage signals of the public coupling point between the distributed photovoltaic (PV) system and power grid, and calculate the energy value of each decomposed frequency band. Secondly, the network is trained using the constructed energy characteristic matrix as a neural network learning sample. At last, in order to achieve the function of identification for islanding detection, lots of samples are trained in the neural network. Based on the actual circumstance of PV operation in the ADN, the MATLAB/SIMULINK simulation model of the ADN is established. After the simulation, there are good output results, which show that the method has the characteristics of high identification accuracy and strong generalization ability.
The accuracy and reliability of Kalman filter are easily affected by the gross errors in observations. Although robust Kalman filter based on equivalent weight function models can reduce the impact of gross errors on filtering results, the conventional equivalent weight function models are more suitable for the observations with the same noise level. For Precise Point Positioning (PPP) with multiple types of observations that have different measuring accuracy and noise levels, the filtering results obtained with conventional robust equivalent weight function models are not the best ones. For this problem, a classification robust equivalent weight function model based on the t-inspection statistics is proposed, which has better performance than the conventional equivalent weight function models in the case of no more than one gross error in a certain type of observations. However, in the case of multiple gross errors in a certain type of observations, the performance of the conventional robust Kalman filter based on the two kinds of equivalent weight function models are barely satisfactory due to the interaction between gross errors. To address this problem, an improved classification robust Kalman filtering method is further proposed in this paper. To verify and evaluate the performance of the proposed method, simulation tests were carried out based on the GPS/BDS data and their results were compared with those obtained with the conventional robust Kalman filtering method. The results show that the improved classification robust Kalman filtering method can effectively reduce the impact of multiple gross errors on the positioning results and significantly improve the positioning accuracy and reliability of PPP.
The Gaussian mixture model (GMM) method is popular and efficient for voice conversion (VC), but it is often subject to overfitting. In this paper, the principal component regression (PCR) method is adopted for the spectral mapping between source speech and target speech, and the numbers of principal components are adjusted properly to prevent the overfitting. Then, in order to better model the nonlinear relationships between the source speech and target speech, the kernel principal component regression (KPCR) method is also proposed. Moreover, a KPCR combined with GMM method is further proposed to improve the accuracy of conversion. In addition, the discontinuity and oversmoothing problems of the traditional GMM method are also addressed. On the one hand, in order to solve the discontinuity problem, the adaptive median filter is adopted to smooth the posterior probabilities. On the other hand, the two mixture components with higher posterior probabilities for each frame are chosen for VC to reduce the oversmoothing problem. Finally, the objective and subjective experiments are carried out, and the results demonstrate that the proposed approach shows greatly better performance than the GMM method. In the objective tests, the proposed method shows lower cepstral distances and higher identification rates than the GMM method. While in the subjective tests, the proposed method obtains higher scores of preference and perceptual quality.
The microstructures and mechanical properties of T92 martensitic steel/Super304 austenitic steel weld joints with three welding consumables were investigated. Three types of welding materials ERNiCr-3, ERNiCrCoMo-1and T-304H were utilized to obtain dissimilar welds by using gas tungsten arc weld (GTAW). The results show that heat affect zone (HAZ) of T92 steel consists of coarse-grained and fine-grained tempered martensites. The microstructures of joints produced from ERNiCrCoMo-1 consist of equiaxed dendrite and columnar dendrite grains, which are more complicated than that of ERNiCr-3. In the tensile tests, joints constructed from ERNiCrCoMo-1 and T-304H met the ASME standard. The highest fracture energy was observed in specimens with the welding material ERNiCrCoMo-1. Ni content in weld seam of ERNiCrCoMo-1 was highest, which was above 40%. In conclusion, the nickel alloy ERNiCrCoMo-1 was the most suitable welding material for joints produced from T92 martensitic steel/Super304 austenitic steel.
Abstract This paper investigates the problem of adaptive robust simultaneous stabilization (ARSS) of two dissipative Hamiltonian systems (DHSs), and proposes a number of results on the controller parameterization design. Firstly, an adaptive H∞ control design approach is presented by using the dissipative Hamiltonian structural for the case that there are both external disturbances and parametric uncertainties in two DHSs. Secondly, an algorithm for solving tuning parameters of the controller is proposed using symbolic computation. The proposed controller parameterization method avoids solving Hamilton-Jacobi-Issacs (HJI) equations and the obtained controller is easier as compared to some existing ones. Finally, an illustrative example is presented to show that the ARSS controller obtained in this paper works very well.
To reduce the influence of the static unbalance on an infrared missile guidance system, a new static unbalance measure system for the gimbals axes has been developed. Considering the coupling effects caused by a mass eccentricity, the static balance condition and measure sequence for each gimbal axis are obtained. A novel static unbalance test approach is proposed after analyzing the dynamic model of the measured gimbal axis. This approach is to drive the measured gimbal axis to do sinusoidal reciprocating motion in a small angle and collect its drive currents in real time. Then the static unbalance of the measured gimbal axis can be obtained by the current multi-cycle integration. Also a measuring system using the proposed approach has been developed. A balanced simulator is used to verify the proposed approach by the load and repeatability tests. The results show the proposed approach enhances the efficiency of the static unbalance measurement, and the developed measuring system is able to achieve a high precision with a greater stability.
Owing to the dramatic change in the thermal conductivity of 4He when its temperature crosses the transition of superfluid (HeI) and normalfluid (HeII), a sealed-cell with a capillary is used to realize the lambda transition temperature, Tλ. A small heat flow is controlled through the capillary of the sealed-cell so as to realize the coexistence of HeI and HeII and maintain the stay of HeI/HeII interface in the capillary. A stable and flat lambda transition temperature "plateau" is obtained. Because there is a depression effect of Tλ caused by the heat flow through the capillary, a series of heat flows and several temperature plateaus are made and an extrapolation is applied to determine Tλ with zero heat flow. A rhodium-iron resistance thermometer with series number A34 (RIRT A34) has been used in 24 Tλ -realization experiments to derive Tλ with a standard deviation of 0.022mK, which proves the stability and reproducibility of Tλ.
In the present investigation, the morphology of Ti inclusions in high strength tire cord steel was investigated and their precipitation behavior was discussed using a precipitation and growth model. The results show that Ti inclusions mainly exist in the form of TiN. The two-dimensional characterization of Ti inclusions is square-like with sharp edges and corners, while its three-dimensional shape exhibits a cubic or rectangular-prism morphology. The Ti inclusions do not precipitate when the solid fraction of tire cord during solidification is less than 0.987, and their final radius is closely related to the cooling rate and initial concentration product. The higher the cooling speed, the smaller the final radius, when the cooling speed is constant, the final radius of Ti inclusions is mainly determined by the initial concentration product, w[N]0×w[Ti]0. In order to retard the precipitation and growth of Ti inclusions in tire cord steel, the cooling rate and initial concentration product can be taken into consideration.
Abstract In this paper, the method of periodically pinning intermittent control is introduced to solve the problem of outer synchronization between two complex networks. Based on the Lyapunov stability theory, differential inequality method and adaptive technique, some simple synchronous criteria have been derived analytically. At last, both the theoretical and numerical analysis illustrate the effectiveness of the proposed control methodology. This method not only reduces the conservatism of control gain but also saves the cost of production.These advantages make this method having a large application scope in the real production process.
With the increasing number of electric vehicles (EVs), the disordered charging of a large number of EVs will have a large influence on the power grid. The problems of charging and discharging optimization management for EVs are studied in this paper. The distribution of characteristic quantities of charging behaviour such as the starting time and charging duration are analysed. The results show that charging distribution is in line with a logarithmic normal distribution. An EV charging behaviour model is established, and error calibration is carried out. The result shows that the error is within its permitted scope. The daily EV charge load is obtained by using the Latin hypercube Monte Carlo statistical method. Genetic particle swarm optimization (PSO) is proposed to optimize the proportion of AC 1, AC 2 and DC charging equipment, and the optimal solution can not only meet the needs of users but also reduce equipment investment and the EV peak valley difference, so the effectiveness of the method is verified.
This paper proposes a new dc-side active filter for wind generators that combines 12-pulse polygon auto-transformer rectifier with dc-side current injection method and dual-buck full-bridge inverter having not the “shoot-through” problem in conventional bridge-type inverters, and therefore this system with the character low harmonic distortion and high reliability. The proposed dc-side active filter is realized by using dual-buck full bridge converter, which directly injects compensation current at dc-side of two six-pulse diode bridges rectifiers. Compared with the conventional three-phase active power filter at ac-side, the system with the dc-side active filter draws nearly sinusoidal current by shaping the diode bridges output current to be triangular without using the instantaneous reactive power compensation technology, only using simple hysteretic current control, even though under load variation and unbalanced voltage disturbances, and while an acceptable linear approximation to the accurate waveform of injection current is recommended. The perfor- mance of the system was simulated using MATLAB/Simulink, and the possibility of the dc-side active filter eliminating current harmonics was confirmed in steady and transient states. The simulation results indicate, the system has a total harmonic distortion of current reduced closely to 1%, and a high power factor on the wind generator side.
This paper proposes a speech enhancement method using the multi-scales and multi-thresholds of the auditory perception wavelet transform, which is suitable for a low SNR (signal to noise ratio) environment. This method achieves the goal of noise reduction according to the threshold processing of the human ear's auditory masking effect on the auditory perception wavelet transform parameters of a speech signal. At the same time, in order to prevent high frequency loss during the process of noise suppression, we first make a voicing decision based on the speech signals. Afterwards, we process the unvoiced sound segment and the voiced sound segment according to the different thresholds and different judgments. Lastly, we perform objective and subjective tests on the enhanced speech. The results show that, compared to other spectral subtractions, our method keeps the components of unvoiced sound intact, while it suppresses the residual noise and the background noise. Thus, the enhanced speech has better clarity and intelligibility.