Search

To improve the interfacial adhesion and mechanical performance of PBO fiber composites, CNTs were uniformly grafted onto them at a high-density. The grafting of CNTs with massive reactive groups can improve the surface wettability and interfacial interaction of PBO fibers with epoxy resin. The IFSS and ILSS values of the modified composites (PBO-CNT-3) increased by 103.09 and 62.73%, respectively. As CNTs can strengthen interfacial regions of the composites, the mechanical properties (hardness and modulus) of the interphase were enhanced significantly. This led to the effective transfer of interfacial load, elimination of stress concentration, and improvement in the structural stability of the composites. As a result, the impact strength of the modified composites (PBO-CNT-3) was up to 103.76 kJ/m2 (an increase of 56.24%) compared to the original composites. The surface morphology and deformation behavior of the fractured composites indicate that the interfacial failure mode of the composites grafted with CNTs changes from adhesive failure to both cohesive and substrate failure. This strategy of grafting CNTs at a high-density opens a new avenue for the interfacial regulation of structural composites, ultra-capacitor, sensor, and catalytic materials.

The purpose of this study is to compare the clinical outcomes of laparoscopic liver resection versus open liver resection for recurrent hepatocellular carcinoma (RHCC). Published studies which investigated laparoscopic versus open liver resection for RHCC were identified, and meta-analysis was used for statistical analysis. Six studies were analyzed by meta-analysis method, and cumulative 335 cases were included in this study. Laparoscopic liver resection was performed in 145 cases, and open liver resection was performed in 190 cases. Meta-analysis showed that there was no difference in operative time and 90-day mortality between the laparoscopic group and the open group (p = 0.06 and p = 0.06 respectively); Nevertheless, compared with the open group, the laparoscopic group resulted in significantly lower rate of in-hospital complication (p

Background: To observe the effect of centipede scolopendra extract on gallbladder carcinoma (GBC) and further investigate its underlying mechanism.Methods: The GBC cell line GBC-SD was purchased and cultured. Small interfering RNA (siRNA) was constructed. The mRNA expression levels of PUMA were measured by reverse transcription-quantitative PCR (RT-qPCR) and protein expression levels of p53, PUMA, Bax and Bcl-2 were measured by western blotting respectively. Viability and proliferation were detected using MTT and colony formation assays respectively. The apoptosis rate was determined by Annexin-V-FITC/PI double staining. Results: The GBC-SD cell line was successfully obtained and cultured. MTT and colony formation assays demonstrated that the viability and proliferation of GBC-SD cells could be markedly inhibited by centipede scolopendra extract in a concentration-dependent manner in the limited concentration range. Following pretreatment with centipede scolopendra extract, RT-qPCR demonstrated that the expression levels of PUMA were markedly increased in the GBC-SD cells, and western blotting showed that the high expression of PUMA was accompanied by upregulation of Bax and downregulation of p53 and Bcl-2 in the GBC-SD cells. However, this effect has proved hard to reproduce after PUMA-siRNA. Flow cytometry revealed that the apoptosis rate was 9.8±2.2%, 25.3±3.6%, 10.6±2.0%, and 13.5±2.4% in control group, centipede scolopendra extract group, PUMA-siRNA group, and centipede scolopendra extract combined with PUMA-siRNA group respectively. Conclusions: Centipede scolopendra extract could induce the apoptosis of GBC-SD cells by promoting the PUMA-Bax signaling pathway. It could serve as a potential novel therapy for GBC in clinical practice.

The p53-upregulated modulator of apoptosis (PUMA) has been reported to be involved in various types of cancer. However, its potential biological role in gallbladder carcinoma (GBC) has not been fully elucidated. The present study aimed to determine the expression levels of PUMA and its biological effects on GBC. The mRNA and protein expression levels of PUMA in GBC tissues and cell lines were measured using reverse transcription-quantitative PCR and western blotting, respectively. The effects of PUMA overexpression on cell viability, proliferation and invasive ability were determined in vitro using the MTT, colony formation and Transwell invasion assays, respectively. The apoptotic rates were detected using the Annexin V-FITC apoptosis detection kit. Furthermore, follow-up of patients with GBC was performed to identify the association between PUMA expression levels and GBC prognosis. The results of the present study demonstrated that the expression levels of PUMA were significantly lower in the GBC tissues and cell lines compared with those in adjacent normal gallbladder tissues and normal gallbladder cells, respectively. Further experiments indicated that overexpression of PUMA inhibited the viability, proliferation and invasive ability of GBC cells compared with those in the control-transfected GBC cells. In addition, overexpression of PUMA significantly promoted apoptosis in GBC cells. Furthermore, overexpression of PUMA inhibited epithelial-mesenchymal transition, and promoted Bax upregulation and Bcl-2 downregulation compared with those in the control group. Low PUMA expression levels were associated with a short overall survival time in patients with GBC. In conclusions, PUMA may act as a tumor suppressor in GBC and may serve as a potential novel treatment target for human GBC.

Nonalcoholic steatohepatitis (NASH) has rapidly become the most common cause of chronic liver diseases. We aimed to explore the incidence and distribution characteristics of NASH by sex, region and sociodemographic index (SDI). We collected data, including sex and region, on NASH-related liver cirrhosis from the 2017 GBD study. The age-standardized incidence rates (ASRs) and estimated annual percentage changes (EAPCs) were used to estimate the incidence trend and distribution characteristics. Globally, the incidence of liver cirrhosis caused by NASH increased from 178,430 cases in 1990 to 367,780 cases in 2017, an increase of approximately 105.56%. The ASR of NASH increased by an average of 1.35% per year (95% CI 1.28–1.42). Meanwhile, large differences in the ASR and the EAPC were observed across regions. The middle-high SDI region had the highest increase among all five SDI regions, followed by middle SDI region. In addition, Eastern Europe, Andean Latin America and Central Asia showed a more significant growth trend of ASR. In contrast, the high SDI region demonstrated the slowest increasing trend of ASR, and the high-income Asia Pacific demonstrated a decreasing trend among the 21 regions. Liver cirrhosis has caused a huge and rising health burden in many countries and regions. In addition, with the growth of obesity, population and aging, NASH might replace viral hepatitis as the most important cause of liver cirrhosis in the near future. Therefore, appropriate interventions are needed in coming decades to realize early diagnosis and prevention of NASH-related liver cirrhosis.

Constructing interface with customized structures of fiber composites is an effective method of achieving high performance. Herein, the comb-like polymer interface with a rigid-flexibility transition structure was constructed on the PBO fiber surface through the layer-by-layer (LBL) method. Compared with original PBO fiber composites, the interfacial adhesion and stability of interface structures were improved significantly due to the LBL construction of comb-like polymers interface. In modified fiber (PBO–P3) composites, the IFSS and ILSS value were increased by 76.30 and 39.31%, respectively. Meanwhile, dynamic mechanical properties and hydrothermal aging resistance were also enhanced obviously. The main contributors for improved interfacial adhesion could be the enlarged interface region with rigid-flexible transition structure, complicated interface contact, enhanced chemical bonding and mechanical interlocking near interface area.

In this study, the interfacial properties of PBO fiber were enhanced significantly through constructing the rigid dendritic polymers on its surface. The rigid branched structure and massive functional groups of dendritic polymers endowed the interphase with more powerful physical entanglement and mechanical interlocking, abundant chemical bonding, improved interfacial compatibility and moderate mechanical properties. Compared with untreated PBO fiber composites, the interfacial shear strength and interlaminar shear strength of modified PBO fiber (PBO-M2) composites increased by 81.49 and 42.17%, respectively. Meanwhile, the impact strength raised from 68.15 to 103.28 kJ/m2 due to the construction of rigid dendritic polymers. Dynamic mechanical evaluation also indicated that the storage modulus (at 30 °C) of PBO-M2 composites increased from 34 ± 2 to 47 ± 3 GPa. Moreover, the hydrothermal aging resistance of PBO-M2 composites was also markedly improved.

Cross-beam experiment system(CBES)[1] as a high degree nonlinear, strong coupled MIMO control system has very high application value in the engineering and military affairs. Based on the rule of constructing the global identical terminal function[2], a kind of speedy terminal function[4] is validated as the global identical terminal function and the basic theory of the global identical terminal sliding mode control is expatiated; then exponential reaching law[3] is adopted to design the controller and a variable domain fuzzy controller[7,8] is adopted to approximate parameter of reaching law. The approach can not only weaken chattering, improve speed of error convergence and precision of the controller, but also assure robustness of the system. Simulation result shows the effectiveness of the approach presented.

The flight simulation table servo system has serious friction which impact on the control performance in low speed. In this paper, we derived the input- output characteristics of second-order linear active disturbance rejection controller (LADRC), and proposed the algorithm of LADRC based on repetitive control compensation. The results of tracking control on the flight simulation table servo system in matlab/ simulink software environment proved the validity of the algorithm.

In this paper, a new correction method for Dead Reckoning (DR) navigation system is proposed based on digital map. An improved Map-Match algorithm is adopted, including a new “road correction” algorithm and a new “road projection” algorithm based on fuzzy theory and geometry theory. New information that contains the similarity of the road is introduced to the communication protocol between DR system and Map-Match system, which greatly enhances the robustness of the data fusion period. Based on the information provided by digital map, the DR system can not only corrects the position output, but also estimates the odometer scale factor error. The result of road test proves that the new method greatly improves the performance of DR system in long distance navigation.

In this paper, considering the performance of short-time working, inertial flight and high impulse of launch for projectile, an improved square root unscented Kalman filter (UKF) is used. According to the special motional rule of projectile, only use three low-cost MEMS accelerometers as inertial measurement unit to measure the specific force, and construct the linear state equation and nonlinear measurement equation of nonlinear system. Use the square root UKF to estimate the state of system, which effectively enhances the stability of filter and restrains the divergence of filter. Reduce the number of sigma points from 2n+1 to n+2, which improves the computational efficiency and real-time performance of filter. The experimental results in a three-axis flight test rotary table show that the improved square root UKF obtains the good precision of estimation and satisfies the request of real-time response.

The error model of marine strapdown inertial navigation system on the swaying base is nonlinear, while the azimuth angle is large. For the nonlinear error model, a new recursive Gaussian Particle filter based on randomized Quasi Monte Carlo is proposed. The randomized Quasi Monte Carlo methods use the weighted randomized low discrepancy particles to replace the weighted random samples, in order to avoid the possible gaps and clusters that arise from random sampling in Monte Carlo methods, and improve the sampling efficiency and calculation accuracy. The simulation experiment shows that the new approach obtains the better estimation performance in initial alignment of large azimuth misalignment on the swaying base of the marine strapdown inertial navigation system.

In order to satisfy the request of real-time response, an improved unscented Kalman filter (UKF) is studied for the projectile's attitude determination in this paper. The inertial measurement unit (IMU) used to determinate the attitude of projectile is composed of only five low-cost micro electro-mechanical system (MEMS) accelerometers. A sensor measurement data fusion scheme is designed including high and low range configuration. UKF is used to estimate the state of system. The speed of computation of UKF is improved by reducing the number of sigma points. The experimental results in three-axis flight rotary table show that the improved UKF quickly converges and satisfies the request of real-time response.

The scale factor of fiber optic gyroscope (FOG) varied with the environment temperature. This nonlinear variation seriously influences the precision of the FOG. In this article, the back propagation neural network (BPNN) based on chaos particle swarm optimization (CPSO) is used to compensate the scale factor error. It is testified by experiment, that CPSO-BPNN algorithm is an ideal method to fit the variation of scale factor with temperature, which can greatly decrease the angular rate error of FOG caused by scale factor error and guarantee the measuring precision of FOG at different temperature.

In this paper, a new adaptive genetic algorithm (GA)-based radial basis function (RBF) neural network with optimal selection clustering algorithm (OSCA) is proposed for the fault diagnosis of micro electro-mechanical system (MEMS) gyroscopes and accelerometers of strapdown inertial navigation system (SINS). The number of hidden layer nodes and parameters of RBF neural network are obtained by using OSCA. The connection weights are encoded to generate the chromosome, which is operated by adaptive GA. Orthogonal least square algorithm (OLS) is used to train the weights and gradient descent algorithm (GDA) with momentum term is used to estimate the parameters of Gaussian function. Adaptive GA, OLS and GDA with momentum term iterate alternately. Experimental results show that the proposed GA-based RBF neural network with OSCA quickly converges and effectively improves the diagnostic accuracy rate of SINS fault diagnosis.

This paper established a linear dynamic model of the rocket using segmental ballistic linearization methodology based on small turbulence theory. Based on the model, the application of linear adjoint method in rocket is studied. Ballistic error is deduced and analyzed. Finally the feasibility of applying linear adjoint method to rocket error is testified through computer simulation.

In this paper, a data fusion algorithm for DR/GPS/Map-Match (MM) is proposed and implemented. DR is used as the primary navigation system while GPS and MM are used as aiding systems. The algorithm consists of 3 sub-algorithms, which are DR-GPS data fusion algorithm, Map-Match algorithm, and DR parameter correction algorithm. The data fusion algorithm first fuses the DR output and GPS which yields the input of the MM system. The MM algorithm chooses the proper road and project the vehicle position onto the road, which is based on a fuzzy road choosing theory that takes the distance and azimuth difference between the vehicle and alternative road into consideration. A similarity flag which represents the reliability of the MM data is proposed to enhance the robustness of the data fusion between DR and MM. The MM data is used not only to update positioning information of the DR but also to correct the parameters such as gyroscope scale factor and odometer scale factor, which greatly helps prevent the DR error from going wild.

In this paper, a filtering algorithm is studied for the agile projectile's attitude determination. An incomplete inertial measurement unit (IMU) composed of only three low-cost micro electro-mechanical system (MEMS) accelerometers is used to determinate the attitude of agile projectile. Considering the gravity vector remains constant around the firing position in a short time, the agile projectile's attitude and rotary speed in flight is estimated by using filtering algorithm according to the information of three accelerometers. The experimental results in three-axis flight rotary table show that the filtering algorithm in this paper quickly converges and the precision of estimation is high.

In this paper, a new radial basis function (RBF) neural network with fuzzy c-means clustering algorithm based on genetic algorithm (GA) is proposed for the fault diagnosis of gyroscopes and accelerometers of strapdown inertial navigation system (SINS). The fuzzy c-means algorithm (FCM) tends to fall into the local optimum. The fuzzy c-means clustering algorithm combined with GA (FGA) obtains the global optimal cluster centers. FGA is used to provide the optimal cluster centers for RBF neural network, and a second order learning algorithm is used to train the parameters and weights of RBF neural network. Experimental results show that the proposed RBF neural network with FGA quickly converges and effectively improves the diagnostic accuracy rate of SINS fault diagnosis.

In order to restrain the influence of random disturbance on the attitude determination of in-motion rolling projectile, a new hybrid filtering algorithm, which combines unscented Kalman filter (UKF) with improved adaptive BP neural network based on particle swarm optimization (PSO), is proposed. When the attitude determination of rolling projectile is influenced by random disturbance, the output of neural network will replace that of UKF. The validity of hybrid algorithm is verified through the experiment, in which three low-cost micro electro-mechanical system (MEMS) accelerometers are used as strapdown inertial measurement units (IMUs) to determine rolling projectile attitude. Experiment results show that the proposed hybrid filtering algorithm is effective and robust, and it can effectively enhance the precision of state estimation and restrain the influence of dynamic random disturbance.

This paper provides an improved search algorithm for optimal route planning by rebuilding the search area in intelligent transport system. The theory foundation is that the classical Dijsktra algorithm has not any directional feature during searching the optimal path, and the bidirectional Dijsktra has its own limit. Based on the analysis of the two algorithms, the new improved algorithm proposed in this paper reduces the search area and the time complexity. Finally, combining with the practical application of route planning algorithm in intelligent transport system, one example is given. Theory analysis and test result show that the improved algorithm costs less search time and visits less nodes of road network. Besides that, some methods are proposed to handle unexpected disturbance, such as accident or traffic limit. Two models for introducing dynamics in the system are introduced as individual edge dynamics and geometrical objects. These methods are useful in practice.

In this paper the UDUT continuous-discrete unscented Kalman filter (UKF) for state estimation of continuous-time nonlinear systems is proposed. UDUT scalar update is introduced into the measurement update procedure of continuous-discrete UKF (CDUKF). It is pointed out that this form is sometimes more efficient than the standard CDUKF. Computational complexity of the two forms of CDUKF is analyzed. Reentry vehicle tracking problem is used to demonstrate that the UDUT CDUKF is sometimes faster than the standard form.