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Saponins from Rhizoma Panacis Majoris (SRPM), the bioactive component in Rhizoma Panacis Majoris, have been used extensively as a remedy for liver injury diseases and achieved good clinical efficacy, but the underlying mechanisms remain poorly understood. The goal of our present study was to further confirm SRPM hepatoprotective effect, and evaluate that whether SRPM attenuate oxidative stress and fibrosis in carbon tetrachloride (CCl4)-induced hepatic injury, based on these results, investigate the probable mechanisms involved. At first, the separation and purification of SRPM were studied. And then, in the animal experiment, the male Sprague-Dawley rats were randomly divided into control, model, l-SRPM and h-SRPM group. Hepatic fibrosis model were made according to our previous studies reported. At the same time, the experimental rats were treated respectively with relative drugs, once a day for 8 weeks. Hepatoprotective effects of SRPM were evaluated by liver function, total antioxidant capacity and total-superoxide dismutase, histopathological observations and the hepatic fibrosis relative gene expressions. In the study, we found that SRPM significantly improved liver function, serum antioxidation level, reversed the upregulated α-SMA and TIMP1 mRNA expressions, and further increased the MMP1 mRNA expression. Our studies indicated that SRPM exerted beneficially hepatoprotective effects on the CCl4 induced hepatic fibrosis, mainly enhancing liver tissue antioxidant capacity, reducing the lipid peroxidation of hepatocyte membranes, and then alleviating hepatic fibrosis and hepatic cell death.

Steroidal saponin: (1β,3β,5β,25S)-spirostan-1,3-diol1-[α-L-rhamnopyranosyl-(1→2)-β-D-xylopyranoside] (RCE-4) is the most abundant and bioactive members in Reineckia carnea, has been reported to possess antiinflammatory activity, but the underlying mechanisms remain largely unknown. The present aim was to study expression of inflammatory cytokines, on the basis of this investigation, the possible mechanism of RCE-4 was elucidated. In the present study, we found that the concentrations of TNF-α, IL-1β and IL-6 released from LPS-stimulated RAW264.7cells significantly increased compared to control (P

Multi-robot System (MRS) for intelligent creel consists of automatic winder, transferring, transiting and supplying robot and provides the possibilities of the flexibility and automation of textile industry workshop. Based on the principle of centralized management and distributed control the system and designs distributed control system (DCS) of Multi-robot for intelligent creel based on CAN bus. Layered architecture is established consisting of main control layer, communication layer, synchronous coordination layer and execution layer. According to the complex characteristics of the system, a synchronous controller is designed to allocate and coordinate task,improving the intelligence of the system. Coordination controller also realizes function of CAN Bridge.

In order to solve the revolutionary labor cost, carpet loom yarn waste and production efficiency problem, the author puts forward a kind of new intelligent creel which is based on coreless package storage device. This paper summarizes the automatic winding system of intelligent creel and originally proposes the concept coreless package. The automatic winding unit is responsible for coreless package winding and auxiliary industrial robot finishes gripping, clipping and getting the yarn on. The system designs distributed control system (DCS) of Multi-robot for Intelligent creel based on CAN bus.

The computer control software is becoming complicate, to simplify the development of software, this paper proposes: the background control module of the control software is built automatically by a compiler according to a text descripting the nodes movement sequence, then the background control module and the interface are linked by shared variables. The method proposed is achieved by LabVIEW in the end.

Mobile devices such as smartphones have been used widely used nowadays for their portability, flexibility and functionality. Embedded operating systems have provided powerful support to these devices. More complex applications can be developed and used for them. However, mobile devices are still resource limited and this is a problem for many programs such as 3D picture display programs. In this paper, a novel approach is proposed to optimize the performance of 3D picture processing programs. The process of 3D picture processing was analyzed and scratchpads were used as the on-chip buffer for it. The experimental results showed that our approach could achieve its design target.

With the rapid development of embedded technology, mobile devices have been widely used than before. Face recognition has also been taken as a key application with PCA as the basic algorithm. Though PCA can provide basic information processing, it still has some problems to be used for mobile devices. The movement of the faces increases the difficulty of the recognition and the limited resources of mobile devices propose more constraints to traditional PCA algorithm. A novel approach is presented to optimize PCA based face recognition for better performance and faster recognition speed. The experiments show that the new approach can achieve its target though the optimization.

According to the traditional UMDH network modeling with the least square method to recognize parameters ,it's easy to fall into local minimum ,and with the result that the prediction effect is not ideal. This paper puts forward to combine the simulated annealing algorithm and genetic algorithm, and introduces the combined algorithm to the UMDH network which is used to identify some of its description type coefficient. In this paper ,it describes the simulated annealing genetic algorithm ,and constructs the UMDH network model based on this algorithm, and the model is applied to the simulation of debris flow prediction research ,forecast average relative error reached 3. 54%. The results show that the algorithm not only ensuring the global optimization but also preventing premature convergence, improve the UMDH network model of global and local searching optimal ability further.

In order to solve the problems of high false alarm rate and fail rate in intrusion detection system of Computer Integrated Process System (CIPS) network, this paper takes advantage that Genetic Algorithm (GA) possesses overall optimization seeking ability and neural network has formidable approaching ability to the non-linear mapping to propose an intrusion detection model based on Genetic Algorithm Neural Network (GANN) with self-learning and adaptive capacity, which includes data collection module, data preprocessing module, neural network analysis module and intrusion alarm module. To overcome the shortcomings that GA is easy to fall into the extreme value and searches slowly, it improves the adjusting method of GANN fitness value and optimizes the parameter settings of GA. The improved GA is used to optimize BP neural network. Simulation results show that the model makes the detection rate of the system enhance to 97.11%.