Multivariable Robust Fault Tolerant Control For Work-Class Remotely Operated Vehicle

To deal with complex disturbances and the presence of partial loss of propeller effectiveness in work-class remotely operated vehicles (ROVs), a method of robust fault tolerant control is proposed, which is based on adaptive sliding mode control. In this approach, adaptive technique is employed to estimate the bounds’ information of external complex disturbances and the effectiveness loss of the propeller. And a sliding mode controller is then designed to achieve fault tolerant control and external disturbance rejection. Corresponding stability of the closed-loop control system is analyzed using Lyapunov stability theory. Apply this method to trajectory tracking control of work-class ROVs, the simulation results validate that great fault tolerant capability and a good performance of external disturbance rejection can be achieved even under partial loss of propeller effectiveness

Event-triggered Synchronization of Multi-agent Systems with Partial Input Saturation

This paper is concerned with the distributed event/self-triggered synchronization problem for general linear multi-agent systems with partial input saturation. Both the event-based and self-triggered laws are designed using the local sampled, possibly saturated, state, which ensures the bounded synchronization of the multi-agent systems, and exclusion of the Zeno-behavior. The continuous communication between agents is avoided under these triggering protocols. Different from the existing related works, we show the fully distributed design for multi-agent systems, where the synchronization criteria, the designed input laws, and the proposed triggering protocols do not depend on any global information of the communication topology. In addition, the computation load of multi-agent systems is reduced significantly

Tissue and ontogenic expression profiles of FATP1 and FATP4 genes in goose

Fatty acid transport proteins (FATPs) are a family of proteins involved in fatty acid uptake and activation. The tissues and ontogenic expression profiles of the critical genes participating in fatty acid metabolism have little been systematically investigated in goose. To gain insight into the gene-regulation processes in goose fatty   acid metabolism, we detected the expression profiles of FATP1 and FATP4 transcripts in goose tissues using  the quantitative real-time PCR method in two goose breeds: Zhejiang white goose and Landes goose. The   results show that FATP1 and FATP4 genes were ubiquitously expressed in all seven studied geese tissues. Both genes exhibited tissue-specific expression pattern in mRNA level with the highest expression level in leg   muscle and the lowest in abdominal fat. The liver and heart were also two important tissues for both of genes expression. The growth points at 35 and 56 days were important points for both of genes expression. In   addition, for the two breeds, both genes showed Zhejiang white goose had higher expression than Landes  goose. It can be speculated that the expression of FATP1 and FATP4 genes may have breed-specific. The   results could serve as a primary reference for the expression profile of goose fatty acid metabolism.Key words: Expression pattern, FATP1, FATP4, Landes goose, Zhejiang white goose

Probing onset of strong localization and electron-electron interactions with the presence of direct insulator-quantum Hall transition

We have performed low-temperature transport measurements on a disordered two-dimensional electron system (2DES). Features of the strong localization leading to the quantum Hall effect are observed after the 2DES undergoes a direct insulator-quantum Hall transition with increasing the perpendicular magnetic field. However, such a transition does not correspond to the onset of strong localization. The temperature dependences of the Hall resistivity and Hall conductivity reveal the importance of the electron-electron interaction effects to the observed transition in our study.Comment: 9 pages, 4 figure

In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine

Coronary artery disease (CAD) is the leading causes of deaths in the world. The differentiation of syndrome (ZHENG) is the criterion of diagnosis and therapeutic in TCM. Therefore, syndrome prediction in silico can be improving the performance of treatment. In this paper, we present a Bayesian network framework to construct a high-confidence syndrome predictor based on the optimum subset, that is, collected by Support Vector Machine (SVM) feature selection. Syndrome of CAD can be divided into asthenia and sthenia syndromes. According to the hierarchical characteristics of syndrome, we firstly label every case three types of syndrome (asthenia, sthenia, or both) to solve several syndromes with some patients. On basis of the three syndromes' classes, we design SVM feature selection to achieve the optimum symptom subset and compare this subset with Markov blanket feature select using ROC. Using this subset, the six predictors of CAD's syndrome are constructed by the Bayesian network technique. We also design Naïve Bayes, C4.5 Logistic, Radial basis function (RBF) network compared with Bayesian network. In a conclusion, the Bayesian network method based on the optimum symptoms shows a practical method to predict six syndromes of CAD in TCM

Metabolism of polyamines and kidney disease: A promising therapeutic target

Background: More than 850 million people worldwide suffer from acute and chronic kidney diseases (CKD) which are tremendous socioeconomic burdens for society. Currently, the treatment choices for CKD are limited. There is a great need to understand the underlying mechanisms of the development of CKD in order to develop potential therapeutic strategies. Summary: The alteration in cellular metabolism has emerged as an important common pathological mechanism in different kidney diseases. Metabolic intervening and reprogramming will yield new insights to prevent and slow the progression of kidney disease. As one essential component of cellular metabolisms in fuel-source preferences (glucose, fatty acids, or ketones), the polyamine compound metabolism comprising the metabolites (spermine, spermidine, and putrescine) and their biosynthetic and catabolic enzymes are an endogenous pathophysiological regulator that is arising as a potential therapeutic object for many diseases. Key Messages: This article aims to review current knowledge on polyamine metabolism and physiological processes, and its potential regulatory and beneficial roles in immunoregulation, mitochondrial homeostasis, autophagy, DNA damage, and kidney diseases, and thus provide a novel therapeutic opportunity for kidney diseases