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The problems of observer-based feedback control and stability analysis for a T-S fuzzy system are investigated in this paper. Based on system output variable, a membership function dependent observer and a controller subject to observer errors are constructed to estimate the unknown system state and establish the closed-loop feedback control system. The derived stability criteria, which is not numerically solvable, is converted to a solvable optimization problem. An improved membership function dependent approach is proposed to reduce the conservativeness. The approximated values of membership functions and their derivatives are calculated based on the proposed piecewise-function method. Then, a piecewise decaying rate setting technique is presented to adjust the error convergent speed. A three-rule fuzzy system stability analysis example is given to show the conservativeness reduction effects, while an inverted pendulum cart control process is used to show the effectiveness of the proposed observer-based control scheme.

Clustering is a fundamental analysis tool aiming at classifying data points into groups based on their similarity or distance. It has found successful applications in all natural and social sciences, including biology, physics, economics, chemistry, astronomy, psychology, and so on. Among numerous existent algorithms, hierarchical clustering algorithms are of a particular advantage as they can provide results under different resolutions without any predetermined number of clusters and unfold the organization of resulted clusters. At the same time, they suffer a variety of drawbacks and thus are either time-consuming or inaccurate. We propose a novel hierarchical clustering approach on the basis of a simple hypothesis that two reciprocal nearest data points should be grouped in one cluster. Extensive tests on data sets across multiple domains show that our method is much faster and more accurate than the state-of-the-art benchmarks. We further extend our method to deal with the community detection problem in real networks, achieving remarkably better results in comparison with the well-known Girvan-Newman algorithm., 13 pages, 5 figures, 5 supplementary figures, 2 tables

Objective To investigate the effects of polaprezinc (PZ) on cyclophosphamide (CTX)- or cisplatin (DDP)-induced gastric mucosal injury and on a rat model of neurotransmitter-mediated vomiting. Methods Sprague–Dawley rats were divided at random into Control, CTX, DDP, PZ+CTX, and PZ+DDP groups. After 20 days, brain tissues and sera were analyzed for the levels of dopamine (DA), 5-hydroxytryptamine (5-HT), and nuclear factor kappa B (NF-κB). Hematoxylin and eosin-stained sections of stomach, intestine, and brain tissues were examined using light microscopy. Results The levels of DA, 5-HT, and NF-κB in brain and serum samples of rats treated with CTX or DDP were significantly increased compared with those of rats in the Control group. There was a significant decrease in these values in the PZ group. Moreover, PZ reduced damage to brain tissue caused by CTX or DDP. Conclusions PZ decreased the levels of DA, 5-HT, and NF-κB in blood and brain tissues caused by CTX or DDP and reduced the chemotherapy-induced damage to the small intestine, stomach, and brain. These findings can be translated to the clinic to enhance the efficacy and safety of chemotherapy.

Entity information network is used to describe structural relationships between entities. Taking advantage of its extension and heterogeneity, entity information network is more and more widely applied to relationship modeling. Recent years, lots of researches about entity information network modeling have been proposed, while seldom of them concentrate on equipment-standard system with properties of multi-layer, multi-dimension and multi-scale. In order to efficiently deal with some complex issues in equipment-standard system such as standard revising, standard controlling, and production designing, a heterogeneous information network model for equipment-standard system is proposed in this paper. Three types of entities and six types of relationships are considered in the proposed model. Correspondingly, several different similarity-measuring methods are used in the modeling process. The experiments show that the heterogeneous information network model established in this paper can reflect relationships between entities accurately. Meanwhile, the modeling process has a good performance on time consumption.