Dissipativity Analysis and Synthesis for a Class of Nonlinear Stochastic Impulsive Systems

The dissipativity analysis and control problems for a class of nonlinear stochastic impulsive systems (NSISs) are studied. The systems are subject to the nonlinear disturbance, stochastic disturbance, and impulsive effects, which often exist in a wide variety of industrial processes and the sources of instability. Our aim is to analyse the dissipativity and to design the state-feedback controller and impulsive controller based on the dissipativity such that the nonlinear stochastic impulsive systems are stochastic stable and strictly (Q,S,R)-dissipative. The sufficient conditions are obtained in terms of linear matrix inequality (LMI), and a numerical example with simulation is given to show the correctness of the derived results and the effectiveness of the proposed method

Uncertainty management in assessment of FMEA expert based on negation information and belief entropy

The failure mode and effects analysis (FMEA) is a commonly adopted approach in engineering failure analysis, wherein the risk priority number (RPN) is utilized to rank failure modes. However, assessments made by FMEA experts are full of uncertainty. To deal with this issue, we propose a new uncertainty management approach for the assessments given by experts based on negation information and belief entropy in the Dempster–Shafer evidence theory framework. First, the assessments of FMEA experts are modeled as basic probability assignments (BPA) in evidence theory. Next, the negation of BPA is calculated to extract more valuable information from a new perspective of uncertain information. Then, by utilizing the belief entropy, the degree of uncertainty of the negation information is measured to represent the uncertainty of different risk factors in the RPN. Finally, the new RPN value of each failure mode is calculated for the ranking of each FMEA item in risk analysis. The rationality and effectiveness of the proposed method is verified through its application in a risk analysis conducted for an aircraft turbine rotor blade

Amarogentin Inhibits Liver Cancer Cell Angiogenesis after Insufficient Radiofrequency Ablation via Affecting Stemness and the p53-Dependent VEGFA/Dll4/Notch1 Pathway

Background. Whether and how amarogentin suppresses the angiogenesis effect in liver cancer cells after insufficient radiofrequency ablation (iRFA) are still poorly studied. Methods. The number of liver cancer stem cells (LCSCs) and the level of vascular endothelial growth factor A (VEGFA) were assessed in liver cancer tissue after iRFA. Then, CD133-positive cells were detected in iRFA models of HepG2 and Huh7 cell lines treated with amarogentin. Tube formation assays were applied to observe the antiangiogenesis effects of amarogentin. In addition, the angiogenesis-related molecules p53, delta-like ligand 4 (Dll4), and Notch1 were detected in the iRFA cells and mouse models treated with amarogentin. Results. The mRNA and protein expression levels of CD133 and VEGFA were significantly higher in the residual liver cancer tissue than in the liver cancer tissues treated by hepatectomy. Amarogentin then markedly decreased the percentage of CD133-positive cells in the iRFA model in both HepG2 and Huh7 cell lines. The number of tubules formed by human umbilical vein endothelial cells (HUVECs) was significantly decreased by amarogentin. Inversely, the antiangiogenesis effect of amarogentin was counteracted after p53 silencing in the iRFA cell models. Conclusion. Amarogentin prevents the malignant transformation of liver cancer after iRFA via affecting stemness and the p53-dependent VEGFA/Dll4/Notch1 pathway to inhibit cancer cell angiogenesis

An adaptive artificial bee colony algorithm for long-term economic dispatch in cascaded hydropower systems

a b s t r a c t In this paper, we present a novel adaptive artificial bee colony (AABC) algorithm and compare its efficiency with other existing algorithms for long-term dispatch of cascaded hydropower systems. We formulate the long-term economic dispatch of hydropower systems as a complicated nonlinear optimization problem with a group of complex constraints. We analyze the performances of three different values of the control parameter modification rate (MR) in the AABC. We modify the employed bee phase to improve the global optimal capability of the AABC algorithm, and utilize a novel probabilistic method to enhance the search ability of the onlooker bee phase. Furthermore, we change the scout bee phase to avoid local maxima. We demonstrate the performance of the AABC algorithm and compare it with other algorithms using the data from hydropower systems of Three Gorges in China

Comprehensive Evaluation of Energy Efficiency Based on TOPSIS for Protocols of Collaborative Wireless Sensor Networks

Comprehensive evaluation of energy efficiency of protocols under certain cost conditions is a relatively new and ill-defined concept for collaborative wireless sensor networks (CWSN). In this paper, multicriteria decision making (MCDM) theory is introduced into comprehensive evaluation of energy efficiency of clustering protocols, which is the predecessor of collaborative protocols. Parameters about energy efficiency of total network, including cost and benefit parameters, are selected to construct a metrics system for the comprehensive evaluation. Technique for order preference by similarity to ideal solution (TOPSIS) without criterion weight is proposed as the method of MCDM, and it can be used to select most efficient scheme among many schemes. The experimental results show that the proposed method is effective and can be used in CWSN protocol selection and deployment of nodes

Dissipative Delay-Feedback Control for Nonlinear Stochastic Systems with Time-Varying Delay

The dissipative delay-feedback control problems for nonlinear stochastic delay systems (NSDSs) based on dissipativity analysis are studied in this paper. Based on the Lyapunov stability theory and stochastic analysis technique, both delay-independent and delay-dependent dissipativity criteria are established as linear matrix inequalities- (LMIs-) based feasibility tests. The obtained results in this paper for the nominal systems include the available results on H∞ approach and passivity for stochastic delay systems as special cases. The delay-dependent feedback controller is designed by considering the relationship among the time-varying delay, its lower and upper bound, and its differential without ignoring any terms, which effectively reduces the conservative. A numerical example is given to illustrate the theoretical developments