No abstract

An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error covariance matrix. The FNN fusion system was established during multi-node fusion to integrate with the target state estimated data from different nodes and consequently obtain network target state estimation. The feasibility of the algorithm was verified based on a network of nine detection nodes. Experimental results indicated that the proposed algorithm could trace the maneuvering target effectively under sensor failure and unknown system measurement errors. The proposed algorithm exhibited great practicability in the multi-node target tracking of WSNs.

This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view.

Excessive alcohol drinking normally causes alcoholism, which is one of the most damaging psychiatric disorders in the world. However, there are no ideal treatments for alcoholism in clinic. Phosphodiesterase‐4, an enzyme that specifically hydrolyzes intracellular cyclic AMP (cAMP), may play an important role in the regulation of ethanol consumption. This is supported by the findings that inhibition of PDE4 by rolipram, a prototypic PDE4 inhibitor, reduces ethanol intake and self‐administration. Roflumilast, another selective PDE4 inhibitor, has been approved for treatment of chronic obstructive pulmonary diseases in clinic. It was of interest to know whether roflumilast altered ethanol consumption. The two‐bottle choice paradigm was used to assess ethanol intake and preference in C57BL/6J mice treated with roflumilast (1, 3, or 10 mg/kg) or rolipram (0.5 mg/kg; positive control). The effect of roflumilast was verified using ethanol drinking‐in‐dark. Locomotor activity was determined using the open‐field test. Roflumilast decreased ethanol intake and preference in two‐bottle choice in a dose‐dependent manner, with the significant change at the highest dose (10 mg/kg) of roflumilast, similar to rolipram. Neither roflumilast nor rolipram affected sucrose or quinine drinking, although roflumilast at the highest dose decreased locomotor activity. These data provide additional demonstration for the role of PDE4 in ethanol intake and suggest that roflumilast may be beneficial for treatment of alcoholism.