天长天官画的俗信主题与文化阐释

天官作为国人信仰中的神祗人物,实际上是被理想化了的善神、福神形象。天官画是天官信仰的衍生物,亦是集神话、宗教与美术为一体的传统民间画种。天官画在安徽天长地区长期盛行。在传承和应用中,天官画谱系中的神祇人物群体逐渐递增,俗信主题日趋多义化,民俗功能日渐被泛化,即由原初的祈求天官赐福,逐渐拓展到更具体的俗信主题,诸如驱邪禳灾、求财致富、镇宅、保平安等。对于普通的天官信众来说,天官画则被视作"延神"赐福的凭依,并发挥着祥物与镇物的宗教心理功用。

Modeling of temperature-humidity for wood drying based on time-delay neural network

The temperature-humidity models of wood drying were developed based on Time-delay neural network and the identification structures of Time-delay neural network were given. The controlling model and the schedule model, which revealed the relation between controlling signal and temperature-humidity and the relation between wood moisture content and temperature-humidity of wood drying, were separately presented. The models were simulated by using the measured data of the experimental drying kiln. The numerical simulation results showed that the modeling method was feasible, and the models were effective.

Behavioral modeling of RF power amplifiers with time-delay feed-forward neural networks

A novel behavioral model using three-layer time-delay feed-forward neural networks （TDFFNN）is adopted to model radio frequency （RF）power amplifiers exhibiting memory nonlinearities. In order to extract the parameters, the back- propagation algorithm is applied to train the proposed neural networks. The proposed model is verified by the typical odd- order-only memory polynomial model in simulation, and the performance is compared with different numbers of taped delay lines（TDLs） and perceptrons of the hidden layer. For validating the TDFFNN model by experiments, a digital test bench is set up to collect input and output data of power amplifiers at a 60 × 10^6 sample/s sampling rate. The 3.75 MHz 16-QAM signal generated in the vector signal generator（VSG） is chosen as the input signal, when measuring the dynamic AM/AM and AM/PM characteristics of power amplifiers. By comparisons and analyses, the presented model provides a good performance in convergence, accuracy and efficiency, which is approved by simulation results and experimental results in the time domain and frequency domain.

An Incremental Time-delay Neural Network for Dynamical Recurrent Associative Memory

An incremental time-delay neural network based on synapse growth, which is suitable for dynamic control and learning of autonomous robots, is proposed to improve the learning and retrieving performance of dynamical recurrent associative memory architecture. The model allows steady and continuous establishment of associative memory for spatio-temporal regularities and time series in discrete sequence of inputs. The inserted hidden units can be taken as the long-term memories that expand the capacity of network and sometimes may fade away under certain condition. Preliminary experiment has shown that this incremental network may be a promising approach to endow autonomous robots with the ability of adapting to new data without destroying the learned patterns. The system also benefits from its potential chaos character for emergence.

The miRNAs of Herpes Simplex Virus(HSV)

Herpes simplex virus (HSV) is a group of common human pathogens with two serotypes HSV-1 and HSV-2.The prevalence of HSV is worldwide.It primarily infects humans through epithelial cells,when it introduces a latent infection into the nervous system.During viral latency,only a region known as the latency-associated transcript (LAT) is expressed.The discovery of HSV miRNAs helps to draw a larger picture of the infection and pathogenesis of the virus.This review summarizes miRNAs found in HSV-1 and HSV-2 so far.The functional studies of miRNAs in HSV to date indicate that they play a stage-specific role coordinated with viral proteins to maintain the virus life cycle.

Synchronization of a Class of Delayed Neural Networks with Sector Nonlinearity

In this paper, global synchronization is discussed for a general class of delayed neural networks with time-varying and distributed delays. Furthermore, the activation func- tions in the neural networks can be different type. Based on the drive-response concept and the Lyapunov stability theorem, some sufficient criteria are obtained to guarantee the global synchronization of the considered models even when input sector nonlinearity caused by physical limitations is presented in response systems. Finally, a typical example is also given to illustrate the effectiveness of the proposed synchronization scheme.

Advanced Identification Methods for Industrial Processes with Big Time Delays

This paper presents an advanced method for system identification of industrial processes with big time delays. Identification methods based on neural networks, tree partitioning and wavelet networks are presented and analyzed. The obtained results are compared and the tree partitioning method is selected as most appropriate identification method for the water treatment process. The decision was made based on a thorough analysis on the overall fit between the measured data and the results of the simulated model. At the end, we propose possibilities for further research in this area.

Global exponential stability of cellular neural networks with time delays

By using the properties of nonnegative matrices and techniques of differential inequalities,some sufficient conditions for the global exponential stability of cellular neural networks with time delays were obtained.The criteria do not require such conditions as boundedness and differentiability of activation functions.The conditions of the theorem were verified.

Cardiac Neurons Firing Preceding Cortical Neurons Firing by Variable Time Equivalent to RP before Conscious Act

The signals and the neuronal mechanisms that underlying the behavior, actions, and action-directed goals in man and animals during conscious state are not fully understood, and the neuro-dynamic mechanisms and the source of these neuronal signals are not authenticated. Temporal judgment alone can neither account for neural signaling necessary for emergence of conscious act nor explain RP （Readiness Potential, the accepted neural correlate time needed for the neurons to fire） that precedes the onset of action or the latency time of 0.5 ms that precedes the conscious act found by Libet. Neuronal feedback mechanisms between the heart and the brain seem feasible and logical suggestions to be considered, so clearly, I would suggest that the onset of a conscious-directed goal, conscious action, freewill, intension, and the neural signals and mechanisms that control them may depend upon the interaction between two sources： （1） the brain and （2） the heart. The temporal-cardiac （neural system） interaction has been well established in heart-brain interaction studies by many workers who found that the work of the heart precedes that of the brain in EEG （electroencephalography） findings in conscious stimulation, which may explain and account for RP time and the 0.5 ms latency period of Libet＇s important findings. According to my hypothesis （AlFaki 2009） and views, the temporal neurons in the soma to-sensory cortex will respond to conscious stimulation only after receiving neuronal signals from the cardiac neurons in the neural plexus of the heart; after variable millisecond equivalent to RP or Libet＇s latency period prior to temporal neuronal firinging in response to conscious act, this time is the time needed by cardiac neurons to process and signal information to the brain through feedback mechanism and heart-brain interaction.

A Note on ＂Global Exponential Convergence Analysis of Hopfield Neural Networks with Continuously Distributed Delays＂

In this note, we would like to point out that （i） of Corollary 1 given by Zhang et al. （cf Commun. Theor. Phys. 39 （2003） 381） is incorrect in general.

Stability switches and Bogdanov-Takens bifurcation in an inertial two-neuron coupling system with multiple delays

In this paper,we investigate an inertial two-neural coupling system with multiple delays.We analyze the number of equilibrium points and demonstrate the corresponding pitchfork bifurcation.Results show that the system has a unique equilibrium as well as three equilibria for different values of coupling weights.The local asymptotic stability of the equilibrium point is studied using the corresponding characteristic equation.We find that multiple delays can induce the system to exhibit stable switching between the resting state and periodic motion.Stability regions with delay-dependence are exhibited in the parameter plane of the time delays employing the Hopf bifurcation curves.To obtain the global perspective of the system dynamics,stability and periodic activity involving multiple equilibria are investigated by analyzing the intersection points of the pitchfork and Hopf bifurcation curves,called the Bogdanov-Takens(BT)bifurcation.The homoclinic bifurcation and the fold bifurcation of limit cycle are obtained using the BT theoretical results of the third-order normal form.Finally,numerical simulations are provided to support the theoretical analyses.

Exponential H_∞ filtering analysis for discrete-time switched neural networks with random delays using sojourn probabilities

This paper is concerned with the exponential H_∞ filtering problem for a class of discrete-time switched neural networks with random time-varying delays based on the sojourn-probability-dependent method. Using the average dwell time approach together with the piecewise Lyapunov function technique, sufficient conditions are proposed to guarantee the exponential stability for the switched neural networks with random time-varying delays which are characterized by introducing a Bernoulli stochastic variable.Based on the derived H_∞ performance analysis results, the H_∞ filter design is formulated in terms of Linear Matrix Inequalities(LMIs). Finally, two numerical examples are presented to demonstrate the effectiveness of the proposed design procedure.

nNOS expression of hippocampal neurons in aged rats after brain ischemia/reperfusion and its role in DND development

Objective: To study the role of neuronal nitric oxide synthase (nNOS) in aged rats hippocampal delayed neuronal death (DND) following brain ischemia. Methods: Models of incomplete brain ischemia were induced by clipping common carotid artery. A total of 46 aged SD rats were divided into 8 groups: normal control group (Group A, n=5), sham operation group (Group B, n=5), reperfusion 1, 6, 12, 24, 48, and 96 hours groups after brain ischemia for 30 minutes (Group C, D, E, F, G, and H, n=6/group). The expression of nNOS was examined by immunohistochemistry and neuronal ultrastructural changes were observed by the transmission electron microscopy (TEM) at different time points after reperfusion. Results: Immunohistochemistry showed that nNOS expression in the hippocampal neurons was high in Group E, low expression in Group D, moderate expression in Group F and G. There was nearly no expression of nNOS in Group A, B, C, and H. Ultrastructure of hippocampal neurons was damaged more severely in reperfusion over 24 hours groups. Conclusions: Nitric oxide (NO) may be one of the important factors in inducing DND after ischemia/reperfusion.

LOCAL STABILITY AND BIFURCATION IN A THREE-UNIT DELAYED NEURAL NETWORK

A system of three-unit networks with coupled cells is investigated.The general formula for bifurcation direction of Hopf bifurcation is calculated and the estimate formula of period of the periodic solution is given.

Chemical synaptic coupling-induced delay-dependent synchronization transitions in scale-free neuronal networks

Chemical synaptic couplings are more common than electric(gap junction) connections in neurons.In this paper,the firing synchronizations induced by chemical synaptic coupling in chemically delayed scale-free networks of modified Hodgkin-Huxley neurons have been studied.It was found that the chemical coupling-induced synchronization transitions are delay-dependent and much different for various delay lengths.In the absence of delay,the neurons exhibit a transition from chaotic bursting(CB) to bursting synchronization(BS) with desynchronized spikes in each burst;for smaller delay lengths,the firing evolves from CB to spiking synchronization(SS),but for larger delay lengths,there are transitions from CB to intermittently multiple SS behaviors.These findings show that the chemical coupling-induced firing synchronization transitions strongly depend on the chemical delay lengths,and intermittently multiple SS can only occur for larger delay lengths.This result would be helpful for better understanding the joint roles of the chemical coupling and chemical delay in the firing activity of the neurons.

Effect of nerve growth factor and Schwann cells on axon regeneration of distracted inferior alveolar nerve following mandibular lengthening

Objective:To study the effect of nerve growth f actor (NGF) and Schwann cells on axon regeneration of the inferior alveolar nerv e following mandibular lengthening with distraction osteogenesis. Methods:Unilateral mandibular osteodistraction was performed i n 9 healthy adult male goats with a distraction rate of 1 mm/d. Every 3 goats we re killed on days 7, 14 and 28 after mandibular lengthening, respectively. The i nferior alveolar nerves in the distraction callus were harvested and processed f or ultrastructural and NGF immunohistochemical study. The inferior alveolar nerv es from the contralateral side were used as controls. Results:On day 7 after distraction, axon degeneration and Schw ann cell proliferation were observed, and very strong staining of NGF in the dis tracted nerve was detected. On day 14 after distraction, axon regeneration and r emyelination were easily observed, and NGF expression started to decline. On day 28 after distraction, the gray scale of NGF immunoreactivity recovered to the n ormal value and the Schwann cells almost recovered to their normal state. Conclusions:Gradual mandibular osteodistraction can result in mild or moderate axon degeneration of the inferior alveolar nerve. Nerve trauma may stimulate the proliferation of Schwann cells and promote the synthesis and s ecretion of NGF in the Schwann cells. Schwann cells and NGF might play important roles in axon regeneration of the injured inferior alveolar nerve following man dibular lengthening.

Adaptive coupling-enhanced spiking synchronization in Newman-Watts neuronal networks with time delays

In this paper, we study how adaptive coupling with time-periodic growth speed (TPGS) affects the spiking synchronization of weighted adaptive Newman-Watts Hodgkin-Huxley neuron networks with time delays. It is found that the neuronal spiking intermittently exhibits synchronization transitions between desynchronization and in-phase synchronization or anti-phase synchronization as TPGS amplitude or frequency is varied, showing multiple synchronization transitions. These transitions depend on the values of time delay and can occur only when time delay is close to those values that can induce synchronization transitions when the growth speed is fixed. These results show that the adaptive coupling with TPGS has great influence on the spiking synchronization of the neuronal networks and thus plays a crucial role in the information processing and transmission in neural systems.

Bifurcation analysis for Hindmarsh-Rose neuronal model with time-delayed feedback control and application to chaos control

This paper is concerned with bifurcations and chaos control of the Hindmarsh-Rose(HR)neuronal model with the time-delayed feedback control.By stability and bifurcation analysis,we find that the excitable neuron can emit spikes via the subcritical Hopf bifurcation,and exhibits periodic or chaotic spiking/bursting behaviors with the increase of external current.For the purpose of control of chaos,we adopt the time-delayed feedback control,and convert chaos control to the Hopf bifurcation of the delayed feedback system.Then the analytical conditions under which the Hopf bifurcation occurs are given with an explicit formula.Based on this,we show the Hopf bifurcation curves in the two-parameter plane.Finally,some numerical simulations are carried out to support the theoretical results.It is shown that by appropriate choice of feedback gain and time delay,the chaotic orbit can be controlled to be stable.The adopted method in this paper is general and can be applied to other neuronal models.It may help us better understand the bifurcation mechanisms of neural behaviors.

Stability analysis for a class of impulsive competitive neural networks with leakage time-varying delays

In this paper, we consider the existence, the uniqueness, the global exponential stability, the global asymptotic stability, the uniform asymptotic stability and the uniform stability of the equilibrium point of impulsive competitive neural networks with distributed delays and leakage time-varying delays. The existence of a unique equilibrium point is proved by using Brouwer's fixed point theorem. By finding suitable Lyapunov-Krasovskii functional, some sufficient conditions are derived ensuring some kinds of stability. Finally, several examples and their simulations are given to illustrate the effectiveness of the obtained results.

Synchronization criteria for multiple memristor-based neural networks with time delay and inertial term

This present work uses different methods to synchronize the inertial memristor systems with linear coupling. Firstly, the mathematical model of inertial memristor-based neural networks(IMNNs) with time delay is proposed, where the coupling matrix satisfies the diffusion condition, which can be symmetric or asymmetric. Secondly, by using differential inclusion method and Halanay inequality, some algebraic self-synchronization criteria are obtained. Then, via constructing effective Lyapunov functional, designing discontinuous control algorithms, some new sufficient conditions are gained to achieve synchronization of networks. Finally, two illustrative simulations are provided to show the validity of the obtained results, which cannot be contained by each other.