In vitro construction of a recombinant human embryonic brain-derived neurotrophin-4 gene and pEGFP-N1 vector

BACKGROUND: Neurotrophin-4 (NT-4) can promote neuronal growth, development, differentiation, maturation, and survival. NT-4 can also improve recovery and regeneration of injured neurons, but cannot pass through the blood-brain barrier, which limits its ac

Biomimetic pattern recognition theory and its applications

Biomimetic pattern recogntion (BPR), which is based on "cognition" instead of "classification", is much closer to the function of human being. The basis of BPR is the Principle of homology-continuity (PHC), which means the difference between two samples of the same class must be gradually changed. The aim of BPR is to find an optimal covering in the feature space, which emphasizes the "similarity" among homologous group members, rather than "division" in traditional pattern recognition. Some applications of BPR are surveyed, in which the results of BPR are much better than the results of Support Vector Machine. A novel neuron model, Hyper sausage neuron (HSN), is shown as a kind of covering units in BPR. The mathematical description of HSN is given and the 2-dimensional discriminant boundary of HSN is shown. In two special cases, in which samples are distributed in a line segment and a circle, both the HSN networks and RBF networks are used for covering. The results show that HSN networks act better than RBF networks in generalization, especially for small sample set, which are consonant with the results of the applications of BPR. And a brief explanation of the HSN networks' advantages in covering general distributed samples is also given.

Mandarin speech emotion recognition based on high dimensional geometry theory

In this paper, a novel approach for mandarin speech emotion recognition, that is mandarin speech emotion recognition based on high dimensional geometry theory, is proposed. The human emotions are classified into 6 archetypal classes: fear, anger, happiness, sadness, surprise and disgust. According to the characteristics of these emotional speech signals, the amplitude, pitch frequency and formant are used as the feature parameters for speech emotion recognition. The new method called high dimensional geometry theory is applied for recognition. Compared with traditional GSVM model, the new method has some advantages. It is noted that this method has significant values for researches and applications henceforth.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

Wavelet denoising and feature extraction of seismic signal for footstep detection

Seismic sensors are widely used to detect moving target in ground sensor networks. Footstep detection is very important for security surveillance and other applications. Because of non-stationary characteristic of seismic signal and complex environment conditions, footstep detection is a very challenging problem. A novel wavelet denoising method based on singular value decomposition is used to solve these problems. The signal-to-noise ratio (SNR) of raw footstep signal is greatly improved using this strategy. The feature extraction method is also discussed after denosing procedure. Comparing, with kurtosis statistic feature, the wavelet energy feature is more promising for seismic footstep detection, especially in a long distance surveillance.

Performance of an embedded optical vector matrix multiplication processor architecture

An embedded architecture of optical vector matrix multiplier (OVMM) is presented. The embedded architecture is aimed at optimising the data flow of vector matrix multiplier (VMM) to promote its performance. Data dependence is discussed when the OVMM is connected to a cluster system. A simulator is built to analyse the performance according to the architecture. According to the simulation, Amdahl's law is used to analyse the hybrid opto-electronic system. It is found that the electronic part and its interaction with optical part form the bottleneck of system.

Thermal induced facet destructive feature of quantum cascade lasers

We present a study on the facet damage profile of quantum cascade lasers (QCLs). Conspicuous cascade half-loop damage strips on front facet are observed when QCLs catastrophically failed. Due to the large difference on thermal conductivities between active region and the substrate, dominant heat is compulsively driven to the substrate. Abundant heat accumulation and dissipation on substrate build large temperature gradient and thermal lattice mismatch. Thermal-induced stress due to sequential mismatch leads to the occurrence of the multistep damages on front facet. Good agreement is achieved between the observed locations of damaged strips and the calculated results.

construction of feature-matching perception in virtual assembly

An important characteristic of virtual assembly is interaction. Traditional di-rect manipulation in virtual assembly relies on dynamic collision detection, which is very time-consuming and even impossible in desktop virtual assembly environment. Feature-matching isa critical process in harmonious virtual assembly, and is the premise of assembly constraint sens-ing. This paper puts forward an active object-based feature-matching perception mechanism and afeature-matching interactive computing process, both of which make the direct manipulation in vir-tual assembly break away from collision detection. They also help to enhance virtual environmentunderstandability of user intention and promote interaction performance. Experimental resultsshow that this perception mechanism can ensure that users achieve real-time direct manipulationin desktop virtual environment.

Steady-state bright-dark vector spatial solitons in biased photorefractive-photovoltaic crystals

We show that bright-dark vector solitons are possible in biased photorefractive-photovoltaic crystals under steady-state conditions, which result from both the bulk photovoltaic effect and the spatially nonuniform screening of the external bias field. The analytical solutions of these vector solitons can be obtained in the case of \sigma\ much less than 1, where sigma is the parameter controlling the intensities of the two optical beams. In the limit of -1 < sigma much less than 1, these vector solitons can also be determined by use of simple numerical integration procedures. When the bulk photovoltaic effect is neglectable, these vector solitons are bright-dark vector screening solitons studied previously in the \sigma\ much less than 1 regime, and predict bright-dark vector screening solitons in the -1 < sigma less than or equal to 1 regime. When the external bias field is absent, these vector solitons predict bright-dark vector photovoltaic solitons in closed and open circuits. (C) 2002 Elsevier Science B.V. All rights reserved.