Development of a positive-negative selection procedure for gene targeting in fish cells

The gene targeting technique is a powerful tool for analyzing functions of cloned genes and for generating transgenic animals with site-directed integration of foreign genes. In order to develop this technique in fish, positive-negative selection (PNS) and homologous recombination vectors were constructed, and their expression was examined in fish cells. A vector (pNK) for PNS consists of the neomycin resistance gene (neo) as a positive selectable marker gene and the herpes simplex virus (HSV) thymidine kinase (tk) gene as a negative selectable marker gene. Positive selection with geneticin (G418) of epithelioma papulosum of carp (EPC) cells transfected with linearized pNK vector yielded 350 colonies, while double selection of transfected EPC cells with G418 and gancyclovir (Gc) resulted in nearly complete cell death, demonstrating that the PNS procedure is effective in fish cells. Homologous recombination vectors consist of the Xiphophorus melanoma receptor kinase (X mrk(Y)) gene as homologous sequence in addition to the neo and tk genes. Conditions for homologous recombination vector transfection and drug selection were established. After verification of the feasibility of expression of homologous recombination vectors in EPC cells, the first gene targeting experiments were attempted in the Xiphophorus melanoma cell line, PSM. Positive-negative selection of the targeting vector-transfectants led to a low enrichment in this particular cell line. The reasons for the low enrichment in PSM cells were discussed. (C) 2002 Elsevier Science B.V. All rights reserved.

Positive magnetoresistance in In0.53Ga0.47As/In0.52Al0.48As quantum well

Magnetotransport measurements have been carried out on In0.53Ga0.17As/In0.52Al0.48 As quantum wells in a temperature range between 1.5 and 77 K. We have observed a large positive magnetoresistance in the low magnetic field range, but saturating in high magnetic fields. The magnetoresistance results from two occupied subbands in the two-dimensional electron gas. With the intersubband scattering considered, we obtained the subband mobility by analyzing the positive magnetoresistance. It is found that the second subband mobility is larger than that of the first due to the existence of the intersubband scattering.

Effect of implantation of nitrogen into SIMOX buried oxide on its fixed positive charge density

In order to obtain greater radiation hardness for SIMOX (separation by implanted oxygen) materials, nitrogen was implanted into SIMOX BOX (buried oxide). However, it has been found by the C-V technique employed in this work that there is an obvious increase of the fixed positive charge density in the nitrogen-implanted BOX with a 150 out thickness and 4 x 10(15) cm(-2) nitrogen implantation dose, compared with that unimplanted with nitrogen. On the other hand, for the BOX layers with a 375 nm thickness and implanted with 2 x 10(15) and 3 x 10(15) cm(-2) nitrogen doses respectively, the increase of the fixed positive charge density induced by implanted nitrogen has not been observed. The post-implantation annealing conditions are identical for all the nitrogen-implanted samples. The increase in fixed positive charge density in the nitrogen-implanted 150 nm BOX is ascribed to the accumulation of implanted nitrogen near the BOX/Si interface due to the post-implantation annealing process according to SIMS results. In addition, it has also been found that the fixed positive charge density in initial BOX is very small. This means SIMOX BOX has a much lower oxide charge density than thermal SiO2 which contains a lot of oxide charges in most cases.

Geometry property of multi-degree of freedom neurons

In this paper, we study a problem of geometric inequalities for a Multi-degree of Freedom Neurons. Some new geometric inequalities for a Multi-degree of Freedom Neurons are established. As special cases, some known inequalities are deduced.

Determining of the delay time for a heating ventilating and air-conditioning plant using multi-weights neurons approach

This paper presents an multi weights neurons approach to determine the delay time for a Heating ventilating and air-conditioning (HVAC) plan to respond to control actions. The multi weights neurons is a fully connected four-layer network. An acceleration technique was used to improve the general delta rule for the learning process. Experimental data for heating and cooling modes were used with both the multi weights neurons and a traditional mathematical method to determine the delay time. The results show that multi weights neurons can be used effectively determining the delay time for HVAC systems.

Discussion on the basic mathematical models of neurons - Double synaptic weight neuron in general-purpose neurocomputer, theory and application

Based on the introduction of the traditional mathematical models of neurons in general-purpose neurocomputer, a novel all-purpose mathematical model-Double synaptic weight neuron (DSWN) is presented, which can simulate all kinds of neuron architectures, including Radial-Basis-Function (RBF) and Back-propagation (BP) models, etc. At the same time, this new model is realized using hardware and implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. In this paper, the flexibility of the new model has also been described in constructing neural networks and based on the theory of Biomimetic pattern recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-H neurocomputer. The result showed DSWN neural network has great potential in pattern recognition.

Research on multi-degree-of-freedom neurons with weighted graphs

In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

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.

The structure and function of neurons with variable nonlinear transfer function

One novel neuron with variable nonlinear transfer function is firstly proposed, It could also be called as subsection transfer function neuron. With different transfer function components, by virtue of multi-thresholded, the variable transfer function neuron switch on among different nonlinear excitated state. And the comparison of output's transfer characteristics between it and single-thresholded neuron will be illustrated, with some practical application experiments on Bi-level logic operation, at last the simple comparison with conventional BP, RBF, and even DBF NN is taken to expect the development foreground on the variable neuron.. The novel nonlinear transfer function neuron could implement the random nonlinear mapping relationship between input layer and output layer, which could make variable transfer function neuron have one much wider applications on lots of reseach realm such as function approximation pattern recognition data compress and so on.

Face recognition based on PCA and multi-degree of freedom neurons

An algorithm of PCA face recognition based on Multi-degree of Freedom Neurons theory is proposed, which based on the sample sets' topological character in the feature space which is different from "classification". Compare with the traditional PCA+NN algorithm, experiments prove its efficiency.

Research on multi-degree-of-freedom neurons with weighted graphs

In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

Large positive and negative lateral displacements from total internal reflection configuration with a weakly absorbing dielectric film

It is theoretically shown that the simultaneously large positive and negative lateral displacements will appear when the resonant condition is satisfied for a TE-polarized light beam reflected from the total internal reflection configuration with a weakly absorbing dielectric film. Appearance of the enhanced negative lateral displacement is relative to the incidence angle, absorption of the thin Elm and its thickness. If we select an appropriate weakly absorbing dielectric film and its thickness, the simultaneously enhanced positive and negative lateral displacements will appear at different resonant angles. These phenomena may lead to convenient measurements and interesting applications in optical devices.

Controllable negative and positive group delay in transmission through a single quantum well at finite magnetic fields

We investigate the controllable negative and positive group delay in transmission through a single quantum well at the finite longitudinal magnetic fields. It is shown that the magneto-coupling effect between the longitudinal motion component and the transverse Landau orbits plays an important role in the group delay. The group delay depends not only on the width of potential well and the incident energy, but also on the magnetic-field strengthen and the Landau quantum number. The results show that the group delay can be changed from positive to negative by the modulation of the magnetic field. These interesting phenomena may lead to the tunable quantum mechanical delay line. (c) 2007 Elsevier B.V. All rights reserved.