MEIOTIC CHROMOSOME BEHAVIOR IN FEMALE INTERSEXES OF ARTIFICIAL TRIPLOID TRANSPARENT-COLORED CRUCIAN CARP

Chromosome behavior in meiosis was studied by air-drying, C-banding and surface-spreading methods in female intersexes of artificial triploid transparent-colored crucian carp (Carassius auratus). Chromosome pairing and contraction were obviously asynchronous. The preferential pairing of two homologous chromosomes was the major pattern of chromosome pairing, and a few triple pairing, repeated pairing, telomer or centromere associating and multiple pairing were also observed in the pachytene cells. The metaphase I cells were mainly composed of univalents, bivalents and trivalents, as well as few of other multivalents, such as tetravalents, pentavalents, hexavalents and heptavalents, were also found in some metaphase I cells. The chromosome elements including uni-, bi-, tri- and other multivalents varied considerably among the metaphase I cells, and the associating patterns of multivalents were also diverse. Some 6 n and 12 n cells, in which premeiotic endomitosis occurred once or twice, were found at the prophase and first metaphase of meiosis, and the pairing and associating patterns were basically similar to that of the triploid cells.

Artificial nanograting woven by self-assembled nanowires

We report on a new simple route to realize a high resolution nanograting. By adopting an InAlGaAs matrix and strain-compensated technique, we have proved that a uniform self-assembled InAs nanowire array can be fabricated by molecular beam epitaxy (MBE). A nanograting woven by self-assembled semiconductor nanowires shows a conspicuous diffraction feature. The good agreement between the theoretical and experimental values of diffraction peak positions indicates that a uniform nanowire array is a promising nanograting. This simple one-step MBE growth method will open exciting opportunities for the field of clever optics design.

SOC dynamic power management using artificial neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level power management policies. We proposed two PM policies-Back propagation Power Management (BPPM) and Radial Basis Function Power Management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79, 1.45, 1.18-competitive separately for traditional timeout PM, adaptive predictive PM and stochastic PM.

Ground-state properties of an artificial molecule: a simple model calculation for the double quantum dot

The ground state of a double quantum-dot structure is studied by a simplified Anderson-type model. Numerical calculations reveal that the ground-state level of this artificial molecule increases with the increasing single particle level of the dot, and also increases with the decreasing transfer integrals. We show the staircase feature of the electron occupation and the properties of the ground-state eigenvector by varying the;single particle level of the dot.

SOC dynamic power management using artificial neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level power management policies. We proposed two PM policies-Back propagation Power Management (BPPM) and Radial Basis Function Power Management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79 . 1.45 . 1.18-competitive separately for traditional timeout PM . adaptive predictive PM and stochastic PM.

Subretinal implantable artificial photoreceptor

The present study reports a subretinal implant device which can imitate the function of photoreceptor cells. Photodiode (PD) arrays on the chip translate the incident light into current according to the intensity of light. With an electrode at the end of every photodiode, the PDs transfer the current to the remnant healthy visual cells such as bipolar cells and horizontal cells and then activate these cells. Biocompatible character of the materials and artificial photoreceptor itself were tested and the photoelectric characteristics of the chips in simulative condition were described and discussed.

Kinetic Model Study on Enzymatic Hydrolysis of Cellulose Using Artificial Neural Networks

Enzymatic hydrolysis of cellulose was highly complex because of the unclear enzymatic mechanism and many factors that affect the heterogeneous system. Therefore, it is difficult to build a theoretical model to study cellulose hydrolysis by cellulase. Artificial neural network (ANN) was used to simulate and predict this enzymatic reaction and compared with the response surface model (RSM). The independent variables were cellulase amount X-1, substrate concentration X-2, and reaction time X-3, and the response variables were reducing sugar concentration Y-1 and transformation rate of the raw material Y-2. The experimental results showed that ANN was much more suitable for studying the kinetics of the enzymatic hydrolysis than RSM. During the simulation process, relative errors produced by the ANN model were apparently smaller than that by RSM except one and the central experimental points. During the prediction process, values produced by the ANN model were much closer to the experimental values than that produced by RSM. These showed that ANN is a persuasive tool that can be used for studying the kinetics of cellulose hydrolysis catalyzed by cellulase.

Quantum computation using artificial molecules

Two kinds of quantum computation systems using artificial molecules: quantum computer and quantum analog computer are described. The artificial molecule consists of two or three coupled quantum dots stacked along z direction and one single electron, In quantum computer, one-qubit and two-qubit gates are constructed by one molecule and two molecules, respectively. The coupling between two qubits in a quantum gate can be controlled by thin film electrodes. We also constructed a quantum analog computer by designing a three-dot molecule network and mapping a graph 3-colorability problem onto the network. The ground-state configuration of the single electrons in the network corresponds to one of the problem solutions, We numerically study the operations of the two kinds of the quantum computers and demonstrate that they quantum gates can perform the quantum computation and solve complex problems.

Artificial neural networks expecting more advanced microelectronics technology

　

Simultaneous determination of methylene blue and new methylene blue by slab optical waveguide spectroscopy and artificial neural networks

A slab optical waveguide (SOWG) has been used for study of adsorption of both methylene blue (MB) and new methylene blue (NMB) in liquid-solid interface. Adsorption characteristics of MB and NMB on both bare SOWG and silanized SOWG by octadecyltrichlorosilane (ODS) were compared. The simultaneous determinations of both MB and NMB were explored by flow injection SOWG spectrophotometric analysis and artificial neural networks (ANNs) for the first time. Concentrations of MB and NMB were estimated simultaneously with the ANNs. Results obtained with SOWG were compared with those got by conventional UV-visible spectrophotometry. (C) 2003 Elsevier Science B.V All rights reserved.