Advance of molecular marker application in the tobacco research

Tobacco (Nicotiana spp.) is one of the most important commercial crops in the world. During the last two decades, molecular markers have entered the scene of genetic improvement in different fields of agricultural research. The principles and characteristics of several molecular markers such as RFLP, RAPD, AFLP, microsatellites and minisatellites applied in tobacco genetics and breeding were reviewed. The application and development of molecular marker in tobacco genetic research was presentedemphatically in the following areas: evolutionary genetics, population genetics and genotyping of cultivars, mapping and tagging of genes, and diversity analysis of germplasm. Finally, the perspective of molecular marker’s application in tobacco genetic breeding in the future was discussed

Development and application of a loop-mediated isothermal amplification method for rapid detection of Haemophilus parasuis

Haemophilus parasuis is the causative agent of Glässer’s disease that has received much attention recently, due to the increasing economic losses this disease inflicts upon the pig industry worldwide. In this study, loop-mediated isothermal amplification method (LAMP) methodology was designed for diagnosing H. parasuis infections and tested against 56 clinical samples. Two sets of primers for LAMP were designed based on the H. parasuis inf B gene sequence. Target DNA was amplified and visualized on agarose gels after 50 min incubation at 63°C. The LAMP amplicon was also directly visualized in the reaction tubes by the naked eye following the addition of SYBR green I. The detection limit of the inf BLAMP method was 10 cfu mL-1, that was 10 times more sensitive than conventional PCR. Furthermore, positive rates of H. parasuis detection using inf B-LAMP were higher (46.4%, 26/56) than the rates obtained with conventional PCR (33.9%, 19/56). inf B-LAMP specificity analysis demonstrated no crossreactivity with any other swine pathogens. In conclusion, inf B-LAMP was more sensitive and faster and could be carried out in the absence of expensive equipment. Furthermore, the visual readout demonstrated great potential for the use of inf B-LAMP in the clinical detection of H. parasuis.Key words: Glässer’s disease, Haemophilus parasuis, inf B, PCR, LAM

Object-Based Rendering and 3D reconstruction Using a Moveable Image-Based System

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Fault detection of redundant systems based on B-spline neural network

The fault detection and isolation of redundant sensor systems based on B-spline neural networks is presented in this paper. The network is trained using an algorithm with an adaptive learning rate. To further save computation time, the residual vector is transformed from a multivariate B-spline function to an univariate B-spline function. The detection of abrupt and drifting faults using the proposed method is discusses. The performance of the proposed method is illustrated by an example involving a redundant system consisting of six sensors.published_or_final_versio

State estimation with measurement error compensation using neural network

For a system with redundant sensors, the estimated state from the Kalman filter is biased if sensor mounting error existed. To remove this bias, the mounting errors must be compensated first before using the Kalman filter. It is shown that only the projection part of the sensors errors in the measurement space needs to be compensated. If the state of a system is unavailable, a neurofuzzy network can be used to estimate the compensation term. This method is simpler, as it does not require a model for the errors as that proposed in [2]. A sub-optimal Kalman filter with measurement compensation that restrains each row of the Kalman gain matrix to be in the measurement space is also derived. An example is presented to illustrate the performance of the proposed methods.published_or_final_versio

Mode couplings in superstructure fiber Bragg gratings

Author name used in this publication: A-Ping ZhangAuthor name used in this publication: Xiao-Ming Tao2001-2002 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

B-spline recurrent neural network and its application to modelling of non-linear dynamic systems

A new recurrent neural network based on B-spline function approximation is presented. The network can be easily trained and its training converges more quickly than that for other recurrent neural networks. Moreover, an adaptive weight updating algorithm for the recurrent network is proposed. It can speed up the training process of the network greatly and its learning speed is more quickly than existing algorithms, e.g., back-propagation algorithm. Examples are presented comparing the adaptive weight updating algorithm and the constant learning rate method, and illustrating its application to modelling of nonlinear dynamic system.published_or_final_versio

Width and wavelength-tunable optical pulse train generation based on four-wave mixing in highly nonlinear photonic crystal fiber

Author name used in this publication: M. S. DemokanAuthor name used in this publication: H. Y. Tam2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Nonlinear observer design with unknown nonlinearity via B-spline network approach

A novel approach is proposed to the state estimation of a class of nonlinear systems which consist of known linear part and unknown nonlinear part. A linear observer is first designed then a nonlinear compensation term in the nonlinear observer is determined using the proposed “deconvolution method”. The B-spline neural network is used to model the estimated compensation term. Three simulation examples are given to compare the effectiveness of the proposed approach and some analytical approaches.published_or_final_versio

Game-Theoretic Approach to Tourism Supply Chain Coordination under Demand Uncertainty For Package Holidays

Demand uncertainty is one of the most significant characteristics of the tourism industry. In a typical tourism supply chain (TSC) for package holidays, multiple tour operators reserve rooms from a hotel chain in advance according to their demand predictions. Discrepancies between demand predictions and actual demand lead to shortages or unused room reservations, which inevitably leads to reduced profits for the tour operators concerned. This article examines different TSC coordination strategies to determine how they can be used to help alleviate such negative effects. A game-theoretic approach is used to analyze the different coordination relationships between TSC players. Two coordination programs are discussed. The first is a horizontal coordination program in which tour operators exchange shortages or unused reservations with each other. The second is a vertical coordination program in which tour operators trade shortages or unused reservations with hotel chains. Game models are established and analyzed for the two coordination strategies and uncoordinated conditions, respectively. The analytical results suggest that both coordination strategies can be used to reduce the negative impacts of the demand uncertainty. The results also show that the horizontal coordination is preferred to the vertical coordination when the competition among tour operators is fierce.published_or_final_versio