Sequencing, annotation and comparative analysis of nine BACs of giant panda (Ailuropoda melanoleuca)

A 10-fold BAC library for giant panda was constructed and nine BACs were selected to generate finish sequences. These BACs could be used as a validation resource for the de novo assembly accuracy of the whole genome shotgun sequencing reads of giant panda newly generated by the Illumina GA sequencing technology. Complete sanger sequencing, assembly, annotation and comparative analysis were carried out on the selected BACs of a joint length 878 kb. Homologue search and de novo prediction methods were used to annotate genes and repeats. Twelve protein coding genes were predicted, seven of which could be functionally annotated. The seven genes have an average gene size of about 41 kb, an average coding size of about 1.2 kb and an average exon number of 6 per gene. Besides, seven tRNA genes were found. About 27 percent of the BAC sequence is composed of repeats. A phylogenetic tree was constructed using neighbor-join algorithm across five species, including giant panda, human, dog, cat and mouse, which reconfirms dog as the most related species to giant panda. Our results provide detailed sequence and structure information for new genes and repeats of giant panda, which will be helpful for further studies on the giant panda.

Cancer subtypes recognition and its gene expression profiles analysis based on geometrical learning

The accurate recognition of cancer subtypes is very significant in clinic. Especially, the DNA microarray gene expression technology is applied to diagnosing and recognizing cancer types. This paper proposed a method of that recognized cancer subtypes based on geometrical learning. Firstly, the cancer genes expression profiles data was pretreated and selected feature genes by conventional method; then the expression data of feature genes in the training samples was construed each convex hull in the high-dimensional space using training algorithm of geometrical learning, while the independent test set was tested by the recognition algorithm of geometrical learning. The method was applied to the human acute leukemia gene expression data. The accuracy rate reached to 100%. The experiments have proved its efficiency and feasibility.

Fast and effective analysis methods for fiber Raman amplifiers

A series of new single-step methods and their corresponding algorithms with automatic step size adjustment for model equations of fiber Raman amplifiers are proposed and compared in this paper. On the basis of the Newton-Raphson method, multiple shooting algorithms for the two-point boundary value problems involved in solving Raman amplifier propagation equations are constructed. A verified example shows that, compared with the traditional Runge-Kutta methods, the proposed methods can increase the accuracy by more than two orders of magnitude under the same conditions. The simulations for Raman amplifier propagation equations demonstrate that our methods can increase the computing speed by more than 5 times, extend the step size significantly, and improve the stability in comparison with the Dormand-Prince method. The numerical results show that the combination of the multiple shooting algorithms and the proposed methods has the capacity to rapidly and effectively solve the model equations of multipump Raman amplifiers under various conditions such as co-, counter- and bi-directionally pumped schemes, as well as dual-order pumped schemes.

An automatic step adjustment method for average power analysis technique used in fiber amplifiers

An automatic step adjustment (ASA) method for average power analysis (APA) technique used in fiber amplifiers is proposed in this paper for the first time. In comparison with the traditional APA technique, the proposed method has suggested two unique merits such as a higher order accuracy and an ASA mechanism, so that it can significantly shorten the computing time and improve the solution accuracy. A test example demonstrates that, by comparing to the APA technique, the proposed method increases the computing speed by more than a hundredfold under the same errors. By computing the model equations of erbium-doped fiber amplifiers, the numerical results show that our method can improve the solution accuracy by over two orders of magnitude at the same amplifying section number. The proposed method has the capacity to rapidly and effectively compute the model equations of fiber Raman amplifiers and semiconductor lasers. (c) 2006 Optical Society of America

Land-cover classification of China: integrated analysis of AVHRR imagery and geophysical data

Over last two decades, numerous studies have used remotely sensed data from the Advanced Very High Resolution Radiometer (AVHRR) sensors to map land use and land cover at large spatial scales, but achieved only limited success. In this paper, we employed an approach that combines both AVHRR images and geophysical datasets (e.g. climate, elevation). Three geophysical datasets are used in this study: annual mean temperature, annual precipitation, and elevation. We first divide China into nine bio-climatic regions, using the long-term mean climate data. For each of nine regions, the three geophysical data layers are stacked together with AVHRR data and AVHRR-derived vegetation index (Normalized Difference Vegetation Index) data, and the resultant multi-source datasets were then analysed to generate land-cover maps for individual regions, using supervised classification algorithms. The nine land-cover maps for individual regions were assembled together for China. The existing land-cover dataset derived from Landsat Thematic Mapper (TM) images was used to assess the accuracy of the classification that is based on AVHRR and geophysical data. Accuracy of individual regions varies from 73% to 89%, with an overall accuracy of 81% for China. The results showed that the methodology used in this study is, in general, feasible for large-scale land-cover mapping in China.

Application of rough set-based analysis to extract spatial relationship indicator rules: An example of land use in Pearl River Delta

Spatial relations, reflecting the complex association between geographical phenomena and environments, are very important in the solution of geographical issues. Different spatial relations can be expressed by indicators which are useful for the analysis of geographical issues. Urbanization, an important geographical issue, is considered in this paper. The spatial relationship indicators concerning urbanization are expressed with a decision table. Thereafter, the spatial relationship indicator rules are extracted based on the application of rough set theory. The extraction process of spatial relationship indicator rules is illustrated with data from the urban and rural areas of Shenzhen and Hong Kong, located in the Pearl River Delta. Land use vector data of 1995 and 2000 are used. The extracted spatial relationship indicator rules of 1995 are used to identify the urban and rural areas in Zhongshan, Zhuhai and Macao. The identification accuracy is approximately 96.3%. Similar procedures are used to extract the spatial relationship indicator rules of 2000 for the urban and rural areas in Zhongshan, Zhuhai and Macao. An identification accuracy of about 83.6% is obtained.

Non-goal scene analysis for soccer video

The broadcast soccer video is usually recorded by one main camera, which is constantly gazing somewhere of playfield where a highlight event is happening. So the camera parameters and their variety have close relationship with semantic information of soccer video, and much interest has been caught in camera calibration for soccer video. The previous calibration methods either deal with goal scene, or have strict calibration conditions and high complexity. So, it does not properly handle the non-goal scene such as midfield or center-forward scene. In this paper, based on a new soccer field model, a field symbol extraction algorithm is proposed to extract the calibration information. Then a two-stage calibration approach is developed which can calibrate camera not only for goal scene but also for non-goal scene. The preliminary experimental results demonstrate its robustness and accuracy. (c) 2010 Elsevier B.V. All rights reserved.

Miniaturized tris(2,2 '-bipyridyl)ruthenium(II) electrochemiluminescence detection cell for capillary electrophoresis and flow injection analysis

The design and performance of a miniaturized chip-type tris(2,2'-bipyridyl)ruthenium(II) [Ru(bpy)(3)(2+)] electrochemiluminescence (ECL) detection cell suitable for both capillary electrophoresis (CE) and flow injection (FI) analysis are described. The cell was fabricated from two pieces of glass (20 x 15 x 1.7 mm), and the 0.5-mm-diameter platinum disk was used as working electrode held at +1.15 V (vs silver wire quasi-reference), the stainless steel guide tubing as counter electrode, and the silver wire as quasi-reference electrode. The performance traits of the cell in both CE and FI modes were evaluated using tripropylamine, proline, and oxalate and compared favorably to those reported for CE and FI detection cells. The advantages of versatility, sensitivity, and accuracy make the device attractive for the routine analysis of amine-containing species or oxalate by CE and FI with Ru(bPY)(3)(2divided by) ECL detection.

Improved thermal fractionation technique for chain structure analysis of ethylene/alpha-olefin copolymers

In this report, we describe an improved thermal fractionation technique used to characterize the polydispersity of crystalline ethylene sequence length (CESL) of ethylene/alpha -olefin copolymers. After stepwise isothermal crystallization, the crystalline ethylene sequences are sorted into groups by their lengths. The CESLs are estimated using melting points of known hydrocarbons. The content of each group is determined using the calibrated peak area. The statistical terms: the arithmetic mean (L) over bar (n), the weighted mean (L) over bar (w) and the broadness index I = (L) over bar (w)/(L) over bar (n) are used to describe the distribution of CESL. Results show that improved thermal fractionation technique can quantitatively characterize the polydispersity of CESL with a high degree of accuracy.

Simultaneous spectrophotometric determination of zinc, cadmium and mercury with hybrid linear analysis

A new method for simultaneous spectrophotometric determination of Zn, Cd and Hg using 2-(5-Br-2-pyridylazo)-5-diethylaminophenol as the color developing reagent was proposed. The absorption spectra of these three complexes have similar features with severe overlap in visible spectral range. For resolving these spectra, hybrid linear analysis was used, and the pure spectrum of each component was obtained from the calibration mixtures by least squares method. The effects of reaction condition, selection of wavelengths, determination of pure spectrum and additivity of absorbances etc. on the determination were discussed. The proposed method offers the advantages of simple, rapid, and accuracy. It has been successfully applied to the simultaneous determination of Zn, Cd and Hg in synthetic sample. A comparison was also made with the partial least squares method.

Simultaneous spectrophotometric determination of trace iron (III) and aluminum (III) with hybrid linear analysis

Hybrid linear analysis (HLA) was applied to resolution of overlapping spectra of Fe3+-salicylfluorone and Al3+-salicylfluorone complexes and simultaneous spectrophotometric determination of Fe3+ and Al3+. The absorbance matrix of 7 standard mixtures at 41 measuring points ranged from the wavelength of 550 nm to 630 nm was used for calibration. To avoid the effect of interaction between the two components on the determination, the column vector of K matrix obtained from the standard mixtures with least squares was used as the pure spectrum of component. The recoveries of the two elements for the analysis of the synthetic samples were 93.3% similar to 107.5% in the range of the concentration ratio of Fe3+:Al3+ = 10:1 to 1:8. Comparing with the partial least squares (PIS) model, the HLA method was simple, accuracy and precise.