Pipeline Architecture and Parallel Computation-Based Real-Time Stereovision Tracking System for Surgical Navigation

This paper studies the development of a real-time stereovision system to track multiple infrared markers attached to a surgical instrument. Multiple stages of pipeline in field-programmable gate array (FPGA) are developed to recognize the targets in both left and right image planes and to give each target a unique label. The pipeline architecture includes a smoothing filter, an adaptive threshold module, a connected component labeling operation, and a centroid extraction process. A parallel distortion correction method is proposed and implemented in a dual-core DSP. A suitable kinematic model is established for the moving targets, and a novel set of parallel and interactive computation mechanisms is proposed to position and track the targets, which are carried out by a cross-computation method in a dual-core DSP. The proposed tracking system can track the 3-D coordinate, velocity, and acceleration of four infrared markers with a delay of 9.18 ms. Furthermore, it is capable of tracking a maximum of 110 infrared markers without frame dropping at a frame rate of 60 f/s. The accuracy of the proposed system can reach the scale of 0.37 mm RMS along the x- and y-directions and 0.45 mm RMS along the depth direction (the depth is from 0.8 to 0.45 m). The performance of the proposed system can meet the requirements of applications such as surgical navigation, which needs high real time and accuracy capability.

P-QuantWiz:一种基于质谱的并行非标记定量软件

本文设计并实现了基于质谱的非标记定量软件QuantWiz,通过改变肽段定量的顺序,提高了定量软件的时间局部性和质谱数据缓存的命中次数。分析了QuantWiz的多种数据并行策略,设计并实现了按保留时间划分的并行定量软件P-QuantWiz。通过实验验证P-QuantWiz具有良好的并行效率,当进程数为32时,并行效率为63%。

基于质谱的高性能蛋白质非标记定量软件设计与性能优化

本文介绍了定量蛋白质组学中一个较为年轻和重要的新课题：基于质谱的非标记定量。基于质谱的非标记定量技术不使用同位素标记等化学手段，而是通过对质谱原始数据的分析和处理来进行蛋白质定量。 本文对基于质谱的非标记定量技术做了概要性的调研，阐述了此技术中存在的大规模数据处理性能瓶颈问题，并进一步指出了高性能计算尤其是并行计算技术在非标记定量中应用的迫切性和必要性。 针对当前质谱数据可视化辅助分析工具共同存在的一个缺陷，即质谱数据需要全部导入内存，本文设计并实现了质谱可视化辅助分析工具MZ-Analyzer。与其它可视化分析工具不一样的是，MZ-Analyzer没有将质谱数据全部导入主存，而是通过构建外存索引提高质谱数据可视化辅助分析的性能。因此，尽管随着质谱数据量的指数性增长，MZ-Analyzer的性能仍然具有良好的可扩展性。 本文设计并实现了基于质谱的非标记定量软件QuantWiz，通过改变肽段定量的顺序，提高了定量软件的时间局部性和质谱数据缓存的命中次数。分析了QuantWiz的多种数据并行策略，设计并实现了按保留时间划分的并行QuantWiz。通过实验验证并行QuantWiz具有良好的并行效率，当进程数为32时，并行效率为63%。

面向车牌识别的区域分割技术

对车牌识别区域分割过程及相关算法进行了研究和讨论,针对某一类情况提出新的思路及方法:断点分析法确定字符区域位置;漫水法和边缘跟踪法结合进行区域分割。在此基础上,实现了一个汽车车牌识别应用系统。

并行最优路径算法及K优路径算法研究

最优路径问题是计算机科学、运筹学、工程设计等领域很多问题的基础。它的应用包括网络路由、电路设计、交通运输、机器人运动规划、事务调度中关键路径的计算以及VLSI设计等。同时，它也为很多最优化问题提供了解决框架，如背包问题、分子生物学中的序列比对、内接多边形的构造和长度受限的霍夫曼编码等都可以转化成最优路径问题进行求解。 求解网络中最优路径的方法可以分为两大类。一种是标号设定算法（label setting ,LS）,另一种是标号改变算法（label correcting ,LC）。由于网络路径算法的应用越来越强调动态性和及时性，使得高效求解最优路径问题变得越来越重要。在这里，我们利用一种高效的网络划分方法，实现了基于网络划分的LS/LC并行算法。实验结果表明，基于这种网络划分的并行算法对于求解最优路径有很好的加速比和扩展比。 在许多更加复杂的应用中，不仅要求计算出最优路径，而且要求给出前K优路径。K优路径是长期研究的泛化最优路径问题，即不但要求得到最优路径，还要得到次短、再次短等路径。 节点s到节点t的K优路径问题可以分为两大类：一类是求解K优非简单路径，即得到的路径可以包含环路；另一类是求解K优简单路径，即路径是简单通路，不包含环路。经过大量学者的研究，求解K优非简单路径相对容易。Fox 于1975年提出了复杂度为O(m+nlogn) 的求解K优非简单路径的算法，最近， Eppstein于1998年给出了一种优化的求解K优非简单路径的算法，时间复杂度达到了O(m+nlogn+k) ，基本上达到了理论下限。 在2000年对E 的算法进行并行化，时间复杂度为 。求解K优简单路径已被证明是更为具有挑战性，这个问题最先由Hofman和Pavley 在1957年进行开始研究，但几乎所有试图解决该问题的算法时间复杂度都达到指数时间。众所周知，Yen提出了一结果比较好的算法，利用现代的数据结构达到O(kn(n+nlogn)) 时间复杂度。John Hershberger于2007年给出了一个新的求K优路径的算法，该算法基于有效率的替代路径算法,相对于以前的替代路径算法，其加速比可达到O(n) 。在本文中，我们基于John Hershberger给出的K优路径算法，尝试给出其并行的方法，并在SMP的高性能计算机上进行了测试。 关键词 并行算法、最优路径、K优路径、网络划分

Determination of peptides and amino acids from wool and beer with sensitive fluorescent reagent 2-(9-carbazole)-ethyl chloroformate by reverse phase high-performance liquid chromotography and liquid chromotography mass spectrometry

A new method for the sensitive determination of amino acids and peptides using the tagging reagent 2-(9-carbazole)-ethyl chloroformate (CEOC) with fluorescence (FL) detection has been developed. Identification of derivatives was carried out by liquid chromotography mass spectrometry. The chromophore in the 2-(9-fluorenyl)-ethyl chloroformate (FMOC) reagent was replaced by carbazole, which resulted in a sensitive fluorescence lerivatizing agent CEOC. CEOC can easily and quickly label peptides and amino acids. Derivatives are stable enough to be efficiently analyzed by high-performance liquid chromatography. Studies on derivatization demonstrate excellent derivative yields over the pH range 8.8-10.0. Maximal yields close to 100% are observed with three- to fourfold molar reagent excess. Derivatives exhibit strong fluorescence and allow direct injection of the reaction mixture with no significant disturbance from the major fluorescent reagent degradation by-products, such as 2(9-carbazole)-ethanol and bis-(2-(9-carbazole)-ethyl) carbonate. In addition, the detection responses for CEOC derivatives are compared to those obtained with FMOC. The ratios AC(CEOC)/AC(FMOC) = 1.00-1.82 for fluorescence (FL) response and AC'(CEOC)/AC'(FMOC) = 1.00-1.21 for ultraviolet (UV) response are observed (here, AC and AC' are, respectively, FL and UV F response). Separation of the derivatized peptides and amino acids has been optimized on a Hypersil BDS C18 column. Excellent linear responses are observed. This method was used successfully to analyze protein hydrolysates from wool and from direct-derivatized beer. (C) 2003 Elsevier Science (USA). All rights reserved.

Stable Isotope Probing:Linking Functional Activity to Specific Members of Microbial Communities

Linking organisms or groups of organisms to specific functions within natural environments is a fundamental challenge in microbial ecology. Advances in technology for manipulating and analyzing nucleic acids have made it possible to characterize the members of microbial communities without the intervention of laboratory culturing. Results from such studies have shown that the vast majority of soil organisms have never been cultured, highlighting the risks of culture-based approaches in community analysis. The development of culture-independent techniques for following the flow of substrates through microbial communities therefore represents an important advance. These techniques, collectively known as stable isotope probing (SIP), involve introducing a stable isotope-labeled substrate into a microbial community and following the fate of the substrate by extracting diagnostic molecular species such as fatty acids and nucleic acids from the community and determining which specific molecules have incorporated the isotope. The molecules in which the isotope label appears provide identifying information about the organism that incorporated the substrate. Stable isotope probing allows direct observations of substrate assimilation in minimally disturbed communities, and thus represents an exciting new tool for linking microbial identity and function. The use of lipids or nucleic acids as the diagnostic molecule brings different strengths and weaknesses to the experimental approach, and necessitates the use of significantly different instrumentation and analytical techniques. This short review provides an overview of the lipid and nucleic acid approaches, discusses their strengths and weaknesses, gives examples of applications in various settings, and looks at prospects for the future of SIP technology.

混凝土薄壳球形水窖结构的优化设计

分析球形水窖空间结构的应力分布情况并进行几何尺寸优化,避免建设者根据经验来确定球形水窖的厚度、构造及混凝土标号,以节省建窖材料,同时防止应力不足而发生破坏。【方法】利用基于ANSYS平台新开发的窖体有限元分析软件,对实际中窖壁厚度为4和11 cm的混凝土薄壳球形水窖进行空间结构应力分析,同时以水窖耗材量最小为目标函数,以许用应力和变形量为约束条件,对其进行几何尺寸优化。【结果】计算得出窖壁厚度为4和11 cm的水窖最大拉应力分别为1 380.00和447.31 kPa,最大压应力分别为5 153.20和1 896.70 kPa;优化出空窖不利工况下容积为20,30和40 m3的球形水窖窖壁最佳厚度,即栗钙土地区分别为0.051,0.061和0.065m,黄土地区分别为0.050,0.059和0.062 m。【结论】经软件优化计算后的球形水窖结构,既能满足强度和刚度的要求,同时也最大限度地节约了材料用量;利用新开发的窖体结构优化分析软件,能够对球形水窖进行空间应力分析与结构优化,可以作为球形水窖设计软件。

Partially Supervised Neighbor Embedding for Example-Based Image Super-Resolution

Neighbor embedding algorithm has been widely used in example-based super-resolution reconstruction from a single frame, which makes the assumption that neighbor patches embedded are contained in a single manifold. However, it is not always true for complicated texture structure. In this paper, we believe that textures may be contained in multiple manifolds, corresponding to classes. Under this assumption, we present a novel example-based image super-resolution reconstruction algorithm with clustering and supervised neighbor embedding (CSNE). First, a class predictor for low-resolution (LR) patches is learnt by an unsupervised Gaussian mixture model. Then by utilizing class label information of each patch, a supervised neighbor embedding is used to estimate high-resolution (HR) patches corresponding to LR patches. The experimental results show that the proposed method can achieve a better recovery of LR comparing with other simple schemes using neighbor embedding.

Supervised Gaussian Process Latent Variable Model for Dimensionality Reduction

The Gaussian process latent variable model (GP-LVM) has been identified to be an effective probabilistic approach for dimensionality reduction because it can obtain a low-dimensional manifold of a data set in an unsupervised fashion. Consequently, the GP-LVM is insufficient for supervised learning tasks (e. g., classification and regression) because it ignores the class label information for dimensionality reduction. In this paper, a supervised GP-LVM is developed for supervised learning tasks, and the maximum a posteriori algorithm is introduced to estimate positions of all samples in the latent variable space. We present experimental evidences suggesting that the supervised GP-LVM is able to use the class label information effectively, and thus, it outperforms the GP-LVM and the discriminative extension of the GP-LVM consistently. The comparison with some supervised classification methods, such as Gaussian process classification and support vector machines, is also given to illustrate the advantage of the proposed method.

Amplified electrochemical aptasensor taking AuNPs based sandwich sensing platform as a model

Here, we report a sensitive amplified electrochemical impedimetric aptasensor for thrombin, a kind of serine protease that plays important role in thrombosis and haemostasis. For improving detection sensitivity, a sandwich sensing platform is fabricated, in which the thiolated aptamers are firstly immobilized on a gold substrate to capture the thrombin molecules, and then the aptamer functionalized Au nanoparticles (AuNPs) are used to amplify the impedimetric signals.

Enzyme Colorimetric Assay Using Unmodified Silver Nanoparticles

Colorimetric assay based on the unique surface plasmon resonance properties of metallic nanoparticles has received considerable attention in bioassay due to its simplicity, high sensitivity, and low cost. Most of colorimetric methods previously reported employed gold nanoparticles (GNPs) as sensing elements. In this work, we develop a sensitive, selective, simple, and label-free colorimetric assay using unmodified silver nanoparticle (AgNP) probes to detect enzymatic reactions. Enzymatic reactions concerning adenosine triphosphate (ATP) dephosphorylation by calf intestine alkaline phosphatase (CLAP) and peptide phosphorylation by protein kinase A (PKA) were studied.

DNAzyme-based Colorimetric Sensing of Lead (Pb2+) Using Unmodified Gold Nanoparticle Probes

Novel functional oligonucleotides, especially DNAzymes with RNA-cleavage activity, have been intensively studied due to their potential applications in therapeutics and sensors. Taking advantage of the high specificity of 17E DNAzyme for Pb2+, highly sensitive and selective fluorescent, electrochemical and colorimetric sensors have been developed for Pb2+. In this work, we report a simple, sensitive and label-free 17E DNAzyme-based sensor for Pb2+ detection using unmodified gold nanoparticles (GNPs) based on the fact that unfolded single-stranded DNA could be adsorbed on the citrate protected GNPs while double-stranded DNA could not. By our method the substrate cleavage by the 17E DNAzyme in the presence of Pb2+ could be monitored by color change of GNPs, thereby Pb2+ detection was realized.

A sensitive impedimetric thrombin aptasensor based on polyamidoamine dendrimer

A label-free and highly sensitive impedimetric aptasensor based on a polyamidoamine dendrimer modified gold electrode was developed for the determination of thrombin. Amino-terminated polyamidoamine dendrimer was firstly covalently attached to the cysteine functionalized gold electrode through glutaraldehyde coupling. Subsequently, the dendrimer was activated with glutaraldehyde, and amino-modified thrombin aptamer probe was immobilized onto the activated dendrimer monolayer film. The layer-by-layer assembly process was traced by surface plasmon resonance and electrochemical impedance spectroscopy.