Bioinformatic identification of genes encoding C1q-domain-containing proteins in zebrafish

C1q is the first subcomponent of classical pathway in the complement system and a major link between innate and acquired immunities. The globular (gC1q) domain similar with C1q was also found in many non-complement C1q-domain-containing (C1qDC) proteins which have similar crystal structure to that of the multifunctional tumor necrosis factor (TNF) ligand family, and also have diverse functions. In this study, we identified a total of 52 independent gene sequences encoding C1q-domain-containing proteins through comprehensive searches of zebrafish genome, cDNA and EST databases. In comparison to 31 orthologous genes in human and different numbers in other species, a significant selective pressure was suggested during vertebrate evolution. Domain organization of C1q-domain-containing (C1qDC) proteins mainly includes a leading signal peptide, a collagen-like region of variable length, and a C-terminal C1q domain. There are 11 highly conserved residues within the C1q domain, among which 2 are invariant within the zebrafish gene set. A more extensive database searches also revealed homologous C1qDC proteins in other vertebrates, invertebrates and even bacterium, but no homologous sequences for encoding C1qDC proteins were found in many species that have a more recent evolutionary history with zebrafish. Therefore, further studies on C1q-domain-containing genes among different species will help us understand evolutionary mechanism of innate and acquired immunities.

Two cathelicidin genes are present in both rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar)

Further to the previous finding of the rainbow trout rtCATH_1 gene, this paper describes three more cathelicidin genes found in salmonids: two in Atlantic salmon, named asCATH_1 and asCATH_2, and one in rainbow trout, named rtCATH_2. All the three new salmonid cathelicidin genes share the common characteristics of mammalian cathelicidin genes, such as consisting of four exons and possessing a highly conserved preproregion and four invariant cysteines clustered in the C-terminal region of the cathelin-like domain. The asCATH_1 gene is homologous to the rainbow trout rtCATH_1 gene, in that it possesses three repeat motifs of TGGGGGTGGC in exon IV and two cysteine residues in the predicted mature peptide, while the asCATH_2 gene and rtCATH_2 gene are homologues of each other, with 96% nucleotide identity. Salmonid cathelicidins possess the same elastase-sensitive residue, threonine, as hagfish cathelicidins and the rabbit CAP18 molecule. The cleavage site of the four salmonid cathelicidins is within a conserved amino acid motif of QKIRTRR, which is at the beginning of the sequence encoded by exon W. Two 36-residue peptides corresponding to the core part of rtCATH_1 and rtCATH_2 were chemically synthesized and shown to exhibit potent antimicrobial activity. rtCATH_2 was expressed constitutively in gill, head kidney, intestine, skin and spleen, while the expression of rtCATH_1 was inducible in gill, head kidney, and spleen after bacterial challenge. Four cathelicidin genes have now been characterized in salmonids and two were identified in hagfish, confirming that cathelicidin genes evolved early and are likely present in all vertebrates.

Single-electron tunneling depressing synapse for cellular neural networks

In this paper, a cellular neural network with depressing synapses for contrast-invariant pattern classification and synchrony detection is presented, starting from the impulse model of the single-electron tunneling junction. The results of the impulse model and the network are simulated using simulation program with integrated circuit emphasis (SPICE). It is demonstrated that depressing synapses should be an important candidate of robust systems since they exhibit a rapid depression of excitatory postsynaptic potentials for successive presynaptic spikes.

Aharonov-Bohm oscillation and chirality effect in optical activity of single-wall carbon nanotubes

We study the Aharonov-Bohm effect in the optical phenomena of single-wall carbon nanotubes (SWCN) and also their chirality dependence. Especially, we consider the natural optical activity as a proper observable and derive its general expression based on a comprehensive symmetry analysis, which reveals the interplay between the enclosed magnetic flux and the tubule chirality for arbitrary chiral SWCN. A quantitative result for this optical property is given by a gauge invariant tight-binding approximation calculation to stimulate experimental measurements.

Digits speech recognition based on geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems.We observe that this may be true for a recognition tasks based on geometrical learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions via the Hilbert transform. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy, Experiments show method based on ICA and geometrical learning outperforms HMM in different number of train samples.

Continuous speech recognition based on ICA and geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems. We observe that this may be true for recognition tasks based on Geometrical Learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy. Experiments show that the method based on ICA and Geometrical Learning outperforms HMM in a different number of training samples.

Continuous speech recognition based on ICA and geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems. We observe that this may be true for recognition tasks based on Geometrical Learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy. Experiments show that the method based on ICA and Geometrical Learning outperforms HMM in a different number of training samples.

Set invariance in control

The properties of positively invariant sets are involved in many different problems in control theory, such as constrained control, robustness analysis, synthesis and optimization. In this paper we provide an overview of the literature concerning positively invariant sets and their application to the analysis and synthesis of control systems.

分布式系统中必然方式下的谓词检测

本文研究了Definitely模态下分布式计算的谓词检测问题，即判断在计算产生的格状态空间中，是否每条从最小元到最大元的路径都通过一个满足谓词的状态。本文的主要内容有以下四个方面： １、本文建立了一个逻辑公式用来描述一个DNF谓词在Definitely模态下的检测是否为真。这个逻辑公式给出了一个新的方式用以考察对于DNF谓词Definitely模态的含义。由这个逻辑公式可以导出一种原有的区间缩减技术：区间压缩。接下来使用这个逻辑公式，还可以得到两种新的区间缩减技术：区间组合和区间删除。为了进行区间组合和区间删除，本文将计算表示成Hasse图，同时给出了一个化简Hasse图的方法。 ２、本文给出了两类DNF谓词，它们可以按照与合取谓词类似的方式检测，因此有多项式时间的检测算法。这两类DNF谓词是：分离DNF谓词和分离-包含DNF谓词。 ３、必然状态和必然集合在上面两类DNF谓词的检测中起着重要作用，因此本文研究了必然状态和必然集合的一些性质。接下来本文提出了区域独立的概念，区域独立是上面两类DNF谓词有多项式时间检测算法的本质，同时给出了区域独立的一些基本性质。 ４、本文证明了正则谓词在Definitely模态下的检测是coNP完全的，回答了文献中提出的未解决的问题。接下来研究了一种特殊情况下正则谓词在Definitely模态下的检测。这种特殊情况是：计算的所有状态都是一致的，称这时的状态空间为全空间。本文给出了全空间情况下对于正则谓词，Definitely模态和Invariant模态之间的关系。并且给出了一种算法，它在全空间情况下通过测试n条简单路进行Definitely模态下正则谓词的检测，其时间复杂度是O(n|E|)，其中n为计算中进程的个数，|E|是计算中所有事件的个数。

Structural studies of NixFe100-x/Mo magnetic multilayers by x-ray small-angle reflection and high-angle diffraction

Magnetic multilayers [NixFe100-x/Mo-30] grown by dc-magnetron sputtering were investigated by x-ray small-angle reflection and high-angle diffraction. Structural parameters of the multilayers such as the superlattice periods, the interfacial roughness, and interplane distance were obtained. It was found that for our NixFe100-x/Mo system, the Mo layer has bcc structure with [110] preferential orientation, while the preferential orientation of the NixFe100-x layer changes from a fee structure with [111] preferential orientation to a bcc structure with [110] preferential orientation with decreasing values of x. An intermixing layer located in the interlayer region between the NixFe100-x and Mo layers exists in the multilayers, and its thickness is almost invariant with respect to an increase of Mo layer thickness and/or a decrease of x in the region of x greater than or equal to 39. The thickness of the intermixing layer falls to zero when x less than or equal to 23.

图像不变局部特征研究及应用

图像不变局部特征是新近兴起的一类图像特征，基于不变局部特征的图像表示是计算机视觉的热点研究问题，在理论研究和实际应用上都具有重要意义。本论文针对图像不变局部特征的原理特性及应用展开研究：（1）当今流行的不变局部特征检测和描述方法；（2）局部特征组织方式；（3）基于局部不变特征的摄像机运动检测方法；（4）基于局部特征组合的目标模型及识别方法。 深入研究了当今流行的不变局部特征检测子，重点分析了其提取原理、特征结构、不变性阶次、精确度等特性，在此基础上对多种检测子进行比较分析，得出各自的适用范围，并总结出在具体应用环境下的特征选择原则。 针对视频分析中摄像机运动检测的具体应用，提出一种基于尺度不变局部特征的摄像机运动检测方法。该方法选取尺度不变局部特征，采用无序特征集合的方式表示图像帧，通过帧间局部特征的匹配，提出归一化软投票的方法鲁棒地估计特征匹配对的位置、尺度的变化，并根据各变化值和投票数的特点识别出摄像机的运动类型。该方法简单、鲁棒，满足了摄像机运动检测的处理速度和准确性需求。 针对基于局部特征的目标表示和识别问题，研究分析现有两种模型bag-of-words和part-based的优缺点，将二者结合，提出一种局部特征组合的目标表示模型和相应的识别算法。该方法在半局部区域内的特征同时进行外观描述和空间位置编码，并用数据挖掘中的频繁项挖掘技术自动提取出表征目标的特征组合，作为子模型。目标模型由一系列子模型构成，子模型的数量及每个子模型中包含的部件数目均自动从训练集中发现，是完全目标自适应的。所提方法克服了bag-of-words方法表达的精确性不足、part-based方法训练速度过慢的缺点，在识别问题上得到了较好的总体性能。

Optimized sinusoidal phase mask to extend the depth of field of an incoherent imaging system

Wavefront coding is a powerful technique that can be used to extend the depth of field of an incoherent imaging system. By adding a suitable phase mask to the aperture plane, the optical transfer function of a conventional imaging system can be made defocus invariant. Since 1995, when a cubic phase mask was first suggested, many kinds of phase masks have been proposed to achieve the goal of depth extension. In this Letter, a phase mask based on sinusoidal function is designed to enrich the family of phase masks. Numerical evaluation demonstrates that the proposed mask is not only less sensitive to focus errors than cubic, exponential, and modified logarithmic masks are, but it also has a smaller point-spread-function shifting effect. (C) 2010 Optical Society of America