高分辨雷达距离-多普勒扩展目标广义自适应子空间检测器

本文提出了一种非高斯杂波中的距离-多普勒扩展目标广义自适应子空间检测器(RDST-GASD).采用了频率-慢时间子空间模型来描述宽带雷达回波信号序列.杂波的统计模型采用球不变随机向量描述,各距离单元内的杂波具有相同的归一化协方差矩阵和不同的功率(非均匀),并且假设可以得到只含有杂波的参考单元的数据以估计杂波的协方差矩阵.通过理论分析证明了RDST-GASD对杂波的功率和协方差矩阵都具有恒虚警的性质.对于宽带雷达,在相参处理时间内,目标回波通常存在越距离单元走动,RDST-GASD进行了距离对齐处理,从而实现了有效的相参积累,提高了检测性能.     

新疆膜下滴灌土壤粒径分布及与水盐含量的关系

土壤粒径分布及空间变化是土壤重要的物理特性之一，对土壤水分和溶质运移、土壤侵蚀等有重要意义．研究选用新疆膜下滴灌试验田的563个土壤样品，利用激光衍射粒径分析仪分析土壤粒径分布，采用质地三角分类、分形和多重分形对土壤粒径分布进行研究，探讨土壤粒径特征及与水盐含量的关系．研究区土壤颗粒中粘粒含量偏低，平均值为1．52％，砂粒含量最大，粒径分布呈现复杂的单、双峰分布特征；土壤粒径分布的分形和多重分形与土壤颗粒含量的标准差及最大值有良好的相关性，可以较好地反映土壤粒径分布曲线．膜下滴灌对表层土壤盐分空间分布有较大影响，随着深度增加影响减弱；土壤质地与稳定状态下土壤水盐含量关系密切，特别是对土壤表层盐分聚集和深层土壤水分分布有显著影响．     

基于DSP＆CPLD的便携式振动信号处理系统

为了更准确方便地诊断设备运行特性，结合FFT和小波分析原理设计了一种基于DSP＆CPLD的便携式振动信号处理系统。系统的硬件电路由信号调理电路、数据采集处理模块和外围电路等组成，其软件部分由主程序模块、数据采集处理程序和LCD显示程序等组成，能够实时采集振动信号，显示并存储静态特性、振动波形和频谱等数据。     

基于FPGA的音频分析系统实现

采用Altera公司的FPGA芯片EP2C20作为控制和运算核心，实现对频率范围在20Hz～20kHz的音频信号分析和测试。采用FFT算法对音频信号进行频谱分析和计算处理，实现失真度分析，并完成信号总功率、各分量频率、周期等参数分析测量。采用TFT-LCD作为显示终端，能够直观显示功率谱曲线和各测试参数值。通过软件分析对比测试发现，该系统实时性强，测量准确度高，误差优于0．3％，可以有效完成音频信号分析和处理。     

淮河流域近50年来气候变化及突变分析

基于淮河流域1961~2015年的主要气象数据,采用趋势分析、M-K检验和R/S方法,对淮河流域的气温、降水和日照时数3个要素的时间序列进行趋势分析和突变点检验,结果显示:1淮河流域多年平均气温在时间上呈现明显突变上升趋势,其中大部分站点气温突变出现在20世纪90年代;流域南部的气温上升程度高于北部地区;从整个流域的Hurst指数分析来看,未来淮河流域的年平均气温仍将持续升高,但上升程度不显著。2淮河流域的年降水量在时间上呈现一定的减少趋势,并且发生多次降水突变现象;各站点的降水量变化不大,但均出现多次突变情况;从Hurst指数来看,流域未来的年平均降水量有上升趋势。3流域的年平均日照时数呈现下降趋势,但变化并不显著;各站点均出现明显的日照时数下降现象;从Hurst指数来看,流域未来的日照时数将继续下降。     

非高斯杂波背景中距离扩展目标的自适应积累检测器

针对SIRV建模的非高斯杂波背景中距离扩展目标检测问题,首先,假设杂波协方差矩阵结构已知,利用点目标检测器NMF对每个距离单元多个脉冲回波进行相干积累,再对目标所占距离单元能量进行非相干积累,提出了距离扩展目标的积累检测器NMFI,并推导了NMFI虚警概率与检测门限的关系表达式.其次,利用不含目标的辅助单元数据提出了修正的协方差矩阵迭代估计器MRE,再将估计矩阵代替NMFI中的真实协方差矩阵得到自适应检测器MRE-ANMFI,并证明了MRE-ANMFI对杂波纹理分量和协方差矩阵结构的CFAR特性.最后,利用仿真实验验证了本文方法的有效性.     

炭／炭复合材料微观孔隙结构演化的分形特征

提出了一种用分形理论研究炭／炭（C／C）复合材料制备过程中孔隙演化特征的新方法．基于压汞测试数据，根据海绵分形模型及热力学关系模型导出的多孔介质分形维数计算公式，计算了致密化各阶段C／C复合材料孔隙的分形维数，并研究了分形维数随孔隙演化过程的变化规律．结果表明C／C复合材料属于多孔分形介质，孔隙分形维数随孔隙率的减小而增大，但同时受到热解炭织构形态的影响，从各向同性到高织构热解炭，分形维数减小．分形维数综合反映了C／C复合材料内部孔隙的复杂程度和热解炭的形貌特征，是监控C／C复合材料致密化过程中孔隙演化的一个有效参数．     

充气膜结构零应力态求解

本文首次提出了一种从弹性平衡态到零应力态的逆解析数值分析方法：线性协调矩阵广义逆法．首先，用膜线单元模拟膜面，将膜结构转化成为网格结构；然后，基于杆系结构平衡矩阵理论和小变形假定，建立体系的协调方程．由弹性平衡态预张力和材料参数，计算膜线单元无应力长度和变形量．最后，由协调矩阵M—P广义逆求解协调方程得到节点位移，逆向叠加求出零应力态位形，释放应力．根据该算法，用MATLAB编制了计算程序．算例分析验证了该方法的正确性和高效性，得出一个弹性平衡态对应唯一零应力态的结论．本文对充气膜结构设计具有重要理论意义和实际指导价值．     

线性正则变换的卷积定理及其应用

线性正则变换作为Fourier变换更为广义的形式，已经在光学和信号处理等领域得到了应用，相关的许多性质也已经被导出，但是对应于Fourier变换卷积定理的类似理论却还没有得到．导出了线性正则变换的卷积定理，并在此基础上研究了线性正则域带限信号的均匀采样以及滤波问题，得到了信号的均匀采样和低通重构公式，并提出了一种基于FFT实现的线性正则域乘性滤波器的时域构造方法，与线性正则域实现方法相比，大大降低了计算量．     

基于分形论的霜晶生长模型及计算机模拟

以分形理论的DLA模型为基础建立了霜晶生长的二维模型，并进行计算机模拟．模拟过程中通过改变程序运行循环次数和随机粒子产生的几率从而得到不同条件下霜晶形成及生长过程的模拟图像．利用显微镜对霜晶体的形态进行观察并结合高像素数码相机拍摄到霜晶形成及生长过程中不同时刻的图像．模拟图像与实验图像的对比结果表明两者在形态上取得较好的一致，分形维数相近，从而证实采用程序运行的循环次数来代表霜晶生长时间，通过改变产生随机粒子的几率来模拟霜晶生长过程的密度变化的技术路线是可行的．研究结果表明，用这种分形理论模型模拟霜晶形成及生长过程能够取得较好的效果．论文也对该模型的不足做了客观的分析．     

L1Tc non-LTR retrotransposons from Trypanosoma cruzi contain a functional viral-like self-cleaving 2A sequence in frame with the active proteins they encode

A comparative analysis of 40 Trypanosoma cruzi L1Tc elements showed that the 2A self-cleaving sequence described in viruses is present in them. Of these elements, 72% maintain the canonical 2A motif (DxExNPGP). A high percentage has a conserved point mutation within the motif that has not been previously described. In vitro and in vivo expression of reporter polyproteins showed that the L1Tc2A sequence is functional. Mutations within certain L1Tc2A sequences affect the efficiency of the cleavage. The data indicate that the L1Tc2A sequence may be influencing the L1Tc enzymatic machinery determining the composition and level of the translated products. The residues located immediately upstream of the 2A consensus sequence increase the cleaving efficiency and appear to stabilize the relative amount of translated products. These authors contributed equally to this work. Received 26 January 2006; received after revision 11 April 2006; accepted 21 April 2006     

Volatility forecasting with bivariate multifractal models

This paper examines volatility linkages and forecasting for stock and foreign exchange markets from a novel perspective by utilizing a bivariate Markov-switching multifractal model that accounts for possible interactions between stock and foreign exchange markets. Examining daily data from major advanced and emerging nations, we show that generalized autoregressive conditional heteroskedasticity models generally offer superior volatility forecasts for short horizons, particularly for foreign exchange returns in advanced markets. Multifractal models, on the other hand, offer significant improvements for longer horizons, consistently across most markets. Finally, the bivariate multifractal model provides superior forecasts compared to the univariate alternative in most advanced markets and more consistently for currency returns, while its benefits are limited in the case of emerging markets.     

RNA recognition by double-stranded RNA binding domains: a matter of shape and sequence

The double-stranded RNA binding domain (dsRBD) is a small protein domain of 65–70 amino acids adopting an αβββα fold, whose central property is to bind to double-stranded RNA (dsRNA). This domain is present in proteins implicated in many aspects of cellular life, including antiviral response, RNA editing, RNA processing, RNA transport and, last but not least, RNA silencing. Even though proteins containing dsRBDs can bind to very specific dsRNA targets in vivo, the binding of dsRBDs to dsRNA is commonly believed to be shape-dependent rather than sequence-specific. Interestingly, recent structural information on dsRNA recognition by dsRBDs opens the possibility that this domain performs a direct readout of RNA sequence in the minor groove, allowing a global reconsideration of the principles describing dsRNA recognition by dsRBDs. We review in this article the current structural and molecular knowledge on dsRBDs, emphasizing the intricate relationship between the amino acid sequence, the structure of the domain and its RNA recognition capacity. We especially focus on the molecular determinants of dsRNA recognition and describe how sequence discrimination can be achieved by this type of domain.     

从文献计量分析看世界合成生物学研究现状

合成生物学是生物学的一个新兴分支学科.以美国科学引文索引数据库扩展版数据库(SCI-EXPANDED)收录入库,发表于1990～2010年的3 949篇与合成生物学相关的论文为研究对象,通过对论文的产出规模、地域分布、机构分布、研究热点、学科关联性、知识基础等方面的计量分析,在一定程度上揭示出近年来世界合成生物学的发展是一种成果产出不断丰富,理论研究与应用研究均得到积极推进,与众多学科发展联系紧密,各国科研投入力量在显著加强以及美国在全球一枝独秀的局面.     

Optimal sampling frequency for volatility forecast models for the Indian stock markets

This paper evaluates the performance of conditional variance models using high‐frequency data of the National Stock Index (S&P CNX NIFTY) and attempts to determine the optimal sampling frequency for the best daily volatility forecast. A linear combination of the realized volatilities calculated at two different frequencies is used as benchmark to evaluate the volatility forecasting ability of the conditional variance models (GARCH (1, 1)) at different sampling frequencies. From the analysis, it is found that sampling at 30 minutes gives the best forecast for daily volatility. The forecasting ability of these models is deteriorated, however, by the non‐normal property of mean adjusted returns, which is an assumption in conditional variance models. Nevertheless, the optimum frequency remained the same even in the case of different models (EGARCH and PARCH) and different error distribution (generalized error distribution, GED) where the error is reduced to a certain extent by incorporating the asymmetric effect on volatility. Our analysis also suggests that GARCH models with GED innovations or EGRACH and PARCH models would give better estimates of volatility with lower forecast error estimates. Copyright © 2008 John Wiley & Sons, Ltd.     

Foreign exchange market prediction with multiple classifiers

Foreign exchange market prediction is attractive and challenging. According to the efficient market and random walk hypotheses, market prices should follow a random walk pattern and thus should not be predictable with more than about 50% accuracy. In this article, we investigate the predictability of foreign exchange spot rates of the US dollar against the British pound to show that not all periods are equally random. We used the Hurst exponent to select a period with great predictability. Parameters for generating training patterns were determined heuristically by auto‐mutual information and false nearest‐neighbor methods. Some inductive machine‐learning classifiers—artificial neural network, decision tree, k‐nearest neighbor, and naïve Bayesian classifier—were then trained with these generated patterns. Through appropriate collaboration of these models, we achieved a prediction accuracy of up to 67%. Copyright © 2009 John Wiley & Sons, Ltd.     

Forecasting Daily Variations of Stock Index Returns with a Multifractal Model of Realized Volatility

Multifractal models have recently been introduced as a new type of data‐generating process for asset returns and other financial data. Here we propose an adaptation of this model for realized volatility. We estimate this new model via generalized method of moments and perform forecasting by means of best linear forecasts derived via the Levinson–Durbin algorithm. Its out‐of‐sample performance is compared against other popular time series specifications. Using an intra‐day dataset for five major international stock market indices, we find that the the multifractal model for realized volatility improves upon forecasts of its earlier counterparts based on daily returns and of many other volatility models. While the more traditional RV‐ARFIMA model comes out as the most successful model (in terms of the number of cases in which it has the best forecasts for all combinations of forecast horizons and evaluation criteria), the new model performs often significantly better during the turbulent times of the recent financial crisis. Copyright © 2014 John Wiley & Sons, Ltd.     

分枝杆菌噬菌体 D29的生物学特性研究及其抗耐药结核潜力的探讨

目的研究分枝杆菌噬菌体 D29的生物学特性,为 D29抗耐药结核治疗奠定基础.方法观察噬菌体电镜结构和噬菌斑形态;测定 D29最佳感染复数(MOI);一步生长实验;检测 pH值对 D29活力的影响;斑点法测定裂解谱;中和实验检测抗原性.结果 D29噬菌斑圆形透明,边界清楚;D29尾长129nm,最佳 MOI为10-4;D29感染宿主菌的潜伏期约为50min,裂解量为10;pH值对 D29存活率影响大,酸性环境不影响 D29裂解能力;D29能裂解分枝杆菌临床耐药株;D29K值为1069.50.结论 D29属于长尾噬菌体科(siphoviridae),裂解谱广,抗原性较高,具有抗耐药结核潜力     

PHAB toxins: a unique family of predatory sea anemone toxins evolving via intra-gene concerted evolution defines a new peptide fold

Sea anemone venoms have long been recognized as a rich source of peptides with interesting pharmacological and structural properties, but they still contain many uncharacterized bioactive compounds. Here we report the discovery, three-dimensional structure, activity, tissue localization, and putative function of a novel sea anemone peptide toxin that constitutes a new, sixth type of voltage-gated potassium channel (K_V) toxin from sea anemones. Comprised of just 17 residues, κ-actitoxin-Ate1a (Ate1a) is the shortest sea anemone toxin reported to date, and it adopts a novel three-dimensional structure that we have named the Proline-Hinged Asymmetric β-hairpin (PHAB) fold. Mass spectrometry imaging and bioassays suggest that Ate1a serves a primarily predatory function by immobilising prey, and we show this is achieved through inhibition of Shaker-type K_V channels. Ate1a is encoded as a multi-domain precursor protein that yields multiple identical mature peptides, which likely evolved by multiple domain duplication events in an actinioidean ancestor. Despite this ancient evolutionary history, the PHAB-encoding gene family exhibits remarkable sequence conservation in the mature peptide domains. We demonstrate that this conservation is likely due to intra-gene concerted evolution, which has to our knowledge not previously been reported for toxin genes. We propose that the concerted evolution of toxin domains provides a hitherto unrecognised way to circumvent the effects of the costly evolutionary arms race considered to drive toxin gene evolution by ensuring efficient secretion of ecologically important predatory toxins.