Bounded invariant verification for time-delayed nonlinear networked dynamical systems

We present a technique for bounded invariant verification of nonlinear networked dynamical systems with delayed interconnections. The underlying problem in precise bounded-time verification lies with computing bounds on the sensitivity of trajectories (or solutions) to changes in initial states and inputs of the system. For large networks, computing this sensitivity with precision guarantees is challenging. We introduce the notion of input-to-state (IS) discrepancy of each module or subsystem in a larger nonlinear networked dynamical system. The IS discrepancy bounds the distance between two solutions or trajectories of a module in terms of their initial states and their inputs. Given the IS discrepancy functions of the modules, we show that it is possible to effectively construct a reduced (low dimensional) time-delayed dynamical system, such that the trajectory of this reduced model precisely bounds the distance between the trajectories of the complete network with changed initial states. Using the above results we develop a sound and relatively complete algorithm for bounded invariant verification of networked dynamical systems consisting of nonlinear modules interacting through possibly delayed signals. Finally, we introduce a local version of IS discrepancy and show that it is possible to compute them using only the Lipschitz constant and the Jacobian of the dynamic function of the modules.     

Concurrent combined verification: reducing false positives in automated NMR structure verification through the evaluation of multiple challenge control structures

Automated structure verification using ¹H NMR data or a combination of ¹H and heteronuclear single‐quantum correlation (HSQC) data is gaining more interest as a routine application for qualitative evaluation of large compound libraries produced by synthetic chemistry. The goal of this automated software method is to identify a manageable subset of compounds and data that require human review. In practice, the automated method will flag structure and data combinations that exhibit some inconsistency (i.e. strange chemical shifts, conflicts in multiplicity, or overestimated and underestimated integration values) and validate those that appear consistent. One drawback of this approach is that no automated system can guarantee that all passing structures are indeed correct structures. The major reason for this is that approaches using only ¹H or even ¹H and HSQC spectra often do not provide sufficient information to properly distinguish between similar structures. Therefore, current implementations of automated structure verification systems allow, in principle, false positive results. Presented in this work is a method that greatly reduces the probability of an automated validation system passing incorrect structures (i.e. false positives). This novel method was applied to automatically validate 127 non‐proprietary compounds from several commercial sources. Presented also is the impact of this approach on false positive and false negative results. Copyright © 2012 John Wiley & Sons, Ltd.     

Assessing the Calibration of High-Dimensional Ensemble Forecasts Using Rank Histograms

Any decision-making process that relies on a probabilistic forecast of future events necessarily requires a calibrated forecast. This article proposes new methods for empirically assessing forecast calibration in a multivariate setting where the probabilistic forecast is given by an ensemble of equally probable forecast scenarios. Multivariate properties are mapped to a single dimension through a prerank function and the calibration is subsequently assessed visually through a histogram of the ranks of the observation’s preranks. Average ranking assigns a prerank based on the average univariate rank while band depth ranking employs the concept of functional band depth where the centrality of the observation within the forecast ensemble is assessed. Several simulation examples and a case study of temperature forecast trajectories at Berlin Tegel Airport in Germany demonstrate that both multivariate ranking methods can successfully detect various sources of miscalibration and scale efficiently to high-dimensional settings. Supplemental material in form of computer code is available online.     

基于软件身份标签的安全性研究

当前,由于软件发行商通常不为应用程序和可执行文件（程序文件,共享库,脚本等）提供用以验证其可靠性的关键信息,所以计算机管理员想要自动辨别这些文件是否被第三方修改过变得十分困难.通过与民航飞行的安全性要求进行类比,分析了软件身份标签如何从身份鉴别、应用关联、防止篡改和未知威胁这四方面改善软件的安全性.     

A General Bayesian Model for Speaker Verification

This paper presents a general Bayesian model for speaker verification tasks.It is a generative probability model.Due to its simple analytical property,a computationally efficient expectation-maximization algorithm can be derived to obtain the model parameters.A closedform solution,which allows the scalable size of enrollment set,is given in a full Bayesian way for making speaker verification decisions.Factor analysis technique is employed to model the speaker-specific components,then the redundant information in this model will be dropped.Experimental results are evaluated by both equal error rate and minimum detection cost function.The proposed approach shows promising results on the National institute of standards and technology (NIST) Speaker recognition evaluation (SRE) 2010 extended and 2012 core tasks.Significant improvement is obtained when comparing with Gaussian probabilistic linear discriminant analysis,especially under phone-call conditions and mismatched train-test channel conditions.Contrast experimental results with other popular generative probability models are also presented in this paper.     

Preparation of core–shell structure Fe3O4@SiO2 superparamagnetic microspheres immoblized with iminodiacetic acid as immobilized metal ion affinity adsorbents for His‐tag protein purification

The core–shell structure Fe₃O₄/SiO₂ magnetic microspheres were prepared by a sol–gel method, and immobiled with iminodiacetic acid (IDA) as metal ion affinity ligands for protein adsorption. The size, morphology, magnetic properties and surface modification of magnetic silica nanospheres were characterized by various modern analytical instruments. It was shown that the magnetic silica nanospheres exhibited superparamagnetism with saturation magnetization values of up to 58.1 emu/g. Three divalent metal ions, Cu²⁺, Ni²⁺ and Zn²⁺, were chelated on the Fe₃O₄@SiO₂–IDA magnetic microspheres to adsorb lysozyme. The results indicated that Ni²⁺‐chelating magnetic microspheres had the maximum adsorption capacity for lysozyme of 51.0 mg/g, adsorption equilibrium could be achieved within 60 min and the adsorbed protein could be easily eluted. Furthermore, the synthesized Fe₃O₄@SiO₂–IDA–Ni²⁺ magnetic microspheres were successfully applied for selective enrichment lysozyme from egg white and His‐tag recombinant Homer 1a from the inclusion extraction expressed in Escherichia coli. The result indicated that the magnetic microspheres showed unique characteristics of high selective separation behavior of protein mixture, low nonspecific adsorption, and easy handling. This demonstrates that the magnetic silica microspheres can be used efficiently in protein separation or purification and show great potential in the pretreatment of the biological sample. Copyright © 2015 John Wiley & Sons, Ltd.     

Concise Synthesis of Photocleavable Molecular Tag for Laser Desorption Ionization Mass Spectrometry via Fries Reaction

Abstract

A new synthetic route for the photocleavable molecular tag for laser desorption ionization mass spectrometry (LDI-MS) was achieved using the Fries reaction of 2,6-dimethylphenyl ester as its key reaction. Zirconium chloride was used as uniquely efficient adjuvant to promote the reaction. The molecular tag was obtained in five steps without chromatographic purification.

Supplemental materials are available for this article. Go to the publisher's online edition of Synthetic Communications® to view the free supplemental file.     

面向领域标签辅助的服务聚类方法

Web服务数量的激增对服务发现提出了更高的要求,服务聚类是促进服务发现的一种重要技术.但是,现有服务聚类方法只对单一类型的服务文档进行聚类,缺乏考虑服务的领域特性和服务标签的应用.针对这些问题,本文首先使用本体辅助的支持向量机和面向领域的服务特征降维技术建立服务的特征内容向量,然后使用一种标签辅助的主题服务聚类方法T-LDA建立融合标签信息之后的隐含主题表示,并利用归一化方法消除通用主题的影响,综合上述方法建立一个面向领域标签辅助的Web服务聚类方法DTWSC.实验结果表明,该框架能够提高针对不同类型的服务文档的聚类效果.与LDA、K-Means等方法相比,该方法在聚类纯度、熵和F-Measure指标上均具有更好的效果.     

无源超高频抗金属标签天线设计方法综述

射频识别( RFID)技术的不断发展,对标签天线提出了更高的要求。普通标签天线直接应用于金属表面时,由于受到金属边界的影响,其性能会出现一定程度的下降。详细介绍了4种无源超高频抗金属标签天线的设计方法,包括调整天线与金属面的间距、采用吸波材料、引入高阻抗表面基板、采用平面倒F天线( PIFA)或微带天线结构,并分析了每种方法的优缺点及其对标签天线的阻抗匹配、带宽、尺寸、识别距离以及成本等方面的影响。微带贴片天线不仅具有低剖面、高方向性等优点,而且含有金属接地板,常用作抗金属标签天线的设计原型。在抗金属标签天线的设计与实际应用中,研究者可针对具体要求灵活运用这些设计方法。