涡流检波器特性测量与参数识别

新型涡流检波器已在地质、石油、煤炭人工地震勘探中采用。本文将最新的振动试验方法、数据处理技术及模态参数识别应用到检波器特性参数的确定中。论述它的有效优化方法,并首次将它应用到传感器的标定技术中,做到快速准确测定它的参数值,为检波器的生产、使用提供技术保证,亦为涡流检波器参数综合测试仪研制提供理论基础。     

一种不受相位噪声影响的模态参数识别法

本文提出了一种根据幅值频响数据来识别模态参数的频域识别法.该方法首先通过识别幅值频响函数模型来得到传递函数的零点和极点.鉴于不同结构系统可以有完全相同的幅值频响函数,文中提出了由相位频响数据来判定传递函数零点的号性,以唯一确定传递函数,从而消除了相位噪声对模态参数识别结果的影响.作为例子,文中给出了计算机模拟实验例子和滚动轴承支承动态参数识别的应用实例.     

Numerical discretization-based kernel type estimation methods for ordinary differential equation models

We consider the problem of parameter estimation in both linear and nonlinear ordinary differential equation(ODE) models. Nonlinear ODE models are widely used in applications. But their analytic solutions are usually not available. Thus regular methods usually depend on repetitive use of numerical solutions which bring huge computational cost. We proposed a new two-stage approach which includes a smoothing method(kernel smoothing or local polynomial fitting) in the first stage, and a numerical discretization method(Eulers discretization method, the trapezoidal discretization method,or the Runge–Kutta discretization method) in the second stage. Through numerical simulations, we find the proposed method gains a proper balance between estimation accuracy and computational cost.Asymptotic properties are also presented, which show the consistency and asymptotic normality of estimators under some mild conditions. The proposed method is compared to existing methods in term of accuracy and computational cost. The simulation results show that the estimators with local linear smoothing in the first stage and trapezoidal discretization in the second stage have the lowest average relative errors. We apply the proposed method to HIV dynamics data to illustrate the practicability of the estimator.     

水声通信中基于信道辨识的盲turbo均衡方法

水声信道多途效应明显,造成接收信号存在严重的码间干扰(ISI,Intersymbol interference)。基于最小均方误差(MMSE,Minimum mean square error)准则的turbo均衡器级联了均衡和信道译码,能够有效去除ISI,并获得优良的性能。由于水声信道的时变性,传统MMSE-turbo均衡需要周期性的训练序列,以实现连续可靠的通信。训练序列虽然提高了通信的可靠性,但降低了信息的有效传输速率。因此,为提高通信效率,本文提出了一种盲turbo均衡方法,该方法通过引入新的盲信道辨识器来同时获得信道估计响应和已去除部分ISI的初步均衡输出信号,并为turbo均衡提供初始的响应参数和比特软信息。与水声通信中应用较多的盲判决反馈均衡器(DFE,Decision feedback equalizer)相比,海上实验结果证明本文提出的盲turbo均衡方法抗信道多途衰落的能力较强,并且与传统MMSE-turbo均衡相比无需训练序列,因此提高了信息的有效传输速率。     

Chemical Proteomics and Phenotypic Profiling Identifies the Aryl Hydrocarbon Receptor as a Molecular Target of the Utrophin Modulator Ezutromid

Duchenne muscular dystrophy (DMD) is a fatal muscle‐wasting disease arising from mutations in the dystrophin gene. Upregulation of utrophin to compensate for the missing dystrophin offers a potential therapy independent of patient genotype. The first‐in‐class utrophin modulator ezutromid/SMT C1100 was developed from a phenotypic screen through to a Phase 2 clinical trial. Promising efficacy and evidence of target engagement was observed in DMD patients after 24 weeks of treatment, however trial endpoints were not met after 48 weeks. The objective of this study was to understand the mechanism of action of ezutromid which could explain the lack of sustained efficacy and help development of new generations of utrophin modulators. Using chemical proteomics and phenotypic profiling we show that the aryl hydrocarbon receptor (AhR) is a target of ezutromid. Several lines of evidence demonstrate that ezutromid binds AhR with an apparent K_D of 50 nm  and behaves as an AhR antagonist. Furthermore, other reported AhR antagonists also upregulate utrophin, showing that this pathway, which is currently being explored in other clinical applications including oncology and rheumatoid arthritis, could also be exploited in future DMD therapies.     

Development of supercritical fluid chromatography coupled with mass spectrometry method for characterization of a nonionic surfactant and comparison with liquid chromatography coupled with mass spectrometry method

The supercritical fluid chromatography coupled with mass spectrometry (SFC‐MS) method and liquid chromatography coupled with mass spectrometry (LC‐MS) method were developed for the separation and characterization of poly (ethylene oxide) methyl glucose sesquistearate (PEO‐Glu‐sesquistearate). The products of PEO‐Glu‐sesquistearate are composed of complex oligomers. The relationship between molecular structure of these oligomers and chromatographic retention behavior in both SFC and LC were discussed and compared. As compared with LC, hydrophobic moieties of compounds favor the fast elution in SFC. The different series can be better separated by LC, while the homologues compounds in same series can be better separated by SFC, and SFC‐MS provided more comprehensive structural information. Different series such as PEO‐distearate, PEO‐stearate, PEO, PEO‐Glu‐tetrastearate, PEO‐Glu‐tristearate, PEO‐Glu‐distearate, PEO‐Glu‐stearate, and PEO‐Glu were identified by MS/MS.     

In vitro antiproliferative activity of glabridin derivatives and their in silico target identification

Abstract

Novel Mannich base derivatives of glabridin were synthesized and their antiproliferative activity were performed along with our previously reported glabridin-chalcone hybrids molecules (GCHMs) against various human cell lines MDA-MB-231 (breast adenocarcinoma), HEK-293 (embryonic kidney cell line), K562 (leukemia), MCF-7 (breast adenocarcinoma), HeLa (cervix adenocarcinoma), HepG2 (hepatocellular carcinoma) and WRL-68 (hepatic carcinoma). The result showed that the glabridin significantly reduced cell proliferation with IC₅₀ ranges from 3.67 to 58.30?µM against all the tested cell lines. The remarkable reduction in antiproliferative activity 2’,4’-dimethoxyglabridin and GCHMs compounds with phenolic OH groups protected by methoxy (OCH₃) groups suggested that the free OH groups are essential factor for the antiproliferative activity of glabridin and its derivatives. The Mannich base derivatives of glabridin showed moderate activity IC₅₀ (2.20–>95.78?µM). Furthermore, in silico target identification analysis revealed that AKT1, DECR1 and NOS1 are the potential targets for glabridin and their derivatives.     

几类典型随机非线性系统的辨识

考察实际中常见的三类典型随机非线性系统(即Wiener、Hammerstein和NARX系统)的辨识,首先概述了现有的递推和非递推辨识算法,然后介绍这三类系统的一个统一辨识框架:利用系统所确定的过程的马氏性及混合型,将辨识转化为求函数零点的问题,基于扩张截尾的随机逼近算法,得到了递推、强一致的辨识结果,并给出了数值模拟验证辨识算法收敛到真值.     

基于语言评价信息的知识资本要素识别方法

知识资本是组织创造价值和获取竞争优势的关键资源, 其要素通常具有复杂的关联性, 如何识别知识资本的核心要素、原因要素和结果要素,对于组织进行知识资本管理具有重要意义.本文在构建了知识资本要素识别体系的基础上,借鉴决策试验和评价实验室报告的思想提出了一种基于语言评价信息的知识资本要素识别方法,通过处理和集结专家针对知识资本要素关联给出的语言评价信息,对知识资本要素进行排序与归类.最后通过一个实例分析说明了该方法的应用, 并说明了如何根据识别结果制定相应的策略以便进行知识资本的投资和控制.     

企业协同知识创新的风险识别与评价

协同知识创新是企业降低创新成本,提高创新能力的重要手段.由于企业知识创新具有高度的不确定性和不可预测性,因此,有效地利用企业协同优势,有针对性地降低协同知识创新的风险,是协同知识创新活动得以顺利开展的重要条件.影响协同知识创新的内外因素有很多,利用粗糙集理论对这些因素进行简约,消除冗余因素,得到在协同知识创新中的核心因素;确定约简集因素权重,判断协同知识创新的风险程度,为协同知识创新的决策提供依据.