机载SAR用的GPS/SINS组合导航系统研究

提出了进行SINS姿态校正的四元补偿算法。采用闭环KF（卡尔曼滤波）技术实时校正惯性仪表误差，补偿四元数误差，修正位置，速度误差，GPS／SINS组合导航系统样机的试验结果表明：采用该提出的算法后，组合导航精度较高，在组合导航过程中若去掉GPS信息，短时间内纯SINS的导航精度很高，能够满足SAR对运动补偿精度的要求，待恢复GPS信息后，组合导航系统继续正常工作。     

INS／SAR组合导航系统中的误差修正方法

—本文介绍了ＩＮＳ／ＳＡＲ（合成孔径雷达）组合导航系统中的误差修正原理和方法，描述了如何获得观测量和构造ＩＮＳ／ＳＡＲ组合滤波器。给出的仿真结果证明，这种修正方法能大大提高导航精度，并且具有很强的初始捕获和对准能力。     

INS/GPS/SAR 组合导航系统研究

ＩＮＳ／ＧＰＳ／ＳＡＲ组合导航系统是一种高精度、高容错、多功能系统。本文介绍了它的组合原理和方法。仿真结果证明，该组合导航系统是一个高性能的导航系统。     

The design of fluoroquinolone-based cholinesterase inhibitors: Synthesis,biological evaluation and in silico docking studies

An enhanced acetylcholinesterase (AChE) activity is a hallmark in early stages of Alzheimer's ailment that results in decreased acetylcholine (ACh) levels, which in turn leads to cholinergic dysfunction and neurodegeneration. Consequently, inhibition of both AChE and butyrylcholinesterase (BChE) is important to prolong ACh activity in synapses for the enhanced cholinergic neurotransmission. In this study, a series of new fluoroquinolone derivatives (7a-m) have synthesized and evaluated for AChE and BChE inhibitory activities. The screening results suggested that 7 g bearing ortho fluorophenyl was the most active inhibitor against both AChE and BChE, exhibiting IC₅₀ values of 0.70 ± 0.10 µM and 2.20 ± 0.10 µM, respectively. The structure–activity relationship (SAR) revealed that compounds containing electronegative functions (F, Cl, OMe, N and O) at the ortho position of the phenyl group exhibited higher activities as compared to their meta- and/or para substituted counterparts. Molecular docking studies of synthesized compounds 7a, 7g, 7j and 7l docked into the active site of AChE and 7a-f docked into the active site of BChE revealed that these compounds exhibited conventional H-bonding along with π-π interaction with the active residues of AChE through their electronegative functions and phenyl ring, respectively. All the synthesized compounds are characterized by spectroscopic methods including FT-IR, ¹H- and ¹³C NMR as well as elemental analysis. This is the first example of fluoroquinolone-based cholinesterase inhibitors.     

Development and implementation of (Q)SAR modeling within the CHARMMing web‐user interface

Recent availability of large publicly accessible databases of chemical compounds and their biological activities (PubChem, ChEMBL) has inspired us to develop a web‐based tool for structure activity relationship and quantitative structure activity relationship modeling to add to the services provided by CHARMMing ( www.charmming.org ). This new module implements some of the most recent advances in modern machine learning algorithms—Random Forest, Support Vector Machine, Stochastic Gradient Descent, Gradient Tree Boosting, so forth. A user can import training data from Pubchem Bioassay data collections directly from our interface or upload his or her own SD files which contain structures and activity information to create new models (either categorical or numerical). A user can then track the model generation process and run models on new data to predict activity. © 2014 Wiley Periodicals, Inc.     

Evaluation of in silico tools to predict the skin sensitization potential of chemicals

Public domain and commercial in silico tools were compared for their performance in predicting the skin sensitization potential of chemicals. The packages were either statistical based (Vega, CASE Ultra) or rule based (OECD Toolbox, Toxtree, Derek Nexus). In practice, several of these in silico tools are used in gap filling and read-across, but here their use was limited to make predictions based on presence/absence of structural features associated to sensitization. The top 400 ranking substances of the ATSDR 2011 Priority List of Hazardous Substances were selected as a starting point. Experimental information was identified for 160 chemically diverse substances (82 positive and 78 negative). The prediction for skin sensitization potential was compared with the experimental data. Rule-based tools perform slightly better, with accuracies ranging from 0.6 (OECD Toolbox) to 0.78 (Derek Nexus), compared with statistical tools that had accuracies ranging from 0.48 (Vega) to 0.73 (CASE Ultra – LLNA weak model). Combining models increased the performance, with positive and negative predictive values up to 80% and 84%, respectively. However, the number of substances that were predicted positive or negative for skin sensitization in both models was low. Adding more substances to the dataset will increase the confidence in the conclusions reached. The insights obtained in this evaluation are incorporated in a web database www.asopus.weebly.com that provides a potential end user context for the scope and performance of different in silico tools with respect to a common dataset of curated skin sensitization data.     

Design,Synthesis, and Biological Evaluation of Tetra-Substituted Thiophenes as Inhibitors of p38α MAPK

p38α mitogen-activated protein kinase (MAPK) plays a role in several cellular processes and consequently has been a therapeutic target in inflammatory diseases, cancer, and cardiovascular disease. A number of known p38α MAPK inhibitors contain vicinal 4-fluorophenyl/4-pyridyl rings connected to either a 5- or 6-membered heterocycle. In this study, a small library of substituted thiophene-based compounds bearing the vicinal 4-fluorophenyl/4-pyridyl rings was designed using computational docking as a visualisation tool. Compounds were synthesised and evaluated in a fluorescence polarisation binding assay. The synthesised analogues had a higher binding affinity to the active phosphorylated form of p38α MAPK than the inactive nonphosphorylated form of the protein. 4-(2-(4-fluorophenyl)thiophen-3-yl)pyridine had a K_i value of 0.6 μm to active p38α MAPK highlighting that substitution of the core ring to a thiophene retains affinity to the enzyme and can be utilised in p38α MAPK inhibitors. This compound was further elaborated using a substituted phenyl ring in order to probe the second hydrophobic pocket. Many of these analogues exhibited low micromolar affinity to active p38α MAPK. The suppression of neonatal rat fibroblast collagen synthesis was also observed suggesting that further development of these compounds may lead to potential therapeutics having cardioprotective properties.     

An alignment‐free methodology for modelling field‐based 3D‐structure activity relationships using inductive logic programming

Traditional 3D‐quantitative structure–activity relationship (QSAR)/structure–activity relationship (SAR) methodologies are sensitive to the quality of an alignment step which is required to make molecular structures comparable. Even though many methods have been proposed to solve this problem, they often result in a loss of model interpretability. The requirement of alignment is a restriction imposed by traditional regression methods due to their failure to represent relations between data objects directly. Inductive logic programming (ILP) is a class of machine‐learning methods able to describe relational data directly. We propose a new methodology which is aimed at using the richness in molecular interaction fields (MIFs) without being restricted by any alignment procedure. A set of MIFs is computed and further compressed by finding their minima corresponding to the sites of strongest interaction between a molecule and the applied test probe. ILP uses these minima to build easily interpretable rules about activity expressed as pharmacophore rules in the powerful language of first‐order logic. We use a set of previously published inhibitors of factor Xa of the benzamidine family to discuss the problems, requirements and advantages of the new methodology. Copyright © 2007 John Wiley & Sons, Ltd.     

基于多时相TanDEM-X极化干涉SAR数据的水稻株高反演

水稻株高是水稻本身以及土壤、水文、气象等因素的综合反映,是水稻长势监测的重要指标。准确、高效、大范围的株高反演为水稻品种识别、物候监测、病虫害评估和产量预测等提供了可靠的依据。合成孔径雷达(SAR),具有全天时、全天候、穿透性的优势,成为水稻株高反演的重要手段之一。基于极化干涉测量(PolInSAR)的散射模型的反演算法具有严密的物理模型的支撑及较高的反演精度等特点,成为植被高度反演研究的热点。结合极化干涉SAR技术,构建了一种基于RVoG(Random Volume over Ground)模型的水稻株高反演算法,并利用2015年水稻生长季内9个时相的TanDEM-X极化干涉SAR数据,进行了水稻株高反演试验。首先基于每个时相下的极化干涉SAR数据分别得到8个复相干系数,利用这8个复相干系数在考虑卫星双站模式等情况下进行去相干处理,然后建立适用于水稻田特性的RVoG模型,接着构建基于该模型的水稻株高反演迭代算法,最后对9个时相下的TanDEM-X数据进行研究区的水稻株高反演及精度评定。结果表明,当水稻株高高于0.4m时,该方法的反演结果较好,决定系数(R^2)为0.86,均方根误差RMSE为6.79 cm;当水稻株高较低时(水稻株高小于0.4 m),反演误差在0.1~0.8 m之间,反演结果较差,被明显高估。通过分析认为,基于极化干涉理论,TanDEM-X数据在较好地反映出水稻植株的较大体散射量的前提下,利用所构建的基于RVOG模型的水稻株高反演算法,能够较好地反演株高在0.33~1.2 m的水稻株高。     

基于级联网络的膝关节图像分割与模型构建

采用膝关节模型进行电磁仿真是计算膝关节局部射频功率沉积（SAR）的主要方法,为了构建膝关节模型,本文提出了一种包含两个卷积神经网络——U-Net的级联网络结构,用于膝关节磁共振图像的分割．第一个网络在整幅图上分割肌肉、脂肪等占比较大的组织,并从分割结果中预测软骨与半月板的大致位置信息,第二个网络基于该信息在一个更小的子图上分割小组织以提高分割精度．两个网络均采用焦点损失函数,它们的分割结果合并在一起构成膝关节模型．我们将该方法与其它4种方法的分割结果进行了定量指标的对比研究,并分别构建膝关节模型,计算局部SAR值．结果表明本文提出的级联网络结构可以更精确的构建用于SAR仿真的膝关节模型．