X射线相衬成像应用于惯性约束核聚变多层球壳靶丸检测

随着惯性约束核聚变(ICF)研究的逐步深入,尤其是氘氚(DT)燃料层球壳梯度掺杂的广泛应用,对轻物质界面的诊断需求日益增长.在北京同步辐射形貌成像站的微米CT机上利用类同轴相衬成像方法获取了三层球壳靶丸的相衬图像,最佳空间分辨率达到了2μupm,衬度达到12%;通过分析边缘增强函数和衬度传递函数之间的关系,总结出一套完整的类同轴相衬成像方法,同时将相衬成像结果与吸收成像结果对比.实验结果表明,X射线相衬成像在轻物质界面的分辨中具有明显的优势,能够广泛应用于ICF研究、医学断层扫描CT装置和生物结构等前沿科学领域.     

超声相控阵在多层媒质中的声场模式优化

针对超声在多层媒质中的传播特性,引入相位补偿因子并结合遗传算法, 提出了一种可对多层媒质进行声聚焦控制的方法.利用该方法对16×16二维超声相控阵在多层生物媒质中的多焦点声场模式进行了仿真,计算了生物媒质不同厚度层和不同吸收系数时的声场. 结果表明:该方法能优化多焦点声场模式,抑制旁瓣,提高声场增益,将声强最大限度地聚焦在目标区域内; 改变生物组织不同层的厚度和不同层的吸收系数,焦点位置不发生变化,但焦域内的声强会有所变化.     

Quantitative structure-toxicity relationship: An “in silico study” using electrophilicity and hydrophobicity as descriptors

To investigate the importance and suitability of quantitative structure-toxicity relationship approach in the field of aquatic toxicology, we have performed an extensive study introducing multiple linear regression (MLR) and multilayer perceptron neural network (MLP-NN) techniques. In this study, toxicity (pIGC₅₀) prediction of 169 aliphatic compounds toward Tetrahymena pyriformis (a freshwater protozoa) has been made by using all possible combinations of electrophilicity index (ω), square of electrophilicity index (ω²), cube of electrophilicity index (ω³), hydrophobicity (logP), and its square term {(logP)²} as predictors in the developed models. The MLR and MLP employed to construct the linear prediction models for the complete sets lead to a good correlation coefficient (R²) ranging from 0.703 to 0.779 in case of electronic factors (ω, ω², ω³) and 0.790 to 0.983 in case of lipophilic factors {logP, (logP)²}, respectively, except for amino alcohols. Furthermore, to cross-check the variable selection, a three-set cross-validation approach has been carried out. To demonstrate our overall result, the sum of ranking differences with ties has been evaluated considering the whole data set.     

Potential of glucose measurement in soil and food sample using low molecular weight O-(2-hydroxyl)propyl-3-trimethylammonium chitosan chloride nanoparticle-glucose oxidase immobilised on a natural fibre membrane

Low, medium and high molecular weights O-(2-hydroxyl)propyl-3-trimethylammonium chitosan chloride nanoparticles (L-, M- and H-O-HTCC NP) have been synthesised and used to immobilise glucose oxidase on eggshell membranes for glucose biosensing. Among these O-HTCC NP-based biosensors, L-O-HTCC NP provides the highest sensitivity to glucose with a linear response of 0.012–0.60 mM and a detection limit of 12 μM (S/N = 3). The effect of L-O-HTCC NP and enzyme loading ratio, pH, temperature and phosphate buffer concentration on the sensitivity of the biosensor was studied in detail. The biosensor exhibits fast response time (40 s), good repeatability (3.0%, n = 10) and storage stability (95% of initial sensitivity after 1-year storage). Common interferents including acetic acid, DL-α-alanine, L-ascorbic acid, butyric acid, citric acid, DL-cysteine, ethanol, folic acid, glycine, lactic acid, lactose, propionic acid, sodium benzoate and sucrose do not cause significant interference on the L-O-HTCC NP biosensor. The recoveries 88.3%–102% and 102%–116% and relative standard deviations (RSDs) 3.90%–5.56% and 1.25%–3.00% are respectively, for the soil and food sample analyses. The proposed biosensor method has been applied to determine glucose in soil and food samples with good accuracy and recovery, inferring that it has potential for detection and quantification of diversified samples of different matrices. Finally, it has successfully monitored the changes of glucose contents in soil samples at various incubation times, demonstrating its potential use in environmental and geochemical analysis.     

一种递归神经网络空间分集均衡器

水声信道中的衰变多途特性常引起难以克服的码间干扰(ISI)。为了降低误码率、改善系统性能,本文提出了一种递归神经网络空间分集均衡器。它在传统的空间分集结构中融入了多层感知器,该结构能够充分利用训练信号的信息,在可调权数较少的情况下,能够得到较好的均衡效果;针对该结构,采取了初始设定权值的办法,从而使该均衡器的收敛速度得到大大提高。仿真与湖试试验结果表明,该均衡器结构合理,对空间分集均衡性能有一定的改善。     

Evaluation of laser induced breakdown spectroscopy for multielemental determination in soils under sewage sludge application

Laser induced breakdown spectroscopy (LIBS) is an atomic emission spectroscopy technique for simple, direct and clean analysis, with great application potential in environmental sustainability studies. In a single LIBS spectrum it is possible to obtain qualitative information on the sample composition. However, quantitative analysis requires a reliable model for analytical calibration. Multilayer perceptron (MLP), an artificial neural network, is a multivariate technique that is capable of learning to recognize features from examples. Therefore MLP can be used as a calibration model for analytical determinations. Accordingly, the present study proposes to evaluate the traditional linear fit and MLP models for LIBS calibration, in order to attain a quantitative multielemental method for contaminant determination in soil under sewage sludge application. Two sets of samples, both composed of two kinds of soils were used for calibration and validation, respectively. The analyte concentrations in these samples, used as reference, were determined by a reference analytical method using inductively coupled plasma optical emission spectrometry (ICP OES). The LIBS-MLP was compared to a LIBS-linear fit method. The values determined by LIBS-MLP showed lower prediction errors, correlation above 98% with values determined by ICP OES, higher accuracy and precision, lower limits of detection and great application potential in the analysis of different kinds of soils.     

Solvation effect on the vertical ionization energy of adenine-thymine base pair: From microhydration to bulk

In the present work, we investigate the effect of aqueous environment on the vertical ionization potential (VIP) of adenine-thymine (AT) base pair using a multilayer equation of the motion-coupled cluster method. The microsolvation can cause both blue-shift and red-shit of the IP values. However, the bulk water environment always results in the red-shift of the vertical ionization potential. Our study shows that the correct treatment of the short-range interaction plays an essential role in determining the magnitude of the red-shift. We have developed a biased sampling scheme based on Koopmans' energy, which can significantly speed up the convergence with respect to the number of solvent-solute configurations.     

基于LBP和多层次结构的异质手背静脉身份识别

针对多源异质的手背静脉异质图像的识别研究,提出了基于LBP和多层次结构的识别算法;首先对图像做适当的预处理,然后将LBP特征提取算法编码的手背静脉纹理特征图像作为多层次结构的输入,通过多层次结构的逐层由具体到抽象的特征提取,得到的特征具有更大的鲁棒性;最后该算法在多源异质的手背静脉图像库得到的识别率比传统的算法识别率高,达到96.57%;进一步表明该算法能够较好地解决由于多源异质问题对手背静脉识别所造成的识别率低的影响。     

基于SCFNN之PAM非线性信道均衡器成效研究

自组织型模糊类神经网络(SCFNN)可依据一定的法则自我构建神经网络的组织结构,从而适用于当前控制对象;多层神经元是传统的类神经网络,广泛应用于各个领域;倒传递学习法与最陡坡降法相结合,可使以上两种类神经网络进行有效的融合;目前,信道均衡器上的系统架构种类非常多,各种类神经网络应用于信道均衡器也颇为普遍;在研究SCFNN的基础上,将其应用于通道均衡器确实可行,效果良好;比较了SCFNN与MLP在通道均衡器的成效;仿真表明,在相同通道环境下,SCFNN的训练收敛速度、位错误率与系统敏感度优于MLP,完成结构学习后SCFNN的结构也颇为精简。