悬浮聚合法制备磁性分子印迹聚合物微球

以苯胺和二甲基苯胺为模板分子、甲基丙烯酸(MAA)为功能单体、三羟甲基丙烷三丙烯酸酯(TRIM)为交联单体、Fe3O4为磁性组分,采用悬浮聚合法制备了磁性分子印迹聚合物微球(MMIPMs)。结果表明,改性Fe3O4微粒在MMIPMs中分散较好,MMIPMs在水性介质中对模板分子的选择吸附性较差,但在有机介质中有较好的选择吸附性。     

基于Mel频谱值和深度学习网络的鸟声识别算法*

为了增强网络对鸟鸣声信号的特征学习能力并提高识别精度,提出一种基于深度残差收缩网络和扩张卷积的鸟声识别方法。首先,提取鸟鸣声信号的对数梅尔特征及其一阶和二阶差分系数组成logMel特征集作为网络模型的输入;其次,通过深度残差收缩网络自动学习噪声阈值,减少噪声干扰;然后,引入扩张卷积增大卷积核感受野并利用注意力机制使网络更关注关键帧特征;最后,通过双向长短时记忆网络从学到的局部特征中学习长期依赖关系。以百鸟数据birdsdata鸟声库中的19种中国常见鸟类作为实验对象,识别正确率可以达到96.58%,并对比模型在不同信噪比数据下的识别结果,结果表明该模型在噪声环境下的识别效果优于现有模型。     

Pyrrolic Tripodal Receptors for the Molecular Recognition of Carbohydrates: Ditopic Receptors for Dimannosides

Synthetic ditopic receptors, designed for the molecular recognition of dimannosides, have been prepared by bridging two monotopic units effectively recognizing mannosides with linkers of the appropriate size and flexibility, endowed with hydrogen‐bonding groups. Affinities toward the α and β glycosides of the biologically relevant Manα(1–2)Man disaccharide were measured by NMR spectroscopy and isothermal titration calorimetry (ITC) in polar organic media (30–40 % DMF in chloroform). Significant selectivities and affinities in the micromolar range were observed in most cases, with two newly designed receptors being the most effective receptors of the set, together with a distinct preference of the dimannosides for the (S) enantiomer of the receptor in all cases. A 3D view of the recognition mode was elucidated by a combined NMR spectroscopic/molecular modeling approach, showing the dimannoside included in the cleft of the receptor. Compared to the monotopic precursors, the ditopic receptors showed markedly improved recognition properties, proving the efficacy of the modular receptor design for the recognition of disaccharides.     

贴片电阻表面缺陷自动识别方法

贴片电阻生产过程中的缺陷主要依靠人工在显微镜下检测,速度慢、长期成本高、误检率高.针对贴片电阻单元具有排列整齐、结构简单、图像灰度级少的特点,在贴片电阻图像二值化、边缘提取、直线检测基础上,以相邻电阻单元的相关系数作为电阻缺陷判别依据,提出基于子图投影匹配的快速缺陷检测方法.采用主分量分析法压缩图像数据量,提取缺陷特征,以基于支持向量机对贴片电阻缺陷进行分类并建立实验系统.缺陷检测及识别实验表明,缺陷检测正确率为92.5oo,算法的快速性和识别准确度满足系统快速高精的要求.     

一种基于喹唑啉酮衍生物的荧光探针对次氯酸根离子的识别

次氯酸根(ClO~-)在人体免疫系统中发挥着重要的作用,其识别与检测备受关注。本文设计合成了一种含有喹唑啉酮骨架的腙型荧光探针(HEMQ),并通过~1H NMR、~(13)C NMR、高分辨质谱(HRMS)表征了其结构。探针HEMQ在V(乙醇)∶V(水)=1∶1(c(PBS)=0.02 mol/L,pH=8.7)溶液中对ClO~-具有良好的选择性且响应快速,荧光发生显著猝灭。探针HEMQ对ClO~-具有较高的灵敏度,检测限为1.0×10-4mol/L。此外,ClO~-可引起探针溶液由黄色到无色的颜色变化,因此HEMQ可作为比色、荧光双通道响应的ClO~-探针。     

Fault Recognition of Rolling Bearings Based on Parameter Optimized Multi-Scale Permutation Entropy and Gath-Geva

To extract fault features of rolling bearing vibration signals precisely, a fault diagnosis method based on parameter optimized multi-scale permutation entropy (MPE) and Gath-Geva (GG) clustering is proposed. The method can select the important parameters of MPE method adaptively, overcome the disadvantages of fixed MPE parameters and greatly improve the accuracy of fault identification. Firstly, aiming at the problem of parameter determination and considering the interaction among parameters comprehensively of MPE, taking skewness of MPE as fitness function, the time series length and embedding dimension were optimized respectively by particle swarm optimization (PSO) algorithm. Then the fault features of rolling bearing were extracted by parameter optimized MPE and the standard clustering centers is obtained with GG clustering. Finally, the samples are clustered with the Euclid nearness degree to obtain recognition rate. The validity of the parameter optimization is proved by calculating the partition coefficient and average fuzzy entropy. Compared with unoptimized MPE, the propose method has a higher fault recognition rate.     

基于贝叶斯序贯方法的微波效应实验设计

提出了一种基于贝叶斯验后概率的序贯检验方法,建立了检验的判别准则,给出了判别准则临界值的计算方法。在给定截尾实验次数的条件下,提出了一种截尾方案,建立了截尾判断方法。将其用于解决验证效应物在微波作用下失效概率达到给定水平的微波效应实验设计问题,给出了相应的实验方案和所需样本量的估计。最后,通过实例对上述方法的应用过程进行了说明,并和现有方法进行了分析比较。     

Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems

An approach to dealing with missing data, both during the design and normal operation of a neuro-fuzzy classifier is presented in this paper. Missing values are processed within a general fuzzy min–max neural network architecture utilising hyperbox fuzzy sets as input data cluster prototypes. An emphasis is put on ways of quantifying the uncertainty which missing data might have caused. This takes a form of classification procedure whose primary objective is the reduction of a number of viable alternatives rather than attempting to produce one winning class without supporting evidence. If required, the ways of selecting the most probable class among the viable alternatives found during the primary classification step, which are based on utilising the data frequency information, are also proposed. The reliability of the classification and the completeness of information is communicated by producing upper and lower classification membership values similar in essence to plausibility and belief measures to be found in the theory of evidence or possibility and necessity values to be found in the fuzzy sets theory. Similarities and differences between the proposed method and various fuzzy, neuro-fuzzy and probabilistic algorithms are also discussed. A number of simulation results for well-known data sets are provided in order to illustrate the properties and performance of the proposed approach.     

Critical comparison of radiometric and mass spectrometric methods for the determination of radionuclides in environmental, biological and nuclear waste samples

The radiometric methods, alpha (α)-, beta (β)-, gamma (γ)-spectrometry, and mass spectrometric methods, inductively coupled plasma mass spectrometry, accelerator mass spectrometry, thermal ionization mass spectrometry, resonance ionization mass spectrometry, secondary ion mass spectrometry, and glow discharge mass spectrometry are reviewed for the determination of radionuclides. These methods are critically compared for the determination of long-lived radionuclides important for radiation protection, decommissioning of nuclear facilities, repository of nuclear waste, tracer application in the environmental and biological researches, these radionuclides include ³H, ¹⁴C, ³⁶Cl, ⁴¹Ca, ^59,63Ni, ^89,90Sr, ⁹⁹Tc, ¹²⁹I, ^135,137Cs, ²¹⁰Pb, ^226,228Ra, ²³⁷Np, ²⁴¹Am, and isotopes of thorium, uranium and plutonium. The application of on-line methods (flow injection/sequential injection) for separation of radionuclides and automated determination of radionuclides is also discussed.