4-methoxy-2,6-bis(3,5-dimethylpyrazoyl)-1,3,5-triazine modified carbon paste electrode for trace Cu(Ⅱ) determination by differential pulse volt-ammetry

A differential pulse voltammetric method was developed for the sensitive and selective determination of Cu(Ⅱ) at 4-methoxy-2,6-bis(3,5-dimethylpyrazoyl)-l,3,5-triazine modified carbon paste electrode in 0.05 mol/L KHC8H4O4 solution (pH = 4.02). The oxidation peak of Cu(Ⅱ) was observed at 0.065 V(vs Ag/AgCl) by scanning the potential in positive direc-tion. The analysis procedure consisted of an open circuit accumulation step in stirred sample solution. It was followed by medium exchange to a clean solution and subsequently an anodic potential scan was affected to obtain the voltammetric peak. The current was proportional to the concentration of the Cu(Ⅱ) ion in a range of 1× 10-7-1×10-4 mol/L for 6 min accumulation; the most of metal ions did not interfere with the determination. The developed method was applied to Cu(Ⅱ) determination in coal-ash sample, the results agreed with that of atomic adsorption spectroscopy(AAS).     

TESTING CHANGE-POINTS IN THE EXPLOSIVE GAUSSIAN AUTOREGRESSIVE PROCESSES

Abstract. A functional limit theorem with a particular function class and topology is derived for non-ergodic type time series. This limit theorem allows us to study the asymptotic law of the associated likelihood ratio test (LRT) statistic for testing the presence of a change in the covariance parameter in the explosive Gaussian autoregressive model. We show that the level of the LRT cannot be approximated without introducing appropriate normalization. The limit law of a particular weighted likelihood ratio test is examined through a simulation study and is compared with the well-known Kolmogorov distribution obtained in the stationary case; we conclude that for practical applications when the root is really close to unity one can use the same thresholds as in the stationary case. This procedure is applied to the study of three real time series known to be non-stationary.     

差分脉冲极谱法测定苯胺中微量硝基苯

建立了测定苯胺中微量硝基苯的差式微分脉冲极谱法。试验发现硝基苯在-0.57V(vs.Ag/AgCl)处有一个良好的差分脉冲极谱峰。硝基苯质量浓度在1～600μg/mL的范围内,质量浓度与差分脉冲极谱峰的峰高呈线性关系。此法简便、快速、灵敏,结果准确。     

基于新型混合模型的欠定盲分离方法

针对欠定盲分离问题,提出了一种新的源恢复方法. 在时频域局部区域采用复高斯分布对源信号进行建模,将语音信号的稀疏性和局部平稳性结合在一起,提出了一种新的混合模型来描述观测信号在局部区域的概率分布.通过该模型,将每个时频点的源信号状态的判断问题转换成模型的参数估计和后验概率的计算问题,最后通过子混合矩阵的逆恢复出源信号. 实验结果表明,该方法具有很快的收敛速度,并且比已有方法具有更好的分离性能.     

FREQUENCY DOMAIN TESTS OF MULTIVARIATE GAUSSIANITY AND LINEARITY

A stationary multivariate time series { X _t } is defined as linear if it can be written in the form X _t = ∑^∞ _{j =−∞} A _j e _{t − j} where A _j are square matrices and e _t are independent and identically distributed random vectors. If the e _t } are normally distributed, then { X _t is a multivariate Gaussian linear process. This paper is concerned with the testing of departures of a vector stationary process from multivariate Gaussianity and linearity using the bispectral approach. First the definition and properties of cumulants of random matrices are used to obtain the expressions for the higher-order cumulant and spectral vectors of a linear vector process as defined above. Then it is shown that linearity of a vector process implies constancy of the modulus square of its normalized higher-order spectra whereas the component of such a vector process does not necessarily have a linear representation. Finally, statistics for the testing of multivariate Gaussianity and linearity are proposed.     

印制线路板微孔镀铜研究现状

印制线路板微孔金属化的关键在于在高厚径比的微孔中形成无空洞、无接缝、均匀的铜沉积层.综述了目前微孔填充技术的发展现状,对电镀过程中采用的电流密度、搅拌因素和电流波形等进行了探讨,重点讨论了添加剂对填孔效果的影响及其作用机理.     

A study of process monitoring based on inverse Gaussian distribution

The inverse Gaussian distribution has considerable applications in describing product life, employee service times, and so on. In this paper, the average run length (ARL) unbiased control charts, which monitor the shape and location parameters of the inverse Gaussian distribution respectively, are proposed when the in-control parameters are known. The effects of parameter estimation on the performance of the proposed control charts are also studied. An ARL-unbiased control chart for the shape parameter with the desired ${\mathit{ARL}}_0$, which takes the variability of the parameter estimate into account, is further developed. The performance of the proposed control charts is investigated in terms of the ARL and standard deviation of the run length. Finally, an example is used to illustrate the proposed control charts.     

Efficient data selection for speech recognition based on prior confidence estimation using speech and monophone models

This paper proposes an efficient speech data selection technique that can identify those data that will be well recognized. Conventional confidence measure techniques can also identify well-recognized speech data. However, those techniques require a lot of computation time for speech recognition processing to estimate confidence scores. Speech data with low confidence should not go through the time-consuming recognition process since they will yield erroneous spoken documents that will eventually be rejected. The proposed technique can select the speech data that will be acceptable for speech recognition applications. It rapidly selects speech data with high prior confidence based on acoustic likelihood values and using only speech and monophone models. Experiments show that the proposed confidence estimation technique is over 50 times faster than the conventional posterior confidence measure while providing equivalent data selection performance for speech recognition and spoken document retrieval.     

羧基化高纯单壁碳纳米管修饰电极对乙酰甲喹的高灵敏检测

采用羧基化高纯单壁碳纳米管(c SWCNTs)固载于金电极表面来构筑乙酰甲喹电化学传感器。运用循环伏安法(CV)、差分脉冲伏安法(DPV)和电化学交流阻抗法(EIS)测定传感器的性能。结果显示,该传感器对乙酰甲喹的电化学还原具有显著的催化性能,修饰电极的峰电流达到-128.40μA,是裸电极峰电流的1167倍。通过对传感器性能影响因素的考察,得到最优制备条件为cSWCNTs涂覆量为4μL(质量分数0.10%分散液),搅拌速度1000 r/min,pH=7.0的PBS浓度为0.2 mol/L,-0.5V电压下富集30 min。在该条件下制备的传感器峰电流与乙酰甲喹在1～500nmol/L范围内呈良好的线性关系,相关系数为0.998,方法的检出限为0.76nmol/L。该传感器被成功地应用于实际样品检测,加标回收率在81.7%～124.0%。     

HIGHER ORDER MOMENTS OF SAMPLE AUTOCOVARIANCES AND SAMPLE AUTOCORRELATIONS FROM AN INDEPENDENT TIME SERIES

Abstract. Given length- n sampled time series, generated by an independent distributed process, in this paper we treat the problem of determining the greatest order, in n , that moments of the sample autocovariances and sample autocorrelations can attain. For the sample autocovariance moments, we achieve quite general results; but, for the autocorrelation moments, we restrict study to Gaussian white noise (normal, independent and identically distributed). Our main theorem relates to the cross-moments of the non-centred sample autocovariances, but we also establish a relation between these and the corresponding moments for the centred sample autocovariances.