通用模拟退火用于稳健多元分析校正

模拟退火是一种全局优化算法，具有跨越局部最优点的机制，最小一乘是一种较常用的最小二乘更为稳健的优化准则，更适用于可能偏离正态分布的实际数据集，本文探讨了用最小一乘为准则并利用模拟退火方法同时测定多组分体系的可能性。应用于2－3组分药物体系分析，获得了满意的结果，本文还探讨了改变步长提高模拟退火算法优化精度的方法。     

Synthesis,characterization, and application of griseofulvin surface molecularly imprinted polymers as the selective solid phase extraction sorbent in rat plasma samples

In present study, an investigation was carried out to develop and validate an analytical method for the selective extraction and determination of griseofulvin (GSF) from plasma samples. For this purpose, a rational approach was made to synthesize and characterize the surface molecularly imprinted polymers (SMIPs). The SMIPs were utilized as solid phase extraction (SPE) sorbents. The SMIPs were prepared by using GSF as template molecule on the surface of modified silica particles through a non-covalent technique. The particles demonstrated high adsorption capacity (119.1 µg/mL), fast adsorption equilibrium time (30 min) and good recognition selectivity for the template drug. The scanning electron microscopy and infrared spectroscopy were used to explain the structural and morphological characteristics of the SMIPs and surface non-imprinted polymers. The SPE method was combined with HPLC for plasma analysis. The method validation results demonstrated that the established method possessed good linearity for GSF ranging from 0.1 to 50 µg/mL (R² = 0.997). The limit of detection for this method was 0.02 µg/mL for rat plasma samples. The recoveries of GSF from spiked plasma samples were (90.7–97.7%) and relative standard deviations were (0.9–4.5%). Moreover, the SMIPs as selective SPE sorbent can be reused more than 8 times which is a clear advantage over commercial SPE sorbents. Finally, the usefulness of the proposed strategy was assessed by extraction and detection of GSF in real rat plasma samples.     

Application of a retention database to the identification of individual polychlorinated biphenyl congeners in Aroclors mixture using selected polychlorinated biphenyls as a reference series

The database of the relative retention times (RRTs) of polychlorinated biphenyls (PCBs) reported in literature was used to calculate the retention indices (RIs) of all 209 PCB congeners on temperature programmed capillary column Rtx-5. Calculation of retention indices was based on reference series of seven congeners (PCB IUPAC Nos. 18, 52, 101, 143, 185, 203 and 206) that exhibit linear relative retention time behaviour as a function of chlorine number. The calculated indices were compared to those determined in our laboratory as well as to those obtained by other authors. The proposed indices system was applied for identification individual congeners in mixture of Aroclors 1242:1254:1260, using only reference series of PCBs.     

μs级负充电时不同体积分数去离子水与乙二醇混合液电性能的实验研究

 以去离子水与乙二醇的混合液（体积分数分别为36.5%,48.7%,59.0%及71.2%，以下简称混合液）作为同轴传输线的绝缘介质，进行了μs级高电压负充电条件下的正电极击穿实验，研究了混合液的击穿电压、击穿时间、相对介电常数及电阻率与体积分数的关系。实验结果表明：在充电电压为20kV时，71.2%的混合液比36.5%的混合液的平均击穿电压提高25.1%，平均击穿时间延长10.49%，而相对介电常数减小868%。同时，随着充电时间的缩短，混合液的击穿电压提高。     

2D Burgers equation with large Reynolds number using POD/DEIM and calibration

Model order reduction of the two‐dimensional Burgers equation is investigated. The mathematical formulation of POD/discrete empirical interpolation method (DEIM)‐reduced order model (ROM) is derived based on the Galerkin projection and DEIM from the existing high fidelity‐implicit finite‐difference full model. For validation, we numerically compared the POD ROM, POD/DEIM, and the full model in two cases of Re = 100 and Re = 1000, respectively. We found that the POD/DEIM ROM leads to a speed‐up of CPU time by a factor of O(10). The computational stability of POD/DEIM ROM is maintained by means of a careful selection of POD modes and the DEIM interpolation points. The solution of POD/DEIM in the case of Re = 1000 has an accuracy with error O(10^?3) versus O(10^?4) in the case of Re = 100 when compared with the high fidelity model. For this turbulent flow, a closure model consisting of a Tikhonov regularization is carried out in order to recover the missing information and is developed to account for the small‐scale dissipation effect of the truncated POD modes. It is shown that the computational results of this calibrated ROM exhibit considerable agreement with the high fidelity model, which implies the efficiency of the closure model used. Copyright © 2016 John Wiley & Sons, Ltd.     

Carbon dots with strong excitation-dependent fluorescence changes towards pH. Application as nanosensors for a broad range of pH

In this study, preparation of novel pH-sensitive N-doped carbon dots (NCDs) using glucose and urea is reported. The prepared NCDs present strong excitation-dependent fluorescence changes towards the pH that is a new behavior from these nanomaterials. By taking advantage of this unique behavior, two separated ratiometric pH sensors using emission spectra of the NCDs for both acidic (pH 2.0 to 8.0) and basic (pH 7.0 to 14.0) ranges of pH are constructed. Additionally, by considering the entire Excitation–Emission Matrix (EEM) of NCDs as analytical signal and using a suitable multivariate calibration method, a broad range of pH from 2.0 to 14.0 was well calibrated. The multivariate calibration method was independent from the concentration of NCDs and resulted in a very low average prediction error of 0.067 pH units. No changes in the predicted pH under UV irradiation (for 3 h) and at high ionic strength (up to 2 M NaCl) indicated the high stability of this pH nanosensor. The practicality of this pH nanosensor for pH determination in real water samples was validated with good accuracy and repeatability.     

Effect of gap and flow orientation on two-phase flow in an oil-wet gap: Relative permeability curves and flow structures

Naturally fractured reservoirs contain about 25–30% of the world supply of oil. In these reservoirs, fractures are the dominant flow path. Therefore, a good understanding of transfer parameters such as relative permeability as well as flow regimes occurring in a fracture plays an important role in developing and improving oil production from such complex systems. However, in contrast with gas–liquid flow in a single fracture, the flow of heavy oil and water has received less attention. In this research, a Hele-Shaw apparatus was built to study the flow of water in presence of heavy oil and display different flow patterns under different flow rates and analyze the effect of fracture orientations on relative permeability curves as well as flow regimes. The phase flow rates versus phase saturation results were converted to experimental relative permeability curves. The results of the experiments demonstrate that, depending on fracture and flow orientation, there could be a significant interference between the phases flowing through the fracture. The results also reveal that both phases can flow in both continuous and discontinuous forms. The relative permeability curves show that the oil–water relative permeability not only depends on fluid saturations and flow patterns but also fracture orientation.     

Simultaneous Determination of Acetaminophen and Phenobarbital in Suppositories by Partial Least-Squares Spectrophotometric Calibration

Abstract

The use of partial least-squares spectrophotometric calibration for the simultaneous determination of suppositories in a multicomponent formulation is presented. This method is applied to the deternination of acetaminophen and phenobarbital in suppository preparations. The results show that these components in a molar ratio of about 61:1 in suppositories have been determined simultaneously with high precision.     

Efficient computation of operator‐type response sensitivities for uncertainty quantification and predictive modeling: illustrative application to a spent nuclear fuel dissolver model

This work honors the 75th birthday of Professor Ionel Michael Navon by presenting original results highlighting the computational efficiency of the adjoint sensitivity analysis methodology for function‐valued operator responses by means of an illustrative paradigm dissolver model. The dissolver model analyzed in this work has been selected because of its applicability to material separations and its potential role in diversion activities associated with proliferation and international safeguards. This dissolver model comprises eight active compartments in which the 16 time‐dependent nonlinear differential equations modeling the physical and chemical processes comprise 619 scalar and time‐dependent model parameters, related to the model's equation of state and inflow conditions. The most important response for the dissolver model is the time‐dependent nitric acid in the compartment furthest away from the inlet, where measurements are available at 307 time instances over the transient's duration of 10.5 h. The sensitivities to all model parameters of the acid concentrations at each of these instances in time are computed efficiently by applying the adjoint sensitivity analysis methodology for operator‐valued responses. The uncertainties in the model parameters are propagated using the above‐mentioned sensitivities to compute the uncertainties in the computed responses. A predictive modeling formalism is subsequently used to combine the computational results with the experimental information measured in the compartment furthest from the inlet and then predict optimal values and uncertainties throughout the dissolver. This predictive modeling methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution for the a priori known mean values and uncertainties characterizing the model parameters and the computed and experimentally measured model responses. This approximate a priori distribution is subsequently combined using Bayes' theorem with the “likelihood” provided by the multi‐physics computational models. Finally, the posterior distribution is evaluated using the saddle‐point method to obtain analytical expressions for the optimally predicted values for the parameters and responses of both multi‐physics models, along with corresponding reduced uncertainties. This work shows that even though the experimental data pertains solely to the compartment furthest from the inlet (where the data were measured), the predictive modeling procedure used herein actually improves the predictions and reduces the predicted uncertainties for the entire dissolver, including the compartment furthest from the measurements, because this predictive modeling methodology combines and transmits information simultaneously over the entire phase‐space, comprising all time steps and spatial locations. Copyright © 2016 John Wiley & Sons, Ltd.     

An object-parameter approach to predicting unknown data in incomplete fuzzy soft sets

Incomplete data in soft sets lead to uncertainty and inaccuracy in representing and handling information. This paper introduces notions of complete distance between two objects and relative dominance degree between two parameters. Based on both the notions, an object-parameter method is proposed to predict unknown data in incomplete fuzzy soft sets. The proposal makes full use of known data, including the information from the relationship between known values of all objects on a certain parameter and the information from the relationship between known values of an object on all parameters. The effectiveness of the proposal is verified by many examples under the compared investigation of classical predicted methods.