川中丘陵区地表干湿长程相关性及影响因素研究（研究生论坛）

为探究川中丘陵区干湿动态动力学机制,提供旱涝预测的理论依据。根据川中丘陵区8个气象站点1958~2013年逐日气象资料,采用Penman—Monteith 模型计算潜在蒸散量,构建出湿润指数。在此基础上,基于去趋势波动分析方法（DFA）,对逐月、分季节、极端干湿湿润指数进行长程相关性分析,并探讨了影响湿润指数长程相关性的气象因子。结果表明：除南充、遂宁外,其余地区逐月湿润指数变化长程相关,并非完全随机;分季节与极端干湿湿润指数均具有长程相关性;对于不同季节而言,长程相关性以夏季最强,秋、冬两季次之,春季最弱,对于极端气候而言,极端湿润长程相关性强于极端干旱;通过对湿润指数与气象因子长程相关性一致性分析,降水标度指数与湿润指数标度指数呈显著正相关。     

Synthesis, characterization and properties of chitosan modified with poly(ethylene glycol)-polydimethylsiloxane amphiphilic block copolymers

Synthesis of poly(ethylene glycol)-polydimethylsiloxane amphiphilic block copolymers is discussed herein. Siloxane prepolymer was first prepared via acid-catalyzed ring-opening polymerization of octamethylcyclotetrasiloxane (D₄) to form polydimethylsiloxane (PDMS) prepolymers. It was subsequently functionalized with hydroxy functional groups at both terminals. The hydroxy-terminated PDMS can readily react with acid-terminated poly(ethylene glycol) (PEG diacid) to give PEG-PDMS block copolymers without using any solvent. The PEG diacid was prepared from hydroxy-terminated PEG through the ring-opening reaction of succinic anhydride. Their chemical structures and molecular weights were characterized using ¹H NMR, FTIR and GPC, and thermal properties were determined by DSC. The PEG-PDMS copolymer was incorporated into chitosan in order that PDMS provided surface modification and PEG provided good water swelling properties to chitosan. Critical surface energy and swelling behavior of the modified chitosan as a function of the copolymer compositions and contents were investigated.     

药物中间体2-[(2′-氰基联苯-4-基)甲基氨基]-3-硝苯甲酸乙酯的制备

本文介绍了以3-硝基-2-叔丁氧甲酰氨基苯甲酸乙酯为原料，在碱性条件下与4-(2-氰基苯基)-1-溴甲苯发生亲核取代反应制备2-[(2′-氰基联苯-4-基)甲基氨基]-3-硝苯甲酸乙酯的方法，产品经核磁共振验证其结构，产品收率达83％。本合成工艺条件温和，适合工业化生产。     

Reaction kinetics modeling and thermal properties of epoxy–amines as measured by modulated‐temperature DSC. II. Network‐forming DGEBA + MDA

Reaction‐induced vitrification takes place in the network‐forming epoxy–amine system diglycidyl ether of bisphenol A (DGEBA) + methylenedianiline (MDA) when the glass‐transition temperature (T_g) rises above the cure temperature (T_cure). This chemorheological transition results in diffusion‐controlled reaction and can be followed simultaneously with the reaction rate in modulated‐temperature DSC (MTDSC). To predict the effect of T_cure and the NH/epoxy molar mixing ratio (r) on the reaction rate in chemically controlled conditions, a mechanistic approach was used based on the nonreversing heat flow and heat capacity MTDSC signals, in which the reaction steps of primary (E_1OH = 44 kJ mol^?1) and secondary amine (E_2OH = 48 kJ mol^?1) with the epoxy–hydroxyl complex predominating. The diffusion factor DF as defined by the Rabinowitch approach expresses whether the chemical reaction rate or the diffusion rate determines the overall reaction rate. A model based on the free volume theory together with an Arrhenius temperature dependency was used to calculate the diffusion rate constant in DF as a function of conversion (x) and T_cure. The relation between x, r, and T_g, needed in this model, can be predicted with the Couchman equation. An experimental approximation for DF is the mobility factor DF* obtained from the heat capacity signal at a modulation frequency of 1/60 Hz, normalized for the effect of the reaction heat capacity in the liquid state and the change in C_p in the glassy region with x and T_cure. In this way, an optimized set of diffusion parameters was obtained that, together with the optimized kinetic parameters set, can predict the reaction rate for different cure schedules and for stoichiometric and off‐stoichiometric mixtures. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 91: 2814–2833, 2004     

Epileptic seizure classification in EEG signals using second-order difference plot of intrinsic mode functions

Epilepsy is a neurological disorder which is characterized by transient and unexpected electrical disturbance of the brain. The electroencephalogram (EEG) is a commonly used signal for detection of epileptic seizures. This paper presents a new method for classification of ictal and seizure-free EEG signals. The proposed method is based on the empirical mode decomposition (EMD) and the second-order difference plot (SODP). The EMD method decomposes an EEG signal into a set of symmetric and band-limited signals termed as intrinsic mode functions (IMFs). The SODP of IMFs provides elliptical structure. The 95% confidence ellipse area measured from the SODP of IMFs has been used as a feature in order to discriminate seizure-free EEG signals from the epileptic seizure EEG signals. The feature space obtained from the ellipse area parameters of two IMFs has been used for classification of ictal and seizure-free EEG signals using the artificial neural network (ANN) classifier. It has been shown that the feature space formed using ellipse area parameters of first and second IMFs has given good classification performance. Experimental results on EEG database available by the University of Bonn, Germany, are included to illustrate the effectiveness of the proposed method.     

Computer aided detection system for micro calcifications in digital mammograms

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. Mammogram breast X-ray is considered the most reliable method in early detection of breast cancer. However, it is difficult for radiologists to provide both accurate and uniform evaluation for the enormous mammograms generated in widespread screening. Micro calcification clusters (MCCs) and masses are the two most important signs for the breast cancer, and their automated detection is very valuable for early breast cancer diagnosis. The main objective is to discuss the computer-aided detection system that has been proposed to assist the radiologists in detecting the specific abnormalities and improving the diagnostic accuracy in making the diagnostic decisions by applying techniques splits into three-steps procedure beginning with enhancement by using Histogram equalization (HE) and Morphological Enhancement, followed by segmentation based on Otsu's threshold the region of interest for the identification of micro calcifications and mass lesions, and at last classification stage, which classify between normal and micro calcifications ‘patterns and then classify between benign and malignant micro calcifications. In classification stage; three methods were used, the voting K-Nearest Neighbor classifier (K-NN) with prediction accuracy of 73%, Support Vector Machine classifier (SVM) with prediction accuracy of 83%, and Artificial Neural Network classifier (ANN) with prediction accuracy of 77%.     

超磁致伸缩作动器的率相关Hammerstein模型与H∞鲁棒跟踪控制

利用Hammerstein模型对超磁致伸缩作动器（Giant magnetostrictive actuators,GMA）的率相关迟滞非线性进行建模,分别以改进的 Prandtl-Ishlinskii（Modified Prandtl-Ishlinskii）模型和外因输入自回归模型（Autoregressive model with exogenous input,ARX）代表Hammerstein模型中的静态非线性部分和线性动态部分,并给出了模型的辨识方法. 此模型能在1～100Hz频率范围内较好地描述GMA的率相关迟滞非线性. 提出了带有逆补偿器和H∞鲁棒控制器的二自由度跟踪控制策略,实时跟踪控制实验结果证明了所提策略的有效性.     

聚氨酯弹性体复合抗磨环的研制

介绍了聚氨酯弹性体复合抗磨环的设计及制作过程，并将该产品应用于挖泥船泥泵中。经过试验证明，该产品比传统的钢质抗磨环耐气蚀、耐磨损，使用寿命可延长3倍以上。     

(Ag)_核·(Au)_壳复合纳米粒子的制备

以银原子团簇作晶种,采用微波高压液相合成法制备了分散性好、规则球形的(Ag)核·(Au)壳复合纳米粒子。研究了(Ag)核·(Au)壳复合纳米粒子的紫外可见吸收光谱和共振散射光谱特性。结果表明,液相(Ag)核·(Au)壳复合纳米粒子和高压微波合成的液相金纳米粒子的最强共振散射峰均在580nm处,它们的吸收光谱图相似,最大吸收分别在518.5nm和524.8nm。     

Investigation of kinetics of agglomerate growth in oil agglomeration process

In this study, the kinetics of agglomerate growth in a batch oil agglomeration process has been studied using bituminous coal. The effect of operating variables such as kerosene concentration, pulp density and speed of agitation on the agglomeration process was investigated. It has been found that the second-order kinetic equation describes the growth of agglomerates adequately. The growth of the agglomerates in the oil agglomeration process shows a self-preserving growth. Using this, a characteristic curve has been developed. For the prediction of the size distribution of the agglomerates, the d₅₀ values of the agglomerates must be known. Therefore, a model has been developed by using the kinetic equation for estimation of d₅₀ values of agglomerates for this coal. It was shown that the size distribution of the agglomerates for any levels of the process variables studied can be predicted using the equation of characteristic curve and d₅₀ values. Knowledge obtained from this study will be helpful for technological advancement of this kind of study.