The least element property of center location on tree networks with applications to distance and precedence constrained problems

In the classicalp-center location model on a network there is a set of customers, and the primary objective is to selectp service centers that will minimize the maximum distance of a customer to a closest center. Suppose that thep centers receive their supplies from an existing central depot on the network, e.g. a warehouse. Thus, a secondary objective is to locate the centers that optimize the primary objective as close as possible to the central depot. We consider tree networks and twop-center models. We show that the set of optimal solutions to the primary objective has a semilattice structure with respect to some natural ordering. Using this property we prove that there is ap-center solution to the primary objective that simultaneously minimizes every secondary objective function which is monotone nondecreasing in the distances of thep centers from the existing central depot.Restricting the location models to a rooted path network (real line) we prove that the above results hold for the respective classicalp-median problems as well.     

Rigorous results on the thermodynamics of the dilute Hopfield model

We study the Hopfield model of an autoassociative memory on a random graph onN vertices where the probability of two vertices being joined by a link isp(N). Assuming thatp(N) goes to zero more slowly thanO(1/N), we prove the following results: (1) If the number of stored patternsm(N) is small enough such thatm(N)/Np(N) 0, asN, then the free energy of this model converges, upon proper rescaling, to that of the standard Curie-Weiss model, for almost all choices of the random graph and the random patterns. (2) If in additionm(N) < ln N/ln 2, we prove that there exists, forT< 1, a Gibbs measure associated to each original pattern, whereas for higher temperatures the Gibbs measure is unique. The basic technical result in the proofs is a uniform bound on the difference between the Hamiltonian on a random graph and its mean value.     

Crosslinking of vinyl‐terminated biphenyl and naphthalene side‐chain liquid‐crystalline poly(epichlorohydrin) derivatives

We performed the crosslinking of vinyl‐terminated biphenyl and naphthalene side‐chain liquid‐crystalline polyethers using peroxide‐type initiators with and without the addition of tertiary amine promoters. The crosslinking temperatures were chosen in the range of mesophase stability to allow the mesophase order to be frozen. The biphenyl derivatives, with a high isotropization temperature, were crosslinked to a large extent. This led to anisotropic thermosets. To crosslink naphthalene derivatives, amine promoters were needed, but degrees of crosslinking were lower, and anisotropic elastomers were obtained. Crosslinking processes were studied by differential scanning calorimetry, polarized optical microscopy, and Fourier transform infrared spectroscopy. The nature of the frozen mesophase was confirmed by X‐ray diffraction studies on mechanically oriented samples. © 2002 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 40: 2237–2244, 2002     

Miscible blends through hydrogen bonding: effects on polymer properties

Miscible blends through hydrogen bonding have been intensively studied. The effects of a variety of miscible hydrogen bonded polymer blends on properties such as thermal and thermal oxidative stability, moisture sensitivity, modulus and glass transition temperature are discussed. In addition, the preparation of semi-interpenetrating polymer networks (IPNs) and studies of the effect of crosslinking on the miscibility in hydrogen bonded polymer blends are reviewed.     

聚醋酸乙烯酯/聚丙烯酸甲酯互穿网络聚合物的研究——1.聚合条件对体系相容性的影响

用分步法合成了聚醋酸乙烯酯/聚丙烯酸甲酯互穿网络聚合物(PVAc/PMA-IPN),PVAc和PMA的交联剂分别是丁二酸二烯丙酯(DAS),和二乙烯基苯(DVB)。当DAS用量较小时,VAc聚合时的接枝反应较明显,PVAc网络的交联密度高于化学当量的计算值。动态力学的实验结果表明,丙烯酸甲酯的聚合温度和聚合过程中的溶胶-凝胶转变对PVAc/PMA-IPN体系的相容性有很大影响。     

Investigation of anthropic effects connected with metal ions concentration, organic matter and grain size in Bormida river sediments

An investigation on the sediment composition and grain size was carried out along the Bormida river (Piedmont, Northern Italy). The samples were taken both in the riverbed and on its banks. Multivariate statistical exploratory methods permitted to identify possible sources of primary pollution. In particular, principal component analysis (PCA) showed that there are probably at least three anthropogenic main causes of pollution, one connected with Cr, Ni and Sn, the second with cadmium and the last one with mercury. Some correlations were found between heavy metal ion concentrations and organic matter and/or the sediment grain size. Differences between the samples collected in the riverbed and on the banks were identified and the relationships between the principal components and the distance of the samples from the riverbed and from the hot spot represented by the ACNA industrial site were also analyzed.     

Prediction of Complexation Properties of Crown Ethers Using Computational Neural Networks

A computational neural network method was used for the prediction of stability constants of simple crown ether complexes. The essence of the method lies in the ability of a computer neural network to recognize the structure-property relationships in these host-guest systems. Testing of the computational method has demonstrated that stability constants of alkali metal cation (Na+, K+, Cs+)-crown ether complexes in methanol at 25 °C can be predicted with an average error of ±0.3 log K units based on the chemical structure of the crown ethers alone. The computer model was then used for the preliminary analysis of trends in the stabilities of the above complexes.     

基于支持向量机的羰基化合物红外光谱研究

设计了一个4层分等级分类系统，通过支持向量机技术对羰基化合物的红外光谱成功地进行了信息分类和提取，并与人工神经网络进行比较，结果表明：支持向量机对羰基类化合物红外光谱分类效果优于人工神经网络；另外详细探讨了表征酰胺类化合物的特征光谱峰片段对识圳伯仲叔酰胺的影响，证明了酰胺的N-H伸缩振动峰对识别伯仲叔酰胺贡献最大，为构建红外光谱智能解析系统提供了定量依据。     

人工神经元网络辅助丙烷氨氧化催化剂设计

报道了利用人工神经元网络辅助丙烷氨氧化制丙烯腈催化剂设计的研究进展结果．通过筛选得到了可以拟合该反应体系的神经元网络模型，从而使丙烷转化率和丙烯腈选择性可以表示为催化剂组成的函数，利用培训后的神经元网络模型所得到的权值文件，结合作者自编的优化程序，该网络可用于预测最优的催化剂组成．实验得到丙烯腈收率和选择性可分别达到４３．０％和５６．２４％．     

神经网络法用于多元混酸同时测定

利用多层神经网络误差反向传播算法处理酸碱电位滴定数据，求得出多元混合酸各组分的浓度，优化了神经网络的结构和参数，测定了三组分有机酸混合样品，结果良好，平均相对偏差ＲＳＤ≤４％。