Hydrogen bonding networks controllable by the substitution position of tetrathiafulvalene on the pyridine ring

Because of the effect of pyridine on the substituent position on the TTF group, TTF derivatives exhibit different assembly structures at the interface, which will be of great significance to the construction of functional nanostructures from the molecular design point of view.     

Swelling and network parameters of crosslinked thermoreversible hydrogels of poly(N-ethylacrylamide)

Samples of Poly(N-ethylacrylamide) (PEA) have been synthesized by free radical polymerization in water using N,N′-methylene bis-acrylamide (BIS) as crosslinker. Hydrogels obtained by swelling them in water, 15 wt% KCl and 1 wt% sodium dodecyl sulphate (SDS) were examined by gravimetric, dimensional and compression-strain measurements to afford values of swelling ratio, polymer-solvent interaction parameters, elastic moduli and effective crosslinking density ν_e. Crosslinking inefficiency is evidenced by the low value (0.23) of ν_e relative to the theoretical crosslinking density ν_t based on the content of BIS in the synthesis. A small but finite extrapolated value of ν_e at ν_t = 0 is indicative of hydrophobic physical interactions. In water at 298 K increasing the content of BIS leads to a decrease in swelling and increases in values of elastic moduli and polymer-water interaction parameter. At a fixed content of BIS the values of ν_e and the elastic moduli exhibit an unusual increase with temperature, the crosslinking thus being thermally reversible. It is proposed that this results from a balance between hydrophobic interaction and breakage of hydrophilic hydrogen bonding. Although KCl in the medium decreases the swelling compared with that in water, the opposite effect occurs on incorporation of SDS, which is assumed to confer some polyelectrolyte character to the PEA chains. The finding, that these two swelling media reduce the values of ν_e and elastic moduli cf the value in water, has not been resolved satisfactorily.     

应用反向传播神经网络预测化合物脑血分配系数

选用27种三维结构性质描述符对脑血分配系数预测建立神经网络模型.网络模型选用典型的适合函数逼近的两层结构神经网络对脑血分配系数(lgBB,BB为脑血浓度比)进行预测,计算中采用的模型具有一个双曲正切型激活函数的隐含层和一个线性激活函数的输出层.计算表明,使用小心选择的反向传播神经网络模型对化合物脑血分配系数具有较好的预测能力.     

炭气凝胶及其有机气凝胶前驱体的研究进展

介绍了炭气凝胶及其有机气凝胶前驱体的发展概况，着重总结了制备工艺条件(如催化剂及其浓度、反应物总浓度、反应物配比、溶剂、反应温度及时间、超临界干燥工艺条件和炭化工艺条件等)对有机气凝胶及其相应炭气凝胶中孔网络结构的影响，综述了中孔网络结构改性研究的进展．     

Development and validation of an analytical methodology for the determination of p,p′-DDT, p,p′-DDE and p,p′-DDD in fish oil pills

An analytical methodology was proposed and validated to be applied to the determination of p,p′-DDT and its metabolites p,p′-DDE and p,p′-DDD in fish oil. The analytical procedure presented in this paper involves a single-step clean up process prior to the analysis. A solution of 1,2,3,4-tetrachloronaphtalene was used as internal standard.The analytical technique used was gas chromatography coupled to an electron capture detector. Details on the validation process are provided.The limits of detection ranged from 2.6 to 4.7 pg μL^− 1. The BCR 598 standard reference material (cod liver oil) was used to evaluate the performance of the methodology with satisfactory recoveries for all the compounds.The analytes were determined in three different fish oil pills sold in Spain as a supplementary vitamin support. The sum of p,p′-DDT and metabolites was from 13.2 to 51.3 ng g^− 1, the dominant compound being p,p′-DDE.     

Minimum cost multiflows in undirected networks

LetN = (G, T, c, a) be a network, whereG is an undirected graph,T is a distinguished subset of its vertices (calledterminals), and each edgee ofG has nonnegative integer-valuedcapacity c(e) andcost a(e). Theminimum cost maximum multi(commodity)flow problem (*) studied in this paper is to find ac-admissible multiflowf inG such that: (i)f is allowed to contain partial flows connecting any pairs of terminals, (ii) the total value off is as large as possible, and (iii) the total cost off is as small as possible, subject to (ii). This generalizes, on one hand, the undirected version of the classical minimum cost maximum flow problem (when |T| = 2), and, on the other hand, the problem of finding a maximum fractional packing ofT-paths (whena 0). Lovász and Cherkassky independently proved that the latter has a half-integral optimal solution.A pseudo-polynomial algorithm for solving (*) has been developed earlier and, as its consequence, the theorem on the existence of a half-integral optimal solution for (*) was obtained. In the present paper we give a direct, shorter, proof of this theorem. Then we prove the existence of a half-integral optimal solution for the dual problem. Finally, we show that half-integral optimal primal and dual solutions can be designed by a combinatorial strongly polynomial algorithm, provided that some optimal dual solution is known (the latter can be found, in strongly polynomial time, by use of a version of the ellipsoid method).This work was partially supported by Chaire municipale, Mairie de Grenoble, France.     

基于卡口上下文和深度置信网络的车辆轨迹预测模型研究

针对车辆轨迹预测中节点序列的时序特性和实际路网中的空间关联性,该文提出一种基于深度置信网络和SoftMax (DBN-SoftMax)轨迹预测方法.首先,考虑到轨迹在节点集合中的强稀疏性和一般特征学习方法对新特征的泛化能力不足,该文利用深度置信网络(DBN)较强的无监督特征学习能力,达到提取轨迹局部空间特性的目的;然后,针对轨迹的时序特性,该文采用逻辑回归的预测思路,用当前轨迹集在路网特征空间中的线性组合来预测轨迹;最后,结合自然语言处理领域中的词嵌入的思想,基于实际轨迹中节点存在的上下文关系,运用节点的向量集表征了节点间的交通时空关系.实验结果表明该模型不仅能够有效地提取轨迹特征,并且在拓扑结构复杂的路网中也能得到较好的预测结果.     

基于多尺度圆周频率滤波与卷积神经网络的遥感图像飞机目标检测方法研究

针对遥感图像飞机目标检测因目标尺度不一存在漏警、虚警等问题,该文基于遥感图像中飞机目标形状特征和灰度变化特点提出了一种多尺度圆周频率滤波(MSCFF)与卷积神经网络(CNN)相结合的MSCFF+CNN飞机目标自动检测算法.该算法首先采用多尺度圆周频率滤波器滤除遥感图像复杂背景,实现不同尺度飞机目标候选区域提取;然后,通过构建卷积神经网络(CNN)模型实现候选区域有效分类,最终精确确定飞机目标位置.最后,基于获取的真实遥感图像进行目标检测算法实验验证,经统计该算法的飞机目标检测率为94.38%,虚警率为3.76%,实验结果充分验证了该文算法的有效性,该算法可为机场监管、军事侦察等应用提供重要的技术支持.     

基于超像素级卷积神经网络的多聚焦图像融合算法

该文提出了基于超像素级卷积神经网络(sp-CNN)的多聚焦图像融合算法。该方法首先对源图像进行多尺度超像素分割,将获取的超像素输入sp-CNN,并对输出的初始分类映射图进行连通域操作得到初始决策图;然后根据多幅初始决策图的异同获得不确定区域,并利用空间频率对其再分类,得到阶段决策图;最后利用形态学对阶段决策图进行后处理,并根据所得的最终决策图融合图像。该文算法直接利用超像素分割块进行图像融合,其相较以往利用重叠块的融合算法可达到降低时间复杂度的目的,同时可获得较好的融合效果。     

Computing optimal scalings by parametric network algorithms

Asymmetric scaling of a square matrixA 0 is a matrix of the formXAX ^–1 whereX is a nonnegative, nonsingular, diagonal matrix having the same dimension ofA. Anasymmetric scaling of a rectangular matrixB 0 is a matrix of the formXBY ^–1 whereX andY are nonnegative, nonsingular, diagonal matrices having appropriate dimensions. We consider two objectives in selecting a symmetric scaling of a given matrix. The first is to select a scalingA of a given matrixA such that the maximal absolute value of the elements ofA is lesser or equal that of any other corresponding scaling ofA. The second is to select a scalingB of a given matrixB such that the maximal absolute value of ratios of nonzero elements ofB is lesser or equal that of any other corresponding scaling ofB. We also consider the problem of finding an optimal asymmetric scaling under the maximal ratio criterion (the maximal element criterion is, of course, trivial in this case). We show that these problems can be converted to parametric network problems which can be solved by corresponding algorithms.This research was supported by NSF Grant ECS-83-10213.