Group 14 chalcogenides featuring a bicyclo[3.3.0]octane skeleton

Reactions of mixtures of Cl₂MeSiSiMeCl₂ (1) and Me₂MCl₂ (M=Si, Ge, Sn) with either H₂S/NEt₃ or Li₂E (E=Se, Te) yielded the bicyclo[3.3.0]octanes Me₂M(E)₂Si₂Me₂(E)₂MMe₂. A carbon containing analog, (CH₂)₅C(S)₂Si₂Me₂(S)₂C(CH₂)₅, was prepared from 1 and (CH₂)₅C(SH)₂. Crystal structures of three of these compounds were determined and the observed conformations of the bicyclo[3.3.0]octane skeletons compared with results of density functional theory calculations. Another class of silchalcogenides featuring a bicyclo[3.3.0]octane skeleton, E(Me₂Si)₂Si₂Me₂(SiMe₂)₂E, was formed from the doubly branched hexasilane (ClMe₂Si)₂Si₂Me₂(SiMe₂Cl)₂ and H₂S/NEt₃ or Li₂E. All products were characterized by multinuclear NMR (¹H, ¹³C, ²⁹Si, ⁷⁷Se, ¹¹⁹Sn, and ¹²⁵Te).     

Multicategory Classification by Support Vector Machines

We examine the problem of how to discriminate between objects of three or more classes. Specifically, we investigate how two-class discrimination methods can be extended to the multiclass case. We show how the linear programming (LP) approaches based on the work of Mangasarian and quadratic programming (QP) approaches based on Vapnik's Support Vector Machine (SVM) can be combined to yield two new approaches to the multiclass problem. In LP multiclass discrimination, a single linear program is used to construct a piecewise-linear classification function. In our proposed multiclass SVM method, a single quadratic program is used to construct a piecewise-nonlinear classification function. Each piece of this function can take the form of a polynomial, a radial basis function, or even a neural network. For the k > 2-class problems, the SVM method as originally proposed required the construction of a two-class SVM to separate each class from the remaining classes. Similarily, k two-class linear programs can be used for the multiclass problem. We performed an empirical study of the original LP method, the proposed k LP method, the proposed single QP method and the original k QP methods. We discuss the advantages and disadvantages of each approach.     

Topology of Dupin hypersurfaces with six distinct principal curvatures

Let M be a Dupin hypersurface in the unit sphere with six distinct principal curvatures. We will prove in the present paper that M is either diffeomorphic to or homeomorphic to a tube around an embedded 5-dimensional complex Fermat hypersurface in , where denotes the subgroup and . Moreover, in the former case, all of the focal manifolds are diffeomorphic to ; In the latter case, one of the focal manifolds is homeomorphic to . Received August 29, 1995; in final form May 5, 1997     

Synthesis, characterization and antifungal activity of group 12 metal complexes of 2-acetylpyridine-N-ethylthiosemicarbazone (H4EL) and 2-acetylpyridine-N-oxide-N-ethylthiosemicarbazone (H4ELO)

Reaction of group 12 metal halides in ethanol with the thiosemicarbazones 2-acetylpyridine-⁴N-ethylthiosemicarbazone (H4EL) and 2-acetylpyridine-N-oxide-⁴N-ethylthiosemicarbazone (H4ELO) produced the compounds [M(H4EL)X₂] and [M(H4ELO)X₂] [M=Zn(II), Cd(II) or Hg(II), X=Cl, Br or I]. The ligands and complexes were characterized by elemental analysis and by IR and NMR (¹H, ¹³C, ¹¹³Cd, ¹⁹⁹Hg) spectroscopy, and the structures of H4ELO·H₂O and the complexes [Cd(H4EL)I₂]·2DMSO, [Hg(H4EL)Br₂]–DMSO, [Zn(H4ELO)Cl₂] and [Zn(H4ELO)Br₂] were determined by X-ray diffraction. The metal centers in the complexes have coordination number five, H4EL and H4ELO behaving as neutral NNS- and ONS-tridentate ligands, respectively. The coordination polyhedra are close to tetragonal pyramids, the degree of distortion towards trigonal bipyramids was estimated by τ calculation. Against the pathogenic fungi Aspergillus niger and Paecilomyces variotii, the mercury complexes of H4ELO had activities that at some doses exceeded that of nystatin.     

A magnetic resonance study on the structure of amorphous networks in the Si–B–N(–C) system

The amorphous networks Si₃B₃N₇ and ‘SiBN₃C' are studied by solid-state nuclear magnetic resonance (NMR), continuous-wave and pulse electron paramagnetic resonance (EPR), and by one- and two-dimensional electron nuclear double resonance spectroscopy. In both compounds, boron is found to be coordinated exclusively by nitrogen with close to trigonal planar geometry and close to equal bond lengths. Silicon is four-coordinated by nitrogen with the coordination tetrahedra being distorted to accommodate the coordination preferences of boron. REDOR measurements demonstrate that boron resides in the second coordination sphere of silicon. Carbon incorporation into the Si–B–N network does not lead to any observable changes in NMR parameters including the average dipolar coupling between ¹¹B nuclei which depends on the average distance of the boron atoms. Only spin–lattice relaxation of the nuclei is accelerated due to the generation of paramagnetic centers. The unpaired electrons appear to be delocalized over several carbon atoms and exhibit significant hyperfine couplings to boron, silicon, nitrogen, and some residual protons. In contrast to electron spectroscopic imaging experiments, the magnetic resonance results suggest formation of carbon clusters.     

Equilibrium of a gravitating plasma in a dipolar magnetic field

The equilibria of plasma in a dipolar magnetic field under the gravitational influence of a massive body (a star or black hole) and a self gravitating plasma are considered. Analytical solutions are found that can be useful for understanding the physics of plasma flows in accretion disks and star formation.     

基于分维特征和反向传播神经网络的自然纹理识别

提出一种利用分维特征, 即自然纹理的自相似性进行纹理识别的研究。利用原始图像、高灰度图像、低灰度图像、四个方向（０°, ４５°, ９０°, １３５°）的梯度图像及二阶多分维共八个分维数作为特征值; 分维的计算采用改进的盒子计数法（ＭＢＣＭ）; 最后利用反向传播（ＢＰ）神经网络进行纹理的分类识别。实验结果与其它技术进行了比较, 并提出利用维纳滤波进一步改进分类性能。     

Extensions of Dinkelbach's algorithm for solving non-linear fractional programming problems

Dinkelbach's algorithm was developed to solve convex fractinal programming. This method achieves the optimal solution of the optimisation problem by means of solving a sequence of non-linear convex programming subproblems defined by a parameter. In this paper it is shown that Dinkelbach's algorithm can be used to solve general fractional programming. The applicability of the algorithm will depend on the possibility of solving the subproblems. Dinkelbach's extended algorithm is a framework to describe several algorithms which have been proposed to solve linear fractional programming, integer linear fractional programming, convex fractional programming and to generate new algorithms. The applicability of new cases as nondifferentiable fractional programming and quadratic fractional programming has been studied. We have proposed two modifications to improve the speed-up of Dinkelbachs algorithm. One is to use interpolation formulae to update the parameter which defined the subproblem and another truncates the solution of the suproblem. We give sufficient conditions for the convergence of these modifications. Computational experiments in linear fractional programming, integer linear fractional programming and non-linear fractional programming to evaluate the efficiency of these methods have been carried out.     

考虑不同脉冲形状时群速失配效应在二次谐波自相关法中的影响

本文讨论了在考虑不同脉冲形状时群速失配效应对二次谐波自相关法测量超短光脉冲宽度的影响.结果表明了脉冲形状不同时,群速失配效应对干涉自相关法和强度自相关法的影响不同.     

Personalized Image Classification by Semantic Embedding and Active Learning

Currently, deep learning has shown state-of-the-art performance in image classification with pre-defined taxonomy. However, in a more real-world scenario, different users usually have different classification intents given an image collection. To satisfactorily personalize the requirement, we propose an interactive image classification system with an offline representation learning stage and an online classification stage. During the offline stage, we learn a deep model to extract the feature with higher flexibility and scalability for different users’ preferences. Instead of training the model only with the inter-class discrimination, we also encode the similarity between the semantic-embedding vectors of the category labels into the model. This makes the extracted feature adapt to multiple taxonomies with different granularities. During the online session, an annotation task iteratively alternates with a high-throughput verification task. When performing the verification task, the users are only required to indicate the incorrect prediction without giving the exact category label. For each iteration, our system chooses the images to be annotated or verified based on interactive efficiency optimization. To provide a high interactive rate, a unified active learning algorithm is used to search the optimal annotation and verification set by minimizing the expected time cost. After interactive annotation and verification, the new classified images are used to train a customized classifier online, which reflects the user-adaptive intent of categorization. The learned classifier is then used for subsequent annotation and verification tasks. Experimental results under several public image datasets show that our method outperforms existing methods.