Constructing channel structures based on the assembly of p-sulfonatocalix[4]arene nanocapsules and [M(bpdo)(3)](2+)(M = Cu, Zn)

Novel channel structures based on [M(bpdo)(3)](2+) and p-sulfonatocalix[4]arene nanocapsules have been established; these are sustained exclusively by charge-assisted pi...pi interactions and sorption experiments show the porous materials have selective guest sorption properties.

Lanthanide-hinged calixarene bicapsules: Discrete hexanuclear Ln(III)/phenanthroline/p-sulfonatocalix[4]arene oligomers (Ln = Gd, Tb)

The dumbbell-like calixarene bicapsule in two novel Ln(III)-C4AS compounds was found to be a hexanuclear Ln(III)/phenanthroline/p-sulfonatocalix[4]arene oligomer. The magnetic and luminescent properties of these compounds were examined.

3D metal-organic frameworks incorporating water-soluble tetra-p-sulfonatocalix[4]arene

Water-soluble tetra-p-sulfonatocalix[4]arene, acting as a four-connected node, bridges the rare earth cations into a 3D porous MOF in which 1D smaller circular hydrophilic channels and larger quadratic ones are lined up along the c axis and interconnected to each other by the calixarene cavities and other interstices.

Assembly of Seven Supramolecular Compounds with p-Sulfonatocalix[6]arene

Seven supramolecular compounds comprising p-sulfonatocalix[6]arene and transition metals, {[Cu(Imz)-(phen)(H2O)](4)[C6AS]}center dot 10H(2)O (1), {[Cu(Imz)(2)(phen)](2)[Cu(Imz)(phen)(H2O)(2)](2)[C6AS]}center dot 13.3H(2)O (2), {[M(phen)(2)(H2O)]-[(M(phen)(2)](2)[C6AS]}center dot nH(2)O (3 and 4) (3: M = Co and n = 29.6; 4: M = Zn and n = 29.9), {[Cu(phen)(2)](4)[C6AS]}(2)center dot 13H(2)O (5), [H3O](2)[Co(phen)(3)](2)[C6AS]center dot 10.7H(2)O(6), and [Cu(phen)(2)(H2O)](2){[Cu(phen)(2)](2)[C6AS]}center dot 8H(2)O(7)(phen = 1,10-phenanthroline, C6AS = p-sulfonatocalix[6]arene, Imz = imidazole), have been synthesized by a hydrothermal method and structurally characterized by IR spectroscopy, thermogravimetric-differential thermal analysis (TG-DTA), and single crystal X-ray diffraction.

PH-Dependent syntheses and structures of two Copper(II)/Phenanthroline/p-Sulfonatocalix[4]arene supramolecular compounds with 1D water-filled channels

Two copper-organic framework supramolecular assemblies of p-sulfonatocalix[4]arene and 1,10-phenanthroline Cu-2[C12H8N2][C28H20S4O16][H2O](23.5) (1) and Cu-3[C12H8N2](3)[C28H19S4O16]Cl[H2O](17.6) (2) were obtained by pH-dependent synthesis at room temperature. Both structures show ID water-filled channels (rectangular shape in I and triangular in 2) with the solvent-accessible volume occupying 30.8% (1) and 24.2% (2) of the unit-cell volume, respectively. The calixarene molecules in both structures assume analogous cone shapes of C-2 nu symmetry instead of the conventional C-4 nu symmetry. Their connecting to different amounts of copper/phenanthroline cations leads to the formation of different structures.

Boundary knot method for 2D and 3D Helmholtz and convection-diffusion problems under complicated geometry

The boundary knot method (BKM) of very recent origin is an inherently meshless, integration-free, boundary-type, radial basis function collocation technique for the numerical discretization of general partial differential equation systems. Unlike the method of fundamental solutions, the use of non-singular general solution in the BKM avoids the unnecessary requirement of constructing a controversial artificial boundary outside the physical domain. The purpose of this paper is to extend the BKM to solve 2D Helmholtz and convection-diffusion problems under rather complicated irregular geometry. The method is also first applied to 3D problems. Numerical experiments validate that the BKM can produce highly accurate solutions using a relatively small number of knots. For inhomogeneous cases, some inner knots are found necessary to guarantee accuracy and stability. The stability and convergence of the BKM are numerically illustrated and the completeness issue is also discussed.

A Numerical Study of Indentation Using Indenters of Different Geometry

Finite element simulation of the Berkovich, Vickers, Knoop, and cone indenters was carried out for the indentation of elastic-plastic material. To fix the semiapex angle of the cone, several rules of equivalence were used and examined. Despite the asymmetry and differences in the stress and strain fields, it was established that for the Berkovich and Vickers indenters, the load-displacement relation can closely be simulated by a single cone indenter having a semiapex angle equal to 70.3degrees in accordance with the rule of the volume equivalence. On the other hand, none of the rules is applicable to the Knoop indenter owing to its great asymmetry. The finite element method developed here is also applicable to layered or gradient materials with slight modifications.

A geometry model for tortuosity of flow path in porous media

A simple geometry model for tortuosity of flow path in porous media is proposed based on the assumption that some particles in a porous medium are unrestrictedly overlapped and the others are not. The proposed model is expressed as a function of porosity and there is no empirical constant in this model. The model predictions are compared with those from available correlations obtained numerically and experimentally, both of which are in agreement with each other. The present model can also give the tortuosity with a good approximation near the percolation threshold. The validity of the present tortuosity model is thus verified.

Fractal geometry model for effective thermal conductivity of three-phase porous media

An approximate model, a fractal geometry model, for the effective thermal conductivity of three-phase/unsaturated porous media is proposed based on the thermal-electrical analogy technique and on statistical self-similarity of porous media. The proposed thermal conductivity model is expressed as a function of porosity (related to stage n of Sierpinski carpet), ratio of areas, ratio of component thermal conductivities, and saturation. The recursive algorithm for the thermal conductivity by the proposed model is presented and found to be quite simple. The model predictions are compared with the existing measurements. Good agreement is found between the present model predictions and the existing experimental data. This verifies the validity of the proposed model. (C) 2004 American Institute of Physics.

Effect of absorption on the diffraction efficiency in Fe : LiNbO3 crystal with 90 degrees recording geometry

In this paper the saturated diffraction efficiency has been optimized by considering the effect of the absorption of the recording light on a crossed-beam grating with 90 degrees recording geometry in Fe:LiNbO3 crystals. The dependence of saturated diffraction efficiency on the doping levels with a known oxidation-reduction state, as well as the dependence of saturated diffraction efficiency on oxidation-reduction state with known doping levels, has been investigated. Two competing effects on the saturated diffraction efficiency were discussed, and the intensity profile of the diffracted beam at the output boundary has also been investigated. The results show that the maximal saturated diffraction efficiency can be obtained in crystals with moderate doping levels and modest oxidation state. An experimental verification is performed and the results are consistent with those of the theoretical calculation.

Toll-like receptor 3 regulates Mx expression in rare minnow Gobiocypris rarus after viral infection

Toll-like receptor 3 (TLR3) plays a key role in activating immune responses during viral infection. To study the genes involved in the regulatory function of TLR3 in the rare minnow Gobiocypris rarus after viral infection, a full-length cDNA of TLR3 (GrTLR3) with a splice variant (GrTLR3s) was identified by homologous cloning and RACE techniques. The antiviral effector molecule Mx gene was cloned and partially sequenced. The mRNA expression levels of GrTLR3, GrTLR3s, and Mx were studied in different tissues before and after virus infection by real-time quantitative RT-PCR. The transcripts of all three genes in liver were significantly increased following GCRV infection (P<0.05). The mRNA levels in liver were upregulated at 24 h post-injection for GrTLR3 and GrTLR3s, and at 12 h for Mx. The upregulated expression levels were several folds for GrTLR3s, tens of folds for GrTLR3, and hundreds of folds for Mx. By semi-quantitative RT-PCR, GrTLR3 and Mx expressed at all the developmental stages, whereas GrTLR3s could only be detected at later developmental stages. Using RNAi and transgenic techniques, GrTLR3 mediated Mx expression but GrTLR3s did not. The time-dependent upregulation of receptor and effector, and the Mx over-expression dependent on TLR3, indicated that GrTLR3 regulated Mx expression in viral infection through a configuration change in rare minnow, and its splice variant did not contribute to the process.

The multi-weight neuron with geometry algorithm and its application

A novel approach for multi-dimension signals processing, that is multi-weight neural network based on high dimensional geometry theory, is proposed. With this theory, the geometry algorithm for building the multi-weight neuron is mentioned. To illustrate the advantage of the novel approach, a Chinese speech emotion recognition experiment has been done. From this experiment, the human emotions are classified into 6 archetypal classes: fear, anger, happiness, sadness, surprise and disgust. And the amplitude, pitch frequency and formant are used as the feature parameters for speech emotion recognition. Compared with traditional GSVM model, the new method has its superiority. It is noted that this method has significant values for researches and applications henceforth.

Geometrical learning, descriptive geometry, and biomimetic pattern recognition

Studies on learning problems from geometry perspective have attracted an ever increasing attention in machine learning, leaded by achievements on information geometry. This paper proposes a different geometrical learning from the perspective of high-dimensional descriptive geometry. Geometrical properties of high-dimensional structures underlying a set of samples are learned via successive projections from the higher dimension to the lower dimension until two-dimensional Euclidean plane, under guidance of the established properties and theorems in high-dimensional descriptive geometry. Specifically, we introduce a hyper sausage like geometry shape for learning samples and provides a geometrical learning algorithm for specifying the hyper sausage shapes, which is then applied to biomimetic pattern recognition. Experimental results are presented to show that the proposed approach outperforms three types of support vector machines with either a three degree polynomial kernel or a radial basis function kernel, especially in the cases of high-dimensional samples of a finite size. (c) 2005 Elsevier B.V. All rights reserved.