A new porous 2D coordination polymer built by copper(II) and trimesic acid

A 2D porous material, Cu-3(tmen)(3)(tma)(2)(H2O)(2)(.)6.5H(2)O [tmen = N,N,N',N'-tetramethylethane-1,2-diamine; tmaH(3) = 1,3,5-benzenetricarboxylic acid/trimesic acid], has been synthesized and characterized by X-ray single crystal analysis, variable temperature magnetic measurements, IR spectra and XRPD pattern. The complex consists of 2D layers built by three crystallographically independent Cu(tmen) moieties bridged by tma anions. Of the three copper ions, Cu(1) and Cu(2) present distorted square pyramidal coordination geometry, while the third exhibits a severely distorted octahedral environment. The Cu(1)(tmen) and Cu(2)(tmen) building blocks bridged by tma anions give rise to chains with a zig-zag motif, which are cross-connected by Cu(3)(tmen)-tma polymers sharing metal ions Cu(2) through pendant tma carboxylates. The resulting 2D architecture extends in the crystallographic ab-plane. The adjacent sheets are embedded through the Cu(3)(tmen) tma chains, leaving H2O-filled channels. There are 6.5 lattice water molecules per formula unit, some of which are disordered. Upon heating, the lattice water molecules get eliminated without destroying the crystal morphology and the compound rehydrated reversibly on exposure to humid atmosphere. Magnetic data of the complex have been fitted considering isolated irregular Cu-3 triangles (three different J parameters) by applying the CLUMAG program. The best fit indicates three close comparable J parameters and very weak antiferromagnetic interactions are operative between the metal centers. (C) 2004 Elsevier B.V. All rights reserved.

Pressure-jump X-ray studies of liquid crystal transitions in lipids

In this paper, we give an overview of our studies by static and time-resolved X-ray diffraction of inverse cubic phases and phase transitions in lipids. In 1, we briefly discuss the lyotropic phase behaviour of lipids, focusing attention on non-lamellar structures, and their geometric/topological relationship to fusion processes in lipid membranes. Possible pathways for transitions between different cubic phases are also outlined. In 2, we discuss the effects of hydrostatic pressure on lipid membranes and lipid phase transitions, and describe how the parameters required to predict the pressure dependence of lipid phase transition temperatures can be conveniently measured. We review some earlier results of inverse bicontinuous cubic phases from our laboratory, showing effects such as pressure-induced formation and swelling. In 3, we describe the technique of pressure-jump synchrotron X-ray diffraction. We present results that have been obtained from the lipid system 1:2 dilauroylphosphatidylcholine/lauric acid for cubic-inverse hexagonal, cubic-cubic and lamellar-cubic transitions. The rate of transition was found to increase with the amplitude of the pressure-jump and with increasing temperature. Evidence for intermediate structures occurring transiently during the transitions was also obtained. In 4, we describe an IDL-based 'AXCESS' software package being developed in our laboratory to permit batch processing and analysis of the large X-ray datasets produced by pressure-jump synchrotron experiments. In 5, we present some recent results on the fluid lamellar-Pn3m cubic phase transition of the single-chain lipid 1-monoelaidin, which we have studied both by pressure-jump and temperature-jump X-ray diffraction. Finally, in 6, we give a few indicators of future directions of this research. We anticipate that the most useful technical advance will be the development of pressure-jump apparatus on the microsecond time-scale, which will involve the use of a stack of piezoelectric pressure actuators. The pressure-jump technique is not restricted to lipid phase transitions, but can be used to study a wide range of soft matter transitions, ranging from protein unfolding and DNA unwinding and transitions, to phase transitions in thermotropic liquid crystals, surfactants and block copolymers.

Depression in men in the postnatal period and later child psychopathology: a population cohort study

Objective: Postnatal depression in women is associated with adverse effects on both maternal health and children's development. It is unclear whether depression in men at this time poses comparable risks. The present study set out to assess the association between depression in men in the postnatal period and later psychiatric disorders in their children and to investigate predisposing factors for depression in men following childbirth. Method: A population-based cohort of 10,975 fathers and their children from the Avon Longitudinal Study of Parents and Children (ALSPAC) was recruited in the prenatal period and followed for 7 years. Paternal depressive symptoms were assessed with the Edinburgh Postnatal Depression Scale and later child psychiatric disorder (DSM-IV) with the Development and Well-Being Assessment. Results: Depression in fathers in the postnatal period was significantly associated with psychiatric disorder in their children 7 years later (adjusted OR 1.72, 95% CI 1.07-2.77), most notably oppositional defiant/conduct disorders (adjusted OR 1.94, 95% CI 1.04-3.61), after adjusting for maternal depression and paternal educational level. A history of severe depression and high prenatal symptom scores for depression and anxiety were the strongest predictors of paternal depression in the postnatal period. Conclusions: Depression in fathers in the postnatal period is associated with later psychiatric disorders in their children, independently of maternal postnatal depression. Further research into the risks associated with paternal psychopathology is required because this could represent an important opportunity for public health intervention.

The effects of pre- and postnatal depression in fathers: a natural experiment comparing the effects of exposure to depression on offspring

Background: Depression in fathers in the postnatal period is associated with an increased risk of behavioural problems in their offspring, particularly for boys. The aim of this study was to examine for differential effects of depression in fathers on children's subsequent psychological functioning via a natural experiment comparing prenatal and postnatal exposure. Methods:In a longitudinal population cohort study (the Avon Longitudinal Study of Parents and Children (ALSPAC)) we examined the associations between depression in fathers measured in the prenatal and postnatal period (measured using the Edinburgh Postnatal Depression Scale), and later behavioural/emotional and psychiatric problems in their children, assessed at ages 31/2 and 7 years. Results: Children whose fathers were depressed in both the prenatal and postnatal periods had the highest risks of subsequent psychopathology, measured by total problems at age 31/2 years (Odds Ratio 3.55; 95% confidence interval 2.07, 6.08) and psychiatric diagnosis at age 7 years (OR 2.54; 1.19, 5.41). Few differences emerged when prenatal and postnatal depression exposure were directly compared, but when compared to fathers who were not depressed, boys whose fathers had postnatal depression only had higher rates of conduct problems aged 31/2 years (OR 2.14; 1.22, 3.72) whereas sons of the prenatal group did not (OR 1.41; .75, 2.65). These associations changed little when controlling for maternal depression and other potential confounding factors. Conclusions: The findings of this study suggest that the increased risk of later conduct problems, seen particularly in the sons of depressed fathers, maybe partly mediated through environmental means. In addition, children whose fathers are more chronically depressed appear to be at a higher risk of emotional and behavioural problems. Efforts to identify the precise mechanisms by which transmission of risk may occur should be encouraged to enable the development of focused interventions to mitigate risks for young children.

Parallel Monte Carlo approach for integration of the rendering equation

This paper is addressed to the numerical solving of the rendering equation in realistic image creation. The rendering equation is integral equation describing the light propagation in a scene accordingly to a given illumination model. The used illumination model determines the kernel of the equation under consideration. Nowadays, widely used are the Monte Carlo methods for solving the rendering equation in order to create photorealistic images. In this work we consider the Monte Carlo solving of the rendering equation in the context of the parallel sampling scheme for hemisphere. Our aim is to apply this sampling scheme to stratified Monte Carlo integration method for parallel solving of the rendering equation. The domain for integration of the rendering equation is a hemisphere. We divide the hemispherical domain into a number of equal sub-domains of orthogonal spherical triangles. This domain partitioning allows to solve the rendering equation in parallel. It is known that the Neumann series represent the solution of the integral equation as a infinity sum of integrals. We approximate this sum with a desired truncation error (systematic error) receiving the fixed number of iteration. Then the rendering equation is solved iteratively using Monte Carlo approach. At each iteration we solve multi-dimensional integrals using uniform hemisphere partitioning scheme. An estimate of the rate of convergence is obtained using the stratified Monte Carlo method. This domain partitioning allows easy parallel realization and leads to convergence improvement of the Monte Carlo method. The high performance and Grid computing of the corresponding Monte Carlo scheme are discussed.

Parallel Monte Carlo sampling scheme for sphere and hemisphere

The sampling of certain solid angle is a fundamental operation in realistic image synthesis, where the rendering equation describing the light propagation in closed domains is solved. Monte Carlo methods for solving the rendering equation use sampling of the solid angle subtended by unit hemisphere or unit sphere in order to perform the numerical integration of the rendering equation. In this work we consider the problem for generation of uniformly distributed random samples over hemisphere and sphere. Our aim is to construct and study the parallel sampling scheme for hemisphere and sphere. First we apply the symmetry property for partitioning of hemisphere and sphere. The domain of solid angle subtended by a hemisphere is divided into a number of equal sub-domains. Each sub-domain represents solid angle subtended by orthogonal spherical triangle with fixed vertices and computable parameters. Then we introduce two new algorithms for sampling of orthogonal spherical triangles. Both algorithms are based on a transformation of the unit square. Similarly to the Arvo's algorithm for sampling of arbitrary spherical triangle the suggested algorithms accommodate the stratified sampling. We derive the necessary transformations for the algorithms. The first sampling algorithm generates a sample by mapping of the unit square onto orthogonal spherical triangle. The second algorithm directly compute the unit radius vector of a sampling point inside to the orthogonal spherical triangle. The sampling of total hemisphere and sphere is performed in parallel for all sub-domains simultaneously by using the symmetry property of partitioning. The applicability of the corresponding parallel sampling scheme for Monte Carlo and Quasi-D/lonte Carlo solving of rendering equation is discussed.

A new solution of the rendering equation with stratified Monte Carlo approach

This paper is turned to the advanced Monte Carlo methods for realistic image creation. It offers a new stratified approach for solving the rendering equation. We consider the numerical solution of the rendering equation by separation of integration domain. The hemispherical integration domain is symmetrically separated into 16 parts. First 9 sub-domains are equal size of orthogonal spherical triangles. They are symmetric each to other and grouped with a common vertex around the normal vector to the surface. The hemispherical integration domain is completed with more 8 sub-domains of equal size spherical quadrangles, also symmetric each to other. All sub-domains have fixed vertices and computable parameters. The bijections of unit square into an orthogonal spherical triangle and into a spherical quadrangle are derived and used to generate sampling points. Then, the symmetric sampling scheme is applied to generate the sampling points distributed over the hemispherical integration domain. The necessary transformations are made and the stratified Monte Carlo estimator is presented. The rate of convergence is obtained and one can see that the algorithm is of super-convergent type.

Quasi Monte Carlo approach with uniform separation for solving of the rendering equation, ICNAAM 2007

This paper is directed to the advanced parallel Quasi Monte Carlo (QMC) methods for realistic image synthesis. We propose and consider a new QMC approach for solving the rendering equation with uniform separation. First, we apply the symmetry property for uniform separation of the hemispherical integration domain into 24 equal sub-domains of solid angles, subtended by orthogonal spherical triangles with fixed vertices and computable parameters. Uniform separation allows to apply parallel sampling scheme for numerical integration. Finally, we apply the stratified QMC integration method for solving the rendering equation. The superiority our QMC approach is proved.

Neurofuzzy network model construction using Bézier-Bernstein polynomial functions

Neurofuzzy modelling systems combine fuzzy logic with quantitative artificial neural networks via a concept of fuzzification by using a fuzzy membership function usually based on B-splines and algebraic operators for inference, etc. The paper introduces a neurofuzzy model construction algorithm using Bezier-Bernstein polynomial functions as basis functions. The new network maintains most of the properties of the B-spline expansion based neurofuzzy system, such as the non-negativity of the basis functions, and unity of support but with the additional advantages of structural parsimony and Delaunay input space partitioning, avoiding the inherent computational problems of lattice networks. This new modelling network is based on the idea that an input vector can be mapped into barycentric co-ordinates with respect to a set of predetermined knots as vertices of a polygon (a set of tiled Delaunay triangles) over the input space. The network is expressed as the Bezier-Bernstein polynomial function of barycentric co-ordinates of the input vector. An inverse de Casteljau procedure using backpropagation is developed to obtain the input vector's barycentric co-ordinates that form the basis functions. Extension of the Bezier-Bernstein neurofuzzy algorithm to n-dimensional inputs is discussed followed by numerical examples to demonstrate the effectiveness of this new data based modelling approach.

Co3(SO4)3(OH)2[enH2]: a newS= 3/2 Kagome-type layered sulfate with a unique connectivity

The Kagome lattice, comprising a two-dimensional array of corner-sharing equilateral triangles, is central to the exploration of magnetic frustration. In such a lattice, antiferromagnetic coupling between ions in triangular plaquettes prevents all of the exchange interactions being simultaneously satisfied and a variety of novel magnetic ground states may result at low temperature. Experimental realization of a Kagome lattice remains difficult. The jarosite family of materials of nominal composition AM3(SO4)2(OH)6 (A = monovalent cation; M= Fe3+, Cr3+), offers perhaps one of the most promising manifestations of the phenomenon of magnetic frustration in two dimensions. The magnetic properties of jarosites are however extremely sensitive to the degree of coverage of magnetic sites. Consequently, there is considerable interest in the use of soft chemical techniques for the design and synthesis of novel materials in which to explore the effects of spin, degree of site coverage and connectivity on magnetic frustration.

Geographies of food: 'Afters'

This third and final ‘Geographies of food’ review is based on an online blog conversation provoked by the first and second reviews in the series (Cook et al., 2006; 2008a). Authors of the work featured in these reviews – plus others whose work was not but should have been featured – were invited to respond to them, to talk about their own and other people’s work, and to enter into conversations about – and in the process review – other/new work within and beyond what could be called ‘food geographies’. These conversations were coded, edited, arranged, discussed and rearranged to produce a fragmentary, multi-authored text aiming to convey the rich and multi-stranded content, breadth and character of ongoing food studies research within and beyond geography.

Template-based quadrilateral mesh generation from imaging data

This paper describes a novel template-based meshing approach for generating good quality quadrilateral meshes from 2D digital images. This approach builds upon an existing image-based mesh generation technique called Imeshp, which enables us to create a segmented triangle mesh from an image without the need for an image segmentation step. Our approach generates a quadrilateral mesh using an indirect scheme, which converts the segmented triangle mesh created by the initial steps of the Imesh technique into a quadrilateral one. The triangle-to-quadrilateral conversion makes use of template meshes of triangles. To ensure good element quality, the conversion step is followed by a smoothing step, which is based on a new optimization-based procedure. We show several examples of meshes generated by our approach, and present a thorough experimental evaluation of the quality of the meshes given as examples.