Mixed-dimensional coupling in finite element models

In many finite element analysis models it would be desirable to combine reduced- or lower-dimensional element types with higher-dimensional element types in a single model. In order to achieve compatibility of displacements and stress equilibrium at the junction or interface between the differing element types, it is important in such cases to integrate into the analysis some scheme for coupling the element types. A novel and effective scheme for establishing compatibility and equilibrium at the dimensional interface is described and its merits and capabilities are demonstrated. Copyright (C) 2000 John Wiley & Sons, Ltd.

Selective Imaging of Damaged Bone Structure (Microcracks) Using a Targeting Supramolecular Eu(III) Complex As a Lanthanide Luminescent Contrast Agent

The synthesis and photophysical evaluation of a new supramolecular lanthanide complex is described which was developed as a luminescent contrast agent for bone structure analysis. We show that the Eu(III) emission of this complex is not pH dependent within the physiological pH range, and that its steady state emission is not significantly modulated by a series of group I and II as well as d-metal ions, and that this agent can be successfully employed to image mechanically formed cracks (scratches) in bone samples after 4 or 24 hours, using confocal laser-scanning microscopy.

Nonlinear frequency coupling in dual radio-frequency driven atmospheric pressure plasmas

Plasma ionization, and associated mode transitions, in dual radio-frequency driven atmospheric pressure plasmas are governed through nonlinear frequency coupling in the dynamics of the plasma boundary sheath. Ionization in low-power mode is determined by the nonlinear coupling of electron heating and the momentary local plasma density. Ionization in high-power mode is driven by electron avalanches during phases of transient high electric fields within the boundary sheath. The transition between these distinctly different modes is controlled by the total voltage of both frequency components.

Palladium-mediated reductive coupling, a stereoselective approach to the 8-dehydropumiliotoxin skeleton

Reductive cyclisation of ail E-vinyl bromide with ail allylic acetate proceeds under palladium catalysis 10 give the 8-dehydropumiliotoxin skeleton, a potential advanced precursor to 8-deoxypumiliotoxin alkaloids. Control of the stereochemistry of the E-vinyl bromide precursor is achieved readily using the Kogen or Bruckner bromophosphonate reagents and the reductive cyclisation proceeds with retention of the vinyl bromide stereochemistry. The mechanism for the cyclisation involves an in situ conversion of the allylic acetate to ail allyl stannane followed by ail intramolecular Stille-type coupling.

Multi component coupling reactions of N-acetyl-2-azetine

N-Acetyl-2-azetine undergoes Lewis acid catalysed formal [4+2]-cycloaddition with imines derived from aromatic amines to initially give an approximately 1: 1 mixture of exo-endo-diastereoisomeric 1-(2a,3,4,8b-tetrahydro-2H-1,4-diaza-cyclobuta[a]naphthalen-1-yl)-ethanone cycloadducts which were detected by proton NMR spectroscopy. These products, which were too unstable to isolate, and characterise, reacted further with aromatic amines to give 2,3,4-trisubstituted tetrahydroquinolines in good to excellent yield, predominantly as a single diastereoisomer, with the minor diastereoisomer converting to the major diastereoisomer on silica. The cycloaddition was irreversible and a mechanism is presented for the formation of the major diastereoisomer from the mixture of diastereoisomeric intermediates. A range of conditions is described for converting the 2,3,4-trisubsitituted tetrahydroquinolines into 2,3-disubstituted quinolines.

Three component coupling reactions of N-acetyl-2-azetine-rapid stereoselective entry to 2,3,4-trisubstituted tetrahydroquinolines

N-Acetyl-2-azetine undergoes Lewis acid catalysed [4 + 2]-cycloaddition with imines derived from aromatic amines and gave a 1:1 mixture of exo-endo diastereoisomeric azetidine cycloadducts which reacted further with aromatic amine, to give 2,3,4-trisubsitituted tetrahydroquinolines in good to excellent yield, predominantly as one diastereoisomer.

The synthesis of BRL 49653 - a novel and potent antihyperglycemic agent.

Modifications based upon a metabolite of ciglitazone afforded BRL 49653 (I), a novel potent insulin sensitizer. A facile synthesis of this compd. is described.

Neural Network Modeling of Rheological Parameters of Grouts Containing Viscosity-Modifying Agent

The development of artificial neural network (ANN) models to predict the rheological behavior of grouts is described is this paper and the sensitivity of such parameters to the variation in mixture ingredients is also evaluated. The input parameters of the neural network were the mixture ingredients influencing the rheological behavior of grouts, namely the cement content, fly ash, ground-granulated blast-furnace slag, limestone powder, silica fume, water-binder ratio (w/b), high-range water-reducing admixture, and viscosity-modifying agent (welan gum). The six outputs of the ANN models were the mini-slump, the apparent viscosity at low shear, and the yield stress and plastic viscosity values of the Bingham and modified Bingham models, respectively. The model is based on a multi-layer feed-forward neural network. The details of the proposed ANN with its architecture, training, and validation are presented in this paper. A database of 186 mixtures from eight different studies was developed to train and test the ANN model. The effectiveness of the trained ANN model is evaluated by comparing its responses with the experimental data that were used in the training process. The results show that the ANN model can accurately predict the mini-slump, the apparent viscosity at low shear, the yield stress, and the plastic viscosity values of the Bingham and modified Bingham models of the pseudo-plastic grouts used in the training process. The results can also predict these properties of new mixtures within the practical range of the input variables used in the training with an absolute error of 2%, 0.5%, 8%, 4%, 2%, and 1.6%, respectively. The sensitivity of the ANN model showed that the trend data obtained by the models were in good agreement with the actual experimental results, demonstrating the effect of mixture ingredients on fluidity and the rheological parameters with both the Bingham and modified Bingham models.