Aggregation behavior of amphiphilic D-pi-A molecules bearing recognition group

Aggregation behavior of two amphiphilic D-pi -A molecules bearing barbituric acid as both recogniton group and electron-drawing substituent, 5-(4-dodecyl oxybenzylidene)-(1H, 3H)-2,4,6-pyrimidine trione (PB12) and 5-(4-N,N-didodecyl aminobenzylidene)-(1H,3H)-2,4,6-pyrimidine trione (AB(12)) was studied by UV-visible, fluorescence, and surface voltaic spectroscopies (SPS). The experimental results indicate that PB12 tends to form J-aggregate and AB(12) tends to form H-aggregate under increasing concentration. An intramolecular twisted charge transfer (TICT) emission around 500 nm is observed when J-aggregate is formed between PB12 molecules, and an excimer emission around 600 nm is observed when H-aggregate is formed between AB(12) molecules.

Electrochemical and spectroscopic study of vitamin D-2 by in situ thin layer CD spectroelectrochemistry

The electrooxidation of vitamin D-2 (VD2) was studied by cyclic voltammetry and in situ circular dichroic (CD) spectroelectrochemistry for the first time, The mechanism of electrooxidation and some useful kinetic and adsorption parameters were obtained. The results showed that the oxidation of VD2 in ethanol solution is an irreversible diffusion controlled process following a weak adsorption of the electroinactive product at a glassy carbon electrode, which blocks the electrochemical reaction. The electrooxidation occurs mainly at the triene moieties of the VD2 molecule. The CD spectroelectrochemical data were treated by the double logarithm method together with nonlinear regression, from which the formal potential E-0 = 1.08 V, alphan = 0.245, the standard electrochemical rate constant k(0) = 4.30( +/- 0.58) x 10(-4) cm s(-1) and the adsorption constant beta = 1.77(+/- 0.25) were obtained. (C) 2001 Elsevier Science B.V. All rights reserved.

The channel behavior of gramicidin D in the self-assembled monolayer

It was found for the first time that gramicidin D (GD) molecules can be incorporated into the ODM monolayer which is self-assembled on the surface of the gold electrode and form monovalent cation channels.

Electrochemical study of gramicidin D forming ion-permeable channels in the bilayer lipid membranes

Gramicidin within the lipid bilayer matrix is a well-known channel-forming polypeptide, but the mechanism of the ions across the membrane induced by gramicidin is not well understood. We found that at very low concentration of gramicidin in a bilayer lipid membrane, the channel behavior was controlled by the voltage applied across the membrane. When the voltage is higher than 75 mV, the channel is closing, while lower than 75 mV, the channel is opening. But when the concentration of the gramicidin in the BLMs is high, the channel behavior is changed into voltage-independent. (C) 1998 Elsevier Science Ltd. All rights reserved.

ON THE ANALYSIS OF THE END-NOTCHED FLEXURE SPECIMEN FOR MEASURING MODE-II FRACTURE-TOUGHNESS OF COMPOSITE-MATERIALS

This paper deals with the correction of mode II strain energy release rate, G(II), of composite laminates measured with the end-notched flexure (ENF) specimen. A derivation is given of the expressions for compliance and strain energy release rate, in whic

Electrons in feldspar II: a consideration of the influence of conduction band-tail states on luminescence processes

Poolton, Nigel; Ozanyan, K.B.; Wallinga, J.; Murray, A.S., (2002) 'Electrons in feldspar II: a consideration of the influence of conduction band-tail states on luminescence processes', Physics and Chemistry of Minerals 29(3) pp.217-225 RAE2008

A Self-Organizing Neural Network for Learning a Body-Centered Invariant Representation of 3-D Target Position

This paper describes a self-organizing neural network that rapidly learns a body-centered representation of 3-D target positions. This representation remains invariant under head and eye movements, and is a key component of sensory-motor systems for producing motor equivalent reaches to targets (Bullock, Grossberg, and Guenther, 1993).

Neural Representations for Sensory-Motor Control, III: Learning a Body-Centered Representation of 3-D Target Position

A neural model is described of how the brain may autonomously learn a body-centered representation of 3-D target position by combining information about retinal target position, eye position, and head position in real time. Such a body-centered spatial representation enables accurate movement commands to the limbs to be generated despite changes in the spatial relationships between the eyes, head, body, and limbs through time. The model learns a vector representation--otherwise known as a parcellated distributed representation--of target vergence with respect to the two eyes, and of the horizontal and vertical spherical angles of the target with respect to a cyclopean egocenter. Such a vergence-spherical representation has been reported in the caudal midbrain and medulla of the frog, as well as in psychophysical movement studies in humans. A head-centered vergence-spherical representation of foveated target position can be generated by two stages of opponent processing that combine corollary discharges of outflow movement signals to the two eyes. Sums and differences of opponent signals define angular and vergence coordinates, respectively. The head-centered representation interacts with a binocular visual representation of non-foveated target position to learn a visuomotor representation of both foveated and non-foveated target position that is capable of commanding yoked eye movementes. This head-centered vector representation also interacts with representations of neck movement commands to learn a body-centered estimate of target position that is capable of commanding coordinated arm movements. Learning occurs during head movements made while gaze remains fixed on a foveated target. An initial estimate is stored and a VOR-mediated gating signal prevents the stored estimate from being reset during a gaze-maintaining head movement. As the head moves, new estimates arc compared with the stored estimate to compute difference vectors which act as error signals that drive the learning process, as well as control the on-line merging of multimodal information.