Characterization of spherical particles using high-order neural networks and scanning flow cytometry

We retrieve the radius R, real n and imaginary k parts of the refractive index of homogeneous spherical particles using angular distribution of the light-scattering intensity. To solve the inverse light-scattering problem we use a high-order neural-network technique. The effect of network parameters on optimization is examined. The technique is evaluated for noise-corrupted input data at 0.6 μm<R<10.6 μm, 1.02<n<1.38, and 0<k<0.03. The errors of retrieval for nonabsorbing particles do not exceed 0.05 μm for radius and 0.015 for refractive index. The experimental verification is fulfilled by experimental data retrieved by means of a scanning flow cytometer. The light-scattering profiles of polystyrene beads and spherized red blood cells are processed with the high-order neural networks and a non-linear regression at Mie theory. The parameters retrieved by the high-order neural networks correlate well with the parameters retrieved by the least-square method.     

Resonance phenomena of π-mode forming in multi-element gratings

An analysis of resonances of scattering from multi-element grating formed by a finite number of resonant elements is presented. It has been shown that gratings with three and more elements on its period can support the π-mode. The π-mode of a grating is characterized by the existence of the regions in the vicinity of the grating and along its period where the electromagnetic field has opposite phases. The existence and excitation of the π-mode in finite gratings with resonant cells formed by several scatterers having open cavities have been studied. The particular case of the grating with cells formed by three identical slotted cylinders has been considered in detail. An application of gratings which support the π-mode in electron-vacuum oscillators of millimeter waves for efficient deceleration of electrons and extracting energy from electron beam is discussed.     

Mössbauer studies of EFG of the different57Fe(57Co)-Oxygen configurations in oriented Y−Ba−Cu−O

We have determined the various parameters of the electric field gradient (EFG) for different Fe-oxygen configurations. This was achieved by analyses of a variety of spectra using a procedure which allows fitting of all spectra of oriented 1-2-3 compounds obtained at different tilt angles β simultaneously, taking into account the degree of texture. The use of a point charge model is invalidated because of the high degree of estimated covalence. The Mössbauer parameters are rationalized. The absence of any observed anisotropy of the mean square displacement of the dopant at the Cu(1) site is rather intriguing.     

A Bitangential Interpolation Problem on the Closed Unit Ball for Multipliers of the Arveson Space

We solve a bitangential interpolation problem for contractive multipliers on the Arveson space with an arbitrary interpolating set in the closed unit ball . The solvability criterion is established in terms of positive kernels. The set of all solutions is parametrized by a Redheffer transform. Submitted: February 2, 2002.     

Information processing,memories, and synchronization in chaotic neural network with the time delay

Information processing and two types of memory in an analog neural network model with time delay that produces chaos similar to the human and animal EEGs are considered. There are two levels of information processing in this neural network: the level of individual neurons and the level of the neural network. Similar to the state of brain, the state of chaotic neural network is defined. It is characterized by two types of memories (memory I and memory II) and correlation structure between the neurons. In normal (unperturbed) state, the neural network generates chaotic patterns of averaged neuronal activities (memory I) and patterns of oscillation amplitudes (memory II). In the presence of external stimulation, the activity patterns change, showing changes in both types of memory. As in experiments on stimulation of the brain, the neural network model shows synchronization of neuronal activities due to stimulus measured by Pearson's correlation coefficient. An increase in neural network asymmetry (increase of the neural network excitability) leads to the phenomenon similar to the epilepsy. Modeling of brain injury, Parkinson's disease, and dementia is performed by removing and weakening interneuron connections. In all cases, the chaotic neural network shows a decrease of the degree of chaos and changes in both types of memory similar to those observed in experiments with healthy human subjects and patients with Parkinson's disease and dementia. © 2005 Wiley Periodicals, Inc. Complexity 11:39–52, 2005     

Crystallographic report: Crystal structure of 1‐bromo‐1′‐[(2S)‐N‐(1‐hydroxy‐3‐methylbutane‐2‐yl)]‐ferroceneamide

For the unsymmetrical title compound, 1‐bromo‐1′‐[(2S)‐N‐(1‐hydroxy‐3‐methylbutane‐2‐yl)]‐ferroceneamide, two independent molecules were found in the asymmetric unit. Copyright © 2003 John Wiley & Sons, Ltd.