MEASUREMENT OF SOLID SLURRY FLOW VIA CORRELATION OF ELECTROMAGNETIC FLOW METER, ELECTRICAL RESISTANCE TOMOGRAPHY AND MECHANISTIC MODELLING

The study presented here was carried out to obtain the actual solids flow rate by the combination of electrical resistance tomography and electromagnetic flow meter. A new in-situ measurement method based on measurements of the Electromagnetic Flow Meters (EFM) and Electrical Resistance Tomography (ERT) to study the flow rates of individual phases in a vertical flow was proposed. The study was based on laboratory experiments that were carried out with a 50 mm vertical flow rig for a number of sand concentrations and different mixture velocities. A range of sand slurries with median particle size from 212 mu m to 355 mu m was tested. The solid concentration by volume covered was 5% and 15%, and the corresponding density of 5% was 1078 kg/m(3) and of 15% was 1238 kg/m(3). The flow velocity was between 1.5 m/s and 3.0 m/s. A total of 6 experimental tests were conducted. The equivalent liquid model was adopted to validate in-situ volumetric solids fraction and calculate the slip velocity. The results show that the ERT technique can be used in conjunction with an electromagnetic flow meter as a way of measurement of slurry flow rate in a vertical pipe flow. However it should be emphasized that the EFM results must be treated with reservation when the flow pattern at the EFM mounting position is a non-homogenous flow. The flow rate obtained by the EFM should be corrected considering the slip velocity and the flow pattern.

Quantifying chaos: practical estimation of the correlation dimension

Be it a physical object or a mathematical model, a nonlinear dynamical system can display complicated aperiodic behavior, or "chaos." In many cases, this chaos is associated with motion on a strange attractor in the system's phase space. And the dimension of the strange attractor indicates the effective number of degrees of freedom in the dynamical system.

In this thesis, we investigate numerical issues involved with estimating the dimension of a strange attractor from a finite time series of measurements on the dynamical system.

Of the various definitions of dimension, we argue that the correlation dimension is the most efficiently calculable and we remark further that it is the most commonly calculated. We are concerned with the practical problems that arise in attempting to compute the correlation dimension. We deal with geometrical effects (due to the inexact self-similarity of the attractor), dynamical effects (due to the nonindependence of points generated by the dynamical system that defines the attractor), and statistical effects (due to the finite number of points that sample the attractor). We propose a modification of the standard algorithm, which eliminates a specific effect due to autocorrelation, and a new implementation of the correlation algorithm, which is computationally efficient.

Finally, we apply the algorithm to chaotic data from the Caltech tokamak and the Texas tokamak (TEXT); we conclude that plasma turbulence is not a low- dimensional phenomenon.

Novel approach for region merging and image segmentation for human-computer interaction

For the purpose of human-computer interaction (HCI), a vision-based gesture segmentation approach is proposed. The technique essentially includes skin color detection and gesture segmentation. The skin color detection employs a skin-color artificial neural network (ANN). To merge and segment the region of interest, we propose a novel mountain algorithm. The details of the approach and experiment results are provided. The experimental segmentation accuracy is 96.25%. (C) 2003 Society of Photo-Optical Instrumentation Engineers.

Analysis of temporal structure in spike trains of visual cortical area MT

The temporal structure of neuronal spike trains in the visual cortex can provide detailed information about the stimulus and about the neuronal implementation of visual processing. Spike trains recorded from the macaque motion area MT in previous studies (Newsome et al., 1989a; Britten et al., 1992; Zohary et al., 1994) are analyzed here in the context of the dynamic random dot stimulus which was used to evoke them. If the stimulus is incoherent, the spike trains can be highly modulated and precisely locked in time to the stimulus. In contrast, the coherent motion stimulus creates little or no temporal modulation and allows us to study patterns in the spike train that may be intrinsic to the cortical circuitry in area MT. Long gaps in the spike train evoked by the preferred direction motion stimulus are found, and they appear to be symmetrical to bursts in the response to the anti-preferred direction of motion. A novel cross-correlation technique is used to establish that the gaps are correlated between pairs of neurons. Temporal modulation is also found in psychophysical experiments using a modified stimulus. A model is made that can account for the temporal modulation in terms of the computational theory of biological image motion processing. A frequency domain analysis of the stimulus reveals that it contains a repeated power spectrum that may account for psychophysical and electrophysiological observations.

Some neurons tend to fire bursts of action potentials while others avoid burst firing. Using numerical and analytical models of spike trains as Poisson processes with the addition of refractory periods and bursting, we are able to account for peaks in the power spectrum near 40 Hz without assuming the existence of an underlying oscillatory signal. A preliminary examination of the local field potential reveals that stimulus-locked oscillation appears briefly at the beginning of the trial.

Dynamics of cell–matrix mechanical interactions in three dimensions

The forces cells apply to their surroundings control biological processes such as growth, adhesion, development, and migration. In the past 20 years, a number of experimental techniques have been developed to measure such cell tractions. These approaches have primarily measured the tractions applied by cells to synthetic two-dimensional substrates, which do not mimic in vivo conditions for most cell types. Many cell types live in a fibrous three-dimensional (3D) matrix environment. While studying cell behavior in such 3D matrices will provide valuable insights for the mechanobiology and tissue engineering communities, no experimental approaches have yet measured cell tractions in a fibrous 3D matrix.

This thesis describes the development and application of an experimental technique for quantifying cellular forces in a natural 3D matrix. Cells and their surrounding matrix are imaged in three dimensions with high speed confocal microscopy. The cell-induced matrix displacements are computed from the 3D image volumes using digital volume correlation. The strain tensor in the 3D matrix is computed by differentiating the displacements, and the stress tensor is computed by applying a constitutive law. Finally, tractions applied by the cells to the matrix are computed directly from the stress tensor.

The 3D traction measurement approach is used to investigate how cells mechanically interact with the matrix in biologically relevant processes such as division and invasion. During division, a single mother cell undergoes a drastic morphological change to split into two daughter cells. In a 3D matrix, dividing cells apply tensile force to the matrix through thin, persistent extensions that in turn direct the orientation and location of the daughter cells. Cell invasion into a 3D matrix is the first step required for cell migration in three dimensions. During invasion, cells initially apply minimal tractions to the matrix as they extend thin protrusions into the matrix fiber network. The invading cells anchor themselves to the matrix using these protrusions, and subsequently pull on the matrix to propel themselves forward.

Lastly, this thesis describes a constitutive model for the 3D fibrous matrix that uses a finite element (FE) approach. The FE model simulates the fibrous microstructure of the matrix and matches the cell-induced matrix displacements observed experimentally using digital volume correlation. The model is applied to predict how cells mechanically sense one another in a 3D matrix. It is found that cell-induced matrix displacements localize along linear paths. These linear paths propagate over a long range through the fibrous matrix, and provide a mechanism for cell-cell signaling and mechanosensing. The FE model developed here has the potential to reveal the effects of matrix density, inhomogeneity, and anisotropy in signaling cell behavior through mechanotransduction.

Prevalence and magnitude of body weight and image dissatisfaction among women in dietetics majors

[EN] Some authors have suggested that body weight dissatisfaction may be high in students majoring in dietetics. Therefore, this study was conducted to examine the extent of body weight and image dissatisfaction in a sample of women in dietetics major. Additionally, predictors of magnitude of body weight dissatisfaction were analyzed. Participants were 62 volunteers with normalweight whose mean age was 21.87±1.89 years old (nonrandom sample). The assessment instruments included anthropometric measurements, a somatomorphic matrix test and an eating disorders inventory (EDI-2). Data were analyzed using SPSS vs. 15.0. A larger proportion of students chose an ideal body weight lower than actual weight (67.7%) and body image with less body fat and more muscle mass than actual values (56.4%). The magnitude of body weight dissatisfaction was associated with muscle mass and body fat dissatisfaction, and with the subscale of EDI-2 “body dissatisfaction”. So, from a public health standpoint, we consider important to continue working in this line of research with the aim of better understanding the extent of body weight dissatisfaction in women dietitians, and how this dissatisfaction could interfere with their professional practice.

Reduced deep-tissue image degradation in three-dimensional multiphoton microscopy with concentric two-color two-photon fluorescence excitation

We theoretically demonstrate that enhanced penetration depth in three-dimensional multiphoton microscopy can be achieved using concentric two-color two-photon (C2C2P) fluorescence excitation in which the two excitation beams are separated in space before reaching their common focal spot. Monte Carlo simulation shows that, in comparison with the one-color two-photon excitation scheme, the C2C2P fluorescence microscopy provides a significantly greater penetration depth for imaging into a highly scattering medium. (C) 2008 Optical Society of America.