Study on Granular Dynamics in Vertically Vibrated Beds using Tracking Technique

The study of granular material is of great interest to many researchers in both engineering and science communities. The importance of such a study derives from its complex rheological character and also its significant role in a wide range of industrial applications, such as coal, food, plastics, pharmaceutical, powder metallurgy and mineral processing. A number of recent reports have been focused on the physics of non-cohesive granular material submitted to vertical vibration in either experimental or theoretical approaches. Such a kind of system can be used to separate, mix and dry granular materials in industries. It exhibits different instability behaviour on its surface when under vertical vibration, for example, avalanching, surface fluidization and surface wave, and these phenomena have attracted particular interest of many researchers. However, its fundamental understanding of the instability mechanism is not yet well-understood. This paper is therefore to study the dynamics of granular motion in such a kind of system using Positron Emission Particle Tracking (PEPT), which allows the motion of a single tracer particle to be followed in a non-invasive way. Features of the solids motion such as cycle frequency and dispersion index were investigated via means of authors’ specially-written programmes. Regardless of the surface behaviour, particles are found to travel in rotational movement in horizontal plane. Particle cycle frequency is found to increase strongly with increasing vibration amplitude. Particle dispersion also increased strongly with vibration amplitude. Horizontal dispersion is observed to always exceed vertical dispersion.

Flow patterns in granulating systems

Particle flow patterns were investigated for wet granulation and dry powder mixing in ploughshare mixers using Positron Emission Particle Tracking (PEPT). In a 4-1 mixer, calcium carbonate with mean size 45 mum was granulated using a 50 wt.% solution of glycerol and water as binding fluid, and particle movement was followed using a 600-mum calcium hydroxy-phosphate tracer particle. In a 20-1 mixer, dry powder flow was studied using a 600-mum resin bead tracer particle to simulate the bulk polypropylene powder with mean size 600 mum. Important differences were seen between particle flow patterns for wet and dry systems. Particle speed relative to blade speed was lower in the wet system than in the dry system, with the ratios of average particle speed to blade tip speed for all experiments in the range 0.01-015. In the axial plane, the same particle motion was observed around each blade; this provides a significant advance for modelling flow in ploughshare mixers. For the future, a detailed understanding of the local velocity, acceleration and density variations around a plough blade will reveal the effects of flow patterns in granulating systems on the resultant distribution of granular product attributes such as size, density and strength. (C) 2002 Elsevier Science B.V All rights reserved.

Functional brain maps of Tower of London performance : a positron emission tomography and functional magnetic resonance imaging study

Regional cerebral blood flow (rCBF) and blood oxygenation level-dependent (BOLD) contrasts represent different physiological measures of brain activation. The present study aimed to compare two functional brain imaging techniques (functional magnetic resonance imaging versus [15O] positron emission tomography) when using Tower of London (TOL) problems as the activation task. A categorical analysis (task versus baseline) revealed a significant BOLD increase bilaterally for the dorsolateral prefrontal and inferior parietal cortex and for the cerebellum. A parametric haemodynamic response model (or regression analysis) confirmed a task-difficulty-dependent increase of BOLD and rCBF for the cerebellum and the left dorsolateral prefrontal cortex. In line with previous studies, a task-difficulty-dependent increase of left-hemispheric rCBF was also detected for the premotor cortex, cingulate, precuneus, and globus pallidus. These results imply consistency across the two neuroimaging modalities, particularly for the assessment of prefrontal brain function when using a parametric TOL adaptation.

Clinical application of biomarkers in prostate cancer in men with metabolic syndrome project: Prostate Specific Membrane Antigen (PSMA) Positron Emission Tomography (PET) in diagnosing localised prostate cancer

Localised prostate cancer is a heterogenous disease and a multi-modal approach is required to accurately diagnose and stage the disease. Whilst the use of magnetic resonance imaging (MRI) has become more common, small volume and multi-focal disease are oft en diffi cult to characterise. Prostate specifi c membrane antigen is a cell surface protein, which is expressed in nearly all prostate cancer cells. Its expression is signifi cantly higher in high grade prostate cancer cells. In this study, we compare multi-parametric magnetic resonance imaging and 68-Gallinium-PSMA PET with whole-mount pathology of the prostate to evaluate the applicability of multiparameteric (MP) MRI and 68Ga-PSMA PET in detecting and locating tumour foci in patients with localised prostate cancer.

Measurements of the top-quark mass using charged particle tracking

We present three measurements of the top-quark mass in the lepton plus jets channel with approximately 1.9 fb-1 of integrated luminosity collected with the CDF II detector using quantities with minimal dependence on the jet energy scale. One measurement exploits the transverse decay length of b-tagged jets to determine a top-quark mass of 166.9+9.5-8.5 (stat) +/- 2.9 (syst) GeV/c2, and another the transverse momentum of electrons and muons from W-boson decays to determine a top-quark mass of 173.5+8.8-8.9 (stat) +/- 3.8 (syst) GeV/c2. These quantities are combined in a third, simultaneous mass measurement to determine a top-quark mass of 170.7 +/- 6.3 (stat) +/- 2.6 (syst) GeV/c2.

Measurements of the top-quark mass using charged particle tracking

We present three measurements of the top-quark mass in the lepton plus jets channel with approximately 1.9 fb-1 of integrated luminosity collected with the CDF II detector using quantities with minimal dependence on the jet energy scale. One measurement exploits the transverse decay length of b-tagged jets to determine a top-quark mass of 166.9+9.5-8.5 (stat) +/- 2.9 (syst) GeV/c2, and another the transverse momentum of electrons and muons from W-boson decays to determine a top-quark mass of 173.5+8.8-8.9 (stat) +/- 3.8 (syst) GeV/c2. These quantities are combined in a third, simultaneous mass measurement to determine a top-quark mass of 170.7 +/- 6.3 (stat) +/- 2.6 (syst) GeV/c2.

Image reconstruction by inhomogeneous diffusion for positron emission tomography

In positron emission tomography (PET), image reconstruction is a demanding problem. Since, PET image reconstruction is an ill-posed inverse problem, new methodologies need to be developed. Although previous studies show that incorporation of spatial and median priors improves the image quality, the image artifacts such as over-smoothing and streaking are evident in the reconstructed image. In this work, we use a simple, yet powerful technique to tackle the PET image reconstruction problem. Proposed technique is based on the integration of Bayesian approach with that of finite impulse response (FIR) filter. A FIR filter is designed whose coefficients are determined based on the surface diffusion model. The resulting reconstructed image is iteratively filtered and fed back to obtain the new estimate. Experiments are performed on a simulated PET system. The results show that the proposed approach is better than recently proposed MRP algorithm in terms of image quality and normalized mean square error.

A flame particle tracking analysis of turbulence-chemistry interaction in hydrogen-air premixed flames

Interactions of turbulence, molecular transport, and energy transport, coupled with chemistry play a crucial role in the evolution of flame surface geometry, propagation, annihilation, and local extinction/re-ignition characteristics of intensely turbulent premixed flames. This study seeks to understand how these interactions affect flame surface annihilation of lean hydrogen-air premixed turbulent flames. Direct numerical simulations (DNSs) are conducted at different parametric conditions with a detailed reaction mechanism and transport properties for hydrogen-air flames. Flame particle tracking (FPT) technique is used to follow specific flame surface segments. An analytical expression for the local displacement flame speed (S-d) of a temperature isosurface is considered, and the contributions of transport, chemistry, and kinematics on the displacement flame speed at different turbulence-flame interaction conditions are identified. In general, the displacement flame speed for the flame particles is found to increase with time for all conditions considered. This is because, eventually all flame surfaces and their resident flame particles approach annihilation by reactant island formation at the end of stretching and folding processes induced by turbulence. Statistics of principal curvature evolving in time, obtained using FPT, suggest that these islands are ellipsoidal on average enclosing fresh reactants. Further examinations show that the increase in S-d is caused by the increased negative curvature of the flame surface and eventual homogenization of temperature gradients as these reactant islands shrink due to flame propagation and turbulent mixing. Finally, the evolution of the normalized, averaged, displacement flame speed vs. stretch Karlovitz number are found to collapse on a narrow band, suggesting that a unified description of flame speed dependence on stretch rate may be possible in the Lagrangian description. (C) 2015 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Static and dynamic errors in particle tracking microrheology.

Particle tracking techniques are often used to assess the local mechanical properties of cells and biological fluids. The extracted trajectories are exploited to compute the mean-squared displacement that characterizes the dynamics of the probe particles. Limited spatial resolution and statistical uncertainty are the limiting factors that alter the accuracy of the mean-squared displacement estimation. We precisely quantified the effect of localization errors in the determination of the mean-squared displacement by separating the sources of these errors into two separate contributions. A "static error" arises in the position measurements of immobilized particles. A "dynamic error" comes from the particle motion during the finite exposure time that is required for visualization. We calculated the propagation of these errors on the mean-squared displacement. We examined the impact of our error analysis on theoretical model fluids used in biorheology. These theoretical predictions were verified for purely viscous fluids using simulations and a multiple-particle tracking technique performed with video microscopy. We showed that the static contribution can be confidently corrected in dynamics studies by using static experiments performed at a similar noise-to-signal ratio. This groundwork allowed us to achieve higher resolution in the mean-squared displacement, and thus to increase the accuracy of microrheology studies.

The neural basis of naming impairments in Alzheimer's disease revealed through positron emission tomography.

The naming impairments in Alzheimer's disease (AD) have been attributed to a variety of cognitive processing deficits, including impairments in semantic memory, visual perception, and lexical access. To further understand the underlying biological basis of the naming failures in AD, the present investigation examined the relationship of various classes of naming errors to regional brain measures of cerebral glucose metabolism as measured with 18 F-Fluoro-2-deoxyglucose (FDG) and positron emission tomography (PET). Errors committed on a visual naming test were categorized according to a cognitive processing schema and then examined in relationship to metabolism within specific brain regions. The results revealed an association of semantic errors with glucose metabolism in the frontal and temporal regions. Language access errors, such as circumlocutions, and word blocking nonresponses were associated with decreased metabolism in areas within the left hemisphere. Visuoperceptive errors were related to right inferior parietal metabolic function. The findings suggest that specific brain areas mediate the perceptual, semantic, and lexical processing demands of visual naming and that visual naming problems in dementia are related to dysfunction in specific neural circuits.