Dielectric relaxation of a composite with tungsten nano-layered spherical filler particles

The thickness and conductivity of a surface coating on filler particles in a composite material are critical parameters in controlling the frequency at which dielectric relaxation occurs. In this paper, experimental results are presented for composites formed from tungsten-coated glass microbubbles, embedded in a matrix of paraffin wax. The tungsten coating is of the order of 10 nm thick. There is an outer coating of alumina, a few nm thick, to prevent oxidation of the tungsten and to prevent the formation of conducting pathways in the composite. Dielectric relaxation is observed at around 10 GHz. A remarkable feature of the system is the way in which the relaxation frequency is shifted, by approximately six decades, from the calculated value for a similar composite formed with solid tungsten filler particles (/spl ap/10/sup 16/ Hz). This shift is attributed to the geometrical confinement of the conductor within a thin shell, and to the reduction in conductivity of the thin tungsten layer when compared with the conductivity of bulk tungsten.This is a manuscript of a proceeding published as Bowler, N., I. J. Youngs, K. P. Lymer, and S. Hussain. "Dielectric relaxation of a composite with tungsten nano-layered spherical filler particles." In The 17th Annual Meeting of the IEEE Lasers and Electro-Optics Society, 2004. LEOS 2004., pp. 381-384. IEEE, 2004. DOI: 10.1109/CEIDP.2004.1364267. Copyright 2004 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Posted with permission

Power calculations for multicenter imaging studies controlled by the false discovery rate.

Magnetic resonance imaging (MRI) is widely used in brain imaging research (neuroimaging) to explore structural and functional changes across dispersed neural networks visible only via multisubject experiments. Multicenter investigations are an effective way to increase recruitment rates. This article describes image-based power calculations for a two-group, cross-sectional design specified by the mean effect size and its standard error, sample size, false discovery rate (FDR), and size of the network (i.e., proportion of image locations) that truly demonstrates an effect. Minimum sample size (for fixed effect size) and the minimum effect size (for fixed sample size) are calculated by specifying the acceptable power threshold. Within-center variance was estimated in five participating centers by repeat MRI scanning of 12 healthy participants from whom distributions of gray matter were estimated. The effect on outcome measures when varying FDR and the proportion of true positives is presented. Their spatial patterns reflect within-center variance, which is consistent across centers. Sample sizes 3-6 times larger are needed when detecting effects in subcortical regions compared to the neocortex. Hypothesized multicenter studies of patients with first episode psychosis and control participants were simulated with varying proportions of the cohort recruited at each center. There is little penalty to sample size for recruitment at five centers compared to the center with the lowest variance alone. At 80% power 80 participants per group are required to observe differences in gray matter in high variance regions

The Neuro/PsyGRID calibration experiment: identifying sources of variance and bias in multicenter MRI studies.

Calibration experiments precede multicenter trials to identify potential sources of variance and bias. In support of future imaging studies of mental health disorders and their treatment, the Neuro/PsyGRID consortium commissioned a calibration experiment to acquire functional and structural MRI from twelve healthy volunteers attending five centers on two occasions. Measures were derived of task activation from a working memory paradigm, fractal scaling (Hurst exponent) from resting fMRI, and grey matter distributions from T(1) -weighted sequences. At each intracerebral voxel a fixed-effects analysis of variance estimated components of variance corresponding to factors of center, subject, occasion, and within-occasion order, and interactions of center-by-occasion, subject-by-occasion, and center-by-subject, the latter (since there is no intervention) a surrogate of the expected variance of the treatment effect standard error across centers. A rank order test of between-center differences was indicative of crossover or noncrossover subject-by-center interactions. In general, factors of center, subject and error variance constituted >90% of the total variance, whereas occasion, order, and all interactions were generally <5%. Subject was the primary source of variance (70%-80%) for grey-matter, with error variance the dominant component for fMRI-derived measures. Spatially, variance was broadly homogenous with the exception of fractal scaling measures which delineated white matter, related to the flip angle of the EPI sequence. Maps of P values for the associated F-tests were also derived. Rank tests were highly significant indicating the order of measures across centers was preserved. In summary, center effects should be modeled at the voxel-level using existing and long-standing statistical recommendations