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To characterize the cross-sectional relationship between white matter and reading, we calculated simple, bivariate correlations between Reading Skill and each diffusion metric at the pre-intervention baseline session.
For each diffusion length measurement (planar view, which does not involve sample cleaving), repetitive scans were performed to study the signal decay and compare it to cross-sectional decay as described in the text.
Nanoindentation measurements were carried out across the interdiffusion zone for each diffusion couple, and a correspondence between Er or H and composition is established.
Microstructural analyses by scanning electron microscopy revealed that, for each diffusion couple, an interface separating austenite and martensite was created due to variation of the martensitic transformation temperature at different compositions.
We regard each diffusion item as a distribution of these topics.
Since each diffusion domain is based on the segments of one particular speaker, it is best adapted to that speaker.
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In brief, each diffusion-weighted imaging consisted of a total of 132 near-axial slices acquired with an acceleration factor of 3 (ref. 64), isotropic (1.05 mm3) resolution and coverage of the whole head with a TE of 71.2 ms and with a TR of 7000 ms.
Image distortions and motion artifacts in the DTI dataset were corrected by applying affine alignment of each diffusion-weighted image to the b = 0 image, using FMRIB's Diffusion Toolbox (FSL, version 3.3; www.fmrib.ox.ac.uk/fsl).ac.uk/fsl
Head motion was corrected by registering each diffusion-weighted image to a corresponding image synthesized from a tensor fit to the data (Hagler et al. 2009).
While reviewing each diffusion-weighted image set (cDWI1500, cDWI2000, and cDWI3000) in random order, radiologists identified the location of the index lesion based on its increased signal intensity relative to the background prostate parenchyma.
Eddy current distortions and motion artifacts in the DTI dataset were corrected by applying affine alignment of each diffusion-weighted image to the b = 0 image, using FMRIB's Diffusion Toolbox (FSL, version 3.3; http://www.fmrib.ox.ac.uk/fsl).ac.uk/fsl
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