Role of Surfactants in Carbon Nanotubes Density Gradient Separation

Several strategies aimed at sorting single-walled carbon nanotubes (SWNT) by diameter and/or electronic structure have been developed in recent years. A nondestructive sorting method was recently proposed in which nanotube bundles are dispersed in water-surfactant solutions and submitted to ultracentrifugation in a density gradient. By this method, SWNTs of different diameters are distributed according to their densities along the centrifuge tube. A mixture of two anionic amphiphiles, namely sodium dodecylsulfate (SIDS) and sodium cholate (SC), presented the best performance in discriminating nanotubes by diameter. We present molecular dynamics studies of the water-surfactant-SWNT system. The simulations revealed one aspect of the discriminating power of surfactants: they can actually be attracted toward the interior of the nanotube cage. The binding energies of SDS and SC on the outer nanotube surface are very similar and depend weakly on diameter. The binding inside the tubes, on the contrary, is strongly diameter dependent: SDS fits best inside tubes with diameters ranging from 8 to 9 angstrom, while SC is best accommodated in larger tubes, with diameters in the range 10.5-12 angstrom. The dynamics at room temperature showed that, as the amphiphile moves to the hollow cage, water molecules are dragged together, thereby promoting the nanotube filling. The resulting densities of filled SWNT are in agreement with measured densities.

Longitudinal scaling property of the charge balance function in Au plus Au collisions at root s(NN)=200 GeV

We present measurements of the charge balance function, from the charged particles, for diverse pseudorapidity and transverse momentum ranges in Au + Au collisions at root S(NN) = 200 GeV using the STAR detector at RHIC. We observe that the balance function is boost-invariant within the pseudorapidity coverage vertical bar-1.3, 1.3 vertical bar. The balance function properly scaled by the width of the observed pseudorapidity window does not depend on the position or size of the pseudorapidity window. This scaling property also holds for particles in different transverse momentum ranges. In addition, we find that the width of the balance function decreases monotonically with increasing transverse momentum for all centrality classes. (c) 2010 Elsevier B.V. All rights reserved.

Arterial spin labeling of cerebral perfusion territories using a seperate labeling coil

Purpose: To obtain cerebral perfusion territories of the left, the right. and the posterior circulation in humans with high signal-to-noise ratio (SNR) and robust delineation. Materials and Methods: Continuous arterial spin labeling (CASL) was implemented using a dedicated radio frequency (RF) coil. positioned over the neck, to label the major cerebral feeding arteries in humans. Selective labeling was achieved by flow-driven adiabatic fast passage and by tilting the longitudinal labeling gradient about the Y-axis by theta = +/- 60 degrees. Results: Mean cerebral blood flow (CBF) values in gray matter (GM) and white matter (WM) were 74 +/- 13 mL center dot 100 g(-1) center dot minute(-1) and 14 +/- 13 mL center dot 100 g(-1) center dot minute(-1), respectively (N = 14). There were no signal differences between left and right hemispheres when theta = 0 degrees (P > 0.19), indicating efficient labeling of both hemispheres. When theta = +60 degrees, the signal in GM on the left hemisphere, 0.07 +/- 0.06%, was 92% lower than on the right hemisphere. 0.85 +/- 0.30% (P < 1 x 10(-9)). while for theta = -60 degrees, the signal in the right hemisphere. 0.16 +/- 0.13%, was 82% lower than on the contralateral side. 0.89 +/- 0.22% (P < 1 x 10(-10)). Similar attenuations were obtained in WM. Conclusion: Clear delineation of the left and right cerebral perfusion territories was obtained, allowing discrimination of the anterior and posterior circulation in each hemisphere.

Local influence in estimating equations

Local influence diagnostics based on estimating equations as the role of a gradient vector derived from any fit function are developed for repeated measures regression analysis. Our proposal generalizes tools used in other studies (Cook, 1986: Cadigan and Farrell, 2002), considering herein local influence diagnostics for a statistical model where estimation involves an estimating equation in which all observations are not necessarily independent of each other. Moreover, the measures of local influence are illustrated with some simulated data sets to assess influential observations. Applications using real data are presented. (C) 2010 Elsevier B.V. All rights reserved.