1,642 research outputs found

    Comparison Of Plasma Parameters Obtained With Planar Probe And Optical Spectrometer

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    A planar probe and an optical spectrometer were employed to analyze some parameters in an inductively coupled plasma (ICP). The analyses were performed in Ar, Ar+SF6 and O2 plasmas at 40 mTorr. Typical probe results indicate an ion current of 10-3 A/cm2 and an electron temperature (high energy tail) between 1-2 eV in measurements at high powers. At low powers a distinct discharge regime is observed, typically with low density (low ion current) and high electron temperature. Even though a quantitative analysis has not been done yet, the optical emission studies also showed the presence of these two regimes. © 2006 The Electrochemical Society.41515524Chen, F.F., (1965) Plasma Diagnostic Techniques, , R. H. Huddlestone and S. L. Leonard, Editors, Academic Press, New YorkSudit, I.D., Chen, F.F., (1994) Plasma Sources Sci. Technol, 3, p. 162Laframboise, J.G., Univ, Toronto Inst (1966) Aerospace Studies Rept, 100Braithwaite, N.S.J., Booth, J.P., Cunge, G., (1996) Plasma Sources Science and Technology, 5, p. 677Boffard, J.B., Lin, C.C., DeJoseph Jr, C.A., (2004) J. Phys. D: Appl. Phys, 37, pp. R143Francis, A., (1997) Appl. Phys. Lett, 71, p. 3796Czerwiec, T., Graves, D.B., (2004) J. Phys. D: Appl. Phys, 37, p. 2827Lieberman, M.A., Lichtenberg, A.J., (1994) Principles of Plasma Discharges and Materials Processing, , New York, WileyChapman, B., (1980) Glow Discharge Processes, , John Wiley and SonsL. Swart and P. Verdonck, in Microelectronics Technology and Devices SBMicro2005, C. Claeys, J. W. Swart, N. I. Morimoto and P. Verdonck, Editors, PV 05-8, p. 254, The Electrochemical Society Proceedings Series, Pennington, NJ (2005

    SMM910193 Supplemental Material - Supplemental material for Outlier robust modeling of survival curves in the presence of potentially time-varying coefficients

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    Supplemental material, SMM910193 Supplemental Material for Outlier robust modeling of survival curves in the presence of potentially time-varying coefficients by Jorne Lionel Biccler, Martin Bøgsted, Stefan Van Aelst and Tim Verdonck in Statistical Methods in Medical Research</p

    A computational study of the hemodynamic impact of open- Versus closed-Cell stent design in carotid artery stenting

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    The aim of this study is to analyze the shape and flow changes of a patient-specific carotid artery after carotid artery stenting (CAS) performed using an open-cell (stent-O) or a closed-cell (stent-C) stent design. First, a stent reconstructed from micro-computed tomography (microCT) is virtually implanted in a left carotid artery reconstructed from CT angiography. Second, an objective analysis of the stent-to-vessel apposition is used to quantify the lumen cross-sectional area and the incomplete stent apposition (ISA). Third, the carotid artery lumen is virtually perfused in order to quantify its resistance to flow and its exposure to atherogenic or thrombogenic hemodynamic conditions. After CAS, the minimum cross-sectional area of the internal carotid artery (ICA) (external carotid artery [ECA]) changes by +54% (-12%) with stent-O and +78% (-17%) with stent-C; the resistance to flow of the ICA (ECA) changes by -21% (+13%) with stent-O and -26% (+18%) with stent-C. Both stent designs suffer from ISA but the malapposed stent area is larger with stent-O than stent-C (29.5 vs. 14.8mm2). The untreated vessel is not exposed to atherogenic flow conditions whereas an area of 67.6mm2 (104.9) occurs with stent-O (stent-C). The area of the stent surface exposed to thrombogenic risk is 5.42mm2 (7.7) with stent-O (stent-C). The computer simulations of stenting in a patient's carotid artery reveal a trade-off between cross-sectional size and flow resistance of the ICA (enlarged and circularized) and the ECA (narrowed and ovalized). Such a trade-off, together with malapposition, atherogenic risk, and thrombogenic risk is stent-design dependent

    How can cells sense the elasticity of a substrate? An analysis using a cell tensegrity model

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    A eukaryotic cell attaches and spreads on substrates, whether it is the extracellular matrix naturally produced by the cell itself, or artificial materials, such as tissue-engineered scaffolds. Attachment and spreading require the cell to apply forces in the nN range to the substrate via adhesion sites, and these forces are balanced by the elastic response of the substrate. This mechanical interaction is one determinant of cell morphology and, ultimately, cell phenotype. In this paper we use a finite element model of a cell, with a tensegrity structure to model the cytoskeleton of actin filaments and microtubules, to explore the way cells sense the stiffness of the substrate and thereby adapt to it. To support the computational results, an analytical 1D model is developed for comparison. We find that (i) the tensegrity hypothesis of the cytoskeleton is sufficient to explain the matrix-elasticity sensing, (ii) cell sensitivity is not constant but has a bell-shaped distribution over the physiological matrix-elasticity range, and (iii) the position of the sensitivity peak over the matrix-elasticity range depends on the cytoskeletal structure and in particular on the F-actin organisation. Our model suggests that F-actin reorganisation observed in mesenchymal stem cells (MSCs) in response to change of matrix elasticity is a structural-remodelling process that shifts the sensitivity peak towards the new value of matrix elasticity. This finding discloses a potential regulatory role of scaffold stiffness for cell differentiation
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