142 resultados para DIFFUSE-SCATTERING
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The mathematical model for diffuse fluorescence spectroscopy/imaging is represented by coupled partial differential equations (PDEs), which describe the excitation and emission light propagation in soft biological tissues. The generic closed-form solutions for these coupled PDEs are derived in this work for the case of regular geometries using the Green's function approach using both zero and extrapolated boundary conditions. The specific solutions along with the typical data types, such as integrated intensity and the mean time of flight, for various regular geometries were also derived for both time-and frequency-domain cases. (C) 2013 Optical Society of America
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The analytical solutions for the coupled diffusion equations that are encountered in diffuse fluorescence spectroscopy/ imaging for regular geometries were compared with the well-established numerical models, which are based on the finite element method. Comparison among the analytical solutions obtained using zero boundary conditions and extrapolated boundary conditions (EBCs) was also performed. The results reveal that the analytical solutions are in close agreement with the numerical solutions, and solutions obtained using EBCs are more accurate in obtaining the mean time of flight data compared to their counterpart. The analytical solutions were also shown to be capable of providing bulk optical properties through a numerical experiment using a realistic breast model. (C) 2013 Optical Society of America
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Purpose: Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. Methods: The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. Results: The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. Conclusions: The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time. (C) 2013 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4792459]
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The scattering of carriers by charged dislocations in semiconductors is studied within the framework of the linearized Boltzmann transport theory with an emphasis on examining consequences of the extreme anisotropy of the cylindrically symmetric scattering potential. A new closed-form approximate expression for the carrier mobility valid for all temperatures is proposed. The ratios of quantum and transport scattering times are evaluated after averaging over the anisotropy in the relaxation time. The value of the Hall scattering factor computed for charged dislocation scattering indicates that there may be a factor of two error in the experimental mobility estimates using the Hall data. An expression for the resistivity tensor when the dislocations are tilted with respect to the plane of transport is derived. Finally, an expression for the isotropic relaxation time is derived when the dislocations are located within the sample with a uniform angular distribution.
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Interconnected Os nanochains consisting of ultrafine particles prepared using a simple procedure yield a coupled surface plasmon peak in the visible region and can be used as substrates for surface enhanced Raman scattering of various analytes.
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Phototaxis is a directed swimming response dependent upon the light intensity sensed by microorganisms. Positive phototaxis denotes motion directed towards the source of light and negative phototaxis is motion directed away from it. In this paper, we investigate the onset of bioconvection in a suspension of anisotropic scattering phototactic algae illuminated by collimated radiation at the top. The basic state of the system is defined by the zero fluid flow and the up and down swimming, caused by the positive and negative phototaxis, is balanced by the diffusion. A comprehensive numerical study of the linear stability is presented with particular emphasis on the forward scattering effect. The onset of bioconvection occurs either via a stationary mode or an oscillatory mode. The transition from a stationary mode to an oscillatory mode or vice versa has been observed as the anisotropic coefficient is varied for certain parameter values. (C) 2012 Elsevier Masson SAS. All rights reserved.
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A new approach that can easily incorporate any generic penalty function into the diffuse optical tomographic image reconstruction is introduced to show the utility of nonquadratic penalty functions. The penalty functions that were used include quadratic (l(2)), absolute (l(1)), Cauchy, and Geman-McClure. The regularization parameter in each of these cases was obtained automatically by using the generalized cross-validation method. The reconstruction results were systematically compared with each other via utilization of quantitative metrics, such as relative error and Pearson correlation. The reconstruction results indicate that, while the quadratic penalty may be able to provide better separation between two closely spaced targets, its contrast recovery capability is limited, and the sparseness promoting penalties, such as l(1), Cauchy, and Geman-McClure have better utility in reconstructing high-contrast and complex-shaped targets, with the Geman-McClure penalty being the most optimal one. (C) 2013 Optical Society of America
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Phototaxis is a directed swimming response dependent upon the light intensity sensed by micro-organisms. Positive (negative) phototaxis denotes the motion directed towards (away from) the source of light. Using the phototaxis model of Ghorai, Panda, and Hill ''Bioconvection in a suspension of isotropically scattering phototactic algae,'' Phys. Fluids 22, 071901 (2010)], we investigate two-dimensional phototactic bioconvection in an absorbing and isotropic scattering suspension in the nonlinear regime. The suspension is confined by a rigid bottom boundary, and stress-free top and lateral boundaries. The governing equations for phototactic bioconvection consist of Navier-Stokes equations for an incompressible fluid coupled with a conservation equation for micro-organisms and the radiative transfer equation for light transport. The governing system is solved efficiently using a semi-implicit second-order accurate conservative finite-difference method. The radiative transfer equation is solved by the finite volume method using a suitable step scheme. The resulting bioconvective patterns differ qualitatively from those found by Ghorai and Hill ''Penetrative phototactic bioconvection,'' Phys. Fluids 17, 074101 (2005)] at a higher critical wavelength due to the effects of scattering. The solutions show transition from steady state to periodic oscillations as the governing parameters are varied. Also, we notice the accumulation of micro-organisms in two horizontal layers at two different depths via their mean swimming orientation profile for some governing parameters at a higher scattering albedo. (C) 2013 AIP Publishing LLC.
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Typical image-guided diffuse optical tomographic image reconstruction procedures involve reduction of the number of optical parameters to be reconstructed equal to the number of distinct regions identified in the structural information provided by the traditional imaging modality. This makes the image reconstruction problem less ill-posed compared to traditional underdetermined cases. Still, the methods that are deployed in this case are same as those used for traditional diffuse optical image reconstruction, which involves a regularization term as well as computation of the Jacobian. A gradient-free Nelder-Mead simplex method is proposed here to perform the image reconstruction procedure and is shown to provide solutions that closely match ones obtained using established methods, even in highly noisy data. The proposed method also has the distinct advantage of being more efficient owing to being regularization free, involving only repeated forward calculations. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)
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Bentonite clays are proven to be attractive as buffer and backfill material in high-level nuclear waste repositories around the world. A quick estimation of swelling pressures of the compacted bentonites for different clay-water-electrolyte interactions is essential in the design of buffer and backfill materials. The theoretical studies on the swelling behavior of bentonites are based on diffuse double layer (DDL) theory. To establish theoretical relationship between void ratio and swelling pressure (e versus P), evaluation of elliptic integral and inverse analysis are unavoidable. In this paper, a novel procedure is presented to establish theoretical relationship of e versus P based on the Gouy-Chapman method. The proposed procedure establishes a unique relationship between electric potentials of interacting and non-interacting diffuse clay-water-electrolyte systems. A procedure is, thus, proposed to deduce the relation between swelling pressures and void ratio from the established relation between electric potentials. This approach is simple and alleviates the need for elliptic integral evaluation and also the inverse analysis. Further, application of the proposed approach to estimate swelling pressures of four compacted bentonites, for example, MX 80, Febex, Montigel and Kunigel V1, at different dry densities, shows that the method is very simple and predicts solutions with very good accuracy. Moreover, the proposed procedure provides continuous distributions of e versus P and thus it is computationally efficient when compared with the existing techniques.
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The sparse recovery methods utilize the l(p)-normbased regularization in the estimation problem with 0 <= p <= 1. These methods have a better utility when the number of independent measurements are limited in nature, which is a typical case for diffuse optical tomographic image reconstruction problem. These sparse recovery methods, along with an approximation to utilize the l(0)-norm, have been deployed for the reconstruction of diffuse optical images. Their performancewas compared systematically using both numerical and gelatin phantom cases to show that these methods hold promise in improving the reconstructed image quality.
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Prevention or suppression of protein aggregation is of great importance in the context of protein storage, transportation and delivery. Traditionally chaperones or other chemically active agents are used to stop or diffuse native protein aggregation. We have used gold nanoparticles to prevent thermal aggregation of alcohol dehydrogenase (ADH), a protein that maintains the alcohol level in the liver and stomach. A light-scattering assay has been used to investigate the effect of gold nanoparticles on thermal aggregation of ADH and the result of our study has been summarized in Fig. 1. The scattered light intensity from the solution containing ADH decreases when 45 nm gold nanoparticles are added prior to heating (thermal denaturation) the solution, which indicates prevention of aggregation. The aggregation of the protein is suppressed to the extent of 96% with picomolar concentration of 45 nm gold nanoparticles while micromolar amounts of other proteins and biological substances are necessary to achieve the same effect. The extent varies with the size and the concentration of the gold NPs for the same protein concentration.
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In addition to the chemical nature of the surface, the dimensions of the confining host exert a significant influence on confined protein structures; this results in immense biological implications, especially those concerning the enzymatic activities of the protein. This study probes the structure of hemoglobin (Hb), a model protein, confined inside silica tubes with pore diameters that vary by one order of magnitude (approximate to 20-200 nm). The effect of confinement on the protein structure is probed by comparison with the structure of the protein in solution. Small-angle neutron scattering (SANS), which provides information on protein tertiary and quaternary structures, is employed to study the influence of the tube pore diameter on the structure and configuration of the confined protein in detail. Confinement significantly influences the structural stability of Hb and the structure depends on the Si-tube pore diameter. The high radius of gyration (R-g) and polydispersity of Hb in the 20 nm diameter Si-tube indicates that Hb undergoes a significant amount of aggregation. However, for Si-tube diameters greater or equal to 100 nm, the R-g of Hb is found to be in very close proximity to that obtained from the protein data bank (PDB) reported structure (R-g of native Hb=23.8 angstrom). This strongly indicates that the protein has a preference for the more native-like non-aggregated state if confined inside tubes of diameter greater or equal to 100 nm. Further insight into the Hb structure is obtained from the distance distribution function, p(r), and ab initio models calculated from the SANS patterns. These also suggest that the Si-tube size is a key parameter for protein stability and structure.
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A facile, environmentally friendly approach to synthesize branched Ir nanochain-like structures under mild conditions, using polyfunctional capping molecules in an aqueous medium is reported; the nanostructures exhibit a surface plasmon resonance peak (SPR) in the visible region and serve as an active substrate for surface enhanced Raman scattering studies.
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The sparse estimation methods that utilize the l(p)-norm, with p being between 0 and 1, have shown better utility in providing optimal solutions to the inverse problem in diffuse optical tomography. These l(p)-norm-based regularizations make the optimization function nonconvex, and algorithms that implement l(p)-norm minimization utilize approximations to the original l(p)-norm function. In this work, three such typical methods for implementing the l(p)-norm were considered, namely, iteratively reweighted l(1)-minimization (IRL1), iteratively reweighted least squares (IRLS), and the iteratively thresholding method (ITM). These methods were deployed for performing diffuse optical tomographic image reconstruction, and a systematic comparison with the help of three numerical and gelatin phantom cases was executed. The results indicate that these three methods in the implementation of l(p)-minimization yields similar results, with IRL1 fairing marginally in cases considered here in terms of shape recovery and quantitative accuracy of the reconstructed diffuse optical tomographic images. (C) 2014 Optical Society of America