122 resultados para membrane computing


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The smooth DMS-FEM, recently proposed by the authors, is extended and applied to the geometrically nonlinear and ill-posed problem of a deformed and wrinkled/slack membrane. A key feature of this work is that three-dimensional nonlinear elasticity equations corresponding to linear momentum balance, without any dimensional reduction and the associated approximations, directly serve as the membrane governing equations. Domain discretization is performed with triangular prism elements and the higher order (C1 or more) interelement continuity of the shape functions ensures that the errors arising from possible jumps in the first derivatives of the conventional C0 shape functions do not propagate because the ill-conditioned tangent stiffness matrices are iteratively inverted. The present scheme employs no regularization and exhibits little sensitivity to h-refinement. Although the numerically computed deformed membrane profiles do show some sensitivity to initial imperfections (nonplanarity) in the membrane profile needed to initiate transverse deformations, the overall patterns of the wrinkles and the deformed shapes appear to be less so. Finally, the deformed profiles, computed through the DMS FEM-based weak formulation, are compared with those obtained through an experiment on an ultrathin Kapton membrane, wherein wrinkles form because of the applied boundary displacement conditions. Comparisons with a reported experiment on a rectangular membrane are also provided. These exercises lend credence to the feasibility of the DMS FEM-based numerical route to computing post-wrinkled membrane shapes. Copyright (c) 2012 John Wiley & Sons, Ltd.

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Carbon nanotubes dispersed in polymer matrix have been aligned in the form of fibers and interconnects and cured electrically and by UV light. Conductivity and effective semiconductor tunneling against reverse to forward bias field have been designed to have differentiable current-voltage response of each of the fiber/channel. The current-voltage response is a function of the strain applied to the fibers along axial direction. Biaxial and shear strains are correlated by differentiating signals from the aligned fibers/channels. Using a small doping of magnetic nanoparticles in these composite fibers, magneto-resistance properties are realized which are strong enough to use the resulting magnetostriction as a state variable for signal processing and computing. Various basic analog signal processing tasks such as addition, convolution and filtering etc. can be performed. These preliminary study shows promising application of the concept in combined analog-digital computation in carbon nanotube based fibers. Various dynamic effects such as relaxation, electric field dependent nonlinearities and hysteresis on the output signals are studied using experimental data and analytical model.

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Densely packed nanoparticles distributed in a stable and robust thin film is a highly preferred system for utilizing the various applications of nanoparticles. Here, we report covalent bond mediated layer-by-layer (LbL) self-assembled thin films of nanoparticles embedded in polymer membrane. Polymer with complementary functional group is utilized for fabrication of thin film via covalent bonding. UV-visible spectroscopy, atomic force microscopy (AFM) and scanning electron microscopy (SEM) were used to monitor the growth of LbL thin film. Subsequently, the composite thin film is used for catalysis of an organic electron transfer reaction of p-nitrophenol to p-aminophenol by sodium borohydride. The catalytic activity of these composite films is assayed multiple times, proving its applicability as a catalyst. The kinetic data obtained by monitoring reduction of p-nitrophenol suggest that the reaction rates are directly related to the sizes of the nanoparticle and porosity of the membrane.

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The Reeb graph of a scalar function tracks the evolution of the topology of its level sets. This paper describes a fast algorithm to compute the Reeb graph of a piecewise-linear (PL) function defined over manifolds and non-manifolds. The key idea in the proposed approach is to maximally leverage the efficient contour tree algorithm to compute the Reeb graph. The algorithm proceeds by dividing the input into a set of subvolumes that have loop-free Reeb graphs using the join tree of the scalar function and computes the Reeb graph by combining the contour trees of all the subvolumes. Since the key ingredient of this method is a series of union-find operations, the algorithm is fast in practice. Experimental results demonstrate that it outperforms current generic algorithms by a factor of up to two orders of magnitude, and has a performance on par with algorithms that are catered to restricted classes of input. The algorithm also extends to handle large data that do not fit in memory.

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Guanylyl cyclase C (GC-C) is a multidomain, membrane-associated receptor guanylyl cyclase. GC-C is primarily expressed in the gastrointestinal tract, where it mediates fluid-ion homeostasis, intestinal inflammation, and cell proliferation in a cGMP-dependent manner, following activation by its ligands guanylin, uroguanylin, or the heat-stable enterotoxin peptide (ST). GC-C is also expressed in neurons, where it plays a role in satiation and attention deficiency/hyperactive behavior. GC-C is glycosylated in the extracellular domain, and differentially glycosylated forms that are resident in the endoplasmic reticulum (130 kDa) and the plasma membrane (145 kDa) bind the ST peptide with equal affinity. When glycosylation of human GC-C was prevented, either by pharmacological intervention or by mutation of all of the 10 predicted glycosylation sites, ST binding and surface localization was abolished. Systematic mutagenesis of each of the 10 sites of glycosylation in GC-C, either singly or in combination, identified two sites that were critical for ligand binding and two that regulated ST-mediated activation. We also show that GC-C is the first identified receptor client of the lectin chaperone vesicular integral membrane protein, VIP36. Interaction with VIP36 is dependent on glycosylation at the same sites that allow GC-C to fold and bind ligand. Because glycosylation of proteins is altered in many diseases and in a tissue-dependent manner, the activity and/or glycan-mediated interactions of GC-C may have a crucial role to play in its functions in different cell types.

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Bacteria use a number of small basic proteins for organization and compaction of their genomes. By their interaction with DNA, these nucleoid-associated proteins (NAPs) also influence gene expression. Rv3852, a NAP of Mycobacterium tuberculosis, is conserved among the pathogenic and slow-growing species of mycobacteria. Here, we show that the protein predominantly localizes in the cell membrane and that the carboxy-terminal region with the propensity to form a transmembrane helix is necessary for its membrane localization. The protein is involved in genome organization, and its ectopic expression in Mycobacterium smegmatis resulted in altered nucleoid morphology, defects in biofilm formation, sliding motility, and change in apolar lipid profile. We demonstrate its crucial role in regulating the expression of KasA, KasB, and GroEL1 proteins, which are in turn involved in controlling the surface phenotypes in mycobacteria.

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The contour tree is a topological abstraction of a scalar field that captures evolution in level set connectivity. It is an effective representation for visual exploration and analysis of scientific data. We describe a work-efficient, output sensitive, and scalable parallel algorithm for computing the contour tree of a scalar field defined on a domain that is represented using either an unstructured mesh or a structured grid. A hybrid implementation of the algorithm using the GPU and multi-core CPU can compute the contour tree of an input containing 16 million vertices in less than ten seconds with a speedup factor of upto 13. Experiments based on an implementation in a multi-core CPU environment show near-linear speedup for large data sets.

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Bacterial surface polymers play a major role in the adhesion of bacterial cells to solid surfaces. Lipopolysaccharides (LPS) are essential constituents of the cell walls of almost all Gram-negative bacteria. This paper reports the results of the investigations on the role of outer membrane exopolymers (LPS) of the chemolithotroph, Acidithiobacillus ferrooxidans, in adsorption of the cells onto pyrite and chalcopyrite. Optimization of EDTA treatment for removal of LPS from cell surface and the surface characterization of EDTA-treated cells are outlined. There was no change in cell morphology or loss in cell motility upon treatment with upto 0.04 mM EDTA for 1 h. Partial removal of LPS by EDTA treatment resulted in reduced adsorption of the cells on both pyrite and chalcopyrite. The protein profile of the EDTA-extractable fraction showed presence of certain outer membrane proteins indicating that EDTA treatment results in temporary gaps in the outer membrane. Also, specificity towards pyrite compared to chalcopyrite that was exhibited by untreated cells was lost when their exopolymer layers were stripped off, which could be attributed to the role of outer membrane proteins in the mineral-specificity exhibited by the bacteria. (C) 2013 Elsevier B.V. All rights reserved.

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A computationally efficient approach that computes the optimal regularization parameter for the Tikhonov-minimization scheme is developed for photoacoustic imaging. This approach is based on the least squares-QR decomposition which is a well-known dimensionality reduction technique for a large system of equations. It is shown that the proposed framework is effective in terms of quantitative and qualitative reconstructions of initial pressure distribution enabled via finding an optimal regularization parameter. The computational efficiency and performance of the proposed method are shown using a test case of numerical blood vessel phantom, where the initial pressure is exactly known for quantitative comparison. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)

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Delaunay and Gabriel graphs are widely studied geo-metric proximity structures. Motivated by applications in wireless routing, relaxed versions of these graphs known as Locally Delaunay Graphs (LDGs) and Lo-cally Gabriel Graphs (LGGs) have been proposed. We propose another generalization of LGGs called Gener-alized Locally Gabriel Graphs (GLGGs) in the context when certain edges are forbidden in the graph. Unlike a Gabriel Graph, there is no unique LGG or GLGG for a given point set because no edge is necessarily in-cluded or excluded. This property allows us to choose an LGG/GLGG that optimizes a parameter of interest in the graph. We show that computing an edge max-imum GLGG for a given problem instance is NP-hard and also APX-hard. We also show that computing an LGG on a given point set with dilation ≤k is NP-hard. Finally, we give an algorithm to verify whether a given geometric graph G= (V, E) is a valid LGG.

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The amplitude-modulation (AM) and phase-modulation (PM) of an amplitude-modulated frequency-modulated (AM-FM) signal are defined as the modulus and phase angle, respectively, of the analytic signal (AS). The FM is defined as the derivative of the PM. However, this standard definition results in a PM with jump discontinuities in cases when the AM index exceeds unity, resulting in an FM that contains impulses. We propose a new approach to define smooth AM, PM, and FM for the AS, where the PM is computed as the solution to an optimization problem based on a vector interpretation of the AS. Our approach is directly linked to the fractional Hilbert transform (FrHT) and leads to an eigenvalue problem. The resulting PM and AM are shown to be smooth, and in particular, the AM turns out to be bipolar. We show an equivalence of the eigenvalue formulation to the square of the AS, and arrive at a simple method to compute the smooth PM. Some examples on synthesized and real signals are provided to validate the theoretical calculations.

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Pore-forming toxins are known for their ability to efficiently form transmembrane pores which eventually leads to cell lysis. The dynamics of lysis and underlying self-assembly or oligomerization pathways leading to pore formation are incompletely understood. In this manuscript the pore-forming kinetics and lysis dynamics of Cytolysin-A (ClyA) toxins on red blood cells (RBCs) are quantified and compared with experimental lysis data. Lysis experiments are carried out on a fixed mass of RBCs, under isotonic conditions in phosphate-buffered saline, for different initial toxin concentrations ranging from 2.94-14.7 nM. Kinetic models which account for monomer binding, conformation and oligomerization to form the dodecameric ClyA pore complex are developed and lysis is assumed to occur when the number of pores per RBC (n(p)) exceeds a critical number, n(pc). By analysing the model in a sublytic regime (n(p) < n(pc)) the number of pores per RBC to initiate lysis is found to lie between 392 and 768 for the sequential oligomerization mechanism and between 5300 and 6300 for the non-sequential mechanism. Rupture rates which are first order in the number of RBCs are seen to provide the best agreement with the lysis experiments. The time constants for pore formation are estimated to lie between 1 and 20 s and monomer conformation time scales were found to be 2-4 times greater than the oligomerization times. Cell rupture takes places in 100s of seconds, and occurs predominantly with a steady number of pores ranging from 515 to 11 000 on the RBC surface for the sequential mechanism. Both the sequential irreversible and non-sequential kinetics provide similar predictions of the hemoglobin release dynamics, however the hemoglobin released as a function of the toxin concentration was accurately captured only with the sequential model. Each mechanism develops a distinct distribution of mers on the surface, providing a unique experimentally observable fingerprint to identify the underlying oligomerization pathways. Our study offers a method to quantify the extent and dynamics of lysis which is an important aspect of developing novel drug and gene delivery strategies based on pore-forming toxins.