993 resultados para Interaction parameter
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Curcumin, derived from rhizomes of the Curcuma longa plant, is known to possess a wide range of medicinal properties. We have examined the interaction of curcumin with actin and determined their binding and thermodynamic parameters using isothermal titration calorimetry. Curcumin is weakly fluorescent in aqueous solution, and binding to actin enhances fluorescence several fold with a large blue shift in the emission maximum. Curcumin inhibits microfilament formation, which is similar to its role in inhibiting microtubule formation. We synthesized a series of stable curcumin analogues to examine their affinity for actin and their ability to inhibit actin self-assembly. Results show that curcumin is a ligand with two symmetrical halves, each of which possesses no activity individually. Oxazole, pyrazole, and acetyl derivatives are less effective than curcumin at inhibiting actin self-assembly, whereas a benzylidiene derivative is more effective. Cell biology studies suggest that disorganization of the actin network leads to destabilization of filaments in the presence of curcumin. Molecular docking reveals that curcumin binds close to the cytochalasin binding site of actin. Further molecular dynamics studies reveal a possible allosteric effect in which curcumin binding at the barbed end of actin is transmitted to the pointed end, where conformational changes disrupt interactions with the adjacent actin monomer to interrupt filament formation. Finally, the recognition and binding of actin by curcumin is yet another example of its unique ability to target multiple receptors.
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A finite difference method for a time-dependent singularly perturbed convection-diffusion-reaction problem involving two small parameters in one space dimension is considered. We use the classical implicit Euler method for time discretization and upwind scheme on the Shishkin-Bakhvalov mesh for spatial discretization. The method is analysed for convergence and is shown to be uniform with respect to both the perturbation parameters. The use of the Shishkin-Bakhvalov mesh gives first-order convergence unlike the Shishkin mesh where convergence is deteriorated due to the presence of a logarithmic factor. Numerical results are presented to validate the theoretical estimates obtained.
Bayesian parameter identification in dynamic state space models using modified measurement equations
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When Markov chain Monte Carlo (MCMC) samplers are used in problems of system parameter identification, one would face computational difficulties in dealing with large amount of measurement data and (or) low levels of measurement noise. Such exigencies are likely to occur in problems of parameter identification in dynamical systems when amount of vibratory measurement data and number of parameters to be identified could be large. In such cases, the posterior probability density function of the system parameters tends to have regions of narrow supports and a finite length MCMC chain is unlikely to cover pertinent regions. The present study proposes strategies based on modification of measurement equations and subsequent corrections, to alleviate this difficulty. This involves artificial enhancement of measurement noise, assimilation of transformed packets of measurements, and a global iteration strategy to improve the choice of prior models. Illustrative examples cover laboratory studies on a time variant dynamical system and a bending-torsion coupled, geometrically non-linear building frame under earthquake support motions. (C) 2015 Elsevier Ltd. All rights reserved.
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Quantifying distributional behavior of extreme events is crucial in hydrologic designs. Intensity Duration Frequency (IDF) relationships are used extensively in engineering especially in urban hydrology, to obtain return level of extreme rainfall event for a specified return period and duration. Major sources of uncertainty in the IDF relationships are due to insufficient quantity and quality of data leading to parameter uncertainty due to the distribution fitted to the data and uncertainty as a result of using multiple GCMs. It is important to study these uncertainties and propagate them to future for accurate assessment of return levels for future. The objective of this study is to quantify the uncertainties arising from parameters of the distribution fitted to data and the multiple GCM models using Bayesian approach. Posterior distribution of parameters is obtained from Bayes rule and the parameters are transformed to obtain return levels for a specified return period. Markov Chain Monte Carlo (MCMC) method using Metropolis Hastings algorithm is used to obtain the posterior distribution of parameters. Twenty six CMIP5 GCMs along with four RCP scenarios are considered for studying the effects of climate change and to obtain projected IDF relationships for the case study of Bangalore city in India. GCM uncertainty due to the use of multiple GCMs is treated using Reliability Ensemble Averaging (REA) technique along with the parameter uncertainty. Scale invariance theory is employed for obtaining short duration return levels from daily data. It is observed that the uncertainty in short duration rainfall return levels is high when compared to the longer durations. Further it is observed that parameter uncertainty is large compared to the model uncertainty. (C) 2015 Elsevier Ltd. All rights reserved.
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In the family of iron-based superconductors, LaFeAsO-type materials possess the simplest electronic structure due to their pronounced two-dimensionality. And yet they host superconductivity with the highest transition temperature T-c approximate to 55K. Early theoretical predictions of their electronic structure revealed multiple large circular portions of the Fermi surface with a very good geometrical overlap (nesting), believed to enhance the pairing interaction and thus superconductivity. The prevalence of such large circular features in the Fermi surface has since been associated with many other iron-based compounds and has grown to be generally accepted in the field. In this work we show that a prototypical compound of the 1111-type, SmFe0.92Co0.08AsO, is at odds with this description and possesses a distinctly different Fermi surface, which consists of two singular constructs formed by the edges of several bands, pulled to the Fermi level from the depths of the theoretically predicted band structure by strong electronic interactions. Such singularities dramatically affect the low-energy electronic properties of the material, including superconductivity. We further argue that occurrence of these singularities correlates with the maximum superconducting transition temperature attainable in each material class over the entire family of iron-based superconductors.
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In last 40 years, CeO2 has been found to play a major role in the area of auto exhaust catalysis due to its unique redox properties. Catalytic activity is enhanced when CeO2 is added to the noble metals supported Al2O3 catalysts. Reason for increase in catalytic activity is due to higher dispersion of noble metals in the form of ions in CeO2. This has led to the idea of substitution of noble metal ions in CeO2 lattice acting as adsorption sites instead of nanocrystalline noble metal particles on CeO2. In this article, a brief review of synthesis, structure and catalytic properties of noble metal ions dispersed on CeO2 resulting in noble metal ionic catalysts (NMIC) like Ce1-xMxO2-delta, Ce1-x-yTixMyO2-delta, Ce1-x-yZrxMyO2-delta, Ce1-x-ySnxMyO2-delta and Ce1-x-yFexMyO2-delta (M = Pt, Pd, Rh and Ru) are presented. Substitution of Ti, Zr, Sn and Fe in CeO2 increases oxygen storage capacities (OSC) due to structural distortion, whereas dispersion of noble metal ions in Ti, Zr, Sn and Fe substituted CeO2 supports increase both OSC and catalytic activities. Electronic interaction between noble metal ions and CeO2 in NMICs responsible for higher OSC and higher catalytic activities is discussed. (C) 2015 Published by Elsevier B.V.
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Areca nut consumption has been implicated in the progression of Oral Submucous fibrosis (OSF); an inflammatory precancerous fibrotic condition. Our previous studies have demonstrated the activation of TGF-beta signaling in epithelial cells by areca nut components and also propose a role for epithelial expressed TGF-beta in the pathogenesis of OSF. Although the importance of epithelial cells in the manifestation of OSF has been proposed, the actual effectors are fibroblast cells. However, the role of areca nut and TGF-beta in the context of fibroblast response has not been elucidated. Therefore, to understand their role in the context of fibroblast response in OSF pathogenesis, human gingival fibroblasts (hGF) were treated with areca nut and/or TGF-beta followed by transcriptome profiling. The gene expression profile obtained was compared with the previously published transcriptome profiles of OSF tissues and areca nut treated epithelial cells. The analysis revealed regulation of 4666 and 1214 genes by areca nut and TGF-beta treatment respectively. The expression of 413 genes in hGF cells was potentiated by areca nut and TGF-beta together. Further, the differentially expressed genes of OSF tissues compared to normal tissues overlapped significantly with areca nut and TGF-beta induced genes in epithelial and hGF cells. Several positively enriched pathways were found to be common between OSF tissues and areca nut + TGF-beta treated hGF cells. In concordance, areca nut along with TGF-beta enhanced fibroblast activation as demonstrated by potentiation of alpha SMA, gamma SMA and collagen gel contraction by hGF cells. Furthermore, TGF-beta secreted by areca nut treated epithelial cells influenced fibroblast activation and other genes implicated in fibrosis. These data establish a role for areca nut influenced epithelial cells in OSF progression by activation of fibroblasts and emphasizes the importance of epithelial-mesenchymal interaction in OSF.
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We investigate methods to explore the CP nature of the t (t) over barh coupling at the LHC, focusing on associated production of the Higgs boson with a t (t) over bar pair. We first discuss the constraints implied by low-energy observables and by the Higgs-rate information from available LHC data, emphasizing that they cannot provide conclusive evidence on the nature of this coupling. We then investigate kinematic observables that could probe the t (t) over barh coupling directly, in particular, quantities that can be constructed out of just laboratory-frame kinematics. We define one such observable by exploiting the fact that t (t) over bar spin correlations do also carry information about the CP nature of the t (t) over barh coupling. Finally, we introduce a CP-odd quantity and a related asymmetry, able to probe CP violation in the t (t) over barh coupling and likewise, constructed out of laboratory-frame momenta only.
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Multifrequency atomic force microscopy is a powerful nanoscale imaging and characterization technique that involves excitation of the atomic force microscope (AFM) probe and measurement of its response at multiple frequencies. This paper reports the design, fabrication, and evaluation of AFM probes with a specified set of torsional eigen-frequencies that facilitate enhancement of sensitivity in multifrequency AFM. A general approach is proposed to design the probes, which includes the design of their generic geometry, adoption of a simple lumped-parameter model, guidelines for determination of the initial dimensions, and an iterative scheme to obtain a probe with the specified eigen-frequencies. The proposed approach is employed to design a harmonic probe wherein the second and the third eigen-frequencies are the corresponding harmonics of the first eigen-frequency. The probe is subsequently fabricated and evaluated. The experimentally evaluated eigen-frequencies and associated mode shapes are shown to closely match the theoretical results. Finally, a simulation study is performed to demonstrate significant improvements in sensitivity to the second-and the third-harmonic spectral components of the tip-sample interaction force with the harmonic probe compared to that of a conventional probe.
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For a multilayered specimen, the back-scattered signal in frequency-domain optical-coherence tomography (FDOCT) is expressible as a sum of cosines, each corresponding to a change of refractive index in the specimen. Each of the cosines represent a peak in the reconstructed tomogram. We consider a truncated cosine series representation of the signal, with the constraint that the coefficients in the basis expansion be sparse. An l(2) (sum of squared errors) data error is considered with an l(1) (summation of absolute values) constraint on the coefficients. The optimization problem is solved using Weiszfeld's iteratively reweighted least squares (IRLS) algorithm. On real FDOCT data, improved results are obtained over the standard reconstruction technique with lower levels of background measurement noise and artifacts due to a strong l(1) penalty. The previous sparse tomogram reconstruction techniques in the literature proposed collecting sparse samples, necessitating a change in the data capturing process conventionally used in FDOCT. The IRLS-based method proposed in this paper does not suffer from this drawback.
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Turbulence-transport-chemistry interaction plays a crucial role on the flame surface geometry, local and global reactionrates, and therefore, on the propagation and extinction characteristics of intensely turbulent, premixed flames encountered in LPP gas-turbine combustors. The aim of the present work is to understand these interaction effects on the flame surface annihilation and extinction of lean premixed flames, interacting with near isotropic turbulence. As an example case, lean premixed H-2-air mixture is considered so as to enable inclusion of detailed chemistry effects in Direct Numerical Simulations (DNS). The work is carried out in two phases namely, statistically planar flames and ignition kernel, both interacting with near isotropic turbulence, using the recently proposed Flame Particle Tracking (FPT) technique. Flame particles are surface points residing and commoving with an iso-scalar surface within a premixed flame. Tracking flame particles allows us to study the evolution of propagating surface locations uniquely identified with time. In this work, using DNS and FPT we study the flame speed, reaction rate and transport histories of such flame particles residing on iso-scalar surfaces. An analytical expression for the local displacement flame speed (SO is derived, and the contribution of transport and chemistry on the displacement flame speed is identified. An examination of the results of the planar case leads to a conclusion that the cause of variation in S-d may be attributed to the effects of turbulent transport and heat release rate. In the second phase of this work, the sustenance of an ignition kernel is examined in light of the S-curve. A newly proposed Damkohler number accounting for local turbulent transport and reaction rates is found to explain either the sustenance or otherwise propagation of flame kernels in near isotropic turbulence.
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A mathematical model is developed to simulate the co-transport of viruses and colloids in unsaturated porous media under steady-state flow conditions. The virus attachment to the mobile and immobile colloids is described using a linear reversible kinetic model. Colloid transport is assumed to be decoupled from virus transport; that is, we assume that colloids are not affected by the presence of attached viruses on their surface. The governing equations,are solved numerically using an alternating three-step operator splitting approach. The model is verified by fitting three sets of experimental data published in the literature: (1) Syngouna and Chrysikopoulos (2013) and (2) Walshe et al. (2010), both on the co-transport of viruses and clay colloids under saturated conditions, and (3) Syngouna and Cluysikopoulos (2015) for the co-transport of viruses and clay colloids under unsaturated conditions. We found a good agreement between observed and fitted breakthrough curves (BTCs) under both saturated and unsaturated conditions. Then, the developed model was used to simulate the co-transport of viruses and colloids in porous media under unsaturated conditions, with the aim of understanding the relative importance of various processes on the co-transport of viruses and colloids in unsaturated porous media. The virus retention in porous media in the presence of colloids is greater during unsaturated conditions as compared to the saturated conditions due to: (1) virus attachment to the air-water interface (AWI), and (2) co-deposition of colloids with attached viruses on its surface to the AWL A sensitivity analysis of the model to various parameters showed that the virus attachment to AWI is the most sensitive parameter affecting the BTCs of both free viruses and total mobile viruses and has a significant effect on all parts of the BTC. The free and the total mobile viruses BTCs are mainly influenced by parameters describing virus attachment to the AIM, virus interaction with mobile and immobile colloids, virus attachment to solid-water interface (SWI), and colloid interaction with SWI and AWL The virus BTC is relatively insensitive to parameters describing the maximum adsorption capacity of the AWI for colloids, inlet colloid concentration, virus detachment rate coefficient from the SW!, maximum adsorption capacity of the AWI for viruses and inlet virus concentration. (C) 2015 Elsevier B.V. All rights reserved.
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Naturally formed CdTe/CdS core/shell quantum dot (QD) structures in the presence of surface stabilizing agents have been synthesized by a hydrothermal method. Size and temperature dependent photoluminescence (PL) spectra have been investigated to understand the exciton-phonon interaction, and radiative and nonradiative relaxation of carriers in these QDs. The PL of these aqueous CdTe QDs (3.0-4.8 nm) has been studied in the temperature range 15-300 K. The strength of the exciton-LO-phonon coupling, as reflected in the Huang-Rhys parameter `S' is found to increase from 1.13 to 1.51 with the QD size varying from 4.8 to 3.0 nm. The PL linewidth (FWHM) increases with increase in temperature and is found to have a maximum in the case of QDs of 3.0 nm in size, where the exciton-acoustic phonon coupling coefficient is enhanced to 51 mu eV K-1, compared to the bulk value of 0.72 mu eV K-1. To understand the nonradiative processes, which affect the relaxation of carriers, the integrated PL intensity is observed as a function of temperature. The integrated PL intensity remains constant until 50 K for relatively large QDs (3.9-4.8 nm) beyond which a thermally activated process takes over. Below 150 K, a small activation energy, 45-19 meV, is found to be responsible for the quenching of the PL. Above 150 K, the thermal escape from the dot assisted by scattering with multiple longitudinal optical (LO) phonons is the main mechanism for the fast quenching of the PL. Besides this high temperature quenching, interestingly for relatively smaller size QDs (3.4-3.0 nm), the PL intensity enhances as the temperature increases up to 90-130 K, which is attributed to the emission of carriers from interface/trap states having an activation energy in the range of 6-13 meV.
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Biomolecular recognition underlying drug-target interactions is determined by both binding affinity and specificity. Whilst, quantification of binding efficacy is possible, determining specificity remains a challenge, as it requires affinity data for multiple targets with the same ligand dataset. Thus, understanding the interaction space by mapping the target space to model its complementary chemical space through computational techniques are desirable. In this study, active site architecture of FabD drug target in two apicomplexan parasites viz. Plasmodium falciparum (PfFabD) and Toxoplasma gondii (TgFabD) is explored, followed by consensus docking calculations and identification of fifteen best hit compounds, most of which are found to be derivatives of natural products. Subsequently, machine learning techniques were applied on molecular descriptors of six FabD homologs and sixty ligands to induce distinct multivariate partial-least square models. The biological space of FabD mapped by the various chemical entities explain their interaction space in general. It also highlights the selective variations in FabD of apicomplexan parasites with that of the host. Furthermore, chemometric models revealed the principal chemical scaffolds in PfFabD and TgFabD as pyrrolidines and imidazoles, respectively, which render target specificity and improve binding affinity in combination with other functional descriptors conducive for the design and optimization of the leads.
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Using polydispersity index as an additional order parameter we investigate freezing/melting transition of Lennard-Jones polydisperse systems (with Gaussian polydispersity in size), especially to gain insight into the origin of the terminal polydispersity. The average inherent structure (IS) energy and root mean square displacement (RMSD) of the solid before melting both exhibit quite similar polydispersity dependence including a discontinuity at solid-liquid transition point. Lindemann ratio, obtained from RMSD, is found to be dependent on temperature. At a given number density, there exists a value of polydispersity index (delta (P)) above which no crystalline solid is stable. This transition value of polydispersity(termed as transition polydispersity, delta (P) ) is found to depend strongly on temperature, a feature missed in hard sphere model systems. Additionally, for a particular temperature when number density is increased, delta (P) shifts to higher values. This temperature and number density dependent value of delta (P) saturates surprisingly to a value which is found to be nearly the same for all temperatures, known as terminal polydispersity (delta (TP)). This value (delta (TP) similar to 0.11) is in excellent agreement with the experimental value of 0.12, but differs from hard sphere transition where this limiting value is only 0.048. Terminal polydispersity (delta (TP)) thus has a quasiuniversal character. Interestingly, the bifurcation diagram obtained from non-linear integral equation theories of freezing seems to provide an explanation of the existence of unique terminal polydispersity in polydisperse systems. Global bond orientational order parameter is calculated to obtain further insights into mechanism for melting.