905 resultados para root mean square roughness


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Proline plays an important role in the secondary structure of proteins. In the pursuit of understanding its structural role, Proline containing helices with constraints have been studied by employing molecular dynamics (MD) technique. In the present study, the constraint introduced is a threonine residue, whose sidechain has intramolecular hydrogen bond interaction with the backbone oxygen atom. The three systems that have been chosen for characterization are: (1) Ace-(Ala)12−Thr-Pro-(Ala)10−NHMe, (2) Ace-(Ala)13-Pro-Ala-Thr- (Ala)8-NHMe and (3) Ace-(Ala)13-Pro-(Ala)3-Thr-(Ala)6-NHMe. The equilibrium structures and structural transitions have been identified by monitoring the backbone dihedral angles, bend related parameters and the hydrogen bond interactions. The MD averages and root mean square (r.m.s.) fluctuations are compared and discussed. Energy minimization has been carried out on selected MD simulated points in order to analyze the characteristics of different conformations.

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Normal mode sound propagation in an isovelocity ocean with random narrow-band surface waves is considered, assuming the root-mean-square wave height to be small compared to the acoustic wavelength. Nonresonant interaction among the normal modes is studied straightforward perturbation technique. The more interesting case of resonant interaction is investigated using the method of multiple scales to obtain a pair of stochastic coupled amplitude equations which are solved using the Peano-Baker expansion technique. Equations for the spatial evolution of the first and second moments of the mode amplitudes are also derived and solved. It is shown that, irrespective of the initial conditions, the mean values of the mode amplitudes tend to zero asymptotically with increasing range, the mean-square amplitudes tend towards a state of equipartition of energy, and the total energy of the modes is conserved.

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The catalytic conversion of adenosine triphosphate (ATP) and adenosine monophosphate (AMP) to adenosine diphosphate (ADP) by adenylate kinase (ADK) involves large amplitude, ligand induced domain motions, involving the opening and the closing of ATP binding domain (LID) and AMP binding domain (NMP) domains, during the repeated catalytic cycle. We discover and analyze an interesting dynamical coupling between the motion of the two domains during the opening, using large scale atomistic molecular dynamics trajectory analysis, covariance analysis, and multidimensional free energy calculations with explicit water. Initially, the LID domain must open by a certain amount before the NMP domain can begin to open. Dynamical correlation map shows interesting cross-peak between LID and NMP domain which suggests the presence of correlated motion between them. This is also reflected in our calculated two-dimensional free energy surface contour diagram which has an interesting elliptic shape, revealing a strong correlation between the opening of the LID domain and that of the NMP domain. Our free energy surface of the LID domain motion is rugged due to interaction with water and the signature of ruggedness is evident in the observed root mean square deviation variation and its fluctuation time correlation functions. We develop a correlated dynamical disorder-type theoretical model to explain the observed dynamic coupling between the motion of the two domains in ADK. Our model correctly reproduces several features of the cross-correlation observed in simulations. (C) 2011 American Institute of Physics. doi:10.1063/1.3516588]

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A new feature-based technique is introduced to solve the nonlinear forward problem (FP) of the electrical capacitance tomography with the target application of monitoring the metal fill profile in the lost foam casting process. The new technique is based on combining a linear solution to the FP and a correction factor (CF). The CF is estimated using an artificial neural network (ANN) trained using key features extracted from the metal distribution. The CF adjusts the linear solution of the FP to account for the nonlinear effects caused by the shielding effects of the metal. This approach shows promising results and avoids the curse of dimensionality through the use of features and not the actual metal distribution to train the ANN. The ANN is trained using nine features extracted from the metal distributions as input. The expected sensors readings are generated using ANSYS software. The performance of the ANN for the training and testing data was satisfactory, with an average root-mean-square error equal to 2.2%.

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A successful protein-protein docking study culminates in identification of decoys at top ranks with near-native quaternary structures. However, this task remains enigmatic because no generalized scoring functions exist that effectively infer decoys according to the similarity to near-native quaternary structures. Difficulties arise because of the highly irregular nature of the protein surface and the significant variation of the nonbonding and solvation energies based on the chemical composition of the protein-protein interface. In this work, we describe a novel method combining an interface-size filter, a regression model for geometric compatibility (based on two correlated surface and packing parameters), and normalized interaction energy (calculated from correlated nonbonded and solvation energies), to effectively rank decoys from a set of 10,000 decoys. Tests on 30 unbound binary protein-protein complexes show that in 16 cases we can identify at least one decoy in top three ranks having <= 10 angstrom backbone root mean square deviation from true binding geometry. Comparisons with other state-of-art methods confirm the improved ranking power of our method without the use of any experiment-guided restraints, evolutionary information, statistical propensities, or modified interaction energy equations. Tests on 118 less-difficult bound binary protein-protein complexes with <= 35% sequence redundancy at the interface showed that in 77% cases, at least 1 in 10,000 decoys were identified with <= 5 angstrom backbone root mean square deviation from true geometry at first rank. The work will promote the use of new concepts where correlations among parameters provide more robust scoring models. It will facilitate studies involving molecular interactions, including modeling of large macromolecular assemblies and protein structure prediction. (C) 2010 Wiley Periodicals, Inc. J Comput Chem 32: 787-796, 2011.

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The three dimensional structure of a 32 residue three disulfide scorpion toxin, BTK-2, from the Indian red scorpion Mesobuthus tamulus has been determined using isotope edited solution NMR methods. Samples for structural and electrophysiological studies were prepared using recombinant DNA methods. Electrophysiological studies show that the peptide is active against hK(v)1.1 channels. The structure of BTK-2 was determined using 373 distance restraints from NOE data, 66 dihedral angle restraints from NOE, chemical shift and scalar coupling data, 6 constraints based on disulfide linkages and 8 constraints based on hydrogen bonds. The root mean square deviation (r.m.s.d) about the averaged co-ordinates of the backbone (N, C-alpha, C') and all heavy atoms are 0.81 +/- 0.23 angstrom and 1.51 +/- 0.29 angstrom respectively. The backbone dihedral angles (phi and psi) for all residues occupy the favorable and allowed regions of the Ramachandran map. The three dimensional structure of BTK-2 is composed of three well defined secondary structural regions that constitute the alpha-beta-beta, structural motif. Comparisons between the structure of BTK-2 and other closely related scorpion toxins pointed towards distinct differences in surface properties that provide insights into the structure-function relationships among this important class of voltage-gated potassium channel inhibiting peptides. (C) 2011 Elsevier B.V. All rights reserved.

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In this work, an attempt is made to gain a better understanding of the breakage of low-viscosity drops in turbulent flows by determining the dynamics of deformation of an inviscid drop in response to a pressure variation acting on the drop surface. Known scaling relationships between wavenumbers and frequencies, and between pressure fluctuations and velocity fluctuations in the inertial subrange are used in characterizing the pressure fluctuation. The existence of a maximum stable drop diameter d(max) follows once scaling laws of turbulent flow are used to correlate the magnitude of the disruptive forces with the duration for which they act. Two undetermined dimensionless quantities, both of order unity, appear in the equations of continuity, motion, and the boundary conditions in terms of pressure fluctuations applied on the surface. One is a constant of proportionality relating root-mean-square values of pressure and velocity differences between two points separated by a distance l. The other is a Weber number based on turbulent stresses acting on the drop and the resisting stresses in the drop due to interfacial tension. The former is set equal to 1, and the latter is determined by studying the interaction of a drop of diameter equal to d(max) with a pressure fluctuation of length scale equal to the drop diameter. The model is then used to study the breakage of drops of diameter greater than d(max) and those with densities different from that of the suspending fluid. It is found that, at least during breakage of a drop of diameter greater than d(max) by interaction with a fluctuation of equal length scale, a satellite drop is always formed between two larger drops. When very large drops are broken by smaller-length-scale fluctuations, highly deformed shapes are produced suggesting the possibility of further fragmentation due to instabilities. The model predicts that as the dispersed-phase density increases, d(max) decreases.

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Ligand-induced conformational changes in proteins are of immense functional relevance. It is a major challenge to elucidate the network of amino acids that are responsible for the percolation of ligand-induced conformational changes to distal regions in the protein from a global perspective. Functionally important subtle conformational changes (at the level of side-chain noncovalent interactions) upon ligand binding or as a result of environmental variations are also elusive in conventional studies such as those using root-mean-square deviations (r.m.s.d.s). In this article, the network representation of protein structures and their analyses provides an efficient tool to capture these variations (both drastic and subtle) in atomistic detail in a global milieu. A generalized graph theoretical metric, using network parameters such as cliques and/or communities, is used to determine similarities or differences between structures in a rigorous manner. The ligand-induced global rewiring in the protein structures is also quantified in terms of network parameters. Thus, a judicious use of graph theory in the context of protein structures can provide meaningful insights into global structural reorganizations upon perturbation and can also be helpful for rigorous structural comparison. Data sets for the present study include high-resolution crystal structures of serine proteases from the S1A family and are probed to quantify the ligand-induced subtle structural variations.

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We report the C-HETSERF experiment for determination of long- and short-range homo- and heteronuclear scalar couplings ((n)J(HH) and (n)J(XH), n >= 1) of organic molecules with a low sensitivity dilute heteronucleus in natural abundance. The method finds significant advantage in measurement of relative signs of long-range heteronuclear total couplings in chiral organic liquid crystal. The advantage of the method is demonstrated for the measurement of residual dipolar couplings (RDCs) in enantiomers oriented in the chiral liquid crystal with a focus to unambiguously assign R/S designation in a 2D spectrum. The alignment tensor calculated from the experimental RDCs and with the computed structures of enantiomers obtained by DFT calculations provides the size of the back-calculated RDCs. Smaller root-mean-square deviations (rmsd) between experimental and calculated RDCs indicate better agreement with the input structure and its correct designation of the stereogenic center.

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This paper presents computational and experimental results on a new burner configuration with a mild combustion concept with heat release rates up to 10 MW/m(3). The burner configuration is shown to achieve mild combustion by using air at ambient temperature at high recirculation rates (similar to250%-290%) both experimentally and computationally. The principal features of the configuration are: (1) a burner with forward exit for exhaust gases; (2) injection of gaseous fuel and air as multiple, alternate, peripheral highspeed jets at the bottom at ambient temperature, thus creating high enough recirculation rates of the hot combustion products into fresh incoming reactants; and (3) use of a suitable geometric artifice-a frustum of a cone to help recirculation. The computational studies have been used to reveal the details of the flow and to optimize the combustor geometry based on recirculation rates. Measures, involving root mean square temperature fluctuations, distribution of temperature and oxidizer concentration inside the proposed burner, and a classical turbulent diffusion jet flame, are used to distinguish between them quantitatively. The system, operated at heat release rates of 2 to 10 MW/m(3) (compared to 0.02 to 0.32 MW/m(3) in the earlier studies), shows a 10-15 dB reduction in noise in the mild combustion mode compared to a simple open-top burner and exhaust NOx emission below 10 ppm for a 3 kW burner with 10% excess air. The peak temperature is measured around 1750 K, approximately 300 K lower than the peak temperature in a conventional burner.

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The effect of fluid velocity fluctuations on the dynamics of the particles in a turbulent gas–solid suspension is analysed in the low-Reynolds-number and high Stokes number limits, where the particle relaxation time is long compared with the correlation time for the fluid velocity fluctuations, and the drag force on the particles due to the fluid can be expressed by the modified Stokes law. The direct numerical simulation procedure is used for solving the Navier–Stokes equations for the fluid, the particles are modelled as hard spheres which undergo elastic collisions and a one-way coupling algorithm is used where the force exerted by the fluid on the particles is incorporated, but not the reverse force exerted by the particles on the fluid. The particle mean and root-mean-square (RMS) fluctuating velocities, as well as the probability distribution function for the particle velocity fluctuations and the distribution of acceleration of the particles in the central region of the Couette (where the velocity profile is linear and the RMS velocities are nearly constant), are examined. It is found that the distribution of particle velocities is very different from a Gaussian, especially in the spanwise and wall-normal directions. However, the distribution of the acceleration fluctuation on the particles is found to be close to a Gaussian, though the distribution is highly anisotropic and there is a correlation between the fluctuations in the flow and gradient directions. The non-Gaussian nature of the particle velocity fluctuations is found to be due to inter-particle collisions induced by the large particle velocity fluctuations in the flow direction. It is also found that the acceleration distribution on the particles is in very good agreement with the distribution that is calculated from the velocity fluctuations in the fluid, using the Stokes drag law, indicating that there is very little correlation between the fluid velocity fluctuations and the particle velocity fluctuations in the presence of one-way coupling. All of these results indicate that the effect of the turbulent fluid velocity fluctuations can be accurately represented by an anisotropic Gaussian white noise.

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The particle and fluid velocity fluctuations in a turbulent gas-particle suspension are studied experimentally using two-dimensional particle image velocimetry with the objective of comparing the experiments with the predictions of fluctuating force simulations. Since the fluctuating force simulations employ force distributions which do not incorporate the modification of fluid turbulence due to the particles, it is of importance to quantify the turbulence modification in the experiments. For experiments carried out at a low volume fraction of 9.15 x 10(-5) (mass loading is 0.19), where the viscous relaxation time is small compared with the time between collisions, it is found that the gas-phase turbulence is not significantly modified by the presence of particles. Owing to this, quantitative agreement is obtained between the results of experiments and fluctuating force simulations for the mean velocity and the root mean square of the fluctuating velocity, provided that the polydispersity in the particle size is incorporated in the simulations. This is because the polydispersity results in a variation in the terminal velocity of the particles which could induce collisions and generate fluctuations; this mechanism is absent if all of the particles are of equal size. It is found that there is some variation in the particle mean velocity very close to the wall depending on the wall-collision model used in the simulations, and agreement with experiments is obtained only when the tangential wall-particle coefficient of restitution is 0.7. The mean particle velocity is in quantitative agreement for locations more than 10 wall units from the wall of the channel. However, there are systematic differences between the simulations and theory for the particle concentrations, possibly due to inadequate control over the particle feeding at the entrance. The particle velocity distributions are compared both at the centre of the channel and near the wall, and the shape of the distribution function near the wall obtained in experiments is accurately predicted by the simulations. At the centre, there is some discrepancy between simulations and experiment for the distribution of the fluctuating velocity in the flow direction, where the simulations predict a bi-modal distribution whereas only a single maximum is observed in the experiments, although both distributions are skewed towards negative fluctuating velocities. At a much higher particle mass loading of 1.7, where the time between collisions is smaller than the viscous relaxation time, there is a significant increase in the turbulent velocity fluctuations by similar to 1-2 orders of magnitude. Therefore, it becomes necessary to incorporate the modified fluid-phase intensity in the fluctuating force simulation; with this modification, the mean and mean-square fluctuating velocities are within 20-30% of the experimental values.

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More than six years after the great (M-w 9.2) Sumatra-Andaman earthquake, postevent processes responsible for relaxation of the coseismic stress change remain controversial. Modeling of Andaman Islands Global Positioning System (GPS) displacements indicated early near-field motions were dominated by slip down-dip of the rupture, but various researchers ascribe elements of relaxation to dominantly poroelastic, dominantly viscoelastic, and dominantly fault slip processes, depending primarily on their measurement sampling and modeling tools used. After subtracting a pre-2004 interseismic velocity, significant transient motion during the 2008.5-2010.5 epoch confirms that postseismic relaxation processes continue in Andaman. Modeling three-component velocities as viscoelastic flow yields a weighted root-mean-square (wrms) misfit that always exceeds the wrms of the measured signal (26.3 mm/yr). The best-fitting models are those that yield negligible deformation, indicating the model parameters have no real physical meaning. GPS velocities are well fit (wrms 4.0 mm/yr) by combining a viscoelastic flow model that best fits the horizontal velocities with similar to 50 cm/yr thrust slip down-dip of the coseismic rupture. Both deep slip and flow respond to stress changes, and each can significantly change stress in the realm of the other; it therefore is reasonable to expect that both transient deep slip and viscoelastic flow will influence surface deformation long after a great earthquake.

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The rapidly growing structure databases enhance the probability of finding identical sequences sharing structural similarity. Structure prediction methods are being used extensively to abridge the gap between known protein sequences and the solved structures which is essential to understand its specific biochemical and cellular functions. In this work, we plan to study the ambiguity between sequence-structure relationships and examine if sequentially identical peptide fragments adopt similar three-dimensional structures. Fragments of varying lengths (five to ten residues) were used to observe the behavior of sequence and its three-dimensional structures. The STAMP program was used to superpose the three-dimensional structures and the two parameters (Sequence Structure Similarity Score (Sc) and Root Mean Square Deviation value) were employed to classify them into three categories: similar, intermediate and dissimilar structures. Furthermore, the same approach was carried out on all the three-dimensional protein structures solved in the two organisms, Mycobacterium tuberculosis and Plasmodium falciparum to validate our results.

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In this study, an effort has been made to study heavy rainfall events during cyclonic storms over Indian Ocean. This estimate is based on microwave observations from tropical rainfall measuring mission (TRMM) Microwave Imager (TMI). Regional scattering index (SI) developed for Indian region based on measurements at 19-, 21- and 85-GHz brightness temperature and polarization corrected temperature (PCT) at 85 GHz have been utilized in this study. These PCT and SI are collocated against Precipitation Radar (PR) onboard TRMM to establish a relationship between rainfall rate, PCT and SI. The retrieval technique using both linear and nonlinear regressions has been developed utilizing SI, PCT and the combination of SI and PCT. The results have been compared with the observations from PR. It was found that a nonlinear algorithm using combination of SI and PCT is more accurate than linear algorithm or nonlinear algorithm using either SI or PCT. Statistical comparison with PR exhibits the correlation coefficients (CC) of 0.68, 0.66 and 0.70, and root mean square error (RMSE) of 1.78, 1.96 and 1.68 mm/h from the observations of SI, PCT and combination of SI and PCT respectively using linear regressions. When nonlinear regression is used, the CC of 0.73, 0.71, 0.79 and RMSE of 1.64, 1.95, 1.54 mm/h are observed from the observations of SI, PCT and combination of SI and PCT, respectively. The error statistics for high rain events (above 10 mm/h) shows the CC of 0.58, 0.59, 0.60 and RMSE of 5.07, 5.47, 5.03 mm/h from the observations of SI, PCT and combination of SI and PCT, respectively, using linear regression, and on the other hand, use of nonlinear regression yields the CC of 0.66, 0.64, 0.71 and RMSE of 4.68, 5.78 and 4.02 mm/h from the observations of SI, PCT and combined SI and PCT, respectively.