On the stacking fault energies of some close-packed hexagonal metals

It is now realised (1,2,3) that a knowledge of stacking fault energy is fundamental for an understanding of the mechanical behaviour of metals. There are several processes in which the imperfect dislocations have to recombine locally to form an unextended dislocation . For intersection of two dislocations it is, for example, necessary to form 'constrictions'. Cross slip of extended dislocations also involves constriction. The onset of stage llI work hardening in a crystal with close-packed structure is attributed to cross slip and hence is controlled by the stacking fault energy (SPE). Methods of estimation of SFE are based on either the direct observation of stacking faults in an electron microscope or their effects on the deformation processes.

Primordial Perturbations from a Self-interacting Curvaton

Inflation is a period of accelerated expansion in the very early universe, which has the appealing aspect that it can create primordial perturbations via quantum fluctuations. These primordial perturbations have been observed in the cosmic microwave background, and these perturbations also function as the seeds of all large-scale structure in the universe. Curvaton models are simple modifications of the standard inflationary paradigm, where inflation is driven by the energy density of the inflaton, but another field, the curvaton, is responsible for producing the primordial perturbations. The curvaton decays after inflation as ended, where the isocurvature perturbations of the curvaton are converted into adiabatic perturbations. Since the curvaton must decay, it must have some interactions. Additionally realistic curvaton models typically have some self-interactions. In this work we consider self-interacting curvaton models, where the self-interaction is a monomial in the potential, suppressed by the Planck scale, and thus the self-interaction is very weak. Nevertheless, since the self-interaction makes the equations of motion non-linear, it can modify the behaviour of the model very drastically. The most intriguing aspect of this behaviour is that the final properties of the perturbations become highly dependent on the initial values. Departures of Gaussian distribution are important observables of the primordial perturbations. Due to the non-linearity of the self-interacting curvaton model and its sensitivity to initial conditions, it can produce significant non-Gaussianity of the primordial perturbations. In this work we investigate the non-Gaussianity produced by the self-interacting curvaton, and demonstrate that the non-Gaussianity parameters do not obey the analytically derived approximate relations often cited in the literature. Furthermore we also consider a self-interacting curvaton with a mass in the TeV-scale. Motivated by realistic particle physics models such as the Minimally Supersymmetric Standard Model, we demonstrate that a curvaton model within the mass range can be responsible for the observed perturbations if it can decay late enough.

Self-Assembly of Biopolymers on Colloidal Particles via Hydrogen Bonding

Fabrication of multilayer microcapsules via layer-by-layer approach through hydrogen bonding has attracted enormous interest due to its strong response to pH. In this communication, we have prepared hydrogen-bonded multilayer microcapsule without using any cross-linking agent by using DNA base pair (adenine and thymine) modified biocompatible polymers. The growth of the self-assembly on colloidal (melamine formaldehyde: MF) particles has been monitored with zeta potential measurement. The capsules were obtained on dissolution of MF particles at 0.1N HCl. The capsules were characterized with scanning electron microscopy. Moreover, we have observed the salt induced microscopic change in self-assembly of this system on the surface of colloidal particles.

A Dynamic Migration Model for self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

Propagation of a spherical shock in an inhomogeneous self-gravitating or nongravitating system

The propagation of a shock wave of finite strength due to an explosion into inhomogeneous nongravitating and self-gravitating systems has been considered, using similarity principles, supposing that the density varies as an inverse power of distance from the centre of explosion. A large number of systems, characterised by different density exponents and different adiabatic coefficients of the gas have been considered for different shock strengths. The numerical integration from the shock inward has been continued to the surface of singularity where density tends to infinity and which acts like a piston in the self-gravitating case and to the surface where the velocity gradient tends to infinity in the nongravitating case. The effect of variation of shock strength, density exponent and adiabatic coefficient on the location of these singularities and on the distribution of flow parameters behind the shock has been studied. The initial energy of the system and the manner of release of the explosion energy influence strongly the flow behind the shock. The results have been graphically depicted.

Multivariate Techniques for Identifying Diffractive Interactions at the LHC

Close to one half of the LHC events are expected to be due to elastic or inelastic diffractive scattering. Still, predictions based on extrapolations of experimental data at lower energies differ by large factors in estimating the relative rate of diffractive event categories at the LHC energies. By identifying diffractive events, detailed studies on proton structure can be carried out. The combined forward physics objects: rapidity gaps, forward multiplicity and transverse energy flows can be used to efficiently classify proton-proton collisions. Data samples recorded by the forward detectors, with a simple extension, will allow first estimates of the single diffractive (SD), double diffractive (DD), central diffractive (CD), and non-diffractive (ND) cross sections. The approach, which uses the measurement of inelastic activity in forward and central detector systems, is complementary to the detection and measurement of leading beam-like protons. In this investigation, three different multivariate analysis approaches are assessed in classifying forward physics processes at the LHC. It is shown that with gene expression programming, neural networks and support vector machines, diffraction can be efficiently identified within a large sample of simulated proton-proton scattering events. The event characteristics are visualized by using the self-organizing map algorithm.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

Extended self-similarity works for the Burgers equation and why

Extended self-similarity (ESS), a procedure that remarkably extends the range of scaling for structure functions in Navier-Stokes turbulence and thus allows improved determination of intermittency exponents, has never been fully explained. We show that ESS applies to Burgers turbulence at high Reynolds numbers and we give the theoretical explanation of the numerically observed improved scaling at both the IR and UV end, in total a gain of about three quarters of a decade: there is a reduction of subdominant contributions to scaling when going from the standard structure function representation to the ESS representation. We conjecture that a similar situation holds for three-dimensional incompressible turbulence and suggest ways of capturing subdominant contributions to scaling.

Instability of the self-similar flow into a cavity

In this paper we have investigated the instability of the self-similar flow behind the boundary of a collapsing cavity. The similarity solutions for the flow into a cavity in a fluid obeying a gas law p = Kργ, K = constant and 7 ≥ γ > 1 has been solved by Hunter, who finds that for the same value of γ there are two self-similar flows, one with accelerating cavity boundary and other with constant velocity cavity boundary. We find here that the first of these two flows is unstable. We arrive at this result only by studying the propagation of disturbances in the neighbourhood of the singular point.

On self-interacting oligoribonucleotides. I. Absorption and optical rotatory dispersion of 2′-5′- and 3′-5′-oligoguanylic acids

A series of 2′-5′-oligoguanylic acids are prepared by reacting G(cyclic)p with takadiastase T1 ribonuclease and separating the products chromatographically. The 3′-5′-oligoguanylic acids are obtained by separating the products of alkaline degradation of 3′-5′-poly(G). The optical rotatory dispersion and hypochromism of both 2′-5′- and 3′-5′-oligoguanylic acids are studied at two different pH. The optical rotatory dispersion spectrum of 2′-5′-GpG is significantly different from that of 3′-5′-GpG. The magnitude of rotation of the long-wavelength peak of 2′-5′-GpG is larger than that of 3′-5′-GpG. This finding contradicts the explanation that the extra stability and more intense circular dichroism band of other 3′-5′-dinucleoside monophosphates is due to H-bond formation between 2′-OH and either the base or the phosphate oxygen. The end phosphate group has a marked effect on the spectrum of GpG between 230 and 250 mμ. In addition the optical rotatory dispersion spectra of 2′-5′ exhibit strong pH, temperature, and solvent dependence between 230 and 250 mμ. ΔH and AS for order ⇌ disorder transition is estimated to be 9.7 kcal/mole and 35.2 eu, respectively. The optical rotatory dispersion spectra of guanine-rich oligoribonucleotides, GpGpC, GpGpU, GpGpGpC, and GpGpGpU are compared to the calculated optical rotatory dispersion from the semiempirical expression of Cantor and Tinoco, using measured optical rotatory dispersion of dimers. Contrary to previous studies, agreement is found not at all satisfactory. However, optical rotatory dispersion of 3′-5′-GpGpGpC and GpGpGpU can be estimated from the semiempirical expression, if a next-nearest interaction parameter is introduced empirically. Such interaction parameter can be calculated from the measured properties of trinucleotide sequences like GpGpG, GpGpC, and GpGpU, assuming that only the nearest-neighbor interaction is important. The optical rotatory dispersion of single-stranded poly(G) is also predicted. The importance of syn-anti equilibrium and next-nearest-neighbor interaction in oligoguanylic acids is suggested as a probable explanation.

Clustering and solute-vacancy binding energies in Al-4.4% Zn alloy with 0.01% ternary additions

Isochronal and isothermal ageing experiments have been carried out to determine the influence of 0.01 at. % addition of a second solute on the clustering rate in the quenched Al-4,4 a/o Zn alloy. The influence of quenching and ageing temperatures has been interpreted to obtain the apparent vacancy formation and vacancy migration energies in the various ternary alloys. Using a vacancy-aided clustering model the following values of binding free energy have been evaluated: Ce-0.18; Dy-0.24; Fe-0.18; Li-0.25; Mn-0.27; Nb-0.18; Pt-0.23; Sb-0.21; Si-0.30; Y-0.25; and Yb-0.23 (± 0.02 eV). These binding energy values refer to that between a solute atom and a single vacancy. The values of vacancy migration energy (c. 0.4 eV) and the experimental activation energy for solute diffusion (c. 1.1 eV) are unaffected by the presence of the ternary atoms in the Al-Zn alloy.

Glucose-Triggered Drug Delivery from Borate Mediated Layer-by-Layer Self-Assembly

In this study, we report a novel approach for glucose-triggered anticancer drug delivery from the self-assembly of neutral poly(vinyln alcohol) (PVA) and chitosan. In the present study, we have fabricated multilayer thin film of PVA-borate and chitosan on colloidal particle (MF particle) and monitored the layer-by-layer growth using Zetapotential measurements. Formation of multilayer membrane on MF particle has been further characterized with transmission electron microscopy (TEM) and confocal laser scanning microscopy (CLSM). Subsequently,disintegration of multilayer thin film and microcapsules was observed in presence of glucose. We investigated the disassembly of PVA-borate and chitosan self-assembly under CLSM and atomic force microscopy. These results suggest that this multilayer thin film is very efficient for encapsulation and release of DOX molecules above certain concentration of glucose (25 mM). This glucose-sensitive self-assembly is relevant for the application of anticancer therapeutic drug delivery.

Possible use of self-calibration to reduce systematic uncertainties in determining distance-redshift relation via gravitational radiation from merging binaries

By observing mergers of compact objects, future gravity wave experiments would measure the luminosity distance to a large number of sources to a high precision but not their redshifts. Given the directional sensitivity of an experiment, a fraction of such sources (gold plated) can be identified optically as single objects in the direction of the source. We show that if an approximate distance-redshift relation is known then it is possible to statistically resolve those sources that have multiple galaxies in the beam. We study the feasibility of using gold plated sources to iteratively resolve the unresolved sources, obtain the self-calibrated best possible distance-redshift relation and provide an analytical expression for the accuracy achievable. We derive the lower limit on the total number of sources that is needed to achieve this accuracy through self-calibration. We show that this limit depends exponentially on the beam width and give estimates for various experimental parameters representative of future gravitational wave experiments DECIGO and BBO.