Lamination-dependent shear deformation models for cylindrical bending of angle-ply laminates

Lamination-dependent shear corrective terms in the analysis of flexure of laminates are derived from a priori assumed linear thicknesswise distributions for gradients of transverse shear stresses and using them in the two in-plane equilibrium equations of elasticity in each ply. Adding these corrective terms to (i) Classical Laminate Plate Theory (CLPT) displacements and (ii) Classical Laminate Shear Deformation Theory (CLSDT) displacements, four new refined lamination-dependent shear deformation models for angle-ply laminates are developed. Performance of these models is evaluated by comparing the results from these models with those from exact elasticity solutions for antisymmetric 2-ply laminates and for 4-ply [15/-15](s) laminates. In general, the model with shear corrective terms based on CLPT and added to CLSDT displacements is sufficient and predicts good estimates, both qualitatively and quantitatively, for all displacements and stresses.

A New Class of Exactly Solvable Interacting Fermion Models in One Dimension

We investigate a model containing two species of one-dimensional fermions interacting via a gauge field determined by the positions of all particles of the opposite species. The model can be salved exactly via a simple unitary transformation. Nevertheless, correlation functions exhibit nontrivial interaction-dependent exponents. A similar model defined on a lattice is introduced and solved. Various generalizations, e.g., to the case of internal symmetries of the fermions, are discussed. The present treatment also clarifies certain aspects of Luttinger's original solution of the "Luttinger model."

Estimating the Threshold Surface Density of Gp120-CCR5 Complexes Necessary for HIV-1 Envelope-Mediated Cell-Cell Fusion

Reduced expression of CCR5 on target CD4(+) cells lowers their susceptibility to infection by R5-tropic HIV-1, potentially preventing transmission of infection and delaying disease progression. Binding of the HIV-1 envelope (Env) protein gp120 with CCR5 is essential for the entry of R5 viruses into target cells. The threshold surface density of gp120-CCR5 complexes that enables HIV-1 entry remains poorly estimated. We constructed a mathematical model that mimics Env-mediated cell-cell fusion assays, where target CD4(+)CCR5(+) cells are exposed to effector cells expressing Env in the presence of a coreceptor antagonist and the fraction of target cells fused with effector cells is measured. Our model employs a reaction network-based approach to describe protein interactions that precede viral entry coupled with the ternary complex model to quantify the allosteric interactions of the coreceptor antagonist and predicts the fraction of target cells fused. By fitting model predictions to published data of cell-cell fusion in the presence of the CCR5 antagonist vicriviroc, we estimated the threshold surface density of gp120-CCR5 complexes for cell-cell fusion as similar to 20 mu m(-2). Model predictions with this threshold captured data from independent cell-cell fusion assays in the presence of vicriviroc and rapamycin, a drug that modulates CCR5 expression, as well as assays in the presence of maraviroc, another CCR5 antagonist, using sixteen different Env clones derived from transmitted or early founder viruses. Our estimate of the threshold surface density of gp120-CCR5 complexes necessary for HIV-1 entry thus appears robust and may have implications for optimizing treatment with coreceptor antagonists, understanding the non-pathogenic infection of non-human primates, and designing vaccines that suppress the availability of target CD4(+)CCR5(+) cells.

Instability, intermittency, and multiscaling in discrete growth models of kinetic roughening

We show by numerical simulations that discretized versions of commonly studied continuum nonlinear growth equations (such as the Kardar-Parisi-Zhangequation and the Lai-Das Sarma-Villain equation) and related atomistic models of epitaxial growth have a generic instability in which isolated pillars (or grooves) on an otherwise flat interface grow in time when their height (or depth) exceeds a critical value. Depending on the details of the model, the instability found in the discretized version may or may not be present in the truly continuum growth equation, indicating that the behavior of discretized nonlinear growth equations may be very different from that of their continuum counterparts. This instability can be controlled either by the introduction of higher-order nonlinear terms with appropriate coefficients or by restricting the growth of pillars (or grooves) by other means. A number of such ''controlled instability'' models are studied by simulation. For appropriate choice of the parameters used for controlling the instability, these models exhibit intermittent behavior, characterized by multiexponent scaling of height fluctuations, over the time interval during which the instability is active. The behavior found in this regime is very similar to the ''turbulent'' behavior observed in recent simulations of several one- and two-dimensional atomistic models of epitaxial growth.

Low threshold ovonic switching in a-Si:H/InSb heterostructures

a-Si:H/InSb structures have been fabricated by glow discharge deposition of a-Si on bulk InSb substrates in hydrogen atmosphere. The structure shows interesting switching properties, toggling between a high resistance and a conducting state with OFF to ON resistance ratio of 10(6) at remarkably low threshold voltages of 0.3 V at room temperature. The low threshold voltage for this structure, as compared to the higher switching threshold of about 30 V for other a-Si based structures, has been achieved by the use of InSb as a substrate, capable of high carrier injection. (C) 1997 Published by Elsevier Science Ltd.

Multiscale stochastic approximation for parametric optimization of hidden Markov models

A two-time scale stochastic approximation algorithm is proposed for simulation-based parametric optimization of hidden Markov models, as an alternative to the traditional approaches to ''infinitesimal perturbation analysis.'' Its convergence is analyzed, and a queueing example is presented.

Non-exponentiality in electron transfer kinetics: Static versus dynamic disorder models

Non-exponential electron transfer kinetics in complex systems are often analyzed in terms of a quenched, static disorder model. In this work we present an alternative analysis in terms of a simple dynamic disorder model where the solvent is characterized by highly non-exponential dynamics. We consider both low and high barrier reactions. For the former, the main result is a simple analytical expression for the survival probability of the reactant. In this case, electron transfer, in the long time, is controlled by the solvent polarization relaxation-in agreement with the analyses of Rips and Jortner and of Nadler and Marcus. The short time dynamics is also non-exponential, but for different reasons. The high barrier reactions, on the other hand, show an interesting dynamic dependence on the electronic coupling element, V-el.

On the problem of spurious patterns in neural associative memory models

The problem of spurious patterns in neural associative memory models is discussed, Some suggestions to solve this problem from the literature are reviewed and their inadequacies are pointed out, A solution based on the notion of neural self-interaction with a suitably chosen magnitude is presented for the Hebb learning rule. For an optimal learning rule based on linear programming, asymmetric dilution of synaptic connections is presented as another solution to the problem of spurious patterns, With varying percentages of asymmetric dilution it is demonstrated numerically that this optimal learning rule leads to near total suppression of spurious patterns. For practical usage of neural associative memory networks a combination of the two solutions with the optimal learning rule is recommended to be the best proposition.

Relative performances of textural models in estimating soil moisture characteristic

The soil moisture characteristic (SMC) forms an important input to mathematical models of water and solute transport in the unsaturated-soil zone. Owing to their simplicity and ease of use, texture-based regression models are commonly used to estimate the SMC from basic soil properties. In this study, the performances of six such regression models were evaluated on three soils. Moisture characteristics generated by the regression models were statistically compared with the characteristics developed independently from laboratory and in-situ retention data of the soil profiles. Results of the statistical performance evaluation, while providing useful information on the errors involved in estimating the SMC, also highlighted the importance of the nature of the data set underlying the regression models. Among the models evaluated, the one possessing an underlying data set of in-situ measurements was found to be the best estimator of the in-situ SMC for all the soils. Considerable errors arose when a textural model based on laboratory data was used to estimate the field retention characteristics of unsaturated soils.

Statistical thermodynamics of lattice models in zeolites: Implications of local versus global mean field interactions

The statistical thermodynamics of adsorption in caged zeolites is developed by treating the zeolite as an ensemble of M identical cages or subsystems. Within each cage adsorption is assumed to occur onto a lattice of n identical sites. Expressions for the average occupancy per cage are obtained by minimizing the Helmholtz free energy in the canonical ensemble subject to the constraints of constant M and constant number of adsorbates N. Adsorbate-adsorbate interactions in the Brag-Williams or mean field approximation are treated in two ways. The local mean field approximation (LMFA) is based on the local cage occupancy and the global mean field approximation (GMFA) is based on the average coverage of the ensemble. The GMFA is shown to be equivalent in formulation to treating the zeolite as a collection of interacting single site subsystems. In contrast, the treatment in the LMFA retains the description of the zeolite as an ensemble of identical cages, whose thermodynamic properties are conveniently derived in the grand canonical ensemble. For a z coordinated lattice within the zeolite cage, with epsilon(aa) as the adsorbate-adsorbate interaction parameter, the comparisons for different values of epsilon(aa)(*)=epsilon(aa)z/2kT, and number of sites per cage, n, illustrate that for -1 0. We compare the isotherms predicted with the LMFA with previous GMFA predictions [K. G. Ayappa, C. R. Kamala, and T. A. Abinandanan, J. Chem. Phys. 110, 8714 (1999)] (which incorporates both the site volume reduction and a coverage-dependent epsilon(aa)) for xenon and methane in zeolite NaA. In all cases the predicted isotherms are very similar, with the exception of a small steplike feature present in the LMFA for xenon at higher coverages. (C) 1999 American Institute of Physics. [S0021-9606(99)70333-8].

In-situ power monitoring scheme and its application in dynamic voltage and threshold scaling for digital CMOS integrated circuits

An in-situ power monitoring technique for Dynamic Voltage and Threshold scaling (DVTS) systems is proposed which measures total power consumed by load circuit using sleep transistor acting as power sensor. Design details of power monitor are examined using simulation framework in UMC 90nm CMOS process. Experimental results of test chip fabricated in AMS 0.35µm CMOS process are presented. The test chip has variable activity between 0.05 and 0.5 and has PMOS VTH control through nWell contact. Maximum resolution obtained from power monitor is 0.25mV. Overhead of power monitor in terms of its power consumption is 0.244 mW (2.2% of total power of load circuit). Lastly, power monitor is used to demonstrate closed loop DVTS system. DVTS algorithm shows 46.3% power savings using in-situ power monitor.

Assessment of conditional moment closure models of turbulent autoignition using DNS data

A systematic assessment of the submodels of conditional moment closure (CMC) formalism for the autoignition problem is carried out using direct numerical simulation (DNS) data. An initially non-premixed, n-heptane/air system, subjected to a three-dimensional, homogeneous, isotropic, and decaying turbulence, is considered. Two kinetic schemes, (1) a one-step and (2) a reduced four-step reaction mechanism, are considered for chemistry An alternative formulation is developed for closure of the mean chemical source term , based on the condition that the instantaneous fluctuation of excess temperature is small. With this model, it is shown that the CMC equations describe the autoignition process all the way up to near the equilibrium limit. The effect of second-order terms (namely, conditional variance of temperature excess sigma(2) and conditional correlations of species q(ij)) in modeling is examined. Comparison with DNS data shows that sigma(2) has little effect on the predicted conditional mean temperature evolution, if the average conditional scalar dissipation rate is properly modeled. Using DNS data, a correction factor is introduced in the modeling of nonlinear terms to include the effect of species fluctuations. Computations including such a correction factor show that the species conditional correlations q(ij) have little effect on model predictions with a one-step reaction, but those q(ij) involving intermediate species are found to be crucial when four-step reduced kinetics is considered. The "most reactive mixture fraction" is found to vary with time when a four-step kinetics is considered. First-order CMC results are found to be qualitatively wrong if the conditional mean scalar dissipation rate is not modeled properly. The autoignition delay time predicted by the CMC model compares excellently with DNS results and shows a trend similar to experimental data over a range of initial temperatures.