Dynamics of history-dependent epidemics in temporal networks

The structural properties of temporal networks often influence the dynamical processes that occur on these networks, e.g., bursty interaction patterns have been shown to slow down epidemics. In this paper, we investigate the effect of link lifetimes on the spread of history-dependent epidemics. We formulate an analytically tractable activity-driven temporal network model that explicitly incorporates link lifetimes. For Markovian link lifetimes, we use mean-field analysis for computing the epidemic threshold, while the effect of non-Markovian link lifetimes is studied using simulations. Furthermore, we also study the effect of negative correlation between the number of links spawned by an individual and the lifetimes of those links. Such negative correlations may arise due to the finite cognitive capacity of the individuals. Our investigations reveal that heavy-tailed link lifetimes slow down the epidemic, while negative correlations can reduce epidemic prevalence. We believe that our results help shed light on the role of link lifetimes in modulating diffusion processes on temporal networks.

Fabrication and Nonlinear Thermomechanical Analysis of SU8 Thermal Actuator

SU8-based micromechanical structures are widely used as thermal actuators in the development of compliant micromanipulation tools. This paper reports the design, nonlinear thermomechanical analysis, fabrication, and thermal actuation of SU8 actuators. The thermomechanical analysis of the actuator incorporates nonlinear temperature-dependent properties of SU8 polymer to accurately model its thermal response during actuation. The designed SU8 thermal actuators are fabricated using surface micromachining techniques and the electrical interconnects are made to them using flip-chip bonding. The issues due to thermal stress during fabrication are discussed and a novel strategy is proposed to release the thermal stress in the fabricated actuators. Subsequent characterization of the actuator using an optical profilometer reveals excellent thermal response, good repeatability, and low hysteresis. The average deflection is similar to 8.5 mu m for an actuation current of similar to 5 mA. The experimentally obtained deflection profile and the tip deflection at different currents are both shown to be in good agreement with the predictions of the nonlinear thermomechanical model. This underscores the need to consider nonlinearities when modeling the response of SU8 thermal actuators. 2015-0087]

State space formulation of ammonia reactor dynamics

The specific objective of this paper is to develop a state space model of a tubular ammonia reactor which is the heart of an ammonia plant in a fertiliser complex. A ninth order model with three control inputs and two disturbance inputs is generated from the nonlinear distributed model using linearization and lumping approximations. The lumped model is chosen such that the steady state temperature at the exit of the catalyst bed computed from the simplified state space model is close enough to the one computed from the nonlinear steady state model. The model developed in this paper is very useful for the design of continuous/discrete versions of single variable/multivariable control algorithms.

Negative resistance mode of forced oscillations of a string

A new mode of driven nonlinear vibrations of a stretched string is investigated with reference to conditions of existence, properties, and regions of stability. It is shown that this mode exhibits negative resistance properties at all frequencies and driving force amplitudes. Discovery of this mode helps to fill certain gaps in the theory of forced nonlinear vibrations of strings.

An optimal dynamic inversion-based neuro-adaptive approach for treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an innovative technique is presented to design an automatic drug administration strategy for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used to design the controller (medication dosage). First, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat the nominal model patients (patients who can be described by the mathematical model used here with the nominal parameter values) effectively. However, since the system parameters for a realistic model patient can be different from that of the nominal model patients, simulation studies for such patients indicate that the nominal controller is either inefficient or, worse, ineffective; i.e. the trajectory of the number of cancer cells either shows non-satisfactory transient behavior or it grows in an unstable manner. Hence, to make the drug dosage history more realistic and patient-specific, a model-following neuro-adaptive controller is augmented to the nominal controller. In this adaptive approach, a neural network trained online facilitates a new adaptive controller. The training process of the neural network is based on Lyapunov stability theory, which guarantees both stability of the cancer cell dynamics as well as boundedness of the network weights. From simulation studies, this adaptive control design approach is found to be very effective to treat the CML disease for realistic patients. Sufficient generality is retained in the mathematical developments so that the technique can be applied to other similar nonlinear control design problems as well.

Modeling of magnetostrictive materials and structures

The constitutive model for a magnetostrictive material and its effect on the structural response is presented in this article. The example of magnetostrictive material considered is the TERFENOL-D. As like the piezoelectric material, this material has two constitutive laws, one of which is the sensing law and the other is the actuation law, both of which are highly coupled and non-linear. For the purpose of analysis, the constitutive laws can be characterized as coupled or uncoupled and linear or non linear. Coupled model is studied without assuming any explicit direct relationship with magnetic field. In the linear coupled model, which is assumed to preserve the magnetic flux line continuity, the elastic modulus, the permeability and magneto-elastic constant are assumed as constant. In the nonlinear-coupled model, the nonlinearity is decoupled and solved separately for the magnetic domain and the mechanical domain using two nonlinear curves, namely the stress vs. strain curve and the magnetic flux density vs. magnetic field curve. This is performed by two different methods. In the first, the magnetic flux density is computed iteratively, while in the second, the artificial neural network is used, where in the trained network will give the necessary strain and magnetic flux density for a given magnetic field and stress level. The effect of nonlinearity is demonstrated on a simple magnetostrictive rod.

Non-Fermi liquid theory of quantum hall effects

Within the Grassmannian U(2N)/U(N) x U(N) nonlinear sigma-model representation of localization, one can study the low-energy dynamics of both a free and interacting electron gas. We study the crossover between these two fundamentally different physical problems. We show how the topological arguments for the exact quantization of the Hall conductance are extended to include the Coulomb interaction problem. We discuss dynamical scaling and make contact with the theory of variable range hopping. (C) 2005 Pleiades Publishing, Inc.

Dynamics of Stick-Slip: Some Universal and Not So Universal Features

Stick-slip is usually observed in driven dissipative threshold systems. In these set of lectures, we discuss, some generic and system specific features of stickslip systems by considering a few examples wherein there has been some progress in understanding the associated dynamics. In most stick slip systems, both at low and high drive rates, the system slides smoothly, but within a window of drive rates, the motion becomes intermittent; the system alternately “sticks” till the stress builds up to a threshold value, and then “slips” when the stress is rapidly released. This intermittent motion can be traced to the existence of an unstable branch separating the two resistive branches in the force-drive-rate relation. While the two resistive branches are experimentally measurable, the unstable branch is usually not measurable and is only inferred.

A neuro-adaptive augmented optimal dynamic inversion approach for effective and efficient treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an efficient technique is presented for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used for the control (medication) synthesis. First, taking a set of nominal parameters, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat nominal patients (patients having same nominal parameters as used for the control design) effectively. However, since the parameters of an actual patient can be different from that of the ideal patient, to make the treatment strategy more effective and efficient, a model-following neuro-adaptive controller is augmented to the nominal controller. In this approach, a neural network trained online (based on Lyapunov stability theory) facilitates a new adaptive controller, computed online. From the simulation studies, this adaptive control design approach (treatment strategy) is found to be very effective to treat the CML disease for actual patients. Sufficient generality is retained in the theoretical developments in this paper, so that the techniques presented can be applied to other similar problem as well. Note that the technique presented is computationally non-intensive and all computations can be carried out online.

Robust multivariable controllers for a tublar ammonia reactor

The specific objective of this paper is to develop multivariable controllers that would achieve asymptotic regulation in the presence of parameter variations and disturbance inputs for a tubular reactor used in ammonia synthesis. A ninth order state space model with three control inputs and two disturbance inputs is generated from the nonlinear distributed model using linearization and lumping approximations. Using this model, an approach for control system design is developed keeping in view the imperfections of the model and the measurability of the state variables. Specifically, the design of feedforward and robust integral controllers using state and output feedback is considered. Also, the design of robust multiloop proportional integral controllers is presented. Finally the performance of these controllers is evaluated through simulation.

Effective action and adiabatic expansions for the 1-D and 2-D hubbard models at half-filling

We analyze here the occurrence of antiferromagnetic (AFM) correlations in the half-filled Hubbard model in one and two space dimensions using a natural fermionic representation of the model and a newly proposed way of implementing the half-filling constraint. We find that our way of implementing the constraint is capable of enforcing it exactly already at the lowest levels of approximation. We discuss how to develop a systematic adiabatic expansion for the model and how Berry's phase contributions arise quite naturally from the adiabatic expansion. At low temperatures and in the continuum limit the model gets mapped onto an O(3) nonlinear sigma model (NLsigma). A topological, Wess-Zumino term is present in the effective action of the ID NLsigma as expected, while no topological terms are present in 2D. Some specific difficulties that arise in connection with the implementation of an adiabatic expansion scheme within a thermodynamic context are also discussed, and we hint at possible solutions.

Effective drug dosage design for treatment of infectious diseases using dynamic inversion

A generic nonlinear mathematical model describing the human immunological dynamics is used to design an effective automatic drug administration scheme. Even though the model describes the effects of various drugs on the dynamic system, this work is confined to the drugs that kill the invading pathogen and heal the affected organ. From a system theoretic point of view, the drug inputs can be interpreted as control inputs, which can be designed based on control theoretic concepts. The controller is designed based on the principle of dynamic inversion and is found to be effective in curing the �nominal model patient� by killing the invading microbes and healing the damaged organ. A major advantage of this technique is that it leads to a closed-form state feedback form of control. It is also proved from a rigorous mathematical analysis that the internal dynamics of the system remains stable when the proposed controller is applied. A robustness study is also carried out for testing the effectiveness of the drug administration scheme for parameter uncertainties. It is observed from simulation studies that the technique has adequate robustness for many �realistic model patients� having off-nominal parameter values as well.

Electrical and magneto-resistance of Co/CNT/epoxy thin film for strain and magnetic field sensing

Cobalt and iron nanoparticles are doped in carbon nanotube (CNT)/polymer matrix composites and studied for strain and magnetic field sensing properties. Characterization of these samples is done for various volume fractions of each constituent (Co and Fe nanoparticles and CNTs) and also for cases when only either of the metallic components is present. The relation between the magnetic field and polarization-induced strain are exploited. The electronic bandgap change in the CNTs is obtained by a simplified tight-binding formulation in terms of strain and magnetic field. A nonlinear constitutive model of glassy polymer is employed to account for (1) electric bias field dependent softening/hardening (2) CNT orientations as a statistical ensemble and (3) CNT volume fraction. An effective medium theory is then employed where the CNTs and nanoparticles are treated as inclusions. The intensity of the applied magnetic field is read indirectly as the change in resistance of the sample. Very small magnetic fields can be detected using this technique since the resistance is highly sensitive to strain. Its sensitivity due to the CNT volume fraction is also discussed. The advantage of this sensor lies in the fact that it can be molded into desirable shape and can be used in fabrication of embedded sensors where the material can detect external magnetic fields on its own. Besides, the stress-controlled hysteresis of the sample can be used in designing memory devices. These composites have potential for use in magnetic encoders, which are made of a magnetic field sensor and a barcode.

Coupled electro-mechanical response of an electroactive polymer cantilever structure and its application in energy harvesting

Ionic polymer-metal composites (IPMC), piezoelectric polymer composites and nematic elastomer composites are materials, which exhibit characteristics of both sensors and actuators. Large deformation and curvature are observed in these systems when electric potential is applied. Effects of geometric non-linearity due to the chargeinduced motion in these materials are poorly understood. In this paper, a coupled model for understanding the behavior of an ionic polymer beam undergoing large deformation and large curvature is presented. Maxwell's equations and charge transport equations are considered which couple the distribution of the ion concentration and the pressure gradient along length of a cantilever beam with interdigital electrodes. A nonlinear constitutive model is derived accounting for the visco-elasto-plastic behavior of these polymers and based on the hypothesis that the presence of electrical charge stretches/contracts bonds, which give rise to electrical field dependent softening/hardening. Polymer chain orientation in statistical sense plays a role on such softening or hardening. Elementary beam kinematics with large curvature is considered. A model for understanding the deformation due to electrostatic repulsion between asymmetrical charge distributions across the cross-sections is presented. Experimental evidence that Silver(Ag) nanoparticle coated IPMCs can be used for energy harvesting is reported. An IPMC strip is vibrated in different environments and the electric power against a resistive load is measured. The electrical power generated was observed to vary with the environment with maximum power being generated when the strip is in wet state. IPMC based energy harvesting systems have potential applications in tidal wave energy harvesting, residual environmental energy harvesting to power MEMS and NEMS devices.

Field emission properties of carbon nanotube arrays with defects and impurities

Field emission from carbon nanotubes (CNTs) in the form of arrays or thin films give rise to several strongly correlated process of electromechanical interaction and degradation. Such processes are mainly due to (1) electron-phonon interaction (2) electromechanical force field leading to stretching of CNTs (3) ballistic transport induced thermal spikes, coupled with high dynamic stress, leading to degradation of emission performance at the device scale. Fairly detailed physics based models of CNTs considering the aspects (1) and (2) above have already been developed by these authors, and numerical results indicate good agreement with experimental results. What is missing in such a system level modeling approach is the incorporation of structural defects and vacancies or charge impurities. This is a practical and important problem due to the fact that degradation of field emission performance is indeed observed in experimental I-V curves. What is not clear from these experiments is whether such degradation in the I-V response is due to dynamic reorientation of the CNTs or due to the defects or due to both of these effects combined. Non-equilibrium Green’s function based simulations using a tight-binding Hamiltonian for single CNT segment show up the localization of carrier density at various locations of the CNTs. About 11% decrease in the drive current with steady difference in the drain current in the range of 0.2-0.4V of the gate voltage was reported in literature when negative charge impurity was introduced at various locations of the CNT over a length of ~20nm. In the context of field emission from CNT tips, a simplistic estimate of defects have been introduced by a correction factor in the Fowler-Nordheim formulae. However, a more detailed physics based treatment is required, while at the same time the device-scale simulation is necessary. The novelty of our present approach is the following. We employ a concept of effective stiffness degradation for segments of CNTs, which is due to structural defects, and subsequently, we incorporate the vacancy defects and charge impurity effects in the Green’s function based approach. Field emission induced current-voltage characteristics of a vertically aligned CNT array on a Cu-Cr substrate is then simulated using a detailed nonlinear mechanistic model of CNTs coupled with quantum hydrodynamics. An array of 10 vertically aligned and each 12 m long CNTs is considered for the device scale analysis. Defect regions are introduced randomly over the CNT length. The result shows the decrease in the longitudinal strain due to defects. Contrary to the expected influence of purely mechanical degradation, this result indicates that the charge impurity and hence weaker transport can lead to a different electromechanical force field, which ultimately can reduce the strain. However, there could be significant fluctuation in such strain field due to electron-phonon coupling. The effect of such fluctuations (with defects) is clearly evident in the field emission current history. The average current also decreases significantly due to such defects.