Inverse Problem for Fractional Brownian Motion with Discrete Data

The problem of recovering information from measurement data has already been studied for a long time. In the beginning, the methods were mostly empirical, but already towards the end of the sixties Backus and Gilbert started the development of mathematical methods for the interpretation of geophysical data. The problem of recovering information about a physical phenomenon from measurement data is an inverse problem. Throughout this work, the statistical inversion method is used to obtain a solution. Assuming that the measurement vector is a realization of fractional Brownian motion, the goal is to retrieve the amplitude and the Hurst parameter. We prove that under some conditions, the solution of the discretized problem coincides with the solution of the corresponding continuous problem as the number of observations tends to infinity. The measurement data is usually noisy, and we assume the data to be the sum of two vectors: the trend and the noise. Both vectors are supposed to be realizations of fractional Brownian motions, and the goal is to retrieve their parameters using the statistical inversion method. We prove a partial uniqueness of the solution. Moreover, with the support of numerical simulations, we show that in certain cases the solution is reliable and the reconstruction of the trend vector is quite accurate.

Routes of Hendra Virus Excretion in Naturally-Infected Flying-Foxes: Implications for Viral Transmission and Spillover Risk

Pteropid bats or flying-foxes (Chiroptera: Pteropodidae) are the natural host of Hendra virus (HeV) which sporadically causes fatal disease in horses and humans in eastern Australia. While there is strong evidence that urine is an important infectious medium that likely drives bat to bat transmission and bat to horse transmission, there is uncertainty about the relative importance of alternative routes of excretion such as nasal and oral secretions, and faeces. Identifying the potential routes of HeV excretion in flying-foxes is important to effectively mitigate equine exposure risk at the bat-horse interface, and in determining transmission rates in host-pathogen models. The aim of this study was to identify the major routes of HeV excretion in naturally infected flying-foxes, and secondarily, to identify between-species variation in excretion prevalence. A total of 2840 flying-foxes from three of the four Australian mainland species (Pteropus alecto, P. poliocephalus and P. scapulatus) were captured and sampled at multiple roost locations in the eastern states of Queensland and New South Wales between 2012 and 2014. A range of biological samples (urine and serum, and urogenital, nasal, oral and rectal swabs) were collected from anaesthetized bats, and tested for HeV RNA using a qRT-PCR assay targeting the M gene. Forty-two P. alecto (n = 1410) had HeV RNA detected in at least one sample, and yielded a total of 78 positive samples, at an overall detection rate of 1.76% across all samples tested in this species (78/4436). The rate of detection, and the amount of viral RNA, was highest in urine samples (>serum, packed haemocytes >faecal >nasal >oral), identifying urine as the most plausible source of infection for flying-foxes and for horses. Detection in a urine sample was more efficient than detection in urogenital swabs, identifying the former as the preferred diagnostic sample. The detection of HeV RNA in serum is consistent with haematogenous spread, and with hypothesised latency and recrudesence in flying-foxes. There were no detections in P. poliocephalus (n = 1168 animals; n = 2958 samples) or P. scapulatus (n = 262 animals; n = 985 samples), suggesting (consistent with other recent studies) that these species are epidemiologically less important than P. alecto in HeV infection dynamics. The study is unprecedented in terms of the individual animal approach, the large sample size, and the use of a molecular assay to directly determine infection status. These features provide a high level of confidence in the veracity of our findings, and a sound basis from which to more precisely target equine risk mitigation strategies.

Physicochemical, Electrochemical, and Spectroscopic Characterization of Zinc-Based Room-Temperature Molten Electrolytes and Their Application in Rechargeable Batteries

Room-temperature zinc ion-conducting molten electrolytes based on acetamide, urea, and zinc perchlorate or zinc triflate have been prepared and characterized by various physicochemical, spectroscopic, and electrochemical techniques. The ternary molten electrolytes are easy to prepare and can be handled under ambient conditions. They show excellent stability, high ionic conductivity, relatively low viscosity, and other favorable physicochemical and electrochemical properties that make them good electrolytes for rechargeable zinc batteries. Specific conductivities of 3.4 and 0.5 mS cm(-1) at 25 degrees C are obtained for zinc-perchlorate-and zinc-triflate-containing melts, respectively. Vibrational spectroscopic data reveal that the free ion concentration is high in the optimized composition. Rechargeable Zn batteries have been assembled using the molten electrolytes, with gamma-MnO2 as the positive electrode and Zn as the negative electrode. They show excellent electrochemical characteristics with high discharge capacities. This study opens up the possibility of using acetamide-based molten electrolytes as alternate electrolytes in rechargeable zinc batteries. (C) 2009 The Electrochemical Society.

Magnesium ion conducting, room temperature molten electrolytes

Room temperature, magnesium ion conducting binary molten electrolyte consisting of acetamide and magnesium perchlorate has been prepared and characterized. The molten liquid is very stable and shows high ionic conductivity, of the order of several mS cm(-1) at 25 degrees C with other favourable physicochemical properties. Vibrational spectroscopic studies reveal that the free ion concentration is higher than that of ion pairs and aggregates in the melt. The electrochemical reversibility of magnesium deposition and dissolution is demonstrated using voltammetry and impedance studies. Preliminary studies on rechargeable batteries assembled using gamma-MnO2 and Mg metal as the electrodes together with the molten electrolyte show high discharge capacity.

Soft matter lithium salt electrolytes: ion conduction and application to rechargeable batteries

Soft matter provides diverse opportunities for the development of electrolytes for all solid state lithium batteries. Here we review soft matter solid electrolytes for lithium batteriesthat are primarily obtained starting from liquid electrolytic systems. This concept of solid electrolyte synthesis from liquid is significantly different from prevalent approaches. The novelty of our approach is discussed in the light of various fundamental issues and in relation to its application to rechargeable lithium batteries.

Spin-Probe ESR Studies on Nanocomposite Polymer Electrolytes

The possibility of using spin-probe electron spin resonance (ESR) as a tool to study glass transition temperature, T g, of polymer electrolytes is explored in 4 hydroxy 2,2,6,6 tetramethylpiperidine N oxyl (TEMPOL) doped composite polymer electrolyte (PEG)46LiClO4 dispersed with nanoparticles of hydrotalcite. The T g is estimated from the measured values of T 50G, the temperature at which the extrema separation 2A zz of the broad powder spectrum decreases to 50 G. In another method, the correlation time τc for the spin probe dynamics was determined by computer simulation of the ESR spectra and T g has been identified as the temperature at which τc begins to show temperature dependence. While both methods give values of T g close to those obtained from differential scanning calorimetry, it is concluded that more work is required to establish spin-probe ESR as a reliable technique for the determination of T g.

Beyond fractional derivatives: local approximation of other convolution integrals

Dynamic systems involving convolution integrals with decaying kernels, of which fractionally damped systems form a special case, are non-local in time and hence infinite dimensional. Straightforward numerical solution of such systems up to time t needs O(t(2)) computations owing to the repeated evaluation of integrals over intervals that grow like t. Finite-dimensional and local approximations are thus desirable. We present here an approximation method which first rewrites the evolution equation as a coupled in finite-dimensional system with no convolution, and then uses Galerkin approximation with finite elements to obtain linear, finite-dimensional, constant coefficient approximations for the convolution. This paper is a broad generalization, based on a new insight, of our prior work with fractional order derivatives (Singh & Chatterjee 2006 Nonlinear Dyn. 45, 183-206). In particular, the decaying kernels we can address are now generalized to the Laplace transforms of known functions; of these, the power law kernel of fractional order differentiation is a special case. The approximation can be refined easily. The local nature of the approximation allows numerical solution up to time t with O(t) computations. Examples with several different kernels show excellent performance. A key feature of our approach is that the dynamic system in which the convolution integral appears is itself approximated using another system, as distinct from numerically approximating just the solution for the given initial values; this allows non-standard uses of the approximation, e. g. in stability analyses.

Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2 *-weighted magnetic resonance imaging at 7T

PURPOSE To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. METHODS We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. RESULTS We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. CONCLUSIONS We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain.

Oxide Particle Surface Chemistry and Ion Transport in "Soggy Sand" Electrolytes

The crucial role of oxide surface chemical composition on ion transport in "soggy sand" electrolytes is discussed in a systematic manner. A prototype soggy sand electrolytic system comprising aerosil silica functionalized with various hydrophilic and hydrophobic moieties dispersed in lithium perchlorate-ethylene glycol solution was used for the study. Detailed rheology studies show that the attractive particle network in the case of the composite with unmodified aerosil silica (with surface silanol groups) is most favorable for percolation in ionic conductivity, as well as rendering the composite with beneficial elastic mechanical properties: Though weaker in strength compared to the composite with unmodified aerosil particles, attractive particle networks are also observed in composites of aerosil particles with surfaces partially substituted with hydrophobic groups. The percolation in ionic conductivity is, however, dependent on the size of the hydrophobic moiety. No spanning attractive particle network was formed for aerosil particles with surfaces modified with stronger hydrophilic groups (than silanol), and as a result, no percolation in ionic conductivity was observed. The composite with hydrophilic particles was a sol, contrary to gels obtained in the case of unmodified aerosil, and partially substituted with hydrophobic groups.

Dynamics of Barrierless and Activated Chemical Reactions in a Dispersive Medium within the Fractional Diffusion Equation Approach

Barrierless chemical reactions have often been modeled as a Brownian motion on a one-dimensional harmonic potential energy surface with a position-dependent reaction sink or window located near the minimum of the surface. This simple (but highly successful) description leads to a nonexponential survival probability only at small to intermediate times but exponential decay in the long-time limit. However, in several reactive events involving proteins and glasses, the reactions are found to exhibit a strongly nonexponential (power law) decay kinetics even in the long time. In order to address such reactions, here, we introduce a model of barrierless chemical reaction where the motion along the reaction coordinate sustains dispersive diffusion. A complete analytical solution of the model can be obtained only in the frequency domain, but an asymptotic solution is obtained in the limit of long time. In this case, the asymptotic long-time decay of the survival probability is a power law of the Mittag−Leffler functional form. When the barrier height is increased, the decay of the survival probability still remains nonexponential, in contrast to the ordinary Brownian motion case where the rate is given by the Smoluchowski limit of the well-known Kramers' expression. Interestingly, the reaction under dispersive diffusion is shown to exhibit strong dependence on the initial state of the system, thus predicting a strong dependence on the excitation wavelength for photoisomerization reactions in a dispersive medium. The theory also predicts a fractional viscosity dependence of the rate, which is often observed in the reactions occurring in complex environments.

Fractional damping: Stochastic origin and finite approximations

Fractional-order derivatives appear in various engineering applications including models for viscoelastic damping. Damping behavior of materials, if modeled using linear, constant coefficient differential equations, cannot include the long memory that fractional-order derivatives require. However, sufficiently great rnicrostructural disorder can lead, statistically, to macroscopic behavior well approximated by fractional order derivatives. The idea has appeared in the physics literature, but may interest an engineering audience. This idea in turn leads to an infinite-dimensional system without memory; a routine Galerkin projection on that infinite-dimensional system leads to a finite dimensional system of ordinary differential equations (ODEs) (integer order) that matches the fractional-order behavior over user-specifiable, but finite, frequency ranges. For extreme frequencies (small or large), the approximation is poor. This is unavoidable, and users interested in such extremes or in the fundamental aspects of true fractional derivatives must take note of it. However, mismatch in extreme frequencies outside the range of interest for a particular model of a real material may have little engineering impact.

Polymer melt dynamics: Microscopic roots of fractional viscoelasticity

The rheological properties of polymer melts and other complex macromolecular fluids are often successfully modeled by phenomenological constitutive equations containing fractional differential operators. We suggest a molecular basis for such fractional equations in terms of the generalized Langevin equation (GLE) that underlies the renormalized Rouse model developed by Schweizer [J. Chem. Phys. 91, 5802 (1989)]. The GLE describes the dynamics of the segments of a tagged chain under the action of random forces originating in the fast fluctuations of the surrounding polymer matrix. By representing these random forces as fractional Gaussian noise, and transforming the GLE into an equivalent diffusion equation for the density of the tagged chain segments, we obtain an analytical expression for the dynamic shear relaxation modulus G(t), which we then show decays as a power law in time. This power-law relaxation is the root of fractional viscoelastic behavior.