Stochastic analysis of epidemics on adaptive time varying networks

Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an ``adaptive threshold,'' i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

Computational framework to integrate the effect of antigen recognition on disease epidemiology outcome: multi-scale approach

Human Leukocyte Antigen (HLA) plays an important role, in presenting foreign pathogens to our immune system, there by eliciting early immune responses. HLA genes are highly polymorphic, giving rise to diverse antigen presentation capability. An important factor contributing to enormous variations in individual responses to diseases is differences in their HLA profiles. The heterogeneity in allele specific disease responses decides the overall disease epidemiological outcome. Here we propose an agent based computational framework, capable of incorporating allele specific information, to analyze disease epidemiology. This framework assumes a SIR model to estimate average disease transmission and recovery rate. Using epitope prediction tool, it performs sequence based epitope detection for a given the pathogenic genome and derives an allele specific disease susceptibility index depending on the epitope detection efficiency. The allele specific disease transmission rate, that follows, is then fed to the agent based epidemiology model, to analyze the disease outcome. The methodology presented here has a potential use in understanding how a disease spreads and effective measures to control the disease.

l(1)-K-SVD: A robust dictionary learning algorithm with simultaneous update

We develop a new dictionary learning algorithm called the l(1)-K-svp, by minimizing the l(1) distortion on the data term. The proposed formulation corresponds to maximum a posteriori estimation assuming a Laplacian prior on the coefficient matrix and additive noise, and is, in general, robust to non-Gaussian noise. The l(1) distortion is minimized by employing the iteratively reweighted least-squares algorithm. The dictionary atoms and the corresponding sparse coefficients are simultaneously estimated in the dictionary update step. Experimental results show that l(1)-K-SVD results in noise-robustness, faster convergence, and higher atom recovery rate than the method of optimal directions, K-SVD, and the robust dictionary learning algorithm (RDL), in Gaussian as well as non-Gaussian noise. For a fixed value of sparsity, number of dictionary atoms, and data dimension, l(1)-K-SVD outperforms K-SVD and RDL on small training sets. We also consider the generalized l(p), 0 < p < 1, data metric to tackle heavy-tailed/impulsive noise. In an image denoising application, l(1)-K-SVD was found to result in higher peak signal-to-noise ratio (PSNR) over K-SVD for Laplacian noise. The structural similarity index increases by 0.1 for low input PSNR, which is significant and demonstrates the efficacy of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.

Stress-induced phase transformation and pseudo-elastic/pseudo-plastic recovery in intermetallic Ni-Al nanowires

Extensive molecular dynamics (MD) simulations have been performed in a B2-NiAl nanowire using an embedded atom method (EAM) potential. We show a stress induced B2 -> body-centered-tetragonal (BCT) phase transformation and a novel temperature and cross-section dependent pseudo-elastic/pseudo-plastic recovery from such an unstable BCT phase with a recoverable strain of similar to 30% as compared to 5-8% in polycrystalline materials. Such a temperature and cross-section dependent pseudo-elastic/pseudo-plastic strain recovery can be useful in various interesting applications of shape memory and strain sensing in nanoscale devices. Effects of size, temperature, and strain rate on the structural and mechanical properties have also been analyzed in detail. For a given size of the nanowire the yield stress of both the B2 and the BCT phases is found to decrease with increasing temperature, whereas for a given temperature and strain rate the yield stress of both the B2 and the BCT phase is found to increase with increase in the cross-sectional dimensions of the nanowire. A constant elastic modulus of similar to 80 GPa of the B2 phase is observed in the temperature range of 200-500 K for nanowires of cross-sectional dimensions in the range of 17.22-28.712 angstrom, whereas the elastic modulus of the BCT phase shows a decreasing trend with an increase in the temperature.

Influence of Cooling Rate on the Enthalpy Relaxation and Fragility of a Metallic Glass

Structural relaxation behavior of a rapidly quenched (RQ) and a slowly cooled Pd40Cu30Ni10P20 metallic glass was investigated and compared. Differential scanning calorimetry was employed to monitor the relaxation enthalpies at the glass transition temperature, T-g , and the Kolrausch-Williams-Watts (KWW) stretched exponential function was used to describe its variation with annealing time. It was found that the rate of enthalpy recovery is higher in the ribbon, implying that the bulk is more resistant to relaxation at low temperatures of annealing. This was attributed to the possibility of cooling rate affecting the locations where the glasses get trapped within the potential energy landscape. The RQ process traps a larger amount of free volume, resulting in higher fragility, and in turn relaxes at the slightest thermal excitation (annealing). The slowly cooled bulk metallic glass (BMG), on the other hand, entraps lower free volume and has more short-range ordering, hence requiring a large amount of perturbation to access lower energy basins.

A novel fiber-coated strong base-type anion exchanger with superfast kinetics. Removal and recovery of silver thiosulfate from aqueous solutions

A commercial acrylic fiber with 92% (w/w) acrylonitrile content was partially hydrolyzed converting a fraction of the nitrile (-CN) groups to carboxylic acid (-COOH) groups, to coat the fiber with polyethylenimine (PEI) resin, which was then crosslinked with glutaraldehyde and further quaternized with ethyl chloroacetate to produce a novel strong-base anionic exchanger in the form of fiber. Designated as PAN(QPEI.XG)(Cl-), the fibrous sorbent was compared with a commercial bead-form resin Amberlite IRA-458(Cl-) in respect of sorption capacity, selectivity, and kinetics for removal of silver thiosulfate complexes from aqueous solutions. Though the saturation level of [Ag(S2O3)(2)](3-) on PAN(QPEI.XG)(Cl-) is considerably less than that on IRA-458(Cl-), the gel-coated fibrous sorbent exhibits, as compared to the bead-form sorbent, a significantly higher sorption selectivity for the silver thiosulfate complex in the presence of excess of other anions Such as S2O32-, SO42-, and Cl-, and a remarkably faster rate of both sorption and stripping. The initial uptake of the sorbate by the fibrous sorbent is nearly instantaneous, reaching up to similar to 80% of the saturation capacity within 10 s, as compared to only similar to 12% on the bead-form sorbent. The high initial rate of uptake fits a shell-core kinetic model for sorption on fiber of cylindrical geometry. With 4M HCl, the stripping of the sorbed silver complex from the fibrous sorbent is clean and nearly instantaneous, while, in contrast, a much slower rate of stripping on the bead-form sorbent leads to its fouling due to a slow decomposition of the silver thiosulfate complex in the acidic medium.

The influence of temperature and strain rate on the deformation response and microstructural evolution during hot compression of a titanium alloy Ti-6Al-4V-0.1B

Hot deformation behavior of a hypoeutectic Ti-6Al-4V-0.1B alloy in (alpha + beta) phase field is investigated in the present study with special reference to flow response, kinetics and microstructural evolution. For a comparison, the base alloy Ti-6Al-4V was also studied under identical conditions. Dynamic recovery of alpha phase occurs at low temperatures while softening due to globularization and/or dynamic recrystallization dominates at high temperatures irrespective of boron addition. Microstructural features for both the alloys display bending and kinking of alpha lamellae for near alpha test temperatures. Unlike Ti-6Al-4V, no sign of instability formation was observed in Ti-6Al-4V-0.1B for any deformation condition except for cavitation around TiB particles, due to deformation incompatibility and strain accumulation at the particle-matrix interface. The absence of macroscopic instabilities and early initiation of softening mechanisms as a result of boron addition has been attributed to microstructural features (e.g. refined prior beta grain and alpha colony size, absence of grain boundary alpha layer, presence of TiB particles at prior beta boundaries, etc.) of the respective alloys prior to deformation. (C) 2012 Elsevier B.V. All rights reserved.

Modified Greedy Pursuits for Improving Sparse Recovery

Compressive Sensing (CS) theory combines the signal sampling and compression for sparse signals resulting in reduction in sampling rate. In recent years, many recovery algorithms have been proposed to reconstruct the signal efficiently. Subspace Pursuit and Compressive Sampling Matching Pursuit are some of the popular greedy methods. Also, Fusion of Algorithms for Compressed Sensing is a recently proposed method where several CS reconstruction algorithms participate and the final estimate of the underlying sparse signal is determined by fusing the estimates obtained from the participating algorithms. All these methods involve solving a least squares problem which may be ill-conditioned, especially in the low dimension measurement regime. In this paper, we propose a step prior to least squares to ensure the well-conditioning of the least squares problem. Using Monte Carlo simulations, we show that in low dimension measurement scenario, this modification improves the reconstruction capability of the algorithm in clean as well as noisy measurement cases.

Population Recovery of Nicobar Long-Tailed Macaque Macaca fascicularis umbrosus following a Tsunami in the Nicobar Islands, India

Natural disasters pose a threat to isolated populations of species with restricted distributions, especially those inhabiting islands. The Nicobar long tailed macaque. Macaca fascicularis umbrosus, is one such species found in the three southernmost islands (viz. Great Nicobar, Little Nicobar and Katchal) of the Andaman and Nicobar archipelago, India. These islands were hit by a massive tsunami (Indian Ocean tsunami, 26 December 2004) after a 9.2 magnitude earthquake. Earlier studies Umapathy et al. 2003; Sivakumar, 2004] reported a sharp decline in the population of M. f. umbrosus after thetsunami. We studied the distribution and population status of M. f. umbrosus on thethree Nicobar Islands and compared our results with those of the previous studies. We carried out trail surveys on existing paths and trails on three islands to get encounter rate as measure of abundance. We also checked the degree of inundation due to tsunami by using Normalized Difference Water Index (NDWI) on landsat imageries of the study area before and after tsunami. Theencounter rate of groups per kilometre of M. f. umbrosus in Great Nicobar, Little Nicobar and Katchal was 0.30, 0.35 and 0.48 respectively with the mean group size of 39 in Great Nicobar and 43 in Katchal following the tsunami. This was higher than that reported in the two earlier studies conducted before and after the tsunami. Post tsunami, there was a significant change in the proportion of adult males, adult females and immatures, but mean group size did not differ as compared to pre tsunami. The results show that population has recovered from a drastic decline caused by tsunami, but it cannot be ascertained whether it has reached stability because of the altered group structure. This study demonstrates the effect of natural disasters on island occurring species.

Mechanical processing and microstructural control in hot working of hot isostatically pressed P/M IN-100 superalloy

The hot deformation behavior of hot isostatically pressed (HIPd) P/M IN-100 superalloy has been studied in the temperature range 1000-1200 degrees C and strain rate range 0.0003-10 s(-1) using hot compression testing. A processing map has been developed on the basis of these data and using the principles of dynamic materials modelling. The map exhibited three domains: one at 1050 degrees C and 0.01 s(-1), with a peak efficiency of power dissipation of approximate to 32%, the second at 1150 degrees C and 10 s(-1), with a peak efficiency of approximate to 36% and the third at 1200 degrees C and 0.1 s(-1), with a similar efficiency. On the basis of optical and electron microscopic observations, the first domain was interpreted to represent dynamic recovery of the gamma phase, the second domain represents dynamic recrystallization (DRX) of gamma in the presence of softer gamma', while the third domain represents DRX of the gamma phase only. The gamma' phase is stable upto 1150 degrees C, gets deformed below this temperature and the chunky gamma' accumulates dislocations, which at larger strains cause cracking of this phase. At temperatures lower than 1080 degrees C and strain rates higher than 0.1 s(-1), the material exhibits flow instability, manifested in the form of adiabatic shear bands. The material may be subjected to mechanical processing without cracking or instabilities at 1200 degrees C and 0.1 s(-1), which are the conditions for DRX of the gamma phase.

Free Energy Gap Dependence of the Electron-Transfer Rate from the Inverted to the Normal Region

numerical study of the free energy gap (FEG) dependence of the electron-transfer rate in polar solvents is presented. This study is based on the generalized multidimensional hybrid model, which not only includes the solvent polarization and the molecular vibration modes, but also the biphasic polar response of the solvent. The free energy gap dependence is found to be sensitive to several factors, including the solvent relaxation rate, the electronic coupling between the surfaces, the frequency of the high-frequency quantum vibrational mode, and the magnitude of the solvent reorganization energy. It is shown that in some cases solvent relaxation can play an important role even in the Marcus normal regime. The minimal hybrid model involves a large number of parameters, giving rise to a diverse non-Marcus FEG behavior which is often determined collectively by these parameters. The model gives the linear free energy gap dependence of the logarithmic rate over a substantial range of FEG, spanning from the normal to the inverted regime. However, even for favorable values of the relevant parameters, a linear free energy gap dependence of the rate could be obtained only over a range of 5000-6000 cm(-1) (compared to the experimentally observed range of 10000 cm(-1) reported by Benniston et al.). The present work suggests several extensions/generalizations of the hybrid model which might be necessary to fully understand the observed free energy gap dependence.

High-temperature deformation processing of Ti-24Al-20Nb

Power dissipation maps have been generated in the temperature range of 900 degrees C to 1150 degrees C and strain rate range of 10(-3) to 10 s(-1) for a cast aluminide alloy Ti-24Al-20Nb using dynamic material model. The results define two distinct regimes of temperature and strain rate in which efficiency of power dissipation is maximum. The first region, centered around 975 degrees C/0.1 s(-1), is shown to correspond to dynamic recrystallization of the alpha(2) phase and the second, centered around 1150 degrees C/0.001 s(-1), corresponds to dynamic recovery and superplastic deformation of the beta phase. Thermal activation analysis using the power law creep equation yielded apparent activation energies of 854 and 627 kJ/mol for the first and second regimes, respectively. Reanalyzing the data by alternate methods yielded activation energies in the range of 170 to 220 kJ/mol and 220 to 270 kJ/mol for the first and second regimes, respectively. Cross slip was shown to constitute the activation barrier in both cases. Two distinct regimes of processing instability-one at high strain rates and the other at the low strain rates in the lower temperature regions-have been identified, within which shear bands are formed.

Optimal barrier subdivision for Kramers' escape rate

We examine the effect of subdividing the potential barrier along the reaction coordinate on Kramers' escape rate for a model potential. Using the known supersymmetric potential approach, we show the existence of an optimal number of subdivisions that maximizes the rate.

Oxygen transfer and energy dissipation rate in surface aerator

The dissipation rate of turbulent kinetic energy (epsilon) is a key parameter for mixing in surface aerators. In particular, determination epsilon across the impeller stream, where the most intensive mixing takes place, is essential to ascertain that an appropriate degree of mixing is achieved. Present work by using commercial software VisiMix (R) calculates the energy dissipation rate in geometrically similar unbaffled surface aeration systems in order to scale-up the oxygen transfer process. It is found that in geometrically similar system, oxygen transfer rate is uniquely correlated with dissipation rate of energy. Simulation or scale-up equation governing oxygen transfer rate and dissipation rate of energy has been developed in the present work.

Oxygen transfer and energy dissipation rate in surface aerator

The dissipation rate of turbulent kinetic energy(e)is a key parameter for mixing in surface aerators. In particular, determination e across the impeller stream, where the most intensive mixing takes place, is essential to ascertain that an appropriate degree of mixing is achieved. Present work by using commercial software VisiMix calculates the energy dissipation rate in geometrically similar unbaffled surface aeration systems in order to scale-up the oxygen transfer process. It is found that in geometrically similar system,oxygen transfer rate is uniquely correlated with dissipation rate of energy. Simulation or scale-up equation governing oxygen transfer rate and dissipation rate of energy has been developed in the present work.