Fourier´s law from a chain of coupled anharmonic oscillators under energy conserving shot noise.

We analyze the transport of heat along a chain of particles interacting through anharmonic potentials consisting of quartic terms in addition to harmonic quadratic terms and subject to heat reservoirs at its ends. Each particle is also subject to an impulsive shot noise with exponentially distributed waiting times whose effect is to change the sign of its velocity, thus conserving the energy of the chain. We show that the introduction of this energy conserving stochastic noise leads to Fourier's law. That is for large system size L the heat current J behaves as J ‘approximately’ 1/L, which amounts to say that the conductivity k is constant. The conductivity is related to the current by J = kΔT/L, where ΔT is the difference in the temperatures of the reservoirs. The behavior of heat conductivity k for small intensities¸ of the shot noise and large system sizes L are obtained by assuming a scaling behavior of the type k = ‘L POT a Psi’(L’lambda POT a/b’) where a and b are scaling exponents. For the pure harmonic case a = b = 1, characterizing a ballistic conduction of heat when the shot noise is absent. For the anharmonic case we found values for the exponents a and b smaller then 1 and thus consistent with a superdiffusive conduction of heat without the shot noise. We also show that the heat conductivity is not constant but is an increasing function of temperature.

Heat conduction in a chain of harmonic and anharmonic oscillators under the presence of an energy conserving noise

Reproducing Fourier's law of heat conduction from a microscopic stochastic model is a long standing challenge in statistical physics. As was shown by Rieder, Lebowitz and Lieb many years ago, a chain of harmonically coupled oscillators connected to two heat baths at different temperatures does not reproduce the diffusive behaviour of Fourier's law, but instead a ballistic one with an infinite thermal conductivity. Since then, there has been a substantial effort from the scientific community in identifying the key mechanism necessary to reproduce such diffusivity, which usually revolved around anharmonicity and the effect of impurities. Recently, it was shown by Dhar, Venkateshan and Lebowitz that Fourier's law can be recovered by introducing an energy conserving noise, whose role is to simulate the elastic collisions between the atoms and other microscopic degrees of freedom, which one would expect to be present in a real solid. For a one-dimensional chain this is accomplished numerically by randomly flipping - under the framework of a Poisson process with a variable “rate of collisions" - the sign of the velocity of an oscillator. In this poster we present Langevin simulations of a one-dimensional chain of oscillators coupled to two heat baths at different temperatures. We consider both harmonic and anharmonic (quartic) interactions, which are studied with and without the energy conserving noise. With these results we are able to map in detail how the heat conductivity k is influenced by both anharmonicity and the energy conserving noise. We also present a detailed analysis of the behaviour of k as a function of the size of the system and the rate of collisions, which includes a finite-size scaling method that enables us to extract the relevant critical exponents. Finally, we show that for harmonic chains, k is independent of temperature, both with and without the noise. Conversely, for anharmonic chains we find that k increases roughly linearly with the temperature of a given reservoir, while keeping the temperature difference fixed.

Irreversibility by competition on a Glauber-Ising model by means of the entropy production.

An out of equilibrium Ising model subjected to an irreversible dynamics is analyzed by means of a stochastic dynamics, on a effort that aims to understand the observed critical behavior as consequence of the intrinsic microscopic characteristics. The study focus on the kinetic phase transitions that take place by assuming a lattice model with inversion symmetry and under the influence of two competing Glauber dynamics, intended to describe the stationary states using the entropy production, which characterize the system behavior and clarifies its reversibility conditions. Thus, it is considered a square lattice formed by two sublattices interconnected, each one of which is in contact with a heat bath at different temperature from the other. Analytical and numerical treatments are faced, using mean-field approximations and Monte Carlo simulations. For the one dimensional model exact results for the entropy production were obtained, though in this case the phase transition that takes place in the two dimensional counterpart is not observed, fact which is in accordance with the behavior shared by lattice models presenting inversion symmetry. Results found for the stationary state show a critical behavior of the same class as the equilibrium Ising model with a phase transition of the second order, which is evidenced by a divergence with an exponent µ ¼ 0:003 of the entropy production derivative.

Subcutaneous Tissue Thickness is an Independent Predictor of Image Noise in Cardiac CT

Background: Few data on the definition of simple robust parameters to predict image noise in cardiac computed tomography (CT) exist. Objectives: To evaluate the value of a simple measure of subcutaneous tissue as a predictor of image noise in cardiac CT. Methods: 86 patients underwent prospective ECG-gated coronary computed tomographic angiography (CTA) and coronary calcium scoring (CAC) with 120 kV and 150 mA. The image quality was objectively measured by the image noise in the aorta in the cardiac CTA, and low noise was defined as noise < 30HU. The chest anteroposterior diameter and lateral width, the image noise in the aorta and the skin-sternum (SS) thickness were measured as predictors of cardiac CTA noise. The association of the predictors and image noise was performed by using Pearson correlation. Results: The mean radiation dose was 3.5 ± 1.5 mSv. The mean image noise in CT was 36.3 ± 8.5 HU, and the mean image noise in non-contrast scan was 17.7 ± 4.4 HU. All predictors were independently associated with cardiac CTA noise. The best predictors were SS thickness, with a correlation of 0.70 (p < 0.001), and noise in the non-contrast images, with a correlation of 0.73 (p < 0.001). When evaluating the ability to predict low image noise, the areas under the ROC curve for the non-contrast noise and for the SS thickness were 0.837 and 0.864, respectively. Conclusion: Both SS thickness and CAC noise are simple accurate predictors of cardiac CTA image noise. Those parameters can be incorporated in standard CT protocols to adequately adjust radiation exposure.

Optimization of thin noise barrier designs using Evolutionary Algorithms and a Dual BEM Formulation

[EN]This works aims at assessing the acoustic efficiency of differente this noise barrier models. These designs frequently feature complex profiles and their implementarion in shape optimization processes may not always be easy in terms of determining their topological feasibility. A methodology to conduct both overall shape and top edge optimisations of thin cross section acoustic barriers by idealizing them as profiles with null boundary thickness is proposed.

Noisy Oncology: applications of bounded noise transitions in modelling tumor growth

I tumori macroscopici e microscopici, dopo la loro prima fase di crescita, sono composti da un numero medio elevato di cellule. Così, in assenza di perturbazioni esterne, la loro crescita e i punti di equilibrio possono essere descritti da equazioni differenziali. Tuttavia, il tumore interagisce fortemente col macroambiente che lo circonda e di conseguenza una descrizione del tutto deterministica risulta a volte inappropriata. In questo caso si può considerare l'interazione con fluttuazioni statistiche, causate da disturbi esterni, utilizzando le equazioni differenziali stocastiche (SDE). Questo è vero in modo particolare quando si cerca di modellizzare tumori altamente immunogenici che interagiscono con il sistema immunitario, in quanto la complessità di questa interazione risulta in fenomeni di multistabilità. Così, il rumore può provocare disturbi e indurre transizioni di stato (Noise-Induced-Transitions). E' importante notare che una NIT può avere implicazioni profonde sulla vita di un paziente, dal momento che una transizione da uno stato di equilibrio piccolo, nelle dimensioni del tumore, ad uno stato di equilibrio macroscopico, nella maggior parte dei casi significa il passaggio dalla vita alla morte. Generalmente l'approccio standard è quello di modellizzare le fluttuazioni stocastiche dei parametri per mezzo di rumore gaussiano bianco o colorato. In alcuni casi però questa procedura è altamente inadeguata, a causa della illimitatezza intrinseca dei rumori gaussiani che può portare a gravi incongruenze biologiche: pertanto devono essere utilizzati dei rumori "limitati", che, tuttavia, sono molto meno studiati di quelli gaussiani. Inoltre, l'insorgenza di NIT dipende dal tipo di rumore scelto, che rivela un nuovo livello di complessità in biologia. Lo scopo di questa tesi è quello di studiare le applicazioni di due tipi diversi di "rumori limitati" nelle transizioni indotte in due casi: interazione tra tumore e sistema immunitario e chemioterapia dei tumori. Nel primo caso, abbiamo anche introdotto un nuovo modello matematico di terapia, che estende, in modo nuovo, il noto modello di Norton-Simon.

Nonlinear three-dimensional noise filter with low-dose CT angiography: effect on the detection of small high-contrast objects in a phantom model

To study the effect of a nonlinear noise filter on the detection of simulated endoleaks in a phantom with 80- and 100-kVp multidetector computed tomographic (CT) angiography.

Dose modulated retrospective ECG-gated versus non-gated 64-row CT angiography of the aorta at the same radiation dose: Comparison of motion artifacts, diagnostic confidence and signal-to-noise-ratios

To compare ECG-gated and non-gated CT angiography of the aorta at the same radiation dose, with regard to motion artifacts (MA), diagnostic confidence (DC) and signal-to-noise-ratios (SNRs).

Performance Tuning Non-Uniform Sampling for Sensitivity Enhancement of Signal-Limited Biological NMR

Non-uniform sampling (NUS) has been established as a route to obtaining true sensitivity enhancements when recording indirect dimensions of decaying signals in the same total experimental time as traditional uniform incrementation of the indirect evolution period. Theory and experiments have shown that NUS can yield up to two-fold improvements in the intrinsic signal-to-noise ratio (SNR) of each dimension, while even conservative protocols can yield 20-40 % improvements in the intrinsic SNR of NMR data. Applications of biological NMR that can benefit from these improvements are emerging, and in this work we develop some practical aspects of applying NUS nD-NMR to studies that approach the traditional detection limit of nD-NMR spectroscopy. Conditions for obtaining high NUS sensitivity enhancements are considered here in the context of enabling H-1,N-15-HSQC experiments on natural abundance protein samples and H-1,C-13-HMBC experiments on a challenging natural product. Through systematic studies we arrive at more precise guidelines to contrast sensitivity enhancements with reduced line shape constraints, and report an alternative sampling density based on a quarter-wave sinusoidal distribution that returns the highest fidelity we have seen to date in line shapes obtained by maximum entropy processing of non-uniformly sampled data.