Dynamic properties of Lennard Jones fluids and liquid metals

The dependence of the dynamic properties of liquid metals and Lennard-Jones fluids on the characteristics of the interaction potentials is analyzed. Molecular-dynamics simulations of liquids in analogous conditions but assuming that their particles interact either through a Lennard-Jones or a liquid-metal potential were carried out. The Lennard-Jones potentials were chosen so that both the effective size of the particles and the depth of the potential well were very close to those of the liquid-metal potentials. In order to investigate the extent to which the dynamic properties of liquids depend on the short-range attractive interactions as well as on the softness of the potential cores, molecular-dynamics simulations of the same systems but assuming purely repulsive interactions with the same potential cores were also performed. The study includes both singleparticle dynamic properties, such as the velocity autocorrelation functions, and collective dynamic properties, such as the intermediate scattering funcfunctions, and collective dynamic properties, such as the intermediate scattering functions, the dynamic structure factors, the longitudinal and transverse current correlations, and the transport coefficients.

Stochastic resonance in nonpotential systems

We propose a method to analytically show the possibility for the appearance of a maximum in the signal-to-noise ratio in nonpotential systems. We apply our results to the FitzHugh-Nagumo model under a periodic external forcing, showing that the model exhibits stochastic resonance. The procedure that we follow is based on the reduction to a one-dimensional dynamics in the adiabatic limit and in the topology of the phase space of the systems under study. Its application to other nonpotential systems is also discussed.

Stochastic resonance in a system of magnetic particles

We show that a dispersion of monodomain ferromagnetic particles in a solid phase exhibits stochastic resonance when a driven linearly polarized magnetic field is applied. By using an adiabatic approach, we calculate the power spectrum, the distribution of residence times, and the mean first passage time. The behavior of these quantities is similar to the behavior of corresponding quantities in other systems where stochastic resonance has also been observed.

Improving Offender Programming, Data Download, Iowa Department of Corrections, June 2012

In 2008, the Iowa Department of Corrections embarked on a comprehensive audit of all institutional andcommunity corrections offender programs that receive corrections funding. The audit focused on the degree towhich each program adheres to evidence-based practices principles (what works best). The audit areas are listedbelow along with some examples of the questions asked about each program:

Data-driven clustering : new methods and applications

Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

Postmortem dynamic CT-angiography : P30

Purpose: Forensic imaging and especially forensic radiology is a new trend in forensic medicine. More and more forensic institutes set up their own CT-scanner in order to perform postmortem cross-sectional imaging. Due to this trend, a new subspecialty was born: the forensic radiology. To image the vascular system after death, a postmortem CT- angiography can be performed. Methods and materials: In the Institute of Forensic Medicine in Lausanne, a science group has been created with specialists of different medical fields that has set up a new technique of forensic CT-angiography. The method consists in the creation of a postmortem circulation by the use of a modified heart lung machine. As circulating liquid Angiofil, an oily contrast agent, is injected. Results: With the aid of this technique, the whole vascular system of a deceased person can be imaged in detail without autopsy. The circulating contrast allows demonstrating the vascular system when it is under pressure, similarly to living patients. First experiences showed, that vascular pathologies such as cardiac tamponade and aortic dissection can be well demonstrated. Since the oily Angiofil strictly remains in the intravascular space, no artifacts had been observed during the CT-examination and the later performed autopsy. Conclusion: Post-mortem dynamic CT angiography is of great advantage in forensic pathology, because the detailed mapping of the entire vascular system is almost impossible with conventional autopsy tools.

New Violence Risk Assessment Aids Parole and Offender Programming Decisions, Data Download, Department of Corrections

In recent years, the Department of Corrections has made major strides in assessing offenders’ risk to reoffend, particularly in measuring changes in that risk over time. Earlier this year, the DOC worked with the Board of Parole to develop a risk assessment that focuses on assessing offenders’ risk to commit violent crimes.

Stochastic generation of homogeneous isotropic turbulence with well-defined-spectra

A precise and simple computational model to generate well-behaved two-dimensional turbulent flows is presented. The whole approach rests on the use of stochastic differential equations and is general enough to reproduce a variety of energy spectra and spatiotemporal correlation functions. Analytical expressions for both the continuous and the discrete versions, together with simulation algorithms, are derived. Results for two relevant spectra, covering distinct ranges of wave numbers, are given.

Reaction-diffusion fronts under stochastic advection

We study front propagation in stirred media using a simplified modelization of the turbulent flow. Computer simulations reveal the existence of the two limiting propagation modes observed in recent experiments with liquid phase isothermal reactions. These two modes respectively correspond to a wrinkled although sharp propagating interface and to a broadened one. Specific laws relative to the enhancement of the front velocity in each regime are confirmed by our simulations.

Self-organizing propagation patterns from dynamic self-assembly in monolayers

Propagation of localized orientational waves, as imaged by Brewster angle microscopy, is induced by low intensity linearly polarized light inside axisymmetric smectic-C confined domains in a photosensitive molecular thin film at the air/water interface (Langmuir monolayer). Results from numerical simulations of a model that couples photoreorientational effects and long-range elastic forces are presented. Differences are stressed between our scenario and the paradigmatic wave phenomena in excitable chemical media.

Further insights on dynamic morphological transitions in quasi-two-dimensional electrodeposition

Dynamic morphological transitions in thin-layer electrodeposits obtained from copper sulphate solutions have been studied. The chemical composition of the electrodeposits indicates that they appear as a consequence of the competition between copper and cuprous oxide formation. In addition, the Ohmic control of the process is verified at initial stages of the deposit growth. At higher deposit developments, gravity-induced convection currents play a role in the control of the whole process and affect the position of these transitions.

Generation of dynamic structures in nonequilibrium reactive membranes

We present a nonequlibrium approach for the study of a flexible bilayer whose two components induce distinct curvatures. In turn, the two components are interconverted by an externally promoted reaction. Phase separation of the two species in the surface results in the growth of domains characterized by different local composition and curvature modulations. This domain growth is limited by the effective mixing due to the interconversion reaction, leading to a finite characteristic domain size. In addition to these effects, first introduced in our earlier work [ Phys. Rev. E 71 051906 (2005)], the important new feature is the assumption that the reactive process actively affects the local curvature of the bilayer. Specifically, we suggest that a force energetically activated by external sources causes a modification of the shape of the membrane at the reaction site. Our results show the appearance of a rich and robust dynamical phenomenology that includes the generation of traveling and/or oscillatory patterns. Linear stability analysis, amplitude equations, and numerical simulations of the model kinetic equations confirm the occurrence of these spatiotemporal behaviors in nonequilibrium reactive bilayers.

Diffusion of passive scalars under stochastic convection

The diffusion of passive scalars convected by turbulent flows is addressed here. A practical procedure to obtain stochastic velocity fields with well¿defined energy spectrum functions is also presented. Analytical results are derived, based on the use of stochastic differential equations, where the basic hypothesis involved refers to a rapidly decaying turbulence. These predictions are favorable compared with direct computer simulations of stochastic differential equations containing multiplicative space¿time correlated noise.