Mocarts: a lightweight radiation transport simulator for easy handling of complex sensing geometries

In functional neuroimaging (fNIRS), elaborated sensing geometries pairing multiple light sources and detectors arranged over the tissue surface are needed. A variety of software tools for probing forward models of radiation transport in tissue exist, but their handling of sensing geometries and specification of complex tissue architectures is, most times, cumbersome. In this work, we introduce a lightweight simulator, Monte Carlo Radiation Transport Simulator (MOCARTS) that attends these demands for simplifying specification of tissue architectures and complex sensing geometries. An object-oriented architecture facilitates such goal. The simulator core is evolved from the Monte Carlo Multi-Layer (mcml) tool but extended to support multi-channel simulations. Verification against mcml yields negligible error (RMSE~4-10e-9) over a photon trajectory. Full simulations show concurrent validity of the proposed tool. Finally, the ability of the new software to simulate multi-channel sensing geometries and to define biological tissue models in an intuitive nested-hierarchy way are exemplified

Temperature dependent magnetization dynamics of magnetic nanoparticles

Recent experimental and theoretical studies show that the switching behavior of magnetic nanoparticles can be well controlled by external time-dependent magnetic fields. In this work, we inspect theoretically the influence of the temperature and the magnetic anisotropy on the spin-dynamics and the switching properties of single domain magnetic nanoparticles (Stoner-particles). Our theoretical tools are the Landau-Lifshitz-Gilbert equation extended as to deal with finite temperatures within a Langevine framework. Physical quantities of interest are the minimum field amplitudes required for switching and the corresponding reversal times of the nanoparticle's magnetic moment. In particular, we contrast the cases of static and time-dependent external fields and analyze the influence of damping for a uniaxial and a cubic anisotropy.Comment: accepted by Journal of Physics: Condensed Matte

OVRO N2H+ Observations of Class 0 Protostars: Constraints on the Formation of Binary Stars

We present the results of an interferometric study of the N2H+(1--0) emission from nine nearby, isolated, low-mass protostellar cores, using the OVRO millimeter array. The main goal of this study is the kinematic characterization of the cores in terms of rotation, turbulence, and fragmentation. Eight of the nine objects have compact N2H+ cores with FWHM radii of 1200 -- 3500 AU, spatially coinciding with the thermal dust continuum emission. The only more evolved (Class I) object in the sample (CB 188) shows only faint and extended N2H+ emission. The mean N2H+ line width was found to be 0.37 km/s. Estimated virial masses range from 0.3 to 1.2 M_sun. We find that thermal and turbulent energy support are about equally important in these cores, while rotational support is negligible. The measured velocity gradients across the cores range from 6 to 24 km/s/pc. Assuming these gradients are produced by bulk rotation, we find that the specific angular momenta of the observed Class 0 protostellar cores are intermediate between those of dense (prestellar) molecular cloud cores and the orbital angular momenta of wide PMS binary systems. There appears to be no evolution (decrease) of angular momentum from the smallest prestellar cores via protostellar cores to wide PMS binary systems. In the context that most protostellar cores are assumed to fragment and form binary stars, this means that most of the angular momentum contained in the collapse region is transformed into orbital angular momentum of the resulting stellar binary systems.Comment: 35 pages, 9 figures (one in color), 6 tables. Accepted by ApJ (to appear in Nov. 2007

Horseshoe-based Bayesian nonparametric estimation of effective population size trajectories

Phylodynamics is an area of population genetics that uses genetic sequence data to estimate past population dynamics. Modern state-of-the-art Bayesian nonparametric methods for recovering population size trajectories of unknown form use either change-point models or Gaussian process priors. Change-point models suffer from computational issues when the number of change-points is unknown and needs to be estimated. Gaussian process-based methods lack local adaptivity and cannot accurately recover trajectories that exhibit features such as abrupt changes in trend or varying levels of smoothness. We propose a novel, locally-adaptive approach to Bayesian nonparametric phylodynamic inference that has the flexibility to accommodate a large class of functional behaviors. Local adaptivity results from modeling the log-transformed effective population size a priori as a horseshoe Markov random field, a recently proposed statistical model that blends together the best properties of the change-point and Gaussian process modeling paradigms. We use simulated data to assess model performance, and find that our proposed method results in reduced bias and increased precision when compared to contemporary methods. We also use our models to reconstruct past changes in genetic diversity of human hepatitis C virus in Egypt and to estimate population size changes of ancient and modern steppe bison. These analyses show that our new method captures features of the population size trajectories that were missed by the state-of-the-art methods.Comment: 36 pages, including supplementary informatio

TEMPORAL AND SPATIAL DISTRIBUTION OF POACEAE POLLEN IN AREAS OF SOUTHERN UNITED KINGDOM, SPAIN AND PORTUGAL

Overall, longer Poaceae pollen seasons coincided with earlier pollen season start dates. Winter rainfall noticeably affects the intensity of Poaceae pollen seasons in Mediterranean areas, but this was not as important in Worcester. Weekly data from Worcester followed a similar pattern to that of Badajoz and Évora but at a distance of more than 1500 km and 4-5 weeks later

Phonon runaway in nanotube quantum dots

We explore electronic transport in a nanotube quantum dot strongly coupled with vibrations and weakly with leads and the thermal environment. We show that the recent observation of anomalous conductance signatures in single-walled carbon nanotube (SWCNT) quantum dots can be understood quantitatively in terms of current driven `hot phonons' that are strongly correlated with electrons. Using rate equations in the many-body configuration space for the joint electron-phonon distribution, we argue that the variations are indicative of strong electron-phonon coupling requiring an analysis beyond the traditional uncorrelated phonon-assisted transport (Tien-Gordon) approach.Comment: 8 pages, 6 figure