Reanalysis of the FEROS observations of HIP 11952

Aims. We reanalyze FEROS observations of the star HIP 11952 to reassess the existence of the proposed planetary system. Methods. The radial velocity of the spectra were measured by cross-correlating the observed spectrum with a synthetic template. We also analyzed a large dataset of FEROS and HARPS archival data of the calibrator HD 10700 spanning over more than five years. We compared the barycentric velocities computed by the FEROS and HARPS pipelines. Results. The barycentric correction of the FEROS-DRS pipeline was found to be inaccurate and to introduce an artificial one-year period with a semi-amplitude of 62 m/s. Thus the reanalysis of the FEROS data does not support the existence of planets around HIP 11952.Comment: 7 pages, 8 figures, 1 tabl

DotAligner:Identification and clustering of RNA structure motifs

Abstract The diversity of processed transcripts in eukaryotic genomes poses a challenge for the classification of their biological functions. Sparse sequence conservation in non-coding sequences and the unreliable nature of RNA structure predictions further exacerbate this conundrum. Here, we describe a computational method, DotAligner, for the unsupervised discovery and classification of homologous RNA structure motifs from a set of sequences of interest. Our approach outperforms comparable algorithms at clustering known RNA structure families, both in speed and accuracy. It identifies clusters of known and novel structure motifs from ENCODE immunoprecipitation data for 44 RNA-binding proteins

Cardiac cell modelling: Observations from the heart of the cardiac physiome project

In this manuscript we review the state of cardiac cell modelling in the context of international initiatives such as the IUPS Physiome and Virtual Physiological Human Projects, which aim to integrate computational models across scales and physics. In particular we focus on the relationship between experimental data and model parameterisation across a range of model types and cellular physiological systems. Finally, in the context of parameter identification and model reuse within the Cardiac Physiome, we suggest some future priority areas for this field

Mapping QGP properties in Pb--Pb and Xe--Xe collisions at the LHC

A phenomenological analysis of the experimental measurements of transverse momentum spectra of identified charged hadrons and strange hyperons in \PbPb and \XeXe collisions at the LHC is presented. The analysis is based on the relativistic fluid dynamics description implemented in the numerically efficient \fluidum approach. Building on our previous work, we separate in our treatment the chemical and kinetic freeze-out, and incorporate the partial chemical equilibrium to describe the late stages of the collision evolution. This analysis makes use of Bayesian inference to determine key parameters of the QGP evolution and its properties including the shear and bulk viscosity to entropy ratios, the initialisation time, the initial entropy density, and the freeze-out temperatures. The physics parameters and their posterior probabilities are extracted using a global search in multidimensional space with modern machine learning tools, such as ensembles of neural networks. We employ our newly developed fast framework to assess systematic uncertainties in the extracted model parameters by systematically varying key components of our analysis.Comment: 17 pages, 7 figure

Thin film evolution equations from (evaporating) dewetting liquid layers to epitaxial growth

In the present contribution we review basic mathematical results for three physical systems involving self-organising solid or liquid films at solid surfaces. The films may undergo a structuring process by dewetting, evaporation/condensation or epitaxial growth, respectively. We highlight similarities and differences of the three systems based on the observation that in certain limits all of them may be described using models of similar form, i.e., time evolution equations for the film thickness profile. Those equations represent gradient dynamics characterized by mobility functions and an underlying energy functional. Two basic steps of mathematical analysis are used to compare the different system. First, we discuss the linear stability of homogeneous steady states, i.e., flat films; and second the systematics of non-trivial steady states, i.e., drop/hole states for dewetting films and quantum dot states in epitaxial growth, respectively. Our aim is to illustrate that the underlying solution structure might be very complex as in the case of epitaxial growth but can be better understood when comparing to the much simpler results for the dewetting liquid film. We furthermore show that the numerical continuation techniques employed can shed some light on this structure in a more convenient way than time-stepping methods. Finally we discuss that the usage of the employed general formulation does not only relate seemingly not related physical systems mathematically, but does as well allow to discuss model extensions in a more unified way

Diffusive and ballistic current spin-polarization in magnetron-sputtered L1o-ordered epitaxial FePt

We report on the structural, magnetic, and electron transport properties of a L1o-ordered epitaxial iron-platinum alloy layer fabricated by magnetron-sputtering on a MgO(001) substrate. The film studied displayed a long range chemical order parameter of S~0.90, and hence has a very strong perpendicular magnetic anisotropy. In the diffusive electron transport regime, for temperatures ranging from 2 K to 258 K, we found hysteresis in the magnetoresistance mainly due to electron scattering from magnetic domain walls. At 2 K, we observed an overall domain wall magnetoresistance of about 0.5 %. By evaluating the spin current asymmetry alpha = sigma_up / sigma_down, we were able to estimate the diffusive spin current polarization. At all temperatures ranging from 2 K to 258 K, we found a diffusive spin current polarization of > 80%. To study the ballistic transport regime, we have performed point-contact Andreev-reflection measurements at 4.2 K. We obtained a value for the ballistic current spin polarization of ~42% (which compares very well with that of a polycrystalline thin film of elemental Fe). We attribute the discrepancy to a difference in the characteristic scattering times for oppositely spin-polarized electrons, such scattering times influencing the diffusive but not the ballistic current spin polarization.Comment: 22 pages, 13 figure

Concept and optical design of the cross-disperser module for CRIRES

This is the peer reviewed version of the following article: Oliva, Ernesto, A. Tozzi, D. Ferruzzi, L. Origlia, A. Hatzes, R. Follert, T. Loewinger et al. "Concept and optical design of the cross-disperser module for CRIRES+." In SPIE Astronomical Telescopes+ Instrumentation, pp. 91477R-91477R. International Society for Optics and Photonics, 2014, which has been published in final form at 10.1117/12.2054381

Modeling effects of voltage dependent properties of the cardiac muscarinic receptor on human sinus node function

The cardiac muscarinic receptor (M2R) regulates heart rate, in part, by modulating the ace-tylcholine (ACh) activated K⁺ current I$_{K,ACh}$ through dissociation of G-proteins, that in turn activate K$_{ ACh}$ channels. Recently, M2Rs were noted to exhibit intrinsic voltage sensitivity, i.e. their affinity for ligands varies in a voltage dependent manner. The voltage sensitivity of M2R implies that the affinity for Ach (and thus the Ach effect) varies throughout the time course of a cardiac electrical cycle. The aim of this study was to investigate the contribution of M2R voltage sensitivity to the rate and shape of the human sinus node action potentials in physiological and pathophysiological conditions. We developed a Markovian model of the I$_{K,ACh}$ modulation by voltage and integrated it into a computational model of human sinus node. We performed simulations with the integrated model varying Ach concentration and voltage sensitivity. Low Ach exerted a larger effect on I$_{K,ACh}$ at hyperpolarized versus depolarized membrane voltages. This led to a slowing of the pacemaker rate due to an attenuated slope of phase 4 depolarization with only marginal effect on action potential duration and amplitude. We also simulated the theoretical effects of genetic variants that alter the voltage sensitivity of M2R. Modest negative shifts in voltage sensitivity, predicted to increase the affinity of the receptor for ACh, slowed the rate of phase 4 depolarization and slowed heart rate, while modest positive shifts increased heart rate. These simulations support our hypothesis that altered M2R voltage sensitivity contributes to disease and provide a novel mechanistic foundation to study clinical disorders such as atrial fibrillation and inappropriate sinus tachycardia

Parameter Estimation of Ion Current Formulations Requires Hybrid Optimization Approach to Be Both Accurate and Reliable

Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved the way toward tailored therapies in the last years. To fully leverage in silico models in future research, these models need to be adapted to reflect pathologies, genetic alterations, or pharmacological effects, however. A common approach is to leave the structure of established models unaltered and estimate the values of a set of parameters. Today’s high-throughput patch clamp data acquisition methods require robust, unsupervised algorithms that estimate parameters both accurately and reliably. In this work, two classes of optimization approaches are evaluated: gradient-based trust-region-reflective and derivative-free particle swarm algorithms. Using synthetic input data and different ion current formulations from the Courtemanche et al. electrophysiological model of human atrial myocytes, we show that neither of the two schemes alone succeeds to meet all requirements. Sequential combination of the two algorithms did improve the performance to some extent but not satisfactorily. Thus, we propose a novel hybrid approach coupling the two algorithms in each iteration. This hybrid approach yielded very accurate estimates with minimal dependency on the initial guess using synthetic input data for which a ground truth parameter set exists. When applied to measured data, the hybrid approach yielded the best fit, again with minimal variation. Using the proposed algorithm, a single run is sufficient to estimate the parameters. The degree of superiority over the other investigated algorithms in terms of accuracy and robustness depended on the type of current. In contrast to the non-hybrid approaches, the proposed method proved to be optimal for data of arbitrary signal to noise ratio. The hybrid algorithm proposed in this work provides an important tool to integrate experimental data into computational models both accurately and robustly allowing to assess the often non-intuitive consequences of ion channel-level changes on higher levels of integration