Spin-orbit induced longitudinal spin-polarized currents in non-magnetic solids

For certain non-magnetic solids with low symmetry the occurrence of spin-polarized longitudinal currents is predicted. These arise due to an interplay of spin-orbit interaction and the particular crystal symmetry. This result is derived using a group-theoretical scheme that allows investigating the symmetry properties of any linear response tensor relevant to the field of spintronics. For the spin conductivity tensor it is shown that only the magnetic Laue group has to be considered in this context. Within the introduced general scheme also the spin Hall- and additional related transverse effects emerge without making reference to the two-current model. Numerical studies confirm these findings and demonstrate for (Au$_{1-x}$Pt$_{\rm x}$)$_4$Sc that the longitudinal spin conductivity may be in the same order of magnitude as the conventional transverse one. The presented formalism only relies on the magnetic space group and therefore is universally applicable to any type of magnetic order.Comment: 5 pages, 1 table, 2 figures (3 & 2 subfigures

Thermal noise influences fluid flow in thin films during spinodal dewetting

Experiments on dewetting thin polymer films confirm the theoretical prediction that thermal noise can strongly influence characteristic time-scales of fluid flow and cause coarsening of typical length scales. Comparing the experiments with deterministic simulations, we show that the Navier-Stokes equation has to be extended by a conserved bulk noise term to accomplish the observed spectrum of capillary waves. Due to thermal fluctuations the spectrum changes from an exponential to a power law decay for large wavevectors. Also the time evolution of the typical wavevector of unstable perturbations exhibits noise induced coarsening that is absent in deterministic hydrodynamic flow.Comment: 4 pages, 3 figure

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

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

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

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

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

RNA secondary structure prediction from multi-aligned sequences

It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.Comment: A preprint of an invited review manuscript that will be published in a chapter of the book `Methods in Molecular Biology'. Note that this version of the manuscript may differ from the published versio