1,140 research outputs found

    Spin-orbit coupling and intrinsic spin mixing in quantum dots

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    Spin-orbit coupling effects are studied in quantum dots in InSb, a narrow-gap material. Competition between different Rashba and Dresselhaus terms is shown to produce wholesale changes in the spectrum. The large (and negative) gg-factor and the Rashba field produce states where spin is no longer a good quantum number and intrinsic flips occur at moderate magnetic fields. For dots with two electrons, a singlet-triplet mixing occurs in the ground state, with observable signatures in intraband FIR absorption, and possible importance in quantum computation.Comment: REVTEX4 text with 3 figures (high resolution figs available by request). Submitted to PR

    Identifying a few foot-and-mouth disease virus signature nucleotide strings for computational genotyping

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    <p>Abstract</p> <p>Background</p> <p>Serotypes of the Foot-and-Mouth disease viruses (FMDVs) were generally determined by biological experiments. The computational genotyping is not well studied even with the availability of whole viral genomes, due to uneven evolution among genes as well as frequent genetic recombination. Naively using sequence comparison for genotyping is only able to achieve a limited extent of success.</p> <p>Results</p> <p>We used 129 FMDV strains with known serotype as training strains to select as many as 140 most serotype-specific nucleotide strings. We then constructed a linear-kernel Support Vector Machine classifier using these 140 strings. Under the leave-one-out cross validation scheme, this classifier was able to assign correct serotype to 127 of these 129 strains, achieving 98.45% accuracy. It also assigned serotype correctly to an independent test set of 83 other FMDV strains downloaded separately from NCBI GenBank.</p> <p>Conclusion</p> <p>Computational genotyping is much faster and much cheaper than the wet-lab based biological experiments, upon the availability of the detailed molecular sequences. The high accuracy of our proposed method suggests the potential of utilizing a few signature nucleotide strings instead of whole genomes to determine the serotypes of novel FMDV strains.</p

    Biomechanics-informed Neural Networks for Myocardial Motion Tracking in MRI

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    Image registration is an ill-posed inverse problem which often requires regularisation on the solution space. In contrast to most of the current approaches which impose explicit regularisation terms such as smoothness, in this paper we propose a novel method that can implicitly learn biomechanics-informed regularisation. Such an approach can incorporate application-specific prior knowledge into deep learning based registration. Particularly, the proposed biomechanics-informed regularisation leverages a variational autoencoder (VAE) to learn a manifold for biomechanically plausible deformations and to implicitly capture their underlying properties via reconstructing biomechanical simulations. The learnt VAE regulariser then can be coupled with any deep learning based registration network to regularise the solution space to be biomechanically plausible. The proposed method is validated in the context of myocardial motion tracking on 2D stacks of cardiac MRI data from two different datasets. The results show that it can achieve better performance against other competing methods in terms of motion tracking accuracy and has the ability to learn biomechanical properties such as incompressibility and strains. The method has also been shown to have better generalisability to unseen domains compared with commonly used L2 regularisation schemes.Comment: The paper is early accepted by MICCAI 202

    Spin dynamics in semiconductors

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    This article reviews the current status of spin dynamics in semiconductors which has achieved a lot of progress in the past years due to the fast growing field of semiconductor spintronics. The primary focus is the theoretical and experimental developments of spin relaxation and dephasing in both spin precession in time domain and spin diffusion and transport in spacial domain. A fully microscopic many-body investigation on spin dynamics based on the kinetic spin Bloch equation approach is reviewed comprehensively.Comment: a review article with 193 pages and 1103 references. To be published in Physics Reports

    Feasibility studies of time-like proton electromagnetic form factors at PANDA at FAIR

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    Simulation results for future measurements of electromagnetic proton form factors at \PANDA (FAIR) within the PandaRoot software framework are reported. The statistical precision with which the proton form factors can be determined is estimated. The signal channel pˉpe+e\bar p p \to e^+ e^- is studied on the basis of two different but consistent procedures. The suppression of the main background channel, i.e.\textit{i.e.} pˉpπ+π\bar p p \to \pi^+ \pi^-, is studied. Furthermore, the background versus signal efficiency, statistical and systematical uncertainties on the extracted proton form factors are evaluated using two different procedures. The results are consistent with those of a previous simulation study using an older, simplified framework. However, a slightly better precision is achieved in the PandaRoot study in a large range of momentum transfer, assuming the nominal beam conditions and detector performance
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