Tunable Fano effect in parallel-coupled double quantum dot system

With the help of the Green function technique and the equation of motion approach, the electronic transport through a parallel-coupled double quantum dot(DQD) is theoretically studied. Owing to the inter-dot coupling, the bonding and antibonding states of the artificial quantum-dot-molecule may constitute an appropriate basis set. Based on this picture, the Fano interference in the conductance spectra of the DQD system is readily explained. The possibility of manipulating the Fano lineshape in the tunnelling spectra of the DQD system is explored by tuning the dot-lead coupling, the inter-dot coupling, the magnetic flux threading the ring connecting dots and leads, and the flux difference between two sub-rings. It has been found that by making use of various tuning, the direction of the asymmetric tail of Fano lineshape may be flipped by external fields, and the continuous conductance spectra may be magnetically manipulated with lineshape retained. More importantly, by adjusting the magnetic flux, the function of two molecular states can be exchanged, giving rise to a swap effect, which might play a role as a qubit in the quantum computation.Comment: 9 pages, 10 figure

Fano Effect through Parallel-coupled Double Coulomb Islands

By means of the non-equilibrium Green function and equation of motion method, the electronic transport is theoretically studied through a parallel-coupled double quantum dots(DQD) in the presence of the on-dot Coulomb correlation, with an emphasis put on the quantum interference. It has been found that in the Coulomb blockage regime, the quantum interference between the bonding and antiboding DQD states or that between their Coulomb blockade counterparts may result in the Fano resonance in the conductance spectra, and the Fano peak doublet may be observed under certain non-equilibrium condition. The possibility of manipulating the Fano lineshape is predicted by tuning the dot-lead coupling and magnetic flux threading the ring connecting the dots and leads. Similar to the case without Coulomb interaction, the direction of the asymmetric tail of Fano lineshape can be flipped by the external field. Most importantly, by tuning the magnetic flux, the function of four relevant states can be interchanged, giving rise to the swap effect, which might play a key role as a qubit in the quantum computation.Comment: 7 pages, 5 figure

Phonon-assisted Kondo Effect in a Single-Molecule Transistor out of Equilibrium

The joint effect of the electron-phonon interaction and Kondo effect on the nonequilibrium transport through the single molecule transistor is investigated by using the improved canonical transformation scheme and extended equation of motion approach. Two types of Kondo phonon-satellites with different asymmetric shapes are fully confirmed in the spectral function, and are related to the electron spin singlet or hole spin singlet, respectively. Moreover, when a moderate Zeeman splitting is caused by a local magnetic field, the Kondo satellites in the spin resolved spectral function are found disappeared on one side of the main peak, which is opposite for different spin component. All these peculiar signatures that manifest themselves in the nonlinear differential conductance, are explained with a clear physics picture.Comment: 12 pages, 6 figure

Comparative genomics of Toll-like receptor signalling in five species

<p>Abstract</p> <p>Background</p> <p>Over the last decade, several studies have identified quantitative trait loci (QTL) affecting variation of immune related traits in mammals. Recent studies in humans and mice suggest that part of this variation may be caused by polymorphisms in genes involved in Toll-like receptor (TLR) signalling. In this project, we used a comparative approach to investigate the importance of TLR-related genes in comparison with other immunologically relevant genes for resistance traits in five species by associating their genomic location with previously published immune-related QTL regions.</p> <p>Results</p> <p>We report the genomic localisation of <it>TLR1-10 </it>and ten associated signalling molecules in sheep and pig using <it>in-silico </it>and/or radiation hybrid (RH) mapping techniques and compare their positions with their annotated homologues in the human, cattle and mouse whole genome sequences. We also report medium-density RH maps for porcine chromosomes 8 and 13. A comparative analysis of the positions of previously published relevant QTLs allowed the identification of homologous regions that are associated with similar health traits in several species and which contain TLR related and other immunologically relevant genes. Additional evidence was gathered by examining relevant gene expression and association studies.</p> <p>Conclusion</p> <p>This comparative genomic approach identified eight genes as potentially causative genes for variations of health related traits. These include susceptibility to clinical mastitis in dairy cattle, general disease resistance in sheep, cattle, humans and mice, and tolerance to protozoan infection in cattle and mice. Four TLR-related genes (<it>TLR1</it>, <it>6</it>, <it>MyD88</it>, <it>IRF3</it>) appear to be the most likely candidate genes underlying QTL regions which control the resistance to the same or similar pathogens in several species. Further studies are required to investigate the potential role of polymorphisms within these genes.</p

I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences

The I4U consortium was established to facilitate a joint entry to NIST speaker recognition evaluations (SRE). The latest edition of such joint submission was in SRE 2018, in which the I4U submission was among the best-performing systems. SRE'18 also marks the 10-year anniversary of I4U consortium into NIST SRE series of evaluation. The primary objective of the current paper is to summarize the results and lessons learned based on the twelve sub-systems and their fusion submitted to SRE'18. It is also our intention to present a shared view on the advancements, progresses, and major paradigm shifts that we have witnessed as an SRE participant in the past decade from SRE'08 to SRE'18. In this regard, we have seen, among others, a paradigm shift from supervector representation to deep speaker embedding, and a switch of research challenge from channel compensation to domain adaptation.Comment: 5 page

Current induced anisotropic magnetoresistance in topological insulator films

Topological insulators are insulating in the bulk but possess spin-momentum locked metallic surface states protected by time-reversal symmetry. The existence of these surface states has been confirmed by angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy (STM). Detecting these surface states by transport measurement, which might at first appear to be the most direct avenue, was shown to be much more challenging than expected. Here, we report a detailed electronic transport study in high quality Bi2Se3 topological insulator thin films. Measurements under in-plane magnetic field, along and perpendicular to the bias current show opposite magnetoresistance. We argue that this contrasting behavior is related to the locking of the spin and current direction providing evidence for helical spin structure of the topological surface states

Inferring causal molecular networks: empirical assessment through a community-based effort.

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks