Domain wall propagation through spin wave emission

We theoretically study field-induced domain wall (DW) motion in an electrically insulating ferromagnet with hard- and easy-axis anisotropies. DWs can propagate along a dissipationless wire through spin wave emission locked into the known soliton velocity at low fields. In the presence of damping, the mode appears before the Walker breakdown field for strong out-of-plane magnetic anisotropy, and the usual Walker rigid-body propagation mode becomes unstable when the field is between the maximal-DW-speed field and Walker breakdown field.Comment: 4 pages, 4 figure

Thomas Decomposition of Algebraic and Differential Systems

In this paper we consider disjoint decomposition of algebraic and non-linear partial differential systems of equations and inequations into so-called simple subsystems. We exploit Thomas decomposition ideas and develop them into a new algorithm. For algebraic systems simplicity means triangularity, squarefreeness and non-vanishing initials. For differential systems the algorithm provides not only algebraic simplicity but also involutivity. The algorithm has been implemented in Maple

Tracing the Evolution of Temperature in Near Fermi Energy Heavy Ion Collisions

The kinetic energy variation of emitted light clusters has been employed as a clock to explore the time evolution of the temperature for thermalizing composite systems produced in the reactions of 26A, 35A and 47A MeV $^{64}$Zn with $^{58}$Ni, $^{92}$Mo and $^{197}$Au. For each system investigated, the double isotope ratio temperature curve exhibits a high maximum apparent temperature, in the range of 10-25 MeV, at high ejectile velocity. These maximum values increase with increasing projectile energy and decrease with increasing target mass. The time at which the maximum in the temperature curve is reached ranges from 80 to 130 fm/c after contact. For each different target, the subsequent cooling curves for all three projectile energies are quite similar. Temperatures comparable to those of limiting temperature systematics are reached 30 to 40 fm/c after the times corresponding to the maxima, at a time when AMD-V transport model calculations predict entry into the final evaporative or fragmentation stage of de-excitation of the hot composite systems. Evidence for the establishment of thermal and chemical equilibrium is discussed.Comment: 9 pages, 5 figure

HIV Gag mimics the Tsg101-recruiting activity of the human Hrs protein

The HIV-1 Gag protein recruits the cellular factor Tsg101 to facilitate the final stages of virus budding. A conserved P(S/T)AP tetrapeptide motif within Gag (the “late domain”) binds directly to the NH2-terminal ubiquitin E2 variant (UEV) domain of Tsg101. In the cell, Tsg101 is required for biogenesis of vesicles that bud into the lumen of late endosomal compartments called multivesicular bodies (MVBs). However, the mechanism by which Tsg101 is recruited from the cytoplasm onto the endosomal membrane has not been known. Now, we report that Tsg101 binds the COOH-terminal region of the endosomal protein hepatocyte growth factor–regulated tyrosine kinase substrate (Hrs; residues 222–777). This interaction is mediated, in part, by binding of the Tsg101 UEV domain to the Hrs 348PSAP351 motif. Importantly, Hrs222–777 can recruit Tsg101 and rescue the budding of virus-like Gag particles that are missing native late domains. These observations indicate that Hrs normally functions to recruit Tsg101 to the endosomal membrane. HIV-1 Gag apparently mimics this Hrs activity, and thereby usurps Tsg101 and other components of the MVB vesicle fission machinery to facilitate viral budding

Torquetenovirus Serum Load and Long-Term Outcomes in Renal Transplant Recipients

Following transplantation, patients must take immunosuppressive medication for life. Torquetenovirus (TTV) is thought to be marker for immunosuppression, and TTV-DNA levels after organ transplantation have been investigated, showing high TTV levels, associated with increased risk of infections, and low TTV levels associated with increased risk of rejection. However, this has been investigated in studies with relatively short follow-up periods. We hypothesized that TTV levels can be used to assess long term outcomes after renal transplantation. Serum samples of 666 renal transplant recipients were tested for TTV DNA. Samples were taken at least one year after renal transplantation, when TTV levels are thought to be relatively stable. Patient data was reviewed for graft failure, all-cause mortality and death due to infectious causes. Our data indicates that high TTV levels, sampled more than one year post-transplantation, are associated with all-cause mortality with a hazard ratio (HR) of 1.12 (95% CI, 1.02-1.23) per log10 increase in TTV viral load, (p = 0.02). Additionally, high TTV levels were also associated with death due to infectious causes (HR 1.20 (95% CI 1.01-1.43), p = 0.04). TTV levels decrease in the years following renal transplantation, but remain elevated longer than previously thought. This study shows that TTV level may aid in predicting long-term outcomes, all-cause mortality and death due to an infectious cause in renal transplant patients sampled over one year post-transplantation

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics

Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data. The implementation of GBHC is available at https://sites. google.com/site/gaussianbhc

Medoid-based clustering using ant colony optimization

The application of ACO-based algorithms in data mining has been growing over the last few years, and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach. Most recent works about unsupervised learning have focused on clustering, showing the potential of ACO-based techniques. However, there are still clustering areas that are almost unexplored using these techniques, such as medoid-based clustering. Medoid-based clustering methods are helpful—compared to classical centroid-based techniques—when centroids cannot be easily defined. This paper proposes two medoid-based ACO clustering algorithms, where the only information needed is the distance between data: one algorithm that uses an ACO procedure to determine an optimal medoid set (METACOC algorithm) and another algorithm that uses an automatic selection of the number of clusters (METACOC-K algorithm). The proposed algorithms are compared against classical clustering approaches using synthetic and real-world datasets

First direct detection of an exoplanet by optical interferometry; Astrometry and K-band spectroscopy of HR8799 e

To date, infrared interferometry at best achieved contrast ratios of a few times $10^{-4}$ on bright targets. GRAVITY, with its dual-field mode, is now capable of high contrast observations, enabling the direct observation of exoplanets. We demonstrate the technique on HR8799, a young planetary system composed of four known giant exoplanets. We used the GRAVITY fringe tracker to lock the fringes on the central star, and integrated off-axis on the HR8799e planet situated at 390 mas from the star. Data reduction included post-processing to remove the flux leaking from the central star and to extract the coherent flux of the planet. The inferred K band spectrum of the planet has a spectral resolution of 500. We also derive the astrometric position of the planet relative to the star with a precision on the order of 100$\,\mu$as. The GRAVITY astrometric measurement disfavors perfectly coplanar stable orbital solutions. A small adjustment of a few degrees to the orbital inclination of HR 8799 e can resolve the tension, implying that the orbits are close to, but not strictly coplanar. The spectrum, with a signal-to-noise ratio of $\approx 5$ per spectral channel, is compatible with a late-type L brown dwarf. Using Exo-REM synthetic spectra, we derive a temperature of $1150\pm50$\,K and a surface gravity of $10^{4.3\pm0.3}\,$cm/s$^{2}$. This corresponds to a radius of $1.17^{+0.13}_{-0.11}\,R_{\rm Jup}$ and a mass of $10^{+7}_{-4}\,M_{\rm Jup}$, which is an independent confirmation of mass estimates from evolutionary models. Our results demonstrate the power of interferometry for the direct detection and spectroscopic study of exoplanets at close angular separations from their stars.Comment: published in A&

The Carnegie Supernova Project: First Near-Infrared Hubble Diagram to z~0.7

The Carnegie Supernova Project (CSP) is designed to measure the luminosity distance for Type Ia supernovae (SNe Ia) as a function of redshift, and to set observational constraints on the dark energy contribution to the total energy content of the Universe. The CSP differs from other projects to date in its goal of providing an I-band {rest-frame} Hubble diagram. Here we present the first results from near-infrared (NIR) observations obtained using the Magellan Baade telescope for SNe Ia with 0.1 < z < 0.7. We combine these results with those from the low-redshift CSP at z <0.1 (Folatelli et al. 2009). We present light curves and an I-band Hubble diagram for this first sample of 35 SNe Ia and we compare these data to 21 new SNe Ia at low redshift. These data support the conclusion that the expansion of the Universe is accelerating. When combined with independent results from baryon acoustic oscillations (Eisenstein et al. 2005), these data yield Omega_m = 0.27 +/- 0.0 (statistical), and Omega_DE = 0.76 +/- 0.13 (statistical) +/- 0.09 (systematic), for the matter and dark energy densities, respectively. If we parameterize the data in terms of an equation of state, w, assume a flat geometry, and combine with baryon acoustic oscillations, we find that w = -1.05 +/- 0.13 (statistical) +/- 0.09 (systematic). The largest source of systematic uncertainty on w arises from uncertainties in the photometric calibration, signaling the importance of securing more accurate photometric calibrations for future supernova cosmology programs. Finally, we conclude that either the dust affecting the luminosities of SNe Ia has a different extinction law (R_V = 1.8) than that in the Milky Way (where R_V = 3.1), or that there is an additional intrinsic color term with luminosity for SNe Ia independent of the decline rate.Comment: 44 pages, 23 figures, 9 tables; Accepted for publication in the Astrophysical Journa

Hydroclimatic Variability and Predictability: A Survey of Recent Research

Recent research in large-scale hydroclimatic variability is surveyed, focusing on five topics: (i) variability in general, (ii) droughts, (iii) floods, (iv) land-atmosphere coupling, and (v) hydroclimatic prediction. Each surveyed topic is supplemented by illustrative examples of recent research, as presented at a 2016 symposium honoring the career of Professor Eric Wood. Taken together, the recent literature and the illustrative examples clearly show that current research into hydroclimatic variability is strong, vibrant, and multifaceted