Permalloy-based carbon nanotube spin-valve

In this Letter we demonstrate that Permalloy (Py), a widely used Ni/Fe alloy, forms contacts to carbon nanotubes (CNTs) that meet the requirements for the injection and detection of spin-polarized currents in carbon-based spintronic devices. We establish the material quality and magnetization properties of Py strips in the shape of suitable electrical contacts and find a sharp magnetization switching tunable by geometry in the anisotropic magnetoresistance (AMR) of a single strip at cryogenic temperatures. In addition, we show that Py contacts couple strongly to CNTs, comparable to Pd contacts, thereby forming CNT quantum dots at low temperatures. These results form the basis for a Py-based CNT spin-valve exhibiting very sharp resistance switchings in the tunneling magnetoresistance, which directly correspond to the magnetization reversals in the individual contacts observed in AMR experiments.Comment: 3 page

Tail emission from a ring-like jet: its application to shallow decays of early afterglows and to GRB 050709

Similar to the pulsar, the magnetic axis and the spin axis of the gamma-ray burst source may not lie on the same line. This may cause a ring-like jet due to collimation of the precessing magnetic axis. We analyze the tail emission from such a jet, and find that it has a shallow decay phase with temporal index equal to -1/2 if the Lorentz factor of the ejecta is not very high. This phase is consistent with the shallow decay phase of some early X-ray afterglow detected by {\it{swift}}. The ring-like jet has a tail cusp with sharp rising and very sharp decay. This effect can provide an explanation for the re-brightening and sharp decay of the X-ray afterglow of GRB 050709.Comment: 6 pages, 2 figures. Accepted by ChJA

Calorimetric Investigation of CeRu2Ge2 up to 8 GPa

We have developed a calorimeter able to give a qualitative picture of the specific heat of a sample under high pressure up to approximately 10 GPa. The principle of ac-calorimetry was adapted to the conditions in a high pressure clamp. The performance of this technique was successfully tested with the measurement of the specific heat of CeRu2Ge2 in the temperature range 1.5 K<T<12 K. The phase diagram of its magnetic phases is consistent with previous transport measurements.Comment: 5 pages, 4 figure

Pushing 1D CCSNe to explosions: model and SN 1987A

We report on a method, PUSH, for triggering core-collapse supernova explosions of massive stars in spherical symmetry. We explore basic explosion properties and calibrate PUSH such that the observables of SN1987A are reproduced. Our simulations are based on the general relativistic hydrodynamics code AGILE combined with the detailed neutrino transport scheme IDSA for electron neutrinos and ALS for the muon and tau neutrinos. To trigger explosions in the otherwise non-exploding simulations, we rely on the neutrino-driven mechanism. The PUSH method locally increases the energy deposition in the gain region through energy deposition by the heavy neutrino flavors. Our setup allows us to model the explosion for several seconds after core bounce. We explore the progenitor range 18-21M$_{\odot}$. Our studies reveal a distinction between high compactness (HC) and low compactness (LC) progenitor models, where LC models tend to explore earlier, with a lower explosion energy, and with a lower remnant mass. HC models are needed to obtain explosion energies around 1 Bethe, as observed for SN1987A. However, all the models with sufficiently high explosion energy overproduce $^{56}$Ni. We conclude that fallback is needed to reproduce the observed nucleosynthesis yields. The nucleosynthesis yields of $^{57-58}$Ni depend sensitively on the electron fraction and on the location of the mass cut with respect to the initial shell structure of the progenitor star. We identify a progenitor and a suitable set of PUSH parameters that fit the explosion properties of SN1987A when assuming 0.1M$_{\odot}$ of fallback. We predict a neutron star with a gravitational mass of 1.50M$_{\odot}$. We find correlations between explosion properties and the compactness of the progenitor model in the explored progenitors. However, a more complete analysis will require the exploration of a larger set of progenitors with PUSH.Comment: revised version as accepted by ApJ (results unchanged, text modified for clarification, a few references added); 26 pages, 20 figure

Nucleosynthesis in 2D Core-Collapse Supernovae of 11.2 and 17.0 M⊙_{\odot} Progenitors: Implications for Mo and Ru Production

Core-collapse supernovae are the first polluters of heavy elements in the galactic history. As such, it is important to study the nuclear compositions of their ejecta, and understand their dependence on the progenitor structure (e.g., mass, compactness, metallicity). Here, we present a detailed nucleosynthesis study based on two long-term, two-dimensional core-collapse supernova simulations of a 11.2 M$_{\odot}$ and a 17.0 M$_{\odot}$ star. We find that in both models nuclei well beyond the iron group (up to $Z \approx 44$) can be produced, and discuss in detail also the nucleosynthesis of the p-nuclei $^{92,94}$Mo and $^{96,98}$Ru. While we observe the production of $^{92}$Mo and $^{94}$Mo in slightly neutron-rich conditions in both simulations, $^{96,98}$Ru can only be produced efficiently via the $\nu$p-process. Furthermore, the production of Ru in the $\nu$p-process heavily depends on the presence of very proton-rich material in the ejecta. This disentanglement of production mechanisms has interesting consequences when comparing to the abundance ratios between these isotopes in the solar system and in presolar grains.Comment: 48 pages, 19 figures, accepted for publication in: J. Phys. G: Nucl. Part. Phy

The Effect of Cigarette Smoking on Diabetic Peripheral Neuropathy: A Systematic Review and Meta-Analysis.

OBJECTIVE: Studies suggest that smoking may be a risk factor for the development of microvascular complications such as diabetic peripheral neuropathy (DPN). The objective of this study was to assess the relationship between smoking and DPN in persons with type 1 or type 2 diabetes. RESEARCH DESIGN AND METHODS: A systematic review of the PubMed, Embase, and Cochrane clinical trials databases was conducted for the period from January 1966 to November 2014 for cohort, cross-sectional and case-control studies that assessed the relationship between smoking and DPN. Separate meta-analyses for prospective cohort studies and case-control or cross-sectional studies were performed using random effects models. RESULTS: Thirty-eight studies (10 prospective cohort and 28 cross-sectional) were included. The prospective cohort studies included 5558 participants without DPN at baseline. During follow-up ranging from 2 to 10 years, 1550 cases of DPN occurred. The pooled unadjusted odds ratio (OR) of developing DPN associated with smoking was 1.26 (95% CI 0.86-1.85; I(2) = 74%; evidence grade: low strength). Stratified analyses of the prospective studies revealed that studies of higher quality and with better levels of adjustment and longer follow-up showed a significant positive association between smoking and DPN, with less heterogeneity. The cross-sectional studies included 27,594 participants. The pooled OR of DPN associated with smoking was 1.42 (95% CI 1.21-1.65; I(2) = 65%; evidence grade: low strength). There was no evidence of publication bias. CONCLUSIONS: Smoking may be associated with an increased risk of DPN in persons with diabetes. Further studies are needed to test whether this association is causal and whether smoking cessation reduces the risk of DPN in adults with diabetes

Forecasting and Granger Modelling with Non-linear Dynamical Dependencies

Traditional linear methods for forecasting multivariate time series are not able to satisfactorily model the non-linear dependencies that may exist in non-Gaussian series. We build on the theory of learning vector-valued functions in the reproducing kernel Hilbert space and develop a method for learning prediction functions that accommodate such non-linearities. The method not only learns the predictive function but also the matrix-valued kernel underlying the function search space directly from the data. Our approach is based on learning multiple matrix-valued kernels, each of those composed of a set of input kernels and a set of output kernels learned in the cone of positive semi-definite matrices. In addition to superior predictive performance in the presence of strong non-linearities, our method also recovers the hidden dynamic relationships between the series and thus is a new alternative to existing graphical Granger techniques.Comment: Accepted for ECML-PKDD 201

Rates and patterns of great ape retrotransposition

Cataloged from PDF version of article.We analyzed 83 fully sequenced great ape genomes for mobile element insertions, predicting a total of 49,452 fixed and polymorphic Alu and long interspersed element 1 (L1) insertions not present in the human reference assembly and assigning each retrotransposition event to a different time point during great ape evolution. We used these homoplasy-free markers to construct a mobile element insertions-based phylogeny of humans and great apes and demonstrate their differential power to discern ape subspecies and populations. Within this context, we find a good correlation between L1 diversity and single-nucleotide polymorphism heterozygosity (r(2) = 0.65) in contrast to Alu repeats, which show little correlation (r(2) = 0.07). We estimate that the "rate" of Alu retrotransposition has differed by a factor of 15-fold in these lineages. Humans, chimpanzees, and bonobos show the highest rates of Alu accumulation-the latter two since divergence 1.5 Mya. The L1 insertion rate, in contrast, has remained relatively constant, with rates differing by less than a factor of three. We conclude that Alu retrotransposition has been the most variable form of genetic variation during recent human-great ape evolution, with increases and decreases occurring over very short periods of evolutionary time