Analysis of self--averaging properties in the transport of particles through random media

We investigate self-averaging properties in the transport of particles through random media. We show rigorously that in the subdiffusive anomalous regime transport coefficients are not self--averaging quantities. These quantities are exactly calculated in the case of directed random walks. In the case of general symmetric random walks a perturbative analysis around the Effective Medium Approximation (EMA) is performed.Comment: 4 pages, RevTeX , No figures, submitted to Physical Review E (Rapid Communication

Inter edge Tunneling in Quantum Hall Line Junctions

We propose a scenario to understand the puzzling features of the recent experiment by Kang and coworkers on tunneling between laterally coupled quantum Hall liquids by modeling the system as a pair of coupled chiral Luttinger liquid with a point contact tunneling center. We show that for filling factors $\nu\sim1$ the effects of the Coulomb interactions move the system deep into strong tunneling regime, by reducing the magnitude of the Luttinger parameter $K$, leading to the appearance of a zero-bias differential conductance peak of magnitude $G_t=Ke^2/h$ at zero temperature. The abrupt appearance of the zero bias peak as the filling factor is increased past a value $\nu^* \gtrsim 1$, and its gradual disappearance thereafter can be understood as a crossover controlled by the main energy scales of this system: the bias voltage $V$, the crossover scale $T_K$, and the temperature $T$. The low height of the zero bias peak $\sim 0.1e^2/h$ observed in the experiment, and its broad finite width, can be understood naturally within this picture. Also, the abrupt reappearance of the zero-bias peak for $\nu \gtrsim 2$ can be explained as an effect caused by spin reversed electrons, \textit{i. e.} if the 2DEG is assumed to have a small polarization near $\nu\sim2$. We also predict that as the temperature is lowered $\nu^*$ should decrease, and the width of zero-bias peak should become wider. This picture also predicts the existence of similar zero bias peak in the spin tunneling conductance near for $\nu \gtrsim 2$.Comment: 17 pages, 8 figure

Demonstration of the event identification capabilities of the NEXT-White detector

In experiments searching for neutrinoless double-beta decay, the possibility of identifying the two emitted electrons is a powerful tool in rejecting background events and therefore improving the overall sensitivity of the experiment. In this paper we present the first measurement of the efficiency of a cut based on the different event signatures of double and single electron tracks, using the data of the NEXT-White detector, the first detector of the NEXT experiment operating underground. Using a 228Th calibration source to produce signal-like and background-like events with energies near 1.6 MeV, a signal efficiency of 71.6 ± 1.5 stat± 0.3 sys% for a background acceptance of 20.6 ± 0.4 stat± 0.3 sys% is found, in good agreement with Monte Carlo simulations. An extrapolation to the energy region of the neutrinoless double beta decay by means of Monte Carlo simulations is also carried out, and the results obtained show an improvement in background rejection over those obtained at lower energies. [Figure not available: see fulltext.

Energy calibration of the NEXT-White detector with 1% resolution near Q ββ of 136Xe

Excellent energy resolution is one of the primary advantages of electroluminescent high-pressure xenon TPCs. These detectors are promising tools in searching for rare physics events, such as neutrinoless double-beta decay (ββ0ν), which require precise energy measurements. Using the NEXT-White detector, developed by the NEXT (Neutrino Experiment with a Xenon TPC) collaboration, we show for the first time that an energy resolution of 1% FWHM can be achieved at 2.6 MeV, establishing the present technology as the one with the best energy resolution of all xenon detectors for ββ0ν searches. [Figure not available: see fulltext.

Radiogenic backgrounds in the NEXT double beta decay experiment

Natural radioactivity represents one of the main backgrounds in the search for neutrinoless double beta decay. Within the NEXT physics program, the radioactivity- induced backgrounds are measured with the NEXT-White detector. Data from 37.9 days of low-background operations at the Laboratorio Subterráneo de Canfranc with xenon depleted in 136Xe are analyzed to derive a total background rate of (0.84±0.02) mHz above 1000 keV. The comparison of data samples with and without the use of the radon abatement system demonstrates that the contribution of airborne-Rn is negligible. A radiogenic background model is built upon the extensive radiopurity screening campaign conducted by the NEXT collaboration. A spectral fit to this model yields the specific contributions of 60Co, 40K, 214Bi and 208Tl to the total background rate, as well as their location in the detector volumes. The results are used to evaluate the impact of the radiogenic backgrounds in the double beta decay analyses, after the application of topological cuts that reduce the total rate to (0.25±0.01) mHz. Based on the best-fit background model, the NEXT-White median sensitivity to the two-neutrino double beta decay is found to be 3.5σ after 1 year of data taking. The background measurement in a Qββ±100 keV energy window validates the best-fit background model also for the neutrinoless double beta decay search with NEXT-100. Only one event is found, while the model expectation is (0.75±0.12) events. [Figure not available: see fulltext.]

Low-diffusion Xe-He gas mixtures for rare-event detection: electroluminescence yield

High pressure xenon Time Projection Chambers (TPC) based on secondary scintillation (electroluminescence) signal amplification are being proposed for rare event detection such as directional dark matter, double electron capture and double beta decay detection. The discrimination of the rare event through the topological signature of primary ionisation trails is a major asset for this type of TPC when compared to single liquid or double-phase TPCs, limited mainly by the high electron diffusion in pure xenon. Helium admixtures with xenon can be an attractive solution to reduce the electron diffu- sion significantly, improving the discrimination efficiency of these optical TPCs. We have measured the electroluminescence (EL) yield of Xe–He mixtures, in the range of 0 to 30% He and demonstrated the small impact on the EL yield of the addition of helium to pure xenon. For a typical reduced electric field of 2.5 kV/cm/bar in the EL region, the EL yield is lowered by ∼ 2%, 3%, 6% and 10% for 10%, 15%, 20% and 30% of helium concentration, respectively. This decrease is less than what has been obtained from the most recent simulation framework in the literature. The impact of the addition of helium on EL statistical fluctuations is negligible, within the experimental uncertainties. The present results are an important benchmark for the simulation tools to be applied to future optical TPCs based on Xe-He mixtures. [Figure not available: see fulltext.]

Sensitivity of a tonne-scale NEXT detector for neutrinoless double beta decay searches

The Neutrino Experiment with a Xenon TPC (NEXT) searches for the neutrinoless double-beta decay of Xe-136 using high-pressure xenon gas TPCs with electroluminescent amplification. A scaled-up version of this technology with about 1 tonne of enriched xenon could reach in less than 5 years of operation a sensitivity to the half-life of neutrinoless double-beta decay decay better than 1E27 years, improving the current limits by at least one order of magnitude. This prediction is based on a well-understood background model dominated by radiogenic sources. The detector concept presented here represents a first step on a compelling path towards sensitivity to the parameter space defined by the inverted ordering of neutrino masses, and beyond.Comment: 22 pages, 11 figure

Snail1 factor behaves as a therapeutic target in renal fibrosis.

Kidney fibrosis is a devastating disease that leads to organ failure, and no specific treatment is available to preserve organ function. In fibrosis, myofibroblasts accumulate in the interstitium leading to massive deposition of extracellular matrix and organ disfunction. The origin of myofibroblasts is multiple and the contribution of renal epithelial cells after undergoing epithelial-to-mesenchymal transition (EMT) is still debated. In a model unable to reactivate the EMT inducer Snail1 upon damage, we show that Snail1 is required in renal epithelial cells for the development of fibrosis. Damage-mediated Snail1 reactivation induces a partial EMT that relays fibrotic and inflammatory signals to the interstitium through the activation of TGF-β and NF-B pathways. Snail1-induced fibrosis can be reverted in vivo and inhibiting Snail1 in a model of obstructive nephropathy highly ameliorates fibrosis. These results reconcile conflicting data on the role of EMT in renal fibrosis and provide avenues for the design of antifibrotic therapies.pre-print8435 K

An insight into imbalanced Big Data classification: outcomes and challenges

Big Data applications are emerging during the last years, and researchers from many disciplines are aware of the high advantages related to the knowledge extraction from this type of problem. However, traditional learning approaches cannot be directly applied due to scalability issues. To overcome this issue, the MapReduce framework has arisen as a “de facto” solution. Basically, it carries out a “divide-and-conquer” distributed procedure in a fault-tolerant way to adapt for commodity hardware. Being still a recent discipline, few research has been conducted on imbalanced classification for Big Data. The reasons behind this are mainly the difficulties in adapting standard techniques to the MapReduce programming style. Additionally, inner problems of imbalanced data, namely lack of data and small disjuncts, are accentuated during the data partitioning to fit the MapReduce programming style. This paper is designed under three main pillars. First, to present the first outcomes for imbalanced classification in Big Data problems, introducing the current research state of this area. Second, to analyze the behavior of standard pre-processing techniques in this particular framework. Finally, taking into account the experimental results obtained throughout this work, we will carry out a discussion on the challenges and future directions for the topic.This work has been partially supported by the Spanish Ministry of Science and Technology under Projects TIN2014-57251-P and TIN2015-68454-R, the Andalusian Research Plan P11-TIC-7765, the Foundation BBVA Project 75/2016 BigDaPTOOLS, and the National Science Foundation (NSF) Grant IIS-1447795