6,939 research outputs found

    Riesz potentials and nonlinear parabolic equations

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    The spatial gradient of solutions to nonlinear degenerate parabolic equations can be pointwise estimated by the caloric Riesz potential of the right hand side datum, exactly as in the case of the heat equation. Heat kernels type estimates persist in the nonlinear cas

    Impact of comorbidities on the duration of COPD patients' hospital episodes

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    AbstractThe duration of inpatient episodes due to COPD and the factors that affect it have recently been an object of increasing attention, as the aim has been to shorten inpatient periods and thereby to cut health-care costs. All hospital episodes of patients aged over 45 for a primary diagnosis of COPD equal or less than 150 days in duration were drawn from the treatment register maintained by the National Research and Development Centre for Welfare and Health. The lengths of these 152 569 inpatient periods were analysed for sex, age and secondary diagnoses by covariance analysis. The mean age of men at the beginning of the hospital episode was 70.6 years and that of women 70.1 years. Men accounted for 76.9% of all inpatient episodes. Covariance analysis of the data with age standardised as 70.5 years yielded a mean hospital episode length of 8.9 (95% confidence interval (CI) 8.8–9.0) days. The mean length of hospital episodes without a secondary diagnosis was 7.7 (95% CI 7.6–7.7) days and that with a secondary diagnosis was 10.5 (95% CI 10.5–10.6) days. The longest inpatient episodes were recorded for the patients with secondary diagnoses of pneumonia, 14.7 (95% CI 14.2–15.2) days, and cerebral ischaemia, 14.2 (95% CI 13.5–14.9) days. Concurrent diseases prolonged the hospital episodes of COPD patients. At the beginning of a hospital episode, it is possible to estimate its duration and the need for different treatments based on the patient's age and secondary diagnoses

    Biomass functions for mountain birch in the Vuoskojärvi Integrate Monitoring area

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    Deep Generative Variational Autoencoding for Replay Spoof Detection in Automatic Speaker Verification

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    Automatic speaker verification (ASV) systems are highly vulnerable to presentation attacks, also called spoofing attacks. Replay is among the simplest attacks to mount - yet difficult to detect reliably. The generalization failure of spoofing countermeasures (CMs) has driven the community to study various alternative deep learning CMs. The majority of them are supervised approaches that learn a human-spoof discriminator. In this paper, we advocate a different, deep generative approach that leverages from powerful unsupervised manifold learning in classification. The potential benefits include the possibility to sample new data, and to obtain insights to the latent features of genuine and spoofed speech. To this end, we propose to use variational autoencoders (VAEs) as an alternative backend for replay attack detection, via three alternative models that differ in their class-conditioning. The first one, similar to the use of Gaussian mixture models (GMMs) in spoof detection, is to train independently two VAEs - one for each class. The second one is to train a single conditional model (C-VAE) by injecting a one-hot class label vector to the encoder and decoder networks. Our final proposal integrates an auxiliary classifier to guide the learning of the latent space. Our experimental results using constant-Q cepstral coefficient (CQCC) features on the ASVspoof 2017 and 2019 physical access subtask datasets indicate that the C-VAE offers substantial improvement in comparison to training two separate VAEs for each class. On the 2019 dataset, the C-VAE outperforms the VAE and the baseline GMM by an absolute 9-10% in both equal error rate (EER) and tandem detection cost function (t-DCF) metrics. Finally, we propose VAE residuals --- the absolute difference of the original input and the reconstruction as features for spoofing detection. The proposed frontend approach augmented with a convolutional neural network classifier demonstrated substantial improvement over the VAE backend use case

    Coexistence of pairing gaps in three-component Fermi gases

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    We study a three-component superfluid Fermi gas in a spherically symmetric harmonic trap using the Bogoliubov-deGennes method. We predict a coexistence phase in which two pairing field order parameters are simultaneously nonzero, in stark contrast to studies performed for trapped gases using local density approximation. We also discuss the role of atom number conservation in the context of a homogeneous system.Comment: Text revised, added two figures and three reference

    Discovery of a New Deeply Eclipsing SU UMa-Type Dwarf Nova, IY UMa (= TmzV85)

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    We discovered a new deeply eclipsing SU UMa-type dwarf nova, IY UMa, which experienced a superoutburst in 2000 January. Our monitoring revealed two distinct outbursts, which suggest a superoutburst interval of ~800 d, or its half, and an outburst amplitude of 5.4 mag. From time-series photometry during the superoutburst, we determined a superhump and orbital period of 0.07588 d and 0.0739132 d, respectively.Comment: 5 pages, 3 figures, accepted by PASJ lette

    Readout of solid-state charge qubits using a single-electron pump

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    A major difficulty in realizing a solid-state quantum computer is the reliable measurement of the states of the quantum registers. In this paper, we propose an efficient readout scheme making use of the resonant tunneling of a ballistic electron produced by a single electron pump. We treat the measurement interaction in detail by modeling the full spatial configuration, and show that for pumped electrons with suitably chosen energy the transmission coefficient is very sensitive to the qubit state. We further show that by using a short sequence of pumping events, coupled with a simple feedback control procedure, the qubit can be measured with high accuracy.Comment: 5 pages, revtex4, 4 eps figures. v2: published versio

    Cepstral trajectories in linguistic units for text-independent speaker recognition

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    The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-35292-8_3Proceedings of IberSPEECH, held in Madrid (Spain) on 2012.In this paper, the contributions of different linguistic units to the speaker recognition task are explored by means of temporal trajectories of their MFCC features. Inspired by successful work in forensic speaker identification, we extend the approach based on temporal contours of formant frequencies in linguistic units to design a fully automatic system that puts together both forensic and automatic speaker recognition worlds. The combination of MFCC features and unit-dependent trajectories provides a powerful tool to extract individualizing information. At a fine-grained level, we provide a calibrated likelihood ratio per linguistic unit under analysis (extremely useful in applications such as forensics), and at a coarse-grained level, we combine the individual contributions of the different units to obtain a highly discriminative single system. This approach has been tested with NIST SRE 2006 datasets and protocols, consisting of 9,720 trials from 219 male speakers for the 1side-1side English-only task, and development data being extracted from 367 male speakers from 1,808 conversations from NIST SRE 2004 and 2005 datasetsSupported by MEC grant PR-2010-123, MICINN project TEC09-14179, ForBayes project CCG10-UAM/TIC-5792 and Cátedra UAM-Telefónica

    Cooper-pair resonances and subgap Coulomb blockade in a superconducting single-electron transistor

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    We have fabricated and measured superconducting single-electron transistors with Al leads and Nb islands. At bias voltages below the gap of Nb we observe clear signatures of resonant tunneling of Cooper pairs, and of Coulomb blockade of the subgap currents due to linewidth broadening of the energy levels in the superconducting density of states of Nb. The experimental results are in good agreement with numerical simulations.Comment: 4 pages, 3 figure
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