Performance Analysis for Control- and User-Plane Separation based RAN with Non-Uniformly Distributed Users

In the control- and user-plane separation (CUPS) based radio access networks (RANs), control-signaling and data are transmitted by the control base stations (CBSs) and data base stations (DBSs), respectively. However, existing studies usually model the C/U-planes as two separate homogeneous networks, neglecting the dependence among the two planes and users. To address this problem, we analyze the coverage probability, spectrum efficiency (SE) and delay considering the dependent features among CBSs, DBSs, and non-uniformly distributed users based on stochastic geometry. Firstly, we present an analytical model for CUPS, where the DBSs are deployed at user hotspots based on Poisson point processes (PPPs), users are clustered around DBSs based on Poisson cluster processes (PCPs), and CBSs are deployed according to a dependent thinning of locations of DBSs based on Matérn hard-core processes (MHCPs). Secondly, we design novel distance-based fractional frequency reuse (FFR) schemes by exploiting the properties of PCP and MHCP to improve the coverage of cell edge users. Thirdly, we derive the distributions of user downlink rates, which are used to analyze the average queueing delay under M/M/C queueing model. Numerical results are presented to verify the efficiency of the proposed model compared to independently distributed BSs and users, and show the dependent BS deployment could significantly improve the coverage of the network

Acoustic Microscopy Using Amplitude and Phase Measurements

We have built a low-frequency scanning acoustic microscope (SAM) that measures both amplitude and phase. The majority of SAMs simply measure the amplitude of the reflected signal. Measuring the phase gives a great deal more information. For one thing, the phase is very sensitive to height variations. Measuring the phase also gives us the ability to do signal processing on the resulting images, such as removing the effects of surface features from defocused images of subsurface defects

Oropharyngeal mucositis-specific quality-of-life measure in patients with cancer therapy.

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Joint Uncertainty Decoding for Noise Robust Subspace Gaussian Mixture Models

Abstract—Joint uncertainty decoding (JUD) is a model-based noise compensation technique for conventional Gaussian Mixture Model (GMM) based speech recognition systems. Unlike vector Taylor series (VTS) compensation which operates on the individual Gaussian components in an acoustic model, JUD clusters the Gaussian components into a smaller number of classes, sharing the compensation parameters for the set of Gaussians in a given class. This significantly reduces the computational cost. In this paper, we investigate noise compensation for subspace Gaussian mixture model (SGMM) based speech recognition systems using JUD. The total number of Gaussian components in an SGMM is typically very large. Therefore direct compensation of the individual Gaussian components, as performed by VTS, is computationally expensive. In this paper we show that JUDbased noise compensation can be successfully applied to SGMMs in a computationally efficient way. We evaluate the JUD/SGMM technique on the standard Aurora 4 corpus. Our experimental results indicate that the JUD/SGMM system results in lower word error rates compared with a conventional GMM system with either VTS-based or JUD-based noise compensation. Index Terms—subspace Gaussian mixture model, vector Taylor series, joint uncertainty decoding, noise robust ASR, Aurora

Cathelicidin preserves intestinal barrier function in polymicrobial sepsis.

ObjectivesThe intestinal epithelium compartmentalizes the sterile bloodstream and the commensal bacteria in the gut. Accumulating evidence suggests that this barrier is impaired in sepsis, aggravating systemic inflammation. Previous studies reported that cathelicidin is differentially expressed in various tissues in sepsis. However, its role in sepsis-induced intestinal barrier dysfunction has not been investigated.DesignTo examine the role of cathelicidin in polymicrobial sepsis, cathelicidin wild-(Cnlp+/+) and knockout (Cnlp-/-) mice underwent cecal-ligation and puncture (CLP) followed by the assessment of septic mortality and morbidity as well as histological, biochemical, immunological, and transcriptomic analyses in the ileal tissues. We also evaluated the prophylactic and therapeutic efficacies of vitamin D3 (an inducer of endogenous cathelicidin) in the CLP-induced murine polymicrobial sepsis model.ResultsThe ileal expression of cathelicidin was increased by three-fold after CLP, peaking at 4 h. Knockout of Cnlp significantly increased 7-day mortality and was associated with a higher murine sepsis score. Alcian-blue staining revealed a reduced number of mucin-positive goblet cells, accompanied by reduced mucin expression. Increased number of apoptotic cells and cleavage of caspase-3 were observed. Cnlp deletion increased intestinal permeability to 4kD fluorescein-labeled dextran and reduced the expression of tight junction proteins claudin-1 and occludin. Notably, circulating bacterial DNA load increased more than two-fold. Transcriptome analysis revealed upregulation of cytokine/inflammatory pathway. Depletion of Cnlp induced more M1 macrophages and neutrophils compared with the wild-type mice after CLP. Mice pre-treated with cholecalciferol (an inactive form of vitamin D3) or treated with 1alpha, 25-dihydroxyvitamin D3 (an active form of VD3) had decreased 7-day mortality and significantly less severe symptoms. Intriguingly, the administration of cholecalciferol after CLP led to worsened 7-day mortality and the associated symptoms.ConclusionsEndogenous cathelicidin promotes intestinal barrier integrity accompanied by modulating the infiltration of neutrophils and macrophages in polymicrobial sepsis. Our data suggested that 1alpha, 25-dihydroxyvitamin D3 but not cholecalciferol is a potential therapeutic agent for treating sepsis

Second trimester inflammatory and metabolic markers in women delivering preterm with and without preeclampsia.

ObjectiveInflammatory and metabolic pathways are implicated in preterm birth and preeclampsia. However, studies rarely compare second trimester inflammatory and metabolic markers between women who deliver preterm with and without preeclampsia.Study designA sample of 129 women (43 with preeclampsia) with preterm delivery was obtained from an existing population-based birth cohort. Banked second trimester serum samples were assayed for 267 inflammatory and metabolic markers. Backwards-stepwise logistic regression models were used to calculate odds ratios.ResultsHigher 5-α-pregnan-3β,20α-diol disulfate, and lower 1-linoleoylglycerophosphoethanolamine and octadecanedioate, predicted increased odds of preeclampsia.ConclusionsAmong women with preterm births, those who developed preeclampsia differed with respect metabolic markers. These findings point to potential etiologic underpinnings for preeclampsia as a precursor to preterm birth

Yang-Mills instantons and dyons on homogeneous G_2-manifolds

We consider Lie G-valued Yang-Mills fields on the space R x G/H, where G/H is a compact nearly K"ahler six-dimensional homogeneous space, and the manifold R x G/H carries a G_2-structure. After imposing a general G-invariance condition, Yang-Mills theory with torsion on R x G/H is reduced to Newtonian mechanics of a particle moving in R^6, R^4 or R^2 under the influence of an inverted double-well-type potential for the cases G/H = SU(3)/U(1)xU(1), Sp(2)/Sp(1)xU(1) or G_2/SU(3), respectively. We analyze all critical points and present analytical and numerical kink- and bounce-type solutions, which yield G-invariant instanton configurations on those cosets. Periodic solutions on S^1 x G/H and dyons on iR x G/H are also given.Comment: 1+26 pages, 14 figures, 6 miniplot

Acoustic Microscopy with Mixed Mode Transducers

The new amplitude-phase acoustic microscope is versatile; it operates in a wide frequency range 1--200 MHz, with selection of longitudinal, shear, and mixed modes. This enables it to be used in many NDE applications for different kinds of materials. Besides the application examples presented in this paper (bulk defect imaging of lossy materials or at deep locations; leads of IC chip in epoxy package; amplitude images of surface crack on Si nitride ball bearing; thin Au film on quartz), this system can also be applied for residual stress and anisotropy mapping with high accuracy and good spatial resolution. 7 refs, 6 figs

An Evolutionary Approach to Automatic Keyword Selection for Twitter Data Analysis

In this paper, we propose an approach to intelligent and automatic keyword selection for the purpose of Twitter data collection and analysis. The proposed approach makes use of a combination of deep learning and evolutionary computing. As some context for application, we present the proposed algorithm using the case study of public health surveillance over Twitter, which is a field with a lot of interest. We also describe an optimization objective function particular to the keyword selection problem, as well as metrics for evaluating Twitter keywords, namely: reach and tweet retreival power, on top of traditional metrics such as precision. In our experiments, our evolutionary computing approach achieved a tweet retreival power of 0.55, compared to 0.35 achieved by the baseline human approach