Miracle-dz/UniFAR-FTUs huggingface dataset:
Voice quality prediction models and their application in VoIP networks

The primary aim of this paper is to present new models for objective, nonintrusive, prediction of voice quality for IP networks and to illustrate their application to voice quality monitoring and playout buffer control in VoIP networks. The contributions of the paper are threefold. First, we present a new methodology for developing perceptually accurate models for nonintrusive prediction of voice quality which avoids time-consuming subjective tests. The methodology is generic and as such it has wide applicability in multimedia applications. Second, based on the new methodology, we present efficient regression models for predicting conversational voice quality nonintrusively for four modern codecs (G.729, G.723.1, AMR and iLBC). Third, we illustrate the usefulness of the models in two main applications - voice quality prediction for real Internet VoIP traces and perceived quality-driven playout buffer optimization. For voice quality prediction, the results show that the models have accuracy close to the combined ITU PESQ/E-model method using real Internet traces (correlation coefficient over 0.98). For playout buffer optimization, the proposed buffer algorithm provides an optimum voice quality when compared to five other buffer algorithms for all the traces considered
Mammalian translation elongation factor eEF1A2: X-ray structure and new features of GDP/GTP exchange mechanism in higher eukaryotes

Eukaryotic elongation factor eEF1A transits between the GTP- and GDP-bound conformations during the ribosomal polypeptide chain elongation. eEF1A*GTP establishes a complex with the aminoacyl-tRNA in the A site of the 80S ribosome. Correct codon–anticodon recognition triggers GTP hydrolysis, with subsequent dissociation of eEF1A*GDP from the ribosome. The structures of both the ‘GTP’- and ‘GDP’-bound conformations of eEF1A are unknown. Thus, the eEF1A-related ribosomal mechanisms were anticipated only by analogy with the bacterial homolog EF-Tu. Here, we report the first crystal structure of the mammalian eEF1A2*GDP complex which indicates major differences in the organization of the nucleotide-binding domain and intramolecular movements of eEF1A compared to EF-Tu. Our results explain the nucleotide exchange mechanism in the mammalian eEF1A and suggest that the first step of eEF1A*GDP dissociation from the 80S ribosome is the rotation of the nucleotide-binding domain observed after GTP hydrolysis.
First gamma-rays from galaxy clusters. Preliminary evidence of the association of galaxy clusters with EGRET unidentified gamma-ray sources

The vast majority of the celestial gamma-ray sources detected so far have not yet been identified with secure coun- terparts at other wavelenghts. Here we report preliminary evidence for an association between galaxy clusters and unidentified gamma-ray sources of high galactic latitude (|b| > 20 deg) in the Third EGRET catalog. All of the clusters which are most prob- ably associated with EGRET sources show evidence of strong radio emission either because they host radio galaxies/sources in their environments or because they have a radio halo or relic inhabiting their intracluster medium. The cluster radio emission suggests that the relativistic particles (electrons, protons), which are diffusing in the intracluster medium, might be also respon- sible for their gamma-ray emission. Beyond the spatial associations of clusters with unidentified EGRET sources, we found a correlation between the radio flux at 1.4 GHz of the cluster's brightest source and the gamma-ray flux, F(>100 MeV), of the associated EGRET source. For the most probable EGRET-cluster associations we also found a further correlation between the X-ray luminosity of galaxy clusters and the gamma-ray luminosity of the associated gamma-ray source under the hypothesis that the EGRET sources have the same cluster redshifts. Such correlations are consistent with the theoretical expectations and strengthen the probability of a true, physical association between galaxy clusters and gamma-ray sources.
Learning under Distributed Weak Supervision

The availability of training data for supervision is a frequently encountered bottleneck of medical image analysis methods. While typically established by a clinical expert rater, the increase in acquired imaging data renders traditional pixel-wise segmentations less feasible. In this paper, we examine the use of a crowdsourcing platform for the distribution of super-pixel weak annotation tasks and collect such annotations from a crowd of non-expert raters. The crowd annotations are subsequently used for training a fully convolutional neural network to address the problem of fetal brain segmentation in T2-weighted MR images. Using this approach we report encouraging results compared to highly targeted, fully supervised methods and potentially address a frequent problem impeding image analysis research.
Control of Electron Transfer and Catalysis in Neuronal Nitric-oxide Synthase (nNOS) by a Hinge Connecting Its FMN and FAD-NADPH Domains*

Background: Two flexible hinges may control electron transfer and catalysis in NOS enzymes. Results: Shortening or extending the FMN-FAD/NADPH hinge lowered NO synthesis, altered electron transfer, and uncoupled NADPH consumption. Conclusion: Native hinge length achieves a best compromise between NADPH oxidation, electron transfer, and NO synthesis. Significance: Determining how hinge length impacts catalysis helps reveal enzyme structure-activity relationships in NOS. In nitric-oxide synthases (NOSs), two flexible hinges connect the FMN domain to the rest of the enzyme and may guide its interactions with partner domains for electron transfer and catalysis. We investigated the role of the FMN-FAD/NADPH hinge in rat neuronal NOS (nNOS) by constructing mutants that either shortened or lengthened this hinge by 2, 4, and 6 residues. Shortening the hinge progressively inhibited electron flux through the calmodulin (CaM)-free and CaM-bound nNOS to cytochrome c, whereas hinge lengthening relieved repression of electron flux in CaM-free nNOS and had no impact or slowed electron flux through CaM-bound nNOS to cytochrome c. How hinge length influenced heme reduction depended on whether enzyme flavins were pre-reduced with NADPH prior to triggering heme reduction. Without pre-reduction, changing the hinge length was deleterious; with pre-reduction, the hinge shortening was deleterious, and hinge lengthening increased heme reduction rates beyond wild type. Flavin fluorescence and stopped-flow kinetic studies on CaM-bound enzymes suggested hinge lengthening slowed the domain-domain interaction needed for FMN reduction. All hinge length changes lowered NO synthesis activity and increased uncoupled NADPH consumption. We conclude that several aspects of catalysis are sensitive to FMN-FAD/NADPH hinge length and that the native hinge allows a best compromise among the FMN domain interactions and associated electron transfer events to maximize NO synthesis and minimize uncoupled NADPH consumption.
ErgoDesk: A Framework for Two- and Three-Dimensional Interaction at the ActiveDesk

We present ErgoDesk, a software and hardware framework for interacting at an ActiveDesk, a rear-projected drafting table-sized display. ErgoDesk represents a new interaction paradigm, based on physical props, multimodal input and a stereo-on-demand display surface, that seamlessly s upports transitions between a variety 2D and 3D interaction techniques. We provide a detailed discussion of the ErgoDesk framework’s major features including: the layout of physical props; the transitions between 2D and 3D interactions; the use of gestural and spoken input; and the transformation model for converting between real-world and virtual environment coordinates. We also discuss the design of ErgoSketch, a conceptual 3D modeling application built on the ErgoDesk framework, and our usability experiences with both over the past year.
Effective Denoising and Classification of Hyperspectral Images Using Curvelet Transform and Singular Spectrum Analysis

Hyperspectral imaging (HSI) classification has become a popular research topic in recent years, and effective feature extraction is an important step before the classification task. Traditionally, spectral feature extraction techniques are applied to the HSI data cube directly. This paper presents a novel algorithm for HSI feature extraction by exploiting the curvelet-transformed domain via a relatively new spectral feature processing technique-singular spectrum analysis (SSA). Although the wavelet transform has been widely applied for HSI data analysis, the curvelet transform is employed in this paper since it is able to separate image geometric details and background noise effectively. Using the support vector machine classifier, experimental results have shown that features extracted by SSA on curvelet coefficients have better performance in terms of classification accuracy over features extracted on wavelet coefficients. Since the proposed approach mainly relies on SSA for feature extraction on the spectral dimension, it actually belongs to the spectral feature extraction category. Therefore, the proposed method has also been compared with some state-of-the-art spectral feature extraction techniques to show its efficacy. In addition, it has been proven that the proposed method is able to remove the undesirable artifacts introduced during the data acquisition process. By adding an extra spatial postprocessing step to the classified map achieved using the proposed approach, we have shown that the classification performance is comparable with several recent spectral-spatial classification methods.
Macrophages present exogenous antigens by class I major histocompatibility complex molecules via a secretory pathway as a consequence of interferon‐γ activation

Macrophages can process and present exogenous antigens on major histocompatibility complex (MHC) class I molecules through an alternative mechanism involving the internalization of antigens and the secretion of peptides loading MHC class I molecules at the cell surface. In this paper, we found that interferon‐γ (IFN‐γ) ‐activated macrophages infected with Salmonella typhimurum secreted peptides able to load empty MHC Kb molecules on co‐cultured TAP‐2‐deficient RMA‐S cells, added as targets for peptide loading. The increase in class I Kb on the RMA‐S cells, resulting from the macrophage‐derived peptides, exhibited a comparable stability as the direct addition of an exogenous Kb‐binding peptide (OVA257–264) to the RMA‐S cells. In both cases, the Kb complexes were stable for at least 3 hr after separating the RMA‐S cells from the macrophages. The endosomal inhibitors, leupeptin and ammonium chloride, did not inhibit the release of peptides and the increase in Kb staining on the RMA‐S cells in the co‐culture systems. Brefeldin A also had no effect. P815 cells previously co‐cultured with Salmonella‐infected macrophages became targets for cytotoxic T lymphocytes isolated from Salmonella‐infected BALB/c mice. Taken together, our data suggest that IFN‐γ‐activated macrophages process exogenous antigens in an intracellular compartment where serine proteases generate peptides released to the external environment for loading empty MHC class I molecules at the cell surface. This TAP‐independent mechanism for the MHC class I presentation may be involved in priming cytotoxic T lymphocytes against intracellular pathogens in vivo.
Optimal and approximate computation of summary statistics for range aggregates

Fast estimates for aggregate queries are useful in database query optimization, approximate query answering and online query processing. Hence, there has been a lot of focus on “selectivity estimation”, that is, computing summary statistics on the underlying data and using that to answer aggregate queries fast and to a reasonable approximation. We present two sets of results for range aggregate queries, which are amongst the most common queries. First, we focus on a histogram as summary statistics and present algorithms for constructing histograms that are provably optimal (or provably approximate) for range queries; these algorithms take (pseudo-) polynomial time. These are the first known optimality or approximation results for arbitrary range queries; previously known results were optimal only for restricted range queries (such as equality queries, hierarchical or prefix range queries). Second, we focus on wavelet-based representations as summary statistics and present fast algorithms for picking wavelet statistics that are provably optimal for range queries. No previously-known wavelet-based methods have this property. We perform an experimental study of the various summary representations show the benefits of our algorithms over the known methods.
Building and Evaluation of a Distributed Neural Classifier

This article describes an automatic method for building of distributed neural classifiers for pattern recognition. The methodology is based upon the detection of reliable regions in the representation space, i.e. clusters exclusively composed of patterns from the same class. This detection is performed using a hierarchical clustering method associated with the supervised information provided by a professor. The proposed methodology consists of associating each of these regions with a Multi-Layer Perceptron (MLP) which has to recognise elements inside its region, while rejecting all others. Experimental results for a real problem (handwritten digit recognition) reveal an interesting generalisation behaviour of the distributed classifier in comparison to the k-nearest neighbour algorithm as well as a single MLP.
Reactive Nitrogen Intermediates Have a Bacteriostatic Effect on Mycobacterium tuberculosis In Vitro

ABSTRACT Susceptibility of six isolates of Mycobacterium tuberculosis (CB3.3, CDC1551, RJ2E, C.C.13, H37Rv, and H37Ra) and two isolates of Mycobacterium bovis (Ravenel and BCG) to reactive oxygen intermediates (ROI) and reactive nitrogen intermediates (RNI) was determined by standard in vitro survival assays. After 21 days of incubation, the survival of most strains exposed to either acidified sodium nitrite (ASN) or hydrogen peroxide (H2O2) was significantly lower than the same strains unexposed to these RNI or ROI products. However, after 50 days of incubation, these differences in susceptibility became less apparent for strains exposed to ASN but not for strains exposed to H2O2. The recovery of these strains after exposure to RNI suggests that the effect of RNI on M. tuberculosis is bacteriostatic. The in vitro concentrations of ROI and RNI used in these assays were higher than those expected in vivo. These observations suggest that, in vivo, RNI expression at physiologically achievable concentrations may keep M. tuberculosis from proliferating but that removal of RNI may allow the organisms to proliferate. Furthermore, the ability of some M. tuberculosis strains to cause rapidly progressive disease may relate to their intrinsic levels of RNI and ROI resistance.
Network Coding Theory - Part II: Multiple Source

Store-and-forward had been the predominant technique for transmitting information through a network until its optimality was refuted by network coding theory. Network coding offers a new paradigm for network communications and has generated abundant research interest in information and coding theory, networking, switching, wireless communications, cryptography, computer science, operations research, and matrix theory.
Spatially adaptive color filter array interpolation for noiseless and noisy data

Conventional single‐chip digital cameras use color filter arrays (CFA) to sample different spectral components. Demosaicing algorithms interpolate these data to complete red, green, and blue values for each image pixel, to produce an RGB image. In this article, we propose a novel demosaicing algorithm for the Bayer CFA. For the algorithm design, we assume that, following the concept proposed in (Zhang and Wu, IEEE Trans Image Process 14 ( 2005 ), 2167–2178), the initial interpolation estimates of color channels contain two additive components: the true values of color intensities and the errors that are considered as an additive noise. A specially designed signal‐adaptive filter is used to remove this so‐called demosaicing noise. This filter is based on the local polynomial approximation (LPA) and the paradigm of the intersection of confidence intervals applied to select varying scales of LPA. This technique is nonlinear and spatially‐adaptive with respect to the smoothness and irregularities of the image. The presented CFA interpolation (CFAI) technique takes significant advantage from assuming that the original data is noise‐free. Nevertheless, in many applications, the observed data is noisy, where the noise is treated as an important intrinsic degradation of the data. We develop an adaptation of the proposed CFAI for noisy data, integrating the denoising and CFAI into a single procedure. It is assumed that the data is given according to the Bayer pattern and corrupted by signal‐dependant noise common for charge‐coupled device and complementary‐symmetry/metal‐oxide semiconductor sensors. The efficiency of the proposed approach is demonstrated by experimental results with simulated and real data. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 105–122, 2007
Tackling the Load Uncertainty Challenges for Energy Consumption Scheduling in Smart Grid

In this paper, we propose a novel optimization-based real-time residential load management algorithm that takes into account load uncertainty in order to minimize the energy payment for each user. Unlike most existing demand side management algorithms that assume perfect knowledge of users' energy needs, our design only requires knowing some statistical estimates of the future load demand. Moreover, we consider real-time pricing combined with inclining block rate tariffs. In our problem formulation, we take into account different types of constraints on the operation of different appliances such as must-run appliances, controllable appliances that are interruptible, and controllable appliances that are not interruptible. Our design is multi-stage. As the demand information of the appliances is gradually revealed over time, the operation schedule of controllable appliances is updated accordingly. Simulation results confirm that the proposed energy consumption scheduling algorithm can benefit both users, by reducing their energy expenses, and utility companies, by improving the peak-to-average ratio of the aggregate load demand.
Q-score: proactive service quality assessment in a large IPTV system

In large-scale IPTV systems, it is essential to maintain high service quality while providing a wider variety of service features than typical traditional TV. Thus service quality assessment systems are of paramount importance as they monitor the user-perceived service quality and alert when issues occurs. For IPTV systems, however, there is no simple metric to represent user-perceived service quality and Quality of Experience (QoE). Moreover, there is only limited user feedback, often in the form of noisy and delayed customer calls. Therefore, we aim to approximate the QoE through a selected set of performance indicators in a proactive (i.e., detect issues before customers reports to call centers) and scalable fashion. In this paper, we present a service quality assessment framework, Q-score, which accurately learns a small set of performance indicators most relevant to user-perceived service quality, and proactively infers service quality in a single score. We evaluate Q-score using network data collected from a commercial IPTV service provider and show that Q-score is able to predict 60% of the service problems that are reported by customers with 0.1% false positives. Through Q-score, we have (i) gained insight into various types of service problems causing user dissatisfaction, including why users tend to react promptly to sound issues while late to video issues; (ii) identified and quantified the opportunity to proactively detect the service quality degradation of individual customers before severe performance impact occurs; and (iii) observed possibility to allocate customer care workforce to potentially troubling service areas before issues break out.
A Study of Spatial and Temporal Mass and Heat Transport of Hydrothermal Features in Norris Geyser Basin, Yellowstone National Park

In geothermal areas, the ground heat flux at and near the surface is mainly a combination of near-surface geothermal heat flux and the heat flux from absorbed solar shortwave radiation and atmospheric longwave radiation. In these areas, latent heat flux and sensible heat flux are mostly lost to the atmosphere as the ground temperature was mostly much higher than the surrounding atmosphere. Challenges still remain in removing the radiant flux due to absorbed solar radiation from thermal infrared remote sensing imagery that are mostly acquired during nights of mostly sunny days to avoid the effect of clouds. Removing the absorbed solar radiant effect from the images will allow for a more precise spatial estimate of radiant output due to the geothermal source allowing for temporal monitoring of the geothermal system. In this study a simple method based on a comparison of continuous measurement of conductive soil heat flux, surface four-way radiations, and ground temperature at and near the ground surface is propose to estimate the conductive heat flux due to solar radiation in a daily and seasonal basis. The heat flux due to solar radiation was estimated by comparing the average conductive heat flux at the surface when net radiation values (Rn) were negative and the ground temperature gradient values (ΔT) were positive (heat flows from the subsurface towards the surface), among selected overcast winter days and sunny summer days after 12 accounting for the heat lost by snow melt during the winter days. To results were validated through comparison with literature values estimated in non-geothermal grounds with similar surface albedo and atmospheric conditions, where the ground heat flux is mainly from solar and atmospheric longwave radiations. The estimated conductive heat flux from solar radiation was used to estimate the radiant geothermal flux assuming that the ratio between the estimated conductive heat flux and radiant flux from absorbed solar and atmospheric radiations equals the ration between the estimated total conductive heat flux and radiant flux estimated from high resolution thermal infrared imagery acquired for Norris Geyser Basin. This assumption assumes that the ratio between the conductive ground heat flux at the surface and the radiant flux at the same location is constant.
International Research Institute for Climate and Society

The mission of the IRI is to enhance society’s capability to understand, anticipate and manage the impacts of climate in order to improve human welfare and the environment, especially in developing countries. The IRI conducts this mission through strategic and applied research, education, capacity building, and by providing forecasts and information products with an emphasis on practical and verifiable utility and partnership.