19,614 research outputs found

    The importance of screening in children who snore

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    It is important to screen for OSAS in children who snore, as early treatment of OSAS can prevent neurocognitive, behavioural, cardiovascular and metabolic consequences. Paediatricians should always investigate sleep habits and the possible presence of snoring, respiratory efforts or pauses during routine examination of children. These instruments may be effectively used to identify patients with OSAS, and the specificity and positive predictive value may be increased by adding other screening instruments such as nocturnal pulse oximetry [10]. The sleep questionnaires are instruments that can be used to screen patient candidates for a PSG study for suspected OSAS, and to identify those with a mild form of SDB, enabling early treatment

    The genus of the configuration spaces for Artin groups of affine type

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    Let (W,S)(W,S) be a Coxeter system, SS finite, and let GWG_{W} be the associated Artin group. One has configuration spaces Y, YW,Y,\ Y_{W}, where GW=π1(YW),G_{W}=\pi_1(Y_{W}), and a natural WW-covering fW: Y→YW.f_{W}:\ Y\to Y_{W}. The Schwarz genus g(fW)g(f_{W}) is a natural topological invariant to consider. In this paper we generalize this result by computing the Schwarz genus for a class of Artin groups, which includes the affine-type Artin groups. Let K=K(W,S)K=K(W,S) be the simplicial scheme of all subsets J⊂SJ\subset S such that the parabolic group WJ W_J is finite. We introduce the class of groups for which dim(K)dim(K) equals the homological dimension of K,K, and we show that g(fW)g(f_{W}) is always the maximum possible for such class of groups. For affine Artin groups, such maximum reduces to the rank of the group. In general, it is given by dim(XW)+1,dim(X_{W})+1, where XW⊂YW X_{ W}\subset Y_{ W} is a well-known CWCW-complex which has the same homotopy type as YW. Y_{ W}.Comment: To appear in Atti Accad. Naz. Lincei Rend. Lincei Mat. App

    Can potassium provide a tool for better cancer immunotherapy?

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    Organic loading rate: a promising microbial management tool in anaerobic digestion

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    This study investigated the effect of changes in organic loading rate (OLR) and feedstock on the volatile fatty acids (VFAs) production and their potential use as a bioengineering management tool to improve stability of anaerobic digesters. Digesters were exposed to one or two changes in OLR using the same or different co-substrates (Fat Oil and Grease waste (FOG) and/or glycerol). Although all the OLR fluctuations produced a decrease in biogas and methane production, the digesters exposed twice to glycerol showed faster recovery towards stable conditions after the second OLR change. This was correlated with the composition of the VFAs produced and their mode of production, from parallel to sequential, resulting in a more efficient recovery from inhibition of methanogenesis. The change in acids processing after the first OLR increase induced a shift in the microbial community responsible of the process optimisation when the digesters were exposed to a subsequent OLR increase with the same feedstock. When the digesters were exposed to an OLR change with a different feedstock (FOG), the recovery took 7d longer than with the same one (glycerol). However, the microbial community showed functional resilience and was able to perform similarly to pre-exposure conditions. Thus, changes in operational conditions can be used to influence microbial community structure for anaerobic digestion (AD) optimisation. Finally, shorter recovery times and increased resilience of digesters were linked to higher numbers of Clostridia incertae sedis XV, suggesting that this group may be a good candidate for AD bioaugmentation to speed up recovery after process instability or OLR increase

    Civic Engagement and Service Learning Partnerships

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    Service learning is designed to promote volunteerism and civic awareness. Community engagement in higher education specifically involves university members partnering with local community organizations to address a need. Students engage with community partners through service learning and other activities (Moore & Mendez, 2014). Service learning is a practice that connects new knowledge and social responsibility through active learning (Benson & Younkin, 1996).https://digitalscholarship.unlv.edu/btp_expo/1083/thumbnail.jp

    Lead isotopic measurements in archeological objects

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    Pb isotopic analyses on metal artifacts help constrain their provenance. Useful and reliable data require analytical protocols that ensure accuracy and monitor precision. The interpretation can sometimes be ambiguous because natural ore deposits frequently have overlapping Pb isotopic compositions. In most cases, however, provenances can be reliably narrowed down. For the Alpine region, a pattern of small, strongly localized mine exploitations in pre-Roman times, supplemented by some long-distance trading, is taking shape

    Facet-Based Browsing in Video Retrieval: A Simulation-Based Evaluation

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    In this paper we introduce a novel interactive video retrieval approach which uses sub-needs of an information need for querying and organising the search process. The underlying assumption of this approach is that the search effectiveness will be enhanced when employed for interactive video retrieval. We explore the performance bounds of a faceted system by using the simulated user evaluation methodology on TRECVID data sets and also on the logs of a prior user experiment with the system. We discuss the simulated evaluation strategies employed in our evaluation and the effect on the use of both textual and visual features. The facets are simulated by the use of clustering the video shots using textual and visual features. The experimental results of our study demonstrate that the faceted browser can potentially improve the search effectiveness

    Parsimonious Mahalanobis Kernel for the Classification of High Dimensional Data

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    The classification of high dimensional data with kernel methods is considered in this article. Exploit- ing the emptiness property of high dimensional spaces, a kernel based on the Mahalanobis distance is proposed. The computation of the Mahalanobis distance requires the inversion of a covariance matrix. In high dimensional spaces, the estimated covariance matrix is ill-conditioned and its inversion is unstable or impossible. Using a parsimonious statistical model, namely the High Dimensional Discriminant Analysis model, the specific signal and noise subspaces are estimated for each considered class making the inverse of the class specific covariance matrix explicit and stable, leading to the definition of a parsimonious Mahalanobis kernel. A SVM based framework is used for selecting the hyperparameters of the parsimonious Mahalanobis kernel by optimizing the so-called radius-margin bound. Experimental results on three high dimensional data sets show that the proposed kernel is suitable for classifying high dimensional data, providing better classification accuracies than the conventional Gaussian kernel
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