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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Wenjuan Wu Guang-Fa Wang Xiaoying Gu Hong Gao ... Jungang Xie
A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not.
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Clinical Characteristics of Coronavirus Disease 2019 in China
Peng Peng Ruchong Chen Lan-juan Li Ya-hua Hu ... Chunliang Lei
Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of...
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A fast learning algorithm for deep belief nets
Geoffrey E. Hinton Yee Whye Teh Simon Osindero
We show how to use "complementary priors" to eliminate the explaining-away effects that make inference difficult in densely connected belief nets that have many hidden layers. Using complementary priors, we derive a fast, greedy algorithm that can learn deep, directed belief networks one layer at a time, provided the top two layers form an undirected associative memory. The fast, greedy algorithm is used to initialize a slower learning procedure that fine-tunes the weights using a contrastive version of the wake-sleep algorithm. After fine-tuning, a network with three hidden layers forms a very good generative model of the joint distribution of handwritten digit images and their labels. This generative model gives better digit classification than the best discriminative learning algorithms. The low-dimensional manifolds on which the digits lie are modeled by long ravines in the free-energy landscape of the top-level associative memory, and it is easy to explore these ravines by using the directed connections to display what the associative memory has in mind.
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OLEX2: a complete structure solution, refinement and analysis program
Luc J. Bourhis Judith A. K. Howard Oleg Dolomanov Richard J. Gildea Horst Puschmann
New software, OLEX2, has been developed for the determination, visualization and analysis of molecular crystal structures. The software has a portable mouse-driven workflow-oriented and fully comprehensive graphical user interface for structure solution, refinement and report generation, as well as novel tools for structure analysis. OLEX2 seamlessly links all aspects of the structure solution, refinement and publication process and presents them in a single workflow-driven package, with the ultimate goal of producing an application which will be useful to both chemists and crystallographers.
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Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC
Eric Lancon A. C. Schaffer M. George Mossadek Talby ... Peter Wienemann
A search for the Standard Model Higgs boson in proton–proton collisions with the ATLAS detector at the LHC is presented. The datasets used correspond to integrated luminosities of approximately 4.8 fb−1 collected at View the MathML source in 2011 and 5.8 fb−1 at View the MathML source in 2012. Individual searches in the channels H→ZZ(⁎)→4l, H→γγ and H→WW(⁎)→eνμν in the 8 TeV data are combined with previously published results of searches for H→ZZ(⁎), WW(⁎), View the MathML source and τ+τ− in the 7 TeV data and results from improved analyses of the H→ZZ(⁎)→4l and H→γγ channels in the 7 TeV data. Clear evidence for the production of a neutral boson with a measured mass of View the MathML source is presented. This observation, which has a significance of 5.9 standard deviations, corresponding to a background fluctuation probability of 1.7×10−9, is compatible with the production and decay of the Standard Model Higgs boson.
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Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
Alexander Tuzhilin Gediminas Adomavicius
This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main categories: content-based, collaborative, and hybrid recommendation approaches. This paper also describes various limitations of current recommendation methods and discusses possible extensions that can improve recommendation capabilities and make recommender systems applicable to an even broader range of applications. These extensions include, among others, an improvement of understanding of users and items, incorporation of the contextual information into the recommendation process, support for multicriteria ratings, and a provision of more flexible and less intrusive types of recommendations.
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2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk in Adults A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines
Patrick E. McBride Alice H. Lichtenstein C. Noel Bairey Merz Neil J. Stone ... Sidney C. Smith
Karen M. Eddleman, BS, Nicole M. Jarrett, Ken LaBresh, MD, Lev Nevo, MD, Janusz Wnek, PhD Jeffrey L. Anderson, MD, FACC, FAHA, Chair , Jonathan L. Halperin, MD, FACC, FAHA, Chair-Elect , Nancy M. Albert, PhD, CCNS, CCRN, FAHA, Biykem Bozkurt, MD, PhD, FACC, FAHA, Ralph G. Brindis, MD, MPH, MACC,
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2017 ESC/EACTS Guidelines for the management of valvular heart disease
Per Johan Holm Christian W. Hamm Emmanuel Lansac Patrizio Lancellotti ... Olaf Wendler
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Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Detection, Evaluation, and Treatment of High Blood Cholesterol Education Program (NCEP) Expert Panel on Executive Summary of the Third Report of the National
Nigel Unwin William C. Taylor
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Secure spread spectrum watermarking for multimedia
Ingemar J. Cox J. Kilian T. Shamoon F.T. Leighton
This paper presents a secure (tamper-resistant) algorithm for watermarking images, and a methodology for digital watermarking that may be generalized to audio, video, and multimedia data. We advocate that a watermark should be constructed as an independent and identically distributed (i.i.d.) Gaussian random vector that is imperceptibly inserted in a spread-spectrum-like fashion into the perceptually most significant spectral components of the data. We argue that insertion of a watermark under this regime makes the watermark robust to signal processing operations (such as lossy compression, filtering, digital-analog and analog-digital conversion, requantization, etc.), and common geometric transformations (such as cropping, scaling, translation, and rotation) provided that the original image is available and that it can be successfully registered against the transformed watermarked image. In these cases, the watermark detector unambiguously identifies the owner. Further, the use of Gaussian noise, ensures strong resilience to multiple-document, or collusional, attacks. Experimental results are provided to support these claims, along with an exposition of pending open problems.
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"GrabCut": interactive foreground extraction using iterated graph cuts
Andrew Blake Carsten Rother Vladimir Kolmogorov
The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g. Magic Wand, or edge (contrast) information, e.g. Intelligent Scissors. Recently, an approach based on optimization by graph-cut has been developed which successfully combines both types of information. In this paper we extend the graph-cut approach in three respects. First, we have developed a more powerful, iterative version of the optimisation. Secondly, the power of the iterative algorithm is used to simplify substantially the user interaction needed for a given quality of result. Thirdly, a robust algorithm for "border matting" has been developed to estimate simultaneously the alpha-matte around an object boundary and the colours of foreground pixels. We show that for moderately difficult examples the proposed method outperforms competitive tools.
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