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Yi Chen

Bio: Yi Chen is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Large Hadron Collider & Medicine. The author has an hindex of 217, co-authored 4342 publications receiving 293080 citations. Previous affiliations of Yi Chen include Rochester Institute of Technology & National Institutes of Health.


Papers
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Journal ArticleDOI
Georges Aad1, Alexander Kupco2, Peter Davison3, Samuel Webb4  +2879 moreInstitutions (213)
TL;DR: In this paper, a search for heavy Majorana neutrinos in events containing a pair of high-p(T) leptons of the same charge and high p(t) jets is presented, which is consistent with the background-only hypothesis based on the Standard Model expectation.
Abstract: A search for heavy Majorana neutrinos in events containing a pair of high-p(T) leptons of the same charge and high-p(T) jets is presented. The search uses 20.3 fb(-1) of pp collision data collected with the ATLAS detector at the CERN Large Hadron Collider with a centre-of-mass energy of root s = 8TeV. The data are found to be consistent with the background-only hypothesis based on the Standard Model expectation. In the context of a Type-I seesaw mechanism, limits are set on the production cross-section times branching ratio for production of heavy Majorana neutrinos in the mass range between 100 and 500 GeV. The limits are subsequently interpreted as limits on the mixing between the heavy Majorana neutrinos and the Standard Model neutrinos. In the context of a left-right symmetric model, limits on the production cross-section times branching ratio are set with respect to the masses of heavy Majorana neutrinos and heavy gauge bosons W-R and Z'.

196 citations

Proceedings ArticleDOI
27 Mar 2017
TL;DR: This paper proposes an accelerator-friendly neural-network training method, by leveraging the inherent self-healing capability of the neural- network, to prevent the large-weight synapses from being mapped to the abnormal memristors based on the fault/variation distribution in the RRAM crossbar.
Abstract: RRAM crossbar consisting of memristor devices can naturally carry out the matrix-vector multiplication; it thereby has gained a great momentum as a highly energy-efficient accelerator for neuromorphic computing. The resistance variations and stuck-at faults in the memristor devices, however, dramatically degrade not only the chip yield, but also the classification accuracy of the neural-networks running on the RRAM crossbar. Existing hardware-based solutions cause enormous overhead and power consumption, while software-based solutions are less efficient in tolerating stuck-at faults and large variations. In this paper, we propose an accelerator-friendly neural-network training method, by leveraging the inherent self-healing capability of the neural-network, to prevent the large-weight synapses from being mapped to the abnormal memristors based on the fault/variation distribution in the RRAM crossbar. Experimental results show the proposed method can pull the classification accuracy (10%–45% loss in previous works) up close to ideal level with ≤ 1% loss.

195 citations

Journal ArticleDOI
TL;DR: In this article, a new kind of carbon nitride (CNx) nanofiber has been prepared by the calcination of polypyrrole nanowires at 800 °C.
Abstract: A new kind of carbon nitride (CNx) nanofiber has been prepared by the calcination of polypyrrole nanowires at 800 °C. The product maintained a wire-like morphology during calcination, and the pyrrolic nitrogen in the polypyrrole nanowires gradually changed to pyridinic and graphitic nitrogen as annealing temperature increased. These CNx nanofibers, prepared at 800 °C, have a nitrogen concentration of about 10%. Pt nanoparticles with average size of ∼3 nm could therefore be easily immobilized onto the CNx nanofibers because of the inherent chemical activity arising from the nitrogen incorporation. The Pt/CNx composite catalyst thus obtained has a large electrochemically active area and gives good electrocatalytic performance for methanol oxidation, both in activity and stability, suggesting it has potential application in fuel cells.

195 citations

Journal ArticleDOI
Morad Aaboud, Georges Aad1, Brad Abbott2, Jalal Abdallah3  +2829 moreInstitutions (197)
TL;DR: In this paper, the mass of the $W$ boson was measured based on proton-proton collision data recorded in 2011 at a centre-of-mass energy of 7 TeV with the ATLAS detector at the LHC.
Abstract: A measurement of the mass of the $W$ boson is presented based on proton-proton collision data recorded in 2011 at a centre-of-mass energy of 7 TeV with the ATLAS detector at the LHC, and corresponding to 4.6 fb$^{-1}$ of integrated luminosity. The selected data sample consists of $7.8 \times 10^6$ candidates in the $W\rightarrow \mu u$ channel and $5.9 \times 10^6$ candidates in the $W\rightarrow e u$ channel. The $W$-boson mass is obtained from template fits to the reconstructed distributions of the charged lepton transverse momentum and of the $W$ boson transverse mass in the electron and muon decay channels, yielding \begin{eqnarray} m_W &=& 80370 \pm 7 \, (\textrm{stat.}) \pm 11 \, (\textrm{exp. syst.}) \pm 14 \, (\textrm{mod. syst.}) \, \textrm{MeV} &=& 80370 \pm 19 \, \textrm{MeV}, \end{eqnarray} where the first uncertainty is statistical, the second corresponds to the experimental systematic uncertainty, and the third to the physics-modelling systematic uncertainty. A measurement of the mass difference between the $W^+$ and $W^-$ bosons yields $m_{W^+}-m_{W^-} = -29 \pm 28$ MeV.

195 citations

Journal ArticleDOI
Xiuli Chai1, Zhihua Gan2, Yang Kang2, Yi Chen1, Xianxing Liu2 
TL;DR: A novel image encryption scheme employing the memristive hyperchaotic system, cellular automata and DNA sequence operations, which consists of diffusion process and a dynamic DNA encoding scheme, which is highly secure enough to resist common attacks.
Abstract: A novel image encryption scheme employing the memristive hyperchaotic system, cellular automata (CA) and DNA sequence operations is presented, which consists of diffusion process. SHA 256 hash function is used to give the secret key and compute the initial values of the chaotic system. Moreover, a dynamic DNA encoding scheme is introduced. Two DNA rule matrices for encoding the plain image and two-dimensional (2D) CA are generated from chaotic sequences, and they are controlled by the plain image, so that there are different DNA encoding rules for different original image. Besides, we manipulate block diffusion encryption method to the plain image in order to save time. The previous diffused block image and 2D CA are combined to affect the encryption effect of the current block image. Among them, 2D CA is updated by the local rule computed from the previous diffused sub image, and its initial configuration is determined by the chaotic sequences. Simulation results and security analyses both confirm that the proposed image encryption scheme not only demonstrates extraordinary encryption performance, but also resists various attacks. It can be applied in secure image and video communication fields. A novel chaos-based image encryption scheme is presented.The proposed encryption algorithm is sensitive to the plain image.This algorithm is highly secure enough to resist common attacks.

195 citations


Cited by
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[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
Abstract: Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules. The major component of KEGG is the PATHWAY database that consists of graphical diagrams of biochemical pathways including most of the known metabolic pathways and some of the known regulatory pathways. The pathway information is also represented by the ortholog group tables summarizing orthologous and paralogous gene groups among different organisms. KEGG maintains the GENES database for the gene catalogs of all organisms with complete genomes and selected organisms with partial genomes, which are continuously re-annotated, as well as the LIGAND database for chemical compounds and enzymes. Each gene catalog is associated with the graphical genome map for chromosomal locations that is represented by Java applet. In addition to the data collection efforts, KEGG develops and provides various computational tools, such as for reconstructing biochemical pathways from the complete genome sequence and for predicting gene regulatory networks from the gene expression profiles. The KEGG databases are daily updated and made freely available (http://www.genome.ad.jp/kegg/).

24,024 citations

Journal ArticleDOI
TL;DR: The philosophy and design of the limma package is reviewed, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

22,147 citations

Journal ArticleDOI
TL;DR: Atherosclerosis is an inflammatory disease as discussed by the authors, and it is a major cause of death in the United States, Europe, and much of Asia, despite changes in lifestyle and use of new pharmacologic approaches to lower plasma cholesterol concentrations.
Abstract: Atherosclerosis is an inflammatory disease. Because high plasma concentrations of cholesterol, in particular those of low-density lipoprotein (LDL) cholesterol, are one of the principal risk factors for atherosclerosis,1 the process of atherogenesis has been considered by many to consist largely of the accumulation of lipids within the artery wall; however, it is much more than that. Despite changes in lifestyle and the use of new pharmacologic approaches to lower plasma cholesterol concentrations,2,3 cardiovascular disease continues to be the principal cause of death in the United States, Europe, and much of Asia.4,5 In fact, the lesions of atherosclerosis represent . . .

19,881 citations