Protein residue-residue contacts dictate the topology of protein structure and play an important role in structural biology, especially in de novo protein structure prediction. Accurate prediction of residue contacts ...
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ISBN:
(纸本)9781509016129
Protein residue-residue contacts dictate the topology of protein structure and play an important role in structural biology, especially in de novo protein structure prediction. Accurate prediction of residue contacts could improve the performance of de novo protein structure prediction methods. In this study, a novel method based on learning-to-rank (RRCRank) has been presented to predict protein residue-residue contacts. The proposed method formulates the contacts prediction problem as a ranking problem. Firstly, the contact probabilities of residue pairs are predicted by ensemble machine-learning classifiers and correlated mutations approaches. And then, the proposed method integrates the complementary outputs of machine-learning and correlated mutations approaches and uses the learning-to-rank algorithm to rank residue pairs based on their probabilities to be contacts. Benchmarked on the CASP11 dataset, the proposed method achieves an improved performance for all three categories of contacts (short-range, medium-range and long-range contacts), which shows the proposed method based on learning-to-rank could take advantage of machine-learning and correlated mutations approaches and could provide the state-of-the-art performance.
This paper proposes a novel probabilistic graphical model, called MTHMM-P, for partitioning general nonrigid motion into piecewise elastic motion, so as to achieve nonrigid motion estimation without the need of any a ...
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In order to build a fault-tolerant network, heterogeneous facilities are arranged in the network to prevent homogeneous faults from causing serious damage. This paper uses edge-colored graph to investigate the feature...
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In order to build a fault-tolerant network, heterogeneous facilities are arranged in the network to prevent homogeneous faults from causing serious damage. This paper uses edge-colored graph to investigate the features of a network topology which is survivable after a set of homogeneous devices malfunction. We propose an approach to designing such networks under arbitrary parameters. We also show that the proposed approach can be used to optimize inter-router connections in network-on-chip to reduce the additional consum!otion of energy and time delay.
Big data applications that rely on relational databases gradually expose limitations on scalability and performance. In recent years, Hadoop ecosystem has been widely adopted as an evolving solution. This paper presen...
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ISBN:
(纸本)9781509038077
Big data applications that rely on relational databases gradually expose limitations on scalability and performance. In recent years, Hadoop ecosystem has been widely adopted as an evolving solution. This paper presents the migration of a legacy data analytics application in a provincial data center. The target platform follows "no one size fits all" method. Considering different workloads, data storage is hybrid with distributed file system (HDFS) and distributed NoSQL database. Beyond the architecture re-design, we focus on the problem of data model transformation from relational database to NoSQL database. We propose a query-aware approach to free developers from tedious manual work. The approach generates query-specific views (NoView) for NoSQL and re-structures the views to align with NoSQL's data model. Our results show that the migrated application achieves high scalability and high performance. We believe that our practice provides valuable insights (such as NoSQL data modeling methodology), and the techniques can be easily applied to other similar migrations.
The Large Area Telescope (LAT) aboard the Fermi spacecraft routinely observes high-energy emission from gamma-ray bursts (GRBs). Here we present the second catalog of LAT-detected GRBs, covering the first 10 years of ...
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Component based enterprise systems are becoming extremely complex in which the availability and usability are influenced intensively by the system's anomalies. Anomaly prediction is highly important for ensuring a...
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Component based enterprise systems are becoming extremely complex in which the availability and usability are influenced intensively by the system's anomalies. Anomaly prediction is highly important for ensuring a system's stability, which aims at preventing anomaly from occurring through pre-failure warning. However, due to the system's complex nature and the noise from monitoring, capturing pre-failure symptoms is a challenging problem. In this paper, we present a sequential and an averaged recurrent neural networks (RNN) models for distributed systems and component based systems. Specifically, we use cycle representation to capture cyclical system behaviors, which can be used to improve prediction accuracy. The anomaly data used in the experiments is collected from RUBis, IBM System S, and the component based system of enterprise T. The experimental results show that our proposed methods can achieve high prediction accuracy with satisfying lead time. Our recurrent neural networks model also demonstrates time efficiency for monitoring large-scale systems.
This Letter presents the results of a search for pair-produced particles of masses above 100 GeV that each decay into at least four quarks. Using data collected by the CMS experiment at the LHC in 2015–2016, correspo...
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This Letter presents the results of a search for pair-produced particles of masses above 100 GeV that each decay into at least four quarks. Using data collected by the CMS experiment at the LHC in 2015–2016, corresponding to an integrated luminosity of 38.2 fb−1, reconstructed particles are clustered into two large jets of similar mass, each consistent with four-parton substructure. No statistically significant excess of data over the background prediction is observed in the distribution of average jet mass. Pair-produced squarks with dominant hadronic R-parity-violating decays into four quarks and with masses between 0.10 and 0.72 TeV are excluded at 95% confidence level. Similarly, pair-produced gluinos that decay into five quarks are also excluded with masses between 0.10 and 1.41 TeV at 95% confidence level. These are the first constraints that have been placed on pair-produced particles with masses below 400 GeV that decay into four or five quarks, bridging a significant gap in the coverage of R-parity-violating supersymmetry parameter space.
The χb1(3P) and χb2(3P) states are observed through their ϒ(3S)γ decays, using an event sample of proton-proton collisions collected by the CMS experiment at the CERN LHC. The data were collected at a center-of-mas...
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The χb1(3P) and χb2(3P) states are observed through their ϒ(3S)γ decays, using an event sample of proton-proton collisions collected by the CMS experiment at the CERN LHC. The data were collected at a center-of-mass energy of 13 TeV and correspond to an integrated luminosity of 80.0 fb−1. The ϒ(3S) mesons are identified through their dimuon decay channel, while the low-energy photons are detected after converting to e+e− pairs in the silicon tracker, leading to a χb(3P) mass resolution of 2.2 MeV. This is the first time that the J=1 and 2 states are well resolved and their masses individually measured: 10513.42±0.41(stat)±0.18(syst) MeV and 10524.02±0.57(stat)±0.18(syst) MeV; they are determined with respect to the world-average value of the ϒ(3S) mass, which has an uncertainty of 0.5 MeV. The mass splitting is measured to be 10.60±0.64(stat)±0.17(syst) MeV.
As an important characteristic of social media (i.e. Flickr or Facebook), user communities or groups are beginning to attract increasing attention. Most of the previous studies on group recommendation only consider a ...
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Efficient resource utilization requires that emerging datacenter interconnects support both high performance communication and efficient remote resource sharing. These goals require that the network be more tightly co...
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Efficient resource utilization requires that emerging datacenter interconnects support both high performance communication and efficient remote resource sharing. These goals require that the network be more tightly coupled with the CPU chips. Designing a new interconnection technology thus requires considering not only the interconnection itself, but also the design of the processors that will rely on it. In this paper, we study memory hierarchy implications for the design of high-speed datacenter interconnects particularly as they affect remote memory access -- and we use PCIe as the vehicle for our investigations. To that end, we build three complementary platforms： a PCIe-interconnected prototype server with which we measure and analyze current bottlenecks; a software simulator that lets us model microarchitectural and cache hierarchy changes; and an FPGA prototype system with a streamlined switchless customized protocol Thunder with which we study hardware optimizations outside the processor. We highlight several architectural modifications to better support remote memory access and communication, and quantify their impact and ]imitations.
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