3,013 research outputs found
ShenZhen transportation system (SZTS): a novel big data benchmark suite
Data analytics is at the core of the supply chain for both products and services in modern economies and societies. Big data workloads, however, are placing unprecedented demands on computing technologies, calling for a deep understanding and characterization of these emerging workloads. In this paper, we propose ShenZhen Transportation System (SZTS), a novel big data Hadoop benchmark suite comprised of real-life transportation analysis applications with real-life input data sets from Shenzhen in China. SZTS uniquely focuses on a specific and real-life application domain whereas other existing Hadoop benchmark suites, such as HiBench and CloudRank-D, consist of generic algorithms with synthetic inputs. We perform a cross-layer workload characterization at the microarchitecture level, the operating system (OS) level, and the job level, revealing unique characteristics of SZTS compared to existing Hadoop benchmarks as well as general-purpose multi-core PARSEC benchmarks. We also study the sensitivity of workload behavior with respect to input data size, and we propose a methodology for identifying representative input data sets
Imaging Neural Activity in the Primary Somatosensory Cortex Using Thy1-GCaMP6s Transgenic Mice
The mammalian brain exhibits marked symmetry across the sagittal plane. However, detailed description of neural dynamics in symmetric brain regions in adult mammalian animals remains elusive. In this study, we describe an experimental procedure for measuring calcium dynamics through dual optical windows above bilateral primary somatosensory corticies (S1) in Thy1-GCaMP6s transgenic mice using 2-photon (2P) microscopy. This method enables recordings and quantifications of neural activity in bilateral mouse brain regions one at a time in the same experiment for a prolonged period in vivo. Key aspects of this method, which can be completed within an hour, include minimally invasive surgery procedures for creating dual optical windows, and the use of 2P imaging. Although we only demonstrate the technique in the S1 area, the method can be applied to other regions of the living brain facilitating the elucidation of structural and functional complexities of brain neural networks
Detection and localization of continuous gravitational waves with pulsar timing arrays: the role of pulsar terms
A pulsar timing array is a Galactic-scale detector of nanohertz gravitational
waves (GWs). Its target signals contain two components: the `Earth term' and
the `pulsar term' corresponding to GWs incident on the Earth and pulsar
respectively. In this work we present a Frequentist method for the detection
and localization of continuous waves that takes into account the pulsar term
and is significantly faster than existing methods. We investigate the role of
pulsar terms by comparing a full-signal search with an Earth-term-only search
for non-evolving black hole binaries. By applying the method to synthetic data
sets, we find that (i) a full-signal search can slightly improve the detection
probability (by about five percent); (ii) sky localization is biased if only
Earth terms are searched for and the inclusion of pulsar terms is critical to
remove such a bias; (iii) in the case of strong detections (with
signal-to-noise ratio 30), it may be possible to improve pulsar
distance estimation through GW measurements.Comment: 12 pages, 9 figures, typos corrected. To match the published version.
Code implementing this method is available at the PPTA Wiki pag
Diniconazole
The asymmetric unit of the title compound [systematic name: (E)-1-(2,4-dichlorophenyl)-4,4-dimethyl-2-(1H-1,2,4-triazol-1-yl)pent-1-en-3-ol], C15H17Cl2N3O, contains two molecules in which the dihedral angles between the triazole and benzene rings are 9.4 (2) and 35.0 (2)°. In the crystal, the molecules are linked by O—H⋯N hydrogen bonds, forming C(7) chains propagating in [010]
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