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H2S Sensors: Fumarate‐Based fcu‐MOF Thin Film Grown on a Capacitive Interdigitated Electrode

Angewandte Chemie 2016年第51期128卷 16111-16115页

作者： Omar Yassine Osama Shekhah Ayalew H. Assen Youssef Belmabkhout Khaled N. Salama Mohamed Eddaoudi Sensors Lab Electrical Engineering Program Division of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology Thuwal 23955-6900 Saudi Arabia Functional Materials Design Discovery and Development research group (FMD3) Advanced Membranes & Porous Materials Center Division of Physical Sciences and Engineering King Abdullah University of Science and Technology Thuwal 23955-6900 Saudi Arabia

Herein we report the fabrication of an advanced sensor for the detection of hydrogen sulfide (H 2 S) at room temperature, using thin films of rare‐earth metal (RE)‐based metal–organic framework (MOF) with underlying fcu topology. This unique MOF‐based sensor is made via the in situ growth of fumarate‐based fcu ‐MOF (fum‐ fcu ‐MOF) thin film on a capacitive interdigitated electrode. The sensor showed a remarkable detection sensitivity for H 2 S at concentrations down to 100 ppb, with the lower detection limit around 5 ppb. The fum‐ fcu ‐MOF sensor exhibits a highly desirable detection selectivity towards H 2 S vs. CH 4 , NO 2 , H 2 , and C 7 H 8 as well as an outstanding H 2 S sensing stability as compared to other reported MOFs.

关键词： H2S Interdigital-Elektroden Metall-organische Gerüstverbindungen Seltenerdmetalle Sensoren

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Preconditioning techniques for reduced basis methods for parameterized elliptic partial differential equations

Preconditioning techniques for reduced basis methods for par...

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作者： Elman, Howard C. Forstall, Virginia Department of Computer Science Institute for Advanced Computer Studies University of Maryland College ParkMD20742 United States Applied Mathematics and Statistics and Scientific Computation Program University of Maryland College ParkMD20742 United States

The reduced basis methodology is an efficient approach to solve parameterized discrete partial differential equations when the solution is needed at many parameter values. An offline step approximates the solution space, and an online step utilizes this approximation, the reduced basis, to solve a smaller reduced problem, which provides an accurate estimate of the solution. Traditionally, the reduced problem is solved using direct methods. However, the size of the reduced system needed to produce solutions of a given accuracy depends on the characteristics of the problem, and it may happen that the size is significantly smaller than that of the original discrete problem but large enough to make direct solution costly. In this scenario, it may be more effective to use iterative methods to solve the reduced problem. We construct preconditioners for reduced iterative methods which are derived from preconditioners for the full problem. This approach permits reduced basis methods to be practical for larger bases than direct methods allow. We illustrate the effectiveness of iterative methods for solving reduced problems by considering two examples, the steady-state diffusion and convection-diffusion-reaction equations. © 2015 Society for Industrial and Applied Mathematics.

关键词： Iterative methods

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Joint analysis of Dark Energy Survey Year 3 data and CMB lensing from SPT and Planck. I. Construction of CMB lensing maps and modeling choices

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Physical Review D 2023年第2期107卷 023529-023529页

作者： Y. Omori E. J. Baxter C. Chang O. Friedrich A. Alarcon O. Alves A. Amon F. Andrade-Oliveira K. Bechtol M. R. Becker G. M. Bernstein J. Blazek L. E. Bleem H. Camacho A. Campos A. Carnero Rosell M. Carrasco Kind R. Cawthon R. Chen A. Choi J. Cordero T. M. Crawford M. Crocce C. Davis J. DeRose S. Dodelson C. Doux A. Drlica-Wagner K. Eckert T. F. Eifler F. Elsner J. Elvin-Poole S. Everett X. Fang A. Ferté P. Fosalba M. Gatti G. Giannini D. Gruen R. A. Gruendl I. Harrison K. Herner H. Huang E. M. Huff D. Huterer M. Jarvis E. Krause N. Kuropatkin P.-F. Leget P. Lemos A. R. Liddle N. MacCrann J. McCullough J. Muir J. Myles A. Navarro-Alsina S. Pandey Y. Park A. Porredon J. Prat M. Raveri R. P. Rollins A. Roodman R. Rosenfeld A. J. Ross E. S. Rykoff C. Sánchez J. Sanchez L. F. Secco I. Sevilla-Noarbe E. Sheldon T. Shin M. A. Troxel I. Tutusaus T. N. Varga N. Weaverdyck R. H. Wechsler W. L. K. Wu B. Yanny B. Yin Y. Zhang J. Zuntz T. M. C. Abbott M. Aguena S. Allam J. Annis D. Bacon B. A. Benson E. Bertin S. Bocquet D. Brooks D. L. Burke J. E. Carlstrom J. Carretero C. L. Chang R. Chown M. Costanzi L. N. da Costa A. T. Crites M. E. S. Pereira T. de Haan J. De Vicente S. Desai H. T. Diehl M. A. Dobbs P. Doel W. Everett I. Ferrero B. Flaugher D. Friedel J. Frieman J. García-Bellido E. Gaztanaga E. M. George T. Giannantonio N. W. Halverson S. R. Hinton G. P. Holder D. L. Hollowood W. L. Holzapfel K. Honscheid J. D. Hrubes D. J. James L. Knox K. Kuehn O. Lahav A. T. Lee M. Lima D. Luong-Van M. March J. J. McMahon P. Melchior F. Menanteau S. S. Meyer R. Miquel L. Mocanu J. J. Mohr R. Morgan T. Natoli S. Padin A. Palmese F. Paz-Chinchón A. Pieres A. A. Plazas Malagón C. Pryke C. L. Reichardt A. K. Romer J. E. Ruhl E. Sanchez K. K. Schaffer M. Schubnell S. Serrano E. Shirokoff M. Smith Z. Staniszewski A. A. Stark E. Suchyta G. Tarle D. Thomas C. To J. D. Vieira J. Weller R. Williamson Department of Astronomy and Astrophysics University of Chicago Chicago Illinois 60637 USA Kavli Institute for Cosmological Physics University of Chicago Chicago Illinois 60637 USA Department of Physics Stanford University 382 Via Pueblo Mall Stanford California 94305 USA Kavli Institute for Particle Astrophysics and Cosmology P. O. Box 2450 Stanford University Stanford California 94305 USA Institute for Astronomy University of Hawai’i 2680 Woodlawn Drive Honolulu Hawaii 96822 USA Kavli Institute for Cosmology University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom Argonne National Laboratory 9700 South Cass Avenue Lemont Illinois 60439 USA Department of Physics University of Michigan Ann Arbor Michigan 48109 USA Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 Rio de Janeiro RJ 20921-400 Brazil Physics Department 2320 Chamberlin Hall University of Wisconsin-Madison 1150 University Avenue Madison Wisconsin 53706-1390 USA Department of Physics and Astronomy University of Pennsylvania Philadelphia Pennsylvania 19104 USA Department of Physics Northeastern University Boston Massachusetts 02115 USA Laboratory of Astrophysics École Polytechnique Fédérale de Lausanne (EPFL) Observatoire de Sauverny 1290 Versoix Switzerland High-Energy Physics Division Argonne National Laboratory 9700 South Cass Avenue. Argonne Illinois 60439 USA Instituto de Física Teórica Universidade Estadual Paulista São Paulo 01140-070 Brazil Department of Physics Carnegie Mellon University Pittsburgh Pennsylvania 15312 USA Instituto de Astrofisica de Canarias E-38205 La Laguna Tenerife Spain Universidad de La Laguna Departamento Astrofísica E-38206 La Laguna Tenerife Spain Center for Astrophysical Surveys National Center for Supercomputing Applications 1205 West Clark Street Urbana Illinois 61801 USA Department of Astronomy University of Illinois at Urbana-Champaign 1002 W. Green Street Urbana Illinois 61801 USA Physic

Joint analyses of cross-correlations between measurements of galaxy positions, galaxy lensing, and lensing of the cosmic microwave background (CMB) offer powerful constraints on the large-scale structure of the Universe. In a forthcoming analysis, we will present cosmological constraints from the analysis of such cross-correlations measured using Year 3 data from the Dark Energy Survey (DES), and CMB data from the South Pole Telescope (SPT) and Planck. Here we present two key ingredients of this analysis: (1) an improved CMB lensing map in the SPT-SZ survey footprint and (2) the analysis methodology that will be used to extract cosmological information from the cross-correlation measurements. Relative to previous lensing maps made from the same CMB observations, we have implemented techniques to remove contamination from the thermal Sunyaev Zel’dovich effect, enabling the extraction of cosmological information from smaller angular scales of the cross-correlation measurements than in previous analyses with DES Year 1 data. We describe our model for the cross-correlations between these maps and DES data, and validate our modeling choices to demonstrate the robustness of our analysis. We then forecast the expected cosmological constraints from the galaxy survey-CMB lensing auto and cross-correlations. We find that the galaxy-CMB lensing and galaxy shear-CMB lensing correlations will on their own provide a constraint on S8=σ8Ωm/0.3 at the few percent level, providing a powerful consistency check for the DES-only constraints. We explore scenarios where external priors on shear calibration are removed, finding that the joint analysis of CMB lensing cross-correlations can provide constraints on the shear calibration amplitude at the 5% to 10% level.

关键词： Cosmic microwave background Cosmological parameters Dark matter Evolution of the Universe Gravitational lenses Large scale structure of the Universe

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Joint analysis of Dark Energy Survey Year 3 data and CMB lensing from SPT and Planck. II. Cross-correlation measurements and cosmological constraints

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Physical Review D 2023年第2期107卷 023530-023530页

作者： C. Chang Y. Omori E. J. Baxter C. Doux A. Choi S. Pandey A. Alarcon O. Alves A. Amon F. Andrade-Oliveira K. Bechtol M. R. Becker G. M. Bernstein F. Bianchini J. Blazek L. E. Bleem H. Camacho A. Campos A. Carnero Rosell M. Carrasco Kind R. Cawthon R. Chen J. Cordero T. M. Crawford M. Crocce C. Davis J. DeRose S. Dodelson A. Drlica-Wagner K. Eckert T. F. Eifler F. Elsner J. Elvin-Poole S. Everett X. Fang A. Ferté P. Fosalba O. Friedrich M. Gatti G. Giannini D. Gruen R. A. Gruendl I. Harrison K. Herner H. Huang E. M. Huff D. Huterer M. Jarvis A. Kovacs E. Krause N. Kuropatkin P.-F. Leget P. Lemos A. R. Liddle N. MacCrann J. McCullough J. Muir J. Myles A. Navarro-Alsina Y. Park A. Porredon J. Prat M. Raveri R. P. Rollins A. Roodman R. Rosenfeld A. J. Ross E. S. Rykoff C. Sánchez J. Sanchez L. F. Secco I. Sevilla-Noarbe E. Sheldon T. Shin M. A. Troxel I. Tutusaus T. N. Varga N. Weaverdyck R. H. Wechsler W. L. K. Wu B. Yanny B. Yin Y. Zhang J. Zuntz T. M. C. Abbott M. Aguena S. Allam J. Annis D. Bacon B. A. Benson E. Bertin S. Bocquet D. Brooks D. L. Burke J. E. Carlstrom J. Carretero C. L. Chang R. Chown M. Costanzi L. N. da Costa A. T. Crites M. E. S. Pereira T. de Haan J. De Vicente S. Desai H. T. Diehl M. A. Dobbs P. Doel W. Everett I. Ferrero B. Flaugher D. Friedel J. Frieman J. García-Bellido E. Gaztanaga E. M. George T. Giannantonio N. W. Halverson S. R. Hinton G. P. Holder D. L. Hollowood W. L. Holzapfel K. Honscheid J. D. Hrubes D. J. James L. Knox K. Kuehn O. Lahav A. T. Lee M. Lima D. Luong-Van M. March J. J. McMahon P. Melchior F. Menanteau S. S. Meyer R. Miquel L. Mocanu J. J. Mohr R. Morgan T. Natoli S. Padin A. Palmese F. Paz-Chinchón A. Pieres A. A. Plazas Malagón C. Pryke C. L. Reichardt M. Rodríguez-Monroy A. K. Romer J. E. Ruhl E. Sanchez K. K. Schaffer M. Schubnell S. Serrano E. Shirokoff M. Smith Z. Staniszewski A. A. Stark E. Suchyta G. Tarle D. Thomas C. To J. D. Vieira J. Weller R. Williamson Department of Astronomy and Astrophysics University of Chicago Chicago Illinois 60637 USA Kavli Institute for Cosmological Physics University of Chicago Chicago Illinois 60637 USA Department of Physics Stanford University 382 Via Pueblo Mall Stanford California 94305 USA Kavli Institute for Particle Astrophysics & Cosmology P. O. Box 2450 Stanford University Stanford California 94305 USA Institute for Astronomy University of Hawai‘i 2680 Woodlawn Drive Honolulu Hawaii 96822 USA Department of Physics and Astronomy University of Pennsylvania Philadelphia Pennsylvania 19104 USA California Institute of Technology 1200 East California Blvd MC 249-17 Pasadena California 91125 USA Argonne National Laboratory 9700 South Cass Avenue Lemont Illinois 60439 USA Department of Physics University of Michigan Ann Arbor Michigan 48109 USA Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 Rio de Janeiro RJ - 20921-400 Brazil Physics Department 2320 Chamberlin Hall University of Wisconsin-Madison 1150 University Avenue Madison Wisconsin 53706-1390 School of Physics University of Melbourne Parkville Victoria 3010 Australia Department of Physics Northeastern University Boston Massachusetts 02115 USA Laboratory of Astrophysics École Polytechnique Fédérale de Lausanne (EPFL) Observatoire de Sauverny 1290 Versoix Switzerland Instituto de Física Teórica Universidade Estadual Paulista São Paulo Brazil Department of Physics Carnegie Mellon University Pittsburgh Pennsylvania 15312 USA Instituto de Astrofisica de Canarias E-38205 La Laguna Tenerife Spain Universidad de La Laguna Dpto. Astrofísica E-38206 La Laguna Tenerife Spain Center for Astrophysical Surveys National Center for Supercomputing Applications 1205 West Clark St. Urbana Illinois 61801 USA Department of Astronomy University of Illinois at Urbana-Champaign 1002 W. Green Street Urbana Illinois 61801 USA Physics Department William Jewell College Liberty Missouri 6

Cross-correlations of galaxy positions and galaxy shears with maps of gravitational lensing of the cosmic microwave background (CMB) are sensitive to the distribution of large-scale structure in the Universe. Such cross-correlations are also expected to be immune to some of the systematic effects that complicate correlation measurements internal to galaxy surveys. We present measurements and modeling of the cross-correlations between galaxy positions and galaxy lensing measured in the first three years of data from the Dark Energy Survey with CMB lensing maps derived from a combination of data from the 2500 deg2 SPT-SZ survey conducted with the South Pole Telescope and full-sky data from the Planck satellite. The CMB lensing maps used in this analysis have been constructed in a way that minimizes biases from the thermal Sunyaev Zel’dovich effect, making them well suited for cross-correlation studies. The total signal-to-noise of the cross-correlation measurements is 23.9 (25.7) when using a choice of angular scales optimized for a linear (nonlinear) galaxy bias model. We use the cross-correlation measurements to obtain constraints on cosmological parameters. For our fiducial galaxy sample, which consist of four bins of magnitude-selected galaxies, we find constraints of Ωm=0.272−0.052+0.032 and S8≡σ8Ωm/0.3=0.736−0.028+0.032 (Ωm=0.245−0.044+0.026 and S8=0.734−0.028+0.035) when assuming linear (nonlinear) galaxy bias in our modeling. Considering only the cross-correlation of galaxy shear with CMB lensing, we find Ωm=0.270−0.061+0.043 and S8=0.740−0.029+0.034. Our constraints on S8 are consistent with recent cosmic shear measurements, but lower than the values preferred by primary CMB measurements from Planck.

关键词： Cosmic microwave background Cosmological parameters Large scale structure of the Universe

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Optimal CMB lensing reconstruction and parameter estimation with SPTpol data

arXiv

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arXiv 2020年

作者： Millea, Marius Daley, C.M. Chou, T.-L. Anderes, E. Ade, P.A.R. Anderson, A.J. Austermann, J.E. Avva, J.S. Beall, J.A. Bender, A.N. Benson, B.A. Bianchini, F. Bleem, L.E. Carlstrom, J.E. Chang, C.L. Chaubal, P. Chiang, H.C. Citron, R. Corbett Moran, C. Crawford, T.M. Crites, A.T. de Haan, T. Dobbs, M.A. Everett, W. Gallicchio, J. George, E.M. Goeckner-Wald, N. Guns, S. Gupta, N. Halverson, N.W. Henning, J.W. Hilton, G.C. Holder, G.P. Holzapfel, W.L. Hrubes, J.D. Huang, N. Hubmayr, J. Irwin, K.D. Knox, L. Lee, A.T. Li, D. Lowitz, A. McMahon, J.J. Meyer, S.S. Mocanu, L.M. Montgomery, J. Natoli, T. Nibarger, J.P. Noble, G. Novosad, V. Omori, Y. Padin, S. Patil, S. Pryke, C. Reichardt, C.L. Ruhl, J.E. Saliwanchik, B.R. Schaffer, K.K. Sievers, C. Smecher, G. Stark, A.A. Thorne, B. Tucker, C. Veach, T. Vieira, J.D. Wang, G. Whitehorn, N. Wu, W.L.K. Yefremenko, V. Department of Physics University of California BerkeleyCA94720 United States Astronomy Department University of Illinois at Urbana-Champaign 1002 W. Green Street UrbanaIL61801 United States Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Statistics University of California One Shields Avenue DavisCA95616 United States Cardiff University CardiffCF10 3XQ United Kingdom Fermi National Accelerator Laboratory MS209 P.O. Box 500 BataviaIL60510 United States NIST Quantum Devices Group 325 Broadway Mailcode 817.03 BoulderCO80305 United States Department of Physics University of Colorado BoulderCO80309 United States High Energy Physics Division Argonne National Laboratory 9700 S. Cass Avenue ArgonneIL60439 United States Department of Astronomy and Astrophysics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States School of Physics University of Melbourne ParkvilleVIC3010 Australia Enrico Fermi Institute University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Physics McGill University 3600 Rue University MontrealQCH3A 2T8 Canada School of Mathematics Statistics & Computer Science University of KwaZulu-Natal Durban South Africa University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Jet Propulsion Laboratory PasadenaCA91109 United States Dunlap Institute for Astronomy & Astrophysics University of Toronto 50 St George St TorontoONM5S 3H4 Canada Department of Astronomy & Astrophysics University of Toronto 50 St George St TorontoONM5S 3H4 Canada Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Canadian Institute for Advanced Research CIFAR Program in Gravity Extreme Universe TorontoONM5G 1Z8 Canada Department of Astrophysical and Pla

We perform the first simultaneous Bayesian parameter inference and optimal reconstruction of the gravitational lensing of the cosmic microwave background (CMB), using 100 deg2 of polarization observations from the SPTpol receiver on the South Pole Telescope. These data reach noise levels as low as 5.8 µK-arcmin in polarization, which are low enough that the typically used quadratic estimator (QE) technique for analyzing CMB lensing is significantly sub-optimal. Conversely, the Bayesian procedure extracts all lensing information from the data and is optimal at any noise level. We infer the amplitude of the gravitational lensing potential to be Aφ = 0.949 ±0.122 using the Bayesian pipeline, consistent with our QE pipeline result, but with 17% smaller error bars. The Bayesian analysis also provides a simple way to account for systematic uncertainties, performing a similar job as frequentist "bias hardening," and reducing the systematic uncertainty on Aφ due to polarization calibration from almost half of the statistical error to effectively zero. Finally, we jointly constrain Aφ along with AL, the amplitude of lensing-like effects on the CMB power spectra, demonstrating that the Bayesian method can be used to easily infer parameters both from an optimal lensing reconstruction and from the delensed CMB, while exactly accounting for the correlation between the two. These results demonstrate the feasibility of the Bayesian approach on real data, and pave the way for future analysis of deep CMB polarization measurements with SPT-3G, Simons Observatory, and CMB-S4, where improvements relative to the QE can reach 1.5 times tighter constraints on Aφ and 7 times lower effective lensing reconstruction noise. Copyright © 2020, The Authors. All rights reserved.

关键词： Cosmology

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Energy Aware Dynamic Routing Using SDN for a Campus Network

Energy Aware Dynamic Routing Using SDN for a Campus Network

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International Conference on Network-Based Information Systems (NBIS)

作者： Malik Najmus Siraj Nadeem Javaid Qaisar Shafi Zaheer Ahmed Umar Qasim Zahoor Ali Khan Center for Advanced Studies in Engineering (CASE) Islamabad Pakistan Pakistan COMSATS Institute of Information Technology Islamabad Pakistan School of Electrical Engineering and Computer Science (SEECS) NUST Islamabad Pakistan University of Alberta Edmonton AB Canada CIS Higher Colleges of Technology UAE Internetworking Program Dalhousie University Halifax NS Canada

ISBN: (纸本)9781509009800

Increase in traffic over internet by large number of mobile devices results into high energy consumption on network devices. In this paper, we address the necessity to reduce the energy consumption in a campus network that includes both wired and wireless network devices. Specifically, we propose dynamic link rate adaptation mechanism on Software Defined Network (SDN) switches and control power consumption on Access Points (APs) by using users association to an AP. Moreover, our online flow routing approach dynamically routes user traffic in order to decrease the overall energy consumption of whole network while taking in consideration Quality of Service (QoS), acceptance ratio on forwarding table and link BandWidth (BW) constraints. Our simulation result shows that our approach results in 3.69% less power consumption, and furthermore, there is no congested links nor overflow in flow table as compared to Dijkstra Ant colony Power (DAPower) that has 2 congested links for 150 users in a network, each generating 34 flows.

关键词： Power demand Routing Energy consumption Control systems Software Wireless communication Ports (computers)

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Measurements of B-mode polarization of the cosmic microwave background from 500 square degrees of SPTpol data

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Physical Review D 2020年第12期101卷 122003-122003页

作者： J. T. Sayre C. L. Reichardt J. W. Henning P. A. R. Ade A. J. Anderson J. E. Austermann J. S. Avva J. A. Beall A. N. Bender B. A. Benson F. Bianchini L. E. Bleem J. E. Carlstrom C. L. Chang P. Chaubal H. C. Chiang R. Citron C. Corbett Moran T. M. Crawford A. T. Crites T. de Haan M. A. Dobbs W. Everett J. Gallicchio E. M. George A. Gilbert N. Gupta N. W. Halverson N. Harrington G. C. Hilton G. P. Holder W. L. Holzapfel J. D. Hrubes N. Huang J. Hubmayr K. D. Irwin L. Knox A. T. Lee D. Li A. Lowitz J. J. McMahon S. S. Meyer L. M. Mocanu J. Montgomery A. Nadolski T. Natoli J. P. Nibarger G. Noble V. Novosad S. Padin S. Patil C. Pryke J. E. Ruhl B. R. Saliwanchik K. K. Schaffer C. Sievers G. Smecher A. A. Stark C. Tucker K. Vanderlinde T. Veach J. D. Vieira G. Wang N. Whitehorn W. L. K. Wu V. Yefremenko Department of Astrophysical and Planetary Sciences University of Colorado Boulder Colorado 80309 USA Department of Physics University of Colorado Boulder Colorado 80309 USA Physics Department Center for Education and Research in Cosmology and Astrophysics Case Western Reserve University Cleveland Ohio 44106 USA School of Physics University of Melbourne Parkville Victoria 3010 Australia High Energy Physics Division Argonne National Laboratory 9700 S. Cass Avenue Argonne Illinois 60439 USA Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Cardiff University Cardiff CF10 3XQ United Kingdom Fermi National Accelerator Laboratory MS209 P.O. Box 500 Batavia Illinois 60510 USA NIST Quantum Devices Group 325 Broadway Mailcode 817.03 Boulder Colorado 80305 USA Department of Physics University of California Berkeley California 94720 USA Department of Astronomy and Astrophysics University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Department of Physics University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Enrico Fermi Institute University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Department of Physics McGill University 3600 Rue University Montreal Quebec H3A 2T8 Canada School of Mathematics Statistics & Computer Science University of KwaZulu-Natal Durban South Africa University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA TAPIR Walter Burke Institute for Theoretical Physics California Institute of Technology 1200 E California Boulevard Pasadena California 91125 USA California Institute of Technology MS 249-17 1216 E. California Boulevard Pasadena California 91125 USA Physics Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Canadian Institute for Advanced Research CIFAR Program in Gravity and the Extreme Universe Toronto Ontario M5G 1Z8 Canada Harvey Mudd College 301 Platt

We report a B-mode power spectrum measurement from the cosmic microwave background (CMB) polarization anisotropy observations made using the SPTpol instrument on the South Pole Telescope. This work uses 500 deg2 of SPTpol data, a five-fold increase over the last SPTpol B-mode release. As a result, the bandpower uncertainties have been reduced by more than a factor of two, and the measurement extends to lower multipoles: 52<ℓ<2301. Data from both 95 and 150 GHz are used, allowing for three cross-spectra: 95 GHz × 95 GHz, 95 GHz × 150 GHz, and 150 GHz × 150 GHz. B-mode power is detected at very high significance; we find P(BB<0)=5.8×10−71, corresponding to a 18.1σ detection of power. With a prior on the galactic dust from Planck, WMAP and BICEP2/Keck observations, the SPTpol B-mode data can be used to set an upper limit on the tensor-to-scalar ratio, r<0.44 at 95% confidence (the expected 1σ constraint on r given the measurement uncertainties is 0.22). We find the measured B-mode power is consistent with the Planck best-fit ΛCDM model predictions. Scaling the predicted lensing B-mode power in this model by a factor Alens, the data prefer Alens=1.17±0.13. These data are currently the most precise measurements of B-mode power at ℓ>320.

关键词： Cosmic microwave background Cosmological parameters Inflation Primordial magnetic fields

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3-D reconstruction of digital outcrop model based on multiple view images and terrestrial laser scanning 16

3-D reconstruction of digital outcrop model based on multipl...

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16th Brazilian Symposium on GeoInformatics, GEOINFO 2015

作者： Da Silva, Reginaldo Macedônio Veronez, Maurício Roberto Gonzaga, Luiz Tognoli, Francisco M.W. De Souza, Marcelo Kehl Inocencio, Leonardo Campos VIZLab Advanced Visualization Laboratory UNISINOS São LeopoldoRS Brazil PPGEO Graduate Program on Geology UNISINOS São LeopoldoRS Brazil PIPCA Applied Computer Science Graduate Program - UNISINOS São LeopoldoRS Brazil

This paper presents a comparative study about 3D reconstruction based on active and passive sensors, mainly LiDAR - Terrestrial Laser Scanner (TLS) and raster images (photography), respectively. An accuracy analysis has been performed in the positioning of outcrop point clouds obtained by both techniques. To make the comparison feasible, datasets are composed by point clouds generated from multiple images in different poses using a consumer digital camera and directly by terrestrial laser scanner. After preprocessing stages to obtain these point clouds, both are compared, through the positional discrepancies and standard deviation. A preliminary analysis has been shown the feasible employment of digital image jointly 3D reconstruction method for digital outcrop modeling, concerning with data acquisition at low cost without significantly lost of accuracy when compared with LiDAR. © 2015 National Institute for Space Research INPE All rights reserved.

关键词： Image reconstruction

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Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

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Scientific data 2021年第1期8卷 242页

作者： Julien Cohen-Adad Eva Alonso-Ortiz Mihael Abramovic Carina Arneitz Nicole Atcheson Laura Barlow Robert L Barry Markus Barth Marco Battiston Christian Büchel Matthew Budde Virginie Callot Anna J E Combes Benjamin De Leener Maxime Descoteaux Paulo Loureiro de Sousa Marek Dostál Julien Doyon Adam Dvorak Falk Eippert Karla R Epperson Kevin S Epperson Patrick Freund Jürgen Finsterbusch Alexandru Foias Michela Fratini Issei Fukunaga Claudia A M Gandini Wheeler-Kingshott Giancarlo Germani Guillaume Gilbert Federico Giove Charley Gros Francesco Grussu Akifumi Hagiwara Pierre-Gilles Henry Tomáš Horák Masaaki Hori James Joers Kouhei Kamiya Haleh Karbasforoushan Miloš Keřkovský Ali Khatibi Joo-Won Kim Nawal Kinany Hagen H Kitzler Shannon Kolind Yazhuo Kong Petr Kudlička Paul Kuntke Nyoman D Kurniawan Slawomir Kusmia René Labounek Maria Marcella Laganà Cornelia Laule Christine S Law Christophe Lenglet Tobias Leutritz Yaou Liu Sara Llufriu Sean Mackey Eloy Martinez-Heras Loan Mattera Igor Nestrasil Kristin P O'Grady Nico Papinutto Daniel Papp Deborah Pareto Todd B Parrish Anna Pichiecchio Ferran Prados Àlex Rovira Marc J Ruitenberg Rebecca S Samson Giovanni Savini Maryam Seif Alan C Seifert Alex K Smith Seth A Smith Zachary A Smith Elisabeth Solana Y Suzuki George Tackley Alexandra Tinnermann Jan Valošek Dimitri Van De Ville Marios C Yiannakas Kenneth A Weber Ii Nikolaus Weiskopf Richard G Wise Patrik O Wyss Junqian Xu NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. jcohen@polymtl.ca. Functional Neuroimaging Unit CRIUGM Université de Montréal Montreal QC Canada. jcohen@polymtl.ca. Mila - Quebec AI Institute Montreal QC Canada. jcohen@polymtl.ca. NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. Department of Radiology Swiss Paraplegic Centre Nottwil Switzerland. Centre for Advanced Imaging The University of Queensland Brisbane Australia. Department of Radiology University of British Columbia Vancouver BC Canada. Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown MA USA. Department of Radiology Harvard Medical School Boston MA USA. Harvard-Massachusetts Institute of Technology Health Sciences & Technology Cambridge MA USA. School of Information Technology and Electrical Engineering The University of Queensland Brisbane Australia. NMR Research Unit Queen Square MS Centre UCL Queen Square Institute of Neurology Faculty of Brain Sciences University College London London UK. Department of Systems Neuroscience University Medical Center Hamburg-Eppendorf Hamburg Germany. Department of Neurosurgery Medical College of Wisconsin Milwaukee WI USA. Aix-Marseille Univ CNRS CRMBM Marseille France. APHM Hopital Universitaire Timone CEMEREM Marseille France. Vanderbilt University Institute of Imaging Science Vanderbilt University Medical Center Nashville TN USA. Department of Computer and Software Engineering Polytechnique Montreal Montreal Canada. CHU Sainte-Justine Research Centre Montreal QC Canada. Centre de Recherche CHUS CIMS Sherbrooke Canada. Sherbrooke Connectivity Imaging Lab (SCIL) Computer Science department Université de Sherbrooke Sherbrooke Canada. Université de Strasbourg CNRS ICube Strasbourg France. UHB - University Hospital Brno and Masaryk University Department of Radiology and Nuclear

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Addendum: The FAIR Guiding Principles for scientific data management and stewardship

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Scientific data 2019年第1期6卷 6页

作者： Mark D Wilkinson Michel Dumontier Ijsbrand Jan Aalbersberg Gabrielle Appleton Myles Axton Arie Baak Niklas Blomberg Jan-Willem Boiten Luiz Bonino da Silva Santos Philip E Bourne Jildau Bouwman Anthony J Brookes Tim Clark Mercè Crosas Ingrid Dillo Olivier Dumon Scott Edmunds Chris T Evelo Richard Finkers Alejandra Gonzalez-Beltran Alasdair J G Gray Paul Groth Carole Goble Jeffrey S Grethe Jaap Heringa Peter A C 't Hoen Rob Hooft Tobias Kuhn Ruben Kok Joost Kok Scott J Lusher Maryann E Martone Albert Mons Abel L Packer Bengt Persson Philippe Rocca-Serra Marco Roos Rene van Schaik Susanna-Assunta Sansone Erik Schultes Thierry Sengstag Ted Slater George Strawn Morris A Swertz Mark Thompson Johan van der Lei Erik van Mulligen Andra Waagmeester Peter Wittenburg Katherine Wolstencroft Jun Zhao Barend Mons Center for Plant Biotechnology and Genomics Universidad Politécnica de Madrid Madrid 28223 Spain. Stanford University Stanford 94305-5411 USA. Elsevier Amsterdam 1043 NX The Netherlands. Nature Genetics New York 10004-1562 USA. Euretos and Phortos Consultants Rotterdam 2741 CA The Netherlands. ELIXIR Wellcome Genome Campus Hinxton CB10 1SA UK. Lygature Eindhoven 5656 AG The Netherlands. Vrije Universiteit Amsterdam Dutch Techcenter for Life Sciences Amsterdam 1081 HV The Netherlands. Office of the Director National Institutes of Health Rockville 20892 USA. TNO Zeist 3700 AJ The Netherlands. Department of Genetics University of Leicester Leicester LE1 7RH UK. Harvard Medical School Boston Massachusetts MA 02115 USA. Harvard University Cambridge Massachusetts MA 02138 USA. Data Archiving and Networked Services (DANS) The Hague 2593 HW The Netherlands. GigaScience Beijing Genomics Institute Shenzhen 518083 China. Department of Bioinformatics Maastricht University Maastricht 6200 MD The Netherlands. Wageningen UR Plant Breeding Wageningen 6708 PB The Netherlands. Oxford e-Research Center University of Oxford Oxford OX1 3QG UK. Heriot-Watt University Edinburgh EH14 4AS UK. School of Computer Science University of Manchester Manchester M13 9PL UK. Center for Research in Biological Systems School of Medicine University of California San Diego La Jolla California 92093-0446 USA. Dutch Techcenter for the Life Sciences Utrecht 3501 DE The Netherlands. Department of Human Genetics Leiden University Medical Center Dutch Techcenter for the Life Sciences Leiden 2300 RC The Netherlands. Dutch TechCenter for Life Sciences and ELIXIR-NL Utrecht 3501 DE The Netherlands. VU University Amsterdam Amsterdam 1081 HV The Netherlands. Leiden Center of Data Science Leiden University Leiden 2300 RA The Netherlands. Netherlands eScience Center Amsterdam 1098 XG The Netherlands. National Center for Microscopy and Imaging Research UCSD San Di

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