检索结果-内蒙古大学图书馆

Transcript expression-aware annotation improves rare variant interpretation (vol 581, pg 452, 2020)

NATURE 2021年第7846期590卷 E54-E54页

作者： Cummings, Beryl B. Karczewski, Konrad J. Kosmicki, Jack A. Seaby, Eleanor G. Watts, Nicholas A. Singer-Berk, Moriel Mudge, Jonathan M. Karjalainen, Juha Satterstrom, F. Kyle O'Donnell-Luria, Anne H. Poterba, Timothy Seed, Cotton Solomonson, Matthew Alfoldi, Jessica Daly, Mark J. MacArthur, Daniel G. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Analytical and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Genomic Informatics Group University Hospital Southampton Southampton UK Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA USA Division of Genetics and Genomics Boston Children’s Hospital Boston MA USA Department of Pediatrics Harvard Medical School Boston MA USA European Molecular Biology Laboratory European Bioinformatics Institute Wellcome Genome Campus Hinxton Cambridge UK Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Broad Genomics Broad Institute of MIT and Harvard Cambridge MA USA National Heart & Lung Institute and MRC London Institute of Medical Sciences Imperial College London London UK Cardiovascular Research Centre Royal Brompton & Harefield Hospitals NHS Trust London UK Cardiac Arrhythmia Service and Cardiovascular Research Center Massachusetts General Hospital Boston MA USA Estonian Genome Center Institute of Genomics University of Tartu Tartu Estonia Department of Medicine Harvard Medical School Boston MA USA Cardiac Arrhythmia Service Massachusetts General Hospital Boston MA USA Division of General Internal Medicine Massachusetts General Hospital Boston MA USA Institute for Molecular Medicine FIMM University of Helsinki Helsinki Finland Department of Public Health Faculty of Medicine University of Helsinki Helsinki Finland Department of Genetics Harvard Medical School Boston MA USA Data Sciences Platform Broad Institute of MIT and Harvard Cambridge MA USA Genomics Platform Broad Institute of MIT and Harvard Cambridge MA USA Wellcome Sanger Institute Hinxton Cambridgeshire UK Unidad de Investigaci

来源：评论

学校读者我要写书评

暂无评论

25th Annual Computational neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

引用

BMC neuroscience 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

关键词：

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Optimal CMB lensing reconstruction and parameter estimation with SPTpol data

arXiv

引用

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

来源：评论

学校读者我要写书评

暂无评论

Detection of carotid artery stenosis via electronic stethoscope: A preliminary study with heart sound segmentation

Detection of carotid artery stenosis via electronic stethosc...

引用

IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Jin-For Li An-Bang Liu Wei-Min Liu Dept. of Computer Science and Information Engineering National Chung-Cheng University Taiwan Neuroscience Center Taiwan

ISBN: (纸本)9781479987467

Carotid stenosis is an important indicator and one of the main causes of ischemic stroke. Since the stenosis transformation is gradual, the patients usually can't be aware of abnormality immediately. Therefore a convenient non-invasive examination method is needed to help the general public monitor the status of carotid artery stenosis. In this work we used electronic stethoscope to record the sound of blood flow, and extract the systolic fragments. The experimental results reveal the approximate entropy can be used as a preliminary feature to detect carotid stenosis (p

关键词： Blood flow Heart Stethoscope Entropy Carotid arteries Feature extraction Data analysis

来源：评论

学校读者我要写书评

暂无评论

Searching for Anisotropic Cosmic Birefringence with Polarization Data from SPTpol

arXiv

引用

arXiv 2020年

作者： Bianchini, F. Wu, W.L.K. Ade, P.A.R. Anderson, A.J. Austermann, J.E. Avva, J.S. Balkenhol, L. Baxter, E. Beall, J.A. Bender, A.N. Benson, B.A. Bleem, L.E. Carlstrom, J.E. Chang, C.L. Chaubal, P. Chiang, H.C. Chou, T.L. Citron, R. Moran, C. Corbett Crawford, T.M. Crites, A.T. Haan, T. de Dobbs, M.A. Everett, W. Gallicchio, J. George, E.M. Gilbert, A. 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. Manzotti, A. McMahon, J.J. Meyer, S.S. Millea, M. Mocanu, L.M. Montgomery, J. Nadolski, A. 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. Simard, G. Smecher, G. Stark, A.A. Story, K.T. Tucker, C. Vanderlinde, K. Veach, T. Vieira, J.D. Wang, G. Whitehorn, N. Yefremenko, V. School of Physics University of Melbourne ParkvilleVIC3010 Australia Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 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 Department of Physics University of California BerkeleyCA94720 United States Institute for Astronomy University of Hawai’i 2680 Woodlawn Drive HonoluluHI96822 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 Department of Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States 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 Department of Physics University of Chicago ChicagoIL60637 United States University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States TAPIR Walter Burke Institute for Theoretical Physics California Institute of Technology 1200 E California Blvd PasadenaCA91125 United States California Institute of Technology MS 249-17 1216 E. California Blvd. PasadenaCA91125 United States Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Canadian Institute for Advanced Research CIFAR Program in Gravity and the Extreme Universe TorontoONM5G 1Z8 Canada Department of Astrophysical and Planetary Sciences University of Colorado BoulderCO80309 U

来源：评论

学校读者我要写书评

暂无评论

Exploring equivalence metrics to analyze behavior in a naked mole rat colony 28

Exploring equivalence metrics to analyze behavior in a naked...

引用

28th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2015

作者： Imberman, Susan P. Kress, Michael E. McCloskey, Dan P. Dept. Psychology College of Staten Island 2800 Victory Blvd Staten IslandNY10314 United States CSI/IBR Center for Developmental Neuroscience College of Staten Island 2800 Victory Blvd Staten IslandNY10314 United States Vice President of Technology Systems College of Staten Island 2800 Victory Blvd Staten IslandNY10314 United States Dept. Computer Science College of Staten Island 2800 Victory Blvd Staten IslandNY10314 United States Doctoral Program Computer Science the Graduate Center CUNY United States

ISBN: (纸本)9781577357308

Many Stat. and Data Mining Techniques Have Been Used to Analyze the Deluge of Data Generated by Comp. Sensing Devices. Behav. Psychologists Traditionally Have Relied on low-tech Methodologies for Observing Anim. Behav. in the Wild and the Lab.. These Methods Are Time Intensive and Laborious. When the Observed Anim. Is A Colony Anim., with Many Individuals to Observe, Traditional Methods Fail We Inject RFID Passive Transponders under the Skin of Our Stud. Anim., the Naked Mole-rat . RFID Readers Are Placed Throughout the Housing Environ., Allowing Us to Track Anim. Movements As They Move Through These Areas, with Sub-second Resolution for Long Periods of Time. This Methodol. Generates Huge Amounts of Data Requiring Big Data Analyt. Techniques. in This Paper, We Investigate Equivalence Metrics, Specifically the Pearson Correlation Coefficient and Hamming Distance, to Analyze Behav. Changes in the Social Netwk. Struct. of A Naked Mole Rat Colony. Our Results Showed That A Pearson Correlation Was Sufficient to Detect Equip. Error and Hamming Distance Could Detect Changes in Colony Behav.. Copyright 2015, Assoc. for the Adv. of Artif. Intell. . All Rights Reserved.

关键词： Hamming distance

来源：评论

学校读者我要写书评

暂无评论

Variational inference for latent variables and uncertain inputs in Gaussian processes

The Journal of Machine Learning Research

引用

The Journal of Machine Learning Research 2016年第1期17卷

作者： Kevin Murphy Bernhard Schölkopf Andreas C. Damianou Michalis K. Titsias Neil D. Lawrence Google MPI for Intelligent Systems Dept. of Computer Science and Sheffield Institute for Translational Neuroscience University of Sheffield UK Department of Informatics Athens University of Economics and Business Greece

The Gaussian process latent variable model (GP-LVM) provides a flexible approach for non-linear dimensionality reduction that has been widely applied. However, the current approach for training GP-LVMs is based on maximum likelihood, where the latent projection variables are maximised over rather than integrated out. In this paper we present a Bayesian method for training GP-LVMs by introducing a non-standard variational inference framework that allows to approximately integrate out the latent variables and subsequently train a GP-LVM by maximising an analytic lower bound on the exact marginal likelihood. We apply this method for learning a GP-LVM from i.i.d. observations and for learning non-linear dynamical systems where the observations are temporally correlated. We show that a benefit of the variational Bayesian procedure is its robustness to overfitting and its ability to automatically select the dimensionality of the non-linear latent space. The resulting framework is generic, flexible and easy to extend for other purposes, such as Gaussian process regression with uncertain or partially missing inputs. We demonstrate our method on synthetic data and standard machine learning benchmarks, as well as challenging real world datasets, including high resolution video data.

关键词： Gaussian processes dynamical systems latent variable models uncertain inputs variational inference

来源：评论

学校读者我要写书评

暂无评论

An improved measurement of the secondary cosmic microwave background anisotropies from the SPT-SZ + SPTpol surveys

arXiv

引用

arXiv 2020年

作者： Reichardt, Christian L. Patil, S. Ade, P.A.R. Anderson, A.J. Austermann, J.E. Avva, J.S. Baxter, E. 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. Chou, T.L. Citron, R. Moran, C. Corbett Crawford, T.M. Crites, A.T. de Haan, T. Dobbs, M.A. Everett, W. Gallicchio, J. George, E.M. Gilbert, A. Gupta, N. Halverson, N.W. Harrington, N. 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. Luong-Van, D. McMahon, J.J. Mehl, J. Meyer, S.S. Millea, M. Mocanu, L.M. Mohr, J.J. Montgomery, J. Nadolski, A. Natoli, T. Nibarger, J.P. Noble, G. Novosad, V. Omori, Y. Padin, S. Pryke, C. Ruhl, J.E. Saliwanchik, B.R. Sayre, J.T. Schaffer, K.K. Shirokoff, E. Sievers, C. Smecher, G. Spieler, H.G. Staniszewski, Z. Stark, A.A. Tucker, C. Vanderlinde, K. Veach, T. Vieira, J.D. Wang, G. Whitehorn, N. Williamson, R. Wu, W.L.K. Yefremenko, V. School of Physics University of Melbourne ParkvilleVIC3010 Australia 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 Department of Physics University of California BerkeleyCA94720 United States Institute for Astronomy University of Hawaii 2680 Woodlawn Drive HonoluluHI96822 United States Department of Physics and Astronomy University of Pennsylvania PhiladelphiaPA19104 United States High Energy Physics Division Argonne National Laboratory 9700 S. Cass Avenue ArgonneIL60439 United States Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Astronomy and Astrophysics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States 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 4800 Oak Grove Drive PasadenaCA91109 United States California Institute of Technology MS 249-17 1216 E. California Blvd. PasadenaCA91125 United States Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Canadian Institute for Advanced Research CIFAR Program in Gravity the Extreme Universe TorontoONM5G 1Z8 Canada Department of Astrophysical and Planetary Sciences University of Colorado BoulderCO80309 United States Harvey Mudd College 301 Platt Blv

We report new measurements of millimeter-wave power spectra in the angular multipole range 2000 ≤ ` ≤ 11, 000 (angular scales 50 & θ & 10). By adding 95 and 150 GHz data from the low-noise 500 deg2 SPTpol survey to the SPT-SZ three-frequency 2540 deg2 survey, we substantially reduce the uncertainties in these bands. These power spectra include contributions from the primary cosmic microwave background, cosmic infrared background, radio galaxies, and thermal and kinematic Sunyaev-Zel’dovich (SZ) effects. The data favor a thermal SZ (tSZ) power at 143 GHz of D3000tSZ = 3.42±0.54 µK2 and a kinematic SZ (kSZ) power of D3000kSZ = 3.0 ±1.0 µK2. This is the first measurement of kSZ power at ≥ 3 σ. We study the implications of the measured kSZ power for the epoch of reionization, finding the duration of reionization to be ∆zre = 1.1+1−067 (∆zre Copyright © 2020, The Authors. All rights reserved.

关键词： Cosmology

来源：评论

学校读者我要写书评

暂无评论

Bridging Higher Education and Market Dynamics in a Business Intelligence Framework

Bridging Higher Education and Market Dynamics in a Business ...

引用

International Conference on Developments in eSystems Engineering (DESE)

作者： Izzeldin Elhassan Fanny Klett Computer Science Dept. PhD program Sudan University of Science and Technology Khartoum Sudan German Workforce ADL Partnership Laboratory Germany

ISBN: (纸本)9781509018628

The expansion of urbanization and demographic changes defines not only economic demands but makes governments increasingly experience a serious force toward a sustainable development, which causes a need for a qualified and retaining competitive workforce. In view of this trend, governments and businesses start considering technology as vital enabler to solve the rising urbanization issues and improve the living and working environments according to a set of priorities. Simultaneously, competency and skills development are seen as the critical issue for the workforce and the workplaces. Accordingly, the complex interrelationship between strategic management, human capital management, and the overall quality management in an educational as well as enterprise setting move closer to the focus of research. This paper discusses an emerging area of research, which explores the utilization of both, advanced technologies in terms of business intelligence and analytic techniques in a multicomponent architecture and a sustainable competency-based human capital strategy. The novel approach targets at an alignment of one of the most important higher education outputs, namely the human capital, with market needs and thus, maximizing the benefits of higher education in achieving sustainable economic development.

关键词： Education Organizations Economics Market research Data mining Decision making

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：