Institution
University of São Paulo
Education•São Paulo, Brazil•
About: University of São Paulo is a education organization based out in São Paulo, Brazil. It is known for research contribution in the topics: Population & Context (language use). The organization has 136513 authors who have published 272320 publications receiving 5127869 citations. The organization is also known as: USP & Universidade de São Paulo.
Topics: Population, Context (language use), Medicine, Health care, Immune system
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12 Aug 2012TL;DR: This work shows that by using a combination of four novel ideas the authors can search and mine truly massive time series for the first time, and shows that in large datasets they can exactly search under DTW much more quickly than the current state-of-the-art Euclidean distance search algorithms.
Abstract: Most time series data mining algorithms use similarity search as a core subroutine, and thus the time taken for similarity search is the bottleneck for virtually all time series data mining algorithms. The difficulty of scaling search to large datasets largely explains why most academic work on time series data mining has plateaued at considering a few millions of time series objects, while much of industry and science sits on billions of time series objects waiting to be explored. In this work we show that by using a combination of four novel ideas we can search and mine truly massive time series for the first time. We demonstrate the following extremely unintuitive fact; in large datasets we can exactly search under DTW much more quickly than the current state-of-the-art Euclidean distance search algorithms. We demonstrate our work on the largest set of time series experiments ever attempted. In particular, the largest dataset we consider is larger than the combined size of all of the time series datasets considered in all data mining papers ever published. We show that our ideas allow us to solve higher-level time series data mining problem such as motif discovery and clustering at scales that would otherwise be untenable. In addition to mining massive datasets, we will show that our ideas also have implications for real-time monitoring of data streams, allowing us to handle much faster arrival rates and/or use cheaper and lower powered devices than are currently possible.
969 citations
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TL;DR: The PLATO 2.0 mission as discussed by the authors has been selected for ESA's M3 launch opportunity (2022/24) to provide accurate key planet parameters (radius, mass, density and age) in statistical numbers.
Abstract: PLATO 2.0 has recently been selected for ESA’s M3 launch opportunity (2022/24). Providing accurate key planet parameters (radius, mass, density and age) in statistical numbers, it addresses fundamental questions such as: How do planetary systems form and evolve? Are there other systems with planets like ours, including potentially habitable planets? The PLATO 2.0 instrument consists of 34 small aperture telescopes (32 with 25 s readout cadence and 2 with 2.5 s candence) providing a wide field-of-view (2232 deg 2) and a large photometric magnitude range (4–16 mag). It focusses on bright (4–11 mag) stars in wide fields to detect and characterize planets down to Earth-size by photometric transits, whose masses can then be determined by ground-based radial-velocity follow-up measurements. Asteroseismology will be performed for these bright stars to obtain highly accurate stellar parameters, including masses and ages. The combination of bright targets and asteroseismology results in high accuracy for the bulk planet parameters: 2 %, 4–10 % and 10 % for planet radii, masses and ages, respectively. The planned baseline observing strategy includes two long pointings (2–3 years) to detect and bulk characterize planets reaching into the habitable zone (HZ) of solar-like stars and an additional step-and-stare phase to cover in total about 50 % of the sky. PLATO 2.0 will observe up to 1,000,000 stars and detect and characterize hundreds of small planets, and thousands of planets in the Neptune to gas giant regime out to the HZ. It will therefore provide the first large-scale catalogue of bulk characterized planets with accurate radii, masses, mean densities and ages. This catalogue will include terrestrial planets at intermediate orbital distances, where surface temperatures are moderate. Coverage of this parameter range with statistical numbers of bulk characterized planets is unique to PLATO 2.0. The PLATO 2.0 catalogue allows us to e.g.: - complete our knowledge of planet diversity for low-mass objects, - correlate the planet mean density-orbital distance distribution with predictions from planet formation theories,- constrain the influence of planet migration and scattering on the architecture of multiple systems, and - specify how planet and system parameters change with host star characteristics, such as type, metallicity and age. The catalogue will allow us to study planets and planetary systems at different evolutionary phases. It will further provide a census for small, low-mass planets. This will serve to identify objects which retained their primordial hydrogen atmosphere and in general the typical characteristics of planets in such low-mass, low-density range. Planets detected by PLATO 2.0 will orbit bright stars and many of them will be targets for future atmosphere spectroscopy exploring their atmosphere. Furthermore, the mission has the potential to detect exomoons, planetary rings, binary and Trojan planets. The planetary science possible with PLATO 2.0 is complemented by its impact on stellar and galactic science via asteroseismology as well as light curves of all kinds of variable stars, together with observations of stellar clusters of different ages. This will allow us to improve stellar models and study stellar activity. A large number of well-known ages from red giant stars will probe the structure and evolution of our Galaxy. Asteroseismic ages of bright stars for different phases of stellar evolution allow calibrating stellar age-rotation relationships. Together with the results of ESA’s Gaia mission, the results of PLATO 2.0 will provide a huge legacy to planetary, stellar and galactic science.
965 citations
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Bela Abolfathi1, D. S. Aguado2, Gabriela Aguilar3, Carlos Allende Prieto2 +361 more•Institutions (94)
TL;DR: SDSS-IV is the fourth generation of the Sloan Digital Sky Survey and has been in operation since 2014 July. as discussed by the authors describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14).
Abstract: The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014-2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V.
965 citations
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Utrecht University1, Naturalis2, Duke University3, Institut de recherche pour le développement4, Institut national de la recherche agronomique5, Museu Paraense Emílio Goeldi6, University of California, Berkeley7, University of Leeds8, Empresa Brasileira de Pesquisa Agropecuária9, National Institute of Amazonian Research10, National University of Saint Anthony the Abbot in Cuzco11, University of Exeter12, World Wide Fund for Nature13, Universidad Autónoma Gabriel René Moreno14, Norwegian University of Life Sciences15, Max Planck Society16, James Cook University17, Universidade do Estado de Mato Grosso18, University of Amsterdam19, Silver Spring Networks20, State University of Campinas21, University of Edinburgh22, University of Los Andes23, Smithsonian Conservation Biology Institute24, National University of Colombia25, University of East Anglia26, Central University of Ecuador27, Centre national de la recherche scientifique28, Humboldt State University29, New York Botanical Garden30, Universidade Federal do Acre31, Paul Sabatier University32, Missouri Botanical Garden33, Amazon.com34, University of Texas at Austin35, University of Florida36, Venezuelan Institute for Scientific Research37, Environmental Change Institute38, Federal Rural University of Amazonia39, University of São Paulo40, State University of Norte Fluminense41, Smithsonian Tropical Research Institute42, University of Wisconsin–Milwaukee43, Northern Arizona University44, Aarhus University45, Tropenbos International46, University of Kent47, Royal Botanic Gardens48, Universidad Nacional de la Amazonía Peruana49, University of Missouri–St. Louis50, Fairchild Tropical Botanic Garden51, Florida International University52, Wake Forest University53
TL;DR: The finding that Amazonia is dominated by just 227 tree species implies that most biogeochemical cycling in the world’s largest tropical forest is performed by a tiny sliver of its diversity.
Abstract: The vast extent of the Amazon Basin has historically restricted the study of its tree communities to the local and regional scales. Here, we provide empirical data on the commonness, rarity, and richness of lowland tree species across the entire Amazon Basin and Guiana Shield (Amazonia), collected in 1170 tree plots in all major forest types. Extrapolations suggest that Amazonia harbors roughly 16,000 tree species, of which just 227 (1.4%) account for half of all trees. Most of these are habitat specialists and only dominant in one or two regions of the basin. We discuss some implications of the finding that a small group of species—less diverse than the North American tree flora—accounts for half of the world’s most diverse tree community.
963 citations
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TL;DR: It is hypothesized that collagen degradation occurred over time, via host-derived matrix metalloproteinases that are released slowly over time through proteolytic enzyme inhibitors or mineral oil.
Abstract: Incompletely infiltrated collagen fibrils in acid-etched dentin are susceptible to degradation. We hypothesize that degradation can occur in the absence of bacteria. Partially demineralized collagen matrices (DCMs) prepared from human dentin were stored in artificial saliva. Control specimens were stored in artificial saliva containing proteolytic enzyme inhibitors, or pure mineral oil. We retrieved them at 24 hrs, 90 and 250 days to examine the extent of degradation of DCM. In the 24-hour experimental and 90- and 250-day control specimens, we observed 5- to 6-microm-thick layers of DCM containing banded collagen fibrils. DCMs were almost completely destroyed in the 250-day experimental specimens, but not when incubated with enzyme inhibitors or mineral oil. Functional enzyme analysis of dentin powder revealed low levels of collagenolytic activity that was inhibited by protease inhibitors or 0.2% chlorhexidine. We hypothesize that collagen degradation occurred over time, via host-derived matrix metalloproteinases that are released slowly over time.
962 citations
Authors
Showing all 138091 results
Name | H-index | Papers | Citations |
---|---|---|---|
George M. Whitesides | 240 | 1739 | 269833 |
Peter Libby | 211 | 932 | 182724 |
Robert C. Nichol | 187 | 851 | 162994 |
Paul M. Thompson | 183 | 2271 | 146736 |
Terrie E. Moffitt | 182 | 594 | 150609 |
Douglas R. Green | 182 | 661 | 145944 |
Richard B. Lipton | 176 | 2110 | 140776 |
Robin M. Murray | 171 | 1539 | 116362 |
George P. Chrousos | 169 | 1612 | 120752 |
David A. Bennett | 167 | 1142 | 109844 |
Barry M. Popkin | 157 | 751 | 90453 |
David H. Adams | 155 | 1613 | 117783 |
Joao Seixas | 153 | 1538 | 115070 |
Matthias Egger | 152 | 901 | 184176 |
Ichiro Kawachi | 149 | 1216 | 90282 |