210 research outputs found

    Challenges for Sustained Observing and Forecasting Systems in the Mediterranean Sea

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    The Mediterranean community represented in this paper is the result of more than 30 years of EU and nationally funded coordination, which has led to key contributions in science concepts and operational initiatives. Together with the establishment of operational services, the community has coordinated with universities, research centers, research infrastructures and private companies to implement advanced multi-platform and integrated observing and forecasting systems that facilitate the advancement of operational services, scientific achievements and mission-oriented innovation. Thus, the community can respond to societal challenges and stakeholders needs, developing a variety of fit-for-purpose services such as the Copernicus Marine Service. The combination of state-of-the-art observations and forecasting provides new opportunities for downstream services in response to the needs of the heavily populated Mediterranean coastal areas and to climate change. The challenge over the next decade is to sustain ocean observations within the research community, to monitor the variability at small scales, e.g., the mesoscale/submesoscale, to resolve the sub-basin/seasonal and inter-annual variability in the circulation, and thus establish the decadal variability, understand and correct the model-associated biases and to enhance model-data integration and ensemble forecasting for uncertainty estimation. Better knowledge and understanding of the level of Mediterranean variability will enable a subsequent evaluation of the impacts and mitigation of the effect of human activities and climate change on the biodiversity and the ecosystem, which will support environmental assessments and decisions. Further challenges include extending the science-based added-value products into societal relevant downstream services and engaging with communities to build initiatives that will contribute to the 2030 Agenda and more specifically to SDG14 and the UN's Decade of Ocean Science for sustainable development, by this contributing to bridge the science-policy gap. The Mediterranean observing and forecasting capacity was built on the basis of community best practices in monitoring and modeling, and can serve as a basis for the development of an integrated global ocean observing system

    Challenges for Sustained Observing and Forecasting Systems in the Mediterranean Sea

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    The Mediterranean community represented in this paper is the result of more than 30 years of EU and nationally funded coordination, which has led to key contributions in science concepts and operational initiatives. Together with the establishment of operational services, the community has coordinated with universities, research centers, research infrastructures and private companies to implement advanced multi-platform and integrated observing and forecasting systems that facilitate the advancement of operational services, scientific achievements and mission-oriented innovation. Thus, the community can respond to societal challenges and stakeholders needs, developing a variety of fit-for-purpose services such as the Copernicus Marine Service. The combination of state-of-the-art observations and forecasting provides new opportunities for downstream services in response to the needs of the heavily populated Mediterranean coastal areas and to climate change. The challenge over the next decade is to sustain ocean observations within the research community, to monitor the variability at small scales, e.g., the mesoscale/submesoscale, to resolve the sub-basin/seasonal and inter-annual variability in the circulation, and thus establish the decadal variability, understand and correct the model-associated biases and to enhance model-data integration and ensemble forecasting for uncertainty estimation. Better knowledge and understanding of the level of Mediterranean variability will enable a subsequent evaluation of the impacts and mitigation of the effect of human activities and climate change on the biodiversity and the ecosystem, which will support environmental assessments and decisions. Further challenges include extending the science-based added-value products into societal relevant downstream services and engaging with communities to build initiatives that will contribute to the 2030 Agenda and more specifically to SDG14 and the UN's Decade of Ocean Science for sustainable development, by this contributing to bridge the science-policy gap. The Mediterranean observing and forecasting capacity was built on the basis of community best practices in monitoring and modeling, and can serve as a basis for the development of an integrated global ocean observing system

    Clinical phenotypes of acute heart failure based on signs and symptoms of perfusion and congestion at emergency department presentation and their relationship with patient management and outcomes

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    Objective To compare the clinical characteristics and outcomes of patients with acute heart failure (AHF) according to clinical profiles based on congestion and perfusion determined in the emergency department (ED). Methods and results Overall, 11 261 unselected AHF patients from 41 Spanish EDs were classified according to perfusion (normoperfusion = warm; hypoperfusion = cold) and congestion (not = dry; yes = wet). Baseline and decompensation characteristics were recorded as were the main wards to which patients were admitted. The primary outcome was 1-year all-cause mortality; secondary outcomes were need for hospitalisation during the index AHF event, in-hospital all-cause mortality, prolonged hospitalisation, 7-day post-discharge ED revisit for AHF and 30-day post-discharge rehospitalisation for AHF. A total of 8558 patients (76.0%) were warm+ wet, 1929 (17.1%) cold+ wet, 675 (6.0%) warm+ dry, and 99 (0.9%) cold+ dry; hypoperfused (cold) patients were more frequently admitted to intensive care units and geriatrics departments, and warm+ wet patients were discharged home without admission. The four phenotypes differed in most of the baseline and decompensation characteristics. The 1-year mortality was 30.8%, and compared to warm+ dry, the adjusted hazard ratios were significantly increased for cold+ wet (1.660; 95% confidence interval 1.400-1.968) and cold+ dry (1.672; 95% confidence interval 1.189-2.351). Hypoperfused (cold) phenotypes also showed higher rates of index episode hospitalisation and in-hospital mortality, while congestive (wet) phenotypes had a higher risk of prolonged hospitalisation but decreased risk of rehospitalisation. No differences were observed among phenotypes in ED revisit risk. Conclusions Bedside clinical evaluation of congestion and perfusion of AHF patients upon ED arrival and classification according to phenotypic profiles proposed by the latest European Society of Cardiology guidelines provide useful complementary information and help to rapidly predict patient outcomes shortly after ED patient arrival

    Global transpiration data from sap flow measurements: The SAPFLUXNET database

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    Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80% of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50% of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56% of the datasets. Many datasets contain data for species that make up 90% or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (10.5281/zenodo.3971689; Poyatos et al., 2020a). The "sapfluxnetr"R package-designed to access, visualize, and process SAPFLUXNET data-is available from CRAN. © 2021 Rafael Poyatos et al.This research was supported by the Minis-terio de Economía y Competitividad (grant no. CGL2014-55883-JIN), the Ministerio de Ciencia e Innovación (grant no. RTI2018-095297-J-I00), the Ministerio de Ciencia e Innovación (grant no. CAS16/00207), the Agència de Gestió d’Ajuts Universitaris i de Recerca (grant no. SGR1001), the Alexander von Humboldt-Stiftung (Humboldt Research Fellowship for Experienced Researchers (RP)), and the Institució Catalana de Recerca i Estudis Avançats (Academia Award (JMV)). Víctor Flo was supported by the doctoral fellowship FPU15/03939 (MECD, Spain)

    Erratum: “Searches for Gravitational Waves from Known Pulsars at Two Harmonics in 2015–2017 LIGO Data” (2019, ApJ, 879, 10)

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    Due to an error at the publisher, in the published article the number of pulsars presented in the paper is incorrect in multiple places throughout the text. Specifically, "222" pulsars should be "221." Additionally, the number of pulsars for which we have EM observations that fully overlap with O1 and O2 changes from "168" to "167." Elsewhere, in the machine-readable table of Table 1 and in Table 2, the row corresponding to pulsar J0952-0607 should be excised as well. Finally, in the caption for Table 2 the number of pulsars changes from "188" to "187.

    Searches for gravitational waves from known pulsars at two harmonics in 2015-2017 LIGO data

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    International audienceWe present a search for gravitational waves from 222 pulsars with rotation frequencies ≳10 Hz. We use advanced LIGO data from its first and second observing runs spanning 2015–2017, which provides the highest-sensitivity gravitational-wave data so far obtained. In this search we target emission from both the l = m = 2 mass quadrupole mode, with a frequency at twice that of the pulsar’s rotation, and the l = 2, m = 1 mode, with a frequency at the pulsar rotation frequency. The search finds no evidence for gravitational-wave emission from any pulsar at either frequency. For the l = m = 2 mode search, we provide updated upper limits on the gravitational-wave amplitude, mass quadrupole moment, and fiducial ellipticity for 167 pulsars, and the first such limits for a further 55. For 20 young pulsars these results give limits that are below those inferred from the pulsars’ spin-down. For the Crab and Vela pulsars our results constrain gravitational-wave emission to account for less than 0.017% and 0.18% of the spin-down luminosity, respectively. For the recycled millisecond pulsar J0711−6830 our limits are only a factor of 1.3 above the spin-down limit, assuming the canonical value of 1038 kg m2 for the star’s moment of inertia, and imply a gravitational-wave-derived upper limit on the star’s ellipticity of 1.2 × 10−8. We also place new limits on the emission amplitude at the rotation frequency of the pulsars

    Genome Sequence of the Pea Aphid Acyrthosiphon pisum

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    Aphids are important agricultural pests and also biological models for studies of insect-plant interactions, symbiosis, virus vectoring, and the developmental causes of extreme phenotypic plasticity. Here we present the 464 Mb draft genome assembly of the pea aphid Acyrthosiphon pisum. This first published whole genome sequence of a basal hemimetabolous insect provides an outgroup to the multiple published genomes of holometabolous insects. Pea aphids are host-plant specialists, they can reproduce both sexually and asexually, and they have coevolved with an obligate bacterial symbiont. Here we highlight findings from whole genome analysis that may be related to these unusual biological features. These findings include discovery of extensive gene duplication in more than 2000 gene families as well as loss of evolutionarily conserved genes. Gene family expansions relative to other published genomes include genes involved in chromatin modification, miRNA synthesis, and sugar transport. Gene losses include genes central to the IMD immune pathway, selenoprotein utilization, purine salvage, and the entire urea cycle. The pea aphid genome reveals that only a limited number of genes have been acquired from bacteria; thus the reduced gene count of Buchnera does not reflect gene transfer to the host genome. The inventory of metabolic genes in the pea aphid genome suggests that there is extensive metabolite exchange between the aphid and Buchnera, including sharing of amino acid biosynthesis between the aphid and Buchnera. The pea aphid genome provides a foundation for post-genomic studies of fundamental biological questions and applied agricultural problems

    Search of the early O3 LIGO data for continuous gravitational waves from the Cassiopeia A and Vela Jr. supernova remnants

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    partially_open1412sìWe present directed searches for continuous gravitational waves from the neutron stars in the Cassiopeia A (Cas A) and Vela Jr. supernova remnants. We carry out the searches in the LIGO detector data from the first six months of the third Advanced LIGO and Virgo observing run using the weave semicoherent method, which sums matched-filter detection-statistic values over many time segments spanning the observation period. No gravitational wave signal is detected in the search band of 20–976 Hz for assumed source ages greater than 300 years for Cas A and greater than 700 years for Vela Jr. Estimates from simulated continuous wave signals indicate we achieve the most sensitive results to date across the explored parameter space volume, probing to strain magnitudes as low as ∼6.3×10^−26 for Cas A and ∼5.6×10^−26 for Vela Jr. at frequencies near 166 Hz at 95% efficiency.openAbbott, R.; Abbott, T. D.; Acernese, F.; Ackley, K.; Adams, C.; Adhikari, N.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agarwal, D.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Albanesi, S.; Allocca, A.; Altin, P. A.; Amato, A.; Anand, C.; Anand, S.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Andrade, T.; Andres, N.; Andrić, T.; Angelova, S. V.; Ansoldi, S.; Antelis, J. M.; Antier, S.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arène, M.; Arnaud, N.; Aronson, S. M.; Arun, K. G.; Asali, Y.; Ashton, G.; Assiduo, M.; Aston, S. M.; Astone, P.; Aubin, F.; Austin, C.; Babak, S.; Badaracco, F.; Bader, M. K. M.; Badger, C.; Bae, S.; Baer, A. M.; Bagnasco, S.; Bai, Y.; Baird, J.; Ball, M.; Ballardin, G.; Ballmer, S. W.; Balsamo, A.; Baltus, G.; Banagiri, S.; Bankar, D.; Barayoga, J. C.; Barbieri, C.; Barish, B. C.; Barker, D.; Barneo, P.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Barton, M. A.; Bartos, I.; Bassiri, R.; Basti, A.; Bawaj, M.; Bayley, J. C.; Baylor, A. C.; Bazzan, M.; Bécsy, B.; Bedakihale, V. M.; Bejger, M.; Belahcene, I.; Benedetto, V.; Beniwal, D.; Bennett, T. F.; Bentley, J. D.; BenYaala, M.; Bergamin, F.; Berger, B. K.; Bernuzzi, S.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Beveridge, D.; Bhandare, R.; Bhardwaj, U.; Bhattacharjee, D.; Bhaumik, S.; Bilenko, I. A.; Billingsley, G.; Bini, S.; Birney, R.; Birnholtz, O.; Biscans, S.; Bischi, M.; Biscoveanu, S.; Bisht, A.; Biswas, B.; Bitossi, M.; Bizouard, M.-A.; Blackburn, J. K.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bobba, F.; Bode, N.; Boer, M.; Bogaert, G.; Boldrini, M.; Bonavena, L. D.; Bondu, F.; Bonilla, E.; Bonnand, R.; Booker, P.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, N.; Bose, S.; Bossilkov, V.; Boudart, V.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Bramley, A.; Branch, A.; Branchesi, M.; Brau, J. E.; Breschi, M.; Briant, T.; Briggs, J. H.; Brillet, A.; Brinkmann, M.; Brockill, P.; Brooks, A. F.; Brooks, J.; Brown, D. D.; Brunett, S.; Bruno, G.; Bruntz, R.; Bryant, J.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buscicchio, R.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Bustillo, J. Calderón; Callaghan, J. D.; Callister, T. A.; Calloni, E.; Cameron, J.; Camp, J. B.; Canepa, M.; Canevarolo, S.; Cannavacciuolo, M.; Cannon, K. C.; Cao, H.; Capote, E.; Carapella, G.; Carbognani, F.; Carlin, J. B.; Carney, M. F.; Carpinelli, M.; Carrillo, G.; Carullo, G.; Carver, T. L.; Diaz, J. Casanueva; Casentini, C.; Castaldi, G.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Ceasar, M.; Cella, G.; Cerdá-Durán, P.; Cesarini, E.; Chaibi, W.; Chakravarti, K.; Subrahmanya, S. Chalathadka; Champion, E.; Chan, C.-H.; Chan, C.; Chan, C. L.; Chan, K.; Chandra, K.; Chanial, P.; Chao, S.; Charlton, P.; Chase, E. A.; Chassande-Mottin, E.; Chatterjee, C.; Chatterjee, Debarati; Chatterjee, Deep; Chaturvedi, M.; Chaty, S.; Chen, H. Y.; Chen, J.; Chen, X.; Chen, Y.; Chen, Z.; Cheng, H.; Cheong, C. K.; Cheung, H. Y.; Chia, H. Y.; Chiadini, F.; Chiarini, G.; Chierici, R.; Chincarini, A.; Chiofalo, M. L.; Chiummo, A.; Cho, G.; Cho, H. S.; Choudhary, R. K.; Choudhary, S.; Christensen, N.; Chu, Q.; Chua, S.; Chung, K. W.; Ciani, G.; Ciecielag, P.; Cieślar, M.; Cifaldi, M.; Ciobanu, A. A.; Ciolfi, R.; Cipriano, F.; Cirone, A.; Clara, F.; Clark, E. N.; Clark, J. A.; Clarke, L.; Clearwater, P.; Clesse, S.; Cleva, F.; Coccia, E.; Codazzo, E.; Cohadon, P.-F.; Cohen, D. E.; Cohen, L.; Colleoni, M.; Collette, C. G.; Colombo, A.; Colpi, M.; Compton, C. M.; Constancio, M.; Conti, L.; Cooper, S. J.; Corban, P.; Corbitt, T. R.; Cordero-Carrión, I.; Corezzi, S.; Corley, K. R.; Cornish, N.; Corre, D.; Corsi, A.; Cortese, S.; Costa, C. A.; Cotesta, R.; Coughlin, M. W.; Coulon, J.-P.; Countryman, S. T.; Cousins, B.; Couvares, P.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Criswell, A. W.; Croquette, M.; Crowder, S. G.; Cudell, J. R.; Cullen, T. J.; Cumming, A.; Cummings, R.; Cunningham, L.; Cuoco, E.; Curyło, M.; Dabadie, P.; Canton, T. Dal; Dall’Osso, S.; Dálya, G.; Dana, A.; DaneshgaranBajastani, L. M.; D’Angelo, B.; Danilishin, S.; D’Antonio, S.; Danzmann, K.; Darsow-Fromm, C.; Dasgupta, A.; Datrier, L. E. H.; Datta, S.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Davis, D.; Davis, M. C.; Daw, E. J.; Dean, R.; DeBra, D.; Deenadayalan, M.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Favero, V.; De Lillo, F.; De Lillo, N.; Del Pozzo, W.; DeMarchi, L. M.; De Matteis, F.; D’Emilio, V.; Demos, N.; Dent, T.; Depasse, A.; De Pietri, R.; De Rosa, R.; De Rossi, C.; DeSalvo, R.; De Simone, R.; Dhurandhar, S.; Díaz, M. C.; Diaz-Ortiz, M.; Didio, N. A.; Dietrich, T.; Di Fiore, L.; Di Fronzo, C.; Di Giorgio, C.; Di Giovanni, F.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Ding, B.; Di Pace, S.; Di Palma, I.; Di Renzo, F.; Divakarla, A. K.; Dmitriev, A.; Doctor, Z.; D’Onofrio, L.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Drago, M.; Driggers, J. C.; Drori, Y.; Ducoin, J.-G.; Dupej, P.; Durante, O.; D’Urso, D.; Duverne, P.-A.; Dwyer, S. E.; Eassa, C.; Easter, P. J.; Ebersold, M.; Eckhardt, T.; Eddolls, G.; Edelman, B.; Edo, T. B.; Edy, O.; Effler, A.; Eichholz, J.; Eikenberry, S. S.; Eisenmann, M.; Eisenstein, R. A.; Ejlli, A.; Engelby, E.; Errico, L.; Essick, R. C.; Estellés, H.; Estevez, D.; Etienne, Z.; Etzel, T.; Evans, M.; Evans, T. M.; Ewing, B. E.; Fafone, V.; Fair, H.; Fairhurst, S.; Farah, A. M.; Farinon, S.; Farr, B.; Farr, W. M.; Farrow, N. W.; Fauchon-Jones, E. J.; Favaro, G.; Favata, M.; Fays, M.; Fazio, M.; Feicht, J.; Fejer, M. M.; Fenyvesi, E.; Ferguson, D. L.; Fernandez-Galiana, A.; Ferrante, I.; Ferreira, T. A.; Fidecaro, F.; Figura, P.; Fiori, I.; Fishbach, M.; Fisher, R. P.; Fittipaldi, R.; Fiumara, V.; Flaminio, R.; Floden, E.; Fong, H.; Font, J. A.; Fornal, B.; Forsyth, P. W. F.; Franke, A.; Frasca, S.; Frasconi, F.; Frederick, C.; Freed, J. P.; Frei, Z.; Freise, A.; Frey, R.; Fritschel, P.; Frolov, V. V.; Fronzé, G. G.; Fulda, P.; Fyffe, M.; Gabbard, H. A.; Gadre, B. U.; Gair, J. R.; Gais, J.; Galaudage, S.; Gamba, R.; Ganapathy, D.; Ganguly, A.; Gaonkar, S. G.; Garaventa, B.; García-Núñez, C.; García-Quirós, C.; Garufi, F.; Gateley, B.; Gaudio, S.; Gayathri, V.; Gemme, G.; Gennai, A.; George, J.; Gerberding, O.; Gergely, L.; Gewecke, P.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, Shaon; Ghosh, Shrobana; Giacomazzo, B.; Giacoppo, L.; Giaime, J. A.; Giardina, K. D.; Gibson, D. R.; Gier, C.; Giesler, M.; Giri, P.; Gissi, F.; Glanzer, J.; Gleckl, A. E.; Godwin, P.; Goetz, E.; Goetz, R.; Gohlke, N.; Goncharov, B.; González, G.; Gopakumar, A.; Gosselin, M.; Gouaty, R.; Gould, D. W.; Grace, B.; Grado, A.; Granata, M.; Granata, V.; Grant, A.; Gras, S.; Grassia, P.; Gray, C.; Gray, R.; Greco, G.; Green, A. C.; Green, R.; Gretarsson, A. M.; Gretarsson, E. M.; Griffith, D.; Griffiths, W.; Griggs, H. L.; Grignani, G.; Grimaldi, A.; Grimm, S. J.; Grote, H.; Grunewald, S.; Gruning, P.; Guerra, D.; Guidi, Gianluca; Guimaraes, A. R.; Guixé, G.; Gulati, H. K.; Guo, H.-K.; Guo, Y.; Gupta, Anchal; Gupta, Anuradha; Gupta, P.; Gustafson, E. K.; Gustafson, R.; Guzman, F.; Haegel, L.; Halim, O.; Hall, E. D.; Hamilton, E. Z.; Hammond, G.; Haney, M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hannuksela, O.; Hansen, H.; Hansen, T. J.; Hanson, J.; Harder, T.; Hardwick, T.; Haris, K.; Harms, J.; Harry, G. M.; Harry, I. W.; Hartwig, D.; Haskell, B.; Hasskew, R. K.; Haster, C.-J.; Haughian, K.; Hayes, F. J.; Healy, J.; Heidmann, A.; Heidt, A.; Heintze, M. C.; Heinze, J.; Heinzel, J.; Heitmann, H.; Hellman, F.; Hello, P.; Helmling-Cornell, A. F.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennes, E.; Hennig, J.; Hennig, M. H.; Hernandez, A. G.; Vivanco, F. Hernandez; Heurs, M.; Hild, S.; Hill, P.; Hines, A. S.; Hochheim, S.; Hofman, D.; Hohmann, J. N.; Holcomb, D. G.; Holland, N. A.; Hollows, I. J.; Holmes, Z. J.; Holt, K.; Holz, D. E.; Hopkins, P.; Hough, J.; Hourihane, S.; Howell, E. J.; Hoy, C. G.; Hoyland, D.; Hreibi, A.; Hsu, Y.; Huang, Y.; Hübner, M. T.; Huddart, A. D.; Hughey, B.; Hui, V.; Husa, S.; Huttner, S. H.; Huxford, R.; Huynh-Dinh, T.; Idzkowski, B.; Iess, A.; Ingram, C.; Isi, M.; Isleif, K.; Iyer, B. R.; JaberianHamedan, V.; Jacqmin, T.; Jadhav, S. J.; Jadhav, S. P.; James, A. L.; Jan, A. Z.; Jani, K.; Janquart, J.; Janssens, K.; Janthalur, N. N.; Jaranowski, P.; Jariwala, D.; Jaume, R.; Jenkins, A. C.; Jenner, K.; Jeunon, M.; Jia, W.; Johns, G. R.; Jones, A. W.; Jones, D. I.; Jones, J. D.; Jones, P.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Juste, V.; Kalaghatgi, C. V.; Kalogera, V.; Kamai, B.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kao, Y.; Kapadia, S. J.; Kapasi, D. P.; Karat, S.; Karathanasis, C.; Karki, S.; Kashyap, R.; Kasprzack, M.; Kastaun, W.; Katsanevas, S.; Katsavounidis, E.; Katzman, W.; Kaur, T.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Key, J. S.; Khadka, S.; Khalili, F. Y.; Khan, S.; Khazanov, E. A.; Khetan, N.; Khursheed, M.; Kijbunchoo, N.; Kim, C.; Kim, J. C.; Kim, K.; Kim, W. S.; Kim, Y.-M.; Kimball, C.; Kinley-Hanlon, M.; Kirchhoff, R.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Knee, A. M.; Knowles, T. D.; Knyazev, E.; Koch, P.; Koekoek, G.; Koley, S.; Kolitsidou, P.; Kolstein, M.; Komori, K.; Kondrashov, V.; Kontos, A.; Koper, N.; Korobko, M.; Kovalam, M.; Kozak, D. B.; Kringel, V.; Krishnendu, N. V.; Królak, A.; Kuehn, G.; Kuei, F.; Kuijer, P.; Kumar, A.; Kumar, P.; Kumar, Rahul; Kumar, Rakesh; Kuns, K.; Kuwahara, S.; Lagabbe, P.; Laghi, D.; Lalande, E.; Lam, T. L.; Lamberts, A.; Landry, M.; Lane, B. B.; Lang, R. N.; Lange, J.; Lantz, B.; La Rosa, I.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lecoeuche, Y. K.; Lee, H. M.; Lee, H. W.; Lee, J.; Lee, K.; Lehmann, J.; Lemaître, A.; Leroy, N.; Letendre, N.; Levesque, C.; Levin, Y.; Leviton, J. N.; Leyde, K.; Li, A. K. Y.; Li, B.; Li, J.; Li, T. G. F.; Li, X.; Linde, F.; Linker, S. D.; Linley, J. N.; Littenberg, T. B.; Liu, J.; Liu, K.; Liu, X.; Llamas, F.; Llorens-Monteagudo, M.; Lo, R. K. L.; Lockwood, A.; London, L. T.; Longo, A.; Lopez, D.; Portilla, M. Lopez; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lott, T. P.; Lough, J. D.; Lousto, C. O.; Lovelace, G.; Lucaccioni, J. F.; Lück, H.; Lumaca, D.; Lundgren, A. P.; Lynam, J. E.; Macas, R.; MacInnis, M.; Macleod, D. M.; MacMillan, I. A. O.; Macquet, A.; Hernandez, I. 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    GW190425 : observation of a compact binary coalescence with total mass ~ 3.4 M o

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    On 2019 April 25, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9. The Virgo detector was also taking data that did not contribute to detection due to a low signal-to-noise ratio, but were used for subsequent parameter estimation. The 90% credible intervals for the component masses range from to if we restrict the dimensionless component spin magnitudes to be smaller than 0.05). These mass parameters are consistent with the individual binary components being neutron stars. However, both the source-frame chirp mass and the total mass of this system are significantly larger than those of any other known binary neutron star (BNS) system. The possibility that one or both binary components of the system are black holes cannot be ruled out from gravitational-wave data. We discuss possible origins of the system based on its inconsistency with the known Galactic BNS population. Under the assumption that the signal was produced by a BNS coalescence, the local rate of neutron star mergers is updated to 250-2810
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