Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.;
2016-01-01
This article provides supplemental information for a Letter reporting the rate of (BBH) coalescences inferred from 16 days of coincident Advanced LIGO observations surrounding the transient (GW) signal GW150914. In that work wereported various rate estimates whose 90% confidence intervals fell in the range 2600 Gpc(exp -3) yr(exp -1). Here we givedetails on our method and computations, including information about our search pipelines, a derivation of ourlikelihood function for the analysis, a description of the astrophysical search trigger distribution expected frommerging BBHs, details on our computational methods, a description of the effects and our model for calibrationuncertainty, and an analytic method for estimating our detector sensitivity, which is calibrated to our measurements.
Studying Microquasars with X-Ray Polarimetry
Directory of Open Access Journals (Sweden)
Giorgio Matt
2018-03-01
Full Text Available Microquasars are Galactic black hole systems in which matter is transferred from a donor star and accretes onto a black hole of, typically, 10–20 solar masses. The presence of an accretion disk and a relativistic jet made them a scaled down analogue of quasars—thence their name. Microquasars feature prominently in the scientific goals of X-ray polarimeters, because a number of open questions, which are discussed in this paper, can potentially be answered: the geometry of the hot corona believed to be responsible for the hard X-ray emission; the role of the jet; the spin of the black hole.
JET TRAILS AND MACH CONES: THE INTERACTION OF MICROQUASARS WITH THE INTERSTELLAR MEDIUM
International Nuclear Information System (INIS)
Yoon, D.; Morsony, B.; Heinz, S.; Wiersema, K.; Fender, R. P.; Russell, D. M.; Sunyaev, R.
2011-01-01
A subset of microquasars exhibits high peculiar velocity with respect to the local standard of rest due to the kicks they receive when being born in supernovae. The interaction between the radio plasma released by microquasar jets from such high-velocity binaries with the interstellar medium must lead to the production of trails and bow shocks similar to what is observed in narrow-angle tailed radio galaxies and pulsar wind nebulae. We present a set of numerical simulations of this interaction that illuminate the long-term dynamical evolution and the observational properties of these microquasar bow-shock nebulae and trails. We find that this interaction always produces a structure that consists of a bow shock, a trailing neck, and an expanding bubble. Using our simulations to model emission, we predict that the shock surrounding the bubble and the neck should be visible in H α emission, the interior of the bubble should be visible in synchrotron radio emission, and only the bow shock is likely to be detectable in X-ray emission. We construct an analytic model for the evolution of the neck and bubble shape and compare this model with observations of the X-ray binary SAX J1712.6-3739.
Environment of micro-quasars and other high energy sources in our galaxy
International Nuclear Information System (INIS)
Fuchs, Yael
2001-01-01
This thesis presents the study of the environment of two micro-quasars and one soft gamma-ray repeater (SGR), mainly based on infrared (IR) images taken with ISOCAM, the camera on board of the ISO satellite, between 4 to 18 micron. The results are compared to other wavelengths ones, from radio to X-ray. GRS1915+105's study reveals mid-IR thermal emission from dust surrounding the micro-quasar, and probably heated by its activity. The multi-wavelength observation of two possible counterpart of this X-ray binary relativistic jet interactions with the surrounding medium, situated at more than 10 parsec from the source, are inconclusive. SS433 has also been observed with PHOT, another instrument on board of ISO, spectroscopically at 2-12 micron and in far IR photometry. Spectra and mass-loss estimate imply the visible companion of this micro-quasar, the nature of which has never been precisely determined, to be likely a Wolf-Rayet star. The mass ejected by this star escapes from the X-ray binary to form probably dust surrounding the system and emitting in far IR. W50, the radio nebula surrounding SS433 and elongated under its relativistic jet action has been partly mapped at 15 micron. No particular emission was found in the eastern lobe. In the western lobe, IR hot-spots, partly corresponding to radio emission and coincident with molecular clouds, lie in the apparent X-ray relativistic jet course, and they possibly trace its interactions with the denser medium of this lobe. Near and mid-IR images of SGR1806-20 do not show any evidence of its high energy activity, but they reveal a young star cluster still enshrouded in their birth cloud, which could also be the original place of the SGR, and then possibly be a key for the understanding of its particular properties. (author) [fr
Astronomers Trace Microquasar's Path Back in Time
2003-01-01
Astronomers have traced the orbit through our Milky Way Galaxy of a voracious neutron star and a companion star it is cannibalizing, and conclude that the pair joined more than 30 million years ago and probably were catapulted out of a cluster of stars far from the Galaxy's center. Path of Microquasar and Sun Path of Microquasar (red) and Sun (yellow) through the Milky Way Galaxy for the past 230 million years. Animations: GIF Version MPEG Version CREDIT: Mirabel & Rodrigues, NRAO/AUI/NSF The pair of stars, called Scorpius X-1, form a "microquasar," in which material sucked from the "normal" star forms a rapidly-rotating disk around the superdense neutron star. The disk becomes so hot it emits X-rays, and also spits out "jets" of subatomic particles at nearly the speed of light. Using precise positional data from the National Science Foundation's Very Long Baseline Array (VLBA) and from optical telescopes, Felix Mirabel, an astrophysicist at the Institute for Astronomy and Space Physics of Argentina and French Atomic Energy Commission, and Irapuan Rodrigues, also of the French Atomic Energy Commission, calculated that Scorpius X-1 is not orbiting the Milky Way's center in step with most other stars, but instead follows an eccentric path far above and below the Galaxy's plane. Scorpius X-1, discovered with a rocket-borne X-ray telescope in 1962, is about 9,000 light-years from Earth. It is the brightest continuous source of X-rays beyond the Solar System. The 1962 discovery and associated work earned a share of the 2002 Nobel Prize in physics for Riccardo Giacconi. Mirabel and Rodrigues used a number of published observations to calculate the path of Scorpius X-1 over the past few million years. "This is the most accurate determination we have made of the path of an X-ray binary," said Mirabel. By tracing the object's path backward in time, the scientists were able to conclude that the neutron star and its companion have been traveling together for more than 30
Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Phythian-Adams, A.T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.T.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, R.D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Behnke, B.; Bejger, M.; Bell, A. S.; Bell, C. J.; Berger, B. K.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, M.J.; Birney, R.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, A.L.S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, J.G.; Bogan, C.; Bohe, A.; Bojtos, P.; Bond, T.C; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Brooks, A. F.; Brown, A.D.; Brown, D.; Brown, N. M.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderon Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Diaz, J. Casanueva; Casentini, C.; Caudill, S.; Cavaglia, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Baiardi, L. Cerboni; Cerretani, G.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chan, M.; Chao, D. S.; Charlton, P.; Chassande-Mottin, E.; Chen, H. Y.; Chen, Y; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Qian; Chua, S. E.; Chung, E.S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P. -F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M., Jr.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, A.C.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J. -P.; Countryman, S. T.; Couvares, P.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, A.L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dattilo, V.; Dave, I.; Daveloza, H. P.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; De, S.; Debra, D.; Debreczeni, G.; Degallaix, J.; De laurentis, M.; Deleglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.A.; Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Dhurandhar, S.; Diaz, M. C.; Di Fiore, L.; Giovanni, M.G.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H. -B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etzel, T.; Evans, T. M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.M.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M; Fong, H.; Fournier, J. -D.; Franco, S; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gatto, A.; Gaur, G.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.P.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; Gonzalez, R.G.; Castro, J. M. Gonzalez; Gopakumar, A.; Gordon, A; Gorodetsky, M. L.; Gossan, S. E.; Lee-Gosselin, M.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.M.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. 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H.; Ohme, F.; Oliver, M. B.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.S; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Porter, E. K.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Puerrer, M.; Qi, H.; Qin, J.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. 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S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Setyawati, Y.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shao, Z.M.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, António Dias da; Simakov, D.; Singer, A; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, R. J. E.; Smith, N.D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stevenson-Moore, P.; Stone, J.R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sutton, P. J.; Swinkels, B. L.; Szczepanczyk, M. J.; Tacca, M.D.; Talukder, D.; Tanner, D. B.; Tapai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, W.R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Toyra, D.; Travasso, F.; Traylor, G.; Trifiro, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; Vallisneri, M.; van Bakel, N.; van Beuzekom, M.G.; van den Brand, J. F. J.; Van Den Broeck, C.F.F.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasuth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P.J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Vicere, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J. -Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, MT; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L. -W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.M.; Wesels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Williams, D.R.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Wright, J.L.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, H.; Yvert, M.; Zadrozny, A.; Zangrando, L.; Zanolin, M.; Zendri, J. -P.; Zevin, M.; Zhang, F.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zucker, M. E.; Zuraw, S. E.
2016-01-01
This article provides supplemental information for a Letter reporting the rate of (BBH) coalescences inferred from 16 days of coincident Advanced LIGO observations surrounding the transient (GW) signal GW150914. In that work we reported various rate estimates whose 90% confidence intervals fell in
Decoherence effect in neutrinos produced in microquasar jets
Mosquera, M. E.; Civitarese, O.
2018-04-01
We study the effect of decoherence upon the neutrino spectra produced in microquasar jets. In order to analyse the precession of the polarization vector of neutrinos we have calculated its time evolution by solving the corresponding equations of motion, and by assuming two different scenarios, namely: (i) the mixing between two active neutrinos, and (ii) the mixing between one active and one sterile neutrino. The results of the calculations corresponding to these scenarios show that the onset of decoherence does not depends on the activation of neutrino-neutrino interactions when realistic values of the coupling are used in the calculations. We discuss also the case of neutrinos produced in windy microquasars and compare the results which those obtained with more conventional models of microquasars.
The micro-quasars, witness of the extremes physics
International Nuclear Information System (INIS)
2002-01-01
Hopeful the micro-quasars, the astronomers reveal indirectly the black holes presence, invisible in the galaxies. They are extraordinary laboratories to understand the high energies physics and test the general relativity. For the first time, an international scientific team observes their energy emissions evolution. (A.L.B.)
DEFF Research Database (Denmark)
Møller, Jesper
2010-01-01
Chapter 9: This contribution concerns statistical inference for parametric models used in stochastic geometry and based on quick and simple simulation free procedures as well as more comprehensive methods based on a maximum likelihood or Bayesian approach combined with markov chain Monte Carlo...... (MCMC) techniques. Due to space limitations the focus is on spatial point processes....
DEFF Research Database (Denmark)
Møller, Jesper
(This text written by Jesper Møller, Aalborg University, is submitted for the collection ‘Stochastic Geometry: Highlights, Interactions and New Perspectives', edited by Wilfrid S. Kendall and Ilya Molchanov, to be published by ClarendonPress, Oxford, and planned to appear as Section 4.1 with the ......(This text written by Jesper Møller, Aalborg University, is submitted for the collection ‘Stochastic Geometry: Highlights, Interactions and New Perspectives', edited by Wilfrid S. Kendall and Ilya Molchanov, to be published by ClarendonPress, Oxford, and planned to appear as Section 4.......1 with the title ‘Inference'.) This contribution concerns statistical inference for parametric models used in stochastic geometry and based on quick and simple simulation free procedures as well as more comprehensive methods using Markov chain Monte Carlo (MCMC) simulations. Due to space limitations the focus...
Gigantic Cosmic Corkscrew Reveals New Details About Mysterious Microquasar
2004-10-01
Making an extra effort to image a faint, gigantic corkscrew traced by fast protons and electrons shot out from a mysterious microquasar paid off for a pair of astrophysicists who gained new insights into the beast's inner workings and also resolved a longstanding dispute over the object's distance. Microquasar SS 433 VLA Image of Microquasar SS 433 CREDIT: Blundell & Bowler, NRAO/AUI/NSF (Click on Image for Larger Version) The astrophysicists used the National Science Foundation's Very Large Array (VLA) radio telescope to capture the faintest details yet seen in the plasma jets emerging from the microquasar SS 433, an object once dubbed the "enigma of the century." As a result, they have changed scientists' understanding of the jets and settled the controversy over its distance "beyond all reasonable doubt," they said. SS 433 is a neutron star or black hole orbited by a "normal" companion star. The powerful gravity of the neutron star or black hole draws material from the stellar wind of its companion into an accretion disk of material tightly circling the dense central object prior to being pulled onto it. This disk propels jets of fast protons and electrons outward from its poles at about a quarter of the speed of light. The disk in SS 433 wobbles like a child's top, causing its jets to trace a corkscrew in the sky every 162 days. The new VLA study indicates that the speed of the ejected particles varies over time, contrary to the traditional model for SS 433. "We found that the actual speed varies between 24 percent to 28 percent of light speed, as opposed to staying constant," said Katherine Blundell, of the University of Oxford in the United Kingdom. "Amazingly, the jets going in both directions change their speeds simultaneously, producing identical speeds in both directions at any given time," Blundell added. Blundell worked with Michael Bowler, also of Oxford. The scientists' findings have been accepted by the Astrophysical Journal Letters. SS 433 New VLA
Energy Technology Data Exchange (ETDEWEB)
Abbott, B. P.; Abbott, R.; Abernathy, M. R.; Adhikari, R. X. [LIGO, California Institute of Technology, Pasadena, CA 91125 (United States); Abbott, T. D. [Louisiana State University, Baton Rouge, LA 70803 (United States); Acernese, F.; Addesso, P. [Università di Salerno, Fisciano, I-84084 Salerno (Italy); Ackley, K. [University of Florida, Gainesville, FL 32611 (United States); Adams, C. [LIGO Livingston Observatory, Livingston, LA 70754 (United States); Adams, T. [Laboratoire d’Annecy-le-Vieux de Physique des Particules (LAPP), Université Savoie Mont Blanc, CNRS/IN2P3, F-74941 Annecy-le-Vieux (France); Adya, V. B.; Affeldt, C.; Allen, B. [Albert-Einstein-Institut, Max-Planck-Institut für Gravitationsphysik, D-30167 Hannover (Germany); Agathos, M.; Agatsuma, K. [Nikhef, Science Park, 1098 XG Amsterdam (Netherlands); Aggarwal, N. [LIGO, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States); Aguiar, O. D. [Instituto Nacional de Pesquisas Espaciais, 12227-010 São José dos Campos, São Paulo (Brazil); Aiello, L. [INFN, Gran Sasso Science Institute, I-67100 L’Aquila (Italy); Ain, A. [Inter-University Centre for Astronomy and Astrophysics, Pune 411007 (India); Ajith, P. [International Centre for Theoretical Sciences, Tata Institute of Fundamental Research, Bangalore 560012 (India); Collaboration: LIGO Scientific Collaboration and Virgo Collaboration; and others
2016-12-01
This article provides supplemental information for a Letter reporting the rate of (BBH) coalescences inferred from 16 days of coincident Advanced LIGO observations surrounding the transient (GW) signal GW150914. In that work we reported various rate estimates whose 90% confidence intervals fell in the range 2–600 Gpc{sup −3} yr{sup −1}. Here we give details on our method and computations, including information about our search pipelines, a derivation of our likelihood function for the analysis, a description of the astrophysical search trigger distribution expected from merging BBHs, details on our computational methods, a description of the effects and our model for calibration uncertainty, and an analytic method for estimating our detector sensitivity, which is calibrated to our measurements.
A time dependent search for neutrino emission from micro-quasars with the ANTARES telescope
International Nuclear Information System (INIS)
Galata, S.
2012-01-01
The ANTARES collaboration has successfully built, deployed and is currently operating an underwater Cherenkov detector dedicated to high energy neutrino astronomy. The primary aim of the experiment is to detect cosmic sources of neutrinos in order to reveal the production sites of cosmic rays. Among the sources likely to be significant sources of neutrinos are those accelerating relativistic jets, like gamma ray bursts, active galactic nuclei and micro-quasars. Micro-quasars are binary systems formed by a compact object accreting mass from a companion star. The mass transfer causes the emission of X-rays, whereas the onset of magnetic forces in the accreting plasma can cause the acceleration of relativistic jets, which are observed by radio telescopes via their non-thermal synchrotron emission. In some systems, a correlation between X-ray and radio light curves indicates an interplay between accretion and ejection respectively. Some micro-quasars are also high energy and very high energy gamma ray emitters. In this thesis, a time dependent search for neutrino emission from micro-quasars was performed with a multi-messenger approach (photon/neutrino). The data from the X-ray monitors RXTE/ASM and SWIFT/BAT, and the gamma-ray telescope FERMI/LAT were used to select transient events in which the source was supposed to accelerate relativistic jets. The restriction of the analysis to the ejection periods allows a drastic reduction of atmospheric muon and neutrino background, and thus to increase the chances of a discovery. The search was performed with the ANTARES data taken between 2007 and 2010. Statistical analysis was carried out using an un-binned likelihood method based on a likelihood ratio test. The cuts for the event selection were optimized in order to maximize the chance of a discovery. As no neutrino signal was observed in correlation with these micro-quasars, upper limits on the neutrino fluxes of the micro-quasars under study were calculated and compared
Modulated High-Energy Gamma-Ray Emission from the Micro-quasar Cygnus X-3
International Nuclear Information System (INIS)
Abdo, A.A.; Cheung, C.C.; Dermer, C.D.; Grove, J.E.; Johnson, W.N.; Lovellette, M.N.; Makeev, A.; Ray, P.S.; Strickman, M.S.; Wood, K.S.; Abdo, A.A.; Cheung, C.C.; Ackermann, M.; Ajello, M.; Bechtol, K.; Berenji, B.; Blandford, R.D.; Bloom, E.D.; Borgland, A.W.; Cameron, R.A.; Chiang, J.; Claus, R.; Digel, S.W.; Silva, E.D.E.; Drell, P.S.; Dubois, R.; Focke, W.B.; Glanzman, T.; Godfrey, G.; Hayashida, M.; Johannesson, G.; Johnson, A.S.; Kamae, T.; Kocian, M.L.; Lande, J.; Madejski, G.M.; Michelson, P.F.; Mitthumsiri, W.; Monzani, M.E.; Moskalenko, I.V.; Murgia, S.; Nolan, P.L.; Paneque, D.; Reimer, A.; Reimer, O.; Rochester, L.S.; Romani, R.W.; Tanaka, T.; Thayer, J.B.; Tramacere, A.; Uchiyama, Y.; Usher, T.L.; Waite, A.P.; Wang, P.; Ackermann, M.; Ajello, M.; Bechtol, K.; Berenji, B.; Blandford, R.D.; Bloom, E.D.; Borgland, A.W.; Cameron, R.A.; Chiang, J.; Claus, R.; Digel, S.W.; Silva, E.D.E.; Drell, P.S.; Dubois, R.; Focke, W.B.; Glanzman, T.; Godfrey, G.; Hayashida, M.; Johannesson, G.; Johnson, A.S.; Kamae, T.; Kocian, M.L.; Lande, J.; Madejski, G.M.; Michelson, P.F.; Mitthumsiri, W.; Monzani, M.E.; Moskalenko, I.V.; Murgia, S.; Nolan, P.L.; Paneque, D.; Reimer, A.; Reimer, O.; Rochester, L.S.; Romani, R.W.; Tanaka, T.; Thayer, J.B.; Tramacere, A.; Uchiyama, Y.; Usher, T.L.; Waite, A.P.; Wang, P.; Axelsson, M.; Hjalmarsdotter, L.; Axelsson, M.; Conrad, J.; Hjalmarsdotter, L.; Jackson, M.S.; Meurer, C.; Ryde, F.; Ylinen, T.; Baldini, L.; Bellazzini, R.; Brez, A.; Kuss, M.; Latronico, L.; Omodei, N.; Pesce-Rollins, M.; Razzano, M.; Sgro, C.; Ballet, J.; Casandjian, J.M.; Chaty, S.; Corbel, S.; Grenier, I.A.; Koerding, E.; Rodriguez, J.; Starck, J.L.; Tibaldo, L.
2009-01-01
Micro-quasars are accreting black holes or neutron stars in binary systems with associated relativistic jets. Despite their frequent outburst activity, they have never been unambiguously detected emitting high-energy gamma rays. The Fermi Large Area Telescope (LAT) has detected a variable high-energy source coinciding with the position of the x-ray binary and micro-quasar Cygnus X-3. Its identification with Cygnus X-3 is secured by the detection of its orbital period in gamma rays, as well as the correlation of the LAT flux with radio emission from the relativistic jets of Cygnus X-3. The gamma-ray emission probably originates from within the binary system, opening new areas in which to study the formation of relativistic jets. (authors)
Ransom, Katherine M.; Bell, Andrew M.; Barber, Quinn E.; Kourakos, George; Harter, Thomas
2018-05-01
This study is focused on nitrogen loading from a wide variety of crop and land-use types in the Central Valley, California, USA, an intensively farmed region with high agricultural crop diversity. Nitrogen loading rates for several crop types have been measured based on field-scale experiments, and recent research has calculated nitrogen loading rates for crops throughout the Central Valley based on a mass balance approach. However, research is lacking to infer nitrogen loading rates for the broad diversity of crop and land-use types directly from groundwater nitrate measurements. Relating groundwater nitrate measurements to specific crops must account for the uncertainty about and multiplicity in contributing crops (and other land uses) to individual well measurements, and for the variability of nitrogen loading within farms and from farm to farm for the same crop type. In this study, we developed a Bayesian regression model that allowed us to estimate land-use-specific groundwater nitrogen loading rate probability distributions for 15 crop and land-use groups based on a database of recent nitrate measurements from 2149 private wells in the Central Valley. The water and natural, rice, and alfalfa and pasture groups had the lowest median estimated nitrogen loading rates, each with a median estimate below 5 kg N ha-1 yr-1. Confined animal feeding operations (dairies) and citrus and subtropical crops had the greatest median estimated nitrogen loading rates at approximately 269 and 65 kg N ha-1 yr-1, respectively. In general, our probability-based estimates compare favorably with previous direct measurements and with mass-balance-based estimates of nitrogen loading. Nitrogen mass-balance-based estimates are larger than our groundwater nitrate derived estimates for manured and nonmanured forage, nuts, cotton, tree fruit, and rice crops. These discrepancies are thought to be due to groundwater age mixing, dilution from infiltrating river water, or denitrification
Havinga, Paul J.M.; Jansen, P.G.; Lijding, M.E.M.; Scholten, Johan
2004-01-01
Ambient systems are networked embedded systems integrated with everyday environments and supporting people in their activities. These systems will create a Smart Surrounding for people to facilitate and enrich daily life and increase productivity at work. Such systems will be quite different from
Ahnen, M. L.; Ansoldi, S.; Antonelli, L. A.; Arcaro, C.; Babić, A.; Banerjee, B.; Bangale, P.; Barres de Almeida, U.; Barrio, J. A.; Becerra González, J.; Bednarek, W.; Bernardini, E.; Berti, A.; Bhattacharyya, W.; Biasuzzi, B.; Biland, A.; Blanch, O.; Bonnefoy, S.; Bonnoli, G.; Carosi, R.; Carosi, A.; Chatterjee, A.; Colin, P.; Colombo, E.; Contreras, J. L.; Cortina, J.; Covino, S.; Cumani, P.; da Vela, P.; Dazzi, F.; de Angelis, A.; de Lotto, B.; de Oña Wilhelmi, E.; di Pierro, F.; Doert, M.; Domínguez, A.; Dominis Prester, D.; Dorner, D.; Doro, M.; Einecke, S.; Eisenacher Glawion, D.; Elsaesser, D.; Engelkemeier, M.; Fallah Ramazani, V.; Fernández-Barral, A.; Fidalgo, D.; Fonseca, M. V.; Font, L.; Fruck, C.; Galindo, D.; García López, R. J.; Garczarczyk, M.; Gaug, M.; Giammaria, P.; Godinović, N.; Gora, D.; Guberman, D.; Hadasch, D.; Hahn, A.; Hassan, T.; Hayashida, M.; Herrera, J.; Hose, J.; Hrupec, D.; Ishio, K.; Konno, Y.; Kubo, H.; Kushida, J.; Kuveždić, D.; Lelas, D.; Lindfors, E.; Lombardi, S.; Longo, F.; López, M.; Maggio, C.; Majumdar, P.; Makariev, M.; Maneva, G.; Manganaro, M.; Mannheim, K.; Maraschi, L.; Mariotti, M.; Martínez, M.; Mazin, D.; Menzel, U.; Minev, M.; Mirzoyan, R.; Moralejo, A.; Moreno, V.; Moretti, E.; Neustroev, V.; Niedzwiecki, A.; Nievas Rosillo, M.; Nilsson, K.; Ninci, D.; Nishijima, K.; Noda, K.; Nogués, L.; Paiano, S.; Palacio, J.; Paneque, D.; Paoletti, R.; Paredes, J. M.; Paredes-Fortuny, X.; Pedaletti, G.; Peresano, M.; Perri, L.; Persic, M.; Prada Moroni, P. G.; Prandini, E.; Puljak, I.; Garcia, J. R.; Reichardt, I.; Rhode, W.; Ribó, M.; Rico, J.; Righi, C.; Saito, T.; Satalecka, K.; Schroeder, S.; Schweizer, T.; Sitarek, J.; Šnidarić, I.; Sobczynska, D.; Stamerra, A.; Strzys, M.; Surić, T.; Takalo, L.; Tavecchio, F.; Temnikov, P.; Terzić, T.; Tescaro, D.; Teshima, M.; Torres, D. F.; Torres-Albà, N.; Treves, A.; Vanzo, G.; Vazquez Acosta, M.; Vovk, I.; Ward, J. E.; Will, M.; Zarić, D.; MAGIC Collaboration; Bosch-Ramon, V.; Pooley, G. G.; Trushkin, S. A.; Zanin, R.
2017-12-01
The microquasar Cygnus X-1 displays the two typical soft and hard X-ray states of a black hole transient. During the latter, Cygnus X-1 shows a one-sided relativistic radio-jet. Recent detection of the system in the high energy (HE; E ≳ 60 MeV) gamma-ray range with Fermi-LAT associates this emission with the outflow. Former MAGIC observations revealed a hint of flaring activity in the very high-energy (VHE; E ≳ 100 GeV) regime during this X-ray state. We analyse ∼97 h of Cygnus X-1 data taken with the MAGIC telescopes between July 2007 and October 2014. To shed light on the correlation between hard X-ray and VHE gamma rays as previously suggested, we study each main X-ray state separately. We perform an orbital phase-folded analysis to look for variability in the VHE band. Additionally, to place this variability behaviour in a multiwavelength context, we compare our results with Fermi-LAT, AGILE, Swift-BAT, MAXI, RXTE-ASM, AMI and RATAN-600 data. We do not detect Cygnus X-1 in the VHE regime. We establish upper limits for each X-ray state, assuming a power-law distribution with photon index Γ = 3.2. For steady emission in the hard and soft X-ray states, we set integral upper limits at 95 per cent confidence level for energies above 200 GeV at 2.6 × 10-12 photons cm-2 s-1 and 1.0 × 10-11 photons cm-2 s-1, respectively. We rule out steady VHE gamma-ray emission above this energy range, at the level of the MAGIC sensitivity, originating in the interaction between the relativistic jet and the surrounding medium, while the emission above this flux level produced inside the binary still remains a valid possibility.
Kološ, Martin; Tursunov, Arman; Stuchlík, Zdeněk
2017-12-01
The study of quasi-periodic oscillations (QPOs) of X-ray flux observed in the stellar-mass black hole binaries can provide a powerful tool for testing of the phenomena occurring in the strong gravity regime. Magnetized versions of the standard geodesic models of QPOs can explain the observationally fixed data from the three microquasars. We perform a successful fitting of the HF QPOs observed for three microquasars, GRS 1915+105, XTE 1550-564 and GRO 1655-40, containing black holes, for magnetized versions of both epicyclic resonance and relativistic precession models and discuss the corresponding constraints of parameters of the model, which are the mass and spin of the black hole and the parameter related to the external magnetic field. The estimated magnetic field intensity strongly depends on the type of objects giving the observed HF QPOs. It can be as small as 10^{-5} G if electron oscillatory motion is relevant, but it can be by many orders higher for protons or ions (0.02-1 G), or even higher for charged dust or such exotic objects as lighting balls, etc. On the other hand, if we know by any means the magnetic field intensity, our model implies strong limit on the character of the oscillating matter, namely its specific charge.
Energy Technology Data Exchange (ETDEWEB)
Kolos, Martin; Tursunov, Arman; Stuchlik, Zdenek [Silesian University in Opava, Institute of Physics and Research Centre of Theoretical Physics and Astrophysics, Faculty of Philosophy and Science, Opava (Czech Republic)
2017-12-15
The study of quasi-periodic oscillations (QPOs) of X-ray flux observed in the stellar-mass black hole binaries can provide a powerful tool for testing of the phenomena occurring in the strong gravity regime. Magnetized versions of the standard geodesic models of QPOs can explain the observationally fixed data from the three microquasars. We perform a successful fitting of the HF QPOs observed for three microquasars, GRS 1915+105, XTE 1550-564 and GRO 1655-40, containing black holes, for magnetized versions of both epicyclic resonance and relativistic precession models and discuss the corresponding constraints of parameters of the model, which are the mass and spin of the black hole and the parameter related to the external magnetic field. The estimated magnetic field intensity strongly depends on the type of objects giving the observed HF QPOs. It can be as small as 10{sup -5} G if electron oscillatory motion is relevant, but it can be by many orders higher for protons or ions (0.02-1 G), or even higher for charged dust or such exotic objects as lighting balls, etc. On the other hand, if we know by any means the magnetic field intensity, our model implies strong limit on the character of the oscillating matter, namely its specific charge. (orig.)
Compressional heating in magnetized disks neighborhood: from the galactic center to micro-quasars
International Nuclear Information System (INIS)
Belmont, Renaud
2005-01-01
Faint, magnetized and energetic plasmas are very common media in Astrophysics. This thesis is dedicated to two specific cases characterized by a thin disk geometry: the Galactic center and the corona of micro-quasars. In both cases, observations show evidence for a faint and very hot plasma (at 100 million and 1 billion degrees) whose origin is unknown; some clues seem also to indicate a strong, large scale bipolar magnetic field. At the Galactic Center, the gas temperature is such that, if it were collisional and mostly composed by hydrogen, it would escape quickly, so that the power required to sustain the related energy losses would be huge. We however show that the specific conditions of this region can lead to form a helium plasma that is confined by the Galactic potential. In this favorable situation, we study a possible heating mechanism based on the high viscosity of the hot plasma and friction with cold molecular clouds flowing in this region. The corona of micro-quasars is a very similar issue but it is probably weakly collisional. In this regime we study a heating by magnetic pumping, by which the resonance between the periodic motion of some coronal ions and the periodic excitation by an instability in the disc itself can energize the corona. We show that this mechanism is inefficient to explain the hot temperature. (author) [fr
MASTER OPTICAL POLARIZATION VARIABILITY DETECTION IN THE MICROQUASAR V404 CYG/GS 2023+33
Energy Technology Data Exchange (ETDEWEB)
Lipunov, Vladimir M.; Kornilov, V.; Vlasenko, D. [M.V. Lomonosov Moscow State University, Physics Department, Leninskie gory, GSP-1, Moscow, 119991 (Russian Federation); Gorbovskoy, E.; Tiurina, N.; Balanutsa, P.; Kuznetsov, A. [M.V. Lomonosov Moscow State University, Sternberg Astronomical Institute, Universitetsky pr., 13, Moscow, 119234 (Russian Federation); Krushinskiy, V. [Kourovka Astronomical Observatory, Ural Federal University, Lenin ave. 51, Ekaterinburg 620000 (Russian Federation); Budnev, N.; Gress, O.; Ivanov, K.; Yazev, S. [Applied Physics Institute, Irkutsk State University, 20, Gagarin blvd, 664003, Irkutsk (Russian Federation); Tlatov, A. [Kislovodsk Solar Station of the Main (Pulkovo) Observatory RAS, P.O. Box 45, ul. Gagarina 100, Kislovodsk 357700 (Russian Federation); Rebolo Lopez, R.; Serra-Ricart, M.; Israelyan, G.; Lodieu, N. [Instituto de Astrofsica de Canarias, C/Via Lctea, s/n E-38205, La Laguna, Tenerife (Spain); Buckley, D. A. H. [South African Astronomical Observatory, P.O. Box 9, Observatory 7935, Cape Town (South Africa); Sergienko, Yu.; Gabovich, A. [Blagoveschensk State Pedagogical University, Lenin str., 104, Amur Region, Blagoveschensk 675000 (Russian Federation); and others
2016-12-20
On 2015 June 15, the Swift space observatory discovered that the Galactic black hole candidate V404 Cyg was undergoing another active X-ray phase, after 25 years of inactivity. The 12 telescopes of the MASTER Global Robotic Net located at six sites across four continents were the first ground-based observatories to start optical monitoring of the microquasar after its gamma-ray wake up at 18{sup h} 34{sup m} 09{sup s} U.T. on 2015 June 15. In this paper, we report, for the first time, the discovery of variable optical linear polarization, changing by 4%–6% over a timescale of ∼1 hr, on two different epochs. We can conclude that the additional variable polarization arises from the relativistic jet generated by the black hole in V404 Cyg. The polarization variability correlates with optical brightness changes, increasing when the flux decreases.
VLBA "Movie" Gives Scientists New Insights On Workings of Mysterious Microquasars
2004-01-01
Astronomers have made a 42-day movie showing unprecedented detail of the inner workings of a strange star system that has puzzled scientists for more than two decades. Their work is providing new insights that are changing scientists' understanding of the enigmatic stellar pairs known as microquasars. SS 433 Frame from SS 433 Movie: End to end is some 200 billion miles. CREDIT: Mioduszewski et al., NRAO/AUI/NSF Image Files Single Frame Overall Jet View (above image) VLBA Movie (animated gif, 2.3 MB) Animated graphic of SS 433 System (18MB) (Created using software by Robert Hynes, U.Texas) Annotated brightening graphic Unannotated brightening Frame 1 Unannotated brightening Frame 2 "This once-a-day series of exquisitely-detailed images is the best look anyone has ever had at a microquasar, and already has made us change our thinking about how these things work," said Amy Mioduszewski, of the National Radio Astronomy Observatory (NRAO), in Socorro, New Mexico. The astronomers used the National Science Foundation's Very Long Baseline Array (VLBA), a system of radio telescopes stretching from Hawaii to the Caribbean, to follow daily changes in a binary-star system called SS 433, some 15,000 light-years from Earth in the constellation Aquila. Mioduszewski worked with Michael Rupen, Greg Taylor and Craig Walker, all of NRAO. They reported their findings to the American Astronomical Society's meeting in Atlanta, Georgia. SS 433 consists of a neutron star or black hole orbited by a "normal" companion star. The powerful gravity of the neutron star or black hole is drawing material from the stellar wind of its companion into an accretion disk of material tightly circling the dense, central object prior to being pulled onto that object. This disk propels jets of subatomic particles outward from its poles. In SS 433, the particles in the jets move at 26 percent of the speed of light; in other microquasars, the jet material moves at 90-95 percent of light speed. The disk in SS
Constraints on Mass, Spin and Magnetic Field of Microquasar H 1743-322 from Observations of QPOs
Tursunov, A. A.; Kološ, M.
2018-03-01
The study of quasi-periodic oscillations (QPOs) of X-ray flux observed in many microquasars can provide a powerful tool for testing of the phenomena occurring in strong gravity regime. QPOs phenomena can be well related to the oscillations of charged particles in accretion disks orbiting Kerr black holes immersed in external large-scalemagnetic fields. In the present paper we study the model ofmagnetic relativistic precession and provide estimations of the mass and spin of the central object of the microquasar H 1743-322 which is a candidate for a black hole. Moreover, we discuss the possible values of external magnetic field and study its influence on the motion of charged particles around rotating black hole.
Constraints on mass, spin and magnetic field of microquasar H~1743-322 from observations of QPOs
Tursunov, Arman; Kološ, Martin
2018-01-01
The study of quasi-periodic oscillations (QPOs) of X-ray flux observed in many microquasars can provide a powerful tool for testing of the phenomena occurring in strong gravity regime. QPOs phenomena can be well related to the oscillations of charged particles in accretion disks orbiting Kerr black holes immersed in external large-scale magnetic fields. In the present paper we study the model of magnetic relativistic precession and provide estimations of the mass and spin of the central objec...
The Giant Flares of the Microquasar Cygnus X-3: X-Rays States and Jets
Directory of Open Access Journals (Sweden)
Sergei Trushkin
2017-11-01
Full Text Available We report on two giant radio flares of the X-ray binary microquasar Cyg X-3, consisting of a Wolf–Rayet star and probably a black hole. The first flare occurred on 13 September 2016, 2000 days after a previous giant flare in February 2011, as the RATAN-600 radio telescope daily monitoring showed. After 200 days on 1 April 2017, we detected a second giant flare. Both flares are characterized by the increase of the fluxes by almost 2000-times (from 5–10 to 17,000 mJy at 4–11 GHz during 2–7 days, indicating relativistic bulk motions from the central region of the accretion disk around a black hole. The flaring light curves and spectral evolution of the synchrotron radiation indicate the formation of two relativistic collimated jets from the binaries. Both flares occurred when the source went from hypersoft X-ray states to soft ones, i.e. hard fluxes (Swift/BAT 15–50 keV data dropped to zero, the soft X-ray fluxes (MAXI 2–10 keV data staying high, and then later, the binary came back to a hard state. Both similar giant flares indicated the unchanged mechanism of the jets’ formation in Cyg X-3, probably in conditions of strong stellar wind and powerful accretion onto a black hole.
THE VARIABLE NEAR-INFRARED COUNTERPART OF THE MICROQUASAR GRS 1758–258
International Nuclear Information System (INIS)
Luque-Escamilla, Pedro L.; Martí, Josep; Muñoz-Arjonilla, Álvaro J.
2014-01-01
We present a new study of the microquasar system GRS 1758–258 in the near-infrared domain based on archival observations with the Hubble Space Telescope and the NICMOS camera. In addition to confirming the near-infrared counterpart pointed out by Muñoz-Arjonilla et al., we show that this object displays significant photometric variability. From its average magnitudes, we also find that GRS 1758–258 fits well within the correlation between the optical/near-infrared and X-ray luminosity known to exist for low-mass, black-hole candidate X-ray binaries in a hard state. Moreover, the spectral energy distribution built using all radio, near-infrared, and X-ray data available closest in time to the NICMOS observations can be reasonably interpreted in terms of a self-absorbed radio jet and an irradiated accretion disk model around a stellar-mass black hole. All these facts match the expected behavior of a compact binary system and strengthen our confidence in the counterpart identification
International Nuclear Information System (INIS)
Kadowaki, L. H. S.; Pino, E. M. de Gouveia Dal; Singh, C. B.
2015-01-01
Fast magnetic reconnection events can be a very powerful mechanism operating in the core region of microquasars and active galactic nuclei (AGNs). In earlier work, it has been suggested that the power released by fast reconnection events between the magnetic field lines lifting from the inner accretion disk region and the lines anchored into the central black hole could accelerate relativistic particles and produce the observed radio emission from microquasars and low luminosity AGNs (LLAGNs). Moreover, it has been proposed that the observed correlation between the radio emission and the mass of these sources, spanning 10 10 orders of magnitude in mass, might be related to this process. In the present work, we revisit this model comparing two different fast magnetic reconnection mechanisms, namely, fast reconnection driven by anomalous resistivity (AR) and by turbulence. We apply the scenario above to a much larger sample of sources (including also blazars, and gamma-ray bursts—GRBs), and find that LLAGNs and microquasars do confirm the trend above. Furthermore, when driven by turbulence, not only their radio but also their gamma-ray emission can be due to magnetic power released by fast reconnection, which may accelerate particles to relativistic velocities in the core region of these sources. Thus the turbulent-driven fast reconnection model is able to reproduce verywell the observed emission. On the other hand, the emission from blazars and GRBs does not follow the same trend as that of the LLAGNs and microquasars, indicating that the radio and gamma-ray emission in these cases is produced beyond the core, along the jet, by another population of relativistic particles, as expected
Caticha, Ariel
2011-03-01
In this tutorial we review the essential arguments behing entropic inference. We focus on the epistemological notion of information and its relation to the Bayesian beliefs of rational agents. The problem of updating from a prior to a posterior probability distribution is tackled through an eliminative induction process that singles out the logarithmic relative entropy as the unique tool for inference. The resulting method of Maximum relative Entropy (ME), includes as special cases both MaxEnt and Bayes' rule, and therefore unifies the two themes of these workshops—the Maximum Entropy and the Bayesian methods—into a single general inference scheme.
Kroese, A.H.; van der Meulen, E.A.; Poortema, Klaas; Schaafsma, W.
1995-01-01
The making of statistical inferences in distributional form is conceptionally complicated because the epistemic 'probabilities' assigned are mixtures of fact and fiction. In this respect they are essentially different from 'physical' or 'frequency-theoretic' probabilities. The distributional form is
Caticha, Ariel
2010-01-01
In this tutorial we review the essential arguments behing entropic inference. We focus on the epistemological notion of information and its relation to the Bayesian beliefs of rational agents. The problem of updating from a prior to a posterior probability distribution is tackled through an eliminative induction process that singles out the logarithmic relative entropy as the unique tool for inference. The resulting method of Maximum relative Entropy (ME), includes as special cases both MaxEn...
Aggelopoulos, Nikolaos C
2015-08-01
Perceptual inference refers to the ability to infer sensory stimuli from predictions that result from internal neural representations built through prior experience. Methods of Bayesian statistical inference and decision theory model cognition adequately by using error sensing either in guiding action or in "generative" models that predict the sensory information. In this framework, perception can be seen as a process qualitatively distinct from sensation, a process of information evaluation using previously acquired and stored representations (memories) that is guided by sensory feedback. The stored representations can be utilised as internal models of sensory stimuli enabling long term associations, for example in operant conditioning. Evidence for perceptual inference is contributed by such phenomena as the cortical co-localisation of object perception with object memory, the response invariance in the responses of some neurons to variations in the stimulus, as well as from situations in which perception can be dissociated from sensation. In the context of perceptual inference, sensory areas of the cerebral cortex that have been facilitated by a priming signal may be regarded as comparators in a closed feedback loop, similar to the better known motor reflexes in the sensorimotor system. The adult cerebral cortex can be regarded as similar to a servomechanism, in using sensory feedback to correct internal models, producing predictions of the outside world on the basis of past experience. Copyright © 2015 Elsevier Ltd. All rights reserved.
Rohatgi, Vijay K
2003-01-01
Unified treatment of probability and statistics examines and analyzes the relationship between the two fields, exploring inferential issues. Numerous problems, examples, and diagrams--some with solutions--plus clear-cut, highlighted summaries of results. Advanced undergraduate to graduate level. Contents: 1. Introduction. 2. Probability Model. 3. Probability Distributions. 4. Introduction to Statistical Inference. 5. More on Mathematical Expectation. 6. Some Discrete Models. 7. Some Continuous Models. 8. Functions of Random Variables and Random Vectors. 9. Large-Sample Theory. 10. General Meth
Energy Technology Data Exchange (ETDEWEB)
Kim, Jeong-Sook; Kim, Sang Joon [School of Space Science, Kyunghee University, Seocheon-dong, Giheung-si, Gyeonggi-do 446-701 (Korea, Republic of); Kim, Soon-Wook [Korea Astronomy and Space Science Institute, 776 Daedeokdaero, Yuseong, Daejeon 305-348 (Korea, Republic of); Kurayama, Tomoharu [Graduate School of Science and Engineering, Kagoshima University, 1-21-35 Korimoto, Kagoshima, Kagoshima 890-0065 (Japan); Honma, Mareki [National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588 (Japan); Sasao, Tetsuo, E-mail: evony@kasi.re.kr, E-mail: skim@kasi.re.kr [Yaeyama Star Club, Ookawa, Ishigaki, Okinawa 904-0022 (Japan)
2013-07-20
We present a radio observation of microquasar Cyg X-3 during an X-ray state transition from ultrasoft to hard state in the 2007 May-June flare using the VLBI Exploration of Radio Astrometry at 22 GHz. During the transition, a short-lived mini-flare of {approx}< 3 hr was detected prior to the major flare. In such a transition, a jet ejection is believed to occur, but there have been no direct observations to support it. An analysis of Gaussian fits to the observed visibility amplitudes shows a time variation of the source axis, or a structural change, during the mini-flare. Our model fits, together with other multiwavelength observations in the radio, soft, and hard X-rays, and the shock-in-jet models for other flaring activities at GHz wavebands, suggest a high possibility of synchrotron flares during the mini-flare, indicative of a predominant contribution from jet activity. Therefore, the mini-flare with an associated structural change is indicative of a jet ejection event in the state transition from ultrasoft to hard state.
Circumstances surrounding aneurysmal subarachnoid hemorrhage
Schievink, W. I.; Karemaker, J. M.; Hageman, L. M.; van der Werf, D. J.
1989-01-01
The circumstances surrounding aneurysmal subarachnoid hemorrhage were investigated in a group of 500 consecutive patients admitted to a neurosurgical center. Subarachnoid hemorrhage occurred during stressful events in 42.8% of the patients, during nonstrenuous activities in 34.4%, and during rest or
Opportunity's Surroundings on Sol 1818
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this full-circle view of the rover's surroundings during the 1,818th Martian day, or sol, of Opportunity's surface mission (March 5, 2009). South is at the center; north at both ends. The rover had driven 80.3 meters (263 feet) southward earlier on that sol. Tracks from the drive recede northward in this view. The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and lighter-toned bedrock. This view is presented as a cylindrical projection with geometric seam correction.
Opportunity's Surroundings on Sol 1687
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this 360-degree view of the rover's surroundings on the 1,687th Martian day, or sol, of its surface mission (Oct. 22, 2008). Opportunity had driven 133 meters (436 feet) that sol, crossing sand ripples up to about 10 centimeters (4 inches) tall. The tracks visible in the foreground are in the east-northeast direction. Opportunity's position on Sol 1687 was about 300 meters southwest of Victoria Crater. The rover was beginning a long trek toward a much larger crater, Endeavour, about 12 kilometers (7 miles) to the southeast. This view is presented as a cylindrical projection with geometric seam correction.
Opportunity's Surroundings on Sol 1798
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this 180-degree view of the rover's surroundings during the 1,798th Martian day, or sol, of Opportunity's surface mission (Feb. 13, 2009). North is on top. The rover had driven 111 meters (364 feet) southward on the preceding sol. Tracks from that drive recede northward in this view. For scale, the distance between the parallel wheel tracks is about 1 meter (about 40 inches). The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and lighter-toned bedrock. This view is presented as a cylindrical projection with geometric seam correction.
DEFF Research Database (Denmark)
Andersen, Jesper
2009-01-01
Collateral evolution the problem of updating several library-using programs in response to API changes in the used library. In this dissertation we address the issue of understanding collateral evolutions by automatically inferring a high-level specification of the changes evident in a given set ...... specifications inferred by spdiff in Linux are shown. We find that the inferred specifications concisely capture the actual collateral evolution performed in the examples....
Binaural Rendering in MPEG Surround
Directory of Open Access Journals (Sweden)
Kristofer Kjörling
2008-04-01
Full Text Available This paper describes novel methods for evoking a multichannel audio experience over stereo headphones. In contrast to the conventional convolution-based approach where, for example, five input channels are filtered using ten head-related transfer functions, the current approach is based on a parametric representation of the multichannel signal, along with either a parametric representation of the head-related transfer functions or a reduced set of head-related transfer functions. An audio scene with multiple virtual sound sources is represented by a mono or a stereo downmix signal of all sound source signals, accompanied by certain statistical (spatial properties. These statistical properties of the sound sources are either combined with statistical properties of head-related transfer functions to estimate Ã¢Â€Âœbinaural parametersÃ¢Â€Â that represent the perceptually relevant aspects of the auditory scene or used to create a limited set of combined head-related transfer functions that can be applied directly on the downmix signal. Subsequently, a binaural rendering stage reinstates the statistical properties of the sound sources by applying the estimated binaural parameters or the reduced set of combined head-related transfer functions directly on the downmix. If combined with parametric multichannel audio coders such as MPEG Surround, the proposed methods are advantageous over conventional methods in terms of perceived quality and computational complexity.
Energy Technology Data Exchange (ETDEWEB)
Petrov, S.
1996-10-01
Languages with a solvable implication problem but without complete and consistent systems of inference rules (`poor` languages) are considered. The problem of existence of finite complete and consistent inference rule system for a ``poor`` language is stated independently of the language or rules syntax. Several properties of the problem arc proved. An application of results to the language of join dependencies is given.
Bayesian statistical inference
Directory of Open Access Journals (Sweden)
Bruno De Finetti
2017-04-01
Full Text Available This work was translated into English and published in the volume: Bruno De Finetti, Induction and Probability, Biblioteca di Statistica, eds. P. Monari, D. Cocchi, Clueb, Bologna, 1993.Bayesian statistical Inference is one of the last fundamental philosophical papers in which we can find the essential De Finetti's approach to the statistical inference.
Geometric statistical inference
International Nuclear Information System (INIS)
Periwal, Vipul
1999-01-01
A reparametrization-covariant formulation of the inverse problem of probability is explicitly solved for finite sample sizes. The inferred distribution is explicitly continuous for finite sample size. A geometric solution of the statistical inference problem in higher dimensions is outlined
Bailer-Jones, Coryn A. L.
2017-04-01
Preface; 1. Probability basics; 2. Estimation and uncertainty; 3. Statistical models and inference; 4. Linear models, least squares, and maximum likelihood; 5. Parameter estimation: single parameter; 6. Parameter estimation: multiple parameters; 7. Approximating distributions; 8. Monte Carlo methods for inference; 9. Parameter estimation: Markov chain Monte Carlo; 10. Frequentist hypothesis testing; 11. Model comparison; 12. Dealing with more complicated problems; References; Index.
Nagao, Makoto
1990-01-01
Knowledge and Inference discusses an important problem for software systems: How do we treat knowledge and ideas on a computer and how do we use inference to solve problems on a computer? The book talks about the problems of knowledge and inference for the purpose of merging artificial intelligence and library science. The book begins by clarifying the concept of """"knowledge"""" from many points of view, followed by a chapter on the current state of library science and the place of artificial intelligence in library science. Subsequent chapters cover central topics in the artificial intellig
Logical inference and evaluation
International Nuclear Information System (INIS)
Perey, F.G.
1981-01-01
Most methodologies of evaluation currently used are based upon the theory of statistical inference. It is generally perceived that this theory is not capable of dealing satisfactorily with what are called systematic errors. Theories of logical inference should be capable of treating all of the information available, including that not involving frequency data. A theory of logical inference is presented as an extension of deductive logic via the concept of plausibility and the application of group theory. Some conclusions, based upon the application of this theory to evaluation of data, are also given
Probability and Statistical Inference
Prosper, Harrison B.
2006-01-01
These lectures introduce key concepts in probability and statistical inference at a level suitable for graduate students in particle physics. Our goal is to paint as vivid a picture as possible of the concepts covered.
On quantum statistical inference
Barndorff-Nielsen, O.E.; Gill, R.D.; Jupp, P.E.
2003-01-01
Interest in problems of statistical inference connected to measurements of quantum systems has recently increased substantially, in step with dramatic new developments in experimental techniques for studying small quantum systems. Furthermore, developments in the theory of quantum measurements have
2018-02-15
expressed a variety of inference techniques on discrete and continuous distributions: exact inference, importance sampling, Metropolis-Hastings (MH...without redoing any math or rewriting any code. And although our main goal is composable reuse, our performance is also good because we can use...control paths. • The Hakaru language can express mixtures of discrete and continuous distributions, but the current disintegration transformation
Introductory statistical inference
Mukhopadhyay, Nitis
2014-01-01
This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques.Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate topics. Introductory Statistical Inference studies multivariate random variables, exponential families of dist
Design Issues and Inference in Experimental L2 Research
Hudson, Thom; Llosa, Lorena
2015-01-01
Explicit attention to research design issues is essential in experimental second language (L2) research. Too often, however, such careful attention is not paid. This article examines some of the issues surrounding experimental L2 research and its relationships to causal inferences. It discusses the place of research questions and hypotheses,…
The rate of binary Black Hole mergers inferred from Advanced LIGO observations surrounding GW150914
Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Phythian-Adams, A.T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.T.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, R.D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Behnke, B.; Bejger, M.; Bell, A. S.; Bell, C. J.; Berger, B. K.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, M.J.; Birney, R.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, J.G.; Bogan, C.; Bohe, A.; Bojtos, P.; Bond, C.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Brooks, A. F.; Brown, A.D.; Brown, D.; Brown, N. M.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderon Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Diaz, J. Casanueva; Casentini, C.; Caudill, S.; Cavaglia, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Baiardi, L. Cerboni; Cerretani, G.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chan, M.; Chao, D. S.; Charlton, P.; Chassande-Mottin, E.; Chen, H. Y.; Chen, Y; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, S. S. Y.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P. -F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M., Jr.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J. -P.; Countryman, S. T.; Couvares, P.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, Laura; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dattilo, V.; Dave, I.; Daveloza, H. P.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; De, S.; Debra, D.; Debreczeni, G.; Degallaix, J.; De laurentis, M.; Deleglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.A.; Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Dhurandhar, S.; Diaz, M. C.; Di Fiore, L.; Giovanni, M. Di; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H. -B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M; Fong, H.; Fournier, J. -D.; Franco, S; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gatto, A.; Gaur, G.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.P.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; Gonzalez, Idelmis G.; Castro, J. M. Gonzalez; Gopakumar, A.; Gordon, N. A.; Gorodetsky, M. L.; Gossan, S. E.; Lee-Gosselin, M.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.M.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, A.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C. -J.; Haughian, K.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Hofman, D.; Hollitt, S. E.; Holt, K.; Holz, D. E.; Hopkins, P.; Hosken, D. J.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huang, S.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Idrisy, A.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J. -M.; Isi, M.; Islas, G.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jang, D.H.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jimenez-Forteza, F.; Johnson, W.; Jones, I.D.; Jones, R.; Jonker, R. J. G.; Ju, L.; Haris, K.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kefelian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.E.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khan, I.; Khan., S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, C.; Kim, J.; Kim, K.; Kim, Nam-Gyu; Kim, Namjun; Kim, Y.M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Kokeyama, K.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Krishnan, B.; Krolak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C.H.; Lee, K.H.; Lee, M.H.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B. M.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Logue, J.; Lombardi, A. L.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lueck, H.; Lundgren, A. P.; Luo, J.; Lynch, R.; Ma, Y.; MacDonald, T.T.; Machenschalk, B.; Maclnnis, M.; Macleod, D. M.; Magana-Sandoval, F.; Magee, R. M.; Mageswaran, M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Marka, S.; Marka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R.M.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; Mclntyre, G.; Mclver, J.; McManus, D. J.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B.C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, S.D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P.G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Gutierrez-Neri, M.; Neunzert, A.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.S; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Porter, E. K.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Puerrer, M.; Qi, H.; Qin, J.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romanov, G.; Romie, J. H.; Rosinska, D.; Rowan, S.; Ruediger, A.; Ruggi, P.; Ryan, K.; Sachdev, Perminder S; Sadecki, T.; Sadeghian, L.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J; Schmidt, P.; Schnabel, R.B.; Schofield, R. M. S.; Schoenbeck, A.; Schreiber, K.E.C.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Setyawati, Y.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shao, Z.M.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, António Dias da; Simakov, D.; Singer, A; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, R. J. E.; Smith, N.D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stevenson-Moore, P.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sutton, P. J.; Swinkels, B. L.; Szczepanczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tapai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, W.R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Toyra, D.; Travasso, F.; Traylor, G.; Trifiro, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; Vallisneri, M.; van Bakel, N.; Van Beuzekom, Martin; van den Brand, J. F. J.; Van Den Broeck, C.F.F.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasuth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P.J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Vicere, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J. -Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, MT; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L. -W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Wesels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Williams, D.R.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Wright, J.L.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, H.; Yvert, M.; Zadrozny, A.; Zangrando, L.; Zanolin, M.; Zendri, J. -P.; Zevin, M.; Zhang, F.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.
2016-01-01
A transient gravitational-wave signal, GW150914, was identified in the twin Advanced LIGO detectors on 2015 September 2015 at 09: 50: 45 UTC. To assess the implications of this discovery, the detectors remained in operation with unchanged configurations over a period of 39 days around the time of
Type Inference with Inequalities
DEFF Research Database (Denmark)
Schwartzbach, Michael Ignatieff
1991-01-01
of (monotonic) inequalities on the types of variables and expressions. A general result about systems of inequalities over semilattices yields a solvable form. We distinguish between deciding typability (the existence of solutions) and type inference (the computation of a minimal solution). In our case, both......Type inference can be phrased as constraint-solving over types. We consider an implicitly typed language equipped with recursive types, multiple inheritance, 1st order parametric polymorphism, and assignments. Type correctness is expressed as satisfiability of a possibly infinite collection...
Watson, Jane
2007-01-01
Inference, or decision making, is seen in curriculum documents as the final step in a statistical investigation. For a formal statistical enquiry this may be associated with sophisticated tests involving probability distributions. For young students without the mathematical background to perform such tests, it is still possible to draw informal…
Hybrid Optical Inference Machines
1991-09-27
with labels. Now, events. a set of facts cal be generated in the dyadic form "u, R 1,2" Eichmann and Caulfield (19] consider the same type of and can...these enceding-schemes. These architectures are-based pri- 19. G. Eichmann and H. J. Caulfield, "Optical Learning (Inference)marily on optical inner
Inference rule and problem solving
Energy Technology Data Exchange (ETDEWEB)
Goto, S
1982-04-01
Intelligent information processing signifies an opportunity of having man's intellectual activity executed on the computer, in which inference, in place of ordinary calculation, is used as the basic operational mechanism for such an information processing. Many inference rules are derived from syllogisms in formal logic. The problem of programming this inference function is referred to as a problem solving. Although logically inference and problem-solving are in close relation, the calculation ability of current computers is on a low level for inferring. For clarifying the relation between inference and computers, nonmonotonic logic has been considered. The paper deals with the above topics. 16 references.
Religion's relationship with social boundaries surrounding gender ...
African Journals Online (AJOL)
Religion's relationship with social boundaries surrounding gender. ... is associated with segregation, marginalization and differentiation between men and women. ... are necessary in the society it should not be mistaken for gender inequality.
Stochastic processes inference theory
Rao, Malempati M
2014-01-01
This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.
Making Type Inference Practical
DEFF Research Database (Denmark)
Schwartzbach, Michael Ignatieff; Oxhøj, Nicholas; Palsberg, Jens
1992-01-01
We present the implementation of a type inference algorithm for untyped object-oriented programs with inheritance, assignments, and late binding. The algorithm significantly improves our previous one, presented at OOPSLA'91, since it can handle collection classes, such as List, in a useful way. Abo......, the complexity has been dramatically improved, from exponential time to low polynomial time. The implementation uses the techniques of incremental graph construction and constraint template instantiation to avoid representing intermediate results, doing superfluous work, and recomputing type information....... Experiments indicate that the implementation type checks as much as 100 lines pr. second. This results in a mature product, on which a number of tools can be based, for example a safety tool, an image compression tool, a code optimization tool, and an annotation tool. This may make type inference for object...
Directory of Open Access Journals (Sweden)
João Paulo Monteiro
2001-12-01
Full Text Available Russell's The Problems of Philosophy tries to establish a new theory of induction, at the same time that Hume is there accused of an irrational/ scepticism about induction". But a careful analysis of the theory of knowledge explicitly acknowledged by Hume reveals that, contrary to the standard interpretation in the XXth century, possibly influenced by Russell, Hume deals exclusively with causal inference (which he never classifies as "causal induction", although now we are entitled to do so, never with inductive inference in general, mainly generalizations about sensible qualities of objects ( whether, e.g., "all crows are black" or not is not among Hume's concerns. Russell's theories are thus only false alternatives to Hume's, in (1912 or in his (1948.
Causal inference in econometrics
Kreinovich, Vladik; Sriboonchitta, Songsak
2016-01-01
This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.
Active inference and learning.
Friston, Karl; FitzGerald, Thomas; Rigoli, Francesco; Schwartenbeck, Philipp; O Doherty, John; Pezzulo, Giovanni
2016-09-01
This paper offers an active inference account of choice behaviour and learning. It focuses on the distinction between goal-directed and habitual behaviour and how they contextualise each other. We show that habits emerge naturally (and autodidactically) from sequential policy optimisation when agents are equipped with state-action policies. In active inference, behaviour has explorative (epistemic) and exploitative (pragmatic) aspects that are sensitive to ambiguity and risk respectively, where epistemic (ambiguity-resolving) behaviour enables pragmatic (reward-seeking) behaviour and the subsequent emergence of habits. Although goal-directed and habitual policies are usually associated with model-based and model-free schemes, we find the more important distinction is between belief-free and belief-based schemes. The underlying (variational) belief updating provides a comprehensive (if metaphorical) process theory for several phenomena, including the transfer of dopamine responses, reversal learning, habit formation and devaluation. Finally, we show that active inference reduces to a classical (Bellman) scheme, in the absence of ambiguity. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Learning Convex Inference of Marginals
Domke, Justin
2012-01-01
Graphical models trained using maximum likelihood are a common tool for probabilistic inference of marginal distributions. However, this approach suffers difficulties when either the inference process or the model is approximate. In this paper, the inference process is first defined to be the minimization of a convex function, inspired by free energy approximations. Learning is then done directly in terms of the performance of the inference process at univariate marginal prediction. The main ...
Probabilistic inductive inference: a survey
Ambainis, Andris
2001-01-01
Inductive inference is a recursion-theoretic theory of learning, first developed by E. M. Gold (1967). This paper surveys developments in probabilistic inductive inference. We mainly focus on finite inference of recursive functions, since this simple paradigm has produced the most interesting (and most complex) results.
Multimodel inference and adaptive management
Rehme, S.E.; Powell, L.A.; Allen, Craig R.
2011-01-01
Ecology is an inherently complex science coping with correlated variables, nonlinear interactions and multiple scales of pattern and process, making it difficult for experiments to result in clear, strong inference. Natural resource managers, policy makers, and stakeholders rely on science to provide timely and accurate management recommendations. However, the time necessary to untangle the complexities of interactions within ecosystems is often far greater than the time available to make management decisions. One method of coping with this problem is multimodel inference. Multimodel inference assesses uncertainty by calculating likelihoods among multiple competing hypotheses, but multimodel inference results are often equivocal. Despite this, there may be pressure for ecologists to provide management recommendations regardless of the strength of their study’s inference. We reviewed papers in the Journal of Wildlife Management (JWM) and the journal Conservation Biology (CB) to quantify the prevalence of multimodel inference approaches, the resulting inference (weak versus strong), and how authors dealt with the uncertainty. Thirty-eight percent and 14%, respectively, of articles in the JWM and CB used multimodel inference approaches. Strong inference was rarely observed, with only 7% of JWM and 20% of CB articles resulting in strong inference. We found the majority of weak inference papers in both journals (59%) gave specific management recommendations. Model selection uncertainty was ignored in most recommendations for management. We suggest that adaptive management is an ideal method to resolve uncertainty when research results in weak inference.
Enhancement of Afterimage Colors by Surrounding Contours
Directory of Open Access Journals (Sweden)
Takao Sato
2011-05-01
Full Text Available Presenting luminance contours surrounding the adapted areas in test phase enhances color afterimages in both duration and color appearance. The presence of surrounding contour is crucial to some color phenomenon such as van Lier's afterimage, but the contour-effect itself has not been seriously examined. In this paper, we compared the contour-effect to color afterimages and to actually colored patches to examine the nature of color information subserving color-aftereffect. In the experiment, observers were adapted for 1 sec to a small colored square (red, green, yellow, or blue presented on a gray background. Then, a test field either with or without surrounding contour was presented. Observers matched the color of a test-patch located near the afterimage to the color of afterimage. It was found that the saturation of negative afterimage was almost doubled by the presence of surrounding contours. There was no effect of luminance contrast or polarity of contours. In contrast, no enhancement of saturation by surrounding contours was observed for actually colored patches even though the colors of patches were equalized to that of afterimage without contours. This dissociation in the contour-effect demonstrates the crucial difference between the color information for aftereffects and for ordinary bottom-up color perception.
Explaining preferences for home surroundings and locations
DEFF Research Database (Denmark)
Andersen, Hans Skifter
2011-01-01
This article is based on a survey carried out in Denmark that asked a random sample of the population about their preferences for home surroundings and locations. It shows that the characteristics of social surroundings are very important and can be divided into three independent dimensions......: avoiding social nuisances, preferring social homogeneity and living close to one’s social network and place of origin. The study shows that most people have many detailed preferences, whereas some have very few. This confirms an earlier theory that some people are very connected to certain places...... with given characteristics and thus do not have priorities regarding home surroundings and locations. For others, mostly young people and singles, home is just a place to sleep and relax, whereas life is lived elsewhere. For this group, there are only preferences for location and there are few specific...
Nonparametric statistical inference
Gibbons, Jean Dickinson
2010-01-01
Overall, this remains a very fine book suitable for a graduate-level course in nonparametric statistics. I recommend it for all people interested in learning the basic ideas of nonparametric statistical inference.-Eugenia Stoimenova, Journal of Applied Statistics, June 2012… one of the best books available for a graduate (or advanced undergraduate) text for a theory course on nonparametric statistics. … a very well-written and organized book on nonparametric statistics, especially useful and recommended for teachers and graduate students.-Biometrics, 67, September 2011This excellently presente
Emotional inferences by pragmatics
Iza-Miqueleiz, Mauricio
2017-01-01
It has for long been taken for granted that, along the course of reading a text, world knowledge is often required in order to establish coherent links between sentences (McKoon & Ratcliff 1992, Iza & Ezquerro 2000). The content grasped from a text turns out to be strongly dependent upon the reader’s additional knowledge that allows a coherent interpretation of the text as a whole. The world knowledge directing the inference may be of distinctive nature. Gygax et al. (2007) showed that m...
DEFF Research Database (Denmark)
Andersen, Jesper; Lawall, Julia
2010-01-01
A key issue in maintaining Linux device drivers is the need to keep them up to date with respect to evolutions in Linux internal libraries. Currently, there is little tool support for performing and documenting such changes. In this paper we present a tool, spdiff, that identifies common changes...... developers can use it to extract an abstract representation of the set of changes that others have made. Our experiments on recent changes in Linux show that the inferred generic patches are more concise than the corresponding patches found in commits to the Linux source tree while being safe with respect...
Smart Chips for Smart Surroundings -- 4S
Schuler, Eberhard; König, Ralf; Becker, Jürgen; Rauwerda, G.K.; van de Burgwal, M.D.; Smit, Gerardus Johannes Maria; Cardoso, João M.P.; Hübner, Michael
2011-01-01
The overall mission of the 4S project (Smart Chips for Smart Surroundings) was to define and develop efficient flexible, reconfigurable core building blocks, including the supporting tools, for future Ambient System Devices. Reconfigurability offers the needed flexibility and adaptability, it
Childhood Suicide and Myths Surrounding It.
Greene, Dorothea B.
1994-01-01
Dispels five misconceptions surrounding the suicide of children: that children under the age of six do not commit suicide; that suicide in latency years is extremely rare; that psychodynamically and developmentally true depression is not possible in childhood; that child cannot understand finality of death; and that children are cognitively and…
Identification of β-SiC surrounded by relatable surrounding diamond ...
Indian Academy of Sciences (India)
β-SiC is identified in the presence of a relatable surrounding diamond medium using subtle, but discernible Raman ... Change in the nature of the surrounding material structure and its .... intensity implies very low graphite content in thin film. In.
Feature Inference Learning and Eyetracking
Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.
2009-01-01
Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…
An Inference Language for Imaging
DEFF Research Database (Denmark)
Pedemonte, Stefano; Catana, Ciprian; Van Leemput, Koen
2014-01-01
We introduce iLang, a language and software framework for probabilistic inference. The iLang framework enables the definition of directed and undirected probabilistic graphical models and the automated synthesis of high performance inference algorithms for imaging applications. The iLang framewor...
Energy Technology Data Exchange (ETDEWEB)
Chertkov, Michael [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ahn, Sungsoo [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of); Shin, Jinwoo [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of)
2017-05-25
Computing partition function is the most important statistical inference task arising in applications of Graphical Models (GM). Since it is computationally intractable, approximate methods have been used to resolve the issue in practice, where meanfield (MF) and belief propagation (BP) are arguably the most popular and successful approaches of a variational type. In this paper, we propose two new variational schemes, coined Gauged-MF (G-MF) and Gauged-BP (G-BP), improving MF and BP, respectively. Both provide lower bounds for the partition function by utilizing the so-called gauge transformation which modifies factors of GM while keeping the partition function invariant. Moreover, we prove that both G-MF and G-BP are exact for GMs with a single loop of a special structure, even though the bare MF and BP perform badly in this case. Our extensive experiments, on complete GMs of relatively small size and on large GM (up-to 300 variables) confirm that the newly proposed algorithms outperform and generalize MF and BP.
Social Inference Through Technology
Oulasvirta, Antti
Awareness cues are computer-mediated, real-time indicators of people’s undertakings, whereabouts, and intentions. Already in the mid-1970 s, UNIX users could use commands such as “finger” and “talk” to find out who was online and to chat. The small icons in instant messaging (IM) applications that indicate coconversants’ presence in the discussion space are the successors of “finger” output. Similar indicators can be found in online communities, media-sharing services, Internet relay chat (IRC), and location-based messaging applications. But presence and availability indicators are only the tip of the iceberg. Technological progress has enabled richer, more accurate, and more intimate indicators. For example, there are mobile services that allow friends to query and follow each other’s locations. Remote monitoring systems developed for health care allow relatives and doctors to assess the wellbeing of homebound patients (see, e.g., Tang and Venables 2000). But users also utilize cues that have not been deliberately designed for this purpose. For example, online gamers pay attention to other characters’ behavior to infer what the other players are like “in real life.” There is a common denominator underlying these examples: shared activities rely on the technology’s representation of the remote person. The other human being is not physically present but present only through a narrow technological channel.
Opportunity's Surroundings on Sol 1818 (Vertical)
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this full-circle view of the rover's surroundings during the 1,818th Martian day, or sol, of Opportunity's surface mission (March 5, 2009). South is at the center; north at both ends. This view is presented as a vertical projection with geometric seam correction. North is at the top. The rover had driven 80.3 meters (263 feet) southward earlier on that sol. Tracks from the drive recede northward in this view. The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and lighter-toned bedrock.
Opportunity's Surroundings on Sol 1818 (Polar)
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this full-circle view of the rover's surroundings during the 1,818th Martian day, or sol, of Opportunity's surface mission (March 5, 2009). South is at the center; north at both ends. This view is presented as a polar projection with geometric seam correction. North is at the top. The rover had driven 80.3 meters (263 feet) southward earlier on that sol. Tracks from the drive recede northward in this view. The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and lighter-toned bedrock.
Crust Structure Data of Seas Surrounding Turkey
International Nuclear Information System (INIS)
Maden, N.; Gelisli, K.
2007-01-01
Black Sea, Aegean, Mediterranean and Marmara Sea, which surround the Turkey, have not been examined with respect to the Geological, Geophysical and other natural sciences sufficiently. In fact, it is not attach importance the Turkish seas adequately and abandoned with respect to the scientific researches. The most important reason of this situation is the lack of the education of the Marine Sciences in the Turkish Universities. In this study, it is tried to construct a crustal structure data base of the surrounding seas of the Turkey by collecting crustal structure data sets done by different authors in different times so far. The data acquired in the base are collected from different data base sources by dragging. The Moho depth in the eastern and western basin of the Black sea is 22 km and 19 km, respectively. In the Marmara Sea the Moho depth is 24 km. The moho value in the southern Aegean is 20 km, in the northern Aegean the moho depth is 30 km. on the other hand, the moho depth value in the eastern and western basin of the Mediterranean Sea are 15-20 km and 25-30 km, respectively
Optimization methods for logical inference
Chandru, Vijay
2011-01-01
Merging logic and mathematics in deductive inference-an innovative, cutting-edge approach. Optimization methods for logical inference? Absolutely, say Vijay Chandru and John Hooker, two major contributors to this rapidly expanding field. And even though ""solving logical inference problems with optimization methods may seem a bit like eating sauerkraut with chopsticks. . . it is the mathematical structure of a problem that determines whether an optimization model can help solve it, not the context in which the problem occurs."" Presenting powerful, proven optimization techniques for logic in
Opportunity's Surroundings on Sol 1798 (Polar)
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this 180-degree view of the rover's surroundings during the 1,798th Martian day, or sol, of Opportunity's surface mission (Feb. 13, 2009). North is on top. This view is presented as a polar projection with geometric seam correction. The rover had driven 111 meters (364 feet) southward on the preceding sol. Tracks from that drive recede northward in this view. For scale, the distance between the parallel wheel tracks is about 1 meter (about 40 inches). The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and lighter-toned bedrock.
Opportunity's Surroundings After Sol 1820 Drive (Polar)
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this full-circle view of the rover's surroundings during the 1,820th to 1,822nd Martian days, or sols, of Opportunity's surface mission (March 7 to 9, 2009). This view is presented as a polar projection with geometric seam correction. North is at the top. The rover had driven 20.6 meters toward the northwest on Sol 1820 before beginning to take the frames in this view. Tracks from that drive recede southwestward. For scale, the distance between the parallel wheel tracks is about 1 meter (about 40 inches). The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and small exposures of lighter-toned bedrock.
Opportunity's Surroundings on Sol 1798 (Vertical)
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this 180-degree view of the rover's surroundings during the 1,798th Martian day, or sol, of Opportunity's surface mission (Feb. 13, 2009). North is on top. This view is presented as a vertical projection with geometric seam correction. The rover had driven 111 meters (364 feet) southward on the preceding sol. Tracks from that drive recede northward in this view. For scale, the distance between the parallel wheel tracks is about 1 meter (about 40 inches). The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and lighter-toned bedrock.
Opportunity's Surroundings on Sol 1687 (Vertical)
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this 360-degree view of the rover's surroundings on the 1,687th Martian day, or sol, of its surface mission (Oct. 22, 2008). Opportunity had driven 133 meters (436 feet) that sol, crossing sand ripples up to about 10 centimeters (4 inches) tall. The tracks visible in the foreground are in the east-northeast direction. Opportunity's position on Sol 1687 was about 300 meters southwest of Victoria Crater. The rover was beginning a long trek toward a much larger crater, Endeavour, about 12 kilometers (7 miles) to the southeast. This view is presented as a vertical projection with geometric seam correction.
Opportunity's Surroundings After Sol 1820 Drive (Vertical)
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this full-circle view of the rover's surroundings during the 1,820th to 1,822nd Martian days, or sols, of Opportunity's surface mission (March 7 to 9, 2009). This view is presented as a vertical projection with geometric seam correction. North is at the top. The rover had driven 20.6 meters toward the northwest on Sol 1820 before beginning to take the frames in this view. Tracks from that drive recede southwestward. For scale, the distance between the parallel wheel tracks is about 1 meter (about 40 inches). The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and small exposures of lighter-toned bedrock.
Opportunity's Surroundings on Sol 1687 (Polar)
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this 360-degree view of the rover's surroundings on the 1,687th Martian day, or sol, of its surface mission (Oct. 22, 2008). Opportunity had driven 133 meters (436 feet) that sol, crossing sand ripples up to about 10 centimeters (4 inches) tall. The tracks visible in the foreground are in the east-northeast direction. Opportunity's position on Sol 1687 was about 300 meters southwest of Victoria Crater. The rover was beginning a long trek toward a much larger crater, Endeavour, about 12 kilometers (7 miles) to the southeast. This view is presented as a polar projection with geometric seam correction.
Opportunity's Surroundings After Sol 1820 Drive
2009-01-01
NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this full-circle view of the rover's surroundings during the 1,820th to 1,822nd Martian days, or sols, of Opportunity's surface mission (March 7 to 9, 2009). South is at the center; north at both ends. The rover had driven 20.6 meters toward the northwest on Sol 1820 before beginning to take the frames in this view. Tracks from that drive recede southwestward. For scale, the distance between the parallel wheel tracks is about 1 meter (about 40 inches). The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and small exposures of lighter-toned bedrock. This view is presented as a cylindrical projection with geometric seam correction.
Towards Semantic Understanding of Surrounding Vehicular Maneuvers
DEFF Research Database (Denmark)
Kristoffersen, Miklas Strøm; Dueholm, Jacob Velling; Satzoda, Ravi K.
2016-01-01
This paper proposes the use of multiple low-cost visual sensors to obtain a surround view of the ego-vehicle for semantic understanding. A multi-perspective view will assist the analysis of naturalistic driving studies (NDS), by automating the task of data reduction of the observed sequences...... into events. A user-centric vision-based framework is presented using a vehicle detector and tracker in each separate perspective. Multi-perspective trajectories are estimated and analyzed to extract 14 different events, including potential dangerous behaviors such as overtakes and cut-ins. The system...... is tested on ten sequences of real-world data collected on U. S. highways. The results show the potential use of multiple low-cost visual sensors for semantic understanding around the ego-vehicle....
Lovelock black holes surrounded by quintessence
Energy Technology Data Exchange (ETDEWEB)
Ghosh, Sushant G. [University of KwaZulu-Natal, Astrophysics and Cosmology Research Unit, School of Mathematics, Statistics and Computer Science, Durban (South Africa); Centre for Theoretical Physics, Multidisciplinary Centre for Advanced Research and Studies (MCARS), New Delhi (India); Maharaj, Sunil D.; Baboolal, Dharmanand; Lee, Tae-Hun [University of KwaZulu-Natal, Astrophysics and Cosmology Research Unit, School of Mathematics, Statistics and Computer Science, Durban (South Africa)
2018-02-15
Lovelock gravity consisting of the dimensionally continued Euler densities is a natural generalization of general relativity to higher dimensions such that equations of motion are still second order, and the theory is free of ghosts. A scalar field with a positive potential that yields an accelerating universe has been termed quintessence. We present exact black hole solutions in D-dimensional Lovelock gravity surrounded by quintessence matter and also perform a detailed thermodynamical study. Further, we find that the mass, entropy and temperature of the black hole are corrected due to the quintessence background. In particular, we find that a phase transition occurs with a divergence of the heat capacity at the critical horizon radius, and that specific heat becomes positive for r{sub h} < r{sub c} allowing the black hole to become thermodynamically stable. (orig.)
Lovelock black holes surrounded by quintessence
Ghosh, Sushant G.; Maharaj, Sunil D.; Baboolal, Dharmanand; Lee, Tae-Hun
2018-02-01
Lovelock gravity consisting of the dimensionally continued Euler densities is a natural generalization of general relativity to higher dimensions such that equations of motion are still second order, and the theory is free of ghosts. A scalar field with a positive potential that yields an accelerating universe has been termed quintessence. We present exact black hole solutions in D-dimensional Lovelock gravity surrounded by quintessence matter and also perform a detailed thermodynamical study. Further, we find that the mass, entropy and temperature of the black hole are corrected due to the quintessence background. In particular, we find that a phase transition occurs with a divergence of the heat capacity at the critical horizon radius, and that specific heat becomes positive for r_h
International Nuclear Information System (INIS)
1984-03-01
An aerial radiological survey was performed over the area surrounding the Shoreham Nuclear Power Station during 5 to 9 June 1983. The survey, which covered an area of 338 square kilometers (131 square miles), also encompassed the entire Brookhaven National Laboratory (BNL) facility. The highest radiation exposure rate, over 1 milliroentgen per hour (mR/h), was inferred from data measured directly over the BNL facility. This detected activity was due to the presence of cobalt-58, cobalt-60 and cesium-137, which was consistent with normal BNL operations. With the exception of the BNL facility, the only detected man-made radioactivity was found near a cottage in Moriches, New York and was due to the presence of cobalt-60. For the remainder of the survey area, the inferred radiation exposure rates varied generally from 6 to 12 microroentgens per hour (μR/h). The reported exposure rate values include an estimated cosmic ray contribution of 3.7 μR/h. Ground-based measurements, conducted concurrently with the aerial survey, were compared to the inferred aerial results. Pressurized ionization chamber readings and a group of soil samples were acquired from five locations within the survey area. The exposure rate values obtained from these measurements were consistent with those inferred from the aerial results. 11 references, 12 figures, 3 tables
On principles of inductive inference
Kostecki, Ryszard Paweł
2011-01-01
We propose an intersubjective epistemic approach to foundations of probability theory and statistical inference, based on relative entropy and category theory, and aimed to bypass the mathematical and conceptual problems of existing foundational approaches.
Statistical inference via fiducial methods
Salomé, Diemer
1998-01-01
In this thesis the attention is restricted to inductive reasoning using a mathematical probability model. A statistical procedure prescribes, for every theoretically possible set of data, the inference about the unknown of interest. ... Zie: Summary
Statistical inference for stochastic processes
National Research Council Canada - National Science Library
Basawa, Ishwar V; Prakasa Rao, B. L. S
1980-01-01
The aim of this monograph is to attempt to reduce the gap between theory and applications in the area of stochastic modelling, by directing the interest of future researchers to the inference aspects...
Active inference, communication and hermeneutics.
Friston, Karl J; Frith, Christopher D
2015-07-01
Hermeneutics refers to interpretation and translation of text (typically ancient scriptures) but also applies to verbal and non-verbal communication. In a psychological setting it nicely frames the problem of inferring the intended content of a communication. In this paper, we offer a solution to the problem of neural hermeneutics based upon active inference. In active inference, action fulfils predictions about how we will behave (e.g., predicting we will speak). Crucially, these predictions can be used to predict both self and others--during speaking and listening respectively. Active inference mandates the suppression of prediction errors by updating an internal model that generates predictions--both at fast timescales (through perceptual inference) and slower timescales (through perceptual learning). If two agents adopt the same model, then--in principle--they can predict each other and minimise their mutual prediction errors. Heuristically, this ensures they are singing from the same hymn sheet. This paper builds upon recent work on active inference and communication to illustrate perceptual learning using simulated birdsongs. Our focus here is the neural hermeneutics implicit in learning, where communication facilitates long-term changes in generative models that are trying to predict each other. In other words, communication induces perceptual learning and enables others to (literally) change our minds and vice versa. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Optimal inference with suboptimal models: Addiction and active Bayesian inference
Schwartenbeck, Philipp; FitzGerald, Thomas H.B.; Mathys, Christoph; Dolan, Ray; Wurst, Friedrich; Kronbichler, Martin; Friston, Karl
2015-01-01
When casting behaviour as active (Bayesian) inference, optimal inference is defined with respect to an agent’s beliefs – based on its generative model of the world. This contrasts with normative accounts of choice behaviour, in which optimal actions are considered in relation to the true structure of the environment – as opposed to the agent’s beliefs about worldly states (or the task). This distinction shifts an understanding of suboptimal or pathological behaviour away from aberrant inference as such, to understanding the prior beliefs of a subject that cause them to behave less ‘optimally’ than our prior beliefs suggest they should behave. Put simply, suboptimal or pathological behaviour does not speak against understanding behaviour in terms of (Bayes optimal) inference, but rather calls for a more refined understanding of the subject’s generative model upon which their (optimal) Bayesian inference is based. Here, we discuss this fundamental distinction and its implications for understanding optimality, bounded rationality and pathological (choice) behaviour. We illustrate our argument using addictive choice behaviour in a recently described ‘limited offer’ task. Our simulations of pathological choices and addictive behaviour also generate some clear hypotheses, which we hope to pursue in ongoing empirical work. PMID:25561321
Opportunity's Surroundings on Sol 1798 (Stereo)
2009-01-01
[figure removed for brevity, see original site] Left-eye view of a color stereo pair for PIA11850 [figure removed for brevity, see original site] Right-eye view of a color stereo pair for PIA11850 NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this stereo 180-degree view of the rover's surroundings during the 1,798th Martian day, or sol, of Opportunity's surface mission (Feb. 13, 2009). North is on top. This view combines images from the left-eye and right-eye sides of the navigation camera. It appears three-dimensional when viewed through red-blue glasses with the red lens on the left. The rover had driven 111 meters (364 feet) southward on the preceding sol. Tracks from that drive recede northward in this view. For scale, the distance between the parallel wheel tracks is about 1 meter (about 40 inches). The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and lighter-toned bedrock. This view is presented as a cylindrical-perspective projection with geometric seam correction.
Opportunity's Surroundings on Sol 1818 (Stereo)
2009-01-01
[figure removed for brevity, see original site] Left-eye view of a color stereo pair for PIA11846 [figure removed for brevity, see original site] Right-eye view of a color stereo pair for PIA11846 NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this full-circle view of the rover's surroundings during the 1,818th Martian day, or sol, of Opportunity's surface mission (March 5, 2009). South is at the center; north at both ends. This view combines images from the left-eye and right-eye sides of the navigation camera. It appears three-dimensional when viewed through red-blue glasses with the red lens on the left. The rover had driven 80.3 meters (263 feet) southward earlier on that sol. Tracks from the drive recede northward in this view. The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and lighter-toned bedrock. This view is presented as a cylindrical-perspective projection with geometric seam correction.
Opportunity's Surroundings on Sol 1687 (Stereo)
2009-01-01
[figure removed for brevity, see original site] Left-eye view of a color stereo pair for PIA11739 [figure removed for brevity, see original site] Right-eye view of a color stereo pair for PIA11739 NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this stereo, 360-degree view of the rover's surroundings on the 1,687th Martian day, or sol, of its surface mission (Oct. 22, 2008). The view appears three-dimensional when viewed through red-blue glasses. Opportunity had driven 133 meters (436 feet) that sol, crossing sand ripples up to about 10 centimeters (4 inches) tall. The tracks visible in the foreground are in the east-northeast direction. Opportunity's position on Sol 1687 was about 300 meters southwest of Victoria Crater. The rover was beginning a long trek toward a much larger crater, Endeavour, about 12 kilometers (7 miles) to the southeast. This panorama combines right-eye and left-eye views presented as cylindrical-perspective projections with geometric seam correction.
Opportunity's Surroundings After Sol 1820 Drive (Stereo)
2009-01-01
[figure removed for brevity, see original site] Left-eye view of a color stereo pair for PIA11841 [figure removed for brevity, see original site] Right-eye view of a color stereo pair for PIA11841 NASA's Mars Exploration Rover Opportunity used its navigation camera to take the images combined into this full-circle view of the rover's surroundings during the 1,820th to 1,822nd Martian days, or sols, of Opportunity's surface mission (March 7 to 9, 2009). This view combines images from the left-eye and right-eye sides of the navigation camera. It appears three-dimensional when viewed through red-blue glasses with the red lens on the left. The rover had driven 20.6 meters toward the northwest on Sol 1820 before beginning to take the frames in this view. Tracks from that drive recede southwestward. For scale, the distance between the parallel wheel tracks is about 1 meter (about 40 inches). The terrain in this portion of Mars' Meridiani Planum region includes dark-toned sand ripples and small exposures of lighter-toned bedrock. This view is presented as a cylindrical-perspective projection with geometric seam correction.
The lithosphere-asthenosphere: Italy and surroundings
International Nuclear Information System (INIS)
Panza, G.F.; Aoudia, A.; Pontevivo, A.; Chimera, G.; Raykova, R.
2003-02-01
The velocity-depth distribution of the lithosphere-asthenosphere in the Italian region and surroundings is imaged, with a lateral resolution of about 100 km, by surface wave velocity tomography and non-linear inversion. Maps of the Moho depth, of the thickness of the lithosphere and of the shear-wave velocities, down to depths of 200 km and more, are constructed. A mantle wedge, identified in the uppermost mantle along the Apennines and the Calabrian Arc, underlies the principal recent volcanoes, and partial melting can be relevant in this part of the uppermost mantle. In Calabria a lithospheric doubling is seen, in connection with the subduction of the Ionian lithosphere. The asthenosphere is shallow in the Southern Tyrrhenian Sea. High velocity bodies, cutting the asthenosphere, outline the Adria-lonian subduction in the Tyrrhenian Sea and the deep-reaching lithospheric root in the Western Alps. Less deep lithospheric roots are seen in the Central Apennines. The lithosphere-asthenosphere properties delineate a differentiation between the northern and the southern sectors of the Adriatic Sea, likely attesting the fragmentation of Adria. (author)
The lithosphere-asthenosphere Italy and surroundings
Panza, G F; Chimera, G; Pontevivo, A; Raykova, R
2003-01-01
The velocity-depth distribution of the lithosphere-asthenosphere in the Italian region and surroundings is imaged, with a lateral resolution of about 100 km, by surface wave velocity tomography and non-linear inversion. Maps of the Moho depth, of the thickness of the lithosphere and of the shear-wave velocities, down to depths of 200 km and more, are constructed. A mantle wedge, identified in the uppermost mantle along the Apennines and the Calabrian Arc, underlies the principal recent volcanoes, and partial melting can be relevant in this part of the uppermost mantle. In Calabria a lithospheric doubling is seen, in connection with the subduction of the Ionian lithosphere. The asthenosphere is shallow in the Southern Tyrrhenian Sea. High velocity bodies, cutting the asthenosphere, outline the Adria-lonian subduction in the Tyrrhenian Sea and the deep-reaching lithospheric root in the Western Alps. Less deep lithospheric roots are seen in the Central Apennines. The lithosphere-asthenosphere properties delineat...
INTERSTELLAR MAGNETIC FIELD SURROUNDING THE HELIOPAUSE
International Nuclear Information System (INIS)
Whang, Y. C.
2010-01-01
This paper presents a three-dimensional analytical solution, in the limit of very low plasma β-ratio, for the distortion of the interstellar magnetic field surrounding the heliopause. The solution is obtained using a line dipole method that is the integration of point dipole along a semi-infinite line; it represents the magnetic field caused by the presence of the heliopause. The solution allows the variation of the undisturbed magnetic field at any inclination angle. The heliosphere is considered as having blunt-nosed geometry on the upwind side and it asymptotically approaches a cylindrical geometry having an open exit for the continuous outflow of the solar wind on the downwind side. The heliopause is treated as a magnetohydrodynamic tangential discontinuity; the interstellar magnetic field lines at the boundary are tangential to the heliopause. The interstellar magnetic field is substantially distorted due to the presence of the heliopause. The solution shows the draping of the field lines around the heliopause. The magnetic field strength varies substantially near the surface of the heliopause. The effect on the magnetic field due to the presence of the heliopause penetrates very deep into the interstellar space; the depth of penetration is of the same order of magnitude as the scale length of the heliosphere.
Understanding community norms surrounding tobacco sales.
Directory of Open Access Journals (Sweden)
Patricia A McDaniel
Full Text Available In the US, denormalizing tobacco use is key to tobacco control; less attention has been paid to denormalizing tobacco sales. However, some localities have placed limits on the number and type of retailers who may sell tobacco, and some retailers have abandoned tobacco sales voluntarily. Understanding community norms surrounding tobacco sales may help accelerate tobacco denormalization.We conducted 15 focus groups with customers of California, New York, and Ohio retailers who had voluntarily discontinued tobacco sales to examine normative assumptions about where cigarettes should or should not be sold, voluntary decisions to discontinue tobacco sales, and government limits on such sales.Groups in all three states generally agreed that grocery stores that sold healthy products should not sell tobacco; California groups saw pharmacies similarly, while this was a minority opinion in the other two states. Convenience stores were regarded as a natural place to sell tobacco. In each state, it was regarded as normal and commendable for some stores to want to stop selling tobacco, although few participants could imagine convenience stores doing so. Views on government's role in setting limits on tobacco sales varied, with California and New York participants generally expressing support for restrictions, and Ohio participants expressing opposition. However, even those who expressed opposition did not approve of tobacco sales in all possible venues. Banning tobacco sales entirely was not yet normative.Limiting the ubiquitous availability of tobacco sales is key to ending the tobacco epidemic. Some limits on tobacco sales appear to be normative from the perspective of community members; it may be possible to shift norms further by problematizing the ubiquitous presence of cigarettes and drawing connections to other products already subject to restrictions.
Understanding community norms surrounding tobacco sales.
McDaniel, Patricia A; Malone, Ruth E
2014-01-01
In the US, denormalizing tobacco use is key to tobacco control; less attention has been paid to denormalizing tobacco sales. However, some localities have placed limits on the number and type of retailers who may sell tobacco, and some retailers have abandoned tobacco sales voluntarily. Understanding community norms surrounding tobacco sales may help accelerate tobacco denormalization. We conducted 15 focus groups with customers of California, New York, and Ohio retailers who had voluntarily discontinued tobacco sales to examine normative assumptions about where cigarettes should or should not be sold, voluntary decisions to discontinue tobacco sales, and government limits on such sales. Groups in all three states generally agreed that grocery stores that sold healthy products should not sell tobacco; California groups saw pharmacies similarly, while this was a minority opinion in the other two states. Convenience stores were regarded as a natural place to sell tobacco. In each state, it was regarded as normal and commendable for some stores to want to stop selling tobacco, although few participants could imagine convenience stores doing so. Views on government's role in setting limits on tobacco sales varied, with California and New York participants generally expressing support for restrictions, and Ohio participants expressing opposition. However, even those who expressed opposition did not approve of tobacco sales in all possible venues. Banning tobacco sales entirely was not yet normative. Limiting the ubiquitous availability of tobacco sales is key to ending the tobacco epidemic. Some limits on tobacco sales appear to be normative from the perspective of community members; it may be possible to shift norms further by problematizing the ubiquitous presence of cigarettes and drawing connections to other products already subject to restrictions.
Interactive Instruction in Bayesian Inference
DEFF Research Database (Denmark)
Khan, Azam; Breslav, Simon; Hornbæk, Kasper
2018-01-01
An instructional approach is presented to improve human performance in solving Bayesian inference problems. Starting from the original text of the classic Mammography Problem, the textual expression is modified and visualizations are added according to Mayer’s principles of instruction. These pri......An instructional approach is presented to improve human performance in solving Bayesian inference problems. Starting from the original text of the classic Mammography Problem, the textual expression is modified and visualizations are added according to Mayer’s principles of instruction....... These principles concern coherence, personalization, signaling, segmenting, multimedia, spatial contiguity, and pretraining. Principles of self-explanation and interactivity are also applied. Four experiments on the Mammography Problem showed that these principles help participants answer the questions...... that an instructional approach to improving human performance in Bayesian inference is a promising direction....
On Maximum Entropy and Inference
Directory of Open Access Journals (Sweden)
Luigi Gresele
2017-11-01
Full Text Available Maximum entropy is a powerful concept that entails a sharp separation between relevant and irrelevant variables. It is typically invoked in inference, once an assumption is made on what the relevant variables are, in order to estimate a model from data, that affords predictions on all other (dependent variables. Conversely, maximum entropy can be invoked to retrieve the relevant variables (sufficient statistics directly from the data, once a model is identified by Bayesian model selection. We explore this approach in the case of spin models with interactions of arbitrary order, and we discuss how relevant interactions can be inferred. In this perspective, the dimensionality of the inference problem is not set by the number of parameters in the model, but by the frequency distribution of the data. We illustrate the method showing its ability to recover the correct model in a few prototype cases and discuss its application on a real dataset.
Eight challenges in phylodynamic inference
Directory of Open Access Journals (Sweden)
Simon D.W. Frost
2015-03-01
Full Text Available The field of phylodynamics, which attempts to enhance our understanding of infectious disease dynamics using pathogen phylogenies, has made great strides in the past decade. Basic epidemiological and evolutionary models are now well characterized with inferential frameworks in place. However, significant challenges remain in extending phylodynamic inference to more complex systems. These challenges include accounting for evolutionary complexities such as changing mutation rates, selection, reassortment, and recombination, as well as epidemiological complexities such as stochastic population dynamics, host population structure, and different patterns at the within-host and between-host scales. An additional challenge exists in making efficient inferences from an ever increasing corpus of sequence data.
Problem solving and inference mechanisms
Energy Technology Data Exchange (ETDEWEB)
Furukawa, K; Nakajima, R; Yonezawa, A; Goto, S; Aoyama, A
1982-01-01
The heart of the fifth generation computer will be powerful mechanisms for problem solving and inference. A deduction-oriented language is to be designed, which will form the core of the whole computing system. The language is based on predicate logic with the extended features of structuring facilities, meta structures and relational data base interfaces. Parallel computation mechanisms and specialized hardware architectures are being investigated to make possible efficient realization of the language features. The project includes research into an intelligent programming system, a knowledge representation language and system, and a meta inference system to be built on the core. 30 references.
Impacts of Artificial Reefs on Surrounding Ecosystems
Manoukian, Sarine
Artificial reefs are becoming a popular biological and management component in shallow water environments characterized by soft seabed, representing both important marine habitats and tools to manage coastal fisheries and resources. An artificial reef in the marine environment acts as an open system with exchange of material and energy, altering the physical and biological characteristics of the surrounding area. Reef stability will depend on the balance of scour, settlement, and burial resulting from ocean conditions over time. Because of the unstable nature of sediments, they require a detailed and systematic investigation. Acoustic systems like high-frequency multibeam sonar are efficient tools in monitoring the environmental evolution around artificial reefs, whereas water turbidity can limit visual dive and ROV inspections. A high-frequency multibeam echo sounder offers the potential of detecting fine-scale distribution of reef units, providing an unprecedented level of resolution, coverage, and spatial definition. How do artificial reefs change over time in relation to the coastal processes? How accurately does multibeam technology map different typologies of artificial modules of known size and shape? How do artificial reefs affect fish school behavior? What are the limitations of multibeam technology for investigating fish school distribution as well as spatial and temporal changes? This study addresses the above questions and presents results of a new approach for artificial reef seafloor mapping over time, based upon an integrated analysis of multibeam swath bathymetry data and geoscientific information (backscatter data analysis, SCUBA observations, physical oceanographic data, and previous findings on the geology and sedimentation processes, integrated with unpublished data) from Senigallia artificial reef, northwestern Adriatic Sea (Italy) and St. Petersburg Beach Reef, west-central Florida continental shelf. A new approach for observation of fish
Object-Oriented Type Inference
DEFF Research Database (Denmark)
Schwartzbach, Michael Ignatieff; Palsberg, Jens
1991-01-01
We present a new approach to inferring types in untyped object-oriented programs with inheritance, assignments, and late binding. It guarantees that all messages are understood, annotates the program with type information, allows polymorphic methods, and can be used as the basis of an op...
Inference in hybrid Bayesian networks
DEFF Research Database (Denmark)
Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael
2009-01-01
Since the 1980s, Bayesian Networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability-techniques (like fault trees...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....
Mixed normal inference on multicointegration
Boswijk, H.P.
2009-01-01
Asymptotic likelihood analysis of cointegration in I(2) models, see Johansen (1997, 2006), Boswijk (2000) and Paruolo (2000), has shown that inference on most parameters is mixed normal, implying hypothesis test statistics with an asymptotic 2 null distribution. The asymptotic distribution of the
Statistical inference and Aristotle's Rhetoric.
Macdonald, Ranald R
2004-11-01
Formal logic operates in a closed system where all the information relevant to any conclusion is present, whereas this is not the case when one reasons about events and states of the world. Pollard and Richardson drew attention to the fact that the reasoning behind statistical tests does not lead to logically justifiable conclusions. In this paper statistical inferences are defended not by logic but by the standards of everyday reasoning. Aristotle invented formal logic, but argued that people mostly get at the truth with the aid of enthymemes--incomplete syllogisms which include arguing from examples, analogies and signs. It is proposed that statistical tests work in the same way--in that they are based on examples, invoke the analogy of a model and use the size of the effect under test as a sign that the chance hypothesis is unlikely. Of existing theories of statistical inference only a weak version of Fisher's takes this into account. Aristotle anticipated Fisher by producing an argument of the form that there were too many cases in which an outcome went in a particular direction for that direction to be plausibly attributed to chance. We can therefore conclude that Aristotle would have approved of statistical inference and there is a good reason for calling this form of statistical inference classical.
International Nuclear Information System (INIS)
1986-05-01
An aerial radiological survey was performed over the area surrounding the Enrico Fermi Atomic Power Plant during the period 27 to 30 May 1986. The survey covered a 64-square-kilometer (25-square-mile) area around the plant. The deteted radiation was due to the presence of varying concentrations of naturally-occurring radioactive materials. Radionuclides of the uranium and thorium decay chains and radioactive potassium were found. For the majority of the survey area, the inferred radiation exposure rate levels varied between 10 and 12 microroentgens per hour (μR/h). The reported exposure rate values included an estimated cosmic ray contribution of 3.7 μR/h. Ground-based measurements, conducted concurrently with the aerial survey, were compared to the inferred aerial results. Pressurized ionization chamber readings and a group of soil samples were acquired at five locations within the survey area. The exposure rate values obtained from these ground-based measurements were in good agreement with the corresponding inferred aerial values. No evidence was found of any radioactive contamination which might have occurred as a result of plant operations. This conclusion was supported by the results of the soil samples analyses and the comparison of the current survey data with those obtained in September 1970. 7 refs., 5 figs., 1 tab
The genetic assimilation in language borrowing inferred from Jing People.
Huang, Xiufeng; Zhou, Qinghui; Bin, Xiaoyun; Lai, Shu; Lin, Chaowen; Hu, Rong; Xiao, Jiashun; Luo, Dajun; Li, Yingxiang; Wei, Lan-Hai; Yeh, Hui-Yuan; Chen, Gang; Wang, Chuan-Chao
2018-02-28
The Jing people are a recognized ethnic group in Guangxi, southwest China, who are the immigrants from Vietnam during the 16th century. They speak Vietnamese but with lots of language borrowings from Cantonese, Zhuang, and Mandarin. However, it's unclear if there is large-scale gene flow from surrounding populations into Jing people during their language change due to the very limited genetic information of this population. We collected blood samples from 37 Jing and 3 Han Chinese individuals from Wanwei, Shanxin, and Wutou islands in Guangxi and genotyped about 600,000 genome-wide single nucleotide polymorphisms (SNPs). We used Principal Component Analysis (PCA), ADMIXTURE analysis, f statistics, qpWave and qpAdm to infer the population genetic structure and admixture. Our data revealed that the Jing people are genetically similar to the populations in southwest China and mainland Southeast Asia. But compared with Vietnamese, they show significant evidence of gene flow from surrounding East Asians. The admixture proportion is estimated to be around 35-42% in different Jing groups using southern Han Chinese as a proxy. The majority of the paternal lineages of Jing people are most likely from surrounding East Asians. We conclude that the formation and language change of present-day Jing people have involved genetic assimilation of surrounding East Asian populations. The language borrowing, in this case, is not only a cultural phenomenon but has involved demic diffusion. © 2018 Wiley Periodicals, Inc.
Statistical learning and selective inference.
Taylor, Jonathan; Tibshirani, Robert J
2015-06-23
We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.
Bayesian inference with ecological applications
Link, William A
2009-01-01
This text is written to provide a mathematically sound but accessible and engaging introduction to Bayesian inference specifically for environmental scientists, ecologists and wildlife biologists. It emphasizes the power and usefulness of Bayesian methods in an ecological context. The advent of fast personal computers and easily available software has simplified the use of Bayesian and hierarchical models . One obstacle remains for ecologists and wildlife biologists, namely the near absence of Bayesian texts written specifically for them. The book includes many relevant examples, is supported by software and examples on a companion website and will become an essential grounding in this approach for students and research ecologists. Engagingly written text specifically designed to demystify a complex subject Examples drawn from ecology and wildlife research An essential grounding for graduate and research ecologists in the increasingly prevalent Bayesian approach to inference Companion website with analyt...
Statistical inference an integrated approach
Migon, Helio S; Louzada, Francisco
2014-01-01
Introduction Information The concept of probability Assessing subjective probabilities An example Linear algebra and probability Notation Outline of the bookElements of Inference Common statistical modelsLikelihood-based functions Bayes theorem Exchangeability Sufficiency and exponential family Parameter elimination Prior Distribution Entirely subjective specification Specification through functional forms Conjugacy with the exponential family Non-informative priors Hierarchical priors Estimation Introduction to decision theoryBayesian point estimation Classical point estimation Empirical Bayes estimation Comparison of estimators Interval estimation Estimation in the Normal model Approximating Methods The general problem of inference Optimization techniquesAsymptotic theory Other analytical approximations Numerical integration methods Simulation methods Hypothesis Testing Introduction Classical hypothesis testingBayesian hypothesis testing Hypothesis testing and confidence intervalsAsymptotic tests Prediction...
Bayesian inference on proportional elections.
Directory of Open Access Journals (Sweden)
Gabriel Hideki Vatanabe Brunello
Full Text Available Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software.
Causal inference based on counterfactuals
Directory of Open Access Journals (Sweden)
Höfler M
2005-09-01
Full Text Available Abstract Background The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. Discussion This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. Summary Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept.
System Support for Forensic Inference
Gehani, Ashish; Kirchner, Florent; Shankar, Natarajan
Digital evidence is playing an increasingly important role in prosecuting crimes. The reasons are manifold: financially lucrative targets are now connected online, systems are so complex that vulnerabilities abound and strong digital identities are being adopted, making audit trails more useful. If the discoveries of forensic analysts are to hold up to scrutiny in court, they must meet the standard for scientific evidence. Software systems are currently developed without consideration of this fact. This paper argues for the development of a formal framework for constructing “digital artifacts” that can serve as proxies for physical evidence; a system so imbued would facilitate sound digital forensic inference. A case study involving a filesystem augmentation that provides transparent support for forensic inference is described.
Probability biases as Bayesian inference
Directory of Open Access Journals (Sweden)
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
Statistical inference on residual life
Jeong, Jong-Hyeon
2014-01-01
This is a monograph on the concept of residual life, which is an alternative summary measure of time-to-event data, or survival data. The mean residual life has been used for many years under the name of life expectancy, so it is a natural concept for summarizing survival or reliability data. It is also more interpretable than the popular hazard function, especially for communications between patients and physicians regarding the efficacy of a new drug in the medical field. This book reviews existing statistical methods to infer the residual life distribution. The review and comparison includes existing inference methods for mean and median, or quantile, residual life analysis through medical data examples. The concept of the residual life is also extended to competing risks analysis. The targeted audience includes biostatisticians, graduate students, and PhD (bio)statisticians. Knowledge in survival analysis at an introductory graduate level is advisable prior to reading this book.
Nonparametric Bayesian inference in biostatistics
Müller, Peter
2015-01-01
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...
Statistical inference a short course
Panik, Michael J
2012-01-01
A concise, easily accessible introduction to descriptive and inferential techniques Statistical Inference: A Short Course offers a concise presentation of the essentials of basic statistics for readers seeking to acquire a working knowledge of statistical concepts, measures, and procedures. The author conducts tests on the assumption of randomness and normality, provides nonparametric methods when parametric approaches might not work. The book also explores how to determine a confidence interval for a population median while also providing coverage of ratio estimation, randomness, and causal
On Quantum Statistical Inference, II
Barndorff-Nielsen, O. E.; Gill, R. D.; Jupp, P. E.
2003-01-01
Interest in problems of statistical inference connected to measurements of quantum systems has recently increased substantially, in step with dramatic new developments in experimental techniques for studying small quantum systems. Furthermore, theoretical developments in the theory of quantum measurements have brought the basic mathematical framework for the probability calculations much closer to that of classical probability theory. The present paper reviews this field and proposes and inte...
Nonparametric predictive inference in reliability
International Nuclear Information System (INIS)
Coolen, F.P.A.; Coolen-Schrijner, P.; Yan, K.J.
2002-01-01
We introduce a recently developed statistical approach, called nonparametric predictive inference (NPI), to reliability. Bounds for the survival function for a future observation are presented. We illustrate how NPI can deal with right-censored data, and discuss aspects of competing risks. We present possible applications of NPI for Bernoulli data, and we briefly outline applications of NPI for replacement decisions. The emphasis is on introduction and illustration of NPI in reliability contexts, detailed mathematical justifications are presented elsewhere
Variational inference & deep learning : A new synthesis
Kingma, D.P.
2017-01-01
In this thesis, Variational Inference and Deep Learning: A New Synthesis, we propose novel solutions to the problems of variational (Bayesian) inference, generative modeling, representation learning, semi-supervised learning, and stochastic optimization.
Variational inference & deep learning: A new synthesis
Kingma, D.P.
2017-01-01
In this thesis, Variational Inference and Deep Learning: A New Synthesis, we propose novel solutions to the problems of variational (Bayesian) inference, generative modeling, representation learning, semi-supervised learning, and stochastic optimization.
Continuous Integrated Invariant Inference, Phase I
National Aeronautics and Space Administration — The proposed project will develop a new technique for invariant inference and embed this and other current invariant inference and checking techniques in an...
Variations on Bayesian Prediction and Inference
2016-05-09
inference 2.2.1 Background There are a number of statistical inference problems that are not generally formulated via a full probability model...problem of inference about an unknown parameter, the Bayesian approach requires a full probability 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND...the problem of inference about an unknown parameter, the Bayesian approach requires a full probability model/likelihood which can be an obstacle
Adaptive Inference on General Graphical Models
Acar, Umut A.; Ihler, Alexander T.; Mettu, Ramgopal; Sumer, Ozgur
2012-01-01
Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform updates to conditional dependencies. The goal of adaptive inference is to take advantage of what is preserved in the model and perform inference more rapidly than from scratch. In this paper, we describe techniques for adaptive inference on general graphs that support marginal computation and updates to the conditional ...
HIV behavioural surveillance among refugees and surrounding host ...
African Journals Online (AJOL)
We used a standardised behavioural surveillance survey (BSS), modified to be directly relevant to populations in conflict and post-conflict settings as well as to their surrounding host populations, to survey the populations of a refugee settlement in south-western Uganda and its surrounding area. Two-stage probability ...
Investigation of the readout electronics of DELPHI surround muon chamber
International Nuclear Information System (INIS)
Khovanskij, N.; Krumshtejn, Z.; Ol'shevskij, A.; Sadovskij, A.; Sedykh, Yu.; Molnar, J.; Sicho, P.; Tomsa, Z.
1995-01-01
The characteristics of the readout electronics of the DELPHI surround muon chambers with various AMPLEX chips (AMPLEX 16 and AMPLEX-SICAL) are presented. This electronics is studied in a cosmic rays test of the real surround muon chamber model. 4 refs., 6 figs., 1 tab
Stimulus size dependence of hue changes induced by chromatic surrounds.
Kellner, Christian Johannes; Wachtler, Thomas
2016-03-01
A chromatic surround induces a change in the perceived hue of a stimulus. This shift in hue depends on the chromatic difference between the stimulus and the surround. We investigated how chromatic induction varies with stimulus size and whether the size dependence depends on the surround hue. Subjects performed asymmetric matching of color stimuli with different sizes in surrounds of different chromaticities. Generally, induced hue shifts decreased with increasing stimulus size. This decrease was quantitatively different for different surround hues. However, when size effects were normalized to an overall induction strength, the chromatic specificity was largely reduced. The separability of inducer chromaticity and stimulus size suggests that these effects are mediated by different neural mechanisms.
Sweller, Naomi; Hayes, Brett K
2010-08-01
Three studies examined how task demands that impact on attention to typical or atypical category features shape the category representations formed through classification learning and inference learning. During training categories were learned via exemplar classification or by inferring missing exemplar features. In the latter condition inferences were made about missing typical features alone (typical feature inference) or about both missing typical and atypical features (mixed feature inference). Classification and mixed feature inference led to the incorporation of typical and atypical features into category representations, with both kinds of features influencing inferences about familiar (Experiments 1 and 2) and novel (Experiment 3) test items. Those in the typical inference condition focused primarily on typical features. Together with formal modelling, these results challenge previous accounts that have characterized inference learning as producing a focus on typical category features. The results show that two different kinds of inference learning are possible and that these are subserved by different kinds of category representations.
Generative inference for cultural evolution.
Kandler, Anne; Powell, Adam
2018-04-05
One of the major challenges in cultural evolution is to understand why and how various forms of social learning are used in human populations, both now and in the past. To date, much of the theoretical work on social learning has been done in isolation of data, and consequently many insights focus on revealing the learning processes or the distributions of cultural variants that are expected to have evolved in human populations. In population genetics, recent methodological advances have allowed a greater understanding of the explicit demographic and/or selection mechanisms that underlie observed allele frequency distributions across the globe, and their change through time. In particular, generative frameworks-often using coalescent-based simulation coupled with approximate Bayesian computation (ABC)-have provided robust inferences on the human past, with no reliance on a priori assumptions of equilibrium. Here, we demonstrate the applicability and utility of generative inference approaches to the field of cultural evolution. The framework advocated here uses observed population-level frequency data directly to establish the likely presence or absence of particular hypothesized learning strategies. In this context, we discuss the problem of equifinality and argue that, in the light of sparse cultural data and the multiplicity of possible social learning processes, the exclusion of those processes inconsistent with the observed data might be the most instructive outcome. Finally, we summarize the findings of generative inference approaches applied to a number of case studies.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'. © 2018 The Author(s).
sick: The Spectroscopic Inference Crank
Casey, Andrew R.
2016-03-01
There exists an inordinate amount of spectral data in both public and private astronomical archives that remain severely under-utilized. The lack of reliable open-source tools for analyzing large volumes of spectra contributes to this situation, which is poised to worsen as large surveys successively release orders of magnitude more spectra. In this article I introduce sick, the spectroscopic inference crank, a flexible and fast Bayesian tool for inferring astrophysical parameters from spectra. sick is agnostic to the wavelength coverage, resolving power, or general data format, allowing any user to easily construct a generative model for their data, regardless of its source. sick can be used to provide a nearest-neighbor estimate of model parameters, a numerically optimized point estimate, or full Markov Chain Monte Carlo sampling of the posterior probability distributions. This generality empowers any astronomer to capitalize on the plethora of published synthetic and observed spectra, and make precise inferences for a host of astrophysical (and nuisance) quantities. Model intensities can be reliably approximated from existing grids of synthetic or observed spectra using linear multi-dimensional interpolation, or a Cannon-based model. Additional phenomena that transform the data (e.g., redshift, rotational broadening, continuum, spectral resolution) are incorporated as free parameters and can be marginalized away. Outlier pixels (e.g., cosmic rays or poorly modeled regimes) can be treated with a Gaussian mixture model, and a noise model is included to account for systematically underestimated variance. Combining these phenomena into a scalar-justified, quantitative model permits precise inferences with credible uncertainties on noisy data. I describe the common model features, the implementation details, and the default behavior, which is balanced to be suitable for most astronomical applications. Using a forward model on low-resolution, high signal
Inferring network structure from cascades
Ghonge, Sushrut; Vural, Dervis Can
2017-07-01
Many physical, biological, and social phenomena can be described by cascades taking place on a network. Often, the activity can be empirically observed, but not the underlying network of interactions. In this paper we offer three topological methods to infer the structure of any directed network given a set of cascade arrival times. Our formulas hold for a very general class of models where the activation probability of a node is a generic function of its degree and the number of its active neighbors. We report high success rates for synthetic and real networks, for several different cascade models.
SICK: THE SPECTROSCOPIC INFERENCE CRANK
Energy Technology Data Exchange (ETDEWEB)
Casey, Andrew R., E-mail: arc@ast.cam.ac.uk [Institute of Astronomy, University of Cambridge, Madingley Road, Cambdridge, CB3 0HA (United Kingdom)
2016-03-15
There exists an inordinate amount of spectral data in both public and private astronomical archives that remain severely under-utilized. The lack of reliable open-source tools for analyzing large volumes of spectra contributes to this situation, which is poised to worsen as large surveys successively release orders of magnitude more spectra. In this article I introduce sick, the spectroscopic inference crank, a flexible and fast Bayesian tool for inferring astrophysical parameters from spectra. sick is agnostic to the wavelength coverage, resolving power, or general data format, allowing any user to easily construct a generative model for their data, regardless of its source. sick can be used to provide a nearest-neighbor estimate of model parameters, a numerically optimized point estimate, or full Markov Chain Monte Carlo sampling of the posterior probability distributions. This generality empowers any astronomer to capitalize on the plethora of published synthetic and observed spectra, and make precise inferences for a host of astrophysical (and nuisance) quantities. Model intensities can be reliably approximated from existing grids of synthetic or observed spectra using linear multi-dimensional interpolation, or a Cannon-based model. Additional phenomena that transform the data (e.g., redshift, rotational broadening, continuum, spectral resolution) are incorporated as free parameters and can be marginalized away. Outlier pixels (e.g., cosmic rays or poorly modeled regimes) can be treated with a Gaussian mixture model, and a noise model is included to account for systematically underestimated variance. Combining these phenomena into a scalar-justified, quantitative model permits precise inferences with credible uncertainties on noisy data. I describe the common model features, the implementation details, and the default behavior, which is balanced to be suitable for most astronomical applications. Using a forward model on low-resolution, high signal
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
2013-01-01
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Inference in hybrid Bayesian networks
International Nuclear Information System (INIS)
Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio
2009-01-01
Since the 1980s, Bayesian networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability techniques (like fault trees and reliability block diagrams). However, limitations in the BNs' calculation engine have prevented BNs from becoming equally popular for domains containing mixtures of both discrete and continuous variables (the so-called hybrid domains). In this paper we focus on these difficulties, and summarize some of the last decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability.
SICK: THE SPECTROSCOPIC INFERENCE CRANK
International Nuclear Information System (INIS)
Casey, Andrew R.
2016-01-01
There exists an inordinate amount of spectral data in both public and private astronomical archives that remain severely under-utilized. The lack of reliable open-source tools for analyzing large volumes of spectra contributes to this situation, which is poised to worsen as large surveys successively release orders of magnitude more spectra. In this article I introduce sick, the spectroscopic inference crank, a flexible and fast Bayesian tool for inferring astrophysical parameters from spectra. sick is agnostic to the wavelength coverage, resolving power, or general data format, allowing any user to easily construct a generative model for their data, regardless of its source. sick can be used to provide a nearest-neighbor estimate of model parameters, a numerically optimized point estimate, or full Markov Chain Monte Carlo sampling of the posterior probability distributions. This generality empowers any astronomer to capitalize on the plethora of published synthetic and observed spectra, and make precise inferences for a host of astrophysical (and nuisance) quantities. Model intensities can be reliably approximated from existing grids of synthetic or observed spectra using linear multi-dimensional interpolation, or a Cannon-based model. Additional phenomena that transform the data (e.g., redshift, rotational broadening, continuum, spectral resolution) are incorporated as free parameters and can be marginalized away. Outlier pixels (e.g., cosmic rays or poorly modeled regimes) can be treated with a Gaussian mixture model, and a noise model is included to account for systematically underestimated variance. Combining these phenomena into a scalar-justified, quantitative model permits precise inferences with credible uncertainties on noisy data. I describe the common model features, the implementation details, and the default behavior, which is balanced to be suitable for most astronomical applications. Using a forward model on low-resolution, high signal
International Nuclear Information System (INIS)
Dai, Z. G.; Wang, J. S.; Yu, Y. W.
2017-01-01
In this paper, we propose a new scenario in which a rapidly rotating strongly magnetized pulsar without any surrounding supernova ejecta repeatedly produces fast radio bursts (FRBs) via a range of possible mechanisms; simultaneously, an ultra-relativistic electron/positron pair wind from the pulsar sweeps up its ambient dense interstellar medium, giving rise to a non-relativistic pulsar wind nebula (PWN). We show that the synchrotron radio emission from such a PWN is bright enough to account for the recently discovered persistent radio source associated with the repeating FRB 121102 within reasonable ranges of the model parameters. Our PWN scenario is consistent with the non-evolution of the dispersion measure inferred from all of the repeating bursts observed in four years.
Energy Technology Data Exchange (ETDEWEB)
Dai, Z. G.; Wang, J. S. [School of Astronomy and Space Science, Nanjing University, Nanjing 210093 (China); Yu, Y. W., E-mail: dzg@nju.edu.cn [Institute of Astrophysics, Central China Normal University, Wuhan 430079 (China)
2017-03-20
In this paper, we propose a new scenario in which a rapidly rotating strongly magnetized pulsar without any surrounding supernova ejecta repeatedly produces fast radio bursts (FRBs) via a range of possible mechanisms; simultaneously, an ultra-relativistic electron/positron pair wind from the pulsar sweeps up its ambient dense interstellar medium, giving rise to a non-relativistic pulsar wind nebula (PWN). We show that the synchrotron radio emission from such a PWN is bright enough to account for the recently discovered persistent radio source associated with the repeating FRB 121102 within reasonable ranges of the model parameters. Our PWN scenario is consistent with the non-evolution of the dispersion measure inferred from all of the repeating bursts observed in four years.
Changes in unique hues induced by chromatic surrounds.
Klauke, Susanne; Wachtler, Thomas
2016-03-01
A chromatic surround can have a strong influence on the perceived hue of a stimulus. We investigated whether chromatic induction has similar effects on the perception of colors that appear pure and unmixed (unique red, green, blue, and yellow) as on other colors. Subjects performed unique hue settings of stimuli in isoluminant surrounds of different chromaticities. Compared with the settings in a neutral gray surround, unique hue settings altered systematically with chromatic surrounds. The amount of induced hue shift depended on the difference between stimulus and surround hues, and was similar for unique hue settings as for settings of nonunique hues. Intraindividual variability in unique hue settings was roughly twice as high as for settings obtained in asymmetric matching experiments, which may reflect the presence of a reference stimulus in the matching task. Variabilities were also larger with chromatic surrounds than with neutral gray surrounds, for both unique hue settings and matching of nonunique hues. The results suggest that the neural representations underlying unique hue percepts are influenced by the same neural processing mechanisms as the percepts of other colors.
Subjective randomness as statistical inference.
Griffiths, Thomas L; Daniels, Dylan; Austerweil, Joseph L; Tenenbaum, Joshua B
2018-06-01
Some events seem more random than others. For example, when tossing a coin, a sequence of eight heads in a row does not seem very random. Where do these intuitions about randomness come from? We argue that subjective randomness can be understood as the result of a statistical inference assessing the evidence that an event provides for having been produced by a random generating process. We show how this account provides a link to previous work relating randomness to algorithmic complexity, in which random events are those that cannot be described by short computer programs. Algorithmic complexity is both incomputable and too general to capture the regularities that people can recognize, but viewing randomness as statistical inference provides two paths to addressing these problems: considering regularities generated by simpler computing machines, and restricting the set of probability distributions that characterize regularity. Building on previous work exploring these different routes to a more restricted notion of randomness, we define strong quantitative models of human randomness judgments that apply not just to binary sequences - which have been the focus of much of the previous work on subjective randomness - but also to binary matrices and spatial clustering. Copyright © 2018 Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Reiman, R.; Bluitt, C.M.
1993-10-01
An aerial radiological survey was conducted over the Vermont Yankee Nuclear Power Station in Vernon, Vermont, during the period August 7 through August 17, 1989. The survey was conducted at an altitude of 300 feet (91 meters) over a 65-square-mile (168-square-kilometer) area centered on the power station. The purpose of the survey was to document the terrestrial gamma radiation environment of the Vermont Yankee Power Station and surrounding area. The results of the aerial survey are reported as inferred gamma radiation exposure rates at 1 meter above ground level in the form of a contour map. Outside the plant boundary, exposure rates were found to vary between 6 and 10 microroentgens per hour (μR/h) and were attributed to naturally occurring uranium, thorium, and radioactive potassium gamma emitters. The aerial data were compared to ground-based open-quotes benchmarkclose quotes exposure rate measurements and radionuclide assays of soil samples obtained within the survey boundary. The ground-based measurements were found to be in good agreement with those inferred from the aerial measuring system
International Nuclear Information System (INIS)
Boyns, P.K.; Bluitt, C.M.
1993-09-01
An aerial radiological survey was conducted over the Yankee Rowe Nuclear Power Station in Rowe, Massachusetts, during the period August 17--24, 1989. The survey was conducted at an altitude of 300 feet (91 meters) over an 87-square-mile (225-square-kilometer) area centered on the power station. The purpose of the survey was to document the terrestrial gamma radiation environment of the Yankee Rowe Power Station and the surrounding area. The results of the aerial survey are reported as inferred gamma radiation exposure rates at 1 meter above ground level in the form of a contour map. Outside the plant boundary, exposure rates were found to vary between 6 and 10 microroentgens per hour (μR/h) and were attributed to naturally-occurring uranium, thorium, and radioactive potassium gamma emitters. The aerial data were compared to ground-based ''benchmark'' exposure rate measurements and radionuclide assays of soil samples obtained within the survey boundary. The ground-based measurements were found to be in good agreement with those inferred from the aerial measuring system
An aerial radiological survey of the Sandia National Laboratories and surrounding area
International Nuclear Information System (INIS)
Riedhauser, S.R.
1994-06-01
A team from the Remote Sensing Laboratory conducted an aerial radiological survey of the area surrounding the Sandia National Laboratories and Kirtland Air Force Base in Albuquerque, New Mexico, during March and April 1993. The survey team measured the terrestrial gamma radiation at the site to determine the levels of natural and man-made radiation. This survey includes the areas covered by a previous survey in 1981. The results of the aerial survey show a background exposure rate which varies between 5 and 18 μR/h plus an approximate 6 μR/h contribution from cosmic rays. The major radioactive isotopes found in this survey were: potassium-40, thallium-208, bismuth-214, and actinium-228, which are all naturally-occurring isotopes, and cobalt-60, cesium-137, and excess amounts of thallium-208 and actinium-228, which are due to human actions in the survey area. In regions away from man-made activity, the exposure rates inferred from this survey's gamma ray measurements agree almost exactly with the exposure rates inferred from the 1981 survey. In addition to the aerial measurements, another survey team conducted in situ and soil sample radiation measurements at three sites within the survey perimeter. These ground-based measurements agree with the aerial measurements within ± 5%
A synchronous surround increases the motion strength gain of motion.
Linares, Daniel; Nishida, Shin'ya
2013-11-12
Coherent motion detection is greatly enhanced by the synchronous presentation of a static surround (Linares, Motoyoshi, & Nishida, 2012). To further understand this contextual enhancement, here we measured the sensitivity to discriminate motion strength for several pedestal strengths with and without a surround. We found that the surround improved discrimination of low and medium motion strengths, but did not improve or even impaired discrimination of high motion strengths. We used motion strength discriminability to estimate the perceptual response function assuming additive noise and found that the surround increased the motion strength gain, rather than the response gain. Given that eye and body movements continuously introduce transients in the retinal image, it is possible that this strength gain occurs in natural vision.
Surrounding Moving Obstacle Detection for Autonomous Driving Using Stereo Vision
Directory of Open Access Journals (Sweden)
Hao Sun
2013-06-01
Full Text Available Detection and tracking surrounding moving obstacles such as vehicles and pedestrians are crucial for the safety of mobile robotics and autonomous vehicles. This is especially the case in urban driving scenarios. This paper presents a novel framework for surrounding moving obstacles detection using binocular stereo vision. The contributions of our work are threefold. Firstly, a multiview feature matching scheme is presented for simultaneous stereo correspondence and motion correspondence searching. Secondly, the multiview geometry constraint derived from the relative camera positions in pairs of consecutive stereo views is exploited for surrounding moving obstacles detection. Thirdly, an adaptive particle filter is proposed for tracking of multiple moving obstacles in surrounding areas. Experimental results from real-world driving sequences demonstrate the effectiveness and robustness of the proposed framework.
Contamination of nebulisers and surrounding air at the bedside of ...
African Journals Online (AJOL)
An air sampler was used to collect air samples from the surrounding bedside environment. .... individualised resealable plastic bags and stored upside down in a cooler .... conventional and mesh technology nebulisers used at home by adults.
Glow phenomenon surrounding the vertical stabilizer and OMS pods
1994-01-01
This 35mm frame, photographed as the Space Shuttle Columbia was orbiting Earth during a 'night' pass, documents the glow phenomenon surrounding the vertical stabilizer and the Orbital Maneuvering System (OMS) pods of the spacecraft.
Monitoring program of surrounding of the NPP SE-EBO
International Nuclear Information System (INIS)
Dobis, L.; Kostial, J.
1997-01-01
The paper dealt with monitoring program of radiation control of surrounding of the NPP Bohunice, which has the aim: (1) to ensure the control of influence of work of the NPP Bohunice on the environment in their surrounding; (2) to ensure the back-ground for regular brief of control and supervisory organs about condition of the environment in surrounding of the NPP Bohunice; (3) to maintain the expected technical level of control of the NPP Bohunice and to exploit optimally the technical means; (4) to solicit permanently the data about the radioactivity of environment in surrounding of the NPP Bohunice for forming of files of the data; (5) to exploit purposefully the technical equipment, technical workers and to maintain their in permanent emergency and technical eligibility for the case of the breakdown; (6) to obtain permanently the files of the values for qualification of the reference levels. This program of monitoring includes the radiation control of surrounding of the NPP Bohunice, in the time of normal work of power-station's blocks, inclusively of all types of trouble-shooting and repairer works in surrounding of the NPP Bohunice, up to distance 20 km from power-station. The monitoring includes: outlets from the NPP Bohunice, monitoring of radiation characteristics in surrounding of the NPP Bohunice, (aerosols, fall-outs, soil), the links of food chains: (grass and fodder, milk, agriculture products), hydrosphere in surrounding (surface waters, drink water, bores of radiation control in complex of the NPP Bohunice, components of the hydrosphere), measurement of radiation from external sources (measurement of the dose rates, measurement of the doses [sk
Chromatic induction from surrounding stimuli under perceptual suppression.
Horiuchi, Koji; Kuriki, Ichiro; Tokunaga, Rumi; Matsumiya, Kazumichi; Shioiri, Satoshi
2014-11-01
The appearance of colors can be affected by their spatiotemporal context. The shift in color appearance according to the surrounding colors is called color induction or chromatic induction; in particular, the shift in opponent color of the surround is called chromatic contrast. To investigate whether chromatic induction occurs even when the chromatic surround is imperceptible, we measured chromatic induction during interocular suppression. A multicolor or uniform color field was presented as the surround stimulus, and a colored continuous flash suppression (CFS) stimulus was presented to the dominant eye of each subject. The subjects were asked to report the appearance of the test field only when the stationary surround stimulus is invisible by interocular suppression with CFS. The resulting shifts in color appearance due to chromatic induction were significant even under the conditions of interocular suppression for all surround stimuli. The magnitude of chromatic induction differed with the surround conditions, and this difference was preserved regardless of the viewing conditions. The chromatic induction effect was reduced by CFS, in proportion to the magnitude of chromatic induction under natural (i.e., no-CFS) viewing conditions. According to an analysis with linear model fitting, we revealed the presence of at least two kinds of subprocesses for chromatic induction that reside at higher and lower levels than the site of interocular suppression. One mechanism yields different degrees of chromatic induction based on the complexity of the surround, which is unaffected by interocular suppression, while the other mechanism changes its output with interocular suppression acting as a gain control. Our results imply that the total chromatic induction effect is achieved via a linear summation of outputs from mechanisms that reside at different levels of visual processing.
Lower complexity bounds for lifted inference
DEFF Research Database (Denmark)
Jaeger, Manfred
2015-01-01
instances of the model. Numerous approaches for such “lifted inference” techniques have been proposed. While it has been demonstrated that these techniques will lead to significantly more efficient inference on some specific models, there are only very recent and still quite restricted results that show...... the feasibility of lifted inference on certain syntactically defined classes of models. Lower complexity bounds that imply some limitations for the feasibility of lifted inference on more expressive model classes were established earlier in Jaeger (2000; Jaeger, M. 2000. On the complexity of inference about...... that under the assumption that NETIME≠ETIME, there is no polynomial lifted inference algorithm for knowledge bases of weighted, quantifier-, and function-free formulas. Further strengthening earlier results, this is also shown to hold for approximate inference and for knowledge bases not containing...
An aerial radiological survey of the Ames Laboratory and surrounding area, Ames, Iowa
International Nuclear Information System (INIS)
Maurer, R.J.
1993-04-01
An aerial radiological survey of the Ames Laboratory and surrounding area in Ames, Iowa, was conducted during the period July 15--25, 1991. The purpose of the survey was to measure and document the terrestrial radiological environment at the Ames Laboratory and the surrounding area for use in effective environmental management and emergency response planning. The aerial survey was flown at an altitude of 200 feet (61 meters) along a series of parallel lines 350 feet (107 meters) apart. The survey encompassed an area of 36 square miles (93 square kilometers) and included the city of Ames, Iowa, and the Iowa State University. The results are reported as exposure rates at 1 meter above ground level (inferred from the aerial data) in the form of a gamma radiation contour map. Typical background exposure rates were found to vary from 7 to 9 microroentgens per hour (μR/h). No anomalous radiation levels were detected at the Ames Laboratory. However, one anomalous radiation source was detected at an industrial storage yard in the city of Ames. In support of the aerial survey, ground-based exposure rate and soil sample measurements were obtained at several sites within the survey perimeter. The results of the aerial and ground-based measurements were found to agree within the expected uncertainty of ±15%
International Nuclear Information System (INIS)
1992-11-01
An aerial radiological survey of the Paducah Gaseous Diffusion Plant (PGDP) and surrounding area in Paducah, Kentucky, was conducted during May 15--25, 1990. The purpose of the survey was to measure and document the terrestrial radiological environment at the PGDP and surrounding area for use in effective environmental management and emergency response planning. The aerial survey was flown at an altitude of 61 meters (200 feet) along a series of parallel lines 107 meters (350 feet) apart. The survey encompassed an area of 62 square kilometers (24 square miles), bordered on the north by the Ohio River. The results of the aerial survey are reported as inferred exposure rates at 1 meter above ground level in the form of a gamma radiation contour map. Typical background exposure rates were found to vary from 5 to 12 microroentgens per hour (μR/h). Protactinium-234m, a radioisotope indicative of uranium-238, was detected at several facilities at the PGDR. In support of the aerial survey, ground-based exposure rate and soil sample measurements were obtained at several sites within the survey perimeter. The results of the aerial and ground-based measurements were found to agree within ±15%
Statistical inference for financial engineering
Taniguchi, Masanobu; Ogata, Hiroaki; Taniai, Hiroyuki
2014-01-01
This monograph provides the fundamentals of statistical inference for financial engineering and covers some selected methods suitable for analyzing financial time series data. In order to describe the actual financial data, various stochastic processes, e.g. non-Gaussian linear processes, non-linear processes, long-memory processes, locally stationary processes etc. are introduced and their optimal estimation is considered as well. This book also includes several statistical approaches, e.g., discriminant analysis, the empirical likelihood method, control variate method, quantile regression, realized volatility etc., which have been recently developed and are considered to be powerful tools for analyzing the financial data, establishing a new bridge between time series and financial engineering. This book is well suited as a professional reference book on finance, statistics and statistical financial engineering. Readers are expected to have an undergraduate-level knowledge of statistics.
Type inference for correspondence types
DEFF Research Database (Denmark)
Hüttel, Hans; Gordon, Andy; Hansen, Rene Rydhof
2009-01-01
We present a correspondence type/effect system for authenticity in a π-calculus with polarized channels, dependent pair types and effect terms and show how one may, given a process P and an a priori type environment E, generate constraints that are formulae in the Alternating Least Fixed......-Point (ALFP) logic. We then show how a reasonable model of the generated constraints yields a type/effect assignment such that P becomes well-typed with respect to E if and only if this is possible. The formulae generated satisfy a finite model property; a system of constraints is satisfiable if and only...... if it has a finite model. As a consequence, we obtain the result that type/effect inference in our system is polynomial-time decidable....
Causal inference in public health.
Glass, Thomas A; Goodman, Steven N; Hernán, Miguel A; Samet, Jonathan M
2013-01-01
Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action's consequences rather than the less precise notion of a risk factor's causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world.
Inference Attacks and Control on Database Structures
Directory of Open Access Journals (Sweden)
Muhamed Turkanovic
2015-02-01
Full Text Available Today’s databases store information with sensitivity levels that range from public to highly sensitive, hence ensuring confidentiality can be highly important, but also requires costly control. This paper focuses on the inference problem on different database structures. It presents possible treats on privacy with relation to the inference, and control methods for mitigating these treats. The paper shows that using only access control, without any inference control is inadequate, since these models are unable to protect against indirect data access. Furthermore, it covers new inference problems which rise from the dimensions of new technologies like XML, semantics, etc.
Directory of Open Access Journals (Sweden)
Paula Eveline Ribeiro D’Anunciação
2013-01-01
Full Text Available In recent years, there has been increasing interest in matrix-type influence on forest fragments. Terrestrial amphibians are good bioindicators for this kind of research because of low vagility and high philopatry. This study compared richness, abundance, and species composition of terrestrial amphibians through pitfall traps in two sets of semideciduous seasonal forest fragments in southeastern Brazil, according to the predominant surrounding matrix (sugar cane and pasture. There were no differences in richness, but fragments surrounded by sugar cane had the lowest abundance of amphibians, whereas fragments surrounded by pastures had greater abundance. The most abundant species, Rhinella ornata, showed no biometric differences between fragment groups but like many other amphibians sampled showed very low numbers of individuals in fragments dominated by sugar cane fields. Our data indicate that the sugar cane matrix negatively influences the community of amphibians present in fragments surrounded by this type of land use.
A descriptivist approach to trait conceptualization and inference.
Jonas, Katherine G; Markon, Kristian E
2016-01-01
In their recent article, How Functionalist and Process Approaches to Behavior Can Explain Trait Covariation, Wood, Gardner, and Harms (2015) underscore the need for more process-based understandings of individual differences. At the same time, the article illustrates a common error in the use and interpretation of latent variable models: namely, the misuse of models to arbitrate issues of causation and the nature of latent variables. Here, we explain how latent variables can be understood simply as parsimonious summaries of data, and how statistical inference can be based on choosing those summaries that minimize information required to represent the data using the model. Although Wood, Gardner, and Harms acknowledge this perspective, they underestimate its significance, including its importance to modeling and the conceptualization of psychological measurement. We believe this perspective has important implications for understanding individual differences in a number of domains, including current debates surrounding the role of formative versus reflective latent variables. (c) 2015 APA, all rights reserved).
LAIT: a local ancestry inference toolkit.
Hui, Daniel; Fang, Zhou; Lin, Jerome; Duan, Qing; Li, Yun; Hu, Ming; Chen, Wei
2017-09-06
Inferring local ancestry in individuals of mixed ancestry has many applications, most notably in identifying disease-susceptible loci that vary among different ethnic groups. Many software packages are available for inferring local ancestry in admixed individuals. However, most of these existing software packages require specific formatted input files and generate output files in various types, yielding practical inconvenience. We developed a tool set, Local Ancestry Inference Toolkit (LAIT), which can convert standardized files into software-specific input file formats as well as standardize and summarize inference results for four popular local ancestry inference software: HAPMIX, LAMP, LAMP-LD, and ELAI. We tested LAIT using both simulated and real data sets and demonstrated that LAIT provides convenience to run multiple local ancestry inference software. In addition, we evaluated the performance of local ancestry software among different supported software packages, mainly focusing on inference accuracy and computational resources used. We provided a toolkit to facilitate the use of local ancestry inference software, especially for users with limited bioinformatics background.
Forward and backward inference in spatial cognition.
Directory of Open Access Journals (Sweden)
Will D Penny
Full Text Available This paper shows that the various computations underlying spatial cognition can be implemented using statistical inference in a single probabilistic model. Inference is implemented using a common set of 'lower-level' computations involving forward and backward inference over time. For example, to estimate where you are in a known environment, forward inference is used to optimally combine location estimates from path integration with those from sensory input. To decide which way to turn to reach a goal, forward inference is used to compute the likelihood of reaching that goal under each option. To work out which environment you are in, forward inference is used to compute the likelihood of sensory observations under the different hypotheses. For reaching sensory goals that require a chaining together of decisions, forward inference can be used to compute a state trajectory that will lead to that goal, and backward inference to refine the route and estimate control signals that produce the required trajectory. We propose that these computations are reflected in recent findings of pattern replay in the mammalian brain. Specifically, that theta sequences reflect decision making, theta flickering reflects model selection, and remote replay reflects route and motor planning. We also propose a mapping of the above computational processes onto lateral and medial entorhinal cortex and hippocampus.
Generative Inferences Based on Learned Relations
Chen, Dawn; Lu, Hongjing; Holyoak, Keith J.
2017-01-01
A key property of relational representations is their "generativity": From partial descriptions of relations between entities, additional inferences can be drawn about other entities. A major theoretical challenge is to demonstrate how the capacity to make generative inferences could arise as a result of learning relations from…
Inference in models with adaptive learning
Chevillon, G.; Massmann, M.; Mavroeidis, S.
2010-01-01
Identification of structural parameters in models with adaptive learning can be weak, causing standard inference procedures to become unreliable. Learning also induces persistent dynamics, and this makes the distribution of estimators and test statistics non-standard. Valid inference can be
Fiducial inference - A Neyman-Pearson interpretation
Salome, D; VonderLinden, W; Dose,; Fischer, R; Preuss, R
1999-01-01
Fisher's fiducial argument is a tool for deriving inferences in the form of a probability distribution on the parameter space, not based on Bayes's Theorem. Lindley established that in exceptional situations fiducial inferences coincide with posterior distributions; in the other situations fiducial
Uncertainty in prediction and in inference
Hilgevoord, J.; Uffink, J.
1991-01-01
The concepts of uncertainty in prediction and inference are introduced and illustrated using the diffraction of light as an example. The close re-lationship between the concepts of uncertainty in inference and resolving power is noted. A general quantitative measure of uncertainty in
Causal inference in economics and marketing.
Varian, Hal R
2016-07-05
This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference.
Nonparametric predictive inference in statistical process control
Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.
2000-01-01
New methods for statistical process control are presented, where the inferences have a nonparametric predictive nature. We consider several problems in process control in terms of uncertainties about future observable random quantities, and we develop inferences for these random quantities hased on
The Impact of Disablers on Predictive Inference
Cummins, Denise Dellarosa
2014-01-01
People consider alternative causes when deciding whether a cause is responsible for an effect (diagnostic inference) but appear to neglect them when deciding whether an effect will occur (predictive inference). Five experiments were conducted to test a 2-part explanation of this phenomenon: namely, (a) that people interpret standard predictive…
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Darwiche, Adnan; Chavira, Mark
2006-01-01
We describe in this paper a system for exact inference with relational Bayesian networks as defined in the publicly available PRIMULA tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference...
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Chavira, Mark; Darwiche, Adnan
2004-01-01
We describe a system for exact inference with relational Bayesian networks as defined in the publicly available \\primula\\ tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference by evaluating...
Placental vascular responses are dependent on surrounding tissue
DEFF Research Database (Denmark)
Brøgger, Torbjørn Halle
-depth understanding of the mechanism regulating blood flow and perfusion is necessary if we are to come up with new ideas for intervention and treatment. Method: From fresh born placentas stem villi arteries were carefully dissected. The artery branches were divided. The surrounding tissue was removed from one end...... and was left untouched in the other end. Then using wire myography they were investigated in terms of contractility and sensitivity to physiological relevant human-like agonists. Results: Sensitivity to PGF2α, Tx-analog, 5-HT and endothelin-1 was significantly lower in arteries with intact surrounding tissue...... compared to arteries stripped of the tissue. The maximal force development was also significantly lower in arteries with surrounding tissue, when they were depolarized high extracellular [K+] or stimulated with PGF2α or endotheline-1. Conclusion: The perivascular tissue significantly alters stem villi...
Placental vascular responses are dependent on surrounding tissue
DEFF Research Database (Denmark)
Brøgger, Torbjørn Halle
. Materials and methods. From fresh born placentas, stem villi arteries were carefully dissected. The artery branches were divided. The surrounding tissue was removed from one end and was left untouched in the other end.Then, using wire myography, they were investigated in terms of contractility...... and sensitivity to physiological relevant human-like agonists. Results. Sensitivity to PGF2α, Tx-analog, 5-HT and endothelin-1 was significantly lower in arteries with intact surrounding tissue compared to arteries stripped of the tissue. The maximal force development was also significantly lower in arteries...... with surrounding tissue when they were depolarized high extracellular [K+] or stimulated with PGF2α or endotheline-1. Conclusion. The perivascular tissue significantly alters stem villi arteries' sensitivity and force development in a suppressive way. This implicates a new aspect of blood flow regulation...
Surrounding rock stress analysis of underground high level waste repository
International Nuclear Information System (INIS)
Liu Wengang; Wang Ju; Wang Guangdi
2006-01-01
During decay of nuclear waste, enormous energy was released, which results in temperature change of surrounding rock of depository. Thermal stress was produced because thermal expansion of rock was controlled. Internal structure of surrounding rock was damaged and strength of rock was weakened. So, variation of stress was a dynamic process with the variation of temperature. BeiShan region of Gansu province was determined to be the depository field in the future, it is essential to make research on granite in this region. In the process of experiment, basic physical parameters of granite were analyzed preliminary with MTS. Long range temperature and stress filed was simulated considering the damage effect of surrounding rock, and rules of temperature and stress was achieved. (authors)
Extended likelihood inference in reliability
International Nuclear Information System (INIS)
Martz, H.F. Jr.; Beckman, R.J.; Waller, R.A.
1978-10-01
Extended likelihood methods of inference are developed in which subjective information in the form of a prior distribution is combined with sampling results by means of an extended likelihood function. The extended likelihood function is standardized for use in obtaining extended likelihood intervals. Extended likelihood intervals are derived for the mean of a normal distribution with known variance, the failure-rate of an exponential distribution, and the parameter of a binomial distribution. Extended second-order likelihood methods are developed and used to solve several prediction problems associated with the exponential and binomial distributions. In particular, such quantities as the next failure-time, the number of failures in a given time period, and the time required to observe a given number of failures are predicted for the exponential model with a gamma prior distribution on the failure-rate. In addition, six types of life testing experiments are considered. For the binomial model with a beta prior distribution on the probability of nonsurvival, methods are obtained for predicting the number of nonsurvivors in a given sample size and for predicting the required sample size for observing a specified number of nonsurvivors. Examples illustrate each of the methods developed. Finally, comparisons are made with Bayesian intervals in those cases where these are known to exist
Reinforcement learning or active inference?
Friston, Karl J; Daunizeau, Jean; Kiebel, Stefan J
2009-07-29
This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain.
Reinforcement learning or active inference?
Directory of Open Access Journals (Sweden)
Karl J Friston
2009-07-01
Full Text Available This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain.
Active inference and epistemic value.
Friston, Karl; Rigoli, Francesco; Ognibene, Dimitri; Mathys, Christoph; Fitzgerald, Thomas; Pezzulo, Giovanni
2015-01-01
We offer a formal treatment of choice behavior based on the premise that agents minimize the expected free energy of future outcomes. Crucially, the negative free energy or quality of a policy can be decomposed into extrinsic and epistemic (or intrinsic) value. Minimizing expected free energy is therefore equivalent to maximizing extrinsic value or expected utility (defined in terms of prior preferences or goals), while maximizing information gain or intrinsic value (or reducing uncertainty about the causes of valuable outcomes). The resulting scheme resolves the exploration-exploitation dilemma: Epistemic value is maximized until there is no further information gain, after which exploitation is assured through maximization of extrinsic value. This is formally consistent with the Infomax principle, generalizing formulations of active vision based upon salience (Bayesian surprise) and optimal decisions based on expected utility and risk-sensitive (Kullback-Leibler) control. Furthermore, as with previous active inference formulations of discrete (Markovian) problems, ad hoc softmax parameters become the expected (Bayes-optimal) precision of beliefs about, or confidence in, policies. This article focuses on the basic theory, illustrating the ideas with simulations. A key aspect of these simulations is the similarity between precision updates and dopaminergic discharges observed in conditioning paradigms.
Ancient Biomolecules and Evolutionary Inference.
Cappellini, Enrico; Prohaska, Ana; Racimo, Fernando; Welker, Frido; Pedersen, Mikkel Winther; Allentoft, Morten E; de Barros Damgaard, Peter; Gutenbrunner, Petra; Dunne, Julie; Hammann, Simon; Roffet-Salque, Mélanie; Ilardo, Melissa; Moreno-Mayar, J Víctor; Wang, Yucheng; Sikora, Martin; Vinner, Lasse; Cox, Jürgen; Evershed, Richard P; Willerslev, Eske
2018-04-25
Over the last decade, studies of ancient biomolecules-particularly ancient DNA, proteins, and lipids-have revolutionized our understanding of evolutionary history. Though initially fraught with many challenges, the field now stands on firm foundations. Researchers now successfully retrieve nucleotide and amino acid sequences, as well as lipid signatures, from progressively older samples, originating from geographic areas and depositional environments that, until recently, were regarded as hostile to long-term preservation of biomolecules. Sampling frequencies and the spatial and temporal scope of studies have also increased markedly, and with them the size and quality of the data sets generated. This progress has been made possible by continuous technical innovations in analytical methods, enhanced criteria for the selection of ancient samples, integrated experimental methods, and advanced computational approaches. Here, we discuss the history and current state of ancient biomolecule research, its applications to evolutionary inference, and future directions for this young and exciting field. Expected final online publication date for the Annual Review of Biochemistry Volume 87 is June 20, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Bayesian Inference Methods for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand
2013-01-01
This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development...... of Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation...... analysis of the complex prior representation, where we show that the ability to induce sparse estimates of a given prior heavily depends on the inference method used and, interestingly, whether real or complex variables are inferred. We also show that the Bayesian estimators derived from the proposed...
EI: A Program for Ecological Inference
Directory of Open Access Journals (Sweden)
Gary King
2004-09-01
Full Text Available The program EI provides a method of inferring individual behavior from aggregate data. It implements the statistical procedures, diagnostics, and graphics from the book A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data (King 1997. Ecological inference, as traditionally defined, is the process of using aggregate (i.e., "ecological" data to infer discrete individual-level relationships of interest when individual-level data are not available. Ecological inferences are required in political science research when individual-level surveys are unavailable (e.g., local or comparative electoral politics, unreliable (racial politics, insufficient (political geography, or infeasible (political history. They are also required in numerous areas of ma jor significance in public policy (e.g., for applying the Voting Rights Act and other academic disciplines ranging from epidemiology and marketing to sociology and quantitative history.
Ornitocenosis of the Sursky pond and its close the surroundings
International Nuclear Information System (INIS)
Lacko, J.; Ambrus, B.; Fupso, A.
2013-01-01
The paper focuses on the qualitative-quantitative research of fishpond bird community of the Sursky and its surroundings as well as on analysis of seasonal population dynamics of the avifauna as well as on placing the determined species into environmental groups and guilds. Another object is the comparison of our results with recent work focused on research of bird communities on this site.
Review of Ordered Anarchy: Jasay and his Surroundings
Directory of Open Access Journals (Sweden)
Aschwin de Wolf
2009-02-01
Full Text Available Anthony de Jasay is among the most important social thinkers of our time. His oeuvre offers a sustained critique of government and its defenders. In the book Ordered Anarchy: Jasay and His Surroundings, colleagues and friends pay tribute to the man in the form of an inspiring collection of essays.
Neutron spectrum in small iron pile surrounded by lead reflector
International Nuclear Information System (INIS)
Kimura, Itsuro; Hayashi, S.A.; Kobayashi, Katsuhei; Matsumura, Tetsuo; Nishihara, Hiroshi.
1978-01-01
In order to save the quantity of sample material, a possibility to assess group constants of a reactor material through measurement and analysis of neutron spectrum in a small sample pile surrounded by a reflector of heavy moderator, was investigated. As the sample and the reflector, we chose iron and lead, respectively. Although the time dispersion in moderation of neutrons was considerably prolonged by the lead reflector, this hardly interferes with the assessment of group constants. Theoretical calculation revealed that both the neutron flux spectrum and the sensitivity coefficient of group constants in an iron sphere, 35 cm in diameter surrounded by the lead reflector, 25 cm thick, were close to those of the bare iron sphere, 108 cm in diameter. The neutron spectra in a small iron pile surrounded by a lead reflector were experimentally obtained by the time-of-flight method with an electron linear accelerator and the result was compared with the predicted values. It could be confirmed that a small sample pile surrounded by a reflector, such as lead, was as useful as a much larger bulk pile for the assessment of group constants of a reactor material. (auth.)
Linking disadvantaged housing areas to the surrounding city
DEFF Research Database (Denmark)
Stender, Marie
Several disadvantaged social housing areas in Denmark are currently undergo-ing thorough physical refurbishments, aiming to integrate them better with the surrounding city. The ambition is to attract new users and residents by opening up the borders of the area and establish attractive, new...
Ecological mechanisms linking protected areas to surrounding lands.
Hansen, Andrew J; DeFries, Ruth
2007-06-01
Land use is expanding and intensifying in the unprotected lands surrounding many of the world's protected areas. The influence of this land use change on ecological processes is poorly understood. The goal of this paper is to draw on ecological theory to provide a synthetic framework for understanding how land use change around protected areas may alter ecological processes and biodiversity within protected areas and to provide a basis for identifying scientifically based management alternatives. We first present a conceptual model of protected areas embedded within larger ecosystems that often include surrounding human land use. Drawing on case studies in this Invited Feature, we then explore a comprehensive set of ecological mechanisms by which land use on surrounding lands may influence ecological processes and biodiversity within reserves. These mechanisms involve changes in ecosystem size, with implications for minimum dynamic area, species-area effect, and trophic structure; altered flows of materials and disturbances into and out of reserves; effects on crucial habitats for seasonal and migration movements and population source/sink dynamics; and exposure to humans through hunting, poaching, exotics species, and disease. These ecological mechanisms provide a basis for assessing the vulnerability of protected areas to land use. They also suggest criteria for designing regional management to sustain protected areas in the context of surrounding human land use. These design criteria include maximizing the area of functional habitats, identifying and maintaining ecological process zones, maintaining key migration and source habitats, and managing human proximity and edge effects.
The bird species of pandam wildlife park and the surrounding ...
African Journals Online (AJOL)
The effect of time of day as well as vegetation variables on bird species diversity in the park and surrounding farmlands was also conducted. 10 transects in each study site were surveyed twice between during the dry season and vegetation variables (trees, fingers, finger-rings two- hand, grazing, farming, canopy cover, ...
Experiences during the decontamination process of areas surrounding to Fukushima
International Nuclear Information System (INIS)
Molina, G.
2014-10-01
In this work the experience gained during the decontamination of areas surrounding to Fukushima NPP, rugged during the earthquake and tsunami in 2011 and caused the contamination with fission products in these areas is described. Actions taken by the Japanese government are reported and some of the techniques used, the intervention levels and the progress made and disposal techniques considered are presented. (Author)
Traditional Indian customs surrounding birth A review | Chalmers ...
African Journals Online (AJOL)
Since 1960, only a few studies have been made of traditional custOIns surrounding birth in Indian culture. Very few of these have described customs followed by Indians in South Africa. A review of these publications is presented here. Customs described include religious, social and psychological aspects of behaviour in ...
Vasculature surrounding a nodule: A novel lung cancer biomarker.
Wang, Xiaohua; Leader, Joseph K; Wang, Renwei; Wilson, David; Herman, James; Yuan, Jian-Min; Pu, Jiantao
2017-12-01
To investigate whether the vessels surrounding a nodule depicted on non-contrast, low-dose computed tomography (LDCT) can discriminate benign and malignant screen detected nodules. We collected a dataset consisting of LDCT scans acquired on 100 subjects from the Pittsburgh Lung Screening study (PLuSS). Fifty subjects were diagnosed with lung cancer and 50 subjects had suspicious nodules later proven benign. For the lung cancer cases, the location of the malignant nodule in the LDCT scans was known; while for the benign cases, the largest nodule in the LDCT scan was used in the analysis. A computer algorithm was developed to identify surrounding vessels and quantify the number and volume of vessels that were connected or near the nodule. A nonparametric receiver operating characteristic (ROC) analysis was performed based on a single nodule per subject to assess the discriminability of the surrounding vessels to provide a lung cancer diagnosis. Odds ratio (OR) were computed to determine the probability of a nodule being lung cancer based on the vessel features. The areas under the ROC curves (AUCs) for vessel count and vessel volume were 0.722 (95% CI=0.616-0.811, plung cancer group 9.7 (±9.6) compared to the non-lung cancer group 4.0 (±4.3) CONCLUSION: Our preliminary results showed that malignant nodules are often surrounded by more vessels compared to benign nodules, suggesting that the surrounding vessel characteristics could serve as lung cancer biomarker for indeterminate nodules detected during LDCT lung cancer screening using only the information collected during the initial visit. Copyright © 2017 Elsevier B.V. All rights reserved.
Statistical inference an integrated Bayesianlikelihood approach
Aitkin, Murray
2010-01-01
Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian treatment of parameter inference and model comparisons that can be used with simple diffuse prior specifications. This novel approach provides new solutions to difficult model comparison problems and offers direct Bayesian counterparts of frequentist t-tests and other standard statistical methods for hypothesis testing.After an overview of the competing theories of statistical inference, the book introduces the Bayes/likelihood approach used throughout. It pre
International Nuclear Information System (INIS)
Colton, D.P.
1983-08-01
An aerial radiological survey was performed over the area surrounding the Three Mile Island Nuclear Station during October 26 to 30, 1982. The survey covered an 82-square-kilometer area centered on the nuclear plant and encompassed the communities of Middletown, York Haven, Goldsboro and Royalton, Pennsylvania. The highest radiation exposure rates, up to a maximum of 200 microroentgens per hour (μR/h), were inferred from data measured directly over the TMI facilities. This detected radiation was due to the presence of cobalt-58, cobalt-60 and cesium-137, which was consistent with normal plant operations. Similar activity is routinely observed in aerial surveys over nuclear power plants which have been or are presently in an operational mode. For the remainder of the survey area, the inferred radiation exposure rates varied from 6 to 14 μR/h. The reported exposure rate values include an estimated cosmic ray contribution of 3.7 μR/h. Ground-based measurements, conducted during the time of the aerial survey, were compared to the aerial results. Pressurized ionization chamber readings and a group of soil samples were acquired at several locations within the survey area, along the river banks upstream and downstream of the survey area, and at the ground-based locations used for a previous aerial survey which was conducted in 1976. The exposure rate values obtained from these measurements were in agreement with the corresponding aerial data. With the exception of the activity observed within the TMI facilities, no evidence of any contamination which might have occurred as a result of past reactor operations or the 1979 TMI Unit 2 accident was detected from the aerial survey data. This was further supported by the results of the soil sample analyses and the comparison with the 1976 aerial survey data. 7 references, 12 figures, 4 tables
Inferring Domain Plans in Question-Answering
National Research Council Canada - National Science Library
Pollack, Martha E
1986-01-01
The importance of plan inference in models of conversation has been widely noted in the computational-linguistics literature, and its incorporation in question-answering systems has enabled a range...
Scalable inference for stochastic block models
Peng, Chengbin; Zhang, Zhihua; Wong, Ka-Chun; Zhang, Xiangliang; Keyes, David E.
2017-01-01
Community detection in graphs is widely used in social and biological networks, and the stochastic block model is a powerful probabilistic tool for describing graphs with community structures. However, in the era of "big data," traditional inference
Efficient algorithms for conditional independence inference
Czech Academy of Sciences Publication Activity Database
Bouckaert, R.; Hemmecke, R.; Lindner, S.; Studený, Milan
2010-01-01
Roč. 11, č. 1 (2010), s. 3453-3479 ISSN 1532-4435 R&D Projects: GA ČR GA201/08/0539; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : conditional independence inference * linear programming approach Subject RIV: BA - General Mathematics Impact factor: 2.949, year: 2010 http://library.utia.cas.cz/separaty/2010/MTR/studeny-efficient algorithms for conditional independence inference.pdf
Yang, Chengsheng; Lu, Zhong; Zhang, Qin; Zhao, Chaoying; Peng, Jianbing; Ji, Lingyun
2018-05-01
The Longyao ground fissure (LGF) is the longest and most active among more than 1000 ground fissures on the North China Plain. There have been many studies on the formation mechanism of the LGF, due to its scientific importance and its potential for damage to the environment. These studies have been based on both regional tectonic analysis and numerical simulations. In order to provide a better understanding of the formation mechanism, the deformation of the crack and its surrounding environment should be taken into consideration. In this paper, PS-InSAR technology was employed to assess the ground deformation of LGF and its surrounding area, using L-band ALOS-1 PALSAR images from 2007 to 2011. The characteristics of ground deformation, relationships between fissure activity and surrounding faults and groundwater exploitation were analyzed. This study shows that the north side of Longyao fault (LF) is uplifting while the south side is subsiding. This provides the tectonic conditions responsible for the activity of the ground fissure. Local groundwater exploitation also plays an important role in the development of ground fissures. InSAR observations were modeled to infer the loading depth (-2.8 km) and the slip rate (31.1 mm/yr) of LF.
Ultrastructural relationship of the phagophore with surrounding organelles.
Biazik, Joanna; Ylä-Anttila, Päivi; Vihinen, Helena; Jokitalo, Eija; Eskelinen, Eeva-Liisa
2015-01-01
Phagophore nucleates from a subdomain of the endoplasmic reticulum (ER) termed the omegasome and also makes contact with other organelles such as mitochondria, Golgi complex, plasma membrane and recycling endosomes during its formation. We have used serial block face scanning electron microscopy (SB-EM) and electron tomography (ET) to image phagophore biogenesis in 3 dimensions and to determine the relationship between the phagophore and surrounding organelles at high resolution. ET was performed to confirm whether membrane contact sites (MCSs) are evident between the phagophore and those surrounding organelles. In addition to the known contacts with the ER, we identified MCSs between the phagophore and membranes from putative ER exit sites, late endosomes or lysosomes, the Golgi complex and mitochondria. We also show that one phagophore can have simultaneous MCSs with more than one organelle. Future membrane flux experiments are needed to determine whether membrane contacts also signify lipid translocation.
Trajectories and Maneuvers of Surrounding Vehicles with Panoramic Camera Arrays
DEFF Research Database (Denmark)
Dueholm, Jacob Velling; Kristoffersen, Miklas Strøm; Satzoda, Ravi K.
2016-01-01
Vision-based research for intelligent vehicles have traditionally focused on specific regions around a vehicle, such as a front looking camera for, e.g., lane estimation. Traffic scenes are complex and vital information could be lost in unobserved regions. This paper proposes a framework that uses...... four visual sensors for a full surround view of a vehicle in order to achieve an understanding of surrounding vehicle behaviors. The framework will assist the analysis of naturalistic driving studies by automating the task of data reduction of the observed trajectories. To this end, trajectories...... are estimated using a vehicle detector together with a multiperspective optimized tracker in each view. The trajectories are transformed to a common ground plane, where they are associated between perspectives and analyzed to reveal tendencies around the ego-vehicle. The system is tested on sequences from 2.5 h...
Mechanical Characteristics Analysis of Surrounding Rock on Anchor Bar Reinforcement
Gu, Shuan-cheng; Zhou, Pan; Huang, Rong-bin
2018-03-01
Through the homogenization method, the composite of rock and anchor bar is considered as the equivalent material of continuous, homogeneous, isotropic and strength parameter enhancement, which is defined as reinforcement body. On the basis of elasticity, the composite and the reinforcement are analyzed, Based on strengthening theory of surrounding rock and displacement equivalent conditions, the expression of reinforcement body strength parameters and mechanical parameters is deduced. The example calculation shows that the theoretical results are close to the results of the Jia-mei Gao[9], however, closer to the results of FLAC3D numerical simulation, it is proved that the model and surrounding rock reinforcement body theory are reasonable. the model is easy to analyze and calculate, provides a new way for determining reasonable bolt support parameters, can also provides reference for the stability analysis of underground cavern bolting support.
On the criticality of inferred models
Mastromatteo, Iacopo; Marsili, Matteo
2011-10-01
Advanced inference techniques allow one to reconstruct a pattern of interaction from high dimensional data sets, from probing simultaneously thousands of units of extended systems—such as cells, neural tissues and financial markets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to singular values of parameters, akin to critical points in physics where phase transitions occur. These are points where the response of physical systems to external perturbations, as measured by the susceptibility, is very large and diverges in the limit of infinite size. We show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher information) are directly related to the susceptibility of the inferred model. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. This region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time scales naturally yield models which are close to criticality.
On the criticality of inferred models
International Nuclear Information System (INIS)
Mastromatteo, Iacopo; Marsili, Matteo
2011-01-01
Advanced inference techniques allow one to reconstruct a pattern of interaction from high dimensional data sets, from probing simultaneously thousands of units of extended systems—such as cells, neural tissues and financial markets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to singular values of parameters, akin to critical points in physics where phase transitions occur. These are points where the response of physical systems to external perturbations, as measured by the susceptibility, is very large and diverges in the limit of infinite size. We show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher information) are directly related to the susceptibility of the inferred model. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. This region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time scales naturally yield models which are close to criticality
Polynomial Chaos Surrogates for Bayesian Inference
Le Maitre, Olivier
2016-01-06
The Bayesian inference is a popular probabilistic method to solve inverse problems, such as the identification of field parameter in a PDE model. The inference rely on the Bayes rule to update the prior density of the sought field, from observations, and derive its posterior distribution. In most cases the posterior distribution has no explicit form and has to be sampled, for instance using a Markov-Chain Monte Carlo method. In practice the prior field parameter is decomposed and truncated (e.g. by means of Karhunen- Lo´eve decomposition) to recast the inference problem into the inference of a finite number of coordinates. Although proved effective in many situations, the Bayesian inference as sketched above faces several difficulties requiring improvements. First, sampling the posterior can be a extremely costly task as it requires multiple resolutions of the PDE model for different values of the field parameter. Second, when the observations are not very much informative, the inferred parameter field can highly depends on its prior which can be somehow arbitrary. These issues have motivated the introduction of reduced modeling or surrogates for the (approximate) determination of the parametrized PDE solution and hyperparameters in the description of the prior field. Our contribution focuses on recent developments in these two directions: the acceleration of the posterior sampling by means of Polynomial Chaos expansions and the efficient treatment of parametrized covariance functions for the prior field. We also discuss the possibility of making such approach adaptive to further improve its efficiency.
A Bayesian Network Schema for Lessening Database Inference
National Research Council Canada - National Science Library
Chang, LiWu; Moskowitz, Ira S
2001-01-01
.... The authors introduce a formal schema for database inference analysis, based upon a Bayesian network structure, which identifies critical parameters involved in the inference problem and represents...
Diversity of vascular plants of Piestany and surroundings (presentation)
International Nuclear Information System (INIS)
Penzesova, A.; Galusova, T.
2013-01-01
In this presentation is a summary of the results of floristic research aimed at determining diversity of vascular plants of Piestany and its surroundings. Plant taxa we determined using the designation keys. We have compiled a list of plant species occurring in the monitored area, we evaluated the selected botanical-phytogeographical characteristics of flora, we've put together a list of local protected, endangered and rare species and a list of local invasive and expansive species according to sources. (Authors)
Methods of Assessing Noise Nuisance of Real Estate Surroundings
Directory of Open Access Journals (Sweden)
Szopińska Kinga
2016-03-01
Full Text Available Testing what factors create the market value of real estate is key information when preparing property valuations as well as other opinions and professional evaluations on the basis of which court verdicts or administrative decisions are made. One of the factors influencing the value of some real estate is the level of noise present in the surroundings, which can lead to the occurrence of noise nuisance negatively affecting social relations.
Numerical Simulation on Zonal Disintegration in Deep Surrounding Rock Mass
Directory of Open Access Journals (Sweden)
Xuguang Chen
2014-01-01
Full Text Available Zonal disintegration have been discovered in many underground tunnels with the increasing of embedded depth. The formation mechanism of such phenomenon is difficult to explain under the framework of traditional rock mechanics, and the fractured shape and forming conditions are unclear. The numerical simulation was carried out to research the generating condition and forming process of zonal disintegration. Via comparing the results with the geomechanical model test, the zonal disintegration phenomenon was confirmed and its mechanism is revealed. It is found to be the result of circular fracture which develops within surrounding rock mass under the high geostress. The fractured shape of zonal disintegration was determined, and the radii of the fractured zones were found to fulfill the relationship of geometric progression. The numerical results were in accordance with the model test findings. The mechanism of the zonal disintegration was revealed by theoretical analysis based on fracture mechanics. The fractured zones are reportedly circular and concentric to the cavern. Each fracture zone ruptured at the elastic-plastic boundary of the surrounding rocks and then coalesced into the circular form. The geometric progression ratio was found to be related to the mechanical parameters and the ground stress of the surrounding rocks.
Numerical simulation on zonal disintegration in deep surrounding rock mass.
Chen, Xuguang; Wang, Yuan; Mei, Yu; Zhang, Xin
2014-01-01
Zonal disintegration have been discovered in many underground tunnels with the increasing of embedded depth. The formation mechanism of such phenomenon is difficult to explain under the framework of traditional rock mechanics, and the fractured shape and forming conditions are unclear. The numerical simulation was carried out to research the generating condition and forming process of zonal disintegration. Via comparing the results with the geomechanical model test, the zonal disintegration phenomenon was confirmed and its mechanism is revealed. It is found to be the result of circular fracture which develops within surrounding rock mass under the high geostress. The fractured shape of zonal disintegration was determined, and the radii of the fractured zones were found to fulfill the relationship of geometric progression. The numerical results were in accordance with the model test findings. The mechanism of the zonal disintegration was revealed by theoretical analysis based on fracture mechanics. The fractured zones are reportedly circular and concentric to the cavern. Each fracture zone ruptured at the elastic-plastic boundary of the surrounding rocks and then coalesced into the circular form. The geometric progression ratio was found to be related to the mechanical parameters and the ground stress of the surrounding rocks.
Enhanced sources of acoustic power surrounding AR 11429
International Nuclear Information System (INIS)
Donea, Alina; Hanson, Christopher
2013-01-01
Multi-frequency power maps of the local acoustic oscillations show acoustic enhancements (''acoustic-power halos'') at high frequencies surrounding large active region. Computational seismic holography reveals a high-frequency ''acoustic-emission halo'', or ''seismic glory'' surrounding large active regions. In this study, we have applied computational seismic holography to map the seismic seismic source density surrounding AR 11429. Studies of HMI/SDO Doppler data, shows that the ''acoustic halos'' and the ''seismic glories'' are prominent at high frequencies 5–8 mHz. We investigate morphological properties of acoustic-power and acoustic emission halos around an active region to see if they are spatially correlated. Details about the local magnetic field from vectormagnetograms of AR 11429 are included. We identify a 15'' region of seismic deficit power (dark moat) shielding the white-light boundary of the active region. The size of the seismic moat is related to region of intermediate magnetic field strength. The acoustic moat is circled by the halo of enhanced seismic amplitude as well as enhanced seismic emission. Overall, the results suggest that features are related. However, if we narrow the frequency band to 5.5 – 6.5 mHz, we find that the seismic source density dominates over the local acoustic power, suggesting the existence of sources that emit more energy downward into the solar interior than upward toward the solar surface.
Tissue reaction surrounding miniscrews for orthodontic anchorage: An animal experiment
Directory of Open Access Journals (Sweden)
Stephanie Shih-Hsuan Chen
2012-03-01
Results and conclusions: (1 Tissue surrounding roots damaged by a miniscrew showed a significant inflammatory response. (2 Root resorption was occasionally observed after 3 weeks following insertion of a miniscrew even if the miniscrew was not in direct contact with the root. (3 Root repair was noted with a cementoblast lining along the resorption surface at as early as 3 weeks after miniscrew insertion. Alveolar bone filled in the lesion when the root damage was large so that the contour of the alveolar bone followed that of the damaged root, with the width of the periodontal ligament space being maintained. (4 Stable miniscrews were mainly those which did not contact adjacent roots, and for which the surrounding tissue showed only a small inflammatory response with some extent of direct bone contact around the miniscrew. On the contrary, most of the failed miniscrews were those which had direct contact with adjacent roots, and which exhibited severe tissue inflammation and were covered by thick layers of soft tissue. Failure was detected 3 weeks after insertion. Surprisingly, the epithelial lining surrounding the miniscrews might not have spontaneously resolved 6 weeks after screw removal. Persistent infection in the sinus tract was noted, and this would require attention.
A permeability barrier surrounds taste buds in lingual epithelia
Dando, Robin; Pereira, Elizabeth; Kurian, Mani; Barro-Soria, Rene; Chaudhari, Nirupa
2014-01-01
Epithelial tissues are characterized by specialized cell-cell junctions, typically localized to the apical regions of cells. These junctions are formed by interacting membrane proteins and by cytoskeletal and extracellular matrix components. Within the lingual epithelium, tight junctions join the apical tips of the gustatory sensory cells in taste buds. These junctions constitute a selective barrier that limits penetration of chemosensory stimuli into taste buds (Michlig et al. J Comp Neurol 502: 1003–1011, 2007). We tested the ability of chemical compounds to permeate into sensory end organs in the lingual epithelium. Our findings reveal a robust barrier that surrounds the entire body of taste buds, not limited to the apical tight junctions. This barrier prevents penetration of many, but not all, compounds, whether they are applied topically, injected into the parenchyma of the tongue, or circulating in the blood supply, into taste buds. Enzymatic treatments indicate that this barrier likely includes glycosaminoglycans, as it was disrupted by chondroitinase but, less effectively, by proteases. The barrier surrounding taste buds could also be disrupted by brief treatment of lingual tissue samples with DMSO. Brief exposure of lingual slices to DMSO did not affect the ability of taste buds within the slice to respond to chemical stimulation. The existence of a highly impermeable barrier surrounding taste buds and methods to break through this barrier may be relevant to basic research and to clinical treatments of taste. PMID:25209263
A permeability barrier surrounds taste buds in lingual epithelia.
Dando, Robin; Pereira, Elizabeth; Kurian, Mani; Barro-Soria, Rene; Chaudhari, Nirupa; Roper, Stephen D
2015-01-01
Epithelial tissues are characterized by specialized cell-cell junctions, typically localized to the apical regions of cells. These junctions are formed by interacting membrane proteins and by cytoskeletal and extracellular matrix components. Within the lingual epithelium, tight junctions join the apical tips of the gustatory sensory cells in taste buds. These junctions constitute a selective barrier that limits penetration of chemosensory stimuli into taste buds (Michlig et al. J Comp Neurol 502: 1003-1011, 2007). We tested the ability of chemical compounds to permeate into sensory end organs in the lingual epithelium. Our findings reveal a robust barrier that surrounds the entire body of taste buds, not limited to the apical tight junctions. This barrier prevents penetration of many, but not all, compounds, whether they are applied topically, injected into the parenchyma of the tongue, or circulating in the blood supply, into taste buds. Enzymatic treatments indicate that this barrier likely includes glycosaminoglycans, as it was disrupted by chondroitinase but, less effectively, by proteases. The barrier surrounding taste buds could also be disrupted by brief treatment of lingual tissue samples with DMSO. Brief exposure of lingual slices to DMSO did not affect the ability of taste buds within the slice to respond to chemical stimulation. The existence of a highly impermeable barrier surrounding taste buds and methods to break through this barrier may be relevant to basic research and to clinical treatments of taste. Copyright © 2015 the American Physiological Society.
A formal model of interpersonal inference
Directory of Open Access Journals (Sweden)
Michael eMoutoussis
2014-03-01
Full Text Available Introduction: We propose that active Bayesian inference – a general framework for decision-making – can equally be applied to interpersonal exchanges. Social cognition, however, entails special challenges. We address these challenges through a novel formulation of a formal model and demonstrate its psychological significance. Method: We review relevant literature, especially with regards to interpersonal representations, formulate a mathematical model and present a simulation study. The model accommodates normative models from utility theory and places them within the broader setting of Bayesian inference. Crucially, we endow people's prior beliefs, into which utilities are absorbed, with preferences of self and others. The simulation illustrates the model's dynamics and furnishes elementary predictions of the theory. Results: 1. Because beliefs about self and others inform both the desirability and plausibility of outcomes, in this framework interpersonal representations become beliefs that have to be actively inferred. This inference, akin to 'mentalising' in the psychological literature, is based upon the outcomes of interpersonal exchanges. 2. We show how some well-known social-psychological phenomena (e.g. self-serving biases can be explained in terms of active interpersonal inference. 3. Mentalising naturally entails Bayesian updating of how people value social outcomes. Crucially this includes inference about one’s own qualities and preferences. Conclusion: We inaugurate a Bayes optimal framework for modelling intersubject variability in mentalising during interpersonal exchanges. Here, interpersonal representations are endowed with explicit functional and affective properties. We suggest the active inference framework lends itself to the study of psychiatric conditions where mentalising is distorted.
Estimating uncertainty of inference for validation
Energy Technology Data Exchange (ETDEWEB)
Booker, Jane M [Los Alamos National Laboratory; Langenbrunner, James R [Los Alamos National Laboratory; Hemez, Francois M [Los Alamos National Laboratory; Ross, Timothy J [UNM
2010-09-30
We present a validation process based upon the concept that validation is an inference-making activity. This has always been true, but the association has not been as important before as it is now. Previously, theory had been confirmed by more data, and predictions were possible based on data. The process today is to infer from theory to code and from code to prediction, making the role of prediction somewhat automatic, and a machine function. Validation is defined as determining the degree to which a model and code is an accurate representation of experimental test data. Imbedded in validation is the intention to use the computer code to predict. To predict is to accept the conclusion that an observable final state will manifest; therefore, prediction is an inference whose goodness relies on the validity of the code. Quantifying the uncertainty of a prediction amounts to quantifying the uncertainty of validation, and this involves the characterization of uncertainties inherent in theory/models/codes and the corresponding data. An introduction to inference making and its associated uncertainty is provided as a foundation for the validation problem. A mathematical construction for estimating the uncertainty in the validation inference is then presented, including a possibility distribution constructed to represent the inference uncertainty for validation under uncertainty. The estimation of inference uncertainty for validation is illustrated using data and calculations from Inertial Confinement Fusion (ICF). The ICF measurements of neutron yield and ion temperature were obtained for direct-drive inertial fusion capsules at the Omega laser facility. The glass capsules, containing the fusion gas, were systematically selected with the intent of establishing a reproducible baseline of high-yield 10{sup 13}-10{sup 14} neutron output. The deuterium-tritium ratio in these experiments was varied to study its influence upon yield. This paper on validation inference is the
Deep Learning for Population Genetic Inference.
Sheehan, Sara; Song, Yun S
2016-03-01
Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.
Deep Learning for Population Genetic Inference.
Directory of Open Access Journals (Sweden)
Sara Sheehan
2016-03-01
Full Text Available Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data to the output (e.g., population genetic parameters of interest. We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history. Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.
Deep Learning for Population Genetic Inference
Sheehan, Sara; Song, Yun S.
2016-01-01
Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme. PMID:27018908
Inferring Phylogenetic Networks Using PhyloNet.
Wen, Dingqiao; Yu, Yun; Zhu, Jiafan; Nakhleh, Luay
2018-07-01
PhyloNet was released in 2008 as a software package for representing and analyzing phylogenetic networks. At the time of its release, the main functionalities in PhyloNet consisted of measures for comparing network topologies and a single heuristic for reconciling gene trees with a species tree. Since then, PhyloNet has grown significantly. The software package now includes a wide array of methods for inferring phylogenetic networks from data sets of unlinked loci while accounting for both reticulation (e.g., hybridization) and incomplete lineage sorting. In particular, PhyloNet now allows for maximum parsimony, maximum likelihood, and Bayesian inference of phylogenetic networks from gene tree estimates. Furthermore, Bayesian inference directly from sequence data (sequence alignments or biallelic markers) is implemented. Maximum parsimony is based on an extension of the "minimizing deep coalescences" criterion to phylogenetic networks, whereas maximum likelihood and Bayesian inference are based on the multispecies network coalescent. All methods allow for multiple individuals per species. As computing the likelihood of a phylogenetic network is computationally hard, PhyloNet allows for evaluation and inference of networks using a pseudolikelihood measure. PhyloNet summarizes the results of the various analyzes and generates phylogenetic networks in the extended Newick format that is readily viewable by existing visualization software.
INTERACTIONS OF THE INFRARED BUBBLE N4 WITH ITS SURROUNDINGS
Energy Technology Data Exchange (ETDEWEB)
Liu, Hong-Li; Li, Jin-Zeng; Yuan, Jing-Hua; Huang, Maohai; Huang, Ya-Fang; Zhang, Si-Ju [National Astronomical Observatories, Chinese Academy of Sciences, 20A Datun Road, Chaoyang District, Beijing 100012 (China); Wu, Yuefang [Department of Astronomy, Peking University, 100871 Beijing (China); Liu, Tie [Korea Astronomy and Space Science Institute 776, Daedeokdae-ro, Yuseong-gu, Daejeon, 305-348 (Korea, Republic of); Dubner, G.; Paron, S.; Ortega, M. E. [1Instituto de Astronomía y Física del Espacio (IAFE, CONICET-UBA), CC 67, Suc. 28, 1428 Buenos Aires (Argentina); Molinari, Sergio [Istituto di Astrofisica e Planetologia Spaziali—IAPS, Istituto Nazionale di Astrofisica—INAF, via Fosso del Cavaliere 100, I-00133 Roma (Italy); Zavagno, Annie; Samal, Manash R., E-mail: hlliu@nao.cas.cn [Aix Marseille Universit, CNRS, LAM (Laboratoire d’Astrophysique de Marseille) UMR 7326, F-13388, Marseille (France)
2016-02-10
The physical mechanisms that induce the transformation of a certain mass of gas in new stars are far from being well understood. Infrared bubbles associated with H ii regions have been considered to be good samples for investigating triggered star formation. In this paper we report on the investigation of the dust properties of the infrared bubble N4 around the H ii region G11.898+0.747, analyzing its interaction with its surroundings and star formation histories therein, with the aim of determining the possibility of star formation triggered by the expansion of the bubble. Using Herschel PACS and SPIRE images with a wide wavelength coverage, we reveal the dust properties over the entire bubble. Meanwhile, we are able to identify six dust clumps surrounding the bubble, with a mean size of 0.50 pc, temperature of about 22 K, mean column density of 1.7 × 10{sup 22} cm{sup −2}, mean volume density of about 4.4 × 10{sup 4} cm{sup −3}, and a mean mass of 320 M{sub ⊙}. In addition, from PAH emission seen at 8 μm, free–free emission detected at 20 cm, and a probability density function in special regions, we could identify clear signatures of the influence of the H ii region on the surroundings. There are hints of star formation, though further investigation is required to demonstrate that N4 is the triggering source.
Blooming Trees: Substructures and Surrounding Groups of Galaxy Clusters
Yu, Heng; Diaferio, Antonaldo; Serra, Ana Laura; Baldi, Marco
2018-06-01
We develop the Blooming Tree Algorithm, a new technique that uses spectroscopic redshift data alone to identify the substructures and the surrounding groups of galaxy clusters, along with their member galaxies. Based on the estimated binding energy of galaxy pairs, the algorithm builds a binary tree that hierarchically arranges all of the galaxies in the field of view. The algorithm searches for buds, corresponding to gravitational potential minima on the binary tree branches; for each bud, the algorithm combines the number of galaxies, their velocity dispersion, and their average pairwise distance into a parameter that discriminates between the buds that do not correspond to any substructure or group, and thus eventually die, and the buds that correspond to substructures and groups, and thus bloom into the identified structures. We test our new algorithm with a sample of 300 mock redshift surveys of clusters in different dynamical states; the clusters are extracted from a large cosmological N-body simulation of a ΛCDM model. We limit our analysis to substructures and surrounding groups identified in the simulation with mass larger than 1013 h ‑1 M ⊙. With mock redshift surveys with 200 galaxies within 6 h ‑1 Mpc from the cluster center, the technique recovers 80% of the real substructures and 60% of the surrounding groups; in 57% of the identified structures, at least 60% of the member galaxies of the substructures and groups belong to the same real structure. These results improve by roughly a factor of two the performance of the best substructure identification algorithm currently available, the σ plateau algorithm, and suggest that our Blooming Tree Algorithm can be an invaluable tool for detecting substructures of galaxy clusters and investigating their complex dynamics.
Earthquakes in Switzerland and surrounding regions during 2007
Energy Technology Data Exchange (ETDEWEB)
Baer, M.; Deichmann, N.; Clinton, J.; Husen, S.; Faeh, D.; Giardini, D.; Kaestli, P.; Kradolfer, U.; Wiemer, S
2008-12-15
This report of the Swiss Seismological Service summarizes the seismic activity in Switzerland and surrounding regions during 2007. During this period, 531 earthquakes and 92 quarry blasts were detected and located in the region under consideration. Of these earthquakes, 30 are aftershocks of the stimulation of a proposed geothermal reservoir beneath the city of Basel in December of 2006. With 20 events with {mu}{sub {iota}} {>=} 2.5, four of which were artificially induced, the seismic activity in the year 2007 was far below the average over the previous 32 years. (author)
Isoperimetric inequalities in surround system and space science
JiaJin Wen; Jun Yuan; ShanHe Wu
2016-01-01
Abstract By means of the algebraic, analysis, convex geometry, computer, and inequality theories we establish the following isoperimetric inequality in the centered 2-surround system S ( 2 ) { P , Γ , l } $S^{(2)} \\{P,\\varGamma ,l \\}$ : ( 1 | Γ | ∮ Γ r ¯ P p ) 1 / p ⩽ | Γ | 4 π sin l π | Γ | [ csc l π | Γ | + cot 2 l π | Γ | ln ( tan l π | Γ | + sec l π | Γ | ) ] , ∀ p ⩽ − 2 . $$\\begin{aligned}& \\biggl(\\frac{1}{|\\varGamma |} \\oint_{\\varGamma }\\bar{r}_{P}^{p} \\biggr)^{1/p}\\leqslant\\frac{|\\varG...
Induced radioactivity in a 4 MW target and its surroundings
Agosteo, Stefano; Otto, Thomas; Silari, Marco
2003-01-01
An important aspect of a future CERN Neutrino Factory is the material activation arising from a 2.2 GeV, 4 MW proton beam striking a mercury target. An estimation of the hadronic inelastic interactions and the production of residual nuclei in the target, the magnetic horn, the decay tunnel, the surrounding rock and a downstream dump was performed by the Monte Carlo hadronic cascade code FLUKA. The aim was both to assess the dose equivalent rate to be expected during maintenance work and to evaluate the amount of residual radioactivity, which will have to be disposed of after the facility has ceased operation.
Mutual seismic interaction between tunnels and the surrounding granular soil
Directory of Open Access Journals (Sweden)
Mohamed Ahmed Abdel-Motaal
2014-12-01
Study results show that the maximum exerted straining actions in tunnel lining are directly proportional to the relative stiffness between tunnel and surrounding soil (lining thickness and soil shear modulus. Moreover, it is highly affected by the peak ground acceleration and the tunnel location (embedment depth. A comprehensive study is performed to show the effect of tunnel thickness and tunnel diameter on both the induced bending moment and lining deformation. In general, it is concluded that seismic analysis should be considered in regions subjected to peak ground acceleration greater than 0.15g.
Earthquakes in Switzerland and surrounding regions during 2007
International Nuclear Information System (INIS)
Baer, M.; Deichmann, N.; Clinton, J.; Husen, S.; Faeh, D.; Giardini, D.; Kaestli, P.; Kradolfer, U.; Wiemer, S.
2008-01-01
This report of the Swiss Seismological Service summarizes the seismic activity in Switzerland and surrounding regions during 2007. During this period, 531 earthquakes and 92 quarry blasts were detected and located in the region under consideration. Of these earthquakes, 30 are aftershocks of the stimulation of a proposed geothermal reservoir beneath the city of Basel in December of 2006. With 20 events with Μ ι ≥ 2.5, four of which were artificially induced, the seismic activity in the year 2007 was far below the average over the previous 32 years. (author)
Diversity of vascular plants of Piestany and surroundings
International Nuclear Information System (INIS)
Penzesova, A.; Galusova, T.
2013-01-01
In the present work is a summary of the results of floristic research aimed at determining diversity of vascular plants of Piestany and its surroundings. Plant taxa we determined using the designation keys. We have compiled a list of plant species occurring in the monitored area, we evaluated the selected botanical-phytogeographical characteristics of flora, we've put together a list of local protected, endangered and rare species and a list of local invasive and expansive species according to sources. (Authors)
One Japanese case on taxation surrounding foreign trust
SUZUKI, Yuya
2015-01-01
Taxation surrounding trust at cross-border situation is paid attention to byworldwide basis. Japan is not exception. According to recent Japanesejurisprudence, where a trust had been established in accordance with State law ofNew Jersey, the U.S., it was disputed whether or not the act settling that trust fellwithin “shintaku koui (an act of trust)” and one of the related members, who had beena minor child at that time, fell within “jyueki sha (beneficiary)” under JapaneseInheritance Tax Act....
Goal inferences about robot behavior : goal inferences and human response behaviors
Broers, H.A.T.; Ham, J.R.C.; Broeders, R.; De Silva, P.; Okada, M.
2014-01-01
This explorative research focused on the goal inferences human observers draw based on a robot's behavior, and the extent to which those inferences predict people's behavior in response to that robot. Results show that different robot behaviors cause different response behavior from people.
Using Alien Coins to Test Whether Simple Inference Is Bayesian
Cassey, Peter; Hawkins, Guy E.; Donkin, Chris; Brown, Scott D.
2016-01-01
Reasoning and inference are well-studied aspects of basic cognition that have been explained as statistically optimal Bayesian inference. Using a simplified experimental design, we conducted quantitative comparisons between Bayesian inference and human inference at the level of individuals. In 3 experiments, with more than 13,000 participants, we…
Explanatory Preferences Shape Learning and Inference.
Lombrozo, Tania
2016-10-01
Explanations play an important role in learning and inference. People often learn by seeking explanations, and they assess the viability of hypotheses by considering how well they explain the data. An emerging body of work reveals that both children and adults have strong and systematic intuitions about what constitutes a good explanation, and that these explanatory preferences have a systematic impact on explanation-based processes. In particular, people favor explanations that are simple and broad, with the consequence that engaging in explanation can shape learning and inference by leading people to seek patterns and favor hypotheses that support broad and simple explanations. Given the prevalence of explanation in everyday cognition, understanding explanation is therefore crucial to understanding learning and inference. Copyright © 2016 Elsevier Ltd. All rights reserved.
Fuzzy logic controller using different inference methods
International Nuclear Information System (INIS)
Liu, Z.; De Keyser, R.
1994-01-01
In this paper the design of fuzzy controllers by using different inference methods is introduced. Configuration of the fuzzy controllers includes a general rule-base which is a collection of fuzzy PI or PD rules, the triangular fuzzy data model and a centre of gravity defuzzification algorithm. The generalized modus ponens (GMP) is used with the minimum operator of the triangular norm. Under the sup-min inference rule, six fuzzy implication operators are employed to calculate the fuzzy look-up tables for each rule base. The performance is tested in simulated systems with MATLAB/SIMULINK. Results show the effects of using the fuzzy controllers with different inference methods and applied to different test processes
Uncertainty in prediction and in inference
International Nuclear Information System (INIS)
Hilgevoord, J.; Uffink, J.
1991-01-01
The concepts of uncertainty in prediction and inference are introduced and illustrated using the diffraction of light as an example. The close relationship between the concepts of uncertainty in inference and resolving power is noted. A general quantitative measure of uncertainty in inference can be obtained by means of the so-called statistical distance between probability distributions. When applied to quantum mechanics, this distance leads to a measure of the distinguishability of quantum states, which essentially is the absolute value of the matrix element between the states. The importance of this result to the quantum mechanical uncertainty principle is noted. The second part of the paper provides a derivation of the statistical distance on the basis of the so-called method of support
A Learning Algorithm for Multimodal Grammar Inference.
D'Ulizia, A; Ferri, F; Grifoni, P
2011-12-01
The high costs of development and maintenance of multimodal grammars in integrating and understanding input in multimodal interfaces lead to the investigation of novel algorithmic solutions in automating grammar generation and in updating processes. Many algorithms for context-free grammar inference have been developed in the natural language processing literature. An extension of these algorithms toward the inference of multimodal grammars is necessary for multimodal input processing. In this paper, we propose a novel grammar inference mechanism that allows us to learn a multimodal grammar from its positive samples of multimodal sentences. The algorithm first generates the multimodal grammar that is able to parse the positive samples of sentences and, afterward, makes use of two learning operators and the minimum description length metrics in improving the grammar description and in avoiding the over-generalization problem. The experimental results highlight the acceptable performances of the algorithm proposed in this paper since it has a very high probability of parsing valid sentences.
Examples in parametric inference with R
Dixit, Ulhas Jayram
2016-01-01
This book discusses examples in parametric inference with R. Combining basic theory with modern approaches, it presents the latest developments and trends in statistical inference for students who do not have an advanced mathematical and statistical background. The topics discussed in the book are fundamental and common to many fields of statistical inference and thus serve as a point of departure for in-depth study. The book is divided into eight chapters: Chapter 1 provides an overview of topics on sufficiency and completeness, while Chapter 2 briefly discusses unbiased estimation. Chapter 3 focuses on the study of moments and maximum likelihood estimators, and Chapter 4 presents bounds for the variance. In Chapter 5, topics on consistent estimator are discussed. Chapter 6 discusses Bayes, while Chapter 7 studies some more powerful tests. Lastly, Chapter 8 examines unbiased and other tests. Senior undergraduate and graduate students in statistics and mathematics, and those who have taken an introductory cou...
Grammatical inference algorithms, routines and applications
Wieczorek, Wojciech
2017-01-01
This book focuses on grammatical inference, presenting classic and modern methods of grammatical inference from the perspective of practitioners. To do so, it employs the Python programming language to present all of the methods discussed. Grammatical inference is a field that lies at the intersection of multiple disciplines, with contributions from computational linguistics, pattern recognition, machine learning, computational biology, formal learning theory and many others. Though the book is largely practical, it also includes elements of learning theory, combinatorics on words, the theory of automata and formal languages, plus references to real-world problems. The listings presented here can be directly copied and pasted into other programs, thus making the book a valuable source of ready recipes for students, academic researchers, and programmers alike, as well as an inspiration for their further development.>.
Statistical inference based on divergence measures
Pardo, Leandro
2005-01-01
The idea of using functionals of Information Theory, such as entropies or divergences, in statistical inference is not new. However, in spite of the fact that divergence statistics have become a very good alternative to the classical likelihood ratio test and the Pearson-type statistic in discrete models, many statisticians remain unaware of this powerful approach.Statistical Inference Based on Divergence Measures explores classical problems of statistical inference, such as estimation and hypothesis testing, on the basis of measures of entropy and divergence. The first two chapters form an overview, from a statistical perspective, of the most important measures of entropy and divergence and study their properties. The author then examines the statistical analysis of discrete multivariate data with emphasis is on problems in contingency tables and loglinear models using phi-divergence test statistics as well as minimum phi-divergence estimators. The final chapter looks at testing in general populations, prese...
Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics.
Directory of Open Access Journals (Sweden)
Ruben Coen-Cagli
Full Text Available Spatial context in images induces perceptual phenomena associated with salience and modulates the responses of neurons in primary visual cortex (V1. However, the computational and ecological principles underlying contextual effects are incompletely understood. We introduce a model of natural images that includes grouping and segmentation of neighboring features based on their joint statistics, and we interpret the firing rates of V1 neurons as performing optimal recognition in this model. We show that this leads to a substantial generalization of divisive normalization, a computation that is ubiquitous in many neural areas and systems. A main novelty in our model is that the influence of the context on a target stimulus is determined by their degree of statistical dependence. We optimized the parameters of the model on natural image patches, and then simulated neural and perceptual responses on stimuli used in classical experiments. The model reproduces some rich and complex response patterns observed in V1, such as the contrast dependence, orientation tuning and spatial asymmetry of surround suppression, while also allowing for surround facilitation under conditions of weak stimulation. It also mimics the perceptual salience produced by simple displays, and leads to readily testable predictions. Our results provide a principled account of orientation-based contextual modulation in early vision and its sensitivity to the homogeneity and spatial arrangement of inputs, and lends statistical support to the theory that V1 computes visual salience.
Effectively Communicating the Uncertainties Surrounding Ebola Virus Transmission.
Directory of Open Access Journals (Sweden)
Andy Kilianski
2015-10-01
Full Text Available The current Ebola virus outbreak has highlighted the uncertainties surrounding many aspects of Ebola virus virology, including routes of transmission. The scientific community played a leading role during the outbreak-potentially, the largest of its kind-as many of the questions surrounding ebolaviruses have only been interrogated in the laboratory. Scientists provided an invaluable resource for clinicians, public health officials, policy makers, and the lay public in understanding the progress of Ebola virus disease and the continuing outbreak. Not all of the scientific communication, however, was accurate or effective. There were multiple instances of published articles during the height of the outbreak containing potentially misleading scientific language that spurred media overreaction and potentially jeopardized preparedness and policy decisions at critical points. Here, we use articles declaring the potential for airborne transmission of Ebola virus as a case study in the inaccurate reporting of basic science, and we provide recommendations for improving the communication about unknown aspects of disease during public health crises.
Effectively Communicating the Uncertainties Surrounding Ebola Virus Transmission.
Kilianski, Andy; Evans, Nicholas G
2015-10-01
The current Ebola virus outbreak has highlighted the uncertainties surrounding many aspects of Ebola virus virology, including routes of transmission. The scientific community played a leading role during the outbreak-potentially, the largest of its kind-as many of the questions surrounding ebolaviruses have only been interrogated in the laboratory. Scientists provided an invaluable resource for clinicians, public health officials, policy makers, and the lay public in understanding the progress of Ebola virus disease and the continuing outbreak. Not all of the scientific communication, however, was accurate or effective. There were multiple instances of published articles during the height of the outbreak containing potentially misleading scientific language that spurred media overreaction and potentially jeopardized preparedness and policy decisions at critical points. Here, we use articles declaring the potential for airborne transmission of Ebola virus as a case study in the inaccurate reporting of basic science, and we provide recommendations for improving the communication about unknown aspects of disease during public health crises.
REMOTE SENSING EFFICIENCY FOR URBAN ANALYSIS OF MECCA AND SURROUNDS
Directory of Open Access Journals (Sweden)
A. Imam
2016-06-01
Full Text Available Situated in the southwest of Saudi Arabia, Mecca is considered the spiritual capital of one and a half billion worldwide Muslims. The city is visited by millions of pilgrims every year. It has undergone significant changes in land cover (LC since the government first embarked on a series of ambitious development projects 20 years ago to accommodate the growing number of pilgrims and citizens. The main objective of our study is to detect, identify, analyze and measure the evolving land cover and urban morphology composition from multi-temporal satellite images. To characterize the morphological change during a period of twenty years, four satellite images, acquired in 1998 by Landsat TM and in 2003, 2008 and 2013 by Landsat ETM+, were classified into five main categories: Urban, Street, Soil and Vegetation. In addition, DEM has been extracted and included as Mountain. Change detection (CD analysis is applied using post-classification comparison and GIS. As part of the study, morphological index, such as, Entropy is included for better understanding of urban structures behaviour. Mecca and its surroundings show a noticeable increase in urban and vegetation cover. Urban cover (UC changes were divided into five radial directions: Northeast, Southeast, Southwest, East, and Northwest. These changes are influenced by mountain ranges surrounding the city and the highways. These revelations can play a significant role towards future planning and development activities, which may further promote urban growth.
Remote Sensing Efficiency for Urban Analysis of Mecca and Surrounds
Imam, Ayman; Alhaddad, Bahaa; Roca, Josep
2016-06-01
Situated in the southwest of Saudi Arabia, Mecca is considered the spiritual capital of one and a half billion worldwide Muslims. The city is visited by millions of pilgrims every year. It has undergone significant changes in land cover (LC) since the government first embarked on a series of ambitious development projects 20 years ago to accommodate the growing number of pilgrims and citizens. The main objective of our study is to detect, identify, analyze and measure the evolving land cover and urban morphology composition from multi-temporal satellite images. To characterize the morphological change during a period of twenty years, four satellite images, acquired in 1998 by Landsat TM and in 2003, 2008 and 2013 by Landsat ETM+, were classified into five main categories: Urban, Street, Soil and Vegetation. In addition, DEM has been extracted and included as Mountain. Change detection (CD) analysis is applied using post-classification comparison and GIS. As part of the study, morphological index, such as, Entropy is included for better understanding of urban structures behaviour. Mecca and its surroundings show a noticeable increase in urban and vegetation cover. Urban cover (UC) changes were divided into five radial directions: Northeast, Southeast, Southwest, East, and Northwest. These changes are influenced by mountain ranges surrounding the city and the highways. These revelations can play a significant role towards future planning and development activities, which may further promote urban growth.
MRI of normal pituitary glands and their surrounding structures
International Nuclear Information System (INIS)
Sato, Yoshiyuki
1991-01-01
Normal MRI appearances of the pituitary glands and their surrounding structures were evaluated in 332 patients without sellar and parasellar diseases. The height of the pituitary gland was maximum at 10-19 years of age reflecting hormonal activity. The width of the pituitary gland decreased, while that of the cavernous sinus increased with aging. This is probably due to atherosclerotic change of the internal carotid artery. Females younger than 30 years of age tended to show a convex upper surface of the pituitary gland and the displacement of the pituitary stalk was common after 50 years of age. Almost all of the anterior lobe of the pituitary gland showed isointensity relative to the pons or cerebral cortex and the majority (85.1%) of the posterior lobe showed hyperintensity. However, the anterior lobe in 2 newborns showed hyperintensity similar to the normal posterior lobe in adults. The posterior lobe was located off the midline in 19.1% of the subjects. One case of pars intermedia cyst was discovered among 14 subjects who were administered Gd-DTPA. The dural membrane between the pituitary gland and cavernous sinus was recognizable only in 8.6% on the right side and 7.5% on the left side. Primary empty sella was identified in 4.5%. Knowledge of the above normal ranges and variations of the pituitary gland and its surrounding structures is important in diagnosing sellar and parasellar lesions. (author) 52 refs
TRIGGERED STAR FORMATION SURROUNDING WOLF-RAYET STAR HD 211853
Energy Technology Data Exchange (ETDEWEB)
Liu Tie; Wu Yuefang; Zhang Huawei [Department of Astronomy, Peking University, 100871 Beijing (China); Qin Shengli, E-mail: liutiepku@gmail.com [I. Physikalisches Institut, Universitaet zu Koeln, Zuelpicher Str. 77, 50937 Koeln (Germany)
2012-05-20
The environment surrounding Wolf-Rayet (W-R) star HD 211853 is studied in molecular, infrared, as well as radio, and H I emission. The molecular ring consists of well-separated cores, which have a volume density of 10{sup 3} cm{sup -3} and kinematic temperature {approx}20 K. Most of the cores are under gravitational collapse due to external pressure from the surrounding ionized gas. From the spectral energy distribution modeling toward the young stellar objects, the sequential star formation is revealed on a large scale in space spreading from the W-R star to the molecular ring. A small-scale sequential star formation is revealed toward core 'A', which harbors a very young star cluster. Triggered star formations are thus suggested. The presence of the photodissociation region, the fragmentation of the molecular ring, the collapse of the cores, and the large-scale sequential star formation indicate that the 'collect and collapse' process functions in this region. The star-forming activities in core 'A' seem to be affected by the 'radiation-driven implosion' process.
TRIGGERED STAR FORMATION SURROUNDING WOLF-RAYET STAR HD 211853
International Nuclear Information System (INIS)
Liu Tie; Wu Yuefang; Zhang Huawei; Qin Shengli
2012-01-01
The environment surrounding Wolf-Rayet (W-R) star HD 211853 is studied in molecular, infrared, as well as radio, and H I emission. The molecular ring consists of well-separated cores, which have a volume density of 10 3 cm –3 and kinematic temperature ∼20 K. Most of the cores are under gravitational collapse due to external pressure from the surrounding ionized gas. From the spectral energy distribution modeling toward the young stellar objects, the sequential star formation is revealed on a large scale in space spreading from the W-R star to the molecular ring. A small-scale sequential star formation is revealed toward core 'A', which harbors a very young star cluster. Triggered star formations are thus suggested. The presence of the photodissociation region, the fragmentation of the molecular ring, the collapse of the cores, and the large-scale sequential star formation indicate that the 'collect and collapse' process functions in this region. The star-forming activities in core 'A' seem to be affected by the 'radiation-driven implosion' process.
Improved Inference of Heteroscedastic Fixed Effects Models
Directory of Open Access Journals (Sweden)
Afshan Saeed
2016-12-01
Full Text Available Heteroscedasticity is a stern problem that distorts estimation and testing of panel data model (PDM. Arellano (1987 proposed the White (1980 estimator for PDM with heteroscedastic errors but it provides erroneous inference for the data sets including high leverage points. In this paper, our attempt is to improve heteroscedastic consistent covariance matrix estimator (HCCME for panel dataset with high leverage points. To draw robust inference for the PDM, our focus is to improve kernel bootstrap estimators, proposed by Racine and MacKinnon (2007. The Monte Carlo scheme is used for assertion of the results.
Likelihood inference for unions of interacting discs
DEFF Research Database (Denmark)
Møller, Jesper; Helisova, K.
2010-01-01
This is probably the first paper which discusses likelihood inference for a random set using a germ-grain model, where the individual grains are unobservable, edge effects occur and other complications appear. We consider the case where the grains form a disc process modelled by a marked point...... process, where the germs are the centres and the marks are the associated radii of the discs. We propose to use a recent parametric class of interacting disc process models, where the minimal sufficient statistic depends on various geometric properties of the random set, and the density is specified......-based maximum likelihood inference and the effect of specifying different reference Poisson models....
IMAGINE: Interstellar MAGnetic field INference Engine
Steininger, Theo
2018-03-01
IMAGINE (Interstellar MAGnetic field INference Engine) performs inference on generic parametric models of the Galaxy. The modular open source framework uses highly optimized tools and technology such as the MultiNest sampler (ascl:1109.006) and the information field theory framework NIFTy (ascl:1302.013) to create an instance of the Milky Way based on a set of parameters for physical observables, using Bayesian statistics to judge the mismatch between measured data and model prediction. The flexibility of the IMAGINE framework allows for simple refitting for newly available data sets and makes state-of-the-art Bayesian methods easily accessible particularly for random components of the Galactic magnetic field.
Inferring causality from noisy time series data
DEFF Research Database (Denmark)
Mønster, Dan; Fusaroli, Riccardo; Tylén, Kristian
2016-01-01
Convergent Cross-Mapping (CCM) has shown high potential to perform causal inference in the absence of models. We assess the strengths and weaknesses of the method by varying coupling strength and noise levels in coupled logistic maps. We find that CCM fails to infer accurate coupling strength...... and even causality direction in synchronized time-series and in the presence of intermediate coupling. We find that the presence of noise deterministically reduces the level of cross-mapping fidelity, while the convergence rate exhibits higher levels of robustness. Finally, we propose that controlled noise...
Bui, Thi Thu Hien; Belli, Martina; Fassina, Lorenzo; Vigone, Giulia; Merico, Valeria; Garagna, Silvia; Zuccotti, Maurizio
2017-05-01
Full-grown mouse antral oocytes are classified as surrounding nucleolus (SN) or not-surrounding nucleolus (NSN), depending on the respective presence or absence of a ring of Hoechst-positive chromatin surrounding the nucleolus. In culture, both types of oocytes resume meiosis and reach the metaphase II (MII) stage, but following insemination, NSN oocytes arrest at the two-cell stage whereas SN oocytes may develop to term. By coupling time-lapse bright-field microscopy with image analysis based on particle image velocimetry, we provide the first systematic measure of the changes to the cytoplasmic movement velocity (CMV) occurring during the germinal vesicle-to-MII (GV-to-MII) transition of these two types of oocytes. Compared to SN oocytes, NSN oocytes display a delayed GV-to-MII transition, which can be mostly explained by retarded germinal vesicle break down and first polar body extrusion. SN and NSN oocytes also exhibit significantly different CMV profiles at four main time-lapse intervals, although this difference was not predictive of SN or NSN oocyte origin because of the high variability in CMV. When CMV profile was analyzed through a trained artificial neural network, however, each single SN or NSN oocyte was blindly identified with a probability of 92.2% and 88.7%, respectively. Thus, the CMV profile recorded during meiotic resumption may be exploited as a cytological signature for the non-invasive assessment of the oocyte developmental potential, and could be informative for the analysis of the GV-to-MII transition of oocytes of other species. © 2017 Wiley Periodicals, Inc.
Directory of Open Access Journals (Sweden)
Vito Antonio Cimmelli
2015-07-01
Full Text Available A nonlocal model for heat transfer with phonons and electrons is applied to infer the steady-state radial temperature profile in a circular layer surrounding an inner hot component. Such a profile, following by the numerical solution of the heat equation, predicts that the temperature behaves in an anomalous way, since for radial distances from the heat source smaller than the mean-free path of phonons and electrons, it increases for increasing distances. The compatibility of this temperature behavior with the second law of thermodynamics is investigated by calculating numerically the local entropy production as a function of the radial distance. It turns out that such a production is positive and strictly decreasing with the radial distance.
International Nuclear Information System (INIS)
Von Nessi, G T; Hole, M J
2014-01-01
We present recent results and technical breakthroughs for the Bayesian inference of tokamak equilibria using force-balance as a prior constraint. Issues surrounding model parameter representation and posterior analysis are discussed and addressed. These points motivate the recent advancements embodied in the Bayesian Equilibrium Analysis and Simulation Tool (BEAST) software being presently utilized to study equilibria on the Mega-Ampere Spherical Tokamak (MAST) experiment in the UK (von Nessi et al 2012 J. Phys. A 46 185501). State-of-the-art results of using BEAST to study MAST equilibria are reviewed, with recent code advancements being systematically presented though out the manuscript. (paper)
Model averaging, optimal inference and habit formation
Directory of Open Access Journals (Sweden)
Thomas H B FitzGerald
2014-06-01
Full Text Available Postulating that the brain performs approximate Bayesian inference generates principled and empirically testable models of neuronal function – the subject of much current interest in neuroscience and related disciplines. Current formulations address inference and learning under some assumed and particular model. In reality, organisms are often faced with an additional challenge – that of determining which model or models of their environment are the best for guiding behaviour. Bayesian model averaging – which says that an agent should weight the predictions of different models according to their evidence – provides a principled way to solve this problem. Importantly, because model evidence is determined by both the accuracy and complexity of the model, optimal inference requires that these be traded off against one another. This means an agent’s behaviour should show an equivalent balance. We hypothesise that Bayesian model averaging plays an important role in cognition, given that it is both optimal and realisable within a plausible neuronal architecture. We outline model averaging and how it might be implemented, and then explore a number of implications for brain and behaviour. In particular, we propose that model averaging can explain a number of apparently suboptimal phenomena within the framework of approximate (bounded Bayesian inference, focussing particularly upon the relationship between goal-directed and habitual behaviour.
Efficient Bayesian inference for ARFIMA processes
Graves, T.; Gramacy, R. B.; Franzke, C. L. E.; Watkins, N. W.
2015-03-01
Many geophysical quantities, like atmospheric temperature, water levels in rivers, and wind speeds, have shown evidence of long-range dependence (LRD). LRD means that these quantities experience non-trivial temporal memory, which potentially enhances their predictability, but also hampers the detection of externally forced trends. Thus, it is important to reliably identify whether or not a system exhibits LRD. In this paper we present a modern and systematic approach to the inference of LRD. Rather than Mandelbrot's fractional Gaussian noise, we use the more flexible Autoregressive Fractional Integrated Moving Average (ARFIMA) model which is widely used in time series analysis, and of increasing interest in climate science. Unlike most previous work on the inference of LRD, which is frequentist in nature, we provide a systematic treatment of Bayesian inference. In particular, we provide a new approximate likelihood for efficient parameter inference, and show how nuisance parameters (e.g. short memory effects) can be integrated over in order to focus on long memory parameters, and hypothesis testing more directly. We illustrate our new methodology on the Nile water level data, with favorable comparison to the standard estimators.
Campbell's and Rubin's Perspectives on Causal Inference
West, Stephen G.; Thoemmes, Felix
2010-01-01
Donald Campbell's approach to causal inference (D. T. Campbell, 1957; W. R. Shadish, T. D. Cook, & D. T. Campbell, 2002) is widely used in psychology and education, whereas Donald Rubin's causal model (P. W. Holland, 1986; D. B. Rubin, 1974, 2005) is widely used in economics, statistics, medicine, and public health. Campbell's approach focuses on…
Bayesian structural inference for hidden processes
Strelioff, Christopher C.; Crutchfield, James P.
2014-04-01
We introduce a Bayesian approach to discovering patterns in structurally complex processes. The proposed method of Bayesian structural inference (BSI) relies on a set of candidate unifilar hidden Markov model (uHMM) topologies for inference of process structure from a data series. We employ a recently developed exact enumeration of topological ɛ-machines. (A sequel then removes the topological restriction.) This subset of the uHMM topologies has the added benefit that inferred models are guaranteed to be ɛ-machines, irrespective of estimated transition probabilities. Properties of ɛ-machines and uHMMs allow for the derivation of analytic expressions for estimating transition probabilities, inferring start states, and comparing the posterior probability of candidate model topologies, despite process internal structure being only indirectly present in data. We demonstrate BSI's effectiveness in estimating a process's randomness, as reflected by the Shannon entropy rate, and its structure, as quantified by the statistical complexity. We also compare using the posterior distribution over candidate models and the single, maximum a posteriori model for point estimation and show that the former more accurately reflects uncertainty in estimated values. We apply BSI to in-class examples of finite- and infinite-order Markov processes, as well to an out-of-class, infinite-state hidden process.
HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR
International Nuclear Information System (INIS)
Schneider, Michael D.; Dawson, William A.; Hogg, David W.; Marshall, Philip J.; Bard, Deborah J.; Meyers, Joshua; Lang, Dustin
2015-01-01
Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxy properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics
Interest, Inferences, and Learning from Texts
Clinton, Virginia; van den Broek, Paul
2012-01-01
Topic interest and learning from texts have been found to be positively associated with each other. However, the reason for this positive association is not well understood. The purpose of this study is to examine a cognitive process, inference generation, that could explain the positive association between interest and learning from texts. In…
Ignorability in Statistical and Probabilistic Inference
DEFF Research Database (Denmark)
Jaeger, Manfred
2005-01-01
When dealing with incomplete data in statistical learning, or incomplete observations in probabilistic inference, one needs to distinguish the fact that a certain event is observed from the fact that the observed event has happened. Since the modeling and computational complexities entailed...
Inverse Ising inference with correlated samples
International Nuclear Information System (INIS)
Obermayer, Benedikt; Levine, Erel
2014-01-01
Correlations between two variables of a high-dimensional system can be indicative of an underlying interaction, but can also result from indirect effects. Inverse Ising inference is a method to distinguish one from the other. Essentially, the parameters of the least constrained statistical model are learned from the observed correlations such that direct interactions can be separated from indirect correlations. Among many other applications, this approach has been helpful for protein structure prediction, because residues which interact in the 3D structure often show correlated substitutions in a multiple sequence alignment. In this context, samples used for inference are not independent but share an evolutionary history on a phylogenetic tree. Here, we discuss the effects of correlations between samples on global inference. Such correlations could arise due to phylogeny but also via other slow dynamical processes. We present a simple analytical model to address the resulting inference biases, and develop an exact method accounting for background correlations in alignment data by combining phylogenetic modeling with an adaptive cluster expansion algorithm. We find that popular reweighting schemes are only marginally effective at removing phylogenetic bias, suggest a rescaling strategy that yields better results, and provide evidence that our conclusions carry over to the frequently used mean-field approach to the inverse Ising problem. (paper)
Evolutionary inference via the Poisson Indel Process.
Bouchard-Côté, Alexandre; Jordan, Michael I
2013-01-22
We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.
Culture and Pragmatic Inference in Interpersonal Communication
African Journals Online (AJOL)
cognitive process, and that the human capacity for inference is crucially important ... been noted that research in interpersonal communication is currently pushing the ... communicative actions, the social-cultural world of everyday life is not only ... personal experiences of the authors', as documented over time and recreated ...
Inference and the Introductory Statistics Course
Pfannkuch, Maxine; Regan, Matt; Wild, Chris; Budgett, Stephanie; Forbes, Sharleen; Harraway, John; Parsonage, Ross
2011-01-01
This article sets out some of the rationale and arguments for making major changes to the teaching and learning of statistical inference in introductory courses at our universities by changing from a norm-based, mathematical approach to more conceptually accessible computer-based approaches. The core problem of the inferential argument with its…
Statistical Inference on the Canadian Middle Class
Directory of Open Access Journals (Sweden)
Russell Davidson
2018-03-01
Full Text Available Conventional wisdom says that the middle classes in many developed countries have recently suffered losses, in terms of both the share of the total population belonging to the middle class, and also their share in total income. Here, distribution-free methods are developed for inference on these shares, by means of deriving expressions for their asymptotic variances of sample estimates, and the covariance of the estimates. Asymptotic inference can be undertaken based on asymptotic normality. Bootstrap inference can be expected to be more reliable, and appropriate bootstrap procedures are proposed. As an illustration, samples of individual earnings drawn from Canadian census data are used to test various hypotheses about the middle-class shares, and confidence intervals for them are computed. It is found that, for the earlier censuses, sample sizes are large enough for asymptotic and bootstrap inference to be almost identical, but that, in the twenty-first century, the bootstrap fails on account of a strange phenomenon whereby many presumably different incomes in the data are rounded to one and the same value. Another difference between the centuries is the appearance of heavy right-hand tails in the income distributions of both men and women.
Spurious correlations and inference in landscape genetics
Samuel A. Cushman; Erin L. Landguth
2010-01-01
Reliable interpretation of landscape genetic analyses depends on statistical methods that have high power to identify the correct process driving gene flow while rejecting incorrect alternative hypotheses. Little is known about statistical power and inference in individual-based landscape genetics. Our objective was to evaluate the power of causalmodelling with partial...
Cortical information flow during inferences of agency
Dogge, Myrthel; Hofman, Dennis; Boersma, Maria; Dijkerman, H Chris; Aarts, Henk
2014-01-01
Building on the recent finding that agency experiences do not merely rely on sensorimotor information but also on cognitive cues, this exploratory study uses electroencephalographic recordings to examine functional connectivity during agency inference processing in a setting where action and outcome
Quasi-Experimental Designs for Causal Inference
Kim, Yongnam; Steiner, Peter
2016-01-01
When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…
The importance of learning when making inferences
Directory of Open Access Journals (Sweden)
Jorg Rieskamp
2008-03-01
Full Text Available The assumption that people possess a repertoire of strategies to solve the inference problems they face has been made repeatedly. The experimental findings of two previous studies on strategy selection are reexamined from a learning perspective, which argues that people learn to select strategies for making probabilistic inferences. This learning process is modeled with the strategy selection learning (SSL theory, which assumes that people develop subjective expectancies for the strategies they have. They select strategies proportional to their expectancies, which are updated on the basis of experience. For the study by Newell, Weston, and Shanks (2003 it can be shown that people did not anticipate the success of a strategy from the beginning of the experiment. Instead, the behavior observed at the end of the experiment was the result of a learning process that can be described by the SSL theory. For the second study, by Br"oder and Schiffer (2006, the SSL theory is able to provide an explanation for why participants only slowly adapted to new environments in a dynamic inference situation. The reanalysis of the previous studies illustrates the importance of learning for probabilistic inferences.
Colligation, Or the Logical Inference of Interconnection
DEFF Research Database (Denmark)
Falster, Peter
1998-01-01
laws or assumptions. Yet interconnection as an abstract concept seems to be without scientific underpinning in pure logic. Adopting a historical viewpoint, our aim is to show that the reasoning of interconnection may be identified with a neglected kind of logical inference, called "colligation...
Colligation or, The Logical Inference of Interconnection
DEFF Research Database (Denmark)
Franksen, Ole Immanuel; Falster, Peter
2000-01-01
laws or assumptions. Yet interconnection as an abstract concept seems to be without scientific underpinning in oure logic. Adopting a historical viewpoint, our aim is to show that the reasoning of interconnection may be identified with a neglected kind of logical inference, called "colligation...
Inferring motion and location using WLAN RSSI
Kavitha Muthukrishnan, K.; van der Zwaag, B.J.; Havinga, Paul J.M.; Fuller, R.; Koutsoukos, X.
2009-01-01
We present novel algorithms to infer movement by making use of inherent fluctuations in the received signal strengths from existing WLAN infrastructure. We evaluate the performance of the presented algorithms based on classification metrics such as recall and precision using annotated traces
MAPPING THE SURROUNDINGS AS A REQUIREMENT FOR AUTONOMOUS DRIVING
Directory of Open Access Journals (Sweden)
M. Steininger
2016-11-01
Full Text Available Motivated by the hype around driverless cars and the challenges of the sensor integration and data processing, this paper presents a model for using a XBox One Microsoft Kinect stereo camera as sensor for mapping the surroundings. Today, the recognition of the environment of the car is mostly done by a mix of sensors like LiDAR, RADAR and cameras. In the case of the outdoor delivery challenge Robotour 2016 with model cars in scale 1:5, it is our goal to solve the task with one camera only. To this end, a three-stage approach was developed. The test results show that our approach can detect and locate objects at a range of up to eight meters in order to incorporate them as barriers in the navigation process.
Natural occurring radioactivity in Palmyra and its surrounding
International Nuclear Information System (INIS)
Al-Masri, M. S.; Shwekani, R.; Raja, G.; Hushari, M.; Al-Hent, R.; Issa, M.
2006-06-01
In this work, the natural radiation background has been carried out for Palmyra city and its surroundings area. The study has covered gamma radiation measurements, indoor radon gas concentration and radionuclides levels in environmental samples (soil, water, plat). The results showed that indoor radon gas concentrations and radiation exposure rates are within the background levels. Also, the results showed that there is no artificial radiation in the area and there is no correlation between the natural radiation levels and the reported cancer cases. Therefore, the reported cancer cases in this area may be due to non-radiation cases, which must be investigated, or they are within the natural levels in Syria unless accurate statistics proves the opposite. (author)
Physical geography of the Nete basin and surroundings
International Nuclear Information System (INIS)
Beerten, K.
2011-01-01
The report briefly describes the main features of the physical geography of the Nete basin (Campine region, Belgium) and its immediate surroundings. First, an integrated overview of the topography, morphology and hydrography is given. This overview serves as the basis for the assessment of the morphological stability of the region and also explains the relationship between the topography and the hydrology. Furthermore, special attention is paid to soil science including a quantitative survey of some soil characteristics data. Another part of this report deals with erosion processes caused by water and wind action, and the (potential) impact on the morphology. Finally, the palaeogeographical evolution during the Quaternary is discussed. This evolution shows that the environment is stable over 10 000 years or more in the current and similar climatic conditions. Altering climatic conditions, notably glacial-interglacial periods, have impacted erosion with periods of strong erosion.
Precision Security: Integrating Video Surveillance with Surrounding Environment Changes
Directory of Open Access Journals (Sweden)
Wenfeng Wang
2018-01-01
Full Text Available Video surveillance plays a vital role in maintaining the social security although, until now, large uncertainty still exists in danger understanding and recognition, which can be partly attributed to intractable environment changes in the backgrounds. This article presents a brain-inspired computing of attention value of surrounding environment changes (EC with a processes-based cognition model by introducing a ratio value λ of EC-implications within considered periods. Theoretical models for computation of warning level of EC-implications to the universal video recognition efficiency (quantified as time cost of implication-ratio variations from λk to λk+1, k=1,2,… are further established. Imbedding proposed models into the online algorithms is suggested as a future research priority towards precision security for critical applications and, furthermore, schemes for a practical implementation of such integration are also preliminarily discussed.
A Study of the Flow Field Surrounding Interacting Line Fires
Directory of Open Access Journals (Sweden)
Trevor Maynard
2016-01-01
Full Text Available The interaction of converging fires often leads to significant changes in fire behavior, including increased flame length, angle, and intensity. In this paper, the fluid mechanics of two adjacent line fires are studied both theoretically and experimentally. A simple potential flow model is used to explain the tilting of interacting flames towards each other, which results from a momentum imbalance triggered by fire geometry. The model was validated by measuring the velocity field surrounding stationary alcohol pool fires. The flow field was seeded with high-contrast colored smoke, and the motion of smoke structures was analyzed using a cross-correlation optical flow technique. The measured velocities and flame angles are found to compare reasonably with the predicted values, and an analogy between merging fires and wind-blown flames is proposed.
Teacher Leadership: Everyday Practices Surrounding Work- Related Stress
Directory of Open Access Journals (Sweden)
Chiweshe Nigel
2015-06-01
Full Text Available This interpretivist study contributes to our scholarly understanding of how everyday practices surrounding work-related stress in education affect teacher leadership and successful learning outcomes. Insights are drawn from our long-standing engagement in the field where we observed how teaching staff, students, and management interacted. These observations were supplemented by in-depth interviews with 20 teaching staff. Our findings reveal competing demands and practices across the individual intrapersonal environment and the work related environment. There were three key themes that emerged in answer to the core research question: 1 the role of relational practices in managing teacher burnout, 2 the role of surveillance practices in education and 3 the role of assimilating practices in education. Drawing insights from these practices, we develop a conceptual framework that will help us to see relations at work anew, and develop a deeper understanding of ‘sickies’, motivation, learning outcomes and teacher leadership opportunities in education
Biogeography of azooxanthellate corals in the Caribbean and surrounding areas
Dawson, J.
2002-04-01
Biogeographic patterns for azooxanthellate corals are not as well known as those of zooxanthellate (primarily reef-building) corals. I analyzed occurrences of 129 species of azooxanthellate corals in 19 geopolitical regions in the Caribbean and surrounding areas. I performed an unweighted pair-group method with arithmetic averages (UPGMA) cluster analysis using Bray-Curtis' similarity measure on the complete data set and shallow- and deep-water subsets of the data. The results indicate two provinces, each with a widespread (tropical and subtropical distributions) component to its fauna. One province has a tropical and primarily insular component to it, while the other has a subtropical and primarily continental component. By contrast, zooxanthellate corals have a uniform faunal composition throughout the Caribbean. Moreover, zooxanthellate corals have half as many species in the Caribbean as the azooxanthellate corals even though their global diversities are equal. These differences in diversity and geographic distribution patterns should be considered when developing conservation strategies.
The surrounding tissue modifies the placental stem villous vascular responses
DEFF Research Database (Denmark)
Brøgger, Torbjørn; Forman, Axel; Aalkjær, Christian
2014-01-01
is available. In-depth understanding of the mechanisms involved in control of placental vascular tone are needed to develop new tissue targets for therapeutic intervention. Method: From fresh born placentas segments of stem villous arteries were carefully dissected. The artery branches were divided....... The surrounding trophoblast was removed from one end and left intact in the other, and the segment was divided to give two ring preparations, with or without trophoblast. The preparations were mounted in wire myographs and responses to vasoactive agents were compared. Results: pD2values for PGF2α, Tx-analog U...... or endotheline-1. These differences partly disappeared in the presence of L-NAME. Conclusion: The perivascular tissue significantly reduces sensitivity and force development of stem villous arteries, partly due to release of NO This represents a new mechanism for control of human stem villous artery tone....
Influence of surrounding environment on subcritical crack growth in marble
Nara, Yoshitaka; Kashiwaya, Koki; Nishida, Yuki; , Toshinori, Ii
2017-06-01
Understanding subcritical crack growth in rock is essential for determining appropriate measures to ensure the long-term integrity of rock masses surrounding structures and for construction from rock material. In this study, subcritical crack growth in marble was investigated experimentally, focusing on the influence of the surrounding environment on the relationship between the crack velocity and stress intensity factor. The crack velocity increased with increasing temperature and/or relative humidity. In all cases, the crack velocity increased with increasing stress intensity factor. However, for Carrara marble (CM) in air, we observed a region in which the crack velocity still increased with temperature, but the increase in the crack velocity with increasing stress intensity factor was not significant. This is similar to Region II of subcritical crack growth observed in glass in air. Region II in glass is controlled by mass transport to the crack tip. In the case of rock, the transport of water to the crack tip is important. In general, Region II is not observed for subcritical crack growth in rock materials, because rocks contain water. Because the porosity of CM is very low, the amount of water contained in the marble is also very small. Therefore, our results imply that we observed Region II in CM. Because the crack velocity increased in both water and air with increasing temperature and humidity, we concluded that dry conditions at low temperature are desirable for the long-term integrity of a carbonate rock mass. Additionally, mass transport to the crack tip is an important process for subcritical crack growth in rock with low porosity.
Quasars Probing Quasars: the Circumgalactic Medium Surrounding z ~ 2 Quasars
Lau, Marie; Quasars Probing Quasars survey
2018-01-01
Understanding the circumgalactic medium--the gaseous halo surrounding a galaxy, is an integral part to understanding galaxy evolution. The z ~ 2-3 universe is interesting as this is when the star formation rate and AGN activity peak. My thesis concludes the decade-long Quasars Probing Quasars survey designed for studying massive galaxy formation and quasar feedback. I use background quasar sightlines that pass close to foreground quasars to study the circumgalactic medium of quasar-host galaxies in absorption. My sample of 149 quasar pairs involve spectra taken with 17 different optical and near IR instruments. I present results on the statistical and physical properties of the circumgalactic medium. The circumgalactic medium is enriched even beyond the virial radius. The alpha/Fe abundance ratio is enhanced, suggesting enrichment from core-collapse supernovae. The cool gas mass within the virial radius is enough to fuel star formation for another Gyr, and may account for 1/3 of the baryonic budget of the galaxy halo. The ionization state increases with projected distance from the quasar, which implies the quasar does not dominate the ionizing radiation flux. However, detection of fluorescent Lyman-alpha emission and NV absorption imply these transverse absorbers are partially illuminated by the quasar. In one peculiar case, the absorbing clump has density >100 cm^-3 and sub-parsec size. The average absorption in the circumgalactic medium exhibits large velocity widths, and is asymmetric about the systemic redshift of the galaxies. The widths are consistent with gravitational motions and Hubble flow, and outflows are not required to explain them. The asymmetry can be explained if the ionizing radiation from the quasar is anisotropic or intermittent and the gas is not in inflow. My results pose challenges for cosmological hydrodynamic simulations to produce a substantial cool gas reservoir surrounding quasars, that is also enriched and shows extreme kinematics.
International Nuclear Information System (INIS)
1994-05-01
An aerial radiological survey was conducted over the Fort Calhoun Nuclear Power Plant in Fort Calhoun, Nebraska, during the period June 19 through June 28, 1993. The survey was conducted at an altitude of 150 feet (46 meters) over a 25-square-mile (65-square-kilometer) area centered on the power station. The purpose of the survey was to document the terrestrial gamma radiation environment of the Fort Calhoun Nuclear Power Plant and surrounding area. The results of the aerial survey are reported as inferred gamma radiation exposure rates at 1 meter above ground level in the form of a contour map. Outside the plant boundary, exposure rates were found to vary between 6 and 12 microroentgens per hour and were attributed to naturally-occurring uranium, thorium, and potassium. The aerial data were compared to ground-based benchmark exposure rate measurements and radionuclide assays of soil samples obtained within the survey boundary. The ground-based measurements were found to be in good agreement with those inferred from the aerial measuring system. A previous survey was conducted on August 9 and 10, 1972, before the plant began operation. Exposure rates measured in both surveys were consistent with normal terrestrial background
How A Black Hole Lights Up Its Surroundings
Kohler, Susanna
2017-10-01
How do the supermassive black holes that live at the centers of galaxies influence their environments? New observations of a distant active galaxy offer clues about this interaction.Signs of CoevolutionPlot demonstrating the m-sigma relation, the empirical correlation between the stellar velocity dispersion of a galactic bulge and the mass of the supermassive black hole at its center. [Msigma]We know that the centers of active galaxies host supermassive black holes with masses of millions to billions of suns. One mystery surrounding these beasts is that they are observed to evolve simultaneously with their host galaxies for instance, an empirical relationship is seen between the growth of a black hole and the growth of its host galaxys bulge. This suggests that there must be a feedback mechanism through which the evolution of a black hole is linked to that of its host galaxy.One proposed source of this coupling is the powerful jets emitted from the poles of these supermassive black holes. These jets are thought to be produced as some of the material accreting onto the black hole is flung out, confined by surrounding gas and magnetic fields. Because the jets of hot gas and radiation extend outward through the host galaxy, they provide a means for the black hole to influence the gas and dust of its surroundings.In our current model of a radio-loud active galactic nuclei,a region of hot, ionized gas the narrow-line region lies beyond the sphere of influence of the supermassive black hole. [C.M. Urry and P. Padovani]Clues in the Narrow-Line RegionThe region of gas thought to sit just outside of the black holes sphere of influence (at a distance of perhaps a thousand to a few thousand light-years) is known as the narrow line region so named because we observe narrow emission lines from this gas. Given its hot, ionized state, this gas must somehow be being pummeled with energy. In the canonical picture, radiation from the black hole heats the gas directly in a process
Active inference, sensory attenuation and illusions.
Brown, Harriet; Adams, Rick A; Parees, Isabel; Edwards, Mark; Friston, Karl
2013-11-01
Active inference provides a simple and neurobiologically plausible account of how action and perception are coupled in producing (Bayes) optimal behaviour. This can be seen most easily as minimising prediction error: we can either change our predictions to explain sensory input through perception. Alternatively, we can actively change sensory input to fulfil our predictions. In active inference, this action is mediated by classical reflex arcs that minimise proprioceptive prediction error created by descending proprioceptive predictions. However, this creates a conflict between action and perception; in that, self-generated movements require predictions to override the sensory evidence that one is not actually moving. However, ignoring sensory evidence means that externally generated sensations will not be perceived. Conversely, attending to (proprioceptive and somatosensory) sensations enables the detection of externally generated events but precludes generation of actions. This conflict can be resolved by attenuating the precision of sensory evidence during movement or, equivalently, attending away from the consequences of self-made acts. We propose that this Bayes optimal withdrawal of precise sensory evidence during movement is the cause of psychophysical sensory attenuation. Furthermore, it explains the force-matching illusion and reproduces empirical results almost exactly. Finally, if attenuation is removed, the force-matching illusion disappears and false (delusional) inferences about agency emerge. This is important, given the negative correlation between sensory attenuation and delusional beliefs in normal subjects--and the reduction in the magnitude of the illusion in schizophrenia. Active inference therefore links the neuromodulatory optimisation of precision to sensory attenuation and illusory phenomena during the attribution of agency in normal subjects. It also provides a functional account of deficits in syndromes characterised by false inference
International Nuclear Information System (INIS)
1985-10-01
An aerial radiological survey was performed over the area surrounding the Feed Materials Production Center, located near Fernald, Ohio, during the period April 24 to 27, 1985. The survey covered a 70-square-kilometer (27-square-mile) area centered on the plant. The highest exposure rates, in excess of 0.35 milliroentgens per hour (mR/h), were inferred from the data measured directly over the plant. This radiation was due to the presence of nuclides which were consistent with normal plant operations. For the remainder of the survey area, the inferred radiation exposure rates, varying from 6 to 12 microroentgens per hour (μR/h), were due to naturally-occurring potassium, uranium, thorium, and daughter products. The reported exposure rate values include an estimated cosmic ray contribution of 3.7μR/h. Ground-based measurements, conducted during the time of the aerial survey, were compared to the aerial results. Pressurized ionization chamber readings and a group of soil samples were acquired at several locations within the survey area. The exposure rate values obtained from these measurements were in agreement with the inferred aerial results. Soil sample results showed several areas just outside the site boundary with slightly elevated amounts of U-238. The levels, however, were well below the detection limit of the aerial system. The only off-site area that showed apparent above background activity in the aerial data was directly west of the storage silos. The symmetric shape of the contours, however, suggests that these elevated levels are due to ''shine'' from material stored on-site in the silos and not to actual off-site contamination. Detailed comparison of the 1985 aerial survey data with a previous survey conducted in 1976 showed no significant change in any area outside the plant boundary. 6 refs., 9 figs., 3 tabs
Analysing land cover and land use change in the Matobo National Park and surroundings in Zimbabwe
Scharsich, Valeska; Mtata, Kupakwashe; Hauhs, Michael; Lange, Holger; Bogner, Christina
2016-04-01
Natural forests are threatened worldwide, therefore their protection in National Parks is essential. Here, we investigate how this protection status affects the land cover. To answer this question, we analyse the surface reflectance of three Landsat images of Matobo National Park and surrounding in Zimbabwe from 1989, 1998 and 2014 to detect changes in land cover in this region. To account for the rolling countryside and the resulting prominent shadows, a topographical correction of the surface reflectance was required. To infer land cover changes it is not only necessary to have some ground data for the current satellite images but also for the old ones. In particular for the older images no recent field study could help to reconstruct these data reliably. In our study we follow the idea that land cover classes of pixels in current images can be transferred to the equivalent pixels of older ones if no changes occurred meanwhile. Therefore we combine unsupervised clustering with supervised classification as follows. At first, we produce a land cover map for 2014. Secondly, we cluster the images with clara, which is similar to k-means, but suitable for large data sets. Whereby the best number of classes were determined to be 4. Thirdly, we locate unchanged pixels with change vector analysis in the images of 1989 and 1998. For these pixels we transfer the corresponding cluster label from 2014 to 1989 and 1998. Subsequently, the classified pixels serve as training data for supervised classification with random forest, which is carried out for each image separately. Finally, we derive land cover classes from the Landsat image in 2014, photographs and Google Earth and transfer them to the other two images. The resulting classes are shrub land; forest/shallow waters; bare soils/fields with some trees/shrubs; and bare light soils/rocks, fields and settlements. Subsequently the three different classifications are compared and land changes are mapped. The main changes are
International Nuclear Information System (INIS)
Maurer, R.J.
1989-09-01
An aerial radiological survey of the Oak Ridge Reservation (ORR) and surrounding area in Oak Ridge, Tennessee, was conducted from September 12--29, 1989. The purpose of the survey was to measure and document the site's terrestrial radiological environment for use in effective environmental management and emergency response planning. The aerial survey was flown at an altitude of 91 meters (300 feet) along a series of parallel lines 152 meters (500 feet) apart. The survey encompassed an area of 440 square kilometers (170 square miles) as defined by the Tennessee Valley Authority Map S-16A of the entire Oak Ridge Reservation and adjacent area. The results of the aerial survey are reported as inferred exposure rates at 1 meter above ground level (AGL) in the form of a radiation contour map. Typical background exposure rates were found to vary from 5 to 14 microroentgens per hour (μR/h). The man-made radionuclides, cobalt-60, cesium-137, and protactinium-234m (a radioisotope indicative of depleted uranium), were detected at several facilities on the site. In support of the aerial survey, ground-based exposure rate and soil sample measurements were obtained at several locations within the survey boundary. In addition to the large scale aerial survey, two special flyovers were requested by the Department of Energy. The first request was to conduct a survey of a 1-mile x 2-mile area in south Knoxville, Tennessee. The area had been used previously to store contaminated scrap metals from operations at the Oak Ridge site. The second request was to fly several passes over a 5-mile length of railroad tracks leading from the Oak Ridge Y-12 Plant, north through the city of Oak Ridge. The railroad tracks had been previously used in the transport of cesium-137
Tomography images of the Alpine roots and surrounding upper mantle
Plomerova, Jaroslava; Babuska, Vladislav
2017-04-01
Teleseismic body-wave tomography represents powerful tool to study regional velocity structure of the upper mantle and to image velocity anomalies, such as subducted lithosphere plates in collisional zones. In this contribution, we recapitulate 3D models of the upper mantle beneath the Alps, which developed at a collision zone of the Eurasian and African plates. Seismic tomography studies indicate a leading role of the rigid mantle lithosphere that functioned as a major stress guide during the plate collisions. Interactions of the European lithosphere with several micro-plates in the south resulted in an arcuate shape of this mountain range on the surface and in a complicated geometry of the Alpine subductions in the mantle. Early models with one bended lithosphere root have been replaced with more advanced models showing two separate lithosphere roots beneath the Western and Eastern Alps (Babuska et al., Tectonophysics 1990; Lippitsch et al., JGR 2003). The standard isotropic velocity tomography, based on pre-AlpArray data (the currently performed passive seismic experiment in the Alps and surroundings) images the south-eastward dipping curved slab of the Eurasian lithosphere in the Western Alps. On the contrary, beneath the Eastern Alps the results indicate a very steep northward dipping root that resulted from the collision of the European plate with the Adriatic microplate. Dando et al. (2011) interpret high-velocity heterogeneities at the bottom of their regional tomographic model as a graveyard of old subducted lithospheres. High density of stations, large amount of rays and dense ray-coverage of the volume studied are not the only essential pre-requisites for reliable tomography results. A compromise between the amount of pre-processed data and the high-quality of the tomography input (travel-time residuals) is of the high importance as well. For the first time, the existence of two separate roots beneath the Alps has been revealed from carefully pre
Likelihood inference for unions of interacting discs
DEFF Research Database (Denmark)
Møller, Jesper; Helisová, Katarina
To the best of our knowledge, this is the first paper which discusses likelihood inference or a random set using a germ-grain model, where the individual grains are unobservable edge effects occur, and other complications appear. We consider the case where the grains form a disc process modelled...... is specified with respect to a given marked Poisson model (i.e. a Boolean model). We show how edge effects and other complications can be handled by considering a certain conditional likelihood. Our methodology is illustrated by analyzing Peter Diggle's heather dataset, where we discuss the results...... of simulation-based maximum likelihood inference and the effect of specifying different reference Poisson models....
An Intuitive Dashboard for Bayesian Network Inference
International Nuclear Information System (INIS)
Reddy, Vikas; Farr, Anna Charisse; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K D V
2014-01-01
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++
The NIFTY way of Bayesian signal inference
International Nuclear Information System (INIS)
Selig, Marco
2014-01-01
We introduce NIFTY, 'Numerical Information Field Theory', a software package for the development of Bayesian signal inference algorithms that operate independently from any underlying spatial grid and its resolution. A large number of Bayesian and Maximum Entropy methods for 1D signal reconstruction, 2D imaging, as well as 3D tomography, appear formally similar, but one often finds individualized implementations that are neither flexible nor easily transferable. Signal inference in the framework of NIFTY can be done in an abstract way, such that algorithms, prototyped in 1D, can be applied to real world problems in higher-dimensional settings. NIFTY as a versatile library is applicable and already has been applied in 1D, 2D, 3D and spherical settings. A recent application is the D 3 PO algorithm targeting the non-trivial task of denoising, deconvolving, and decomposing photon observations in high energy astronomy
The NIFTy way of Bayesian signal inference
Selig, Marco
2014-12-01
We introduce NIFTy, "Numerical Information Field Theory", a software package for the development of Bayesian signal inference algorithms that operate independently from any underlying spatial grid and its resolution. A large number of Bayesian and Maximum Entropy methods for 1D signal reconstruction, 2D imaging, as well as 3D tomography, appear formally similar, but one often finds individualized implementations that are neither flexible nor easily transferable. Signal inference in the framework of NIFTy can be done in an abstract way, such that algorithms, prototyped in 1D, can be applied to real world problems in higher-dimensional settings. NIFTy as a versatile library is applicable and already has been applied in 1D, 2D, 3D and spherical settings. A recent application is the D3PO algorithm targeting the non-trivial task of denoising, deconvolving, and decomposing photon observations in high energy astronomy.
Bayesianism and inference to the best explanation
Directory of Open Access Journals (Sweden)
Valeriano IRANZO
2008-01-01
Full Text Available Bayesianism and Inference to the best explanation (IBE are two different models of inference. Recently there has been some debate about the possibility of “bayesianizing” IBE. Firstly I explore several alternatives to include explanatory considerations in Bayes’s Theorem. Then I distinguish two different interpretations of prior probabilities: “IBE-Bayesianism” (IBE-Bay and “frequentist-Bayesianism” (Freq-Bay. After detailing the content of the latter, I propose a rule for assessing the priors. I also argue that Freq-Bay: (i endorses a role for explanatory value in the assessment of scientific hypotheses; (ii avoids a purely subjectivist reading of prior probabilities; and (iii fits better than IBE-Bayesianism with two basic facts about science, i.e., the prominent role played by empirical testing and the existence of many scientific theories in the past that failed to fulfil their promises and were subsequently abandoned.
Dopamine, reward learning, and active inference
Directory of Open Access Journals (Sweden)
Thomas eFitzgerald
2015-11-01
Full Text Available Temporal difference learning models propose phasic dopamine signalling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward. Nevertheless, a large body of data also shows that dopamine is not necessary for learning, and that dopamine depletion primarily affects task performance. We offer a resolution to this paradox based on an hypothesis that dopamine encodes the precision of beliefs about alternative actions, and thus controls the outcome-sensitivity of behaviour. We extend an active inference scheme for solving Markov decision processes to include learning, and show that simulated dopamine dynamics strongly resemble those actually observed during instrumental conditioning. Furthermore, simulated dopamine depletion impairs performance but spares learning, while simulated excitation of dopamine neurons drives reward learning, through aberrant inference about outcome states. Our formal approach provides a novel and parsimonious reconciliation of apparently divergent experimental findings.
Dopamine, reward learning, and active inference.
FitzGerald, Thomas H B; Dolan, Raymond J; Friston, Karl
2015-01-01
Temporal difference learning models propose phasic dopamine signaling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward. Nevertheless, a large body of data also shows that dopamine is not necessary for learning, and that dopamine depletion primarily affects task performance. We offer a resolution to this paradox based on an hypothesis that dopamine encodes the precision of beliefs about alternative actions, and thus controls the outcome-sensitivity of behavior. We extend an active inference scheme for solving Markov decision processes to include learning, and show that simulated dopamine dynamics strongly resemble those actually observed during instrumental conditioning. Furthermore, simulated dopamine depletion impairs performance but spares learning, while simulated excitation of dopamine neurons drives reward learning, through aberrant inference about outcome states. Our formal approach provides a novel and parsimonious reconciliation of apparently divergent experimental findings.
Inferring genetic interactions from comparative fitness data.
Crona, Kristina; Gavryushkin, Alex; Greene, Devin; Beerenwinkel, Niko
2017-12-20
Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite Plasmodium vivax , the fungus Aspergillus niger , and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.
An emergent approach to analogical inference
Thibodeau, Paul H.; Flusberg, Stephen J.; Glick, Jeremy J.; Sternberg, Daniel A.
2013-03-01
In recent years, a growing number of researchers have proposed that analogy is a core component of human cognition. According to the dominant theoretical viewpoint, analogical reasoning requires a specific suite of cognitive machinery, including explicitly coded symbolic representations and a mapping or binding mechanism that operates over these representations. Here we offer an alternative approach: we find that analogical inference can emerge naturally and spontaneously from a relatively simple, error-driven learning mechanism without the need to posit any additional analogy-specific machinery. The results also parallel findings from the developmental literature on analogy, demonstrating a shift from an initial reliance on surface feature similarity to the use of relational similarity later in training. Variants of the model allow us to consider and rule out alternative accounts of its performance. We conclude by discussing how these findings can potentially refine our understanding of the processes that are required to perform analogical inference.
Pointwise probability reinforcements for robust statistical inference.
Frénay, Benoît; Verleysen, Michel
2014-02-01
Statistical inference using machine learning techniques may be difficult with small datasets because of abnormally frequent data (AFDs). AFDs are observations that are much more frequent in the training sample that they should be, with respect to their theoretical probability, and include e.g. outliers. Estimates of parameters tend to be biased towards models which support such data. This paper proposes to introduce pointwise probability reinforcements (PPRs): the probability of each observation is reinforced by a PPR and a regularisation allows controlling the amount of reinforcement which compensates for AFDs. The proposed solution is very generic, since it can be used to robustify any statistical inference method which can be formulated as a likelihood maximisation. Experiments show that PPRs can be easily used to tackle regression, classification and projection: models are freed from the influence of outliers. Moreover, outliers can be filtered manually since an abnormality degree is obtained for each observation. Copyright © 2013 Elsevier Ltd. All rights reserved.
Statistical inference from imperfect photon detection
International Nuclear Information System (INIS)
Audenaert, Koenraad M R; Scheel, Stefan
2009-01-01
We consider the statistical properties of photon detection with imperfect detectors that exhibit dark counts and less than unit efficiency, in the context of tomographic reconstruction. In this context, the detectors are used to implement certain positive operator-valued measures (POVMs) that would allow us to reconstruct the quantum state or quantum process under consideration. Here we look at the intermediate step of inferring outcome probabilities from measured outcome frequencies, and show how this inference can be performed in a statistically sound way in the presence of detector imperfections. Merging outcome probabilities for different sets of POVMs into a consistent quantum state picture has been treated elsewhere (Audenaert and Scheel 2009 New J. Phys. 11 023028). Single-photon pulsed measurements as well as continuous wave measurements are covered.
An Intuitive Dashboard for Bayesian Network Inference
Reddy, Vikas; Charisse Farr, Anna; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K. D. V.
2014-03-01
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.
Working with sample data exploration and inference
Chaffe-Stengel, Priscilla
2014-01-01
Managers and analysts routinely collect and examine key performance measures to better understand their operations and make good decisions. Being able to render the complexity of operations data into a coherent account of significant events requires an understanding of how to work well with raw data and to make appropriate inferences. Although some statistical techniques for analyzing data and making inferences are sophisticated and require specialized expertise, there are methods that are understandable and applicable by anyone with basic algebra skills and the support of a spreadsheet package. By applying these fundamental methods themselves rather than turning over both the data and the responsibility for analysis and interpretation to an expert, managers will develop a richer understanding and potentially gain better control over their environment. This text is intended to describe these fundamental statistical techniques to managers, data analysts, and students. Statistical analysis of sample data is enh...
Parametric inference for biological sequence analysis.
Pachter, Lior; Sturmfels, Bernd
2004-11-16
One of the major successes in computational biology has been the unification, by using the graphical model formalism, of a multitude of algorithms for annotating and comparing biological sequences. Graphical models that have been applied to these problems include hidden Markov models for annotation, tree models for phylogenetics, and pair hidden Markov models for alignment. A single algorithm, the sum-product algorithm, solves many of the inference problems that are associated with different statistical models. This article introduces the polytope propagation algorithm for computing the Newton polytope of an observation from a graphical model. This algorithm is a geometric version of the sum-product algorithm and is used to analyze the parametric behavior of maximum a posteriori inference calculations for graphical models.
Inferences on Children’s Reading Groups
Directory of Open Access Journals (Sweden)
Javier González García
2009-05-01
Full Text Available This article focuses on the non-literal information of a text, which can be inferred from key elements or clues offered by the text itself. This kind of text is called implicit text or inference, due to the thinking process that it stimulates. The explicit resources that lead to information retrieval are related to others of implicit information, which have increased their relevance. In this study, during two courses, how two teachers interpret three stories and how they establish a debate dividing the class into three student groups, was analyzed. The sample was formed by two classes of two urban public schools of Burgos capital (Spain, and two of public schools of Tampico (Mexico. This allowed us to observe an increasing percentage value of the group focused in text comprehension, and a lesser percentage of the group perceiving comprehension as a secondary objective.
A nebula of gases from Io surrounding Jupiter.
Krimigis, Stamatios M; Mitchell, Donald G; Hamilton, Douglas C; Dandouras, Jannis; Armstrong, Thomas P; Bolton, Scott J; Cheng, Andrew F; Gloeckler, George; Hsieh, K C; Keath, Edwin P; Krupp, Norbert; Lagg, Andreas; Lanzerotti, Louis J; Livi, Stefano; Mauk, Barry H; McEntire, Richard W; Roelof, Edmond C; Wilken, Berend; Williams, Donald J
2002-02-28
Several planetary missions have reported the presence of substantial numbers of energetic ions and electrons surrounding Jupiter; relativistic electrons are observable up to several astronomical units (au) from the planet. A population of energetic (>30[?]keV) neutral particles also has been reported, but the instrumentation was not able to determine the mass or charge state of the particles, which were subsequently labelled energetic neutral atoms. Although images showing the presence of the trace element sodium were obtained, the source and identity of the neutral atoms---and their overall significance relative to the loss of charged particles from Jupiter's magnetosphere---were unknown. Here we report the discovery by the Cassini spacecraft of a fast (>103[?]km[?]s-1) and hot magnetospheric neutral wind extending more than 0.5[?]au from Jupiter, and the presence of energetic neutral atoms (both hot and cold) that have been accelerated by the electric field in the solar wind. We suggest that these atoms originate in volcanic gases from Io, undergo significant evolution through various electromagnetic interactions, escape Jupiter's magnetosphere and then populate the environment around the planet. Thus a 'nebula' is created that extends outwards over hundreds of jovian radii.
Earthquakes in Switzerland and surrounding regions during 2006
Energy Technology Data Exchange (ETDEWEB)
Baer, M.; Deichmann, N.; Braunmiller, J.; Clinton, J.; Husen, S.; Faeh, D.; Giardini, D.; Kaestli, P.; Kradolfer, U.; Wiemer, S
2007-12-15
This report of the Swiss Seismological Service summarizes the seismic activity in Switzerland and surrounding regions during 2006. During this period, 572 earthquakes and 91 quarry blasts were detected and located in the region under consideration. Of these earthquakes, two occurred in conjunction with the construction of the new Gotthard railway tunnel and 165 were induced artificially by the stimulation of a proposed geothermal reservoir beneath the city of Basel. With 20 events with {mu}{sub {iota}} {>=} 2.5, five of which were artificially induced, the seismic activity in the year 2006 was far below the average over the previous 31 years. Nevertheless, six events were felt by the public, most prominently the strongest of the induced Basel events ({mu}{sub {iota}} 3.4), which caused some non-structural building damage. Noteworthy are also the two earthquakes near Cortaillod ({mu}{sub {iota}} 3.2), on the shore of Lake Neuchatel, and in Val Mora ({mu}{sub {iota}} 3.5), between the Engadin and Val Muestair, as well as the 42 aftershocks of the {mu}{sub {iota}} 4.9 Vallorcine earthquake, between Martigny and Chamonix, of September 2005. (author)
Mercury's interior, surface, and surrounding environment latest discoveries
Clark, Pamela Elizabeth
2015-01-01
This SpringerBrief details the MESSENGER Mission, the findings of which present challenges to widely held conventional views and remaining mysteries surrounding the planet. The work answers the question of why Mercury is so dense, and the implications from geochemical data on its planetary formation. It summarizes imaging and compositional data from the terrestrial planet surface processes and explains the geologic history of Mercury. It also discusses the lack of southern hemisphere coverage. Our understanding of the planet Mercury has been in a transitional phase over the decades since Mariner 10. The influx of new data from the NASA MESSENGER Mission since it was inserted into the orbit of Mercury in March of 2011 has greatly accelerated that shift. The combined compositional data of relatively high volatiles (S, K), relatively low refractories (Al, Ca), and low crustal iron, combined with an active, partially molten iron rich core, has major implications for Mercury and Solar System formation. From a s...
Groundwater quality in Taiz City and surrounding area, Yemen Republic
International Nuclear Information System (INIS)
Metwali, R.
2002-01-01
Fifty one water samples were collected from production wells used for human consumption from Taiz City and its surroundings, Yemen Republic. The water quality was investigated with respect to bacteriological and physico-chemical parameters. The achieved results revealed that most water samples, especially from private wells, contain a high number of total coliforms (TC) which exceed the permissible limit recommended by the World Health Organization, WHO (1996). Also faecal coliforms (FC) were recorded in the majority of polluted samples. A quantitative estimation was done for each of temperature (18-26C), pH (6.12-8.79), total hardness (58-2200 mg/L), electrical conductivity (218-4600 m.Mohs), total dissolved solids (117-3700mg/L), nitrate (10-187mg/L) and type of aquifer (rocky and alluvium). It is worthy to notice that from the total of fifty-one wells, there was pollution in (65%) of them. Recommendations were suggested for the treatment of the water of such polluted wells and rigid government control in a trial to prevent human and animal illness. (author)
Motor training reduces surround inhibition in the motor cortex.
Akkad, Haya; Di Stasio, Flavio; Tibold, Robert; Kassavetis, Panagiotis; Rothwell, John C; Edwards, Mark J
2016-06-01
Surround inhibition (SI) is thought to facilitate focal contraction of a hand muscle by keeping nearby muscles silent. Unexpectedly, SI is reduced in skilled pianists. We tested whether repeated practice of focal contraction in non-pianists could reduce SI. Motor-evoked potentials were elicited by transcranial magnetic stimulation in the relaxed abductor digiti minimi randomly at the onset and 5s after offset of a 2s focal contraction (10% maximum) of the first dorsal interosseous (FDI). Over 5 blocks of 40 trials participants obtained points for increasing contraction speed and stability in FDI. In a final block, the interval between contractions was varied randomly to increase attention to the task. Over the first 5 blocks, SI declined as performance (points scored) improved. In the final "attention" block SI increased towards baseline without affecting performance. Although SI may be useful during the early stages of learning, skilled focal finger movement does not require SI to prevent activity in non-involved muscles. This could be due to better targeting of the excitatory command to move. Results from the final block suggest that increased attention can re-engage SI when task parameters change. SI is not necessary for successful focal contraction, but may contribute during learning and during attention to task. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Democratizing rendering for multiple viewers in surround VR systems
Schulze, Jürgen P.
2012-03-01
We present a new approach for how multiple users\\' views can be rendered in a surround virtual environment without using special multi-view hardware. It is based on the idea that different parts of the screen are often viewed by different users, so that they can be rendered from their own view point, or at least from a point closer to their view point than traditionally expected. The vast majority of 3D virtual reality systems are designed for one head-tracked user, and a number of passive viewers. Only the head tracked user gets to see the correct view of the scene, everybody else sees a distorted image. We reduce this problem by algorithmically democratizing the rendering view point among all tracked users. Researchers have proposed solutions for multiple tracked users, but most of them require major changes to the display hardware of the VR system, such as additional projectors or custom VR glasses. Our approach does not require additional hardware, except the ability to track each participating user. We propose three versions of our multi-viewer algorithm. Each of them balances image distortion and frame rate in different ways, making them more or less suitable for certain application scenarios. Our most sophisticated algorithm renders each pixel from its own, optimized camera perspective, which depends on all tracked users\\' head positions and orientations. © 2012 IEEE.
Kim, Hyun-Jung; King, Glen C.; Park, Yeonjoon; Lee, Kunik; Choi, Sang H.
2011-01-01
Direct conversion of thermal energy to electricity by thermoelectric (TE) devices may play a key role in future energy production and utilization. However, relatively poor performance of current TE materials has slowed development of new energy conversion applications. Recent reports have shown that the dimensionless Figure of Merit, ZT, for TE devices can be increased beyond the state-of-the-art level by nanoscale structuring of materials to reduce their thermal conductivity. New morphologically designed TE materials have been fabricated at the NASA Langley Research Center, and their characterization is underway. These newly designed materials are based on semiconductor crystal grains whose surfaces are surrounded by metallic nanoparticles. The nanoscale particles are used to tailor the thermal and electrical conduction properties for TE applications by altering the phonon and electron transport pathways. A sample of bismuth telluride decorated with metallic nanoparticles showed less thermal conductivity and twice the electrical conductivity at room temperature as compared to pure Bi2Te3. Apparently, electrons cross easily between semiconductor crystal grains via the intervening metallic nanoparticle bridges, but phonons are scattered at the interfacing gaps. Hence, if the interfacing gap is larger than the mean free path of the phonon, thermal energy transmission from one grain to others is reduced. Here we describe the design and analysis of these new materials that offer substantial improvements in thermoelectric performance.
Sound Environments Surrounding Preterm Infants Within an Occupied Closed Incubator.
Shimizu, Aya; Matsuo, Hiroya
2016-01-01
Preterm infants often exhibit functional disorders due to the stressful environment in the neonatal intensive care unit (NICU). The sound pressure level (SPL) in the NICU is often much higher than the levels recommended by the American Academy of Pediatrics. Our study aims to describe the SPL and sound frequency levels surrounding preterm infants within closed incubators that utilize high frequency oscillation (HFO) or nasal directional positive airway pressure (nasal-DPAP) respiratory settings. This is a descriptive research study of eight preterm infants (corrected agenoise levels were observed and the results were compared to the recommendations made by neonatal experts. Increased noise levels, which have reported to affect neonates' ability to self-regulate, could increase the risk of developing attention deficit disorder, and may result in tachycardia, bradycardia, increased intracranial pressure, and hypoxia. The care provider should closely assess for adverse effects of higher sound levels generated by different modes of respiratory support and take measures to ensure that preterm infants are protected from exposure to noise exceeding the optimal safe levels. Copyright © 2016 Elsevier Inc. All rights reserved.
Preliminary Analysis of Slope Stability in Kuok and Surrounding Areas
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Dewandra Bagus Eka Putra
2016-12-01
Full Text Available The level of slope influenced by the condition of the rocks beneath the surface. On high level of slopes, amount of surface runoff and water transport energy is also enlarged. This caused by greater gravity, in line with the surface tilt from the horizontal plane. In other words, topsoil eroded more and more. When the slope becomes twice as steep, then the amount of erosion per unit area be 2.0 - 2.5 times more. Kuok and surrounding area is the road access between the West Sumatra and Riau which plays an important role economies of both provinces. The purpose of this study is to map the locations that have fairly steep slopes and potential mode of landslides. Based on SRTM data obtained, the roads in Kuok area has a minimum elevation of + 33 m and a maximum + 217.329 m. Rugged road conditions with slope ranging from 24.08 ° to 44.68 ° causing this area having frequent landslides. The result of slope stability analysis in a slope near the Water Power Plant Koto Panjang, indicated that mode of active failure is toppling failure or rock fall and the potential zone of failure is in the center part of the slope.
Democratizing rendering for multiple viewers in surround VR systems
Schulze, Jü rgen P.; Acevedo-Feliz, Daniel; Mangan, John; Prudhomme, Andrew; Nguyen, Phi Khanh; Weber, Philip P.
2012-01-01
We present a new approach for how multiple users' views can be rendered in a surround virtual environment without using special multi-view hardware. It is based on the idea that different parts of the screen are often viewed by different users, so that they can be rendered from their own view point, or at least from a point closer to their view point than traditionally expected. The vast majority of 3D virtual reality systems are designed for one head-tracked user, and a number of passive viewers. Only the head tracked user gets to see the correct view of the scene, everybody else sees a distorted image. We reduce this problem by algorithmically democratizing the rendering view point among all tracked users. Researchers have proposed solutions for multiple tracked users, but most of them require major changes to the display hardware of the VR system, such as additional projectors or custom VR glasses. Our approach does not require additional hardware, except the ability to track each participating user. We propose three versions of our multi-viewer algorithm. Each of them balances image distortion and frame rate in different ways, making them more or less suitable for certain application scenarios. Our most sophisticated algorithm renders each pixel from its own, optimized camera perspective, which depends on all tracked users' head positions and orientations. © 2012 IEEE.
Ultrastructural study of tissues surrounding replanted teeth and dental implants.
Shioya, Kazuhiro; Sawada, Takashi; Miake, Yasuo; Inoue, Sadayuki; Yanagisawa, Takaaki
2009-03-01
The aim of this study was to describe the ultrastructure of the dentogingival border at replanted teeth and implants. Wistar rats (8 weeks old) were divided into groups for replantation and implantation experiments. In the former, the upper right first molars were extracted and then immediately replanted. In the latter, pure titanium implants were used. All tissues were fixed, demineralized and embedded in epoxy resin for ultrastructural observations. One week after replantation, the junctional epithelium was lost, and the oral sulcular epithelium covered the enamel surface. The amount of the epithelium increased in 2 weeks, and resembled the junctional epithelium, and the internal basal lamina and hemidesmosomes were formed in 4 weeks. One week after implantation, peri-implant epithelium was formed, and in 2 and 4 weeks, this epithelium with aggregated connective tissue cells were observed. In 8 weeks, the peri-implant epithelium receded, and aligned special cells with surrounding elongated fibroblasts and bundles of collagen fibers appeared to seal the implant interface. In replantation of the tooth, the internal basal lamina remained at the surface of the enamel of the replanted tooth, which is likely to be related to regeneration of the junctional epithelium and the attachment apparatus at the epithelium-tooth interface. Following implantation, a layer of cells with characteristics of connective tissue cells, but no junctional epithelium and attachment apparatus, was formed to seal the site of the implant.
Earthquakes in Switzerland and surrounding regions during 2006
International Nuclear Information System (INIS)
Baer, M.; Deichmann, N.; Braunmiller, J.; Clinton, J.; Husen, S.; Faeh, D.; Giardini, D.; Kaestli, P.; Kradolfer, U.; Wiemer, S.
2007-01-01
This report of the Swiss Seismological Service summarizes the seismic activity in Switzerland and surrounding regions during 2006. During this period, 572 earthquakes and 91 quarry blasts were detected and located in the region under consideration. Of these earthquakes, two occurred in conjunction with the construction of the new Gotthard railway tunnel and 165 were induced artificially by the stimulation of a proposed geothermal reservoir beneath the city of Basel. With 20 events with Μ ι ≥ 2.5, five of which were artificially induced, the seismic activity in the year 2006 was far below the average over the previous 31 years. Nevertheless, six events were felt by the public, most prominently the strongest of the induced Basel events (Μ ι 3.4), which caused some non-structural building damage. Noteworthy are also the two earthquakes near Cortaillod (Μ ι 3.2), on the shore of Lake Neuchatel, and in Val Mora (Μ ι 3.5), between the Engadin and Val Muestair, as well as the 42 aftershocks of the Μ ι 4.9 Vallorcine earthquake, between Martigny and Chamonix, of September 2005. (author)
What can offer us reclaimed landscape surrounding future lake Medard
Energy Technology Data Exchange (ETDEWEB)
Hrajnohova-Gillarova, H.; Kazmierski, T.; Martis, M. [Czech Univ. of Life Sciences, Prague (Czech Republic); Pecharova, E. [Czech Univ. of Life Sciences, Prague (Czech Republic); South-Bohemian Univ., Ceske Budejovice (Czech Republic)
2010-07-01
Soon after closing down a mine, the landscape that had been systematically disturbed by mining, should start to serve people from neighbouring towns and villages. This study characterized the Medard site located in the western part of the Czech Republic. The future Lake Medard includes the area of the former Medard-Libik Mine. Medard was an opencast brown coal mine, where mining finished in 2000 and reclamation plans involve its flooding until the year 2013. Forestry reclamation was also in progress. This paper presented a survey that was designed to help determine what the reclaimed landscape surrounding the future Lake Medard could offer. The paper provided background information on Medard Lake and outlined the methodology and results of the study. The methodology involved use of recent orthophotomaps, a study of the future lake Medard and data from the field survey. The study examined the long-term impacts on the social and environmental situation in the area. It was concluded that, once the reclamations are finished, there should be natural trails with information and educational infrastructure so that visitors to the area can learn about the places of interest. 17 refs., 6 figs.
Inferring Genetic Ancestry: Opportunities, Challenges, and Implications
Royal, Charmaine D.; Novembre, John; Fullerton, Stephanie M.; Goldstein, David B.; Long, Jeffrey C.; Bamshad, Michael J.; Clark, Andrew G.
2010-01-01
Increasing public interest in direct-to-consumer (DTC) genetic ancestry testing has been accompanied by growing concern about issues ranging from the personal and societal implications of the testing to the scientific validity of ancestry inference. The very concept of “ancestry” is subject to misunderstanding in both the general and scientific communities. What do we mean by ancestry? How exactly is ancestry measured? How far back can such ancestry be defined and by which genetic tools? How ...
Spatial Inference Based on Geometric Proportional Analogies
Mullally, Emma-Claire; O'Donoghue, Diarmuid P.
2006-01-01
We describe an instance-based reasoning solution to a variety of spatial reasoning problems. The solution centers on identifying an isomorphic mapping between labelled graphs that represent some problem data and a known solution instance. We describe a number of spatial reasoning problems that are solved by generating non-deductive inferences, integrating topology with area (and other) features. We report the accuracy of our algorithm on different categories of spatial reasoning tasks from th...
Inferring ontology graph structures using OWL reasoning
Rodriguez-Garcia, Miguel Angel
2018-01-05
Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies\\' semantic content remains a challenge.We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies\\' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph .Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.
Role of Speaker Cues in Attention Inference
Jin Joo Lee; Cynthia Breazeal; David DeSteno
2017-01-01
Current state-of-the-art approaches to emotion recognition primarily focus on modeling the nonverbal expressions of the sole individual without reference to contextual elements such as the co-presence of the partner. In this paper, we demonstrate that the accurate inference of listeners’ social-emotional state of attention depends on accounting for the nonverbal behaviors of their storytelling partner, namely their speaker cues. To gain a deeper understanding of the role of speaker cues in at...
Inferring ontology graph structures using OWL reasoning.
Rodríguez-García, Miguel Ángel; Hoehndorf, Robert
2018-01-05
Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies' semantic content remains a challenge. We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph . Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.
Constrained bayesian inference of project performance models
Sunmola, Funlade
2013-01-01
Project performance models play an important role in the management of project success. When used for monitoring projects, they can offer predictive ability such as indications of possible delivery problems. Approaches for monitoring project performance relies on available project information including restrictions imposed on the project, particularly the constraints of cost, quality, scope and time. We study in this paper a Bayesian inference methodology for project performance modelling in ...
Using metacognitive cues to infer others' thinking
André Mata; Tiago Almeida
2014-01-01
Three studies tested whether people use cues about the way other people think---for example, whether others respond fast vs. slow---to infer what responses other people might give to reasoning problems. People who solve reasoning problems using deliberative thinking have better insight than intuitive problem-solvers into the responses that other people might give to the same problems. Presumably because deliberative responders think of intuitive responses before they think o...
Thermodynamics of statistical inference by cells.
Lang, Alex H; Fisher, Charles K; Mora, Thierry; Mehta, Pankaj
2014-10-03
The deep connection between thermodynamics, computation, and information is now well established both theoretically and experimentally. Here, we extend these ideas to show that thermodynamics also places fundamental constraints on statistical estimation and learning. To do so, we investigate the constraints placed by (nonequilibrium) thermodynamics on the ability of biochemical signaling networks to estimate the concentration of an external signal. We show that accuracy is limited by energy consumption, suggesting that there are fundamental thermodynamic constraints on statistical inference.
Bootstrap inference when using multiple imputation.
Schomaker, Michael; Heumann, Christian
2018-04-16
Many modern estimators require bootstrapping to calculate confidence intervals because either no analytic standard error is available or the distribution of the parameter of interest is nonsymmetric. It remains however unclear how to obtain valid bootstrap inference when dealing with multiple imputation to address missing data. We present 4 methods that are intuitively appealing, easy to implement, and combine bootstrap estimation with multiple imputation. We show that 3 of the 4 approaches yield valid inference, but that the performance of the methods varies with respect to the number of imputed data sets and the extent of missingness. Simulation studies reveal the behavior of our approaches in finite samples. A topical analysis from HIV treatment research, which determines the optimal timing of antiretroviral treatment initiation in young children, demonstrates the practical implications of the 4 methods in a sophisticated and realistic setting. This analysis suffers from missing data and uses the g-formula for inference, a method for which no standard errors are available. Copyright © 2018 John Wiley & Sons, Ltd.
Inferring epidemic network topology from surveillance data.
Directory of Open Access Journals (Sweden)
Xiang Wan
Full Text Available The transmission of infectious diseases can be affected by many or even hidden factors, making it difficult to accurately predict when and where outbreaks may emerge. One approach at the moment is to develop and deploy surveillance systems in an effort to detect outbreaks as timely as possible. This enables policy makers to modify and implement strategies for the control of the transmission. The accumulated surveillance data including temporal, spatial, clinical, and demographic information, can provide valuable information with which to infer the underlying epidemic networks. Such networks can be quite informative and insightful as they characterize how infectious diseases transmit from one location to another. The aim of this work is to develop a computational model that allows inferences to be made regarding epidemic network topology in heterogeneous populations. We apply our model on the surveillance data from the 2009 H1N1 pandemic in Hong Kong. The inferred epidemic network displays significant effect on the propagation of infectious diseases.
Role of Speaker Cues in Attention Inference
Directory of Open Access Journals (Sweden)
Jin Joo Lee
2017-10-01
Full Text Available Current state-of-the-art approaches to emotion recognition primarily focus on modeling the nonverbal expressions of the sole individual without reference to contextual elements such as the co-presence of the partner. In this paper, we demonstrate that the accurate inference of listeners’ social-emotional state of attention depends on accounting for the nonverbal behaviors of their storytelling partner, namely their speaker cues. To gain a deeper understanding of the role of speaker cues in attention inference, we conduct investigations into real-world interactions of children (5–6 years old storytelling with their peers. Through in-depth analysis of human–human interaction data, we first identify nonverbal speaker cues (i.e., backchannel-inviting cues and listener responses (i.e., backchannel feedback. We then demonstrate how speaker cues can modify the interpretation of attention-related backchannels as well as serve as a means to regulate the responsiveness of listeners. We discuss the design implications of our findings toward our primary goal of developing attention recognition models for storytelling robots, and we argue that social robots can proactively use speaker cues to form more accurate inferences about the attentive state of their human partners.
Cortical information flow during inferences of agency
Directory of Open Access Journals (Sweden)
Myrthel eDogge
2014-08-01
Full Text Available Building on the recent finding that agency experiences do not merely rely on sensorimotor information but also on cognitive cues, this exploratory study uses electroencephalographic recordings to examine functional connectivity during agency inference processing in a setting where action and outcome are independent. Participants completed a computerized task in which they pressed a button followed by one of two color words (red or blue and rated their experienced agency over producing the color. Before executing the action, a matching or mismatching color word was pre-activated by explicitly instructing participants to produce the color (goal condition or by briefly presenting the color word (prime condition. In both conditions, experienced agency was higher in matching versus mismatching trials. Furthermore, increased electroencephalography (EEG-based connectivity strength was observed between parietal and frontal nodes and within the (prefrontal cortex when color-outcomes matched with goals and participants reported high agency. This pattern of increased connectivity was not identified in trials where outcomes were pre-activated through primes. These results suggest that different connections are involved in the experience and in the loss of agency, as well as in inferences of agency resulting from different types of pre-activation. Moreover, the findings provide novel support for the involvement of a fronto-parietal network in agency inferences.
Phylogenetic Inference of HIV Transmission Clusters
Directory of Open Access Journals (Sweden)
Vlad Novitsky
2017-10-01
Full Text Available Better understanding the structure and dynamics of HIV transmission networks is essential for designing the most efficient interventions to prevent new HIV transmissions, and ultimately for gaining control of the HIV epidemic. The inference of phylogenetic relationships and the interpretation of results rely on the definition of the HIV transmission cluster. The definition of the HIV cluster is complex and dependent on multiple factors, including the design of sampling, accuracy of sequencing, precision of sequence alignment, evolutionary models, the phylogenetic method of inference, and specified thresholds for cluster support. While the majority of studies focus on clusters, non-clustered cases could also be highly informative. A new dimension in the analysis of the global and local HIV epidemics is the concept of phylogenetically distinct HIV sub-epidemics. The identification of active HIV sub-epidemics reveals spreading viral lineages and may help in the design of targeted interventions.HIVclustering can also be affected by sampling density. Obtaining a proper sampling density may increase statistical power and reduce sampling bias, so sampling density should be taken into account in study design and in interpretation of phylogenetic results. Finally, recent advances in long-range genotyping may enable more accurate inference of HIV transmission networks. If performed in real time, it could both inform public-health strategies and be clinically relevant (e.g., drug-resistance testing.
Causal inference of asynchronous audiovisual speech
Directory of Open Access Journals (Sweden)
John F Magnotti
2013-11-01
Full Text Available During speech perception, humans integrate auditory information from the voice with visual information from the face. This multisensory integration increases perceptual precision, but only if the two cues come from the same talker; this requirement has been largely ignored by current models of speech perception. We describe a generative model of multisensory speech perception that includes this critical step of determining the likelihood that the voice and face information have a common cause. A key feature of the model is that it is based on a principled analysis of how an observer should solve this causal inference problem using the asynchrony between two cues and the reliability of the cues. This allows the model to make predictions abut the behavior of subjects performing a synchrony judgment task, predictive power that does not exist in other approaches, such as post hoc fitting of Gaussian curves to behavioral data. We tested the model predictions against the performance of 37 subjects performing a synchrony judgment task viewing audiovisual speech under a variety of manipulations, including varying asynchronies, intelligibility, and visual cue reliability. The causal inference model outperformed the Gaussian model across two experiments, providing a better fit to the behavioral data with fewer parameters. Because the causal inference model is derived from a principled understanding of the task, model parameters are directly interpretable in terms of stimulus and subject properties.
Functional neuroanatomy of intuitive physical inference.
Fischer, Jason; Mikhael, John G; Tenenbaum, Joshua B; Kanwisher, Nancy
2016-08-23
To engage with the world-to understand the scene in front of us, plan actions, and predict what will happen next-we must have an intuitive grasp of the world's physical structure and dynamics. How do the objects in front of us rest on and support each other, how much force would be required to move them, and how will they behave when they fall, roll, or collide? Despite the centrality of physical inferences in daily life, little is known about the brain mechanisms recruited to interpret the physical structure of a scene and predict how physical events will unfold. Here, in a series of fMRI experiments, we identified a set of cortical regions that are selectively engaged when people watch and predict the unfolding of physical events-a "physics engine" in the brain. These brain regions are selective to physical inferences relative to nonphysical but otherwise highly similar scenes and tasks. However, these regions are not exclusively engaged in physical inferences per se or, indeed, even in scene understanding; they overlap with the domain-general "multiple demand" system, especially the parts of that system involved in action planning and tool use, pointing to a close relationship between the cognitive and neural mechanisms involved in parsing the physical content of a scene and preparing an appropriate action.
Elements of Causal Inference: Foundations and Learning Algorithms
DEFF Research Database (Denmark)
Peters, Jonas Martin; Janzing, Dominik; Schölkopf, Bernhard
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning......A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning...
Integrating distributed Bayesian inference and reinforcement learning for sensor management
Grappiolo, C.; Whiteson, S.; Pavlin, G.; Bakker, B.
2009-01-01
This paper introduces a sensor management approach that integrates distributed Bayesian inference (DBI) and reinforcement learning (RL). DBI is implemented using distributed perception networks (DPNs), a multiagent approach to performing efficient inference, while RL is used to automatically
Bootstrapping phylogenies inferred from rearrangement data
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Lin Yu
2012-08-01
Full Text Available Abstract Background Large-scale sequencing of genomes has enabled the inference of phylogenies based on the evolution of genomic architecture, under such events as rearrangements, duplications, and losses. Many evolutionary models and associated algorithms have been designed over the last few years and have found use in comparative genomics and phylogenetic inference. However, the assessment of phylogenies built from such data has not been properly addressed to date. The standard method used in sequence-based phylogenetic inference is the bootstrap, but it relies on a large number of homologous characters that can be resampled; yet in the case of rearrangements, the entire genome is a single character. Alternatives such as the jackknife suffer from the same problem, while likelihood tests cannot be applied in the absence of well established probabilistic models. Results We present a new approach to the assessment of distance-based phylogenetic inference from whole-genome data; our approach combines features of the jackknife and the bootstrap and remains nonparametric. For each feature of our method, we give an equivalent feature in the sequence-based framework; we also present the results of extensive experimental testing, in both sequence-based and genome-based frameworks. Through the feature-by-feature comparison and the experimental results, we show that our bootstrapping approach is on par with the classic phylogenetic bootstrap used in sequence-based reconstruction, and we establish the clear superiority of the classic bootstrap for sequence data and of our corresponding new approach for rearrangement data over proposed variants. Finally, we test our approach on a small dataset of mammalian genomes, verifying that the support values match current thinking about the respective branches. Conclusions Our method is the first to provide a standard of assessment to match that of the classic phylogenetic bootstrap for aligned sequences. Its
Bootstrapping phylogenies inferred from rearrangement data.
Lin, Yu; Rajan, Vaibhav; Moret, Bernard Me
2012-08-29
Large-scale sequencing of genomes has enabled the inference of phylogenies based on the evolution of genomic architecture, under such events as rearrangements, duplications, and losses. Many evolutionary models and associated algorithms have been designed over the last few years and have found use in comparative genomics and phylogenetic inference. However, the assessment of phylogenies built from such data has not been properly addressed to date. The standard method used in sequence-based phylogenetic inference is the bootstrap, but it relies on a large number of homologous characters that can be resampled; yet in the case of rearrangements, the entire genome is a single character. Alternatives such as the jackknife suffer from the same problem, while likelihood tests cannot be applied in the absence of well established probabilistic models. We present a new approach to the assessment of distance-based phylogenetic inference from whole-genome data; our approach combines features of the jackknife and the bootstrap and remains nonparametric. For each feature of our method, we give an equivalent feature in the sequence-based framework; we also present the results of extensive experimental testing, in both sequence-based and genome-based frameworks. Through the feature-by-feature comparison and the experimental results, we show that our bootstrapping approach is on par with the classic phylogenetic bootstrap used in sequence-based reconstruction, and we establish the clear superiority of the classic bootstrap for sequence data and of our corresponding new approach for rearrangement data over proposed variants. Finally, we test our approach on a small dataset of mammalian genomes, verifying that the support values match current thinking about the respective branches. Our method is the first to provide a standard of assessment to match that of the classic phylogenetic bootstrap for aligned sequences. Its support values follow a similar scale and its receiver
Type Inference for Session Types in the Pi-Calculus
DEFF Research Database (Denmark)
Graversen, Eva Fajstrup; Harbo, Jacob Buchreitz; Huttel, Hans
2014-01-01
In this paper we present a direct algorithm for session type inference for the π-calculus. Type inference for session types has previously been achieved by either imposing limitations and restriction on the π-calculus, or by reducing the type inference problem to that for linear types. Our approach...
Reasoning about Informal Statistical Inference: One Statistician's View
Rossman, Allan J.
2008-01-01
This paper identifies key concepts and issues associated with the reasoning of informal statistical inference. I focus on key ideas of inference that I think all students should learn, including at secondary level as well as tertiary. I argue that a fundamental component of inference is to go beyond the data at hand, and I propose that statistical…
Statistical Inference at Work: Statistical Process Control as an Example
Bakker, Arthur; Kent, Phillip; Derry, Jan; Noss, Richard; Hoyles, Celia
2008-01-01
To characterise statistical inference in the workplace this paper compares a prototypical type of statistical inference at work, statistical process control (SPC), with a type of statistical inference that is better known in educational settings, hypothesis testing. Although there are some similarities between the reasoning structure involved in…
Morphological Segregation in the Surroundings of Cosmic Voids
Energy Technology Data Exchange (ETDEWEB)
Ricciardelli, Elena; Tamone, Amelie [Laboratoire d’Astrophysique, École Polytechnique Fédérale de Lausanne (EPFL), 1290 Sauverny (Switzerland); Cava, Antonio [Observatoire de Genève, Université de Genève, 51 Ch. des Maillettes, 1290 Versoix (Switzerland); Varela, Jesus, E-mail: elena.ricciardelli@epfl.ch [Centro de Estudios de Física del Cosmos de Aragón (CEFCA), Plaza San Juan 1, E-44001 Teruel (Spain)
2017-09-01
We explore the morphology of galaxies living in the proximity of cosmic voids, using a sample of voids identified in the Sloan Digital Sky Survey Data Release 7. At all stellar masses, void galaxies exhibit morphologies of a later type than galaxies in a control sample, which represent galaxies in an average density environment. We interpret this trend as a pure environmental effect, independent of the mass bias, due to a slower galaxy build-up in the rarefied regions of voids. We confirm previous findings about a clear segregation in galaxy morphology, with galaxies of a later type being found at smaller void-centric distances with respect to the early-type galaxies. We also show, for the first time, that the radius of the void has an impact on the evolutionary history of the galaxies that live within it or in its surroundings. In fact, an enhanced fraction of late-type galaxies is found in the proximity of voids larger than the median void radius. Likewise, an excess of early-type galaxies is observed within or around voids of a smaller size. A significant difference in galaxy properties in voids of different sizes is observed up to 2 R {sub void}, which we define as the region of influence of voids. The significance of this difference is greater than 3 σ for all the volume-complete samples considered here. The fraction of star-forming galaxies shows the same behavior as the late-type galaxies, but no significant difference in stellar mass is observed in the proximity of voids of different sizes.
Isoperimetric inequalities in surround system and space science
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JiaJin Wen
2016-02-01
Full Text Available Abstract By means of the algebraic, analysis, convex geometry, computer, and inequality theories we establish the following isoperimetric inequality in the centered 2-surround system S ( 2 { P , Γ , l } $S^{(2} \\{P,\\varGamma ,l \\}$ : ( 1 | Γ | ∮ Γ r ¯ P p 1 / p ⩽ | Γ | 4 π sin l π | Γ | [ csc l π | Γ | + cot 2 l π | Γ | ln ( tan l π | Γ | + sec l π | Γ | ] , ∀ p ⩽ − 2 . $$\\begin{aligned}& \\biggl(\\frac{1}{|\\varGamma |} \\oint_{\\varGamma }\\bar{r}_{P}^{p} \\biggr^{1/p}\\leqslant\\frac{|\\varGamma |}{4\\pi}\\sin\\frac{l\\pi}{|\\varGamma |} \\biggl[ \\csc \\frac{l\\pi}{|\\varGamma |}+\\cot^{2} \\frac{l\\pi}{|\\varGamma |} \\ln \\biggl(\\tan \\frac{l\\pi}{|\\varGamma |}+\\sec\\frac{l\\pi}{|\\varGamma |} \\biggr \\biggr], \\\\& \\quad \\forall p\\leqslant -2. \\end{aligned}$$ As an application of the inequality in space science, we obtain the best lower bounds of the mean λ-gravity norm ∥ F λ ( Γ , P ∥ ‾ $\\overline{\\Vert {\\mathbf{F}}_{\\lambda} ( \\varGamma ,P \\Vert }$ as follows: ∥ F λ ( Γ , P ∥ ‾ ≜ 1 | Γ | ∮ Γ 1 ∥ A − P ∥ λ ⩾ ( 2 π | Γ | λ , ∀ λ ⩾ 2 . $$\\overline{\\bigl\\Vert {\\mathbf{F}}_{\\lambda} ( \\varGamma ,P \\bigr\\Vert } \\triangleq\\frac{1}{|\\varGamma |} \\oint_{\\varGamma }\\frac{1}{\\|A-P\\|^{\\lambda }}\\geqslant \\biggl(\\frac{2\\pi}{|\\varGamma |} \\biggr^{\\lambda},\\quad \\forall \\lambda\\geqslant2. $$
Rain Simulation for the Test of Automotive Surround Sensors
Hasirlioglu, Sinan; Riener, Andreas; Doric, Igor
2017-04-01
The WHO Global Health Observatory data indicates that over 1.25 million people die in traffic accidents annually. To save lives, car manufacturers spend lot of efforts on the development of novel safety systems aiming to avoid or mitigate accidents and provide maximum protection for vehicle occupants as well as vulnerable road users. All the safety features mainly rely on data from surround sensors such as radar, lidar and camera and intelligent vehicles today use these environmental data for instant decision making and vehicle control. As already small errors in sensor data measurements could lead to catastrophes like major injuries or road traffic fatalities, it is of utmost importance to ensure high reliability and accuracy of sensors and safety systems. This work focuses on the influence of environmental factors such as rain conditions, as it is known that rain drops scatter the electromagnetic waves. The result is incorrect measurements with a direct negative impact on environment detection. To identify potential problems of sensors under varying environmental conditions, systems are today tested in real-world settings with two main problems: First, tests are time-consuming and second, environmental conditions are not reproducible. Our approach to test the influence of weather on automotive sensors is to use an indoor rain simulator. Our artificial rain maker, installed at CARISSMA (Center of Automotive Research on Integrated Safety Systems and Measurement Area), is parametrized with rain characteristics measured in the field using a standard disdrometer. System behavior on artificial rain is compared and validated with natural rainfall. With this simulator it is finally possible to test environmental influence at various levels and under reproducible conditions. This saves lot of efforts required for the test process itself and furthermore has a positive impact on the reliability of sensor systems due to the fact that test driven development is enabled.
Issues surrounding orphan disease and orphan drug policies in Europe.
Denis, Alain; Mergaert, Lut; Fostier, Christel; Cleemput, Irina; Simoens, Steven
2010-01-01
An orphan disease is a disease with a very low prevalence. Although there are 5000-7000 orphan diseases, only 50 orphan drugs (i.e. drugs developed to treat orphan diseases) were marketed in the EU by the end of 2008. In 2000, the EU implemented policies specifically designed to stimulate the development of orphan drugs. While decisions on orphan designation and the marketing authorization of orphan drugs are made at the EU level, decisions on drug reimbursement are made at the member state level. The specific features of orphan diseases and orphan drugs make them a high-priority issue for policy makers. The aim of this article is to identify and discuss several issues surrounding orphan disease and drug policies in Europe. The present system of orphan designation allows for drugs for non-orphan diseases to be designated as orphan drugs. The economic factors underlying orphan designation can be questioned in some cases, as a low prevalence of a certain indication does not equal a low return on investment for the drug across its indications. High-quality evidence about the clinical added value of orphan drugs is rarely available at the time of marketing authorization, due to the low number of patients. A balance must be struck between ethical and economic concerns. To this effect, there is a need to initiate a societal dialogue on this issue, to clarify what society wants and accepts in terms of ethical and economic consequences. The growing budgetary impact of orphan drugs puts pressure on drug expenditure. Indications can be extended for an orphan drug and the total prevalence across indications is not considered. Finally, cooperation needs to be fostered in the EU, particularly through a standardized approach to the creation and use of registries. These issues require further attention from researchers, policy makers, health professionals, patients, pharmaceutical companies and other stakeholders with a view to optimizing orphan disease and drug policies in
Inferring the palaeoenvironment of ancient bacteria on the basis of resurrected proteins
Gaucher, Eric A.; Thomson, J. Michael; Burgan, Michelle F.; Benner, Steven A.
2003-01-01
Features of the physical environment surrounding an ancestral organism can be inferred by reconstructing sequences of ancient proteins made by those organisms, resurrecting these proteins in the laboratory, and measuring their properties. Here, we resurrect candidate sequences for elongation factors of the Tu family (EF-Tu) found at ancient nodes in the bacterial evolutionary tree, and measure their activities as a function of temperature. The ancient EF-Tu proteins have temperature optima of 55-65 degrees C. This value seems to be robust with respect to uncertainties in the ancestral reconstruction. This suggests that the ancient bacteria that hosted these particular genes were thermophiles, and neither hyperthermophiles nor mesophiles. This conclusion can be compared and contrasted with inferences drawn from an analysis of the lengths of branches in trees joining proteins from contemporary bacteria, the distribution of thermophily in derived bacterial lineages, the inferred G + C content of ancient ribosomal RNA, and the geological record combined with assumptions concerning molecular clocks. The study illustrates the use of experimental palaeobiochemistry and assumptions about deep phylogenetic relationships between bacteria to explore the character of ancient life.
Malle, Bertram F; Holbrook, Jess
2012-04-01
People interpret behavior by making inferences about agents' intentionality, mind, and personality. Past research studied such inferences 1 at a time; in real life, people make these inferences simultaneously. The present studies therefore examined whether 4 major inferences (intentionality, desire, belief, and personality), elicited simultaneously in response to an observed behavior, might be ordered in a hierarchy of likelihood and speed. To achieve generalizability, the studies included a wide range of stimulus behaviors, presented them verbally and as dynamic videos, and assessed inferences both in a retrieval paradigm (measuring the likelihood and speed of accessing inferences immediately after they were made) and in an online processing paradigm (measuring the speed of forming inferences during behavior observation). Five studies provide evidence for a hierarchy of social inferences-from intentionality and desire to belief to personality-that is stable across verbal and visual presentations and that parallels the order found in developmental and primate research. (c) 2012 APA, all rights reserved.
Hofmann, B
2008-06-01
Are there similarities between scientific and moral inference? This is the key question in this article. It takes as its point of departure an instance of one person's story in the media changing both Norwegian public opinion and a brand-new Norwegian law prohibiting the use of saviour siblings. The case appears to falsify existing norms and to establish new ones. The analysis of this case reveals similarities in the modes of inference in science and morals, inasmuch as (a) a single case functions as a counter-example to an existing rule; (b) there is a common presupposition of stability, similarity and order, which makes it possible to reason from a few cases to a general rule; and (c) this makes it possible to hold things together and retain order. In science, these modes of inference are referred to as falsification, induction and consistency. In morals, they have a variety of other names. Hence, even without abandoning the fact-value divide, there appear to be similarities between inference in science and inference in morals, which may encourage communication across the boundaries between "the two cultures" and which are relevant to medical humanities.
Arvidson, R. E. (Principal Investigator)
1982-01-01
Progress in the preparation of manuscripts on the discovery of a Precambrian rift running NW-SE through Missouri as seen in free air and Bouguer gravity anomalies and in HCMM data, and on digital image processing of potential field and topographic data on the rift is reported. Copies of the papers are attached. Contrast-enhanced HCMM images that have been transformed to Mercator projections are presented. Shaded relief map overlays of thermal and apparent thermal inertia images used as part of a masers thesis examining correlations between HCMM data products, linears, and geologic units are presented. Progress in examination of the difference in information content of daytime infrared, night time infrared, albedo, and thermal inertia images and their application to he identification of linears not directly controlled by topography is reported. Thermal infrared and albedo data were coded as hue, saturation and brightness values to generate a color display, which is included.
Behavioural aspects surrounding medicine purchases from pharmacies in Australia
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Emmerton L
2008-09-01
Full Text Available Objective: This study aimed to produce current data regarding behavioural aspects of non-prescription (over-the-counter medicine purchases, in light of changes in the pharmaceutical market and increasing provision of professional services in pharmacies.Methods: Data were collected in 15 community pharmacies in South-East Queensland, Australia, over 540 hours in five days in August, 2006. The method, previously validated, involved documentation of both observational and interview data. Fifteen trained researchers were stationed in a selected pharmacy each to unobtrusively observe all eligible sales of non-prescription medicines, and, where possible, interview the purchasers post-sale. Non-response was supplemented by observational data and recall by the salesperson. The data included details of the purchase and purchasing behaviour, while new questions addressed issues of topical importance, including customers’ privacy concerns. A selection of the analyses is reported here.Results: In total, 3470 purchases were documented (135-479 per pharmacy, with customers of 67.5% of purchases (74.7% excluding an outlier pharmacy participating in the survey. Customers averaged 1.2 non-prescription medicines per transaction. Two-thirds (67.2% of customers were female, and 38.8% of the customers were aged 31-45 years. Analgesics and respiratory medicines accounted for two-thirds of the sales data (33.4% and 32.4%, respectively. Intended-brand purchases comprised 71% of purchases (2004/2824; in-store substitution then occurred in 8.8% of these cases, mainly following recommendations by pharmacy staff. Medicines intended for self-use comprised 62.9% of purchases (1752/2785. First-time purchases (30.8%, 799/2594 were more commonly influenced by pharmacy staff than by advertising.Conclusions: This study used validated methods adapted to a changing marketplace, thus providing data that both confirm and add to knowledge surrounding medicine purchases. Despite the
Highly Enriched Uranium Metal Cylinders Surrounded by Various Reflector Materials
International Nuclear Information System (INIS)
Bernard Jones; J. Blair Briggs; Leland Monteirth
2007-01-01
A series of experiments was performed at Los Alamos Scientific Laboratory in 1958 to determine critical masses of cylinders of Oralloy (Oy) reflected by a number of materials. The experiments were all performed on the Comet Universal Critical Assembly Machine, and consisted of discs of highly enriched uranium (93.3 wt.% 235U) reflected by half-inch and one-inch-thick cylindrical shells of various reflector materials. The experiments were performed by members of Group N-2, particularly K. W. Gallup, G. E. Hansen, H. C. Paxton, and R. H. White. This experiment was intended to ascertain critical masses for criticality safety purposes, as well as to compare neutron transport cross sections to those obtained from danger coefficient measurements with the Topsy Oralloy-Tuballoy reflected and Godiva unreflected critical assemblies. The reflector materials examined in this series of experiments are as follows: magnesium, titanium, aluminum, graphite, mild steel, nickel, copper, cobalt, molybdenum, natural uranium, tungsten, beryllium, aluminum oxide, molybdenum carbide, and polythene (polyethylene). Also included are two special configurations of composite beryllium and iron reflectors. Analyses were performed in which uncertainty associated with six different parameters was evaluated; namely, extrapolation to the uranium critical mass, uranium density, 235U enrichment, reflector density, reflector thickness, and reflector impurities. In addition to the idealizations made by the experimenters (removal of the platen and diaphragm), two simplifications were also made to the benchmark models that resulted in a small bias and additional uncertainty. First of all, since impurities in core and reflector materials are only estimated, they are not included in the benchmark models. Secondly, the room, support structure, and other possible surrounding equipment were not included in the model. Bias values that result from these two simplifications were determined and associated
Severe blood-brain barrier disruption and surrounding tissue injury.
Chen, Bo; Friedman, Beth; Cheng, Qun; Tsai, Phil; Schim, Erica; Kleinfeld, David; Lyden, Patrick D
2009-12-01
Blood-brain barrier opening during ischemia follows a biphasic time course, may be partially reversible, and allows plasma constituents to enter brain and possibly damage cells. In contrast, severe vascular disruption after ischemia is unlikely to be reversible and allows even further extravasation of potentially harmful plasma constituents. We sought to use simple fluorescent tracers to allow wide-scale visualization of severely damaged vessels and determine whether such vascular disruption colocalized with regions of severe parenchymal injury. Severe vascular disruption and ischemic injury was produced in adult Sprague Dawley rats by transient occlusion of the middle cerebral artery for 1, 2, 4, or 8 hours, followed by 30 minutes of reperfusion. Fluorescein isothiocyanate-dextran (2 MDa) was injected intravenously before occlusion. After perfusion-fixation, brain sections were processed for ultrastructure or fluorescence imaging. We identified early evidence of tissue damage with Fluoro-Jade staining of dying cells. With increasing ischemia duration, greater quantities of high molecular weight dextran-fluorescein isothiocyanate invaded and marked ischemic regions in a characteristic pattern, appearing first in the medial striatum, spreading to the lateral striatum, and finally involving cortex; maximal injury was seen in the mid-parietal areas, consistent with the known ischemic zone in this model. The regional distribution of the severe vascular disruption correlated with the distribution of 24-hour 2,3,5-triphenyltetrazolium chloride pallor (r=0.75; P<0.05) and the cell death marker Fluoro-Jade (r=0.86; P<0.05). Ultrastructural examination showed significantly increased areas of swollen astrocytic foot process and swollen mitochondria in regions of high compared to low leakage, and compared to contralateral homologous regions (ANOVA P<0.01). Dextran extravasation into the basement membrane and surrounding tissue increased significantly from 2 to 8 hours of
Nonparametric inference of network structure and dynamics
Peixoto, Tiago P.
The network structure of complex systems determine their function and serve as evidence for the evolutionary mechanisms that lie behind them. Despite considerable effort in recent years, it remains an open challenge to formulate general descriptions of the large-scale structure of network systems, and how to reliably extract such information from data. Although many approaches have been proposed, few methods attempt to gauge the statistical significance of the uncovered structures, and hence the majority cannot reliably separate actual structure from stochastic fluctuations. Due to the sheer size and high-dimensionality of many networks, this represents a major limitation that prevents meaningful interpretations of the results obtained with such nonstatistical methods. In this talk, I will show how these issues can be tackled in a principled and efficient fashion by formulating appropriate generative models of network structure that can have their parameters inferred from data. By employing a Bayesian description of such models, the inference can be performed in a nonparametric fashion, that does not require any a priori knowledge or ad hoc assumptions about the data. I will show how this approach can be used to perform model comparison, and how hierarchical models yield the most appropriate trade-off between model complexity and quality of fit based on the statistical evidence present in the data. I will also show how this general approach can be elegantly extended to networks with edge attributes, that are embedded in latent spaces, and that change in time. The latter is obtained via a fully dynamic generative network model, based on arbitrary-order Markov chains, that can also be inferred in a nonparametric fashion. Throughout the talk I will illustrate the application of the methods with many empirical networks such as the internet at the autonomous systems level, the global airport network, the network of actors and films, social networks, citations among
Impact of noise on molecular network inference.
Directory of Open Access Journals (Sweden)
Radhakrishnan Nagarajan
Full Text Available Molecular entities work in concert as a system and mediate phenotypic outcomes and disease states. There has been recent interest in modelling the associations between molecular entities from their observed expression profiles as networks using a battery of algorithms. These networks have proven to be useful abstractions of the underlying pathways and signalling mechanisms. Noise is ubiquitous in molecular data and can have a pronounced effect on the inferred network. Noise can be an outcome of several factors including: inherent stochastic mechanisms at the molecular level, variation in the abundance of molecules, heterogeneity, sensitivity of the biological assay or measurement artefacts prevalent especially in high-throughput settings. The present study investigates the impact of discrepancies in noise variance on pair-wise dependencies, conditional dependencies and constraint-based Bayesian network structure learning algorithms that incorporate conditional independence tests as a part of the learning process. Popular network motifs and fundamental connections, namely: (a common-effect, (b three-chain, and (c coherent type-I feed-forward loop (FFL are investigated. The choice of these elementary networks can be attributed to their prevalence across more complex networks. Analytical expressions elucidating the impact of discrepancies in noise variance on pairwise dependencies and conditional dependencies for special cases of these motifs are presented. Subsequently, the impact of noise on two popular constraint-based Bayesian network structure learning algorithms such as Grow-Shrink (GS and Incremental Association Markov Blanket (IAMB that implicitly incorporate tests for conditional independence is investigated. Finally, the impact of noise on networks inferred from publicly available single cell molecular expression profiles is investigated. While discrepancies in noise variance are overlooked in routine molecular network inference, the
Bayesian Estimation and Inference using Stochastic Hardware
Directory of Open Access Journals (Sweden)
Chetan Singh Thakur
2016-03-01
Full Text Available In this paper, we present the implementation of two types of Bayesian inference problems to demonstrate the potential of building probabilistic algorithms in hardware using single set of building blocks with the ability to perform these computations in real time. The first implementation, referred to as the BEAST (Bayesian Estimation and Stochastic Tracker, demonstrates a simple problem where an observer uses an underlying Hidden Markov Model (HMM to track a target in one dimension. In this implementation, sensors make noisy observations of the target position at discrete time steps. The tracker learns the transition model for target movement, and the observation model for the noisy sensors, and uses these to estimate the target position by solving the Bayesian recursive equation online. We show the tracking performance of the system and demonstrate how it can learn the observation model, the transition model, and the external distractor (noise probability interfering with the observations. In the second implementation, referred to as the Bayesian INference in DAG (BIND, we show how inference can be performed in a Directed Acyclic Graph (DAG using stochastic circuits. We show how these building blocks can be easily implemented using simple digital logic gates. An advantage of the stochastic electronic implementation is that it is robust to certain types of noise, which may become an issue in integrated circuit (IC technology with feature sizes in the order of tens of nanometers due to their low noise margin, the effect of high-energy cosmic rays and the low supply voltage. In our framework, the flipping of random individual bits would not affect the system performance because information is encoded in a bit stream.
Bayesian Estimation and Inference Using Stochastic Electronics.
Thakur, Chetan Singh; Afshar, Saeed; Wang, Runchun M; Hamilton, Tara J; Tapson, Jonathan; van Schaik, André
2016-01-01
In this paper, we present the implementation of two types of Bayesian inference problems to demonstrate the potential of building probabilistic algorithms in hardware using single set of building blocks with the ability to perform these computations in real time. The first implementation, referred to as the BEAST (Bayesian Estimation and Stochastic Tracker), demonstrates a simple problem where an observer uses an underlying Hidden Markov Model (HMM) to track a target in one dimension. In this implementation, sensors make noisy observations of the target position at discrete time steps. The tracker learns the transition model for target movement, and the observation model for the noisy sensors, and uses these to estimate the target position by solving the Bayesian recursive equation online. We show the tracking performance of the system and demonstrate how it can learn the observation model, the transition model, and the external distractor (noise) probability interfering with the observations. In the second implementation, referred to as the Bayesian INference in DAG (BIND), we show how inference can be performed in a Directed Acyclic Graph (DAG) using stochastic circuits. We show how these building blocks can be easily implemented using simple digital logic gates. An advantage of the stochastic electronic implementation is that it is robust to certain types of noise, which may become an issue in integrated circuit (IC) technology with feature sizes in the order of tens of nanometers due to their low noise margin, the effect of high-energy cosmic rays and the low supply voltage. In our framework, the flipping of random individual bits would not affect the system performance because information is encoded in a bit stream.
Pillow, Bradford H; Pearson, Raeanne M; Hecht, Mary; Bremer, Amanda
2010-01-01
Children and adults rated their own certainty following inductive inferences, deductive inferences, and guesses. Beginning in kindergarten, participants rated deductions as more certain than weak inductions or guesses. Deductions were rated as more certain than strong inductions beginning in Grade 3, and fourth-grade children and adults differentiated strong inductions, weak inductions, and informed guesses from pure guesses. By Grade 3, participants also gave different types of explanations for their deductions and inductions. These results are discussed in relation to children's concepts of cognitive processes, logical reasoning, and epistemological development.
Robust Inference with Multi-way Clustering
A. Colin Cameron; Jonah B. Gelbach; Douglas L. Miller; Doug Miller
2009-01-01
In this paper we propose a variance estimator for the OLS estimator as well as for nonlinear estimators such as logit, probit and GMM. This variance estimator enables cluster-robust inference when there is two-way or multi-way clustering that is non-nested. The variance estimator extends the standard cluster-robust variance estimator or sandwich estimator for one-way clustering (e.g. Liang and Zeger (1986), Arellano (1987)) and relies on similar relatively weak distributional assumptions. Our...
Approximate Inference and Deep Generative Models
CERN. Geneva
2018-01-01
Advances in deep generative models are at the forefront of deep learning research because of the promise they offer for allowing data-efficient learning, and for model-based reinforcement learning. In this talk I'll review a few standard methods for approximate inference and introduce modern approximations which allow for efficient large-scale training of a wide variety of generative models. Finally, I'll demonstrate several important application of these models to density estimation, missing data imputation, data compression and planning.
Abductive Inference using Array-Based Logic
DEFF Research Database (Denmark)
Frisvad, Jeppe Revall; Falster, Peter; Møller, Gert L.
The notion of abduction has found its usage within a wide variety of AI fields. Computing abductive solutions has, however, shown to be highly intractable in logic programming. To avoid this intractability we present a new approach to logicbased abduction; through the geometrical view of data...... employed in array-based logic we embrace abduction in a simple structural operation. We argue that a theory of abduction on this form allows for an implementation which, at runtime, can perform abductive inference quite efficiently on arbitrary rules of logic representing knowledge of finite domains....
DEFF Research Database (Denmark)
Andersen, Jesper; Lawall, Julia Laetitia
2008-01-01
A key issue in maintaining Linux device drivers is the need to update drivers in response to evolutions in Linux internal libraries. Currently, there is little tool support for performing and documenting such changes. In this paper we present a tool, spfind, that identifies common changes made...... developers can use it to extract an abstract representation of the set of changes that others have made. Our experiments on recent changes in Linux show that the inferred generic patches are more concise than the corresponding patches found in commits to the Linux source tree while being safe with respect...
Inverse Ising Inference Using All the Data
Aurell, Erik; Ekeberg, Magnus
2012-03-01
We show that a method based on logistic regression, using all the data, solves the inverse Ising problem far better than mean-field calculations relying only on sample pairwise correlation functions, while still computationally feasible for hundreds of nodes. The largest improvement in reconstruction occurs for strong interactions. Using two examples, a diluted Sherrington-Kirkpatrick model and a two-dimensional lattice, we also show that interaction topologies can be recovered from few samples with good accuracy and that the use of l1 regularization is beneficial in this process, pushing inference abilities further into low-temperature regimes.
Radiological impact of phosphogypsum in the Surrounding Ecosystem
International Nuclear Information System (INIS)
Al-Attar, L.; Al-Oudat, M.; Budier, Y.; Khalili, H.; Hamwi, A.; Kanakri, S.
2011-01-01
This study was carried out to assess the radiological impact of Syrian PG piles in the compartments of the surrounding ecosystem. Therefore, estimating the distribution of naturally occurring radionuclides (i.e. 2 26 Ra, 2 38 U, 2 32 Th, 2 10 Po and 2 10 Pb) in the raw materials, product and by-product of the Syrian phosphate fertilizer industry was essential. The obtained data revealed that 2 26 Ra retained in PG with a mean activity of 318 Bq kg-1. Uranium content in PG was low since it remained in the produced phosphoric acid. However, over 80% of 2 32 Th, 2 10 Po and 2 10 Pb partitioned in PG. The presence of PG piles did not increase the concentration of 2 22 Rn nor gamma rays exposure dose in the studied area. The annual effective dose was only 0.082 mSv y-1. The geometric mean of total suspended solids was ca. 85 g m-3. The concentration of the radionuclides in filtration and runoff waters were below the detection limits; and were much lower than the permissible limits set for drinking water by the WHO in ground and Qattina Lake waters. Eastern sites soil samples of PG piles were of the highest activity concentrations, due to the characterised western and north-western wind in the area, but remained within the natural levels reported in Syrian soil. The impact of PG piles on plants varied upon the plant species. Significantly, higher concentrations of the radionuclides were recorded for grass in comparison to broad-leaved plants. Among the species that naturally grown on PG piles, Inula, Ecballium and Polygonium may be radionuclides accumulators. Nevertheless, a determined effort is needed on national level to achieve a common and coherent approach to regulate PG piles or to consider it a resource material rather than waste or residue. The presence of PG piles did not increase the concentration of 2 22 Rn nor gamma rays exposure dose in the studied area. The annual effective dose was only 0.082 mSv y -1 . The geometric mean of total suspended solids was ca
Quantum Enhanced Inference in Markov Logic Networks.
Wittek, Peter; Gogolin, Christian
2017-04-19
Markov logic networks (MLNs) reconcile two opposing schools in machine learning and artificial intelligence: causal networks, which account for uncertainty extremely well, and first-order logic, which allows for formal deduction. An MLN is essentially a first-order logic template to generate Markov networks. Inference in MLNs is probabilistic and it is often performed by approximate methods such as Markov chain Monte Carlo (MCMC) Gibbs sampling. An MLN has many regular, symmetric structures that can be exploited at both first-order level and in the generated Markov network. We analyze the graph structures that are produced by various lifting methods and investigate the extent to which quantum protocols can be used to speed up Gibbs sampling with state preparation and measurement schemes. We review different such approaches, discuss their advantages, theoretical limitations, and their appeal to implementations. We find that a straightforward application of a recent result yields exponential speedup compared to classical heuristics in approximate probabilistic inference, thereby demonstrating another example where advanced quantum resources can potentially prove useful in machine learning.
Inferring network topology from complex dynamics
International Nuclear Information System (INIS)
Shandilya, Srinivas Gorur; Timme, Marc
2011-01-01
Inferring the network topology from dynamical observations is a fundamental problem pervading research on complex systems. Here, we present a simple, direct method for inferring the structural connection topology of a network, given an observation of one collective dynamical trajectory. The general theoretical framework is applicable to arbitrary network dynamical systems described by ordinary differential equations. No interference (external driving) is required and the type of dynamics is hardly restricted in any way. In particular, the observed dynamics may be arbitrarily complex; stationary, invariant or transient; synchronous or asynchronous and chaotic or periodic. Presupposing a knowledge of the functional form of the dynamical units and of the coupling functions between them, we present an analytical solution to the inverse problem of finding the network topology from observing a time series of state variables only. Robust reconstruction is achieved in any sufficiently long generic observation of the system. We extend our method to simultaneously reconstructing both the entire network topology and all parameters appearing linear in the system's equations of motion. Reconstruction of network topology and system parameters is viable even in the presence of external noise that distorts the original dynamics substantially. The method provides a conceptually new step towards reconstructing a variety of real-world networks, including gene and protein interaction networks and neuronal circuits.
Inferring climate sensitivity from volcanic events
Energy Technology Data Exchange (ETDEWEB)
Boer, G.J. [Environment Canada, University of Victoria, Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); Stowasser, M.; Hamilton, K. [University of Hawaii, International Pacific Research Centre, Honolulu, HI (United States)
2007-04-15
The possibility of estimating the equilibrium climate sensitivity of the earth-system from observations following explosive volcanic eruptions is assessed in the context of a perfect model study. Two modern climate models (the CCCma CGCM3 and the NCAR CCSM2) with different equilibrium climate sensitivities are employed in the investigation. The models are perturbed with the same transient volcano-like forcing and the responses analysed to infer climate sensitivities. For volcano-like forcing the global mean surface temperature responses of the two models are very similar, despite their differing equilibrium climate sensitivities, indicating that climate sensitivity cannot be inferred from the temperature record alone even if the forcing is known. Equilibrium climate sensitivities can be reasonably determined only if both the forcing and the change in heat storage in the system are known very accurately. The geographic patterns of clear-sky atmosphere/surface and cloud feedbacks are similar for both the transient volcano-like and near-equilibrium constant forcing simulations showing that, to a considerable extent, the same feedback processes are invoked, and determine the climate sensitivity, in both cases. (orig.)
Facility Activity Inference Using Radiation Networks
Energy Technology Data Exchange (ETDEWEB)
Rao, Nageswara S. [ORNL; Ramirez Aviles, Camila A. [ORNL
2017-11-01
We consider the problem of inferring the operational status of a reactor facility using measurements from a radiation sensor network deployed around the facility’s ventilation off-gas stack. The intensity of stack emissions decays with distance, and the sensor counts or measurements are inherently random with parameters determined by the intensity at the sensor’s location. We utilize the measurements to estimate the intensity at the stack, and use it in a one-sided Sequential Probability Ratio Test (SPRT) to infer on/off status of the reactor. We demonstrate the superior performance of this method over conventional majority fusers and individual sensors using (i) test measurements from a network of 21 NaI detectors, and (ii) effluence measurements collected at the stack of a reactor facility. We also analytically establish the superior detection performance of the network over individual sensors with fixed and adaptive thresholds by utilizing the Poisson distribution of the counts. We quantify the performance improvements of the network detection over individual sensors using the packing number of the intensity space.
Models for inference in dynamic metacommunity systems
Dorazio, Robert M.; Kery, Marc; Royle, J. Andrew; Plattner, Matthias
2010-01-01
A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species- and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity.
Causal inference, probability theory, and graphical insights.
Baker, Stuart G
2013-11-10
Causal inference from observational studies is a fundamental topic in biostatistics. The causal graph literature typically views probability theory as insufficient to express causal concepts in observational studies. In contrast, the view here is that probability theory is a desirable and sufficient basis for many topics in causal inference for the following two reasons. First, probability theory is generally more flexible than causal graphs: Besides explaining such causal graph topics as M-bias (adjusting for a collider) and bias amplification and attenuation (when adjusting for instrumental variable), probability theory is also the foundation of the paired availability design for historical controls, which does not fit into a causal graph framework. Second, probability theory is the basis for insightful graphical displays including the BK-Plot for understanding Simpson's paradox with a binary confounder, the BK2-Plot for understanding bias amplification and attenuation in the presence of an unobserved binary confounder, and the PAD-Plot for understanding the principal stratification component of the paired availability design. Published 2013. This article is a US Government work and is in the public domain in the USA.
Inferring relevance in a changing world
Directory of Open Access Journals (Sweden)
Robert C Wilson
2012-01-01
Full Text Available Reinforcement learning models of human and animal learning usually concentrate on how we learn the relationship between different stimuli or actions and rewards. However, in real world situations stimuli are ill-defined. On the one hand, our immediate environment is extremely multi-dimensional. On the other hand, in every decision-making scenario only a few aspects of the environment are relevant for obtaining reward, while most are irrelevant. Thus a key question is how do we learn these relevant dimensions, that is, how do we learn what to learn about? We investigated this process of representation learning experimentally, using a task in which one stimulus dimension was relevant for determining reward at each point in time. As in real life situations, in our task the relevant dimension can change without warning, adding ever-present uncertainty engendered by a constantly changing environment. We show that human performance on this task is better described by a suboptimal strategy based on selective attention and serial hypothesis testing rather than a normative strategy based on probabilistic inference. From this, we conjecture that the problem of inferring relevance in general scenarios is too computationally demanding for the brain to solve optimally. As a result the brain utilizes approximations, employing these even in simplified scenarios in which optimal representation learning is tractable, such as the one in our experiment.
Automated adaptive inference of phenomenological dynamical models
Daniels, Bryan
Understanding the dynamics of biochemical systems can seem impossibly complicated at the microscopic level: detailed properties of every molecular species, including those that have not yet been discovered, could be important for producing macroscopic behavior. The profusion of data in this area has raised the hope that microscopic dynamics might be recovered in an automated search over possible models, yet the combinatorial growth of this space has limited these techniques to systems that contain only a few interacting species. We take a different approach inspired by coarse-grained, phenomenological models in physics. Akin to a Taylor series producing Hooke's Law, forgoing microscopic accuracy allows us to constrain the search over dynamical models to a single dimension. This makes it feasible to infer dynamics with very limited data, including cases in which important dynamical variables are unobserved. We name our method Sir Isaac after its ability to infer the dynamical structure of the law of gravitation given simulated planetary motion data. Applying the method to output from a microscopically complicated but macroscopically simple biological signaling model, it is able to adapt the level of detail to the amount of available data. Finally, using nematode behavioral time series data, the method discovers an effective switch between behavioral attractors after the application of a painful stimulus.
Graphical models for inferring single molecule dynamics
Directory of Open Access Journals (Sweden)
Gonzalez Ruben L
2010-10-01
Full Text Available Abstract Background The recent explosion of experimental techniques in single molecule biophysics has generated a variety of novel time series data requiring equally novel computational tools for analysis and inference. This article describes in general terms how graphical modeling may be used to learn from biophysical time series data using the variational Bayesian expectation maximization algorithm (VBEM. The discussion is illustrated by the example of single-molecule fluorescence resonance energy transfer (smFRET versus time data, where the smFRET time series is modeled as a hidden Markov model (HMM with Gaussian observables. A detailed description of smFRET is provided as well. Results The VBEM algorithm returns the model’s evidence and an approximating posterior parameter distribution given the data. The former provides a metric for model selection via maximum evidence (ME, and the latter a description of the model’s parameters learned from the data. ME/VBEM provide several advantages over the more commonly used approach of maximum likelihood (ML optimized by the expectation maximization (EM algorithm, the most important being a natural form of model selection and a well-posed (non-divergent optimization problem. Conclusions The results demonstrate the utility of graphical modeling for inference of dynamic processes in single molecule biophysics.
Quantum Enhanced Inference in Markov Logic Networks
Wittek, Peter; Gogolin, Christian
2017-04-01
Markov logic networks (MLNs) reconcile two opposing schools in machine learning and artificial intelligence: causal networks, which account for uncertainty extremely well, and first-order logic, which allows for formal deduction. An MLN is essentially a first-order logic template to generate Markov networks. Inference in MLNs is probabilistic and it is often performed by approximate methods such as Markov chain Monte Carlo (MCMC) Gibbs sampling. An MLN has many regular, symmetric structures that can be exploited at both first-order level and in the generated Markov network. We analyze the graph structures that are produced by various lifting methods and investigate the extent to which quantum protocols can be used to speed up Gibbs sampling with state preparation and measurement schemes. We review different such approaches, discuss their advantages, theoretical limitations, and their appeal to implementations. We find that a straightforward application of a recent result yields exponential speedup compared to classical heuristics in approximate probabilistic inference, thereby demonstrating another example where advanced quantum resources can potentially prove useful in machine learning.
Causal Inference in the Perception of Verticality.
de Winkel, Ksander N; Katliar, Mikhail; Diers, Daniel; Bülthoff, Heinrich H
2018-04-03
The perceptual upright is thought to be constructed by the central nervous system (CNS) as a vector sum; by combining estimates on the upright provided by the visual system and the body's inertial sensors with prior knowledge that upright is usually above the head. Recent findings furthermore show that the weighting of the respective sensory signals is proportional to their reliability, consistent with a Bayesian interpretation of a vector sum (Forced Fusion, FF). However, violations of FF have also been reported, suggesting that the CNS may rely on a single sensory system (Cue Capture, CC), or choose to process sensory signals based on inferred signal causality (Causal Inference, CI). We developed a novel alternative-reality system to manipulate visual and physical tilt independently. We tasked participants (n = 36) to indicate the perceived upright for various (in-)congruent combinations of visual-inertial stimuli, and compared models based on their agreement with the data. The results favor the CI model over FF, although this effect became unambiguous only for large discrepancies (±60°). We conclude that the notion of a vector sum does not provide a comprehensive explanation of the perception of the upright, and that CI offers a better alternative.
Constraint Satisfaction Inference : Non-probabilistic Global Inference for Sequence Labelling
Canisius, S.V.M.; van den Bosch, A.; Daelemans, W.; Basili, R.; Moschitti, A.
2006-01-01
We present a new method for performing sequence labelling based on the idea of using a machine-learning classifier to generate several possible output sequences, and then applying an inference procedure to select the best sequence among those. Most sequence labelling methods following a similar
Baykiev, E.; Guerri, M.; Fullea, J.
2017-12-01
The availability of unprecedented resolution aeromagnetic data in Ireland (Tellus project, http://www.tellus.ie/) in conjunction with new satellite magnetic data (e.g., ESÁs Swarm mission) has opened the possibility of detailed modelling of the Irish subsurface magnetic structure. A detailed knowledge of the magnetic characteristics (susceptibility, magnetite content) of the crust is relevant for a number of purposes, including geological mapping and mineral and geothermal energy prospection. In this work we model the magnetic structure of Ireland and surrounding areas using primarily aeromagnetic and satellite observations but also other geophysical data sets. To this aim we use a geophysical-petrological modelling tool (LitMod) in which key properties of rocks (i.e., density, electrical conductivity and seismic velocities) that can be inferred from geophysical data (gravity, seismic, EM) are self consistently determined based on the thermochemical conditions (using the software Perple_X). In contrast to the mantle, where thermodynamic equilibrium is prevalent, in the crust metastable conditions are dominant, i.e. rock properties may not be representative of the current, in situ, temperature and pressure conditions. Instead, the rock properties inferred from geophysical data may be reflecting the mineralogy stable at rock formation conditions. In addition, temperature plays a major role in the distribution of the long wavelength crustal magnetic anomalies. Magnetite retains its magnetic properties below its Curie temperature (585 ºC) and the depth of Curie's isotherm provides an estimate of the thickness of the magnetic crust. Hence, a precise knowledge of the crustal geotherm is required to consistently model crustal magnetic anomalies. In this work LitMod has been modified to account for metastable crustal lithology, to predict susceptibility in the areas below Curie's temperature, and to compute magnetic anomalies based on a magnetic tesseroid approach. The
Structure of the lithosphere-asthenosphere and volcanism in the Tyrrhenian Sea and surroundings
International Nuclear Information System (INIS)
Panza, G.F.; Aoudia, A.; Pontevivo, A.; Sarao, A.; Peccerillo, A.
2003-01-01
The Italian peninsula and the Tyrrhenian Sea are some of the geologically most complex regions on Earth. Such a complexity is expressed by large lateral and vertical variations of the physical properties as inferred from the lithosphere-asthenosphere structure and by the wide varieties of Polio-Quaternary magmatic rocks ranging from teacloth to calcalkaline to sodium- and potassium-alkaline and ultra- alkaline compositions. The integration of geophysical, petrological and geochemical data allows us to recognise various sectors in the Tyrrhenian Sea and surrounding areas and compare different volcanic complexes in order to better constrain the regional geodynamics. A thin crust overlying a soft mantle (10% of partial melting) is typical of the back arc volcanism of the central Tyrrhenian Sea (Magnaghi, Vavilov and Marsili) where tholeiitic rocks dominate. Similar lithosphere-asthenosphere structure is observed for Ustica, Vulture and Etna volcanoes where the geochemical signatures could be related to the contamination of the side intraplate mantle by material coming from the either ancient or active roll-back. The lithosphere-asthenosphere structure and geochemical-isotopic composition do not change significantly when we move to the Stromboli-Campanian volcanoes, where we identify a well developed low-velocity layer, about 10 km thick, below a thin lid, overlain by a thin continental crust. The geochemical signature of the nearby Ischia volcano is characteristic of the Campanian sector and the relative lithosphere-asthenosphere structure may likely represent a transition to the back arc volcanism sector acting in the central Tyrrhenian. The difference in terms of structure beneath Stromboli and the nearby Vulcano and Lipari is confirmed by different geochemical signatures. The affinity between Vulcano, Lipari and Etna could be explained by their common position along the Tindari-Letoianni-Malta fault zone. A low velocity mantle wedge, just below the Moho, is present
Human brain lesion-deficit inference remapped.
Mah, Yee-Haur; Husain, Masud; Rees, Geraint; Nachev, Parashkev
2014-09-01
Our knowledge of the anatomical organization of the human brain in health and disease draws heavily on the study of patients with focal brain lesions. Historically the first method of mapping brain function, it is still potentially the most powerful, establishing the necessity of any putative neural substrate for a given function or deficit. Great inferential power, however, carries a crucial vulnerability: without stronger alternatives any consistent error cannot be easily detected. A hitherto unexamined source of such error is the structure of the high-dimensional distribution of patterns of focal damage, especially in ischaemic injury-the commonest aetiology in lesion-deficit studies-where the anatomy is naturally shaped by the architecture of the vascular tree. This distribution is so complex that analysis of lesion data sets of conventional size cannot illuminate its structure, leaving us in the dark about the presence or absence of such error. To examine this crucial question we assembled the largest known set of focal brain lesions (n = 581), derived from unselected patients with acute ischaemic injury (mean age = 62.3 years, standard deviation = 17.8, male:female ratio = 0.547), visualized with diffusion-weighted magnetic resonance imaging, and processed with validated automated lesion segmentation routines. High-dimensional analysis of this data revealed a hidden bias within the multivariate patterns of damage that will consistently distort lesion-deficit maps, displacing inferred critical regions from their true locations, in a manner opaque to replication. Quantifying the size of this mislocalization demonstrates that past lesion-deficit relationships estimated with conventional inferential methodology are likely to be significantly displaced, by a magnitude dependent on the unknown underlying lesion-deficit relationship itself. Past studies therefore cannot be retrospectively corrected, except by new knowledge that would render them redundant
Meta-learning framework applied in bioinformatics inference system design.
Arredondo, Tomás; Ormazábal, Wladimir
2015-01-01
This paper describes a meta-learner inference system development framework which is applied and tested in the implementation of bioinformatic inference systems. These inference systems are used for the systematic classification of the best candidates for inclusion in bacterial metabolic pathway maps. This meta-learner-based approach utilises a workflow where the user provides feedback with final classification decisions which are stored in conjunction with analysed genetic sequences for periodic inference system training. The inference systems were trained and tested with three different data sets related to the bacterial degradation of aromatic compounds. The analysis of the meta-learner-based framework involved contrasting several different optimisation methods with various different parameters. The obtained inference systems were also contrasted with other standard classification methods with accurate prediction capabilities observed.
Active Inference, homeostatic regulation and adaptive behavioural control.
Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl
2015-11-01
We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Bayesian inference data evaluation and decisions
Harney, Hanns Ludwig
2016-01-01
This new edition offers a comprehensive introduction to the analysis of data using Bayes rule. It generalizes Gaussian error intervals to situations in which the data follow distributions other than Gaussian. This is particularly useful when the observed parameter is barely above the background or the histogram of multiparametric data contains many empty bins, so that the determination of the validity of a theory cannot be based on the chi-squared-criterion. In addition to the solutions of practical problems, this approach provides an epistemic insight: the logic of quantum mechanics is obtained as the logic of unbiased inference from counting data. New sections feature factorizing parameters, commuting parameters, observables in quantum mechanics, the art of fitting with coherent and with incoherent alternatives and fitting with multinomial distribution. Additional problems and examples help deepen the knowledge. Requiring no knowledge of quantum mechanics, the book is written on introductory level, with man...
Bayesian inference and updating of reliability data
International Nuclear Information System (INIS)
Sabri, Z.A.; Cullingford, M.C.; David, H.T.; Husseiny, A.A.
1980-01-01
A Bayes methodology for inference of reliability values using available but scarce current data is discussed. The method can be used to update failure rates as more information becomes available from field experience, assuming that the performance of a given component (or system) exhibits a nonhomogeneous Poisson process. Bayes' theorem is used to summarize the historical evidence and current component data in the form of a posterior distribution suitable for prediction and for smoothing or interpolation. An example is given. It may be appropriate to apply the methodology developed here to human error data, in which case the exponential model might be used to describe the learning behavior of the operator or maintenance crew personnel
Automatic inference of indexing rules for MEDLINE
Directory of Open Access Journals (Sweden)
Shooshan Sonya E
2008-11-01
Full Text Available Abstract Background: Indexing is a crucial step in any information retrieval system. In MEDLINE, a widely used database of the biomedical literature, the indexing process involves the selection of Medical Subject Headings in order to describe the subject matter of articles. The need for automatic tools to assist MEDLINE indexers in this task is growing with the increasing number of publications being added to MEDLINE. Methods: In this paper, we describe the use and the customization of Inductive Logic Programming (ILP to infer indexing rules that may be used to produce automatic indexing recommendations for MEDLINE indexers. Results: Our results show that this original ILP-based approach outperforms manual rules when they exist. In addition, the use of ILP rules also improves the overall performance of the Medical Text Indexer (MTI, a system producing automatic indexing recommendations for MEDLINE. Conclusion: We expect the sets of ILP rules obtained in this experiment to be integrated into MTI.
Progression inference for somatic mutations in cancer
Directory of Open Access Journals (Sweden)
Leif E. Peterson
2017-04-01
Full Text Available Computational methods were employed to determine progression inference of genomic alterations in commonly occurring cancers. Using cross-sectional TCGA data, we computed evolutionary trajectories involving selectivity relationships among pairs of gene-specific genomic alterations such as somatic mutations, deletions, amplifications, downregulation, and upregulation among the top 20 driver genes associated with each cancer. Results indicate that the majority of hierarchies involved TP53, PIK3CA, ERBB2, APC, KRAS, EGFR, IDH1, VHL, etc. Research into the order and accumulation of genomic alterations among cancer driver genes will ever-increase as the costs of nextgen sequencing subside, and personalized/precision medicine incorporates whole-genome scans into the diagnosis and treatment of cancer. Keywords: Oncology, Cancer research, Genetics, Computational biology
Inferring Phylogenetic Networks from Gene Order Data
Directory of Open Access Journals (Sweden)
Alexey Anatolievich Morozov
2013-01-01
Full Text Available Existing algorithms allow us to infer phylogenetic networks from sequences (DNA, protein or binary, sets of trees, and distance matrices, but there are no methods to build them using the gene order data as an input. Here we describe several methods to build split networks from the gene order data, perform simulation studies, and use our methods for analyzing and interpreting different real gene order datasets. All proposed methods are based on intermediate data, which can be generated from genome structures under study and used as an input for network construction algorithms. Three intermediates are used: set of jackknife trees, distance matrix, and binary encoding. According to simulations and case studies, the best intermediates are jackknife trees and distance matrix (when used with Neighbor-Net algorithm. Binary encoding can also be useful, but only when the methods mentioned above cannot be used.
Supplier Selection Using Fuzzy Inference System
Directory of Open Access Journals (Sweden)
hamidreza kadhodazadeh
2014-01-01
Full Text Available Suppliers are one of the most vital parts of supply chain whose operation has significant indirect effect on customer satisfaction. Since customer's expectations from organization are different, organizations should consider different standards, respectively. There are many researches in this field using different standards and methods in recent years. The purpose of this study is to propose an approach for choosing a supplier in a food manufacturing company considering cost, quality, service, type of relationship and structure standards of the supplier organization. To evaluate supplier according to the above standards, the fuzzy inference system has been used. Input data of this system includes supplier's score in any standard that is achieved by AHP approach and the output is final score of each supplier. Finally, a supplier has been selected that although is not the best in price and quality, has achieved good score in all of the standards.
Gene expression inference with deep learning.
Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui
2016-06-15
Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Systematic parameter inference in stochastic mesoscopic modeling
Energy Technology Data Exchange (ETDEWEB)
Lei, Huan; Yang, Xiu [Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Li, Zhen [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)
2017-02-01
We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.
State-Space Inference and Learning with Gaussian Processes
Turner, R; Deisenroth, MP; Rasmussen, CE
2010-01-01
18.10.13 KB. Ok to add author version to spiral, authors hold copyright. State-space inference and learning with Gaussian processes (GPs) is an unsolved problem. We propose a new, general methodology for inference and learning in nonlinear state-space models that are described probabilistically by non-parametric GP models. We apply the expectation maximization algorithm to iterate between inference in the latent state-space and learning the parameters of the underlying GP dynamics model. C...
International Nuclear Information System (INIS)
Jiang Zhongming; Zhang Xinmin
2008-01-01
Excavation of tunnel changes not only the stresses and deformation of tunnel surrounding rock, but also disturbs the underground water environment in tunnel surrounding rock Water migration happens due to variation of pore water pressure and redistribution. Based on the mechanics of porous media, saturated and unsaturated hydro-mechanical coupling analysis method is employed to study the variation of the stresses, deformation and pore pressure of the surrounding rock. Case study indicates that the excavation of tunnel will induce redistribution of stress and pore water pressure. Redistribution of pore water pressure will seriously affect on evaluation of surrounding rock stability and diffusion of nucleon in the pore water. (authors)
Probabilistic logic networks a comprehensive framework for uncertain inference
Goertzel, Ben; Goertzel, Izabela Freire; Heljakka, Ari
2008-01-01
This comprehensive book describes Probabilistic Logic Networks (PLN), a novel conceptual, mathematical and computational approach to uncertain inference. A broad scope of reasoning types are considered.
Parametric statistical inference basic theory and modern approaches
Zacks, Shelemyahu; Tsokos, C P
1981-01-01
Parametric Statistical Inference: Basic Theory and Modern Approaches presents the developments and modern trends in statistical inference to students who do not have advanced mathematical and statistical preparation. The topics discussed in the book are basic and common to many fields of statistical inference and thus serve as a jumping board for in-depth study. The book is organized into eight chapters. Chapter 1 provides an overview of how the theory of statistical inference is presented in subsequent chapters. Chapter 2 briefly discusses statistical distributions and their properties. Chapt
Directory of Open Access Journals (Sweden)
Shicheng Li
2016-08-01
Full Text Available As the world’s highest railway, and the longest highland railway, the Qinghai–Tibet Railway (QTR has been paid considerable attention by researchers. However, most attention has been paid to the ecological and environmental issues affecting it, and sustainable ecological, social, and economic development-related studies of the QTR are rare. In this study, by analyzing the passenger traffic, freight traffic, passenger-kilometers, and freight-kilometers of the QTR for the period 1982–2013 and the transport structure of the Tibetan Plateau (TP for 1990–2013, the evolutionary process of the transport system in the TP following the construction of the QTR has been revealed. Subsequently, by comparing Gross Domestic Product (GDP, population, industrial structure, and urbanization level at the county and 1 km scales between surrounding and non-surrounding areas of the QTR, the differences in socioeconomic performance before and after its construction were detected. The results show that (1 in the TP, the highway-dominated transport system will break up and an integrated and sustainable transport system will form; (2 at the county scale, the annual growth rates of GDP of counties surrounding the QTR were greater than those of non-surrounding counties for the period 2000–2010. At the 1 km scale, following the opening of the completed line, the GDP of surrounding areas had a greater growth rate than before; (3 analysis at the county and 1 km scales indicated that population was not aggregated into the surrounding areas of the QTR in the period 2000–2010; (4 in terms of industrial structure, the proportion of primary industry decreased continuously, while the proportion of secondary and tertiary industries increased overall in the period 1984–2012. The QTR had no obvious impact on changes in the urbanization level of its surrounding areas.
Serang, Oliver
2014-01-01
Exact Bayesian inference can sometimes be performed efficiently for special cases where a function has commutative and associative symmetry of its inputs (called “causal independence”). For this reason, it is desirable to exploit such symmetry on big data sets. Here we present a method to exploit a general form of this symmetry on probabilistic adder nodes by transforming those probabilistic adder nodes into a probabilistic convolution tree with which dynamic programming computes exact probabilities. A substantial speedup is demonstrated using an illustration example that can arise when identifying splice forms with bottom-up mass spectrometry-based proteomics. On this example, even state-of-the-art exact inference algorithms require a runtime more than exponential in the number of splice forms considered. By using the probabilistic convolution tree, we reduce the runtime to and the space to where is the number of variables joined by an additive or cardinal operator. This approach, which can also be used with junction tree inference, is applicable to graphs with arbitrary dependency on counting variables or cardinalities and can be used on diverse problems and fields like forward error correcting codes, elemental decomposition, and spectral demixing. The approach also trivially generalizes to multiple dimensions. PMID:24626234
Making inference from wildlife collision data: inferring predator absence from prey strikes
Directory of Open Access Journals (Sweden)
Peter Caley
2017-02-01
Full Text Available Wildlife collision data are ubiquitous, though challenging for making ecological inference due to typically irreducible uncertainty relating to the sampling process. We illustrate a new approach that is useful for generating inference from predator data arising from wildlife collisions. By simply conditioning on a second prey species sampled via the same collision process, and by using a biologically realistic numerical response functions, we can produce a coherent numerical response relationship between predator and prey. This relationship can then be used to make inference on the population size of the predator species, including the probability of extinction. The statistical conditioning enables us to account for unmeasured variation in factors influencing the runway strike incidence for individual airports and to enable valid comparisons. A practical application of the approach for testing hypotheses about the distribution and abundance of a predator species is illustrated using the hypothesized red fox incursion into Tasmania, Australia. We estimate that conditional on the numerical response between fox and lagomorph runway strikes on mainland Australia, the predictive probability of observing no runway strikes of foxes in Tasmania after observing 15 lagomorph strikes is 0.001. We conclude there is enough evidence to safely reject the null hypothesis that there is a widespread red fox population in Tasmania at a population density consistent with prey availability. The method is novel and has potential wider application.
Making inference from wildlife collision data: inferring predator absence from prey strikes.
Caley, Peter; Hosack, Geoffrey R; Barry, Simon C
2017-01-01
Wildlife collision data are ubiquitous, though challenging for making ecological inference due to typically irreducible uncertainty relating to the sampling process. We illustrate a new approach that is useful for generating inference from predator data arising from wildlife collisions. By simply conditioning on a second prey species sampled via the same collision process, and by using a biologically realistic numerical response functions, we can produce a coherent numerical response relationship between predator and prey. This relationship can then be used to make inference on the population size of the predator species, including the probability of extinction. The statistical conditioning enables us to account for unmeasured variation in factors influencing the runway strike incidence for individual airports and to enable valid comparisons. A practical application of the approach for testing hypotheses about the distribution and abundance of a predator species is illustrated using the hypothesized red fox incursion into Tasmania, Australia. We estimate that conditional on the numerical response between fox and lagomorph runway strikes on mainland Australia, the predictive probability of observing no runway strikes of foxes in Tasmania after observing 15 lagomorph strikes is 0.001. We conclude there is enough evidence to safely reject the null hypothesis that there is a widespread red fox population in Tasmania at a population density consistent with prey availability. The method is novel and has potential wider application.
An oxygen-rich dust disk surrounding an evolved star in the Red Rectangle
Waters, LBFM; Waelkens, C; van Winckel, H; Molster, FJ; Tielens, AGGM; van Loon, JT; Morris, PW; Cami, J; Bouwman, J; de Koter, A; de Jong, T; de Graauw, T
1998-01-01
The Red Rectangle(1) is the prototype of a class of carbon-rich reflection nebulae surrounding low-mass stars in the final stages of evolution. The central star of this nebula has ejected most of its layers (during the red-giant phase), which now form the surrounding cloud, and is rapidly evolving
Influence of Surrounding Colors in the Illuminant-Color Mode on Color Constancy
Directory of Open Access Journals (Sweden)
Kazuho Fukuda
2011-05-01
Full Text Available On color constancy, we showed that brighter surrounding colors had greater influence than dim colors (Uchikawa, Kitazawa, MacLeod, Fukuda, 2010 APCV. Increasing luminance of a stimulus causes the change in appearance from the surface-color to the illuminant-color mode. However it is unknown whether the visual system considers such color appearance mode of surrounding colors to achieve color constancy. We investigated the influence of surrounding colors that appeared illuminant on color constancy. The stimulus was composed of a central test stimulus and surrounding six colors: bright and dim red, green and blue. The observers adjusted the chromaticity of the test stimulus to be appeared as an achromatic surface. The luminance balance of three bright surrounding colors was equalized with that of the optimal colors in three illuminant conditions, then, the luminance of one of the three bright colors was varied in the range beyond the critical luminance of color appearance mode transition. The results showed that increasing luminance of a bright surrounding color shifted the observers' achromatic setting toward its chromaticity, but this effect diminished for the surrounding color in the illuminant-color mode. These results suggest that the visual system considers color appearance mode of surrounding colors to accomplish color constancy.
Modifications of center-surround, spot detection and dot-pattern selective operators
Petkov, Nicolai; Visser, Wicher T.
2005-01-01
This paper describes modifications of the models of center-surround and dot-pattern selective cells proposed previously. These modifications concern mainly the normalization of the difference of Gaussians (DoG) function used to model center-surround receptive fields, the normalization of
The nature of surround-induced depolarizing responses in goldfish cones
Kraaij, D. A.; Spekreijse, H.; Kamermans, M.
2000-01-01
Cones in the vertebrate retina project to horizontal and bipolar cells and the horizontal cells feedback negatively to cones. This organization forms the basis for the center/surround organization of the bipolar cells, a fundamental step in the visual signal processing. Although the surround
Directory of Open Access Journals (Sweden)
P. J. Watson
2013-12-01
Full Text Available According to the Religious Openness Hypothesis, the religious and psychological openness of American Christians is obscured by a defensive ghettoization of thought associated with a Religious Fundamentalist Ideological Surround and can be discovered instead within a Biblical Foundationalist Ideological Surround. A test of this claim examined Religious Fundamentalism, Biblical Foundationalism, Quest, and Multidimensional Quest Scales in 432 undergraduates. Christian Religious Reflection, Religious Schema, and Religious Orientation measures clarified these two ideological surrounds. Partial correlations controlling for Biblical Foundationalism described a Religious Fundamentalist Ideological Surround that more strongly rejected Quest and that more generally displayed a failure to integrate faith with intellect. Partial correlations controlling for Religious Fundamentalism revealed a Biblical Foundationalist Ideological Surround that was more open to Quest and that offered numerous demonstrations of an ability to unite faith with intellect. These data supplemented previous investigations in demonstrating that Christianity and other traditional religions have ideological resources for promoting a faithful intellect.
Making Inferences in Adulthood: Falling Leaves Mean It's Fall.
Zandi, Taher; Gregory, Monica E.
1988-01-01
Assessed age differences in making inferences from prose. Older adults correctly answered mean of 10 questions related to implicit information and 8 related to explicit information. Young adults answered mean of 7 implicit and 12 explicit information questions. In spite of poorer recall of factual details, older subjects made inferences to greater…
Statistical Inference and Patterns of Inequality in the Global North
Moran, Timothy Patrick
2006-01-01
Cross-national inequality trends have historically been a crucial field of inquiry across the social sciences, and new methodological techniques of statistical inference have recently improved the ability to analyze these trends over time. This paper applies Monte Carlo, bootstrap inference methods to the income surveys of the Luxembourg Income…
Causal Effect Inference with Deep Latent-Variable Models
Louizos, C; Shalit, U.; Mooij, J.; Sontag, D.; Zemel, R.; Welling, M.
2017-01-01
Learning individual-level causal effects from observational data, such as inferring the most effective medication for a specific patient, is a problem of growing importance for policy makers. The most important aspect of inferring causal effects from observational data is the handling of
A Comparative Analysis of Fuzzy Inference Engines in Context of ...
African Journals Online (AJOL)
Fuzzy inference engine has found successful applications in a wide variety of fields, such as automatic control, data classification, decision analysis, expert engines, time series prediction, robotics, pattern recognition, etc. This paper presents a comparative analysis of three fuzzy inference engines, max-product, max-min ...
General Purpose Probabilistic Programming Platform with Effective Stochastic Inference
2018-04-01
REFERENCES 74 LIST OF ACRONYMS 80 ii List of Figures Figure 1. The problem of inferring curves from data while simultaneously choosing the...bottom path) as the inverse problem to computer graphics (top path). ........ 18 Figure 18. An illustration of generative probabilistic graphics for 3D...Building these systems involves simultaneously developing mathematical models, inference algorithms and optimized software implementations. Small changes
A Comparative Analysis of Fuzzy Inference Engines in Context of ...
African Journals Online (AJOL)
PROF. O. E. OSUAGWU
Fuzzy Inference engine is an important part of reasoning systems capable of extracting correct conclusions from ... is known as the inference, or rule definition portion, of fuzzy .... minimal set of decision rules based on input- ... The study uses Mamdani FIS model and. Sugeno FIS ... control of induction motor drive. [18] study.
Deontic Introduction: A Theory of Inference from Is to Ought
Elqayam, Shira; Thompson, Valerie A.; Wilkinson, Meredith R.; Evans, Jonathan St. B. T.; Over, David E.
2015-01-01
Humans have a unique ability to generate novel norms. Faced with the knowledge that there are hungry children in Somalia, we easily and naturally infer that we ought to donate to famine relief charities. Although a contentious and lively issue in metaethics, such inference from "is" to "ought" has not been systematically…
Causal inference in survival analysis using pseudo-observations
DEFF Research Database (Denmark)
Andersen, Per K; Syriopoulou, Elisavet; Parner, Erik T
2017-01-01
Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs ...
Vanegas, Carlos A; Aliaga, Daniel G; Benes, Bedrich; Waddell, Paul
2009-01-01
Urban simulation models and their visualization are used to help regional planning agencies evaluate alternative transportation investments, land use regulations, and environmental protection policies. Typical urban simulations provide spatially distributed data about number of inhabitants, land prices, traffic, and other variables. In this article, we build on a synergy of urban simulation, urban visualization, and computer graphics to automatically infer an urban layout for any time step of the simulation sequence. In addition to standard visualization tools, our method gathers data of the original street network, parcels, and aerial imagery and uses the available simulation results to infer changes to the original urban layout and produce a new and plausible layout for the simulation results. In contrast with previous work, our approach automatically updates the layout based on changes in the simulation data and thus can scale to a large simulation over many years. The method in this article offers a substantial step forward in building integrated visualization and behavioral simulation systems for use in community visioning, planning, and policy analysis. We demonstrate our method on several real cases using a 200 GB database for a 16,300 km2 area surrounding Seattle.
Hedge, Jessica; Wilson, Daniel J
2014-11-25
Phylogenetic inference in bacterial genomics is fundamental to understanding problems such as population history, antimicrobial resistance, and transmission dynamics. The field has been plagued by an apparent state of contradiction since the distorting effects of recombination on phylogeny were discovered more than a decade ago. Researchers persist with detailed phylogenetic analyses while simultaneously acknowledging that recombination seriously misleads inference of population dynamics and selection. Here we resolve this paradox by showing that phylogenetic tree topologies based on whole genomes robustly reconstruct the clonal frame topology but that branch lengths are badly skewed. Surprisingly, removing recombining sites can exacerbate branch length distortion caused by recombination. Phylogenetic tree reconstruction is a popular approach for understanding the relatedness of bacteria in a population from differences in their genome sequences. However, bacteria frequently exchange regions of their genomes by a process called homologous recombination, which violates a fundamental assumption of phylogenetic methods. Since many researchers continue to use phylogenetics for recombining bacteria, it is important to understand how recombination affects the conclusions drawn from these analyses. We find that whole-genome sequences afford great accuracy in reconstructing evolutionary relationships despite concerns surrounding the presence of recombination, but the branch lengths of the phylogenetic tree are indeed badly distorted. Surprisingly, methods to reduce the impact of recombination on branch lengths can exacerbate the problem. Copyright © 2014 Hedge and Wilson.
Cholinergic enhancement reduces orientation-specific surround suppression but not visual crowding
Directory of Open Access Journals (Sweden)
Anna A. Kosovicheva
2012-09-01
Full Text Available Acetylcholine (ACh reduces the spatial spread of excitatory fMRI responses in early visual cortex and the receptive field sizes of V1 neurons. We investigated the perceptual consequences of these physiological effects of ACh with surround suppression and crowding, two tasks that involve spatial interactions between visual field locations. Surround suppression refers to the reduction in perceived stimulus contrast by a high-contrast surround stimulus. For grating stimuli, surround suppression is selective for the relative orientations of the center and surround, suggesting that it results from inhibitory interactions in early visual cortex. Crowding refers to impaired identification of a peripheral stimulus in the presence of flankers and is thought to result from excessive integration of visual features. We increased synaptic ACh levels by administering the cholinesterase inhibitor donepezil to healthy human subjects in a placebo-controlled, double-blind design. In Exp. 1, we measured surround suppression of a central grating using a contrast discrimination task with three conditions: 1 surround grating with the same orientation as the center (parallel, 2 surround orthogonal to the center, or 3 no surround. Contrast discrimination thresholds were higher in the parallel than in the orthogonal condition, demonstrating orientation-specific surround suppression (OSSS. Cholinergic enhancement reduced thresholds only in the parallel condition, thereby reducing OSSS. In Exp. 2, subjects performed a crowding task in which they reported the identity of a peripheral letter flanked by letters on either side. We measured the critical spacing between the target and flanking letters that allowed reliable identification. Cholinergic enhancement had no effect on critical spacing. Our findings suggest that ACh reduces spatial interactions in tasks involving segmentation of visual field locations but that these effects may be limited to early visual cortical
Bayesian inference of radiation belt loss timescales.
Camporeale, E.; Chandorkar, M.
2017-12-01
Electron fluxes in the Earth's radiation belts are routinely studied using the classical quasi-linear radial diffusion model. Although this simplified linear equation has proven to be an indispensable tool in understanding the dynamics of the radiation belt, it requires specification of quantities such as the diffusion coefficient and electron loss timescales that are never directly measured. Researchers have so far assumed a-priori parameterisations for radiation belt quantities and derived the best fit using satellite data. The state of the art in this domain lacks a coherent formulation of this problem in a probabilistic framework. We present some recent progress that we have made in performing Bayesian inference of radial diffusion parameters. We achieve this by making extensive use of the theory connecting Gaussian Processes and linear partial differential equations, and performing Markov Chain Monte Carlo sampling of radial diffusion parameters. These results are important for understanding the role and the propagation of uncertainties in radiation belt simulations and, eventually, for providing a probabilistic forecast of energetic electron fluxes in a Space Weather context.
Scalable inference for stochastic block models
Peng, Chengbin
2017-12-08
Community detection in graphs is widely used in social and biological networks, and the stochastic block model is a powerful probabilistic tool for describing graphs with community structures. However, in the era of "big data," traditional inference algorithms for such a model are increasingly limited due to their high time complexity and poor scalability. In this paper, we propose a multi-stage maximum likelihood approach to recover the latent parameters of the stochastic block model, in time linear with respect to the number of edges. We also propose a parallel algorithm based on message passing. Our algorithm can overlap communication and computation, providing speedup without compromising accuracy as the number of processors grows. For example, to process a real-world graph with about 1.3 million nodes and 10 million edges, our algorithm requires about 6 seconds on 64 cores of a contemporary commodity Linux cluster. Experiments demonstrate that the algorithm can produce high quality results on both benchmark and real-world graphs. An example of finding more meaningful communities is illustrated consequently in comparison with a popular modularity maximization algorithm.
Probabilistic learning and inference in schizophrenia
Averbeck, Bruno B.; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S.
2010-01-01
Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behaviour remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behaviour, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. PMID:20810252
Heuristics as Bayesian inference under extreme priors.
Parpart, Paula; Jones, Matt; Love, Bradley C
2018-05-01
Simple heuristics are often regarded as tractable decision strategies because they ignore a great deal of information in the input data. One puzzle is why heuristics can outperform full-information models, such as linear regression, which make full use of the available information. These "less-is-more" effects, in which a relatively simpler model outperforms a more complex model, are prevalent throughout cognitive science, and are frequently argued to demonstrate an inherent advantage of simplifying computation or ignoring information. In contrast, we show at the computational level (where algorithmic restrictions are set aside) that it is never optimal to discard information. Through a formal Bayesian analysis, we prove that popular heuristics, such as tallying and take-the-best, are formally equivalent to Bayesian inference under the limit of infinitely strong priors. Varying the strength of the prior yields a continuum of Bayesian models with the heuristics at one end and ordinary regression at the other. Critically, intermediate models perform better across all our simulations, suggesting that down-weighting information with the appropriate prior is preferable to entirely ignoring it. Rather than because of their simplicity, our analyses suggest heuristics perform well because they implement strong priors that approximate the actual structure of the environment. We end by considering how new heuristics could be derived by infinitely strengthening the priors of other Bayesian models. These formal results have implications for work in psychology, machine learning and economics. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Aesthetic quality inference for online fashion shopping
Chen, Ming; Allebach, Jan
2014-03-01
On-line fashion communities in which participants post photos of personal fashion items for viewing and possible purchase by others are becoming increasingly popular. Generally, these photos are taken by individuals who have no training in photography with low-cost mobile phone cameras. It is desired that photos of the products have high aesthetic quality to improve the users' online shopping experience. In this work, we design features for aesthetic quality inference in the context of online fashion shopping. Psychophysical experiments are conducted to construct a database of the photos' aesthetic evaluation, specifically for photos from an online fashion shopping website. We then extract both generic low-level features and high-level image attributes to represent the aesthetic quality. Using a support vector machine framework, we train a predictor of the aesthetic quality rating based on the feature vector. Experimental results validate the efficacy of our approach. Metadata such as the product type are also used to further improve the result.
Information-Theoretic Inference of Common Ancestors
Directory of Open Access Journals (Sweden)
Bastian Steudel
2015-04-01
Full Text Available A directed acyclic graph (DAG partially represents the conditional independence structure among observations of a system if the local Markov condition holds, that is if every variable is independent of its non-descendants given its parents. In general, there is a whole class of DAGs that represents a given set of conditional independence relations. We are interested in properties of this class that can be derived from observations of a subsystem only. To this end, we prove an information-theoretic inequality that allows for the inference of common ancestors of observed parts in any DAG representing some unknown larger system. More explicitly, we show that a large amount of dependence in terms of mutual information among the observations implies the existence of a common ancestor that distributes this information. Within the causal interpretation of DAGs, our result can be seen as a quantitative extension of Reichenbach’s principle of common cause to more than two variables. Our conclusions are valid also for non-probabilistic observations, such as binary strings, since we state the proof for an axiomatized notion of “mutual information” that includes the stochastic as well as the algorithmic version.
Probabilistic learning and inference in schizophrenia.
Averbeck, Bruno B; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S
2011-04-01
Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behavior remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behavior, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving a noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. Published by Elsevier B.V.
Active Inference and Learning in the Cerebellum.
Friston, Karl; Herreros, Ivan
2016-09-01
This letter offers a computational account of Pavlovian conditioning in the cerebellum based on active inference and predictive coding. Using eyeblink conditioning as a canonical paradigm, we formulate a minimal generative model that can account for spontaneous blinking, startle responses, and (delay or trace) conditioning. We then establish the face validity of the model using simulated responses to unconditioned and conditioned stimuli to reproduce the sorts of behavior that are observed empirically. The scheme's anatomical validity is then addressed by associating variables in the predictive coding scheme with nuclei and neuronal populations to match the (extrinsic and intrinsic) connectivity of the cerebellar (eyeblink conditioning) system. Finally, we try to establish predictive validity by reproducing selective failures of delay conditioning, trace conditioning, and extinction using (simulated and reversible) focal lesions. Although rather metaphorical, the ensuing scheme can account for a remarkable range of anatomical and neurophysiological aspects of cerebellar circuitry-and the specificity of lesion-deficit mappings that have been established experimentally. From a computational perspective, this work shows how conditioning or learning can be formulated in terms of minimizing variational free energy (or maximizing Bayesian model evidence) using exactly the same principles that underlie predictive coding in perception.
Inferring gene networks from discrete expression data
Zhang, L.
2013-07-18
The modeling of gene networks from transcriptional expression data is an important tool in biomedical research to reveal signaling pathways and to identify treatment targets. Current gene network modeling is primarily based on the use of Gaussian graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which generate counts of mRNAtranscripts in cell samples.We propose a generalized linear model to fit the discrete gene expression data and assume that the log ratios of the mean expression levels follow a Gaussian distribution.We restrict the gene network structures to decomposable graphs and derive the graphs by selecting the covariance matrix of the Gaussian distribution with the hyper-inverse Wishart priors. Furthermore, we incorporate prior network models based on gene ontology information, which avails existing biological information on the genes of interest. We conduct simulation studies to examine the performance of our discrete graphical model and apply the method to two real datasets for gene network inference. © The Author 2013. Published by Oxford University Press. All rights reserved.
Bayesian Inference of a Multivariate Regression Model
Directory of Open Access Journals (Sweden)
Marick S. Sinay
2014-01-01
Full Text Available We explore Bayesian inference of a multivariate linear regression model with use of a flexible prior for the covariance structure. The commonly adopted Bayesian setup involves the conjugate prior, multivariate normal distribution for the regression coefficients and inverse Wishart specification for the covariance matrix. Here we depart from this approach and propose a novel Bayesian estimator for the covariance. A multivariate normal prior for the unique elements of the matrix logarithm of the covariance matrix is considered. Such structure allows for a richer class of prior distributions for the covariance, with respect to strength of beliefs in prior location hyperparameters, as well as the added ability, to model potential correlation amongst the covariance structure. The posterior moments of all relevant parameters of interest are calculated based upon numerical results via a Markov chain Monte Carlo procedure. The Metropolis-Hastings-within-Gibbs algorithm is invoked to account for the construction of a proposal density that closely matches the shape of the target posterior distribution. As an application of the proposed technique, we investigate a multiple regression based upon the 1980 High School and Beyond Survey.
Logical inference techniques for loop parallelization
Oancea, Cosmin E.; Rauchwerger, Lawrence
2012-01-01
This paper presents a fully automatic approach to loop parallelization that integrates the use of static and run-time analysis and thus overcomes many known difficulties such as nonlinear and indirect array indexing and complex control flow. Our hybrid analysis framework validates the parallelization transformation by verifying the independence of the loop's memory references. To this end it represents array references using the USR (uniform set representation) language and expresses the independence condition as an equation, S = Ø, where S is a set expression representing array indexes. Using a language instead of an array-abstraction representation for S results in a smaller number of conservative approximations but exhibits a potentially-high runtime cost. To alleviate this cost we introduce a language translation F from the USR set-expression language to an equally rich language of predicates (F(S) ⇒ S = Ø). Loop parallelization is then validated using a novel logic inference algorithm that factorizes the obtained complex predicates (F(S)) into a sequence of sufficient-independence conditions that are evaluated first statically and, when needed, dynamically, in increasing order of their estimated complexities. We evaluate our automated solution on 26 benchmarks from PERFECTCLUB and SPEC suites and show that our approach is effective in parallelizing large, complex loops and obtains much better full program speedups than the Intel and IBM Fortran compilers. Copyright © 2012 ACM.
BAYESIAN INFERENCE OF CMB GRAVITATIONAL LENSING
Energy Technology Data Exchange (ETDEWEB)
Anderes, Ethan [Department of Statistics, University of California, Davis, CA 95616 (United States); Wandelt, Benjamin D.; Lavaux, Guilhem [Sorbonne Universités, UPMC Univ Paris 06 and CNRS, UMR7095, Institut d’Astrophysique de Paris, F-75014, Paris (France)
2015-08-01
The Planck satellite, along with several ground-based telescopes, has mapped the cosmic microwave background (CMB) at sufficient resolution and signal-to-noise so as to allow a detection of the subtle distortions due to the gravitational influence of the intervening matter distribution. A natural modeling approach is to write a Bayesian hierarchical model for the lensed CMB in terms of the unlensed CMB and the lensing potential. So far there has been no feasible algorithm for inferring the posterior distribution of the lensing potential from the lensed CMB map. We propose a solution that allows efficient Markov Chain Monte Carlo sampling from the joint posterior of the lensing potential and the unlensed CMB map using the Hamiltonian Monte Carlo technique. The main conceptual step in the solution is a re-parameterization of CMB lensing in terms of the lensed CMB and the “inverse lensing” potential. We demonstrate a fast implementation on simulated data, including noise and a sky cut, that uses a further acceleration based on a very mild approximation of the inverse lensing potential. We find that the resulting Markov Chain has short correlation lengths and excellent convergence properties, making it promising for applications to high-resolution CMB data sets in the future.
Virtual reality and consciousness inference in dreaming.
Hobson, J Allan; Hong, Charles C-H; Friston, Karl J
2014-01-01
This article explores the notion that the brain is genetically endowed with an innate virtual reality generator that - through experience-dependent plasticity - becomes a generative or predictive model of the world. This model, which is most clearly revealed in rapid eye movement (REM) sleep dreaming, may provide the theater for conscious experience. Functional neuroimaging evidence for brain activations that are time-locked to rapid eye movements (REMs) endorses the view that waking consciousness emerges from REM sleep - and dreaming lays the foundations for waking perception. In this view, the brain is equipped with a virtual model of the world that generates predictions of its sensations. This model is continually updated and entrained by sensory prediction errors in wakefulness to ensure veridical perception, but not in dreaming. In contrast, dreaming plays an essential role in maintaining and enhancing the capacity to model the world by minimizing model complexity and thereby maximizing both statistical and thermodynamic efficiency. This perspective suggests that consciousness corresponds to the embodied process of inference, realized through the generation of virtual realities (in both sleep and wakefulness). In short, our premise or hypothesis is that the waking brain engages with the world to predict the causes of sensations, while in sleep the brain's generative model is actively refined so that it generates more efficient predictions during waking. We review the evidence in support of this hypothesis - evidence that grounds consciousness in biophysical computations whose neuronal and neurochemical infrastructure has been disclosed by sleep research.
Inferring human mobility using communication patterns
Palchykov, Vasyl; Mitrović, Marija; Jo, Hang-Hyun; Saramäki, Jari; Pan, Raj Kumar
2014-08-01
Understanding the patterns of mobility of individuals is crucial for a number of reasons, from city planning to disaster management. There are two common ways of quantifying the amount of travel between locations: by direct observations that often involve privacy issues, e.g., tracking mobile phone locations, or by estimations from models. Typically, such models build on accurate knowledge of the population size at each location. However, when this information is not readily available, their applicability is rather limited. As mobile phones are ubiquitous, our aim is to investigate if mobility patterns can be inferred from aggregated mobile phone call data alone. Using data released by Orange for Ivory Coast, we show that human mobility is well predicted by a simple model based on the frequency of mobile phone calls between two locations and their geographical distance. We argue that the strength of the model comes from directly incorporating the social dimension of mobility. Furthermore, as only aggregated call data is required, the model helps to avoid potential privacy problems.
Inference-based procedural modeling of solids
Biggers, Keith
2011-11-01
As virtual environments become larger and more complex, there is an increasing need for more automated construction algorithms to support the development process. We present an approach for modeling solids by combining prior examples with a simple sketch. Our algorithm uses an inference-based approach to incrementally fit patches together in a consistent fashion to define the boundary of an object. This algorithm samples and extracts surface patches from input models, and develops a Petri net structure that describes the relationship between patches along an imposed parameterization. Then, given a new parameterized line or curve, we use the Petri net to logically fit patches together in a manner consistent with the input model. This allows us to easily construct objects of varying sizes and configurations using arbitrary articulation, repetition, and interchanging of parts. The result of our process is a solid model representation of the constructed object that can be integrated into a simulation-based environment. © 2011 Elsevier Ltd. All rights reserved.
Multiple sequence alignment accuracy and phylogenetic inference.
Ogden, T Heath; Rosenberg, Michael S
2006-04-01
Phylogenies are often thought to be more dependent upon the specifics of the sequence alignment rather than on the method of reconstruction. Simulation of sequences containing insertion and deletion events was performed in order to determine the role that alignment accuracy plays during phylogenetic inference. Data sets were simulated for pectinate, balanced, and random tree shapes under different conditions (ultrametric equal branch length, ultrametric random branch length, nonultrametric random branch length). Comparisons between hypothesized alignments and true alignments enabled determination of two measures of alignment accuracy, that of the total data set and that of individual branches. In general, our results indicate that as alignment error increases, topological accuracy decreases. This trend was much more pronounced for data sets derived from more pectinate topologies. In contrast, for balanced, ultrametric, equal branch length tree shapes, alignment inaccuracy had little average effect on tree reconstruction. These conclusions are based on average trends of many analyses under different conditions, and any one specific analysis, independent of the alignment accuracy, may recover very accurate or inaccurate topologies. Maximum likelihood and Bayesian, in general, outperformed neighbor joining and maximum parsimony in terms of tree reconstruction accuracy. Results also indicated that as the length of the branch and of the neighboring branches increase, alignment accuracy decreases, and the length of the neighboring branches is the major factor in topological accuracy. Thus, multiple-sequence alignment can be an important factor in downstream effects on topological reconstruction.
Phylogenetic inference with weighted codon evolutionary distances.
Criscuolo, Alexis; Michel, Christian J
2009-04-01
We develop a new approach to estimate a matrix of pairwise evolutionary distances from a codon-based alignment based on a codon evolutionary model. The method first computes a standard distance matrix for each of the three codon positions. Then these three distance matrices are weighted according to an estimate of the global evolutionary rate of each codon position and averaged into a unique distance matrix. Using a large set of both real and simulated codon-based alignments of nucleotide sequences, we show that this approach leads to distance matrices that have a significantly better treelikeness compared to those obtained by standard nucleotide evolutionary distances. We also propose an alternative weighting to eliminate the part of the noise often associated with some codon positions, particularly the third position, which is known to induce a fast evolutionary rate. Simulation results show that fast distance-based tree reconstruction algorithms on distance matrices based on this codon position weighting can lead to phylogenetic trees that are at least as accurate as, if not better, than those inferred by maximum likelihood. Finally, a well-known multigene dataset composed of eight yeast species and 106 codon-based alignments is reanalyzed and shows that our codon evolutionary distances allow building a phylogenetic tree which is similar to those obtained by non-distance-based methods (e.g., maximum parsimony and maximum likelihood) and also significantly improved compared to standard nucleotide evolutionary distance estimates.
Primate diversification inferred from phylogenies and fossils.
Herrera, James P
2017-12-01
Biodiversity arises from the balance between speciation and extinction. Fossils record the origins and disappearance of organisms, and the branching patterns of molecular phylogenies allow estimation of speciation and extinction rates, but the patterns of diversification are frequently incongruent between these two data sources. I tested two hypotheses about the diversification of primates based on ∼600 fossil species and 90% complete phylogenies of living species: (1) diversification rates increased through time; (2) a significant extinction event occurred in the Oligocene. Consistent with the first hypothesis, analyses of phylogenies supported increasing speciation rates and negligible extinction rates. In contrast, fossils showed that while speciation rates increased, speciation and extinction rates tended to be nearly equal, resulting in zero net diversification. Partially supporting the second hypothesis, the fossil data recorded a clear pattern of diversity decline in the Oligocene, although diversification rates were near zero. The phylogeny supported increased extinction ∼34 Ma, but also elevated extinction ∼10 Ma, coinciding with diversity declines in some fossil clades. The results demonstrated that estimates of speciation and extinction ignoring fossils are insufficient to infer diversification and information on extinct lineages should be incorporated into phylogenetic analyses. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
Logical inference techniques for loop parallelization
Oancea, Cosmin E.
2012-01-01
This paper presents a fully automatic approach to loop parallelization that integrates the use of static and run-time analysis and thus overcomes many known difficulties such as nonlinear and indirect array indexing and complex control flow. Our hybrid analysis framework validates the parallelization transformation by verifying the independence of the loop\\'s memory references. To this end it represents array references using the USR (uniform set representation) language and expresses the independence condition as an equation, S = Ø, where S is a set expression representing array indexes. Using a language instead of an array-abstraction representation for S results in a smaller number of conservative approximations but exhibits a potentially-high runtime cost. To alleviate this cost we introduce a language translation F from the USR set-expression language to an equally rich language of predicates (F(S) ⇒ S = Ø). Loop parallelization is then validated using a novel logic inference algorithm that factorizes the obtained complex predicates (F(S)) into a sequence of sufficient-independence conditions that are evaluated first statically and, when needed, dynamically, in increasing order of their estimated complexities. We evaluate our automated solution on 26 benchmarks from PERFECTCLUB and SPEC suites and show that our approach is effective in parallelizing large, complex loops and obtains much better full program speedups than the Intel and IBM Fortran compilers. Copyright © 2012 ACM.
Inferring Molecular Processes Heterogeneity from Transcriptional Data.
Gogolewski, Krzysztof; Wronowska, Weronika; Lech, Agnieszka; Lesyng, Bogdan; Gambin, Anna
2017-01-01
RNA microarrays and RNA-seq are nowadays standard technologies to study the transcriptional activity of cells. Most studies focus on tracking transcriptional changes caused by specific experimental conditions. Information referring to genes up- and downregulation is evaluated analyzing the behaviour of relatively large population of cells by averaging its properties. However, even assuming perfect sample homogeneity, different subpopulations of cells can exhibit diverse transcriptomic profiles, as they may follow different regulatory/signaling pathways. The purpose of this study is to provide a novel methodological scheme to account for possible internal, functional heterogeneity in homogeneous cell lines, including cancer ones. We propose a novel computational method to infer the proportion between subpopulations of cells that manifest various functional behaviour in a given sample. Our method was validated using two datasets from RNA microarray experiments. Both experiments aimed to examine cell viability in specific experimental conditions. The presented methodology can be easily extended to RNA-seq data as well as other molecular processes. Moreover, it complements standard tools to indicate most important networks from transcriptomic data and in particular could be useful in the analysis of cancer cell lines affected by biologically active compounds or drugs.
Contingency inferences driven by base rates: Valid by sampling
Directory of Open Access Journals (Sweden)
Florian Kutzner
2011-04-01
Full Text Available Fiedler et al. (2009, reviewed evidence for the utilization of a contingency inference strategy termed pseudocontingencies (PCs. In PCs, the more frequent levels (and, by implication, the less frequent levels are assumed to be associated. PCs have been obtained using a wide range of task settings and dependent measures. Yet, the readiness with which decision makers rely on PCs is poorly understood. A computer simulation explored two potential sources of subjective validity of PCs. First, PCs are shown to perform above chance level when the task is to infer the sign of moderate to strong population contingencies from a sample of observations. Second, contingency inferences based on PCs and inferences based on cell frequencies are shown to partially agree across samples. Intriguingly, this criterion and convergent validity are by-products of random sampling error, highlighting the inductive nature of contingency inferences.
Quantum-Like Representation of Non-Bayesian Inference
Asano, M.; Basieva, I.; Khrennikov, A.; Ohya, M.; Tanaka, Y.
2013-01-01
This research is related to the problem of "irrational decision making or inference" that have been discussed in cognitive psychology. There are some experimental studies, and these statistical data cannot be described by classical probability theory. The process of decision making generating these data cannot be reduced to the classical Bayesian inference. For this problem, a number of quantum-like coginitive models of decision making was proposed. Our previous work represented in a natural way the classical Bayesian inference in the frame work of quantum mechanics. By using this representation, in this paper, we try to discuss the non-Bayesian (irrational) inference that is biased by effects like the quantum interference. Further, we describe "psychological factor" disturbing "rationality" as an "environment" correlating with the "main system" of usual Bayesian inference.
Statistical causal inferences and their applications in public health research
Wu, Pan; Chen, Ding-Geng
2016-01-01
This book compiles and presents new developments in statistical causal inference. The accompanying data and computer programs are publicly available so readers may replicate the model development and data analysis presented in each chapter. In this way, methodology is taught so that readers may implement it directly. The book brings together experts engaged in causal inference research to present and discuss recent issues in causal inference methodological development. This is also a timely look at causal inference applied to scenarios that range from clinical trials to mediation and public health research more broadly. In an academic setting, this book will serve as a reference and guide to a course in causal inference at the graduate level (Master's or Doctorate). It is particularly relevant for students pursuing degrees in Statistics, Biostatistics and Computational Biology. Researchers and data analysts in public health and biomedical research will also find this book to be an important reference.
Human Inferences about Sequences: A Minimal Transition Probability Model.
Directory of Open Access Journals (Sweden)
Florent Meyniel
2016-12-01
Full Text Available The brain constantly infers the causes of the inputs it receives and uses these inferences to generate statistical expectations about future observations. Experimental evidence for these expectations and their violations include explicit reports, sequential effects on reaction times, and mismatch or surprise signals recorded in electrophysiology and functional MRI. Here, we explore the hypothesis that the brain acts as a near-optimal inference device that constantly attempts to infer the time-varying matrix of transition probabilities between the stimuli it receives, even when those stimuli are in fact fully unpredictable. This parsimonious Bayesian model, with a single free parameter, accounts for a broad range of findings on surprise signals, sequential effects and the perception of randomness. Notably, it explains the pervasive asymmetry between repetitions and alternations encountered in those studies. Our analysis suggests that a neural machinery for inferring transition probabilities lies at the core of human sequence knowledge.
Bayesian methods for hackers probabilistic programming and Bayesian inference
Davidson-Pilon, Cameron
2016-01-01
Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples a...
Inferring climate variability from skewed proxy records
Emile-Geay, J.; Tingley, M.
2013-12-01
Many paleoclimate analyses assume a linear relationship between the proxy and the target climate variable, and that both the climate quantity and the errors follow normal distributions. An ever-increasing number of proxy records, however, are better modeled using distributions that are heavy-tailed, skewed, or otherwise non-normal, on account of the proxies reflecting non-normally distributed climate variables, or having non-linear relationships with a normally distributed climate variable. The analysis of such proxies requires a different set of tools, and this work serves as a cautionary tale on the danger of making conclusions about the underlying climate from applications of classic statistical procedures to heavily skewed proxy records. Inspired by runoff proxies, we consider an idealized proxy characterized by a nonlinear, thresholded relationship with climate, and describe three approaches to using such a record to infer past climate: (i) applying standard methods commonly used in the paleoclimate literature, without considering the non-linearities inherent to the proxy record; (ii) applying a power transform prior to using these standard methods; (iii) constructing a Bayesian model to invert the mechanistic relationship between the climate and the proxy. We find that neglecting the skewness in the proxy leads to erroneous conclusions and often exaggerates changes in climate variability between different time intervals. In contrast, an explicit treatment of the skewness, using either power transforms or a Bayesian inversion of the mechanistic model for the proxy, yields significantly better estimates of past climate variations. We apply these insights in two paleoclimate settings: (1) a classical sedimentary record from Laguna Pallcacocha, Ecuador (Moy et al., 2002). Our results agree with the qualitative aspects of previous analyses of this record, but quantitative departures are evident and hold implications for how such records are interpreted, and
Vertically Integrated Seismological Analysis II : Inference
Arora, N. S.; Russell, S.; Sudderth, E.
2009-12-01
Methods for automatically associating detected waveform features with hypothesized seismic events, and localizing those events, are a critical component of efforts to verify the Comprehensive Test Ban Treaty (CTBT). As outlined in our companion abstract, we have developed a hierarchical model which views detection, association, and localization as an integrated probabilistic inference problem. In this abstract, we provide more details on the Markov chain Monte Carlo (MCMC) methods used to solve this inference task. MCMC generates samples from a posterior distribution π(x) over possible worlds x by defining a Markov chain whose states are the worlds x, and whose stationary distribution is π(x). In the Metropolis-Hastings (M-H) method, transitions in the Markov chain are constructed in two steps. First, given the current state x, a candidate next state x‧ is generated from a proposal distribution q(x‧ | x), which may be (more or less) arbitrary. Second, the transition to x‧ is not automatic, but occurs with an acceptance probability—α(x‧ | x) = min(1, π(x‧)q(x | x‧)/π(x)q(x‧ | x)). The seismic event model outlined in our companion abstract is quite similar to those used in multitarget tracking, for which MCMC has proved very effective. In this model, each world x is defined by a collection of events, a list of properties characterizing those events (times, locations, magnitudes, and types), and the association of each event to a set of observed detections. The target distribution π(x) = P(x | y), the posterior distribution over worlds x given the observed waveform data y at all stations. Proposal distributions then implement several types of moves between worlds. For example, birth moves create new events; death moves delete existing events; split moves partition the detections for an event into two new events; merge moves combine event pairs; swap moves modify the properties and assocations for pairs of events. Importantly, the rules for
Network inference via adaptive optimal design
Directory of Open Access Journals (Sweden)
Stigter Johannes D
2012-09-01
Full Text Available Abstract Background Current research in network reverse engineering for genetic or metabolic networks very often does not include a proper experimental and/or input design. In this paper we address this issue in more detail and suggest a method that includes an iterative design of experiments based, on the most recent data that become available. The presented approach allows a reliable reconstruction of the network and addresses an important issue, i.e., the analysis and the propagation of uncertainties as they exist in both the data and in our own knowledge. These two types of uncertainties have their immediate ramifications for the uncertainties in the parameter estimates and, hence, are taken into account from the very beginning of our experimental design. Findings The method is demonstrated for two small networks that include a genetic network for mRNA synthesis and degradation and an oscillatory network describing a molecular network underlying adenosine 3’-5’ cyclic monophosphate (cAMP as observed in populations of Dyctyostelium cells. In both cases a substantial reduction in parameter uncertainty was observed. Extension to larger scale networks is possible but needs a more rigorous parameter estimation algorithm that includes sparsity as a constraint in the optimization procedure. Conclusion We conclude that a careful experiment design very often (but not always pays off in terms of reliability in the inferred network topology. For large scale networks a better parameter estimation algorithm is required that includes sparsity as an additional constraint. These algorithms are available in the literature and can also be used in an adaptive optimal design setting as demonstrated in this paper.
On the Hardness of Topology Inference
Acharya, H. B.; Gouda, M. G.
Many systems require information about the topology of networks on the Internet, for purposes like management, efficiency, testing of new protocols and so on. However, ISPs usually do not share the actual topology maps with outsiders; thus, in order to obtain the topology of a network on the Internet, a system must reconstruct it from publicly observable data. The standard method employs traceroute to obtain paths between nodes; next, a topology is generated such that the observed paths occur in the graph. However, traceroute has the problem that some routers refuse to reveal their addresses, and appear as anonymous nodes in traces. Previous research on the problem of topology inference with anonymous nodes has demonstrated that it is at best NP-complete. In this paper, we improve upon this result. In our previous research, we showed that in the special case where nodes may be anonymous in some traces but not in all traces (so all node identifiers are known), there exist trace sets that are generable from multiple topologies. This paper extends our theory of network tracing to the general case (with strictly anonymous nodes), and shows that the problem of computing the network that generated a trace set, given the trace set, has no general solution. The weak version of the problem, which allows an algorithm to output a "small" set of networks- any one of which is the correct one- is also not solvable. Any algorithm guaranteed to output the correct topology outputs at least an exponential number of networks. Our results are surprisingly robust: they hold even when the network is known to have exactly two anonymous nodes, and every node as well as every edge in the network is guaranteed to occur in some trace. On the basis of this result, we suggest that exact reconstruction of network topology requires more powerful tools than traceroute.
Statistical Inference for Data Adaptive Target Parameters.
Hubbard, Alan E; Kherad-Pajouh, Sara; van der Laan, Mark J
2016-05-01
Consider one observes n i.i.d. copies of a random variable with a probability distribution that is known to be an element of a particular statistical model. In order to define our statistical target we partition the sample in V equal size sub-samples, and use this partitioning to define V splits in an estimation sample (one of the V subsamples) and corresponding complementary parameter-generating sample. For each of the V parameter-generating samples, we apply an algorithm that maps the sample to a statistical target parameter. We define our sample-split data adaptive statistical target parameter as the average of these V-sample specific target parameters. We present an estimator (and corresponding central limit theorem) of this type of data adaptive target parameter. This general methodology for generating data adaptive target parameters is demonstrated with a number of practical examples that highlight new opportunities for statistical learning from data. This new framework provides a rigorous statistical methodology for both exploratory and confirmatory analysis within the same data. Given that more research is becoming "data-driven", the theory developed within this paper provides a new impetus for a greater involvement of statistical inference into problems that are being increasingly addressed by clever, yet ad hoc pattern finding methods. To suggest such potential, and to verify the predictions of the theory, extensive simulation studies, along with a data analysis based on adaptively determined intervention rules are shown and give insight into how to structure such an approach. The results show that the data adaptive target parameter approach provides a general framework and resulting methodology for data-driven science.
Inferring modules from human protein interactome classes
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Chaurasia Gautam
2010-07-01
Full Text Available Abstract Background The integration of protein-protein interaction networks derived from high-throughput screening approaches and complementary sources is a key topic in systems biology. Although integration of protein interaction data is conventionally performed, the effects of this procedure on the result of network analyses has not been examined yet. In particular, in order to optimize the fusion of heterogeneous interaction datasets, it is crucial to consider not only their degree of coverage and accuracy, but also their mutual dependencies and additional salient features. Results We examined this issue based on the analysis of modules detected by network clustering methods applied to both integrated and individual (disaggregated data sources, which we call interactome classes. Due to class diversity, we deal with variable dependencies of data features arising from structural specificities and biases, but also from possible overlaps. Since highly connected regions of the human interactome may point to potential protein complexes, we have focused on the concept of modularity, and elucidated the detection power of module extraction algorithms by independent validations based on GO, MIPS and KEGG. From the combination of protein interactions with gene expressions, a confidence scoring scheme has been proposed before proceeding via GO with further classification in permanent and transient modules. Conclusions Disaggregated interactomes are shown to be informative for inferring modularity, thus contributing to perform an effective integrative analysis. Validation of the extracted modules by multiple annotation allows for the assessment of confidence measures assigned to the modules in a protein pathway context. Notably, the proposed multilayer confidence scheme can be used for network calibration by enabling a transition from unweighted to weighted interactomes based on biological evidence.
Mihelj, M.; van den Broek, Egon
2008-01-01
In his new book (2007), Marvin Minsky states that Artificial Intelligence (AI) needs empathy to become truly smart, as is illustrated through human-human interaction. The latter also holds for Virtual Reality (VR), where the interest increases to unravel the emotional state of users has to be
Directory of Open Access Journals (Sweden)
Mogens Steffensen
2013-05-01
Full Text Available Research in insurance and finance was always intersecting although they were originally and generally viewed as separate disciplines. Insurance is about transferring risks between parties such that the burdens of risks are borne by those who can. This makes insurance transactions a beneficial activity for the society. It calls on detection, modelling, valuation, and controlling of risks. One of the main sources of control is diversification of risks and in that respect it becomes an issue in itself to clarify diversifiability of risks. However, many diversifiable risks are not, by nature or by contract design, separable from non-diversifiable risks that are, on the other hand, sometimes traded in financial markets and sometimes not. A key observation is that the economic risk came before the insurance contract: Mother earth destroys and kills incidentally and mercilessly, but the uncertainty of economic consequences can be more or less cleverly distributed by the introduction of an insurance market.
Confronting, Confirming, and Dispelling Myths Surrounding ERP-in-the-Cloud
DEFF Research Database (Denmark)
Beaulieu, Tanya; C. Martin, Todd; Sarker, Saonee
2015-01-01
on the topic, there is substantial uncertainty surrounding the benefits and challenges of ERP cloud computing. Consequently, as often is the case with new technologies, popular myths surrounding the technology are used to make adoption and implementation decisions. As a first step toward providing an informed...... with stakeholders related to an ERP cloud-based solution. Our results dispel some of the myths, while supporting others, and highlight how ERP vendors work around the different types of challenges surrounding this technology. Our study also helps understand the benefits of ERP cloud computing, and informs about how...
Ensemble stacking mitigates biases in inference of synaptic connectivity.
Chambers, Brendan; Levy, Maayan; Dechery, Joseph B; MacLean, Jason N
2018-01-01
A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches.
Causal inference in biology networks with integrated belief propagation.
Chang, Rui; Karr, Jonathan R; Schadt, Eric E
2015-01-01
Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.
International Nuclear Information System (INIS)
Hopkins, H.A.; McCall, K.A.
1994-05-01
An aerial radiological survey was conducted over the Oyster Creek Nuclear Power Plant in Forked River, New Jersey, during the period September 18 through September 24, 1992. The survey was conducted at an altitude of 150 feet (46 meters) over a 26-square-mile (67-square-kilometer) area centered on the power station. The purpose of the survey was to document the terrestrial gamma radiation environment of the Oyster Creek Nuclear Power plant and surrounding area. The results of the aerial survey are reported as inferred gamma radiation exposure rates at 1 meter above ground level in the form of a contour map. Outside the plant boundary, exposure rates were found to vary between 4 and 10 microroentgens per hour and were attributed to naturally-occurring uranium, thorium, and radioactive potassium gamma emitters. The aerial data were compared to ground-based benchmark exposure rate measurements and radionuclide assays of soil samples obtained within the survey boundary. The ground-based measurements were found to be in good agreement with those inferred from the aerial measuring system. A previous survey of the power plant was conducted in August 1969 during its initial startup phase. Exposure rates and radioactive isotopes revealed in both surveys were consistent and within normal terrestrial background levels
Tarlowski, Andrzej
2018-01-01
There is a lively debate concerning the role of conceptual and perceptual information in young children's inductive inferences. While most studies focus on the role of basic level categories in induction the present research contributes to the debate by asking whether children's inductions are guided by ontological constraints. Two studies use a novel inductive paradigm to test whether young children have an expectation that all animals share internal commonalities that do not extend to perceptually similar inanimates. The results show that children make category-consistent responses when asked to project an internal feature from an animal to either a dissimilar animal or a similar toy replica. However, the children do not have a universal preference for category-consistent responses in an analogous task involving vehicles and vehicle toy replicas. The results also show the role of context and individual factors in inferences. Children's early reliance on ontological commitments in induction cannot be explained by perceptual similarity or by children's sensitivity to the authenticity of objects.
Directory of Open Access Journals (Sweden)
Andrzej Tarlowski
2018-04-01
Full Text Available There is a lively debate concerning the role of conceptual and perceptual information in young children's inductive inferences. While most studies focus on the role of basic level categories in induction the present research contributes to the debate by asking whether children's inductions are guided by ontological constraints. Two studies use a novel inductive paradigm to test whether young children have an expectation that all animals share internal commonalities that do not extend to perceptually similar inanimates. The results show that children make category-consistent responses when asked to project an internal feature from an animal to either a dissimilar animal or a similar toy replica. However, the children do not have a universal preference for category-consistent responses in an analogous task involving vehicles and vehicle toy replicas. The results also show the role of context and individual factors in inferences. Children's early reliance on ontological commitments in induction cannot be explained by perceptual similarity or by children's sensitivity to the authenticity of objects.
Bayesian inference of substrate properties from film behavior
International Nuclear Information System (INIS)
Aggarwal, R; Demkowicz, M J; Marzouk, Y M
2015-01-01
We demonstrate that by observing the behavior of a film deposited on a substrate, certain features of the substrate may be inferred with quantified uncertainty using Bayesian methods. We carry out this demonstration on an illustrative film/substrate model where the substrate is a Gaussian random field and the film is a two-component mixture that obeys the Cahn–Hilliard equation. We construct a stochastic reduced order model to describe the film/substrate interaction and use it to infer substrate properties from film behavior. This quantitative inference strategy may be adapted to other film/substrate systems. (paper)
Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation
DEFF Research Database (Denmark)
Brouwer, Thomas; Frellsen, Jes; Liò, Pietro
2017-01-01
In this paper, we study the trade-offs of different inference approaches for Bayesian matrix factorisation methods, which are commonly used for predicting missing values, and for finding patterns in the data. In particular, we consider Bayesian nonnegative variants of matrix factorisation and tri......-factorisation, and compare non-probabilistic inference, Gibbs sampling, variational Bayesian inference, and a maximum-a-posteriori approach. The variational approach is new for the Bayesian nonnegative models. We compare their convergence, and robustness to noise and sparsity of the data, on both synthetic and real...
Working memory supports inference learning just like classification learning.
Craig, Stewart; Lewandowsky, Stephan
2013-08-01
Recent research has found a positive relationship between people's working memory capacity (WMC) and their speed of category learning. To date, only classification-learning tasks have been considered, in which people learn to assign category labels to objects. It is unknown whether learning to make inferences about category features might also be related to WMC. We report data from a study in which 119 participants undertook classification learning and inference learning, and completed a series of WMC tasks. Working memory capacity was positively related to people's classification and inference learning performance.
Surrogate based approaches to parameter inference in ocean models
Knio, Omar
2016-01-06
This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.
Ensemble stacking mitigates biases in inference of synaptic connectivity
Directory of Open Access Journals (Sweden)
Brendan Chambers
2018-03-01
Full Text Available A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches. Mapping the routing of spikes through local circuitry is crucial for understanding neocortical computation. Under appropriate experimental conditions, these maps can be used to infer likely patterns of synaptic recruitment, linking activity to underlying anatomical connections. Such inferences help to reveal the synaptic implementation of population dynamics and computation. We compare a number of standard functional measures to infer underlying connectivity. We find that regularization impacts measures
Brain Imaging, Forward Inference, and Theories of Reasoning
Heit, Evan
2015-01-01
This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities. PMID:25620926
Fast and scalable inference of multi-sample cancer lineages.
Popic, Victoria
2015-05-06
Somatic variants can be used as lineage markers for the phylogenetic reconstruction of cancer evolution. Since somatic phylogenetics is complicated by sample heterogeneity, novel specialized tree-building methods are required for cancer phylogeny reconstruction. We present LICHeE (Lineage Inference for Cancer Heterogeneity and Evolution), a novel method that automates the phylogenetic inference of cancer progression from multiple somatic samples. LICHeE uses variant allele frequencies of somatic single nucleotide variants obtained by deep sequencing to reconstruct multi-sample cell lineage trees and infer the subclonal composition of the samples. LICHeE is open source and available at http://viq854.github.io/lichee .
Fast and scalable inference of multi-sample cancer lineages.
Popic, Victoria; Salari, Raheleh; Hajirasouliha, Iman; Kashef-Haghighi, Dorna; West, Robert B; Batzoglou, Serafim
2015-01-01
Somatic variants can be used as lineage markers for the phylogenetic reconstruction of cancer evolution. Since somatic phylogenetics is complicated by sample heterogeneity, novel specialized tree-building methods are required for cancer phylogeny reconstruction. We present LICHeE (Lineage Inference for Cancer Heterogeneity and Evolution), a novel method that automates the phylogenetic inference of cancer progression from multiple somatic samples. LICHeE uses variant allele frequencies of somatic single nucleotide variants obtained by deep sequencing to reconstruct multi-sample cell lineage trees and infer the subclonal composition of the samples. LICHeE is open source and available at http://viq854.github.io/lichee .
International Conference on Trends and Perspectives in Linear Statistical Inference
Rosen, Dietrich
2018-01-01
This volume features selected contributions on a variety of topics related to linear statistical inference. The peer-reviewed papers from the International Conference on Trends and Perspectives in Linear Statistical Inference (LinStat 2016) held in Istanbul, Turkey, 22-25 August 2016, cover topics in both theoretical and applied statistics, such as linear models, high-dimensional statistics, computational statistics, the design of experiments, and multivariate analysis. The book is intended for statisticians, Ph.D. students, and professionals who are interested in statistical inference. .
Brain imaging, forward inference, and theories of reasoning.
Heit, Evan
2014-01-01
This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities.
Surrogate based approaches to parameter inference in ocean models
Knio, Omar
2016-01-01
This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.
Hurricane Gustav Aerial Photography: Rapid ResponseImagery of the Surrounding Regions After Landfall
National Oceanic and Atmospheric Administration, Department of Commerce — The imagery posted on this site is of the surrounding regionsafter Hurricane Gustav made landfall. The aerial photography missions wereconducted by the NOAA Remote...
Montoya, Lorena; Junger, Marianne; Ongena, Yfke
This article examines how residential property and its surroundings influence day- and night-time residential burglary. Crime Prevention Through Environmental Design (CPTED) principles of territoriality, surveillance, access control, target hardening, image maintenance, and activity support underpin
Montoya, L.; Junger, Marianne; Ongena, Yfke
This article examines how residential property and its surroundings influence day- and night-time residential burglary. Crime Prevention Through Environmental Design (CPTED) principles of territoriality, surveillance, access control, target hardening, image maintenance, and activity support underpin
CSIR Research Space (South Africa)
Van Greunen, DG
2017-02-01
Full Text Available A series of twenty seven acetylcholinesterase inhibitors, as potential agents for the treatment of Alzheimer's disease, were designed and synthesised based upon previously unexplored chemical space surrounding the molecular skeleton of the drug...
Origin of Sinuous Channels on the SW Apron of Ascraeus Mons and the Surrounding Plains, Mars
Schierl, Z. P.; Spencer, P.; Signorella, J.; Collins, A.; Schwans, B.; de Wet, A. P.; Bleacher, J. E.
2012-03-01
We used a variety of spacecraft imagery to determine the most likely origin for a network of sinuous channels found on the southwest apron of Ascraeus Mons and that extend out onto the surrounding plains.
LENUS (Irish Health Repository)
Mohamed, Seif
2010-05-01
This study was designed to evaluate the effect of surface contamination on osseointegration of dental implants surrounded by a circumferential bone defect and to compare osseointegration around Osseotite with that around Nanotite implants.
2017-09-01
The Pullman Transportation Plan provides a holistic set of recommendations to improve access to and from Pullman National Monument and its surrounding neighborhoods for both visitors and residents. In this plan, we identify short-, medium-, and long-...
National Oceanic and Atmospheric Administration, Department of Commerce — The imagery posted on this site is of the Florida panhandle and surrounding regions after Hurricane Dennis made landfall. The regions photographed range from...
National Oceanic and Atmospheric Administration, Department of Commerce — The imagery posted on this site is of the surrounding regions after Hurricane Humberto made landfall. The aerial photography missions were conducted by the NOAA...
Hurricane Ike Aerial Photography: Rapid ResponseImagery of the Surrounding Regions After Landfall
National Oceanic and Atmospheric Administration, Department of Commerce — The imagery posted on this site is of the surrounding regionsafter Hurricane Ike made landfall. The aerial photography missions wereconducted by the NOAA Remote...
National Oceanic and Atmospheric Administration, Department of Commerce — The imagery posted on this site is of the surrounding regions after Tropical Storm Ernesto made landfall. The aerial photography missions were conducted by the NOAA...
Seismic Tomography of the Arabian-Eurasian Collision Zone and Surrounding Areas
National Research Council Canada - National Science Library
Toksoz, M. N; Van der Hilst, Robert D; Sun, Youshun; Gulen, Levent; Kalafat, Dogan; Kuleli, Huseyin S; Li, Chang; Zhang, Haijiang
2008-01-01
... and surrounding areas, including Iran, Arabia, Eastern Turkey, and the Caucasus. The Arabian-Eurasian plate boundary is a complex tectonic zone shaped by continent-continent collision processes...
Models and Inference for Multivariate Spatial Extremes
Vettori, Sabrina
2017-12-07
The development of flexible and interpretable statistical methods is necessary in order to provide appropriate risk assessment measures for extreme events and natural disasters. In this thesis, we address this challenge by contributing to the developing research field of Extreme-Value Theory. We initially study the performance of existing parametric and non-parametric estimators of extremal dependence for multivariate maxima. As the dimensionality increases, non-parametric estimators are more flexible than parametric methods but present some loss in efficiency that we quantify under various scenarios. We introduce a statistical tool which imposes the required shape constraints on non-parametric estimators in high dimensions, significantly improving their performance. Furthermore, by embedding the tree-based max-stable nested logistic distribution in the Bayesian framework, we develop a statistical algorithm that identifies the most likely tree structures representing the data\\'s extremal dependence using the reversible jump Monte Carlo Markov Chain method. A mixture of these trees is then used for uncertainty assessment in prediction through Bayesian model averaging. The computational complexity of full likelihood inference is significantly decreased by deriving a recursive formula for the nested logistic model likelihood. The algorithm performance is verified through simulation experiments which also compare different likelihood procedures. Finally, we extend the nested logistic representation to the spatial framework in order to jointly model multivariate variables collected across a spatial region. This situation emerges often in environmental applications but is not often considered in the current literature. Simulation experiments show that the new class of multivariate max-stable processes is able to detect both the cross and inner spatial dependence of a number of extreme variables at a relatively low computational cost, thanks to its Bayesian hierarchical
P1-13: Color Induction from Surround Color under Interocular Suppression
Directory of Open Access Journals (Sweden)
Ichiro Kuriki
2012-10-01
Full Text Available The effect of surround colors on color appearance is known to subserve color constancy in humans, but how multiple mechanisms in the visual system are involved in this effect is controversial. We used an interocular-suppression technique to examine how the effect occurs at the level higher than the interaction of binocular information. A test color chip (1.7 × 1.7 deg visual angle was presented in a static surround either with continuous-flash suppression in the dominant eye (CFS condition to make the surround inperceptible or without the suppression (no-CFS condition. The surround stimulus was either a Mondrian or a uniform field of the same mean chromaticity. Stimuli were simulated OSA color chips under red, white (D65, or green illuminant color and were presented on a CRT display. Unique yellows were measured by asking the subjects to judge whether the test stimulus appeared reddish or greenish. Two sizes of the surround stimuli (widths of 1 deg and 4 deg were used. Results showed significant shifts in unique yellow even under the CFS conditions, except for the 1 deg uniform-surround condition. Under the no-CFS condition, the shifts showed remarkable difference between subjects, except for the 4 deg Mondrian-surround condition. Interestingly, trends of the shifts showed high consistency within each subject, across conditions. These results indicate that mechanisms at both higher and lower levels than the neuronal site of interocular suppression are involved, and that the color shifts follow each subject's strategy in the higher-order mechanisms when only insufficient clues are available in the surround to estimate illuminant color.
Snir, Avigal; Rafaeli, Eshkol; Gadassi, Reuma; Berenson, Kathy; Downey, Geraldine
2015-07-01
Nonsuicidal self-injury (NSSI) is a perplexing phenomenon that may have differing motives. The present study used experience sampling methods (ESM) which inquired explicitly about the motives for NSSI, but also enabled a temporal examination of the antecedents/consequences of NSSI; these allow us to infer other motives which were not explicitly endorsed. Adults (n = 152, aged 18-65) with borderline personality disorder (BPD), avoidant personality disorder (APD), or no psychopathology participated in a 3-week computerized diary study. We examined 5 classes of explicit motives for engaging in NSSI, finding support primarily for internally directed rather than interpersonally directed ones. We then used multilevel regression to examine changes in affect, cognition, and behavior surrounding moments of NSSI acts/urges compared with control moments (i.e., without NSSI). We examined changes in 5 scales of inferred motives, designed to correspond to the 5 classes of explicit motives. The results highlight differing motives for NSSI among individuals with BPD and APD, with some similarities (mostly in the explicit motives) and some differences (mostly in the inferred motives) between the disorders. Despite their infrequent explicit endorsement, fluctuations in interpersonally oriented scales were found surrounding NSSI acts/urges. This highlights the need to continue attending to interpersonal aspects of NSSI in research and in clinical practice. Additionally, NSSI urges, like acts, were followed by decline in affective/interpersonal distress (although in a delayed manner). Thus, interventions that build distress tolerance and enhance awareness for affective changes, and for antecedent/consequence patterns in NSSI, could help individuals resist the urge to self-injure. (c) 2015 APA, all rights reserved).
Directory of Open Access Journals (Sweden)
Zhang Yuan
2016-01-01
Full Text Available A self-designed experimental installation for transient heat transfer in the modelling surrounding rock mass of high geothermal roadways was elaborated in this paper. By utilizing the new installation, the temperature variation rules in surrounding rock mass of the high geothermal roadway during mechanical ventilation were studied. The results show that the roadway wall temperature decreases dramatically at the early stage of ventilation, and the temperature at every position of the surrounding rock mass is decreasing constantly with time passing by. From roadway wall to deep area, the temperature gradually increases until reaching original rock temperature. The relationship between dimensionless temperature and dimensionless radius demonstrates approximately exponential function. Meanwhile, the temperature disturbance range in the simulated surrounding rock mass extends gradually from the roadway wall to deep area in the surrounding rock mass. Besides, as the air velocity increases, heat loss in the surrounding rock mass rises and the ratio of temperature reduction becomes larger, the speed of disturbance range expansion also gets faster.
In Situ Observation of Hard Surrounding Rock Displacement at 2400-m-Deep Tunnels
Feng, Xia-Ting; Yao, Zhi-Bin; Li, Shao-Jun; Wu, Shi-Yong; Yang, Cheng-Xiang; Guo, Hao-Sen; Zhong, Shan
2018-03-01
This paper presents the results of in situ investigation of the internal displacement of hard surrounding rock masses within deep tunnels at China's Jinping Underground Laboratory Phase II. The displacement evolution of the surrounding rock during the entire excavation processes was monitored continuously using pre-installed continuous-recording multi-point extensometers. The evolution of excavation-damaged zones and fractures in rock masses were also observed using acoustic velocity testing and digital borehole cameras, respectively. The results show four kinds of displacement behaviours of the hard surrounding rock masses during the excavation process. The displacement in the inner region of the surrounding rock was found to be greater than that of the rock masses near the tunnel's side walls in some excavation stages. This leads to a multi-modal distribution characteristic of internal displacement for hard surrounding rock masses within deep tunnels. A further analysis of the evolution information on the damages and fractures inside the surrounding rock masses reveals the effects of excavation disturbances and local geological conditions. This recognition can be used as the reference for excavation and supporting design and stability evaluations of hard-rock tunnels under high-stress conditions.
Study on the Optimal Equivalent Radius in Calculating the Heat Dissipation of Surrounding Rock
Directory of Open Access Journals (Sweden)
H. T. Song
2015-11-01
Full Text Available The heat dissipation of surrounding rock of a non-circular roadway is computed using an equivalent circular roadway approach under three circumstances when the area, perimeter, or hydraulic diameter of the circular roadway is equal to the non-circular roadway to obtain the optimal equivalent radius. The differential equations of heat conduction for unstable surrounding rock are established in cylindrical and rectangular coordinate systems using dimensionless analysis method. The calculation formulas of heat dissipation capacity and heat transfer resistance are derived from differential equations. Based on the method of equivalent radius, the similarities and differences between non-circular and circular roadways in calculating the heat dissipation of surrounding rock are discussed. Using the finite volume method, the calculation models for non-circular and circular roadways in the heat dissipation of surrounding rock are also established, among the non-circular roadways including three circumstances, namely, trapezoid, rectangle, and arch. The relation errors of heat dissipation of the surrounding rock of the three equivalent circular roadway methods are investigated for the three non-circular roadways. Results show that the calculation approach with equal perimeters is the best for the heat dissipation of surrounding rock of non-circular roadways.
Indirect Inference for Stochastic Differential Equations Based on Moment Expansions
Ballesio, Marco; Tempone, Raul; Vilanova, Pedro
2016-01-01
We provide an indirect inference method to estimate the parameters of timehomogeneous scalar diffusion and jump diffusion processes. We obtain a system of ODEs that approximate the time evolution of the first two moments of the process
ESPRIT: Exercise Sensing and Pose Recovery Inference Tool, Phase I
National Aeronautics and Space Administration — We propose to develop ESPRIT: an Exercise Sensing and Pose Recovery Inference Tool, in support of NASA's effort in developing crew exercise technologies for...
Automated Flight Safety Inference Engine (AFSIE) System, Phase I
National Aeronautics and Space Administration — We propose to develop an innovative Autonomous Flight Safety Inference Engine (AFSIE) system to autonomously and reliably terminate the flight of an errant launch...
Classification versus inference learning contrasted with real-world categories.
Jones, Erin L; Ross, Brian H
2011-07-01
Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories--what each category is like--while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.
Efficient Exact Inference With Loss Augmented Objective in Structured Learning.
Bauer, Alexander; Nakajima, Shinichi; Muller, Klaus-Robert
2016-08-19
Structural support vector machine (SVM) is an elegant approach for building complex and accurate models with structured outputs. However, its applicability relies on the availability of efficient inference algorithms--the state-of-the-art training algorithms repeatedly perform inference to compute a subgradient or to find the most violating configuration. In this paper, we propose an exact inference algorithm for maximizing nondecomposable objectives due to special type of a high-order potential having a decomposable internal structure. As an important application, our method covers the loss augmented inference, which enables the slack and margin scaling formulations of structural SVM with a variety of dissimilarity measures, e.g., Hamming loss, precision and recall, Fβ-loss, intersection over union, and many other functions that can be efficiently computed from the contingency table. We demonstrate the advantages of our approach in natural language parsing and sequence segmentation applications.
BagReg: Protein inference through machine learning.
Zhao, Can; Liu, Dao; Teng, Ben; He, Zengyou
2015-08-01
Protein inference from the identified peptides is of primary importance in the shotgun proteomics. The target of protein inference is to identify whether each candidate protein is truly present in the sample. To date, many computational methods have been proposed to solve this problem. However, there is still no method that can fully utilize the information hidden in the input data. In this article, we propose a learning-based method named BagReg for protein inference. The method firstly artificially extracts five features from the input data, and then chooses each feature as the class feature to separately build models to predict the presence probabilities of proteins. Finally, the weak results from five prediction models are aggregated to obtain the final result. We test our method on six public available data sets. The experimental results show that our method is superior to the state-of-the-art protein inference algorithms. Copyright © 2015 Elsevier Ltd. All rights reserved.
The Human Cochlear Mechanical Nonlinearity Inferred via Psychometric Functions
Directory of Open Access Journals (Sweden)
Nizami Lance
2013-12-01
Extension of the model of Schairer and colleagues results in credible cochlear nonlinearities in man, suggesting that forward-masking provides a non-invasive way to infer the human mechanical cochlear nonlinearity.
A general Bayes weibull inference model for accelerated life testing
International Nuclear Information System (INIS)
Dorp, J. Rene van; Mazzuchi, Thomas A.
2005-01-01
This article presents the development of a general Bayes inference model for accelerated life testing. The failure times at a constant stress level are assumed to belong to a Weibull distribution, but the specification of strict adherence to a parametric time-transformation function is not required. Rather, prior information is used to indirectly define a multivariate prior distribution for the scale parameters at the various stress levels and the common shape parameter. Using the approach, Bayes point estimates as well as probability statements for use-stress (and accelerated) life parameters may be inferred from a host of testing scenarios. The inference procedure accommodates both the interval data sampling strategy and type I censored sampling strategy for the collection of ALT test data. The inference procedure uses the well-known MCMC (Markov Chain Monte Carlo) methods to derive posterior approximations. The approach is illustrated with an example
Inference method using bayesian network for diagnosis of pulmonary nodules
International Nuclear Information System (INIS)
Kawagishi, Masami; Iizuka, Yoshio; Yamamoto, Hiroyuki; Yakami, Masahiro; Kubo, Takeshi; Fujimoto, Koji; Togashi, Kaori
2010-01-01
This report describes the improvements of a naive Bayes model that infers the diagnosis of pulmonary nodules in chest CT images based on the findings obtained when a radiologist interprets the CT images. We have previously introduced an inference model using a naive Bayes classifier and have reported its clinical value based on evaluation using clinical data. In the present report, we introduce the following improvements to the original inference model: the selection of findings based on correlations and the generation of a model using only these findings, and the introduction of classifiers that integrate several simple classifiers each of which is specialized for specific diagnosis. These improvements were found to increase the inference accuracy by 10.4% (p<.01) as compared to the original model in 100 cases (222 nodules) based on leave-one-out evaluation. (author)
Bayesian inference of chemical kinetic models from proposed reactions
Galagali, Nikhil; Marzouk, Youssef M.
2015-01-01
© 2014 Elsevier Ltd. Bayesian inference provides a natural framework for combining experimental data with prior knowledge to develop chemical kinetic models and quantify the associated uncertainties, not only in parameter values but also in model
Inference of beliefs and emotions in patients with Alzheimer's disease.
Zaitchik, Deborah; Koff, Elissa; Brownell, Hiram; Winner, Ellen; Albert, Marilyn
2006-01-01
The present study compared 20 patients with mild to moderate Alzheimer's disease with 20 older controls (ages 69-94 years) on their ability to make inferences about emotions and beliefs in others. Six tasks tested their ability to make 1st-order and 2nd-order inferences as well as to offer explanations and moral evaluations of human action by appeal to emotions and beliefs. Results showed that the ability to infer emotions and beliefs in 1st-order tasks remains largely intact in patients with mild to moderate Alzheimer's. Patients were able to use mental states in the prediction, explanation, and moral evaluation of behavior. Impairment on 2nd-order tasks involving inference of mental states was equivalent to impairment on control tasks, suggesting that patients' difficulty is secondary to their cognitive impairments. ((c) 2006 APA, all rights reserved).
Efficient design and inference in distributed Bayesian networks: an overview
de Oude, P.; Groen, F.C.A.; Pavlin, G.; Bezhanishvili, N.; Löbner, S.; Schwabe, K.; Spada, L.
2011-01-01
This paper discusses an approach to distributed Bayesian modeling and inference, which is relevant for an important class of contemporary real world situation assessment applications. By explicitly considering the locality of causal relations, the presented approach (i) supports coherent distributed
SDG multiple fault diagnosis by real-time inverse inference
International Nuclear Information System (INIS)
Zhang Zhaoqian; Wu Chongguang; Zhang Beike; Xia Tao; Li Anfeng
2005-01-01
In the past 20 years, one of the qualitative simulation technologies, signed directed graph (SDG) has been widely applied in the field of chemical fault diagnosis. However, the assumption of single fault origin was usually used by many former researchers. As a result, this will lead to the problem of combinatorial explosion and has limited SDG to the realistic application on the real process. This is mainly because that most of the former researchers used forward inference engine in the commercial expert system software to carry out the inverse diagnosis inference on the SDG model which violates the internal principle of diagnosis mechanism. In this paper, we present a new SDG multiple faults diagnosis method by real-time inverse inference. This is a method of multiple faults diagnosis from the genuine significance and the inference engine use inverse mechanism. At last, we give an example of 65t/h furnace diagnosis system to demonstrate its applicability and efficiency
SDG multiple fault diagnosis by real-time inverse inference
Energy Technology Data Exchange (ETDEWEB)
Zhang Zhaoqian; Wu Chongguang; Zhang Beike; Xia Tao; Li Anfeng
2005-02-01
In the past 20 years, one of the qualitative simulation technologies, signed directed graph (SDG) has been widely applied in the field of chemical fault diagnosis. However, the assumption of single fault origin was usually used by many former researchers. As a result, this will lead to the problem of combinatorial explosion and has limited SDG to the realistic application on the real process. This is mainly because that most of the former researchers used forward inference engine in the commercial expert system software to carry out the inverse diagnosis inference on the SDG model which violates the internal principle of diagnosis mechanism. In this paper, we present a new SDG multiple faults diagnosis method by real-time inverse inference. This is a method of multiple faults diagnosis from the genuine significance and the inference engine use inverse mechanism. At last, we give an example of 65t/h furnace diagnosis system to demonstrate its applicability and efficiency.
Bayesian Information Criterion as an Alternative way of Statistical Inference
Directory of Open Access Journals (Sweden)
Nadejda Yu. Gubanova
2012-05-01
Full Text Available The article treats Bayesian information criterion as an alternative to traditional methods of statistical inference, based on NHST. The comparison of ANOVA and BIC results for psychological experiment is discussed.
Statistical inferences for bearings life using sudden death test
Directory of Open Access Journals (Sweden)
Morariu Cristin-Olimpiu
2017-01-01
Full Text Available In this paper we propose a calculus method for reliability indicators estimation and a complete statistical inferences for three parameters Weibull distribution of bearings life. Using experimental values regarding the durability of bearings tested on stands by the sudden death tests involves a series of particularities of the estimation using maximum likelihood method and statistical inference accomplishment. The paper detailing these features and also provides an example calculation.
Inference in {open_quotes}poor{close_quotes} languages
Energy Technology Data Exchange (ETDEWEB)
Petrov, S. [Oak Ridge National Lab., TN (United States)
1996-12-31
Languages with a solvable implication problem but without complete and consistent systems of inference rules ({open_quote}poor{close_quote} languages) are considered. The problem of existence of a finite, complete, and consistent inference rule system for a {open_quotes}poor{close_quotes} language is stated independently of the language or the rule syntax. Several properties of the problem are proved. An application of the results to the language of join dependencies is given.
Inference of a Nonlinear Stochastic Model of the Cardiorespiratory Interaction
Smelyanskiy, V. N.; Luchinsky, D. G.; Stefanovska, A.; McClintock, P. V.
2005-03-01
We reconstruct a nonlinear stochastic model of the cardiorespiratory interaction in terms of a set of polynomial basis functions representing the nonlinear force governing system oscillations. The strength and direction of coupling and noise intensity are simultaneously inferred from a univariate blood pressure signal. Our new inference technique does not require extensive global optimization, and it is applicable to a wide range of complex dynamical systems subject to noise.