156 research outputs found

    Image Encryption Using Random Bit Sequence Based on Chaotic Maps

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    ϒ production in p–Pb collisions at √sNN=8.16 TeV

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    ϒ production in p–Pb interactions is studied at the centre-of-mass energy per nucleon–nucleon collision √sNN = 8.16 TeV with the ALICE detector at the CERN LHC. The measurement is performed reconstructing bottomonium resonances via their dimuon decay channel, in the centre-of-mass rapidity intervals 2.03 < ycms < 3.53 and −4.46 < ycms < −2.96, down to zero transverse momentum. In this work, results on the ϒ(1S) production cross section as a function of rapidity and transverse momentum are presented. The corresponding nuclear modification factor shows a suppression of the ϒ(1S) yields with respect to pp collisions, both at forward and backward rapidity. This suppression is stronger in the low transverse momentum region and shows no significant dependence on the centrality of the interactions. Furthermore, the ϒ(2S) nuclear modification factor is evaluated, suggesting a suppression similar to that of the ϒ(1S). A first measurement of the ϒ(3S) has also been performed. Finally, results are compared with previous ALICE measurements in p–Pb collisions at √sNN = 5.02 TeV and with theoretical calculations.publishedVersio

    (Anti-)deuteron production in pp collisions at 1as=13TeV

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    The study of (anti-)deuteron production in pp collisions has proven to be a powerful tool to investigate the formation mechanism of loosely bound states in high-energy hadronic collisions. In this paper the production of (anti-)deuterons is studied as a function of the charged particle multiplicity in inelastic pp collisions at s=13 TeV using the ALICE experiment. Thanks to the large number of accumulated minimum bias events, it has been possible to measure (anti-)deuteron production in pp collisions up to the same charged particle multiplicity (d Nch/ d \u3b7 3c 26) as measured in p\u2013Pb collisions at similar centre-of-mass energies. Within the uncertainties, the deuteron yield in pp collisions resembles the one in p\u2013Pb interactions, suggesting a common formation mechanism behind the production of light nuclei in hadronic interactions. In this context the measurements are compared with the expectations of coalescence and statistical hadronisation models (SHM)

    Multiplicity dependence of inclusive J/psi production at midrapidity in pp collisions at root s=13 TeV

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    Measurements of the inclusive J/psi yield as a function of charged-particle pseudorapidity density dN(ch)/d eta in pp collisions at root s = 13 TeV with ALICE at the LHC are reported. The J/psi meson yield is measured at midrapidity (vertical bar y vertical bar <0.9) in the dielectron channel, for events selected based on the charged-particle multiplicity at midrapidity (vertical bar eta vertical bar <1) and at forward rapidity (-3.7 <eta <-1.7 and 2.8 <eta <5.1); both observables are normalized to their corresponding averages in minimum bias events. The increase of the normalized J/psi yield with normalized dN(ch)/d eta is significantly stronger than linear and dependent on the transverse momentum. The data are compared to theoretical predictions, which describe the observed trends well, albeit not always quantitatively. (C) 2020 European Organization for Nuclear Research. Published by Elsevier B.V.Peer reviewe

    J/psi production as a function of charged-particle pseudorapidity density in p-Pb collisions at root s(NN)=5.02 TeV

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    We report measurements of the inclusive J/ψ yield and average transverse momentum as a function of charged-particle pseudorapidity density dNch/dη in p–Pb collisions at sNN=5.02TeV with ALICE at the LHC. The observables are normalised to their corresponding averages in non-single diffractive events. An increase of the normalised J/ψ yield with normalised dNch/dη, measured at mid-rapidity, is observed at mid-rapidity and backward rapidity. At forward rapidity, a saturation of the relative yield is observed for high charged-particle multiplicities. The normalised average transverse momentum at forward and backward rapidities increases with multiplicity at low multiplicities and saturates beyond moderate multiplicities. In addition, the forward-to-backward nuclear modification factor ratio is also reported, showing an increasing suppression of J/ψ production at forward rapidity with respect to backward rapidity for increasing charged-particle multiplicity

    Multiplicity dependence of (anti-)deuteron production in pp collisions at root s=7 TeV

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    none1019siIn this letter, the production of deuterons and anti-deuterons in pp collisions at root s = 7 TeV is studied as a function of the charged-particle multiplicity density at mid-rapidity with the ALICE detector at the LHC. Production yields are measured at mid-rapidity in five multiplicity classes and as a function of the deuteron transverse momentum (p(T)). The measurements are discussed in the context of hadron-coalescence models. The coalescence parameter B-2, extracted from the measured spectra of (anti-)deuteronsand primary (anti-)protons, exhibits no significant p(T)-dependence for p(T) < 3 GeV/c, in agreement with the expectations of a simple coalescence picture. At fixed transverse momentum per nucleon, the B-2 parameter is found to decrease smoothly from low multiplicity pp to Pb-Pb collisions, in qualitative agreement with more elaborate coalescence models. The measured mean transverse momentum of (anti-)deuterons in pp is not reproduced by the Blast-Wave model calculations that simultaneously describe pion, kaon and proton spectra, in contrast to central Pb-Pb collisions. The ratio between the p(T)-integrated yield of deuterons to protons, d/p, is found to increase with the charged-particle multiplicity, as observed in inelastic pp collisions at different centre-of-mass energies. The d/p ratios are reported in a wide range, from the lowest to the highest multiplicity values measured in pp collisions at the LHC. (C) 2019 The Author(s). Published by Elsevier B.VnoneAcharya, S.; Acosta, F. T.; Adamova, D.; Adhya, S. P.; Adler, A.; Adolfsson, J.; Aggarwal, M. M.; Rinella, G. Aglieri; Agnello, M.; Ahammed, Z.; Ahmad, S.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Al-Turany, M.; Alam, S. N.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alfanda, H. M.; Alfaro Molina, R.; Ali, B.; Ali, Y.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altenkamper, L.; Altsybeev, I; Anaam, M. N.; Andrei, C.; Andreou, D.; Andrews, H. A.; Andronic, A.; Angeletti, M.; Anguelov, V; Anson, C.; Anticic, T.; Antinori, F.; Antonioli, P.; Anwar, R.; Apadula, N.; Aphecetche, L.; Appelshaeuser, H.; Arcelli, S.; Arnaldi, R.; Arratia, M.; Arsene, I. C.; Arslandok, M.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badala, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Ball, M.; Baral, R. C.; Barbera, R.; Barioglio, L.; Barnafoldi, G. G.; Barnby, L. S.; Barret, V; Bartalini, P.; Barth, K.; Bartsch, E.; Bastid, N.; Basu, S.; Batigne, G.; Batyunya, B.; Batzing, P. C.; Bauri, D.; Bazo Alba, J. L.; Bearden, I. G.; Bedda, C.; Behera, N. K.; Belikov, I; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Beltran, L. G. E.; Belyaev, V; Bencedi, G.; Beole, S.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhatt, H.; Bhattacharjee, B.; Bianchi, A.; Bianchi, L.; Bianchi, N.; Bielcik, J.; Bielcikova, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Blair, J. T.; Blau, D.; Blume, C.; Boca, G.; Bock, F.; Bogdanov, A.; Boldizsar, L.; Bolozdynya, A.; Bombara, M.; Bonomi, G.; Bonora, M.; Borel, H.; Borissov, A.; Borri, M.; Botta, E.; Bourjau, C.; Bratrud, L.; Braun-Munzinger, P.; Bregant, M.; Broker, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Buckland, M. D.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buhler, P.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Caffarri, D.; Caines, H.; Caliva, A.; Calvo Villar, E.; Camacho, R. S.; Camerini, P.; Capon, A. A.; Carnesecchi, F.; Castellanos, J. Castillo; Castro, A. J.; Casula, E. A. R.; Sanchez, C. Ceballos; Chakraborty, P.; Chandra, S.; Chang, B.; Chang, W.; Chapeland, S.; Chartier, M.; Chattopadhyay, S.; Chauvin, A.; Cheshkov, C.; Cheynis, B.; Barroso, V. Chibante; Chinellato, D. D.; Cho, S.; Chochula, P.; Chowdhury, T.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Concas, M.; Balbastre, G. Conesa; del Valle, Z. Conesa; Contin, G.; Contreras, J. G.; Cormier, T. M.; Morales, Y. Corrales; Cortese, P.; Cosentino, M. R.; Costa, F.; Costanza, S.; Crkovska, J.; Crochet, P.; Cuautle, E.; Cunqueiro, L.; Dabrowski, D.; Dahms, T.; Dainese, A.; Damas, F. P. A.; Dani, S.; Danisch, M. C.; Danu, A.; Das, D.; Das, I; Das, S.; Dash, A.; Dash, S.; Dashi, A.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; De Souza, R. D.; Degenhardt, H. F.; Deisting, A.; Deloff, A.; Delsanto, S.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Diaz, R. A.; Dietel, T.; Dillenseger, P.; Ding, Y.; Divia, R.; Djuvsland, O.; Dobrin, A.; Domenicis Gimenez, D.; Doenigus, B.; Dordic, O.; Dubey, A. K.; Dubla, A.; Dudi, S.; Duggal, A. K.; Dukhishyam, M.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Engel, H.; Epple, E.; Erazmus, B.; Erhardt, F.; Erokhin, A.; Ersdal, M. R.; Espagnon, B.; Eulisse, G.; Eum, J.; Evans, D.; Evdokimov, S.; Fabbietti, L.; Faggin, M.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Fernandez Tellez, A.; Ferrero, A.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiorenza, G.; Flor, F.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francisco, A.; Frankenfeld, U.; Fronze, G. G.; Fuchs, U.; Furget, C.; Furs, A.; Girard, M. Fusco; Gaardhoje, J. J.; Gagliardi, M.; Gago, A. M.; Gajdosova, K.; Galvan, C. D.; Ganoti, P.; Garabatos, C.; Garcia-Solis, E.; Garg, K.; Gargiulo, C.; Garner, K.; Gasik, P.; Gauger, E. F.; Gay Ducati, M. B.; Germain, M.; Ghosh, J.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Glaessel, P.; Gomez Coral, D. M.; Ramirez, A. Gomez; Gonzalez, V; Gonzalez-Zamora, P.; Gorbunov, S.; Gorlich, L.; Gotovac, S.; Grabski, V; Graczykowski, L. K.; Graham, K. L.; Greiner, L.; Grelli, A.; Grigoras, C.; Grigoriev, V; Grigoryan, A.; Grigoryan, S.; Gronefeld, J. M.; Grosa, F.; Grosse-Oetringhaus, J. F.; Grosso, R.; Guernane, R.; Guerzoni, B.; Guittiere, M.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Guzman, I. B.; Haake, R.; Habib, M. K.; Hadjidakis, C.; Hamagaki, H.; Hamar, G.; Hamid, M.; Hamon, J. C.; Hannigan, R.; Haque, M. R.; Harlenderova, A.; Harris, J. W.; Harton, A.; Hassan, H.; Hatzifotiadou, D.; Hauer, P.; Hayashi, S.; Heckel, S. T.; Hellbaer, E.; Helstrup, H.; Herghelegiu, A.; Hernandez, E. G.; Herrera Corral, G.; Herrmann, F.; Hetland, K. F.; Hilden, T. E.; Hillemanns, H.; Hills, C.; Hippolyte, B.; Hohlweger, B.; Horak, D.; Hornung, S.; Hosokawa, R.; Hota, J.; Hristov, P.; Huang, C.; Hughes, C.; Huhn, P.; Humanic, T. J.; Hushnud, H.; Husova, L. A.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Iddon, J. P.; Ilkaev, R.; Inaba, M.; Ippolitov, M.; Islam, M. S.; Ivanov, M.; Ivanov, V; Izucheev, V; Jacak, B.; Jacazio, N.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jaelani, S.; Jahnke, C.; Jakubowska, M. J.; Janik, M. A.; Jercic, M.; Jevons, O.; Bustamante, R. T. Jimenez; Jin, M.; Jones, P. G.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kang, J. H.; Kaplin, V; Kar, S.; Uysal, A. Karasu; Karavichev, O.; Karavicheva, T.; Karczmarczyk, P.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keil, M.; Ketzer, B.; Khabanova, Z.; Khan, A. M.; Khan, S.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Khatun, A.; Khuntia, A.; Kielbowicz, M. M.; Kileng, B.; Kim, B.; Kim, D.; Kim, D. J.; Kim, E. J.; Kim, H.; Kim, J. S.; Kim, J.; Kim, M.; Kim, S.; Kim, T.; Kindra, K.; Kirsch, S.; Kisel, I; Kiselev, S.; Kisiel, A.; Klay, J. L.; Klein, C.; Klein, J.; Klein, S.; Klein-Boesing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Koehler, M. K.; Kollegger, T.; Kondratyeva, N.; Kondratyuk, E.; Konopka, P. J.; Konyushikhin, M.; Koska, L.; Kovalenko, O.; Kovalenko, V; Kowalski, M.; Kralik, I; Kravcakova, A.; Kreis, L.; Krivda, M.; Krizek, F.; Krueger, M.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kucera, V; Kuhn, C.; Kuijer, P. G.; Kumar, L.; Kumar, S.; Kundu, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kushpil, S.; Kvapil, J.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Lai, Y. S.; Langoy, R.; Lapidus, K.; Lardeux, A.; Larionov, P.; Laudi, E.; Lavicka, R.; Lazareva, T.; Lea, R.; Leardini, L.; Lee, S.; Lehas, F.; Lehner, S.; Lehrbach, J.; Lemmon, R. C.; Leon Monzon, I; Levai, P.; Li, X.; Li, X. L.; Lien, J.; Lietava, R.; Lim, B.; Lindal, S.; Lindenstruth, V; Lindsay, S. W.; Lippmann, C.; Lisa, M. A.; Litichevskyi, V; Liu, A.; Ljunggren, H. M.; Llope, W. J.; Lodato, D. F.; Loginov, V; Loizides, C.; Loncar, P.; Lopez, X.; Lopez Torres, E.; Luettig, P.; Luhder, J. R.; Lunardon, M.; Luparello, G.; Lupi, M.; Maevskaya, A.; Mager, M.; Mahmood, S. M.; Mahmoud, T.; Maire, A.; Majka, R. D.; Malaev, M.; Malik, Q. W.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V; Manso, F.; Manzari, V; Mao, Y.; Marchisone, M.; Mares, J.; Margagliotti, G., V; Margotti, A.; Margutti, J.; Marin, A.; Markert, C.; Marquard, M.; Martin, N. A.; Martinengo, P.; Martinez, J. L.; Martinez, M., I; Garcia, G. Martinez; Pedreira, M. Martinez; Masciocchi, S.; Masera, M.; Masoni, A.; Massacrier, L.; Masson, E.; Mastroserio, A.; Mathis, A. M.; Matuoka, P. F. T.; Matyja, A.; Mayer, C.; Mazzilli, M.; Mazzoni, M. A.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Meres, M.; Mhlanga, S.; Miake, Y.; Micheletti, L.; Mieskolainen, M. M.; Mihaylov, D. L.; Mikhaylov, K.; Mischke, A.; Mishra, A. N.; Miskowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, A. P.; Mohanty, B.; Khan, M. Mohisin; Mondal, M. M.; Mordasini, C.; De Godoy, D. A. Moreira; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Mrnjavac, T.; Muccifora, V; Mudnic, E.; Muehlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Muenning, K.; Munzer, R. H.; Murakami, H.; Murray, S.; Musa, L.; Musinsky, J.; Myers, C. J.; Myrcha, J. W.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Nassirpour, A. F.; Natal da Luz, H.; Nattrass, C.; Navarro, S. R.; Nayak, K.; Nayak, R.; Nayak, T. K.; Nazarenko, S.; De Oliveira, R. A. Negrao; Nellen, L.; Nesbo, S., V; Neskovic, G.; Ng, F.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Ogino, M.; Ohlson, A.; Oleniacz, J.; Oliveira Da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Pachmayer, Y.; Pacik, V; Pagano, D.; Paic, G.; Palni, P.; Pan, J.; Pandey, A. K.; Panebianco, S.; Papikyan, V; Pareek, P.; Park, J.; Parkkila, J. E.; Parmar, S.; Passfeld, A.; Pathak, S. P.; Patra, R. N.; Paul, B.; Pei, H.; Peitzmann, T.; Peng, X.; Pereira, L. G.; Da Costa, H. Pereira; Peresunko, D.; Perez, G. M.; Lezama, E. Perez; Peskov, V; Pestov, Y.; Petracek, V; Petrovici, M.; Pezzi, R. P.; Piano, S.; Pikna, M.; Pillot, P.; Pimentel, L. O. D. L.; Pinazza, O.; Pinsky, L.; Pisano, S.; Piyarathna, D. B.; Ploskon, M.; Planinic, M.; Pliquett, F.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Poppenborg, H.; Porteboeuf-Houssais, S.; Pozdniakov, V; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I; Puccio, M.; Punin, V; Puranapanda, K.; Putschke, J.; Quishpe, R. E.; Ragoni, S.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Raniwala, R.; Raniwala, S.; Rasanen, S. S.; Rascanu, B. T.; Rath, R.; Ratza, V; Ravasenga, I; Read, K. F.; Redlich, K.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reshetin, A.; Revol, J-P; Reygers, K.; Riabov, V; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rode, S. P.; Rodriguez Cahuantzi, M.; Roed, K.; Rogalev, R.; Rogochaya, E.; Rohr, D.; Rohrich, D.; Rokita, P. S.; Ronchetti, F.; Rosas, E. D.; Roslon, K.; Rosnet, P.; Rossi, A.; Rotondi, A.; Roukoutakis, F.; Roy, A.; Roy, P.; Rueda, O., V; Rui, R.; Rumyantsev, B.; Rustamov, A.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Saarinen, S.; Sadhu, S.; Sadovsky, S.; Safarik, K.; Saha, S. K.; Sahoo, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Sambyal, S.; Samsonov, V; Sandoval, A.; Sarkar, A.; Sarkar, D.; Sarkar, N.; Sarma, P.; Sarti, V. M.; Sas, M. H. P.; Scapparone, E.; Schaefer, B.; Schambach, J.; Scheid, H. S.; Schiaua, C.; Schicker, R.; Schmah, A.; Schmidt, C.; Schmidt, H. R.; Schmidt, M. O.; Schmidt, M.; Schmidt, N., V; Schmier, A. R.; Schukraft, J.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Sefcik, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I; Senyukov, S.; Serradilla, E.; Sett, P.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shahoyan, R.; Shaikh, W.; Shangaraev, A.; Sharma, A.; Sharma, M.; Sharma, N.; Sheikh, A., I; Shigaki, K.; Shimomura, M.; Shirinkin, S.; Shou, Q.; Sibiriak, Y.; Siddhanta, S.; Siemiarczuk, T.; Silvermyr, D.; Simatovic, G.; Simonetti, G.; Singh, R.; Singhal, V; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Sochan, J.; Soncco, C.; Song, J.; Songmoolnak, A.; Soramel, F.; Sorensen, S.; Sozzi, F.; Sputowska, I; Stachel, J.; Stan, I; Stankus, P.; Stenlund, E.; Stocco, D.; Storetvedt, M. M.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Sumbera, M.; Sumowidagdo, S.; Suzuki, K.; Swain, S.; Szabo, A.; Szarka, I; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tarhini, M.; Tarzila, M. G.; Tauro, A.; Tejeda Munoz, G.; Telesca, A.; Terrevoli, C.; Thakur, D.; Thakur, S.; Thomas, D.; Thoresen, F.; Tieulent, R.; Tikhonov, A.; Timmins, A. R.; Toia, A.; Topilskaya, N.; Toppi, M.; Torres, S. R.; Tripathy, S.; Tripathy, T.; Trogolo, S.; Trombetta, G.; Tropp, L.; Trubnikov, V; Trzaska, W. H.; Trzcinski, T. P.; Trzeciak, B. A.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Umaka, E. N.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vala, M.; Valencia Palomo, L.; Valle, N.; van der Kolk, N.; van Doremalen, L. V. R.; Van Hoorne, J. 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C.; Zardoshti, N.; Zarochentsev, A.; Zavada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zhalov, M.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, C.; Zherebchevskii, V; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zhu, Y.; Zichichi, A.; Zimmermann, M. B.; Zinovjev, G.; Zurlo, N.Acharya, S.; Acosta, F. T.; Adamova, D.; Adhya, S. P.; Adler, A.; Adolfsson, J.; Aggarwal, M. M.; Rinella, G. Aglieri; Agnello, M.; Ahammed, Z.; Ahmad, S.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Al-Turany, M.; Alam, S. N.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alfanda, H. M.; Alfaro Molina, R.; Ali, B.; Ali, Y.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altenkamper, L.; Altsybeev, I; Anaam, M. N.; Andrei, C.; Andreou, D.; Andrews, H. A.; Andronic, A.; Angeletti, M.; Anguelov, V; Anson, C.; Anticic, T.; Antinori, F.; Antonioli, P.; Anwar, R.; Apadula, N.; Aphecetche, L.; Appelshaeuser, H.; Arcelli, S.; Arnaldi, R.; Arratia, M.; Arsene, I. 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    Two-stage artificial intelligence model for jointly measurement of atherosclerotic wall thickness and plaque burden in carotid ultrasound: A screening tool for cardiovascular/stroke risk assessment

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    Motivation: The early screening of cardiovascular diseases (CVD) can lead to effective treatment. Thus, accurate and reliable atherosclerotic carotid wall detection and plaque measurements are crucial. Current measurement methods are time-consuming and do not utilize the power of knowledge-based paradigms such as artificial intelligence (AI). We present an AI-based methodology for the joint automated detection and measurement of wall thickness and carotid plaque (CP) in the form of carotid intima-media thickness (cIMT) and total plaque area (TPA), a class of AtheroEdge™ system (AtheroPoint™, CA, USA). Method: The novel system consists of two stages, and each stage comprises an independent deep learning (DL) model. In Stage I, the first DL model segregates the common carotid artery (CCA) patches from ultrasound (US) images into the rectangular wall and non-wall patches. The characterized wall patches are integrated to form the region of interest (ROI), which is then fed into Stage II. In Stage II, the second DL model segments the far wall region. Lumen-intima (LI) and media-adventitial (MA) boundaries are then extracted from the wall region, which is then used for cIMT and PA measurement. Results: Using the database of 250 carotid scans, the cIMT error using the AI model is 0.0935±0.0637 mm, which is lower than those of all previous methods. The PA error is found to be 2.7939±2.3702 mm2. The system&apos;s correlation coefficient (CC) between AI and ground truth (GT) values for cIMT is 0.99 (p &amp;lt; 0.0001), which is higher compared with the CC of 0.96 (p &amp;lt; 0.0001) shown by the earlier DL method. The CC for PA between AI and GT values is 0.89 (p &amp;lt; 0.0001). Conclusion: A novel AI-based strategy was applied to carotid US images for the joint detection of carotid wall thickness (cWT) and plaque area (PA), followed by cIMT and PA measurement. This AI-based strategy shows improved performance using the patch technique compared with previous methods using full carotid scans. © 2020 Elsevier Lt

    Global perspective on carotid intima-media thickness and plaque: Should the current measurement guidelines be revisited?

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    Carotid intima-media thickness (cIMT) and carotid plaque (CP) currently act as risk predictors for CVD/Stroke risk assessment. Over 2000 articles have been published that cover either use cIMT/CP or alterations of cIMT/ CP and additional image-based phenotypes to associate cIMT related markers with CVD/Stroke risk. These articles have shown variable results, which likely reflect a lack of standardization in the tools for measurement, risk stratification, and risk assessment. Guidelines for cIMT/CP measurement are influenced by major factors like the atherosclerosis disease itself, conventional risk factors, 10-year measurement tools, types of CVD/ Stroke risk calculators, incomplete validation of measurement tools, and the fast pace of computer technology advancements. This review discusses the following major points: 1) the American Society of Echocardiography and Mannheim guidelines for cIMT/CP measurements; 2) forces that influence the guidelines; and 3) calculators for risk stratification and assessment under the influence of advanced intelligence methods. The review also presents the knowledge-based learning strategies such as machine and deep learning which may play a future role in CVD/stroke risk assessment. We conclude that both machine learning and non-machine learning strategies will flourish for current and 10-year CVD/Stroke risk prediction as long as they integrate image-based phenotypes with conventional risk factors. COPYRIGHT© 2019 EDIZIONI MINERVA MEDICA
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