Author: "Pandolfi, S." - Searchworks@Jio Institute Digital Library Search Results

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1. Euclid. I. Overview of the Euclid mission

Author: Euclid Collaboration, Mellier, Y., Abdurro'uf, Barroso, J. A. Acevedo, Achúcarro, A., Adamek, J., Adam, R., Addison, G. E., Aghanim, N., Aguena, M., Ajani, V., Akrami, Y., Al-Bahlawan, A., Alavi, A., Albuquerque, I. S., Alestas, G., Alguero, G., Allaoui, A., Allen, S. W., Allevato, V., Alonso-Tetilla, A. V., Altieri, B., Alvarez-Candal, A., Alvi, S., Amara, A., Amendola, L., Amiaux, J., Andika, I. T., Andreon, S., Andrews, A., Angora, G., Angulo, R. E., Annibali, F., Anselmi, A., Anselmi, S., Arcari, S., Archidiacono, M., Aricò, G., Arnaud, M., Arnouts, S., Asgari, M., Asorey, J., Atayde, L., Atek, H., Atrio-Barandela, F., Aubert, M., Aubourg, E., Auphan, T., Auricchio, N., Aussel, B., Aussel, H., Avelino, P. P., Avgoustidis, A., Avila, S., Awan, S., Azzollini, R., Baccigalupi, C., Bachelet, E., Bacon, D., Baes, M., Bagley, M. B., Bahr-Kalus, B., Balaguera-Antolinez, A., Balbinot, E., Balcells, M., Baldi, M., Baldry, I., Balestra, A., Ballardini, M., Ballester, O., Balogh, M., Bañados, E., Barbier, R., Bardelli, S., Baron, M., Barreiro, T., Barrena, R., Barriere, J. -C., Barros, B. J., Barthelemy, A., Bartolo, N., Basset, A., Battaglia, P., Battisti, A. J., Baugh, C. M., Baumont, L., Bazzanini, L., Beaulieu, J. -P., Beckmann, V., Belikov, A. N., Bel, J., Bellagamba, F., Bella, M., Bellini, E., Benabed, K., Bender, R., Benevento, G., Bennett, C. L., Benson, K., Bergamini, P., Bermejo-Climent, J. R., Bernardeau, F., Bertacca, D., Berthe, M., Berthier, J., Bethermin, M., Beutler, F., Bevillon, C., Bhargava, S., Bhatawdekar, R., Bianchi, D., Bisigello, L., Biviano, A., Blake, R. P., Blanchard, A., Blazek, J., Blot, L., Bosco, A., Bodendorf, C., Boenke, T., Böhringer, H., Boldrini, P., Bolzonella, M., Bonchi, A., Bonici, M., Bonino, D., Bonino, L., Bonvin, C., Bon, W., Booth, J. T., Borgani, S., Borlaff, A. S., Borsato, E., Bose, B., Botticella, M. T., Boucaud, A., Bouche, F., Boucher, J. S., Boutigny, D., Bouvard, T., Bouwens, R., Bouy, H., Bowler, R. A. A., Bozza, V., Bozzo, E., Branchini, E., Brando, G., Brau-Nogue, S., Brekke, P., Bremer, M. N., Brescia, M., Breton, M. -A., Brinchmann, J., Brinckmann, T., Brockley-Blatt, C., Brodwin, M., Brouard, L., Brown, M. L., Bruton, S., Bucko, J., Buddelmeijer, H., Buenadicha, G., Buitrago, F., Burger, P., Burigana, C., Busillo, V., Busonero, D., Cabanac, R., Cabayol-Garcia, L., Cagliari, M. S., Caillat, A., Caillat, L., Calabrese, M., Calabro, A., Calderone, G., Calura, F., Quevedo, B. Camacho, Camera, S., Campos, L., Canas-Herrera, G., Candini, G. P., Cantiello, M., Capobianco, V., Cappellaro, E., Cappelluti, N., Cappi, A., Caputi, K. I., Cara, C., Carbone, C., Cardone, V. F., Carella, E., Carlberg, R. G., Carle, M., Carminati, L., Caro, F., Carrasco, J. M., Carretero, J., Carrilho, P., Duque, J. Carron, Carry, B., Carvalho, A., Carvalho, C. S., Casas, R., Casas, S., Casenove, P., Casey, C. M., Cassata, P., Castander, F. J., Castelao, D., Castellano, M., Castiblanco, L., Castignani, G., Castro, T., Cavet, C., Cavuoti, S., Chabaud, P. -Y., Chambers, K. C., Charles, Y., Charlot, S., Chartab, N., Chary, R., Chaumeil, F., Cho, H., Chon, G., Ciancetta, E., Ciliegi, P., Cimatti, A., Cimino, M., Cioni, M. -R. L., Claydon, R., Cleland, C., Clément, B., Clements, D. L., Clerc, N., Clesse, S., Codis, S., Cogato, F., Colbert, J., Cole, R. E., Coles, P., Collett, T. E., Collins, R. S., Colodro-Conde, C., Colombo, C., Combes, F., Conforti, V., Congedo, G., Conseil, S., Conselice, C. J., Contarini, S., Contini, T., Conversi, L., Cooray, A. R., Copin, Y., Corasaniti, P. -S., Corcho-Caballero, P., Corcione, L., Cordes, O., Corpace, O., Correnti, M., Costanzi, M., Costille, A., Courbin, F., Mifsud, L. Courcoult, Courtois, H. M., Cousinou, M. -C., Covone, G., Cowell, T., Cragg, C., Cresci, G., Cristiani, S., Crocce, M., Cropper, M., Crouzet, P. E, Csizi, B., Cuby, J. -G., Cucchetti, E., Cucciati, O., Cuillandre, J. -C., Cunha, P. A. C., Cuozzo, V., Daddi, E., D'Addona, M., Dafonte, C., Dagoneau, N., Dalessandro, E., Dalton, G. B., D'Amico, G., Dannerbauer, H., Danto, P., Das, I., Da Silva, A., da Silva, R., Doumerg, W. d'Assignies, Daste, G., Davies, J. E., Davini, S., Dayal, P., de Boer, T., Decarli, R., De Caro, B., Degaudenzi, H., Degni, G., de Jong, J. T. A., de la Bella, L. F., de la Torre, S., Delhaise, F., Delley, D., Delucchi, G., De Lucia, G., Denniston, J., De Paolis, F., De Petris, M., Derosa, A., Desai, S., Desjacques, V., Despali, G., Desprez, G., De Vicente-Albendea, J., Deville, Y., Dias, J. D. F., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Diego, J. M., Di Ferdinando, D., Di Giorgio, A. M., Dimauro, P., Dinis, J., Dolag, K., Dolding, C., Dole, H., Sánchez, H. Domínguez, Doré, O., Dournac, F., Douspis, M., Dreihahn, H., Droge, B., Dryer, B., Dubath, F., Duc, P. -A., Ducret, F., Duffy, C., Dufresne, F., Duncan, C. A. J., Dupac, X., Duret, V., Durrer, R., Durret, F., Dusini, S., Ealet, A., Eggemeier, A., Eisenhardt, P. R. M., Elbaz, D., Elkhashab, M. Y., Ellien, A., Endicott, J., Enia, A., Erben, T., Vigo, J. A. Escartin, Escoffier, S., Sanz, I. Escudero, Essert, J., Ettori, S., Ezziati, M., Fabbian, G., Fabricius, M., Fang, Y., Farina, A., Farina, M., Farinelli, R., Farrens, S., Faustini, F., Feltre, A., Ferguson, A. M. N., Ferrando, P., Ferrari, A. G., Ferré-Mateu, A., Ferreira, P. G., Ferreras, I., Ferrero, I., Ferriol, S., Ferruit, P., Filleul, D., Finelli, F., Finkelstein, S. L., Finoguenov, A., Fiorini, B., Flentge, F., Focardi, P., Fonseca, J., Fontana, A., Fontanot, F., Fornari, F., Fosalba, P., Fossati, M., Fotopoulou, S., Fouchez, D., Fourmanoit, N., Frailis, M., Fraix-Burnet, D., Franceschi, E., Franco, A., Franzetti, P., Freihoefer, J., Frenk, C. . S., Frittoli, G., Frugier, P. -A., Frusciante, N., Fumagalli, A., Fumagalli, M., Fumana, M., Fu, Y., Gabarra, L., Galeotta, S., Galluccio, L., Ganga, K., Gao, H., García-Bellido, J., Garcia, K., Gardner, J. P., Garilli, B., Gaspar-Venancio, L. -M., Gasparetto, T., Gautard, V., Gavazzi, R., Gaztanaga, E., Genolet, L., Santos, R. Genova, Gentile, F., George, K., Gerbino, M., Ghaffari, Z., Giacomini, F., Gianotti, F., Gibb, G. P. S., Gillard, W., Gillis, B., Ginolfi, M., Giocoli, C., Girardi, M., Giri, S. K., Goh, L. W. K., Gómez-Alvarez, P., Gonzalez-Perez, V., Gonzalez, A. H., Gonzalez, E. J., Gonzalez, J. C., Beauchamps, S. Gouyou, Gozaliasl, G., Gracia-Carpio, J., Grandis, S., Granett, B. R., Granvik, M., Grazian, A., Gregorio, A., Grenet, C., Grillo, C., Grupp, F., Gruppioni, C., Gruppuso, A., Guerbuez, C., Guerrini, S., Guidi, M., Guillard, P., Gutierrez, C. M., Guttridge, P., Guzzo, L., Gwyn, S., Haapala, J., Haase, J., Haddow, C. R., Hailey, M., Hall, A., Hall, D., Hamaus, N., Haridasu, B. S., Harnois-Déraps, J., Harper, C., Hartley, W. G., Hasinger, G., Hassani, F., Hatch, N. A., Haugan, S. V. H., Häußler, B., Heavens, A., Heisenberg, L., Helmi, A., Helou, G., Hemmati, S., Henares, K., Herent, O., Hernández-Monteagudo, C., Heuberger, T., Hewett, P. C., Heydenreich, S., Hildebrandt, H., Hirschmann, M., Hjorth, J., Hoar, J., Hoekstra, H., Holland, A. D., Holliman, M. S., Holmes, W., Hook, I., Horeau, B., Hormuth, F., Hornstrup, A., Hosseini, S., Hu, D., Hudelot, P., Hudson, M. J., Huertas-Company, M., Huff, E. M., Hughes, A. C. N., Humphrey, A., Hunt, L. K., Huynh, D. D., Ibata, R., Ichikawa, K., Iglesias-Groth, S., Ilbert, O., Ilić, S., Ingoglia, L., Iodice, E., Israel, H., Israelsson, U. E., Izzo, L., Jablonka, P., Jackson, N., Jacobson, J., Jafariyazani, M., Jahnke, K., Jain, B., Jansen, H., Jarvis, M. J., Jasche, J., Jauzac, M., Jeffrey, N., Jhabvala, M., Jimenez-Teja, Y., Muñoz, A. Jimenez, Joachimi, B., Johansson, P. H., Joudaki, S., Jullo, E., Kajava, J. J. E., Kang, Y., Kannawadi, A., Kansal, V., Karagiannis, D., Kärcher, M., Kashlinsky, A., Kazandjian, M. V., Keck, F., Keihänen, E., Kerins, E., Kermiche, S., Khalil, A., Kiessling, A., Kiiveri, K., Kilbinger, M., Kim, J., King, R., Kirkpatrick, C. C., Kitching, T., Kluge, M., Knabenhans, M., Knapen, J. H., Knebe, A., Kneib, J. -P., Kohley, R., Koopmans, L. V. E., Koskinen, H., Koulouridis, E., Kou, R., Kovács, A., Kovačić, I., Kowalczyk, A., Koyama, K., Kraljic, K., Krause, O., Kruk, S., Kubik, B., Kuchner, U., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lacasa, F., Lacey, C. G., La Franca, F., Lagarde, N., Lahav, O., Laigle, C., La Marca, A., La Marle, O., Lamine, B., Lam, M. C., Lançon, A., Landt, H., Langer, M., Lapi, A., Larcheveque, C., Larsen, S. S., Lattanzi, M., Laudisio, F., Laugier, D., Laureijs, R., Laurent, V., Lavaux, G., Lawrenson, A., Lazanu, A., Lazeyras, T., Boulc'h, Q. Le, Brun, A. M. C. Le, Brun, V. Le, Leclercq, F., Lee, S., Graet, J. Le, Legrand, L., Leirvik, K. N., Jeune, M. Le, Lembo, M., Mignant, D. Le, Lepinzan, M. D., Lepori, F., Reun, A. Le, Leroy, G., Lesci, G. F., Lesgourgues, J., Leuzzi, L., Levi, M. E., Liaudat, T. I., Libet, G., Liebing, P., Ligori, S., Lilje, P. B., Lin, C. -C., Linde, D., Linder, E., Lindholm, V., Linke, L., Li, S. -S., Liu, S. J., Lloro, I., Lobo, F. S. N., Lodieu, N., Lombardi, M., Lombriser, L., Lonare, P., Longo, G., López-Caniego, M., Lopez, X. Lopez, Alvarez, J. Lorenzo, Loureiro, A., Loveday, J., Lusso, E., Macias-Perez, J., Maciaszek, T., Maggio, G., Magliocchetti, M., Magnard, F., Magnier, E. A., Magro, A., Mahler, G., Mainetti, G., Maino, D., Maiorano, E., Malavasi, N., Mamon, G. A., Mancini, C., Mandelbaum, R., Manera, M., Manjón-García, A., Mannucci, F., Mansutti, O., Outeiro, M. Manteiga, Maoli, R., Maraston, C., Marcin, S., Marcos-Arenal, P., Margalef-Bentabol, B., Marggraf, O., Marinucci, D., Marinucci, M., Markovic, K., Marleau, F. R., Marpaud, J., Martignac, J., Martín-Fleitas, J., Martin-Moruno, P., Martin, E. L., Martinelli, M., Martinet, N., Martin, H., Martins, C. J. A. P., Marulli, F., Massari, D., Massey, R., Masters, D. C., Matarrese, S., Matsuoka, Y., Matthew, S., Maughan, B. J., Mauri, N., Maurin, L., Maurogordato, S., McCarthy, K., McConnachie, A. W., McCracken, H. J., McDonald, I., McEwen, J. D., McPartland, C. J. R., Medinaceli, E., Mehta, V., Mei, S., Melchior, M., Melin, J. -B., Ménard, B., Mendes, J., Mendez-Abreu, J., Meneghetti, M., Mercurio, A., Merlin, E., Metcalf, R. B., Meylan, G., Migliaccio, M., Mignoli, M., Miller, L., Miluzio, M., Milvang-Jensen, B., Mimoso, J. P., Miquel, R., Miyatake, H., Mobasher, B., Mohr, J. J., Monaco, P., Monguió, M., Montoro, A., Mora, A., Dizgah, A. Moradinezhad, Moresco, M., Moretti, C., Morgante, G., Morisset, N., Moriya, T. J., Morris, P. W., Mortlock, D. J., Moscardini, L., Mota, D. F., Mottet, S., Moustakas, L. A., Moutard, T., Müller, T., Munari, E., Murphree, G., Murray, C., Murray, N., Musi, P., Nadathur, S., Nagam, B. C., Nagao, T., Naidoo, K., Nakajima, R., Nally, C., Natoli, P., Navarro-Alsina, A., Girones, D. Navarro, Neissner, C., Nersesian, A., Nesseris, S., Nguyen-Kim, H. N., Nicastro, L., Nichol, R. C., Nielbock, M., Niemi, S. -M., Nieto, S., Nilsson, K., Noller, J., Norberg, P., Nouri-Zonoz, A., Ntelis, P., Nucita, A. A., Nugent, P., Nunes, N. J., Nutma, T., Ocampo, I., Odier, J., Oesch, P. A., Oguri, M., Oliveira, D. Magalhaes, Onoue, M., Oosterbroek, T., Oppizzi, F., Ordenovic, C., Osato, K., Pacaud, F., Pace, F., Padilla, C., Paech, K., Pagano, L., Page, M. J., Palazzi, E., Paltani, S., Pamuk, S., Pandolfi, S., Paoletti, D., Paolillo, M., Papaderos, P., Pardede, K., Parimbelli, G., Parmar, A., Partmann, C., Pasian, F., Passalacqua, F., Paterson, K., Patrizii, L., Pattison, C., Paulino-Afonso, A., Paviot, R., Peacock, J. A., Pearce, F. R., Pedersen, K., Peel, A., Peletier, R. F., Ibanez, M. Pellejero, Pello, R., Penny, M. T., Percival, W. J., Perez-Garrido, A., Perotto, L., Pettorino, V., Pezzotta, A., Pezzuto, S., Philippon, A., Pierre, M., Piersanti, O., Pietroni, M., Piga, L., Pilo, L., Pires, S., Pisani, A., Pizzella, A., Pizzuti, L., Plana, C., Polenta, G., Pollack, J. E., Poncet, M., Pöntinen, M., Pool, P., Popa, L. A., Popa, V., Popp, J., Porciani, C., Porth, L., Potter, D., Poulain, M., Pourtsidou, A., Pozzetti, L., Prandoni, I., Pratt, G. W., Prezelus, S., Prieto, E., Pugno, A., Quai, S., Quilley, L., Racca, G. D., Raccanelli, A., Rácz, G., Radinović, S., Radovich, M., Ragagnin, A., Ragnit, U., Raison, F., Ramos-Chernenko, N., Ranc, C., Rasera, Y., Raylet, N., Rebolo, R., Refregier, A., Reimberg, P., Reiprich, T. H., Renk, F., Renzi, A., Retre, J., Revaz, Y., Reylé, C., Reynolds, L., Rhodes, J., Ricci, F., Ricci, M., Riccio, G., Ricken, S. O., Rissanen, S., Risso, I., Rix, H. -W., Robin, A. C., Rocca-Volmerange, B., Rocci, P. -F., Rodenhuis, M., Rodighiero, G., Monroy, M. Rodriguez, Rollins, R. P., Romanello, M., Roman, J., Romelli, E., Romero-Gomez, M., Roncarelli, M., Rosati, P., Rosset, C., Rossetti, E., Roster, W., Rottgering, H. J. A., Rozas-Fernández, A., Ruane, K., Rubino-Martin, J. A., Rudolph, A., Ruppin, F., Rusholme, B., Sacquegna, S., Sáez-Casares, I., Saga, S., Saglia, R., Sahlén, M., Saifollahi, T., Sakr, Z., Salvalaggio, J., Salvaterra, R., Salvati, L., Salvato, M., Salvignol, J. -C., Sánchez, A. G., Sanchez, E., Sanders, D. B., Sapone, D., Saponara, M., Sarpa, E., Sarron, F., Sartori, S., Sartoris, B., Sassolas, B., Sauniere, L., Sauvage, M., Sawicki, M., Scaramella, R., Scarlata, C., Scharré, L., Schaye, J., Schewtschenko, J. A., Schindler, J. -T., Schinnerer, E., Schirmer, M., Schmidt, F., Schmidt, M., Schneider, A., Schneider, M., Schneider, P., Schöneberg, N., Schrabback, T., Schultheis, M., Schulz, S., Schuster, N., Schwartz, J., Sciotti, D., Scodeggio, M., Scognamiglio, D., Scott, D., Scottez, V., Secroun, A., Sefusatti, E., Seidel, G., Seiffert, M., Sellentin, E., Selwood, M., Semboloni, E., Sereno, M., Serjeant, S., Serrano, S., Setnikar, G., Shankar, F., Sharples, R. M., Short, A., Shulevski, A., Shuntov, M., Sias, M., Sikkema, G., Silvestri, A., Simon, P., Sirignano, C., Sirri, G., Skottfelt, J., Slezak, E., Sluse, D., Smith, G. P., Smith, L. C., Smith, R. E., Smit, S. J. A., Soldano, F., Solheim, B. G. B., Sorce, J. G., Sorrenti, F., Soubrie, E., Spinoglio, L., Mancini, A. Spurio, Stadel, J., Stagnaro, L., Stanco, L., Stanford, S. A., Starck, J. -L., Stassi, P., Steinwagner, J., Stern, D., Stone, C., Strada, P., Strafella, F., Stramaccioni, D., Surace, C., Sureau, F., Suyu, S. H., Swindells, I., Szafraniec, M., Szapudi, I., Taamoli, S., Talia, M., Tallada-Crespí, P., Tanidis, K., Tao, C., Tarrío, P., Tavagnacco, D., Taylor, A. N., Taylor, J. E., Taylor, P. L., Teixeira, E. M., Tenti, M., Idiago, P. Teodoro, Teplitz, H. I., Tereno, I., Tessore, N., Testa, V., Testera, G., Tewes, M., Teyssier, R., Theret, N., Thizy, C., Thomas, P. D., Toba, Y., Toft, S., Toledo-Moreo, R., Tolstoy, E., Tommasi, E., Torbaniuk, O., Torradeflot, F., Tortora, C., Tosi, S., Tosti, S., Trifoglio, M., Troja, A., Trombetti, T., Tronconi, A., Tsedrik, M., Tsyganov, A., Tucci, M., Tutusaus, I., Uhlemann, C., Ulivi, L., Urbano, M., Vacher, L., Vaillon, L., Valageas, P., Valdes, I., Valentijn, E. A., Valenziano, L., Valieri, C., Valiviita, J., Broeck, M. Van den, Vassallo, T., Vavrek, R., Vega-Ferrero, J., Venemans, B., Venhola, A., Ventura, S., Kleijn, G. Verdoes, Vergani, D., Verma, A., Vernizzi, F., Veropalumbo, A., Verza, G., Vescovi, C., Vibert, D., Viel, M., Vielzeuf, P., Viglione, C., Viitanen, A., Villaescusa-Navarro, F., Vinciguerra, S., Visticot, F., Voggel, K., von Wietersheim-Kramsta, M., Vriend, W. J., Wachter, S., Walmsley, M., Walth, G., Walton, D. M., Walton, N. A., Wander, M., Wang, L., Wang, Y., Weaver, J. R., Weller, J., Wetzstein, M., Whalen, D. J., Whittam, I. H., Widmer, A., Wiesmann, M., Wilde, J., Williams, O. R., Winther, H. -A., Wittje, A., Wong, J. H. W., Wright, A. H., Yankelevich, V., Yeung, H. W., Yoon, M., Youles, S., Yung, L. Y. A., Zacchei, A., Zalesky, L., Zamorani, G., Vitorelli, A. Zamorano, Marc, M. Zanoni, Zennaro, M., Zerbi, F. M., Zinchenko, I. A., Zoubian, J., Zucca, E., and Zumalacarregui, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'
Published: 2024

2. Atomistic deformation mechanism of silicon under laser-driven shock compression

Author: Pandolfi, S., Brown, S. Brennan, Stubley, P. G., Higginbotham, A., Bolme, C. A., Lee, H. J., Nagler, B., Galtier, E., Sandberg, R., Yang, W., Mao, W. L., Wark, J. S., and Gleason, A.
Subjects: Condensed Matter - Materials Science
Abstract: Silicon (Si) is one of the most abundant elements on Earth, and it is the most important and widely used semiconductor, constituting the basis of modern electronic devices. Despite extensive study, some properties of Si remain elusive. For example, the behaviour of Si under high pressure, in particular at the ultra-high strain rates characteristic of dynamic compression, has been a matter of debate for decades. A detailed understanding of how Si deforms is crucial for a variety of fields, ranging from planetary science to materials design. Simulations suggest that in Si the shear stress generated during shock compression is released inelastically, i.e., via a high-pressure phase transition, challenging the classical picture of relaxation via defect-mediated plasticity. However, experiments at the short timescales characteristic of shock compression are challenging, and direct evidence supporting either deformation mechanism remain elusive. Here, we use sub-picosecond, highly-monochromatic x-ray diffraction to study (100)-oriented single-crystal Si under laser-driven shock compression. We provide the first unambiguous, time-resolved picture of Si deformation at ultra-high strain rates, demonstrating the predicted inelastic shear release. Our results resolve the longstanding controversy on silicon deformation under dynamic compression, and provide direct proof of strain rate-dependent deformation mechanisms in a non-metallic system, which is key for the study of planetary-relevant materials.
Published: 2021
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3. Shock compression experiments using the DiPOLE 100-X laser on the high energy density instrument at the European x-ray free electron laser: Quantitative structural analysis of liquid Sn

Author: Gorman, M, Mcgonegle, D, Smith, R, Singh, S, Jenkins, T, Mcwilliams, R, Albertazzi, B, Ali, S, Antonelli, L, Armstrong, M, Baehtz, C, Ball, O, Banerjee, S, Belonoshko, A, Benuzzi-Mounaix, A, Bolme, C, Bouffetier, V, Briggs, R, Buakor, K, Butcher, T, Di Dio Cafiso, S, Cerantola, V, Chantel, J, Di Cicco, A, Clarke, S, Coleman, A, Collier, J, Collins, G, Comley, A, Coppari, F, Cowan, T, Cristoforetti, G, Cynn, H, Descamps, A, Dorchies, F, Duff, M, Dwivedi, A, Edwards, C, Eggert, J, Errandonea, D, Fiquet, G, Galtier, E, Laso Garcia, A, Ginestet, H, Gizzi, L, Gleason, A, Goede, S, Gonzalez, J, Harmand, M, Hartley, N, Heighway, P, Hernandez-Gomez, C, Higginbotham, A, Höppner, H, Husband, R, Hutchinson, T, Hwang, H, Lazicki, A, Keen, D, Kim, J, Koester, P, Konopkova, Z, Kraus, D, Krygier, A, Labate, L, Lee, Y, Liermann, H, Mason, P, Masruri, M, Massani, B, Mcbride, E, Mcguire, C, Mchardy, J, Merkel, S, Morard, G, Nagler, B, Nakatsutsumi, M, Nguyen-Cong, K, Norton, A, Oleynik, I, Otzen, C, Ozaki, N, Pandolfi, S, Peake, D, Pelka, A, Pereira, K, Phillips, J, Prescher, C, Preston, T, Randolph, L, Ranjan, D, Ravasio, A, Redmer, R, Rips, J, Santamaria-Perez, D, Savage, D, Schoelmerich, M, Schwinkendorf, J, Smith, J, Sollier, A, Spear, J, Spindloe, C, Stevenson, M, Strohm, C, Suer, T, Tang, M, Toncian, M, Toncian, T, Tracy, S, Trapananti, A, Tschentscher, T, Tyldesley, M, Vennari, C, Vinci, T, Vogel, S, Volz, T, Vorberger, J, Walsh, J, Wark, J, Willman, J, Wollenweber, L, Zastrau, U, Brambrink, E, Appel, K, Mcmahon, M, Gorman, M. G., McGonegle, D., Smith, R. F., Singh, S., Jenkins, T., McWilliams, R. S., Albertazzi, B., Ali, S. J., Antonelli, L., Armstrong, M. R., Baehtz, C., Ball, O. B., Banerjee, S., Belonoshko, A. B., Benuzzi-Mounaix, A., Bolme, C. A., Bouffetier, V., Briggs, R., Buakor, K., Butcher, T., Di Dio Cafiso, S., Cerantola, V., Chantel, J., Di Cicco, A., Clarke, S., Coleman, A. L., Collier, J., Collins, G. W., Comley, A. J., Coppari, F., Cowan, T. E., Cristoforetti, G., Cynn, H., Descamps, A., Dorchies, F., Duff, M. J., Dwivedi, A., Edwards, C., Eggert, J. H., Errandonea, D., Fiquet, G., Galtier, E., Laso Garcia, A., Ginestet, H., Gizzi, L., Gleason, A., Goede, S., Gonzalez, J. M., Harmand, M., Hartley, N. J., Heighway, P. G., Hernandez-Gomez, C., Higginbotham, A., Höppner, H., Husband, R. J., Hutchinson, T. M., Hwang, H., Lazicki, A. E., Keen, D. A., Kim, J., Koester, P., Konopkova, Z., Kraus, D., Krygier, A., Labate, L., Lee, Y., Liermann, H. -P., Mason, P., Masruri, M., Massani, B., McBride, E. E., McGuire, C., McHardy, J. D., Merkel, S., Morard, G., Nagler, B., Nakatsutsumi, M., Nguyen-Cong, K., Norton, A. -M., Oleynik, I. I., Otzen, C., Ozaki, N., Pandolfi, S., Peake, D. J., Pelka, A., Pereira, K. A., Phillips, J. P., Prescher, C., Preston, T. R., Randolph, L., Ranjan, D., Ravasio, A., Redmer, R., Rips, J., Santamaria-Perez, D., Savage, D. J., Schoelmerich, M., Schwinkendorf, J. -P., Smith, J., Sollier, A., Spear, J., Spindloe, C., Stevenson, M., Strohm, C., Suer, T. -A., Tang, M., Toncian, M., Toncian, T., Tracy, S. J., Trapananti, A., Tschentscher, T., Tyldesley, M., Vennari, C. E., Vinci, T., Vogel, S. C., Volz, T. J., Vorberger, J., Walsh, J. P. S., Wark, J. S., Willman, J. T., Wollenweber, L., Zastrau, U., Brambrink, E., Appel, K., McMahon, M. I., Gorman, M, Mcgonegle, D, Smith, R, Singh, S, Jenkins, T, Mcwilliams, R, Albertazzi, B, Ali, S, Antonelli, L, Armstrong, M, Baehtz, C, Ball, O, Banerjee, S, Belonoshko, A, Benuzzi-Mounaix, A, Bolme, C, Bouffetier, V, Briggs, R, Buakor, K, Butcher, T, Di Dio Cafiso, S, Cerantola, V, Chantel, J, Di Cicco, A, Clarke, S, Coleman, A, Collier, J, Collins, G, Comley, A, Coppari, F, Cowan, T, Cristoforetti, G, Cynn, H, Descamps, A, Dorchies, F, Duff, M, Dwivedi, A, Edwards, C, Eggert, J, Errandonea, D, Fiquet, G, Galtier, E, Laso Garcia, A, Ginestet, H, Gizzi, L, Gleason, A, Goede, S, Gonzalez, J, Harmand, M, Hartley, N, Heighway, P, Hernandez-Gomez, C, Higginbotham, A, Höppner, H, Husband, R, Hutchinson, T, Hwang, H, Lazicki, A, Keen, D, Kim, J, Koester, P, Konopkova, Z, Kraus, D, Krygier, A, Labate, L, Lee, Y, Liermann, H, Mason, P, Masruri, M, Massani, B, Mcbride, E, Mcguire, C, Mchardy, J, Merkel, S, Morard, G, Nagler, B, Nakatsutsumi, M, Nguyen-Cong, K, Norton, A, Oleynik, I, Otzen, C, Ozaki, N, Pandolfi, S, Peake, D, Pelka, A, Pereira, K, Phillips, J, Prescher, C, Preston, T, Randolph, L, Ranjan, D, Ravasio, A, Redmer, R, Rips, J, Santamaria-Perez, D, Savage, D, Schoelmerich, M, Schwinkendorf, J, Smith, J, Sollier, A, Spear, J, Spindloe, C, Stevenson, M, Strohm, C, Suer, T, Tang, M, Toncian, M, Toncian, T, Tracy, S, Trapananti, A, Tschentscher, T, Tyldesley, M, Vennari, C, Vinci, T, Vogel, S, Volz, T, Vorberger, J, Walsh, J, Wark, J, Willman, J, Wollenweber, L, Zastrau, U, Brambrink, E, Appel, K, Mcmahon, M, Gorman, M. G., McGonegle, D., Smith, R. F., Singh, S., Jenkins, T., McWilliams, R. S., Albertazzi, B., Ali, S. J., Antonelli, L., Armstrong, M. R., Baehtz, C., Ball, O. B., Banerjee, S., Belonoshko, A. B., Benuzzi-Mounaix, A., Bolme, C. A., Bouffetier, V., Briggs, R., Buakor, K., Butcher, T., Di Dio Cafiso, S., Cerantola, V., Chantel, J., Di Cicco, A., Clarke, S., Coleman, A. L., Collier, J., Collins, G. W., Comley, A. J., Coppari, F., Cowan, T. E., Cristoforetti, G., Cynn, H., Descamps, A., Dorchies, F., Duff, M. J., Dwivedi, A., Edwards, C., Eggert, J. H., Errandonea, D., Fiquet, G., Galtier, E., Laso Garcia, A., Ginestet, H., Gizzi, L., Gleason, A., Goede, S., Gonzalez, J. M., Harmand, M., Hartley, N. J., Heighway, P. G., Hernandez-Gomez, C., Higginbotham, A., Höppner, H., Husband, R. J., Hutchinson, T. M., Hwang, H., Lazicki, A. E., Keen, D. A., Kim, J., Koester, P., Konopkova, Z., Kraus, D., Krygier, A., Labate, L., Lee, Y., Liermann, H. -P., Mason, P., Masruri, M., Massani, B., McBride, E. E., McGuire, C., McHardy, J. D., Merkel, S., Morard, G., Nagler, B., Nakatsutsumi, M., Nguyen-Cong, K., Norton, A. -M., Oleynik, I. I., Otzen, C., Ozaki, N., Pandolfi, S., Peake, D. J., Pelka, A., Pereira, K. A., Phillips, J. P., Prescher, C., Preston, T. R., Randolph, L., Ranjan, D., Ravasio, A., Redmer, R., Rips, J., Santamaria-Perez, D., Savage, D. J., Schoelmerich, M., Schwinkendorf, J. -P., Smith, J., Sollier, A., Spear, J., Spindloe, C., Stevenson, M., Strohm, C., Suer, T. -A., Tang, M., Toncian, M., Toncian, T., Tracy, S. J., Trapananti, A., Tschentscher, T., Tyldesley, M., Vennari, C. E., Vinci, T., Vogel, S. C., Volz, T. J., Vorberger, J., Walsh, J. P. S., Wark, J. S., Willman, J. T., Wollenweber, L., Zastrau, U., Brambrink, E., Appel, K., and McMahon, M. I.
Abstract: X-ray free electron laser (XFEL) sources coupled to high-power laser systems offer an avenue to study the structural dynamics of materials at extreme pressures and temperatures. The recent commissioning of the DiPOLE 100-X laser on the high energy density (HED) instrument at the European XFEL represents the state-of-the-art in combining x-ray diffraction with laser compression, allowing for compressed materials to be probed in unprecedented detail. Here, we report quantitative structural measurements of molten Sn compressed to 85(5) GPa and ∼ 3500 K. The capabilities of the HED instrument enable liquid density measurements with an uncertainty of ∼ 1 % at conditions which are extremely challenging to reach via static compression methods. We discuss best practices for conducting liquid diffraction dynamic compression experiments and the necessary intensity corrections which allow for accurate quantitative analysis. We also provide a polyimide ablation pressure vs input laser energy for the DiPOLE 100-X drive laser which will serve future users of the HED instrument.
Published: 2024

4. Shock compression experiments using the DiPOLE 100-X laser on the high energy density instrument at the European x-ray free electron laser: Quantitative structural analysis of liquid Sn

Author: Gorman, M. G., primary, McGonegle, D., additional, Smith, R. F., additional, Singh, S., additional, Jenkins, T., additional, McWilliams, R. S., additional, Albertazzi, B., additional, Ali, S. J., additional, Antonelli, L., additional, Armstrong, M. R., additional, Baehtz, C., additional, Ball, O. B., additional, Banerjee, S., additional, Belonoshko, A. B., additional, Benuzzi-Mounaix, A., additional, Bolme, C. A., additional, Bouffetier, V., additional, Briggs, R., additional, Buakor, K., additional, Butcher, T., additional, Di Dio Cafiso, S., additional, Cerantola, V., additional, Chantel, J., additional, Di Cicco, A., additional, Clarke, S., additional, Coleman, A. L., additional, Collier, J., additional, Collins, G. W., additional, Comley, A. J., additional, Coppari, F., additional, Cowan, T. E., additional, Cristoforetti, G., additional, Cynn, H., additional, Descamps, A., additional, Dorchies, F., additional, Duff, M. J., additional, Dwivedi, A., additional, Edwards, C., additional, Eggert, J. H., additional, Errandonea, D., additional, Fiquet, G., additional, Galtier, E., additional, Laso Garcia, A., additional, Ginestet, H., additional, Gizzi, L., additional, Gleason, A., additional, Goede, S., additional, Gonzalez, J. M., additional, Harmand, M., additional, Hartley, N. J., additional, Heighway, P. G., additional, Hernandez-Gomez, C., additional, Higginbotham, A., additional, Höppner, H., additional, Husband, R. J., additional, Hutchinson, T. M., additional, Hwang, H., additional, Lazicki, A. E., additional, Keen, D. A., additional, Kim, J., additional, Koester, P., additional, Konopkova, Z., additional, Kraus, D., additional, Krygier, A., additional, Labate, L., additional, Lee, Y., additional, Liermann, H.-P., additional, Mason, P., additional, Masruri, M., additional, Massani, B., additional, McBride, E. E., additional, McGuire, C., additional, McHardy, J. D., additional, Merkel, S., additional, Morard, G., additional, Nagler, B., additional, Nakatsutsumi, M., additional, Nguyen-Cong, K., additional, Norton, A.-M., additional, Oleynik, I. I., additional, Otzen, C., additional, Ozaki, N., additional, Pandolfi, S., additional, Peake, D. J., additional, Pelka, A., additional, Pereira, K. A., additional, Phillips, J. P., additional, Prescher, C., additional, Preston, T. R., additional, Randolph, L., additional, Ranjan, D., additional, Ravasio, A., additional, Redmer, R., additional, Rips, J., additional, Santamaria-Perez, D., additional, Savage, D. J., additional, Schoelmerich, M., additional, Schwinkendorf, J.-P., additional, Smith, J., additional, Sollier, A., additional, Spear, J., additional, Spindloe, C., additional, Stevenson, M., additional, Strohm, C., additional, Suer, T.-A., additional, Tang, M., additional, Toncian, M., additional, Toncian, T., additional, Tracy, S. J., additional, Trapananti, A., additional, Tschentscher, T., additional, Tyldesley, M., additional, Vennari, C. E., additional, Vinci, T., additional, Vogel, S. C., additional, Volz, T. J., additional, Vorberger, J., additional, Walsh, J. P. S., additional, Wark, J. S., additional, Willman, J. T., additional, Wollenweber, L., additional, Zastrau, U., additional, Brambrink, E., additional, Appel, K., additional, and McMahon, M. I., additional
Published: 2024
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5. Radiation and heat transport in divergent shock–bubble interactions

Author: Kurzer-Ogul, K., primary, Haines, B. M., additional, Montgomery, D. S., additional, Pandolfi, S., additional, Sauppe, J. P., additional, Leong, A. F. T., additional, Hodge, D., additional, Kozlowski, P. M., additional, Marchesini, S., additional, Cunningham, E., additional, Galtier, E., additional, Khaghani, D., additional, Lee, H. J., additional, Nagler, B., additional, Sandberg, R. L., additional, Gleason, A. E., additional, Aluie, H., additional, and Shang, J. K., additional
Published: 2024
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6. Caregiving burden among informal caregivers of African American cancer survivors

Author: Schwartz, K., Beebe-Dimmer, J., Hastert, T. A., Ruterbusch, J. J., Mantey, J., Harper, F., Thompson, H., Pandolfi, S., and Schwartz, A. G.
Published: 2021
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7. Release dynamics of nanodiamonds created by laser-driven shock-compression of polyethylene terephthalate

Author: (0000-0001-6363-1780) Heuser, B., Bergermann, A., Stevenson, M. G., Ranjan, D., He, Z., Lütgert, J., Schumacher, S., Bethkenhagen, M., Descamps, A., Galtier, E., Gleason, A. E., Khaghani, D., Glenn, G. D., Cunningham, E. F., Glenzer, S. H., Hartley, N. J., Hernandez, J.-A., Humphries, O. S., Katagiri, K., Ja Lee, H., McBride, E. E., Miyanishi, K., Nagler, B., Ofori-Okai, B., Ozaki, N., Pandolfi, S., Qu, C., Thomas May, P., Redmer, R., Schoenwaelder, C., Sueda, K., Yabuuchi, T., Yabashi, M., Lukic, B., Rack, A., Zinta, L. M. V., Vinci, T., Benuzzi-Mounaix, A., Ravasio, A., (0000-0002-6350-4180) Kraus, D., (0000-0001-6363-1780) Heuser, B., Bergermann, A., Stevenson, M. G., Ranjan, D., He, Z., Lütgert, J., Schumacher, S., Bethkenhagen, M., Descamps, A., Galtier, E., Gleason, A. E., Khaghani, D., Glenn, G. D., Cunningham, E. F., Glenzer, S. H., Hartley, N. J., Hernandez, J.-A., Humphries, O. S., Katagiri, K., Ja Lee, H., McBride, E. E., Miyanishi, K., Nagler, B., Ofori-Okai, B., Ozaki, N., Pandolfi, S., Qu, C., Thomas May, P., Redmer, R., Schoenwaelder, C., Sueda, K., Yabuuchi, T., Yabashi, M., Lukic, B., Rack, A., Zinta, L. M. V., Vinci, T., Benuzzi-Mounaix, A., Ravasio, A., and (0000-0002-6350-4180) Kraus, D.
Abstract: Laser-driven dynamic compression experiments of plastic materials have found surprisingly fast formation of nanodiamonds (ND) via X-ray probing. This mechanism is relevant for planetary models, but could also open efficient synthesis routes for tailored NDs. We investigate the release mechanics of compressed NDs by molecular dynamics simulation of the isotropic expansion of finite size diamond from different P-T states. Analysing the structural integrity along different release paths via molecular dynamic simulations, we found substantial disintegration rates upon shock release, increasing with the on-Hugnoiot shock temperature. We also find that recrystallization can occur after the expansion and hence during the release, depending on subsequent cooling mechanisms. Our study suggests higher ND recovery rates from off-Hugoniot states, e.g., via double-shocks, due to faster cooling. Laser-driven shock compression experiments of polyethylene terephthalate (PET) samples with in situ X-ray probing at the simulated conditions found diamond signal that persists up to 11 ns after breakout. In the diffraction pattern, we observed peak shifts, which we attribute to thermal expansion of the NDs and thus a total release of pressure, which indicates the stability of the released NDs.
Published: 2024

8. Variable selection for hidden Markov models with continuous variables and missing data

Author: Pennoni, F, Bartolucci, F, Pandolfi, S, Pennoni, F, Bartolucci, F, and Pandolfi, S
Abstract: We propose a variable selection method for multivariate hidden Markov models with continuous responses that are partially or completely missing at a given time occasion. Through this procedure, we achieve a dimensionality reduction by selecting the subset of the most informative responses for clustering individuals and simultaneously choosing the optimal number of these clusters corresponding to latent states. The approach is based on comparing different model specifications in terms of the subset of responses assumed to be dependent on the latent states, and it relies on a greedy search algorithm based on the Bayesian information criterion seen as an approximation of the Bayes factor. A suitable expectation-maximization algorithm is employed to obtain maximum likelihood estimates of the model parameters under the missing-at-random assumption. The proposal is illustrated via Monte Carlo simulation and an application where development indicators collected over eighteen years are selected, and countries are clustered into groups to evaluate their growth over time.
Published: 2024

9. Evolution of the fine-structure constant in runaway dilaton models

Author: Martins, C. J. A. P., Vielzeuf, P. E., Martinelli, M., Calabrese, E., and Pandolfi, S.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract: We study the detailed evolution of the fine-structure constant $\alpha$ in the string-inspired runaway dilaton class of models of Damour, Piazza and Veneziano. We provide constraints on this scenario using the most recent $\alpha$ measurements and discuss ways to distinguish it from alternative models for varying $\alpha$. For model parameters which saturate bounds from current observations, the redshift drift signal can differ considerably from that of the canonical $\Lambda$CDM paradigm at high redshifts. Measurements of this signal by the forthcoming European Extremely Large Telescope (E-ELT), together with more sensitive $\alpha$ measurements, will thus dramatically constrain these scenarios., Comment: 11 pages, 4 figures
Published: 2015
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10. Planck 2015 results. XX. Constraints on inflation

Author: Planck Collaboration, Ade, P. A. R., Aghanim, N., Arnaud, M., Arroja, F., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., Banday, A. J., Barreiro, R. B., Bartolo, N., Battaner, E., Benabed, K., Benoit, A., Benoit-Levy, A., Bernard, J. -P., Bersanelli, M., Bielewicz, P., Bock, J. J., Bonaldi, A., Bonavera, L., Bond, J. R., Borrill, J., Bouchet, F. R., Boulanger, F., Bucher, M., Burigana, C., Butler, R. C., Calabrese, E., Cardoso, J. -F., Catalano, A., Challinor, A., Chamballu, A., Chary, R. -R., Chiang, H. C., Christensen, P. R., Church, S., Clements, D. L., Colombi, S., Colombo, L. P. L., Combet, C., Contreras, D., Couchot, F., Coulais, A., Crill, B. P., Curto, A., Cuttaia, F., Danese, L., Davies, R. D., Davis, R. J., de Bernardis, P., de Rosa, A., de Zotti, G., Delabrouille, J., Desert, F. -X., Diego, J. M., Dole, H., Donzelli, S., Dore, O., Douspis, M., Ducout, A., Dupac, X., Efstathiou, G., Elsner, F., Ensslin, T. A., Eriksen, H. K., Fergusson, J., Finelli, F., Forni, O., Frailis, M., Fraisse, A. A., Franceschi, E., Frejsel, A., Frolov, A., Galeotta, S., Galli, S., Ganga, K., Gauthier, C., Giard, M., Giraud-Heraud, Y., Gjerlow, E., Gonzalez-Nuevo, J., Gorski, K. M., Gratton, S., Gregorio, A., Gruppuso, A., Gudmundsson, J. E., Hamann, J., Handley, W., Hansen, F. K., Hanson, D., Harrison, D. L., Henrot-Versille, S., Hernandez-Monteagudo, C., Herranz, D., Hildebrandt, S. R., Hivon, E., Hobson, M., Holmes, W. A., Hornstrup, A., Hovest, W., Huang, Z., Huffenberger, K. M., Hurier, G., Jaffe, A. H., Jaffe, T. R., Jones, W. C., Juvela, M., Keihanen, E., Keskitalo, R., Kim, J., Kisner, T. S., Kneissl, R., Knoche, J., Kunz, M., Kurki-Suonio, H., Lagache, G., Lahteenmaki, A., Lamarre, J. -M., Lasenby, A., Lattanzi, M., Lawrence, C. R., Leonardi, R., Lesgourgues, J., Levrier, F., Lewis, A., Liguori, M., Lilje, P. B., Linden-Vornle, M., Lopez-Caniego, M., Lubin, P. M., Ma, Y. -Z., Macias-Perez, J. F., Maggio, G., Maino, D., Mandolesi, N., Mangilli, A., Maris, M., Martin, P. G., Martinez-Gonzalez, E., Masi, S., Matarrese, S., McGehee, P., Meinhold, P. R., Melchiorri, A., Mendes, L., Mennella, A., Migliaccio, M., Mitra, S., Miville-Deschenes, M. -A., Molinari, D., Moneti, A., Montier, L., Morgante, G., Mortlock, D., Moss, A., Munchmeyer, M., Munshi, D., Murphy, J. A., Naselsky, P., Nati, F., Natoli, P., Netterfield, C. B., Norgaard-Nielsen, H. U., Noviello, F., Novikov, D., Novikov, I., Oxborrow, C. A., Paci, F., Pagano, L., Pajot, F., Paladini, R., Pandolfi, S., Paoletti, D., Pasian, F., Patanchon, G., Pearson, T. J., Peiris, H. V., Perdereau, O., Perotto, L., Perrotta, F., Pettorino, V., Piacentini, F., Piat, M., Pierpaoli, E., Pietrobon, D., Plaszczynski, S., Pointecouteau, E., Polenta, G., Popa, L., Pratt, G. W., Prezeau, G., Prunet, S., Puget, J. -L., Rachen, J. P., Reach, W. T., Rebolo, R., Reinecke, M., Remazeilles, M., Renault, C., Renzi, A., Ristorcelli, I., Rocha, G., Rosset, C., Rossetti, M., Roudier, G., Rowan-Robinson, M., Rubino-Martin, J. A., Rusholme, B., Sandri, M., Santos, D., Savelainen, M., Savini, G., Scott, D., Seiffert, M. D., Shellard, E. P. S., Shiraishi, M., Spencer, L. D., Stolyarov, V., Stompor, R., Sudiwala, R., Sunyaev, R., Sutton, D., Suur-Uski, A. -S., Sygnet, J. -F., Tauber, J. A., Terenzi, L., Toffolatti, L., Tomasi, M., Tristram, M., Trombetti, T., Tucci, M., Tuovinen, J., Valenziano, L., Valiviita, J., Van Tent, B., Vielva, P., Villa, F., Wade, L. A., Wandelt, B. D., Wehus, I. K., White, M., Yvon, D., Zacchei, A., Zibin, J. P., and Zonca, A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present the implications for cosmic inflation of the Planck measurements of the cosmic microwave background (CMB) anisotropies in both temperature and polarization based on the full Planck survey. The Planck full mission temperature data and a first release of polarization data on large angular scales measure the spectral index of curvature perturbations to be $n_\mathrm{s} = 0.968 \pm 0.006$ and tightly constrain its scale dependence to $d n_s/d \ln k =-0.003 \pm 0.007$ when combined with the Planck lensing likelihood. When the high-$\ell$ polarization data is included, the results are consistent and uncertainties are reduced. The upper bound on the tensor-to-scalar ratio is $r_{0.002} < 0.11$ (95% CL), consistent with the B-mode polarization constraint $r< 0.12$ (95% CL) obtained from a joint BICEP2/Keck Array and Planck analysis. These results imply that $V(\phi) \propto \phi^2$ and natural inflation are now disfavoured compared to models predicting a smaller tensor-to-scalar ratio, such as $R^2$ inflation. Three independent methods reconstructing the primordial power spectrum are investigated. The Planck data are consistent with adiabatic primordial perturbations. We investigate inflationary models producing an anisotropic modulation of the primordial curvature power spectrum as well as generalized models of inflation not governed by a scalar field with a canonical kinetic term. The 2015 results are consistent with the 2013 analysis based on the nominal mission data., Comment: 68 pages, 59 figures, 18 tables; updates to match the published version
Published: 2015
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11. Planck 2015 results. I. Overview of products and scientific results

Author: Planck Collaboration, Adam, R., Ade, P. A. R., Aghanim, N., Akrami, Y., Alves, M. I. R., Arnaud, M., Arroja, F., Aumont, J., Baccigalupi, C., Ballardini, M., Banday, A. J., Barreiro, R. B., Bartlett, J. G., Bartolo, N., Basak, S., Battaglia, P., Battaner, E., Battye, R., Benabed, K., Benoît, A., Benoit-Lévy, A., Bernard, J. -P., Bersanelli, M., Bertincourt, B., Bielewicz, P., Bonaldi, A., Bonavera, L., Bond, J. R., Borrill, J., Bouchet, F. R., Boulanger, F., Bucher, M., Burigana, C., Butler, R. C., Calabrese, E., Cardoso, J. -F., Carvalho, P., Casaponsa, B., Castex, G., Catalano, A., Challinor, A., Chamballu, A., Chary, R. -R., Chiang, H. C., Chluba, J., Christensen, P. R., Church, S., Clemens, M., Clements, D. L., Colombi, S., Colombo, L. P. L., Combet, C., Comis, B., Contreras, D., Couchot, F., Coulais, A., Crill, B. P., Cruz, M., Curto, A., Cuttaia, F., Danese, L., Davies, R. D., Davis, R. J., de Bernardis, P., de Rosa, A., de Zotti, G., Delabrouille, J., Delouis, J. -M., Désert, F. -X., Di Valentino, E., Dickinson, C., Diego, J. M., Dolag, K., Dole, H., Donzelli, S., Doré, O., Douspis, M., Ducout, A., Dunkley, J., Dupac, X., Efstathiou, G., Eisenhardt, P. R. M., Elsner, F., Enßlin, T. A., Eriksen, H. K., Falgarone, E., Fantaye, Y., Farhang, M., Feeney, S., Fergusson, J., Fernandez-Cobos, R., Feroz, F., Finelli, F., Florido, E., Forni, O., Frailis, M., Fraisse, A. A., Franceschet, C., Franceschi, E., Frejsel, A., Frolov, A., Galeotta, S., Galli, S., Ganga, K., Gauthier, C., Génova-Santos, R. T., Gerbino, M., Ghosh, T., Giard, M., Giraud-Héraud, Y., Giusarma, E., Gjerløw, E., González-Nuevo, J., Górski, K. M., Grainge, K. J. B., Gratton, S., Gregorio, A., Gruppuso, A., Gudmundsson, J. E., Hamann, J., Handley, W., Hansen, F. K., Hanson, D., Harrison, D. L., Heavens, A., Helou, G., Henrot-Versillé, S., Hernández-Monteagudo, C., Herranz, D., Hildebrandt, S. R., Hivon, E., Hobson, M., Holmes, W. A., Hornstrup, A., Hovest, W., Huang, Z., Huffenberger, K. M., Hurier, G., Ilić, S., Jaffe, A. H., Jaffe, T. R., Jin, T., Jones, W. C., Juvela, M., Karakci, A., Keihänen, E., Keskitalo, R., Kiiveri, K., Kim, J., Kisner, T. S., Kneissl, R., Knoche, J., Krachmalnicoff, N., Kunz, M., Kurki-Suonio, H., Lacasa, F., Lagache, G., Lähteenmäki, A., Lamarre, J. -M., Langer, M., Lasenby, A., Lattanzi, M., Lawrence, C. R., Jeune, M. Le, Leahy, J. P., Lellouch, E., Leonardi, R., León-Tavares, J., Lesgourgues, J., Levrier, F., Lewis, A., Liguori, M., Lilje, P. B., Linden-Vørnle, M., Lindholm, V., Liu, H., López-Caniego, M., Lubin, P. M., Ma, Y. -Z., Macías-Pérez, J. F., Maggio, G., Mak, D. S. Y., Mandolesi, N., Mangilli, A., Marchini, A., Marcos-Caballero, A., Marinucci, D., Marshall, D. J., Martin, P. G., Martinelli, M., Martínez-González, E., Masi, S., Matarrese, S., Mazzotta, P., McEwen, J. D., McGehee, P., Mei, S., Meinhold, P. R., Melchiorri, A., Melin, J. -B., Mendes, L., Mennella, A., Migliaccio, M., Mikkelsen, K., Mitra, S., Miville-Deschênes, M. -A., Molinari, D., Moneti, A., Montier, L., Moreno, R., Morgante, G., Mortlock, D., Moss, A., Mottet, S., Müenchmeyer, M., Munshi, D., Murphy, J. A., Narimani, A., Naselsky, P., Nastasi, A., Nati, F., Natoli, P., Negrello, M., Netterfield, C. B., Nørgaard-Nielsen, H. U., Noviello, F., Novikov, D., Novikov, I., Olamaie, M., Oppermann, N., Orlando, E., Oxborrow, C. A., Paci, F., Pagano, L., Pajot, F., Paladini, R., Pandolfi, S., Paoletti, D., Partridge, B., Pasian, F., Patanchon, G., Pearson, T. J., Peel, M., Peiris, H. V., Pelkonen, V. -M., Perdereau, O., Perotto, L., Perrott, Y. C., Perrotta, F., Pettorino, V., Piacentini, F., Piat, M., Pierpaoli, E., Pietrobon, D., Plaszczynski, S., Pogosyan, D., Pointecouteau, E., Polenta, G., Popa, L., Pratt, G. W., Prézeau, G., Prunet, S., Puget, J. -L., Rachen, J. P., Racine, B., Reach, W. T., Rebolo, R., Reinecke, M., Remazeilles, M., Renault, C., Renzi, A., Ristorcelli, I., Rocha, G., Roman, M., Romelli, E., Rosset, C., Rossetti, M., Rotti, A., Roudier, G., d'Orfeuil, B. Rouillé, Rowan-Robinson, M., Rubiño-Martín, J. A., Ruiz-Granados, B., Rumsey, C., Rusholme, B., Said, N., Salvatelli, V., Salvati, L., Sandri, M., Sanghera, H. S., Santos, D., Saunders, R. D. E., Sauvé, A., Savelainen, M., Savini, G., Schaefer, B. M., Schammel, M. P., Scott, D., Seiffert, M. D., Serra, P., Shellard, E. P. S., Shimwell, T. W., Shiraishi, M., Smith, K., Souradeep, T., Spencer, L. D., Spinelli, M., Stanford, S. A., Stern, D., Stolyarov, V., Stompor, R., Strong, A. W., Sudiwala, R., Sunyaev, R., Sutter, P., Sutton, D., Suur-Uski, A. -S., Sygnet, J. -F., Tauber, J. A., Tavagnacco, D., Terenzi, L., Texier, D., Toffolatti, L., Tomasi, M., Tornikoski, M., Tristram, M., Troja, A., Trombetti, T., Tucci, M., Tuovinen, J., Türler, M., Umana, G., Valenziano, L., Valiviita, J., Van Tent, B., Vassallo, T., Vidal, M., Viel, M., Vielva, P., Villa, F., Wade, L. A., Walter, B., Wandelt, B. D., Watson, R., Wehus, I. K., Welikala, N., Weller, J., White, M., White, S. D. M., Wilkinson, A., Yvon, D., Zacchei, A., Zibin, J. P., and Zonca, A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The European Space Agency's Planck satellite, dedicated to studying the early Universe and its subsequent evolution, was launched 14~May 2009 and scanned the microwave and submillimetre sky continuously between 12~August 2009 and 23~October 2013. In February~2015, ESA and the Planck Collaboration released the second set of cosmology products based on data from the entire Planck mission, including both temperature and polarization, along with a set of scientific and technical papers and a web-based explanatory supplement. This paper gives an overview of the main characteristics of the data and the data products in the release, as well as the associated cosmological and astrophysical science results and papers. The science products include maps of the cosmic microwave background (CMB), the thermal Sunyaev-Zeldovich effect, and diffuse foregrounds in temperature and polarization, catalogues of compact Galactic and extragalactic sources (including separate catalogues of Sunyaev-Zeldovich clusters and Galactic cold clumps), and extensive simulations of signals and noise used in assessing the performance of the analysis methods and assessment of uncertainties. The likelihood code used to assess cosmological models against the Planck data are described, as well as a CMB lensing likelihood. Scientific results include cosmological parameters deriving from CMB power spectra, gravitational lensing, and cluster counts, as well as constraints on inflation, non-Gaussianity, primordial magnetic fields, dark energy, and modified gravity., Comment: 40 pages, 24 figures
Published: 2015
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12. Reionization and CMB non-Gaussianity

Author: Munshi, D., Corasaniti, P. S., Coles, P., Heavens, A., and Pandolfi, S.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We show how cross-correlating a high redshift external tracer field, such as the 21cm neutral hydrogen distribution and product maps involving Cosmic Microwave Background (CMB) temperature and polarisation fields, that probe mixed bispectrum involving these fields, can help to determine the reionization history of the Universe, beyond what can be achieved from cross-spectrum analysis. Taking clues from recent studies for the detection of primordial non-Gaussianity (Munshi & Heavens 2010), we develop a set of estimators that can study reionization using a power spectrum associated with the bispectrum (or skew-spectrum). We use the matched filtering inherent in this method to investigate different reionization histories. We check to what extent they can be used to rule out various models of reionization and study cross contamination from different sources such as the lensing of the CMB. The estimators can be fine-tuned to optimize study of a specific reionization history. We consider three different types of tracers in our study, namely: proto-galaxies; 21cm maps of neutral hydrogen; quasars. We also consider four alternative models of reionization. We find that the cumulative signal-to-noise (S/N) for detection at $\ell_{max}=2000$ can reach $\mathcal{O}(70)$ for cosmic variance limited all-sky experiments. Combining 100GHz, 143GHz and 217GHz channels of the Planck experiment, we find that the (S/N) lies in the range $\mathcal{O}(5)-\mathcal{O}(35)$. The (S/N) depends on the specific choice of a tracer field, and multiple tracers can be effectively used to map out the entire reionization history with reasonable S/N. Contamination from weak lensing is investigated and found to be negligible, and the effects of Thomson scattering from patchy reionizationare also considered., Comment: 16 pages, 8 figures; MNRAS in press
Published: 2014
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13. Mutations in LZTR1 drive human disease by dysregulating RAS ubiquitination

Author: Steklov, M., Pandolfi, S., Baietti, M. F., Batiuk, A., Carai, P., Najm, P., Zhang, M., Jang, H., Renzi, F., Cai, Y., Asbagh, L. Abbasi, Pastor, T., De Troyer, M., Simicek, M., Radaelli, E., Brems, H., Legius, E., Tavernier, J., Gevaert, K., Impens, F., Messiaen, L., Nussinov, R., Heymans, S., Eyckerman, S., and Sablina, A. A.
Published: 2018

14. Maximum likelihood inference for hidden Markov models with parsimonious parametrizations of transition matrices

Author: Pandolfi, S, Bartolucci, F, Pennoni, F, Pandolfi, S., Bartolucci, F., Pennoni, F., Pandolfi, S, Bartolucci, F, Pennoni, F, Pandolfi, S., Bartolucci, F., and Pennoni, F.
Abstract: In longitudinal data analysis, hidden Markov (HM) models are fundamental tools, especially when the analysis is focused on transitions or the need to cluster individuals dynamically. When individual covariates are available in the dataset, a typical problem is how to parametrize the transition probabilities based on these covariates in a parsimonious way. In fact, standard multinomial parametrizations of these probabilities lead to models with many parameters, which are also difficult to interpret and, consequently, to unstable parameter estimates. To overcome the above problems, different parametrizations of the transition probabilities of HM models with covariates are introduced based on multinomial logit models formulated by two different choices of the reference state of each logit. These parametrizations rely on constraints having a straightforward interpretation, making the model much more parsimonious. Estimation based on the maximum likelihood (ML) approach is developed under different constraints based on the Expectation-Maximization algorithm. Steps of Newton-Raphson type are also included to improve the algorithm’s convergence speed
Published: 2023

15. Dark Energy coupling with electromagnetism as seen from future low-medium redshift probes

Author: Calabrese, E., Martinelli, M., Pandolfi, S., Cardone, V. F., Martins, C. J. A. P., Spiro, S., and Vielzeuf, P. E.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Beyond the standard cosmological model the late-time accelerated expansion of the universe can be reproduced by the introduction of an additional dynamical scalar field. In this case, the field is expected to be naturally coupled to the rest of the theory's fields, unless a (still unknown) symmetry suppresses this coupling. Therefore, this would possibly lead to some observational consequences, such as space-time variations of nature's fundamental constants. In this paper we investigate the coupling between a dynamical Dark Energy model and the electromagnetic field, and the corresponding evolution of the fine structure constant ($\alpha$) with respect to the standard local value $\alpha_0$. In particular, we derive joint constraints on two dynamical Dark Energy model parametrizations (the Chevallier-Polarski-Linder and Early Dark Energy model) and on the coupling with electromagnetism $\zeta$, forecasting future low-medium redshift observations. We combine supernovae and weak lensing measurements from the Euclid experiment with high-resolution spectroscopy measurements of fundamental couplings and the redshift drift from the European Extremely Large Telescope, highlighting the contribution of each probe. Moreover, we also consider the case where the field driving the $\alpha$ evolution is not the one responsible for cosmic acceleration and investigate how future observations can constrain this scenario., Comment: 15 pages, 12 figures
Published: 2013
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16. Planck 2013 results. I. Overview of products and scientific results

Author: Planck Collaboration, Ade, P. A. R., Aghanim, N., Alves, M. I. R., Armitage-Caplan, C., Arnaud, M., Ashdown, M., Atrio-Barandela, F., Aumont, J., Aussel, H., Baccigalupi, C., Banday, A. J., Barreiro, R. B., Barrena, R., Bartelmann, M., Bartlett, J. G., Bartolo, N., Basak, S., Battaner, E., Battye, R., Benabed, K., Benoît, A., Benoit-Lévy, A., Bernard, J. -P., Bersanelli, M., Bertincourt, B., Bethermin, M., Bielewicz, P., Bikmaev, I., Blanchard, A., Bobin, J., Bock, J. J., Böhringer, H., Bonaldi, A., Bonavera, L., Bond, J. R., Borrill, J., Bouchet, F. R., Boulanger, F., Bourdin, H., Bowyer, J. W., Bridges, M., Brown, M. L., Bucher, M., Burenin, R., Burigana, C., Butler, R. C., Calabrese, E., Cappellini, B., Cardoso, J. -F., Carr, R., Carvalho, P., Casale, M., Castex, G., Catalano, A., Challinor, A., Chamballu, A., Chary, R. -R., Chen, X., Chiang, H. C., Chiang, L. -Y, Chon, G., Christensen, P. R., Churazov, E., Church, S., Clemens, M., Clements, D. L., Colombi, S., Colombo, L. P. L., Combet, C., Comis, B., Couchot, F., Coulais, A., Crill, B. P., Cruz, M., Curto, A., Cuttaia, F., Da Silva, A., Dahle, H., Danese, L., Davies, R. D., Davis, R. J., de Bernardis, P., de Rosa, A., de Zotti, G., Déchelette, T., Delabrouille, J., Delouis, J. -M., Démoclès, J., Désert, F. -X., Dick, J., Dickinson, C., Diego, J. M., Dolag, K., Dole, H., Donzelli, S., Doré, O., Douspis, M., Ducout, A., Dunkley, J., Dupac, X., Efstathiou, G., Elsner, F., Enßlin, T. A., Eriksen, H. K., Fabre, O., Falgarone, E., Falvella, M. C., Fantaye, Y., Fergusson, J., Filliard, C., Finelli, F., Flores-Cacho, I., Foley, S., Forni, O., Fosalba, P., Frailis, M., Fraisse, A. A., Franceschi, E., Freschi, M., Fromenteau, S., Frommert, M., Gaier, T. C., Galeotta, S., Gallegos, J., Galli, S., Gandolfo, B., Ganga, K., Gauthier, C., Génova-Santos, R. T., Ghosh, T., Giard, M., Giardino, G., Gilfanov, M., Girard, D., Giraud-Héraud, Y., Gjerløw, E., González-Nuevo, J., Górski, K. M., Gratton, S., Gregorio, A., Gruppuso, A., Gudmundsson, J. E., Haissinski, J., Hamann, J., Hansen, F. K., Hansen, M., Hanson, D., Harrison, D. L., Heavens, A., Helou, G., Hempel, A., Henrot-Versillé, S., Hernández-Monteagudo, C., Herranz, D., Hildebrandt, S. R., Hivon, E., Ho, S., Hobson, M., Holmes, W. A., Hornstrup, A., Hou, Z., Hovest, W., Huey, G., Huffenberger, K. M., Hurier, G., Ilić, S., Jaffe, A. H., Jaffe, T. R., Jasche, J., Jewell, J., Jones, W. C., Juvela, M., Kalberla, P., Kangaslahti, P., Keihänen, E., Kerp, J., Keskitalo, R., Khamitov, I., Kiiveri, K., Kim, J., Kisner, T. S., Kneissl, R., Knoche, J., Knox, L., Kunz, M., Kurki-Suonio, H., Lacasa, F., Lagache, G., Lähteenmäki, A., Lamarre, J. -M., Langer, M., Lasenby, A., Lattanzi, M., Laureijs, R. J., Lavabre, A., Lawrence, C. R., Jeune, M. Le, Leach, S., Leahy, J. P., Leonardi, R., León-Tavares, J., Leroy, C., Lesgourgues, J., Lewis, A., Li, C., Liddle, A., Liguori, M., Lilje, P. B., Linden-Vørnle, M., Lindholm, V., López-Caniego, M., Lowe, S., Lubin, P. M., Macías-Pérez, J. F., MacTavish, C. J., Maffei, B., Maggio, G., Maino, D., Mandolesi, N., Mangilli, A., Marcos-Caballero, A., Marinucci, D., Maris, M., Marleau, F., Marshall, D. J., Martin, P. G., Martínez-González, E., Masi, S., Massardi, M., Matarrese, S., Matsumura, T., Matthai, F., Maurin, L., Mazzotta, P., McDonald, A., McEwen, J. D., McGehee, P., Mei, S., Meinhold, P. R., Melchiorri, A., Melin, J. -B., Mendes, L., Menegoni, E., Mennella, A., Migliaccio, M., Mikkelsen, K., Millea, M., Miniscalco, R., Mitra, S., Miville-Deschênes, M. -A., Molinari, D., Moneti, A., Montier, L., Morgante, G., Morisset, N., Mortlock, D., Moss, A., Munshi, D., Murphy, J. A., Naselsky, P., Nati, F., Natoli, P., Negrello, M., Nesvadba, N. P. H., Netterfield, C. B., Nørgaard-Nielsen, H. U., North, C., Noviello, F., Novikov, D., Novikov, I., O'Dwyer, I. J., Orieux, F., Osborne, S., O'Sullivan, C., Oxborrow, C. A., Paci, F., Pagano, L., Pajot, F., Paladini, R., Pandolfi, S., Paoletti, D., Partridge, B., Pasian, F., Patanchon, G., Paykari, P., Pearson, D., Pearson, T. J., Peel, M., Peiris, H. V., Perdereau, O., Perotto, L., Perrotta, F., Pettorino, V., Piacentini, F., Piat, M., Pierpaoli, E., Pietrobon, D., Plaszczynski, S., Platania, P., Pogosyan, D., Pointecouteau, E., Polenta, G., Ponthieu, N., Popa, L., Poutanen, T., Pratt, G. W., Prézeau, G., Prunet, S., Puget, J. -L., Pullen, A. R., Rachen, J. P., Racine, B., Rahlin, A., Räth, C., Reach, W. T., Rebolo, R., Reinecke, M., Remazeilles, M., Renault, C., Renzi, A., Riazuelo, A., Ricciardi, S., Riller, T., Ringeval, C., Ristorcelli, I., Robbers, G., Rocha, G., Roman, M., Rosset, C., Rossetti, M., Roudier, G., Rowan-Robinson, M., Rubiño-Martín, J. A., Ruiz-Granados, B., Rusholme, B., Salerno, E., Sandri, M., Sanselme, L., Santos, D., Savelainen, M., Savini, G., Schaefer, B. M., Schiavon, F., Scott, D., Seiffert, M. D., Serra, P., Shellard, E. P. S., Smith, K., Smoot, G. F., Souradeep, T., Spencer, L. D., Starck, J. -L., Stolyarov, V., Stompor, R., Sudiwala, R., Sunyaev, R., Sureau, F., Sutter, P., Sutton, D., Suur-Uski, A. -S., Sygnet, J. -F., Tauber, J. A., Tavagnacco, D., Taylor, D., Terenzi, L., Texier, D., Toffolatti, L., Tomasi, M., Torre, J. -P., Tristram, M., Tucci, M., Tuovinen, J., Türler, M., Tuttlebee, M., Umana, G., Valenziano, L., Valiviita, J., Van Tent, B., Varis, J., Vibert, L., Viel, M., Vielva, P., Villa, F., Vittorio, N., Wade, L. A., Wandelt, B. D., Watson, C., Watson, R., Wehus, I. K., Welikala, N., Weller, J., White, M., White, S. D. M., Wilkinson, A., Winkel, B., Xia, J. -Q., Yvon, D., Zacchei, A., Zibin, J. P., and Zonca, A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The ESA's Planck satellite, dedicated to studying the early Universe and its subsequent evolution, was launched 14 May 2009 and has been scanning the microwave and submillimetre sky continuously since 12 August 2009. This paper gives an overview of the mission and its performance, the processing, analysis, and characteristics of the data, the scientific results, and the science data products and papers in the release. The science products include maps of the CMB and diffuse extragalactic foregrounds, a catalogue of compact Galactic and extragalactic sources, and a list of sources detected through the SZ effect. The likelihood code used to assess cosmological models against the Planck data and a lensing likelihood are described. Scientific results include robust support for the standard six-parameter LCDM model of cosmology and improved measurements of its parameters, including a highly significant deviation from scale invariance of the primordial power spectrum. The Planck values for these parameters and others derived from them are significantly different from those previously determined. Several large-scale anomalies in the temperature distribution of the CMB, first detected by WMAP, are confirmed with higher confidence. Planck sets new limits on the number and mass of neutrinos, and has measured gravitational lensing of CMB anisotropies at greater than 25 sigma. Planck finds no evidence for non-Gaussianity in the CMB. Planck's results agree well with results from the measurements of baryon acoustic oscillations. Planck finds a lower Hubble constant than found in some more local measures. Some tension is also present between the amplitude of matter fluctuations derived from CMB data and that derived from SZ data. The Planck and WMAP power spectra are offset from each other by an average level of about 2% around the first acoustic peak.
Published: 2013
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17. Planck 2013 results. XXII. Constraints on inflation

Author: Planck Collaboration, Ade, P. A. R., Aghanim, N., Armitage-Caplan, C., Arnaud, M., Ashdown, M., Atrio-Barandela, F., Aumont, J., Baccigalupi, C., Banday, A. J., Barreiro, R. B., Bartlett, J. G., Bartolo, N., Battaner, E., Benabed, K., Benoit, A., Benoit-Levy, A., Bernard, J. -P., Bersanelli, M., Bielewicz, P., Bobin, J., Bock, J. J., Bonaldi, A., Bond, J. R., Borrill, J., Bouchet, F. R., Bridges, M., Bucher, M., Burigana, C., Butler, R. C., Calabrese, E., Cardoso, J. -F., Catalano, A., Challinor, A., Chamballu, A., Chiang, H. C., Chiang, L. -Y, Christensen, P. R., Church, S., Clements, D. L., Colombi, S., Colombo, L. P. L., Couchot, F., Coulais, A., Crill, B. P., Curto, A., Cuttaia, F., Danese, L., Davies, R. D., Davis, R. J., de Bernardis, P., de Rosa, A., de Zotti, G., Delabrouille, J., Delouis, J. -M., Desert, F. -X., Dickinson, C., Diego, J. M., Dole, H., Donzelli, S., Dore, O., Douspis, M., Dunkley, J., Dupac, X., Efstathiou, G., Ensslin, T. A., Eriksen, H. K., Finelli, F., Forni, O., Frailis, M., Franceschi, E., Galeotta, S., Ganga, K., Gauthier, C., Giard, M., Giardino, G., Giraud-Hiraud, Y., Gonzalez-Nuevo, J., Gorski, K. M., Gratton, S., Gregorio, A., Gruppuso, A., Hamann, J., Hansen, F. K., Hanson, D., Harrison, D., Henrot-Versille, S., Hernandez-Monteagudo, C., Herranz, D., Hildebrandt, S. R., Hivon, E., Hobson, M., Holmes, W. A., Hornstrup, A., Hovest, W., Huffenberger, K. M., Jaffe, A. H., Jaffe, T. R., Jones, W. C., Juvela, M., Keihanen, E., Keskitalo, R., Kisner, T. S., Kneissl, R., Knoche, J., Knox, L., Kunz, M., Kurki-Suonio, H., Lagache, G., Lahteenmaki, A., Lamarre, J. -M., Lasenby, A., Laureijs, R. J., Lawrence, C. R., Leach, S., Leahy, J. P., Leonardi, R., Lesgourgues, J., Lewis, A., Liguori, M., Lilje, P. B., Linden-Vernle, M., Lopez-Caniego, M., Lubin, P. M., Macias-Perez, J. F., Maffei, B., Maino, D., Mandolesi, N., Maris, M., Marshall, D. J., Martin, P. G., Martinez-Gonzalez, E., Masi, S., Massardi, M., Matarrese, S., Matthai, F., Mazzotta, P., Meinhold, P. R., Melchiorri, A., Mendes, L., Mennella, A., Migliaccio, M., Mitra, S., Miville-Deschenes, M. -A., Moneti, A., Montier, L., Morgante, G., Mortlock, D., Moss, A., Munshi, D., Murphy, J. A., Naselsky, P., Nati, F., Natoli, P., Netterfield, C. B., Norgaard-Nielsen, H. U., Noviello, F., Novikov, D., Novikov, I., O'Dwyer, I. J., Osborne, S., Oxborrow, C. A., Paci, F., Pagano, L., Pajot, F., Paladini, R., Pandolfi, S., Paoletti, D., Partridge, B., Pasian, F., Patanchon, G., Peiris, H. V., Perdereau, O., Perotto, L., Perrotta, F., Piacentini, F., Piat, M., Pierpaoli, E., Pietrobon, D., Plaszczynski, S., Pointecouteau, E., Polenta, G., Ponthieu, N., Popa, L., Poutanen, T., Pratt, G. W., Prezeau, G., Prunet, S., Puget, J. -L., Rachen, J. P., Rebolo, R., Reinecke, M., Remazeilles, M., Renault, C., Ricciardi, S., Riller, T., Ristorcelli, I., Rocha, G., Rosset, C., Roudier, G., Rowan-Robinson, M., Rubino-Martin, J. A., Rusholme, B., Sandri, M., Santos, D., Savelainen, M., Savini, G., Scott, D., Seiffert, M. D., Shellard, E. P. S., Spencer, L. D., Starck, J. -L., Stolyarov, V., Stompor, R., Sudiwala, R., Sunyaev, R., Sureau, F., Sutton, D., Suur-Uski, A. -S., Sygnet, J. -F., Tauber, J. A., Tavagnacco, D., Terenzi, L., Toffolatti, L., Tomasi, M., Treguer-Goudineau, J., Tristram, M., Tucci, M., Tuovinen, J., Valenziano, L., Valiviita, J., Van Tent, B., Varis, J., Vielva, P., Villa, F., Vittorio, N., Wade, L. A., Wandelt, B. D., White, M., Wilkinson, A., Yvon, D., Zacchei, A., Zibin, J. P., and Zonca, A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We analyse the implications of the Planck data for cosmic inflation. The Planck nominal mission temperature anisotropy measurements, combined with the WMAP large-angle polarization, constrain the scalar spectral index to $n_s = 0.9603 \pm 0.0073$, ruling out exact scale invariance at over 5 $\sigma$. Planck establishes an upper bound on the tensor-to-scalar ratio of r < 0.11 (95% CL). The Planck data thus shrink the space of allowed standard inflationary models, preferring potentials with V" < 0. Exponential potential models, the simplest hybrid inflationary models, and monomial potential models of degree n > 2 do not provide a good fit to the data. Planck does not find statistically significant running of the scalar spectral index, obtaining $d n_s/d ln k = -0.0134 \pm 0.0090$. Several analyses dropping the slow-roll approximation are carried out, including detailed model comparison and inflationary potential reconstruction. We also investigate whether the primordial power spectrum contains any features. We find that models with a parameterized oscillatory feature improve the fit $\chi^2$ by ~ 10; however, Bayesian evidence does not prefer these models. We constrain several single-field inflation models with generalized Lagrangians by combining power spectrum data with bounds on $f_\mathrm{NL}$ measured by Planck. The fractional primordial contribution of CDM isocurvature modes in the curvaton and axion scenarios has upper bounds of 0.25% or 3.9% (95% CL), respectively. In models with arbitrarily correlated CDM or neutrino isocurvature modes, an anticorrelation can improve $\chi^2$ by approximatively 4 as a result of slightly lowering the theoretical prediction for the $\ell<40$ multipoles relative to the higher multipoles. Nonetheless, the data are consistent with adiabatic initial conditions., Comment: 44 pages, 25 figures, 12 tables; updated version; small changes to match the published version
Published: 2013
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18. A generalized Multiple-try Metropolis version of the Reversible Jump algorithm

Author: Pandolfi, S., Bartolucci, F., and Friel, N.
Subjects: Statistics - Methodology
Abstract: The Reversible Jump algorithm is one of the most widely used Markov chain Monte Carlo algorithms for Bayesian estimation and model selection. A generalized multiple-try version of this algorithm is proposed. The algorithm is based on drawing several proposals at each step and randomly choosing one of them on the basis of weights (selection probabilities) that may be arbitrary chosen. Among the possible choices, a method is employed which is based on selection probabilities depending on a quadratic approximation of the posterior distribution. Moreover, the implementation of the proposed algorithm for challenging model selection problems, in which the quadratic approximation is not feasible, is considered. The resulting algorithm leads to a gain in efficiency with respect to the Reversible Jump algorithm, and also in terms of computational effort. The performance of this approach is illustrated for real examples involving a logistic regression model and a latent class model.
Published: 2010

19. Harrison-Z'eldovich primordial spectrum is consistent with observations

Author: Pandolfi, S., Cooray, A., Giusarma, E., Kolb, E. W., Melchiorri, A., Mena, O., and Serra, P.
Subjects: Astrophysics - Cosmology and Extragalactic Astrophysics, Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology
Abstract: Inflation predicts primordial scalar perturbations with a nearly scale-invariant spectrum and a spectral index approximately unity (the Harrison--Zel'dovich (HZ) spectrum). The first important step for inflationary cosmology is to check the consistency of the HZ primordial spectrum with current observations. Recent analyses have claimed that a HZ primordial spectrum is excluded at more than 99% c.l.. Here we show that the HZ spectrum is only marginally disfavored if one considers a more general reionization scenario. Data from the Planck mission will settle the issue., Comment: 4 Pages, 2 Figures
Published: 2010
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20. Crystal structure, optical bandgap, P–V–T equation of state and high-pressure in situ XRD synthesis of Zintl clathrate Na8B8Si38

Author: Courac (Kurakevych), A., primary, Demoucron, M., additional, Pandolfi, S., additional, Strobel, T. A., additional, Mezouar, M., additional, and Le Godec, Y., additional
Published: 2023
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21. Oxygen-ozone autohemotherapy in breast cancer patients suffering from fatigue and musculoskeletal pain upon aromatase inhibitors treatment: a case-series study.

Author: TIRELLI, U., VALDENASSI, L., FRANZINI, M., PANDOLFI, S., FISICHELLA, R., and CHIRUMBOLO, S.
Abstract: OBJECTIVE: In patients with breast cancer and positive hormone receptors, aromatase inhibitors are effective in reducing the risk of recurrences and are active in progressing the disease in this setting. On the other hand, fatigue and painful musculoskeletal side effects can significantly reduce treatment compliance. With no further treatment options to control these symptoms, non-pharmaceutical interventions, such as oxygen-ozone therapy, may play a role in managing rheumatologic symptomatology inasmuch. We have previously reported evidence on the effectiveness of oxygen-ozone in the treatment of pain and fatigue in chronic fatigue syndrome and fibromyalgia patients and in oncological patients as well. PATIENTS AND METHODS: In this study, we reported 6 cases of patients (mean age 64 yrs, all Caucasian females) with breast cancer upon treatment with anastrozole (Arimidex®), suffering from musculoskeletal pain, weakness and fatigue, and therefore treated with oxygen-ozone major autohemotherapy according to the Italian Scientific Society of Oxygen Ozone Therapy (SIOOT) protocol. Pain was measured with a 10-item Numerical Rating Scale (NRS) and fatigue with a 7-item Fatigue Scoring Scale (FSS). RESULTS: A reduction of at least 66% of pain (from 9.43 ±0.54 SD to 2.36 ±1.32 SD, p<0.001) and 66.26% of fatigue were obtained for all the cases. Pain and fatigue disappeared within one month from ozone therapy, and a healthy painless state lasted for many months following the oxygen-ozone therapy. CONCLUSIONS: The oxygen-ozone therapy is a sound opportunity for breast cancer patients to reduce anti-aromatase-induced pain, fatigue, and musculoskeletal symptoms. [ABSTRACT FROM AUTHOR]
Published: 2023

22. Maximum likelihood estimation of Hidden Markov models for continuous longitudinal data with missing responses and dropout

Author: Yuichi Mori, Hiroshi Yadohisa, Tomokazu Fujino, Hidetoshi Murakami, Wataru Sakamoto, Fumitake Sakaori, Hirohito Sakurai, Yoshikazu Terada, Makoto Tomita, Kensuke Okada, Kosuke Okusa, Koji Yamamoto, Michio Yamamoto, Yoshiro Yamamoto, Yoshitomo Akimoto, Pennoni, F, Bartolucci, F, Pandolfi, S, Pandolfi, S., Yuichi Mori, Hiroshi Yadohisa, Tomokazu Fujino, Hidetoshi Murakami, Wataru Sakamoto, Fumitake Sakaori, Hirohito Sakurai, Yoshikazu Terada, Makoto Tomita, Kensuke Okada, Kosuke Okusa, Koji Yamamoto, Michio Yamamoto, Yoshiro Yamamoto, Yoshitomo Akimoto, Pennoni, F, Bartolucci, F, Pandolfi, S, and Pandolfi, S.
Abstract: We propose a Hidden Markov (HM) model for continuous longitudinal data with missing responses and dropout, thus extending the finite mixture model of multivariate Gaussian distributions. As known, the HM models assume the existence of an unobservable process, which follows a Markov chain with a discrete number of hidden states, affecting the distribution of the observed outcomes. We consider multivariate continuous responses that, for the same time occasion, are assumed to be correlated, according to a specific variance-covariance matrix, even conditionally on the latent states. For the analysis of such data, missing observations represent a relevant problem since dropout or non-monotone missing data patterns could occur. We propose an approach for inference with missing data by exploiting the steps of the Expectation-Maximization (EM) algorithm on the basis of suitable recursions. The resulting EM algorithm provides exact maximum likelihood estimates of model parameters under the missing-at-random (MAR) assumption, where the missing patterns are independent of the missing responses given all the observed data. The resulting HM model accounts for different types of missing pattern: (i) partially missing outcomes at a given time occasion; (ii) completely missing outcomes at a given time occasion (intermittent pattern); (iii) dropout before the end of the period of observation (monotone pattern). The estimation algorithm is also employed when there are available covariates supposed to affect the distribution of the latent process and, in particular, the initial and the transition probabilities of the Markov chain. In this way, it is possible to identify latent or unobserved clusters of units with homogeneous behavior and understand the influence of the covariates on the dynamic allocation of the individuals between states over time. The approach is illustrated by a Monte Carlo simulation study involving different scenarios. We also report an application based on the w
Published: 2022

23. Discrete latent variable models: Recent and advances and perspectives

Author: Coretto, P, Giordano, G, La Rocca, M, Parrella, ML, Rampichini, C, Bartolucci, F, Greenacre, M, Pandolfi, S, Pennoni, F, Coretto, P, Giordano, G, La Rocca, M, Parrella, ML, Rampichini, C, Bartolucci, F, Greenacre, M, Pandolfi, S, and Pennoni, F
Abstract: After a review of the class of discrete latent variable models in terms of formulation and estimation methods, recent advances and perspectives regarding these models are illustrated. We consider in detail the stochastic block model for social networks and models for spatio-temporal data. Among these developments, we discuss, in particular, the analysis of longitudinal compositional data about expenditures of the Spanish regions over several decades.
Published: 2023

24. A hidden Markov model for continuous longitudinal data with missing responses and dropout

Author: Pandolfi, S, Bartolucci, F, Pennoni, F, Pandolfi, S, Bartolucci, F, and Pennoni, F
Abstract: We propose a hidden Markov model for multivariate continuous longitudinal responses with covariates that accounts for three different types of missing pattern: (I) partially missing outcomes at a given time occasion, (II) completely missing outcomes at a given time occasion (intermittent pattern), and (III) dropout before the end of the period of observation (monotone pattern). The missing-at-random (MAR) assumption is formulated to deal with the first two types of missingness, while to account for the informative dropout, we rely on an extra absorbing state. Estimation of the model parameters is based on the maximum likelihood method that is implemented by an expectation-maximization (EM) algorithm relying on suitable recursions. The proposal is illustrated by a Monte Carlo simulation study and an application based on historical data on primary biliary cholangitis.
Published: 2023

25. Maximum likelihood estimation of hidden Markov models for continuous longitudinal data with missing responses and dropout

Author: Pandolfi, S., Pandolfi, S, Bartolucci, F, Pennoni, F, Pandolfi, S., Bartolucci, F., Pennoni, F., Pandolfi, S., Pandolfi, S, Bartolucci, F, Pennoni, F, Pandolfi, S., Bartolucci, F., and Pennoni, F.
Published: 2021

26. Dimensionality of the Latent Structure and Item Selection via Latent Class Multidimensional IRT Models

Author: Bartolucci, F., Montanari, G. E., and Pandolfi, S.
Abstract: With reference to a questionnaire aimed at assessing the performance of Italian nursing homes on the basis of the health conditions of their patients, we investigate two relevant issues: dimensionality of the latent structure and discriminating power of the items composing the questionnaire. The approach is based on a multidimensional item response theory model, which assumes a two-parameter logistic parameterization for the response probabilities. This model represents the health status of a patient by latent variables having a discrete distribution and, therefore, it may be seen as a constrained version of the latent class model. On the basis of the adopted model, we implement a hierarchical clustering algorithm aimed at assessing the actual number of dimensions measured by the questionnaire. These dimensions correspond to disjoint groups of items. Once the number of dimensions is selected, we also study the discriminating power of every item, so that it is possible to select the subset of these items which is able to provide an amount of information close to that of the full set. We illustrate the proposed approach on the basis of the data collected on 1,051 elderly people hosted in a sample of Italian nursing homes. (Contains 10 tables and 1 figure.)
Published: 2012
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27. High-pressure high-temperature crystallography of silicon

Author: Courac, A., primary, Pandolfi, S., additional, Crichton, W., additional, and Le Godec, Y., additional
Published: 2022
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28. Introduction to LMest

Author: Bartolucci, F., Bartolucci, F, Pandolfi, S, Pennoni, F, Serafini, A, Bartolucci, F., Pandolfi, S., Pennoni, F., Serafini, A., Bartolucci, F., Bartolucci, F, Pandolfi, S, Pennoni, F, Serafini, A, Bartolucci, F., Pandolfi, S., Pennoni, F., and Serafini, A.
Published: 2020

29. Discrete Latent Variable Models

Author: Bartolucci, F, Pandolfi, S, Pennoni, F, Bartolucci, F, Pandolfi, S, and Pennoni, F
Abstract: We review the discrete latent variable approach, which is very popular in statistics and related fields. It allows us to formulate interpretable and flexible models that can be used to analyze complex datasets in the presence of articulated dependence structures among variables. Specific models including discrete latent variables are illustrated, such as finite mixture, latent class, hidden Markov, and stochastic block models. Algorithms for maximum likelihood and Bayesian estimation of these models are reviewed, focusing, in particular, on the expectation–maximization algorithm and the Markov chain Monte Carlo method with data augmentation. Model selection, particularly concerning the number of support points of the latent distribution, is discussed. The approach is illustrated by summarizing applications avail- able in the literature; a brief review of the main software packages to handle discrete latent variable models is also provided. Finally, some possible developments in this literature are suggested.
Published: 2022

30. Diamond formation kinetics in shock-compressed C-H-O samples recorded by small-angle X-ray scattering and X-ray diffraction

Author: He, Z., Rödel, M., Lütgert, J., Bergermann, A., Bethkenhagen, M., Chekrygina, D., (0000-0002-5845-000X) Cowan, T., Descamps, A., French, M., Galtier, E., Gleason, A. E., Glenn, G. D., Glenzer, S. H., Inubushi, Y., (0000-0002-6268-2436) Hartley, N., Hernandez, J.-A., Heuser, B., (0000-0001-6748-0422) Humphries, O. S., Kamimura, N., Katagiri, K., Khaghani, D., Ja Lee, H., McBride, E. E., Miyanishi, K., Nagler, B., Ofori-Okai, B., Ozaki, N., Pandolfi, S., Qu, C., (0000-0002-8641-4794) Ranjan, D., Redmer, R., Schoenwaelder, C., (0000-0001-5489-5952) Schuster, A., Stevenson, M. G., Sueda, K., Togashi, T., Vinci, T., (0000-0001-8090-2626) Voigt, K., (0000-0001-5926-9192) Vorberger, J., Yabashi, M., Yabuuchi, T., Zinta, L. M. V., Ravasio, A., (0000-0002-6350-4180) Kraus, D., He, Z., Rödel, M., Lütgert, J., Bergermann, A., Bethkenhagen, M., Chekrygina, D., (0000-0002-5845-000X) Cowan, T., Descamps, A., French, M., Galtier, E., Gleason, A. E., Glenn, G. D., Glenzer, S. H., Inubushi, Y., (0000-0002-6268-2436) Hartley, N., Hernandez, J.-A., Heuser, B., (0000-0001-6748-0422) Humphries, O. S., Kamimura, N., Katagiri, K., Khaghani, D., Ja Lee, H., McBride, E. E., Miyanishi, K., Nagler, B., Ofori-Okai, B., Ozaki, N., Pandolfi, S., Qu, C., (0000-0002-8641-4794) Ranjan, D., Redmer, R., Schoenwaelder, C., (0000-0001-5489-5952) Schuster, A., Stevenson, M. G., Sueda, K., Togashi, T., Vinci, T., (0000-0001-8090-2626) Voigt, K., (0000-0001-5926-9192) Vorberger, J., Yabashi, M., Yabuuchi, T., Zinta, L. M. V., Ravasio, A., and (0000-0002-6350-4180) Kraus, D.
Abstract: Extreme conditions inside ice giants like Uranus and Neptune can result in peculiar chemistry and structural transitions, e.g., the precipitation of diamonds or superionic water, as so far experimentally observed only for pure C-H and H2O systems, respectively. Here we investigate a stoichiometric mixture of C and H2O by shock-compressing PET plastics and performing in situ X-ray probing. We observe diamond formation at pressures between 72±7 GPa and 125±13 GPa at temperatures ranging from ~3500 K to ~6000 K. Combining X-ray diffraction and small angle X-ray scattering, we access the kinetics of this exotic reaction. The observed demixing of C and H2O suggests that diamond precipitation inside the ice giants is enhanced by oxygen, which can lead to isolated water and thus the formation of superionic structures relevant to the planets’ magnetic fields. Moreover, our measurements indicate a way of producing nanodiamonds by simple laser-driven shock-compression of cheap PET plastics.
Published: 2022

31. Field evaluation of new olive (Olea europaea L.) selections and effects of genotype and environment on productivity and fruit characteristics

Author: Padula, G., Giordani, E., Bellini, E., Rosati, A., Pandolfi, S., Paoletti, A., Pannelli, G., Ripa, V., De Rose, F., Perri, E., Buccoliero, A., and Mennone, C.
Published: 2008

32. Qualitative evaluation of olive oils from new olive selections and effects of genotype and environment on oil quality

Author: Ripa, V., De Rose, F., Caravita, M.A., Parise, M.R., Perri, E., Rosati, A., Pandolfi, S., Paoletti, A., Pannelli, G., Padula, G., Giordani, E., Bellini, E., Buccoliero, A., and Mennone, C.
Published: 2008

33. A comparison of some criteria for states selection in the latent Markov model for longitudinal data

Author: Bacci, S., Pandolfi, S., and Pennoni, F.
Published: 2014
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34. Diversity in socio-economic growth at country level: a multivariate hidden Markov model

Author: Pandolfi, S, Bartolucci, F, Pennoni, F, Serafini, A, Pandolfi, S, Bartolucci, F, Pennoni, F, and Serafini, A
Subjects: SECS-S/01 - STATISTICA, continuous outcomes, countries inequalities, dynamic clustering, missing data
Abstract: We use data derived from the World Bank and UNESCO Institute for Statis- tics, which are referred to 217 countries followed for 18 years, from 2000 to 2017, to study the persistence of economic conditions at country level over time. We consider several variables, such as GDP per capita, educational levels, life expectancy at birth, infant mortality rate, school enrollment, government expenditure in education, and the value of the Gini index that measures the inequality level of the distribution of income through household survey data (Schultz, 1998). These variables are related to the human development index proposed by the United Nations Development Programme (1990) for measuring the well-being at country level. The proposed approach allow us to charac- terize disparities among countries in a dynamic fashion so as to evaluate the changes in inequality over time by estimating a multivariate hidden Markov (HM) model (Bartolucci, Farcomeni, and Pennoni, 2013; Zucchini, MacDonald, and Langrock, 2016), also known as latent Markov model. In particular we pro- vide a dynamic clustering of the countries on the basis of the observed economic variables and, in turn, this permits to analyze inequalities in the development level. The resulting clustering is obtained by relying on a model tailored for longitudinal data rather than by predetermined threshold values as currently adopted by many international organizations to classify countries. The HM model assumes the existence of an unobservable process, which follows a Markov chain with a discrete number of latent states, affecting the distribution of the observed variables. In particular, we consider multivariate continuous re- sponses that, for the same time occasion, are assumed to be correlated accord- ing to a specific variance-covariance matrix, even conditionally on the latent states. In such a context, maximum likelihood estimation of model parameters is straightforward by means of the Expectation-Maximization (EM) algorithm (Dempster, Laird, and Rubin, 1977). Missing observations represent a relevant problem in this analysis, where values for some countries may be not available. Therefore, in this work, we also propose an approach for inference with missing data based on modifying the standard steps of the EM algorithm in a suitable way. In particular, we assume a structure of missing at random (MAR) re- sponses (Little and Rubin, 2002) where the missing patterns are independent of the missing responses given all the observed data. The resulting EM algorithm provides exact maximum likelihood estimates of the model parameters. Since the resulting latent states may be ordered according to the average values of the economic variables, inequalities among countries are detected for each year on the basis of the estimated posterior probabilities of the countries of be- longing to each latent state. In this way, we also explore patterns of disparities among countries and track their evolution from a dynamic perspective.
Published: 2020

35. Fibromyalgia treated with oxygen-ozone auto-haemotherapy (O2-O3-AHT): a case study on 200 patients with a modified 10-PI-NRS evaluation.

Author: TIRELLI, U., FRANZINI, M., VALDENASSI, L., PANDOLFI, S., TAIBI, R., and CHIRUMBOLO, S.
Abstract: OBJECTIVE: Fibromyalgia (FM) is a concerning chronic disease showing as widespread pain, muscle stiffness, sleep disturbances, chronic fatigue, and depressed mood, for which no sound therapy is yet available to date. In this article we assessed a wider patients' cohort the efficacy of oxygen-ozone autohemotherapy (O2-O3-AHT) previously reported. PATIENTS AND METHODS: A number of 200 FM-patients accessed the study and were treated with 3-4 runs of O2-O3-AHT, following their signed consent. A modified 10 points-PI-NRS were used to evaluate pain intensity before and after the conclusion of the complete ozone-treatment cycle (1 month). Kruskall-Wallis' test and other statistics were used at p<0.05 level of significance. RESULTS: A quite complete rehabilitation of the musculoskeletal function and of the overall arthralgia was observed in 76% of the patients at one month of follow-up. The number of patients having a reduction in the PI-NRS score from 10 (the maximal observed) to 3 (including 10-1 and 10-2) following only two runs of O2-O3-AHT was 23.5%, whereas only 17.5% did not show any significant improvement (ΔPI-NRS = 0 o r 1), so a ssessing that the efficacy of O2-O3-AHT, independently from ages, encompassed at least 41% in a moderate way and 64.5% of the treated patients, as a whole. CONCLUSIONS: Oxygen-ozone autohemotherapy represents a formidable therapeutic approach for FM, deserving further studies to be made in order to fully elucidate ozone effect of this pathology. [ABSTRACT FROM AUTHOR]
Published: 2022

36. WIP1 phosphatase modulates the Hedgehog signaling by enhancing GLI1 function

Author: Pandolfi, S, Montagnani, V, Penachioni, J Y, Vinci, M C, Olivito, B, Borgognoni, L, and Stecca, B
Published: 2013
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37. Thermal expansion of liquid Fe-S alloy at high pressure

Author: Xu, F., primary, Morard, G., additional, Guignot, N., additional, Rivoldini, A., additional, Manthilake, G., additional, Chantel, J., additional, Xie, L., additional, Yoneda, A., additional, King, A., additional, Boulard, E., additional, Pandolfi, S., additional, Ryerson, F.J., additional, and Antonangeli, D., additional
Published: 2021
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38. A Hidden Markov Model for Variable Selection with Missing Values.

Author: Perna, C, Salvati, N, Schirripa Spagnolo, F, Pennoni, F, Bartolucci, F, Pandolfi, S, Perna, C, Salvati, N, Schirripa Spagnolo, F, Pennoni, F, Bartolucci, F, and Pandolfi, S
Abstract: We propose a hidden Markov model for longitudinal multivariate continuous responses, accounting for missing data under the missing at random assumption. Maximum likelihood estimation of this model is carried out through the Expectation-Maximization algorithm. To address the problem of dimensionality reduction, we develop a greedy search algorithm based on the Bayesian Information Criterion. We illustrate the proposal through a dataset collected by the World Bank and UNESCO Institute for Statistics on the basis of which we dynamically cluster countries according to the selected variables observed during the period 2000-2017.
Published: 2021

39. Variable selection in hidden Markov models with missing data

Author: Pennoni, F, Bartolucci, F, Pandolfi, S, Pennoni, F, Bartolucci, F, and Pandolfi, S
Abstract: A novel variable and model selection method is proposed to analyze multiple time-series and panel data based on a Hidden Markov (HM) model for multivariate continuous responses. We consider an approach for inference, under the missing-at-random assumption to account for missing data, focusing on the maximum likelihood estimation of the model parameters through a modified Expectation-Maximization (EM) algorithm. We develop a greedy forward-backward algorithm based on the Bayesian Information Criterion (BIC) seen as an approximation of the Bayes factor. In this way, we achieve a dimensionality reduction of the complete set of response variables to a smaller subset and thus we select the most useful variables for clustering purposes. The BIC is also used to choose the optimal number of latent states during the steps of the greedy search algorithm. In applying the selection method, the estimation of multivariate linear regression models is required. In the presence of missing values in the set of independent variables, we adopt a sort of multiple imputations based on the posterior expected values obtained at the convergence of the EM algorithm of the estimated HM model. To illustrate the proposal we use a collection of macroeconomic indicators provided by the World Bank related to 217 countries followed over a long period of time. The chosen HM model allows us to dynamically characterize countries’ transitions between hidden states representing different levels of development.
Published: 2021

40. SOX2 regulates self-renewal and tumorigenicity of human melanoma-initiating cells

Author: Santini, R, Pietrobono, S, Pandolfi, S, Montagnani, V, D’Amico, M, Penachioni, J Y, Vinci, M C, Borgognoni, L, and Stecca, B
Published: 2014
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41. Hidden Markov models for continuous multivariate data with missing responses

Author: Pennoni, F, Bartolucci, F, Serafini, A, Pandolfi, S, Theodore Chadjipadelis, Pennoni, F, Bartolucci, F, Serafini, A, and Pandolfi, S
Subjects: multivariate Gaussian distribution, SECS-S/01 - STATISTICA, Expectation-Maximization algorithm, forward-backward recursion, hierarchical clustering
Abstract: Hidden Markov models represent a popular tool for the analysis of longitudinal data, allowing the dynamic clustering of sample units on the basis of a set of repeated responses. In the literature on longitudinal data analysis, these models are typically used in the presence of multivariate categorical data, that is, when more categorical responses are observed at each time occasion. These formulations rely on the assumption of local independence, according to which the responses are conditionally independent given the latent states. Such assumption also simplifies the treatment of missing responses when the missing-at-random assumption is plausible. Here, we deal with the case of continuous multivariate responses in which, as in a Gaussian mixture models, it is natural to assume that the continuous responses for the same time occasion are correlated, according to a specific variance-covariance matrix, even conditionally on the latent states. Although maximum likelihood estimation of this model is straightforward in standard cases using the Expectation-Maximization algorithm, we focus on its estimation when: (i) suitable constraints on the variance-covariance matrix are assumed; (ii) there are missing responses. The constraints we refer to are commonly adopted in the literature of Gaussian finite mixture models. Regarding the assumptions on the generation of missing data we focus on the missing-at-random assumption and we also account for possible individual covariates that may directly affect the responses (in addition to the latent states). In particular, we propose an Expectation Maximization (EM) algorithm that provides exact maximum likelihood estimates and also computes standard errors for the parameter estimates. The proposed approach is illustrated by a simulation study, to evaluate the computational load, and through a real case analysis. We also show how the proposal may be useful in a context of time-series analysis with an application to financial data. An R implementation of the proposed algorithm is made available by the authors within the LMest package.
Published: 2019

42. Sjögren syndrome successfully treated with oxygen-ozone auto-hemotherapy (O2-O3-AHT): a case report.

Author: VALDENASSI, L., ROSSI, E., CORSETTI, M. T., SARLI, R., BELLARDI, D., CHIRUMBOLO, S., SIMONETTI, V., PANDOLFI, S., and FRANZINI, M.
Abstract: OBJECTIVE: Sjögren syndrome (SS) is an autoimmune disorder, affecting about 16,000 individuals in Italy, yet lacking a standardized therapy protocol and a plain inclusion in the reimbursed healthcare services. This raises many controversial issues about how managing the SS patient, to relief pain and discomfort and improve patients' health and social life. The ozone therapy resulted successful in previous reports, and therefore, it was used in this case report. CASE PRESENTATION: A 69-years old female outpatient, showing positivity to Schirmer's test, was previously diagnosed as a primary Sjögren syndrome, who later developed an autoimmune thyroiditis and showed the presence of rheumatoid factors. The patient suffered from a marked ocular dryness, subsequently to a purported endothelitis, alongside with fatigue and pain. Laboratory tests showed a positive ANA 1:320 in a speckled pattern with negative anti-SSA and anti-SSB tests. From December 2020 to January 2021 she underwent 2 routes of three sessions of oxygen-ozone autohemotherapy (O2-O3 AHT), as described below and improved, with only 2 sessions, her symptomatology and clinical outcome, as ocular dryness, fatigue and pain, rapidly disappeared. CONCLUSIONS: The use of ozone in the therapy of SS is a straightforward, affordable and feasible approach to treat primary Sjögren syndrome without significant side effects. [ABSTRACT FROM AUTHOR]
Published: 2022

43. Caregiving burden among informal caregivers of African American cancer survivors

Author: Schwartz, K., primary, Beebe-Dimmer, J., additional, Hastert, T. A., additional, Ruterbusch, J. J., additional, Mantey, J., additional, Harper, F., additional, Thompson, H., additional, Pandolfi, S., additional, and Schwartz, A. G., additional
Published: 2020
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44. Polarization Selectivity in Vibrational Electron-Energy-Loss Spectroscopy

Author: Radtke, G., primary, Taverna, D., additional, Menguy, N., additional, Pandolfi, S., additional, Courac, A., additional, Le Godec, Y., additional, Krivanek, O. L., additional, and Lovejoy, T. C., additional
Published: 2019
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45. Acute myeloid leukemia cells constitutively express the immunoregulatory enzyme indoleamine 2,3-dioxygenase

Author: Curti, A, Aluigi, M, Pandolfi, S, Ferri, E, Isidori, A, Salvestrini, V, Durelli, I, Horenstein, A L, Fiore, F, Massaia, M, Piccioli, M, Pileri, S A, Zavatto, E, D'Addio, A, Baccarani, M, and Lemoli, R M
Published: 2007
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46. The Paradox of Self-Fertile Varieties in the Context of Self-Incompatible Genotypes in Olive

Author: Alagna, F., Caceres, M. E., Pandolfi, S., Collani, Silvio, Mousavi, S., Mariotti, R., Cultrera, N. G. M., Baldoni, L., Barcaccia, G., Alagna, F., Caceres, M. E., Pandolfi, S., Collani, Silvio, Mousavi, S., Mariotti, R., Cultrera, N. G. M., Baldoni, L., and Barcaccia, G.
Abstract: Olive, representing one of the most important fruit crops of the Mediterranean area, is characterized by a general low fruit yield, due to numerous constraints, including alternate bearing, low flower viability, male-sterility, inter-incompatibility, and self-incompatibility (SI). Early efforts to clarify the genetic control of SI in olive gave conflicting results, and only recently, the genetic control of SI has been disclosed, revealing that olive possesses an unconventional homomorphic sporophytic diallelic system of SI, dissimilar from other described plants. This system, characterized by the presence of two SI groups, prevents self-fertilization and regulates inter-compatibility between cultivars, such that cultivars bearing the same incompatibility group are incompatible. Despite the presence of a functional SI, some varieties, in particular conditions, are able to set seeds following self-fertilization, a mechanism known as pseudo-self-compatibility (PSC), as widely reported in previous literature. Here, we summarize the results of previous works on SI in olive, particularly focusing on the occurrence of self-fertility, and offer a new perspective in view of the recent elucidation of the genetic architecture of the SI system in olive. Recent advances in research aimed at unraveling the molecular bases of SI and its breakdown in olive are also presented. The clarification of these mechanisms may have a huge impact on orchard management and will provide fundamental information for the future of olive breeding programs.
Published: 2019
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47. Hidden Markov models for continuous multivariate data with missing responses

Author: Theodore Chadjipadelis, Pennoni, F, Bartolucci, F, Serafini, A, Pandolfi, S, Theodore Chadjipadelis, Pennoni, F, Bartolucci, F, Serafini, A, and Pandolfi, S
Abstract: Hidden Markov models represent a popular tool for the analysis of longitudinal data, allowing the dynamic clustering of sample units on the basis of a set of repeated responses. In the literature on longitudinal data analysis, these models are typically used in the presence of multivariate categorical data, that is, when more categorical responses are observed at each time occasion. These formulations rely on the assumption of local independence, according to which the responses are conditionally independent given the latent states. Such assumption also simplifies the treatment of missing responses when the missing-at-random assumption is plausible. Here, we deal with the case of continuous multivariate responses in which, as in a Gaussian mixture models, it is natural to assume that the continuous responses for the same time occasion are correlated, according to a specific variance-covariance matrix, even conditionally on the latent states. Although maximum likelihood estimation of this model is straightforward in standard cases using the Expectation-Maximization algorithm, we focus on its estimation when: (i) suitable constraints on the variance-covariance matrix are assumed; (ii) there are missing responses. The constraints we refer to are commonly adopted in the literature of Gaussian finite mixture models. Regarding the assumptions on the generation of missing data we focus on the missing-at-random assumption and we also account for possible individual covariates that may directly affect the responses (in addition to the latent states). In particular, we propose an Expectation Maximization (EM) algorithm that provides exact maximum likelihood estimates and also computes standard errors for the parameter estimates. The proposed approach is illustrated by a simulation study, to evaluate the computational load, and through a real case analysis. We also show how the proposal may be useful in a context of time-series analysis with an application to financial data. A
Published: 2019

48. LMest: Generalized Latent Markov Models for longitudinal continuous and categorical data

Author: Bartolucci, F, Bartolucci, F, Pandolfi, S, Pennoni, F, Farcomeni, A, Serafini, A, PANDOLFI, SARA, Bartolucci, F, Bartolucci, F, Pandolfi, S, Pennoni, F, Farcomeni, A, Serafini, A, and PANDOLFI, SARA
Abstract: La libreria LMest permette di specificare e stimare i modelli Hidden o Latent Markov (LM) per l'analisi di dati longitudinali sia continui che categoriali. Le covariate sono presenti nei modelli in base ad adeguate parametrizzazioni. Varie tipologie di modelli possono essere stimati utilizzando la struttura dei dati sia in formato long che wide. La stima di massima verosimiglianza è ottenuta con l'algoritmo Expectation-Maximization implementato attraverso routines Fortran. La libreria permette di trattare risposte mancanti, drop-out e valori mancanti secondo una struttura non-monotona. Gli errori standard per i parametri stimati vengono calcolati attraverso la matrice di informazione ottenuta in modo esatto oppure approssimato. La libreria include alcuni esempi e dei dati sia reali che simulati., The package LMest is a framework for specifying and fitting Latent (or Hidden) Markov (LM) models, which are tailored for the analysis of longitudinal continuous and categorical data. Covariates are also included in the model specification through suitable parameterizations. Different LM models are estimated through specific functions requiring a data frame in long format. Maximum likelihood estimation of model parameters is performed through the Expectation-Maximization algorithm, which is implemented by relying on Fortran routines. The package allows us to deal with missing responses, including drop-out and non-monotonic missingness, under the missing-at-random assumption. Standard errors for the parameter estimates are obtained by exact computation of the information matrix or through reliable numerical approximations of this matrix. The package also provides some examples and real and simulated data sets.
Published: 2019

49. Planck 2015 results. I. Overview of products and scientific results

Author: Adam, R., Ade, P. A. R., Aghanim, N., Akrami, Y., Alves, M. I. R., Argueeso, F., Arnaud, M., Arroja, F., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., Banday, A. J., Barreiro, R. B., Bartlett, J. G., Bartolo, N., Basak, S., Battaglia, P., Battaner, E., Battye, R., Benabed, K., Benoit, A., Benoit-Levy, A., Bernard, J. -P., Bersanelli, M., Bertincourt, B., Bielewicz, P., Bikmaev, I., Bock, J. J., Boehringer, H., Bonaldi, A., Bonavera, L., Bond, J. R., Borrill, J., Bouchet, F. R., Boulanger, F., Bucher, M., Burenin, R., Burigana, C., Butler, R. C., Calabrese, E., Cardoso, J. -F., Carvalho, P., Casaponsa, B., Castex, G., Catalano, A., Challinor, A., Chamballu, A., Chary, R. -R., Chiang, H. C., Chluba, J., Chon, G., Christensen, P. R., Church, S., Clemens, M., Clements, D. L., Colombi, S., Colombo, L. P. L., Combet, C., Comis, B., Contreras, D., Couchot, F., Coulais, A., Crill, B. P., Cruz, M., Curto, A., Cuttaia, F., Danese, L., Davies, R. D., Davis, R. J., Bernardis, P. de, Rosa, A. de, Zotti, G. de, Delabrouille, J., Delouis, J. -M., Desert, F. -X., Di Valentino, E., Dickinson, C., Diego, J. M., Dolag, K., Dole, H., Donzelli, S., Dore, O., Douspis, M., Ducout, A., Dunkley, J., Dupac, X., Efstathiou, G., Eisenhardt, P. R. M., Elsner, F., Ensslin, T. A., Eriksen, H. K., Falgarone, E., Fantaye, Y., Farhang, M., Feeney, S., Fergusson, J., Fernandez-Cobos, R., Feroz, F., Finelli, F., Florido, E., Forni, O., Frailis, M., Fraisse, A. A., Franceschet, C., Franceschi, E., Frejsel, A., Frolov, A., Galeotta, S., Galli, S., Ganga, K., Gauthier, C., Genova-Santos, R. T., Gerbino, M., Ghosh, T., Giard, M., Giraud-Heraud, Y., Giusarma, E., Gjerlow, E., Gonzalez-Nuevo, J., Gorski, K. M., Grainge, K. J. B., Gratton, S., Gregorio, A., Gruppuso, A., Gudmundsson, J. E., Hamann, J., Handley, W., Hansen, F. K., Hanson, D., Harrison, D. L., Heavens, A., Helou, G., Henrot-Versille, S., Hernandez-Monteagudo, C., Herranz, D., Hildebrandt, S. R., Hivon, E., Hobson, M., Holmes, W. A., Hornstrup, A., Hovest, W., Huang, Z., Huffenberger, K. M., Hurier, G., Ilic, S., Jaffe, A. H., Jaffe, T. R., Jin, T., Jones, W. C., Juvela, M., Karakci, A., Keihanen, E., Keskitalo, R., Khamitov, I., Kiiveri, K., Kim, J., Kisner, T. S., Kneissl, R., Knoche, J., Knox, L., Krachmalnicoff, N., Kunz, M., Kurki-Suonio, H., Lacasa, F. [UNESP], Lagache, G., Lahteenmaki, A., Lamarre, J. -M., Langer, M., Lasenby, A., Lattanzi, M., Lawrence, C. R., Le Jeune, M., Leahy, J. P., Lellouch, E., Leonardi, R., Leon-Tavares, J., Lesgourgues, J., Levrier, F., Lewis, A., Liguori, M., Lilje, P. B., Lilley, M., Linden-Vornle, M., Lindholm, V., Liu, H., Lopez-Caniego, M., Lubin, P. M., Ma, Y. -Z., Macias-Perez, J. F., Maggio, G., Maino, D., Mak, D. S. Y., Mandolesi, N., Mangilli, A., Marchini, A., Marcos-Caballero, A., Marinucci, D., Maris, M., Marshall, D. J., Martin, P. G., Martinelli, M., Martinez-Gonzalez, E., Masi, S., Matarrese, S., Mazzotta, P., McEwen, J. D., McGehee, P., Mei, S., Meinhold, P. R., Melchiorri, A., Melin, J. -B., Mendes, L., Mennella, A., Migliaccio, M., Mikkelsen, K., Millea, M., Mitra, S., Miville-Deschenes, M. -A., Molinari, D., Moneti, A., Montier, L., Moreno, R., Morgante, G., Mortlock, D., Moss, A., Mottet, S., Muenchmeyer, M., Munshi, D., Murphy, J. A., Narimani, A., Naselsky, P., Nastasi, A., Nati, F., Natoli, P., Negrello, M., Netterfield, C. B., Norgaard-Nielsen, H. U., Noviello, F., Novikov, D., Novikov, I., Olamaie, M., Oppermann, N., Orlando, E., Oxborrow, C. A., Paci, F., Pagano, L., Pajot, F., Paladini, R., Pandolfi, S., Paoletti, D., Partridge, B., Pasian, F., Patanchon, G., Pearson, T. J., Peel, M., Peiris, H. V., Pelkonen, V. -M., Perdereau, O., Perotto, L., Perrott, Y. C., Perrotta, F., Pettorino, V., Piacentini, F., Piat, M., Pierpaoli, E., Pietrobon, D., Plaszczynski, S., Pogosyan, D., Pointecouteau, E., Polenta, G., Popa, L., Pratt, G. W., Prezeau, G., Prunet, S., Puget, J. -L., Rachen, J. P., Racine, B., Reach, W. T., Rebolo, R., Reinecke, M., Remazeilles, M., Renault, C., Renzi, A., Ristorcelli, I., Rocha, G., Roman, M., Romelli, E., Rosset, C., Rossetti, M., Rotti, A., Roudier, G., d'Orfeuil, B. Rouille, Rowan-Robinson, M., Rubino-Martin, J. A., Ruiz-Granados, B., Rumsey, C., Rusholme, B., Said, N., Salvatelli, V., Salvati, L., Sandri, M., Sanghera, H. S., Santos, D., Saunders, R. D. E., Sauve, A., Savelainen, M., Savini, G., Schaefer, B. M., Schammel, M. P., Scott, D., Seiffert, M. D., Serra, P., Shellard, E. P. S., Shimwell, T. W., Shiraishi, M., Smith, K., Souradeep, T., Spencer, L. D., Spinelli, M., Stanford, S. A., Stern, D., Stolyarov, V., Stompor, R., Strong, A. W., Sudiwala, R., Sunyaev, R., Sutter, P., Sutton, D., Suur-Uski, A. -S., Sygnet, J. -F., Tauber, J. A., Tavagnacco, D., Terenzi, L., Texier, D., Toffolatti, L., Tomasi, M., Tornikoski, M., Tramonte, D., Tristram, M., Troja, A., Trombetti, T., Tucci, M., Tuovinen, J., Turler, M., Umana, G., Valenziano, L., Valiviita, J., Van Tent, F., Vassallo, T., Vibert, L., Vidal, M., Viel, M., Vielva, P., Villa, F., Wade, L. A., Walter, B., Wandelt, B. D., Watson, R., Wehus, I. K., Welikala, N., Weller, J., White, M., White, S. D. M., Wilkinson, A., Yvon, D., Zacchei, A., Zibin, J. P., Zonca, A., Planck Collaboration, Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Hélium : du fondamental aux applications (HELFA), Institut Néel (NEEL), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Laboratoire de l'Accélérateur Linéaire (LAL), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Sud - Paris 11 (UP11), CPT - E3 Cosmologie, Centre de Physique Théorique - UMR 7332 (CPT), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Planck, AstroParticule et Cosmologie (APC (UMR_7164)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Hélium : du fondamental aux applications (NEEL - HELFA), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Théorique d'Orsay [Orsay] (LPT), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), Adam, R., Ade, P. A. R., Aghanim, N., Akrami, Y., Alves, M. I. R., Arguëso, F., Arnaud, M., Arroja, F., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., Banday, A. J., Barreiro, R. B., Bartlett, J. G., Bartolo, N., Basak, S., Battaglia, PAOLA MARIA, Battaner, E., Battye, R., Benabed, K., Benoît, A., Benoit Lévy, A., Bernard, J. P., Bersanelli, M., Bertincourt, B., Bielewicz, P., Bikmaev, I., Bock, J. J., Böhringer, H., Bonaldi, A., Bonavera, L., Bond, J. R., Borrill, J., Bouchet, F. R., Boulanger, F., Bucher, M., Burenin, R., Burigana, C., Butler, R. C., Calabrese, E., Cardoso, J. F., Carvalho, P., Casaponsa, B., Castex, G., Catalano, A., Challinor, A., Chamballu, A., Chary, R. R., Chiang, H. C., Chluba, J., Chon, G., Christensen, P. R., Church, S., Clemens, M., Clements, D. L., Colombi, S., Colombo, L. P. L., Combet, C., Comis, B., Contreras, D., Couchot, F., Coulais, A., Crill, B. P., Cruz, M., Curto, A., Cuttaia, F., Danese, L., Davies, R. D., Davis, R. J., De Bernardis, P., De Rosa, A., De Zotti, G., Delabrouille, J., Delouis, J. M., Désert, F. X., Di Valentino, E., Dickinson, C., Diego, J. M., Dolag, K., Dole, H., Donzelli, Simona, Doré, O., Douspis, M., Ducout, A., Dunkley, J., Dupac, X., Efstathiou, G., Eisenhardt, P. R. M., Elsner, F., Enßlin, T. A., Eriksen, H. K., Falgarone, E., Fantaye, Y., Farhang, M., Feeney, S., Fergusson, J., Fernandez Cobos, R., Feroz, F., Finelli, F., Florido, E., Forni, O., Frailis, M., Fraisse, A. A., Franceschet, C., Franceschi, E., Frejsel, A., Frolov, A., Galeotta, S., Galli, S., Ganga, K., Gauthier, C., Génova Santos, R. T., Gerbino, M., Ghosh, T., Giard, M., Giraud Héraud, Y., Giusarma, E., Gjerløw, E., González Nuevo, J., Górski, K. M., Grainge, K. J. B., Gratton, S., Gregorio, Anna, Gruppuso, A., Gudmundsson, J. E., Hamann, J., Handley, W., Hansen, F. K., Hanson, D., Harrison, D. L., Heavens, A., Helou, G., Henrot Versillé, S., Hernández Monteagudo, C., Herranz, D., Hildebrandt, S. R., Hivon, E., Hobson, M., Holmes, W. A., Hornstrup, A., Hovest, W., Huang, Z., Huffenberger, K. M., Hurier, G., Ilić, S., Jaffe, A. H., Jaffe, T. R., Jin, T., Jones, W. C., Juvela, M., Karakci, A., Keihänen, E., Keskitalo, R., Khamitov, I., Kiiveri, K., Kim, J., Kisner, T. S., Kneissl, R., Knoche, J., Knox, L., Krachmalnicoff, N., Kunz, M., Kurki Suonio, H., Lacasa, F., Lagache, G., Lähteenmäki, A., Lamarre, J. M., Langer, M., Lasenby, A., Lattanzi, M., Lawrence, C. R, Le Jeune, M., Leahy, J. P., Lellouch, E., Leonardi, R., León Tavares, J., Lesgourgues, J., Levrier, F., Lewis, A., Liguori, M., Lilje, P. B., Lilley, M., Linden Vørnle, M., Lindholm, V., Liu, H., López Caniego, M., Lubin, P. M., Ma, Y. Z., Maciás Pérez, J. F., Maggio, G., Maino, D., Mak, D. S. Y., Mandolesi, N., Mangilli, A., Marchini, A., Marcos Caballero, A., Marinucci, D., Maris, M., Marshall, D. J., Martin, P. G., Martinelli, M., Martínez González, E., Masi, S., Matarrese, S., Mazzotta, P., Mcewen, J. D., Mcgehee, P., Mei, S., Meinhold, P. R., Melchiorri, A., Melin, J. B., Mendes, L., Mennella, A., Migliaccio, M., Mikkelsen, K., Millea, M., Mitra, S., Miville Deschênes, M. A., Molinari, D., Moneti, A., Montier, L., Moreno, R., Morgante, G., Mortlock, D., Moss, A., Mottet, S., Münchmeyer, M., Munshi, D., Murphy, J. A., Narimani, A., Naselsky, P., Nastasi, A., Nati, F., Natoli, P., Negrello, M., Netterfield, C. B., Nørgaard Nielsen, H. U., Noviello, F., Novikov, D., Novikov, I., Olamaie, M., Oppermann, N., Orlando, Elena, Oxborrow, C. A., Paci, F., Pagano, L., Pajot, F., Paladini, R., Pandolfi, S., Paoletti, D., Partridge, B., Pasian, F., Patanchon, G., Pearson, T. J., Peel, M., Peiris, H. V., Pelkonen, V. M., Perdereau, O., Perotto, L., Perrott, Y. C., Perrotta, F., Pettorino, V., Piacentini, F., Piat, M., Pierpaoli, E., Pietrobon, D., Plaszczynski, S., Pogosyan, D., Pointecouteau, E., Polenta, G., Popa, L., Pratt, G. W., Prézeau, G., Prunet, S., Puget, J. L., Rachen, J. P., Racine, B., Reach, W. T., Rebolo, R., Reinecke, M., Remazeilles, M., Renault, C., Renzi, A., Ristorcelli, I., Rocha, G., Roman, M., Romelli, Erik, Rosset, C., Rossetti, M., Rotti, A., Roudier, G., Rouillé D'orfeuil, B., Rowan Robinson, M., Rubinõ Martín, J. A., Ruiz Granados, B., Rumsey, C., Rusholme, B., Said, N., Salvatelli, V., Salvati, L., Sandri, M., Sanghera, H. S., Santos, D., Saunders, R. D. E., Sauvé, A., Savelainen, M., Savini, G., Schaefer, B. M., Schammel, M. P., Scott, D., Seiffert, M. D., Serra, P., Shellard, E. P. S., Shimwell, T. W., Shiraishi, M., Smith, K., Souradeep, T., Spencer, L. D., Spinelli, M., Stanford, S. A., Stern, D., Stolyarov, V., Stompor, R., Strong, A. W., Sudiwala, R., Sunyaev, R., Sutter, P., Sutton, D., Suur Uski, A. S., Sygnet, J. F., Tauber, J. A., Tavagnacco, Daniele, Terenzi, L., Texier, D., Toffolatti, L., Tomasi, M., Tornikoski, M., Tramonte, D., Tristram, M., Troja, A., Trombetti, T., Tucci, M., Tuovinen, J., Türler, M., Umana, G., Valenziano, L., Valiviita, J., Van Tent, F., Vassallo, T., Vibert, L., Vidal, M., Viel, Matteo, Vielva, P., Villa, F., Wade, L. A., Walter, B., Wandelt, B. D., Watson, R., Wehus, I. K., Welikala, N., Weller, J., White, M., White, S. D. M., Wilkinson, A., Yvon, D., Zacchei, A., Zibin, J. P., Zonca, A., Universidade de São Paulo (USP), Aalto Univ, Dept Radio Sci & Engn, Acad Sci Tatarstan, African Inst Math Sci, Agenzia Spaziale Italiana Sci Data Ctr, Aix Marseille Univ, Univ Cam bridge, Univ KwaZulu Natal, ALMA Santiago Cent Off, CGEE, Univ Toronto, IRAP, Trinity Coll Dublin, CALTECH, Univ Cambridge, CEFCA, Lawrence Berkeley Natl Lab, CSIC, CEA Saclay, Tech Univ Denmark, Univ Geneva, Univ Copenhagen, Univ La Laguna ULL, Univ Oviedo, Univ Cantabria, Kazan Fed Univ, Radboud Univ Nijmegen, Univ British Columbia, Univ Southern Calif, Johns Hopkins Univ, UCL, Univ Sussex, Florida State Univ, Univ Helsinki, Princeton Univ, Univ Alberta, Univ Calif Berkeley, Univ Calif Davis, Univ Calif Santa Barbara, Univ Illinois, Univ Padua, Univ Bologna, Univ Ferrara, Univ Roma La Sapienza, Univ Milan, Univ Trieste, Univ Roma Tor Vergata, Niels Bohr Inst, ESO Vitacura, ESAC, ESTEC, Univ Turku, Observ Paris, INFN, HGSFP, Heidelberg Univ, Haverford Coll, Universidade Estadual Paulista (Unesp), INAF, IASF Bologna, IASF Milano, Univ Roma Sapienza, Natl Inst Nucl Phys, Univ Grenoble Alpes, CNRS, IUCAA, Imperial Coll London, Univ Joseph Fourier Grenoble I, Inst Univ France, Univ Paris Saclay, Inst Astrophys Paris, Rhein Westfal TH Aachen, Inst Space Sci, Univ Oslo, INAOE, Inst Astrofis Canarias, Ist Nazl Astrofis, Ist Nazl Fis Nucl, Univ Manchester, Univ Chicago, Kavli Inst Cosmol Cambridge, Univ Paris 11, Telecom ParisTech, Univ Paris Sud 11, Russian Acad Sci, Natl Taiwan Univ, Max Planck Inst Astrophys, Max Planck Inst Extraterr Phys, McGill Univ, Moscow Inst Phys & Technol, Univ Coll London, Natl Univ Ireland, Nicolaus Copernicus Astron Ctr, Nordita Nord Inst Theoret Phys, Perimeter Inst Theoret Phys, Shahid Beheshti Univ, SISSA, Univ E Campus, Cardiff Univ, Univ Nottingham, Simon Fraser Univ, UPMC, Stanford Univ, Sterrewacht Leiden, Univ Oxford, Univ Sydney, TUBITAK Natl Observ, Stockholm Univ, CERN, UPMC Univ Paris 06, Univ Toulouse, Stratospher Observ Infrared Astron, Ludwig Maximilian Univ Munich, Univ Granada, Univ Warsaw Observ, Science and Technology Facilities Council (STFC), Imperial College Trust, The Leverhulme Trust, Adam, R, Ade, P, Aghanim, N, Akrami, Y, Alves, M, Argueso, F, Arnaud, M, Arroja, F, Ashdown, M, Aumont, J, Baccigalupi, C, Ballardini, M, Banday, A, Barreiro, R, Bartlett, J, Bartolo, N, Basak, S, Battaglia, P, Battaner, E, Battye, R, Benabed, K, Benoit, A, Benoit-Levy, A, Bernard, J, Bersanelli, M, Bertincourt, B, Bielewicz, P, Bikmaev, I, Bock, J, Bohringer, H, Bonaldi, A, Bonavera, L, Bond, J, Borrill, J, Bouchet, F, Boulanger, F, Bucher, M, Burenin, R, Burigana, C, Butler, R, Calabrese, E, Cardoso, J, Carvalho, P, Casaponsa, B, Castex, G, Catalano, A, Challinor, A, Chamballu, A, Chary, R, Chiang, H, Chluba, J, Chon, G, Christensen, P, Church, S, Clemens, M, Clements, D, Colombi, S, Colombo, L, Combet, C, Comis, B, Contreras, D, Couchot, F, Coulais, A, Crill, B, Cruz, M, Curto, A, Cuttaia, F, Danese, L, Davies, R, Davis, R, De Bernardis, P, De Rosa, A, De Zotti, G, Delabrouille, J, Delouis, J, Desert, F, Di Valentino, E, Dickinson, C, Diego, J, Dolag, K, Dole, H, Donzelli, S, Dore, O, Douspis, M, Ducout, A, Dunkley, J, Dupac, X, Efstathiou, G, Eisenhardt, P, Elsner, F, Ensslin, T, Eriksen, H, Falgarone, E, Fantaye, Y, Farhang, M, Feeney, S, Fergusson, J, Fernandez-Cobos, R, Feroz, F, Finelli, F, Florido, E, Forni, O, Frailis, M, Fraisse, A, Franceschet, C, Franceschi, E, Frejsel, A, Frolov, A, Galeotta, S, Galli, S, Ganga, K, Gauthier, C, Genova-Santos, R, Gerbino, M, Ghosh, T, Giard, M, Giraud-Heraud, Y, Giusarma, E, Gjerlow, E, Gonzalez-Nuevo, J, Gorski, K, Grainge, K, Gratton, S, Gregorio, A, Gruppuso, A, Gudmundsson, J, Hamann, J, Handley, W, Hansen, F, Hanson, D, Harrison, D, Heavens, A, Helou, G, Henrot-Versille, S, Hernandez-Monteagudo, C, Herranz, D, Hildebrandt, S, Hivon, E, Hobson, M, Holmes, W, Hornstrup, A, Hovest, W, Huang, Z, Huffenberger, K, Hurier, G, Ilic, S, Jaffe, A, Jaffe, T, Jin, T, Jones, W, Juvela, M, Karakci, A, Keihanen, E, Keskitalo, R, Khamitov, I, Kiiveri, K, Kim, J, Kisner, T, Kneissl, R, Knoche, J, Knox, L, Krachmalnicoff, N, Kunz, M, Kurki-Suonio, H, Lacasa, F, Lagache, G, Lahteenmaki, A, Lamarre, J, Langer, M, Lasenby, A, Lattanzi, M, Lawrence, C, Le Jeune, M, Leahy, J, Lellouch, E, Leonardi, R, Leon-Tavares, J, Lesgourgues, J, Levrier, F, Lewis, A, Liguori, M, Lilje, P, Lilley, M, Linden-Vornle, M, Lindholm, V, Liu, H, Lopez-Caniego, M, Lubin, P, Ma, Y, Macias-Perez, J, Maggio, G, Maino, D, Mak, D, Mandolesi, N, Mangilli, A, Marchini, A, Marcos-Caballero, A, Marinucci, D, Maris, M, Marshall, D, Martin, P, Martinelli, M, Martinez-Gonzalez, E, Masi, S, Matarrese, S, Mazzotta, P, Mcewen, J, Mcgehee, P, Mei, S, Meinhold, P, Melchiorri, A, Melin, J, Mendes, L, Mennella, A, Migliaccio, M, Mikkelsen, K, Millea, M, Mitra, S, Miville-Deschenes, M, Molinari, D, Moneti, A, Montier, L, Moreno, R, Morgante, G, Mortlock, D, Moss, A, Mottet, S, Munchmeyer, M, Munshi, D, Murphy, J, Narimani, A, Naselsky, P, Nastasi, A, Nati, F, Natoli, P, Negrello, M, Netterfield, C, Norgaard-Nielsen, H, Noviello, F, Novikov, D, Novikov, I, Olamaie, M, Oppermann, N, Orlando, E, Oxborrow, C, Paci, F, Pagano, L, Pajot, F, Paladini, R, Pandolfi, S, Paoletti, D, Partridge, B, Pasian, F, Patanchon, G, Pearson, T, Peel, M, Peiris, H, Pelkonen, V, Perdereau, O, Perotto, L, Perrott, Y, Perrotta, F, Pettorino, V, Piacentini, F, Piat, M, Pierpaoli, E, Pietrobon, D, Plaszczynski, S, Pogosyan, D, Pointecouteau, E, Polenta, G, Popa, L, Pratt, G, Prezeau, G, Prunet, S, Puget, J, Rachen, J, Racine, B, Reach, W, Rebolo, R, Reinecke, M, Remazeilles, M, Renault, C, Renzi, A, Ristorcelli, I, Rocha, G, Roman, M, Romelli, E, Rosset, C, Rossetti, M, Rotti, A, Roudier, G, Rouille D'orfeuil, B, Rowan-Robinson, M, Rubino-Martin, J, Ruiz-Granados, B, Rumsey, C, Rusholme, B, Said, N, Salvatelli, V, Salvati, L, Sandri, M, Sanghera, H, Santos, D, Saunders, R, Sauve, A, Savelainen, M, Savini, G, Schaefer, B, Schammel, M, Scott, D, Seiffert, M, Serra, P, Shellard, E, Shimwell, T, Shiraishi, M, Smith, K, Souradeep, T, Spencer, L, Spinelli, M, Stanford, S, Stern, D, Stolyarov, V, Stompor, R, Strong, A, Sudiwala, R, Sunyaev, R, Sutter, P, Sutton, D, Suur-Uski, A, Sygnet, J, Tauber, J, Tavagnacco, D, Terenzi, L, Texier, D, Toffolatti, L, Tomasi, M, Tornikoski, M, Tramonte, D, Tristram, M, Troja, A, Trombetti, T, Tucci, M, Tuovinen, J, Turler, M, Umana, G, Valenziano, L, Valiviita, J, Van Tent, F, Vassallo, T, Vibert, L, Vidal, M, Viel, M, Vielva, P, Villa, F, Wade, L, Walter, B, Wandelt, B, Watson, R, Wehus, I, Welikala, N, Weller, J, White, M, White, S, Wilkinson, A, Yvon, D, Zacchei, A, Zibin, J, and Zonca, A
Subjects: error [data analysis method], Cosmology: observations – Cosmic background radiation – Surveys – Space vehicles: instruments – Instrumentation: detectors, gravitation: model, [SDU.ASTR.CO]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], Astronomy, Cosmic microwave background, cosmic background radiation: polarization, Astrophysics, Surveys, Cosmic background radiation, Cosmology: observation, 01 natural sciences, Cosmology, cosmological model: parameter space, Space vehicles: instruments, Instrumentation: detectors, dark energy, Survey, observations [Cosmology], 010303 astronomy & astrophysics, detectors [Instrumentation], QB, media_common, Physics, Instrumentation: detector, data analysis method: error, Cosmology: observations, Astrophysics::Instrumentation and Methods for Astrophysics, Planck temperature, Polarization (waves), Settore FIS/02 - Fisica Teorica, Modelli e Metodi Matematici, parameter space [cosmological model], non-Gaussianity, Sunyaev-Zel'dovich effect, astro-ph.CO, symbols, galaxy: cluster, detector [Instrumentation], Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics and Astronomy, power spectrum [cosmic background radiation], satellite: Planck, Cosmology and Nongalactic Astrophysics (astro-ph.CO), Astrophysics::High Energy Astrophysical Phenomena, media_common.quotation_subject, FOS: Physical sciences, observation [Cosmology], Astrophysics::Cosmology and Extragalactic Astrophysics, Space vehicles: instrument, efficiency [data analysis method], Astronomy & Astrophysics, primordial [magnetic field], microwaves, NO, instruments [Space vehicles], [PHYS.ASTR.CO]Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], symbols.namesake, gravitation: lens, Settore FIS/05 - Astronomia e Astrofisica, data analysis method: efficiency, cluster [galaxy], 0103 physical sciences, instrument [Space vehicles], polarization [cosmic background radiation], lens [gravitation], cosmic background radiation: power spectrum, inflation, Planck, numerical calculations, Astrophysics::Galaxy Astrophysics, 010308 nuclear & particles physics, Astronomy and Astrophysics, Space and Planetary Science, temperature [cosmic background radiation], magnetic field: primordial, model [gravitation], Astronomy and Astrophysic, cosmic background radiation: temperature, 0201 Astronomical And Space Sciences, Gravitational lens, Sky, Dark energy, ddc:520, Planck [satellite], experimental results
Abstract: Planck is a project of the European Space Agency in cooperation with the scientific community, which started in 1993.SIC, MINECO, JA, and RES (Spain); ERC and PRACE (EU)., Adam, R., Ade, P.A.R., Aghanim, N., Akrami, Y., Alves, M.I.R., Arguëso, F., Arnaud, M., Arroja, F., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., Banday, A.J., Barreiro, R.B., Bartlett, J.G., Bartolo, N., Basak, S., Battaglia, P., Battaner, E., Battye, R., Benabed, K., Benoît, A., Benoit-Lévy, A., Bernard, J.-P., Bersanelli, M., Bertincourt, B., Bielewicz, P., Bikmaev, I., Bock, J.J., Böhringer, H., Bonaldi, A., Bonavera, L., Bond, J.R., Borrill, J., Bouchet, F.R., Boulanger, F., Bucher, M., Burenin, R., Burigana, C., Butler, R.C., Calabrese, E., Cardoso, J.-F., Carvalho, P., Casaponsa, B., Castex, G., Catalano, A., Challinor, A., Chamballu, A., Chary, R.-R., Chiang, H.C., Chluba, J., Chon, G., Christensen, P.R., Church, S., Clemens, M., Clements, D.L., Colombi, S., Colombo, L.P.L., Combet, C., Comis, B., Contreras, D., Couchot, F., Coulais, A., Crill, B.P., Cruz, M., Curto, A., Cuttaia, F., Danese, L., Davies, R.D., Davis, R.J., De Bernardis, P., De Rosa, A., De Zotti, G., Delabrouille, J., Delouis, J.-M., Désert, F.-X., Di Valentino, E., Dickinson, C., Diego, J.M., Dolag, K., Dole, H., Donzelli, S., Doré, O., Douspis, M., Ducout, A., Dunkley, J., Dupac, X., Efstathiou, G., Eisenhardt, P.R.M., Elsner, F., Enßlin, T.A., Eriksen, H.K., Falgarone, E., Fantaye, Y., Farhang, M., Feeney, S., Fergusson, J., Fernandez-Cobos, R., Feroz, F., Finelli, F., Florido, E., Forni, O., Frailis, M., Fraisse, A.A., Franceschet, C., Franceschi, E., Frejsel, A., Frolov, A., Galeotta, S., Galli, S., Ganga, K., Gauthier, C., Génova-Santos, R.T., Gerbino, M., Ghosh, T., Giard, M., Giraud-Héraud, Y., Giusarma, E., Gjerløw, E., González-Nuevo, J., Górski, K.M., Grainge, K.J.B., Gratton, S., Gregorio, A., Gruppuso, A., Gudmundsson, J.E., Hamann, J., Handley, W., Hansen, F.K., Hanson, D., Harrison, D.L., Heavens, A., Helou, G., Henrot-Versillé, S., Hernández-Monteagudo, C., Herranz, D., Hildebrandt, S.R., Hivon, E., Hobson, M., Holmes, W.A., Hornstrup, A., Hovest, W., Huang, Z., Huffenberger, K.M., Hurier, G., Ilić, S., Jaffe, A.H., Jaffe, T.R., Jin, T., Jones, W.C., Juvela, M., Karakci, A., Keihänen, E., Keskitalo, R., Khamitov, I., Kiiveri, K., Kim, J., Kisner, T.S., Kneissl, R., Knoche, J., Knox, L., Krachmalnicoff, N., Kunz, M., Kurki-Suonio, H., Lacasa, F., Lagache, G., Lähteenmäki, A., Lamarre, J.-M., Langer, M., Lasenby, A., Lattanzi, M., Lawrence, C.R., Le Jeune, M., Leahy, J.P., Lellouch, E., Leonardi, R., León-Tavares, J., Lesgourgues, J., Levrier, F., Lewis, A., Liguori, M., Lilje, P.B., Lilley, M., Linden-Vørnle, M., Lindholm, V., Liu, H., López-Caniego, M., Lubin, P.M., Ma, Y.-Z., Maciás-Pérez, J.F., Maggio, G., Maino, D., Mak, D.S.Y., Mandolesi, N., Mangilli, A., Marchini, A., Marcos-Caballero, A., Marinucci, D., Maris, M., Marshall, D.J., Martin, P.G., Martinelli, M., Martínez-González, E., Masi, S., Matarrese, S., Mazzotta, P., Mcewen, J.D., Mcgehee, P., Mei, S., Meinhold, P.R., Melchiorri, A., Melin, J.-B., Mendes, L., Mennella, A., Migliaccio, M., Mikkelsen, K., Millea, M., Mitra, S., Miville-Deschênes, M.-A., Molinari, D., Moneti, A., Montier, L., Moreno, R., Morgante, G., Mortlock, D., Moss, A., Mottet, S., Münchmeyer, M., Munshi, D., Murphy, J.A., Narimani, A., Naselsky, P., Nastasi, A., Nati, F., Natoli, P., Negrello, M., Netterfield, C.B., Nørgaard-Nielsen, H.U., Noviello, F., Novikov, D., Novikov, I., Olamaie, M., Oppermann, N., Orlando, E., Oxborrow, C.A., Paci, F., Pagano, L., Pajot, F., Paladini, R., Pandolfi, S., Paoletti, D., Partridge, B., Pasian, F., Patanchon, G., Pearson, T.J., Peel, M., Peiris, H.V., Pelkonen, V.-M., Perdereau, O., Perotto, L., Perrott, Y.C., Perrotta, F., Pettorino, V., Piacentini, F., Piat, M., Pierpaoli, E., Pietrobon, D., Plaszczynski, S., Pogosyan, D., Pointecouteau, E., Polenta, G., Popa, L., Pratt, G.W., Prézeau, G., Prunet, S., Puget, J.-L., Rachen, J.P., Racine, B., Reach, W.T., Rebolo, R., Reinecke, M., Remazeilles, M., Renault, C., Renzi, A., Ristorcelli, I., Rocha, G., Roman, M., Romelli, E., Rosset, C., Rossetti, M., Rotti, A., Roudier, G., Rouillé D'orfeuil, B., Rowan-Robinson, M., Rubinõ-Martín, J.A., Ruiz-Granados, B., Rumsey, C., Rusholme, B., Said, N., Salvatelli, V., Salvati, L., Sandri, M., Sanghera, H.S., Santos, D., Saunders, R.D.E., Sauvé, A., Savelainen, M., Savini, G., Schaefer, B.M., Schammel, M.P., Scott, D., Seiffert, M.D., Serra, P., Shellard, E.P.S., Shimwell, T.W., Shiraishi, M., Smith, K., Souradeep, T., Spencer, L.D., Spinelli, M., Stanford, S.A., Stern, D., Stolyarov, V., Stompor, R., Strong, A.W., Sudiwala, R., Sunyaev, R., Sutter, P., Sutton, D., Suur-Uski, A.-S., Sygnet, J.-F., Tauber, J.A., Tavagnacco, D., Terenzi, L., Texier, D., Toffolatti, L., Tomasi, M., Tornikoski, M., Tramonte, D., Tristram, M., Troja, A., Trombetti, T., Tucci, M., Tuovinen, J., Türler, M., Umana, G., Valenziano, L., Valiviita, J., Van Tent, F., Vassallo, T., Vibert, L., Vidal, M., Viel, M., Vielva, P., Villa, F., Wade, L.A., Walter, B., Wandelt, B.D., Watson, R., Wehus, I.K., Welikala, N., Weller, J., White, M., White, S.D.M., Wilkinson, A., Yvon, D., Zacchei, A., Zibin, J.P., Zonca, A.
Published: 2016

50. Fatigue in post-acute sequelae of SARS-CoV2 (PASC) treated with oxygen-ozone autohemotherapy – preliminary results on 100 patients.

Author: TIRELLI, U., FRANZINI, M., VALDENASSI, L., PISCONTI, S., TAIBI, R., TORRISI, C., PANDOLFI, S., and CHIRUMBOLO, S.
Abstract: OBJECTIVE: Post-acute sequelae of SARS-CoV2 infection (PASC) are a novel terminology used to describe post-COVID persistent symptoms, mimicking somehow the previously described chronic fatigue syndrome (CFS). In this manuscript, we evaluated a therapeutical approach to address PASC-derived fatigue in a cohort of past-COVID-19 positive patients. PATIENTS AND METHODS: A number of 100 patients, previously diagnosed as COVID-19 positive subjects and meeting our eligibility criteria, was diagnosed having PASC-related fatigue. They were recruited in the study and treated with oxygen-ozone autohemotherapy (O2-O3-AHT), according to the SIOOT protocol. Patients’ response to O2-O3-AHT and changes in fatigue were measured with the 7-scoring Fatigue Severity Scale (FSS), according to previously published protocols. RESULTS: Statistics assessed that the effects of O2-O3-AHT on fatigue reduced PASC symptoms by 67%, as a mean, in all the investigated cohort of patients (H = 148.4786 p < 0.0001) (Figure 1). Patients following O2-O3- AHT therapy, quite completely recovered for PASC-associated fatigue, a quote amounting to about two fifths (around 40%) of the whole cohort undergoing ozone treatment and despite most of patients were female subjects, the effect was not influenced by sex distribution (H = 0.7353, p = 0.39117). CONCLUSIONS: Ozone therapy is able to recover normal functionality and to relief pain and discomfort in the form of PASC-associated fatigue in at least 67% of patients suffering from post-COVID sequelae, aside from sex and age distribution. [ABSTRACT FROM AUTHOR]
Published: 2021

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