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  1. Article ; Online: COVID-19 therapy optimization by AI-driven biomechanical simulations.

    Agrimi, E / Diko, A / Carlotti, D / Ciardiello, A / Borthakur, M / Giagu, S / Melchionna, S / Voena, C

    European physical journal plus

    2023  Volume 138, Issue 2, Page(s) 182

    Abstract: The COVID-19 disease causes pneumonia in many patients that in the most serious cases evolves into the Acute Distress Respiratory Syndrome (ARDS), requiring assisted ventilation and intensive care. In this context, identification of patients at high risk ...

    Abstract The COVID-19 disease causes pneumonia in many patients that in the most serious cases evolves into the Acute Distress Respiratory Syndrome (ARDS), requiring assisted ventilation and intensive care. In this context, identification of patients at high risk of developing ARDS is a key point for early clinical management, better clinical outcome and optimization in using the limited resources available in the intensive care units. We propose an AI-based prognostic system that makes predictions of oxygen exchange with arterial blood by using as input lung Computed Tomography (CT), the air flux in lungs obtained from biomechanical simulations and Arterial Blood Gas (ABG) analysis. We developed and investigated the feasibility of this system on a small clinical database of proven COVID-19 cases where the initial CT and various ABG reports were available for each patient. We studied the time evolution of the ABG parameters and found correlation with the morphological information extracted from CT scans and disease outcome. Promising results of a preliminary version of the prognostic algorithm are presented. The ability to predict the evolution of patients' respiratory efficiency would be of crucial importance for disease management.
    Language English
    Publishing date 2023-02-27
    Publishing country Germany
    Document type Journal Article
    ISSN 2190-5444
    ISSN (online) 2190-5444
    DOI 10.1140/epjp/s13360-023-03744-5
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  2. Article ; Conference proceedings: A pre-training model for intestinal metaplasia recognition in the gastric corpus: preliminary data analysis

    Ligato, I. / De Magistris, G. / Dilaghi, E. / Cozza, G. / Ciardiello, A. / Voena, C. / Giagu, S. / Annibale, B. / Napoli, C. / Esposito, G.

    Endoscopy

    2024  Volume 56, Issue S 02

    Event/congress ESGE Days 2024, Berlin, Germany, 2024-04-25
    Language English
    Publishing date 2024-04-01
    Publisher Georg Thieme Verlag KG
    Publishing place Stuttgart ; New York
    Document type Article ; Conference proceedings
    ZDB-ID 80120-3
    ISSN 1438-8812 ; 0013-726X
    ISSN (online) 1438-8812
    ISSN 0013-726X
    DOI 10.1055/s-0044-1782810
    Database Thieme publisher's database

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  3. Book ; Online: Fast Neural Network Inference on FPGAs for Triggering on Long-Lived Particles at Colliders

    Coccaro, Andrea / Di Bello, Francesco Armando / Giagu, Stefano / Rambelli, Lucrezia / Stocchetti, Nicola

    2023  

    Abstract: Experimental particle physics demands a sophisticated trigger and acquisition system capable to efficiently retain the collisions of interest for further investigation. Heterogeneous computing with the employment of FPGA cards may emerge as a trending ... ...

    Abstract Experimental particle physics demands a sophisticated trigger and acquisition system capable to efficiently retain the collisions of interest for further investigation. Heterogeneous computing with the employment of FPGA cards may emerge as a trending technology for the triggering strategy of the upcoming high-luminosity program of the Large Hadron Collider at CERN. In this context, we present two machine-learning algorithms for selecting events where neutral long-lived particles decay within the detector volume studying their accuracy and inference time when accelerated on commercially available Xilinx FPGA accelerator cards. The inference time is also confronted with a CPU- and GPU-based hardware setup. The proposed new algorithms are proven efficient for the considered benchmark physics scenario and their accuracy is found to not degrade when accelerated on the FPGA cards. The results indicate that all tested architectures fit within the latency requirements of a second-level trigger farm and that exploiting accelerator technologies for real-time processing of particle-physics collisions is a promising research field that deserves additional investigations, in particular with machine-learning models with a large number of trainable parameters.

    Comment: 12 pages, 10 figures, 2 tables
    Keywords High Energy Physics - Experiment ; Computer Science - Machine Learning ; Physics - Instrumentation and Detectors
    Subject code 006
    Publishing date 2023-07-11
    Publishing country us
    Document type Book ; Online
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  4. Article ; Online: Preliminary results in using Deep Learning to emulate BLOB, a nuclear interaction model.

    Ciardiello, A / Asai, M / Caccia, B / Cirrone, G A P / Colonna, M / Dotti, A / Faccini, R / Giagu, S / Messina, A / Napolitani, P / Pandola, L / Wright, D H / Mancini-Terracciano, C

    Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)

    2020  Volume 73, Page(s) 65–72

    Abstract: Purpose: A reliable model to simulate nuclear interactions is fundamental for Ion-therapy. We already showed how BLOB ("Boltzmann-Langevin One Body"), a model developed to simulate heavy ion interactions up to few hundreds of MeV/u, could simulate also ! ...

    Abstract Purpose: A reliable model to simulate nuclear interactions is fundamental for Ion-therapy. We already showed how BLOB ("Boltzmann-Langevin One Body"), a model developed to simulate heavy ion interactions up to few hundreds of MeV/u, could simulate also
    Methods: The BLOB final state is a Probability Density Function (PDF) of finding a nucleon in a position of the phase space. We discretised this PDF and trained a Variational Auto-Encoder (VAE) to reproduce such a discrete PDF. As a proof of concept, we developed and trained a VAE to emulate BLOB in simulating the interactions of
    Results: The distributions obtained from the VAE are similar to the input ones and the computation time needed to use the VAE as a generator is negligible.
    Conclusions: We show that it is possible to use a Deep Learning approach to emulate a model developed to simulate nuclear reactions in the energy range of interest for Ion-therapy. We foresee the implementation of the generation part in C++ and to interface it with the most used Monte Carlo toolkit: Geant4.
    MeSH term(s) Deep Learning ; Monte Carlo Method ; Radiobiology
    Language English
    Publishing date 2020-04-21
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 1122650-x
    ISSN 1724-191X ; 1120-1797
    ISSN (online) 1724-191X
    ISSN 1120-1797
    DOI 10.1016/j.ejmp.2020.04.005
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  5. Article ; Online: Multimodal evaluation of

    Ciardiello, Andrea / Altieri, Saverio / Ballarini, Francesca / Bocci, Valerio / Bortolussi, Silva / Cansolino, Laura / Carlotti, Daniele / Ciocca, Mario / Faccini, Riccardo / Facoetti, Angelica / Ferrari, Cinzia / Ficcadenti, Luca / Furfaro, Emiliano / Giagu, Stefano / Iacoangeli, Francesco / Macioce, Giampiero / Mancini-Terracciano, Carlo / Messina, Andrea / Milazzo, Luisa /
    Pacifico, Severina / Piccolella, Simona / Postuma, Ian / Rotili, Dante / Vercesi, Valerio / Voena, Cecilia / Vulcano, Francesca / Capuani, Silvia

    Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)

    2022  Volume 94, Page(s) 75–84

    Abstract: Purpose: One of the obstacles to the application of Boron Neutron Capture Therapy (BNCT) and Proton Boron Fusion Therapy (PBFT) concerns the measurement of borated carriers' biodistribution. The objective of the present study was to evaluate the in ... ...

    Abstract Purpose: One of the obstacles to the application of Boron Neutron Capture Therapy (BNCT) and Proton Boron Fusion Therapy (PBFT) concerns the measurement of borated carriers' biodistribution. The objective of the present study was to evaluate the in vitro internalization of the
    Materials and methods: The
    Results: Our studies suggested that
    Conclusions: The ability of
    MeSH term(s) Boron ; Boron Compounds ; Boron Neutron Capture Therapy ; Humans ; Pancreatic Neoplasms/radiotherapy ; Proton Therapy ; Tissue Distribution
    Chemical Substances Boron Compounds ; Boron (N9E3X5056Q)
    Language English
    Publishing date 2022-01-06
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 1122650-x
    ISSN 1724-191X ; 1120-1797
    ISSN (online) 1724-191X
    ISSN 1120-1797
    DOI 10.1016/j.ejmp.2021.12.011
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  6. Article ; Online: High-precision measurement of the

    Aaltonen, T / Amerio, S / Amidei, D / Anastassov, A / Annovi, A / Antos, J / Apollinari, G / Appel, J A / Arisawa, T / Artikov, A / Asaadi, J / Ashmanskas, W / Auerbach, B / Aurisano, A / Azfar, F / Badgett, W / Bae, T / Barbaro-Galtieri, A / Barnes, V E /
    Barnett, B A / Barria, P / Bartos, P / Bauce, M / Bedeschi, F / Behari, S / Bellettini, G / Bellinger, J / Benjamin, D / Beretvas, A / Bhatti, A / Bland, K R / Blumenfeld, B / Bocci, A / Bodek, A / Bortoletto, D / Boudreau, J / Boveia, A / Brigliadori, L / Bromberg, C / Brucken, E / Budagov, J / Budd, H S / Burkett, K / Busetto, G / Bussey, P / Butti, P / Buzatu, A / Calamba, A / Camarda, S / Campanelli, M / Carls, B / Carlsmith, D / Carosi, R / Carrillo, S / Casal, B / Casarsa, M / Castro, A / Catastini, P / Cauz, D / Cavaliere, V / Cerri, A / Cerrito, L / Chen, Y C / Chertok, M / Chiarelli, G / Chlachidze, G / Cho, K / Chokheli, D / Clark, A / Clarke, C / Convery, M E / Conway, J / Corbo, M / Cordelli, M / Cox, C A / Cox, D J / Cremonesi, M / Cruz, D / Cuevas, J / Culbertson, R / d'Ascenzo, N / Datta, M / de Barbaro, P / Demortier, L / Deninno, M / D'Errico, M / Devoto, F / Di Canto, A / Di Ruzza, B / Dittmann, J R / Donati, S / D'Onofrio, M / Dorigo, M / Driutti, A / Ebina, K / Edgar, R / Elagin, A / Erbacher, R / Errede, S / Esham, B / Farrington, S / Fernández Ramos, J P / Field, R / Flanagan, G / Forrest, R / Franklin, M / Freeman, J C / Frisch, H / Funakoshi, Y / Galloni, C / Garfinkel, A F / Garosi, P / Gerberich, H / Gerchtein, E / Giagu, S / Giakoumopoulou, V / Gibson, K / Ginsburg, C M / Giokaris, N / Giromini, P / Glagolev, V / Glenzinski, D / Gold, M / Goldin, D / Golossanov, A / Gomez, G / Gomez-Ceballos, G / Goncharov, M / González López, O / Gorelov, I / Goshaw, A T / Goulianos, K / Gramellini, E / Grosso-Pilcher, C / Guimaraes da Costa, J / Hahn, S R / Han, J Y / Happacher, F / Hara, K / Hare, M / Harr, R F / Harrington-Taber, T / Hatakeyama, K / Hays, C / Heinrich, J / Herndon, M / Hocker, A / Hong, Z / Hopkins, W / Hou, S / Hughes, R E / Husemann, U / Hussein, M / Huston, J / Introzzi, G / Iori, M / Ivanov, A / James, E / Jang, D / Jayatilaka, B / Jeon, E J / Jindariani, S / Jones, M / Joo, K K / Jun, S Y / Junk, T R / Kambeitz, M / Kamon, T / Karchin, P E / Kasmi, A / Kato, Y / Ketchum, W / Keung, J / Kilminster, B / Kim, D H / Kim, H S / Kim, J E / Kim, M J / Kim, S H / Kim, S B / Kim, Y J / Kim, Y K / Kimura, N / Kirby, M / Kondo, K / Kong, D J / Konigsberg, J / Kotwal, A V / Kreps, M / Kroll, J / Kruse, M / Kuhr, T / Kurata, M / Laasanen, A T / Lammel, S / Lancaster, M / Lannon, K / Latino, G / Lee, H S / Lee, J S / Leo, S / Leone, S / Lewis, J D / Limosani, A / Lipeles, E / Lister, A / Liu, Q / Liu, T / Lockwitz, S / Loginov, A / Lucchesi, D / Lucà, A / Lueck, J / Lujan, P / Lukens, P / Lungu, G / Lys, J / Lysak, R / Madrak, R / Maestro, P / Malik, S / Manca, G / Manousakis-Katsikakis, A / Marchese, L / Margaroli, F / Marino, P / Matera, K / Mattson, M E / Mazzacane, A / Mazzanti, P / McNulty, R / Mehta, A / Mehtala, P / Menzione, A / Mesropian, C / Miao, T / Michielin, E / Mietlicki, D / Mitra, A / Miyake, H / Moed, S / Moggi, N / Moon, C S / Moore, R / Morello, M J / Mukherjee, A / Muller, Th / Murat, P / Mussini, M / Nachtman, J / Nagai, Y / Naganoma, J / Nakano, I / Napier, A / Nett, J / Nigmanov, T / Nodulman, L / Noh, S Y / Norniella, O / Oakes, L / Oh, S H / Oh, Y D / Okusawa, T / Orava, R / Ortolan, L / Pagliarone, C / Palencia, E / Palni, P / Papadimitriou, V / Parker, W / Pauletta, G / Paulini, M / Paus, C / Phillips, T J / Piacentino, G / Pianori, E / Pilot, J / Pitts, K / Plager, C / Pondrom, L / Poprocki, S / Potamianos, K / Pranko, A / Prokoshin, F / Ptohos, F / Punzi, G / Redondo Fernández, I / Renton, P / Rescigno, M / Rimondi, F / Ristori, L / Robson, A / Rodriguez, T / Rolli, S / Ronzani, M / Roser, R / Rosner, J L / Ruffini, F / Ruiz, A / Russ, J / Rusu, V / Sakumoto, W K / Sakurai, Y / Santi, L / Sato, K / Saveliev, V / Savoy-Navarro, A / Schlabach, P / Schmidt, E E / Schwarz, T / Scodellaro, L / Scuri, F / Seidel, S / Seiya, Y / Semenov, A / Sforza, F / Shalhout, S Z / Shears, T / Shepard, P F / Shimojima, M / Shochet, M / Shreyber-Tecker, I / Simonenko, A / Sliwa, K / Smith, J R / Snider, F D / Song, H / Sorin, V / St Denis, R / Stancari, M / Stentz, D / Strologas, J / Sudo, Y / Sukhanov, A / Suslov, I / Takemasa, K / Takeuchi, Y / Tang, J / Tecchio, M / Teng, P K / Thom, J / Thomson, E / Thukral, V / Toback, D / Tokar, S / Tollefson, K / Tomura, T / Torre, S / Torretta, D / Totaro, P / Trovato, M / Ukegawa, F / Uozumi, S / Vázquez, F / Velev, G / Vellidis, K / Vernieri, C / Vidal, M / Vilar, R / Vizán, J / Vogel, M / Volpi, G / Wagner, P / Wallny, R / Wang, S M / Waters, D / Wester, W C / Whiteson, D / Wicklund, A B / Wilbur, S / Williams, H H / Wilson, J S / Wilson, P / Winer, B L / Wittich, P / Wolbers, S / Wolfmeister, H / Wright, T / Wu, X / Wu, Z / Yamamoto, K / Yamato, D / Yang, T / Yang, U K / Yang, Y C / Yao, W-M / Yeh, G P / Yi, K / Yoh, J / Yorita, K / Yoshida, T / Yu, G B / Yu, I / Zanetti, A M / Zeng, Y / Zhou, C / Zucchelli, S

    Science (New York, N.Y.)

    2022  Volume 376, Issue 6589, Page(s) 170–176

    Abstract: The mass of ... ...

    Abstract The mass of the
    Language English
    Publishing date 2022-04-07
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 128410-1
    ISSN 1095-9203 ; 0036-8075
    ISSN (online) 1095-9203
    ISSN 0036-8075
    DOI 10.1126/science.abk1781
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  7. Book ; Online: An Update to the Letter of Intent for MATHUSLA

    Alpigiani, Cristiano / Arteaga-Velázquez, Juan Carlos / Ball, Austin / Barak, Liron / Barron, Jared / Batell, Brian / Beacham, James / Benhammo, Yan / Caballero-Mora, Karen Salomé / Camarri, Paolo / Cardarelli, Roberto / Chou, John Paul / Cui, Wentao / Curtin, David / Diamond, Miriam / Dienes, Keith R. / Dougherty, Liam Andrew / Di Sciascio, Giuseppe / Drewes, Marco /
    Etzion, Erez / Essig, Rouven / Evans, Jared / Téllez, Arturo Fernández / Fischer, Oliver / Freeman, Jim / Gall, Jonathan / Garabaglu, Ali / Giagu, Stefano / Greenberg, Stephen Elliott / Gomber, Bhawna / Guida, Roberto / Haas, Andy / Heng, Yuekun / Hsu, Shih-Chieh / Iaselli, Giuseppe / Johns, Ken / Kvam, Audrey / Lazic, Dragoslav / Li, Liang / Liberti, Barbara / Liu, Zhen / Lubatti, Henry / Luo, Lillian / Marsella, Giovanni / Hernández, Mario Iván Martínez / McCullough, Matthew / McKeen, David / Meade, Patrick / Mizrachi, Gilad / Morales-Olivares, O. G. / Morrissey, David / Moshe, Meny Raviv / Policicchio, Antonio / Proffitt, Mason / Ramirez, Dennis Cazar / Reece, Matthew / Robertson, Steven H. / Rodríguez-Cahuantzi, Mario / de Roeck, Albert / Roepe, Amber / Rothberg, Joe / Russell, James John / Russell, Heather / Santonico, Rinaldo / Schioppa, Marco / Shelton, Jessie / Shuve, Brian / Silver, Yiftah / Di Stante, Luigi / Stolarski, Daniel / Strauss, Mike / Strom, David / Stupak, John / Vasquez, Martin A. Subieta / Swain, Sanjay Kumar / Muñoz, Guillermo Tejeda / Thayil, Steffie Ann / Thomas, Brooks / Tsai, Yuhsin / Torro, Emma / Watts, Gordon / Young, Charles / Zurita, Jose

    Search for Long-Lived Particles at the HL-LHC

    2020  

    Abstract: We report on recent progress in the design of the proposed MATHUSLA Long Lived Particle (LLP) detector for the HL-LHC, updating the information in the original Letter of Intent (LoI), see CDS:LHCC-I-031, arXiv:1811.00927. A suitable site has been ... ...

    Abstract We report on recent progress in the design of the proposed MATHUSLA Long Lived Particle (LLP) detector for the HL-LHC, updating the information in the original Letter of Intent (LoI), see CDS:LHCC-I-031, arXiv:1811.00927. A suitable site has been identified at LHC Point 5 that is closer to the CMS Interaction Point (IP) than assumed in the LoI. The decay volume has been increased from 20 m to 25 m in height. Engineering studies have been made in order to locate much of the decay volume below ground, bringing the detector even closer to the IP. With these changes, a 100 m x 100 m detector has the same physics reach for large c$\tau$ as the 200 m x 200 m detector described in the LoI and other studies. The performance for small c$\tau$ is improved because of the proximity to the IP. Detector technology has also evolved while retaining the strip-like sensor geometry in Resistive Plate Chambers (RPC) described in the LoI. The present design uses extruded scintillator bars read out using wavelength shifting fibers and silicon photomultipliers (SiPM). Operations will be simpler and more robust with much lower operating voltages and without the use of greenhouse gases. Manufacturing is straightforward and should result in cost savings. Understanding of backgrounds has also significantly advanced, thanks to new simulation studies and measurements taken at the MATHUSLA test stand operating above ATLAS in 2018. We discuss next steps for the MATHUSLA collaboration, and identify areas where new members can make particularly important contributions.

    Comment: 22 pages + references, 12 Figures
    Keywords Physics - Instrumentation and Detectors ; High Energy Physics - Experiment ; High Energy Physics - Phenomenology
    Subject code 621
    Publishing date 2020-09-03
    Publishing country us
    Document type Book ; Online
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  8. Article ; Online: Constraints on Sub-GeV Dark-Matter-Electron Scattering from the DarkSide-50 Experiment.

    Agnes, P / Albuquerque, I F M / Alexander, T / Alton, A K / Araujo, G R / Asner, D M / Ave, M / Back, H O / Baldin, B / Batignani, G / Biery, K / Bocci, V / Bonfini, G / Bonivento, W / Bottino, B / Budano, F / Bussino, S / Cadeddu, M / Cadoni, M /
    Calaprice, F / Caminata, A / Canci, N / Candela, A / Caravati, M / Cariello, M / Carlini, M / Carpinelli, M / Catalanotti, S / Cataudella, V / Cavalcante, P / Cavuoti, S / Cereseto, R / Chepurnov, A / Cicalò, C / Cifarelli, L / Cocco, A G / Covone, G / D'Angelo, D / D'Incecco, M / D'Urso, D / Davini, S / De Candia, A / De Cecco, S / De Deo, M / De Filippis, G / De Rosa, G / De Vincenzi, M / Demontis, P / Derbin, A V / Devoto, A / Di Eusanio, F / Di Pietro, G / Dionisi, C / Downing, M / Edkins, E / Empl, A / Fan, A / Fiorillo, G / Fomenko, K / Franco, D / Gabriele, F / Gabrieli, A / Galbiati, C / Garcia Abia, P / Ghiano, C / Giagu, S / Giganti, C / Giovanetti, G K / Gorchakov, O / Goretti, A M / Granato, F / Gromov, M / Guan, M / Guardincerri, Y / Gulino, M / Hackett, B R / Hassanshahi, M H / Herner, K / Hosseini, B / Hughes, D / Humble, P / Hungerford, E V / Ianni, Al / Ianni, An / Ippolito, V / James, I / Johnson, T N / Kahn, Y / Keeter, K / Kendziora, C L / Kochanek, I / Koh, G / Korablev, D / Korga, G / Kubankin, A / Kuss, M / La Commara, M / Lai, M / Li, X / Lisanti, M / Lissia, M / Loer, B / Longo, G / Ma, Y / Machado, A A / Machulin, I N / Mandarano, A / Mapelli, L / Mari, S M / Maricic, J / Martoff, C J / Messina, A / Meyers, P D / Milincic, R / Mishra-Sharma, S / Monte, A / Morrocchi, M / Mount, B J / Muratova, V N / Musico, P / Nania, R / Navrer Agasson, A / Nozdrina, A O / Oleinik, A / Orsini, M / Ortica, F / Pagani, L / Pallavicini, M / Pandola, L / Pantic, E / Paoloni, E / Pazzona, F / Pelczar, K / Pelliccia, N / Pesudo, V / Picciau, E / Pocar, A / Pordes, S / Poudel, S S / Pugachev, D A / Qian, H / Ragusa, F / Razeti, M / Razeto, A / Reinhold, B / Renshaw, A L / Rescigno, M / Riffard, Q / Romani, A / Rossi, B / Rossi, N / Sablone, D / Samoylov, O / Sands, W / Sanfilippo, S / Sant, M / Santorelli, R / Savarese, C / Scapparone, E / Schlitzer, B / Segreto, E / Semenov, D A / Shchagin, A / Sheshukov, A / Singh, P N / Skorokhvatov, M D / Smirnov, O / Sotnikov, A / Stanford, C / Stracka, S / Suffritti, G B / Suvorov, Y / Tartaglia, R / Testera, G / Tonazzo, A / Trinchese, P / Unzhakov, E V / Verducci, M / Vishneva, A / Vogelaar, B / Wada, M / Waldrop, T J / Wang, H / Wang, Y / Watson, A W / Westerdale, S / Wojcik, M M / Wojcik, M / Xiang, X / Xiao, X / Yang, C / Ye, Z / Zhu, C / Zichichi, A / Zuzel, G

    Physical review letters

    2018  Volume 121, Issue 11, Page(s) 111303

    Abstract: We present new constraints on sub-GeV dark-matter particles scattering off electrons based on 6780.0 kg d of data collected with the DarkSide-50 dual-phase argon time projection chamber. This analysis uses electroluminescence signals due to ionized ... ...

    Abstract We present new constraints on sub-GeV dark-matter particles scattering off electrons based on 6780.0 kg d of data collected with the DarkSide-50 dual-phase argon time projection chamber. This analysis uses electroluminescence signals due to ionized electrons extracted from the liquid argon target. The detector has a very high trigger probability for these signals, allowing for an analysis threshold of three extracted electrons, or approximately 0.05 keVee. We calculate the expected recoil spectra for dark matter-electron scattering in argon and, under the assumption of momentum-independent scattering, improve upon existing limits from XENON10 for dark-matter particles with masses between 30 and 100  MeV/c^{2}.
    Language English
    Publishing date 2018-09-08
    Publishing country United States
    Document type Journal Article
    ZDB-ID 208853-8
    ISSN 1079-7114 ; 0031-9007
    ISSN (online) 1079-7114
    ISSN 0031-9007
    DOI 10.1103/PhysRevLett.121.111303
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Low-Mass Dark Matter Search with the DarkSide-50 Experiment.

    Agnes, P / Albuquerque, I F M / Alexander, T / Alton, A K / Araujo, G R / Asner, D M / Ave, M / Back, H O / Baldin, B / Batignani, G / Biery, K / Bocci, V / Bonfini, G / Bonivento, W / Bottino, B / Budano, F / Bussino, S / Cadeddu, M / Cadoni, M /
    Calaprice, F / Caminata, A / Canci, N / Candela, A / Caravati, M / Cariello, M / Carlini, M / Carpinelli, M / Catalanotti, S / Cataudella, V / Cavalcante, P / Cavuoti, S / Cereseto, R / Chepurnov, A / Cicalò, C / Cifarelli, L / Cocco, A G / Covone, G / D'Angelo, D / D'Incecco, M / D'Urso, D / Davini, S / De Candia, A / De Cecco, S / De Deo, M / De Filippis, G / De Rosa, G / De Vincenzi, M / Demontis, P / Derbin, A V / Devoto, A / Di Eusanio, F / Di Pietro, G / Dionisi, C / Downing, M / Edkins, E / Empl, A / Fan, A / Fiorillo, G / Fomenko, K / Franco, D / Gabriele, F / Gabrieli, A / Galbiati, C / Garcia Abia, P / Ghiano, Chiara / Giagu, S / Giganti, C / Giovanetti, G K / Gorchakov, O / Goretti, A M / Granato, F / Gromov, M / Guan, M / Guardincerri, Y / Gulino, M / Hackett, B R / Hassanshahi, M H / Herner, K / Hosseini, B / Hughes, D / Humble, P / Hungerford, E V / Ianni, Al / Ianni, An / Ippolito, V / James, I / Johnson, T N / Kahn, Y / Keeter, K / Kendziora, C L / Kochanek, I / Koh, G / Korablev, D / Korga, G / Kubankin, A / Kuss, M / La Commara, M / Lai, M / Li, X / Lisanti, M / Lissia, M / Loer, B / Longo, G / Ma, Y / Machado, A A / Machulin, I N / Mandarano, A / Mapelli, L / Mari, S M / Maricic, J / Martoff, C J / Messina, A / Meyers, P D / Milincic, R / Mishra-Sharma, S / Monte, A / Morrocchi, M / Mount, B J / Muratova, V N / Musico, P / Nania, R / Navrer Agasson, A / Nozdrina, A O / Oleinik, A / Orsini, M / Ortica, F / Pagani, L / Pallavicini, M / Pandola, L / Pantic, E / Paoloni, E / Pazzona, F / Pelczar, K / Pelliccia, N / Pesudo, V / Pocar, A / Pordes, S / Poudel, S S / Pugachev, D A / Qian, H / Ragusa, F / Razeti, M / Razeto, A / Reinhold, B / Renshaw, A L / Rescigno, M / Riffard, Q / Romani, A / Rossi, B / Rossi, N / Sablone, D / Samoylov, O / Sands, W / Sanfilippo, S / Sant, M / Santorelli, R / Savarese, C / Scapparone, E / Schlitzer, B / Segreto, E / Semenov, D A / Shchagin, A / Sheshukov, A / Singh, P N / Skorokhvatov, M D / Smirnov, O / Sotnikov, A / Stanford, C / Stracka, S / Suffritti, G B / Suvorov, Y / Tartaglia, R / Testera, G / Tonazzo, A / Trinchese, P / Unzhakov, E V / Verducci, M / Vishneva, A / Vogelaar, B / Wada, M / Waldrop, T J / Wang, H / Wang, Y / Watson, A W / Westerdale, S / Wojcik, M M / Wojcik, M / Xiang, X / Xiao, X / Yang, C / Ye, Z / Zhu, C / Zichichi, A / Zuzel, G

    Physical review letters

    2018  Volume 121, Issue 8, Page(s) 81307

    Abstract: We present the results of a search for dark matter weakly interacting massive particles (WIMPs) in the mass range below 20  GeV/c^{2} using a target of low-radioactivity argon with a 6786.0 kg d exposure. The data were obtained using the DarkSide-50 ... ...

    Abstract We present the results of a search for dark matter weakly interacting massive particles (WIMPs) in the mass range below 20  GeV/c^{2} using a target of low-radioactivity argon with a 6786.0 kg d exposure. The data were obtained using the DarkSide-50 apparatus at Laboratori Nazionali del Gran Sasso. The analysis is based on the ionization signal, for which the DarkSide-50 time projection chamber is fully efficient at 0.1  keVee. The observed rate in the detector at 0.5  keVee is about 1.5  event/keVee/kg/d and is almost entirely accounted for by known background sources. We obtain a 90% C.L. exclusion limit above 1.8  GeV/c^{2} for the spin-independent cross section of dark matter WIMPs on nucleons, extending the exclusion region for dark matter below previous limits in the range 1.8-6  GeV/c^{2}.
    Language English
    Publishing date 2018-09-07
    Publishing country United States
    Document type Journal Article
    ZDB-ID 208853-8
    ISSN 1079-7114 ; 0031-9007
    ISSN (online) 1079-7114
    ISSN 0031-9007
    DOI 10.1103/PhysRevLett.121.081307
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Search for the Exotic Meson X(5568) with the Collider Detector at Fermilab.

    Aaltonen, T / Amerio, S / Amidei, D / Anastassov, A / Annovi, A / Antos, J / Apollinari, G / Appel, J A / Arisawa, T / Artikov, A / Asaadi, J / Ashmanskas, W / Auerbach, B / Aurisano, A / Azfar, F / Badgett, W / Bae, T / Barbaro-Galtieri, A / Barnes, V E /
    Barnett, B A / Barria, P / Bartos, P / Bauce, M / Bedeschi, F / Behari, S / Bellettini, G / Bellinger, J / Benjamin, D / Beretvas, A / Bhatti, A / Bland, K R / Blumenfeld, B / Bocci, A / Bodek, A / Bortoletto, D / Boudreau, J / Boveia, A / Brigliadori, L / Bromberg, C / Brucken, E / Budagov, J / Budd, H S / Burkett, K / Busetto, G / Bussey, P / Butti, P / Buzatu, A / Calamba, A / Camarda, S / Campanelli, M / Canelli, F / Carls, B / Carlsmith, D / Carosi, R / Carrillo, S / Casal, B / Casarsa, M / Castro, A / Catastini, P / Cauz, D / Cavaliere, V / Cerri, A / Cerrito, L / Chen, Y C / Chertok, M / Chiarelli, G / Chlachidze, G / Cho, K / Chokheli, D / Clark, A / Clarke, C / Convery, M E / Conway, J / Corbo, M / Cordelli, M / Cox, C A / Cox, D J / Cremonesi, M / Cruz, D / Cuevas, J / Culbertson, R / d'Ascenzo, N / Datta, M / de Barbaro, P / Demortier, L / Deninno, M / D'Errico, M / Devoto, F / Di Canto, A / Di Ruzza, B / Dittmann, J R / Donati, S / D'Onofrio, M / Dorigo, M / Driutti, A / Ebina, K / Edgar, R / Elagin, A / Erbacher, R / Errede, S / Esham, B / Farrington, S / Fernández Ramos, J P / Field, R / Flanagan, G / Forrest, R / Franklin, M / Freeman, J C / Frisch, H / Funakoshi, Y / Galloni, C / Garfinkel, A F / Garosi, P / Gerberich, H / Gerchtein, E / Giagu, S / Giakoumopoulou, V / Gibson, K / Ginsburg, C M / Giokaris, N / Giromini, P / Glagolev, V / Glenzinski, D / Gold, M / Goldin, D / Golossanov, A / Gomez, G / Gomez-Ceballos, G / Goncharov, M / González López, O / Gorelov, I / Goshaw, A T / Goulianos, K / Gramellini, E / Grosso-Pilcher, C / Guimaraes da Costa, J / Hahn, S R / Han, J Y / Happacher, F / Hara, K / Hare, M / Harr, R F / Harrington-Taber, T / Hatakeyama, K / Hays, C / Heinrich, J / Herndon, M / Hocker, A / Hong, Z / Hopkins, W / Hou, S / Hughes, R E / Husemann, U / Hussein, M / Huston, J / Introzzi, G / Iori, M / Ivanov, A / James, E / Jang, D / Jayatilaka, B / Jeon, E J / Jindariani, S / Jones, M / Joo, K K / Jun, S Y / Junk, T R / Kambeitz, M / Kamon, T / Karchin, P E / Kasmi, A / Kato, Y / Ketchum, W / Keung, J / Kilminster, B / Kim, D H / Kim, H S / Kim, J E / Kim, M J / Kim, S H / Kim, S B / Kim, Y J / Kim, Y K / Kimura, N / Kirby, M / Kondo, K / Kong, D J / Konigsberg, J / Kotwal, A V / Kreps, M / Kroll, J / Kruse, M / Kuhr, T / Kurata, M / Laasanen, A T / Lammel, S / Lancaster, M / Lannon, K / Latino, G / Lee, H S / Lee, J S / Leo, S / Leone, S / Lewis, J D / Limosani, A / Lipeles, E / Lister, A / Liu, Q / Liu, T / Lockwitz, S / Loginov, A / Lucchesi, D / Lucà, A / Lueck, J / Lujan, P / Lukens, P / Lungu, G / Lys, J / Lysak, R / Madrak, R / Maestro, P / Malik, S / Manca, G / Manousakis-Katsikakis, A / Marchese, L / Margaroli, F / Marino, P / Matera, K / Mattson, M E / Mazzacane, A / Mazzanti, P / McNulty, R / Mehta, A / Mehtala, P / Mesropian, C / Miao, T / Mietlicki, D / Mitra, A / Miyake, H / Moed, S / Moggi, N / Moon, C S / Moore, R / Morello, M J / Mukherjee, A / Muller, Th / Murat, P / Mussini, M / Nachtman, J / Nagai, Y / Naganoma, J / Nakano, I / Napier, A / Nett, J / Nigmanov, T / Nodulman, L / Noh, S Y / Norniella, O / Oakes, L / Oh, S H / Oh, Y D / Okusawa, T / Orava, R / Ortolan, L / Pagliarone, C / Palencia, E / Palni, P / Papadimitriou, V / Parker, W / Pauletta, G / Paulini, M / Paus, C / Phillips, T J / Piacentino, G / Pianori, E / Pilot, J / Pitts, K / Plager, C / Pondrom, L / Poprocki, S / Potamianos, K / Pranko, A / Prokoshin, F / Ptohos, F / Punzi, G / Redondo Fernández, I / Renton, P / Rescigno, M / Rimondi, F / Ristori, L / Robson, A / Rodriguez, T / Rolli, S / Ronzani, M / Roser, R / Rosner, J L / Ruffini, F / Ruiz, A / Russ, J / Rusu, V / Sakumoto, W K / Sakurai, Y / Santi, L / Sato, K / Saveliev, V / Savoy-Navarro, A / Schlabach, P / Schmidt, E E / Schwarz, T / Scodellaro, L / Scuri, F / Seidel, S / Seiya, Y / Semenov, A / Sforza, F / Shalhout, S Z / Shears, T / Shepard, P F / Shimojima, M / Shochet, M / Shreyber-Tecker, I / Simonenko, A / Sliwa, K / Smith, J R / Snider, F D / Song, H / Sorin, V / St Denis, R / Stancari, M / Stentz, D / Strologas, J / Sudo, Y / Sukhanov, A / Suslov, I / Takemasa, K / Takeuchi, Y / Tang, J / Tecchio, M / Teng, P K / Thom, J / Thomson, E / Thukral, V / Toback, D / Tokar, S / Tollefson, K / Tomura, T / Tonelli, D / Torre, S / Torretta, D / Totaro, P / Trovato, M / Ukegawa, F / Uozumi, S / Vázquez, F / Velev, G / Vellidis, C / Vernieri, C / Vidal, M / Vilar, R / Vizán, J / Vogel, M / Volpi, G / Wagner, P / Wallny, R / Wang, S M / Waters, D / Wester, W C / Whiteson, D / Wicklund, A B / Wilbur, S / Williams, H H / Wilson, J S / Wilson, P / Winer, B L / Wittich, P / Wolbers, S / Wolfmeister, H / Wright, T / Wu, X / Wu, Z / Yamamoto, K / Yamato, D / Yang, T / Yang, U K / Yang, Y C / Yao, W-M / Yeh, G P / Yi, K / Yoh, J / Yorita, K / Yoshida, T / Yu, G B / Yu, I / Zanetti, A M / Zeng, Y / Zhou, C / Zucchelli, S

    Physical review letters

    2018  Volume 120, Issue 20, Page(s) 202006

    Abstract: A search for the exotic meson X(5568) decaying into the B_{s}^{0}π^{±} final state is performed using data corresponding to 9.6  fb^{-1} from pp[over ¯] collisions at sqrt[s]=1960  GeV recorded by the Collider Detector at Fermilab. No evidence for this ... ...

    Abstract A search for the exotic meson X(5568) decaying into the B_{s}^{0}π^{±} final state is performed using data corresponding to 9.6  fb^{-1} from pp[over ¯] collisions at sqrt[s]=1960  GeV recorded by the Collider Detector at Fermilab. No evidence for this state is found and an upper limit of 6.7% at the 95% confidence level is set on the fraction of B_{s}^{0} produced through the X(5568)→B_{s}^{0}π^{±} process.
    Language English
    Publishing date 2018-05-18
    Publishing country United States
    Document type Journal Article
    ZDB-ID 208853-8
    ISSN 1079-7114 ; 0031-9007
    ISSN (online) 1079-7114
    ISSN 0031-9007
    DOI 10.1103/PhysRevLett.120.202006
    Database MEDical Literature Analysis and Retrieval System OnLINE

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