451 research outputs found

    Search for SUSY in Final States with Z Bosons

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    A search for SUSY processes leading to final states with Z bosons is performed at a low mass point in the mSUGRA parameter space. The signature of such processes is studied using both a complete and a fast simulation. It is shown that the signal can be seen over the Standard Model background with high significance already at an integrated luminosity of 1fb^-1. The SUSY discovery potential is explored in the m_0,m_1/2 parameter space

    DESIGN AND IMPLEMENTATION OF THE MOBILE GRID RESOURCE MANAGEMENT SYSTEM

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    We present a design of a Mobile Grid Resource Management System aimed at integrating mobile resources to an existing Grid infrastructure, while creating a platform for interoperability with telecommunications providers. In order to reduce the load on an existing infrastructure, we separate responsibilities and run additional features on mobile resources. Finally we present the Ikaros-EG implementation, IkarosM android application and the mobile-Grid concept.The system used for our implementation was the NCSR “Demokritos” ZEUS computer Cluster, where the Ikaros-EG framework consisting of a meta-data collector and the Ikaros-EG plug-in has been installed. The ZEUS cluster has local and Grid access to data and meta-data from numerous scientific experiments. Our objective was to incorporate the mobile resources using the NCSR Demokritos campus wireless infrastructure in order to run applications concerning accounting, statistics, or further data/meta-data formatting

    Accurate and computationally efficient nonlinear static and dynamic analysis of reinforced concrete structures considering damage factors

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    Accurate nonlinear dynamic analysis of reinforced concrete structures is necessary for estimating the behavior of concrete structures during an earthquake. A realistic modeling approach to assess their strength and their ability to carry the expected seismic forces is of great importance. Although a number of constitutive models and modeling approaches have been proposed in order to capture the behavior of reinforced concrete structures under static loading conditions, only a few of these numerical models have been extended to dynamic problems. The objective of this paper is to integrate a computationally efficient 3D detailed modelling of concrete structures with damage factors that take into account the opening and closing of cracks, as well as, damage factors for steel reinforcement considering the surrounding concrete damage level, in order to capture the level of damage and stiffness degradation of structures undergoing many loading cycles. In the adopted numerical model, the concrete domain is discretized with 8-noded isoparametric hexahedral finite elements, which treat cracking with the smeared crack approach, while the steel reinforcement is modeled as embedded beam elements inside the hexahedral mesh. The validity of the proposed method is demonstrated by comparing the numerical response with the corresponding experimental results of various reinforced concrete structural members and structures. Based on the numerical investigation, it was found that the proposed integration of the damage factors with computationally efficient concrete and steel material models can efficiently predict both static and dynamic nonlinear behavior of concrete structures, with the ability to capture the complicated phenomenon of the pinching effect.The European Research Council Advanced Grant “MASTER-Mastering the computational challenges in numerical modeling and optimum design of CNT reinforced composites” (ERC-2011-ADG 20110209).http://www.elsevier.com/locate/engstruct2020-01-01hj2019Civil Engineerin

    A study on implementing a multithreaded version of the SIRENE detector simulation software for high energy neutrinos

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    The primary objective of SIRENE is to simulate the response to neutrino events of any type of high energy neutrino telescope. Additionally, it implements different geometries for a neutrino detector and different configurations and characteristics of photo-multiplier tubes (PMTs) inside the optical modules of the detector through a library of C+ + classes. This could be considered a massive statistical analysis of photo-electrons. Aim of this work is the development of a multithreaded version of the SIRENE detector simulation software for high energy neutrinos. This approach allows utilization of multiple CPU cores leading to a potentially significant decrease in the required execution time compared to the sequential code. We are making use of the OpenMP framework for the production of multithreaded code running on the CPU. Finally, we analyze the feasibility of a GPU-accelerated implementation

    Simplified HYMOD non-linear simulations of a full-scale multistory retrofitted RC structure that undergoes multiple cyclic excitations – an infill RC wall retrofitting study

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    Having the ability to assess the earthquake resistance of retrofitted reinforced concrete (RC) structures through accurate and objective nonlinear cyclic analysis is of great importance for both scientists and professional Civil Engineers. Full-scale RC structure simulations under ultimate limit state cyclic loading conditions through the use of 3D detail modeling techniques, is currently one of the most challenging modeling tasks that any research or commercial software can undertake. The excessive computational demand and the numerical instabilities that occur when dealing with this type of cyclic nonlinear numerical analysis, make this modeling approach impractical. The simplified hybrid modeling (HYMOD) approach is adopted in this work, which overcomes the above numerical limitations and it is used herein to illustrate the capabilities of the method in capturing the experimental results of a full-scale 4-storey RC building that was retrofitted with RC infill walls and carbon fiber reinforced polymer jacketing. This work has the aim to investigate the importance of numerically accounting for the damage that has developed at the concrete and steel domains during the analysis of problems that foresee consecutive cyclic loading tests. Based on the numerical findings, it was concluded that the proposed modeling approach was able to accurately capture the experimental data and predict the capacity degradation of the building specimen. Furthermore, the proposed method was used to numerically investigate different retrofitting configurations that foresaw the use of infill RC walls. The numerical experiments performed in this work demonstrate that the proposed modeling approach provides with the ability to study the cyclic mechanical behavior of full-scale RC structures under ultimate limit state conditions, thus paves the way in performing additional parametric investigations in determining the optimum retrofitting design of RC structures by using different types of interventions.The European Research Council Advanced Grant “MASTER-Mastering the computational challenges in numerical modeling and optimum design of CNT reinforced composites” (ERC-2011-ADG 20110209).http://www.elsevier.com/locate/engstruct2019-12-01hj2018Civil Engineerin

    Atmospheric neutrinos with the first KM3NeT/ORCA data and prospects for measuring the atmospheric neutrino flux

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    KM3NeT is a research infrastructure aiming to study astrophysical sources as well as to perform particle physics studies, through the detection of neutrinos in the abyssal depths of the Mediterranean Sea. The KM3NeT/ORCA detector (Oscillation Research with Cosmics in the Abyss), currently under construction, is deployed at 2450 m depth near Toulon, France. It consists of vertical structures (Detection Units) equipped with spherical Digital Optical Modules, each hosting a set of photomultiplier tubes capable of detecting neutrino events from the Cherenkov radiation induced by the daughter particles. In this contribution, an analysis of data collected with the first 6 Detection Units (ORCA6) leading to a sample of atmospheric neutrino events is described. The angular resolution and the energy reconstruction performance for this event selection, which is a key factor for measuring the atmospheric neutrino flux, are also presented.Article signat per 297 autors/es: M.Ageron, S. Aiello, A. Albert, M. Alshamsi, S. Alves Garre, Z. Aly, A. Ambrosone, F. Ameli, M. Andre, G. Androulakis, M. Anghinolfi, M. Anguita, G. Anton, M. Ardid, S. Ardid, W. Assal, J. Aublin, C. Bagatelas, B. Baret, S. Basegmez du Pree, M. Bendahman, F. Benfenati, E. Berbee, A. M. van den Berg, V. Bertin, S. Beurthey, V. van Beveren, S. Biagi, M. Billault, M. Bissinger, M. Boettcher, M. Bou Cabo, J. Boumaaza, M. Bouta, C. Boutonnet, G. Bouvet, M. Bouwhuis, C. Bozza, H.Brânzas, R. Bruijn, J. Brunner, R. Bruno, E. Buis, R. Buompane, J. Busto, B. Caiffi, L. Caillat, D. Calvo, S. Campion, A. Capone, H. Carduner, V. Carretero, P. Castaldi, S. Celli;, R. Cereseto, M. Chabab, C. Champion, N. Chau, A. Chen, S. Cherubini, V. Chiarella, T. Chiarusi, M. Circella, R. Cocimano, J. A. B. Coelho, A. Coleiro, M. Colomer Molla, S. Colonges, R. Coniglione, A. Cosquer, P. Coyle, M. Cresta, A. Creuso, A. Cruz, G. Cuttone, A. D’Amico, R. Dallier, B. De Martino, M. De Palma, I. Di Palma, A. F. Díaz, D. Diego- Tortosa, C. Distefano, A. Domi, C. Donzaud, D. Dornic, M. Dörr, D. Drouhin, T. Eberl, A. Eddyamoui, T. van Eeden, D. van Eijk, I. El Bojaddaini, H. Eljarrari, D. Elsaesser, A. Enzenhöfer, V. Espinosa, P. Fermani, G. Ferrara, M. D. Filipovic, F. Filippini, J. Fransen, L. A. Fusco, D. Gajanana, T. Gal, J. García Méndez, A. Garcia Soto, E. Garçon, F. Garufi, C. Gatius, N. Geißelbrecht, L. Gialanella, E. Giorgio, S. R. Gozzini, R. Gracia, K. Graf, G. Grella, D. Guderian, C. Guidi, B. Guillon, M. Gutiérrez, J. Haefner, S. Hallmann, H. Hamdaoui, H. van Haren, A. Heijboer, A. Hekalo, L. Hennig, S. Henry, J. J. Hernández-Rey, J. Hofestädt, F. Huang,W. Idrissi Ibnsalih, A. Ilioni, G. Illuminati, C.W. James, D. Janezashvili, P. Jansweijer, M. de Jong, P. de Jong, B. J. Jung, M. Kadler, P. Kalaczynski, O. Kalekin,U. F. Katz, F. Kayzel, P.Keller, N. R. Khan Chowdhury, G. Kistauri, F. van der Knaap, P. Kooijman, A. Kouchner, M. Kreter, V. Kulikovskiy, M. Labalme, P. Lagier, R. Lahmann, P. Lamare, M. Lamoureux, G. Larosa, C. Lastoria, J. Laurence, A. Lazo, R. Le Breton, E. Le Guirriec, S. Le Stum, G. Lehaut, O. Leonardi, F. Leone, E. Leonora, C. Lerouvillois, J. Lesrel, N. Lessing, G. Levi, M. Lincetto, M. Lindsey Clark, T. Lipreau, C. LLorens Alvarez, A. Lonardo, F. Longhitano, D. Lopez-Coto, N. Lumb, L. Maderer, J. Majumdar, J. Manczak, A. Margiotta, A. Marinelli, A. Marini, C. Markou, L. Martin, J. A. Martínez-Mora, A. Martini, F. Marzaioli, S. Mastroianni, K.W. Melis, G. Miele, P. Migliozzi, E. Migneco, P. Mijakowski, L. S. Miranda, C. M. Mollo, M. Mongelli, A. Moussa, R. Muller, P. Musico, M. Musumeci, L. Nauta, S. Navas, C. A. Nicolau, B. Nkosi, B. Ó Fearraigh, M. O’Sullivan, A. Orlando, G. Ottonello, S. Ottonello, J. Palacios González5, G. Papalashvili, R. Papaleo, C. Pastore, A. M. Paun, G. E. Pavalas, G. Pellegrini, C. Pellegrino, M. Perrin-Terrin, V. Pestel, P. Piattelli, C. Pieterse, O. Pisanti, C. Poirè, V. Popa, T. Pradier, F. Pratolongo, I. Probst, G. Pühlhofer, S. Pulvirenti, G. Quéméner, N. Randazzo, A. Rapicavoli, S. Razzaque, D. Real, S. Reck, G. Riccobene, L. Rigalleau, A. Romanov, A. Rovelli, J. Royon, F. Salesa Greus, D. F. E. Samtleben, A. Sánchez Losa, M. Sanguineti, A. Santangelo, D. Santonocito, P. Sapienza, J. Schmelling, J. Schnabel, M. F. Schneider, J. Schumann, H. M. Schutte, J. Seneca, I. Sgura, R. Shanidze, A. Sharma, A. Sinopoulou, B. Spisso, M. Spurio, D. Stavropoulos, J. Steijger, S. M. Stellacci, M. Taiuti, F. Tatone, Y. Tayalati, E. Tenllado, D. Tézier, T. Thakore, S. Theraube, H. Thiersen, P. Timmer, S. Tingay, S. Tsagkli, V. Tsourapis, E. Tzamariudaki, D. Tzanetatos, C. Valieri, V. Van Elewyck, G. Vasileiadis, F. Versari, S. Viola, D. Vivolo, G. de Wasseige, J.Wilms, R.Wojaczynski, E. deWolf, T. Yousfi, S. Zavatarelli, A. Zegarelli, D. Zito, J. D. Zornoza, J. Zúñiga, N. Zywucka.Postprint (published version

    Atmospheric neutrinos with the first detection units of KM3NeT/ARCA

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    The KM3NeT Collaboration is constructing two deep-sea Cherenkov detectors in the Mediterranean Sea, aiming at neutrino oscillation measurements with the ORCA array, while the ARCA array aims at neutrino astronomy in the TeV range. In April 2021, 5 additional detection units were deployed in the ARCA site. The KM3NeT/ARCA instrumented volume is currently similar to the one of the ANTARES neutrino telescope. In this contribution, an analysis of the data obtained with the detector before April 2021 is presented as well as the analysis of the very first data from the new KM3NeT/ARCA configuration. The performance is demonstrated using atmospheric muons and the first atmospheric neutrinos are shown.Article signat per 297 autors/es: M.Ageron, S. Aiello, A. Albert, M. Alshamsi, S. Alves Garre, Z. Aly, A. Ambrosone, F. Ameli, M. Andre, G. Androulakis, M. Anghinolfi, M. Anguita, G. Anton, M. Ardid, S. Ardid, W. Assal, J. Aublin, C. Bagatelas, B. Baret, S. Basegmez du Pree, M. Bendahman, F. Benfenati, E. Berbee, A. M. van den Berg, V. Bertin, S. Beurthey, V. van Beveren, S. Biagi, M. Billault, M. Bissinger, M. Boettcher, M. Bou Cabo, J. Boumaaza, M. Bouta, C. Boutonnet, G. Bouvet, M. Bouwhuis, C. Bozza, H.Brânzas, R. Bruijn, J. Brunner, R. Bruno, E. Buis, R. Buompane, J. Busto, B. Caiffi, L. Caillat, D. Calvo, S. Campion, A. Capone, H. Carduner, V. Carretero, P. Castaldi, S. Celli;, R. Cereseto, M. Chabab, C. Champion, N. Chau, A. Chen, S. Cherubini, V. Chiarella, T. Chiarusi, M. Circella, R. Cocimano, J. A. B. Coelho, A. Coleiro, M. Colomer Molla, S. Colonges, R. Coniglione, A. Cosquer, P. Coyle, M. Cresta, A. Creuso, A. Cruz, G. Cuttone, A. D’Amico, R. Dallier, B. De Martino, M. De Palma, I. Di Palma, A. F. Díaz, D. Diego- Tortosa, C. Distefano, A. Domi, C. Donzaud, D. Dornic, M. Dörr, D. Drouhin, T. Eberl, A. Eddyamoui, T. van Eeden, D. van Eijk, I. El Bojaddaini, H. Eljarrari, D. Elsaesser, A. Enzenhöfer, V. Espinosa, P. Fermani, G. Ferrara, M. D. Filipovic, F. Filippini, J. Fransen, L. A. Fusco, D. Gajanana, T. Gal, J. García Méndez, A. Garcia Soto, E. Garçon, F. Garufi, C. Gatius, N. Geißelbrecht, L. Gialanella, E. Giorgio, S. R. Gozzini, R. Gracia, K. Graf, G. Grella, D. Guderian, C. Guidi, B. Guillon, M. Gutiérrez, J. Haefner, S. Hallmann, H. Hamdaoui, H. van Haren, A. Heijboer, A. Hekalo, L. Hennig, S. Henry, J. J. Hernández-Rey, J. Hofestädt, F. Huang,W. Idrissi Ibnsalih, A. Ilioni, G. Illuminati, C.W. James, D. Janezashvili, P. Jansweijer, M. de Jong, P. de Jong, B. J. Jung, M. Kadler, P. Kalaczynski, O. Kalekin,U. F. Katz, F. Kayzel, P.Keller, N. R. Khan Chowdhury, G. Kistauri, F. van der Knaap, P. Kooijman, A. Kouchner, M. Kreter, V. Kulikovskiy, M. Labalme, P. Lagier, R. Lahmann, P. Lamare, M. Lamoureux, G. Larosa, C. Lastoria, J. Laurence, A. Lazo, R. Le Breton, E. Le Guirriec, S. Le Stum, G. Lehaut, O. Leonardi, F. Leone, E. Leonora, C. Lerouvillois, J. Lesrel, N. Lessing, G. Levi, M. Lincetto, M. Lindsey Clark, T. Lipreau, C. LLorens Alvarez, A. Lonardo, F. Longhitano, D. Lopez-Coto, N. Lumb, L. Maderer, J. Majumdar, J. Manczak, A. Margiotta, A. Marinelli, A. Marini, C. Markou, L. Martin, J. A. Martínez-Mora, A. Martini, F. Marzaioli, S. Mastroianni, K.W. Melis, G. Miele, P. Migliozzi, E. Migneco, P. Mijakowski, L. S. Miranda, C. M. Mollo, M. Mongelli, A. Moussa, R. Muller, P. Musico, M. Musumeci, L. Nauta, S. Navas, C. A. Nicolau, B. Nkosi, B. Ó Fearraigh, M. O’Sullivan, A. Orlando, G. Ottonello, S. Ottonello, J. Palacios González5, G. Papalashvili, R. Papaleo, C. Pastore, A. M. Paun, G. E. Pavalas, G. Pellegrini, C. Pellegrino, M. Perrin-Terrin, V. Pestel, P. Piattelli, C. Pieterse, O. Pisanti, C. Poirè, V. Popa, T. Pradier, F. Pratolongo, I. Probst, G. Pühlhofer, S. Pulvirenti, G. Quéméner, N. Randazzo, A. Rapicavoli, S. Razzaque, D. Real, S. Reck, G. Riccobene, L. Rigalleau, A. Romanov, A. Rovelli, J. Royon, F. Salesa Greus, D. F. E. Samtleben, A. Sánchez Losa, M. Sanguineti, A. Santangelo, D. Santonocito, P. Sapienza, J. Schmelling, J. Schnabel, M. F. Schneider, J. Schumann, H. M. Schutte, J. Seneca, I. Sgura, R. Shanidze, A. Sharma, A. Sinopoulou, B. Spisso, M. Spurio, D. Stavropoulos, J. Steijger, S. M. Stellacci, M. Taiuti, F. Tatone, Y. Tayalati, E. Tenllado, D. Tézier, T. Thakore, S. Theraube, H. Thiersen, P. Timmer, S. Tingay, S. Tsagkli, V. Tsourapis, E. Tzamariudaki, D. Tzanetatos, C. Valieri, V. Van Elewyck, G. Vasileiadis, F. Versari, S. Viola, D. Vivolo, G. de Wasseige, J.Wilms, R.Wojaczynski, E. deWolf, T. Yousfi, S. Zavatarelli, A. Zegarelli, D. Zito, J. D. Zornoza, J. Zúñiga, N. Zywucka. Postprint (published version

    Hydrotherapy (Project Hydriades)

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    Natural resources are being used for the maintenance of health. According to the Law 3498/2006 of the Greek Parliament the natural health spas must be validated for their therapeutic properties. The Association of Municipalities and Communities of Health Springs of Greece signed a contract with the Research Committee of the Aristotle University of Thessaloniki, Greece, in order to conduct the research programme: ‘Study for the documentation of the therapeutic properties of the thermomineral waters’. The main aim of the project is: (1) the study of biological and therapeutic parameters of the natural health sources, (2) the identification of the indications and contraindications of hydrotherapy. Aims parallel to the main ones have been also set

    Event reconstruction for KM3NeT/ORCA using convolutional neural networks

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    The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches
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