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2nd International Conference on Cloud computing and Big Data, CloudCom-Asia 2015

作者： Xie, Tao Chen, Haibao Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China School of Computer and Information Engineering Chuzhou University Chuzhou239000 China

ISBN: (纸本)9783319284293

It is a huge challenge to deploy a cloud computing system in large-scale data centers. In order to help resolve this issue, we propose an automatic cloud system deployment approach with the characteristics of reliability, availability, and load balance. Specifically, we use workflow to deal with the dependencies among the automatic deployment processes of a cloud system. We also design a failover mechanism to avoid the single point failure of the deployment server. Besides, we adopt a load balancing algorithm to solve the bottleneck problem of deploying a cloud system. We implement a prototype, and evaluate it with 16 physical nodes as well as a virtualized environment with 160 virtual machines. Experimental results show that the average deployment time under our approach is lower than that with traditional deployment methods. In addition, it achieves a cloud system deployment success ratio of up to 90%, even in the high-concurrency environment. © Springer International Publishing Switzerland 2015.

关键词： Cloud computing

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Short: CICC: A fine-grained, semantic-aware, and transparent approach to preventing permission leaks for android permission managers 8

Short: CICC: A fine-grained, semantic-aware, and transparent...

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8th ACM Conference on Security and Privacy in Wireless and Mobile Networks, WiSec 2015

作者： Wang, Daibin Yao, Haixia Li, Yingjiu Jin, Hai Zou, Deqing Deng, Robert H. Services Computing Technology and System Lab. Cluster and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China School of Information Systems Singapore Management University Singapore

ISBN: (纸本)9781450336239

Android's permission system offers an all-or-nothing installation choice for users. To make it more flexible, users may choose a popular app tool, called permission manager, to selectively grant or revoke an app's permissions at runtime. A fundamental requirement for such permission manager is that the granted or revoked permissions should be enforced faithfully. However, we discover that none of existing permission managers meet this requirement due to permission leaks. To address this problem, we propose CICC, a finegrained, semantic-aware, and transparent approach for any permission managers to defend against the permission leaks. Compared to existing solutions, CICC is fine-grained because it detects the permission leaks using call-chain information at the component instance level, instead of at the app level or component level. The fine-grained feature enables it to generate a minimal impact on the usability of running apps. CICC is semantic-aware in a sense that it manages call-chains in the whole lifecycle of each component instance. CICC is transparent to users and app developers, and it requires minor modification to permission managers. Our evaluation shows that CICC incurs relatively low performance overhead and power consumption. Copyright 2015 ACM.

关键词： Android Call-chain Permission leaks Permission manager

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Robust image document authentication code with autonomous biometrie key generation, selection, and updating in cloud environment 11

Robust image document authentication code with autonomous bi...

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11th International Conference on Information Assurance and Security, IAS 2015

作者： Abduljabbar, Zaid Ameen Jin, Hai Hussien, Zaid Alaa Yassin, Ali A. Hussain, Mohammed Abdulridha Abbdal, Salah H. Zou, Deqing Cluster and Grid Computing Lab Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China University of Basrah Basrah Iraq Southern Technical University Basrah Iraq

ISBN: (纸本)9781467387156

Recently, security issues are obstructing the development and using of cloud computing services. Authentication and integrity play an important role in the cloud security, and numerous concerns have been raised to recognize any tampering with exchanges of the image document between two entities (sender and receiver) within the cloud environment. However, none of the existing solutions reduce the probability of known attacks by combining cryptographic hash function with a strong factor that should be periodically changed. For this reason, in this paper we propose a robust one-time image document authentication scheme based on combining non-interactive onetime biometric key and a robust wavelet-based cryptographic hashing scheme. The result of the combination is one-time image document authentication code (OMAC). OMAC is hidden in an image document as a cover image through reversible data embedding steganography. The proposed scheme has several important security attributes, such as key agreement, biometric key management, robust OMAC, invulnerability, and efficiency. In biometric key management, key generation, key selection, and key update algorithms are performed autonomously by the sender and the receiver;thus, no interaction between them is needed. © 2015 IEEE.

关键词： Authentication

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Public auditing for secure data storage in cloud through a third party auditor using modern ciphertext

Public auditing for secure data storage in cloud through a t...

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International Symposium on Information Assurance and Security (IAS)

作者： Zaid Alaa Hussien Hai Jin Zaid Ameen Abduljabbar Ali A. Yassin Mohammed Abdulridha Hussain Salah H. Abbdal Deqing Zou Cluster and Grid Computing Laboratory Services Computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China Cluster and Grid Computing Laboratory Huazhong University of Science and Technology Wuhan China University of Basrah Basrah Iraq

ISBN: (纸本)9781467387163

Outsourced data in cloud and computation results are not always trustworthy because data owners lack physical possession and control over the data as a result of virtualization, replication, and migration techniques. Protecting outsourced data from security threats has become a challenging and potentially formidable task in cloud computing; hence, many schemes have focused on ameliorating this problem and on enabling public auditability for cloud data storage security. These schemes drop into two categories: total computation cost and burden on client side. Researchers have used bilinear map technology with public key cryptography. Although this technology is highly efficient, computation time is long and overhead cost is high. The client needs to perform numerous computations to ensure the integrity of data storage. To reduce auditing cost, we propose an efficient and robust scheme to maintain data integrity in cases that involve public auditing. Our scheme adopts modern cipher cryptography with a cryptographic hash function. We consider allowing a third party auditor to preprocess data on behalf of cloud users before uploading them to cloud service providers and then verifying data integrity afterward. Our proposed scheme has important security characteristics, such as privacy, key management, low cost computation, key exchange, low overhead cost, no burden on client side, inability of cloud service providers to create correct verifier respond without data, and one-time key. Finally, efficiency analysis shows that our scheme is faster and more cost-efficient than the bilinear map-based scheme.

关键词： Cloud computing Cryptography Memory Metadata Outsourcing Protocols

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Detecting clinical progression from abnormal regional brain volumes at baseline in genetic frontotemporal dementia: A GENFI study

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Alzheimer's & Dementia 2021年第S1期17卷

作者： Martina Bocchetta Emily G Todd Jennifer M Nicholas Georgia Peakman David M Cash Rhian S Convery Lucy L Russell David L Thomas Juan Eugenio Iglesias John C van Swieten Lize C. Jiskoot Harro Seelaar Barbara Borroni Daniela Galimberti Raquel Sanchez-Valle Robert Laforce Jr. Fermin Moreno Matthis Synofzik Caroline Graff Mario Masellis Maria Carmela Tartaglia James B Rowe Rik Vandenberghe Elizabeth Finger Fabrizio Tagliavini Alexandre Mendonca Isabel Santana Christopher Butler Simon Ducharme Alexander Gerhard Adrian Danek Johannes Levin Markus Otto Sandro Sorbi Isabelle Le Ber Florence Pasquier Jonathan D Rohrer Genetic Frontotemporal dementia Initiative (GENFI) Dementia Research Centre UCL Queen Square Institute of Neurology University College London London United Kingdom Department of Medical Statistics London School of Hygiene and Tropical Medicine London United Kingdom Dementia Research Centre Department of Neurodegenerative Disease UCL Institute of Neurology Queen Square London United Kingdom Dementia Research Centre Queen Square Institute of Neurology University College London London United Kingdom Centre for Medical Image Computing Department of Medical Physics and Biomedical Engineering University College London London United Kingdom Neuroradiological Academic Unit UCL Queen Square Institute of Neurology UCL London United Kingdom Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA Martinos Center for Biomedical Imaging Massachusetts General Hospital and Harvard Medical School Charlestown MA USA Alzheimer Center Erasmus Medical Center Rotterdam Netherlands Erasmus MC Rotterdam Netherlands Erasmus Medical Center Rotterdam Netherlands Centre for Neurodegenerative Disorders Neurology Unit Department of Clinical and Experimental Sciences University of Brescia Brescia Italy University of Milan Milan Italy Department of Biomedical Surgical and Dental Sciences University of Milan Milan Italy Neurology Department Hospital Clínic Institut d'Investigacions Biomediques Barcelona Spain Clinique Interdisciplinaire de Mémoire CHU de Québec/Université Laval/Hôpital de l’Enfant-Jésus Quebec City QC Canada Hospital Universitario Donostia San Sebastian Spain Centre for Neurology and Hertie-Institute for Clinical Brain Research Hoppe-Seyler-Str Tuebingen Germany Karolinska Institutet Department NVS Division of Neurogeriatrics Karolinska Institutet Stockholm Sweden Unit for Hereditary Dementia Theme Aging Karolinska University Hospital-Solna Stockholm Sweden LC Campbell Cognitive Neurology Research Unit Sunnybrook Research Institute Toronto ON Canada T

Background Genetic frontotemporal dementia is highly heterogeneous, with different progression patterns seen between individuals. Using in vivo MR images from the Genetic FTD Initiative (GENFI), we aimed to identify clinical progression in genetic mutation carriers from their brain volumes at baseline. Method Cortical and subcortical volumes of interest (VOIs) were generated using automated parcellation methods on volumetric 3T T1-weighted MRI scans for 480 carriers (198 GRN , 202 C9orf72 , 80 MAPT ). W-scores for 79 VOIs were computed from a linear regression model carried out on 298 non-carrier cognitively normal controls adjusting for the effect of age, sex, total intracranial volume and scanner type. Carriers were divided into three disease stages based on their global CDR® plus NACC FTLD score (CDR-GS): asymptomatic (0), possibly or mildly symptomatic (0.5) and fully symptomatic (1 or more). Cut-off points for each VOI were derived from Youden indices estimated with ROC curves to distinguish between CDR-GS=0 and CDR-GS≥1 within each gene. CDR-GS=0.5 carriers (30 GRN , 32 C9orf72 , 13 MAPT ) were classified as ‘normal’ or ‘abnormal’ based on these cut-off points. We compared the CDR® plus NACC FTLD sum-of-boxes scores (CDR-SOB) at one year follow-up in these two groups. Result Compared to those with normal baseline volumes, C9orf72 expansion carriers at CDR-GS=0.5 showed significantly higher CDR-SOB scores at follow-up if they had abnormal volumes in the total frontal (+5 points), orbitofrontal (+3), dorsolateral prefrontal (+6), or anterior cingulate (+4) cortices, the basal-paralaminar amygdala region (+2), CA1 region of the hippocampus (+4), total hippocampus (+6), cerebellar lobule VIIIb (+4), or lateral ventricles (+8). GRN mutation carriers showed significantly higher CDR-SOB scores if their volumes were abnormal in the frontal (+10), parietal (+14), insula (+8), orbitofrontal (+12), or medial parietal (+7) cortices, or the total hippocampus (+10). MAPT mu

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From brain volumes to subgroup classification in genetic mutation carriers for frontotemporal dementia: A cluster analysis in the GENFI study

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Alzheimer's & Dementia 2021年第S5期17卷

作者： Martina Bocchetta Emily G. Todd Jennifer M. Nicholas Carolin Heller Imogen J. Swift Georgia Peakman David M. Cash Rhian S. Convery Lucy L. Russell David L. Thomas Juan Eugenio Iglesias John C. van Swieten Lize C. Jiskoot Harro Seelaar Barbara Borroni Daniela Galimberti Raquel Sanchez-Valle Robert Laforce Jr. Fermin Moreno Matthis Synofzik Caroline Graff Mario Masellis Maria Carmela Tartaglia James B. Rowe Rik Vandenberghe Elizabeth Finger Fabrizio Tagliavini Alexandre Mendonca Isabel Santana Christopher Butler Simon Ducharme Alexander Gerhard Adrian Danek Johannes Levin Markus Otto Sandro Sorbi Isabelle Le Ber Florence Pasquier Jonathan D. Rohrer Genetic Frontotemporal dementia Initiative (GENFI) Dementia Research Centre UCL Queen Square Institute of Neurology University College London London United Kingdom Department of Medical Statistics London School of Hygiene and Tropical Medicine London United Kingdom Dementia Research Centre Queen Square Institute of Neurology University College London London United Kingdom Centre for Medical Image Computing Department of Medical Physics and Biomedical Engineering University College London London United Kingdom Dementia Research Centre Department of Neurodegenerative Disease UCL Institute of Neurology Queen Square London United Kingdom Neuroradiological Academic Unit UCL Queen Square Institute of Neurology UCL London United Kingdom Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA Martinos Center for Biomedical Imaging Massachusetts General Hospital and Harvard Medical School Charlestown MA USA Alzheimer Center Erasmus Medical Center Rotterdam Netherlands Erasmus MC Rotterdam Netherlands Erasmus Medical Center Rotterdam Netherlands Centre for Neurodegenerative Disorders Neurology Unit Department of Clinical and Experimental Sciences University of Brescia Brescia Italy University of Milan Milan Italy Department of Biomedical Surgical and Dental Sciences University of Milan Milan Italy Neurology Department Hospital Clínic. Institut d'Investigacions Biomediques Barcelona Spain Clinique Interdisciplinaire de Mémoire CHU de Québec/Université Laval/Hôpital de l’Enfant-Jésus Quebec City QC Canada Hospital Universitario Donostia San Sebastian Spain Centre for Neurology and Hertie-Institute for Clinical Brain Research Hoppe-Seyler-Str Tuebingen Germany Karolinska Institutet Department NVS Division of Neurogeriatrics Karolinska Institutet Stockholm Sweden Unit for Hereditary Dementia Theme Aging Karolinska University Hospital-Solna Stockholm Sweden LC Campbell Cognitive Neurology Research Unit Sunnybrook Research Institute Toronto ON Canada T

Background Genetic frontotemporal dementia (FTD) is highly heterogeneous, with carriers of mutations in the same gene manifesting different phenotypes. Using in vivo MR images from the Genetic FTD Initiative (GENFI), we aimed to identify subgroups within the same genetic group whose brains were affected differently. Method Cortical and subcortical volumes of interest were generated using automated parcellation methods on volumetric 3T T1-weighted MRI scans for 479 carriers (198 GRN , 202 C9orf72 , and 79 MAPT mutation carriers). W-scores for 85 volumes of interest were computed from a linear regression model carried out on 298 non-carrier cognitively normal controls adjusting for the effect of age, sex, total intracranial volume and scanner type. cluster analyses with the Ward agglomerating method were performed on all w-scores while considering the three genetic groups independently. The identified clusters were then compared for age, estimated years from onset, global and sum of boxes scores of the CDR® plus NACC FTLD (at baseline and after one year), neurofilament light chain (NfL) levels in the plasma and w-scores in brain regions typically showing early atrophy (Kruskal-Wallis test). Result We identified three clusters among the GRN mutation carriers and four in the MAPT and C9orf72 groups, which were all significantly different for the variables reported in the Table (p-value<0.003). For all three genetic groups, one cluster was formed by patients with a clinical diagnosis of FTD, with more extensive atrophy and increased disease severity. For the remaining clusters, there seemed to be an association with disease severity for MAPT and GRN mutation carriers but not so for C9orf72 expansion carriers where clinical scores were not clearly associated with a specific cluster. Conclusion By only looking at regional brain volumes, we were able to detect different clusters within carriers of mutations in the same gene, with C9orf72 expansion carriers being the most he

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SKVM: Scaling In-Memory Key-Value Store on Multicore

SKVM: Scaling In-Memory Key-Value Store on Multicore

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IEEE Symposium on computers and Communication

作者： Ran Zheng Wenjin Wang Hai Jin Qin Zhang Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology

ISBN: (纸本)9781467371957

SKVM is a high performance in-memory Key-Value (KV) store for multicore, which is designed for high concurrent data access. There are some problems of existing systems dealing with high concurrent data processing on multicore: lock competition, cache coherency overhead, and large numbers of concurrent network connections. To solve the problems and make the in-memory KV store scale well on multicore, high concurrent data access is divided into two steps: high concurrent connection processing and high concurrent data processing. Half sync/half async model (HSHA) is adopted to eliminate network bottle-neck, which can support high concurrent network connection. Through data partition, lock competition is eliminated and cache movement is reduced. Furthermore, consistent hash is adopted as data distribution strategy which can improve the scalability of system on multicore. Though some of these ideas appear elsewhere, SKVM is the first to combine them together. The experimental results show that SKVM can reach at most 2.4× higher throughput than Memcached, and scales near linearly with the number of cores under any workload.

关键词： In-Memory KV store Multicore Scalability Concurrent data access

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Fine-grained and heterogeneous proxy re-encryption for secure cloud storage

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Chinese science Bulletin 2014年第32期59卷 4201-4209页

作者： Peng Xu Hongwu Chen Deqing Zou Hai Jin Services Computing Technology and System Laboratory Cluster and Grid Computing Laboratory School of Computer Science and Technology Huazhong University of Science and Technology

Cloud is an emerging computing *** has drawn extensive attention from both academia and *** its security issues have been considered as a critical obstacle in its rapid *** data owners store their data as plaintext in cloud,they lose the security of their cloud data due to the arbitrary accessibility,specially accessed by the un-trusted *** order to protect the confidentiality of data owners’cloud data,a promising idea is to encrypt data by data owners before storing them in ***,the straightforward employment of the traditional encryption algorithms can not solve the problem well,since it is hard for data owners to manage their private keys,if they want to securely share their cloud data with others in a fine-grained *** this paper,we propose a fine-grained and heterogeneous proxy re-encryption(FHPRE)system to protect the confidentiality of data owners’cloud *** applying the FH-PRE system in cloud,data owners’cloud data can be securely stored in cloud and shared in a fine-grained ***,the heterogeneity support makes our FH-PRE system more efficient than the previous ***,it provides the secure data sharing between two heterogeneous cloud systems,which are equipped with different cryptographic primitives.

关键词：安全问题数据存储加密算法细粒度异构代理计算模式数据共享

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Cost Minimization for Code Offloading with Cellular Traffic Aggregation

Cost Minimization for Code Offloading with Cellular Traffic ...

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IEEE Symposium on computers and Communication

作者： Jiao Song Feng Lu Hai Jin Zaiyang Tang Peng Li Xiaofei Liao Xia Xie Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China

ISBN: (纸本)9781467371957

Code offloading has been proposed to improve the performance and energy-efficiency of mobile devices by sending heavy computation tasks to resourceful cloud, instead of executing all tasks on local mobile devices. Unfortunately, current code offloading techniques are not efficient enough because of high communication cost. In this paper, we propose a novel code offloading strategy with cellular traffic aggregation that aggregates offloaded codes to several mobile devices before sending them to cloud, which can significantly reduce tail energy effect. With the objective of minimizing the total cost of computation and communication, we propose an optimization framework by jointly considering code partition and traffic aggregation. Due to the hardness of this problem, we design an efficient heuristic algorithm and evaluate its performance via extensive simulations. Simulation results demonstrate that the proposed algorithm significantly outperforms existing schemes.

关键词： Code Offloading Cellular Network Traffic Aggregation Energy Efficiency

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Erratum to: Search for supersymmetry in final states with two same-sign or three leptons and jets using 36 fb−1 of = 13 TeV pp collision data with the ATLAS detector

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Journal of High Energy Physics 2019年第8期2019卷 1-19页

作者： Aaboud, M. Aad, G. Abbott, B. Abdinov, O. Abeloos, B. Abidi, S. H. AbouZeid, O. S. Abraham, N. L. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B. S. Adachi, S. Adamczyk, L. Adelman, J. Adersberger, M. Adye, T. Affolder, A. A. Afik, Y. Agatonovic-Jovin, T. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahlen, S. P. Ahmadov, F. Aielli, G. Akatsuka, S. Akerstedt, H. Åkesson, T. P. A. Akilli, E. Akimov, A. V. Alberghi, G. L. Albert, J. Albicocco, P. Alconada Verzini, M. J. Alderweireldt, S. C. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimonti, G. Alison, J. Alkire, S. P. Allbrooke, B. M. M. Allen, B. W. Allport, P. P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A. A. Alstaty, M. I. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M. G. Amadio, B. T. Amaral Coutinho, Y. Amelung, C. Amidei, D. Amor Dos Santos, S. P. Amoroso, S. Amundsen, G. Anastopoulos, C. Ancu, L. S. Andari, N. Andeen, T. Anders, C. F. Anders, J. K. Anderson, K. J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Angerami, A. Anisenkov, A. V. Anjos, N. Annovi, A. Antel, C. Antonelli, M. Antonov, A. Antrim, D. J. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J. P. Araujo Ferraz, V. Arce, A. T. H. Ardell, R. E. Arduh, F. A. Arguin, J-F. Argyropoulos, S. Arik, M. Armbruster, A. J. Armitage, L. J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N. B. Augsten, K. Avolio, G. Axen, B. Ayoub, M. K. Azuelos, G. Baas, A. E. Baca, M. J. Bachacou, H. Bachas, K. Backes, M. Bagnaia, P. Bahmani, M. Bahrasemani, H. Baines, J. T. Bajic, M. Baker, O. K. Baldin, E. M. Balek, P. Balli, F. Balunas, W. K. Banas, E. Bandyopadhyay, A. Banerjee, Sw. Bannoura, A. A. E. Barak, L. Barberio, E. L. Barberis, D. Barbero, M. Barillari, T. Barisits, M-S Barkeloo, J. T. Barklow, T. Barlow, N. Barnes, S. L. Barnett, B. M. Barnett, R. M. Barnovska-Blenessy, Z Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman U.S.A. Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz U.S.A. Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel Center for High Energy Physics University of Oregon Eugene U.S.A. Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Udine Italy ICTP Trieste Italy Department of Physics King’s College London London United Kingdom International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb U.S.A. Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Institute of Physics University of Belgrade Belgrade Serbia Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas – LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos Universidad de Granada Granada Portugal Department of Physics Boston University Boston U.S.A. Joint Institute for Nuclear Research JINR Dubna Dubna Russia INFN Sezione di Roma Tor Vergata Roma Italy Dip

One correction is made to the figure 4e of the paper.

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