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1,370 results on '"Bruno, Raffaele"'

1. Energy-Efficient Deployment of Stateful FaaS Vertical Applications on Edge Data Networks

Author

Cicconetti, Claudio, Bruno, Raffaele, and Passarella, Andrea

Subjects
Computer Science - Networking and Internet Architecture
Abstract

5G and beyond support the deployment of vertical applications, which is particularly appealing in combination with network slicing and edge computing to create a logically isolated environment for executing customer services. Even if serverless computing has gained significant interest as a cloud-native technology its adoption at the edge is lagging, especially because of the need to support stateful tasks, which are commonplace in, e.g., cognitive services, but not fully amenable to being deployed on limited and decentralized computing infrastructures. In this work, we study the emerging paradigm of stateful Function as a Service (FaaS) with lightweight task abstractions in WebAssembly. Specifically, we assess the implications of deploying inter-dependent tasks with an internal state on edge computing resources using a stateless vs. stateful approach and then derive a mathematical model to estimate the energy consumption of a workload with given characteristics, considering the power used for both processing and communication. The model is used in extensive simulations to determine the impact of key factors and assess the energy trade-offs of stateless vs. stateful., Comment: Accepted for presentation at IEEE ICCCN 2024

Published
2024

3. A Machine-Learned Ranking Algorithm for Dynamic and Personalised Car Pooling Services

Author

Campana, Mattia Giovanni, Delmastro, Franca, and Bruno, Raffaele

Subjects
Computer Science - Information Retrieval, Computer Science - Machine Learning
Abstract

Car pooling is expected to significantly help in reducing traffic congestion and pollution in cities by enabling drivers to share their cars with travellers with similar itineraries and time schedules. A number of car pooling matching services have been designed in order to efficiently find successful ride matches in a given pool of drivers and potential passengers. However, it is now recognised that many non-monetary aspects and social considerations, besides simple mobility needs, may influence the individual willingness of sharing a ride, which are difficult to predict. To address this problem, in this study we propose GoTogether, a recommender system for car pooling services that leverages on learning-to-rank techniques to automatically derive the personalised ranking model of each user from the history of her choices (i.e., the type of accepted or rejected shared rides). Then, GoTogether builds the list of recommended rides in order to maximise the success rate of the offered matches. To test the performance of our scheme we use real data from Twitter and Foursquare sources in order to generate a dataset of plausible mobility patterns and ride requests in a metropolitan area. The results show that the proposed solution quickly obtain an accurate prediction of the personalised user's choice model both in static and dynamic conditions., Comment: Accepted from the IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), 2016

Published
2023
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6. A reinforcement learning-based link quality estimation strategy for RPL and its impact on topology management

Author

Ancillotti, Emilio, Vallati, Carlo, Bruno, Raffaele, and Mingozzi, Enzo

Subjects
Computer Science - Networking and Internet Architecture
Abstract

Over the last few years, standardisation efforts are consolidating the role of the Routing Protocol for LowPower and Lossy Networks (RPL) as the standard routing protocol for IPv6 based Wireless Sensor Networks (WSNs). Although many core functionalities are well defined, others are left implementation dependent. Among them, the definition of an efficient link quality estimation (LQE) strategy is of paramount importance, as it influences significantly both the quality of the selected network routes and nodes' energy consumption. In this paper, we present RLProbe, a novel strategy for link quality monitoring in RPL, which accurately measures link quality with minimal overhead and energy waste. To achieve this goal, RLProbe leverages both synchronous and asynchronous monitoring schemes to maintain up-to-date information on link quality and to promptly react to sudden topology changes, e.g. due to mobility. Our solution relies on a reinforcement learning model to drive the monitoring procedures in order to minimise the overhead caused by active probing operations. The performance of the proposed solution is assessed by means of simulations and real experiments. Results demonstrated that RLProbe helps in effectively improving packet loss rates, allowing nodes to promptly react to link quality variations as well as to link failures due to node mobility.

Published
2022
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7. Reliable data delivery in ICN-IoT environments

Author

Borgia, Eleonora, Bruno, Raffaele, and Passarella, Andrea

Subjects
Computer Science - Networking and Internet Architecture
Abstract

In an IoT environment, which is characterized by a multitude of interconnected smart devices with sensing and computational capabilities, many applications are (i) content-based, that is, they are only interested in finding a given type of content rather than the location of data, and (ii) contextualized, that is, the content is generated and consumed in the proximity of the user. In this context, the Information-Centric Networking (ICN) paradigm is an appealing model for efficiently retrieving application data, and the service decentralization towards the network edge helps to reduce the core network load being the data produced by IoT devices mainly confined in the area where they are generated. MobCCN is an ICN-based data delivery protocol that we designed for operating efficiently in such context [1][2], where static and mobile IoT devices are enriched with ICN functions. Specifically, MobCCN leverages an efficient routing and forwarding protocol, exploiting opportunistic contacts among IoT mobile devices, to fill the Forwarding Interest Base (FIB) tables so as to correctly forward Interest packets towards the intended data producers. In this paper, we aim to enhance the reliability of MobCCN by exploring different retransmissions mechanisms, such as retransmissions based on number of duplicate Interests that are received for the same requested content, periodic retransmissions, single path versus disjoint multi-path forwarding, hysteresis mechanism and combinations of them. Extensive simulation results show that, among the analysed MobCCN variants, the one that implements both periodic retransmissions and a hysteresis-based retransmission process ensures the highest delivery rates (up to 95\%) and the shortest network path, with a very limited traffic overhead due to retransmissions., Comment: This work is partly funded by EC under the H2020 INFRADEV-2019-3 SLICES-DS (951850), the H2020 INFRAIA-02-2020 SLICES-SC (101008468) and the H2020 ICT-2020-1 MARVEL (957337) projects

Published
2022
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8. Cellular traffic offloading via Opportunistic Networking with Reinforcement Learning

Author

Valerio, Lorenzo, Bruno, Raffaele, and Passarella, Andrea

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Machine Learning
Abstract

The widespread diffusion of mobile phones is triggering an exponential growth of mobile data traffic that is likely to cause, in the near future, considerable traffic overload issues even in last-generation cellular networks. Offloading part of the traffic to other networks is considered a very promising approach and, in particular, in this paper, we consider offloading through opportunistic networks of users' devices. However, the performance of this solution strongly depends on the pattern of encounters between mobile nodes, which should therefore be taken into account when designing offloading control algorithms. In this paper, we propose an adaptive offloading solution based on the Reinforcement Learning framework and we evaluate and compare the performance of two well-known learning algorithms: Actor-Critic and Q-Learning. More precisely, in our solution the controller of the dissemination process, once trained, is able to select a proper number of content replicas to be injected into the opportunistic network to guarantee the timely delivery of contents to all interested users. We show that our system based on Reinforcement Learning is able to automatically learn a very efficient strategy to reduce the traffic on the cellular network, without relying on any additional context information about the opportunistic network. Our solution achieves a higher level of offloading with respect to other state-of-the-art approaches, in a range of different mobility settings. Moreover, we show that a more refined learning solution, based on the Actor-Critic algorithm, is significantly more efficient than a simpler solution based on Q-learning.

Published
2021
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9. Human-centric Data Dissemination in the IoP: Large-scale Modeling and Evaluation

Author

Mordacchini, Matteo, Conti, Marco, Passarella, Andrea, and Bruno, Raffaele

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Human-Computer Interaction, I.6.5, I.2.11, I.6.1, I.6.8
Abstract

Data management using Device-to-Device (D2D) communications and opportunistic networks (ONs) is one of the main focuses of human-centric pervasive Internet services. In the recently proposed "Internet of People" paradigm, accessing relevant data dynamically generated in the environment nearby is one of the key services. Moreover, personal mobile devices become proxies of their human users while exchanging data in the cyber world and, thus, largely use ONs and D2D communications for exchanging data directly. Recently, researchers have successfully demonstrated the viability of embedding human cognitive schemes in data dissemination algorithms for ONs. In this paper, we consider one such scheme based on the recognition heuristic, a human decision-making scheme used to efficiently assess the relevance of data. While initial evidence about its effectiveness is available, the evaluation of its behaviour in large-scale settings is still unsatisfactory. To overcome these limitations, we have developed a novel hybrid modelling methodology, which combines an analytical model of data dissemination within small-scale communities of mobile users, with detailed simulations of interactions between different communities. This methodology allows us to evaluate the algorithm in large-scale city- and country-wide scenarios. Results confirm the effectiveness of cognitive data dissemination schemes, even when content popularity is very heterogenous.

Published
2021
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10. Making opportunistic networks in IoT environments CCN-ready: A performance evaluation of the MobCCN protocol

Author

Borgia, Eleonora, Bruno, Raffaele, and Passarella, Andrea

Subjects
Computer Science - Networking and Internet Architecture
Abstract

In future IoT environments it is expected that the role of personal devices of mobile users in the physical area where IoT devices are deployed will become more and more important. In particular, due to the push towards decentralisation of services towards the edge, it is likely that a significant share of data generated by IoT devices will be needed by other (mobile) nodes nearby, while global Internet access will be limited only to a small fraction of data. In this context, opportunistic networking schemes can be adopted to build efficient content-centric protocols, through which data generated by IoT devices (or by mobile nodes themselves) can be accessed by the other nodes nearby. In this paper, we propose MobCCN, which is an ICN-compliant protocol for this heterogeneous environment. MobCCN is designed to implement the routing and forwarding mechanisms of the main ICN realisations, such as CCN. The original aspect of MobCCN is to implement an efficient opportunistic networking routing scheme to populate the Forwarding Interest Base (FIB) tables of the nodes, in order to guide the propagation of Interest packets towards nodes that store the required data. Specifically, MobCCN defines the utility of each node as a forwarder of Interest packets for a certain type of content, such that Interest packets can be propagated along a positive utility gradient, until reaching some node storing the data. We evaluate MobCCN against protocols representing two possible endpoints of the spectrum, respectively in terms of minimising the data delivery delay and the resource consumption. Performance results show that MobCCN is very effective and efficient, as it guarantees very high delivery rates and low delays, while keeping the total generated traffic at a reasonable level and also saving local resources.

Published
2021
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11. Next generation IEEE 802.11 Wireless Local Area Networks: Current status, future directions and open challenges

Author

Bellalta, Boris, Bononi, Luciano, Bruno, Raffaele, and Kassler, Andreas

Subjects
Computer Science - Networking and Internet Architecture
Abstract

new generation of Wireless Local Area Networks (WLANs) will make its appearance in the market in the forthcoming years based on the amendments to the IEEE 802.11 standards that have recently been approved or are under development. Examples of the most expected ones are IEEE 802.11aa (Robust Audio Video Transport Streaming), IEEE 802.11ac (Very-high throughput at < 6 GHz), IEEE 802.11af (TV White Spaces) and IEEE 802.11ah (Machine-to-Machine communications) specifications. The aim of this survey is to provide a comprehensive overview of these novel technical features and the related open technical challenges that will drive the future WLAN evolution. In contrast to other IEEE 802.11 surveys, this is a use case oriented study. Specifically, we first describe the three key scenarios in which next-generation WLANs will have to operate. We then review the most relevant amendments for each of these use cases focusing on the additional functionalities and the new technologies they include, such as multi-user MIMO techniques, groupcast communications, dynamic channel bonding, spectrum databases and channel sensing, enhanced power saving mechanisms and efficient small data transmissions. We also discuss the related work to highlight the key issues that must still be addressed. Finally, we review emerging trends that can influence the design of future WLANs, with special focus on software-defined MACs and the internet-working with cellular systems.

Published
2021
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12. Weak Signals in the Mobility Landscape: Car Sharing in Ten European Cities

Author

Boldrini, Chiara, Bruno, Raffaele, and Laarabi, Haitam

Subjects
Computer Science - Machine Learning, Computer Science - Computers and Society
Abstract

Car sharing is one the pillars of a smart transportation infrastructure, as it is expected to reduce traffic congestion, parking demands and pollution in our cities. From the point of view of demand modelling, car sharing is a weak signal in the city landscape: only a small percentage of the population uses it, and thus it is difficult to study reliably with traditional techniques such as households travel diaries. In this work, we depart from these traditional approaches and we leverage web-based, digital records about vehicle availability in 10 European cities for one of the major active car sharing operators. We discuss which sociodemographic and urban activity indicators are associated with variations in car sharing demand, which forecasting approach (among the most popular in the related literature) is better suited to predict pickup and drop-off events, and how the spatio-temporal information about vehicle availability can be used to infer how different zones in a city are used by customers. We conclude the paper by presenting a direct application of the analysis of the dataset, aimed at identifying where to locate maintenance facilities within the car sharing operation area., Comment: This work was partially funded by the ESPRIT, REPLICATE and SoBigData projects, which have received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements No 653395, No 691735, and No 654024, respectively. arXiv admin note: text overlap with arXiv:1708.00497

Published
2021
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13. Monoclonal antibodies against SARS-CoV-2 to prevent COVID-19 worsening in a large multicenter cohort

Author

Soria, Alessandro, Graziano, Francesca, Ghilardi, Giulia, Lapadula, Giuseppe, Gasperina, Daniela Dalla, Benatti, Simone Vasilij, Quiros-Roldan, Eugenia, Milesi, Maurizio, Bai, Francesca, Merli, Marco, Minisci, Davide, Franzetti, Marco, Asperges, Erika, Chiabrando, Filippo, Pocaterra, Daria, Pandolfo, Alessandro, Zanini, Fabio, Lombardi, Domenico, Cappelletti, Anna, Rugova, Alban, Borghesi, Maria Lucia, Squillace, Nicola, Pusterla, Luigi, Piconi, Stefania, Morelli, Paola, Querini, Patrizia Rovere, Bruno, Raffaele, Rusconi, Stefano, Casari, Salvatore, Bandera, Alessandra, Franzetti, Fabio, Travi, Giovanna, D'Arminio Monforte, Antonella, Marchetti, Giulia, Pan, Angelo, Castelli, Francesco, Rizzi, Marco, Dentali, Francesco, Mallardo, Maria, Rossi, Emanuela, Valsecchi, Maria Grazia, Galimberti, Stefania, and Bonfanti, Paolo

Published
2024
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14. Lack of association between classical HLA genes and asymptomatic SARS-CoV-2 infection

Author

Abel, Laurent, Aiuti, Alessandro, Al-Muhsen, Saleh, Al-Mulla, Fahd, Amara, Ali, Anderson, Mark S., Andreakos, Evangelos, Arias, Andrés A., Arkin, Lisa M., Feldman, Hagit Baris, Bastard, Paul, Belot, Alexandre, Biggs, Catherine M., Bogunovic, Dusan, Bolze, Alexandre, Bondarenko, Anastasiia, Borghesi, Alessandro, Bousfiha, Ahmed A., Brodin, Petter, Bryceson, Yenan, Butte, Manish J., Casanova, Jean-Laurent, Casari, Giorgio, Christodoulou, John, Cobat, Aurélie, Colobran, Roger, Condino-Neto, Antonio, Constantinescu, Stefan N., Cooper, Megan A., Dalgard, Clifton L., Desai, Murkesh, Drolet, Beth A., Duval, Xavier, El Baghdadi, Jamila, Eloy, Philippine, Espinosa-Padilla, Sara, Fellay, Jacques, Flores, Carlos, Franco, José Luis, Froidure, Antoine, Gorochov, Guy, Gregersen, Peter K., Grimbacher, Bodo, Haerynck, Filomeen, Hagin, David, Halwani, Rabih, Hammarström, Lennart, Heath, James R., Hsieh, Elena W.Y., Husebye, Eystein, Imai, Kohsuke, Itan, Yuval, Jouanguy, Emmanuelle, Kaja, Elżbieta, Karamitros, Timokratis, Kisand, Kai, Ku, Cheng-Lung, Lau, Yu-Lung, Ling, Yun, Lucas, Carrie L., Maniatis, Tom, Mansouri, Davood, Maródi, László, Mentré, France, Meyts, Isabelle, Milner, Joshua D., Mironska, Kristina, Mogensen, Trine H., Morio, Tomohiro, Ng, Lisa F.P., Notarangelo, Luigi D., Novelli, Antonio, Novelli, Giuseppe, O'Farrelly, Cliona, Okada, Satoshi, Okamoto, Keisuke, Ozcelik, Tayfun, Pan-Hammarström, Qiang, Pape, Jean W., Perez de Diego, Rebeca, Perez-Tur, Jordi, Perlin, David S., Pesole, Graziano, Planas, Anna M., Prando, Carolina, Pujol, Aurora, Puel, Anne, Quintana-Murci, Lluis, Ramaswamy, Sathishkumar, Renia, Laurent, Resnick, Igor, Rodríguez-Gallego, Carlos, Sancho-Shimizu, Vanessa, Sediva, Anna, Seppänen, Mikko R.J., Shahrooei, Mohammad, Shcherbina, Anna, Slaby, Ondrej, Snow, Andrew L., Soler-Palacín, Pere, Soumelis, Vassili, Spaan, András N., Tancevski, Ivan, Tangye, Stuart G., Tayoun, Ahmad Abou, Temel, Şehime Gülsün, Thorball, Christian, Tiberghien, Pierre, Trouillet-Assant, Sophie, Turvey, Stuart E., Uddin, K. M. Furkan, Uddin, Mohammed J., van de Beek, Diederik, Vinh, Donald C., von Bernuth, Horst, Wauters, Joost, Zatz, Mayana, Zawadzki, Pawel, Zhang, Qian, Zhang, Shen-Ying, Bureau, Serge, Vacher, Yannick, Gysembergh-Houal, Anne, Demerville, Lauren, Benleulmi-Chaachoua, Abla, Abad, Sebastien, Abassi, Radhiya, Abdellaoui, Abdelrafie, Abdelmalek, Abdelkrim, Abdoul, Hendy, Abergel, Helene, Abeud, Fariza, Abgrall, Sophie, Abisror, Noemie, Adechian, Marylise, Aderdour, Nordine, Admane, Hakeem Farid, Adnet, Frederic, Afritt, Sara, Agostini, Helene, Aguilar, Claire, Agut, Sophie, Aiello, Tommaso Francesco, Kaci, Marc Ait, Oufella, Hafid Ait, Ajeenthiravasan, Gokula, Alauzy, Virginie, Alby-Laurent, Fanny, Allard, Lucie, Alyanakian, Marie-Alexandra, Borrero, Blanca Amador, Amam, Sabrina, Amrouche, Lucile, Andronikof, Marc, Anglicheau, Dany, Anguel, Nadia, Annane, Djillali, Aounzou, Mohammed, Aparicio, Caroline, Aratus, Gladys, Arlet, Jean-Benoit, Arzoine, Jeremy, Aslangul, Elisabeth, Assefi, Mona, Aubry, Adeline, Audiffred, Laetitia, Audureau, Etienne, Auger, Christelle Nathalie, Auregan, Jean-Charles, Awotar, Celine, Milla, Sonia Ayllon, Azan, Delphine, Azemar, Laurene, Azzouguen, Billal, Elrufaai, Marwa Bachir, Badsi, Aïda, Bakouboula, Prissile, Balcerowiak, Coline, Balde, Fanta, Baldivia, Elodie, Bangamingo, Eliane-Flore, Baptiste, Amandine, Baran-Marszak, Fanny, Barau, Caroline, Barget, Nathalie, Baronnet, Flore, Barthelemy, Romain, Baudel, Jean-Luc, Baudry, Camille, Baudry, Elodie, Beaugerie, Laurent, Belamri, Adel, Belaube, Nicolas, Belilita, Rhida, Bellassen, Pierre, Belmokhtar, Rawan, Beltran, Isabel, Benainous, Ruben, Benallaoua, Mourad, Benamouzig, Robert, Benbara, Amélie, Benhida, Jaouad, Benkhelouf, Anis, Benlagha, Jihene, Benmostafa, Chahinez, Benothmane, Skander, Bentifraouine, Miassa, Berard, Laurence, Bernier, Quentin, Berti, Enora, Bertier, Astrid, Berton, Laure, Bessis, Simon, Beurton, Alexandra, Bianco, Celine, Bianquis, Clara, Bidar, Frank, Blanche, Philippe, Blayau, Clarisse, Bleibtreu, Alexandre, Blin, Emmanuelle, Bloch-Queyrat, Coralie, Boissier, Marie-Christophe, Bollens, Diane, Bolzoni, Marion, Bompard, Rudy pierre, Bonnet, Nicolas, Bonnouvrier, Justine, Botha, Shirmonecrystal, Boucenna, Wissam, Bouchama, Fatiha, Bouchaud, Olivier, Bouchghoul, Hanane, Boudjebla, Taoueslylia, Boudjema, Noel, Bouffard, Catherine, Bougle, Adrien, Bouguerra, Meriem, Bouras, Leila, Bourcier, Agnes, Durand, Anne Bourgarit, Bourrier, Anne, Bouscarat, Fabrice, Bouvry, Diane, Bouziri, Nesrine, Bouzrara, Ons, Bribier, Sarah, Brugier, Delphine, Brunel, Melanie, Bui, Eida, Buisson, Anne, Bukreyeva, Iryna, Bureau, Côme, Cadranel, Jacques, Cailhol, Johann, Calin, Ruxandra, Vega, Clara Campos, Canavaggio, Pauline, Cancella, Marta, Cantin, Delphine, Cao, Albert, Carbillon, Lionel, Carlier, Nicolas, Cassard, Clementine, Castor, Guylaine, Cauchy, Marion, Cha, Olivier, Chaigne, Benjamin, Challal, Salima, Champion, Karine, Chariot, Patrick, Chas, Julie, Chauveau, Simon, Chauvin, Anthony, Chauvin, Clement, Chavarot, Nathalie, Chebbout, Kamélia, Cherai, Mustapha, Cherubini, Ilaria, Chevalier, Amelie, Chiarabini, Thibault, Chinet, Thierry, Chocron, Richard, Choinier, Pascaline, Chommeloux, Juliette, Choquet, Christophe, Choupeaux, Laure, Chousterman, Benjamin, Ciocan, Dragosmarius, Clarke, Ada, Clavere, Gaëlle, Clavier, Florian, Clement, Karine, Clerc, Sebastien, Cohen, Yves, Cohen, Fleur, Cohen, Adrien, Coilly, Audrey, Colboc, Hester, Colin, Pauline, Collet, Magalie, Comarmond, Chloé, Combacon, Emeline, Combes, Alain, Comparon, Celine, Constantin, Jean-Michel, Cordel, Hugues, Cordier, Anne-Gael, Costantini, Adrien, Chalumeau, Nathalie Costedoat, Couffignal, Camille, Coupeau, Doriane, Creange, Alain, Lamarre, Yannie Cuvillier, Da Silveira, Charlène, Guibal El Kayani, Sandrine Dautheville, De Castro, Nathalie, De Rycke, Yann, Del Pozo, Lucie, Delannoy, Quentin, Delay, Mathieu, Deleris, Robin, Delforge, Juliette, Delphine, Laëtitia, Demare, Noemie, Demeret, Sophie, Demoule, Alexandre, Deniau, Aurore, Depret, François, Derolez, Sophie, Derradji, Ouda, Derridj, Nawal, Descamps, Vincent, Deschamps, Lydia, Desconclois, Celine, Desnos, Cyrielle, Desongins, Karine, Dhote, Robin, Diallo, Benjamin, Didier, Morgane, Diemer, Myriam, Diez, Stephane, Djadi-Prat, Juliette, Djamouri Monnory, Fatima-Zohra, Djebara, Siham, Djebra, Naoual, Djietcheu, Minette, Djillali, Hadjer, Djouadi, Nouara, Donneger, Severine, Santos, Catarina Dos, Dournon, Nathalie, Dres, Martin, Droctove, Laura, Drogrey, Marie, Dropy, Margot, Drouet, Elodie, Dubosq, Valérie, Dubreucq, Evelyne, Dubus, Estelle, Duchemann, Boris, Duchenoy, Thibault, Dudoignon, Emmanuel, Dufau, Romain, Dumas, Florence, Duran, Clara, Duron, Emmanuelle, Durrbach, Antoine, Duvivier, Claudine, Ebstein, Nathan, El Khalifa, Jihane, Elabbadi, Alexandre, Elie, Caroline, Ernotte, Gabriel, Esling, Anne, Etienne, Martin, Eyer, Xavier, Fartoukh, Muriel Sarah, Fayali, Takoua, Fermaut, Marion, Fiorentino, Arianna, Fliss, Souha, Fournier, Marie-Céline, Fournier, Benjamin, Francois, Hélène, Freynet, Olivia, Frigout, Yvann, Fromont, Isaure, Fuentes, Axelle, Furet, Thomas, Galand, Joris, Garnier, Marc, Gaubert, Agnes, Gaudry, Stéphane, Gaugain, Samuel, Gauthier, Damien, Gautier, Maxime, Georgin-Lavialle, Sophie, Geromin, Daniela, Ghalayini, Mohamed, Ghaleh, Bijan, Ghezal, Myriam, Gibelin, Aude, Gimeno, Linda, Girard, Benoit, Leprieur, Bénédicte Giroux, Gomes, Doryan, Gomes-Pires, Elisabete, Gouge, Anne, Gouja, Amel, Goulet, Helene, Goupil, Sylvain, De Bouille, Jeanne Goupil, Gras, Julien, Greffe, Segolene, Grimaldi, Lamiae, Guedeney, Paul, Guidet, Bertrand, Guillo, Matthias, Gulczynski, Mariechristelle, Hadjam, Tassadit, Haguenauer, Didier, Hammal, Soumeya, Hammoudi, Nadjib, Hanon, Olivier, Harrois, Anarole, Hausfater, Pierre, Hautem, Coraline, Hekimian, Guillaume, Heming, Nicholas, Hermine, Olivier, Ho, Sylvie, Houllier, Marie, Huot, Benjamin, Huscenot, Tessa, Saied, Wafa Ibn, Ikherbane, Ghilas, Imarazene, Meriem, Ingiliz, Patrick, Iratni, Lina, Jaureguiberry, Stephane, Jean-Marc, Jean-Francois, Jeyarajasingham, Deleena, Jouany, Pauline, Jouis, Veronique, Jourdaine, Clement, Kafif, Ouifiya, Kallala, Rim, Katsahian, Sandrine, Kelesyan, Lilit, Keo, Vixra, Ketz, Flora, Khamis, Warda, Khelili, Enfel, Khellaf, Mehdi, Kotokpo Youkou, Christy Gaëlla, Kounis, Ilias, Kpalma, Gaelle, Krause, Jessica, Labbe, Vincent, Lacombe, Karine, Lacorte, Jean-Marc, Lafont, Anne Gaelle, Lafont, Emmanuel, Lagha, Lynda, Lamhaut, Lionel, Lancelot, Aymeric, Landman, Cecilia, Lanternier, Fanny, Larcheveque, Cecile, Combe, Caroline Lascoux, Lassel, Ludovic, Laverdant, Benjamin, Lavergne, Christophe, Lavillegrand, Jean-Rémi, Lazureanu, Pompilia, Le Guennec, Loïc, Leberre, Lamia, Leblanc, Claire, Leboyer, Marion, Lecomte, Francois, Lecorre, Marine, Leenhardt, Romain, Lefebvre, Marylou, Lefebvre, Bénédicte, Legendre, Paul, Leger, Anne, Legros, Laurence, Legrosse, Justyna, Lehuunghia, Sébastien, Lemarec, Julien, Leporrier-Ext, Jeremie, Lesein, Manon, Lesur, Hubert, Levy, Vincent, Levy, Albert, Lopes, Edwige, Lopes, Amanda, Lopez, Vanessa, Lopinto, Julien, Lortholary, Olivier, Louadah, Badr, Loze, Bénédicte, Lucas, Marie-Laure, Lucasamichi, Axelle, Luong, Liem Binh, Magazimama-Ext, Arouna, Maingret, David, Mameri, Lakhdar, Manivet, Philippe, Mansouri, Cylia, Marcault, Estelle, Marey, Jonathan, Marin, Nathalie, Marois, Clémence, Martin, Olivier, Martineau, Lou, Martinez-Lopez, Cannelle, Martyniuck, Pierre, De Farcy, Pauline Mary, Marzouk, Nessrine, Masmoudi, Rafik, Mebazaa, Alexandre, Mechai, Frédéric, Mecozzi, Fabio, Mediouni, Chamseddine, Megarbane, Bruno, Meghadecha, Mohamed, Mejean, Élodie, Mekinian, Arsene, Abdelhadi, Nour Mekki, Mekni, Rania, Meliti, Thinhinan Sabrina, Lima, Breno Melo, Meng, Paris, Merbah, Soraya, Messani, Fadhila, Messaoudi, Yasmine, Mewasing, Baboo-Irwinsingh, Meziane, Lydia, Michelot-Burger, Carole, Mignot, Françoise, Minka, Fadi Hillary, Miyara, Makoto, Moine, Pierre, Molina, Jean-Michel, Montegnies-Boulet, Anaïs, Monti, Alexandra, Montlahuc, Claire, Montout, Anne-Lise, Moores, Alexandre, Morbieu, Caroline, Mortelette, Helene, Mouly, Stéphane, Muzaffar, Rosita, Nacerddine, Cherifa Iness, Nadal, Marine, Nadif, Hajer, Nassarmadji, Kladoum, Natella, Pierre, Ndingamondze, Sandrine, Neraal, Stefan, Nguyen, Caroline, N'Guyen, Bao, Larmurier, Isabelle Nion, Nlomenyengue, Luc, Noel, Nicolas, Nunes, Hilario, Omar, Edris, Ouazene, Zineb, Ouedraogo, Elise, Ouelaa, Wassila, Oukhedouma, Anissa, Amara, Yasmina Ould, Oya, Herve, Oziel, Johanna, Padilla, Thomas, Paillaud, Elena, Paiva, Solenne, Parfait, Beatrice, Parize, Perrine, Parizot, Christophe, Parrot, Antoine, Pavot, Arthur, Peaudecerf, Laetitia, Pene, Frédéric, Pepin, Marion, Pernet, Julie, Pernin, Claire, Petit, Mylène, Peyrony, Olivier, Pietri, Marie-Pierre, Pietri, Olivia, De Chambrun, Marc Pineton, Pinson, Michelle, Pintado, Claire, Piquard, Valentine, Pires, Christine, Planquette, Benjamin, Poirier, Sandrine, Pomel, Anne-Laure, Pons, Stéphanie, Ponscarme, Diane, Pourcelot, Annegaelle, Pourcher, Valérie, Pouvaret, Anne, Prever, Florian, Previlon, Miresta, Prevost, Margot, Provoost, Marie-Julie, Quemeneur, Cyril, Rafat, Cédric, Rami, Agathe, Ranque, Brigitte, Raphael, Maurice, Raphalen, Jean Herle, Rastoin, Anna, Raux, Mathieu, Rebai, Amani, Reby, Michael, Regent, Alexis, Regrag, Asma, Resche-Rigon, Matthieu, Ressaire, Quentin, Richard, Christian, Richard, Mariecaroline, Robert, Maxence, Rohaut, Benjamin, Rolland-Debord, Camille, Ropers, Jacques, Roque-Afonso, Anne-Marie, Rosso, Charlotte, Rousseaux, Mélanie, Rousseaux, Nabila, Roux, Swasti, Roux, Lorène, Rouzaud, Claire, Rozes, Antoine, Rubenstein, Emma, Sabate, Jean-Marc, Sabet, Sheila, Sacleux, Sophie-Caroline, Kermanach, Nathalie Saidenberg, Saliba, Faouzi, Salmon, Dominique, Savale, Laurent, Savary, Guillaume, Sberro, Rebecca, Scemla, Anne, Schlemmer, Frederic, Schwartz, Mathieu, Sedfi, Saïd, Sefir-Kribel, Samia, Seksik, Philippe, Sellier, Pierre, Selves, Agathe, Sembach, Nicole, Semerano, Luca, Senat, Marie-Victoire, Sene, Damien, Serris, Alexandra, Sese, Lucile, Sghiouar, Naima, Sigaux, Johanna, Siguier, Martin, Silvain, Johanne, Simon, Noémie, Simon, Tabassome, Skandri, Lina Innes, Slimani, Miassa, Snauwaert, Aurélie, Sokol, Harry, Soliman, Heithem, Soltani, Nisrine, Soyer, Benjamin, Steg, Gabriel, Suarez, Lydia, Szwebel, Tali-Anne, Taffame, Kossi, Tandjaoui-Lambiotte, Yacine, Tantet, Claire, Tateo, Mariagrazia, Theodose, Igor, Thiebaud, Pierre clement, Thomas, Caroline, Tiercelet, Kelly, Tisserand, Julie, Tomczak, Carole, Torelino, Krystel, Touam-Ext, Fatima, Toumi, Lilia, Toury, Gustave, Toy-Miou, Mireille, Dinh Thanh Lien, Olivia Tran, Trandinh, Alexy, Treluyer, Jean-Marc, Trinque, Baptiste, Truchot, Jennifer, Tubach, Florence, Tubiana, Sarah, Tunesi, Simone, Turpin, Matthieu, Turpin, Agathe, Urbina, Tomas, Narvaez, Rafael Usubillaga, Uzunhan, Yurdagul, Vaittinadaayar, Prabakar, Valent, Arnaud, Valentian, Maelle, Valin, Nadia, Vallet, Hélène, Vaz, Marina, Vazquezibarra, Miguel-Alejandro, Vedie, Benoit, Velly, Laetitia, Verstuyft, Celine, Viallette, Cedric, Vicaut, Eric, Vignes, Dorothee, Vimpere, Damien, Virlouvet, Myriam, Voiriot, Guillaume, Voisot, Lena, Weiss, Emmanuel, Weiss, Nicolas, Winchenne, Anaïs, Yordanov, Youri, Zafrani, Lara, Zaidan, Mohamad, Zaidi, Wissem, Zak, Cathia, Zarhrate-Ghoul, Aida, Zatout, Ouassila, Zeino, Suzanne, Zeitouni, Michel, Zemirli, Naïma, Zerah, Lorene, Zia, Ounsa, Ziol, Marianne, Zolario, Oceane, Zuber, Julien, Andrejak, Claire, Angoulvant, François, Bachelet, Delphine, Bartoli, Marie, Basmaci, Romain, Behillil, Sylvie, Beluze, Marine, Benkerrou, Dehbia, Bhavsar, Krishna, Bouadma, Lila, Bouchez, Sabelline, Bouscambert, Maude, Cervantes-Gonzalez, Minerva, Chair, Anissa, Chirouze, Catherine, Coelho, Alexandra, Couffin-Cadiergues, Sandrine, d’Ortenzio, Eric, Debray, Marie-Pierre, Deconinck, Laurene, Deplanque, Dominique, Descamps, Diane, Desvallée, Mathilde, Diallo, Alpha, Diouf, Alphonsine, Dorival, Céline, Dubos, François, Elharrar, Brigitte, Enouf, Vincent, Esperou, Hélène, Esposito-Farese, Marina, Etienne, Manuel, Devouge, Eglantine Ferrand, Gault, Nathalie, Gaymard, Alexandre, Ghosn, Jade, Gigante, Tristan, Gilg, Morgane, Guedj, Jérémie, Hoctin, Alexandre, Hoffmann, Isabelle, Houas, Ikram, Hulot, Jean-Sébastien, Jaafoura, Salma, Kaguelidou, Florentia, Kali, Sabrina, Khalil, Antoine, Khan, Coralie, Laouénan, Cédric, Laribi, Samira, Le, Minh, Le Hingrat, Quentin, Le Mestre, Soizic, Le Nagard, Hervé, Lescure, François-Xavier, Letrou, Sophie, Levy, Yves, Lina, Bruno, Lingas, Guillaume, Lucet, Jean-Christophe, Malvy, Denis, Mambert, Marina, Meziane, Amina, Mouquet, Hugo, Mullaert, Jimmy, Neant, Nadège, Nguyen, Duc, Noret, Marion, Nseir, Saad, Papadopoulos, Aurélie, Paul, Christelle, Peiffer-Smadja, Nathan, Perpoint, Thomas, Petrov-Sanchez, Ventzislava, Peytavin, Gilles, Pham, Huong, Picone, Olivier, Puéchal, Oriane, Rabaud, Christian, Rosa-Calatrava, Manuel, Rossignol, Bénédicte, Rossignol, Patrick, Roy, Carine, Schneider, Marion, Su, Richa, Tardivon, Coralie, Tellier, Marie-Capucine, Téoulé, François, Terrier, Olivier, Timsit, Jean-François, Tual, Christelle, Van Der Werf, Sylvie, Vanel, Noémie, Veislinger, Aurélie, Visseaux, Benoit, Wiedemann, Aurélie, Yazdanpanah, Yazdan, Alavoine, Loubna, Burdet, Charles, Charpentier, Charlotte, Dechanet, Aline, Ecobichon, Jean-Luc, Frezouls, Wahiba, Houhou, Nadhira, Lehacaut, Jonathan, Manchon, Pauline, Nouroudine, Mariama, Quintin, Caroline, Thy, Michael, van der Werf, Sylvie, Vignali, Valérie, Chahine, Abir, Waucquier, Nawal, Migaud, Maria-Claire, Djossou, Félix, Mergeay-Fabre, Mayka, Lucarelli, Aude, Demar, Magalie, Bruneau, Léa, Gérardin, Patrick, Maillot, Adrien, Payet, Christine, Laviolle, Bruno, Laine, Fabrice, Paris, Christophe, Desille-Dugast, Mireille, Fouchard, Julie, Pistone, Thierry, Perreau, Pauline, Gissot, Valérie, Goas, Carole L.E., Montagne, Samatha, Richard, Lucie, Bouiller, Kévin, Desmarets, Maxime, Meunier, Alexandre, Bourgeon, Marilou, Lefévre, Benjamin, Jeulin, Hélène, Legrand, Karine, Lomazzi, Sandra, Tardy, Bernard, Gagneux-Brunon, Amandine, Bertholon, Frédérique, Botelho-Nevers, Elisabeth, Kouakam, Christelle, Nicolas, Leturque, Roufai, Layidé, Amat, Karine, Espérou, Hélène, Hendou, Samia, Foti, Giuseppe, Citerio, Giuseppe, Contro, Ernesto, Pesci, Alberto, Valsecchi, Maria Grazia, Cazzaniga, Marina, Bellani, Giacomo, Abad, Jorge, Accordino, Giulia, Angelini, Micol, Aguilera-Albesa, Sergio, Aguiló-Cucurull, Aina, Özkan, Esra Akyüz, Darazam, Ilad Alavi, Roblero Albisures, Jonathan Antonio, Aldave, Juan C., Ramos, Miquel Alfonso, Khan, Taj Ali, Aliberti, Anna, Nadji, Seyed Alireza, Alkan, Gulsum, AlKhater, Suzan A., Allardet-Servent, Jerome, Allende, Luis M., Alonso-Arias, Rebeca, Alshahrani, Mohammed S., Alsina, Laia, Amoura, Zahir, Antolí, Arnau, Arrestier, Romain, Aubart, Mélodie, Auguet, Teresa, Avramenko, Iryna, Aytekin, Gökhan, Azot, Axelle, Bahram, Seiamak, Bajolle, Fanny, Baldanti, Fausto, Baldolli, Aurélie, Ballester, Maite, Barrou, Benoit, Barzaghi, Federica, Basso, Sabrina, Bayhan, Gulsum Iclal, Bezrodnik, Liliana, Bilbao, Agurtzane, Blanchard-Rohner, Geraldine, Blanco, Ignacio, Blandinières, Adeline, Blázquez-Gamero, Daniel, Bloomfield, Marketa, Bolivar-Prados, Mireia, Borie, Raphael, Botdhlo-Nevers, Elisabeth, Bousquet, Aurore, Boutolleau, David, Bouvattier, Claire, Boyarchuk, Oksana, Bravais, Juliette, Briones, M. Luisa, Brunner, Marie-Eve, Bruno, Raffaele, Bueno, Maria Rita P., Bukhari, Huda, Bustamante, Jacinta, Cáceres Agra, Juan José, Capra, Ruggero, Carapito, Raphael, Carrabba, Maria, Casasnovas, Carlos, Caseris, Marion, Cassaniti, Irene, Castelle, Martin, Castelli, Francesco, Castillo de Vera, Martín, Castro, Mateus V., Catherinot, Emilie, Celik, Jale Bengi, Ceschi, Alessandro, Chalumeau, Martin, Charbit, Bruno, Boulanger, Cécile, Clavé, Père, Clotet, Bonaventura, Codina, Anna, Comarmond, Cloé, Comoli, Patrizia, Corsico, Angelo G., Coşkuner, Taner, Cvetkovski, Aleksandar, Cyrus, Cyril, Dalmau, David, Danion, François, Darley, David Ross, Das, Vincent, Dauby, Nicolas, Dauger, Stéphane, De Munte, Paul, de Pontual, Loic, Dehban, Amin, Delplancq, Geoffroy, Desguerre, Isabelle, Di Sabatino, Antonio, Diehl, Jean-Luc, Dobbelaere, Stephanie, Domínguez-Garrido, Elena, Dubost, Clément, Ekwall, Olov, Bozdemir, Şefika Elmas, Elnagdy, Marwa H., Emiroglu, Melike, Endo, Akifumi, Erdeniz, Emine Hafize, Aytekin, Selma Erol, Etxart Lasa, Maria Pilar, Euvrard, Romain, Fabio, Giovanna, Faivre, Laurence, Falck, Antonin, Fartoukh, Muriel, Faure, Morgane, Arquero, Miguel Fernandez, Ferrer, Ricard, Ferreres, Jose, Francois, Bruno, Fumadó, Victoria, Fung, Kitty S.C., Fusco, Francesca, Gagro, Alenka, Solis, Blanca Garcia, Garçon, Pierre, Gaussem, Pascale, Gayretli, Zeynep, Gil-Herrera, Juana, Gilardin, Laurent, Gatineau, Audrey Giraud, Girona-Alarcón, Mònica, Cifuentes Godínez, Karen Alejandra, Goffard, Jean-Christophe, Gonzales, Nacho, Gonzalez-Granado, Luis I., González-Montelongo, Rafaela, Guerder, Antoine, Gülhan, Belgin, Gumucio, Victor Daniel, Hanitsch, Leif Gunnar, Gunst, Jan, Gut, Marta, Hadjadj, Jérôme, Hancerli, Selda, Hariyan, Tetyana, Hatipoglu, Nevin, Heppekcan, Deniz, Hernandez-Brito, Elisa, Ho, Po-ki, Holanda-Peña, María Soledad, Horcajada, Juan P., Hraiech, Sami, Humbert, Linda, Hung, Ivan F.N., Iglesias, Alejandro D., Íñigo-Campos, Antonio, Jamme, Matthieu, Arranz, María Jesús, Jimeno, Marie-Thérèse, Jordan, Iolanda, Kanık-Yüksek, Saliha, Kara, Yalcin, Karahan, Aydın, Karbuz, Adem, Yasar, Kadriye Kart, Kasapcopur, Ozgur, Kashimada, Kenichi, Keles, Sevgi, Demirkol, Yasemin Kendir, Kido, Yasutoshi, Kizil, Can, Kılıç, Ahmet Osman, Klocperk, Adam, Koutsoukou, Antonia, Król, Zbigniew J., Ksouri, Hatem, Kuentz, Paul, Kwan, Arthur M.C., Kwan, Yat Wah M., Kwok, Janette S.Y., Lagier, Jean-Christophe, Lam, David S.Y., Lampropoulou, Vicky, Le Bourgeois, Fleur, Leo, Yee-Sin, Lopez, Rafael Leon, Leung, Daniel, Levin, Michael, Levy, Michael, Lévy, Romain, Li, Zhi, Lilleri, Daniele, Adrian Bolanos Lima, Edson Jose, Linglart, Agnes, López-Collazo, Eduardo, Lorenzo-Salazar, José M., Louapre, Céline, Lubetzki, Catherine, Lung, Kwok-Cheung, Luyt, Charles-Edouard, Lye, David C., Magnone, Cinthia, Marchioni, Enrico, Marioli, Carola, Marjani, Majid, Marques, Laura, Pereira, Jesus Marquez, Martín-Nalda, Andrea, Pueyo, David Martínez, Martinez-Picado, Javier, Marzana, Iciar, Mata-Martínez, Carmen, Mathian, Alexis, Matos, Larissa R.B., Matthews, Gail V., Mayaux, Julien, McLaughlin-Garcia, Raquel, Meersseman, Philippe, Mège, Jean-Louis, Mekontso-Dessap, Armand, Melki, Isabelle, Meloni, Federica, Meritet, Jean-François, Merlani, Paolo, Akcan, Özge Metin, Mezidi, Mehdi, Migeotte, Isabelle, Millereux, Maude, Million, Matthieu, Mirault, Tristan, Mircher, Clotilde, Mirsaeidi, Mehdi, Mizoguchi, Yoko, Modi, Bhavi P., Mojoli, Francesco, Moncomble, Elsa, Melián, Abián Montesdeoca, Martinez, Antonio Morales, Morandeira, Francisco, Morange, Pierre-Emmanuel, Mordacq, Clémence, Morelle, Guillaume, Mouly, Stéphane J., Muñoz-Barrera, Adrián, Nafati, Cyril, Nagashima, Shintaro, Nakagama, Yu, Neven, Bénédicte, Neves, João Farela, Ng, Yuk-Yung, Hubert Nielly, Medina, Yeray Novoa, Cuadros, Esmeralda Nuñez, Karabela, Semsi Nur, Ocejo-Vinyals, J. Gonzalo, Oualha, Mehdi, Ouedrani, Amani, Özçelik, Tayfun, Ozkaya-Parlakay, Aslinur, Pagani, Michele, Papadaki, Maria, Parola, Philippe, Pascreau, Tiffany, Paul, Stéphane, Paz-Artal, Estela, Pedraza, Sigifredo, González Pellecer, Nancy Carolina, Pellegrini, Silvia, Pérez de Diego, Rebeca, Pérez-Fernández, Xosé Luis, Philippe, Aurélien, Philippot, Quentin, Picod, Adrien, Pineton de Chambrun, Marc, Piralla, Antonio, Planas-Serra, Laura, Ploin, Dominique, Poissy, Julien, Poncelet, Géraldine, Poulakou, Garyphallia, Pouletty, Marie S., Pourshahnazari, Persia, Qiu-Chen, Jia Li, Quentric, Paul, Rambaud, Thomas, Raoult, Didier, Raoult, Violette, Rebillat, Anne-Sophie, Redin, Claire, Resmini, Léa, Ricart, Pilar, Richard, Jean-Christophe, Rigo-Bonnin, Raúl, Rivet, Nadia, Rivière, Jacques G., Rocamora-Blanch, Gemma, Rodero, Mathieu P., Rodrigo, Carlos, Rodriguez, Luis Antonio, Rodriguez-Gallego, Carlos, Rodriguez-Palmero, Agustí, Romero, Carolina Soledad, Rothenbuhler, Anya, Roux, Damien, Rovina, Nikoletta, Rozenberg, Flore, Ruch, Yvon, Ruiz, Montse, Ruiz del Prado, Maria Yolanda, Ruiz-Rodriguez, Juan Carlos, Sabater-Riera, Joan, Saks, Kai, Salagianni, Maria, Sanchez, Oliver, Sánchez-Montalvá, Adrián, Sánchez-Ramón, Silvia, Schidlowski, Laire, Schluter, Agatha, Schmidt, Julien, Schmidt, Matthieu, Schuetz, Catharina, Schweitzer, Cyril E., Scolari, Francesco, Seijo, Luis, Seminario, Analia Gisela, Seng, Piseth, Senoglu, Sevtap, Seppänen, Mikko, Llovich, Alex Serra, Siguret, Virginie, Siouti, Eleni, Smadja, David M., Smith, Nikaia, Sobh, Ali, Solanich, Xavier, Solé-Violán, Jordi, Soler, Catherine, Sözeri, Betül, Stella, Giulia Maria, Stepanovskiy, Yuriy, Stoclin, Annabelle, Taccone, Fabio, Taupin, Jean-Luc, Tavernier, Simon J., Tello, Loreto Vidaur, Terrier, Benjamin, Thiery, Guillaume, Thorn, Karolina, Thumerelle, Caroline, Tipu, Imran, Tolstrup, Martin, Tomasoni, Gabriele, Toubiana, Julie, Alvarez, Josep Trenado, Triantafyllia, Vasiliki, Troya, Jesús, Tsang, Owen T.Y., Tserel, Liina, Tso, Eugene Y.K., Tucci, Alessandra, Tüter Öz, Şadiye Kübra, Ursini, Matilde Valeria, Utsumi, Takanori, Vabres, Pierre, Valencia-Ramos, Juan, Van Den Rym, Ana Maria, Vandernoot, Isabelle, Velez-Santamaria, Valentina, Zuniga Veliz, Silvia Patricia, Vidigal, Mateus C., Viel, Sébastien, Villain, Cédric, Vilaire-Meunier, Marie E., Villar-García, Judit, Vincent, Audrey, Van der Linden, Dimitri, Volokha, Alla, Vuotto, Fanny, Wauters, Els, Wu, Alan K.L., Wu, Tak-Chiu, Yahşi, Aysun, Yesilbas, Osman, Yildiz, Mehmet, Young, Barnaby E., Yükselmiş, Ufuk, Zecca, Marco, Zuccaro, Valentina, Van Praet, Jens, Lambrecht, Bart N., Van Braeckel, Eva, Bosteels, Cédric, Hoste, Levi, Hoste, Eric, Bauters, Fré, De Clercq, Jozefien, Heijmans, Catherine, Slabbynck, Hans, Naesens, Leslie, Florkin, Benoit, Young, Mary-Anne, Willis, Amanda, Lapuente-Suanzes, Paloma, de Andrés-Martín, Ana, Berkell, Matilda, Carelli, Valerio, Fiorentino, Alessia, Malhotra, Surbhi, Mattiaccio, Alessandro, Pippucci, Tommaso, Seri, Marco, Tacconelli, Evelina, van Agtmael, Michiel, Algera, Anne Geke, Appelman, Brent, van Baarle, Frank, Bax, Diane, Beudel, Martijn, Bogaard, Harm Jan, Bomers, Marije, Bonta, Peter, Bos, Lieuwe, Botta, Michela, de Brabander, Justin, de Bree, Godelieve, de Bruin, Sanne, Buis, David T.P., Bugiani, Marianna, Bulle, Esther, Chouchane, Osoul, Cloherty, Alex, Dijkstra, Mirjam, Dongelmans, Dave A., Dujardin, Romein W.G., Elbers, Paul, Fleuren, Lucas, Geerlings, Suzanne, Geijtenbeek, Theo, Girbes, Armand, Goorhuis, Bram, Grobusch, Martin P., Hafkamp, Florianne, Hagens, Laura, Hamann, Jorg, Harris, Vanessa, Hemke, Robert, Hermans, Sabine M., Heunks, Leo, Hollmann, Markus, Horn, Janneke, Hovius, Joppe W., de Jong, Menno D., Koning, Rutger, Lim, Endry H.T., van Mourik, Niels, Nellen, Jeaninne, Nossent, Esther J., Paulus, Frederique, Peters, Edgar, Pina-Fuentes, Dan A.I., van der Poll, Tom, Preckel, Bennedikt, Prins, Jan M., Raasveld, Jorinde, Reijnders, Tom, de Rotte, Maurits C.F. J., Schinkel, Michiel, Schultz, Marcus J., Schrauwen, Femke A.P., Schuurmans, Alex, Schuurmans, Jaap, Sigaloff, Kim, Slim, Marleen A., Smeele, Patrick, Smit, Marry, Stijnis, Cornelis S., Stilma, Willemke, Teunissen, Charlotte, Thoral, Patrick, Tsonas, Anissa M., Tuinman, Pieter R., van der Valk, Marc, Veelo, Denise P., Volleman, Carolien, de Vries, Heder, Vught, Lonneke A., van Vugt, Michèle, Wouters, Dorien, Zwinderman, A.H., Brouwer, Matthijs C., Wiersinga, W. Joost, Vlaar, Alexander P.J., Tompkins, Miranda F., Alba, Camille, Hupalo, Daniel N., Rosenberger, John, Sukumar, Gauthaman, Wilkerson, Matthew D., Zhang, Xijun, Lack, Justin, Oler, Andrew J., Dobbs, Kerry, Delmonte, Ottavia M., Danielson, Jeffrey J., Biondi, Andrea, Bettini, Laura Rachele, D’Angiò, Mariella, Beretta, Ilaria, Imberti, Luisa, Sottini, Alessandra, Quaresima, Virginia, Quiros-Roldan, Eugenia, Rossi, Camillo, Castagnoli, Riccardo, Montagna, Daniela, Licari, Amelia, Marseglia, Gian Luigi, Marchal, Astrid, Cirulli, Elizabeth T., Neveux, Iva, Bellos, Evangelos, Thwaites, Ryan S., Schiabor Barrett, Kelly M., Zhang, Yu, Nemes-Bokun, Ivana, Kalinova, Mariya, Catchpole, Andrew, Lack, Justin B., Chiu, Christopher, and Grzymski, Joseph J.

Published
2024
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19. Dynamics of viral DNA shedding and culture viral DNA positivity in different clinical samples collected during the 2022 mpox outbreak in Lombardy, Italy

Author

Cutrera, Miriam, Cuomo, Marianna, De Poli, Federica, Campanini, Giulia, Pitrolo, Antonino Maria Guglielmo, Iskandar, Elizabeth, Cassaniti, Irene, Bruno, Raffaele, Rizzardini, Giuliano, Puoti, Massimo, Castelli, Francesco, Corsico, Laura, Giacomelli, Andrea, Pozza, Giacomo, Casalini, Giacomo, Raccagni, Angelo, Trentacapilli, Bendetta, Bertoni, Costanza, Bruzzesi, Elena, Candela, Caterina, Tesoro, Daniele, Mule, Giovanni, Bandera, Alessandra, Bianca Mariani, Antonio Muscatello, Maffeo, Manuel, Vecchio, Riccardo, Piccinelli, Sara, Piralla, Antonio, Mileto, Davide, Rizzo, Alberto, Ferrari, Guglielmo, Giardina, Federica, Gaiarsa, Stefano, Petazzoni, Greta, Bianchi, Micol, Salari, Federica, Bracchitta, Fiorenza, Sammartino, Josè Camilla, Ferrari, Alessandro, Gagliardi, Gloria, Mancon, Alessandro, Fenizia, Claudio, Biasin, Mara, Rovida, Francesca, Paolucci, Stefania, Percivalle, Elena, Lombardi, Alessandra, Micheli, Valeria, Nozza, Silvia, Castagna, Antonella, Moschese, Davide, Antinori, Spinello, Gori, Andrea, Bonfanti, Paolo, Rossotti, Roberto, D'Arminio Monforte, Antonella, Attanasi, Federica, Tirani, Marcello, Cereda, Danilo, Baldanti, Fausto, and Gismondo, Maria Rita

Published
2024
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20. Preemptive periodic epidemic control reduces life and healthcare system costs without aggravation of social and economic losses

Author

De Nicolao, Giuseppe, Colaneri, Marta, Di Filippo, Alessandro, Blanchini, Franco, Bolzern, Paolo, Colaneri, Patrizio, Giordano, Giulia, and Bruno, Raffaele

Subjects
Electrical Engineering and Systems Science - Systems and Control, Physics - Physics and Society, Quantitative Biology - Populations and Evolution
Abstract

Many countries are managing COVID-19 epidemic by switching between lighter and heavier restrictions. While an open-close and a close-open cycle have comparable socio-economic costs, the former leads to a much heavier burden in terms of deaths and pressure on the healthcare system. An empirical demonstration of the toll ensuing from procrastination was recently observed in Israel, where both cycles were enforced from late August to mid-December 2020, yielding some 1,600 deaths with open-close compared to 440 with close-open., Comment: 14 pages, 5 figures

Published
2021

21. Vaccination and SARS-CoV-2 variants: how much containment is still needed? A quantitative assessment

Author

Giordano, Giulia, Colaneri, Marta, Di Filippo, Alessandro, Blanchini, Franco, Bolzern, Paolo, De Nicolao, Giuseppe, Sacchi, Paolo, Bruno, Raffaele, and Colaneri, Patrizio

Subjects
Quantitative Biology - Populations and Evolution, Electrical Engineering and Systems Science - Systems and Control, Mathematics - Dynamical Systems
Abstract

Despite the progress in medical care, combined population-wide interventions (such as physical distancing, testing and contact tracing) are still crucial to manage the SARS-CoV-2 pandemic, aggravated by the emergence of new highly transmissible variants. We combine the compartmental SIDARTHE model, predicting the course of COVID-19 infections, with a new data-based model that projects new cases onto casualties and healthcare system costs. Based on the Italian case study, we outline several scenarios: mass vaccination campaigns with different paces, different transmission rates due to new variants, and different enforced countermeasures, including the alternation of opening and closure phases. Our results demonstrate that non-pharmaceutical interventions (NPIs) have a higher impact on the epidemic evolution than vaccination, which advocates for the need to keep containment measures in place throughout the vaccination campaign. We also show that, if intermittent open-close strategies are adopted, deaths and healthcare system costs can be drastically reduced, without any aggravation of socioeconomic losses, as long as one has the foresight to start with a closing phase rather than an opening one.

Published
2021
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22. CovidDeep: SARS-CoV-2/COVID-19 Test Based on Wearable Medical Sensors and Efficient Neural Networks

Author

Hassantabar, Shayan, Stefano, Novati, Ghanakota, Vishweshwar, Ferrari, Alessandra, Nicola, Gregory N., Bruno, Raffaele, Marino, Ignazio R., Hamidouche, Kenza, and Jha, Niraj K.

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Neural and Evolutionary Computing
Abstract

The novel coronavirus (SARS-CoV-2) has led to a pandemic. The current testing regime based on Reverse Transcription-Polymerase Chain Reaction for SARS-CoV-2 has been unable to keep up with testing demands, and also suffers from a relatively low positive detection rate in the early stages of the resultant COVID-19 disease. Hence, there is a need for an alternative approach for repeated large-scale testing of SARS-CoV-2/COVID-19. We propose a framework called CovidDeep that combines efficient DNNs with commercially available WMSs for pervasive testing of the virus. We collected data from 87 individuals, spanning three cohorts including healthy, asymptomatic, and symptomatic patients. We trained DNNs on various subsets of the features automatically extracted from six WMS and questionnaire categories to perform ablation studies to determine which subsets are most efficacious in terms of test accuracy for a three-way classification. The highest test accuracy obtained was 98.1%. We also augmented the real training dataset with a synthetic training dataset drawn from the same probability distribution to impose a prior on DNN weights and leveraged a grow-and-prune synthesis paradigm to learn both DNN architecture and weights. This boosted the accuracy of the various DNNs further and simultaneously reduced their size and floating-point operations., Comment: 11 pages, 3 figures

Published
2020

23. The Dead-Alive Physicist experiment: a case-study disproving the hypothesis that consciousness causes the wave-function collapse in the quantum measurement process

Author

Roselli, Carlo and Stella, Bruno Raffaele

Subjects
Quantum Physics, Physics - History and Philosophy of Physics
Abstract

This paper aims to falsify the hypothesis that the observer's consciousness is necessary for quantum measurement. To achieve our target, we propose a variation of the Schroedinger's cat thought experiment called "DAP", short for "Dead-Alive Physicist", in which a human being replaces the cat. This strategy enables us to logically disprove the consistency of the above hypothesis and to oblige its supporters either to be trapped in solipsism or to rely on an alternative interpretation of quantum mechanics in which the role of the conscious observer has to be reviewed. Our analysis hence provides support to clarify the relationship between the observer the objects of her/his experimental observation; this and a few other implications are discussed in the fourth section and in the conclusions., Comment: 9 pages and 2 figures

Published
2020
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24. A SIDARTHE Model of COVID-19 Epidemic in Italy

Author

Giordano, Giulia, Blanchini, Franco, Bruno, Raffaele, Colaneri, Patrizio, Di Filippo, Alessandro, Di Matteo, Angela, Colaneri, Marta, and Force, the COVID19 IRCCS San Matteo Pavia Task

Subjects
Quantitative Biology - Populations and Evolution, Electrical Engineering and Systems Science - Systems and Control, Mathematics - Dynamical Systems
Abstract

In late December 2019, a novel strand of Coronavirus (SARS-CoV-2) causing a severe, potentially fatal respiratory syndrome (COVID-19) was identified in Wuhan, Hubei Province, China and is causing outbreaks in multiple world countries, soon becoming a pandemic. Italy has now become the most hit country outside of Asia: on March 16, 2020, the Italian Civil Protection documented a total of 27980 confirmed cases and 2158 deaths of people tested positive for SARS-CoV-2. In the context of an emerging infectious disease outbreak, it is of paramount importance to predict the trend of the epidemic in order to plan an effective control strategy and to determine its impact. This paper proposes a new epidemic model that discriminates between infected individuals depending on whether they have been diagnosed and on the severity of their symptoms. The distinction between diagnosed and non-diagnosed is important because non-diagnosed individuals are more likely to spread the infection than diagnosed ones, since the latter are typically isolated, and can explain misperceptions of the case fatality rate and of the seriousness of the epidemic phenomenon. Being able to predict the amount of patients that will develop life-threatening symptoms is important since the disease frequently requires hospitalisation (and even Intensive Care Unit admission) and challenges the healthcare system capacity. We show how the basic reproduction number can be redefined in the new framework, thus capturing the potential for epidemic containment. Simulation results are compared with real data on the COVID-19 epidemic in Italy, to show the validity of the model and compare different possible predicted scenarios depending on the adopted countermeasures.

Published
2020
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25. Performance of an AI algorithm during the different phases of the COVID pandemics: what can we learn from the AI and vice versa.

Author

Catalano, Michele, Bortolotto, Chandra, Nicora, Giovanna, Achilli, Marina Francesca, Consonni, Alessio, Ruongo, Lidia, Callea, Giovanni, Lo Tito, Antonio, Biasibetti, Carla, Donatelli, Antonella, Cutti, Sara, Comotto, Federico, Stella, Giulia Maria, Corsico, Angelo, Perlini, Stefano, Bellazzi, Riccardo, Bruno, Raffaele, Filippi, Andrea, and Preda, Lorenzo

Published
2023
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26. Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortium

Author

Aaron, James R., Adam, Atif, Agapito, Giuseppe, Albayrak, Adem, Albi, Giuseppe, Alessiani, Mario, Alloni, Anna, Amendola, Danilo F., Angoulvant, François, Anthony, Li LLJ., Aronow, Bruce J., Ashraf, Fatima, Atz, Andrew, Avillach, Paul, Panickan, Vidul Ayakulangara, Azevedo, Paula S., Badenes, Rafael, Balshi, James, Batugo, Ashley, Beaulieu-Jones, Brendin R., Beaulieu-Jones, Brett K., Bell, Douglas S., Bellasi, Antonio, Bellazzi, Riccardo, Benoit, Vincent, Beraghi, Michele, Bernal-Sobrino, José Luis, Bernaux, Mélodie, Bey, Romain, Bhatnagar, Surbhi, Blanco-Martínez, Alvar, Boeker, Martin, Bonzel, Clara-Lea, Booth, John, Bosari, Silvano, Bourgeois, Florence T., Bradford, Robert L., Brat, Gabriel A., Bréant, Stéphane, Brown, Nicholas W., Bruno, Raffaele, Bryant, William A., Bucalo, Mauro, Bucholz, Emily, Burgun, Anita, Cai, Tianxi, Cannataro, Mario, Carmona, Aldo, Cattelan, Anna Maria, Caucheteux, Charlotte, Champ, Julien, Chen, Jin, Chen, Krista Y., Chiovato, Luca, Chiudinelli, Lorenzo, Cho, Kelly, Cimino, James J., Colicchio, Tiago K., Cormont, Sylvie, Cossin, Sébastien, Craig, Jean B., Cruz-Bermúdez, Juan Luis, Cruz-Rojo, Jaime, Dagliati, Arianna, Daniar, Mohamad, Daniel, Christel, Das, Priyam, Devkota, Batsal, Dionne, Audrey, Duan, Rui, Dubiel, Julien, DuVall, Scott L., Esteve, Loic, Estiri, Hossein, Fan, Shirley, Follett, Robert W., Ganslandt, Thomas, García-Barrio, Noelia, Garmire, Lana X., Gehlenborg, Nils, Getzen, Emily J., Geva, Alon, Goh, Rachel SJ., González, Tomás González, Gradinger, Tobias, Gramfort, Alexandre, Griffier, Romain, Griffon, Nicolas, Grisel, Olivier, Gutiérrez-Sacristán, Alba, Guzzi, Pietro H., Han, Larry, Hanauer, David A., Haverkamp, Christian, Hazard, Derek Y., He, Bing, Henderson, Darren W., Hilka, Martin, Ho, Yuk-Lam, Holmes, John H., Honerlaw, Jacqueline P., Hong, Chuan, Huling, Kenneth M., Hutch, Meghan R., Issitt, Richard W., Jannot, Anne Sophie, Jouhet, Vianney, Kainth, Mundeep K., Kate, Kernan F., Kavuluru, Ramakanth, Keller, Mark S., Kennedy, Chris J., Kernan, Kate F., Key, Daniel A., Kirchoff, Katie, Klann, Jeffrey G., Kohane, Isaac S., Krantz, Ian D., Kraska, Detlef, Krishnamurthy, Ashok K., L'Yi, Sehi, Leblanc, Judith, Lemaitre, Guillaume, Lenert, Leslie, Leprovost, Damien, Liu, Molei, Will Loh, Ne Hooi, Long, Qi, Lozano-Zahonero, Sara, Luo, Yuan, Lynch, Kristine E., Mahmood, Sadiqa, Maidlow, Sarah E., Makoudjou, Adeline, Makwana, Simran, Malovini, Alberto, Mandl, Kenneth D., Mao, Chengsheng, Maram, Anupama, Maripuri, Monika, Martel, Patricia, Martins, Marcelo R., Marwaha, Jayson S., Masino, Aaron J., Mazzitelli, Maria, Mazzotti, Diego R., Mensch, Arthur, Milano, Marianna, Minicucci, Marcos F., Moal, Bertrand, Ahooyi, Taha Mohseni, Moore, Jason H., Moraleda, Cinta, Morris, Jeffrey S., Morris, Michele, Moshal, Karyn L., Mousavi, Sajad, Mowery, Danielle L., Murad, Douglas A., Murphy, Shawn N., Naughton, Thomas P., Breda Neto, Carlos Tadeu, Neuraz, Antoine, Newburger, Jane, Ngiam, Kee Yuan, Njoroge, Wanjiku FM., Norman, James B., Obeid, Jihad, Okoshi, Marina P., Olson, Karen L., Omenn, Gilbert S., Orlova, Nina, Ostasiewski, Brian D., Palmer, Nathan P., Paris, Nicolas, Patel, Lav P., Pedrera-Jiménez, Miguel, Pfaff, Ashley C., Pfaff, Emily R., Pillion, Danielle, Pizzimenti, Sara, Priya, Tanu, Prokosch, Hans U., Prudente, Robson A., Prunotto, Andrea, Quirós-González, Víctor, Ramoni, Rachel B., Raskin, Maryna, Rieg, Siegbert, Roig-Domínguez, Gustavo, Rojo, Pablo, Romero-Garcia, Nekane, Rubio-Mayo, Paula, Sacchi, Paolo, Sáez, Carlos, Salamanca, Elisa, Samayamuthu, Malarkodi Jebathilagam, Sanchez-Pinto, L. Nelson, Sandrin, Arnaud, Santhanam, Nandhini, Santos, Janaina C.C., Sanz Vidorreta, Fernando J., Savino, Maria, Schriver, Emily R., Schubert, Petra, Schuettler, Juergen, Scudeller, Luigia, Sebire, Neil J., Serrano-Balazote, Pablo, Serre, Patricia, Serret-Larmande, Arnaud, Shah, Mohsin A., Hossein Abad, Zahra Shakeri, Silvio, Domenick, Sliz, Piotr, Son, Jiyeon, Sonday, Charles, South, Andrew M., Sperotto, Francesca, Spiridou, Anastasia, Strasser, Zachary H., Tan, Amelia LM., Tan, Bryce W.Q., Tan, Byorn W.L., Tanni, Suzana E., Taylor, Deanne M., Terriza-Torres, Ana I., Tibollo, Valentina, Tippmann, Patric, Toh, Emma MS., Torti, Carlo, Trecarichi, Enrico M., Vallejos, Andrew K., Varoquaux, Gael, Vella, Margaret E., Verdy, Guillaume, Vie, Jill-Jênn, Visweswaran, Shyam, Vitacca, Michele, Wagholikar, Kavishwar B., Waitman, Lemuel R., Wang, Xuan, Wassermann, Demian, Weber, Griffin M., Wolkewitz, Martin, Wong, Scott, Xia, Zongqi, Xiong, Xin, Ye, Ye, Yehya, Nadir, Yuan, William, Zachariasse, Joany M., Zahner, Janet J., Zambelli, Alberto, Zhang, Harrison G., Zöller, Daniela, Zuccaro, Valentina, Zucco, Chiara, Li, Xiudi, Rofeberg, Valerie N., Elias, Matthew D., Laird-Gion, Jessica, and Newburger, Jane W.

Published
2023
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27. Characterization of long COVID temporal sub-phenotypes by distributed representation learning from electronic health record data: a cohort study

Author

Aaron, James R., Agapito, Giuseppe, Albayrak, Adem, Albi, Giuseppe, Alessiani, Mario, Alloni, Anna, Amendola, Danilo F., François Angoulvant, Anthony, Li L.L.J., Aronow, Bruce J., Ashraf, Fatima, Atz, Andrew, Avillach, Paul, Azevedo, Paula S., Balshi, James, Beaulieu-Jones, Brett K., Bell, Douglas S., Bellasi, Antonio, Bellazzi, Riccardo, Benoit, Vincent, Beraghi, Michele, Bernal-Sobrino, José Luis, Bernaux, Mélodie, Bey, Romain, Bhatnagar, Surbhi, Blanco-Martínez, Alvar, Bonzel, Clara-Lea, Booth, John, Bosari, Silvano, Bourgeois, Florence T., Bradford, Robert L., Brat, Gabriel A., Bréant, Stéphane, Brown, Nicholas W., Bruno, Raffaele, Bryant, William A., Bucalo, Mauro, Bucholz, Emily, Burgun, Anita, Cai, Tianxi, Cannataro, Mario, Carmona, Aldo, Caucheteux, Charlotte, Champ, Julien, Chen, Jin, Chen, Krista Y., Chiovato, Luca, Chiudinelli, Lorenzo, Cho, Kelly, Cimino, James J., Colicchio, Tiago K., Cormont, Sylvie, Cossin, Sébastien, Craig, Jean B., Cruz-Bermúdez, Juan Luis, Cruz-Rojo, Jaime, Dagliati, Arianna, Daniar, Mohamad, Daniel, Christel, Das, Priyam, Devkota, Batsal, Dionne, Audrey, Duan, Rui, Dubiel, Julien, DuVall, Scott L., Esteve, Loic, Estiri, Hossein, Fan, Shirley, Follett, Robert W., Ganslandt, Thomas, Barrio, Noelia García, Garmire, Lana X., Gehlenborg, Nils, Getzen, Emily J., Geva, Alon, Gradinger, Tobias, Gramfort, Alexandre, Griffier, Romain, Griffon, Nicolas, Grisel, Olivier, Gutiérrez-Sacristán, Alba, Han, Larry, Hanauer, David A., Haverkamp, Christian, Hazard, Derek Y., He, Bing, Henderson, Darren W., Hilka, Martin, Ho, Yuk-Lam, Holmes, John H., Hong, Chuan, Huling, Kenneth M., Hutch, Meghan R., Issitt, Richard W., Jannot, Anne Sophie, Jouhet, Vianney, Kavuluru, Ramakanth, Keller, Mark S., Kennedy, Chris J., Key, Daniel A., Kirchoff, Katie, Klann, Jeffrey G., Kohane, Isaac S., Krantz, Ian D., Kraska, Detlef, Krishnamurthy, Ashok K., L'Yi, Sehi, Le, Trang T., Leblanc, Judith, Lemaitre, Guillaume, Lenert, Leslie, Leprovost, Damien, Liu, Molei, Will Loh, Ne Hooi, Long, Qi, Lozano-Zahonero, Sara, Luo, Yuan, Lynch, Kristine E., Mahmood, Sadiqa, Maidlow, Sarah E., Makoudjou, Adeline, Malovini, Alberto, Mandl, Kenneth D., Mao, Chengsheng, Maram, Anupama, Martel, Patricia, Martins, Marcelo R., Marwaha, Jayson S., Masino, Aaron J., Mazzitelli, Maria, Mensch, Arthur, Milano, Marianna, Minicucci, Marcos F., Moal, Bertrand, Ahooyi, Taha Mohseni, Moore, Jason H., Moraleda, Cinta, Morris, Jeffrey S., Morris, Michele, Moshal, Karyn L., Mousavi, Sajad, Mowery, Danielle L., Murad, Douglas A., Murphy, Shawn N., Naughton, Thomas P., Breda Neto, Carlos Tadeu, Neuraz, Antoine, Newburger, Jane, Ngiam, Kee Yuan, Njoroge, Wanjiku F.M., Norman, James B., Obeid, Jihad, Okoshi, Marina P., Olson, Karen L., Omenn, Gilbert S., Orlova, Nina, Ostasiewski, Brian D., Palmer, Nathan P., Paris, Nicolas, Patel, Lav P., Pedrera-Jiménez, Miguel, Pfaff, Emily R., Pfaff, Ashley C., Pillion, Danielle, Pizzimenti, Sara, Prokosch, Hans U., Prudente, Robson A., Prunotto, Andrea, Quirós-González, Víctor, Ramoni, Rachel B., Raskin, Maryna, Rieg, Siegbert, Roig-Domínguez, Gustavo, Rojo, Pablo, Rubio-Mayo, Paula, Sacchi, Paolo, Sáez, Carlos, Salamanca, Elisa, Samayamuthu, Malarkodi Jebathilagam, Sanchez-Pinto, L. Nelson, Sandrin, Arnaud, Santhanam, Nandhini, Santos, Janaina C.C., Sanz Vidorreta, Fernando J., Savino, Maria, Schriver, Emily R., Schubert, Petra, Schuettler, Juergen, Scudeller, Luigia, Sebire, Neil J., Serrano-Balazote, Pablo, Serre, Patricia, Serret-Larmande, Arnaud, Shah, Mohsin, Hossein Abad, Zahra Shakeri, Silvio, Domenick, Sliz, Piotr, Son, Jiyeon, Sonday, Charles, South, Andrew M., Spiridou, Anastasia, Strasser, Zachary H., Tan, Amelia L.M., Tan, Bryce W.Q., Tan, Byorn W.L., Tanni, Suzana E., Taylor, Deanne M., Terriza-Torres, Ana I., Tibollo, Valentina, Tippmann, Patric, Toh, Emma M.S., Torti, Carlo, Trecarichi, Enrico M., Tseng, Yi-Ju, Vallejos, Andrew K., Varoquaux, Gael, Vella, Margaret E., Verdy, Guillaume, Vie, Jill-Jênn, Visweswaran, Shyam, Vitacca, Michele, Wagholikar, Kavishwar B., Waitman, Lemuel R., Wang, Xuan, Wassermann, Demian, Weber, Griffin M., Wolkewitz, Martin, Wong, Scott, Xia, Zongqi, Xiong, Xin, Ye, Ye, Yehya, Nadir, Yuan, William, Zambelli, Alberto, Zhang, Harrison G., Zo¨ller, Daniela, Zuccaro, Valentina, Zucco, Chiara, Mesa, Rebecca, and Verdy, Guillame

Published
2023
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31. User-Based Relocation of Stackable Car Sharing

Author

Laarabi, Haitam, Boldrini, Chiara, Bruno, Raffaele, Porter, Helen, and Davidson, Peter

Subjects
Built Environment and Design, Commerce, Management, Tourism and Services, Engineering, Transportation, Logistics and Supply Chains, Civil Engineering, Urban and Regional Planning
Abstract

The relocation of carsharing vehicles is one of the main challenges facing its economic viability, in addition to the operational costs and infrastructure deployment. In this paper, we take advantage of an innovative technological proposal of a one-way carsharing system, to test and validate a user-based relocation strategy. The new technology allows vehicles to be driven in a road train by either an operator (up until eight vehicles) or a customer (up to two). The proposed strategy encourages a customer to take a second vehicle along the way, when he/she happens to be moving from a station with excess of vehicles, to a deficient station. As a case study, we have considered a suburban area of the city of Lyon, of which we have a 2015 household travel survey to build a synthetic population undertaking various activities during a day. Then, we inject this population in a detailed multi-agent and multi-modal transport simulation model, to compare the relocation performance of a lower/upper-bound availability algorithm with three other naively intuitive algorithms. The study shows that: (i) relocation algorithm is very sensitive to the ratio of parking slots to fleet size, and (ii) with the right infrastructure we can relocate one vehicle and generate at least one additional trip.

Published
2019

35. Relocation in Car Sharing Systems with Shared Stackable Vehicles: Modelling Challenges and Outlook

Author

Boldrini, Chiara, Incaini, Riccardo, and Bruno, Raffaele

Subjects
Computer Science - Performance
Abstract

Car sharing is expected to reduce traffic congestion and pollution in cities while at the same time improving accessibility to public transport. However, the most popular form of car sharing, one-way car sharing, still suffers from the vehicle unbalance problem. Innovative solutions to this issue rely on custom vehicles with stackable capabilities: customers or operators can drive a train of vehicles if necessary, thus efficiently bringing several cars from an area with few requests to an area with many requests. However, how to model a car sharing system with stackable vehicles is an open problem in the related literature. In this paper, we propose a queueing theoretical model to fill this gap, and we use this model to derive an upper-bound on user-based relocation capabilities. We also validate, for the first time in the related literature, legacy queueing theoretical models against a trace of real car sharing data. Finally, we present preliminary results about the impact, on car availability, of simple user-based relocation heuristics with stackable vehicles. Our results indicate that user-based relocation schemes that exploit vehicle stackability can significantly improve car availability at stations., Comment: IEEE ITSC 2017: 20th International Conference on Intelligent Transportation Systems, Yokohama, Japan. October 16 - 19, 2017

Published
2017

36. Stackable vs Autonomous Cars for Shared Mobility Systems: a Preliminary Performance Evaluation

Author

Boldrini, Chiara and Bruno, Raffaele

Subjects
Computer Science - Other Computer Science
Abstract

Car sharing is one of the key elements of a Mobility-on-Demand system, but it still suffers from several shortcomings, the most significant of which is the fleet unbalance during the day. What is typically observed in car sharing systems, in fact, is a vehicle shortage in so-called hot spots (i.e., areas with high demand) and vehicle accumulation in cold spots, due to the patterns in people flows during the day. In this work, we overview the main approaches to vehicle redistribution based on the type of vehicles the car sharing fleet is composed of, and we evaluate their performance using a realistic car sharing demand derived for a suburban area around Lyon, France. The main result of this paper is that stackable vehicles can achieve a relocation performance close to that of autonomous vehicles, significantly improving over the no-relocation approach and over traditional relocation with standard cars., Comment: Accepted at the MoD@ITSC2017 workshop

Published
2017

37. Car sharing through the data analysis lens

Author

Boldrini, Chiara, Bruno, Raffaele, and Laarabi, Haitam

Subjects
Computer Science - Computers and Society, Computer Science - Databases, Computer Science - Learning
Abstract

Car sharing is one the pillars of a smart transportation infrastructure, as it is expected to reduce traffic congestion, parking demands and pollution in our cities. From the point of view of demand modelling, car sharing is a weak signal in the city landscape: only a small percentage of the population uses it, and thus it is difficult to study reliably with traditional techniques such as households travel diaries. In this work, we depart from these traditional approaches and we rely on web-based, digital records about vehicle availability in 10 European cities for one of the major active car sharing operators. We discuss how vehicles are used, what are the main characteristics of car sharing trips, whether events happening in certain areas are predictable or not, and how the spatio-temporal information about vehicle availability can be used to infer how different zones in a city are used by customers. We conclude the paper by presenting a direct application of the analysis of the dataset, aimed at identifying where to locate maintenance facilities within the car sharing operational area., Comment: Accepted for KNOWMe: 1st International Workshop on Knowledge Discovery from Mobility and Transportation Systems (colocated with PKDD 2017)

Published
2017

39. The early phase of the COVID-19 epidemic in Lombardy, Italy

Author

Cereda, Danilo, Manica, Mattia, Tirani, Marcello, Rovida, Francesca, Demicheli, Vittorio, Ajelli, Marco, Poletti, Piero, Trentini, Filippo, Guzzetta, Giorgio, Marziano, Valentina, Piccarreta, Raffaella, Barone, Antonio, Magoni, Michele, Deandrea, Silvia, Diurno, Giulio, Lombardo, Massimo, Faccini, Marino, Pan, Angelo, Bruno, Raffaele, Pariani, Elena, Grasselli, Giacomo, Piatti, Alessandra, Gramegna, Maria, Baldanti, Fausto, Melegaro, Alessia, and Merler, Stefano

Published
2021
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40. Clinical features and comorbidity pattern of HCV infected migrants compared to native patients in care in Italy: A real-life evaluation of the PITER cohort

Author

Mazzaro, Cesare, Bertola, Manuela, Schioppa, Ornella, Benedetti, Antonio, Schiadà, Laura, Cucco, Monica, Giacometti, Andrea, Brescini, Laura, Castelletti, Sefora, Fiorentini, Alessandro, Angarano, Gioacchino, Milella, Michele, Di Leo, Alfredo, Rendina, Maria, D'abramo, Fulvio Salvatore, Lillo, Chiara, Iannone, Andrea, Piazzolla, Mariano, Verucchi, Gabriella, Badia, Lorenzo, Piscaglia, Fabio, Benevento, Francesca, Serio, Ilaria, Castelli, Francesco, Zaltron, Serena, Spinetti, Angiola, Odolini, Silvia, Bruno, Raffaele, Mondelli, Mario, Chessa, Luchino, Loi, Martina, Torti, Carlo, Costa, Chiara, Mazzitelli, Maria, Pisani, Vincenzo, Scaglione, Vincenzo, Trecarichi, Enrico Maria, Zignego, Anna Linda, Monti, Monica, Madia, Francesco, Blanc, Pier Luigi, Attala, Letizia, Pierotti, Piera, Salomoni, Elena, Mariabelli, Elisa, Santantonio, Teresa Antonia, Bruno, Serena Rita, Cela, Ester Marina, Bassetti, Matteo, Mazzarello, Giovanni, Alessandrini, Anna Ida, Di Biagio, Antonio, Nicolini, Laura Ambra, Raimondo, Giovanni, Filomia, Roberto, Aghemo, Alessio, Meli, Rossella, Lazzarin, Adriano, Morsica, Giulia, Salpietro, Stefania, Galli, Massimo, Fracanzani, Anna Ludovica, Fatta, Erika, Lombardi, Rosa, Lampertico, Pietro, Borghi, Marta, D'ambrosio, Roberta, Degasperi, Elisabetta, Puoti, Massimo, Baiguera, Chiara, D'amico, Federico, Vinci, Maria, Rumi, Maria Grazia, Zuin, Massimo, Giorgini, Alessia, Zermiani, Paola, Andreone, Pietro, Caraceni, Paolo, Margotti, Marzia, Guarneri, Valeria, Villa, Erica, Bernabucci, Veronica, Bristot, Laura, Paradiso, Maria Luisa, Migliorino, Guglielmo, Beretta, Ilaria, Gambaro, Alessandra, Lapadula, Giuseppe, Spolti, Anna, Soria, Alessandro, Invernizzi, Pietro, Ciaccio, Antonio, LucÀ, Martina, Malinverno, Federica, Ratti, Laura, Coppola, Carmine, Amoruso, Daniela Caterina, Pisano, Federica, Scarano, Ferdinando, Staiano, Laura, Morisco, Filomena, Cossiga, Valentina, Gentile, Ivan, Buonomo, Antonio Riccardo, Foggia, Maria, Zappulo, Emanuela, Federico, Alessandro, Dallio, Marcello, Coppola, Nicola, Sagnelli, Caterina, Martini, Salvatore, Monari, Caterina, Nardone, Gerardo, Sgamato, Costantino, Chemello, Liliana, Cavalletto, Luisa, Sterrantino, Daniela, Russo, Francesco Paolo, Zanetto, Alberto, Zanaga, Paola, Barbaro, Francesco, Brancaccio, Giuseppina, Craxì, Antonio, Petta, Salvatore, Calvaruso, Vincenza, Crapanzano, Luciano, Madonia, Salvatore, Cannizzaro, Marco, Bruno, Erica Maria, Licata, Anna, Amodeo, Simona, Capitano, Adele Rosaria, Ferrari, Carlo, Laccabue, Diletta, Negri, Elisa, Orlandini, Alessandra, Pesci, Marco, Gulminetti, Roberto, Pagnucco, Layla, Parruti, Giustino, Di Stefano, Paola, Brunetto, Maurizia Rossana, Coco, Barbara, Massari, Marco, Corsini, Romina, Garlassi, Elisa, Andreoni, Massimo, Teti, Elisabetta, Cerva, Carlotta, Baiocchi, Lorenzo, Tata, Xhimi, Grassi, Giuseppe, Gasbarrini, Antonio, Pompili, Maurizio, De Siena, Martina, Taliani, Gloria, Biliotti, Elisa, Spaziante, Martina, Persico, Marcello, Masarone, Mario, Aglitti, Andrea, Calvanese, Gemma, Anselmo, Marco, De Leo, Pasqualina, Marturano, Monica, Saracco, Giorgio Maria, Ciancio, Alessia, Ieluzzi, Donatella, Quaranta, Maria Giovanna, Ferrigno, Luigina, D'Angelo, Franca, Saracino, Annalisa, and Kondili, Loeta A.

Published
2021
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41. Bayesian Networks in the Management of Hospital Admissions: A Comparison between Explainable AI and Black Box AI during the Pandemic

Author

Nicora, Giovanna, primary, Catalano, Michele, additional, Bortolotto, Chandra, additional, Achilli, Marina Francesca, additional, Messana, Gaia, additional, Lo Tito, Antonio, additional, Consonni, Alessio, additional, Cutti, Sara, additional, Comotto, Federico, additional, Stella, Giulia Maria, additional, Corsico, Angelo, additional, Perlini, Stefano, additional, Bellazzi, Riccardo, additional, Bruno, Raffaele, additional, and Preda, Lorenzo, additional

Published
2024
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42. Dynamics of viral DNA shedding and culture viral DNA positivity in different clinical samples collected during the 2022 mpox outbreak in Lombardy, Italy

Author

Piralla, Antonio, primary, Mileto, Davide, additional, Rizzo, Alberto, additional, Ferrari, Guglielmo, additional, Giardina, Federica, additional, Gaiarsa, Stefano, additional, Petazzoni, Greta, additional, Bianchi, Micol, additional, Salari, Federica, additional, Bracchitta, Fiorenza, additional, Sammartino, Josè Camilla, additional, Ferrari, Alessandro, additional, Gagliardi, Gloria, additional, Mancon, Alessandro, additional, Fenizia, Claudio, additional, Biasin, Mara, additional, Rovida, Francesca, additional, Paolucci, Stefania, additional, Percivalle, Elena, additional, Lombardi, Alessandra, additional, Micheli, Valeria, additional, Nozza, Silvia, additional, Castagna, Antonella, additional, Moschese, Davide, additional, Antinori, Spinello, additional, Gori, Andrea, additional, Bonfanti, Paolo, additional, Rossotti, Roberto, additional, Monforte, Antonella D'arminio, additional, Attanasi, Federica, additional, Tirani, Marcello, additional, Cereda, Danilo, additional, Baldanti, Fausto, additional, Gismondo, Maria Rita, additional, Cutrera, Miriam, additional, Cuomo, Marianna, additional, De Poli, Federica, additional, Campanini, Giulia, additional, Pitrolo, Antonino Maria Guglielmo, additional, Iskandar, Elizabeth, additional, Cassaniti, Irene, additional, Bruno, Raffaele, additional, Rizzardini, Giuliano, additional, Puoti, Massimo, additional, Castelli, Francesco, additional, Corsico, Laura, additional, Giacomelli, Andrea, additional, Pozza, Giacomo, additional, Casalini, Giacomo, additional, Raccagni, Angelo, additional, Trentacapilli, Bendetta, additional, Bertoni, Costanza, additional, Bruzzesi, Elena, additional, Candela, Caterina, additional, Tesoro, Daniele, additional, Mule, Giovanni, additional, Bandera, Alessandra, additional, Bianca Mariani, Antonio Muscatello, additional, Maffeo, Manuel, additional, Vecchio, Riccardo, additional, and Piccinelli, Sara, additional

Published
2024
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49. Persistence of SARS-CoV-2-specific B and T cell responses in convalescent COVID-19 patients 6–8 months after the infection

Author

Sherina, Natalia, Piralla, Antonio, Du, Likun, Wan, Hui, Kumagai-Braesch, Makiko, Andréll, Juni, Braesch-Andersen, Sten, Cassaniti, Irene, Percivalle, Elena, Sarasini, Antonella, Bergami, Federica, Di Martino, Raffaella, Colaneri, Marta, Vecchia, Marco, Sambo, Margherita, Zuccaro, Valentina, Bruno, Raffaele, Sachs, Michele, Oggionni, Tiberio, Meloni, Federica, Abolhassani, Hassan, Bertoglio, Federico, Schubert, Maren, Byrne-Steele, Miranda, Han, Jian, Hust, Michael, Xue, Yintong, Hammarström, Lennart, Baldanti, Fausto, Marcotte, Harold, and Pan-Hammarström, Qiang

Published
2021
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50. EBV DNA increase in COVID-19 patients with impaired lymphocyte subpopulation count

Author

Bruno, R, Mondelli, M, Brunetti, E, Di Matteo, A, Seminari, E, Maiocchi, L, Zuccaro, V, Pagnucco, L, Mariani, B, Ludovisi, S, Lissandrin, R, Parisi, A, Sacchi, P, Patruno, SFA, Michelone, G, Gulminetti, R, Zanaboni, D, Novati, S, Maserati, R, Orsolini, P, Vecchia, M, Sciarra, M, Asperges, E, Colaneri, M, Di Filippo, A, Sambo, M, Biscarini, S, Lupi, M, Roda, S, Pieri, TC, Gallazzi, I, Sachs, M, Valsecchi, P, Perlini, S, Alfano, C, Bonzano, M, Briganti, F, Crescenzi, G, Falchi, AG, Guarnone, R, Guglielmana, B, Maggi, E, Martino, I, Pettenazza, P, Pioli di Marco, S, Quaglia, F, Sabena, A, Salinaro, F, Speciale, F, Zunino, I, De Lorenzo, M, Secco, G, Dimitry, L, Cappa, G, Maisak, I, Chiodi, B, Sciarrini, M, Barcella, B, Resta, F, Moroni, L, Vezzoni, G, Scattaglia, L, Boscolo, E, Zattera, C, Tassi, MF, Capozza, V, Vignaroli, D, Bazzini, M, Iotti, G, Mojoli, F, Belliato, M, Perotti, L, Mongodi, S, Tavazzi, G, Marseglia, G, Licari, A, Brambilla, I, Barbarini, D, Bruno, A, Cambieri, P, Campanini, G, Cavanna, C., Comolli, G, Corbella, M, Daturi, R, Furione, M, Marone, P, Monzillo, E, Paolucci, S, Parea, M, Percivalle, E, Piralla, A, Rovida, F, Sarasini, A, Zavattoni, M, Adzasehoun, G, Ardizzone, M, Bellotti, L, Brunco, V, Cabano, E, Casali, G, Capella, L, Devitis, D, Dossena, L, Frisco, G, Garbagnoli, G, Gardellini, F, Girello, A, Guerrizio, A, Landini, V, Lucchelli, C, Maliardi, V, Piemontese, P, Pezzaia, S, Premoli, M, Rebuffa, C, Zanello, C, Bagnarino, J, Bergami, F, Bonetti, A, Caneva, G, Cassaniti, I, Corcione, A, Di Martino, R, Di Napoli, A, Ferrari, A, Ferrari, G, Fiorina, L, Gallone, A, Giardina, F, Girardi, A, Mercato, A, Merla, C, Novazzi, F, Ratano, G, Rossi, B, Saveriaempillai, G, Sciabica, IM, Tallarita, M, Vecchio Nepita, E, Vitali, J, Cerino, A, Varchetta, S, Oliviero, B, Mantovani, S, Mele, D, Calvi, M, Tizzoni, M, Nicora, C, Triarico, A, Petronella, V, Marena, C, Muzzi, A, Lago, P, Cutti, S, Novelli, V, Comandatore, F, BatistiBiffignandi, G, Gaiarsa, S, Rettani, M, Bandi, C, Paolucci, Stefania, Cassaniti, Irene, Novazzi, Federica, Fiorina, Loretta, Piralla, Antonio, Comolli, Giuditta, Bruno, Raffaele, Maserati, Renato, Gulminetti, Roberto, Novati, Stefano, Mojoli, Francesco, and Baldanti, Fausto

Published
2021
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