Use of sound recordings and analysis for physics lab practices

[EN] The study of oscillations, waves, and sound is included in most first-year courses on Physics, however, analyzing audio recordings to understand and test physics experiments in laboratory practices is not a common practice, compared for example with the use of visual techniques. In this paper, we fill in this gap showing the usefulness of the application of sound recording and its analysis in Physics Laboratory practices of first-year Engineering University studies. Sound recording is very simple and implemented in commonly available technology tools, such as smartphones. The analysis can be done with ease in free open-source applications, such as Audacity. This means that this experimental procedure can be easily implemented and extensively used, even in distance learning, which is particularly convenient in a pandemic context. In fact, we illustrate in this work how this approach let us to successfully transform two in-person lab practices into sessions that can be run remotely: the study of free fall and measurement of the coefficient of restitution of a ball bouncing when released from a certain height, and the measurement of the speed of vehicles by analyzing the Doppler effect of the sound that the motor vehicles produce. With this, we conclude that this is a powerful technique that should be considered, alone or in combination with other techniques, for instance video analysis, when planning the lab practices of Physics courses.S.A. was supported by the CIDEGENT Program from the Generalitat Valenciana CIDEGENT/2019/043.Ardid-Ramírez, JS.; Marquez, S.; Ardid Ramírez, M. (2021). Use of sound recordings and analysis for physics lab practices. IATED. 7687-7693. https://doi.org/10.21125/inted.2021.1547S7687769

A tweaking principle for executive control: neuronal circuit mechanism for rule-based task switching and conflict resolution

[EN] A hallmark of executive control is the brain's agility to shift between different tasks depending on the behavioral rule currently in play. In this work, we propose a "tweaking hypothesis" for task switching: a weak rule signal provides a small bias that is dramatically amplified by reverberating attractor dynamics in neural circuits for stimulus categorization and action selection, leading to an all-or-none reconfiguration of sensory-motor mapping. Based on this principle, we developed a biologically realistic model with multiple modules for task switching. We found that the model quantitatively accounts for complex task switching behavior: switch cost, congruency effect, and task-response interaction; as well as monkey's single-neuron activity associated with task switching. The model yields several testable predictions, in particular, that category-selective neurons play a key role in resolving sensory-motor conflict. This work represents a neural circuit model for task switching and sheds insights in the brain mechanism of a fundamental cognitive capability.This work was supported by the Office of Naval Research Grant N00014-13-1-0297, The Swartz Foundation Fellowship (S.A.), and John Simon Guggenheim Foundation Fellowship (X.-J.W.). We thank T.A. Engel for fruitful discussions, and A. Compte, J.B. Morton, W. Wei, and T. Womelsdorf for comments on a previous version of the paper. We also thank the reviewers for their thoughtful comments and suggestions.Ardid-Ramírez, JS.; Wang, X. (2013). A tweaking principle for executive control: neuronal circuit mechanism for rule-based task switching and conflict resolution. Journal of Neuroscience. 33(50):19504-19517. https://doi.org/10.1523/JNEUROSCI.1356-13.2013S1950419517335

Análisis del cambio repentino a docencia remota por la COVID-19 en los resultados de aprendizaje: caso de dos asignaturas anuales básicas en Grados de Ingeniería

[EN] In this article we analyse the experience in two basic annual subjects in Engineering Degrees with the aim of determining if there are differences in the degree of achievement of the learning objectives, due to the sudden change to virtual teaching obliged by the COVID-19 lockdown. With this aim, a statistical analysis of the grades obtained by the students is carried out, comparing the periods of in-class teaching with those of forced remote teaching in contrast with the experience of previous courses, where virtual teaching was absent. Results of this analysis do not hold significant differences in the grades of the students associated with the vast transformation in teaching and learning process. Even though the results cannot necessarily conclude that there have not been changes in learning outcomes, they are indicative of a reasonably good adaptability of the teaching and learning process to the sudden new context given by the pandemics.[ES] En este artículo analizamos la experiencia en dos asignaturas básicas anuales en Grados en Ingenierías con el objetivo de determinar si se observan diferencias en el grado de consecución de los objetivos de aprendizaje debido al repentino cambio a docencia virtual por el confinamiento de la COVID-19. Para ello se hace un análisis estadístico de las calificaciones obtenidas por los estudiantes, comparando los periodos de docencia presencial con los de docencia remota forzada y contrastándolos con la experiencia de los cursos precedentes, donde la docencia virtual no era presente. Los resultados de este análisis no sustentan diferencias significativas en las calificaciones de los estudiantes asociados a esta transformación en la docencia. Si bien los resultados no concluyen unívocamente que no haya habido cambios en los resultados de aprendizaje, sí que son indicativos de una buena adaptabilidad de la docencia ante el nuevo contexto de pandemia, en la que se ha sabido acompasar el nivel de exigencia a los condicionantes del entorno en situación de crisis sobrevenida.S. Ardid agradece el apoyo del Programa CIDEGENT de la Generalitat Valenciana, CIDEGENT/2019/043.Ardid Ramírez, M.; Ardid Ramírez, JS.; Herrero Debón, A. (2021). Análisis del cambio repentino a docencia remota por la COVID-19 en los resultados de aprendizaje: caso de dos asignaturas anuales básicas en Grados de Ingeniería. En IN-RED 2021: VII Congreso de Innovación Edicativa y Docencia en Red. Editorial Universitat Politècnica de València. 931-940. https://doi.org/10.4995/INRED2021.2021.13448OCS93194

An integrated microcircuit model of attentional processing in the neocortex

[EN] Selective attention is a fundamental cognitive function that uses top-down signals to orient and prioritize information processing in the brain. Single-cell recordings from behaving monkeys have revealed a number of attention-induced effects on sensory neurons, and have given rise to contrasting viewpoints about the neural underpinning of attentive processing. Moreover, there is evidence that attentional signals originate from the prefrontoparietal working memory network, but precisely how a source area of attention interacts with a sensory system remains unclear. To address these questions, we investigated a biophysically based network model of spiking neurons composed of a reciprocally connected loop of two (sensory and working memory) networks. We found that a wide variety of physiological phenomena induced by selective attention arise naturally in such a system. In particular, our work demonstrates a neural circuit that instantiates the "feature-similarity gain modulation principle," according to which the attentional gain effect on sensory neuronal responses is a graded function of the difference between the attended feature and the preferred feature of the neuron, independent of the stimulus. Furthermore, our model identifies key circuit mechanisms that underlie feature-similarity gain modulation, multiplicative scaling of tuning curve, and biased competition, and provide specific testable predictions. These results offer a synthetic account of the diverse attentional effects, suggesting a canonical neural circuit for feature-based attentional processing in the cortex.This work was supported by the Volkswagen Foundation, the Spanish Ministry of Education and Science (S.A., A.C.), the European Regional Development Fund (A.C.), and the Swartz Foundation (X.-J.W.). A.C. was supported by a Ramón y Cajal Research Fellowship of the Spanish Ministry of Education and Science and by the Researcher Stabilization Program of the Health Department of the Generalitat de Catalunya. We thank S. Treue for helpful discussions on feature-based attention, and E. Marder, J. Mazer, and A. Renart for helpful comments on a previous version of this manuscript.Ardid-Ramírez, JS.; Wang, X.; Compte, A. (2007). An integrated microcircuit model of attentional processing in the neocortex. Journal of Neuroscience. 27(32):8486-8495. https://doi.org/10.1523/JNEUROSCI.1145-07.2007S84868495273

Reconciling coherent oscillation with modulation of irregular spiking activity in selective attention: gamma-range synchronization between sensory and executive cortical areas

[EN] In this computational work, we investigated gamma-band synchronization across cortical circuits associated with selective attention. The model explicitly instantiates a reciprocally connected loop of spiking neurons between a sensory-type (area MT) and an executive-type (prefrontal/parietal) cortical circuit (the source area for top-down attentional signaling). Moreover, unlike models in which neurons behave as clock-like oscillators, in our model single-cell firing is highly irregular (close to Poisson), while local field potential exhibits a population rhythm. In this "sparsely synchronized oscillation" regime, the model reproduces and clarifies multiple observations from behaving animals. Top-down attentional inputs have a profound effect on network oscillatory dynamics while only modestly affecting single-neuron spiking statistics. In addition, attentional synchrony modulations are highly selective: interareal neuronal coherence occurs only when there is a close match between the preferred feature of neurons, the attended feature, and the presented stimulus, a prediction that is experimentally testable. When interareal coherence was abolished, attention-induced gain modulations of sensory neurons were slightly reduced. Therefore, our model reconciles the rate and synchronization effects, and suggests that interareal coherence contributes to large-scale neuronal computation in the brain through modest enhancement of rate modulations as well as a pronounced attention-specific enhancement of neural synchrony.This work was funded by the Volkswagen Foundation, the Spanish Ministry of Science and Innovation, and the European Regional Development Fund. A.C. is supported by the Researcher Stabilization Program of the Health Department of the Generalitat de Catalunya. X.-J.W. is supported by the National Institutes of Health Grant 2R01MH062349 and the Kavli Foundation. We are thankful to Stefan Treue for fruitful discussions and to Jorge Ejarque for technical support in efficiently implementing the search optimization procedure in a grid cluster computing system. Also, we thankfully acknowledge the computer resources and assistance from the Barcelona Supercomputing Center-Centro Nacional de Supercomputación, Spain.Ardid-Ramírez, JS.; Wang, X.; Gomez-Cabrero, D.; Compte, A. (2010). Reconciling coherent oscillation with modulation of irregular spiking activity in selective attention: gamma-range synchronization between sensory and executive cortical areas. Journal of Neuroscience. 30(8):2856-2870. https://doi.org/10.1523/JNEUROSCI.4222-09.2010S2856287030

Flexible resonance in prefrontal networks with strong feedback inhibition

[EN] Oscillations are ubiquitous features of brain dynamics that undergo task-related changes in synchrony, power, and frequency. The impact of those changes on target networks is poorly understood. In this work, we used a biophysically detailed model of prefrontal cortex (PFC) to explore the effects of varying the spike rate, synchrony, and waveform of strong oscillatory inputs on the behavior of cortical networks driven by them. Interacting populations of excitatory and inhibitory neurons with strong feedback inhibition are inhibition-based network oscillators that exhibit resonance (i.e., larger responses to preferred input frequencies). We quantified network responses in terms of mean firing rates and the population frequency of network oscillation; and characterized their behavior in terms of the natural response to asynchronous input and the resonant response to oscillatory inputs. We show that strong feedback inhibition causes the PFC to generate internal (natural) oscillations in the beta/gamma frequency range (>15 Hz) and to maximize principal cell spiking in response to external oscillations at slightly higher frequencies. Importantly, we found that the fastest oscillation frequency that can be relayed by the network maximizes local inhibition and is equal to a frequency even higher than that which maximizes the firing rate of excitatory cells; we call this phenomenon population frequency resonance. This form of resonance is shown to determine the optimal driving frequency for suppressing responses to asynchronous activity. Lastly, we demonstrate that the natural and resonant frequencies can be tuned by changes in neuronal excitability, the duration of feedback inhibition, and dynamic properties of the input. Our results predict that PFC networks are tuned for generating and selectively responding to beta- and gamma-rhythmic signals due to the natural and resonant properties of inhibition-based oscillators. They also suggest strategies for optimizing transcranial stimulation and using oscillatory networks in neuromorphic engineering.This material is based upon research supported by the U. S. Army Research Office under award number ARO W911NF-12-R-0012-02 to N. K., the U. S. Office of Naval Research under award number ONR MURI N00014-16-1-2832 to M. H., and the National Science Foundation under award number NSF DMS-1042134 (Cognitive Rhythms Collaborative: A Discovery Network) to N. K. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Sherfey, JS.; Ardid-Ramírez, JS.; Hass, J.; Hasselmo, ME.; Kopell, NJ. (2018). Flexible resonance in prefrontal networks with strong feedback inhibition. 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Prefrontal oscillations modulate the propagation of neuronal activity required for working memory

[EN] Cognition involves using attended information, maintained in working memory (WM), to guide action. During a cognitive task, a correct response requires flexible, selective gating so that only the appropriate information flows from WM to downstream effectors that carry out the response. In this work, we used biophysically-detailed modeling to explore the hypothesis that network oscillations in prefrontal cortex (PFC), leveraging local inhibition, can independently gate responses to items in WM. The key role of local inhibition was to control the period between spike bursts in the outputs, and to produce an oscillatory response no matter whether the WM item was maintained in an asynchronous or oscillatory state. We found that the WM item that induced an oscillatory population response in the PFC output layer with the shortest period between spike bursts was most reliably propagated. The network resonant frequency (i.e., the input frequency that produces the largest response) of the output layer can be flexibly tuned by varying the excitability of deep layer principal cells. Our model suggests that experimentally-observed modulation of PFC beta-frequency (15-30 Hz) and gamma -frequency (30-80 Hz) oscillations could leverage network resonance and local inhibition to govern the flexible routing of signals in service to cognitive processes like gating outputs from working memory and the selection of rule-based actions. Importantly, we show for the first time that nonspecific changes in deep layer excitability can tune the output gate's resonant frequency, enabling the specific selection of signals encoded by populations in asynchronous or fast oscillatory states. More generally, this represents a dynamic mechanism by which adjusting network excitability can govern the propagation of asynchronous and oscillatory signals throughout neocortex.This work was supported by the U.S. Army Research Office under award number ARO W911NF-12-R-0012-02 to N. K., the U.S. Office of Naval Research under award number ONR MURI N00014-16-1-2832 to M. H. and E. M., the National Institute of Mental Health under award number NIMH R37MH087027 to E. M., and The MIT Picower Institute Faculty Innovation Fund to E. M. We would like to acknowledge Joachim Hass and Michelle McCarthy for early discussions of our modeling results, as well as Andre Bastos and Mikael Lundqvist for discussions relating our modeling work to their experiments.Sherfey, J.; Ardid-Ramírez, JS.; Miller, EK.; Hasselmo, ME.; Kopell, NJ. (2020). Prefrontal oscillations modulate the propagation of neuronal activity required for working memory. 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Feature-specific prediction errors and surprise across macaque fronto-striatal circuits

[EN] To adjust expectations efficiently, prediction errors need to be associated with the precise features that gave rise to the unexpected outcome, but this credit assignment may be problematic if stimuli differ on multiple dimensions and it is ambiguous which feature dimension caused the outcome. Here, we report a potential solution: neurons in four recorded areas of the anterior fronto-striatal networks encode prediction errors that are specific to feature values of different dimensions of attended multidimensional stimuli. The most ubiquitous prediction error occurred for the reward-relevant dimension. Feature-specific prediction error signals a) emerge on average shortly after non-specific prediction error signals, b) arise earliest in the anterior cingulate cortex and later in dorsolateral prefrontal cortex, caudate and ventral striatum, and c) contribute to feature-based stimulus selection after learning. Thus, a widely-distributed feature-specific eligibility trace may be used to update synaptic weights for improved feature-based attention.This work was supported by grant MOP 102482 from the Canadian Institutes of Health Research (T.W.) and the Natural Sciences and Engineering Research Council of Canada (T.W.), as well as by the Brain in Action CREATE-IRTG program (M.O. and T.W.), and by grant LPDS 2012-08 from the Deutsche Akademie der Naturforscher Leopoldina (S.W.). Imaging data provided by the Duke Center for In Vivo Microscopy, an NIH Biomedical Technology Resource (NIHP41EB015897, 1S10OD010683-01). The funders had no role in study design, data collection and analysis, the decision to publish, or the preparation of this manuscript. The authors would like to thank Hongying Wang for technical supportOemisch, M.; Westendorff, S.; Azimi, M.; Hassani, SA.; Ardid-Ramírez, JS.; Tiesinga, P.; Womelsdorf, T. (2019). 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Probing invisible neutrino decay with KM3NeT/ORCA

In the era of precision measurements of the neutrino oscillation parameters, upcoming neutrino experiments will also be sensitive to physics beyond the Standard Model. KM3NeT/ORCA is a neutrino detector optimised for measuring atmospheric neutrinos from a few GeV to around 100 GeV. In this paper, the sensitivity of the KM3NeT/ORCA detector to neutrino decay has been explored. A three-flavour neutrino oscillation scenario, where the third neutrino mass state ¿3 decays into an invisible state, e.g. a sterile neutrino, is considered. We find that KM3NeT/ORCA would be sensitive to invisible neutrino decays with 1/a3 = t3/m3 < 180 ps/eV at 90% confidence level, assuming true normal ordering. Finally, the impact of neutrino decay on the precision of KM3NeT/ORCA measurements for ¿23, ¿m231 and mass ordering have been studied. No significant effect of neutrino decay on the sensitivity to these measurements has been found.Article signat per 255 autors i autores: S. Aiello, A. Albert, S. Alves Garre, Z. Aly, A. Ambrosone, F. Ameli, M. Andre, M. Anghinolfi, M. Anguita, M. Ardid, S. Ardid, J. Aublin, C. Bagatelas, L. Bailly-Salins, B. Baret, S. Basegmez du Pree, Y. Becherini, M. Bendahman, F. Benfenati, E. Berbee, V. Bertin, S. Biagi, M. Boettcher, M. Bou Cabo, J. Boumaaza, M. Bouta, M. Bouwhuis, C. Bozza, H.Brânzaş, R. Bruijn, J. Brunner, R. Bruno, E. Buis, R. Buompane, J. Busto, B. Caiffi, D. Calvo, S. Campion, A. Capone, F. Carenini, V. Carretero, P. Castaldi, S. Celli, L. Cerisy, M. Chabab, N. Chau, A. Chen, R. Cherkaoui El Moursli, S. Cherubini, V. Chiarella, T. Chiarusi, M. Circella, R. Cocimano, J. A. B. Coelho, A. Coleiro, R. Coniglione, P. Coyle, A. Creusot, A. Cruz, G. Cuttone, R. Dallier, Y. Darras, A. De Benedittis, B. De Martino, V. Decoene, R. Del Burgo, I. Di Palma, A. F. Díaz, D. Diego-Tortosa, C. Distefano, A. Domi, C. Donzaud, D. Dornic, M. Dörr, E. Drakopoulou, D. Drouhin, T. Eberl, A. Eddyamoui, T. van Eeden, M. Eff, D. van Eijk, I. El Bojaddaini, S. El Hedri, A. Enzenhöfer, V. Espinosa, G. Ferrara, M. D. Filipović, F. Filippini, L. A. Fusco, J. Gabriel, T. Gal, J. García Méndez, A. Garcia Soto, F. Garufi, C. Gatius Oliver, N. Geißelbrecht, L. Gialanella, E. Giorgio, A. Girardi , I. Goos, S. R. Gozzini, R. Gracia, K. Graf, D. Guderian, C. Guidi, B. Guillon, M. Gutiérrez, L. Haegel, H. van Haren, A. Heijboer, A. Hekalo, L. Hennig, J. J. Hernández-Rey, F. Huang, W. Idrissi Ibnsalih, G. Illuminati, C. W. James, D. Janezashvili, M. de Jong, P. de Jong, B. J. Jung, P. Kalaczyński, O. Kalekin, U. F. Katz, N. R. Khan Chowdhury, G. Kistauri, F. van der Knaap, P. Kooijman, A. Kouchner, V. Kulikovskiy, M. Labalme, R. Lahmann, A. Lakhal, M. Lamoureux, G. Larosa, C. Lastoria, A. Lazo, R. Le Breton, S. Le Stum, G. Lehaut, E. Leonora, N. Lessing, G. Levi, S. Liang, M. Lindsey Clark, F. Longhitano, L. Maderer, J. Majumdar, J. Mańczak, A. Margiotta, A. Marinelli, C. Markou, L. Martin, J. A. Martìnez-Mora, A. Martini, F. Marzaioli, M. Mastrodicasa, S. Mastroianni, K. W. Melis, S. Miccichè, G. Miele, P. Migliozzi, E. Migneco, P. Mijakowski, C. M. Mollo, L. Morales-Gallegos, C. Morley-Wong, A. Moussa, R. Muller, M. R. Musone, M. Musumeci, L. Nauta, S. Navas, C. A. Nicolau, B. Nkosi, B. Ó Fearraigh, A. Orlando, E. Oukacha, J. Palacios González, G. Papalashvili, R. Papaleo, E.J. Pastor Gomez, A. M. Păun, G. E. Păvălaş, C. Pellegrino, S. Peña Martínez, M. Perrin-Terrin, J. Perronnel, V. Pestel, P. Piattelli, O. Pisanti, C. Poirè, V. Popa, T. Pradier, S. Pulvirenti, G. Quéméner, U. Rahaman, N. Randazzo, S. Razzaque, I. C. Rea, D. Real, S. Reck, G. Riccobene, J. Robinson, A. Romanov, F. Salesa Greus, D. F. E. Samtleben, A. Sánchez Losa, M. Sanguineti, C. Santonastaso, D. Santonocito, P. Sapienza, A. Sathe, J. Schnabel, M. F. Schneider, J. Schumann, H. M. Schutte, J. Seneca, I. Sgura, R. Shanidze, A. Sharma, A. Simonelli, A. Sinopoulou, M.V. Smirnov, B. Spisso, M. Spurio, D. Stavropoulos, S. M. Stellacci, M. Taiuti, K. Tavzarashvili, Y. Tayalati, H. Tedjditi, T. Thakore, H. Thiersen, S. Tsagkli, V. Tsourapis, E. Tzamariudaki, V. Van Elewyck, G. Vannoye, G. Vasileiadis, F. Versari, S. Viola, D. Vivolo, H. Warnhofer, J. Wilms, E. de Wolf, H. Yepes-Ramirez, T. Yousfi, S. Zavatarelli, A. Zegarelli, D. Zito, J. D. Zornoza, J. Zúñiga, N. ZywuckaPostprint (published version

KM3NeT broadcast optical data transport system

The optical data transport system of the KM3NeT neutrino telescope at the bottom of the Mediterranean Sea will provide more than 6000 optical modules in the detector arrays with a point-to-point optical connection to the control stations onshore. The ARCA and ORCA detectors of KM3NeT are being installed at a depth of about 3500 m and 2500 m, respectively and their distance to the control stations is about 100 kilometers and 40 kilometers. In particular, the two detectors are optimised for the detection of cosmic neutrinos with energies above about 1 TeV (ARCA) and for the detection of atmospheric neutrinos with energies in the range 1 GeV–1 TeV (ORCA). The expected maximum data rate is 200 Mbps per optical module. The implemented optical data transport system matches the layouts of the networks of electro-optical cables and junction boxes in the deep sea. For efficient use of the fibres in the system the technology of Dense Wavelength Division Multiplexing is applied. The performance of the optical system in terms of measured bit error rates, optical budget are presented. The next steps in the implementation of the system are also discussed.Peer ReviewedArticle signat per 254 autors/es: L. Bailly-Salins, B. Baret, S. Basegmez du Pree, Y. Becherini, M. Bendahman, F. Benfenati, E. Berbee, V. Bertin, S. Biagi, M. Boettcher, M. Bou Cabo, J. Boumaaza, M. Bouta, M. Bouwhuis, C. Bozza, H. Brânzaş, R. Bruijn, Brunner, R. Bruno, E. Buis, R. Buompane, J. Busto, B. Caiffi, D. Calvo, S. Campion, A. Capone, F. Carenini, V. Carretero, P. Castaldi, S. Celli, L. Cerisy, M. Chabab, N. Chau, A. Chen, R. Cherkaoui El Moursli, S. Cherubini, V. Chiarella, T. Chiarusi, M. Circella, R. Cocimano, J.A.B. Coelho, A. Coleiro, R. Coniglione, P. Coyle, A. Creusot, A. Cruz, G. Cuttone, A. D’Amico, R. Dallier, Y. Darras, A. De Benedittis, B. De Martino, R. Del Burgo, I. Di Palma, A.F. Díaz, D. Diego-Tortosa, C. Distefano, A. Domi, C. Donzaud, D. Dornic, M. Dörr, E. Drakopoulou, D. Drouhin, T. Eberl, A. Eddyamoui, T. van Eeden, M. Eff, D. van Eijk,I. El Bojaddaini, S. El Hedri, A. Enzenhöfer, V. Espinosa, G. Ferrara, M.D. Filipović, F. Filippini, L.A. Fusco, J. Gabriel, T. Gal, J. García Méndez, A. Garcia Soto, F. Garufi, C. Gatius Oliver, N. Geißelbrecht, L. Gialanella, E. Giorgio, A. Girardi, I. Goos, S.R. Gozzini, R. Gracia, K. Graf, D. Guderian, C. Guidi, B. Guillon, M. Gutiérrez, L. Haegel, H. van Haren, A. Heijboer, A. Hekalo, L. Hennig, J.J. Hernández-Rey, F. Huang, W. Idrissi Ibnsalih, G. Illuminati, C.W. James, D. Janezashvili, M. de Jong, P. de Jong, B.J. Jung, P. Kalaczyński, O. Kalekin, U.F. Katz, N.R. Khan Chowdhury, G. Kistauri, F. van der Knaap, P. Kooijman, A. Kouchner, V. Kulikovskiy, M. Labalme, R. Lahmann, A. Lakhal, M. Lamoureux, G. Larosa, C. Lastoria, A. Lazo, R. Le Breton, S. Le Stum, G. Lehaut, E. Leonora, N. Lessing, G. Levi, S. Liang, M. Lindsey Clark, F. Longhitano, L. Maderer, J. Majumdar, J. Mańczak, A. Margiotta, A. Marinelli, C. Markou, L. Martin, J.A. Martínez-Mora, A. Martini, F. Marzaioli, M. Mastrodicasa, S. Mastroianni, K.W. Melis, S. Miccichè, G. Miele, P. Migliozzi, E. Migneco, P. Mijakowski, C.M. Mollo, L. Morales-Gallegos, C. Morley-Wong, A. Moussa, R. Muller, M.R. Musone, M. Musumeci, L. Nauta, S. Navas, C.A. Nicolau, B. Nkosi, B. Ó Fearraigh, A. Orlando, E. Oukacha, J. Palacios González, G. Papalashvili, R. Papaleo, E.J. Pastor Gomez, A.M. Păun, G.E. Păvălaş, C. Pellegrino, S. Peña Martínez, M. Perrin-Terrin, J. Perronnel, V. Pestel, P. Piattelli, O. Pisanti, C. Poirè, V. Popa, T. Pradier, S. Pulvirenti, G. Quéméner, U. Rahaman, N. Randazzo, S. Razzaque, I.C. Rea, D. Real, S. Reck, G. Riccobene, J. Robinson, A. Romanov, F. Salesa Greus, D.F.E. Samtleben, A. Sánchez Losa, M. Sanguineti, C. Santonastaso, D. Santonocito, P. Sapienza, A. Sathe, J. Schmelling, J. Schnabel, M.F. Schneider, J. Schumann, H. M. Schutte, J. Seneca, I. Sgura, R. Shanidze, A. Sharma, A. Simonelli, A. Sinopoulou, M.V. Smirnov, B. Spisso, M. Spurio, D. Stavropoulos, S.M. Stellacci, M. Taiuti, K. Tavzarashvili, Y. Tayalati, H. Tedjditi, H. Thiersen, S. Tsagkli, V. Tsourapis, E. Tzamariudaki, V. Van Elewyck, G. Vannoye, G. Vasileiadis, F. Versari, S. Viola, D. Vivolo, H. Warnhofer, J. Wilms, E. de Wolf, H. Yepes-Ramirez, T. Yousfi, S. Zavatarelli, A. Zegarelli, D. Zito, J.D. Zornoza, J. Zúñiga and N. ZywuckaPostprint (published version