El comportamiento colectivo en el deporte

El 29 de mayo de 1985 se registraron en el estadio Heysel de Bruselas 10s mas graves incidentes acaecidos en un campo de futbol europeo: antes de iniciar- se el encuentro final de la Copa de Europa entre el Liverpool y el Juventus, una multitud de supporters ataco una grada de hinchas italianos provocando una ava- lancha que origino 39 muertos y centenares de heridos. Los hechos fueron pre- senciados, a través de la television, por millones de espectadores y causaron en Europa un notable impacto emocional. Durante la semana siguiente a 10s hechos, un equipo de investigadores de la Universidad de Lovaina, se trataba de psicolo- gos sociales especializados en agresion y comportamiento colectivo (CC), anali- zo a fondo el episodio y redacto un documento definiendo científicamente 10 ocu- rrido, buscando las causas y proporcionando soluciones (Rimé et al., 1985). El documento fue publicado por la prensa belga y entregado a las autoridades gu- bernamentales

Hinchas violentos y excitación emocional

En este trabajo hace una reflexión de tipo teórico sobre elpapel que juega la búsqueda de excitación y de emociones en el comportamiento de los hinchas violentos o «hooligans». En la orientación aquí expresada, se examina una innovadora y reciente monografía del psicólogo John Kerr sobre los hooligans, donde se ha aplicado la teoría de la inversión de Apter al problema de los grupos violentos en el fútbol. La perspectiva de Kerr, con su énfasis en la búsqueda de arousal (o excitación) es discutida en un amplio marco junto con otras aportaciones teóricas al tema provenientes de la psicología social y la sociologíaIn this work, is made a theoretical reflection aboutrole played by the quest of excitement and emotions in soccer hooligans violence. In the orientation here expressed, is revised an innovative and recent monograph of psychologist John Kerr about soccer hooligans, where is applied reversal theory of Apter to the problem of these violent groups. The Kerr's perspective, with his emphasis in arousal-seeking is discussed in a broad frameword with other theoretical contributions to the subject that come from social psychology and from pscholog

High-Resolution NMR Spectroscopy at Large Fields with Nitrogen Vacancy Centers

Ensembles of nitrogen-vacancy (NV) centers are used as sensors to detect NMR signals from micron-sized samples at room temperature. In this scenario, the regime of large magnetic fields is especially interesting as it leads to a large nuclear thermal polarisation -- thus, to a strong sensor response even in low concentration samples -- while chemical shifts and J-couplings become more accessible. Nevertheless, this regime remains largely unexplored owing to the difficulties to couple NV-based sensors with high-frequency nuclear signals. In this work, we circumvent this problem with a method that maps the relevant energy shifts in the amplitude of an induced nuclear spin signal that is subsequently transferred to the sensor. This stage is interspersed with free-precession periods of the sample nuclear spins where the sensor does not participate. Thus, our method leads to high spectral resolutions ultimately limited by the coherence of the nuclear spin signal.Comment: 6 pages, 3 figure

Internet y movimientos sociales: un enfoque psicosocial

The influence of lnternet on the development of new social movements is increasing rapidly. For emerging movements and organizations the lnternet is a powerjiul and innovative tool; it promotes social participation and the search for more "direct democracy". Via Internet, social movements can build up an ever wider virtual community. Their skiful protest campaigns represent the prototype of the social revolutions of the future. These new instruments for communication and action promote the"identity paradigm" which emphasizes basic psychosocial aspects such as the social construction of reality, collective identity, values and commitment to social issues.lnternet incide cada vez con más fuerza en el desarrollo y organización de los nuevos movimientos sociales. Las características específicas de la red favorecen su utilización por parte de los movimientos y organizaciones emergentes como una herramienta potente e innovadora de participaciónsocial en la línea de una mayor "democracia directa". A travésde Internet los movimientos sociales consolidan una cada vez mas amplia y coordinada comunidad virtual. Sus ágiles y hábiles acciones de protesta prefiguran ya el prototipo de lo que serán las revoluciones sociales del futuro. Estos nuevos instrumentos de comunicación y de acción impulsan eldenominado "paradigma de la identidad" que enfatiza aspectos psicosociales básicos como la construcción social de la realidad, la identidad colectiva, los valores y la toma de conciencia social

Internet y movimientos sociales: un enfoque psicosocial

The influence of lnternet on the development of new social movements is increasing rapidly. For emerging movements and organizations the lnternet is a powerjiul and innovative tool; it promotes social participation and the search for more 'direct democracy'. Via Internet, social movements can build up an ever wider virtual community. Their skiful protest campaigns represent the prototype of the social revolutions of the future. These new instruments for communication and action promote the 'identity paradigm' which emphasizes basic psychosocial aspects such as the social construction of reality, collective identity, values and commitment to social issues

Learnable Graph Convolutional Attention Networks

Existing Graph Neural Networks (GNNs) compute the message exchange between nodes by either aggregating uniformly (convolving) the features of all the neighboring nodes, or by applying a non-uniform score (attending) to the features. Recent works have shown the strengths and weaknesses of the resulting GNN architectures, respectively, GCNs and GATs. In this work, we aim at exploiting the strengths of both approaches to their full extent. To this end, we first introduce the graph convolutional attention layer (CAT), which relies on convolutions to compute the attention scores. Unfortunately, as in the case of GCNs and GATs, we show that there exists no clear winner between the three (neither theoretically nor in practice) as their performance directly depends on the nature of the data (i.e., of the graph and features). This result brings us to the main contribution of our work, the learnable graph convolutional attention network (L-CAT): a GNN architecture that automatically interpolates between GCN, GAT and CAT in each layer, by adding only two scalar parameters. Our results demonstrate that L-CAT is able to efficiently combine different GNN layers along the network, outperforming competing methods in a wide range of datasets, and resulting in a more robust model that reduces the need of cross-validating.Comment: On review. 31 pages, 6 figure