Casting a new light on the democratic spectator

The idea of citizens being mere spectators who "watch" politics is widespread in public and academic debates. Scholarship in relation to democratic theory tends to see spectatorship as a state in which citizens are politically uninterested, isolated, and passive. Although this understanding aptly captures the problems about the idea of spectatorship, it is only a partial awareness and prevents us from seeing that positive forms of spectatorship are also possible. I show that positive spectatorship occurs when citizens show an interest in one or more political problems and, together with others, strive to understand them better. I consider the distinctive elements of this form of spectatorship characterized by careful observance, relationality, and proactivity. I argue that it is normatively desirable, and I reflect on the ways in which positive spectatorship helps thinking about democratizing politics. Relatedly, I also revisit the theatrical metaphor of politics, which is often associated to the concept of spectatorship as something negative for democracy. I argue that, when combined with a proper understanding of spectatorship, the theatrical metaphor can be used originally to envisage ways forward in the democratization of our societies

Systemic Unsustainability as a Threat to Democracy

Resilient socioeconomic unsustainability poses a threat to democracy whose importance has yet to be fully acknowledged. As the prospect of sustainability transition wanes, so does perceived legitimacy of institutions. This further limits representative institutions' ability to take action, making democratic deepening all the more urgent. I investigate this argument through an illustrative case study, the 2017 People's Climate March. In a context of resilient unsustainability, protesters have little expectation that institutions might address the ecological crisis and this view is likely to spread. New ways of thinking about this problem and a new research agenda are needed

Democratic Deliberation, Social Movements and the Quest for Democratic Politics

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The problem of marginality in public debates: evidence from The Guardian's Charlie Hebdo coverage

Who gets to have a voice in the public debate? Using The Guardian's coverage of the 2015 Charlie Hebdo attack, Andrea Felicetti and Pietro Castelli Gattinara find that women and religious groups, in particular Muslims, had limited visibility; while actors challenging the dominant securitisation narrative were similarly neglected. They conclude that greater attention must be paid to this problem of marginality in democratic systems

Mo.Se.: Segmentación de mosaico de imágenes basado en aprendizaje profundo en cascada

[EN] Mosaic is an ancient type of art used to create decorative images or patterns combining small components. A digital version of a mosaic can be useful for archaeologists, scholars and restorers who are interested in studying, comparing and preserving mosaics. Nowadays, archaeologists base their studies mainly on manual operation and visual observation that, although still fundamental, should be supported by an automatized procedure of information extraction. In this context, this research explains improvements which can change the manual and time-consuming procedure of mosaic tesserae drawing. More specifically, this paper analyses the advantages of using Mo.Se. (Mosaic Segmentation), an algorithm that exploits deep learning and image segmentation techniques; the methodology combines U-Net 3 Network with the Watershed algorithm. The final purpose is to define a workflow which establishes the steps to perform a robust segmentation and obtain a digital (vector) representation of a mosaic. The detailed approach is presented, and theoretical justifications are provided, building various connections with other models, thus making the workflow both theoretically valuable and practically scalable for medium or large datasets. The automatic segmentation process was tested with the high-resolution orthoimage of an ancient mosaic by following a close-range photogrammetry procedure. Our approach has been tested in the pavement of St. Stephen's Church in Umm ar-Rasas, a Jordan archaeological site, located 30 km southeast of the city of Madaba (Jordan). Experimental results show that this generalized framework yields good performances, obtaining higher accuracy compared with other state-of-the-art approaches. Mo.Se. has been validated using publicly available datasets as a benchmark, demonstrating that the combination of learning-based methods with procedural ones enhances segmentation performance in terms of overall accuracy, which is almost 10% higher. This study’s ambitious aim is to provide archaeologists with a tool which accelerates their work of automatically extracting ancient geometric mosaics.Highlights:A Mo.Se. (Mosaic Segmentation) algorithm is described with the purpose to perform robust image segmentation to automatically detect tesserae in ancient mosaics.This research aims to overcome manual and time-consuming procedure of tesserae segmentation by proposing an approach that uses deep learning and image processing techniques, obtaining a digital replica of a mosaic.Extensive experiments show that the proposed framework outperforms state-of-the-art methods with higher accuracy, even compared with publicly available datasets.[ES] El mosaico es un tipo de arte antiguo utilizado para crear imágenes decorativas o patrones de pequeños componentes. Una versión digital de un mosaico puede ser útil a los arqueólogos, estudiosos y restauradores que están interesados en el estudio, la comparación y la preservación de los mosaicos. Hoy en día, los arqueólogos basan sus estudios principalmente en la operación manual y la observación visual que, aunque sigue siendo fundamental, debe ser apoyada con la ayuda de un procedimiento automatizado de extracción de la información. En este contexto, esta investigación tiene la intención de superar el procedimiento manual y lento del dibujo de teselas en mosaico proponiendo Mo.Se. (Mosaic Segmentation), un algoritmo que explota técnicas de aprendizaje profundo y segmentación de imagen; específicamente, la metodología combina la red U-Net 3 con el algoritmo Watershed. El propósito final es definir un flujo de trabajo que establezca los pasos para realizar una segmentación robusta y obtener una representación digital (vectorial) de un mosaico. Se presenta el procedimiento detallado y se proporcionan justificaciones teóricas, construyendo varias conexiones con otros modelos, haciendo que el flujo de trabajo sea teóricamente valioso y prácticamente escalable en conjuntos de datos medianos o grandes. El proceso de segmentación automática se probó con la ortoimagen de alta resolución de un mosaico antiguo, siguiendo un procedimiento de fotogrametría de objeto cercano. Nuestro enfoque se ha probado en el pavimento de la Iglesia de San Esteban en Umm ar-Rasas, un sitio arqueológico de Jordania, ubicado a 30 km al sureste de la ciudad de Madaba (Jordania). Los resultados experimentales muestran que este marco generalizado produce buenos rendimientos, obteniendo una mayor precisión en comparación con otros enfoques de vanguardia. Mo.Se. se ha validado utilizando conjuntos de datos disponibles públicamente como punto de referencia, lo que demuestra que la combinación de métodos basadosen el aprendizaje con métodos procedimentales mejora el rendimiento de la segmentación en casi un 10% en términos de exactitud en general. El ambicioso objetivo de este estudio es proporcionar a los arqueólogos una herramienta que acelere su trabajo de extracción automática de mosaicos geométricos antiguos.This work was partially found within the framework of the project Innovative technologies and training activities for the conservation and enhancement of the archaeological site of Umm er-Rasas (Jordan) funded by Ministero degli Affari Esteri e della Cooperazione Internazionale. The authors would like to express their gratitude to the ISPC CNR and in particular to Dott. Roberto Gabrielli (project leader) and Alessandra Albiero for providing the dataset.Felicetti, A.; Paolanti, M.; Zingaretti, P.; Pierdicca, R.; Malinverni, ES. 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Exercise-induced up-regulation of MMP-1 and IL-8 genes in endurance horses

<p>Abstract</p> <p>Background</p> <p>The stress response is a critical factor in the training of equine athletes; it is important for performance and for protection of the animal against physio-pathological disorders.</p> <p>In this study, the molecular mechanisms involved in the response to acute and strenuous exercise were investigated using peripheral blood mononuclear cells (PBMCs).</p> <p>Results</p> <p>Quantitative real-time PCR (qRT-PCR) was used to detect modifications in transcription levels of the genes for matrix metalloproteinase-1 (<it>MMP-1</it>) and interleukin 8 (<it>IL-8</it>), which were derived from previous genome-wide expression analysis. Significant up-regulation of these two genes was found in 10 horses that had completed a race of 90–120 km in a time-course experimental design.</p> <p>Conclusion</p> <p>These results suggest that <it>MMP-1 </it>and <it>IL-8 </it>are both involved in the exercise-induced stress response, and this represents a starting point from which to understand the adaptive responses to this phenomenon.</p

Exercise induced stress in horses: Selection of the most stable reference genes for quantitative RT-PCR normalization

<p>Abstract</p> <p>Background</p> <p>Adequate stress response is a critical factor during athlete horses' training and is central to our capacity to obtain better performances while safeguarding animal welfare.</p> <p>In order to investigate the molecular mechanisms underlying this process, several studies have been conducted that take advantage of microarray and quantitative real-time PCR (qRT-PCR) technologies to analyse the expression of candidate genes involved in the cellular stress response.</p> <p>Appropriate application of qRT-PCR, however, requires the use of reference genes whose level of expression is not affected by the test, by general physiological conditions or by inter-individual variability.</p> <p>Results</p> <p>The expression of nine potential reference genes was evaluated in lymphocytes of ten endurance horses during strenuous exercise. These genes were tested by qRT-PCR and ranked according to the stability of their expression using three different methods (implemented in <it>geNorm</it>, <it>NormFinder </it>and <it>BestKeeper</it>). Succinate dehydrogenase complex subunit A (<it>SDHA</it>) and hypoxanthine phosphoribosyltransferase (<it>HPRT</it>) always ranked as the two most stably expressed genes. On the other hand, glyceraldehyde-3-phosphate dehydrogenase (<it>GAPDH</it>), transferrin receptor (<it>TFRC</it>) and ribosomal protein L32 (<it>RPL32</it>) were constantly classified as the less reliable controls.</p> <p>Conclusion</p> <p>This study underlines the importance of a careful selection of reference genes for qRT-PCR studies of exercise induced stress in horses. Our results, based on different algorithms and analytical procedures, clearly indicate <it>SDHA </it>and <it>HPRT </it>as the most stable reference genes of our pool.</p

Introduction: The New England Town Meeting: A Founding Myth of American Democracy

Notwithstanding notable exceptions, historical investigation is far from central in deliberative scholarship and even recent work on participatory research stresses the need for more historical work. The aim of our introduction to this collective volume is to assess and to draw attention to the contribution of historical analysis in the current scholarly debate on democracy, in particular regarding the ways in which participation and deliberation emerge and develop in New England’s famous town meetings. Town meetings have traditionally been cited as one of the fullest and earliest realizations of the idea of democratic government and of deliberation at work. Nowadays the great debate on deliberative and participatory democracy has contributed to restoring the town meetings as a symbol of democratic deliberation. The critical study of how one of the oldest and most inspiring forms of democratic participation has evolved is not only a fascinating endeavor in itself, it is also a unique opportunity to better understand how and to what extent these institutional practices, inspired by ideals of deliberation and participation, can support – or impede – the democratization of today’s societies