From rising star to shooting star: where next for Italy’s five star movement?

Italy’s Five Star Movement held a congress on 14-15 November to determine the party’s future. The congress came after disappointing regional election results and a sustained decline in opinion polls since the last Italian general election in 2018. Maria Giovanna Sessa and Giacomo Riccio write that the party must decide whether to embrace its position as a mainstream political actor or to reclaim its anti-system credentials

C3C^{3} : A Command-line Catalogue Cross-matching tool for modern astrophysical survey data

In the current data-driven science era, it is needed that data analysis techniques has to quickly evolve to face with data whose dimensions has increased up to the Petabyte scale. In particular, being modern astrophysics based on multi-wavelength data organized into large catalogues, it is crucial that the astronomical catalog cross-matching methods, strongly dependant from the catalogues size, must ensure efficiency, reliability and scalability. Furthermore, multi-band data are archived and reduced in different ways, so that the resulting catalogues may differ each other in formats, resolution, data structure, etc, thus requiring the highest generality of cross-matching features. We present $C^{3}$ (Command-line Catalogue Cross-match), a multi-platform application designed to efficiently cross-match massive catalogues from modern surveys. Conceived as a stand-alone command-line process or a module within generic data reduction/analysis pipeline, it provides the maximum flexibility, in terms of portability, configuration, coordinates and cross-matching types, ensuring high performance capabilities by using a multi-core parallel processing paradigm and a sky partitioning algorithm.Comment: 6 pages, 4 figures, proceedings of the IAU-325 symposium on Astroinformatics, Cambridge University pres

Intracellular Concentrations of Fosfomycin in Alveolar Macrophages from Weaning Piglets

At weaning, piglets are more susceptible to infectious diseases, being respiratory syndromes one of the most frequent conditions. Fosfomycin is indicated for the treatment of a variety of porcine bacterial pathogens, with MIC90 ranging between 0.25-0.50 µg mLG1 . Fosfomycin exhibits a time-dependent killing. Thus, killing of bacteria occurs when its concentrations remain constantly above the MIC. Fosfomycin concentrations in respiratory cells and epithelial lining fluid of pigs have already been studied. Although, fosfomycin showed clinical efficacy in the treatment of pulmonary diseases, concentrations in alveolar macrophages (biophase for facultative and obligate intracellular microorganisms) have not been established in any species. The present study determined the intracellular concentrations of disodium fosfomycin in alveolar macrophages after a single IM dose of 15 mg kgG1 in the gluteal muscle. Concentrations ranged from 0.14-1.52 µg mLG1 , being lower than those found in epithelial lining fluid (49.03%) and respiratory cells (54.48%). The Cmax was 1.52 µg mLG1 and Tmax was 4 h. Concentrations exceeded the MIC90 for most pathogens of importance in pig production for up to six hours (T>MIC = 6 h). Therefore, fosfomycin may be useful in the treatment of lung infections caused by facultative intracellular microorganisms.Fil: Pérez, Denisa Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencia Veterinarias. Departamento de Fisiopatología. Laboratorio de Toxicología; Argentina. Fundación Bunge y Born; ArgentinaFil: Soraci, Alejandro Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencia Veterinarias. Departamento de Fisiopatología. Laboratorio de Toxicología; ArgentinaFil: Martínez, Guadalupe. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencia Veterinarias. Departamento de Fisiopatología. Laboratorio de Toxicología; ArgentinaFil: Fernández Paggi, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencia Veterinarias. Departamento de Fisiopatología. Laboratorio de Toxicología; ArgentinaFil: Riccio, Maria Belen. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencia Veterinarias. Departamento de Fisiopatología. Laboratorio de Toxicología; ArgentinaFil: Dieguez, Susana Nelly. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencia Veterinarias. Departamento de Fisiopatología. Laboratorio de Toxicología; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Tapia, Maria Ofelia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencia Veterinarias. Departamento de Fisiopatología. Laboratorio de Toxicología; Argentin

Copyright collecting societies e regole di concorrenza

Il libro tratta, in chiave comparatistica, della disciplina delle società di gestione collettiva dei diritti d'autore. Della materia, recentemente, si è interessata la Commissione europea, pubblicando una proposta di direttiva, che dovrebbe essere emanata entro la fine dell'anno. Il libro analizza, in particolare, la necessità di superare l'esclusiva riconosciuta alla SIAE ex art. 180 l.d.a. alla luce della disciplina comunitaria - regole del Trattato e giurisprudenza di Corte di Giustizia e Commissione -, nonché, a livello interno, alla luce della recente liberalizzazione dei diritti connessi

Gigapixel Histopathological Image Analysis using Attention-based Neural Networks

Although CNNs are widely considered as the state-of-the-art models in various applications of image analysis, one of the main challenges still open is the training of a CNN on high resolution images. Different strategies have been proposed involving either a rescaling of the image or an individual processing of parts of the image. Such strategies cannot be applied to images, such as gigapixel histopathological images, for which a high reduction in resolution inherently effects a loss of discriminative information, and in respect of which the analysis of single parts of the image suffers from a lack of global information or implies a high workload in terms of annotating the training images in such a way as to select significant parts. We propose a method for the analysis of gigapixel histopathological images solely by using weak image-level labels. In particular, two analysis tasks are taken into account: a binary classification and a prediction of the tumor proliferation score. Our method is based on a CNN structure consisting of a compressing path and a learning path. In the compressing path, the gigapixel image is packed into a grid-based feature map by using a residual network devoted to the feature extraction of each patch into which the image has been divided. In the learning path, attention modules are applied to the grid-based feature map, taking into account spatial correlations of neighboring patch features to find regions of interest, which are then used for the final whole slide analysis. Our method integrates both global and local information, is flexible with regard to the size of the input images and only requires weak image-level labels. Comparisons with different methods of the state-of-the-art on two well known datasets, Camelyon16 and TUPAC16, have been made to confirm the validity of the proposed model.Comment: The manuscript was submitted to a peer-review journal on January 27t

BIRD: Watershed Based IRis Detection for mobile devices

Communications with a central iris database system using common wireless technologies, such as tablets and smartphones, and iris acquisition out of the field are important functionalities and capabilities of a mobile iris identification device. However, when images are acquired by means of mobile devices under uncontrolled acquisition conditions, noisy images are produced and the effectiveness of the iris recognition system is significantly conditioned. This paper proposes a technique based on watershed transform for iris detection in noisy images captured by mobile devices. The method exploits the information related to limbus to segment the periocular region and merges its score with the iris' one to achieve greater accuracy in the recognition phase