Socialis Phobia

Treballs de l'alumnat del Grau de Comunicació Audiovisual, Facultat d'Informació i Mitjans Audiovisuals, Universitat de Barcelona, Metanarratives. Curs: 2020-2021, Tutor: Josep Rovira. // Director: Pol Gras Lobato; Aj. Direcció: Alba Díaz Ruiz i Eulàlia Català Castro; Productor: Davinia Pérez Lòpez; Aj. Producció: Pol Gras Lobato, Adriá Bernal Ros, Julià Martínez Jerez, Eulàlia Català Castro i Alba Díaz Ruiz; Guionista: Pol Gras Lobato, Adriá Bernal Ros, Julià Martínez Jerez i Davinia Pérez Lòpez; Dir. Fotografia: Pol Gras Lobato i Julià Martínez Jerez; Càmera: Alba Díaz Ruiz; Aj. càmera: Pol Gras Lobato; Il·luminador: Julià Martínez Jerez; Direcció artística: Eulàlia Català Castro; Direcció de so: Davinia Pérez Lòpez; Muntatge: Davinia Pérez Lòpez; Música: Let is Last-Crowander; Postproducció: Davinia Pérez Lòpez. Equip artístic: Aina Cuesta.Aquesta peça reflecteix la por a ser jutjats mitjançant la conversió d’un entorn més amigable a un altre més fred i angoixant. Una noia rep imputs positius de la societat, dels amics, de la gent propera i això la fa feliç. Però com tot en aquesta vida hi ha moments menys agradables y aquests imposts es converteixen en comentaris i crítiques nocius i la danyen. Finalment, malferida acaba reclosa en si mateixa per por a ser jutjada

Patterns of transmission and horizontal gene transfer in the Dioscorea sansibarensis leaf symbiosis revealed by whole-genome sequencing

Leaves of the wild yam species Dioscorea sansibarensis display prominent forerunner or "drip" tips filled with extracellular bacteria of the species Orrella dioscoreae.1 This species of yam is native to Madagascar and tropical Africa and reproduces mainly asexually through aerial bulbils and underground tubers, which also contain a small population of O. dioscoreae.2,3 Despite apparent vertical transmission, the genome of O. dioscoreae does not show any of the hallmarks of genome erosion often found in hereditary symbionts (e.g., small genome size and accumulation of pseudogenes).4-6 We investigated here the range and distribution of leaf symbiosis between D. sansibarensis and O. dioscoreae using preserved leaf samples from herbarium collections that were originally collected from various locations in Africa. We recovered DNA from the extracellular symbiont in all samples, showing that the symbiosis is widespread throughout continental Africa and Madagascar. Despite the degraded nature of this DNA, we constructed 17 symbiont genomes using de novo methods without relying on a reference. Phylogenetic and genomic analyses revealed that horizontal transmission of symbionts and horizontal gene transfer have shaped the evolution of the symbiont. These mechanisms could help explain lack of signs of reductive genome evolution despite an obligate host-associated lifestyle. Furthermore, phylogenetic analysis of D. sansibarensis based on plastid genomes revealed a strong geographical clustering of samples and provided evidence that the symbiosis originated at least 13 mya, earlier than previously estimated.3

Use of soft computing techniques in renewable energy hydrogen hybrid systems

Soft computing techniques are important tools that significantly improve the performance of energy systems. This chapter reviews their many contributions to renewable energy hydrogen hybrid systems, namely those systems that consist of different technologies (photovoltaic and wind, electrolyzers, fuel cells, hydrogen storage, piping, thermal and electrical/electronic control systems) capable as a whole of converting solar energy, storing it as chemical energy (in the form of hydrogen) and turning it back into electrical and thermal energy. Fuzzy logic decision-making methodologies can be applied to select amongst renewable energy alternative or to vary a dump load for regulating wind turbine speed or find the maximum power point available from arrays of photovoltaic modules. Dynamic fuzzy logic controllers can furthermore be utilized to coordinate the flow of hydrogen to fuel cells or employed for frequency control in micro- grid power systems. Neural networks are implemented to model, design and control renewable energy systems and to estimate climatic data such as solar irradiance and wind speeds. They have been demonstrated to predict with good accuracy system power usage and status at any point of time. Neural controls can also help in the minimization of energy production costs by optimal scheduling of power units. Genetic or evolutionary algorithms are able to provide approximate solutions to several complex tasks with high number of variables and non-linearities, like optimal operational strategy of a grid-parallel fuel cell power plant, optimization of control strategies for stand-alone renewable systems and sizing of photovoltaic systems. Particle swarm optimization techniques are applied to find optimal sizing of system components in an effort to minimize costs or coping with system failures to improve service quality. These techniques can also be implemented together to exploit their potential synergies while, at the same time, coping with their possible limitations. This chapter covers soft computing methods applied to renewable energy hybrid hydrogen systems by providing a description of their single or mixed implementation and relevance, together with a discussion of advantages and/or disadvantages in their applications. \uc2\ua9 Springer-Verlag Berlin Heidelberg 2011