Biosensor enzimático quimiluminiscente para la determinación de aminas biógenas basado en la reacción luminol-peróxido de hidrógeno

Las aminas biógenas son compuestos nitrogenados de bajo peso molecular que presentan funciones biológicas importantes en el organismo de seres vivos. Se producen mediante descarboxilación selectiva de determinados aminoácidos, proceso llevado a cabo por microorganismos, generalmente bacterias. Sin embargo, en concentraciones elevadas pueden suponer riesgos en la salud de estos. Por este motivo, es necesario elaborar métodos rápidos de determinación de dichas aminas biógenas, que sean fiables y sencillos.En este trabajo de fin de grado se ha elaborado un método rápido para la determinación de aminas biógenas mediante señales quimiluminiscentes, que son la base de un biosensor enzimático. Estas señales son obtenidas al reaccionar el H2O2 con luminol, el cual se oxida generando luz. Esta reacción luminol/H2O2 necesita de la presencia de un catalizador el cual, en la mayoría de los casos, se acopla con la reacción enzimática entre el peróxido y la peroxidasa de rábano picante (HRP), siendo el Fe(II) presente en el grupo hemo de la enzima el que actúa como catalizador. El método propuesto para la determinación de putrescina se basa en la reacción enzimática con Diamino Oxidasa (DAO), en la que se genera H2O2 y en la utilización de las propiedades catalíticas del centro metálico (Cu(II)) de la enzima en sustitución HRP. Sin embargo en la concentración en la que se encuentra el Cu(II) en la enzima, no presenta poder catalítico notable. Por ello, se consiguió eliminar el Cu(II) e insertar Co(II), obteniéndose una actividad catalítica suficiente, con un rango lineal de 2,43·10-6 M hasta a 10-4 M de putrescina y una DSR(%) de 3,43%. También se comprobó que la cadaverina podía ser determinada con este método quimiluminiscente, si bien para esta amina se tiene menor sensibilidad.Con Tiramina oxidasa TAO-Co(II) resultó imposible dado que las aminas biógenas con las que reacciona (tiramina, tirosina y feniletilamina) presentan anillos aromáticos, los cuales desactivan la quimiluminiscencia (quencher). <br /

Inteligencia emocional en unidades de información: una experiencia formativa desde la AAB

La inteligencia emocional es una herramienta cada día más útil en el desarrollo diario de nuestras vidas, y en el trabajo bibliotecario es fundamental saber utilizarla. Este trabajo presenta el desarrollo de un proyecto llevado a cabo por la Asocia-ción Andaluza de Bibliotecarios al diseñar, organizar y desarrollar las I Jornadas Técnicas de Bibliotecas. Aquí se muestran todos los pasos dados en el desarrollo y ejecución del proyecto con el consecuente éxito en su desarrollo tanto en el ámbito organizativo como en el ámbito profesional

Subsidence damage assessment of a Gothic church using differential interferometry and field data

The Santas Justa and Rufina Gothic church (fourteenth century) has suffered several physical, mechanical, chemical, and biochemical types of pathologies along its history: rock alveolization, efflorescence, biological activity, and capillary ascent of groundwater. However, during the last two decades, a new phenomenon has seriously affected the church: ground subsidence caused by aquifer overexploitation. Subsidence is a process that affects the whole Vega Baja of the Segura River basin and consists of gradual sinking in the ground surface caused by soil consolidation due to a pore pressure decrease. This phenomenon has been studied by differential synthetic aperture radar interferometry techniques, which illustrate settlements up to 100 mm for the 1993–2009 period for the whole Orihuela city. Although no differential synthetic aperture radar interferometry information is available for the church due to the loss of interferometric coherence, the spatial analysis of nearby deformation combined with fieldwork has advanced the current understanding on the mechanisms that affect the Santas Justa and Rufina church. These results show the potential interest and the limitations of using this remote sensing technique as a complementary tool for the forensic analysis of building structures.Roberto Tomás is supported by a Generalitat Valenciana fellowship BEST-2011/225. The European Space Agency (ESA) Terrafirma project has funded all the SAR data processing with the SPN technique. Additionally, this study has been partially financed by the projects: TEC-2008-06764, TEC2011-28201-C02-02 ACOMP/2010/082, VIGROB-157, and 15224/PI/10

Regional subsidence modelling in Murcia city (SE Spain) using 1-D vertical finite element analysis and 2-D interpolation of ground surface displacements

Subsidence is a hazard that may have natural or anthropogenic origin causing important economic losses. The area of Murcia city (SE Spain) has been affected by subsidence due to groundwater overexploitation since the year 1992. The main observed historical piezometric level declines occurred in the periods 1982–1984, 1992–1995 and 2004–2008 and showed a close correlation with the temporal evolution of ground displacements. Since 2008, the pressure recovery in the aquifer has led to an uplift of the ground surface that has been detected by the extensometers. In the present work an elastic hydro-mechanical finite element code has been used to compute the subsidence time series for 24 geotechnical boreholes, prescribing the measured groundwater table evolution. The achieved results have been compared with the displacements estimated through an advanced DInSAR technique and measured by the extensometers. These spatio-temporal comparisons have showed that, in spite of the limited geomechanical data available, the model has turned out to satisfactorily reproduce the subsidence phenomenon affecting Murcia City. The model will allow the prediction of future induced deformations and the consequences of any piezometric level variation in the study area.This work has been supported by the Spanish Ministry of Economy and Competitiveness and EU FEDER funds under projects ESP2013-47780-C2-2-R and TEC2011-28201-C02-02 and by the project 15224/PI/10 from the Regional Agency of Science and Technology in Murcia. The European Space Agency (ESA) Terrafirma project funded all the SAR data processing with the SPN technique

Ecología y desarrollo humano

Con motivo de la publicación de la Encíclica "Laudato si'. Sobre el cuidado de la casa común" del Papa Francisco, la Universidad de Navarra organizó el 18 de marzo de 2016 una jornada interdisciplinar titulada "Ecología y desarrollo humano. Conversaciones sobre Laudato si'". La jornada pretendía incitar tanto al estudio y la profundización intelectual como al compromiso práctico acerca de las propuestas formuladas en la Encíclica. Se recogen en esta publicación los textos de las intervenciones iniciales de los ponentes en cada una de las mesas redondas. Se incluye también el coloquio de la primera mesa redonda sobre "El cuidado de la creación, responsabilidad del cristiano", así como las conclusiones de la jornada, que proponen vías para el desarrollo del compromiso ambiental y social en nuestra Universidad

Artificial intelligence within the interplay between natural and artificial computation:Advances in data science, trends and applications

Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in artificial intelligence and machine learning to the most prospective applications in robotics, neuroscience, brain computer interfaces, medicine and society, in general.BMS - Pfizer(U01 AG024904). Spanish Ministry of Science, projects: TIN2017-85827-P, RTI2018-098913-B-I00, PSI2015-65848-R, PGC2018-098813-B-C31, PGC2018-098813-B-C32, RTI2018-101114-B-I, TIN2017-90135-R, RTI2018-098743-B-I00 and RTI2018-094645-B-I00; the FPU program (FPU15/06512, FPU17/04154) and Juan de la Cierva (FJCI-2017–33022). Autonomous Government of Andalusia (Spain) projects: UMA18-FEDERJA-084. Consellería de Cultura, Educación e Ordenación Universitaria of Galicia: ED431C2017/12, accreditation 2016–2019, ED431G/08, ED431C2018/29, Comunidad de Madrid, Y2018/EMT-5062 and grant ED431F2018/02. PPMI – a public – private partnership – is funded by The Michael J. Fox Foundation for Parkinson’s Research and funding partners, including Abbott, Biogen Idec, F. Hoffman-La Roche Ltd., GE Healthcare, Genentech and Pfizer Inc

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications