Coherence effects in disordered geometries with a field-theory dual

We investigate the holographic dual of a probe scalar in an asymptotically Anti-de-Sitter (AdS) disordered background which is an exact solution of Einstein's equations in three bulk dimensions. Unlike other approaches to model disorder in holography, we are able to explore quantum wave-like interference effects between an oscillating or random source and the geometry. In the weak-disorder limit, we compute analytically and numerically the one-point correlation function of the dual field theory for different choices of sources and backgrounds. The most interesting feature is the suppression of the one-point function in the presence of an oscillating source and weak random background. We have also computed analytically and numerically the two-point function in the weak disorder limit. We have found that, in general, the perturbative contribution induces an additional power-law decay whose exponent depends on the distribution of disorder. For certain choices of the gravity background, this contribution becomes dominant for large separations which indicates breaking of perturbation theory and the possible existence of a phase transition induced by disorder.Comment: 36 pages, 19 figs, v3 accepted versio

Mellora de métodos computacionais semiempíricos para a predición de reactividade química mediante técnicas de “machine learning”

Traballo Fin de Grao en Química. Curso 2020-2021O machine learning e a intelixencia artificial estanse convertindo en técnicas cada vez máis presentes na investigación en química computacional. A medida que temos acceso a unha maior cantidade datos de química cuántica, aumentan as posibilidades de uso de algoritmos intelixentes para a exploración do espazo químico. Por outra parte, aínda non dispoñemos de métodos eficientes para a predición de propiedades de reacción cuantitativas. Entre estas propiedades atópase a enerxía de activación, cuxa predición de forma precisa proporcionaría un método para o descubrimento de novos mecanismos de reacción e forneceríanos control sobre a cinética das reaccións. O presente traballo intenta buscar un algoritmo baseado en machine learning para a predición de enerxías de activación. O noso modelo depende dun cálculo a nivel semiempírico (PM7) e proporciona unha predición a nivel DFT mediante machine learning. Con este procedemento, conseguimos precisión química cun custo computacional reducido. Ademais de obter un rendemento equiparable ao estado da arte, esta alternativa contribúe con descritores personalizados, que poden ser incorporados en novos procedementos de minaría de datos na química. Por último, tamén proporciona unha interpretación do modelo dende a perspectiva da intuición química.El machine learning y la inteligencia artificial se están convirtiendo en técnicas cada vez más presentes en la investigación en química computacional. A medida que tenemos acceso a una mayor cantidad de datos de química cuántica, aumentan las posiblidades de uso de algoritmos inteligentes para la exploración del espacio químico. Por otra parte, todavía no disponemos de métodos eficientes para la predicción de propiedades de reacción cuantitativas. Entre estas propiedades se encuentra la energía de activación, cuya predicción de forma precisa proporcionaría un método para el descubrimiento de nuevos mecanismos de reacción y nos facilitaría el control sobre la cinética de las reacciones. El presente trabajo intenta buscar un algoritmo basado en machine learning para la predicción de energías de activación. Nuestro modelo depende de un cálculo a nivel semiempírico (PM7) y proporciona una predicción a nivel DFT mediante machine learning. Con este procedimiento, conseguimos precisión química con un coste computacional reducido. Además de obtener un rendimiento equiparable al estado del arte, esta alternativa contribuye con descriptores personalizados, que pueden ser incorporados en procedimientos de minería de datos en la química. Por último, también proporciona una interpretación del modelo desde una perspectiva de la intuición química.Machine learning and artificial intelligence are becoming ubiquitous techniques in computational chemistry research. With quantum-chemical data becoming increasingly available, intelligent algorithms are taking the upper hand in the exploration of the chemical space. On the other hand, we still lack efficient algorithms when it comes to predicting quantitative reaction properties. Within this properties, accurately predicting activation energies would enable rapid discovery of new reaction mechanisms and would grant control over chemical kinetics. The present work intends to seek for a machine learning-based algorithm to predict activation energies. Our model relies on a semiempirical calculation (PM7 level of theory) and resorts to machine learning to DFT accuracy. With this procedure, we can obtain chemical accuracy while limiting the computational expenditure. In addition to achieving state of the art performance, this approach contribute with innovative custom descriptors that can be harnessed in data mining techniques in the chemical domain and allow interpretability from the perspective of chemical intuition

The Promotion of Reading and Writing’s specialization: Present, Past and Future

El objetivo de este trabajo es describir y clasificar el contenido de los trabajos especiales de grado (teg) que han sido presentados en la Especialización en Promoción de la Lectura y la Escritura, de la Universidad de Los Andes, Táchira. Para ello, ofreceremos una serie de datos que nos permitirán tener una visión general de estas obras (p. e., comunidades beneficiadas con los teg, tipo de textos promovidos en cada propuesta, etc.). Con estos datos obtenidos procuraremos demostrar la necesidad de mejorar los mecanismos digitales de difusión existentes para estos trabajos. Al final de este artículo propondremos no solo la digitalización de los teg que hasta ahora han recibido la Mención Publicación en este posgrado, sino también la corrección de estilo de estos para subsanar las transgresiones de la norma culta de la lengua escrita que les fueron detectados en una investigación previa (Andrade y García, en prensa)

The Role of ABA in Plant Immunity is Mediated through the PYR1 Receptor

[EN] ABA is involved in plant responses to a broad range of pathogens and exhibits complex antagonistic and synergistic relationships with salicylic acid (SA) and ethylene (ET) signaling pathways, respectively. However, the specific receptor of ABA that triggers the positive and negative responses of ABA during immune responses remains unknown. Through a reverse genetic analysis, we identified that PYR1, a member of the family of PYR/PYL/RCAR ABA receptors, is transcriptionally upregulated and specifically perceives ABA during biotic stress, initiating downstream signaling mediated by ABA-activated SnRK2 protein kinases. This exerts a damping effect on SA-mediated signaling, required for resistance to biotrophic pathogens, and simultaneously a positive control over the resistance to necrotrophic pathogens controlled by ET. We demonstrated that PYR1-mediated signaling exerted control on a priori established hormonal cross-talk between SA and ET, thereby redirecting defense outputs. Defects in ABA/PYR1 signaling activated SA biosynthesis and sensitized plants for immune priming by poising SA-responsive genes for enhanced expression. As a trade-off effect,pyr1-mediated activation of the SA pathway blunted ET perception, which is pivotal for the activation of resistance towards fungal necrotrophs. The specific perception of ABA by PYR1 represented a regulatory node, modulating different outcomes in disease resistance.This research was founded by the Spanish AEI agency by grant BIO2017-82503-R to P.L.R. and by grant RTI2018-098501-B-I00 to P.V.García-Andrade, J.; González, B.; Gonzalez-Guzman, M.; Rodríguez Egea, PL.; Vera Vera, P. (2020). The Role of ABA in Plant Immunity is Mediated through the PYR1 Receptor. International Journal of Molecular Sciences. 21(16):1-21. https://doi.org/10.3390/ijms21165852S1212116Malamy, J., Carr, J. P., Klessig, D. F., & Raskin, I. (1990). 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Bike desk una propuesta de intervención para mejorar el nivel de actividad física y el rendimiento cognitivo en escolares de Educación Primaria

The aim of this study was to analyze the effect of 5 weeks of interactive pedaling during classes on physical fitness, school skills and creativity in primary school children. A total of 89 children (age range = 10-12 years) participated in this study, although due to the COVID-19 pandemic only 37 students could be considered for the analysis of the results. The students were randomly assigned to two groups, experimental group (EG) and control group (CG). The GE performed a moderate to vigorous intensity cycling program with cognitive engagement for 5 weeks, 4 days a week. Physical fitness, school skills and creativity were assessed. No significant differences were found between groups in terms of creativity. The CG experienced significant improvements in numeracy and total ASD. In addition, both groups showed significant improvements in the horizontal jump test. In conclusion, the implementation of pedal machines does not interfere with the academic performance of schoolchildren and can therefore be an effective means of improving students' physical activity levels.El objetivo de este estudio fue analizar el efecto de 5 semanas de pedaleo interactivo durante las clases en la condición física, aptitudes escolares y creatividad en niños de Educación Primaria. Un total de 89 niños (rango de edad = 10-12 años) participaron en este estudio, aunque debido a la pandemia del COVID-19 solo 37 alumnos se pudieron considerar para el análisis de los resultados. Los estudiantes fueron asignados al azar a dos grupos, grupo experimental (GE) y grupo de control (GC). El GE realizó un programa de pedaleo de intensidad moderada a vigorosa con compromiso cognitivo durante 5 semanas, 4 días a la semana. Se evaluaron la aptitud física, las aptitudes escolares y la creatividad. No se encontraron diferencias significativas entre los grupos en cuanto a creatividad se refiere. El GC experimentó mejoras significativas en el cálculo y el total TEA. Además, ambos grupos mostraron mejoras significativas en el test del salto horizontal. En conclusión, la implementación de pedaleadores no interfiere con el rendimiento académico de los escolares por lo que puede ser un medio efectivo para la mejora de los niveles de actividad física del alumnado

Reciprocal regulation between AtNRT2.1 and AtAMT1.1 expression and the kinetics of NH4+ and NO3− influxes

Our results show that AtNRT2.1 expression has a positive effect on the NH4+ ion influx, mediated by the HATS, as also occurs with AtAMT1.1 expression on the NO3− ion influx. AtNRT2.1 expression plays a key role in the regulation of AtAMT1.1 expression and in the NH4+ ion influx, differentiating the nitrogen source, and particularly, the lack of it. Nitrogen starvation produces a compensatory effect by AtAMT1.1 when there is an absence of the AtNRT2.1 gene. Our results also show that, in the atnrt2 mutant lacking both AtNRT2.1 and AtNRT2.2, gene functions present different kinetic parameters on the NH4+ ion influx mediated by the HATS, according to the source and availability of nitrogen. Finally, the absence of AMT1.1 also produces changes in the kinetic parameters of the NO3− influx, showing different Vmax values depending on the source of nitrogen available

Barrier height prediction by machine learning correction of semiempirical calculations

Different machine learning (ML) models are proposed in the present work to predict DFT-quality barrier heights (BHs) from semiempirical quantum-mechanical (SQM) calculations. The ML models include multi-task deep neural network, gradient boosted trees by means of the XGBoost interface, and Gaussian process regression. The obtained mean absolute errors (MAEs) are similar or slightly better than previous models considering the same number of data points. Unlike other ML models employed to predict BHs, entropic effects are included, which enables the prediction of rate constants at different temperatures. The ML corrections proposed in this paper could be useful for rapid screening of the large reaction networks that appear in Combustion Chemistry or in Astrochemistry. Finally, our results show that 70% of the bespoke predictors are amongst the features with the highest impact on model output. This custom-made set of predictors could be employed by future delta-ML models to improve the quantitative prediction of other reaction properties

EL TURISMO MARINERO COMO OPCIÓN DE DESARROLLO LOCAL SOSTENIBLE A PARTIR DEL EMPODERAMIENTO FEMENINO

Marine tourism has become a tourist reference with more than two decades of international expansion and continuous growth. In this context, the present work aims to study marine tourism as an option for sustainable local development through female empowerment. The study has been based on semi-structured interviews with women who lead marine tourism projects in Galicia and on a content analysis of the news on the treatment that the press gives them. The results show that most of the projects are innovative, diversified, participatory and responsible. It is found that, despite the evident progress, it is necessary to further promote female entrepreneurship in the field of marine tourism, in addition to promoting their presence and social projection through the media.El turismo marinero se ha convertido en un referente turístico con más de dos décadas de expansión a nivel internacional y en continuo crecimiento. En este contexto, el presente trabajo tiene como objetivo estudiar el turismo marinero como opción de desarrollo local sostenible a través del empoderamiento femenino. El estudio se ha basado en entrevistas semiestructuradas a mujeres que lideran proyectos de turismo marinero en Galicia y en un análisis de contenido de las noticias sobre el tratamiento que la prensa les otorga. Los resultados evidencian que la mayor parte de los proyectos tienen un carácter innovador, diversificado, participativo y responsable. Se constata que, a pesar del evidente avance, es necesario promover más la iniciativa empresarial femenina en el ámbito del turismo marinero, además de fomentar su presencia y proyección social a través de los medios.&nbsp