Inhomogenous loop quantum cosmology with matter

The linearly polarized Gowdy $T^3$ model with a massless scalar field with the same symmetries as the metric is quantized by applying a hybrid approach. The homogeneous geometry degrees of freedom are loop quantized, fact which leads to the resolution of the cosmological singularity, while a Fock quantization is employed for both matter and gravitational inhomogeneities. Owing to the inclusion of the massless scalar field this system allows us to modelize flat Friedmann-Robertson-Walker cosmologies filled with inhomogeneities propagating in one direction. It provides a perfect scenario to study the quantum back-reaction between the inhomogeneities and the polymeric homogeneous and isotropic background.Comment: 4 pages, Contribution to the proceedings of the Loops 11-Madrid conferenc

Approximation methods in Loop Quantum Cosmology: From Gowdy cosmologies to inhomogeneous models in Friedmann-Robertson-Walker geometries

We develop approximation methods in the hybrid quantization of the Gowdy model with linear polarization and a massless scalar field, for the case of three-torus spatial topology. The loop quantization of the homogeneous gravitational sector of the Gowdy model (according to the improved dynamics prescription) and the presence of inhomogeneities lead to a very complicated Hamiltonian constraint. Therefore, the extraction of physical results calls for the introduction of well justified approximations. We first show how to approximate the homogeneous part of the Hamiltonian constraint, corresponding to Bianchi I geometries, as if it described a Friedmann-Robertson-Walker (FRW) model corrected with anisotropies. This approximation is valid in the high-energy sector of the FRW geometry (concerning its contribution to the constraint) and for anisotropy profiles that are sufficiently smooth. In addition, for certain families of states associated to regimes of physical interest, with negligible effects of the anisotropies and small inhomogeneities, one can approximate the Hamiltonian constraint of the inhomogeneous system by that of an FRW geometry with a relatively simple matter content, and then obtain its solutions.Comment: 20 pages, 3 figures. Minor changes, matches published versio

Inclusion of matter in inhomogeneous loop quantum cosmology

We study the hybrid quantization of the linearly polarized Gowdy $T^3$ model with a massless scalar field with the same symmetries as the metric. For simplicity, we quantize its restriction to the model with local rotational symmetry. Using this hybrid approach, the homogeneous degrees of freedom of the geometry are quantized \`a la loop, leading to the resolution of the cosmological singularity. A Fock quantization is employed both for the matter and the gravitational inhomogeneities. Owing to the inclusion of the massless scalar field this system allows us to modelize flat Friedmann-Robertson-Walker cosmologies filled with inhomogeneities propagating in one direction, providing a perfect scenario to study the quantum back-reaction of the inhomogeneities on the polymeric homogeneous and isotropic background.Comment: 4 pages. Contribution to the Proceedings of Spanish Relativity Meeting ERE2011, Madrid 201

Matter in inhomogeneous loop quantum cosmology: the Gowdy T(3) model

We apply a hybrid approach which combines loop and Fock quantizations to fully quantize the linearly polarized Gowdy $T^3$ model in the presence of a massless scalar field with the same symmetries as the metric. Like in the absence of matter content, the application of loop techniques leads to a quantum resolution of the classical cosmological singularity. Most importantly, thanks to the inclusion of matter, the homogeneous sector of the model contains flat Friedmann-Robertson-Walker (FRW) solutions, which are not allowed in vacuo. Therefore, this model provides a simple setting to study at the quantum level interesting physical phenomena such as the effect of the anisotropies and inhomogeneities on flat FRW cosmologies

Gestión del talento humano en la empresa muebles favian, Chincha, 2021

La presente |tesis de investigación, tuvo como título: “Gestión del Talento Humano en la empresa Muebles Favian, Chincha, 2021.”, y como objetivo general: Describir la Gestión del Talento Humano en la empresa Muebles Favian, Chincha, 2021. Además, tuvo un enfoque cuantitativo, tipo de investigación aplicada, nivel descriptivo y diseño no experimental de corte transversal. La población de la investigación estuvo conformada por 24 colaboradores de ambos sexos que laboran actualmente en la empresa Muebles Favian, se trabajó con una muestra censal, que hizo referencia a la totalidad de la población, se aplicó la técnica de la encuesta y como instrumento el cuestionario enfocado en la variable Gestión del Talento Humano. El resultado obtenido para la variable Gestión del Talento Humano fue alto, puesto que el 75% de los colaboradores manifestaron que siempre se realiza un proceso adecuado al momento de Incorporar a las personas. Así mismo, el 87,50% de los colaboradores manifestaron que siempre se realiza un proceso adecuado al momento de Organizar a las personas. Además, el 75% de los colaboradores de la empresa Muebles Favian detallaron que siempre se realiza un proceso adecuado al momento de Recompensar a las personas. También, el 75% de los colaboradores de la empresa Muebles Favian declararon que siempre se realiza un proceso adecuado al momento de Desarrollar a las personas. Por otro lado, el 70,83% de los colaboradores de la empresa Muebles Favian manifestaron que siempre se realiza un proceso adecuado al momento de Retener a las personas y por último, el 75% de los colaboradores de la empresa Muebles Favian manifestaron que siempre se realiza un proceso adecuado al momento de Auditar a las personas. Por ello, se concluyó, que efectivamente la Gestión del Talento Humano dentro de la empresa Muebles Favian fue alta debido a que el establecimiento presentó un nivel significativo en cada una de las dimensiones, sin embargo, se deben mejorar ciertos aspectos y factores dentro de la Organización para generar en los colaboradores sentido de pertenencia e identificación empresarial

distantia: an open-source toolset to quantify dissimilarity between multivariate ecological time-series

There is a large array of methods to extract knowledge and perform ecological forecasting from ecological time‐series. However, in spite of its importance for data‐mining, pattern‐matching and ecological synthesis, methods to assess their similarity are scarce. We introduce distantia (v1.0.1), an R package providing general toolset to quantify dissimilarity between ecological time‐series, independently of their regularity and number of samples. The functions in distantia provide the means to compute dissimilarity scores by time and by shape and assess their significance, evaluate the partial contribution of each variable to dissimilarity, and align or combine sequences by similarity. We evaluate the sensitivity of the dissimilarity metrics implemented in distantia, describe its structure and functionality, and showcase its applications with two examples. Particularly, we evaluate how geographic factors drive the dissimilarity between nine pollen sequences dated to the Last Interglacial, and compare the temporal dynamics of climate and enhanced vegetation index of three stands across the range of the European beech. We expect this package may enhance the capabilities of researchers from different fields to explore dissimilarity patterns between multivariate ecological time‐series, and aid in generating and testing new hypotheses on why the temporal dynamics of complex‐systems changes over space and time.publishedVersio

HAK transporters from Physcomitrella patens and Yarrowia lipolytica mediate sodium uptake

The widespread presence of Na+ specific uptake systems across plants and fungi is a controversial topic. In this study we identify two HAK genes, one in the moss Physcomitrella patens and the other in the yeast Yarrowia lipolytica, that encode Na+ specific transporters. Because HAK genes are numerous in plants and are duplicated in many fungi, our findings suggest that some HAK genes encode Na+ transporters and that Na+ might play physiological functions in plants and fungi more extensively than is currently thought

Design and operation of a rainfall simulator for field studies of runoff and soil erosion

[Abstract] The present paper describes the design, construction, calibration and operation of a spray rainfall simulator . The design of the plots used for the purpose of this study is also described in order to determine hydrological and erosion parameters. Selected rainfall intensity of 64 mm h- 1 are representative of heavy storm conditions in Galicia. Drop size distribution results in these conditions , a D5 0of 1.2 mm, were similar to those calculated for natural rainfall by BUBENZER (1979). Fall velocities reached were between 75 and 100% terminal velocity, depending on drop diameter and 13.05 Jm- 2m m- 1kinetic energy was obtained Surface area of the plots used was 1 m2, surronded by a metal structure connected to a V-shaped system to collect the surface runoff and sediment produced in the different experiments

Explainable artificial intelligence enhances the ecological interpretability of black-box species distribution models

Species distribution models (SDMs) are widely used in ecology, biogeography and conservation biology to estimate relationships between environmental variables and species occurrence data and make predictions of how their distributions vary in space and time. During the past two decades, the field has increasingly made use of machine learning approaches for constructing and validating SDMs. Model accuracy has steadily increased as a result, but the interpretability of the fitted models, for example the relative importance of predictor variables or their causal effects on focal species, has not always kept pace. Here we draw attention to an emerging subdiscipline of artificial intelligence, explainable AI (xAI), as a toolbox for better interpreting SDMs. xAI aims at deciphering the behavior of complex statistical or machine learning models (e.g. neural networks, random forests, boosted regression trees), and can produce more transparent and understandable SDM predictions. We describe the rationale behind xAI and provide a list of tools that can be used to help ecological modelers better understand complex model behavior at different scales. As an example, we perform a reproducible SDM analysis in R on the African elephant and showcase some xAI tools such as local interpretable model-agnostic explanation (LIME) to help interpret local-scale behavior of the model. We conclude with what we see as the benefits and caveats of these techniques and advocate for their use to improve the interpretability of machine learning SDMs.Peer reviewe