The quantum non-linear σ\sigma-model RG flow and integrability in wormhole geometries

The target space of the non-linear $\sigma$-model is a riemannian manifold. Although it can be any riemannian metric, there are certain physically interesting geometries which are worth to study. Here, we numerically evolve the time-symmetric foliations of a family of spherically symmetric asymptotically flat wormholes under the $1$-loop renormalization group flow of the non-linear $\sigma$-model, the Ricci flow, and under the $2$-loop aproximation, RG-2 flow. We rely over some theorems adapted from the compact case for studying the evolution of different wormhole types, specially those with high curvature zones. Some metrics expand and others contract at the beginning of the flow, however, all metrics pinch-off at a certain time. This is related with the fact that the flow does not converge to a fixed point when its starting geometry is the spatial sections of a Morris-Thorne wormhole, and therefore the corresponding non-linear $\sigma$-model is non-integrable/renormalizable. We present a numerical study of the evolution of wormhole singularities in three dimensions extending the theoretical estimations. Finally, we compute the evolution of the Hamilton's entropy and the Brown-York energy.Comment: 18 p

La facilitación como un mecanismo que incrementa la diversidad vegetal en ambientes extremos

Negative interactions among plants are considered the most important factors determining the shape, structure and dynamics of plant communities, and because of this viewpoint, much research has been devoted to understanding the nature of competitive interactions among plants. However, the result of multiple studies in the last two decades had shown that positive interaction could also play an important role determining the structure and function of terrestrial ecosystems. Facilitation is a type of nontrophic positive interaction that occurs between physiologically independent individuals and is mediated through changes in the abiotic environment or through other organisms. Most of the research in the field of facilitation in the last twenty years has been developed from the stress gradient hypothesis (SGH). Facilitation may act directly or indirectly through different mechanisms. The results of multiple investigations indicate that facilitation can increase the diversity of plant species in harsh environments, where facilitator species can mitigate extreme conditions and benefit other species. Still, few studies have quantified the number of species that are added to a community because facilitation and the challenge is to design experiments and studies to quantify the relative importance of the provision for the maintenance of biodiversity in extreme environments.Tradicionalmente se consideró que las interacciones negativas entre especies de plantas eran la fuerza modeladora de la estructura y el funcionamiento de los ecosistemas, mientras las interacciones positivas eran de poca importancia en ese sentido. Dicha visión ha cambiado en las últimas décadas y actualmente se considera que las interacciones de tipo positivo, también juegan un papel importante para la estructuración y el funcionamiento de los ecosistemas. La facilitación es un tipo de interacción positiva no trófica, que se produce entre plantas fisiológicamente independientes y que está mediada a través de cambios en el entorno abiótico o a través de otros organismos. La mayor parte de la investigación realizada en el campo de la facilitación en los últimos veinte años se ha desarrollado a partir de la hipótesis del gradiente de estrés (HGE). La facilitación puede actuar directa o indirectamente a través de diferentes mecanismos. Los resultados de múltiples investigaciones, indican que la facilitación puede aumentar la diversidad de las especies vegetales en ambientes extremos, donde la presencia de una especie nodriza modifica el ambiente de manera tal, que resulta en una reducción en la frecuencia e intensidad de alguna perturbación física o estrés, permitiendo que las especies menos tolerantes puedan sobrevivir. Sin embargo, existen pocos estudios que cuantifiquen el número de especies que se agregan a una comunidad debido a la facilitación, así el reto es diseñar experimentos y estudios que permitan cuantificar la importancia relativa de la facilitación para el mantenimiento de la biodiversidad en ecosistemas extremos

Aplicativo SIGMA EMBRAPA: versão 1.0 para Windows.

O aplicativo SIGMA Embrapa (Sistema de Gerenciamento de Manutenções) foi desenvolvido a fim de informatizar a Área de Manutenção e equipamentos Laboratoriais (AML), permitindo o registro dos serviçoes realizados, pesquisas no banco de dados e geração de relatórios.bitstream/CNPDIA/8890/1/CT28_98.pd

Cuidados básicos com peagômetros.

bitstream/CNPDIA/9860/1/RT06_97.pd

Homeostatic Response to Three Years of Experimental Warming Suggests High Intrinsic Natural Resistance in the Páramos to Warming in the Short Term

Páramos, tropical alpine ecosystems, host one of the world s most diverse alpine floras, account for the largest water reservoirs in the Andes, and some of the largest soil carbon pools worldwide. It is of global importance to understand the future of this extremely carbon-rich ecosystem in a warmer world and its role on global climate feedbacks. This study presents the result of the first in situ warming experiment in two Colombian páramos using Open-Top Chambers. We evaluated the response to warming of several ecosystem carbon balance-related processes, including decomposition, soil respiration, photosynthesis, plant productivity, and vegetation structure after 3 years of warming. We found that OTCs are an efficient warming method in the páramo, increasing mean air temperature by 1.7°C and mean daytime temperature by 3.4°C. The maximum air temperature differences between OTC and control was 23.1°C. Soil temperature increased only by 0.1°C. After 3 years of warming using 20 OTC (10 per páramo) in a randomized block design, we found no evidence that warming increased CO2 emissions from soil respiration, nor did it increase decomposition rate, photosynthesis or productivity in the two páramos studied. However, total C and N in the soil and vegetation structure are slowly changing as result of warming and changes are site dependent. In Sumapaz, shrubs, and graminoids cover increased in response to warming while in Matarredonda we observed an increase in lichen cover. Whether this change in vegetation might influence the carbon sequestration potential of the páramo needs to be further evaluated. Our results suggest that páramos ecosystems can resist an increase in temperature with no significant alteration of ecosystem carbon balance related processes in the short term. However, the long-term effect of warming could depend on the vegetation changes and how these changes alter the microbial soil composition and soil processes. The differential response among páramos suggest that the response to warming could be highly dependent on the initial conditions and therefore we urgently need more warming experiments in páramos to understand how specific site characteristics will affect their response to warming and their role in global climate feedbacks. © Copyright © 2021 Lasso, Matheus-Arbeláez, Gallery, Garzón-López, Cruz, Leon-Garcia, Aragón, Ayarza-Páez and Curiel Yuste.Special thanks to David Campos, Fabian Salgado, Luis Fernando Rojas, Ewen Dano, Jorge Acosta, Juliana Portilla, and Michelle Guevara that helped with field and lab work. We would like to thank the Sabogal family for allowing the establishment of the OTC and collection of samples in the p?ramo ?Parque Ecol?gico Matarredonda? and to the Lieutenant Colonel Edgar Riveira, Commander of the High Mountain Battalion No. 1 in Sumapaz and all the commanders that follow him and who provided us with accommodation and food in the battalion as well as logistic support in all our field campaigns. Thanks to all the soldiers who always enthusiastically helped us in the field work in Sumapaz. This research was also supported by the Basque Government through the BERC 2018?2021 program, and by the Spanish Ministry of Science, Innovation and Universities through the BC3 Mar?a de Maeztu excellence accreditation (MDM-2017-0714). Funding. Funding for this research comes from the ?Patrimonio Aut?nomo Fondo Nacional de Financiamiento para la Ciencia, la Tecnolog?a y la Innovaci?n Francisco Jos? de Caldas?Colciencias,? grant number 120471451294, granted by Colciencias (today?s Colombian Ministry of Science, Technology and Innovation), from Eloisa Lasso?s FAPA (Fondo de Apoyo para Profesores Asistentes) grant number P12.160422.001 from the Universidad de los Andes, and from the Research Fund to support faculty programs at the Faculty of Sciences at the Universidad de los Andes grant number INV-2019-84-1805

Efectos de la pandemia por Covid-19 en el mercado laboral colombiano: identificando el impacto de restricciones sectoriales a la movilidad

En este trabajo evaluamos el efecto de la pandemia de Covid-19 y las restricciones de movilidad sectoriales implementadas para reducir la velocidad del contagio. Para identificar el efecto de estas políticas, explotamos la variación en el empleo y salarios en los sectores excluidos y no excluidos de las restricciones a la movilidad, así como el momento de su implementación. Las restricciones sectoriales a la movilidad tienen efectos negativos en el empleo, representando aproximadamente una cuarta parte de la pérdida total de empleo entre febrero y abril de 2020. Los patrones regionales de propagación de la enfermedad y otros componentes epidemiológicos y económicos, que afectaron al país durante este período, representan las tres cuartas partes restantes de la pérdida de empleos. Por lo tanto, debemos esperar importantes pérdidas de empleo incluso en ausencia de dichas restricciones. No encontramos un efecto significativo en el promedio de horas trabajadas o los salarios, lo que indica que la mayor parte del ajuste del mercado laboral tuvo lugar en el margen extensivo. Además, las restricciones a la movilidad sectoriales afectan principalmente a los trabajadores asalariados, mientras que el trabajo por cuenta propia responde principalmente a la propagación de la enfermedad.We assess the effect of the Covid-19 pandemic and the lockdown of some economic sectors on the Colombian labor market. We exploit the variation between excluded and non-excluded sectors from the lockdown, as well as the timing of the restriction policies, to identify the effect of sector-specific restriction policies. These restrictions had negative effects on employment, accounting for approximately a quarter of the total job loss between February and April of 2020; the remaining three quarters of the job losses can be attributed to the regional patterns of the disease spread, and other epidemiological and economic factors affecting the whole country during this period. Therefore, we should expect important employment losses even in the absence of such restrictions. In contrast, we find no significant effect of sector-specific restrictions on average worked hours or wages, indicating that most of the adjustment of the labor market took place in the extensive margin. Moreover, sector-specific restrictions only affect salaried workers, while self-employment is more responsive to the disease spread

Obtaining agricultural land cover in Sentinel-2 satellite images with drone image injection using Random Forest in Google Earth Engine

[ES] Para obtener información precisa sobre los cambios de la cubierta terrestre en el sector agrícola, proponemos un método de clasificación supervisada que integra las imágenes del satélite Sentinel-2 con las imágenes obtenidas de los Sistemas de Aeronaves Pilotadas a Distancia (RPAS, por sus siglas en inglés). La metodología se aplicó en la plataforma de Google Earth Engine. Inicialmente, la colección de imágenes de Sentinel-2 se integró en una sola imagen mediante un proceso de reducción de mediana. Posteriormente, se aplicó el método de fusión de imágenes de pansharpening con filtro de paso alto (HPF, por sus siglas en inglés) a las bandas espectrales térmicas para obtener una resolución espacial final de 10 m. Para realizar la integración de las dos fuentes de imágenes, la imagen del RPAS se normalizó utilizando un filtro de textura gaussiano de 5×5 y el píxel se re-muestreó a cinco veces su tamaño original. Este procedimiento se realizó de forma iterativa hasta alcanzar la resolución espacial de la imagen del Sentinel-2. Además, se añadieron a la clasificación los siguientes datos: los índices espectrales, calculados a partir de las bandas de Sentinel-2 y RPAS (por ejemplo, NDVI, NDWI, SIPI, GARI), la información altimétrica y las pendientes de la zona derivadas del MED SRTM. La clasificación supervisada se realizó utilizando la técnica de Random Forest (Machine Learning). La referencia de la semilla de la cubierta terrestre para realizar la clasificación fue capturada manualmente por un experto temático, luego, esta referencia fue distribuida en un 70% para el entrenamiento del algoritmo de Random Forest y en un 30% para validar la clasificación. Los resultados muestran que la incorporación de la imagen RPAS mejora los indicadores de precisión temática en un promedio del 3% en comparación con una clasificación realizada exclusivamente con imágenes de Sentinel-2.[EN] To obtain accurate information on land cover changes in the agricultural sector, we propose a supervised classification method that integrates Sentinel-2 satellite imagery with images surveyed from Remote Piloted Aircraft Systems (RPAS). The methodology was implemented on the Google Earth Engine platform. Initially, the Sentinel-2 imagery collection was integrated into a single image through a median reduction process. Subsequently, the high-pass filter (HPF) pansharpening image fusion method was applied to the thermal spectral bands to obtain a final spatial resolution of 10 m. To perform the integration of the two image sources, the RPAS image was normalized by using a 5X5 gaussian texture filter and the pixel was resampled to five times its original size. This procedure was performed iteratively until reaching the spatial resolution of the Sentinel-2 imagery. Besides, the following inputs were added to the classification: the spectral indices calculated from the Sentinel-2 and RPAS bands (e.g. NDVI, NDWI, SIPI, GARI); altimetric information and slopes of the zone derived from the SRTM DEM. The supervised classification was done by using the Random Forest technique (Machine Learning). The land cover seed reference to perform the classification was manually captured by a thematic expert, then, this reference was distributed in 70% for the training of the Random Forest algorithm and in 30% to validate the classification. The results show that the incorporation of the RPAS image improves thematic accuracy indicators by an average of 3% compared to a classification made exclusively with Sentinel-2 imagery.Departamento Administrativo Nacional de EstadísticaRamírez, M.; Martínez, L.; Montilla, M.; Sarmiento, O.; Lasso, J.; Díaz, S. (2020). Obtención de coberturas del suelo agropecuarias en imágenes satelitales Sentinel-2 con la inyección de imágenes de dron usando Random Forest en Google Earth Engine. Revista de Teledetección. 0(56):49-68. https://doi.org/10.4995/raet.2020.14102OJS496805