Monarquia de España Historia de la vida y hechos del indito monarca ... D. Felipe tercero

Copia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 2009-2010Sign.: a6, []2, A-Z4, 2A-2L4, 2M-2N, []4Texto a dos col.2 h. de grab. calc., la primera árbol genealógico de Felipe III y la segunda retrato del mismoLas h. de lám. son de moneda

Aspectos teórico-metodológicos para el análisis de la incidencia en políticas públicas y la construcción de ciudadanía en la Ciudad de México y la Ciudad de Pereira, Colombia

En los últimos años el tema de la incidencia de las Organizaciones de la Sociedad Civil (OSC) en los asuntos públicos y políticas públicas en los diferentes países de América Latina se ha impulsado desde diferentes perspectivas teóricas y metodológicas. Si bien la visibilidad actual de las organizaciones no es un fenómeno reciente, la consolidación de las democracias, los procesos de descentralización, las reformas económicas estatales y los procesos de participación social desde el Estado han contribuido a legitimar el papel de actores no institucionales en el campo político y público. En México y Colombia, específicamente en la Ciudad de México y la Ciudad de Pereira, la participación de organizaciones de la sociedad civil en asuntos públicos constituye un objeto de estudio reciente para comprender el funcionamiento del régimen político local en un contexto caracterizado por las contradicciones de la alternancia política, el control y el clientelismo político del gobierno hacia las organizaciones, así como el ascenso de nuevos actores sociales en su relación con la política estatal.Facultad de Humanidades y Ciencias de la Educació

Using Biotic Interaction Networks for Prediction in Biodiversity and Emerging Diseases

Abstract: Networks offer a powerful tool for understanding and visualizing inter-species ecological and evolutionary interactions. Previously considered examples, such as trophic networks, are just representations of experimentally observed direct interactions. However, species interactions are so rich and complex it is not feasible to directly observe more than a small fraction. In this paper, using data mining techniques, we show how potential interactions can be inferred from geographic data, rather than by direct observation. An important application area for this methodology is that of emerging diseases, where, often, little is known about inter-species interactions, such as between vectors and reservoirs. Here, we show how using geographic data, biotic interaction networks that model statistical dependencies between species distributions can be used to infer and understand inter-species interactions. Furthermore, we show how such networks can be used to build prediction models. For example, for predicting the most important reservoirs of a disease, or the degree of disease risk associated with a geographical area. We illustrate the general methodology by considering an important emerging disease -Leishmaniasis. This data mining methodology allows for the use of geographic data to construct inferential biotic interaction networks which can then be used to build prediction models with a wide range of applications in ecology, biodiversity and emerging diseases

Exercicio público de secciones cónicas, cálculo infinitesimal y mecánica que en los Reales Estudios de esta corte tendrán Don Juan Nepomuceno Verdugo ..., Don Manuel Ramirez de Arellano, Don Francisco Travesedo, Don Mariano de la Cuesta asistidos por su mestro Don Francisco Verdejo Gonzalez ... el día 1º de julio a las 10 de la mañana

La fecha y la hora del tít. ms.Sign.: a

Using Biotic Interaction Networks for Prediction in Biodiversity and Emerging Diseases

Networks offer a powerful tool for understanding and visualizing inter-species ecological and evolutionary interactions. Previously considered examples, such as trophic networks, are just representations of experimentally observed direct interactions. However, species interactions are so rich and complex it is not feasible to directly observe more than a small fraction. In this paper, using data mining techniques, we show how potential interactions can be inferred from geographic data, rather than by direct observation. An important application area for this methodology is that of emerging diseases, where, often, little is known about inter-species interactions, such as between vectors and reservoirs. Here, we show how using geographic data, biotic interaction networks that model statistical dependencies between species distributions can be used to infer and understand inter-species interactions. Furthermore, we show how such networks can be used to build prediction models. For example, for predicting the most important reservoirs of a disease, or the degree of disease risk associated with a geographical area. We illustrate the general methodology by considering an important emerging disease - Leishmaniasis. This data mining methodology allows for the use of geographic data to construct inferential biotic interaction networks which can then be used to build prediction models with a wide range of applications in ecology, biodiversity and emerging diseases

La inmigración en la UE. Situación y perspectivas para Euskadi

Jornada: La inmigración en la UE. Situación y perspectivas para Euskadi 4 y 5 de noviembre de 200

Spatiotemporal Characteristics of the Largest HIV-1 CRF02_AG Outbreak in Spain: Evidence for Onward Transmissions

Background and Aim: The circulating recombinant form 02_AG (CRF02_AG) is the predominant clade among the human immunodeficiency virus type-1 (HIV-1) non-Bs with a prevalence of 5.97% (95% Confidence Interval-CI: 5.41–6.57%) across Spain. Our aim was to estimate the levels of regional clustering for CRF02_AG and the spatiotemporal characteristics of the largest CRF02_AG subepidemic in Spain.Methods: We studied 396 CRF02_AG sequences obtained from HIV-1 diagnosed patients during 2000–2014 from 10 autonomous communities of Spain. Phylogenetic analysis was performed on the 391 CRF02_AG sequences along with all globally sampled CRF02_AG sequences (N = 3,302) as references. Phylodynamic and phylogeographic analysis was performed to the largest CRF02_AG monophyletic cluster by a Bayesian method in BEAST v1.8.0 and by reconstructing ancestral states using the criterion of parsimony in Mesquite v3.4, respectively.Results: The HIV-1 CRF02_AG prevalence differed across Spanish autonomous communities we sampled from (p < 0.001). Phylogenetic analysis revealed that 52.7% of the CRF02_AG sequences formed 56 monophyletic clusters, with a range of 2–79 sequences. The CRF02_AG regional dispersal differed across Spain (p = 0.003), as suggested by monophyletic clustering. For the largest monophyletic cluster (subepidemic) (N = 79), 49.4% of the clustered sequences originated from Madrid, while most sequences (51.9%) had been obtained from men having sex with men (MSM). Molecular clock analysis suggested that the origin (tMRCA) of the CRF02_AG subepidemic was in 2002 (median estimate; 95% Highest Posterior Density-HPD interval: 1999–2004). Additionally, we found significant clustering within the CRF02_AG subepidemic according to the ethnic origin.Conclusion: CRF02_AG has been introduced as a result of multiple introductions in Spain, following regional dispersal in several cases. We showed that CRF02_AG transmissions were mostly due to regional dispersal in Spain. The hot-spot for the largest CRF02_AG regional subepidemic in Spain was in Madrid associated with MSM transmission risk group. The existence of subepidemics suggest that several spillovers occurred from Madrid to other areas. CRF02_AG sequences from Hispanics were clustered in a separate subclade suggesting no linkage between the local and Hispanic subepidemics

Instrucciones para los seminarios conciliares y eclesiasticos : obra util para todo eclesiastico particularmente para los directores y maestros de los seminarios... ; parte primera...

Marca tip. xil. en portSign.: []\p4\s, a\p8\s, A-G\p8\s, H\p2\sAntepError de pag., duplicadas IX-XI