How do autoimmune diseases cluster in families? A systematic review and meta-analysis

Background: A primary characteristic of complex genetic diseases is that affected individuals tend to cluster in families (that is, familial aggregation). Aggregation of the same autoimmune condition, also referred to as familial autoimmune disease, has been extensively evaluated. However, aggregation of diverse autoimmune diseases, also known as familial autoimmunity, has been overlooked. Therefore, a systematic review and meta-analysis were performed aimed at gathering evidence about this topic. Methods: Familial autoimmunity was investigated in five major autoimmune diseases, namely, rheumatoid arthritis, systemic lupus erythematosus, autoimmune thyroid disease, multiple sclerosis and type 1 diabetes mellitus. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed. Articles were searched in Pubmed and Embase databases. Results: Out of a total of 61 articles, 44 were selected for final analysis. Familial autoimmunity was found in all the autoimmune diseases investigated. Aggregation of autoimmune thyroid disease, followed by systemic lupus erythematosus and rheumatoid arthritis, was the most encountered. Conclusions: Familial autoimmunity is a frequently seen condition. Further study of familial autoimmunity will help to decipher the common mechanisms of autoimmunity.

Los cluster tecnológicos en México y Argentina: una estrategia para el desarrollo local

El objetivo de este trabajo es, por una parte, darle continuidad a la línea de trabajo anterior sobre la industria de software y servicios informáticos, pero en esta oportunidad centrada en el estudio de la dinámica de los cluster tecnológicos en experiencias locales. Para ello se indagará esta dinámica en dos ciudades:Mérida (Yucatán-México) y Rosario (Santa Fe-Argentina). El objetivo de enfocar estos dos casos de estudio se fundamenta en el interés por estas dos ciudades, ya que presentan un perfil productivo innovador, con tasas de crecimiento importante y que además esta estrategia se suma a otras actividades de alto valor agregado. En este sentido la producción de software y de nuevas tecnologías, están creando un clima propicio de desarrollo local. En este trabajo se analiza el contexto socio económico de cada ciudad, los antecedentes de la creación del cluster tecnológico, la cooperación inter empresarial e inter institucional, las políticas públicas territorializadas en el cluster, el perfil y las actividades de las empresas que conforman el mismo, así como las características de sus recursos humanos. The aim of this paper is to give continuity to my previous work about the software industry and information technology services, but this time focused on the study of the dynamics of the cluster technology in local experiences. So the paper inquires this dynamic in two cities: Merida (Yucatan, Mexico) and Rosario (Santa Fe, Argentina).The aim of approaching these two case studies is based on the interest in these two cities, since they have a innovative productive profile, with significant growth rates and that this strategy is  added to other activities of high added value. In this sense the production of software and new technologies, are creating a climate conducive to local development. This paper examines the socio-economic context of each city, the background to the creation of the cluster technology, international cooperation and international institutional business, public policy in the territorial cluster, the profile and activities of the companies in there, and the characteristics of their human resources.  

Fuzzy cluster analysis on Spanish public universities. 'Análisis de agrupaciones difusas en las universidades públicas españolas'.

Resumen basado en el de la publicación

Cluster A maladaptive personality patterns in a non-clinical adolescent population

Resumen tomado de la publicación

Cómo aplicar un cluster jerárquico en SPSS

Resumen basado en el de la publicación

Estrategias empresariales para afrontar la competencia internacional: el caso del cluster de confecciones de la industria textil de Atuntaqui

El comercio mundial tiene múltiples actores que está sumamente bien posicionados y otros que buscan nuevas estrategias para mejorar su posicionamiento. Asimismo, las diferencias entre los mercados internacionales, nacionales y/o locales son notables, mientras los unos se expanden a pasos agigantados, los otros lo hacen paso a paso. Por lo tanto, el presente trabajo tiene como objetivo fundamental determinar las estrategias que las empresas del sector de las confecciones del cluster textil de Atuntaqui pueden implementar para hacer frente a la competencia internacional. Con esta referencia, el trabajo se ha dividido en tres capítulos. El primer capítulo, está conformado por un análisis de los principales elementos conceptuales (cadena global de valor, managment dentro de la CGV y cluster industriales); seguido, se presenta un breve recuento de la industria, el comercio mundial y los principales importadores y exportadores. Luego, se analiza las tendencias globales utilizadas por los países de América Latina y el Caribe, entre los que están: plataforma de exportación, clusters y logística internacional. En el segundo capítulo, se analizan las principales estadísticas sobre el comportamiento histórico de las importaciones y exportaciones, la caracterización de las empresas, el ámbito tecnológico, los costos y gastos en los que se ha incurrido en algunos cantones y sobre el mercado laboral. Para finalizar, el tercer capítulo, cuenta con una perspectiva local de la industria en Atuntaqui, con temas, como: el “cluster” de la industria, la caracterización de las empresas, el clima de negocios, el diagnostico FODA y las principales estrategias.

Running Climate Models On The NERC Cluster Grid Using G-Rex

Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them usually involves complicated workflows implemented as shell scripts. For example, NEMO (Smith et al. 2008) is a state-of-the-art ocean model that is used currently for operational ocean forecasting in France, and will soon be used in the UK for both ocean forecasting and climate modelling. On a typical modern cluster, a particular one year global ocean simulation at 1-degree resolution takes about three hours when running on 40 processors, and produces roughly 20 GB of output as 50000 separate files. 50-year simulations are common, during which the model is resubmitted as a new job after each year. Running NEMO relies on a set of complicated shell scripts and command utilities for data pre-processing and post-processing prior to job resubmission. Grid Remote Execution (G-Rex) is a pure Java grid middleware system that allows scientific applications to be deployed as Web services on remote computer systems, and then launched and controlled as if they are running on the user's own computer. Although G-Rex is general purpose middleware it has two key features that make it particularly suitable for remote execution of climate models: (1) Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model; (2) The client component is a command-line program that can easily be incorporated into existing model work-flow scripts. G-Rex has a REST (Fielding, 2000) architectural style, which allows client programs to be very simple and lightweight and allows users to interact with model runs using only a basic HTTP client (such as a Web browser or the curl utility) if they wish. This design also allows for new client interfaces to be developed in other programming languages with relatively little effort. The G-Rex server is a standard Web application that runs inside a servlet container such as Apache Tomcat and is therefore easy to install and maintain by system administrators. G-Rex is employed as the middleware for the NERC1 Cluster Grid, a small grid of HPC2 clusters belonging to collaborating NERC research institutes. Currently the NEMO (Smith et al. 2008) and POLCOMS (Holt et al, 2008) ocean models are installed, and there are plans to install the Hadley Centre’s HadCM3 model for use in the decadal climate prediction project GCEP (Haines et al., 2008). The science projects involving NEMO on the Grid have a particular focus on data assimilation (Smith et al. 2008), a technique that involves constraining model simulations with observations. The POLCOMS model will play an important part in the GCOMS project (Holt et al, 2008), which aims to simulate the world’s coastal oceans. A typical use of G-Rex by a scientist to run a climate model on the NERC Cluster Grid proceeds as follows :(1) The scientist prepares input files on his or her local machine. (2) Using information provided by the Grid’s Ganglia3 monitoring system, the scientist selects an appropriate compute resource. (3) The scientist runs the relevant workflow script on his or her local machine. This is unmodified except that calls to run the model (e.g. with “mpirun”) are simply replaced with calls to "GRexRun" (4) The G-Rex middleware automatically handles the uploading of input files to the remote resource, and the downloading of output files back to the user, including their deletion from the remote system, during the run. (5) The scientist monitors the output files, using familiar analysis and visualization tools on his or her own local machine. G-Rex is well suited to climate modelling because it addresses many of the middleware usability issues that have led to limited uptake of grid computing by climate scientists. It is a lightweight, low-impact and easy-to-install solution that is currently designed for use in relatively small grids such as the NERC Cluster Grid. A current topic of research is the use of G-Rex as an easy-to-use front-end to larger-scale Grid resources such as the UK National Grid service.

The omega equation and potential vorticity

Two fundamental perspectives on the dynamics of midlatitude weather systems are provided by potential vorticity (PV) and the omega equation. The aim of this paper is to investigate the link between the two perspectives, which has so far received very little attention in the meteorological literature. It also aims to give a quantitative basis for discussion of quasi-geostrophic vertical motion in terms of components associated with system movement, maintaining a constant thermal structure, and with the development of that structure. The former links with the isentropic relative-flow analysis technique. Viewed in a moving frame of reference, the measured development of a system depends on the velocity of that frame of reference. The requirement that the development should be a minimum provides a quantitative method for determining the optimum system velocity. The component of vertical velocity associated with development is shown to satisfy an omega equation with forcing determined from the relative advection of interior PV and boundary temperature. The analysis carries through in the presence of diabatic heating provided the omega equation forcing is based on the interior PV and boundary thermal tendencies, including the heating effect. The analysis is shown to be possible also at the level of the semi-geostrophic approximation. The analysis technique is applied to a number of idealized problems that can be considered to be building blocks for midlatitude synoptic-scale dynamics. They focus on the influences of interior PV, boundary temperature, an interior boundary, baroclinic instability associated with two boundaries, and also diabatic heating. In each case, insights yielded by the new perspective are sought into the dynamical behaviour, especially that related to vertical motion. Copyright © 2003 Royal Meteorological Society