Shade increases cereal production in mediterranean conditions facing the climate change

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Docencia de arquitectura orientada a servicios

Este trabajo presenta los contenidos del curso “Web 2.0: Arquitectura Orientada a Servicios en Java” de la Escuela de Posgrado de la Universidad de Granada. El objetivo del curso es familiarizar al alumno con la programación de ServiciosWeb. Dada la gran variedad de técnicas disponibles para utilizar Arquitectura Orientada a Servicios, se presentan los siguientes temas: utilización de protocolos bien definidos para comunicación y contrato (SOAP y WSDL), creación de Web Services con JAX-WS y orquestación de ServiciosWeb con BPEL. Al final del curso, el alumno será capaz de crear, utilizar y mantener Servicios Web para el desarrollo de aplicaciones interempresariales, utilizando servicios creados o ya disponibles en la web, así como la orquestación lógica de los mismos.SUMMARY: This work presents the contents of the course “Web 2.0: Service Oriented Architecture on Java” from the Graduate School of the University of Granada. The course objective is to familarize students with Web Services programming. Due to the wide variety of available technologies, several subjects are presented: the usage of well-defined protocols to contract and communication (SOAP and WSDL), web services creation using JAX-WS, and service orchestration with BPEL. At the end of the course, students will be capable to create, use and manage Web Services for business applications, using new or available services in the web, and also their logical orchestration.Peer Reviewe

ParaDisEO-Based Design of Parallel and Distributed Evolutionary Algorithms

The original publication is available at www.springerlink.comInternational audienceParaDisEO is a framework dedicated to the design of parallel and distributed metaheuristics including local search methods and evolutionary algorithms. This paper focuses on the latter aspect. We present the three parallel and distributed models implemented in ParaDisEO and show how these can be exploited in a user-friendly, flexible and transparent way. These models can be deployed on distributed memory machines as well as on shared memory multi-processors, taking advantage of the shared memory in the latter case. In addition, we illustrate the instantiation of the models through two applications demonstrating the efficiency and robustness of the framework

Docencia de arquitectura orientada a servicios

Este trabajo presenta los contenidos del curso “Web 2.0: Arquitectura Orientada a Servicios en Java” de la Escuela de Posgrado de la Universidad de Granada. El objetivo del curso es familiarizar al alumno con la programación de ServiciosWeb. Dada la gran variedad de técnicas disponibles para utilizar Arquitectura Orientada a Servicios, se presentan los siguientes temas: utilización de protocolos bien definidos para comunicación y contrato (SOAP y WSDL), creación de Web Services con JAX-WS y orquestación de ServiciosWeb con BPEL. Al final del curso, el alumno será capaz de crear, utilizar y mantener Servicios Web para el desarrollo de aplicaciones interempresariales, utilizando servicios creados o ya disponibles en la web, así como la orquestación lógica de los mismos

Recovery of dialysis patients with COVID-19 : health outcomes 3 months after diagnosis in ERACODA

Background. Coronavirus disease 2019 (COVID-19)-related short-term mortality is high in dialysis patients, but longer-term outcomes are largely unknown. We therefore assessed patient recovery in a large cohort of dialysis patients 3 months after their COVID-19 diagnosis. Methods. We analyzed data on dialysis patients diagnosed with COVID-19 from 1 February 2020 to 31 March 2021 from the European Renal Association COVID-19 Database (ERACODA). The outcomes studied were patient survival, residence and functional and mental health status (estimated by their treating physician) 3 months after COVID-19 diagnosis. Complete follow-up data were available for 854 surviving patients. Patient characteristics associated with recovery were analyzed using logistic regression. Results. In 2449 hemodialysis patients (mean ± SD age 67.5 ± 14.4 years, 62% male), survival probabilities at 3 months after COVID-19 diagnosis were 90% for nonhospitalized patients (n = 1087), 73% for patients admitted to the hospital but not to an intensive care unit (ICU) (n = 1165) and 40% for those admitted to an ICU (n = 197). Patient survival hardly decreased between 28 days and 3 months after COVID-19 diagnosis. At 3 months, 87% functioned at their pre-existent functional and 94% at their pre-existent mental level. Only few of the surviving patients were still admitted to the hospital (0.8-6.3%) or a nursing home (∼5%). A higher age and frailty score at presentation and ICU admission were associated with worse functional outcome. Conclusions. Mortality between 28 days and 3 months after COVID-19 diagnosis was low and the majority of patients who survived COVID-19 recovered to their pre-existent functional and mental health level at 3 months after diagnosis

Analyzing and Modeling Real-World Phenomena with Complex Networks: A Survey of Applications

The success of new scientific areas can be assessed by their potential for contributing to new theoretical approaches and in applications to real-world problems. Complex networks have fared extremely well in both of these aspects, with their sound theoretical basis developed over the years and with a variety of applications. In this survey, we analyze the applications of complex networks to real-world problems and data, with emphasis in representation, analysis and modeling, after an introduction to the main concepts and models. A diversity of phenomena are surveyed, which may be classified into no less than 22 areas, providing a clear indication of the impact of the field of complex networks.Comment: 103 pages, 3 figures and 7 tables. A working manuscript, suggestions are welcome

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost