440 research outputs found
Microbial mats and the search for minimal ecosystems
This article reviews some ecological concepts common to all kinds of ecosystems, describes the characteristics of microbial mats, and focuses on the description of the Ebro Delta microbial mats, to assess whether they fit the concept of a minimal ecosystem. First, microorganisms as components of ecosystems are considered, and some features of microbial life, including ubiquity, size and metabolism, genetic versatility, and strategies to overcome unfavorable conditions, are discussed. Models for ecosystems, regardless of their size, have the same basic components; tropical forests, multilayered planktonic microbial communities, and benthic microbial mats are analogous ecosystems at different scales. The structure –in terms of populations and communities– and ecophysiology of microbial mats are also discussed. The linear distribution of microbial populations along steep gradients of light and hydrogen sulfide allows for the simultaneous presence of different microbial populations. Defining the minimal ecosystem requirements necessary for the survival and proliferation of organisms is crucial in the search for extraterrestrial life and for establishing ecosystems beyond the Earth
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Enriching the Human Phenotype Ontology with inferred axioms from textual descriptions
The Human Phenotype Ontology (HP) is a reference vocabulary of human phenotypic abnormalities. HP, apart from the textual information (general definitions, descriptions, synonyms, etc.) of each ontology concept, also provides computer-readable logical definitions (axioms) of terms that will allow human phenotypic abnormalities to be related to entities from anatomy, pathology, biochemistry and other areas. In this paper we present a prototype to generate new axiomatic knowledge from the textual descriptions of each HP term. The prototype (i) detects terms in the textual descriptions and not found in the given logical expressions, (ii) generates pair combinations of those terms, (iii) builds triples after detecting the most probable relation between the pair of terms using a statistical model and, finally, (iv) suggests the most probable triples to the user so she can decide which ones can be added to the original axioms
Exploring and linking biomedical resources through multidimensional semantic spaces
Background
The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes).
Results
This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource.
Conclusions
Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for integration, exploration, and analysis tasks. Results over a real scenario demonstrate the viability and usefulness of the approach, as well as the quality of the generated multidimensional semantic spaces
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Building conceptual spaces for exploring and linking biomedical resources
The establishment of links between data (e.g., patient records) and Web resources (e.g., literature) and the proper visualization of such discovered knowledge is still a challenge in most Life Science domains (e.g., biomedicine). In this paper we present our contribution to the community in the form of an infrastructure to annotate information resources, to discover relationships among them, and to represent and visualize the new discovered knowledge. Furthermore, we have also implemented a Web-based prototype tool which integrates the proposed infrastructure
Aplicación de nuevas técnicas docentes en la asignatura Sistemas Cliente/Servidor
En este trabajo mostramos nuestras experiencias en
la aplicación de metodologías de aprendizaje cooperativo
y basado en proyectos en la asignatura Sistemas
Cliente/Servidor en los cursos académicos
2008/2009 y 2009/2010.SUMMARY: In this work we present our teaching experience in
the aplication of cooperative and project-based learning
methodologies within the subject Client/Server
Systems in the academic years 2008/2009 and
2009/2010.Peer Reviewe
Automatic symbolic modelling of co-evolutionarily learned robot skills
Proceeding of: 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13–15, 2001Evolutionary based learning systems have proven to be very powerful techniques for solving a wide range of tasks, from prediction to optimization. However, in some cases the learned concepts are unreadable for humans. This prevents a deep semantic analysis of what has been really learned by those systems. We present in this paper an alternative to obtain symbolic models from subsymbolic learning. In the first stage, a subsymbolic learning system is applied to a given task. Then, a symbolic classifier is used for automatically generating the symbolic counterpart of the subsymbolic model. We have tested this approach to obtain a symbolic model of a neural network. The neural network defines a simple controller af an autonomous robot. a competitive coevolutive method has been applied in order to learn the right weights of the neural network. The results show that the obtained symbolic model is very accurate in the task of modelling the subsymbolic system, adding to this its readability characteristic
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First steps in the logic-based assessment of post-composed phenotypic descriptions
In this paper we present a preliminary logic-based evaluation of the integration of post-composed phenotypic descriptions with domain ontologies. The evaluation has been performed using a description logic reasoner together with scalable techniques: ontology modularization and approximations of the logical difference between ontologies
Vicia faba Crop Residues for Sustainable Electricity Generation Using a Sludge-based Microbial Fuel Cell
Microbial fuel cells (MFC) simultaneously degrade organic substrates and generate electricity in a sustainable and eco-friendly way. Here, we built a 4-unit MFC and studied the efficiency of MFC at different conditions, including pH, substrate concentration of Vicia faba agricultural wastes with exoelectrogenic bacteria P. aeruginosa. The exoelectrogenic bacteria were obtained from industrial effluents and used to inoculate the MFCs. The optimized conditions in terms of yielding maximum potential of 802 mV, yielding maximum power density of 283 mW m–2 were reported at a substrate concentration of 6 g L–1 of V. faba waste and pH of 5.5, corresponding to a current density 1255.93 mA m–2. Using exoelectrogenic bacteria from industrial effluents and agricultural wastes resulted in efficient MFC. Thus, the developed MFCs using V. faba agricultural wastes can be used in rural areas that have limited access to electricity, by reusing agricultural wastes and concomitant electricity generation.
This work is licensed under a Creative Commons Attribution 4.0 International License
Un modelo para el tratamiento de sistemas dinámicos basado en la satisfacción de restricciones
En numerosas aplicaciones industriales complejas de plaificación y scheduling, resulta frecuente encontrar casos donde un problema ya resuelto debe ser reconsiderado a causa de una ligera modificación en la instancia de dicho problema. Estas modificaciones se originan generalmente a partir de sucesos externos que implican un cambio de creencias y en consecuencia el conjunto de soluciones obtenido para el problema resuelto ha de modificarse.
Estos casos son referidos generalmente como problemas dinámicos, frente a los problemas estáticos. En los primeros, el conjunto de soluciones puede ser ligeramente modificado, mientras que en los segundos, el conjunto de soluciones es fijo e inalterable.
El tipo de problemas que nos preocupa se refieren a problemas modelados a través de restricciones, concretamente, restricciones lineales sobre variables de dominio finito. Estos tipos de problemas son estáticos, cuando las soluciones obtenidas no son reconsideradas ante el cambio de la instancia del -problema. Los casos dinámicos antes expuestos son resueltos iniciando de nuevo el proceso de resolución con la instancia modificada como si fuese un problema diferente.
Un resolvedor de problemas que reconsidere las soluciones obtenidas en un problema anterior ante un cambio ligero de su instancia lo denominaremos dinámico, frente a la denominación de estático antes utilizada. Así pues, un Sistema Dinámico de Restricciones (SDR) será aquel que considere las soluciones obtenidas para resolver la instancia modificada. Al contrario de los sistemas estáticos, un SDR plantea las modificaciones de las instancias como un único problema.
En este trabajo definiremos un modelo de SDR e identificaremos el tipo de transiciones permitidas en el mismo, y discutiremos como abordar la resolución dinámica del SDR desde diferentes aproximaciones. Además, se propondrán varios métodos para el manejo dinámico de un sistema de restricciones. Finalmente, discutiremos brevemente que opción de las analizadas es la más adecuada para los problemas que estamos abordando.Eje: Aspectos teóricos de la inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI
Un modelo para el tratamiento de sistemas dinámicos basado en la satisfacción de restricciones
En numerosas aplicaciones industriales complejas de plaificación y scheduling, resulta frecuente encontrar casos donde un problema ya resuelto debe ser reconsiderado a causa de una ligera modificación en la instancia de dicho problema. Estas modificaciones se originan generalmente a partir de sucesos externos que implican un cambio de creencias y en consecuencia el conjunto de soluciones obtenido para el problema resuelto ha de modificarse.
Estos casos son referidos generalmente como problemas dinámicos, frente a los problemas estáticos. En los primeros, el conjunto de soluciones puede ser ligeramente modificado, mientras que en los segundos, el conjunto de soluciones es fijo e inalterable.
El tipo de problemas que nos preocupa se refieren a problemas modelados a través de restricciones, concretamente, restricciones lineales sobre variables de dominio finito. Estos tipos de problemas son estáticos, cuando las soluciones obtenidas no son reconsideradas ante el cambio de la instancia del -problema. Los casos dinámicos antes expuestos son resueltos iniciando de nuevo el proceso de resolución con la instancia modificada como si fuese un problema diferente.
Un resolvedor de problemas que reconsidere las soluciones obtenidas en un problema anterior ante un cambio ligero de su instancia lo denominaremos dinámico, frente a la denominación de estático antes utilizada. Así pues, un Sistema Dinámico de Restricciones (SDR) será aquel que considere las soluciones obtenidas para resolver la instancia modificada. Al contrario de los sistemas estáticos, un SDR plantea las modificaciones de las instancias como un único problema.
En este trabajo definiremos un modelo de SDR e identificaremos el tipo de transiciones permitidas en el mismo, y discutiremos como abordar la resolución dinámica del SDR desde diferentes aproximaciones. Además, se propondrán varios métodos para el manejo dinámico de un sistema de restricciones. Finalmente, discutiremos brevemente que opción de las analizadas es la más adecuada para los problemas que estamos abordando.Eje: Aspectos teóricos de la inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI
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