The contributions of junctions and nanowires/nanotubes in conductive networks

Electrical transport in networked materials occurs through percolative clusters composed of a random distribution of two kinds of interconnected elements: elementary nanostructures and nanostructure-nanostructure junctions. Rationalizing the contribution of these microscopic elements to the macroscopic resistance of the system is a fundamental issue to develop this class of materials and related devices. Focusing on networks composed of high-aspect-ratio nanostructures, such as nanowires (NWs) or nanotubes (NTs), these concepts are still raising controversy in modeling and interpretation of experimental data. Despite these incongruences and the large variations induced by disorder in the electrical properties of such networked systems, this work shows that the ratio between the junction and the nanostructure resistance is nearly the same at the microscopic and macroscopic levels, regardless of the network features. In other words, this means that we may assess the relative contribution of nanostructures and junctions to the macroscopic network resistance directly from the knowledge of its microscopic building blocks. Based on experimental data available in the literature, this result is proven to hold for different materials and network densities, ranging from inorganic NWs to organic carbon NTs and from the percolation critical density nc up to, at least, five times nc, respectively

A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching

The identification of nested motifs in genomic sequences is a complex computational problem. The detection of these patterns is important to allow discovery of transposable element (TE) insertions, incomplete reverse transcripts, deletions, and/or mutations. Here, we designed a de novo strategy for detecting patterns that represent nested motifs based on exhaustive searches for pairs of motifs and combinatorial pattern analysis. These patterns can be grouped into three categories: motifs within other motifs, motifs flanked by other motifs, and motifs of large size. Our methodology, applied to genomic sequences from the plant species Aegilops tauschii and Oryza sativa, revealed that it is possible to find putative nested TEs by detecting these three types of patterns. The results were validated though BLAST alignments, which revealed the efficacy and usefulness of the new method, which we call Mamushka.Fil: Romero, José Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Carballido, Jessica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Cs. E Ingeniería de la Computacion; ArgentinaFil: Garbus, Ingrid. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Echenique, Carmen Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Cs. E Ingeniería de la Computacion; Argentin

Initial Sensor Network Design with a Multi-Objective Genetic Algorithm

A Multi-Objective Genetic Algorithm (MOGA) application, which is based on the aggregating approach, is proposed in this article. Its aim is to find a consistent instrument configuration for industrial process plants that will constitute a convenient initial set of input data for structural Observability Analysis Algorithms (OAs). The better this configuration is, the faster the OAs will converge to a satisfactory solution. Algorithmic effectiveness was evaluated through the analysis of small academic case studies. The results obtained through our algorithm show excellent performance. Therefore, it can be stated that the prototype presented in this work is good enough to serve as a sound basis for the development of the definitive MOGA module, whose implementation will support large-size industrial plant models.Sociedad Argentina de Informática e Investigación Operativ

Reproductivity Study of Metal Oxide Gas Sensors Using Two Different Temperature Setups

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ZnO Quasi-1D Nanostructures: Synthesis, Modeling, and Properties for Applications in Conductometric Chemical Sensors

One-dimensional metal oxide nanostructures such as nanowires, nanorods, nanotubes, and nanobelts gained great attention for applications in sensing devices. ZnO is one of the most studied oxides for sensing applications due to its unique physical and chemical properties. In this paper, we provide a review of the recent research activities focused on the synthesis and sensing properties of pure, doped, and functionalized ZnO quasi-one dimensional nanostructures. We describe the development prospects in the preparation methods and modifications of the surface structure of ZnO, and discuss its sensing mechanism. Next, we analyze the sensing properties of ZnO quasi-one dimensional nanostructures, and summarize perspectives concerning future research on their synthesis and applications in conductometric sensing devices

Biclustering in data mining using a memetic multi-objective evolutionary algorithm

In this paper, a new memetic strategy that integrates a multi-objective evolutionary algorithm (the SPEA2) with a local search technique for data mining is presented. The algorithm explores a Term Frequency-Inverse Document Frequency (TF-IDF) data matrix in order to find biclusters that fulfill several objectives. The case of study was a dataset corresponding to the Reuters-21578 corpus. Our algorithm performed satisfactorily, finding biclusters that have large size and coherent values, yielding to undeniably promising outcomes. Nonetheless, more experiments with data from other corpus are necessary, thus leading to more concluding resultsWorkshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

An Evolutionary Algorithm for Automatic Recommendation of Clustering Methods and its Parameters

One of the main problems being faced at the time of performing data clustering consists in the deteremination of the best clustering method together with defining the ideal amount (k) of groups in which these data should be separated. In this paper, a preliminary approximation of a clustering recommender method is presented which, starting from a set of standardized data, suggests the best clustering strategy and also proposes an advisable k value. For this aim, the algorithm considers four indices for evaluating the final structure of clusters: Dunn, Silhouette, Widest Gap and Entropy. The prototype is implemented as a Genetic Algorithm in which individuals are possible configurations of the methods and their parameters. In this first prototype, the algorithm suggests between four partitioning methods namely K-means, PAM, CLARA and, Fanny. Also, the best set of parameters to execute the suggested method is obtained. The prototype was developed in an R environment, and its findings could be corroborated as consistent when compared with a combination of results provided by other methods with similar objectives. The idea of this prototype is to serve as the initial basis for a more complex framework that also incorporates the reduction of matrices with vast numbers of rows.Fil: Carballido, Jessica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Latini, Macarena Anahí. Universidad Nacional del Sur; ArgentinaFil: Ponzoni, Ignacio. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cecchini, Rocío Luján. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentin

Detection of microbial contamination in potable water by Nanowire technology

It is well known that the lack of control and sanitation of water in developing countries has cause very significant epidemiological events. In the last decades the situation of water supplies and sanitation has improve all over the world. Despite of it, in the European Union there are a considerable number of confirmed cases of water-borne infections even though the restrictive law. Electronic Noses (ENs) has shown to be a very effective and fast tool for monitoring microbiological spoilage and quality control. The aim of this study was test the ability of a novel EN for the detection of bacterial presence in potable water in cooperation with analytical (pH) and optical (photometer) techniques. The achieved results notably advocate the use of EN in industry laboratories as a very important tool in water quality control

pdAGMO para configuración inicial de sensores en procesos industriales

En este trabajo se presenta una implementación paralelo-distribuida de un algoritmo genético multiobjetivo (pdAGMO), desarrollado para efectuar la selección de la configuración inicial de sensores en el diseño de instrumentación de plantas de procesos. El pdAGMO fue diseñado empleando el modelo evolutivo de islas y el paradigma masterworker, mientras que para su implementación se empleó la librería de pasaje de mensajes PVM (Parallel Virtual Machine). El desempeño del pdAGMO fue evaluado a través de su aplicación a un caso de estudio industrial correspondiente a una planta de producción de amoníaco. Los resultados alcanzados son muy satisfactorios en términos de speed-up, eficiencia y calidad del diseño de instrumentación.Fil: Asteasuain, Fernando. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; ArgentinaFil: Carballido, Jessica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Vazquez, Gustavo Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Brignole, Nélida Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentin