Aglomeraciones pesqueras en América Latina: ventajas asociadas al enfoque de cluster

Incluye Bibliografía

Evolución y complejidad en el desarrollo de encadenamientos productivos en México: los desafíos de la construcción del cluster aeroespacial en Querétaro

Incluye bibliografía

La formación de un cluster en torno al turismo de naturaleza sustentable en Bonito, Brasil

Incluye Bibliografía

Formación y desarrollo de un cluster globalizado: el caso de la industria del salmón en Chile

Incluye Bibliografía

¿A Chilean wine cluster? governance and upgrading in the phase of internationalization

Includes bibliography

Una estrategia de desarrollo basada en recursos naturales: análisis 'cluster' del complejo de cobre de la Southern Perú

Incluye Bibliografía

El cluster del ecoturismo en San Pedro

Incluye Bibliografía

El cluster del ecoturismo en Bonito, MS

Incluye Bibliografía

Hacia un cluster ecoturístico en Aysén

Incluye Bibliografía

Desarrollo local y alternativas de desarrollo productivo: el impulso de un cluster eco-turístico en la región de Aysén

Incluye Bibliografía

Cluster analysis and artificial neural network on the superovulatory response prediction in mice

Complex biological systems require sophisticated approach for analysis, once there are variables with distinct measure levels to be analyzed at the same time in them. The mouse assisted reproduction, e.g. superovulation and viable embryos production, demand a multidisciplinary control of the environment, endocrinologic and physiologic status of the animals, of the stressing factors and the conditions which are favorable to their copulation and subsequently oocyte fertilization. In the past, analyses with a simplified approach of these variables were not well succeeded to predict the situations that viable embryos were obtained in mice. Thereby, we suggest a more complex approach with association of the Cluster Analysis and the Artificial Neural Network to predict embryo production in superovulated mice. A robust prediction could avoid the useless death of animals and would allow an ethic management of them in experiments requiring mouse embryo.

QK-Means: A clustering technique based on community detection and K-Means for deployment of cluster head nodes

Wireless Sensor Networks (WSN) are a special kind of ad-hoc networks that is usually deployed in a monitoring field in order to detect some physical phenomenon. Due to the low dependability of individual nodes, small radio coverage and large areas to be monitored, the organization of nodes in small clusters is generally used. Moreover, a large number of WSN nodes is usually deployed in the monitoring area to increase WSN dependability. Therefore, the best cluster head positioning is a desirable characteristic in a WSN. In this paper, we propose a hybrid clustering algorithm based on community detection in complex networks and traditional K-means clustering technique: the QK-Means algorithm. Simulation results show that QK-Means detect communities and sub-communities thus lost message rate is decreased and WSN coverage is increased. © 2012 IEEE.

Improving hierarchical document cluster labels through candidate term selection

One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for each of the obtained clusters. In many cases the labels must be built using all the terms in the documents of the collection. This paper presents the SeCLAR method, which explores the use of association rules in the selection of good candidates for labels of hierarchical document clusters. The purpose of this method is to select a subset of terms by exploring the relationship among the terms of each document. Thus, these candidates can be processed by a classical method to generate the labels. An experimental study demonstrates the potential of the proposed approach to improve the precision and recall of labels obtained by classical methods only considering the terms which are potentially more discriminative. © 2012 - IOS Press and the authors. All rights reserved.

A new palladium chelate compound for determination of sulfide

A new palladium chelate compound is described for the determination of sulfide in aqueous samples. The reagent, bis(2-aminobenzoate)palladium(II) (PdA 2), was prepared by reaction of tetrachloropalladate (PdCl 4 -) with 2-aminobenzoic acid. The compound was characterized by infrared spectroscopy and CHN elemental analysis. The measurement was based on the selective reaction of PdA 2 with sulfide in an aqueous medium, which quantitatively produced fluorescent 2-aminobenzoate (λ ex=245nm, λ em=410nm). The analytical response was linear in the range 0.10-20.0μmol (S 2-) L -1 (r>0.99), with a limit of detection of 0.075μmolL -1 and repeatability (RSD) of 3.4%. There was no interference from CO 3 2-, NO 3 -, Cl -, SO 4 2-, Br -, NO 2 -, K +, NH 4 +, Na +, citrate or S 2O 8 2-. The fluorescence intensity decreased in the presence of H 3CCOO -, PO 4 3- and SCN -, while OH - caused a positive interference. The new fluorescent compound was successfully applied for the determination of sulfide in synthetic wastewater and natural water sample. The advantages of the proposed palladium chelate are absence of toxic by-products, simple synthesis procedure of reagent and yield reaction of about 85%, easy handling and fast acquirement of analytical signal. © 2012 Elsevier B.V.

Dba-free palladium intermediates of the Heck-Matsuda reaction

The dba-free Heck-Matsuda reaction was investigated via direct ESI-MS(/MS) monitoring. Palladium species involved in the reduction of Pd(ii) during a Wacker type reaction and several dba-free arylpalladium transient complexes were detected and characterized. Based on these findings, a more comprehensible catalytic cycle for this pivotal reaction is suggested. © 2013 The Royal Society of Chemistry.