EDITORIAL

Esitorial del V6N

Characterization of phenolic profile alterations in metal-polluted bee pollen via capillary electrophoresis

International audienceBee pollen is a conglomerate of plant pollens, and its nutritional contents include bioactive compounds with antioxidant/antiradical potentials. These potentials are conditioned by botanical origin. In Chile, the native flora is diverse and promising in terms of bioactive compounds, but many plants grow in metal-polluted areas. The associated bioaccumulation could negatively affect the antioxidant/antiradical abilities of bee pollen. To assess the relationship between the bioaccumulation of metals and the antioxidant activity of pollen, complete bee pollen was collected near and far from the Llaima Volcano, albeit in ranges that ensured the same botanical origins. Mellisopalynological analysis determined Escallonia rubra pollen was the most abundant native flora in complete bee pollen. Therefore, E. rubra pollen collected near and far from the Llaima Volcano was evaluated for the following: phenolic compounds via colorimetric assays; antioxidant activity via ferric reducing/antioxidant power assays; antiradical activity via 1,1-diphenyl-2-picrylhydrazyl radical assays; and metal contents via inductively coupled plasma optical emission spectrometry. Llaima samples had higher Cu and Fe but lower Mn contents and lower antioxidant and antiradical capacities than did the control samples. These results were supported by subsequent fortification assays in Llaima E. rubra samples. In fortified samples with significantly higher metal contents, antiradical and antioxidant abilities decreased. Moreover, shifts in migration times were found for naringenin, rutine, and caffeic acid after capillary electrophoresis (CE) analysis in fortified samples. In conclusion, the results indicated an inverse correlation between metal contents and antioxidant/antiradical potentials in bee pollen

Trust Levels Definition on Virtual Learning Platforms Through Semantic Languages

Trust level concept is a topic that has opened a knowledge area about the profile evaluation and the people participation in Social Networks. These have presented a high knowledge profit, but at the same time it is necessary to analyze a group of variables to determine the trust participants' degree. In addition, this is a topic that from some years ago has been presenting a big expectation to settle some alternatives to generate confidence in an activer community on internet. To establish these parameters it is important to define a model to abstract some variables that are involved in this process. For this, it is relevant to take into account the semantic languages as one of the alternatives that allow these kinds of activities. The purpose of this article is to analyze the Trust Levels definition in the contents that are shared on Open Source Virtual learning Platforms through the use of a model of representation of semantic languages. The last ones allow determining the trust in the use of learning objects that are shared in this kind of platforms

Design of a trust system for e-commerce platforms based on quality dimensions for linked open datasets

This article describes a proposal about a trust system for e-commerce platform based on semantic web technologies and trust dimensions rules. We try to expose a system that allow to manage communication processes between e-commerce platforms and users in a trustworthy manner. It allows the data flows and transactions gain more trust across the entire process. All of this can be achieved through the inference of rules exposed in the defined ontology, complemented by a cloud-based system with microservices architecture. With the implementation of the system through an e-commerce platform, could consume data from the microservices in order to get inferences about its clients that want to buy or sell something within its system. This system was created based on rules defined by the ontology, as well as the microservices could be used to register information about multiple e-commerce transactions. The result of this work is the Ontology and semantic web rules defined and implemented through protege.info:eu-repo/semantics/publishedVersio

Evaluación financiera y social de la creación de una empresa procesadora de tajadas de plátano maduro fritas congeladas para exportación

El departamento del Magdalena, por mucho tiempo ha sido conocido como productor de banano y que esta producción es exportada al mercado americano y europeo. Es de anotar, que el banano se comercializa sin que se le agregue ningún valor, mientras que el presente trabajo plantea la evaluación financiera y social de la creación una planta procesadora de tajadas de plátano maduro fritas congeladas para la exportación al mercado americano. Podemos decir que a un producto primario (Plátano), le estamos dando transformación y generando valor agregado y que es viable tanto financiera como socialmente, que es el objeto del estudio de este trabajo. Dentro de los aspectos a tener en cuenta están: Un estudio de mercado, un análisis técnico, legal y organizacional del montaje de la empresa, además del estudio financiero y social. El resultado es la rentabilidad del Proyecto

Using grip strength as a cardiovascular risk indicator based on hybrid algorithms

This article shows the application and design of a hybrid algorithm capable of classifying people into risk groups using data such as prehensile strength, body mass index and percentage of fat. The implementation was done on Python and proposes a tool to help make medical decisions regarding the cardiovascular health of patients. The data were taken in a systematic way, k-means and c-means algorithms were used for the classification of the data, for the prediction of new data two vectorial support machines were used, one for the k-means and the other for the c-means, obtaining as a result a 100% of precision in the vectorial support machine with c-means and a 92% in the one of k-means.This article shows the application and design of a hybrid algorithm capable of classifying people into risk groups using data such as prehensile strength, body mass index and percentage of fat. The implementation was done on Python and proposes a tool to help make medical decisions regarding the cardiovascular health of patients. The data were taken in a systematic way, k-means and c-means algorithms were used for the classification of the data, for the prediction of new data two vectorial support machines were used, one for the k-means and the other for the c-means, obtaining as a result a 100% of precision in the vectorial support machine with c-means and a 92% in the one of k-means

Liderazgo directivo y desempeño docente en la I.E. Nº 101000 La Ramada, Cajamarca

El presente trabajo de investigación tiene como propósito principal determinar la relación del Liderazgo directivo y el desempeño docente en el nivel primario de la Institución Educativa Nº 101000 de La Ramada, distrito de Llama, provincia de Chota, Región Cajamarca, en el primer semestre del año 2018. A partir de los autores analizados: Idalberto Chiavenato, Jorge Torres, Albert Bandura, Lesly Estrada, el MINEDU y otros; el liderazgo se asume como un proceso donde una o más personas influyen en otra u otras con la finalidad de alcanzar determinados propósitos para la institución cuyos resultados se proyectan a la sociedad completa rompiendo fronteras en todos los subordinados. Es una investigación de tipo descriptivo correlacional, cuya población está conformada por los 7 docentes de la I.E. Nº 101000 en el distrito de Llama, de los cuales uno es directivo con aula a cargo. A quienes se le aplicaron los instrumentos de evaluación. Al correlacionar las variables liderazgo directivo y desempeño docente se encontró que existe una alta relación positiva de las variables, debido que existe interinfluencia entre la forma cómo el directivo evidencia o muestra su liderazgo y cómo lo perciben, en algunos casos se sigue el ejemplo de parte de la plana docente

Benchmarking among artificial intelligence techniques applied to forecast

The article is about creating a space for multiple tests of demand forecasting techniques, this space is a software development where besides to testing the algorithms on the same database, these code routines can be compared with each other, this tool allows generate forecasts to be usable in decision making on purchases of Distribution Companies. Besides comparing forecasting some simple techniques like Moving Average (MM) and Last Period with other techniques such as Artificial Neural Networks (ARN) and genetic algorithms (GA), the comparison is made taking into account the error criteria of generated forecasts and the processing time of the methods. Throughout the article explains the design, development and implementation of the above methods and their integration with the tool

Using Grip Strength as a Cardiovascular Risk Indicator Based on Hybrid Algorithms

This article shows the application and design of a hybrid algorithm capable of classifying people into risk groups using data such as prehensile strength, body mass index and percentage of fat. The implementation was done on Python and proposes a tool to help make medical decisions regarding the cardiovascular health of patients. The data were taken in a systematic way, k-means and c-means algorithms were used for the classification of the data, for the prediction of new data two vectorial support machines were used, one for the k-means and the other for the c-means, obtaining as a result a 100% of precision in the vectorial support machine with c-means and a 92% in the one of k-means

Exploring the Relevance of Search Engines: An Overview of Google as a Case Study

The huge amount of data on the Internet and the diverse list of strategies used to try to link this information with relevant searches through Linked Data have generated a revolution in data treatment and its representation. Nevertheless, the conventional search engines like Google are kept as strategies with good reception to do search processes. The following article presents a study of the development and evolution of search engines, more specifically, to analyze the relevance of findings based on the number of results displayed in paging systems with Google as a case study. Finally, it is intended to contribute to indexing criteria in search results, based on an approach to Semantic Web as a stage in the evolution of the Web