Problem-based learning for the acquisition of scientific-technical skills in training of future teachers

En esta comunicación se plantea la necesidad de fomentar la capacitación de competencias científico-técnicas en estudiantes del Grado de Magisterio de Educación Infantil. Para ello, se ha diseñado una actividad basada en el aprendizaje basado en problemas en la asignatura de funciones del profesorado. Según los resultados muestran que los alumnos valoran de forma positiva el método, prefiriendo éste al método de enseñanza tradicional basado en la lección magistral. Además, los estudiantes se encuentran más motivados e interesados por el aprendizaje y mejoran en la adquisición de competencias científico-técnicas

YOUTH ANTISOCIAL OR WITH TENDENCIES ACCORDING TO MEXIQUENSES PRECEPTORIES

Se destaca que tales autoridades consideran que estos jóvenes se orientan hacia tales conductas, tanto por cambios personales como por situaciones sociales que enfrentan, otorgándole la responsabilidad a ellos y a sus familias, sin considerar los factores estructurales.En este artículo se analizan algunas ideas de las autoridades de las preceptorías del Estado de México para explicar la existencia de jóvenes con conductas antisociales entre los sectores populares, con base en una investigación cualitativa realizada en el año 2016.SE

Flora briofítica de las ciudades de Toro y Benavente (Zamora, España)

Se presenta el estudio brioflorístico de las ciudades de Toro y Benavente en la provincia de Zamora, del que ha resultado un catálogo de 32 especies de musgos, de las que Eurhynchium pumilum, Scleropodium touretii y Tortella nitida, se citan por primera vez como urbanícelas en España. Se analizan también las querencias ecológicas y los ambientes urbanos en que se recolectaron los briófitos.We present the bryofloristic study of two Spanish towns, Toro and Benavente in Zamora province with a catalogue of 32 species. Eurhynchium pumilum, Scleropodium touretii and Tortella nitida, are reported as urban bryophytes for the first time. The ecology and the urban habitat where the bryophytes were collected are discussed

Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets

Association rule mining is a well-known methodology to discover significant and apparently hidden relations among attributes in a subspace of instances from datasets. Genetic algorithms have been extensively used to find interesting association rules. However, the rule-matching task of such techniques usually requires high computational and memory requirements. The use of efficient computational techniques has become a task of the utmost importance due to the high volume of generated data nowadays. Hence, this paper aims at improving the scalability of quantitative association rule mining techniques based on genetic algorithms to handle large-scale datasets without quality loss in the results obtained. For this purpose, a new representation of the individuals, new genetic operators and a windowing-based learning scheme are proposed to achieve successfully such challenging task. Specifically, the proposed techniques are integrated into the multi-objective evolutionary algorithm named QARGA-M to assess their performances. Both the standard version and the enhanced one of QARGA-M have been tested in several datasets that present different number of attributes and instances. Furthermore, the proposed methodologies have been integrated into other existing techniques based in genetic algorithms to discover quantitative association rules. The comparative analysis performed shows significant improvements of QARGA-M and other existing genetic algorithms in terms of computational costs without losing quality in the results when the proposed techniques are applied.Ministerio de Ciencia y Tecnología TIN2011- 28956-C02-02Junta de Andalucía TIC-7528Junta de Andalucía P12-TIC-1728Universidad Pablo de Olavide APPB81309

Sentimiento de inseguridad y acciones para su gestión entre universitarios en el Estado de México

El sentimiento de inseguridad es un fenómeno que afecta a parte de la población del Estado de México, particularmente por los elevados índices de criminalidad. Sin embargo, hasta el momento no se conoce suficiente sobre la forma en que este sentimiento es manejado y procesado por grupos específicos, como son los estudiantes universitarios. Por ello, el presente trabajo se orienta a dar un acercamiento, mostrando dónde sienten mayor inseguridad estos estudiantes, así como las acciones y estrategias que se despliegan para gestionar estas vivencias y protegerse ante situaciones de delito. El estudio empírico se basa en grupos de enfoques realizados con estudiantes de la universidad estatal, dentro del marco de una investigación mayor. Entre los hallazgos más relevantes destacan diversas prácticas de evitación y protección que los estudiantes universitarios llevan a cabo, quedando patente la necesidad de atender este fenómeno y que las autoridades comprendan su gravedad y, en su caso, definan las acciones y políticas para aumentar la protección y la seguridad

An evolutionary algorithm to discover quantitative association rules in multidimensional time series

An evolutionary approach for finding existing relationships among several variables of a multidimensional time series is presented in this work. The proposed model to discover these relationships is based on quantitative association rules. This algorithm, called QARGA (Quantitative Association Rules by Genetic Algorithm), uses a particular codification of the individuals that allows solving two basic problems. First, it does not perform a previous attribute discretization and, second, it is not necessary to set which variables belong to the antecedent or consequent. Therefore, it may discover all underlying dependencies among different variables. To evaluate the proposed algorithm three experiments have been carried out. As initial step, several public datasets have been analyzed with the purpose of comparing with other existing evolutionary approaches. Also, the algorithm has been applied to synthetic time series (where the relationships are known) to analyze its potential for discovering rules in time series. Finally, a real-world multidimensional time series composed by several climatological variables has been considered. All the results show a remarkable performance of QARGA.Ministerio de Ciencia y Tecnología TIN2007- 68084-C02-02Junta de Andalucia P07-TIC- 0261

Effects of oral glutamine during abdominal radiotherapy on chronic radiation enteritis: a randomized controlled trial

[Abstract] Objective. Glutamine has been proposed as a preventive treatment for toxicity related to cancer therapies. The aim of this study was to test the efficacy of glutamine in the prevention of radiation enteritis. Methods. A randomized, double-blind, controlled trial was performed including 69 patients who were assigned to receive either glutamine (Gln, 30 g/d) or placebo while they were receiving abdominal radiotherapy. Patients were re-evaluated 1 y after completion of treatment. The presence of chronic enteritis was assessed using the Radiation Therapy Oncology Group scale. Nutritional status was evaluated using subjective global assessment, weight, and bioimpedance. Relative risk (RR) and its confidence interval (CI) were also calculated. Results. The trial initially included 69 patients (34 Gln, 35 placebo), but 11 patients were lost during follow-up (4 Gln, 7 placebo; P = 0.296). Chronic enteritis was developed by 14 % of patients: Gln 16.7 % versus placebo 11.1% (RR = 1.33; 95 % CI, 0.35–5.03; P = 0.540). Most cases of enteritis were grade I (75 %), with no differences between groups. The stool frequency increased after radiotherapy in patients who received Gln (from 1 ± 1 to 2 ± 2 stools per day, P = 0.012), but remained unchanged with placebo (1 ± 1 stools per day, P = 0.858; difference between groups P = 0.004). There were no differences between the two groups in terms of weight, fat mass, or fat-free mass index, or between patients with enteritis and those without intestinal toxicity. Conclusions. Chronic enteritis is a relatively infrequent phenomenon, and Gln administration during radiotherapy does not exert a protective effect.Castilla y León. Consejería de Sanidad; GRS 326/B/0

Quantitative Association Rules Applied to Climatological Time Series Forecasting

This work presents the discovering of association rules based on evolutionary techniques in order to obtain relationships among correlated time series. For this purpose, a genetic algorithm has been proposed to determine the intervals that form the rules without discretizing the attributes and allowing the overlapping of the regions covered by the rules. In addition, the algorithm has been tested on real-world climatological time series such as temperature, wind and ozone and results are reported and compared to that of the well-known Apriori algorithm

Selecting the best measures to discover quantitative association rules

The majority of the existing techniques to mine association rules typically use the support and the confidence to evaluate the quality of the rules obtained. However, these two measures may not be sufficient to properly assess their quality due to some inherent drawbacks they present. A review of the literature reveals that there exist many measures to evaluate the quality of the rules, but that the simultaneous optimization of all measures is complex and might lead to poor results. In this work, a principal components analysis is applied to a set of measures that evaluate quantitative association rules' quality. From this analysis, a reduced subset of measures has been selected to be included in the fitness function in order to obtain better values for the whole set of quality measures, and not only for those included in the fitness function. This is a general-purpose methodology and can, therefore, be applied to the fitness function of any algorithm. To validate if better results are obtained when using the function fitness composed of the subset of measures proposed here, the existing QARGA algorithm has been applied to a wide variety of datasets. Finally, a comparative analysis of the results obtained by means of the application of QARGA with the original fitness function is provided, showing a remarkable improvement when the new one is used.Ministerio de Ciencia y Tecnología TIN2011-28956-C0

Obtaining optimal quality measures for quantitative association rules

There exist several works in the literature in which fitness functions based on a combination of weighted measures for the discovery of association rules have been proposed. Nevertheless, some differences in the measures used to assess the quality of association rules could be obtained according to the values of the weights of the measures included in the fitness function. Therefore, user's decision is very important in order to specify the weights of the measures involved in the optimization process. This paper presents a study of well-known quality measures with regard to the weights of the measures that appear in a fitness function. In particular, the fitness function of an existing evolutionary algorithm called QARGA has been considered with the purpose of suggesting the values that should be assigned to the weights, depending on the set of measures to be optimized. As initial step, several experiments have been carried out from 35 public datasets in order to show how the weights for confidence, support, amplitude and number of attributes measures included in the fitness function have an influence on different quality measures according to several minimum support thresholds. Second, statistical tests have been conducted for evaluating when the differences in measures of the rules obtained by QARGA are significative, and thus, to provide the best weights to be considered depending on the group of measures to be optimized. Finally, the results obtained when using the recommended weights for two real-world applications related to ozone and earthquakes are reported.Ministerio de Ciencia y Tecnología TIN2011-28956-C02Junta de Andalucía P12- TIC-1728Universidad Pablo de Olavide APPB81309