Colonization and development of Oribatida mite communities (Acari: Oribatida) in the forest reclaimed limestone mine dumps

In order to study the colonization and development of moss mites (Oribatida) communities in a Scots pine forest of a reclaimed limestone mine dump in Northern Poland, 3 plots from the dump were chosen. The selected plots differed in age, 5 years old, 35 and 50 years old. From a total of 30 samples 499 mites (Acari) were extracted in Tullgren funnel from which 262 were Oribatida. Abundance (N) was analyzed in all mites and after determining the species of both, juvenile and adult stages of oribatids, the following indices were analyzed: Abundance (N), Dominance (D), Species diversity (S), Species richness (s) and Shannon’s diversity index (H). Regarding to the results obtained; oribatid mites were dominant with the highest abundance in all assemblages (Plot 1: 139 Oribatida /299 Acari. Plot 2: 40/55 and Plot 3: 83/145). Tectocepheus velatus showed a very high dominance (45,99%) in plot 1; the highest value for Shannon’s diversity index belonged to plot 3. On the other hand, juvenile’s percentage was significantly higher than adult’s percentage, especially at plot 2 (95,02%). These results made us to conclude that the high abundance of oribatids in the youngest forest is due to T. velatus’s high abundance and that plot 3 is the best habitat for mites. Finally, the high occurrence of juvenile stages requires keeping on studying the area.

Water quality assessment and characterisation of chlorophyll-a variability related to river discharges, within the southeastern Bay of Biscay : evaluation and development of chlorophyll-a algorithms for MODIS and MERIS imagery

222 p. : il.

Design and Development of a Low-Cost Optical Current Sensor

In this paper we demonstrate the design of a low-cost optical current sensor. The sensor principle is the Faraday rotation of a light beam through a magneto-optical material, SF2, when a magnetic field is present. The prototype has a high sensitivity and a high linearity for currents ranging from 0 up to 800 A. The error of the optical fibre sensor is smaller than 1% for electric currents over 175 A.

Initiatives for the improvement of continuous management training

[EN] Purpose. This work aims to present, from the company viewpoint, a structured account of management proposals and practices directed toward improving the intensity and effectiveness of continuous management training (CMT). Design/methodology/approach. The article takes as its main theoretical referents the Theory of Human Capital, the Resource-Based Vision and the contributions made via the new institutional economy with regard to the problems of information asymmetry between companies, employees and training providers and completes the proposals that derive from this theoretical approach. To do this, experience-based contributions are collected from a selection of company training and HR managers from twelve Basque companies characterised by their strong investment in management training. The methodology used was qualitative and obtained by different qualitative techniques: Focus Groups, Nominal Groups and the Delphi Method, which make up the so-called Hybrid Delphi. Findings and implications. The proposals are aimed at the main agents in training activity: training providers, associations and public agents engaged in management training and, particularly, companies themselves. The initiatives seek above all to increase training market transparency, to improve mutual commitments between companies and managers, and to link training and development with culture and strategic management, so that firms make optimal investment in management training. Originality/value. The methodology used is original, and the contributions are consistent with the theory, have a proven practical utility, and are presented in a hierarchy, which facilitates decision making.

Analysis, optimization and development of an answer scoring system

The main contribution of this work is to analyze and describe the state of the art performance as regards answer scoring systems from the SemEval- 2013 task, as well as to continue with the development of an answer scoring system (EHU-ALM) developed in the University of the Basque Country. On the overall this master thesis focuses on finding any possible configuration that lets improve the results in the SemEval dataset by using attribute engineering techniques in order to find optimal feature subsets, along with trying different hierarchical configurations in order to analyze its performance against the traditional one versus all approach. Altogether, throughout the work we propose two alternative strategies: on the one hand, to improve the EHU-ALM system without changing the architecture, and, on the other hand, to improve the system adapting it to an hierarchical con- figuration. To build such new models we describe and use distinct attribute engineering, data preprocessing, and machine learning techniques.