University of Seville

About: University of Seville is a education organization based out in Seville, Andalucía, Spain. It is known for research contribution in the topics: Population & Context (language use). The organization has 20098 authors who have published 47317 publications receiving 947007 citations. The organization is also known as: Universidad de Sevilla.

LCA databases focused on construction materials: A review

Abstract: Evaluation of the environmental impact caused by construction materials frequently presents such obstacles as the mismatch between the construction project location and where the LCA database was made, lack of transparency, and/or the unsuitability of the data to the building project conditions, thereby making it necessary to establish a state-of-the-art review for researchers in order to facilitate selection between the wide variety of databases available. A review of existent LCA databases containing data for building materials has been performed. A list of features and criteria for their evaluation is developed, and subsequently applied in order to compare the various databases. Their methodology, documentation, data quality and comprehensiveness are thereby analysed. Despite the existence of a considerable number of databases, only a few contain data on construction materials. Some projects have been abandoned and several more can be considered incomplete. However, GaBi Database and Ecoinvent stand out for their integrity, usability and dedicated resources. A starting point in the selection of an LCA database for construction materials is provided. With all the information gathered herein, researchers are equipped to make a well-founded choice, and the selection process is certainly improved.

Comparative Study of Predictive and Resonant Controllers in Fault-Tolerant Five-Phase Induction Motor Drives

Abstract: One of the most attractive features of multiphase machines is the fault-tolerant capability due to the higher number of phases. Different postfault control strategies based on hysteresis, proportional integral (PI)-resonant, and predictive techniques have been recently proposed. They all proved their capabilities to withstand fault situations and to preserve the fundamental component of the air-gap field, while achieving minimum losses, maximum torque per ampere, and reducing torque vibrations. Nonetheless, due to their recent introduction, no thorough study has yet appeared comparing the performance of these controllers. In this paper, two open-phase fault-tolerant control schemes are experimentally compared in a real five-phase induction machine. The controllers being compared are based on PI-resonant and predictive control techniques, respectively. The experiments include pre- and postfault situations. Obtained results show that both control methods offer nearly the same performance. When compared, predictive control provides faster control response and superior performance at low-speed operation but is found to be less resilient to fault detection delays and to have higher current ripple. Regarding the controller implementation, it is shown that the transition from prefault to postfault operation involves modeling the nonlinear effects observed when an open-phase fault occurs for the predictive controller and proper retuning of the PI trackers for the PI-resonant controller, to ensure postfault operation.

Impact of Inadequate Empirical Therapy on the Mortality of Patients with Bloodstream Infections: a Propensity Score-Based Analysis

Abstract: The impact of the adequacy of empirical therapy on outcome for patients with bloodstream infections (BSI) is key for determining whether adequate empirical coverage should be prioritized over other, more conservative approaches. Recent systematic reviews outlined the need for new studies in the field, using improved methodologies. We assessed the impact of inadequate empirical treatment on the mortality of patients with BSI in the present-day context, incorporating recent methodological recommendations. A prospective multicenter cohort including all BSI episodes in adult patients was performed in 15 hospitals in Andalucia, Spain, over a 2-month period in 2006 to 2007. The main outcome variables were 14- and 30-day mortality. Adjusted analyses were performed by multivariate analysis and propensity score-based matching. Eight hundred one episodes were included. Inadequate empirical therapy was administered in 199 (24.8%) episodes; mortality at days 14 and 30 was 18.55% and 22.6%, respectively. After controlling for age, Charlson index, Pitt score, neutropenia, source, etiology, and presentation with severe sepsis or shock, inadequate empirical treatment was associated with increased mortality at days 14 and 30 (odds ratios [ORs], 2.12 and 1.56; 95% confidence intervals [95% CI], 1.34 to 3.34 and 1.01 to 2.40, respectively). The adjusted ORs after a propensity score-based matched analysis were 3.03 and 1.70 (95% CI, 1.60 to 5.74 and 0.98 to 2.98, respectively). In conclusion, inadequate empirical therapy is independently associated with increased mortality in patients with BSI. Programs to improve the quality of empirical therapy in patients with suspicion of BSI and optimization of definitive therapy should be implemented.

A technological acceptance of e-learning tools used in practical and laboratory teaching, according to the European higher education area

Abstract: The application of scientific tools to analyse the use of Internet-based e-learning tools in academic settings is in general an ignored area. E-learning tools are actually an emergent topic as a result of the new ideas introduced by the European Higher Education Area. Lifelong learning, or the promotion of student initiative, is the new paradigm of a learner-centred education. In this context, e-learning tools can represent an effective way of supporting this new trend in education. Assuming the premise that successful use of these web-based tools depends primarily on a user's behaviour, the objective of this research is to examine the technology acceptance model (TAM) of web-based e-learning tools used in practical and laboratory teaching. The research hypotheses derived from this model have empirically been validated using the responses to a survey on e-learning usage among 220 users. These responses have been examined through partial least square. The obtained results strongly support the extended TAM in predicting a student's intention to use e-learning and define a set of external variables with a significant influence in the original TAM variables. Surprisingly, perceived ease of use did not posit a significant impact on student attitude or intention towards e-learning tool usage. Therefore, early evaluation of e-learning material is considered essential to providing a framework for further improvements of the tool.