818 research outputs found
Respuesta terapéutica a tiabendazol/ivermectina en un caso clínico de estrongiloidosis canina
En el presente artículo se describe un caso clínico de estrongiloidosis en un perro Beagle de 3 meses de edad que no respondió al tratamiento con los antihelmínticos convencionales a base de benzimidazoles orales, por lo que se procedió al tratamiento parenteral con ivermectina.This paper describes the none therapeutic response of Thiabendazole in a three months Beagle with Strongiloidosis. Ivermectin was the election treatment
Isotope Labelling for Reaction Mechanism Analysis in DBD Plasma Processes
Dielectric barrier discharge (DBD) plasmas and plasma catalysis are becoming an alternative procedure to activate various gas phase reactions. A low-temperature and normal operating pressure are the main advantages of these processes, but a limited energy efficiency and little selectivity control hinder their practical implementation. In this work, we propose the use of isotope labelling to retrieve information about the intermediate reactions that may intervene during the DBD processes contributing to a decrease in their energy efficiency. The results are shown for the wet reforming reaction of methane, using D2O instead of H2O as reactant, and for the ammonia synthesis, using NH3/D2/N2 mixtures. In the two cases, it was found that a significant amount of outlet gas molecules, either reactants or products, have deuterium in their structure (e.g., HD for hydrogen, CDxHy for methane, or NDxHy for ammonia). From the analysis of the evolution of the labelled molecules as a function of power, useful information has been obtained about the exchange events of H by D atoms (or vice versa) between the plasma intermediate species. An evaluation of the number of these events revealed a significant progression with the plasma power, a tendency that is recognized to be detrimental for the energy efficiency of reactant to product transformation. The labelling technique is proposed as a useful approach for the analysis of plasma reaction mechanisms
Information fusion from multiple databases using meta-association rules
Nowadays, data volume, distribution, and volatility make it difficult to search global patterns by applying traditional Data Mining techniques. In the case of data in a distributed environment, sometimes a local analysis of each dataset separately is adequate but some other times a global decision is needed by the analysis of the entire data. Association rules discovering methods typically require a single uniform dataset and managing with the entire set of distributed data is not possible due to its size. To address the scenarios in which satisfying this requirement is not practical or even feasible, we propose a new method for fusing information, in the form of rules, extracted from multiple datasets. The proposed model produces meta-association rules, i.e. rules in which the antecedent or the consequent may contain rules as well, for finding joint correlations among trends found individually in each dataset. In this paper, we describe the formulation and the implementation of two alternative frameworks that obtain, respectively, crisp meta-rules and fuzzy meta-rules. We compare our proposal with the information obtained when the datasets are not separated, in order to see the main differences between traditional association rules and meta-association rules. We also compare crisp and fuzzy methods for meta-association rule mining, observing that the fuzzy approach offers several advantages: it is more accurate since it incorporates the strength or validity of the previous information, produces a more manageable set of rules for human inspection, and allows the incorporation of contextual information to the mining process expressed in a more human-friendly format
Characterization of Alkanolamine Blends for Carbon Dioxide Absorption. Corrosion and Regeneration Studies
There are a lot of research programs focusing on the development of new solvents for carbon dioxide capture. The most important priority should be reducing the energy consumption needed at the regeneration step, but minimizing solvent degradation and its corrosivity is also considered as a priority. In this research, the aqueous blends of 2-amino-2-methyl-1-propanol (AMP: 1 kmol·m−3) and 1-amino-2-propanol (MIPA: 0.1–0.5 kmol·m−3) are characterized in terms of density, viscosity, and surface tension. The carbon dioxide absorption rate and capacity, the regeneration capacity, and the corrosivity of these solvents are also evaluatedFinancial support for this research was obtained under the Project UJA 2016/08/07: “Development of more efficient solvents for carbon dioxide capture-2” (I+D+i Support Plan of the University of Jaen), for which we are gratefulS
Artificial intelligence in wind speed forecasting: a review
Wind energy production has had accelerated growth in recent years, reaching an annual increase of 17% in 2021. Wind speed plays a crucial role in the stability required for power grid operation. However, wind intermittency makes accurate forecasting a complicated process. Implementing new technologies has allowed the development of hybrid models and techniques, improving wind speed forecasting accuracy. Additionally, statistical and artificial intelligence methods, especially artificial neural networks, have been applied to enhance the results. However, there is a concern about identifying the main factors influencing the forecasting process and providing a basis for estimation with artificial neural network models. This paper reviews and classifies the forecasting models used in recent years according to the input model type, the pre-processing and post-processing technique, the artificial neural network model, the prediction horizon, the steps ahead number, and the evaluation metric. The research results indicate that artificial neural network (ANN)-based models can provide accurate wind forecasting and essential information about the specific location of potential wind use for a power plant by understanding the future wind speed values
A Probabilistic Algorithm for Predictive Control With Full-Complexity Models in Non-Residential Buildings
Despite the increasing capabilities of information technologies for data acquisition and processing,
building energy management systems still require manual configuration and supervision to achieve
optimal performance. Model predictive control (MPC) aims to leverage equipment control-particularly
heating, ventilation, and air conditioning (HVAC)-by using a model of the building to capture its dynamic
characteristics and to predict its response to alternative control scenarios. Usually, MPC approaches are based
on simplified linear models, which support faster computation but also present some limitations regarding
interpretability, solution diversification, and longer-term optimization. In this paper, we propose a novel
MPC algorithm that uses a full-complexity grey-box simulation model to optimize HVAC operation in
non-residential buildings. Our system generates hundreds of candidate operation plans, typically for the next
day, and evaluates them in terms of consumption and comfort by means of a parallel simulator configured
according to the expected building conditions (weather and occupancy). The system has been implemented
and tested in an office building in Helsinki, both in a simulated environment and in the real building, yielding
energy savings around 35% during the intermediate winter season and 20% in the whole winter season with
respect to the current operation of the heating equipment.This work was supported in part by the Universidad de Granada under Grant P9-2014-ING, in part by the Spanish Ministry of Science,
Innovation and Universities under Grant TIN2017-91223-EXP, in part by the Spanish Ministry of Economy and Competitiveness under
Grant TIN2015-64776-C3-1-R, and in part by the European Union (Energy IN TIME EeB.NMP.2013-4), under Grant 608981
Surface chemistry and germination improvement of Quinoa seeds subjected to plasma activation
Plasma treatment is recognized as a suitable technology to improve germination efficiency of numerous seeds. In this work Quinoa seeds have been subjected to air plasma treatments both at atmospheric and low pressure and improvements found in germination rate and percentage of success. Seed water uptake by exposure to water vapor, although slightly greater for plasma treated seeds, did not justify the observed germination improvement. To identify other possible factors contributing to germination, the chemical changes experienced by outer parts of the seed upon plasma exposure have been investigated by X-ray photoemission spectroscopy (XPS) and scanning electron microscopy (SEM-EDX). XPS revealed that the outer layers of the Quinoa plasma treated seeds were highly oxidized and appeared enriched in potassium ions and adsorbed nitrate species. Simultaneously, SEM-EDX showed that the enrichment in potassium and other mineral elements extended to the seed pericarp and closer zones. The disappearance from the surface of both potassium ions and nitrate species upon exposure of the plasma treated seeds to water vapor is proposed as a factor favoring germination. The use of XPS to study chemical changes at seed surfaces induced by plasma treatments is deemed very important to unravel the mechanisms contributing to germination improvement
El juego como recurso didáctico para el alumnado con necesidades educativas especiales
This paper discusses the benefits of practicing Physical Education for students with special educational needs, and the use of the game as a teaching resource to help these students to improve relations with others and promote their integration into classes Physical Education. On the other hand, it will reflect on the importance of sporting activities to consolidate equality and solidarity between disabled and non-disabled. In this work sporting activities and games will be grounded in the characteristics of different special educational needs.El presente trabajo trata sobre los beneficios de practicar Educación Física para alumnos y alumnas con necesidades educativas especiales, así como la utilización del juego como recurso didáctico para ayudar a estos alumnos y alumnas a mejorar las relaciones con los demás y favorecer su integración en las clases de Educación Física. Por otro lado, se reflexiona sobre la trascendencia de las actividades deportivas para la consolidación de la igualdad y solidaridad entre personas discapacitadas y no discapacitadas. En este trabajo, las actividades deportivas y los juegos están fundamentados en las características de las diferentes necesidades educativas especiales
THE GAME AS A TEACHING RESOURCE FOR STUDENTS WITH SPECIAL NEEDS
This paper discusses the benefits of practicing Physical Education for students with special educational needs, and the use of the game as a teaching resource to help these students to improve relations with others and promote their integration into classes Physical Education. On the other hand, it will reflect on the importance of sporting activities to consolidate equality and solidarity between disabled and non-disabled. In this work sporting activities and games will be grounded in the characteristics of different special educational needs
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