942 resultados para Model-driven Web engineering
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Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.
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168 p.
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Part 20: Health and Care Networks
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International audience
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The goal of this project is to learn the necessary steps to create a finite element model, which can accurately predict the dynamic response of a Kohler Engines Heavy Duty Air Cleaner (HDAC). This air cleaner is composed of three glass reinforced plastic components and two air filters. Several uncertainties arose in the finite element (FE) model due to the HDAC’s component material properties and assembly conditions. To help understand and mitigate these uncertainties, analytical and experimental modal models were created concurrently to perform a model correlation and calibration. Over the course of the project simple and practical methods were found for future FE model creation. Similarly, an experimental method for the optimal acquisition of experimental modal data was arrived upon. After the model correlation and calibration was performed a validation experiment was used to confirm the FE models predictive capabilities.
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Preliminary calculations using the Covariant Spectator Theory (CST) employed a scalar linear confining interaction and an additional constant vector potential to compute the mesonic mass spectra. In this work we generalize the confining interaction to include more general structures, in particular a vector and also a pseudoscalar part, as suggested by a recent study. A one-gluon-exchange kernel is also implemented to describe the short-range part of the interaction. We solve the simplest CST approxima- tion to the complete Bethe-Salpeter equation, the one-channel spectator equation, using a numerical technique that eliminates all singularities from the kernel. The parameters of the model are determined through a fit to the experimental pseudoscalar meson spectra, with a good agreement for both quarkonia and heavy-light states.
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Identification, prediction, and control of a system are engineering subjects, regardless of the nature of the system. Here, the temporal evolution of the number of individuals with dengue fever weekly recorded in the city of Rio de Janeiro, Brazil, during 2007, is used to identify SIS (susceptible-infective-susceptible) and SIR (susceptible-infective-removed) models formulated in terms of cellular automaton (CA). In the identification process, a genetic algorithm (GA) is utilized to find the probabilities of the state transition S -> I able of reproducing in the CA lattice the historical series of 2007. These probabilities depend on the number of infective neighbors. Time-varying and non-time-varying probabilities, three different sizes of lattices, and two kinds of coupling topology among the cells are taken into consideration. Then, these epidemiological models built by combining CA and GA are employed for predicting the cases of sick persons in 2008. Such models can be useful for forecasting and controlling the spreading of this infectious disease.
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Catalytic ozonation has been recognized in the scientific community as an efficient technique, reaching elevated rates of recalcitrant organic material mineralization, even at the presence of scavenger species of hydroxyl free radicals. This study presents the most significant factors involving the leachate treatment stabilized by the municipal landfill of the city of Guaratingueta, State of Sao Paulo, Brazil, by using a catalytic ozonation activated by metallic ions Fe(3+), Zn(2+), Mn(2+), Ni(2+) and Cr(3+). The Taguchi L(16) orthogonal array and its associated statistical methods were also used in this study. Among the researched ions, the most notable catalysis was obtained with ferric ion, statistically significant in the reduction of COD with a confidence level of 99.5%.
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The perfect mixing model (PMM) is based on parameters derived from the equipment characteristics as well as ore breakage characteristics. Ore characteristics are represented through the appearance function. This function may be determined using JKMRC laboratorial methods or by standard functions. This work describes the model fitting process of the Carajas grinding circuit, using the JKSimMet simulator Two scenarios were used in model fitting exercises: 1) standard appearance function; and 2) appearance fund ion based on testing carried out on samples taken at circuit feed. From this assessment, the appearance function`s influence in the PMM,fit and it`s relation with the breakage rate were determined. The influence of the appearance function on the respective breakage rate distribution was assessed.
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Flow pumps have been developed for classical applications in Engineering, and are important instruments in areas such as Biology and Medicine. Among applications for this kind of device we notice blood pump and chemical reagents dosage in Bioengineering. Furthermore, they have recently emerged as a viable thermal management solution for cooling applications in small-scale electronic devices. This work presents the performance study of a novel principle of a piezoelectric flow pump which is based oil the use of a bimorph piezoelectric actuator inserted in fluid (water). Piezoelectric actuators have some advantages over classical devices, such as lower noise generation and ease of miniaturization. The main objective is the characterization of this piezoelectric pump principle through computational simulations (using finite element software), and experimental tests through a manufactured prototype. Computational data, Such as flow rate and pressure curves, have also been compared with experimental results for validation purposes. (C) 2009 Elsevier B.V. All rights reserved.
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The objective of this paper is to develop a mathematical model for the synthesis of anaerobic digester networks based on the optimization of a superstructure that relies on a non-linear programming formulation. The proposed model contains the kinetic and hydraulic equations developed by Pontes and Pinto [Chemical Engineering journal 122 (2006) 65-80] for two types of digesters, namely UASB (Upflow Anaerobic Sludge Blanket) and EGSB (Expanded Granular Sludge Bed) reactors. The objective function minimizes the overall sum of the reactor volumes. The optimization results show that a recycle stream is only effective in case of a reactor with short-circuit, such as the UASB reactor. Sensitivity analysis was performed in the one and two-digester network superstructures, for the following parameters: UASB reactor short-circuit fraction and the EGSB reactor maximum organic load, and the corresponding results vary considerably in terms of digester volumes. Scenarios for three and four-digester network superstructures were optimized and compared with the results from fewer digesters. (C) 2009 Elsevier B.V. All rights reserved.
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The utilization of tannery sludge in agricultural areas can be an alternative for its disposal and recycling. Despite this procedure may cause the loss of nitrogen by ammonia volatilization, there is no information about this process in tropical soils. For two years a field experiment was carried out in Rolandia (Parana State, Brazil), to evaluate the amount of NH(3) volatilization due to tannery sludge application on agricultural soil. The doses of total N applied varied from zero to 1200 kg ha(-1), maintained at the surface for 89 days, as usual in this region. The alkalinity of the tannery sludge used was equivalent to between 262 and 361 g CaCO(3) per kg. Michaelis-Menten equation was adequate to estimate NH(3)-N volatilization kinetics. The relation between total nitrogen applied as tannery sludge and the potentially volatilized NH(3)-N, calculated by the chemical-kinetics equation resulted in an average determination coefficient of 0.87 (P > 0.01). In this period, the amount of volatilized NH(3) was more intense during the first 30 days; the time to reach half of the maximum NH(3) volatilization (K(m)) was 13 an 9 days for the first and second experiments, respectively. The total loss as ammonia in the whole period corresponded in average to 17.5% of the total N applied and to 35% of the NH(4)(+)-N present in the sludge. If tannery sludge is to be surface applied to supply N for crops, the amounts lost as NH(3) must be taken into consideration. (C) 2010 Elsevier Ltd. All rights reserved.
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Globalisation, increasing complexity, and the need to address triple-bottom line sustainability has seen the proliferation of Learning Organisations (LO) who, by definition, have the capacity to anticipate environmental changes and economic opportunities and adapt accordingly. Such organisations use system dynamics modelling (SDM) for both strategic planning and the promotion of organisational learning. Although SDM has been applied in the context of tourism destination management for predictive reasons, the current literature does not analyse or recognise how this could be used as a foundation for an LO. This study introduces the concept of the Learning Tourism Destinations (LTD) and discusses, on the basis of a review of 6 case studies, the potential of SDM as a tool for the implementation and enhancement of collective learning processes. The results reveal that SDM is capable of promoting communication between stakeholders and stimulating organisational learning. It is suggested that the LTD approach be further utilised and explored.
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A study was carried out to evaluate the feasibility of autologous adipose derived stem cells (ADSC) transplantation into female rabbits` urethra walls as an alternative to intrinsic urethral regeneration. Inguinal fat pad of 12 New Zealand adult female rabbits were harvested and processed to obtain stromal vascular fraction (SVF). The SVF were platted to isolate ADSC. Before urethral injection, cells were labeled with DiI marker. The urethra wall was injected with 1 x 10(7) autologous cells or saline (sham). The urethra was harvested at 2, 4, and 8 weeks to identify DiI-labeled cells. At 2 and 4 weeks, the ADSCs create a nodule localized in the urethral sub-mucosa. At 8 weeks, the ADSCs spread and integrated with the urethra wall from the initial injection site. This is the first study to demonstrate a successful autologous ADSCs transplantation. It confirms that ADSCs can survive and integrate within the urethral wall.
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In the context of an e ort to develop methodologies to support the evaluation of interactive system, this paper investigates an approach to detect graphical user interface bad smells. Our approach consists in detecting user interface bad smells through model-based reverse engineering from source code. Models are used to de ne which widgets are present in the interface, when can particular graphical user interface (GUI) events occur, under which conditions, which system actions are executed, and which GUI state is generated next.