901 resultados para System Compositional Approach


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Direct analysis, with minimal sample pretreatment, of antidepressant drugs, fluoxetine, imipramine, desipramine, amitriptyline, and nortriptyline in biofluids was developed with a total run time of 8 min. The setup consists of two HPLC pumps, injection valve, capillary RAM-ADS-C18 pre-column and a capillary analytical C 18 column connected by means of a six-port valve in backflush mode. Detection was performed with ESI-MS/MS and only 1 mu m of sample was injected. Validation was adequately carried out using FLU-d(5) as internal standard. Calibration curves were constructed under a linear range of 1-250 ng mL(-1) in plasma, being the limit of quantification (LOQ), determined as 1 ng mL(-1), for all the analytes. With the described approach it was possible to reach a quantified mass sensitivity of 0.3 pg for each analyte (equivalent to 1.1-1.3 fmol), translating to a lower sample consumption (in the order of 103 less sample than using conventional methods). (C) 2008 Elsevier B.V. All rights reserved.

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A column switching LC method is presented for the analysis of fluoxetine (FLU) and norfluoxetine (NFLU) by direct injection of human plasma using a lab-made restricted access media (RAM) column. A RAM-BSA-octadecyl silica (C-18) column (40 min x 4.6 mm, 10 mu m) is evaluated in both backflush and foreflush elution modes and coupled with a C-18 lab-made (50 mm x 4.6 mm, 3 pm) analytical column in order to perform online sample preparation. Direct injection of 100 mu L, of plasma samples is possible with the developed approach. In addition, reduction of sample handling is obtained when compared with traditional liquid-liquid extraction (LLE) and SPE. The total analysis time is around 20 min. A LOQ of 15 ng/mL is achieved in a concentration range of 15-500 ng/mL, allowing the therapeutic drug monitoring of clinical samples. The precision values achieved are lower than 15% for all the evaluated points with adequate recovery and accuracy. Furthermore, no matrix interferences are found in the analysis and the proposed method shows to be an adequate alternative for analysis of FLU in plasma.

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Herein, we report a new approach of an FePt nanoparticle formation mechanism studying the evolution of particle size and composition during the synthesis using the modified polyol process. One of the factors limiting their application in ultra-high-density magnetic storage media is the particle-to-particle composition, which affects the A1-to-L1(0) transformation as well as their magnetic properties. There are many controversies in the literature concerning the mechanism of the FePt formation, which seems to be the key to understanding the compositional chemical distribution. Our results convincingly show that, initially, Pt nuclei are formed due to reduction of Pt(acac)(2) by the diol, followed by heterocoagulation of Fe cluster species formed from Fe(acac)(3) thermal decomposition onto the Pt nuclei. Complete reduction of heterocoagulated iron species seems to involve a CO-spillover process, in which the Pt nuclei surface acts as a heterogeneous catalyst, leading to the improvement of the single-particle composition control and allowing a much narrower compositional distribution. Our results show significant decreases in the particle-to-particle composition range, improving the A1-to-L1(0) phase transformation and, consequently, the magnetic properties when compared with other reported methods.

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This thesis is an application of the Almost Ideal Demand System approach of Deaton and Muellbauer,1980, for a particular pharmaceutical, Citalopram, in which GORMAN´s (1971) multi-stage budgeting approach is applied basically since it is one of the most useful approach in estimating demand for differentiated products. Citalopram is an antidepressant drug that is used in the treatment of major depression. As for most other pharmaceuticals whose the patent has expired, there exist branded and generic versions of Citalopram. This paper is aimed to define its demand system with two stage models for the branded version and five generic versions, and to show whether generic versions are able to compete with the branded version. I calculated the own price elasticities, and it made me possible to compare and make a conclusion about the consumers’ choices over the brand and generic drugs. Even though the models need for being developed with some additional variables, estimation results of models and uncompensated price elasticities indicated that the branded version has still power in the market, and generics are able to compete with lower prices. One important point that has to be taken into consideration is that the Swedish pharmaceutical market faced a reform on October 1, 2002, that aims to make consumer better informed about the price and decrease the overall expenditures for pharmaceuticals. Since there were not significantly enough generic sales to take into calculation before the reform, my paper covers sales after the reform.

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This work aims at combining the Chaos theory postulates and Artificial Neural Networks classification and predictive capability, in the field of financial time series prediction. Chaos theory, provides valuable qualitative and quantitative tools to decide on the predictability of a chaotic system. Quantitative measurements based on Chaos theory, are used, to decide a-priori whether a time series, or a portion of a time series is predictable, while Chaos theory based qualitative tools are used to provide further observations and analysis on the predictability, in cases where measurements provide negative answers. Phase space reconstruction is achieved by time delay embedding resulting in multiple embedded vectors. The cognitive approach suggested, is inspired by the capability of some chartists to predict the direction of an index by looking at the price time series. Thus, in this work, the calculation of the embedding dimension and the separation, in Takens‘ embedding theorem for phase space reconstruction, is not limited to False Nearest Neighbor, Differential Entropy or other specific method, rather, this work is interested in all embedding dimensions and separations that are regarded as different ways of looking at a time series by different chartists, based on their expectations. Prior to the prediction, the embedded vectors of the phase space are classified with Fuzzy-ART, then, for each class a back propagation Neural Network is trained to predict the last element of each vector, whereas all previous elements of a vector are used as features.

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An international standard, ISO/DP 9459-4 has been proposed to establish a uniform standard of quality for small, factory-made solar heating systerns. In this proposal, system components are tested separatelyand total system performance is calculated using system simulations based on component model parameter values validated using the results from the component tests. Another approach is to test the whole system in operation under representative conditions, where the results can be used as a measure of the general system performance. The advantage of system testing of this form is that it is not dependent on simulations and the possible inaccuracies of the models. Its disadvantage is that it is restricted to the boundary conditions for the test. Component testing and system simulation is flexible, but requires an accurate and reliable simulation model.The heat store is a key component conceming system performance. Thus, this work focuses on the storage system consisting store, electrical auxiliary heater, heat exchangers and tempering valve. Four different storage system configurations with a volume of 750 litre were tested in an indoor system test using a six -day test sequence. A store component test and system simulation was carried out on one of the four configurations, applying the proposed standard for stores, ISO/DP 9459-4A. Three newly developed test sequences for intemalload side heat exchangers, not in the proposed ISO standard, were also carried out. The MULTIPORT store model was used for this work. This paper discusses the results of the indoor system test, the store component test, the validation of the store model parameter values and the system simulations.

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A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson’s disease.

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Objective: For the evaluation of the energetic performance of combined renewable heating systems that supply space heat and domestic hot water for single family houses, dynamic behaviour, component interactions, and control of the system play a crucial role and should be included in test methods. Methods: New dynamic whole system test methods were developed based on “hardware in the loop” concepts. Three similar approaches are described and their differences are discussed. The methods were applied for testing solar thermal systems in combination with fossil fuel boilers (heating oil and natural gas), biomass boilers, and/or heat pumps. Results: All three methods were able to show the performance of combined heating systems under transient operating conditions. The methods often detected unexpected behaviour of the tested system that cannot be detected based on steady state performance tests that are usually applied to single components. Conclusion: Further work will be needed to harmonize the different test methods in order to reach comparable results between the different laboratories. Practice implications: A harmonized approach for whole system tests may lead to new test standards and improve the accuracy of performance prediction as well as reduce the need for field tests.

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Background  In order to facilitate the collaborative design, system dynamics (SD) with a group modelling approach was used in the early stages of planning a new stroke unit. During six workshops a SD model was created in a multiprofessional group. Aim To explore to which extent and how the use of system dynamics contributed to the collaborative design process. Method A case study was conducted using several data sources. Results SD supported a collaborative design, by facilitating an explicit description of stroke care process, a dialogue and a joint understanding. The construction of the model obliged the group to conceptualise the stroke care and experimentation with the model gave the opportunity to reflect on care. Conclusion SD facilitated the collaborative design process and should be integrated in the early stages of the design process as a quality improvement tool.

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Dynamic system test methods for heating systems were developed and applied by the institutes SERC and SP from Sweden, INES from France and SPF from Switzerland already before the MacSheep project started. These test methods followed the same principle: a complete heating system – including heat generators, storage, control etc., is installed on the test rig; the test rig software and hardware simulates and emulates the heat load for space heating and domestic hot water of a single family house, while the unit under test has to act autonomously to cover the heat demand during a representative test cycle. Within the work package 2 of the MacSheep project these similar – but different – test methods were harmonized and improved. The work undertaken includes:  • Harmonization of the physical boundaries of the unit under test. • Harmonization of the boundary conditions of climate and load. • Definition of an approach to reach identical space heat load in combination with an autonomous control of the space heat distribution by the unit under test. • Derivation and validation of new six day and a twelve day test profiles for direct extrapolation of test results.   The new harmonized test method combines the advantages of the different methods that existed before the MacSheep project. The new method is a benchmark test, which means that the load for space heating and domestic hot water preparation will be identical for all tested systems, and that the result is representative for the performance of the system over a whole year. Thus, no modelling and simulation of the tested system is needed in order to obtain the benchmark results for a yearly cycle. The method is thus also applicable to products for which simulation models are not available yet. Some of the advantages of the new whole system test method and performance rating compared to the testing and energy rating of single components are:  • Interaction between the different components of a heating system, e.g. storage, solar collector circuit, heat pump, control, etc. are included and evaluated in this test. • Dynamic effects are included and influence the result just as they influence the annual performance in the field. • Heat losses are influencing the results in a more realistic way, since they are evaluated under "real installed" and representative part-load conditions rather than under single component steady state conditions.   The described method is also suited for the development process of new systems, where it replaces time-consuming and costly field testing with the advantage of a higher accuracy of the measured data (compared to the typically used measurement equipment in field tests) and identical, thus comparable boundary conditions. Thus, the method can be used for system optimization in the test bench under realistic operative conditions, i.e. under relevant operating environment in the lab.   This report describes the physical boundaries of the tested systems, as well as the test procedures and the requirements for both the unit under test and the test facility. The new six day and twelve day test profiles are also described as are the validation results.

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Architectural description languages (ADLs) are used to specify a high-level, compositional view of a software application, specifying how a system is to be composed from coarse-grain components. ADLs usually come equipped with a formal dynamic semantics, facilitating specification and analysis of distributed and event-based systems. In this paper, we describe the TrustME, an ADL framework that provides both a process and a structural view of web service-based systems. We use Petri-net descriptions to give a dynamic view of business workflow for web service collaboration. We adapt the approach of Schmidt to define a form of Meyer's design-by-contract for configuring workflow architectures. This serves as a configuration-level means of constructing safer, more robust systems.

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In this paper we describe our system for automatically extracting "correct" programs from proofs using a development of the Curry-Howard process. Although program extraction has been developed by many authors, our system has a number of novel features designed to make it very easy to use and as close as possible to ordinary mathematical terminology and practice. These features include 1. the use of Henkin's technique to reduce higher-order logic to many-sorted (first-order) logic; 2. the free use of new rules for induction subject to certain conditions; 3. the extensive use of previously programmed (total, recursive) functions; 4. the use of templates to make the reasoning much closer to normal mathematical proofs and 5. a conceptual distinction between the computational type theory (for representing programs)and the logical type theory (for reasoning about programs). As an example of our system we give a constructive proof of the well known theorem that every graph of even parity, which is non-trivial in the sense that it does not consist of isolated vertices, has a cycle. Given such a graph as input, the extracted program produces a cycle as promised.

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This paper provides a semantics for the UML-RSDS (Reactive System Development Support) subset of UML, using the real-time action logic (RAL) formalism. We show how this semantics can be used to resolve some ambiguities and omissions in UML semantics, and to support reasoning about specifications using the B formal method and tools. We use `semantic profiles' to provide precise semantics for different semantic variation points of UML. We also show how RAL can be used to give a semantics to notations for real-time specification in UML. Unlike other approaches to UML semantics, which concentrate on the class diagram notation, our semantic representation has behaviour as a central element, and can be used to define semantics for use cases, state machines and interactions, in addition to class diagrams.

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In the past decade, compositional modelling (CM) has established itself as the predominant knowledge-based approach to construct mathematical (simulation) models automatically. Although it is mainly applied to physical systems, there is a growing interest in applying CM to other domains, such as ecological and socio-economic systems. Inspired by this observation, this paper presents a method for extending the conventional CM techniques to suit systems that are fundamentally presented by interacting populations of individuals instead of physical components or processes. The work supports building model repositories for such systems, especially in addressing the most critical outstanding issues of granularity and disaggregation in ecological systems modelling.

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Consideration of a wide range of plausible crime scenarios during any crime investigation is important to seek convincing evidence and hence to minimize the likelihood of miscarriages of justice. It is equally important for crime investigators to be able to employ effective and efficient evidence-collection strategies that are likely to produce the most conclusive information under limited available resources. An intelligent decision support system that can assist human investigators by automatically constructing plausible scenarios, and reasoning with the likely best investigating actions will clearly be very helpful in addressing these challenging problems. This paper presents a system for creating scenario spaces from given evidence, based on an integrated application of techniques for compositional modelling and Bayesian network-based evidence evaluation. Methods of analysis are also provided by the use of entropy to exploit the synthesized scenario spaces in order to prioritize investigating actions and hypotheses. These theoretical developments are illustrated by realistic examples of serious crime investigation.