893 resultados para Design of Experiments and Sample Surveys


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At head of title: Engineering and design.

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NAVSHIPS 900, 185A

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Mode of access: Internet.

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The purpose of this thesis is to provide research, supporting paperwork, production photographs and other materials that document the scenic design process for James and the Giant Peach at Adventure Theatre MTC. This thesis contains the following: concept statement, scenic research images collected to express location, and the emotional/ intellectual/ psychological landscapes for the production, preliminary sketches, photographs of the ¼” scale model, drafting plates and supporting paint elevations to communicate the design, prop list and accompanying research, archival production photographs to document the completed design, and finally periodical reviews of the show.

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AbstractThis study aimed to evaluate the effect of the distillation time and the sample mass on the total SO2 content in integral passion fruit juice (Passiflora sp). For the SO2 analysis, a modified version of the Monier-Williams method was used. In this experiment, the distillation time and the sample mass were reduced to half of the values proposed in the original method. The analyses were performed in triplicate for each distilling time x sample mass binomial, making a total of 12 tests, which were performed on the same day. The significance of the effects of the different distillation times and sample mass were evaluated by applying one-factor analysis of variance (ANOVA). For a 95% confidence limit, it was found that the proposed amendments to the distillation time, sample mass, and the interaction between distilling time x sample mass were not significant (p > 0.05) in determining the SO2 content in passion fruit juice. In view of the results that were obtained it was concluded that for integral passion fruit juice it was possible to reduce the distillation time and the sample mass in determining the SO2 content by the Monier-Williams method without affecting the result.

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1. Wildlife managers often require estimates of abundance. Direct methods of estimation are often impractical, especially in closed-forest environments, so indirect methods such as dung or nest surveys are increasingly popular. 2. Dung and nest surveys typically have three elements: surveys to estimate abundance of the dung or nests; experiments to estimate the production (defecation or nest construction) rate; and experiments to estimate the decay or disappearance rate. The last of these is usually the most problematic, and was the subject of this study. 3. The design of experiments to allow robust estimation of mean time to decay was addressed. In most studies to date, dung or nests have been monitored until they disappear. Instead, we advocate that fresh dung or nests are located, with a single follow-up visit to establish whether the dung or nest is still present or has decayed. 4. Logistic regression was used to estimate probability of decay as a function of time, and possibly of other covariates. Mean time to decay was estimated from this function. 5. Synthesis and applications. Effective management of mammal populations usually requires reliable abundance estimates. The difficulty in estimating abundance of mammals in forest environments has increasingly led to the use of indirect survey methods, in which abundance of sign, usually dung (e.g. deer, antelope and elephants) or nests (e.g. apes), is estimated. Given estimated rates of sign production and decay, sign abundance estimates can be converted to estimates of animal abundance. Decay rates typically vary according to season, weather, habitat, diet and many other factors, making reliable estimation of mean time to decay of signs present at the time of the survey problematic. We emphasize the need for retrospective rather than prospective rates, propose a strategy for survey design, and provide analysis methods for estimating retrospective rates.

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The Simulation Automation Framework for Experiments (SAFE) is a project created to raise the level of abstraction in network simulation tools and thereby address issues that undermine credibility. SAFE incorporates best practices in network simulationto automate the experimental process and to guide users in the development of sound scientific studies using the popular ns-3 network simulator. My contributions to the SAFE project: the design of two XML-based languages called NEDL (ns-3 Experiment Description Language) and NSTL (ns-3 Script Templating Language), which facilitate the description of experiments and network simulationmodels, respectively. The languages provide a foundation for the construction of better interfaces between the user and the ns-3 simulator. They also provide input to a mechanism which automates the execution of network simulation experiments. Additionally,this thesis demonstrates that one can develop tools to generate ns-3 scripts in Python or C++ automatically from NSTL model descriptions.

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Localized Magnetic Resonance Spectroscopy (MRS) is in widespread use for clinical brain research. Standard acquisition sequences to obtain one-dimensional spectra suffer from substantial overlap of spectral contributions from many metabolites. Therefore, specially tuned editing sequences or two-dimensional acquisition schemes are applied to extend the information content. Tuning specific acquisition parameters allows to make the sequences more efficient or more specific for certain target metabolites. Cramér-Rao bounds have been used in other fields for optimization of experiments and are now shown to be very useful as design criteria for localized MRS sequence optimization. The principle is illustrated for one- and two-dimensional MRS, in particular the 2D separation experiment, where the usual restriction to equidistant echo time spacings and equal acquisition times per echo time can be abolished. Particular emphasis is placed on optimizing experiments for quantification of GABA and glutamate. The basic principles are verified by Monte Carlo simulations and in vivo for repeated acquisitions of generalized two-dimensional separation brain spectra obtained from healthy subjects and expanded by bootstrapping for better definition of the quantification uncertainties.

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Nanoparticles offer an ideal platform for the delivery of small molecule drugs, subunit vaccines and genetic constructs. Besides the necessity of a homogenous size distribution, defined loading efficiencies and reasonable production and development costs, one of the major bottlenecks in translating nanoparticles into clinical application is the need for rapid, robust and reproducible development techniques. Within this thesis, microfluidic methods were investigated for the manufacturing, drug or protein loading and purification of pharmaceutically relevant nanoparticles. Initially, methods to prepare small liposomes were evaluated and compared to a microfluidics-directed nanoprecipitation method. To support the implementation of statistical process control, design of experiment models aided the process robustness and validation for the methods investigated and gave an initial overview of the size ranges obtainable in each method whilst evaluating advantages and disadvantages of each method. The lab-on-a-chip system resulted in a high-throughput vesicle manufacturing, enabling a rapid process and a high degree of process control. To further investigate this method, cationic low transition temperature lipids, cationic bola-amphiphiles with delocalized charge centers, neutral lipids and polymers were used in the microfluidics-directed nanoprecipitation method to formulate vesicles. Whereas the total flow rate (TFR) and the ratio of solvent to aqueous stream (flow rate ratio, FRR) was shown to be influential for controlling the vesicle size in high transition temperature lipids, the factor FRR was found the most influential factor controlling the size of vesicles consisting of low transition temperature lipids and polymer-based nanoparticles. The biological activity of the resulting constructs was confirmed by an invitro transfection of pDNA constructs using cationic nanoprecipitated vesicles. Design of experiments and multivariate data analysis revealed the mathematical relationship and significance of the factors TFR and FRR in the microfluidics process to the liposome size, polydispersity and transfection efficiency. Multivariate tools were used to cluster and predict specific in-vivo immune responses dependent on key liposome adjuvant characteristics upon delivery a tuberculosis antigen in a vaccine candidate. The addition of a low solubility model drug (propofol) in the nanoprecipitation method resulted in a significantly higher solubilisation of the drug within the liposomal bilayer, compared to the control method. The microfluidics method underwent scale-up work by increasing the channel diameter and parallelisation of the mixers in a planar way, resulting in an overall 40-fold increase in throughput. Furthermore, microfluidic tools were developed based on a microfluidics-directed tangential flow filtration, which allowed for a continuous manufacturing, purification and concentration of liposomal drug products.

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In this thesis, we deal with the design of experiments in the drug development process, focusing on the design of clinical trials for treatment comparisons (Part I) and the design of preclinical laboratory experiments for proteins development and manufacturing (Part II). In Part I we propose a multi-purpose design methodology for sequential clinical trials. We derived optimal allocations of patients to treatments for testing the efficacy of several experimental groups by also taking into account ethical considerations. We first consider exponential responses for survival trials and we then present a unified framework for heteroscedastic experimental groups that encompasses the general ANOVA set-up. The very good performance of the suggested optimal allocations, in terms of both inferential and ethical characteristics, are illustrated analytically and through several numerical examples, also performing comparisons with other designs proposed in the literature. Part II concerns the planning of experiments for processes composed of multiple steps in the context of preclinical drug development and manufacturing. Following the Quality by Design paradigm, the objective of the multi-step design strategy is the definition of the manufacturing design space of the whole process and, as we consider the interactions among the subsequent steps, our proposal ensures the quality and the safety of the final product, by enabling more flexibility and process robustness in the manufacturing.

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1. There are a variety of methods that could be used to increase the efficiency of the design of experiments. However, it is only recently that such methods have been considered in the design of clinical pharmacology trials. 2. Two such methods, termed data-dependent (e.g. simulation) and data-independent (e.g. analytical evaluation of the information in a particular design), are becoming increasingly used as efficient methods for designing clinical trials. These two design methods have tended to be viewed as competitive, although a complementary role in design is proposed here. 3. The impetus for the use of these two methods has been the need for a more fully integrated approach to the drug development process that specifically allows for sequential development (i.e. where the results of early phase studies influence later-phase studies). 4. The present article briefly presents the background and theory that underpins both the data-dependent and -independent methods with the use of illustrative examples from the literature. In addition, the potential advantages and disadvantages of each method are discussed.