989 resultados para Quasi-experiments


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The paper provides a systematic approach to designing the laboratory phase of a multiphase experiment, taking into account previous phases. General principles are outlined for experiments in which orthogonal designs can be employed. Multiphase experiments occur widely, although their multiphase nature is often not recognized. The need to randomize the material produced from the first phase in the laboratory phase is emphasized. Factor-allocation diagrams are used to depict the randomizations in a design and the use of skeleton analysis-of-variance (ANOVA) tables to evaluate their properties discussed. The methods are illustrated using a scenario and a case study. A basis for categorizing designs is suggested. This article has supplementary material online.

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This review focuses on one of the fundamental phenomena that occur upon application of sufficiently strong electric fields to gases, namely the formation and propagation of ionization waves-streamers. The dynamics of streamers is controlled by strongly nonlinear coupling, in localized streamer tip regions, between enhanced (due to charge separation) electric field and ionization and transport of charged species in the enhanced field. Streamers appear in nature (as initial stages of sparks and lightning, as huge structures-sprites above thunderclouds), and are also found in numerous technological applications of electrical discharges. Here we discuss the fundamental physics of the guided streamer-like structures-plasma bullets which are produced in cold atmospheric-pressure plasma jets. Plasma bullets are guided ionization waves moving in a thin column of a jet of plasma forming gases (e.g.,He or Ar) expanding into ambient air. In contrast to streamers in a free (unbounded) space that propagate in a stochastic manner and often branch, guided ionization waves are repetitive and highly-reproducible and propagate along the same path-the jet axis. This property of guided streamers, in comparison with streamers in a free space, enables many advanced time-resolved experimental studies of ionization waves with nanosecond precision. In particular, experimental studies on manipulation of streamers by external electric fields and streamer interactions are critically examined. This review also introduces the basic theories and recent advances on the experimental and computational studies of guided streamers, in particular related to the propagation dynamics of ionization waves and the various parameters of relevance to plasma streamers. This knowledge is very useful to optimize the efficacy of applications of plasma streamer discharges in various fields ranging from health care and medicine to materials science and nanotechnology.

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The aim of this study is to investigate the stress relaxation behavior of single chondrocytes using the Porohyperelastic (PHE) model and inverse Finite Element Analysis (FEA). Firstly, based on Atomic Force Microscopy (AFM) technique, we have found that the chondrocytes exhibited stress relaxation behavior. We explored the mechanism of this stress relaxation behavior and concluded that the intracellular fluid exuding out from the cells during deformation plays the most important role in the stress relaxation. Next, we have applied the inverse FEA technique to determine necessary material parameters for PHE model to simulate this stress relaxation behavior as this model is proven capable of capturing the non-linear behavior and the fluid-solid interaction during the stress relaxation of the single chondrocytes. It is observed that this PHE model can precisely capture the stress relaxation behavior of single chondrocytes and would be a suitable model for cell biomechanics.

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A laboratory experiment was set up in small chambers for monitoring greenhouse gas emissions and determining the most suitable time for sampling. A six-treatment experiment was conducted, including a one week pre-incubation and a week for incubation. Timelines for sampling were 1, 2, 3, 6 and 24 hours after closing the lid of the incubation chambers. Variation in greenhouse gas fluxes was high due to the time of sampling. The rates of gas emissions increased in first three hours and decreased afterward. The rates of greenhouse gas emissions at 3 hours after closing lids was close to the mean for the 24-h period.

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Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In this work, we introduce a method to update the reference views in a hybrid metrictopological map so that a mobile robot can continue to localize itself in a changing environment. The updating mechanism, based on the multi-store model of human memory, incorporates a spherical metric representation of the observed visual features for each node in the map, which enables the robot to estimate its heading and navigate using multi-view geometry, as well as representing the local 3D geometry of the environment. A series of experiments demonstrate the persistence performance of the proposed system in real changing environments, including analysis of the long-term stability.

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Computational models in physiology often integrate functional and structural information from a large range of spatio-temporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and scepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace and refine animal experiments. A fundamental requirement to fulfil these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations between experiments, models and simulations in cardiac electrophysiology. We describe the processes, data and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. Validation must therefore take into account the complex interplay between models, simulations and experiments. Key points for developing strategies for validation are: 1) understanding sources of bio-variability is crucial to the comparison between simulation and experimental results; 2) robustness of techniques and tools is a pre-requisite to conducting physiological investigations using the MSE system; 3) definition and adoption of standards facilitates interoperability of experiments, models and simulations; 4) physiological validation must be understood as an iterative process that defines the specific aspects of electrophysiology the MSE system targets, and is driven by advancements in experimental and computational methods and the combination of both.

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This practice-led PhD project investigates the ways in which society positions children through a broad set of social, cultural and historical considerations and examines these within the frame of theatre making. The study proposes a model of practice that moves beyond participant empowerment toward a more dynamic understanding of the creative process that sees adults and children working together to create mainstream artistic product. It contends that this model creates conditions conducive to authentic theatre making practice with children as evidenced in the researcher’s original performance work Joy Fear and Poetry.

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Social Clothing Experiments was a large-scale outdoor installation staged for the opening of the Pacific Standard Time exhibition at the Getty Center in 2011. It was part of a ten day performance festival.Each body-pillow was made out of second-hand tie-dyed t-shirts that were patch-worked together in various formations. The public was welcomed to move, play and rest with the installation.It explores Wyman's interest in art's role in social engagement and participation.

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A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.

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This article discusses the production of an Indonesian rock past through a case study of the 1970s rock band God Bless, which has been gradually ‘coming back’ since the middle of the 2000s. In doing so, the article documents this comeback, analyses shifts in the band’s position vis-à-vis nationality, and places these shifts in the context of the industrial and aesthetic transformation of Indonesian popular music over the past decade or so. Furthermore, it considers how the range of nostalgic productions associated with the comeback might be understood not only in light of the scholarship on nostalgia, but also the political environment it inhabits.

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In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insuffcient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.