A comparative study of hospital management in Great Britain and Brazil : cost information use

In Great Britain and Brazil healthcare is free at the point of delivery and based study only on citizenship. However, the British NHS is fifty-five years old and has undergone extensive reforms. The Brazilian SUS is barely fifteen years old. This research investigated the middle management mediation role within hospitals comparing managerial planning and control using cost information in Great Britain and Brazil. This investigation was conducted in two stages entailing quantitative and qualitative techniques. The first stage was a survey involving managers of 26 NHS Trusts in Great Britain and 22 public hospitals in Brazil. The second stage consisted of interviews, 10 in Great Britain and 22 in Brazil, conducted in four selected hospitals, two in each country. This research builds on the literature by investigating the interaction of contingency theory and modes of governance in a cross-national study in terms of public hospitals. It further builds on the existing literature by measuring managerial dimensions related to cost information usefulness. The project unveils the practice involved in planning and control processes. It highlights important elements such as the use of predictive models and uncertainty reduction when planning. It uncovers the different mechanisms employed on control processes. It also depicts that planning and control within British hospitals are structured procedures and guided by overall goals. In contrast, planning and control processes in Brazilian hospitals are accidental, involving more ad hoc actions and a profusion of goals. The clinicians in British hospitals have been integrated into the management hierarchy. Their use of cost information in planning and control processes reflects this integration. However, in Brazil, clinicians have been shown to operate more independently and make little use of cost information but the potential signalled for cost information use is seen to be even greater than that of their British counterparts.

The development of a novel in vitro model suitable for the prediction of bioavailability

In vitro studies of drug absorption processes are undertaken to assess drug candidate or formulation suitability, mechanism investigation, and ultimately for the development of predictive models. This study included each of these approaches, with the aim of developing novel in vitro methods for inclusion in a drug absorption model. Two model analgesic drugs, ibuprofen and paracetamol, were selected. The study focused on three main areas, the interaction of the model drugs with co-administered antacids, the elucidation of the mechanisms responsible for the increased absorption rate observed in a novel paracetamol formulation and the development of novel ibuprofen tablet formulations containing alkalising excipients as dissolution promoters.Several novel dissolution methods were developed. A method to study the interaction of drug/excipient mixtures in the powder form was successfully used to select suitable dissolution enhancing exicipents. A method to study intrinsic dissolution rate using paddle apparatus was developed and used to study dissolution mechanisms. Methods to simulate stomach and intestine environments in terms of media composition and volume and drug/antacid doses were developed. Antacid addition greatly increased the dissolution of ibuprofen in the stomach model.Novel methods to measure drug permeability through rat stomach and intestine were developed, using sac methodology. The methods allowed direct comparison of the apparent permeability values obtained. Tissue stability, reproducibility and integrity was observed, with selectivity between paracellular and transcellular markers and hydrophilic and lipophilic compounds within an homologous series of beta-blockers.

Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102:a bioinformatic approach to the prediction of new epitopes

Predictive models of peptide-Major Histocompatibility Complex (MHC) binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102.

The application of remote sensing to the management of urban wildlife habitats

The project set out with two main aims. The first aim was to determine whether large scale multispectral aerial photography could be used to successfully survey and monitor urban wildlife habitats. The second objective was to investigate whether this data source could be used to predict population numbers of selected species expected to be found in a particular habitat type. Panchromatic, colour and colour infra-red, 1:2500 scale aerial photographs, taken in 1981 and 1984, were used. For the orderly extraction of information from the imagery, an urban wildlife habitat classification was devised. This was based on classifications already in use in urban environments by the Nature Conservancy Council. Pilot tests identified that the colour infra-red imagery provided the most accurate results about urban wildlife habitats in the study area of the Blackbrook Valley, Dudley. Both the 1981 and 1984 colour infra-red photographs were analysed and information was obtained about the type, extent and distribution of habitats. In order to investigate whether large scale aerial photographs could be used to predict likely animal population numbers in urban environments, it was decided to limit the investigation to the possible prediction of bird population numbers in Saltwells Local Nature Reserve. A good deal of research has already been completed into the development of models to predict breeding bird population numbers in woodland habitats. These models were analysed to determine whether they could be used successfully with data extracted from the aerial photographs. The projects concluded that 1:2500 scale colour infra-red photographs can provide very useful and very detailed information about the wildlife habitats in an urban area. Such imagery can also provide habitat area data to be used with population predictive models of woodland breeding birds. Using the aerial photographs, further investigations into the relationship between area of habitat and the breeding of individual bird species were inconclusive and need further research.

Improved Criteria for Estimating Calibration Factors for Highway Safety Manual (HSM) Applications

The Highway Safety Manual (HSM) estimates roadway safety performance based on predictive models that were calibrated using national data. Calibration factors are then used to adjust these predictive models to local conditions for local applications. The HSM recommends that local calibration factors be estimated using 30 to 50 randomly selected sites that experienced at least a total of 100 crashes per year. It also recommends that the factors be updated every two to three years, preferably on an annual basis. However, these recommendations are primarily based on expert opinions rather than data-driven research findings. Furthermore, most agencies do not have data for many of the input variables recommended in the HSM. This dissertation is aimed at determining the best way to meet three major data needs affecting the estimation of calibration factors: (1) the required minimum sample sizes for different roadway facilities, (2) the required frequency for calibration factor updates, and (3) the influential variables affecting calibration factors. In this dissertation, statewide segment and intersection data were first collected for most of the HSM recommended calibration variables using a Google Maps application. In addition, eight years (2005-2012) of traffic and crash data were retrieved from existing databases from the Florida Department of Transportation. With these data, the effect of sample size criterion on calibration factor estimates was first studied using a sensitivity analysis. The results showed that the minimum sample sizes not only vary across different roadway facilities, but they are also significantly higher than those recommended in the HSM. In addition, results from paired sample t-tests showed that calibration factors in Florida need to be updated annually. To identify influential variables affecting the calibration factors for roadway segments, the variables were prioritized by combining the results from three different methods: negative binomial regression, random forests, and boosted regression trees. Only a few variables were found to explain most of the variation in the crash data. Traffic volume was consistently found to be the most influential. In addition, roadside object density, major and minor commercial driveway densities, and minor residential driveway density were also identified as influential variables.

Volume averaging of multiphase flows with hydrate formation in subsea pipelines

In oil and gas pipeline operations, the gas, oil, and water phases simultaneously move through pipe systems. The mixture cools as it flows through subsea pipelines, and forms a hydrate formation region, where the hydrate crystals start to grow and may eventually block the pipeline. The potential of pipe blockage due to hydrate formation is one of the most significant flow-assurance problems in deep-water subsea operations. Due to the catastrophic safety and economic implications of hydrate blockage, it is important to accurately predict the simultaneous flow of gas, water, and hydrate particles in flowlines. Currently, there are few or no studies that account for the simultaneous effects of hydrate growth and heat transfer on flow characteristics within pipelines. This thesis presents new and more accurate predictive models of multiphase flows in undersea pipelines to describe the simultaneous flow of gas, water, and hydrate particles through a pipeline. A growth rate model for the hydrate phase is presented and then used in the development of a new three-phase model. The conservation equations of mass, momentum, and energy are formulated to describe the physical phenomena of momentum and heat transfer between the fluid and the wall. The governing equations are solved based on an analytical-numerical approach using a Newton-Raphson method for the nonlinear equations. An algorithm was developed in Matlab software to solve the equations from the inlet to the outlet of the pipeline. The developed models are validated against a single-phase model with mixture properties, and the results of comparative studies show close agreement. The new model predicts the volume fraction and velocity of each phase, as well as the mixture pressure and temperature profiles along the length of the pipeline. The results from the hydrate growth model reveal the growth rate and location where the initial hydrates start to form. Finally, to assess the impact of certain parameters on the flow characteristics, parametric studies have been conducted. The results show the effect of a variation in the pipe diameter, mass flow rate, inlet pressure, and inlet temperature on the flow characteristics and hydrate growth rates.

Results of wave modelling for Moreton Bay, Southeast Queensland, and a reef lagoon off Lizard Island, Great Barrier Reef, Australia

The distribution, abundance, behaviour, and morphology of marine species is affected by spatial variability in the wave environment. Maps of wave metrics (e.g. significant wave height Hs, peak energy wave period Tp, and benthic wave orbital velocity URMS) are therefore useful for predictive ecological models of marine species and ecosystems. A number of techniques are available to generate maps of wave metrics, with varying levels of complexity in terms of input data requirements, operator knowledge, and computation time. Relatively simple "fetch-based" models are generated using geographic information system (GIS) layers of bathymetry and dominant wind speed and direction. More complex, but computationally expensive, "process-based" models are generated using numerical models such as the Simulating Waves Nearshore (SWAN) model. We generated maps of wave metrics based on both fetch-based and process-based models and asked whether predictive performance in models of benthic marine habitats differed. Predictive models of seagrass distribution for Moreton Bay, Southeast Queensland, and Lizard Island, Great Barrier Reef, Australia, were generated using maps based on each type of wave model. For Lizard Island, performance of the process-based wave maps was significantly better for describing the presence of seagrass, based on Hs, Tp, and URMS. Conversely, for the predictive model of seagrass in Moreton Bay, based on benthic light availability and Hs, there was no difference in performance using the maps of the different wave metrics. For predictive models where wave metrics are the dominant factor determining ecological processes it is recommended that process-based models be used. Our results suggest that for models where wave metrics provide secondarily useful information, either fetch- or process-based models may be equally useful.

MicroRNA signatures differentiate preserved from reduced ejection fraction heart failure

AIMS: Differentiation of heart failure with reduced (HFrEF) or preserved (HFpEF) ejection fraction independent of echocardiography is challenging in the community. Diagnostic strategies based on monitoring circulating microRNA (miRNA) levels may prove to be of clinical value in the near future. The aim of this study was to identify a novel miRNA signature that could be a useful HF diagnostic tool and provide valuable clinical information on whether a patient has HFrEF or HFpEF.

METHODS AND RESULTS: MiRNA biomarker discovery was carried out on three patient cohorts, no heart failure (no-HF), HFrEF, and HFpEF, using Taqman miRNA arrays. The top five miRNA candidates were selected based on differential expression in HFpEF and HFrEF (miR-30c, -146a, -221, -328, and -375), and their expression levels were also different between HF and no-HF. These selected miRNAs were further verified and validated in an independent cohort consisting of 225 patients. The discriminative value of BNP as a HF diagnostic could be improved by use in combination with any of the miRNA candidates alone or in a panel. Combinations of two or more miRNA candidates with BNP had the ability to improve significantly predictive models to distinguish HFpEF from HFrEF compared with using BNP alone (area under the receiver operating characteristic curve >0.82).

CONCLUSION: This study has shown for the first time that various miRNA combinations are useful biomarkers for HF, and also in the differentiation of HFpEF from HFrEF. The utility of these biomarker combinations can be altered by inclusion of natriuretic peptide. MiRNA biomarkers may support diagnostic strategies in subpopulations of patients with HF.

Enabling Provenance on the Web: Standardization and Research Questions

Provenance is a record that describes the people, institutions, entities, and activities, involved in producing, influencing, or delivering a piece of data or a thing in the world. Some 10 years after beginning research on the topic of provenance, I co-chaired the provenance working group at the World Wide Web Consortium. The working group published the PROV standard for provenance in 2013. In this talk, I will present some use cases for provenance, the PROV standard and some flagship examples of adoption. I will then move on to our current research area aiming to exploit provenance, in the context of the Sociam, SmartSociety, ORCHID projects. Doing so, I will present techniques to deal with large scale provenance, to build predictive models based on provenance, and to analyse provenance.

Understanding the impact of different cheese-making strategies on Mozzarella cheese properties

Le fromage Mozzarella entre dans la composition de plusieurs mets populaires d’Amérique du Nord. L’aptitude de ce fromage à être râpé et ses propriétés caractéristiques de cuisson en font un ingrédient idéal. Ces qualités sont attribuées principalement aux propriétés physiques particulières de ce fromage sous certaines conditions de cisaillement et de température. Le but de ce projet était d’évaluer l’impact de différentes stratégies couramment mises en oeuvre dans l’industrie fromagère sur la composition, la microstructure et les propriétés physiques du fromage. Diverses stratégies ont été étudiées : les conditions de filage du caillé lors du procédé de « pasta filata », l’addition de protéines sériques dénaturées, le contrôle de la minéralisation et le vieillissement du fromage. Les résultats ont démontré que le contrôle de l’intensité mécanique et thermique fournie lors du filage permettait respectivement de réduire les pertes de solides et d’améliorer la répartition de la phase aqueuse dans la matrice fromagère. L’aptitude au râpage du fromage peut être optimisée en combinant l’utilisation de plusieurs stratégies dont la réduction du calcium colloïdal, un temps de vieillissement adéquat et un râpage à basse température. Par ailleurs, des changements aux facteurs mentionnés précédemment sont apportés lors de l’ajout de protéines sériques dénaturées, ces dernières ayant un impact sur la composition et la structure du fromage. Des modèles prédictifs de l’aptitude au râpage ont été développés en sélectionnant uniquement les descripteurs de composition et de texture pertinents. La perception sensorielle du fromage cuit sur pizza et les propriétés physiques du fromage fondu ont été considérablement influencées par l’évolution physico-chimique du fromage au cours du vieillissement. L’utilisation d’une nouvelle approche pour la caractérisation des propriétés rhéologiques du fromage fondu sous fortes contraintes a permis d’établir de bonnes relations avec les descripteurs sensoriels de texture. Ce travail a permis de valider l’hypothèse que l’utilisation d’une ou plusieurs stratégies simples et accessibles pouvait être mise de l’avant afin d’optimiser les propriétés physiques du fromage Mozzarella. Cela contribue à une meilleure compréhension des facteurs pouvant être contrôlés afin de développer des fromages avec des attributs spécifiques, lorsqu’utilisés comme ingrédient.

Socioeconomic Status and Health Behavior in Nepal

Thesis (Master's)--University of Washington, 2016-07

Flavour symmetries in a renormalizable SO(10) model

In the context of a renormalizable supersymmetric SO(10) Grand Unified Theory, we consider the fermion mass matrices generated by the Yukawa couplings to a 10 circle plus 120 circle plus (126) over bar representation of scalars. We perform a complete investigation of the possibilities of imposing flavour symmetries in this scenario; the purpose is to reduce the number of Yukawa coupling constants in order to identify potentially predictive models. We have found that there are only 14 inequivalent cases of Yukawa coupling matrices, out of which 13 cases are generated by 74 symmetries, with suitable n, and one case is generated by a Z(2) x Z(2) symmetry. A numerical analysis of the 14 cases reveals that only two of them-dubbed A and B in the present paper allow good fits to the experimentally known fermion masses and mixings. (C) 2016 The Authors. Published by Elsevier B.V.

Análise bioclimática do bairro do Renascença II São Luis-MA: realidade e perspectiva do conforto térmico em espaços externos

The present research concerns about outdoor s thermal comfort conditions in hot-humid climate cities, understanding that life quality is a result of the urban object s type built for the human being in an environment with specific climate and morphological characteristics. It is presented as object of study the correlation between the neighborhood Renascença II s microclimate in São Luis /MA-Brazil, hot-humid climate city, and its urban morphological changes. As well as the thermal comfort s satisfaction level of its outdoor users. The research has as general goal to diagnosis the way these transformations caused by the urbanization influence the Renascença II s microclimate, identifying critical spots of the studied area, in order to contribute with land use recommendations based on bioclimatic architecture concepts and supply bases to urban design decisions adequate to the São Luis climate. It is presented as theoretical bases the urban climate, its concepts and elements. After that, the thermal comfort conditioners and its prediction models of thermal comfort sensation in outdoor are presented. The predictive models are presented along with bioclimatic assessment methods. Finally the use of bioclimatic assessment as an effective tool to identify places that need changes or preservation in order to seek environment quality. The applied methodology was based on the studies of Katzschner (1997), complemented by Oliveira s (1988) and Bustos Romero s (2001) studies that suggest an analysis and evaluation of maps of topography, buildings floors, land use, green areas and land covering, in order to overlap their characteristics and identify climate variable s measurements points; then a quantitative analysis of the climate variables (air temperature and humidity, wind speed and direction) of the chosen points takes place. It was perceived that Renaissance II has no permanence areas as squares or parks, its outdoor has little vegetation and presets high land impermeability and built density levels. The majority of the people interviewed said that was comfortable in a range of air temperature between 27,28ºC and 30,71ºC. The elaboration of a neighborhood master plan is important, which defines strategies for improvement of the life quality of its inhabitants

Forecasting exchange rates in the presence of instabilities

Many exchange rate papers articulate the view that instabilities constitute a major impediment to exchange rate predictability. In this thesis we implement Bayesian and other techniques to account for such instabilities, and examine some of the main obstacles to exchange rate models' predictive ability. We first consider in Chapter 2 a time-varying parameter model in which fluctuations in exchange rates are related to short-term nominal interest rates ensuing from monetary policy rules, such as Taylor rules. Unlike the existing exchange rate studies, the parameters of our Taylor rules are allowed to change over time, in light of the widespread evidence of shifts in fundamentals - for example in the aftermath of the Global Financial Crisis. Focusing on quarterly data frequency from the crisis, we detect forecast improvements upon a random walk (RW) benchmark for at least half, and for as many as seven out of 10, of the currencies considered. Results are stronger when we allow the time-varying parameters of the Taylor rules to differ between countries. In Chapter 3 we look closely at the role of time-variation in parameters and other sources of uncertainty in hindering exchange rate models' predictive power. We apply a Bayesian setup that incorporates the notion that the relevant set of exchange rate determinants and their corresponding coefficients, change over time. Using statistical and economic measures of performance, we first find that predictive models which allow for sudden, rather than smooth, changes in the coefficients yield significant forecast improvements and economic gains at horizons beyond 1-month. At shorter horizons, however, our methods fail to forecast better than the RW. And we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients variability to incorporate in the models, as the main factors obstructing predictive ability. Chapter 4 focus on the problem of the time-varying predictive ability of economic fundamentals for exchange rates. It uses bootstrap-based methods to uncover the time-specific conditioning information for predicting fluctuations in exchange rates. Employing several metrics for statistical and economic evaluation of forecasting performance, we find that our approach based on pre-selecting and validating fundamentals across bootstrap replications generates more accurate forecasts than the RW. The approach, known as bumping, robustly reveals parsimonious models with out-of-sample predictive power at 1-month horizon; and outperforms alternative methods, including Bayesian, bagging, and standard forecast combinations. Chapter 5 exploits the predictive content of daily commodity prices for monthly commodity-currency exchange rates. It builds on the idea that the effect of daily commodity price fluctuations on commodity currencies is short-lived, and therefore harder to pin down at low frequencies. Using MIxed DAta Sampling (MIDAS) models, and Bayesian estimation methods to account for time-variation in predictive ability, the chapter demonstrates the usefulness of suitably exploiting such short-lived effects in improving exchange rate forecasts. It further shows that the usual low-frequency predictors, such as money supplies and interest rates differentials, typically receive little support from the data at monthly frequency, whereas MIDAS models featuring daily commodity prices are highly likely. The chapter also introduces the random walk Metropolis-Hastings technique as a new tool to estimate MIDAS regressions.

O equilíbrio entre o trabalho e a vida privada: A adequação das práticas organizacionais às necessidades dos trabalhadores

Dissertação de Mestrado apresentada ao ISPA - Instituto Universitário