931 resultados para multiple linear regression analysis


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High saturated and trans fatty acid intake, the typical dietary pattern of Western populations, favors a proinflammatory status that contributes to generating insulin resistance (IR). We examined whether the consumption of these fatty acids was associated with IR and inflammatory markers. In this cross-sectional study, 127 non-diabetic individuals were allocated to a group without IR and 56 to another with IR, defined as homeostasis model assessment-IR (HOMA-IR) >2.71. Diet was assessed using 24-h food recalls. Multiple linear regression was employed to test independent associations with HOMA-IR. The IR group presented worse anthropometric, biochemical and inflammatory profiles. Energy intake was correlated with abdominal circumference and inversely with adiponectin concentrations (r = -0.227, P = 0.002), while saturated fat intake correlated with inflammatory markers and trans fat with HOMA-IR (r = 0.160, P = 0.030). Abdominal circumference was associated with HOMA-IR (r = 0.430, P < 0.001). In multiple analysis, HOMA-IR remained associated with trans fat intake (β = 1.416, P = 0.039) and body mass index (β = 0.390, P < 0.001), and was also inversely associated with adiponectin (β = -1.637, P = 0.004). Inclusion of other nutrients (saturated fat and added sugar) or other inflammatory markers (IL-6 and CRP) into the models did not modify these associations. Our study supports that trans fat intake impairs insulin sensitivity. The hypothesis that its effect could depend on transcription factors, resulting in expression of proinflammatory genes, was not corroborated. We speculate that trans fat interferes predominantly with insulin signaling via intracellular kinases, which alter insulin receptor substrates.

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Ordered probit regression was used to analyze data of sensory acceptance tests designed to study the effect of brand name on the acceptability of beer samples. Eight different brands of Pilsen beer were evaluated by 101 consumers in two sessions of acceptance tests: blind evaluation and brand information test. Ordered probit regression, although a relatively sophisticated technique compared to others used to analyze sensory data, was chosen to enable the observation of consumers' behavior using graphical interpretations of estimated probabilities plotted against hedonic scales. It can be concluded that brands B, C, and D had a positive effect on the sensory acceptance of the product, whereas brands A, F, G, and H had a negative influence on consumers' evaluation of the samples. On the other hand, brand E had little influence on consumers' assessment.

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This study developed a gluten-free granola and evaluated it during storage with the application of multivariate and regression analysis of the sensory and instrumental parameters. The physicochemical, sensory, and nutritional characteristics of a product containing quinoa, amaranth and linseed were evaluated. The crude protein and lipid contents ranged from 97.49 and 122.72 g kg-1 of food, respectively. The polyunsaturated/saturated, and n-6:n-3 fatty acid ratios ranged from 2.82 and 2.59:1, respectively. Granola had the best alpha-linolenic acid content, nutritional indices in the lipid fraction, and mineral content. There were good hygienic and sanitary conditions during storage; probably due to the low water activity of the formulation, which contributed to inhibit microbial growth. The sensory attributes ranged from 'like very much' to 'like slightly', and the regression models were highly fitted and correlated during the storage period. A reduction in the sensory attribute levels and in the product physical stabilisation was verified by principal component analysis. The use of the affective test acceptance and instrumental analysis combined with statistical methods allowed us to obtain promising results about the characteristics of gluten-free granola.

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Les antipsychotiques (APs) sont fréquemment prescrits pour les troubles comportementaux associés à la démence. Or, ces produits ont fait l'objet de trois mises en garde (2002, 2004, 2005) en raison d'une augmentation du risque d'événement cérébrovasculaire et de décès. L’objectif de ce mémoire est d’évaluer l'utilisation d’APs dans la population de personnes âgées démentes vivant à domicile, et de déterminer l’effet des mises en garde sur les profils observés. Une cohorte rétrospective de 10,969 personnes âgées démentes ayant débuté un traitement par AP entre le 1er janvier 2000 et le 31 décembre 2009 fut identifiée à partir des banques de données de la Régie de l'assurance maladie du Québec (RAMQ). Des séries chronologiques segmentées ont permis de quantifier l’effet des mises en garde sur l'utilisation d’APs. L'effet de la mise en garde de 2005 sur les caractéristiques des patients traités ainsi que sur les profils d'utilisation (dose et durée) a été évalué, respectivement par des modèles de régression logistique et de régression linéaire multivariés. Le taux délivrance d'APs atypiques a augmenté au cours du temps jusqu'à la mise en garde de 2005 pour ensuite diminuer de 8.96% (IC 95% : -11.91% – -6.02%). L'analyse par produit a révélé la même tendance pour la rispéridone, le seul AP approuvé au Canada pour les personnes âgées démentes. En revanche, le taux de délivrance de quétiapine, qui est hors-indication, a continué d'augmenter. Le taux d'initiation de traitement par APs a cependant diminué au cours du temps pour tous les produits. Les mises en garde ne semblent pas être associées avec un changement dans les caractéristiques des patients traités, ni avec les doses et durées d’utilisation. Le manque d'efficacité des mises en garde est probablement en partie lié à l'absence d'alternatives thérapeutiques pour le traitement des troubles psychologiques et comportementaux chez les patients atteints de démence.

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Dans une turbine hydraulique, la rotation des aubes dans l’eau crée une zone de basse pression, amenant l’eau à passer de l’état liquide à l’état gazeux. Ce phénomène de changement de phase est appelé cavitation et est similaire à l’ébullition. Lorsque les cavités de vapeur formées implosent près des parois, il en résulte une érosion sévère des matériaux, accélérant de façon importante la dégradation de la turbine. Un système de détection de l’érosion de cavitation à l’aide de mesures vibratoires, employable sur les turbines en opération, a donc été installé sur quatre groupes turbine-alternateur d’une centrale et permet d’estimer précisément le taux d’érosion en kg/ 10 000 h. Le présent projet vise à répondre à deux objectifs principaux. Premièrement, étudier le comportement de la cavitation sur un groupe turbine-alternateur cible et construire un modèle statistique, dans le but de prédire la variable cavitation en fonction des variables opératoires (tels l’ouverture de vannage, le débit, les niveaux amont et aval, etc.). Deuxièmement, élaborer une méthodologie permettant la reproductibilité de l’étude à d’autres sites. Une étude rétrospective sera effectuée et on se concentrera sur les données disponibles depuis la mise à jour du système en 2010. Des résultats préliminaires ont mis en évidence l’hétérogénéité du comportement de cavitation ainsi que des changements entre la relation entre la cavitation et diverses variables opératoires. Nous nous proposons de développer un modèle probabiliste adapté, en utilisant notamment le regroupement hiérarchique et des modèles de régression linéaire multiple.

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Contexte: L’arthrite juvénile idiopathique (AJI) est l’une des maladies chroniques auto-immune les plus répandues chez les enfants et est caractérisée par des enflures articulaires (maladie active), de la douleur, de la fatigue et des raideurs matinales pouvant restreindre leur niveau de participation aux activités quotidiennes (par exemple: les loisirs, l’activité physique, la mobilité et les soins personnels) à la maison comme à l’école. Participer aux activités de loisirs et à l’activité physique a des bienfaits au niveau de la santé et du développement de tous les enfants et démontrent aussi des effets positifs qui réduisent les symptômes des maladies chroniques telle l’AJI. Malgré ces bienfaits la participation aux loisirs chez les jeunes avec l’AJI demeure largement sous-étudiée. Objectifs: Cette étude vise à évaluer le niveau de participation aux loisirs et à l’activité physique chez les enfants et les adolescents atteints d’AJI, ainsi qu’à identifier les facteurs liés à la maladie, la personne et l’environnement. Méthodes : L’évaluation du niveau de participation et l’exploration des facteurs associés aux loisirs et à l’activité physique ont été complétés par l’entremise d’une revue systématique de la littérature, l’analyse de données d’un échantillon national représentatif d’enfants canadiens atteints d’arthrite âgés entre 5 et 14 ans (npondéré = 4350), ainsi que l’analyse standardisée du niveau de participation aux loisirs à l’aide du Children’s Assessment of Participation and Enjoyment (n=107) et la mesure objective de l’activité physique par accéléromètre (n=76) auprès d’un échantillon d’enfants (âgés entre 8 et 11 ans ) et d’adolescents (âgés entre 12 et 17 ans) suivis en clinique de rhumatologie à l’hôpital de Montréal pour enfants, Centre Universitaire de Santé McGill. Les résultats cliniques ont été comparés à des données normatives, ainsi qu’à un groupe contrôle sans AJI. Nous avons exploré les facteurs associés avec le niveau de participation aux loisirs et à l’activité physique en utilisant les modèles de régression linéaire multiple et l’analyse hiérarchique. Résultats : Les enfants et les adolescents atteints d’AJI participent à une multitude d’activités de loisirs; cependant ils sont moins souvent impliqués dans des activités physiques et de raffinement en comparaison aux autres types d’activités de loisirs. Ceux avec l’AJI étaient en général moins actifs que leurs pairs sans arthrite et la plupart n’atteignaient pas les recommandations nationales d’activité physique. Les garçons avec l’AJI participent plus souvent à des activités physiques et moins aux activités sociales, de raffinement et de développement de soi en comparaison avec les filles ayant l’AJI. En général, être un garçon, être plus âgé, avoir une meilleure motivation pour participer aux activités de motricité globale, avoir un statut socio-économique plus élevé et être d’origine culturelle canadienne sont associés à un niveau de participation plus élevé aux activités physiques. La préférence pour les activités de raffinement, un niveau d’éducation maternelle plus élevé et être une fille étaient associés à un niveau de participation plus élevé aux activités de raffinement. Conclusion: La participation aux loisirs et à l’activité physique en AJI est un concept complexe et semble surtout être expliqué par des facteurs personnels et environnementaux. L’identification des facteurs associés aux loisirs et à l’activité physique est très importante en AJI puisqu’elle peut permettre aux professionnels de la santé de développer des interventions significatives basées sur les activités préférées des enfants, améliorer l’observance au traitement et promouvoir des habitudes de vie saine.

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Summary: Productivity, botanical composition and forage quality of legume-grass swards are important factors for successful arable farming in both organic and conventional farming systems. As these attributes can vary considerably within a field, a non-destructive method of detection while doing other tasks would facilitate a more targeted management of crops, forage and nutrients in the soil-plant-animal system. This study was undertaken to explore the potential of field spectral measurements for a non destructive prediction of dry matter (DM) yield, legume proportion in the sward, metabolizable energy (ME), ash content, crude protein (CP) and acid detergent fiber (ADF) of legume-grass mixtures. Two experiments were conducted in a greenhouse under controlled conditions which allowed collecting spectral measurements which were free from interferences such as wind, passing clouds and changing angles of solar irradiation. In a second step this initial investigation was evaluated in the field by a two year experiment with the same legume-grass swards. Several techniques for analysis of the hyperspectral data set were examined in this study: four vegetation indices (VIs): simple ratio (SR), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and red edge position (REP), two-waveband reflectance ratios, modified partial least squares (MPLS) regression and stepwise multiple linear regression (SMLR). The results showed the potential of field spectroscopy and proved its usefulness for the prediction of DM yield, ash content and CP across a wide range of legume proportion and growth stage. In all investigations prediction accuracy of DM yield, ash content and CP could be improved by legume-specific calibrations which included mixtures and pure swards of perennial ryegrass and of the respective legume species. The comparison between the greenhouse and the field experiments showed that the interaction between spectral reflectance and weather conditions as well as incidence angle of light interfered with an accurate determination of DM yield. Further research is hence needed to improve the validity of spectral measurements in the field. Furthermore, the developed models should be tested on varying sites and vegetation periods to enhance the robustness and portability of the models to other environmental conditions.

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The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.

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Introducción: El Aislamiento de Venas Pulmonares (AVP) es un procedimiento de alto costo al cual son sometidos pacientes con riesgo cardiovascular elevado. Requiere un alto grado de especialización en el personal médico y paramédico que lo ejecuta, con curvas de aprendizaje que sobrepasan los dos años de formación académica y entrenamiento específico. Metodología: Se realizó un estudio de cohorte retrospectivo, donde se incluyeron 88 sujetos sometidos al procedimiento en el lapso comprendido entre el 1º de enero y el 31 de diciembre de 2013, con el objetivo de evaluar su proceso de atención en el Centro Internacional de Arritmias ‘Andrea Natale’ de la FCI – Instituto de Cardiología. Se realizó análisis de regresión lineal y logística múltiple. Resultados: Se encontró que en el 97,73%% de los pacientes el diagnóstico principal era algún tipo de Fibrilación Auricular (FA); a su vez, la comorbilidad más frecuente fue HTA en el 30,68% y ningún paciente presentaba enfermedad coronaria, no hubo diferencias significativas por sexo. La complicación peri operatoria tuvo una incidencia del 3,41%, el 22,73% requirió ingreso a UCI con un promedio de días estancia 0,25+0,51. El 98,86% de la población estudiada recibió educación pos procedimiento acerca de sus cuidados y signos de alarma. Los factores encontrados en el estudio que afectan la duración del procedimiento y la estancia hospitalaria son las interconsultas pre procedimiento, el manejo médico de la cardiomiopatía de base y el uso de anti agregantes plaquetarios pre procedimiento; los cuales, son puntos por mejorar previo al ingreso o programación del paciente para ser llevado a AVP. Discusión: Como recomendaciones específicas se destacan: La necesidad de incluir en el protocolo de preparación para ablación de venas pulmonares la realización de interconsultas a las especialidades requeridas, antes de su ingreso para la realización del procedimiento. Es importante que el paciente que lo amerite haga parte de un programa de falla cardiaca previamente al procedimiento

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Suprathermal electrons (E > 80 eV) carry heat flux away from the Sun. Processes controlling the heat flux are not well understood. To gain insight into these processes, we model heat flux as a linear dependence on two independent parameters: electron number flux and electron pitch angle anisotropy. Pitch angle anisotropy is further modeled as a linear dependence on two solar wind components: magnetic field strength and plasma density. These components show no correlation with number flux, reinforcing its independence from pitch angle anisotropy. Multiple linear regression applied to 2 years of Wind data shows good correspondence between modeled and observed heat flux and anisotropy. The results suggest that the interplay of solar wind parameters and electron number flux results in distinctive heat flux dropouts at heliospheric features like plasma sheets but that these parameters continuously modify heat flux. This is inconsistent with magnetic disconnection as the primary cause of heat flux dropouts. Analysis of fast and slow solar wind regimes separately shows that electron number flux and pitch angle anisotropy are equally correlated with heat flux in slow wind but that number flux is the dominant correlative in fast wind. Also, magnetic field strength correlates better with pitch angle anisotropy in slow wind than in fast wind. The energy dependence of the model fits suggests different scattering processes in fast and slow wind.

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A range of funding schemes and policy instruments exist to effect enhancement of the landscapes and habitats of the UK. While a number of assessments of these mechanisms have been conducted, little research has been undertaken to compare both quantitatively and qualitatively their relative effectiveness across a range of criteria. It is argued that few tools are available for such a multi-faceted evaluation of effectiveness. A form of Multiple Criteria Decision Analysis (MCDA) is justified and utilized as a framework in which to evaluate the effectiveness of nine mechanisms in relation to the protection of existing areas of chalk grassland and the creation of new areas in the South Downs of England. These include established schemes, such as the Countryside Stewardship and Environmentally Sensitive Area Schemes, along with other less common mechanisms, for example, land purchase and tender schemes. The steps involved in applying an MCDA to evaluate such mechanisms are identified and the process is described. Quantitative results from the comparison of the effectiveness of different mechanisms are presented, although the broader aim of the paper is that of demonstrating the performance of MCDA as a tool for measuring the effectiveness of mechanisms aimed at landscape and habitat enhancement.

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Multiple linear regression is used to diagnose the signal of the 11-yr solar cycle in zonal-mean zonal wind and temperature in the 40-yr ECMWF Re-Analysis (ERA-40) dataset. The results of previous studies are extended to 2008 using data from ECMWF operational analyses. This analysis confirms that the solar signal found in previous studies is distinct from that of volcanic aerosol forcing resulting from the eruptions of El Chichón and Mount Pinatubo, but it highlights the potential for confusion of the solar signal and lower-stratospheric temperature trends. A correction to an error that is present in previous results of Crooks and Gray, stemming from the use of a single daily analysis field rather than monthly averaged data, is also presented.