970 resultados para mean-variance estimation
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Various host-related factors have been reported as relevant risk factors for leprosy reactions. To support a new hypothesis that an antigenic load in local tissues that is sufficient to trigger the immune response may come from an external supply of Mycobacterium leprae organisms, the prevalence of reactional leprosy was assessed against the number of household contacts. The number of contacts was ascertained at diagnosis in leprosy patients coming from an endemic area of Brazil. The prevalence of reactions (patients with reactions/total patients) was fitted by binomial regression and the risk difference (RD) was estimated with a semi-robust estimation of variance as a measure of effect. Five regression models were fitted. Model 1 included only the main exposure variable "number of household contacts"; model 2 included all four explanatory variables ("contacts", "fertile age", "number of skin lesions" and "bacillary index") that were found to be associated with the outcome upon univariate analysis; models 3-5 contained various combinations of three predictors. Male and female patients were analyzed separately. In females, household contacts were a significant predictor for leprosy reactions in model 1 [crude RD = 0.06; 95% confidence interval (CI) = 0.01; 0.12] and model 5 (RD = 0.05; CI = 0.02; 0.09), which included contacts, bacillary index and skin lesions as predictors. Other models were unsatisfactory because the joint presence of fertile age and bacillary index was a likely source of multicollinearity. No significant results were obtained for males. The likely interpretation of our findings might suggest that in female patients, leprosy reactions may be triggered by an external spreading of M. leprae by healthy carrier family members. The small number of observations is an obvious limitation of our study which requires larger confirmatory studies.
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Understanding the distribution and composition of species assemblages and being able to predict them in space and time are highly important tasks io investigate the fate of biodiversity in the current global changes context. Species distribution models are tools that have proven useful to predict the potential distribution of species by relating their occurrences to environmental variables. Species assemblages can then be predicted by combining the prediction of individual species models. In the first part of my thesis, I tested the importance of new environmental predictors to improve species distribution prediction. I showed that edaphic variables, above all soil pH and nitrogen content could be important in species distribution models. In a second chapter, I tested the influence of different resolution of predictors on the predictive ability of species distribution models. I showed that fine resolution predictors could ameliorate the models for some species by giving a better estimation of the micro-topographic condition that species tolerate, but that fine resolution predictors for climatic factors still need to be ameliorated. The second goal of my thesis was to test the ability of empirical models to predict species assemblages' characteristics such as species richness or functional attributes. I showed that species richness could be modelled efficiently and that the resulting prediction gave a more realistic estimate of the number of species than when obtaining it by stacking outputs of single species distribution models. Regarding the prediction of functional characteristics (plant height, leaf surface, seed mass) of plant assemblages, mean and extreme values of functional traits were better predictable than indices reflecting the diversity of traits in the community. This approach proved interesting to understand which environmental conditions influence particular aspects of the vegetation functioning. It could also be useful to predict climate change impacts on the vegetation. In the last part of my thesis, I studied the capacity of stacked species distribution models to predict the plant assemblages. I showed that this method tended to over-predict the number of species and that the composition of the community was not predicted exactly either. Finally, I combined the results of macro- ecological models obtained in the preceding chapters with stacked species distribution models and showed that this approach reduced significantly the number of species predicted and that the prediction of the composition is also ameliorated in some cases. These results showed that this method is promising. It needs now to be tested on further data sets. - Comprendre la manière dont les plantes se répartissent dans l'environnement et s'organisent en communauté est une question primordiale dans le contexte actuel de changements globaux. Cette connaissance peut nous aider à sauvegarder la diversité des espèces et les écosystèmes. Des méthodes statistiques nous permettent de prédire la distribution des espèces de plantes dans l'espace géographique et dans le temps. Ces modèles de distribution d'espèces, relient les occurrences d'une espèce avec des variables environnementales pour décrire sa distribution potentielle. Cette méthode a fait ses preuves pour ce qui est de la prédiction d'espèces individuelles. Plus récemment plusieurs tentatives de cumul de modèles d'espèces individuelles ont été réalisées afin de prédire la composition des communautés végétales. Le premier objectif de mon travail est d'améliorer les modèles de distribution en testant l'importance de nouvelles variables prédictives. Parmi différentes variables édaphiques, le pH et la teneur en azote du sol se sont avérés des facteurs non négligeables pour prédire la distribution des plantes. Je démontre aussi dans un second chapitre que les prédicteurs environnementaux à fine résolution permettent de refléter les conditions micro-topographiques subies par les plantes mais qu'ils doivent encore être améliorés avant de pouvoir être employés de manière efficace dans les modèles. Le deuxième objectif de ce travail consistait à étudier le développement de modèles prédictifs pour des attributs des communautés végétales tels que, par exemple, la richesse en espèces rencontrée à chaque point. Je démontre qu'il est possible de prédire par ce biais des valeurs de richesse spécifiques plus réalistes qu'en sommant les prédictions obtenues précédemment pour des espèces individuelles. J'ai également prédit dans l'espace et dans le temps des caractéristiques de la végétation telles que sa hauteur moyenne, minimale et maximale. Cette approche peut être utile pour comprendre quels facteurs environnementaux promeuvent différents types de végétation ainsi que pour évaluer les changements à attendre au niveau de la végétation dans le futur sous différents régimes de changements climatiques. Dans une troisième partie de ma thèse, j'ai exploré la possibilité de prédire les assemblages de plantes premièrement en cumulant les prédictions obtenues à partir de modèles individuels pour chaque espèce. Cette méthode a le défaut de prédire trop d'espèces par rapport à ce qui est observé en réalité. J'ai finalement employé le modèle de richesse en espèce développé précédemment pour contraindre les résultats du modèle d'assemblage de plantes. Cela a permis l'amélioration des modèles en réduisant la sur-prédiction et en améliorant la prédiction de la composition en espèces. Cette méthode semble prometteuse mais de nouveaux tests sont nécessaires pour bien évaluer ses capacités.
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BACKGROUND Several questionnaires have been used to measure health related quality of life (HRQoL) in patients with psoriasis, few have been adapted for use in Spain; none of them was developed specifically for the Spanish population. The purpose of the study was to validate and assess the sensitivity to change of a new questionnaire to measure HRQOL in patients with psoriasis (PSO-LIFE). METHODS Observational, prospective, multicenter study performed in centers around Spain. Patients with active or inactive psoriasis completed the PSO-LIFE together with other Dermatology Quality of Life Index (DLQI) and Psoriasis Disability Index (PDI). A control group of patients with urticaria or atopic dermatitis was also included. Internal consistency and test-retest reliability of the PSO-LIFE were assessed by calculating Cronbach's alpha and Intraclass Correlation Coefficient (ICC). Validity was assessed by examining factorial structure, the capacity to discriminate between groups, and correlations with other measures. Sensitivity to change was measured using effect sizes. RESULTS The final sample included for analysis consisted of 304 patients and 56 controls. Mean (SD) age of psoriasis patients was 45.3 (14.5) years compared to 38.8 (14) years for controls (p < 0.01). Cronbach's alpha for the PSO-LIFE was 0.95 and test-retest reliability using the ICC was 0.98. Factor analysis showed the questionnaire to be unidimensional. Mean (SD) PSO-LIFE scores differed between patients with psoriasis and controls (64.9 [22.5] vs 69.4 [17.3]; p < 0.05), between those with active and inactive disease (57.4 [20.4] vs 76.4 [20.6]; p < 0.01), and between those with visible and non-visible lesions (63.0 [21.9] vs. 74.8 [23.9]; p < 0.01). The correlation between PSO-LIFE and PASI scores was moderate (r = -0.43) while correlations with DLQI and PDI dimensions ranged from moderate to high (between 0.4 and 0.8). Effect size on the PSO-LIFE in patients reporting 'much improved' health status at study completion was 1.01 (large effect size). CONCLUSIONS The present results provide substantial support for the reliability, validity, and responsiveness of the PSO-LIFE questionnaire in the population for which it was designed.
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Over the past decade, significant interest has been expressed in relating the spatial statistics of surface-based reflection ground-penetrating radar (GPR) data to those of the imaged subsurface volume. A primary motivation for this work is that changes in the radar wave velocity, which largely control the character of the observed data, are expected to be related to corresponding changes in subsurface water content. Although previous work has indeed indicated that the spatial statistics of GPR images are linked to those of the water content distribution of the probed region, a viable method for quantitatively analyzing the GPR data and solving the corresponding inverse problem has not yet been presented. Here we address this issue by first deriving a relationship between the 2-D autocorrelation of a water content distribution and that of the corresponding GPR reflection image. We then show how a Bayesian inversion strategy based on Markov chain Monte Carlo sampling can be used to estimate the posterior distribution of subsurface correlation model parameters that are consistent with the GPR data. Our results indicate that if the underlying assumptions are valid and we possess adequate prior knowledge regarding the water content distribution, in particular its vertical variability, this methodology allows not only for the reliable recovery of lateral correlation model parameters but also for estimates of parameter uncertainties. In the case where prior knowledge regarding the vertical variability of water content is not available, the results show that the methodology still reliably recovers the aspect ratio of the heterogeneity.
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This study compared the Spanish (Castilian) and French versions of the 16PF5 and of the NEO-PI-R in Spanish and Swiss samples. The five-factor solution for the 16PF5 only seems clear for the Castilian version, but not for the French version. Indeed, the congruence coefficients for the Tough-Mindedness and the Self-Control dimensions are low. On the other hand, the five-factor solutions are highly similar for both countries concerning the NEO-PI-R, and the congruence coefficients are above .95 for all five dimensions. The low cross-cultural replicability for the 16PF5 makes it difficult to analyze the differences at the mean level for this inventory. For the NEO-PI-R, the differences are generally very small and globally account for 2.6% of the total variance. Spaniards seem to have slightly lower scores on Actions and slightly higher scores on Dutifulness. These differences could either be due to translation problems, sample selection, or cultural differences.
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The present study examines the Five-Factor Model (FFM) of personality and locus of control in French-speaking samples in Burkina Faso (N = 470) and Switzerland (Ns = 1,090, 361), using the Revised NEO Personality Inventory (NEO-PI-R) and Levenson's Internality, Powerful others, and Chance (IPC) scales. Alpha reliabilities were consistently lower in Burkina Faso, but the factor structure of the NEO-PI-R was replicated in both cultures. The intended three-factor structure of the IPC could not be replicated, although a two-factor solution was replicable across the two samples. Although scalar equivalence has not been demonstrated, mean level comparisons showed the hypothesized effects for most of the five factors and locus of control; Burkinabè scored higher in Neuroticism than anticipated. Findings from this African sample generally replicate earlier results from Asian and Western cultures, and are consistent with a biologically-based theory of personality.
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Most people hold beliefs about personality characteristics typical members of their own and others' cultures. These perceptions of national character may be generalizations from personal experience, stereotypes with a "kernel of truth", or inaccurate stereotypes. We obtained national character ratings of 3989 people from 49 cultures and compared them with the average personality scores of culture members assessed by observer ratings and self-reports. National character ratings were reliable but did not converge with assessed traits. Perceptions of national character thus appear to be unfounded stereotypes that may serve the function of maintaining a national identity.
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En aquest treball, es proposa un nou mètode per estimar en temps real la qualitat del producte final en processos per lot. Aquest mètode permet reduir el temps necessari per obtenir els resultats de qualitat de les anàlisi de laboratori. S'utiliza un model de anàlisi de componentes principals (PCA) construït amb dades històriques en condicions normals de funcionament per discernir si un lot finalizat és normal o no. Es calcula una signatura de falla pels lots anormals i es passa a través d'un model de classificació per la seva estimació. L'estudi proposa un mètode per utilitzar la informació de les gràfiques de contribució basat en les signatures de falla, on els indicadors representen el comportament de les variables al llarg del procés en les diferentes etapes. Un conjunt de dades compost per la signatura de falla dels lots anormals històrics es construeix per cercar els patrons i entrenar els models de classifcació per estimar els resultas dels lots futurs. La metodologia proposada s'ha aplicat a un reactor seqüencial per lots (SBR). Diversos algoritmes de classificació es proven per demostrar les possibilitats de la metodologia proposada.
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Decreasing perinatal morbidity and mortality is one of the main goals of obstetrics. Prognosis of preterm births depends on gestational age and birthweight. Multidisciplinary management is discussed with the parents according to these two parameters. In other circumstances, a suspected macrosomy will influence the management of the last weeks of pregnancy. Induction of labor or Cesarean delivery will be considered to avoid shoulder dystocia, brachial plexus injury or perinatal asphyxia. Birthweight needs to be estimated with accuracy, and this article describes the efficiency of various ultrasound weight estimation formulae for small and large fetuses.
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Visceral leishmaniasis, or kala-azar, is recognised as a serious emerging public health problem in India. In this study, environmental parameters, such as land surface temperature (LST) and renormalised difference vegetation indices (RDVI), were used to delineate the association between environmental variables and Phlebotomus argentipes abundance in a representative endemic region of Bihar, India. The adult P. argentipes were collected between September 2009-February 2010 using the hand-held aspirator technique. The distribution of P. argentipes was analysed with the LST and RDVI of the peak and lean seasons. The association between environmental covariates and P. argentipes density was analysed a multivariate linear regression model. The sandfly density at its maximum in September, whereas the minimum density was recorded in January. The regression model indicated that the season, minimum LST, mean LST and mean RDVI were the best environmental covariates for the P. argentipes distribution. The final model indicated that nearly 74% of the variance of sandfly density could be explained by these environmental covariates. This approach might be useful for mapping and predicting the distribution of P. argentipes, which may help the health agencies that are involved in the kala-azar control programme focus on high-risk areas.
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A ubiquitous assessment of swimming velocity (main metric of the performance) is essential for the coach to provide a tailored feedback to the trainee. We present a probabilistic framework for the data-driven estimation of the swimming velocity at every cycle using a low-cost wearable inertial measurement unit (IMU). The statistical validation of the method on 15 swimmers shows that an average relative error of 0.1 ± 9.6% and high correlation with the tethered reference system (rX,Y=0.91 ) is achievable. Besides, a simple tool to analyze the influence of sacrum kinematics on the performance is provided.
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Purpose: Iron overload (IO) has been associated with increased cardiovascular risk (CVR) and metabolic syndrome (MS) in the general population; both elevated CVR and MS are frequent in HIV- patients. Our aim was to analyze the prevalence of IO in a cohort of asymptomatic patients with HIV infection, and related factors. Methods: Cross-sectional study of a cohort of HIV outpatients in regular follow-up. Demographic, epidemiological, clinical, analytical and therapeutic data were collected. Patients completed a questionnaire about CVR factors and 10-year CV disease risk estimation (Framingham score), underwent a physical exam, and a fasting blood analysis. IO was defined as a plasma ferritin level higher than 200 m/L in women and 300 m/L in men. Results: 571 patients (446 men, 125 women), with a mean age of 43.2 years, sexual transmission of HIV in 68.5%, median CD4 count 474 cell/μL (IQR: 308-666), and 36.3% Aids cases 86.2% were on antiretroviral therapy (ART), and 74.8% of them had undetectable HIV viral load 14.6% met MS criteria, and mean CVR at 10 years was 6.67%. IO was detected in 11% of cases. Patients with IO were more immunosuppressed (CD4 count 369 vs 483/μL, p<0.0001), presented a higher prevalence of detectable HIV viral load (17.6% vs 8.9%; p<0.005), and of Aids cases (14.9% vs 8.7%; p<0.023), and lower plasma levels of cholesterol, HDLc and LDLc (154 vs 183, 34 vs 43, 93 vs 110 mg/dL, respectively; p<0.0001. In the multivariate analysis, the only related factor was CD4 count <350 cell/μL (OR 2.86, 95% CI 1.6-4.9; p<0.0001). IO was not associated with CVR nor with MS. Conclusions: IO is not uncommon in HIV patients, and it is only related with immunosuppression defined as CD4 count <350 cell/ mL, and in contrast to general population, it is not related with increased CVR nor with MS.
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A newly identified cytokine, osteoprotegerin (OPG) appears to be involved in the regulation of bone remodeling. In vitro studies suggest that OPG, a soluble member of the TNF receptor family of proteins, inhibits osteoclastogenesis by interrupting the intercellular signaling between osteoblastic stromal cells and osteoclast progenitors. As patients with chronic renal failure (CRF) often have renal osteodystrophy (ROD), we investigated the role of osteoprotegerin (OPG) in ROD, and investigated whether there was any relationship between serum OPG, intact parathyroid (PTH) (iPTH), vitamin D, and trabecular bone. Serum OPG combined with iPTH might be a useful tool in the noninvasive diagnosis of ROD, at least in cases in which the range of PTH values compromises reliable diagnosis. Thirty-six patients on maintenance hemodiafiltration (HDF) and a control group of 36 age and sex matched healthy subjects with no known metabolic bone disease were studied. The following assays were made on serum: iPTH, osteocalcin (BGP), bone alkaline phosphatase, 25(OH)-cholecalciferol, calcium, phosphate, OPG, IGF-1, estradiol, and free testosterone. Serum Ca++, P, B-ALP, BGP, IGF-1, iPTH, and OPG levels were significantly higher in HDF patients than in controls, while DXA measurements and quantitative ultrasound (QUS) parameters were significantly lower. On grouping patients according to their mean OPG levels, we observed significantly lower serum IGF-1, vitamin D3 concentrations, and lumbar spine and hip bone mineral density in the high OPG groups. No correlation was found between OPG and bone turnover markers, whereas a negative correlation was found between serum OPG and IGF-1 levels (r=-0.64, p=0.032). Serum iPTH concentrations were positively correlated with bone alkaline phosphatase (B-ALP) (r=0.69, p=0.038) and BGP (r=0.92, p<0.001). The findings made suggest that an increase in OPG levels may be a compensatory response to elevated bone loss. The low bone mineral density (BMD) levels found in the high OPG group might have been due to the significant decrease in serum IGF-1 and vitamin D3 observed. In conclusion, the findings made in the present study demonstrate that increased OPG in hemodiafiltration patients is only partly due to decreased renal clearance. As it may partly reflect a compensatory response to increased bone loss, this parameter might be helpful in the identification of patients with a marked reduction in trabecular BMD.
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Since 2004, cannabis has been prohibited by the World Anti-Doping Agency for all sports competitions. In the years since then, about half of all positive doping cases in Switzerland have been related to cannabis consumption. In doping urine analysis, the target analyte is 11-nor-9-carboxy-Delta(9)-tetrahydrocannabinol (THC-COOH), the cutoff being 15 ng/mL. However, the wide urinary detection window of the long-term metabolite of Delta(9)-tetrahydrocannabinol (THC) does not allow a conclusion to be drawn regarding the time of consumption or the impact on the physical performance. The purpose of the present study on light cannabis smokers was to evaluate target analytes with shorter urinary excretion times. Twelve male volunteers smoked a cannabis cigarette standardized to 70 mg THC per cigarette. Plasma and urine were collected up to 8 h and 11 days, respectively. Total THC, 11-hydroxy-Delta(9)-tetrahydrocannabinol (THC-OH), and THC-COOH were determined after hydrolysis followed by solid-phase extraction and gas chromatography/mass spectrometry. The limits of quantitation were 0.1-1.0 ng/mL. Eight puffs delivered a mean THC dose of 45 mg. Plasma levels of total THC, THC-OH, and THC-COOH were measured in the ranges 0.2-59.1, 0.1-3.9, and 0.4-16.4 ng/mL, respectively. Peak concentrations were observed at 5, 5-20, and 20-180 min. Urine levels were measured in the ranges 0.1-1.3, 0.1-14.4, and 0.5-38.2 ng/mL, peaking at 2, 2, and 6-24 h, respectively. The times of the last detectable levels were 2-8, 6-96, and 48-120 h. Besides high to very high THC-COOH levels (245 +/- 1,111 ng/mL), THC (3 +/- 8 ng/mL) and THC-OH (51 +/- 246 ng/mL) were found in 65 and 98% of cannabis-positive athletes' urine samples, respectively. In conclusion, in addition to THC-COOH, the pharmacologically active THC and THC-OH should be used as target analytes for doping urine analysis. In the case of light cannabis use, this may allow the estimation of more recent consumption, probably influencing performance during competitions. However, it is not possible to discriminate the intention of cannabis use, i.e., for recreational or doping purposes. Additionally, pharmacokinetic data of female volunteers are needed to interpret cannabis-positive doping cases of female athletes.