980 resultados para Bivariate Exponential
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The objective of this study was to characterize weapon-carrying adolescents and to assess whether weapon carriers differ from weapon users. Data were drawn from a cross-sectional school-based survey of 7548 adolescents aged 16-20 years in Switzerland. Youths carrying a weapon were compared with those who do not. Subsequently, weapon carriers were divided into those who had used it in a fight and those who had not. Individual, family, school and social factors were analyzed using bivariate and stepwise multivariate analysis. For both genders, delinquent behavior and being victim of physical violence were associated with weapon carrying. For males, quarreling while intoxicated, being an apprentice, being sensation seekers, having a tattoo, having a poor relationship with parents and practicing unsafe sex were also related to weapon carrying. Compared with weapon carriers, female weapon users were more likely to be regular smokers. Male weapon users were foreign born, urban and apprentices; had poor school connectedness; practiced unsafe sex and quarreled while intoxicated. Carrying a weapon is a relatively frequent behavior among youths in Switzerland and a sizeable proportion of weapon carriers have used it in a fight. Weapon carrying should be part of the clinical assessment and preventive counseling of adolescents. Preventive programs specific for at-risk youth groups need to be developed.
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Until now it was thought that the retrovirus mouse mammary tumor virus preferentially infects B cells, which thereafter proliferate and differentiate due to superantigen-mediated T cell help. We describe in this study that dendritic cells are infectable at levels comparable to B cells in the first days after virus injection. Moreover, IgM knockout mice have chronically deleted superantigen-reactive T cells after MMTV injection, indicating that superantigen presentation by dendritic cells is sufficient for T cell deletion. In both subsets initially only few cells were infected, but there was an exponential increase in numbers of infected B cells due to superantigen-mediated T cell help, explaining that at the peak of the response infection is almost exclusively found in B cells. The level of infection in vivo was below 1 in 1000 dendritic cells or B cells. Infection levels in freshly isolated dendritic cells from spleen, Langerhans cells from skin, or bone marrow-derived dendritic cells were compared in an in vitro infection assay. Immature dendritic cells such as Langerhans cells or bone marrow-derived dendritic cells were infected 10- to 30-fold more efficiently than mature splenic dendritic cells. Bone marrow-derived dendritic cells carrying an endogenous mouse mammary tumor virus superantigen were highly efficient at inducing a superantigen response in vivo. These results highlight the importance of professional APC and efficient T cell priming for the establishment of a persistent infection by mouse mammary tumor virus.
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We present molecular dynamics (MD) simulations results for dense fluids of ultrasoft, fully penetrable particles. These are a binary mixture and a polydisperse system of particles interacting via the generalized exponential model, which is known to yield cluster crystal phases for the corresponding monodisperse systems. Because of the dispersity in the particle size, the systems investigated in this work do not crystallize and form disordered cluster phases. The clusteringtransition appears as a smooth crossover to a regime in which particles are mostly located in clusters, isolated particles being infrequent. The analysis of the internal cluster structure reveals microsegregation of the big and small particles, with a strong homo-coordination in the binary mixture. Upon further lowering the temperature below the clusteringtransition, the motion of the clusters" centers-of-mass slows down dramatically, giving way to a cluster glass transition. In the cluster glass, the diffusivities remain finite and display an activated temperature dependence, indicating that relaxation in the cluster glass occurs via particle hopping in a nearly arrested matrix of clusters. Finally we discuss the influence of the microscopic dynamics on the transport properties by comparing the MD results with Monte Carlo simulations.
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OBJECTIVE: To assess whether problematic internet use is associated with somatic complaints and whether this association remains when checking for internet activity among a random sample of adolescents living in the canton of Vaud, Switzerland. METHODS: Cross-sectional survey of 3,067 8th graders (50.3% females) divided into average (n = 2,708) and problematic (n = 359) Internet users and compared for somatic complaints (backache, overweight, headaches, musculoskeletal pain, sleep problems and sight problems) controlling for sociodemographic and internet-related variables. Logistic regressions were performed for each complaint and for all of them simultaneously controlling variables significant at the bivariate level. RESULTS: At the multivariate level, when taken separately, problematic internet users were more likely to have a chronic condition (adjusted odds ratio [aOR] with 95% CI: 1.58 [1.11:2.23]) and to report back pain (aOR: 1.46 [1.04:2.05]), overweight (aOR: 1.74 [1.03:2.93]), musculoskeletal pain (aOR: 1.36 [1.00:1.84]) and sleep problems (aOR: 2.16 [1.62:2.88]). When considered in the full model, only sleep problems remained significant (aOR: 2.03 [1.50:2.74]). CONCLUSIONS: Our results confirm that problematic internet users report health problems more frequently, with lack of sleep being the most strongly associated and seeming to act as mediator regarding the other ones. Clinicians should remember to screen for excessive internet use their patients complaining of sleep-related problems, back or musculoskeletal pain or overweight. Clinicians should advise parents to limit the amount of time their adolescent children can spend online for leisure activities. Furthermore, limiting the number of devices used to connect to the internet could help warrant enough sleeping time.
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We analyze the failure process of a two-component system with widely different fracture strength in the framework of a fiber bundle model with localized load sharing. A fraction 0≤α≤1 of the bundle is strong and it is represented by unbreakable fibers, while fibers of the weak component have randomly distributed failure strength. Computer simulations revealed that there exists a critical composition αc which separates two qualitatively different behaviors: Below the critical point, the failure of the bundle is brittle, characterized by an abrupt damage growth within the breakable part of the system. Above αc, however, the macroscopic response becomes ductile, providing stability during the entire breaking process. The transition occurs at an astonishingly low fraction of strong fibers which can have importance for applications. We show that in the ductile phase, the size distribution of breaking bursts has a power law functional form with an exponent μ=2 followed by an exponential cutoff. In the brittle phase, the power law also prevails but with a higher exponent μ=92. The transition between the two phases shows analogies to continuous phase transitions. Analyzing the microstructure of the damage, it was found that at the beginning of the fracture process cracks nucleate randomly, while later on growth and coalescence of cracks dominate, which give rise to power law distributed crack sizes.
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In the root-colonizing biocontrol strain CHA0 of Pseudomonas fluorescens, cell density-dependent synthesis of extracellular, plant-beneficial secondary metabolites and enzymes is positively regulated by the GacS/GacA two-component system. Mutational analysis of the GacS sensor kinase using improved single-copy vectors showed that inactivation of each of the three conserved phosphate acceptor sites caused an exoproduct null phenotype (GacS-), whereas deletion of the periplasmic loop domain had no significant effect on the expression of exoproduct genes. Strain CHA0 is known to synthesize a solvent-extractable extracellular signal that advances and enhances the expression of exoproduct genes during the transition from exponential to stationary growth phase when maximal exoproduct formation occurs. Mutational inactivation of either GacS or its cognate response regulator GacA abolished the strain's response to added signal. Deletion of the linker domain of the GacS sensor kinase caused signal-independent, strongly elevated expression of exoproduct genes at low cell densities. In contrast to the wild-type strain CHA0, the gacS linker mutant and a gacS null mutant were unable to protect tomato plants from crown and root rot caused by Fusarium oxysporum f. sp. radicis-lycopersici in a soil-less microcosm, indicating that, at least in this plant-pathogen system, there is no advantage in using a signal-independent biocontrol strain.
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BACKGROUND: PCR has the potential to detect and precisely quantify specific DNA sequences, but it is not yet often used as a fully quantitative method. A number of data collection and processing strategies have been described for the implementation of quantitative PCR. However, they can be experimentally cumbersome, their relative performances have not been evaluated systematically, and they often remain poorly validated statistically and/or experimentally. In this study, we evaluated the performance of known methods, and compared them with newly developed data processing strategies in terms of resolution, precision and robustness. RESULTS: Our results indicate that simple methods that do not rely on the estimation of the efficiency of the PCR amplification may provide reproducible and sensitive data, but that they do not quantify DNA with precision. Other evaluated methods based on sigmoidal or exponential curve fitting were generally of both poor resolution and precision. A statistical analysis of the parameters that influence efficiency indicated that it depends mostly on the selected amplicon and to a lesser extent on the particular biological sample analyzed. Thus, we devised various strategies based on individual or averaged efficiency values, which were used to assess the regulated expression of several genes in response to a growth factor. CONCLUSION: Overall, qPCR data analysis methods differ significantly in their performance, and this analysis identifies methods that provide DNA quantification estimates of high precision, robustness and reliability. These methods allow reliable estimations of relative expression ratio of two-fold or higher, and our analysis provides an estimation of the number of biological samples that have to be analyzed to achieve a given precision.
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Linear spaces consisting of σ-finite probability measures and infinite measures (improper priors and likelihood functions) are defined. The commutative group operation, called perturbation, is the updating given by Bayes theorem; the inverse operation is the Radon-Nikodym derivative. Bayes spaces of measures are sets of classes of proportional measures. In this framework, basic notions of mathematical statistics get a simple algebraic interpretation. For example, exponential families appear as affine subspaces with their sufficient statistics as a basis. Bayesian statistics, in particular some well-known properties of conjugated priors and likelihood functions, are revisited and slightly extended
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The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.
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Intrauterine growth restriction (IUGR) is one of the leading causes of perinatal mortality and morbidity. Nowadays, this condition is detected in the 3rt and last trimester of gestation when the pathology is already established and success of therapeutic strategies are limited. As the physiopathology of the disease suggests that the problem stems from poor placental implantation, it would be quite advantageous to identify women at increased risk in the first or second trimester of gestation because it then might be possible to offer treatment interventions or at least to establish increased surveillance for high risk pregnancies. Maternal levels of pregnancy-associated plasma protein-A (PAPP-A) and free β human chorionic gonadotropin (free βhCG) has been shown to be effective in first trimester screening for chromosomal abnormalities, primarily trisomies 21, 13 and 18. Previous studies evaluating PAPP-A and free βhCG measured in the first trimester in relation with IUGR have provided conflicting results. Moreover, it has been suggested that black ethnicity is another important predictive factor for fetal growth restriction.Objective: To analyse the association between first trimester serum analytes (PAPP-A and free βhCG) and ethnicity with Intrauterine Growth Restriction.Methods: The study consists in a retrospective cohort, including all singleton pregnancies with complete outcome data that had undergone first trimester screening (PAPP-A and free βhCG) at 11-13+6weeks of gestation between 1/1/2010 - 31/12/2012 in Hospital Universitari Dr Josep Trueta. Biochemical markers are converted to multiples of the median (MoMs) and percentiles 5 and 10 are calculated. The association between free βhCG and PAPP-A with the incidence of IUGR is evaluated in combination with maternal ethnicity. Bivariate and logistic regression analyses are performed to adjust this association for co variables
Resumo:
Intrauterine growth restriction (IUGR) is one of the leading causes of perinatal mortality and morbidity. Nowadays, this condition is detected in the 3rt and last trimester of gestation when the pathology is already established and success of therapeutic strategies are limited. As the physiopathology of the disease suggests that the problem stems from poor placental implantation, it would be quite advantageous to identify women at increased risk in the first or second trimester of gestation because it then might be possible to offer treatment interventions or at least to establish increased surveillance for high risk pregnancies. Maternal levels of pregnancy-associated plasma protein-A (PAPP-A) and free β human chorionic gonadotropin (free βhCG) has been shown to be effective in first trimester screening for chromosomal abnormalities, primarily trisomies 21, 13 and 18. Previous studies evaluating PAPP-A and free βhCG measured in the first trimester in relation with IUGR have provided conflicting results. Moreover, it has been suggested that black ethnicity is another important predictive factor for fetal growth restriction.Objective: To analyse the association between first trimester serum analytes (PAPP-A and free βhCG) and ethnicity with Intrauterine Growth Restriction.Methods: The study consists in a retrospective cohort, including all singleton pregnancies with complete outcome data that had undergone first trimester screening (PAPP-A and free βhCG) at 11-13+6weeks of gestation between 1/1/2010 - 31/12/2012 in Hospital Universitari Dr Josep Trueta. Biochemical markers are converted to multiples of the median (MoMs) and percentiles 5 and 10 are calculated. The association between free βhCG and PAPP-A with the incidence of IUGR is evaluated in combination with maternal ethnicity. Bivariate and logistic regression analyses are performed to adjust this association for co variables
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Aim. To evaluate the usefulness of COOP/WONCA charts as a screening tool for mental disorders in primary care in the immigrant healthcare users in Salt. To measure self-rated health of Salt immigration population using the COOP / WONCA charts and to assess its associated factorsDesign. Descriptive and transversal studyParticipants. 370 non-EU immigrants seniors selected by consecutive sampling stratified by sexMain measures. Personal information will be collected (age, sex, country of origin, years of residency in Spain, number of people living in the household and associated comorbidities). Each participant will complete the COOP/WONCA charts. An analysis of the validity of the diagnostic test will be done: sensibility, specificity, positive predictive value, negative predictive value, ROC curve and area under the curve (AUC). All variables will be subjected to descriptive analysis. Bivariate and multivariate analysis between the variables collected (sex, years of residency in Spain... ) and the results of COOP / WONCA charts will be performedResults. Preliminary results are available on a pilot test with 30 patients. The mental disorder prevalence is around 30%. Sensibility (0,89), specificity (0,89), VPP (0,80), VPN (0,94) cutoff score (3.5) and AUC (0,941). Women, people with 10 or more years of residency in Spain and unemployed people have worse self-rated healthConclusions. Based on the preliminary results, is possible to conclude that COOP/WONCA charts could be an useful, valid and applicable screening test for mental disorders in primary care with immigrant population
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We present results from both, calorimetric and dilatometric studies of the isothermal ordering process taking place in a Cu-Zn-Al shape memory alloy after quenches from Tq temperatures ranging from 350 K to 1200 K. The dissipated energy and the length variations of the system are obtained during the process. The change of these quantities in the whole process have been compared with the difference [MATH] between Ms, measured after the relaxation and Ms measured just after the quench. We obtain that these three quantities present, as a function of Tq, the same qualitative behaviour. These changes are then associated with changes of the L21 ordering after the quench in the system. The relaxational process does not follow a single exponential decay. Instead, a continuous slowing down is observed. A relaxation time [MATH] has been defined to characterize the relaxation rate. We show that [MATH] depends on both the annealing and the quenching (Tq [MATH] 800 K) temperatures through an Arrhenius law.
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Much of the analytical modeling of morphogen profiles is based on simplistic scenarios, where the source is abstracted to be point-like and fixed in time, and where only the steady state solution of the morphogen gradient in one dimension is considered. Here we develop a general formalism allowing to model diffusive gradient formation from an arbitrary source. This mathematical framework, based on the Green's function method, applies to various diffusion problems. In this paper, we illustrate our theory with the explicit example of the Bicoid gradient establishment in Drosophila embryos. The gradient formation arises by protein translation from a mRNA distribution followed by morphogen diffusion with linear degradation. We investigate quantitatively the influence of spatial extension and time evolution of the source on the morphogen profile. For different biologically meaningful cases, we obtain explicit analytical expressions for both the steady state and time-dependent 1D problems. We show that extended sources, whether of finite size or normally distributed, give rise to more realistic gradients compared to a single point-source at the origin. Furthermore, the steady state solutions are fully compatible with a decreasing exponential behavior of the profile. We also consider the case of a dynamic source (e.g. bicoid mRNA diffusion) for which a protein profile similar to the ones obtained from static sources can be achieved.
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In soccer, dead-ball moves are those in which the ball is returned to play from a stationary position following an interruption of play. The aim of this study was to analyse the effectiveness of one such dead-ball move, namely corner kicks, and to identify the key variables that determine the success of a shot or header following a corner, thereby enabling a model of successful corner kicks to be proposed. We recorded 554 corner kicks performed during the 2010 World Cup in South Africa and carried out a univariate, bivariate and multivariate analysis of the data. The results indicated that corners were of limited effectiveness in terms of the success of subsequent shots or headers. The analysis also revealed a series of variables that were significantly related to one another, and this enabled us to propose an explanatory model. Although this model had limited explanatory power, it nonetheless helps to understand the execution of corner kicks in practical terms.