29 resultados para Pechini method and chromium


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Background: The aim of this report is to describe the main characteristics of the design, including response rates, of the Cornella Health Interview Survey Follow-up Study. Methods: The original cohort consisted of 2,500 subjects (1,263 women and 1,237 men) interviewed as part of the 1994 Cornella Health Interview Study. A record linkage to update the address and vital status of the cohort members was carried out using, first a deterministic method, and secondly a probabilistic one, based on each subject's first name and surnames. Subsequently, we attempted to locate the cohort members to conduct the phone follow-up interviews. A pilot study was carried out to test the overall feasibility and to modify some procedures before the field work began. Results: After record linkage, 2,468 (98.7%) subjects were successfully traced. Of these, 91 (3.6%) were deceased, 259 (10.3%) had moved to other towns, and 50 (2.0%) had neither renewed their last municipal census documents nor declared having moved. After using different strategies to track and to retain cohort members, we traced 92% of the CHIS participants. From them, 1,605 subjects answered the follow-up questionnaire. Conclusion: The computerized record linkage maximized the success of the follow-up that was carried out 7 years after the baseline interview. The pilot study was useful to increase the efficiency in tracing and interviewing the respondents.

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In experiments with two-person sequential games we analyzewhether responses to favorable and unfavorable actions dependon the elicitation procedure. In our hot treatment thesecond player responds to the first player s observed actionwhile in our cold treatment we follow the strategy method and have the second player decide on a contingent action foreach and every possible first player move, without firstobserving this move. Our analysis centers on the degree towhich subjects deviate from the maximization of their pecuniaryrewards, as a response to others actions. Our results show nodifference in behavior between the two treatments. We also findevidence of the stability of subjects preferences with respectto their behavior over time and to the consistency of theirchoices as first and second mover.

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Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

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The network revenue management (RM) problem arises in airline, hotel, media,and other industries where the sale products use multiple resources. It can be formulatedas a stochastic dynamic program but the dynamic program is computationallyintractable because of an exponentially large state space, and a number of heuristicshave been proposed to approximate it. Notable amongst these -both for their revenueperformance, as well as their theoretically sound basis- are approximate dynamic programmingmethods that approximate the value function by basis functions (both affinefunctions as well as piecewise-linear functions have been proposed for network RM)and decomposition methods that relax the constraints of the dynamic program to solvesimpler dynamic programs (such as the Lagrangian relaxation methods). In this paperwe show that these two seemingly distinct approaches coincide for the network RMdynamic program, i.e., the piecewise-linear approximation method and the Lagrangianrelaxation method are one and the same.

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A Method is offered that makes it possible to apply generalized canonicalcorrelations analysis (CANCOR) to two or more matrices of different row and column order. The new method optimizes the generalized canonical correlationanalysis objective by considering only the observed values. This is achieved byemploying selection matrices. We present and discuss fit measures to assessthe quality of the solutions. In a simulation study we assess the performance of our new method and compare it to an existing procedure called GENCOM,proposed by Green and Carroll. We find that our new method outperforms the GENCOM algorithm both with respect to model fit and recovery of the truestructure. Moreover, as our new method does not require any type of iteration itis easier to implement and requires less computation. We illustrate the methodby means of an example concerning the relative positions of the political parties inthe Netherlands based on provincial data.

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The structural and electronic properties of Cu2O have been investigated using the periodic Hartree-Fock method and a posteriori density-functional corrections. The lattice parameter, bulk modulus, and elastic constants have been calculated. The electronic structure of and bonding in Cu2O are analyzed and compared with x-ray photoelectron spectroscopy spectra, showing a good agreement for the valence-band states. To check the quality of the calculated electron density, static structure factors and Compton profiles have been calculated, showing a good agreement with the available experimental data. The effective electron and hole masses have been evaluated for Cu2O at the center of the Brillouin zone. The calculated interaction energy between the two interpenetrated frameworks in the cuprite structure is estimated to be around -6.0 kcal/mol per Cu2O formula. The bonding between the two independent frameworks has been analyzed using a bimolecular model and the results indicate an important role of d10-d10 type interactions between copper atoms.

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The structural and electronic properties of Cu2O have been investigated using the periodic Hartree-Fock method and a posteriori density-functional corrections. The lattice parameter, bulk modulus, and elastic constants have been calculated. The electronic structure of and bonding in Cu2O are analyzed and compared with x-ray photoelectron spectroscopy spectra, showing a good agreement for the valence-band states. To check the quality of the calculated electron density, static structure factors and Compton profiles have been calculated, showing a good agreement with the available experimental data. The effective electron and hole masses have been evaluated for Cu2O at the center of the Brillouin zone. The calculated interaction energy between the two interpenetrated frameworks in the cuprite structure is estimated to be around -6.0 kcal/mol per Cu2O formula. The bonding between the two independent frameworks has been analyzed using a bimolecular model and the results indicate an important role of d10-d10 type interactions between copper atoms.

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Background: Declining physical activity is associated with a rising burden of global disease. There is little evidence about effective ways to increase adherence to physical activity. Therefore, interventions are needed that produce sustained increases in adherence to physical activity and are cost-effective. The purpose is to assess the effectiveness of a primary care physical activity intervention in increasing adherence to physical activity in the general population seen in primary care. Method and design: Randomized controlled trial with systematic random sampling. A total of 424 subjects of both sexes will participate; all will be over the age of 18 with a low level of physical activity (according to the International Physical Activity Questionnaire, IPAQ), self-employed and from 9 Primary Healthcare Centres (PHC). They will volunteer to participate in a physical activity programme during 3 months (24 sessions; 2 sessions a week, 60 minutes per session). Participants from each PHC will be randomly allocated to an intervention (IG) and control group (CG). The following parameters will be assessed pre and post intervention in both groups: (1) health-related quality of life (SF-12), (2) physical activity stage of change (Prochaska's stages of change), (3) level of physical activity (IPAQ-short version), (4) change in perception of health (vignettes from the Cooperative World Organization of National Colleges, Academies, and Academic Associations of Family Physicians, COOP/WONCA), (5) level of social support for the physical activity practice (Social Support for Physical Activity Scale, SSPAS), and (6) control based on analysis (HDL, LDL and glycated haemoglobin).Participants' frequency of visits to the PHC will be registered over the six months before and after the programme. There will be a follow up in a face to face interview three, six and twelve months after the programme, with the reduced version of IPAQ, SF-12, SSPAS, and Prochaska's stages. Discussion: The pilot study showed the effectiveness of an enhanced low-cost, evidence-based intervention in increased physical activity and improved social support. If successful in demonstrating long-term improvements, this randomised controlled trial will be the first sustainable physical activity intervention based in primary care in our country to demonstrate longterm adherence to physical activity. Trial Registration: A service of the U.S. National Institutes of Health. Developed by the National Library of Medicine. ClinicalTrials.gov ID: NCT00714831.

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The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.

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The factor structure of a back translated Spanish version (Lega, Caballo and Ellis, 2002) of the Attitudes and Beliefs Inventory (ABI) (Burgess, 1990) is analyzed in a sample of 250 university students.The Spanish version of the ABI is a 48-items self-report inventory using a 5-point Likert scale that assesses rational and irrational attitudes and beliefs. 24-items cover two dimensions of irrationality: a) areas of content (3 subscales), and b) styles of thinking (4 subscales).An Exploratory Factor Analysis (Parallel Analysis with Unweighted Least Squares method and Promin rotation) was performed with the FACTOR 9.20 software (Lorenzo-Seva and Ferrando, 2013).The results reproduced the main four styles of irrational thinking in relation with the three specific contents of irrational beliefs. However, two factors showed a complex configuration with important cross-loadings of different items in content and style. More analyses are needed to review the specific content and style of such items.

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The factor structure of a back translated Spanish version (Lega, Caballo and Ellis, 2002) of the Attitudes and Beliefs Inventory (ABI) (Burgess, 1990) is analyzed in a sample of 250 university students.The Spanish version of the ABI is a 48-items self-report inventory using a 5-point Likert scale that assesses rational and irrational attitudes and beliefs. 24-items cover two dimensions of irrationality: a) areas of content (3 subscales), and b) styles of thinking (4 subscales).An Exploratory Factor Analysis (Parallel Analysis with Unweighted Least Squares method and Promin rotation) was performed with the FACTOR 9.20 software (Lorenzo-Seva and Ferrando, 2013).The results reproduced the main four styles of irrational thinking in relation with the three specific contents of irrational beliefs. However, two factors showed a complex configuration with important cross-loadings of different items in content and style. More analyses are needed to review the specific content and style of such items.

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Although usability evaluations have been focused on assessing different contexts of use, no proper specifications have been addressed towards the particular environment of academic websites in the Spanish-speaking context of use. Considering that this context involves hundreds of millions of potential users, the AIPO Association is running the UsabAIPO Project. The ultimate goal is to promote an adequate translation of international standards, methods and ideal values related to usability in order to adapt them to diverse Spanish-related contexts of use. This article presents the main statistical results coming from the Second and Third Stages of the UsabAIPO Project, where the UsabAIPO Heuristic method (based on Heuristic Evaluation techniques) and seven Cognitive Walkthroughs were performed over 69 university websites. The planning and execution of the UsabAIPO Heuristic method and the Cognitive Walkthroughs, the definition of two usability metrics, as well as the outline of the UsabAIPO Heuristic Management System prototype are also sketched.

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Needle trap devices (NTDs) are a relatively new and promising tool for headspace (HS) analysis. In this study, a dynamic HS sampling procedure is evaluated for the determination of volatile organic compounds (VOCs) in whole blood samples. A full factorial design was used to evaluate the influence of the number of cycles and incubation time and it is demonstrated that the controlling factor in the process is the number of cycles. A mathematical model can be used to determine the most appropriate number of cycles required to adsorb a prefixed amount of VOCs present in the HS phase whenever quantitative adsorption is reached in each cycle. Matrix effect is of great importance when complex biological samples, such as blood, are analyzed. The evaluation of the salting out effect showed a significant improvement in the volatilization of VOCs to the HS in this type of matrices. Moreover, a 1:4 (blood:water) dilution is required to obtain quantitative recoveries of the target analytes when external calibration is used. The method developed gives detection limits in the 0.020–0.080 μg L−1 range (0.1–0.4 μg L−1 range for undiluted blood samples) with appropriate repeatability values (RSD < 15% at high level and <23% at LOQ level). Figure of merits of the method can be improved by using a smaller phase ratio (i.e., an increase in the blood volume and a decrease in the HS volume), which lead to lower detection limits, better repeatability values and greater sensibility. Twenty-eight blood samples have been evaluated with the proposed method and the results agree with those indicated in other studies. Benzene was the only target compound that gave significant differences between blood levels detected in volunteer non-smokers and smokers

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It is well known that regression analyses involving compositional data need special attention because the data are not of full rank. For a regression analysis where both the dependent and independent variable are components we propose a transformation of the components emphasizing their role as dependent and independent variables. A simple linear regression can be performed on the transformed components. The regression line can be depicted in a ternary diagram facilitating the interpretation of the analysis in terms of components. An exemple with time-budgets illustrates the method and the graphical features