973 resultados para score test information matrix artificial regression
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This report presents and discusses selected findings regarding gender differences from an Australian-based study that investigated attitudes of individuals at risk for Huntington's disease (HD) towards genetic risk and predictive testing. Clear gender differences emerged regarding perceived coping capacity with regard to predictive testing, as well as disclosure of the genetic risk for HD to others. Female participants were more likely to disclose their genetic risk to others, including their medical practitioners, while male participants were three times more fearful of disclosing their genetic risk to others. These findings are of interest in light of gender differences that have consistently been reported regarding the uptake of predictive testing for HD, other genetic conditions, and health services more generally. While gender differences cannot provide a fully explanatory framework for differential uptake of predictive genetic testing, men and women may experience and respond differently to the genetic risk for HD and possibly other inherited disorders. The meanings of genetic risk to men and women warrants further exploration, given anticipated increases in genetic testing for more common conditions, especially if post-test interventions are possible. These issues are also relevant within the context of individuals' concerns about the potential for discrimination on the basis of genetic risk or genetic test information.
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Background: Oral itraconazole (ITRA) is used for the treatment of allergic bronchopulmonary aspergillosis in patients with cystic fibrosis (CF) because of its antifungal activity against Aspergillus species. ITRA has an active hydroxy-metabolite (OH-ITRA) which has similar antifungal activity. ITRA is a highly lipophilic drug which is available in two different oral formulations, a capsule and an oral solution. It is reported that the oral solution has a 60% higher relative bioavailability. The influence of altered gastric physiology associated with CF on the pharmacokinetics (PK) of ITRA and its metabolite has not been previously evaluated. Objectives: 1) To estimate the population (pop) PK parameters for ITRA and its active metabolite OH-ITRA including relative bioavailability of the parent after administration of the parent by both capsule and solution and 2) to assess the performance of the optimal design. Methods: The study was a cross-over design in which 30 patients received the capsule on the first occasion and 3 days later the solution formulation. The design was constrained to have a maximum of 4 blood samples per occasion for estimation of the popPK of both ITRA and OH-ITRA. The sampling times for the population model were optimized previously using POPT v.2.0.[1] POPT is a series of applications that run under MATLAB and provide an evaluation of the information matrix for a nonlinear mixed effects model given a particular design. In addition it can be used to optimize the design based on evaluation of the determinant of the information matrix. The model details for the design were based on prior information obtained from the literature, which suggested that ITRA may have either linear or non-linear elimination. The optimal sampling times were evaluated to provide information for both competing models for the parent and metabolite and for both capsule and solution simultaneously. Blood samples were assayed by validated HPLC.[2] PopPK modelling was performed using FOCE with interaction under NONMEM, version 5 (level 1.1; GloboMax LLC, Hanover, MD, USA). The PK of ITRA and OH‑ITRA was modelled simultaneously using ADVAN 5. Subsequently three methods were assessed for modelling concentrations less than the LOD (limit of detection). These methods (corresponding to methods 5, 6 & 4 from Beal[3], respectively) were (a) where all values less than LOD were assigned to half of LOD, (b) where the closest missing value that is less than LOD was assigned to half the LOD and all previous (if during absorption) or subsequent (if during elimination) missing samples were deleted, and (c) where the contribution of the expectation of each missing concentration to the likelihood is estimated. The LOD was 0.04 mg/L. The final model evaluation was performed via bootstrap with re-sampling and a visual predictive check. The optimal design and the sampling windows of the study were evaluated for execution errors and for agreement between the observed and predicted standard errors. Dosing regimens were simulated for the capsules and the oral solution to assess their ability to achieve ITRA target trough concentration (Cmin,ss of 0.5-2 mg/L) or a combined Cmin,ss for ITRA and OH-ITRA above 1.5mg/L. Results and Discussion: A total of 241 blood samples were collected and analysed, 94% of them were taken within the defined optimal sampling windows, of which 31% where taken within 5 min of the exact optimal times. Forty six per cent of the ITRA values and 28% of the OH-ITRA values were below LOD. The entire profile after administration of the capsule for five patients was below LOD and therefore the data from this occasion was omitted from estimation. A 2-compartment model with 1st order absorption and elimination best described ITRA PK, with 1st order metabolism of the parent to OH-ITRA. For ITRA the clearance (ClItra/F) was 31.5 L/h; apparent volumes of central and peripheral compartments were 56.7 L and 2090 L, respectively. Absorption rate constants for capsule (kacap) and solution (kasol) were 0.0315 h-1 and 0.125 h-1, respectively. Comparative bioavailability of the capsule was 0.82. There was no evidence of nonlinearity in the popPK of ITRA. No screened covariate significantly improved the fit to the data. The results of the parameter estimates from the final model were comparable between the different methods for accounting for missing data, (M4,5,6)[3] and provided similar parameter estimates. The prospective application of an optimal design was found to be successful. Due to the sampling windows, most of the samples could be collected within the daily hospital routine, but still at times that were near optimal for estimating the popPK parameters. The final model was one of the potential competing models considered in the original design. The asymptotic standard errors provided by NONMEM for the final model and empirical values from bootstrap were similar in magnitude to those predicted from the Fisher Information matrix associated with the D-optimal design. Simulations from the final model showed that the current dosing regimen of 200 mg twice daily (bd) would provide a target Cmin,ss (0.5-2 mg/L) for only 35% of patients when administered as the solution and 31% when administered as capsules. The optimal dosing schedule was 500mg bd for both formulations. The target success for this dosing regimen was 87% for the solution with an NNT=4 compared to capsules. This means, for every 4 patients treated with the solution one additional patient will achieve a target success compared to capsule but at an additional cost of AUD $220 per day. The therapeutic target however is still doubtful and potential risks of these dosing schedules need to be assessed on an individual basis. Conclusion: A model was developed which described the popPK of ITRA and its main active metabolite OH-ITRA in adult CF after administration of both capsule and solution. The relative bioavailability of ITRA from the capsule was 82% that of the solution, but considerably more variable. To incorporate missing data, using the simple Beal method 5 (using half LOD for all samples below LOD) provided comparable results to the more complex but theoretically better Beal method 4 (integration method). The optimal sparse design performed well for estimation of model parameters and provided a good fit to the data.
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The objective of this thesis is to report the behaviour of mammalian cells with biocompatible synthetic polymers with potential for applications to the human body. Composite hydrogel materials were tested as possible keratoprosthetic devices. It was found that surface topography is an important consideration, pores, channels and fibres exposed on the surface of the hydrogels tested can have significant effects on the extent of cell adheson and proliferation. It is recommended that the core component is fabricated out of one of the following to provide a non cell adhesive base; A8, A11, A13, A22, A23. The haptic periphery fabricated out of one of the following would provide a cell adhesive composite; A16, A30, A33, A37, A38, A42, A43, A44. The presence of vitronectin in the ocular tissue appears to lead to higher cell adhesion to the posterior surface of a contact lens when compared to the anterior surface. Group IV contact lenses adhere more cells than Group II contact lenses - this may indicate that more protein (including vitronectin) is able to adhere to the contact lens due to the Group IV contact lenses high water content and ionic hydrogel matrix. Artificial lung surfactant analogues were found to be non cytotoxic but also decreased cell proliferation when tested at higher concentrations. Poly(lysine ethyl ester adipamide) [PLETESA] had the most favourable response on cell proliferation and commercial styrene/maleic anhydride (pMA/STY sp2) the most pronounced inhibitory response. The mode of action that decreases cell proliferation appears to be through membrane destabilization. Tissue culture well plates coated with PLETESA allowed cells to adhere in a concentration dependent manner, multilaminar liposomes possibly of PLETESA were observed in solution in PLETESA coated wells. Polyhydroxybutryate (PHB) and polyhydroxyvalerate (PHV) blends that contained hydroxyapatite were found to be the most cell adhesive material of those materials tested. The blends that were most susceptible to degradation adhered the most cells in initial stages of degradation. The initial slight increase in cell adhesion may be due to the increased rugosity of the material. As the degradation continued the number of cells adhering to the samples decreased, this may indicate that the polarity was inhibitory to cell adhesion during the later stages of degradation.
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The research compares the usefullness of four remote sensing information sources, these being LANDSAT photographic prints, LANDSAT computer compatible tapes, Metric Camera and SIR-A photographic prints. These sources provide evaluations of the catchment characteristics of the Belize and Sibun river basins in Central America. Map evaluations at 1:250,000 scale are compared to the results of the same scale, remotely sensed information sources. The values of catchment characteristics for both maps and LANDSAT prints are used in multiple regression analysis, providing flood flow formulae, after investigations to provide a suitable dependent variable discharge series are made for short term records. The use of all remotely sensed information sources in providing evaluations of catchment characteristics is discussed. LANDSAT prints and computer compatible tapes of a post flood scene are used to estimate flood distributions and volumes. These are compared to values obtained from unit hydrograph analysis, using the dependent discharge series and evaluate the probable losses from the Belize river to the floodplain, thereby assessing the accuracy of LANDSAT estimates. Information relating to flood behaviour is discussed in terms of basic image presentation as well as image processing. A cost analysis of the purchase and use of all materials is provided. Conclusions of the research indicate that LANDSAT print material may provide information suitable for regression analysis at levels of accuracy as great as those of topographic maps, that the differing information sources are uniquely applicable and that accurate estimates of flood volumes may be determined even by post flood imagery.
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The adequate attitude to the information models and information objects in the culture context is one of the main problems to be investigated on the threshold of information society. The goal of this paper is to outline some problems connected with the main styles of perceiving of the mental and artificially generated information models stored in the information objects and used in the processes of the Information Interaction or simply – in the Inforaction. The culture influence on inforaction is discussed.
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There is growing popularity in the use of composite indices and rankings for cross-organizational benchmarking. However, little attention has been paid to alternative methods and procedures for the computation of these indices and how the use of such methods may impact the resulting indices and rankings. This dissertation developed an approach for assessing composite indices and rankings based on the integration of a number of methods for aggregation, data transformation and attribute weighting involved in their computation. The integrated model developed is based on the simulation of composite indices using methods and procedures proposed in the area of multi-criteria decision making (MCDM) and knowledge discovery in databases (KDD). The approach developed in this dissertation was automated through an IT artifact that was designed, developed and evaluated based on the framework and guidelines of the design science paradigm of information systems research. This artifact dynamically generates multiple versions of indices and rankings by considering different methodological scenarios according to user specified parameters. The computerized implementation was done in Visual Basic for Excel 2007. Using different performance measures, the artifact produces a number of excel outputs for the comparison and assessment of the indices and rankings. In order to evaluate the efficacy of the artifact and its underlying approach, a full empirical analysis was conducted using the World Bank's Doing Business database for the year 2010, which includes ten sub-indices (each corresponding to different areas of the business environment and regulation) for 183 countries. The output results, which were obtained using 115 methodological scenarios for the assessment of this index and its ten sub-indices, indicated that the variability of the component indicators considered in each case influenced the sensitivity of the rankings to the methodological choices. Overall, the results of our multi-method assessment were consistent with the World Bank rankings except in cases where the indices involved cost indicators measured in per capita income which yielded more sensitive results. Low income level countries exhibited more sensitivity in their rankings and less agreement between the benchmark rankings and our multi-method based rankings than higher income country groups.
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The South American electric knifefish, Brachyhypopomus gauderio, uses weakly electric fields to see and communicate in the dark. Only one study to date has investigated natural behavior in this species during the breeding season; this study proposed that B. guarerio has an exploded lek polygyny breeding system. To test this hypothesis, artificial marshes simulating the native vegetation, temperature, and water conductivities of the South American subtropics were created to study seasonal variation in associative behavior of B. gauderio during the breeding and non-breeding seasons. Mark/recapture methods were used to keep track of individual fish and their dispersion inside the experimental designs. The experimental design proved to be extremely successful at eliciting reproduction. Differences were found in seasonal variations of social behaviors between adult and juvenile populations. Although no apparent sex. differences in movement patterns were found during the breeding season; a trend for male-male aversion was found, suggesting male-male avoidance as a possible strategy guiding aspects of social behaviors in this species. Further, movement may be a tactic for mate seeking as the individuals who moved the most during the breeding season obtained the most opposite sex interactions. These findings support the exploded lek polygyny model. Social interactions are subject to complex regulation by social, physiologic and ecological factors; the extent to which these associations are repeatable may provide novel insights on the evolution of sociality as it has been shaped by natural selection.
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Introduction: Polycystic ovary syndrome (PCOS) whose classic features (menstrual irregularity of oligo/ amenorrhea type, chronic anovulation, infertility and hyperandrogenism clinical and/ or biochemical), is associated with aspects of metabolic syndrome (MS), as obesity and insulin resistance. The level of obesity determines different levels of inflammation, increasing cytokines participants of metabolic and endocrine functions, beyond modulate the immune response. Metabolic changes, added to the imbalance of sex hormones underlying irregular menstruation observed in (PCOS) can trigger allergic processes and elevation of total and specific IgE antibodies indicate that a sensitization process was started. Objective: To evaluate the influence of PCOS on biochemical parameters and levels of total and specific IgE to aeroallergens in obese women. Methods: After approval by the Committee of Ethics in Research, were recruited 80 volunteers with BMI ≥ 30 kg/m2 and age between 18 and 45 years. Among these, 40 with PCOS according to the Rotterdam criteria and 40 women without PCOS (control group). All participants were analysed with regard to anthropometric, clinical, gynecological parameters, interviewed using a questionnaire, and underwent blood sampling for realization of laboratory tests of clinical biochemistry: Total cholesterol, LDL-cholesterol, HDL- cholesterol, Triglycerides, Fasting glucose, Urea, Creatinine, Aspartate aminotransferase (AST), Alanine aminotransferase (ALT) and immunological: total and specific IgE to Dermatophagoides pteronyssinus, Blomia tropicalis, Dermatophagoides farinae and Dermatophagoides microceras.Statistical analysis was performed using SPSS 15.0 software through the chi-square tests, Fisher, Student t test and binary logistic regression, with significance level (p <0.05). Results: It was observed in the group of obese women with PCOS that 29 (72.5%) had menstrual cycle variable and 27 (67.5%) had difficulty getting pregnant. According to waist-hip ratio, higher average was also observed in obese PCOS (0.87). Blood level of HDL (36.9 mg/dL) and ALT (29.3 U/L) were above normal levels in obese women with PCOS, with statistically significant relationship. In the analysis of total and specific IgE to D. pteronyssinus high results were also prevalent in obese PCOS, with blood level (365,22 IU/mL) and (6.83 kU/L), respectively, also statistically significant. Conclusions: Observed predominance of cases with high levels of total IgE in the group of obese women with PCOS, 28 (70%) of the participants, whose mean blood concentration of the group was 365.22 IU/mL. In the analysis of Specific IgE between the groups, the allergen Dermatophagoides pteronyssinus showed greater dispersion and average the results of sensitization in the group of obese PCOS, whose mean blood concentration was 6.83 kU/l. Keywords: Obesity, Allergens and Polycystic Ovary Syndrome
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In order to predict compressive strength of geopolymers prepared from alumina-silica natural products, based on the effect of Al 2 O 3 /SiO 2, Na 2 O/Al 2 O 3, Na 2 O/H 2 O, and Na/[Na+K], more than 50 pieces of data were gathered from the literature. The data was utilized to train and test a multilayer artificial neural network (ANN). Therefore a multilayer feedforward network was designed with chemical compositions of alumina silicate and alkali activators as inputs and compressive strength as output. In this study, a feedforward network with various numbers of hidden layers and neurons were tested to select the optimum network architecture. The developed three-layer neural network simulator model used the feedforward back propagation architecture, demonstrated its ability in training the given input/output patterns. The cross-validation data was used to show the validity and high prediction accuracy of the network. This leads to the optimum chemical composition and the best paste can be made from activated alumina-silica natural products using alkaline hydroxide, and alkaline silicate. The research results are in agreement with mechanism of geopolymerization.
Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)MT.1943-5533.0000829
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Coprime and nested sampling are well known deterministic sampling techniques that operate at rates significantly lower than the Nyquist rate, and yet allow perfect reconstruction of the spectra of wide sense stationary signals. However, theoretical guarantees for these samplers assume ideal conditions such as synchronous sampling, and ability to perfectly compute statistical expectations. This thesis studies the performance of coprime and nested samplers in spatial and temporal domains, when these assumptions are violated. In spatial domain, the robustness of these samplers is studied by considering arrays with perturbed sensor locations (with unknown perturbations). Simplified expressions for the Fisher Information matrix for perturbed coprime and nested arrays are derived, which explicitly highlight the role of co-array. It is shown that even in presence of perturbations, it is possible to resolve $O(M^2)$ under appropriate conditions on the size of the grid. The assumption of small perturbations leads to a novel ``bi-affine" model in terms of source powers and perturbations. The redundancies in the co-array are then exploited to eliminate the nuisance perturbation variable, and reduce the bi-affine problem to a linear underdetermined (sparse) problem in source powers. This thesis also studies the robustness of coprime sampling to finite number of samples and sampling jitter, by analyzing their effects on the quality of the estimated autocorrelation sequence. A variety of bounds on the error introduced by such non ideal sampling schemes are computed by considering a statistical model for the perturbation. They indicate that coprime sampling leads to stable estimation of the autocorrelation sequence, in presence of small perturbations. Under appropriate assumptions on the distribution of WSS signals, sharp bounds on the estimation error are established which indicate that the error decays exponentially with the number of samples. The theoretical claims are supported by extensive numerical experiments.
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Objectifs: L’objectif principal de ce mémoire consiste à comprendre les caractéristiques des carrières criminelles d’individus connus de la police pour avoir perpétré une infraction de leurre d’enfants sur Internet. Aussi, par une analyse typologique à l’aide des antécédents criminels, il sera possible d’établir une typologie d’individus ayant leurré des enfants sur Internet. Également, il sera question de vérifier s’il y a un lien entre les caractéristiques des antécédents criminels de ces individus sur la perpétration de l’agression sexuelle hors ligne. Méthodologie: Provenant de données officielles de la communauté policière du Québec, l’échantillon comprend les parcours de criminels ayant perpétré une infraction de leurre d’enfants sur Internet. Des analyses descriptives en lien avec les différents paramètres de la carrière criminelle seront effectuées. Ensuite, des tests de moyenne et une analyse de régression Cox permettront de vérifier la présence ou non d’un lien statistique entre les caractéristiques des antécédents criminels des individus connus de la police pour leurre d’enfants sur Internet et le passage à l’acte physique. Résultats: Les analyses ont montré que la majorité des sujets n’avaient aucun antécédent judiciaire. Pour la plupart, le leurre d’enfants est le crime le plus grave perpétré au cours de leur carrière criminelle. Trois catégories d’individus ont été décelées : les amateurs, les spécialistes et les généralistes. Ce sont les individus polymorphes ayant une carrière criminelle plus grave et plus longue qui sont portés à agresser sexuellement avant le leurre. Cependant, ce sont des individus spécialisés ayant une importante proportion de délits sexuels dans leurs antécédents criminels qui ont plus de chance d’agresser sexuellement suite à l’exploitation sexuelle sur Internet.
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Objectifs: L’objectif principal de ce mémoire consiste à comprendre les caractéristiques des carrières criminelles d’individus connus de la police pour avoir perpétré une infraction de leurre d’enfants sur Internet. Aussi, par une analyse typologique à l’aide des antécédents criminels, il sera possible d’établir une typologie d’individus ayant leurré des enfants sur Internet. Également, il sera question de vérifier s’il y a un lien entre les caractéristiques des antécédents criminels de ces individus sur la perpétration de l’agression sexuelle hors ligne. Méthodologie: Provenant de données officielles de la communauté policière du Québec, l’échantillon comprend les parcours de criminels ayant perpétré une infraction de leurre d’enfants sur Internet. Des analyses descriptives en lien avec les différents paramètres de la carrière criminelle seront effectuées. Ensuite, des tests de moyenne et une analyse de régression Cox permettront de vérifier la présence ou non d’un lien statistique entre les caractéristiques des antécédents criminels des individus connus de la police pour leurre d’enfants sur Internet et le passage à l’acte physique. Résultats: Les analyses ont montré que la majorité des sujets n’avaient aucun antécédent judiciaire. Pour la plupart, le leurre d’enfants est le crime le plus grave perpétré au cours de leur carrière criminelle. Trois catégories d’individus ont été décelées : les amateurs, les spécialistes et les généralistes. Ce sont les individus polymorphes ayant une carrière criminelle plus grave et plus longue qui sont portés à agresser sexuellement avant le leurre. Cependant, ce sont des individus spécialisés ayant une importante proportion de délits sexuels dans leurs antécédents criminels qui ont plus de chance d’agresser sexuellement suite à l’exploitation sexuelle sur Internet.
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Artificial Intelligence is reshaping the field of fashion industry in different ways. E-commerce retailers exploit their data through AI to enhance their search engines, make outfit suggestions and forecast the success of a specific fashion product. However, it is a challenging endeavour as the data they possess is huge, complex and multi-modal. The most common way to search for fashion products online is by matching keywords with phrases in the product's description which are often cluttered, inadequate and differ across collections and sellers. A customer may also browse an online store's taxonomy, although this is time-consuming and doesn't guarantee relevant items. With the advent of Deep Learning architectures, particularly Vision-Language models, ad-hoc solutions have been proposed to model both the product image and description to solve this problems. However, the suggested solutions do not exploit effectively the semantic or syntactic information of these modalities, and the unique qualities and relations of clothing items. In this work of thesis, a novel approach is proposed to address this issues, which aims to model and process images and text descriptions as graphs in order to exploit the relations inside and between each modality and employs specific techniques to extract syntactic and semantic information. The results obtained show promising performances on different tasks when compared to the present state-of-the-art deep learning architectures.
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This paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model generalization capability. Computational efficiency of the density construction is ensured using an orthogonal forward regression, and the algorithm incrementally minimizes the leave-one-out test score. A local regularization method is incorporated naturally into the density construction process to further enforce sparsity. An additional advantage of the proposed algorithm is that it is fully automatic and the user is not required to specify any criterion to terminate the density construction procedure. This is in contrast to an existing state-of-art kernel density estimation method using the support vector machine (SVM), where the user is required to specify some critical algorithm parameter. Several examples are included to demonstrate the ability of the proposed algorithm to effectively construct a very sparse kernel density estimate with comparable accuracy to that of the full sample optimized Parzen window density estimate. Our experimental results also demonstrate that the proposed algorithm compares favorably with the SVM method, in terms of both test accuracy and sparsity, for constructing kernel density estimates.