994 resultados para prediction equations


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Objective To evaluate the association of Doppler of uterine artery and flow-mediated dilation of brachial artery (FMD) in the assessment of placental perfusion and endothelial function to predict preeclampsia. Materials and Methods A total of 91 patients considered as at risk for developing preeclampsia were recruited at the prenatal unit of the authors' institution. All the patients underwent FMD and Doppler of uterine arteries between their 24th and 28th gestational weeks. Calculations of sensitivity and specificity for both isolated and associated methods were performed. Results Nineteen out of the 91 patients developed preeclampsia, while the rest remained normotensive. Doppler flowmetry of uterine arteries with presence of bilateral protodiastolic notch had sensitivity of 63.1% and specificity of 87.5% for the prediction of preeclampsia. Considering a cutoff value of 6.5%, FMD showed sensitivity of 84.2% and specificity of 73.6%. In a parallel analysis, as the two methods were associated, sensitivity was 94.2% and specificity, 64.4%. Conclusion The association of Doppler study of uterine arteries and FMD has proved to be an interesting clinical strategy for the prediction of preeclampsia, which may represent a positive impact on prenatal care of patients considered as at high-risk for developing such a condition.

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Trabecular bone score (TBS) is a gray-level textural index of bone microarchitecture derived from lumbar spine dual-energy X-ray absorptiometry (DXA) images. TBS is a bone mineral density (BMD)-independent predictor of fracture risk. The objective of this meta-analysis was to determine whether TBS predicted fracture risk independently of FRAX probability and to examine their combined performance by adjusting the FRAX probability for TBS. We utilized individual-level data from 17,809 men and women in 14 prospective population-based cohorts. Baseline evaluation included TBS and the FRAX risk variables, and outcomes during follow-up (mean 6.7 years) comprised major osteoporotic fractures. The association between TBS, FRAX probabilities, and the risk of fracture was examined using an extension of the Poisson regression model in each cohort and for each sex and expressed as the gradient of risk (GR; hazard ratio per 1 SD change in risk variable in direction of increased risk). FRAX probabilities were adjusted for TBS using an adjustment factor derived from an independent cohort (the Manitoba Bone Density Cohort). Overall, the GR of TBS for major osteoporotic fracture was 1.44 (95% confidence interval [CI] 1.35-1.53) when adjusted for age and time since baseline and was similar in men and women (p > 0.10). When additionally adjusted for FRAX 10-year probability of major osteoporotic fracture, TBS remained a significant, independent predictor for fracture (GR = 1.32, 95% CI 1.24-1.41). The adjustment of FRAX probability for TBS resulted in a small increase in the GR (1.76, 95% CI 1.65-1.87 versus 1.70, 95% CI 1.60-1.81). A smaller change in GR for hip fracture was observed (FRAX hip fracture probability GR 2.25 vs. 2.22). TBS is a significant predictor of fracture risk independently of FRAX. The findings support the use of TBS as a potential adjustment for FRAX probability, though the impact of the adjustment remains to be determined in the context of clinical assessment guidelines. © 2015 American Society for Bone and Mineral Research.

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In this work is presented and tested (for 106 adducts, mainly of the zinc group halides) two empirical equations supported in TG data to estimate the value of the metal-ligand bond dissociation enthalpy for adducts: <D> (M-O) = t i / g if t i < 420 K and <D> (M-O) = (t i / g ) - 7,75 . 10-2 . t i if t i > 420 K. In this empirical equations, t i is the thermodynamic temperature of the beginning of the thermal decomposition of the adduct, as determined by thermogravimetry, andg is a constant factor that is function of the metal halide considered and of the number of ligands, but is not dependant of the ligand itself. To half of the tested adducts the difference between experimental and calculated values was less than 5%. To about 80% of the tested adducts, the difference between the experimental (calorimetric) and the calculated (using the proposed equations) values are less than 15%.

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Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM), which conciliates the two types of observations

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Experimentally, Ce2O3 films are used to study cerium oxide in its fully or partially reduced state, as present in many applications. We have explored the space of low energy Ce2O3 nanofilms using structure prediction and density functional calculations, yielding more than 30 distinct nanofilm structures. First, our results help to rationalize the roles of thermodynamics and kinetics in the preparation of reduced ceria nanofilms with different bulk crystalline structures (e.g. A-type or bixbyite) depending on the support used. Second, we predict a novel, as yet experimentally unresolved, nanofilm which has a structure that does not correspond to any previously reported bulk A2B3 phase and which has an energetic stability between that of A-type and bixbyite. To assist identification and fabrication of this new Ce2O3 nanofilm we calculate some observable properties and propose supports for its epitaxial growth.

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Automobile bodily injury (BI) claims remain unsettled for a long time after the accident. The estimation of an accurate reserve for Reported But Not Settled (RBNS) claims is therefore vital for insurers. In accordance with the recommendation included in the Solvency II project (CEIOPS, 2007) a statistical model is here implemented for RBNS reserve estimation. Lognormality on empirical compensation cost data is observed for different levels of BI severity. The individual claim provision is estimated by allocating the expected mean compensation for the predicted severity of the victim’s injury, for which the upper bound is also computed. The BI severity is predicted by means of a heteroscedastic multiple choice model, because empirical evidence has found that the variability in the latent severity of injured individuals travelling by car is not constant. It is shown that this methodology can improve the accuracy of RBNS reserve estimation at all stages, as compared to the subjective assessment that has traditionally been made by practitioners.

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A model to solve heat and mass balances during the offdesign load calculations was created. These equations are complex and nonlinear. The main new ideas used in the created offdesign model of a kraft recovery boiler are the use of heat flows as torn iteration variables instead of the current practice of using the mass flows, vectorizing equation solving, thus speeding up the process, using non dimensional variables for solving the multiple heat transfer surface problem and using a new procedure for calculating pressure losses. Recovery boiler heat and mass balances are reduced to vector form. It is shown that these vectorized equations can be solved virtually without iteration. The iteration speed is enhanced by the use of the derived method of calculating multiple heat transfer surfaces simultaneously. To achieve this quick convergence the heat flows were used as the torn iteration parameters. A new method to handle pressure loss calculations with linearization was presented. This method enabled less time to be spent calculating pressure losses. The derived vector representation of the steam generator was used to calculate offdesign operation parameters for a 3000 tds/d example recovery boiler. The model was used to study recovery boiler part load operation and the effect of the black liquor dry solids increase on recovery boiler dimensioning. Heat flows to surface elements for part load calculations can be closely approximated with a previously defined exponent function. The exponential method can be used for the prediction of fouling in kraft recovery boilers. For similar furnaces the firing of 80 % dry solids liquor produces lower hearth heat release rate than the 65 % dry solids liquor if we fire at constant steam flow. The furnace outlet temperatures show that capacity increase with firing rate increase produces higher loadings than capacity increase with dry solids increase. The economizers, boiler banks and furnaces can be dimensioned smaller if we increase the black liquor dry solids content. The main problem with increased black liquor dry solids content is the decrease in the heat available to superheat. Whenever possible the furnace exit temperature should be increased by decreasing the furnace height. The increase in the furnace exit temperature is usually opposed because of fear of increased corrosion.

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The present thesis in focused on the minimization of experimental efforts for the prediction of pollutant propagation in rivers by mathematical modelling and knowledge re-use. Mathematical modelling is based on the well known advection-dispersion equation, while the knowledge re-use approach employs the methods of case based reasoning, graphical analysis and text mining. The thesis contribution to the pollutant transport research field consists of: (1) analytical and numerical models for pollutant transport prediction; (2) two novel techniques which enable the use of variable parameters along rivers in analytical models; (3) models for the estimation of pollutant transport characteristic parameters (velocity, dispersion coefficient and nutrient transformation rates) as functions of water flow, channel characteristics and/or seasonality; (4) the graphical analysis method to be used for the identification of pollution sources along rivers; (5) a case based reasoning tool for the identification of crucial information related to the pollutant transport modelling; (6) and the application of a software tool for the reuse of information during pollutants transport modelling research. These support tools are applicable in the water quality research field and in practice as well, as they can be involved in multiple activities. The models are capable of predicting pollutant propagation along rivers in case of both ordinary pollution and accidents. They can also be applied for other similar rivers in modelling of pollutant transport in rivers with low availability of experimental data concerning concentration. This is because models for parameter estimation developed in the present thesis enable the calculation of transport characteristic parameters as functions of river hydraulic parameters and/or seasonality. The similarity between rivers is assessed using case based reasoning tools, and additional necessary information can be identified by using the software for the information reuse. Such systems represent support for users and open up possibilities for new modelling methods, monitoring facilities and for better river water quality management tools. They are useful also for the estimation of environmental impact of possible technological changes and can be applied in the pre-design stage or/and in the practical use of processes as well.

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Research on color difference evaluation has been active in recent thirty years. Several color difference formulas were developed for industrial applications. The aims of this thesis are to develop the color density which is denoted by comb g and to propose the color density based chromaticity difference formulas. Color density is derived from the discrimination ellipse parameters and color positions in the xy , xyY and CIELAB color spaces, and the color based chromaticity difference formulas are compared with the line element formulas and CIE 2000 color difference formulas. As a result of the thesis, color density represents the perceived color difference accurately, and it could be used to characterize a color by the attribute of perceived color difference from this color.

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Genetic algorithm and partial least square (GA-PLS) and kernel PLS (GA-KPLS) techniques were used to investigate the correlation between retention indices (RI) and descriptors for 117 diverse compounds in essential oils from 5 Pimpinella species gathered from central Turkey which were obtained by gas chromatography and gas chromatography-mass spectrometry. The square correlation coefficient leave-group-out cross validation (LGO-CV) (Q²) between experimental and predicted RI for training set by GA-PLS and GA-KPLS was 0.940 and 0.963, respectively. This indicates that GA-KPLS can be used as an alternative modeling tool for quantitative structure-retention relationship (QSRR) studies.

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Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed.

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O objetivo do trabalho foi testar o modelo WEPP (Water Erosion Prediction Project), através de comparações entre volume de enxurrada e perda de solo observados experimentalmente, provenientes dos segmentos de estradas florestais submetidas à chuva natural com inclinações de 1 e 7% e comprimentos de rampa de 20 e 40 m, e aqueles preditos pelo aplicativo, visando o desenvolvimento de um modelo brasileiro de predição de erosão em estradas florestais. Na determinação da quantidade do material erodido foram instalados tambores coletores, com capacidade de 209,25 litros, localizados na parte inferior das estradas, onde foram inseridas tubulações de PVC de 2 polegadas para coleta dos sedimentos provenientes da estrada propriamente dita. Nos tambores coletores foram feitos orifícios nivelados e perfeitamente iguais, posicionados a 0,65 m do fundo do primeiro e a 0,60 m do fundo do segundo, que funcionaram como um divisor Geib. Nas parcelas de 20 e 40 m de comprimento foram feitos cinco e sete orifícios, respectivamente, no primeiro e segundo tambores. O terceiro tambor foi utilizado para coletar o excedente da enxurrada proveniente do segundo tambor. Os tambores foram ligados em série, através de cano PVC de 2 polegadas. Os dados de volume e intensidade de precipitação diária foram obtidos com a instalação de pluviômetro e pluviógrafo no local. O período de coleta de dados foi de um ano, concentrando-se na época das chuvas. Posteriormente, os arquivos de clima, precipitação, solo, inclinação e comprimento do segmento foram introduzidos e adaptados ao modelo de predição de erosão WEPP com o propósito de testá-lo, visando a confecção de um modelo apropriado às condições brasileiras.