942 resultados para multivariate curve resolution


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ABSTRACT: Despite the reduction in deforestation rate in recent years, the impact of global warming by itself can cause changes in vegetation cover. The objective of this work was to investigate the possible changes on the major Brazilian biome, the Amazon Rainforest, under different climate change scenarios. The dynamic vegetation models may simulate changes in vegetation distribution and the biogeochemical processes due to climate change. Initially, the Inland dynamic vegetation model was forced with initial and boundary conditions provided by CFSR and the Eta regional climate model driven by the historical simulation of HadGEM2-ES. These simulations were validated using the Santarém tower data. In the second part, we assess the impact of a future climate change on the Amazon biome by applying the Inland model forced with regional climate change projections. The projections show that some areas of rainforest in the Amazon region are replaced by deciduous forest type and grassland in RCP4.5 scenario and only by grassland in RCP8.5 scenario at the end of this century. The model indicates a reduction of approximately 9% in the area of tropical forest in RCP4.5 scenario and a further reduction in the RCP8.5 scenario of about 50% in the eastern region of Amazon. Although the increase of CO2 atmospheric concentration may favour the growth of trees, the projections of Eta-HadGEM2-ES show increase of temperature and reduction of rainfall in the Amazon region, which caused the forest degradation in these simulations.

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BACKGROUND To validate a new practical Sepsis Severity Score for patients with complicated intra-abdominal infections (cIAIs) including the clinical conditions at the admission (severe sepsis/septic shock), the origin of the cIAIs, the delay in source control, the setting of acquisition and any risk factors such as age and immunosuppression. METHODS The WISS study (WSES cIAIs Score Study) is a multicenter observational study underwent in 132 medical institutions worldwide during a four-month study period (October 2014-February 2015). Four thousand five hundred thirty-three patients with a mean age of 51.2 years (range 18-99) were enrolled in the WISS study. RESULTS Univariate analysis has shown that all factors that were previously included in the WSES Sepsis Severity Score were highly statistically significant between those who died and those who survived (p < 0.0001). The multivariate logistic regression model was highly significant (p < 0.0001, R2 = 0.54) and showed that all these factors were independent in predicting mortality of sepsis. Receiver Operator Curve has shown that the WSES Severity Sepsis Score had an excellent prediction for mortality. A score above 5.5 was the best predictor of mortality having a sensitivity of 89.2 %, a specificity of 83.5 % and a positive likelihood ratio of 5.4. CONCLUSIONS WSES Sepsis Severity Score for patients with complicated Intra-abdominal infections can be used on global level. It has shown high sensitivity, specificity, and likelihood ratio that may help us in making clinical decisions.

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Univariate statistical control charts, such as the Shewhart chart, do not satisfy the requirements for process monitoring on a high volume automated fuel cell manufacturing line. This is because of the number of variables that require monitoring. The risk of elevated false alarms, due to the nature of the process being high volume, can present problems if univariate methods are used. Multivariate statistical methods are discussed as an alternative for process monitoring and control. The research presented is conducted on a manufacturing line which evaluates the performance of a fuel cell. It has three stages of production assembly that contribute to the final end product performance. The product performance is assessed by power and energy measurements, taken at various time points throughout the discharge testing of the fuel cell. The literature review performed on these multivariate techniques are evaluated using individual and batch observations. Modern techniques using multivariate control charts on Hotellings T2 are compared to other multivariate methods, such as Principal Components Analysis (PCA). The latter, PCA, was identified as the most suitable method. Control charts such as, scores, T2 and DModX charts, are constructed from the PCA model. Diagnostic procedures, using Contribution plots, for out of control points that are detected using these control charts, are also discussed. These plots enable the investigator to perform root cause analysis. Multivariate batch techniques are compared to individual observations typically seen on continuous processes. Recommendations, for the introduction of multivariate techniques that would be appropriate for most high volume processes, are also covered.

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Electromagnetic scattering inverse problems, microwave imaging, reconstruction of dielectric media, remote sensing, tomography

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Background:The applicability of international risk scores in heart surgery (HS) is not well defined in centers outside of North America and Europe.Objective:To evaluate the capacity of the Parsonnet Bernstein 2000 (BP) and EuroSCORE (ES) in predicting in-hospital mortality (IHM) in patients undergoing HS at a reference hospital in Brazil and to identify risk predictors (RP).Methods:Retrospective cohort study of 1,065 patients, with 60.3% patients underwent coronary artery bypass grafting (CABG), 32.7%, valve surgery and 7.0%, CABG combined with valve surgery. Additive and logistic scores models, the area under the ROC (Receiver Operating Characteristic) curve (AUC) and the standardized mortality ratio (SMR) were calculated. Multivariate logistic regression was performed to identify the RP.Results:Overall mortality was 7.8%. The baseline characteristics of the patients were significantly different in relation to BP and ES. AUCs of the logistic and additive BP were 0.72 (95% CI, from 0.66 to 0.78 p = 0.74), and of ES they were 0.73 (95% CI; 0.67 to 0.79 p = 0.80). The calculation of the SMR in BP was 1.59 (95% CI; 1.27 to 1.99) and in ES, 1.43 (95% CI; 1.14 to 1.79). Seven RP of IHM were identified: age, serum creatinine > 2.26 mg/dL, active endocarditis, systolic pulmonary arterial pressure > 60 mmHg, one or more previous HS, CABG combined with valve surgery and diabetes mellitus.Conclusion:Local scores, based on the real situation of local populations, must be developed for better assessment of risk in cardiac surgery.

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Magdeburg, Univ., Fak. für Mathematik, Diss., 2011

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Background: Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective: To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods: The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results: The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion: The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.

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Abstract Background: Cardiac resynchronization therapy (CRT) is the recommended treatment by leading global guidelines. However, 30%-40% of selected patients are non-responders. Objective: To develop an echocardiographic model to predict cardiac death or transplantation (Tx) 1 year after CRT. Method: Observational, prospective study, with the inclusion of 116 patients, aged 64.89 ± 11.18 years, 69.8% male, 68,1% in NYHA FC III and 31,9% in FC IV, 71.55% with left bundle-branch block, and median ejection fraction (EF) of 29%. Evaluations were made in the pre‑implantation period and 6-12 months after that, and correlated with cardiac mortality/Tx at the end of follow-up. Cox and logistic regression analyses were performed with ROC and Kaplan-Meier curves. The model was internally validated by bootstrapping. Results: There were 29 (25%) deaths/Tx during follow-up of 34.09 ± 17.9 months. Cardiac mortality/Tx was 16.3%. In the multivariate Cox model, EF < 30%, grade III/IV diastolic dysfunction and grade III mitral regurgitation at 6‑12 months were independently related to increased cardiac mortality or Tx, with hazard ratios of 3.1, 4.63 and 7.11, respectively. The area under the ROC curve was 0.78. Conclusion: EF lower than 30%, severe diastolic dysfunction and severe mitral regurgitation indicate poor prognosis 1 year after CRT. The combination of two of those variables indicate the need for other treatment options.

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Magdeburg, Univ., Fak. für Naturwiss., Diss., 2009

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Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2009

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Abstract Background: Pulmonary hypertension is associated with poor prognosis in heart failure. However, non-invasive diagnosis is still challenging in clinical practice. Objective: We sought to assess the prognostic utility of non-invasive estimation of pulmonary vascular resistances (PVR) by cardiovascular magnetic resonance to predict adverse cardiovascular outcomes in heart failure with reduced ejection fraction (HFrEF). Methods: Prospective registry of patients with left ventricular ejection fraction (LVEF) < 40% and recently admitted for decompensated heart failure during three years. PVRwere calculated based on right ventricular ejection fraction and average velocity of the pulmonary artery estimated during cardiac magnetic resonance. Readmission for heart failure and all-cause mortality were considered as adverse events at follow-up. Results: 105 patients (average LVEF 26.0 ±7.7%, ischemic etiology 43%) were included. Patients with adverse events at long-term follow-up had higher values of PVR (6.93 ± 1.9 vs. 4.6 ± 1.7estimated Wood Units (eWu), p < 0.001). In multivariate Cox regression analysis, PVR ≥ 5 eWu(cutoff value according to ROC curve) was independently associated with increased risk of adverse events at 9 months follow-up (HR2.98; 95% CI 1.12-7.88; p < 0.03). Conclusions: In patients with HFrEF, the presence of PVR ≥ 5.0 Wu is associated with significantly worse clinical outcome at follow-up. Non-invasive estimation of PVR by cardiac magnetic resonance might be useful for risk stratification in HFrEF, irrespective of etiology, presence of late gadolinium enhancement or LVEF.

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Magdeburg, Univ., Fak. für Mathematik, Diss., 2013