Carotid Intima-Media Thickness and Carotid Plaques Improves Prediction of Obstructive Angiographic Coronary Artery Disease in Women

Does carotid intima-media thickness (cIMT), a surrogate marker of cardiovascular events, have predictive incremental value over established risk factors for stable coronary artery disease (CAD)? Prospective study of 300 patients, with suspected stable CAD, admitted for an elective coronary angiography and carotid ultrasound. The CAD patients had a higher cIMT, which showed a modest predictive accuracy for CAD (area under the receiver-operating characteristic curve 0.638, 95% confidence interval 0.576-0.701, P < .001). The cIMT was an independent predictor of CAD, together with age, gender, and diabetes. C-statistic for CAD prediction by traditional risk factors was not significantly different from a model that included cIMT, carotid plaque presence, or both. However, in women, it was significantly increased by the addition of cIMT or carotid plaque presence. Although cIMT cannot be used as a sole indicator of CAD, it should be considered in the panel of investigations that is requested, particularly in women who are candidates for coronary angiography.

Aircraft Engines Maintenance Costs and Reliability: An Appraisal of the Decision Process to Remove an Engine for a Shop Visit Aiming at Minimum Maintenance Unit Cost

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação.

An application of reliability-based robustness assessment of steel moment resisting frame structures under post-mainshock cascading events

The paper presented herein proposes a reliability-based framework for quantifying the structural robustness considering the occurrence of a major earthquake (mainshock) and subsequent cascading hazard events, such as aftershocks that are triggered by the mainshock. These events can significantly increase the probability of failure of buildings, especially for structures that are damaged during the mainshock. The application of the proposed framework is exemplified through three numerical case studies. The case studies correspond to three SAC steel moment frame buildings of 3-, 9-, and 20- stories, which were designed to pre-Northridge codes and standards. Twodimensional nonlinear finite element models of the buildings are developed using the Open System for Earthquake Engineering Simulation framework (OpenSees), using a finite-length plastic hinge beam model and a bilinear constitutive law with deterioration, and are subjected to multiple mainshock-aftershock seismic sequences. For the three buildings analyzed herein, it is shown that the structural reliability under a single seismic event can be significantly different from that under a sequence of seismic events. The reliability-based robustness indicator used shows that the structural robustness is influenced by the extent by which a structure can distribute damage.

High or low initial setting price?: Initial setting price as prediction of intention to bid in on line auctions

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Correction of the anisotropy in resistivity: application to pore pressure prediction

Dissertação para obtenção do Grau de Mestre em Engenharia Geológica (Georrecursos)

Numerical prediction of diffusion and electric field-induced iron nanoparticle transport

Zero valent iron nanoparticles (nZVI) are considered very promising for the remediation of contaminated soils and groundwaters. However, an important issue related to their limited mobility remains unsolved. Direct current can be used to enhance the nanoparticles transport, based on the same principles of electrokinetic remediation. In this work, a generalized physicochemical model was developed and solved numerically to describe the nZVI transport through porous media under electric field, and with different electrolytes (with different ionic strengths). The model consists of the Nernst–Planck coupled system of equations, which accounts for the mass balance of ionic species in a fluid medium, when both the diffusion and electromigration of the ions are considered. The diffusion and electrophoretic transport of the negatively charged nZVI particles were also considered in the system. The contribution of electroosmotic flow to the overall mass transport was included in the model for all cases. The nZVI effective mobility values in the porous medium are very low (10−7–10−4 cm2 V−1 s−1), due to the counterbalance between the positive electroosmotic flow and the electrophoretic transport of the negatively charged nanoparticles. The higher the nZVI concentration is in the matrix, the higher the aggregation; therefore, low concentration of nZVI suspensions must be used for successful field application.

Development of 3D in vitro models for prediction of hepatic metabolism and toxicity

The development of human cell models that recapitulate hepatic functionality allows the study of metabolic pathways involved in toxicity and disease. The increased biological relevance, cost-effectiveness and high-throughput of cell models can contribute to increase the efficiency of drug development in the pharmaceutical industry. Recapitulation of liver functionality in vitro requires the development of advanced culture strategies to mimic in vivo complexity, such as 3D culture, co-cultures or biomaterials. However, complex 3D models are typically associated with poor robustness, limited scalability and compatibility with screening methods. In this work, several strategies were used to develop highly functional and reproducible spheroid-based in vitro models of human hepatocytes and HepaRG cells using stirred culture systems. In chapter 2, the isolation of human hepatocytes from resected liver tissue was implemented and a liver tissue perfusion method was optimized towards the improvement of hepatocyte isolation and aggregation efficiency, resulting in an isolation protocol compatible with 3D culture. In chapter 3, human hepatocytes were co-cultivated with mesenchymal stem cells (MSC) and the phenotype of both cell types was characterized, showing that MSC acquire a supportive stromal function and hepatocytes retain differentiated hepatic functions, stability of drug metabolism enzymes and higher viability in co-cultures. In chapter 4, a 3D alginate microencapsulation strategy for the differentiation of HepaRG cells was evaluated and compared with the standard 2D DMSO-dependent differentiation, yielding higher differentiation efficiency, comparable levels of drug metabolism activity and significantly improved biosynthetic activity. The work developed in this thesis provides novel strategies for 3D culture of human hepatic cell models, which are reproducible, scalable and compatible with screening platforms. The phenotypic and functional characterization of the in vitro systems performed contributes to the state of the art of human hepatic cell models and can be applied to the improvement of pre-clinical drug development efficiency of the process, model disease and ultimately, development of cell-based therapeutic strategies for liver failure.

Credit default swap (CDS) prediction model & trading strategy

This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.

Prediction of hyperglycemia in preterm newborn infants

Many conditions are associated with hyperglycemia in preterm neonates because they are very susceptible to changes in carbohydrate homeostasis. The purpose of this study was to evaluate the occurrence of hyperglycemia in preterm infants undergoing glucose infusion during the first week of life, and to enumerate the main variables predictive of hyperglycemia. This prospective study (during 1994) included 40 preterm neonates (gestational age <37 weeks); 511 determinations of glycemic status were made in these infants (average 12.8/infant), classified by gestational age, birth weight, glucose infusion rate and clinical status at the time of determination (based on clinical and laboratory parameters). The clinical status was classified as stable or unstable, as an indication of the stability or instability of the mechanisms governing glucose homeostasis at the time of determination of blood glucose; 59 episodes of hyperglycemia (11.5%) were identified. A case-control study was used (case = hyperglycemia; control = normoglycemia) to derive a model for predicting glycemia. The risk factors considered were gestational age (<=31 vs. >31 weeks), birth weight (<=1500 vs. >1500 g), glucose infusion rate (<=6 vs. >6 mg/kg/min) and clinical status (stable vs. unstable). Multivariate analysis by logistic regression gave the following mathematical model for predicting the probability of hyperglycemia: 1/exp{-3.1437 + 0.5819(GA) + 0.9234(GIR) + 1.0978(Clinical status)} The main predictive variables in our study, in increasing order of importance, were gestational age, glucose infusion rate and, the clinical status (stable or unstable) of the preterm newborn infant. The probability of hyperglycemia ranged from 4.1% to 36.9%.

Evaluation of efficacy, reliability, and tolerability of sibutramine in obese patients, with an echocardiographic study

This is a double-blind, placebo-controlled study of the efficacy, safety, and tolerability of sibutramine in the management of obese patients for a 6-month period. METHOD: Sixty-one obese patients (BMI >30, <40 kg/m2), aged 18-65 years were evaluated. In the first phase of the study (30 days), the patients were given a placebo. We monitored compliance with a low-calorie diet (1200 kcal/day) and to the placebo. In the next stage, the double-blind phase (6 months), we compared placebo and sibutramine (10 mg/day). The criteria for evaluating efficacy were weight loss, reduction in body mass index (BMI), and abdominal and hip circumferences. Tolerability was assessed based on reported side effects, variation in arterial blood pressure and heart rate, metabolic profile (fasting glucose, total cholesterol and its fractions, and triglycerides), laboratory tests (renal and hepatic functions), and flow Doppler echocardiogram. RESULTS: We observed a greater weight loss (7.3 kg, 8% vs 2.6 kg, 2.8%) and a reduction in body mass index (7.4% vs 2.1%) in the sibutramine group than in the placebo group. Classifying the patients into 4 subgroups according to weight loss (weight gain, loss <5%, loss of 5% to 9.9%, and loss >10%), we observed a weight loss of >5% in 40% of the patients on sibutramine compared with 12.9% in the placebo group. We also detected weight gain in 45.2% of the placebo group compared to 20% in the sibutramine group. The sibutramine group showed improvement in HDL- cholesterol values (increased by 17%) and triglyceride values (decreased by 12.8%). This group also showed an increase in systolic blood pressure (6.7%, 5 mmHg). There were no changes in echocardiograms comparing the beginning and end of follow-up, and side effects did not lead to discontinuation of treatment. DISCUSSION: Sibutramine proved to be effective for weight loss providing an 8% loss of the initial weight. Compliance to prolonged treatment was good, and side effects did not result in discontinuation of treatment. These data confirmed the good efficacy, tolerability, and safety profiles of sibutramine for treatment of obesity.

Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

Integration of geometric consistency contributory factors in three-leg junctions collision prediction models of Portuguese two-lane national highways

This paper aims at developing a collision prediction model for three-leg junctions located in national roads (NR) in Northern Portugal. The focus is to identify factors that contribute for collision type crashes in those locations, mainly factors related to road geometric consistency, since literature is scarce on those, and to research the impact of three modeling methods: generalized estimating equations, random-effects negative binomial models and random-parameters negative binomial models, on the factors of those models. The database used included data published between 2008 and 2010 of 177 three-leg junctions. It was split in three groups of contributing factors which were tested sequentially for each of the adopted models: at first only traffic, then, traffic and the geometric characteristics of the junctions within their area of influence; and, lastly, factors which show the difference between the geometric characteristics of the segments boarding the junctionsâ area of influence and the segment included in that area were added. The choice of the best modeling technique was supported by the result of a cross validation made to ascertain the best model for the three sets of researched contributing factors. The models fitted with random-parameters negative binomial models had the best performance in the process. In the best models obtained for every modeling technique, the characteristics of the road environment, including proxy measures for the geometric consistency, along with traffic volume, contribute significantly to the number of collisions. Both the variables concerning junctions and the various national highway segments in their area of influence, as well as variations from those characteristics concerning roadway segments which border the already mentioned area of influence have proven their relevance and, therefore, there is a rightful need to incorporate the effect of geometric consistency in the three-leg junctions safety studies.

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

Assessment of the performance of steel fibre reinforced self-compacting concrete in elevated slabs

The reinforcement mechanisms at the cross section level assured by fibres bridging the cracks in steel fibre reinforced self-compacting concrete (SFRSCC) can be significantly amplified at structural level when the SFRSCC is applied in structures with high support redundancy, such is the case of elevated slab systems. To evaluate the potentialities of SFRSCC as the fundamental material of elevated slab systems, a ¼ scale SFRSCC prototype of a residential building was designed, built and tested. The extensive experimental program includes material tests for characterizing the relevant properties of SFRSCC, as well as structural tests for assessing the performance of the prototype at serviceability and ultimate limit conditions. Three distinct approaches where adopted to derive the constitutive laws of the SFRSCC in tension that were used in finite element material nonlinear analysis to evaluate the reliability of these approaches in the prediction of the load carrying capacity of the prototype.