Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Catalyst screening: Refinement of the origin of the volcano curve and its implication in heterogeneous catalysis

Understanding the overall catalytic activity trend for rational catalyst design is one of the core goals in heterogeneous catalysis. In the past two decades, the development of density functional theory (DFT) and surface kinetics make it feasible to theoretically evaluate and predict the catalytic activity variation of catalysts within a descriptor-based framework. Thereinto, the concept of the volcano curve, which reveals the general activity trend, usually constitutes the basic foundation of catalyst screening. However, although it is a widely accepted concept in heterogeneous catalysis, its origin lacks a clear physical picture and definite interpretation. Herein, starting with a brief review of the development of the catalyst screening framework, we use a two-step kinetic model to refine and clarify the origin of the volcano curve with a full analytical analysis by integrating the surface kinetics and the results of first-principles calculations. It is mathematically demonstrated that the volcano curve is an essential property in catalysis, which results from the self-poisoning effect accompanying the catalytic adsorption process. Specifically, when adsorption is strong, it is the rapid decrease of surface free sites rather than the augmentation of energy barriers that inhibits the overall reaction rate and results in the volcano curve. Some interesting points and implications in assisting catalyst screening are also discussed based on the kinetic derivation. Moreover, recent applications of the volcano curve for catalyst design in two important photoelectrocatalytic processes (the hydrogen evolution reaction and dye-sensitized solar cells) are also briefly discussed.

Microstructural-based approach to the interpretation of clays and transitional soils behaviour

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2016.

Economic development and Environmental quality: The environmental Kuznets curve for water pollution

The main aim of this study was to analyze evidence of an environmental Kuznets curve for water pollution in the developing and developed countries. The study was conducted based on a panel data set of 54 countries – that were categorized into six groups of “developed countries”, “developing countries”, “developed countries with low income”, “developed countries with high income” and “coastal countries”- between the years 1995 to 2006. The results do not confirm the inverted U-shape of EKC curve for the developed countries with low income. Based on the estimated turning points and the average GDP per capita, the study revealed at which point of the EKC the countries are. Furthermore, impacts of capital-and-labor ratio as well as trade openness are drawn by estimating different models for the EKC. The magnitude role of each explanatory variable on BOD was calculated by estimating the associated elasticity.

Silenciamento do canal de potássio Eag1 potencializa efeitos da temozolomida em células U-87 MG de glioblastoma multiforme

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Ciências da Saúde, Programa de Pós-Graduação em Ciências da Saúde, 2015.

Ação de anestésicos gerais em canais iônicos

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Biológicas, Departamento de Biologia Molecular, 2016.

Hardware processors for pairing-based cryptography

Bilinear pairings can be used to construct cryptographic systems with very desirable properties. A pairing performs a mapping on members of groups on elliptic and genus 2 hyperelliptic curves to an extension of the finite field on which the curves are defined. The finite fields must, however, be large to ensure adequate security. The complicated group structure of the curves and the expensive field operations result in time consuming computations that are an impediment to the practicality of pairing-based systems. The Tate pairing can be computed efficiently using the ɳT method. Hardware architectures can be used to accelerate the required operations by exploiting the parallelism inherent to the algorithmic and finite field calculations. The Tate pairing can be performed on elliptic curves of characteristic 2 and 3 and on genus 2 hyperelliptic curves of characteristic 2. Curve selection is dependent on several factors including desired computational speed, the area constraints of the target device and the required security level. In this thesis, custom hardware processors for the acceleration of the Tate pairing are presented and implemented on an FPGA. The underlying hardware architectures are designed with care to exploit available parallelism while ensuring resource efficiency. The characteristic 2 elliptic curve processor contains novel units that return a pairing result in a very low number of clock cycles. Despite the more complicated computational algorithm, the speed of the genus 2 processor is comparable. Pairing computation on each of these curves can be appealing in applications with various attributes. A flexible processor that can perform pairing computation on elliptic curves of characteristic 2 and 3 has also been designed. An integrated hardware/software design and verification environment has been developed. This system automates the procedures required for robust processor creation and enables the rapid provision of solutions for a wide range of cryptographic applications.

Triceps and subscapular skinfold thicknesses percentiles and cut-offs for overweight and obesity in a population-based sample of schoolchildren in Bogota, Colombia

OBJECTIVES: The aims of this study were to establish a Colombian smoothed centile charts and LMS tables for tríceps, subscapular and sum tríceps+subscapular skinfolds; appropriate cut-offs were selected using receiver operating characteristic analysis based in a populationbased sample of schoolchildren in Bogota, Colombia and to compare them with international studies. METHODS: A total of 9 618 children and adolescents attending public schools in Bogota, Colombia (55.7% girls; age range of 9–17.9 years). Height, weight, body mass index (BMI), waist circumference, triceps and subscapular skinfold measurements were obtained using standardized methods. We have calculated tríceps+subscapular skinfold (T+SS) sum. Smoothed percentile curves for triceps and subscapular skinfold thickness were derived by the LMS method. Receiver operating characteristics curve (ROC) analyses were used to evaluate the optimal cut-off point of tríceps, subscapular and sum tríceps+subscapular skinfolds for overweight and obesity based on the International Obesity Task Force (IOTF) definitions. Data were compared with international studies. RESULTS: Subscapular, triceps skinfolds and T+SS were significantly higher in girls than in boys (P <0.001). The median values for triceps, subscapular as well as T+SS skinfold thickness increased in a sex-specific pattern with age. The ROC analysis showed that subscapular, triceps skinfolds and T+SS have a high discrimination power in the identification of overweight and obesity in the sample population in this study. Based on the raw non-adjusted data, we found that Colombian boys and girls had high triceps and subscapular skinfolds values than their counterparts from Spain, UK, German and US. CONCLUSIONS: Our results provide sex- and age-specific normative reference standards for the triceps and subscapular skinfold thickness values in a large, population-based sample of 3 schoolchildren and adolescents from an Latin-American population. By providing LMS tables for Latin-American people based on Colombian reference data, we hope to provide quantitative tools for the study of obesity and its complications.

Aging assessment of polyethylene-based insulated low-voltage cables for nuclear applications

This thesis aims at investigating the evolution of physico-chemical and electrical properties relevant to low-voltage power cables for nuclear application when subjected to typical nuclear power plant (NPP) environments i.e., to gamma radiation and high temperature. This research is part of the European Project Horizon 2020 TeaM Cables, which aims at providing a novel methodology for efficient and reliable NPP cable aging management to NPP operators. The analyzed samples consist of both coaxial and twisted pair cables with different polymeric compounds used as primary insulation. Insulating materials are based on the same silane cross-linked polyethylene matrix with different additives and fillers. In order to characterize the material response to the environmental stresses, various experimental techniques have been used. These characterizations range from the microscale chemical response e.g. by FTIR, OIT and DSC, to the macroscale electrical and mechanical behavior. A significant part of this Thesis is given to the correlation of the response to aging among the different measured properties. It has been shown that it could be possible to connect both the chemical and mechanical properties of the investigated XLPE cables with the electrical ones. In particular, the high-frequency dielectric response allows an effective monitoring of both the early periods of aging, controlled by the antioxidant consumption kinetics, and then the subsequent oxidation of the polymer matrix. Therefore, dielectric spectroscopy showed to be capable of assessing the LV cable aging state and, it might be used as an aging marker for cable diagnostic. The last part of the manuscript focuses on the building of a predictive modelling approach of LV cable conditions subjected to radio-chemical aging. It resulted into obtaining a lifetime curve which relates the aging factor to which the cable is subjected to, namely the dose rate, with the limit value of the considered electrical property (tanδ).

Analysis of the impact of stationary energy storage systems in trolleybus grids using Simulink-based modelling

The voltage profile of the catenary between traction substations (TSSs) is affected by the trolleybus current intake and by its position with respect to the TSSs: the higher the current requested by the bus and the further the bus from the TSSs, the deeper the voltage drop. When the voltage drops below 500V, the trolleybus is forced to decrease its consumption by reducing its input current. This thesis deals with the analysis of the improvements that the installation of an BESS produces in the operation of a particularly loaded FS of the DC trolleybus network of the city of Bologna. The stationary BESS is charged by the TSSs during off-peak times and delivers the stored energy when the catenary is overloaded alleviating the load on the TSSs and reducing the voltage drops. Only IMC buses are considered in the prospect of a future disposal of all internal combustion engine vehicles. These trolleybuses cause deeper voltage drops because they absorb enough current to power their traction motor and recharge the on board battery. The control of the BESS aims to keep the catenary voltage within the admissible voltage range and makes sure that all physical limitations are met. A model of FS Marconi Trento Trieste is implemented in Simulink environment to simulate its daily operation and compare the behavior of the trolleybus network with and without BESS. From the simulation without BESS, the best location of the energy storage system is deduced, and the battery control is tuned. Furthermore, from the knowledge of the load curve and the battery control trans-characteristic, it is formulated a prediction of the voltage distribution at BESS connection point. The prediction is then compared with the simulation results to validate the Simulink model. The BESS allows to decrease the voltage drops along the catenary, the Joule losses and the current delivered by the TSSs, indicating that the BESS can be a solution to improve the operation of the trolleybus network.

Developing a radiomic based machine learning model to identify patients with resected non-small-cell lung cancer at high risk of relapse

Background There is a wide variation of recurrence risk of Non-small-cell lung cancer (NSCLC) within the same Tumor Node Metastasis (TNM) stage, suggesting that other parameters are involved in determining this probability. Radiomics allows extraction of quantitative information from images that can be used for clinical purposes. The primary objective of this study is to develop a radiomic prognostic model that predicts a 3 year disease free-survival (DFS) of resected Early Stage (ES) NSCLC patients. Material and Methods 56 pre-surgery non contrast Computed Tomography (CT) scans were retrieved from the PACS of our institution and anonymized. Then they were automatically segmented with an open access deep learning pipeline and reviewed by an experienced radiologist to obtain 3D masks of the NSCLC. Images and masks underwent to resampling normalization and discretization. From the masks hundreds Radiomic Features (RF) were extracted using Py-Radiomics. Hence, RF were reduced to select the most representative features. The remaining RF were used in combination with Clinical parameters to build a DFS prediction model using Leave-one-out cross-validation (LOOCV) with Random Forest. Results and Conclusion A poor agreement between the radiologist and the automatic segmentation algorithm (DICE score of 0.37) was found. Therefore, another experienced radiologist manually segmented the lesions and only stable and reproducible RF were kept. 50 RF demonstrated a high correlation with the DFS but only one was confirmed when clinicopathological covariates were added: Busyness a Neighbouring Gray Tone Difference Matrix (HR 9.610). 16 clinical variables (which comprised TNM) were used to build the LOOCV model demonstrating a higher Area Under the Curve (AUC) when RF were included in the analysis (0.67 vs 0.60) but the difference was not statistically significant (p=0,5147).

[almost An Autobiography: A Study Of Social Scientists In Health Based On The Lattes Curriculum].

Among the various ways of adopting the biographical approach, we used the curriculum vitaes (CVs) of Brazilian researchers who work as social scientists in health as our research material. These CVs are part of the Lattes Platform of CNPq - the National Council for Scientific and Technological Development, which includes Research and Institutional Directories. We analyzed 238 CVs for this study. The CVs contain, among other things, the following information: professional qualifications, activities and projects, academic production, participation in panels for the evaluation of theses and dissertations, research centers and laboratories and a summarized autobiography. In this work there is a brief review of the importance of autobiography for the social sciences, emphasizing the CV as a form of autobiographical practice. We highlight some results, such as it being a group consisting predominantly of women, graduates in social sciences, anthropology, sociology or political science, with postgraduate degrees. The highest concentration of social scientists is located in Brazil's southern and southeastern regions. In some institutions the main activities of social scientists are as teachers and researchers with great thematic diversity in research.

Phylogenetics, Ancestral State Reconstruction, And A New Infrafamilial Classification Of The Pantropical Ochnaceae (medusagynaceae, Ochnaceae S.str., Quiinaceae) Based On Five Dna Regions.

Ochnaceae s.str. (Malpighiales) are a pantropical family of about 500 species and 27 genera of almost exclusively woody plants. Infrafamilial classification and relationships have been controversial partially due to the lack of a robust phylogenetic framework. Including all genera except Indosinia and Perissocarpa and DNA sequence data for five DNA regions (ITS, matK, ndhF, rbcL, trnL-F), we provide for the first time a nearly complete molecular phylogenetic analysis of Ochnaceae s.l. resolving most of the phylogenetic backbone of the family. Based on this, we present a new classification of Ochnaceae s.l., with Medusagynoideae and Quiinoideae included as subfamilies and the former subfamilies Ochnoideae and Sauvagesioideae recognized at the rank of tribe. Our data support a monophyletic Ochneae, but Sauvagesieae in the traditional circumscription is paraphyletic because Testulea emerges as sister to the rest of Ochnoideae, and the next clade shows Luxemburgia+Philacra as sister group to the remaining Ochnoideae. To avoid paraphyly, we classify Luxemburgieae and Testuleeae as new tribes. The African genus Lophira, which has switched between subfamilies (here tribes) in past classifications, emerges as sister to all other Ochneae. Thus, endosperm-free seeds and ovules with partly to completely united integuments (resulting in an apparently single integument) are characters that unite all members of that tribe. The relationships within its largest clade, Ochnineae (former Ochneae), are poorly resolved, but former Ochninae (Brackenridgea, Ochna) are polyphyletic. Within Sauvagesieae, the genus Sauvagesia in its broad circumscription is polyphyletic as Sauvagesia serrata is sister to a clade of Adenarake, Sauvagesia spp., and three other genera. Within Quiinoideae, in contrast to former phylogenetic hypotheses, Lacunaria and Touroulia form a clade that is sister to Quiina. Bayesian ancestral state reconstructions showed that zygomorphic flowers with adaptations to buzz-pollination (poricidal anthers), a syncarpous gynoecium (a near-apocarpous gynoecium evolved independently in Quiinoideae and Ochninae), numerous ovules, septicidal capsules, and winged seeds with endosperm are the ancestral condition in Ochnoideae. Although in some lineages poricidal anthers were lost secondarily, the evolution of poricidal superstructures secured the maintenance of buzz-pollination in some of these genera, indicating a strong selective pressure on keeping that specialized pollination system.

Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.