Preliminary EoS for core-collapse supernova simulations with the QMC model

In this work we present the preliminary results of a complete equation of state (EoS) for core-collapse supernova simulations. We treat uniform matter made of nucleons using the the quark-meson coupling (QMC) model. We show a table with a variety of thermodynamic quantities, which covers the proton fraction range $Y_{p}=0-0.65$ with the linear grid spacing $\Delta Y_{p}=0.01$ ($66$ points) and the density range $\rho_{B}=10^{14}-10^{16}$g.cm$^{-3}$ with the logarithmic grid spacing $\Delta log_{10}(\rho_{B}/[$g.cm$^{-3}])=0.1$ ($21$ points). This preliminary study is performed at zero temperature and our results are compared with the widely used EoS already available in the literature

Automotive Interior Sensing - Imaging Solutions

Esta dissertação recai sobre o problema da deteção de objetos dentro do veículo. Comparando todos os algoritmos do estado da arte, abordagens baseadas em R-CNN destacam-se em termos de "Average Precision". Normalmente, os detectores "two-stage" têm taxas de precisão mais altas enquanto os detectores "one-stage" conseguem alcançar menores tempos de inferência. O Mask R-CNN foi escolhido graças aos altos valores de "Average Precision" obtidos sem comprometer o tempo de inferência, assim como fornecer a segmentação de instância dos objetos. Isto pode ser útil para abordagens como o "Multiview" no qual é importante estabelecer uma ligação entre os pontos da imagem adquirida por uma câmera com os pontos da imagem adquirida por outra câmera noutra posição. Foi necessário testar a adaptabilidade da Mask R-CNN para outros "datasets" alterando o "dataset" do COCO para ter um número de classes diferente do original. No fim, a rede treinada sobre o "dataset" da Bosch, foi a Faster R-CNN em que os pesos da Mask usados foram os pré-treinados sobre o COCO.This dissertation addresses the problem of object detection inside the vehicle. Comparing all the state-of-the-art algorithms, approaches based on R-CNN stand out in terms of Average Precision. Typically two-stage detectors have higher accuracy rates while one-stage detectors reaches lower inference times. Mask R-CNN was chosen thanks to the high values obtained for Average Precision without compromising inference times, as well as providing object instance segmentation. This may be useful for approaches such as Multiview in which it is important to match points of the image acquired from one camera with points of the image acquired by other camera in another position. It was necessary to test the adaptability of Mask R-CNN to other datasets by changing COCO dataset to have different number of classes. At the end, the trained network over Bosch dataset, was Faster R-CNN with Mask weights pre-trained over COCO

Modelling and Development of a Microfluidic Platform for Dielectrophoretic Separation of Polymeric Nanoparticles

The interest surrounding particle separation techniques has increased significantly in the past years, due to its importance in chemical and biological analysis, diagnostics, and food processing, among other areas. Out of the vast array of ways that have been used to separate particles in microfluidics, electric field may be the most common means of separation, given its applicability and versatility. Dielectrophoresis (DEP) occurs in the presence of a non-uniform electric field, and in order to achieve such field, there are two main approaches: by creating an array of metal electrodes along the main channel or by utilizing an electrodeless design. This latter approach is based on creating constrictions on the channel while applying an electric field between the inlet(s) and outlet(s) of the channel. In this work, done in the Department of Materials and Production of the University of Aalborg, five different models were designed and fabricated on a single fused silica wafer via photolithography, with the ultimate purpose of continuously separating particles with diameters of 20 nm and 150 nm. A detailed overview of the designs and COMSOL simulations, as well as the fabrication techniques and processes can be found throughout the work. Successful particle separation was achieved in the simulations, at voltages as low as 35 V, with the use of separation channels with a maximum length of 3.1 mm. The fabrication stage of the work was focused on the development of a robust microfabrication process suitable for small, well-defined channels, and its alignment with metal electrodes. Two different fabrication approaches were presented and analysed

Marcha de mulheres idosas e risco de quedas : influência do histórico de queda e medo de cair

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Ceilândia, Programa de Pós-Graduação em Ciências e Tecnologias em Saúde, 2019.Introdução: fatores preditivos e protetores do risco de queda, na marcha geriátrica, sofrem influência de alterações neuromusculares, como o histórico de quedas, e fatores psicogênicos, os quais causam na marcha uma ação motora cautelosa, como o medo de cair. Objetivo: avaliar o perfil da marcha de idosas hígidas e a influência do histórico de queda e o medo de cair, enquanto preditores do risco de queda. Métodos: a dissertação divide-se em dois artigos: o primeiro trata de uma investigação transversal, que analisou a confiabilidade do Gait Profile Score (GPS) em mulheres idosas. A amostra, com 49 participantes, (72,34±6,44 anos) foi estratificada segundo o auto relato do histórico de queda, nos últimos doze meses, em idosas não caidoras, caidoras e caidoras recorrentes. A análise tridimensional da marcha utilizou dados cinemáticos da pelve, quadril, joelho e tornozelo para compor o cálculo do GPS e do Gait Variable Score (GVS). O segundo artigo caracterizou-se por um ensaio clínico não randomizado, no qual as idosas foram alocadas em quatro grupos, segundo o histórico e medo de quedas. A intervenção consistiu em aplicar uma perturbação fictícia durante à análise tridimensional da marcha, a fim de isolar os efeitos do histórico e do medo de cair, as variáveis idade, gênero, índice de massa corporal, nível cognitivo e força muscular foram considerados como fatores confundidores. Resultados: o GPS revelou ser um índice de alta confiabilidade para aplicação nos estudos da marcha geriátrica. As comparações do perfil de marcha pelo GPS não demonstraram diferenças significativas entre as idosas do estudo. A intervenção constatou que o medo de cair, após a perturbação, causa pior qualidade de marcha em comparação ao histórico de quedas. Esses fatores associados potencializam o risco de queda. Conclusão: o GPS aplicado às idosas permitiu evidenciar a qualidade de um perfil de marcha, caracterizado por uma análise ampla, uma vez que associa todos os planos de movimento das principais articulações do membro inferior. Ao mesmo tempo que é objetivo, ele agrupa as análises cinemáticas angulares. O histórico de queda de forma isolada não foi capaz, portanto, de identificar diferenças no perfil de marcha em idosas. O medo de cair produziu um padrão de marcha cauteloso, que modificou as medidas espaço-temporais e aumentou o GVS das articulações do quadril e do joelho. Esse padrão cauteloso de deslocamento piorou a qualidade de marcha, contribuindo para o aumento do risco de queda.Background: predictive factors and protectors form the risk of falling, in geriatric gait, are influenced by neuromuscular alterations, like the history of falls, and psychogenic influences. They cause in the gait a cautious motor action, with the fear of falling. Objective: evaluate the gait profile of healthy elderly women and the influence of the history and fear of falling as predictors of the risk of falling. Methods: the dissertation is divided in two articles. The first consists of a cross-sectional investigation which analyzed the reliability of the Gait Profile Score (GPS) in elderly women. The sample with 49 subjects (72,34±6,44 years) was stratified accordicng to a self-report on history of falls, in the last twelve months, from: nonfaller, faller and recurrent faller. The three-dimensional analysis of the gait used kinematic data from the pelvis, hip, knee and ankle to build the Gait Variable Score (GVS) and GPS calculations. The second article was characterized by a non-randomized clinical trial, in which the women were divided into four groups, according to their history and fear of falling. The intervention consisted in applying a fake disturbance after the subjects were submitted to three-dimensional analysis of the gait. In order to isolate the effects of both the history and fear of falling, the age, gender, body mass index, cognitive level and muscle strength variables were considered confusing factors. Results: the GPS revealed itself as a very reliable index to apply in studies regarding the geriatric gait. The profile comparisons through the GPS did not show significant differences between the elderly women who participated in the study. The intervention demonstrated that the fear of falling, after a disturbance, results in worse quality of the gait, in juxtaposition with the history of falls. When associated, this factors potentialize the risk of falling. Conclusion: the GPS applied to elder individuals allowed to evidence the quality of the gait profile. This is characterized by an extended analysis, once it associates all the movement planes of the main lower limbs’s articulations. At the same time that it is objective, as it groups the angular kinematics’s analysis. The history of falls, in isolation, was not able to identify the differences between the subjects’s gait profile. The fear of falling resulted in a cautious gait pattern, that modified the space-time measures and increased the hips and knees articulations’s GVS. This cautious movement pattern worsened the gait quality, contributing to the elevation of the risk of falling

VARIANTS of KREISEL'S CONJECTURE on A NEW NOTION of PROVABILITY

Kreisel's conjecture is the statement: if, for all n ∈ ℕ, PA ⊢ksteps φ(n), then PA ⊢ ∀x.φ(x). For a theory of arithmetic T, given a recursive function h, T ⊢≤h φ holds if there is a proof of φ in T whose code is at most h(#φ). This notion depends on the underlying coding. PhT(x) is a provability predicate for ⊢≤h in T. It is shown that there exists a sentence φ and a total recursive function h such that T ⊢≤h PrT(⌈PrT (⌈φ⌉) → φ⌉), but T ⊢/≤h φ, where PrTstands for the standard provability predicate in T. This statement is related to a conjecture by Montagna. Also variants and weakenings of Kreisel's conjecture are studied. By use of reexion principles, one can obtain a theory ThΓ that extends T such that a version of Kreisel's conjecture holds: given a recursive function h and φ(x) a Γ- formula (where Γ is an arbitrarily fixed class of formulas) such that, for all n ∈ N, T ⊢≤h φ(n), then ThΓ⊢ ∀x.φ(x). Derivability conditions are studied for a theory to statisfy the following implication: if T ⊢ ∀x.PhT(pφ(x)q), then T ⊢ ∀x.φ(x). This corresponds to an arithmetization of Kreisel's conjecture. It is shown that, for certain theories, there exists a function h such that ⊢k steps ⊆ ⊢≤h.authorsversionepub_ahead_of_prin