Pulmão “Encarcerado” por um Fibrotórax Calcificado

info:eu-repo/semantics/publishedVersio

Avaliação Económica de Ticagrelor em Prevenção Secundária Pós Síndroma Coronária Aguda

INTRODUCTION AND OBJECTIVES: To estimate the cost-effectiveness and cost-utility of ticagrelor in the treatment of patients with acute coronary syndromes (unstable angina or myocardial infarction with or without ST-segment elevation), including patients treated medically and those undergoing percutaneous coronary intervention or coronary artery bypass grafting. METHODS: A short-term decision tree and a long-term Markov model were used to simulate the evolution of patients' life-cycles. Clinical effectiveness data were collected from the PLATO trial and resource use data were obtained from the Hospital de Santa Marta database, disease-related group legislation and the literature. RESULTS: Ticagrelor provides increases of 0.1276 life years and 0.1106 quality-adjusted life years (QALYs) per patient. From a societal perspective these clinical gains entail an increase in expenditure of €610. Thus the incremental cost per life year saved is €4780 and the incremental cost per QALY is €5517. CONCLUSIONS: The simulation results show that ticagrelor reduces events compared to clopidogrel. The costs of ticagrelor are partially offset by lower costs arising from events prevented. The use of ticagrelor in clinical practice is therefore cost-effective compared to generic clopidogrel

Predictive models for managing financial incentives oriented to companies: Application to Portugal 2020

Since Portugal joined the European Union (EU) that it has been receiving incentives/funds to reduce disparities with other EU countries. Despite this goal, disparities between European regions still exist and the impact of such funds is questionable. What if it is possible to predict the success of such incentives when the funds are awarded to the beneficiaries? Using data from the database of The Agency for Competitiveness and Innovation (IAPMEI), for the programs National Strategic Reference Framework (QREN), and Portugal 2020, two predictive models are developed to estimate the number of applications to be received and the schedule of expected payments to beneficiaries for a four-month period. The results allow for a better prediction, on one hand, of the resources to be allocated to the evaluation process of the applications, and on the other hand, of the financial execution plan for the upcoming period, in order to prepare the financial execution.info:eu-repo/semantics/acceptedVersio

Recomendações para o controle da podridão mole de raízes de mandioca no Estado do Pará.

bitstream/item/39914/1/CircTec9.pd

Exploring the spectroscopic diversity of type Ia supernovae with DRACULA: a machine learning approach

The existence of multiple subclasses of type Ia supernovae (SNeIa) has been the subject of great debate in the last decade. One major challenge inevitably met when trying to infer the existence of one or more subclasses is the time consuming, and subjective, process of subclass definition. In this work, we show how machine learning tools facilitate identification of subtypes of SNeIa through the establishment of a hierarchical group structure in the continuous space of spectral diversity formed by these objects. Using Deep Learning, we were capable of performing such identification in a 4 dimensional feature space (+1 for time evolution), while the standard Principal Component Analysis barely achieves similar results using 15 principal components. This is evidence that the progenitor system and the explosion mechanism can be described by a small number of initial physical parameters. As a proof of concept, we show that our results are in close agreement with a previously suggested classification scheme and that our proposed method can grasp the main spectral features behind the definition of such subtypes. This allows the confirmation of the velocity of lines as a first order effect in the determination of SNIa subtypes, followed by 91bg-like events. Given the expected data deluge in the forthcoming years, our proposed approach is essential to allow a quick and statistically coherent identification of SNeIa subtypes (and outliers). All tools used in this work were made publicly available in the Python package Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy (DRACULA) and can be found within COINtoolbox (https://github.com/COINtoolbox/DRACULA).Comment: 16 pages, 12 figures, accepted for publication in MNRA

Electron Beam Adjustment in PLATO RTS 2 Including the Effect of Air Gaps

Background and Purpose: Beam characterization for electron dose calculations in PLATO RTS 2 treatment planning system requires the tuning of two adjustment parameters: sqx (the initial angular spread) and FMCS (a "fudge" multiple Coulomb scattering parameter). This work provides a set of suggestions to optimise electron dose calculations with PLATO, taking into account the effect of air gaps between the electron applicator and the patient skin. Material and Methods: Two adjustment criteria have been followed: one which uses just one input data set corresponding to the standard (null) air gap and another one that takes into account the whole range of clinically used distances between the electron applicator and the patient surface. The adjusted values of sqx were compared with experimental data and GEANT3 Monte Carlo code results. A systematic study has been carried out of the effect of both adjustment parameters on electron dose calculations in water. Comparisons of dose distributions and point dose values have been done between PLATO RTS2, GEANT3 Monte Carlo code and experimental data. Also the dependence on field size has been assessed. The values of sqx for the different electron energies obtained through the different approaches are discussed. Results and conclusions: The first adjustment criteria yield unrealistic dose distributions whenever the air gap is different from the standard one. A sqx balanced with a proper FMCS parameter leads to reasonably good dose distributions and point dose values that agree with experimental results within less than 1%

Uso de modelos de simulação sócio-bio-econômico integrado como ferramenta para o desenvolvimento agrário na região sudoeste do Rio Grande Sul.

Suporte tecnológico tem sido oferecido aos produtores com a finalidade de aumentar a eficiência produtiva e fornecer subsídios para as suas tomadas de decisões; entretanto, os métodos tradicionais de pesquisa e extensão estão sendo cada vez mais questionados, principalmente quanto ao custo e tempo necessário para oferecer soluções aos problemas enfrentados pelos produtores.bitstream/item/109814/1/USO-DE-MODELOS-DE-SIMULACAO.pd