1,097 research outputs found
Planeamento do Sistema de Gestão da Qualidade: Uma proposta de implementação no NDS-Núcleo Desportivo e Social
O estágio profissionalizante foi realizado na instituição NDS – Núcleo Desportivo e Social, sediada no concelho da Guarda e insere-se no âmbito do mestrado em Sistemas Integrados de Gestão. O estágio teve a duração de 530 horas, com início no dia 9 de outubro de 2017 e conclusão no dia 11 de abril de 2018. O estágio desenvolvido teve como objetivo principal o planeamento e proposta de um Sistema de Gestão da Qualidade para implementar no NDS. Esta é uma entidade que desenvolve duas respostas sociais típicas, o Serviço de Apoio Domiciliário (SAD) e o Centro de Atividades e Tempos Livres (CATL) e uma resposta social atípica, o Rendimento Social de Inserção (RSI). Também desenvolve vários projetos de cariz social e possui diversas modalidades desportivas, para além de ter um Snack-bar e um grupo de cantares.
A realização deste estágio profissionalizante proporcionou à estagiária um segundo contacto com o mundo laboral. Assim, ela pôde pôr em prática os conhecimentos adquiridos ao longo do ano de curso e ganhar algumas bases, prática e experiência numa grande instituição e simultaneamente uma melhor preparação para uma futura entrada no mercado do trabalho. O estágio possibilitou um crescimento não só profissional, mas também enquanto pessoa.
Metodologicamente, o presente relatório desenvolve numa primeira parte, uma revisão bibliográfica sobre o tema da qualidade e da certificação do Sistema de Gestão da Qualidade. Numa segunda parte apresenta o NDS-Núcleo Desportivo e Social e o Sistema de Gestão de Qualidade delineado para a referida entidade suportado na norma NP EN ISO 9001: 2015 (IPQ, 2015b). Espera-se que esta proposta de implementação possa ser relevante para uma futura certificação do NDS, no âmbito da qualidade, segundo a norma NP EN ISO 9001:2015 (IPQ, 2015b)
Critical scaling in standard biased random walks
The spatial coverage produced by a single discrete-time random walk, with
asymmetric jump probability and non-uniform steps, moving on an
infinite one-dimensional lattice is investigated. Analytical calculations are
complemented with Monte Carlo simulations. We show that, for appropriate step
sizes, the model displays a critical phenomenon, at . Its scaling
properties as well as the main features of the fragmented coverage occurring in
the vicinity of the critical point are shown. In particular, in the limit , the distribution of fragment lengths is scale-free, with nontrivial
exponents. Moreover, the spatial distribution of cracks (unvisited sites)
defines a fractal set over the spanned interval. Thus, from the perspective of
the covered territory, a very rich critical phenomenology is revealed in a
simple one-dimensional standard model.Comment: 4 pages, 4 figure
Non-exponential relaxation for anomalous diffusion
We study the relaxation process in normal and anomalous diffusion regimes for
systems described by a generalized Langevin equation (GLE). We demonstrate the
existence of a very general correlation function which describes the relaxation
phenomena. Such function is even; therefore, it cannot be an exponential or a
stretched exponential. However, for a proper choice of the parameters, those
functions can be reproduced within certain intervals with good precision. We
also show the passage from the non-Markovian to the Markovian behaviour in the
normal diffusion regime. For times longer than the relaxation time, the
correlation function for anomalous diffusion becomes a power law for broad-band
noise.Comment: 6 pages, 2 figure
Neuronal deletion of GSK3beta increases microtubule speed in the growth cone and enhances axon regeneration via CRMP-2 and independently of MAP1B and CLASP2
BACKGROUND: In the adult central nervous system, axonal regeneration is abortive. Regulators of microtubule dynamics have emerged as attractive targets to promote axonal growth following injury as microtubule organization is pivotal for growth cone formation. In this study, we used conditioned neurons with high regenerative capacity to further dissect cytoskeletal mechanisms that might be involved in the gain of intrinsic axon growth capacity. RESULTS: Following a phospho-site broad signaling pathway screen, we found that in conditioned neurons with high regenerative capacity, decreased glycogen synthase kinase 3β (GSK3β) activity and increased microtubule growth speed in the growth cone were present. To investigate the importance of GSK3β regulation during axonal regeneration in vivo, we used three genetic mouse models with high, intermediate or no GSK3β activity in neurons. Following spinal cord injury, reduced GSK3β levels or complete neuronal deletion of GSK3β led to increased growth cone microtubule growth speed and promoted axon regeneration. While several microtubule-interacting proteins are GSK3β substrates, phospho-mimetic collapsin response mediator protein 2 (T/D-CRMP-2) was sufficient to decrease microtubule growth speed and neurite outgrowth of conditioned neurons and of GSK3β-depleted neurons, prevailing over the effect of decreased levels of phosphorylated microtubule-associated protein 1B (MAP1B) and through a mechanism unrelated to decreased levels of phosphorylated cytoplasmic linker associated protein 2 (CLASP2). In addition, phospho-resistant T/A-CRMP-2 counteracted the inhibitory myelin effect on neurite growth, further supporting the GSK3β-CRMP-2 relevance during axon regeneration. CONCLUSIONS: Our work shows that increased microtubule growth speed in the growth cone is present in conditions of increased axonal growth, and is achieved following inactivation of the GSK3β-CRMP-2 pathway, enhancing axon regeneration through the glial scar. In this context, our results support that a precise control of microtubule dynamics, specifically in the growth cone, is required to optimize axon regrowth
Two women presenting worsening cutaneous ulcers during pregnancy: diagnosis, immune response, and follow-up
A stellar occultation by the transneptunian object (50000) Quaoar observed by CHEOPS
Context. Stellar occultation is a powerful technique that allows the determination of some physical parameters of the occulting object. The result depends on the photometric accuracy, the temporal resolution, and the number of chords obtained. Space telescopes can achieve high photometric accuracy as they are not affected by atmospheric scintillation.
Aims. Using ESA’s CHEOPS space telescope, we observed a stellar occultation by the transneptunian object (50000) Quaoar. We compare the obtained chord with previous occultations by this object and determine its astrometry with sub-milliarcsecond precision. Also, we determine upper limits to the presence of a global methane atmosphere on the occulting body.
Methods. We predicted and observed a stellar occultation by Quaoar using the CHEOPS space telescope. We measured the occultation light curve from this dataset and determined the dis- and reappearance of the star behind the occulting body. Furthermore, a ground-based telescope in Australia was used to constrain Quaoar’s limb. Combined with results from previous works, these measurements allowed us to obtain a precise position of Quaoar at the occultation time.
Results. We present the results obtained from the first stellar occultation by a transneptunian object using a space telescope orbiting Earth; it was the occultation by Quaoar observed on 2020 June 11. We used the CHEOPS light curve to obtain a surface pressure upper limit of 85 nbar for the detection of a global methane atmosphere. Also, combining this observation with a ground-based observation, we fitted Quaoar’s limb to determine its astrometric position with an uncertainty below 1.0 mas.
Conclusions. This observation is the first of its kind, and it shall be considered as a proof of concept of stellar occultation observations of transneptunian objects with space telescopes orbiting Earth. Moreover, it shows significant prospects for the James Webb Space Telescope
Astrometric positions for 18 irregular satellites of giant planets from 23 years of observations
The irregular satellites of the giant planets are believed to have been
captured during the evolution of the solar system. Knowing their physical
parameters, such as size, density, and albedo is important for constraining
where they came from and how they were captured. The best way to obtain these
parameters are observations in situ by spacecrafts or from stellar occultations
by the objects. Both techniques demand that the orbits are well known. We aimed
to obtain good astrometric positions of irregular satellites to improve their
orbits and ephemeris. We identified and reduced observations of several
irregular satellites from three databases containing more than 8000 images
obtained between 1992 and 2014 at three sites (Observat\'orio do Pico dos Dias,
Observatoire de Haute-Provence, and European Southern Observatory - La Silla).
We used the software PRAIA (Platform for Reduction of Astronomical Images
Automatically) to make the astrometric reduction of the CCD frames. The UCAC4
catalog represented the International Celestial Reference System in the
reductions. Identification of the satellites in the frames was done through
their ephemerides as determined from the SPICE/NAIF kernels. Some procedures
were followed to overcome missing or incomplete information (coordinates,
date), mostly for the older images. We managed to obtain more than 6000
positions for 18 irregular satellites: 12 of Jupiter, 4 of Saturn, 1 of Uranus
(Sycorax), and 1 of Neptune (Nereid). For some satellites the number of
obtained positions is more than 50\% of what was used in earlier orbital
numerical integrations. Comparison of our positions with recent JPL ephemeris
suggests there are systematic errors in the orbits for some of the irregular
satellites. The most evident case was an error in the inclination of Carme.Comment: 9 pages, with 3 being online materia
9-Borafluoren-9-yl and diphenylboron tetracoordinate complexes of F- and Cl-substituted 8-quinolinolato ligands: synthesis, molecular and electronic structures, fluorescence and application in OLED devices
Six new four-coordinate tetrahedral boron complexes, containing 9-borafluoren-9-yl and diphenylboron cores attached to orthogonal fluorine- and chlorine-substituted 8-quinolinolato ligand chromophores, have been synthesised, characterised, and applied as emitters in organic light-emitting diodes (OLEDs). An extensive steady-state and time-resolved photophysical study, in solution and in the solid state, resulted in the first-time report of delayed fluorescence (DF) in solid films of 8-quinolinolato boron complexes. The DF intensity dependence on excitation dose suggests that this emission originates from triplet–triplet annihilation (TTA). Density functional theory (DFT) and time-dependent density functional theory (TDDFT) studies give insight into the ground and excited state geometries, electronic structures, absorption energies, and singlet–triplet gaps in these new organoboron luminophores. Finally, given their highly luminescent behaviour, organic light-emitting diode (OLED) devices were produced using the synthesised organoboron compounds as emissive fluorescent dopants. The best OLED displays green-blue (λmaxEL = 489 nm) electroluminescence with an external quantum efficiency (EQE) of 3.3% and a maximum luminance of 6300 cd m−2
Machine learning and feature selection methods for egfr mutation status prediction in lung cancer
The evolution of personalized medicine has changed the therapeutic strategy from classical chemotherapy and radiotherapy to a genetic modification targeted therapy, and although biopsy is the traditional method to genetically characterize lung cancer tumor, it is an invasive and painful procedure for the patient. Nodule image features extracted from computed tomography (CT) scans have been used to create machine learning models that predict gene mutation status in a noninvasive, fast, and easy-to-use manner. However, recent studies have shown that radiomic features extracted from an extended region of interest (ROI) beyond the tumor, might be more relevant to predict the mutation status in lung cancer, and consequently may be used to significantly decrease the mortality rate of patients battling this condition. In this work, we investigated the relation between image phenotypes and the mutation status of Epidermal Growth Factor Receptor (EGFR), the most frequently mutated gene in lung cancer with several approved targeted-therapies, using radiomic features extracted from the lung containing the nodule. A variety of linear, nonlinear, and ensemble predictive classification models, along with several feature selection methods, were used to classify the binary outcome of wild-type or mutant EGFR mutation status. The results show that a comprehensive approach using a ROI that included the lung with nodule can capture relevant information and successfully predict the EGFR mutation status with increased performance compared to local nodule analyses. Linear Support Vector Machine, Elastic Net, and Logistic Regression, combined with the Principal Component Analysis feature selection method implemented with 70% of variance in the feature set, were the best-performing classifiers, reaching Area Under the Curve (AUC) values ranging from 0.725 to 0.737. This approach that exploits a holistic analysis indicates that information from more extensive regions of the lung containing the nodule allows a more complete lung cancer characterization and should be considered in future radiogenomic studies.This work is financed by the ERDF—European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation—COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT—Fundação para a Ciência e a Tecnologia within project POCI-01-0145-FEDER-030263
Comprehensive perspective for lung cancer characterisation based on AI solutions using CT images
Lung cancer is still the leading cause of cancer death in the world. For this reason, novel approaches for early and more accurate diagnosis are needed. Computer-aided decision (CAD) can be an interesting option for a noninvasive tumour characterisation based on thoracic computed tomography (CT) image analysis. Until now, radiomics have been focused on tumour features analysis, and have not considered the information on other lung structures that can have relevant features for tumour genotype classification, especially for epidermal growth factor receptor (EGFR), which is the mutation with the most successful targeted therapies. With this perspective paper, we aim to explore a comprehensive analysis of the need to combine the information from tumours with other lung structures for the next generation of CADs, which could create a high impact on targeted therapies and personalised medicine. The forthcoming artificial intelligence (AI)-based approaches for lung cancer assessment should be able to make a holistic analysis, capturing information from pathological processes involved in cancer development. The powerful and interpretable AI models allow us to identify novel biomarkers of cancer development, contributing to new insights about the pathological processes, and making a more accurate diagnosis to help in the treatment plan selection.This work is financed by the ERDF–European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation–COMPETE 2020 Programme
and by National Funds through the Portuguese funding agency, FCT–Fundação para a Ciência e a Tecnologia within project POCI-01-0145-FEDER-030263
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