983 resultados para Step Length Estimation


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RESUMO: Arl13b é uma importante proteína ciliar, presente em cílios primários e cílios móveis. Ratinhos mutantes para Arl13b têm comprimento dos cílios reduzido e defeitos nos B-túbulos dos cílios. Como consequência destes fenótipos, deficiências na Arl13b originam, em modelos animais, várias doenças congénitas, incluindo problemas no estabelecimento do eixo esquerda-direita, malformações cerebrais e deformações corporais. Nos seres humanos, deficiências na Arl13b levam a uma doença crónica congénita chamada Síndrome de Joubert. Por outro lado, a sobreexpressão de Arl13b origina cílios mais longos, no entanto existe uma ausência da caracterização dos fenótipos celulares e durante o desenvolvimento embrionário. Neste trabalho, quisemos explorar o efeito da sobre-expressão de Arl13b em embriões de peixezebra. Descobrimos que, ao nível ciliar, a sobre-expressão de Arl13b nas células aumenta o comprimento ciliar em cílios primários e móveis, no entanto, a esses cílios falta adequada acetilação da alfa-tubulina no citoesqueleto feito por microtúbulos. Os nossos resultados mostraram que esse efeito é específico de Arl13b sobre-expressão e quando se manipularam as enzimas responsáveis pela acetilação (Mec17) e pela de-acetilação (HDAC6) encontrámos uma sinergia potencial com ambas. Testámos ainda, que o aumento no comprimento ciliar não estava causalmente relacionado com a falta de acetilação, ou seja, os cílios com menos acetilação não eram necessariamente os mais longos. Também mostrámos que a sobre-expressão de Arl13b é capaz de restaurar o comprimento dos cílios em mutantes com cílios curtos e como isso pode ser explorado para um futuro potencial papel terapêutico para Arl13b. Em seguida, foi avaliado o impacto do aumento da quantidade de Arl13b no desenvolvimento embrionário do peixe-zebra. Observou-se que a sobre-expressão de Arl13b apresentava fenótipos muito fracos, quando comparados com a perda de função dos mutantes de Arl13b. Focados no inesperado fenótipo leve no estabelecimento do eixo esquerda-direita abordámos a questão através do estabelecimento de uma colaboração com matemáticos, descobrimos que os cílios mais longos que potencialmente têm a capacidade de movimentar mais fluido são atenuados por amplitudes de batimento menores, e, como resultado, estes longos cílios não prejudicam o movimento do fluido e consequentemente não afetam o estabelecimento dos padrões de esquerda-direita. Sugerimos assim que a Arl13b é um regulador chave, do comprimento ciliar. Descobrimos uma nova interação com as enzimas de acetilação/de-acetilação e levantamos novas hipóteses quanto aos mecanismos moleculares da função da Arl13b. Propomos um novo modelo para o mecanismo molecular da Arl13b na regulação do comprimento dos cílios onde podemos integrar os nossos resultados com os relatados na literatura. Este trabalho adiciona mais conhecimento para o mecanismo de ação da Arl13b e, portanto, fornece uma importante contribuição para o campo da investigação em cílios.---------------------------------------------------------------------------------------------------------------------- ABSTRACT: Arl13b is an important ciliary protein, present in primary and motile cilia. arl13b-/- mouse mutants have reduced cilia length and cilia B-tubule defects. As a consequence of these phenotypes, Arl13b loss of function animal models suffer from several congenital disorders including left-right problems, brain malformations and body deformations. In humans Arl13b depletion leads to a congenital chronic disease called Joubert Syndrome. On the other hand, overexpressing Arl13b leads to longer cilia but the characterization of the cellular and developmental phenotypes was missing. In this work we explore the effect of Arl13b overexpression in zebrafish embryos. We found that, at the ciliary level, Arl13b overexpression from 1 cell stage produces longer primary and motile cilia, but these cilia lack proper alpha tubulin acetylation of their microtubule cytoskeleton. Our results showed that this effect is specific from Arl13b overexpression and when we manipulated the enzymes responsible for acetylation, Mec17, and de-acetylation, HDAC6, we found a potential synergy of both mec17 knockdown and HDAC6 activity with Arl13b overexpression. We tested that the ciliary increase in length was not causally related to the lack of acetylation, meaning the more de-acetylated cilia were not necessarily the longer ones. We also showed that Arl13b overexpression is able to restore cilia length in short cilia mutants and how that may be explored to a potential future therapeutic role for Arl13b. Next, we evaluated the impact of increasing the amount of Arl13b in zebrafish embryonic development. We observed that Arl13b overexpression presented very mild phenotypes when compared to the loss of function mutants. We focused on the unexpected left-right mild phenotype and by establishing a mathematical modeling collaboration, we found out that the longer cilia generated force was attenuated by smaller beating amplitudes, and as a result, these long cilia were not impairing the cilia generated flow and the establishment of left-right patterning. We suggest that Arl13b is one key cilia length regulator. We disclosed a novel interaction with the acetylation / de-acetylation enzymes and raised new hypothesis as to the mechanisms of Arl13b function. We propose a new model for the Arl13b molecular mechanism of cilia length regulation where we integrate our findings with those reported in the literature. This work adds more knowledge to the Arl13b mechanism of action and therefore provides an important contribution to the cilia research field.

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The moisture content in concrete structures has an important influence in their behavior and performance. Several vali-dated numerical approaches adopt the governing equation for relative humidity fields proposed in Model Code 1990/2010. Nevertheless there is no integrative study which addresses the choice of parameters for the simulation of the humidity diffusion phenomenon, particularly in concern to the range of parameters forwarded by Model Code 1990/2010. A software based on a Finite Difference Method Algorithm (1D and axisymmetric cases) is used to perform sensitivity analyses on the main parameters in a normal strength concrete. Then, based on the conclusions of the sensi-tivity analyses, experimental results from nine different concrete compositions are analyzed. The software is used to identify the main material parameters that better fit the experimental data. In general, the model was able to satisfactory fit the experimental results and new correlations were proposed, particularly focusing on the boundary transfer coeffi-cient.

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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.

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The kinetics of GnP dispersion in polypropylene melt was studied using a prototype small scale modular extensional mixer. Its modular nature enabled the sequential application of a mixing step, melt relaxation, and a second mixing step. The latter could reproduce the flow conditions on the first mixing step, or generate milder flow conditions. The effect of these sequences of flow constraints upon GnP dispersion along the mixer length was studied for composites with 2 and 10 wt.% GnP. The samples collected along the first mixing zone showed a gradual decrease of number and size of GnP agglomerates, at a rate that was independent of the flow conditions imposed to the melt, but dependent on composition. The relaxation zone induced GnP re-agglomeration, and the application of a second mixing step caused variable dispersion results that were largely dependent on the hydrodynamic stresses generated.

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Nowadays, organizations are increasingly looking to invest in business intelligence solutions, mainly private companies in order to get advantage over its competitors, however they do not know what is necessary. Business intelligence allows an analysis of consolidated information in order to obtain more specific outlets and certain indications in order to support the decision making process. You can take the right decision based on the data collected from different information systems present in the organization and outside of them. The textile sector is a sector where concept of Business Intelligence it is not many explored yet. Actually there are few textile companies that have a BI platform. Thus, the article objective is present an architecture and show all the steps by which companies need to spend to implement a successful free homemade Business Intelligence system. As result the proposed approach it was validated using real data aiming assess the steps defined.

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In Intensive Medicine, the presentation of medical information is done in many ways, depending on the type of data collected and stored. The way in which the information is presented can make it difficult for intensivists to quickly understand the patient's condition. When there is the need to cross between several types of clinical data sources the situation is even worse. This research seeks to explore a new way of presenting information about patients, based on the timeframe in which events occur. By developing an interactive Patient Timeline, intensivists will have access to a new environment in real-time where they can consult the patient clinical history and the data collected until the moment. The medical history will be available from the moment in which patients is admitted in the ICU until discharge, allowing intensivist to examine data regarding vital signs, medication, exams, among others. This timeline also intends to, through the use of information and models produced by the INTCare system, combine several clinical data in order to help diagnose the future patients’ conditions. This platform will help intensivists to make more accurate decision. This paper presents the first approach of the solution designed

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Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.

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Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos

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Antimicrobial resistance constitutes one of the major worldwide public health concerns. Bacteria are becoming resistant to the vast majority of antibiotics and nowadays, a common infection can be fatal. To revert this situation, the use of phages for the treatment of bacterial infections has been extensively studied as an alternative therapeutic strategy. Since P. aeruginosa is one of the most common causes of healthcare-associated infections, many studies have reported the in vitro and in vivo antibacterial efficacy of phage therapy against this bacterium. This review collects data of all the P. aeruginosa phages sequenced to date, providing a better understanding about their biodiversity. This review will further address the in vitro and in vivo results obtained by using phages to treat or prevent P. aeruginosa infections as well as the major hurdles associated with this therapy.

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This paper proposes the establishment of a second diameter measuring standard at 30cm shoot extension ('diam30') as input variable for allometric biomass estimation of small and mid-sized plant shoots. This diameter standard is better suited than the diameter at breast height (DBH, i.e. diameter at 1.30m shoot extension) for adequate characterization of plant dimensions in low bushy vegetation or in primary forest undergrowth. The relationships between both diameter standards are established based on a dataset of 8645 tree, liana and palm shoots in secondary and primary forests of central Amazonia (ranging from 1-150mm dbh). Dbh can be predicted from the diam(30) with high precision, the error introduced by diameter transformation is only 2-3% for trees and palms, and 5% for lianas. This is well acceptable for most field study purposes. Relationships deviate slightly from linearity and differ between growth forms. Relationships were markedly similar for different vegetation types (low secondary regrowth vs. primary forests), soils, and selected genera or species. This points to a general validity and applicability of diameter transformations for other field studies. This study provides researchers with a tool for the allometric estimation of biomass in low or structurally heterogeneous vegetation. Rather than applying a uniform diameter standard, the measuring position which best represents the respective plant can be decided on shoot-by-shoot. Plant diameters measured at 30cm height can be transformed to dbh for subsequent allometric biomass estimation. We recommend the use of these diameter transformations only for plants extending well beyond the theoretical minimum shoot length (i.e., >2m height). This study also prepares the ground for the comparability and compatability of future allometric equations specifically developed for small- to mid-sized vegetation components (i.e., bushes, undergrowth) which are based on the diam(30) measuring standard.

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Well-dispersed loads of finely powdered metals, metal oxides, several carbon allotropes or nanoclays are incorporated into highly porous polyamide 6 microcapsules in controllable amounts via an original one-step in situ fabrication technique. It is based on activated anionic polymerization (AAP) of ε-caprolactam in a hydrocarbon solvent performed in the presence of the respective micro- or nanosized loads. The forming microcapsules with typical diameters of 25-50 µm entrap up to 40 wt% of load. Their melt processing produces hybrid thermoplastic composites. Mechanical, electric conductivity and magnetic response measurements show that transforming of in situ loaded microcapsules into composites by melt processing (MP) is a facile and rapid method to fabricate materials with high mechanical resistance and electro-magnetic characteristics sufficient for many industrial applications. This novel concept requires low polymerization temperatures, no functionalization or compatibilization of the loads and it is easy to scale up at industrial production levels.

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The receiver-operating characteristic (ROC) curve is the most widely used measure for evaluating the performance of a diagnostic biomarker when predicting a binary disease outcome. The ROC curve displays the true positive rate (or sensitivity) and the false positive rate (or 1-specificity) for different cut-off values used to classify an individual as healthy or diseased. In time-to-event studies, however, the disease status (e.g. death or alive) of an individual is not a fixed characteristic, and it varies along the study. In such cases, when evaluating the performance of the biomarker, several issues should be taken into account: first, the time-dependent nature of the disease status; and second, the presence of incomplete data (e.g. censored data typically present in survival studies). Accordingly, to assess the discrimination power of continuous biomarkers for time-dependent disease outcomes, time-dependent extensions of true positive rate, false positive rate, and ROC curve have been recently proposed. In this work, we present new nonparametric estimators of the cumulative/dynamic time-dependent ROC curve that allow accounting for the possible modifying effect of current or past covariate measures on the discriminatory power of the biomarker. The proposed estimators can accommodate right-censored data, as well as covariate-dependent censoring. The behavior of the estimators proposed in this study will be explored through simulations and illustrated using data from a cohort of patients who suffered from acute coronary syndrome.

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In longitudinal studies of disease, patients may experience several events through a follow-up period. In these studies, the sequentially ordered events are often of interest and lead to problems that have received much attention recently. Issues of interest include the estimation of bivariate survival, marginal distributions and the conditional distribution of gap times. In this work we consider the estimation of the survival function conditional to a previous event. Different nonparametric approaches will be considered for estimating these quantities, all based on the Kaplan-Meier estimator of the survival function. We explore the finite sample behavior of the estimators through simulations. The different methods proposed in this article are applied to a data set from a German Breast Cancer Study. The methods are used to obtain predictors for the conditional survival probabilities as well as to study the influence of recurrence in overall survival.

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The nitrogen dioxide is a primary pollutant, regarded for the estimation of the air quality index, whose excessive presence may cause significant environmental and health problems. In the current work, we suggest characterizing the evolution of NO2 levels, by using geostatisti- cal approaches that deal with both the space and time coordinates. To develop our proposal, a first exploratory analysis was carried out on daily values of the target variable, daily measured in Portugal from 2004 to 2012, which led to identify three influential covariates (type of site, environment and month of measurement). In a second step, appropriate geostatistical tools were applied to model the trend and the space-time variability, thus enabling us to use the kriging techniques for prediction, without requiring data from a dense monitoring network. This method- ology has valuable applications, as it can provide accurate assessment of the nitrogen dioxide concentrations at sites where either data have been lost or there is no monitoring station nearby.

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Mycotoxins are toxic secondary metabolites produced by filamentous fungi that occur naturally in agricultural commodities worldwide. Aflatoxins, ochratoxin A, patulin, fumonisins, zearalenone, trichothecenes and ergot alkaloids are presently the most important for food and feed safety. These compounds are produced by several species that belong to the Aspergillus, Penicillium, Fusarium and Claviceps genera and can be carcinogenic, mutagenic, teratogenic, cytotoxic, neurotoxic, nephrotoxic, estrogenic and immunosuppressant. Human and animal exposure to mycotoxins is generally assessed by taking into account data on the occurrence of mycotoxins in food and feed as well as data on the consumption patterns of the concerned population. This evaluation is crucial to support measures to reduce consumer exposure to mycotoxins. This work reviews the occurrence and levels of mycotoxins in Portuguese food and feed to provide a global overview of this issue in Portugal. With the information collected, the exposure of the Portuguese population to those mycotoxins is assessed, and the estimated dietary intakes are presented.