8 resultados para Site classification
em Universidade do Minho
Resumo:
Given the current economic situation of the Portuguese municipalities, it is necessary to identify the priority investments in order to achieve a more efficient financial management. The classification of the road network of the municipality according to the occurrence of traffic accidents is fundamental to set priorities for road interventions. This paper presents a model for road network classification based on traffic accidents integrated in a geographic information system. Its practical application was developed through a case study in the municipality of Barcelos. An equation was defined to obtain a road safety index through the combination of the following indicators: severity, property damage only and accident costs. In addition to the road network classification, the application of the model allows to analyze the spatial coverage of accidents in order to determine the centrality and dispersion of the locations with the highest incidence of road accidents. This analysis can be further refined according to the nature of the accidents namely in collision, runoff and pedestrian crashes.
Resumo:
Through the analysis of the exceptional accounting documents of 1517 related to the construction of the Monastery of Jerónimos (Lisbon), this paper discusses the main characteristics of a new model of construction site organization. In the later Middle Ages we can find, among others, two main models of constructing site organization. One, older and more widespread, consisted in a centralized and pyramidal management model. The other, apparently more recent, was based in the existence of several autonomous teams working simultaneously, each one responsible for building a specific part or section of the building. This paper describes and discusses this new organizational model as it was adopted and implemented by João de Castilho (1470–1552) for the construction of the Monastery of Jerónimos in 1517, probably for the first time in Portugal, but with some parallels in other places in Europe.
Resumo:
The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.
Resumo:
Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.
Resumo:
The supercritical fluid technology has been target of many pharmaceuticals investigations in particles production for almost 35 years. This is due to the great advantages it offers over others technologies currently used for the same purpose. A brief history is presented, as well the classification of supercritical technology based on the role that the supercritical fluid (carbon dioxide) performs in the process.
Resumo:
Surgical site infections (SSI) often occur after invasive surgery, which is as a serious health problem, making it important to develop new biomaterials to prevent infections. Spider silk is a natural biomaterial with excellent biocompatibility, low immunogenicity and controllable biodegradability. Through recombinant DNA technology, spider silk-based materials can be bioengineered and functionalized with antimicrobial (AM) peptides 1. The aim of this study is to develop new materials by combining spider silk chimeric proteins with AM properties and silk fibroin extracted from Bombyx mori cocoons to prevent microbial infection. Here, spider silk domains derived from the dragline sequence of the spider Nephila clavipes (6 mer and 15 mer) were fused with the AM peptides Hepcidin and Human Neutrophil peptide 1 (HNP1). The spider silk domain maintained its self-assembly features allowing the formation of beta-sheets to lock in structures without any chemical cross-linking. The AM properties of the developed chimeric proteins showed that 6 mer + HNP1 protein had a broad microbicidal activity against pathogens. The 6 mer + HNP-1 protein was then assembled with different percentages of silk fibroin into multifunctional films. In vitro cell studies with a human fibroblasts cell line (MRC5) showed nontoxic and cytocompatible behavior of the films. The positive cellular response, together with structural properties, suggests that this new fusion protein plus silk fibroin may be good candidates as multifunctional materials to prevent SSI.
Resumo:
Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)
Resumo:
Dissertação de mestrado em Ciências da Comunicação (área de especialização em Informação e Jornalismo)