Safety classification using GIS in decision-making process to define priority road interventions

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.

Removal of Erythrosine B dye from water effluents using crop waste pumpkin seed hulls as adsorbent

Erythrosine B is widely used for coloring in various applications, especially in the food industry, despite its already proved toxicity and carcinogenicity. The agrowaste pumpkin seed hulls were applied as potential adsorbent for the removal of Erythrosine from aqueous solutions. Adsorption mechanism and kinetics were analyzed for design purposes. The seed hulls were characterized by specific techniques before and after dye retention. It was found that the attachment of Erythrosine B molecules on adsorbent surface may be attributed to the interactions between carboxyl and/or carbonyl groups of both dye and agrowaste wall components. A univariate approach followed by a factorial design was applied to study and analyze the experimental results as well as to estimate the combined effects of the process factors on the removal efficiency and dye uptake. Adsorption mechanism may be predominantly due to intraparticle diffusion, dependent on pore size. The four equilibrium models applied fitted the data well; the maximum adsorption capacity for Erythrosine was 16.4 mg/g. The results showed that adsorbent is effective for Erythrosine B removal for a large concentration range in aqueous solutions (5400 mg/L) in batch systems.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

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.

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

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.

Removal of tetracycline from contaminated water by Moringa oleifera seed preparations

The aim of this study was to evaluate tetracycline antibiotic (TA) removal from contaminated water by Moringa oleifera seed preparations. The composition of synthetic water approximate river natural contaminated water and TA simulated its presence as an emerging pollutant. Interactions between TA and protein preparations (extract; fraction and lectin) were also evaluated. TA was determined by solid phase extraction followed by high performance liquid chromatography - mass spectrometry. Moringa extract and flour removed TA from water. Extract removed TA in all concentrations and better removal (40%) was obtained with 40 mg L1; seed flour (particles < 5mm), 1.25 g L1 and 2.50 g L1 removed 28 and 29% of tetracycline, respectively; particles > 5 mm (0.50 g L1) removed 55% of antibiotic. Interactions between TA and seed preparations were assayed by haemagglutinating activity (HA). Specific HA (SHA) of extract (pH 7) was abolished with tetracycline (5 mg L1); fraction (75%) and lectin HA (97%) were inhibited with TA. Extract SHA decreased by 75% at pH 8. Zeta potential (ZP) of extract 700 mg L1 and tetracycline 50 mg L1 , pH range 5 to 8, showed different results. Extract ZP was more negative (10.73 mV to 16.00 mV) than tetracycline ZP (0.27 mV to 20.15 mV); ZP difference was greater in pH 8. The focus of this study was achieved since moringa preparations removed TA from water and compounds interacting with tetracycline involved at least lectin binding sites. This is a natural process, which do not promote environmental damage.

Supercritical fluid and pharmaceutical applications. Part I: Process classification

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.

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)