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.

Behaviour of a dovetail joint solved using force analyses

Dovetail joints are one of the most cornrnonly used joints during Gothic and Baroque periods. Despite being coristructed in the sarne way during the ages, there is no analyticai solution available to help its analysis and design so required in reconstruction works of existing timber structures. An analytical solution based on the principie of virtual works under different types of loading is presented in this paper as weli as differences in bearing capacity of the joint for chosen types of loading, when different wood species are used. The accuracy of the presented solution is confirrned by data obtained from experimental tests of scaied modeis of a dovetail joint.

Intermetallic layer formation and influence in solder joints reliability

Dissertação de mestrado integrado em Materials Engineering

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)