A vegetação na envolvente exterior dos edifícios: impactos, condicionantes e estratégias de intervenção ecoeficientes

Dissertação de mestrado integrado em Arquitectura

FOSTER: facilitate open science training for european research

FOSTER aims to support different stakeholders, especially young researchers, in adopting open access in the context of the European Research Area (ERA) and in complying with the open access policies and rules of participation set out for Horizon 2020 (H2020). FOSTER establish a European-wide training programme on open access and open data, consolidating training activities at downstream level and reaching diverse disciplinary communities and countries in the ERA. The training programme includes different approaches and delivery options: elearning, blearning, self-learning, dissemination of training materials/contents, helpdesk, face-to-face training, especially training-the-trainers, summer schools, seminars, etc.

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.

Mesenchymal stem cells culture on poly(vinylidene fluoride) piezoelectric microspheres

Dissertação de mestrado em Biofísica e Bionanossistemas

Pró-fármacos fotoativáveis do péptido AAPV: síntese e avaliação da libertação controlada por luz

Dissertação de mestrado em Bioquímica Aplicada (área de especialização em Biomedicina)

Desenvolvimento de acessórios de máquinas de movimentação de terras recorrendo a soluções avançadas em aço de alta resistência

Dissertação de mestrado em Tecnologias de Manufatura

Study to determine the cardiovascular risk ofthe population of Guimarães/Vizela, includingthe prevalence of arterial stiffness and early vascular aging syndrome

Tese de Doutoramento em Medicina.

Redes interorganizacionais nas políticas públicas: atores, conexões e configurações organizacionais

Tese de Doutoramento em Sociologia

Clozapine-induced severe eosinophilia: report of a case with good outcome

INTRODUCTION: Clozapine is the antipsychotic of choice in the treatment of refractory schizophrenia. However, its side effects, such as eosinophilia, may preclude its use. METHODS: Case report and literature review. RESULTS: Young woman, 19 years old, diagnosed with hebefrenic schizophrenia, admitted at Unicamp's psychiatry ward after psychotic symptoms relapse. Clozapine was started after unsuccessful attempts with risperidon and olanzapine. By the fourth week of clozapine use, eosinophils began to increase. Drug titration was stopped, but eosinophils counts continued to rise up, reaching the mark of 5200/mm³. Due to severity of psychotic symptoms and to the good response obtained with clozapine, we decided to investigate organs involvement before withdrawing the medication. As the patient had no organs involvement, clozapine was maintained and one month after eosinophils peak, it was already normalized. CONCLUSION: Eosinophilia should not necessarily lead to clozapine's withdrawal. Patients who present eosinophilia must be at rigorous observation for organs involvement, and if there is no such involvement, clozapine might be maintained, considering the possible benign and transitory nature of the eosinophils count elevation.

Development of polymeric nanoparticles containing neuroprotective compounds of Hypericum perforatum

Tese de Doutoramento em Biologia das Plantas - MAP BIOPLANT

Os acordos parassociais: relação com o contrato social e outras questões

Dissertação de mestrado em Direito dos Contratos e da Empresa

Contributos do postal ilustrado para a história do Free Card

Dissertação de mestrado em Ciências da Comunicação (área de especialização em Publicidade e Relações Públicas)

A eficácia da Mediação Familiar no contexto das Responsabilidades Parentais

Dissertação de mestrado em Direito das Crianças, Família e Sucessões

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.

Production of biohydrogen from dark fermentation of organic wastes

Dissertação de mestrado em Bioengenharia