Cinco para ouvir: discursos de ex-reclusos/as sobre a Prisão

Dissertação de mestrado integrado em Psicologia

Análise estratégica da internacionalização da APFF- Administração do Porto da Figueira da Foz

Relatório de estágio de mestrado em Negócios Internacionais

Nanotechnological approaches using curcumin and Withania somnifera: neuroprotection and antimicrobial activities

Tese de Doutoramento em Biologia de Plantas

Development of folate-targeted liposomes for rheumatoid arthritis therapy

Tese de Doutoramento em Biologia Molecular e Ambiental (área de especialização em Biologia Celular e Saúde).

Protein-based nanodevices for therapeutic applications

Tese de Doutoramento em Biologia Molecular e Ambiental (área de especialização em Biologia Celular e Saúde).

Automatically estimating iSAX parameters

The Symbolic Aggregate Approximation (iSAX) is widely used in time series data mining. Its popularity arises from the fact that it largely reduces time series size, it is symbolic, allows lower bounding and is space efficient. However, it requires setting two parameters: the symbolic length and alphabet size, which limits the applicability of the technique. The optimal parameter values are highly application dependent. Typically, they are either set to a fixed value or experimentally probed for the best configuration. In this work we propose an approach to automatically estimate iSAX’s parameters. The approach – AutoiSAX – not only discovers the best parameter setting for each time series in the database, but also finds the alphabet size for each iSAX symbol within the same word. It is based on simple and intuitive ideas from time series complexity and statistics. The technique can be smoothly embedded in existing data mining tasks as an efficient sub-routine. We analyze its impact in visualization interpretability, classification accuracy and motif mining. Our contribution aims to make iSAX a more general approach as it evolves towards a parameter-free method.

Searching for therapeutic strategies in a mouse modelo of Machado-Joseph disease: targeting proteostases

Tese de Doutoramento em Ciências da Saúde

Development of Monoolein-based lipofection vectors for therapeutic siRNA delivery

Tese de Doutoramento em Biologia Molecular e Ambiental - Especialidade em Biologia Celular e Saúde

O trabalho colaborativo na aprendizagem de uma utilização segura da Internet

Relatório de estágio de mestrado em Ensino de Informática

Folate-targeted nanoparticles for rheumatoid arthritis therapy

Rheumatoid arthritis (RA) is the most common inflammatory rheumatic disease, affecting almost 1% of the world population. Although the cause of RA remains unknown, the complex interaction between immune mediators (cytokines and effector cells) is responsible for the joint damage that begins at the synovial membrane. Activated macrophages are critical in the pathogenesis of RA and have been shown to specifically express a receptor for the vitamin folic acid (FA), folate receptor (FR). This particular receptor allows internalization of FA-coupled cargo. In this review we will address the potential of nanoparticles as an effective drug delivery system for therapies that will directly target activated macrophages. Special attention will be given to stealth degree of the nanoparticles as a strategy to avoid clearance by macrophages of the mononuclear phagocytic system (MPS). This review summarizes the application of FA-target nanoparticles as drug delivery systems for RA and proposes prospective future directions.

Lipid based nanocarriers for the delivery of the bioactive compound resveratrol

Dissertação de mestrado em Biofísica e Bionanossistemas

Typologies of post-divorce coparenting and parental well-being, parenting quality and children’s psychological adjustment

First published online: 30 October 2015