Mining biomedical information from scientific literature

The rapid evolution and proliferation of a world-wide computerized network, the Internet, resulted in an overwhelming and constantly growing amount of publicly available data and information, a fact that was also verified in biomedicine. However, the lack of structure of textual data inhibits its direct processing by computational solutions. Information extraction is the task of text mining that intends to automatically collect information from unstructured text data sources. The goal of the work described in this thesis was to build innovative solutions for biomedical information extraction from scientific literature, through the development of simple software artifacts for developers and biocurators, delivering more accurate, usable and faster results. We started by tackling named entity recognition - a crucial initial task - with the development of Gimli, a machine-learning-based solution that follows an incremental approach to optimize extracted linguistic characteristics for each concept type. Afterwards, Totum was built to harmonize concept names provided by heterogeneous systems, delivering a robust solution with improved performance results. Such approach takes advantage of heterogenous corpora to deliver cross-corpus harmonization that is not constrained to specific characteristics. Since previous solutions do not provide links to knowledge bases, Neji was built to streamline the development of complex and custom solutions for biomedical concept name recognition and normalization. This was achieved through a modular and flexible framework focused on speed and performance, integrating a large amount of processing modules optimized for the biomedical domain. To offer on-demand heterogenous biomedical concept identification, we developed BeCAS, a web application, service and widget. We also tackled relation mining by developing TrigNER, a machine-learning-based solution for biomedical event trigger recognition, which applies an automatic algorithm to obtain the best linguistic features and model parameters for each event type. Finally, in order to assist biocurators, Egas was developed to support rapid, interactive and real-time collaborative curation of biomedical documents, through manual and automatic in-line annotation of concepts and relations. Overall, the research work presented in this thesis contributed to a more accurate update of current biomedical knowledge bases, towards improved hypothesis generation and knowledge discovery.

Seismic vulnerability assessment of slender masonry structures

Slender masonry structures are distributed all over the world and constitute a relevant part of the architectural and cultural heritage of humanity. Their protection against earthquakes is a topic of great concern among the scientific community. This concern mainly arises from the strong damage or complete loss suffered by this group of structures due to catastrophic events and the need and interest to preserve them. Although the great progress in technology, and in the knowledge of seismology and earthquake engineering, the preservation of these brittle and massive structures still represents a major challenge. Based on the research developed in this work it is proposed a methodology for the seismic risk assessment of slender masonry structures. The proposed methodology was applied for the vulnerability assessment of Nepalese Pagoda temples which follow very simple construction procedure and construction detailing in relation to seismic resistance requirements. The work is divided in three main parts. Firstly, particular structural fragilities and building characteristics of the important UNESCO classified Nepalese Pagoda temples which affect their seismic performance and dynamic properties are discussed. In the second part the simplified method proposed for seismic vulnerability assessment of slender masonry structures is presented. Finally, the methodology proposed in this work is applied to study Nepalese Pagoda temples, as well as in the efficiency assessment of seismic performance improvement solution compatible with original cultural and technological value.