Modeling and optimization of extracellular polysaccharides production by Enterobacter A47

Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.

Participatory mapping in the design process of a spatial data infrastructure SDI: a case study in the Biosphere Reserve Rio Platano (Honduras)

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Mining protein structure data

The principal topic of this work is the application of data mining techniques, in particular of machine learning, to the discovery of knowledge in a protein database. In the first chapter a general background is presented. Namely, in section 1.1 we overview the methodology of a Data Mining project and its main algorithms. In section 1.2 an introduction to the proteins and its supporting file formats is outlined. This chapter is concluded with section 1.3 which defines that main problem we pretend to address with this work: determine if an amino acid is exposed or buried in a protein, in a discrete way (i.e.: not continuous), for five exposition levels: 2%, 10%, 20%, 25% and 30%. In the second chapter, following closely the CRISP-DM methodology, whole the process of construction the database that supported this work is presented. Namely, it is described the process of loading data from the Protein Data Bank, DSSP and SCOP. Then an initial data exploration is performed and a simple prediction model (baseline) of the relative solvent accessibility of an amino acid is introduced. It is also introduced the Data Mining Table Creator, a program developed to produce the data mining tables required for this problem. In the third chapter the results obtained are analyzed with statistical significance tests. Initially the several used classifiers (Neural Networks, C5.0, CART and Chaid) are compared and it is concluded that C5.0 is the most suitable for the problem at stake. It is also compared the influence of parameters like the amino acid information level, the amino acid window size and the SCOP class type in the accuracy of the predictive models. The fourth chapter starts with a brief revision of the literature about amino acid relative solvent accessibility. Then, we overview the main results achieved and finally discuss about possible future work. The fifth and last chapter consists of appendices. Appendix A has the schema of the database that supported this thesis. Appendix B has a set of tables with additional information. Appendix C describes the software provided in the DVD accompanying this thesis that allows the reconstruction of the present work.

Spatial data infrastructures model for developing countries: A case study of Nigeria

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Discovery and retrieval of Geographic data using Google

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Visualization of clusters in geo-referenced data using three-dimensional self-organizing maps

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Exploratory geospatial data analysis using self-organizing maps

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

Multi-scale vegetation classification using earth observation data of the Sundarban mangrove forest, Bangladesh.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Landslide susceptibility assessment in Karanganyar regency - Indonesia - Comparison of knowledge-based and Data-driven Models

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Providing energy efficiency location-based strategies for buildings using linked open data

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Analysis of benefits of the process of certification on international standars: ISO 9001-2008 for Mapfre Assistencia Portugal

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Data queries over heterogeneous sources

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Intrusion tolerant routing with data consensus in wireless sensor networks

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Mental health care assessed based on structure, process and outcome : a retrospective cohort study

RESUMO: As doenças mentais são comuns, universais e associadas a uma significativa sobrecarga pessoal, familiar, social e económica. Os Serviços de Saúde Mental devem abordar de forma adequada as necessidades dos pacientes e familiares tanto ao nível clínico como também ao nível social. O presente estudo foi realizado num período de grande transformação nos sistemas de saúde primário e de saúde mental em Portugal, num Departamento de Psiquiatria desenvolvido com base nos princípios da OMS. Os objectivos incluem a caracterização: 1) das Unidades Funcionais do Departamento; 2) dos pacientes internados pela primeira vez no internamento de agudos; 3) da utilização dos serviços nas equipas comunitárias após a alta; e 4) da avaliação de alguns dos indicadores de qualidade do departamento, com recurso ao modelo de Donabedian sobre a articulação entre a Estrutura-Processo-Resultados. Metodologia: Foi escolhido um estudo de coorte retrospectivo. Todos os pacientes internados pela primeira vez entre 2008 e 2010 foram incluídos no estudo. Os seus processos clínicos e a base de dados do hospital onde são registados todos os contactos que estes tiveram com os profissionais de saúde mental foram revistos de forma a obter dados sociodemográficos e clínicos, durante o período do estudo e após a alta. Os instrumentos utilizados foram o WHO-ICMHC (Classificação Internacional de Cuidados de Saúde Mental), para caracterizar o Departamento, o AIESMP (Avaliação Inicial de Enfermagem em Saúde Mental e Psiquiatria) para recolha dos dados sociodemográficos, e o VSSS (Escala de Satisfação com os Serviços de Verona) de forma a avaliar a satisfação dos pacientes em relação aos cuidados recebidos. A análise estatística incluiu a análise descritiva, quantitativa e qualitativa dos dados. Resultados: As Unidades Funcionais do Departamento revelaram níveis elevados de articulação e consistência com as necessidades de cuidados psiquiátricos e reabilitação psicossocial dos pacientes. Os 543 pacientes admitidos pela primeira vez eram maioritariamente (56.9%) mulheres, caucasianas (81.2%), com diagnóstico de perturbações do humor (66.3%), internadas voluntariamente (59.7%), e uma idade média de 45.1 anos. Estas eram significativamente mais velhas, mais frequentemente empregadas, casadas/coabitar e tinham uma prevalência mais elevada de perturbações do humor, comparativamente aos homens. O internamento compulsivo era mais significativo nos homens (54.7%). A taxa de abandono no pós-alta (4.2%) e a taxa de reinternamentos (2.9%) na quinzena após a alta revelaram-se inferiores aos padrões na literatura internacional. De forma global, a satisfação dos pacientes com os cuidados de saúde mental foi positiva. Conclusões: Os cuidados prestados mostraram-se eficazes, adaptados e baseados nas necessidades e problemas específicos dos pacientes. A continuidade e a abrangência de cuidados foram difundidos e mantidos ao longo do processo de cuidados. Este Departamento pode ser considerado um exemplo de como proporcionar tratamento digno e eficiente, e uma referência para futuros serviços de psiquiatria.-------------- ABSTRACT: Mental health disorders are common, universal, and associated with heavy personal, family, social and economic burden. Mental health services should be aimed at adequately addressing patients’ and families’ needs at clinical and social level. The current study was carried out at a time of great transformation in the health and mental health systems in Portugal, in a Psychiatric Department developed taking in consideration the WHO principles. The objectives included characterizing: 1) the Psychiatric Department’s different units; 2) the patients admitted for the first time to the inpatient unit; 3) their use of community mental health services after discharge; and 4) assessing some of the department’s quality indicators, with resource to Donabedian’s Structure-Process-Outcome model. Methodology: A retrospective cohort design was chosen. All the firstly admitted patients in the period between 2008 and 2010 were included in the study. Their clinical records and the hospital’s database which registers all of the contacts the patients had with the mental health professionals during the study period, were reviewed to retrieve sociodemographic and clinical data and information on follow-up. The instruments used were the WHO International Classification of Mental Health Care (ICMHC) to characterize the department, the Initial Nurses’ Assessment in Mental Health and Psychiatry (AIESMP) for patients’ sociodemographic data, and the Verona Service Satisfaction Scale (VSSS) to assess patients’ satisfaction with care received. Statistical analysis included descriptive, quantitative and qualitative analysis of the data. Results: The Department’s Functional units revealed high levels of articulation, and were consistent with patients’ needs for psychiatric care and psychosocial rehabilitation. The 543 patients firstly admitted were mainly (56.9%) female, Caucasian (81.2%), diagnosed with mood disorders (66.3%), voluntarily admitted (59.7%), and with a mean age of 45.1 years. Female patients were significantly older, more frequently employed, married/cohabiting and had a higher prevalence of mood disorders when compared to males. Involuntary admission was more significant in males (54.7%). Dropout rates during follow-up (4.2%) and readmission rates (2.9%) in the fortnight following discharge were lower than standards in international literature. Overall patients’ satisfaction with mental health care was positive. Conclusions: The care delivered was effective, adapted and based on the patients’ specific needs and problems. Continuity and comprehensiveness of care was endorsed and maintained throughout the care process. This department may be considered an example of both humane and effective treatment, and a reference for future psychiatric care.

Integrated data model and DSL modifications

Companies are increasingly more and more dependent on distributed web-based software systems to support their businesses. This increases the need to maintain and extend software systems with up-to-date new features. Thus, the development process to introduce new features usually needs to be swift and agile, and the supporting software evolution process needs to be safe, fast, and efficient. However, this is usually a difficult and challenging task for a developer due to the lack of support offered by programming environments, frameworks, and database management systems. Changes needed at the code level, database model, and the actual data contained in the database must be planned and developed together and executed in a synchronized way. Even under a careful development discipline, the impact of changing an application data model is hard to predict. The lifetime of an application comprises changes and updates designed and tested using data, which is usually far from the real, production, data. So, coding DDL and DML SQL scripts to update database schema and data, is the usual (and hard) approach taken by developers. Such manual approach is error prone and disconnected from the real data in production, because developers may not know the exact impact of their changes. This work aims to improve the maintenance process in the context of Agile Platform by Outsystems. Our goal is to design and implement new data-model evolution features that ensure a safe support for change and a sound migration process. Our solution includes impact analysis mechanisms targeting the data model and the data itself. This provides, to developers, a safe, simple, and guided evolution process.