Aplicação móvel android de apoio a gestão de empréstimos e reservas das bibliotecas da Universidade do Minho

Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática

“It’s a complicated situation”. Harm in everyday experiences with technology. A qualitative study with school-aged children

Tese de Doutoramento em Ciências da Educação (Especialidade de Tecnologia Educativa)

Biosurfactants produced by marine microorganisms with therapeutic applications

Marine microorganisms possess unique metabolic and physiological features and are an important source of new biomolecules, such as biosurfactants. Some of these surface-active compounds synthesized by marine microorganisms exhibit antimicrobial, anti-adhesive and anti-biofilm activity against a broad spectrum of human pathogens (including multi-drug resistant pathogens), and could be used instead of the existing drugs to treat infections caused by them. In other cases, these biosurfactants show anti-cancer activity, which could be envisaged as an alternative to conventional therapies. However, marine biosurfactants have not been widely explored, mainly due to the difficulties associated with the isolation and growth of their producing microorganisms. Culture-independent techniques (metagenomics) constitute a promising approach to study the genetic resources of otherwise inaccessible marine microorganisms without the requirement of culturing them, and can contribute to discover novel biosurfactants with significant biological activities. This paper reviews the most relevant biosurfactants produced by marine microorganisms with potential therapeutic applications and discusses future perspectives and opportunities to discover novel molecules from marine environments.

Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.

Behavior-based price discrimination in a multi-dimensional preferences market

NIPE WP 04/ 2016

Development of a novel aptamer-based multi-sensor device for the detection of osteopontin

Doctoral Dissertation for PhD degree in Chemical and Biological Engineering

A design of experiments to assess phosphorous removal and crystal properties in struvite precipitation of source separated urine using different Mg sources

Supplementary data associated with this article can be found, in the online version, at: http://dx.doi.org/10.1016/j.cej.2016.03.148.

Noise mapping for an urban area: study case: old city of Damascus, Syria

Dissertação de mestrado em Engenharia Urbana

Optimização do processo de recolha de resíduos: desenvolvimento de ferramentas de investigação operacional para o problema de orientação de equipas com multi-restrições

Tese de Doutoramento em Engenharia Industrial e de Sistemas.

Single molecule simulation of diffusion and enzyme kinetics

This work presents a molecular-scale agent-based model for the simulation of enzymatic reactions at experimentally measured concentrations. The model incorporates stochasticity and spatial dependence, using diffusing and reacting particles with physical dimensions. We developed strategies to adjust and validate the enzymatic rates and diffusion coefficients to the information required by the computational agents, i.e., collision efficiency, interaction logic between agents, the time scale associated with interactions (e.g., kinetics), and agent velocity. Also, we tested the impact of molecular location (a source of biological noise) in the speed at which the reactions take place. Simulations were conducted for experimental data on the 2-hydroxymuconate tautomerase (EC 5.3.2.6, UniProt ID Q01468) and the Steroid Delta-isomerase (EC 5.3.3.1, UniProt ID P07445). Obtained results demonstrate that our approach is in accordance to existing experimental data and long-term biophysical and biochemical assumptions.

Anaerobic oxidation of methane associated with sulfate reduction in a natural freshwater gas source

The occurrence of anaerobic oxidation of methane (AOM) and trace methane oxidation (TMO) was investigated in a freshwater natural gas source. Sediment samples were taken and analyzed for potential electron acceptors coupled to AOM. Long-term incubations with 13C-labeled CH4 (13CH4) and different electron acceptors showed that both AOM and TMO occurred. In most conditions, 13C-labeled CO2 (13CO2) simultaneously increased with methane formation, which is typical for TMO. In the presence of nitrate, neither methane formation nor methane oxidation occurred. Net AOM was measured only with sulfate as electron acceptor. Here, sulfide production occurred simultaneously with 13CO2 production and no methanogenesis occurred, excluding TMO as a possible source for 13CO2 production from 13CH4. Archaeal 16S rRNA gene analysis showed the highest presence of ANME-2a/b (ANaerobic MEthane oxidizing archaea) and AAA (AOM Associated Archaea) sequences in the incubations with methane and sulfate as compared with only methane addition. Higher abundance of ANME-2a/b in incubations with methane and sulfate as compared with only sulfate addition was shown by qPCR analysis. Bacterial 16S rRNA gene analysis showed the presence of sulfate-reducing bacteria belonging to SEEP-SRB1. This is the first report that explicitly shows that AOM is associated with sulfate reduction in an enrichment culture of ANME-2a/b and AAA methanotrophs and SEEP-SRB1 sulfate reducers from a low-saline environment.