Design and implementation of 3D buildings integration for a Webgl-Based Virtual Globe: a case study of Valencian Cadastre and Fide Building Mode

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

NEGOSEIO: framework for the sustainability of model-oriented enterprise interoperability

Dissertation to obtain the degree of Doctor of Philosophy in Electrical and Computer Engineering(Industrial Information Systems)

A cross-cultural study on the effect of decimal separator on price perception

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

An ANP model to support decision-making in a Portuguese pharmaceutical supply chain

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Design of future distribution grids

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

New visualization model for large scale biosignals analysis

Benefits of long-term monitoring have drawn considerable attention in healthcare. Since the acquired data provides an important source of information to clinicians and researchers, the choice for long-term monitoring studies has become frequent. However, long-term monitoring can result in massive datasets, which makes the analysis of the acquired biosignals a challenge. In this case, visualization, which is a key point in signal analysis, presents several limitations and the annotations handling in which some machine learning algorithms depend on, turn out to be a complex task. In order to overcome these problems a novel web-based application for biosignals visualization and annotation in a fast and user friendly way was developed. This was possible through the study and implementation of a visualization model. The main process of this model, the visualization process, comprised the constitution of the domain problem, the abstraction design, the development of a multilevel visualization and the study and choice of the visualization techniques that better communicate the information carried by the data. In a second process, the visual encoding variables were the study target. Finally, the improved interaction exploration techniques were implemented where the annotation handling stands out. Three case studies are presented and discussed and a usability study supports the reliability of the implemented work.

Glia-Motoneuron dialogue in ALS onset and progression in SOD1G93A-mice model

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the pro-gressive loss of motoneurons (MN). Increasing evidence points glial cells as key players for ALS onset and progression. Indeed, MN-glia signalling pathways involving either neuroprotection or inflammation are likely to be altered in ALS. We aimed to study the molecules related with glial function and/or reactivity by evaluating glial markers and hemichannels, mainly present in astrocytes. We also studied molecules involved in mi-croglia-MN dialogue (CXCR3/CCL21; CX3CR1/CX3CL1; MFG-E8), as well as proliferation (Ki-67) and inflammatory-related molecules (TLR2/4, NLRP3; IL-18) and alarming/calming signals (HMGB1/autotaxin). We used lumbar spinal cord (SC) homogenates from mice expressing a mutant human-SOD1 protein (mSOD1) at presymptomatic and late-symptomatic ALS stages. SJL (WT) mice at same ages were used as controls. We observed decreased expression of genes associated with astrocytic (GFAP and S100B) and microglial (CD11b) markers in mSOD1 at the presymptomatic phase, as well as diminished levels of gap junction components pannexin1 and connexin43 and expression of Ki-67 and decreased autotax-in. In addition, microglial-MN communication was negatively affected in mSOD1 mice as well as in-flammatory response. Interestingly, we observed astrocytic (S100B) and microglial (CD11b) reactivity, increased proliferation (Ki-67) and increased autotaxin expression in symptomatic mSOD1 mice. In-creased MN-microglial dialogue (CXCR3/CCL21; CX3CR1/CX3CL1; MFG-E8) and hemichannel activ-ity, namely connexin43 and pannexin1, were also observed in mSOD1 at the symptomatic phase, along with an elevated inflammatory response as indicated by increased levels of HMGB1 and NLRP3. Our results suggest that decreased autotaxin expression is a feature of the presymptomatic stage, and precede the network of pro-inflammatory-related symptomatic determinants, including HMGB1, CCL21, CX3CL1, and NLRP3. The identification of the molecules and signaling pathways that are dif-ferentially activated along ALS progression will contribute for a better design of therapeutic strategies for disease onset and progression.

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.

Genome-scale metabolic network reconstruction of Polaromonas sp. strain JS666: analysis of cDCE degradation rates and design of experiments for bioremediation improvement

Release of chloroethene compounds into the environment often results in groundwater contamination, which puts people at risk of exposure by drinking contaminated water. cDCE (cis-1,2-dichloroethene) accumulation on subsurface environments is a common environmental problem due to stagnation and partial degradation of other precursor chloroethene species. Polaromonas sp. strain JS666 apparently requires no exotic growth factors to be used as a bioaugmentation agent for aerobic cDCE degradation. Although being the only suitable microorganism found capable of such, further studies are needed for improving the intrinsic bioremediation rates and fully comprehend the metabolic processes involved. In order to do so, a metabolic model, iJS666, was reconstructed from genome annotation and available bibliographic data. FVA (Flux Variability Analysis) and FBA (Flux Balance Analysis) techniques were used to satisfactory validate the predictive capabilities of the iJS666 model. The iJS666 model was able to predict biomass growth for different previously tested conditions, allowed to design key experiments which should be done for further model improvement and, also, produced viable predictions for the use of biostimulant metabolites in the cDCE biodegradation.

Analysis and design of sinusoidal quadrature RC-oscillators

Modern telecommunication equipment requires components that operate in many different frequency bands and support multiple communication standards, to cope with the growing demand for higher data rate. Also, a growing number of standards are adopting the use of spectrum efficient digital modulations, such as quadrature amplitude modulation (QAM) and orthogonal frequency division multiplexing (OFDM). These modulation schemes require accurate quadrature oscillators, which makes the quadrature oscillator a key block in modern radio frequency (RF) transceivers. The wide tuning range characteristics of inductorless quadrature oscillators make them natural candidates, despite their higher phase noise, in comparison with LC-oscillators. This thesis presents a detailed study of inductorless sinusoidal quadrature oscillators. Three quadrature oscillators are investigated: the active coupling RC-oscillator, the novel capacitive coupling RCoscillator, and the two-integrator oscillator. The thesis includes a detailed analysis of the Van der Pol oscillator (VDPO). This is used as a base model oscillator for the analysis of the coupled oscillators. Hence, the three oscillators are approximated by the VDPO. From the nonlinear Van der Pol equations, the oscillators’ key parameters are obtained. It is analysed first the case without component mismatches and then the case with mismatches. The research is focused on determining the impact of the components’ mismatches on the oscillator key parameters: frequency, amplitude-, and quadrature-errors. Furthermore, the minimization of the errors by adjusting the circuit parameters is addressed. A novel quadrature RC-oscillator using capacitive coupling is proposed. The advantages of using the capacitive coupling are that it is noiseless, requires a small area, and has low power dissipation. The equations of the oscillation amplitude, frequency, quadrature-error, and amplitude mismatch are derived. The theoretical results are confirmed by simulation and by measurement of two prototypes fabricated in 130 nm standard complementary metal-oxide-semiconductor (CMOS) technology. The measurements reveal that the power increase due to the coupling is marginal, leading to a figure-of-merit of -154.8 dBc/Hz. These results are consistent with the noiseless feature of this coupling and are comparable to those of the best state-of-the-art RC-oscillators, in the GHz range, but with the lowest power consumption (about 9 mW). The results for the three oscillators show that the amplitude- and the quadrature-errors are proportional to the component mismatches and inversely proportional to the coupling strength. Thus, increasing the coupling strength decreases both the amplitude- and quadrature-errors. With proper coupling strength, a quadrature error below 1° and amplitude imbalance below 1% are obtained. Furthermore, the simulations show that increasing the coupling strength reduces the phase noise. Hence, there is no trade-off between phase noise and quadrature error. In the twointegrator oscillator study, it was found that the quadrature error can be eliminated by adjusting the transconductances to compensate the capacitance mismatch. However, to obtain outputs in perfect quadrature one must allow some amplitude error.

Electro-Optical/Infrared sensor turret integration on an aircraft - structural im-pact on LOCKHEED MARTIN C-130H and design methodology

The growing need to patrol and survey large maritime and terrestrial areas increased the need to integrate external sensors on aircraft in order to accomplish those patrols at increasingly higher altitudes, longer range and not depending upon vehicle type. The main focus of this work is to elaborate a practical, simple, effective and efficient methodology for the aircraft modification procedure resulting from the integration of an Elec-tro-Optical/Infra-Red (EO/IR) turret through a support structure. The importance of the devel-opment of a good methodology relies on the correct management of project variables as time, available resources and project complexity. The key is to deliver a proper tool for a project de-sign team that will be used to create a solution that fulfils all technical, non-technical and certi-fication requirements present in this field of transportation. The created methodology is inde-pendent of two main inputs: sensor model and aircraft model definition, and therefore it is in-tended to deliver the results for different projects besides the one that was presented in this work as a case study. This particular case study presents the development of a structure support for FLIR STAR SAPHIRE III turret integration on the front lower fuselage bulkhead (radome) of the LOCKHEED MARTIN C-130 H. Development of the case study focuses on the study of local structural analysis through the use of Finite Element Method (FEM). Development of this Dissertation resulted in a cooperation between Faculty of Science and Technology - Universidade Nova de Lisboa and the company OGMA - Indústria Aeronáutica de Portugal

A systematic methodology to analyse the performance and design configurations of business interoperability in cooperative industrial networks

This thesis proposes a methodology for modelling business interoperability in a context of cooperative industrial networks. The purpose is to develop a methodology that enables the design of cooperative industrial network platforms that are able to deliver business interoperability and the analysis of its impact on the performance of these platforms. To achieve the proposed objective, two modelling tools have been employed: the Axiomatic Design Theory for the design of interoperable platforms; and Agent-Based Simulation for the analysis of the impact of business interoperability. The sequence of the application of the two modelling tools depends on the scenario under analysis, i.e. whether the cooperative industrial network platform exists or not. If the cooperative industrial network platform does not exist, the methodology suggests first the application of the Axiomatic Design Theory to design different configurations of interoperable cooperative industrial network platforms, and then the use of Agent-Based Simulation to analyse or predict the business interoperability and operational performance of the designed configurations. Otherwise, one should start by analysing the performance of the existing platform and based on the achieved results, decide whether it is necessary to redesign it or not. If the redesign is needed, simulation is once again used to predict the performance of the redesigned platform. To explain how those two modelling tools can be applied in practice, a theoretical modelling framework, a theoretical Axiomatic Design model and a theoretical Agent-Based Simulation model are proposed. To demonstrate the applicability of the proposed methodology and/or to validate the proposed theoretical models, a case study regarding a Portuguese Reverse Logistics cooperative network (Valorpneu network) and a case study regarding a Portuguese construction project (Dam Baixo Sabor network) are presented. The findings of the application of the proposed methodology to these two case studies suggest that indeed the Axiomatic Design Theory can effectively contribute in the design of interoperable cooperative industrial network platforms and that Agent-Based Simulation provides an effective set of tools for analysing the impact of business interoperability on the performance of those platforms. However, these conclusions cannot be generalised as only two case studies have been carried out. In terms of relevance to theory, this is the first time that the network effect is addressed in the analysis of the impact of business interoperability on the performance of networked companies and also the first time that a holistic approach is proposed to design interoperable cooperative industrial network platforms. Regarding the practical implications, the proposed methodology is intended to provide industrial managers a management tool that can guide them easily, and in practical and systematic way, in the design of configurations of interoperable cooperative industrial network platforms and/or in the analysis of the impact of business interoperability on the performance of their companies and the networks where their companies operate.

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.

Design of bio-inspired ionic liquids for protein stabilisation

Ionic Liquids (ILs) consist in organic salts that are liquid at/or near room temperature. Since ILs are entirely composed of ions, the formation of ion pairs is expected to be one essential feature for describing solvation in ILs. In recent years, protein - ionic liquid (P-IL) interactions have been the subject of intensive studies mainly because of their capability to promote folding/unfolding of proteins. However, the ion pairs and their lifetimes in ILs in P-IL thematic is dismissed, since the action of ILs is therefore the result of a subtle equilibrium between anion-cation interaction, ion-solvent and ion-protein interaction. The work developed in this thesis innovates in this thematic, once the design of ILs for protein stabilisation was bio-inspired in the high concentration of organic charged metabolites found in cell milieu. Although this perception is overlooked, those combined concentrations have been estimated to be ~300 mM among the macromolecules at concentrations exceeding 300 g/L (macromolecular crowding) and transient ion-pair can naturally occur with a potential specific biological role. Hence the main objective of this work is to develop new bio-ILs with a detectable ion-pair and understand its effects on protein structure and stability, under crowding environment, using advanced NMR techniques and calorimetric techniques. The choline-glutamate ([Ch][Glu]) IL was synthesized and characterized. The ion-pair was detected in water solutions using mainly the selective NOE NMR technique. Through the same technique, it was possible to detect a similar ion-pair promotion under synthetic and natural crowding environments. Using NMR spectroscopy (protein diffusion, HSQC experiments, and hydrogen-deuterium exchange) and differential scanning calorimetry (DSC), the model protein GB1 (production and purification in isotopic enrichment media) it was studied in the presence of [Ch][Glu] under macromolecular crowding conditions (PEG, BSA, lysozyme). Under dilute condition, it is possible to assert that the [Ch][Glu] induces a preferential hydration by weak and non-specific interactions, which leads to a significant stabilisation. On the other hand, under crowding environment, the [Ch][Glu] ion pair is promoted, destabilising the protein by favourable weak hydrophobic interactions , which disrupt the hydration layer of the protein. However, this capability can mitigates the effect of protein crowders. Overall, this work explored the ion-pair existence and its consequences on proteins in conditions similar to cell milieu. In this way, the charged metabolites found in cell can be understood as key for protein stabilisation.

Proving a market for a startup befor scaling using the hypothesis-driven entrepreneurship process

The year is 2015 and the startup and tech business ecosphere has never seen more activity. In New York City alone, the tech startup industry is on track to amass $8 billion dollars in total funding – the highest in 7 years (CB Insights, 2015). According to the Kauffman Index of Entrepreneurship (2015), this figure represents just 20% of the total funding in the United States. Thanks to platforms that link entrepreneurs with investors, there are simply more funding opportunities than ever, and funding can be initiated in a variety of ways (angel investors, venture capital firms, crowdfunding). And yet, in spite of all this, according to Forbes Magazine (2015), nine of ten startups will fail. Because of the unpredictable nature of the modern tech industry, it is difficult to pinpoint exactly why 90% of startups fail – but the general consensus amongst top tech executives is that “startups make products that no one wants” (Fortune, 2014). In 2011, author Eric Ries wrote a book called The Lean Startup in attempts to solve this all-too-familiar problem. It was in this book where he developed the framework for The Hypothesis-Driven Entrepreneurship Process, an iterative process that aims at proving a market before actually launching a product. Ries discusses concepts such as the Minimum Variable Product, the smallest set of activities necessary to disprove a hypothesis (or business model characteristic). Ries encourages acting briefly and often: if you are to fail, then fail fast. In today’s fast-moving economy, an entrepreneur cannot afford to waste his own time, nor his customer’s time. The purpose of this thesis is to conduct an in-depth of analysis of Hypothesis-Driven Entrepreneurship Process, in order to test market viability of a reallife startup idea, ShowMeAround. This analysis will follow the scientific Lean Startup approach; for the purpose of developing a functional business model and business plan. The objective is to conclude with an investment-ready startup idea, backed by rigorous entrepreneurial study.