Overcoming the “European Paradox”: The role of Regional Innovation Systems (RIS) in translating R&D investments into economic and employment growth

The emergence of the so-called “European Paradox” shows that R&D investment is not maximally effective and that increasing the scale of public R&D expenditures is not sufficient to generate employment and sustained economic growth. Increasing Governmental R&D Investment is far from being a “panacea” for stagnant growth. It is worth noting that Government R&D Investment does not have a statistically significant impact on employment, indicating the need to assess the trade-offs of policies that could lead to significant increases in government expenditure. Surprisingly, Governmental R&D Employment does not contribute to “mass-market” employment, despite its quite important role in reducing Youth-Unemployment. Despite the negative side-effects of Governmental R&D Employment on both GVA and GDP, University R&D Employment appears to have a quite important role in reducing Unemployment, especially Youth-Unemployment, while it also does not have a downside in terms of economic growth. Technological Capacity enhancement is the most effective instrument for reducing Unemployment and is a policy without any downside regarding sustainable economical development. In terms of wider policy implications, the results reinforce the idea that European Commission Research and Innovation policies must be restructured, shifting from a transnational framework to a more localised, measurable and operational approach.

Optimization of export support systems: How to promote exports from Portugal to Germany in the area of information technology and electronics

This work project focuses on developing new approaches which enhance Portuguese exports towards a defined German industry sector within the information technology and electronics fields. Firstly and foremost, information was collected and a set of expert and top managers’ interviews were performed in order to acknowledge the demand of the German market while identifying compatible Portuguese supply capabilities. Among the main findings, Industry 4.0 presents itself as a valuable opportunity in the German market for Portuguese medium sized companies in the embedded systems area of expertise for machinery and equipment companies. In order to achieve the purpose of the work project, an embedded systems platform targeting machinery and equipment companies was suggested as well as it was developed several recommendations on how to implement it. An alternative approach for this platform was also considered within the German market namely the eHealth sector having the purpose of enhancing the current healthcare service provision.

Optimization of export support systems

The present paper is a personal reflection on a work project carried out to promote exports from Portugal to Germany in the IT area, under consideration of the deliverables required by the clients CCILA and Anetie. The project outcome approaches the fact that the majority of the Portuguese market players has disadvantages in size and does rarely coordinate activities among each other, which hinders them to export successfully on a broad scale. To bring together Portuguese delivery potential and German market demand, expert interviews were conducted. Based on the findings, a concept was developed to overcome the domestic collaboration issues in order to strengthen the national exports in the identified sector - embedded systems implementation services for machinery and equipment companies.

Comparateive analysis: Public and private school management systems

The Portuguese educational system has counted, for many years, with the co-existence of both public and private schools. In fact, the country’s growth and development led, in the past, to an increasing demand for free of charge public education that could only be matched through the creation of “publicly-subsidized and privately owned and managed schools”. Still, the demographic evolution of Portugal recently generated a decrease on the demand for public educational services. This situation has raised doubts about the true contribution of this type of school for the public education system. This paper aims at answering this question by isolating the impact of different property and management schemes on the performance of students, resorting to cross-section data on 9th grade students from 2010. The results corroborate the well known result on the relevance of the family socio-economic background for students’ performance, but do also sustain the existence of a significant positive impact of private ownership and management schemes on the overall performance of students. These results suggest that there might be gains associated with the expansion of such schemes within the public education system.

Fiscal adjustments and sovereign default in different government systems

This paper extends the model of Spolaore (2004) about adjustments in di erent government systems for the context of scal adjustments and sovereign default. We introduce asymmetry between groups in income and preferences towards scal reforms. Default a ects di erently each group and becomes a possibility if reforms are not enacted after public nance solvency shocks, in uencing the political game according to its likelihood. With the extensions, new situations which were not possible with the previous framework arise. After the exposition of the model, the Argentine default in 2001 provides an example of the political con icts addressed by the model.

Fractional state space analysis of economic systems

This paper examines modern economic growth according to the multidimensional scaling (MDS) method and state space portrait (SSP) analysis. Electing GDP per capita as the main indicator for economic growth and prosperity, the long-run perspective from 1870 to 2010 identifies the main similarities among 34 world partners’ modern economic growth and exemplifies the historical waving mechanics of the largest world economy, the USA. MDS reveals two main clusters among the European countries and their old offshore territories, and SSP identifies the Great Depression as a mild challenge to the American global performance, when compared to the Second World War and the 2008 crisis.

Blocking tumor exosome release using nanovectorization systems

Exosomes are small membrane vesicles secreted by most cell types, either normal or malignant and are found in most body fluids such as saliva, plasma and breast milk. In the past decade, the interest in these vesicles has been growing more and more since it was found that besides their beneficial functions such as the removal of cellular debris and unnecessary proteins during cell maturation process, they can also interact with other cells and transfer information between them, thus helping diseases like cancer to progress. The present work intended to use gold nanoparticles as vehicles for gene silencing in an attempt to reduce the tumor-derived exosome secretion, regulated by Rab27a protein, and also aimed to compare the exosome secretion between two breast cell lines, MCF7 and MDA. Changes in RAB27A gene expression were measured by Real-time Quantitative PCR and it was revealed a decreased in RAB27A gene expression, as expected. Exosomes were isolated and purified by two different methods, ultracentrifugation and the commercial kit ExoQuick™ Solution, and further characterized using Western Blot analysis. ExoQuick™ Solution was proven to be the most efficient method for exosome isolation and it was revealed that MDA cells secrete more exosomes. Furthermore, the isolated MCF7-derived exosomes were placed together with a normal bronchial/tracheal epithelial cell line (BTEC) for an additional assay, which aimed to observe the uptake of exosomes by other cells and the exosomes’ capability of promoting cell-cell communication. This observation was made based on alterations in the expression levels of c-Myc and miR-21 genes and the fact that they both have an increased expression in BTEC cells incubated with tumor-derived exosomes when compared to control cells (without incubation with the exosomes) lead us to the conclusion that the exosome uptake and exchange of information between the exosomes and the normal cells did occurred.

Development of process control strategies exploiting knowledge from systems biology: application to MDCK suspension cells

Madine Darby Canine Kidney (MDCK) cell lines have been extensively evaluated for their potential as host cells for influenza vaccine production. Recent studies allowed the cultivation of these cells in a fully defined medium and in suspension. However, reaching high cell densities in animal cell cultures still remains a challenge. To address this shortcoming, a combined methodology allied with knowledge from systems biology was reported to study the impact of the cell environment on the flux distribution. An optimization of the medium composition was proposed for both a batch and a continuous system in order to reach higher cell densities. To obtain insight into the metabolic activity of these cells, a detailed metabolic model previously developed by Wahl A. et. al was used. The experimental data of four cultivations of MDCK suspension cells, grown under different conditions and used in this work came from the Max Planck Institute, Magdeburg, Germany. Classical metabolic flux analysis (MFA) was used to estimate the intracellular flux distribution of each cultivation and then combined with partial least squares (PLS) method to establish a link between the estimated metabolic state and the cell environment. The validation of the MFA model was made and its consistency checked. The resulted PLS model explained almost 70% of the variance present in the flux distribution. The medium optimization for the continuous system and for the batch system resulted in higher biomass growth rates than the ones obtained experimentally, 0.034 h-1 and 0.030 h-1, respectively, thus reducing in almost 10 hours the duplication time. Additionally, the optimal medium obtained for the continuous system almost did not consider pyruvate. Overall the proposed methodology seems to be effective and both proposed medium optimizations seem to be promising to reach high cell densities.

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.

Machine diagnosis based on artificial immune systems

Nowadays, many of the manufactory and industrial system has a diagnosis system on top of it, responsible for ensuring the lifetime of the system itself. It achieves this by performing both diagnosis and error recovery procedures in real production time, on each of the individual parts of the system. There are many paradigms currently being used for diagnosis. However, they still fail to answer all the requirements imposed by the enterprises making it necessary for a different approach to take place. This happens mostly on the error recovery paradigms since the great diversity that is nowadays present in the industrial environment makes it highly unlikely for every single error to be fixed under a real time, no production stop, perspective. This work proposes a still relatively unknown paradigm to manufactory. The Artificial Immune Systems (AIS), which relies on bio-inspired algorithms, comes as a valid alternative to the ones currently being used. The proposed work is a multi-agent architecture that establishes the Artificial Immune Systems, based on bio-inspired algorithms. The main goal of this architecture is to solve for a resolution to the error currently detected by the system. The proposed architecture was tested using two different simulation environment, each meant to prove different points of views, using different tests. These tests will determine if, as the research suggests, this paradigm is a promising alternative for the industrial environment. It will also define what should be done to improve the current architecture and if it should be applied in a decentralised system.

Therapeutics bioconjugates: evaluation of iminoboronates as payload delivery system for cancer

The advent of bioconjugation impacted deeply the world of sciences and technology. New biomolecules were found, biological processes were understood, and novel methodologies were formed due to the fast expansion of this area. The possibility of creating new effective therapies for diseases like cancer is one of big applications of this now big area of study. Off target toxicity was always the problem of potent small molecules with high activity towards specific tumour targets. However, chemotherapy is now selective due to powerful linkers that connect targeting molecules with affinity to interesting biological receptors and cytotoxic drugs. This linkers must have very specific properties, such as high stability in plasma, no toxicity, no interference with ligand affinity nor drug potency, and at the same time, be able to lyse once inside the target molecule to release the therapeutic warhead. Bipolar environments between tumour intracellular and extracellular medias are usually exploited by this linkers in order to complete this goal. The work done in this thesis explores a new model for that same task, specific cancer drug delivery. Iminoboronates were studied due to its remarkable selective stability towards a wide pH range and endogenous molecules. A fluorescence probe was design to validate this model by creating an Off/On system and determine the payload release location in situ. A process was optimized to synthetize the probe 8-(1-aminoethyl)-7-hydroxy-coumarin (1) through a reductive amination reaction in a microwave reactor with 61 % yield. A method to conjugate this probe to ABBA was also optimized, obtaining the iminoboronate in good yields in mild conditions. The iminoboronate model was studied regarding its stability in several simulated biological environments and each half-life time was determined, showing the conjugate is stable most of the cases except in tumour intracellular systems. The construction of folate-ABBA-coumarin bioconjugate have been made to complete this evaluation. The ability to be uptaken by a cancer cell through endocytosis process and the conjugation delivery of coumarin fluorescence payload are two features to hope for in this construct.

Learning domain-specific sentiment lexicons with applications to recommender systems

Search is now going beyond looking for factual information, and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present dissertation addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. For this research objective we propose to capture sentiment words that are derived from online users’ reviews. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. To this aim we present a fully generative method that automatically learns a domain-specific lexicon and is fully independent of external sources. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. Therefore, we present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm. Furthermore, entities’ reputation is intrinsically associated with sentiment words that have a positive or negative relation with those entities. Hence, is provided a study that observes the viability of using a domain-specific lexicon to compute entities reputation. Finally, a recommendation system algorithm is improved with the use of sentiment-based ratings and entities reputation.

Synthesis and characterization of C3-symmetric 1,3,5 - Benzenetricarboxamide derived supramolecular systems

The aim of this work was to study the self-assembly process of C3-symmetric molecules. To accomplish this objective 1,3,5 – benzentricarboxamides (BTA) derivatives were obtained. Five C3-symmetric molecules were synthesized in moderate to good yields (39-72%) using azo-benzene, aniline, benzylamine, tryptophan and tyrosine. The aggregation behavior of the BTA derivatives was probed with 1H-NMR spectroscopy, 1H-1H 2D Nuclear Overhauser Effect Spectroscopy (NOESY) and Diffusion Ordered Spectroscopy (DOSY). These experiments allowed to study the influence of H-bonding groups, aromatic rings, unsaturated bonds and the overall geometry in the molecular self-assembly associated with the different structural patterns present on these molecules. The stacking and large molecule behavior where observed in BTA 1, aniline derivative, BTA 4, tyrosine derivative or BTA 5, tryptophan derivative, with several of those discussed functional groups such as unsaturated bonds and H-bonding groups. BTA 5 was used in a few preliminary interaction studies with glucose and ammonium chloride showing interaction with the ammonium ion.