Orthogonal models, structure crossing, nesting and inference

We intend to study the algebraic structure of the simple orthogonal models to use them, through binary operations as building blocks in the construction of more complex orthogonal models. We start by presenting some matrix results considering Commutative Jordan Algebras of symmetric matrices, CJAs. Next, we use these results to study the algebraic structure of orthogonal models, obtained by crossing and nesting simpler ones. Then, we study the normal models with OBS, which can also be orthogonal models. We intend to study normal models with OBS (Orthogonal Block Structure), NOBS (Normal Orthogonal Block Structure), obtaining condition for having complete and suffcient statistics, having UMVUE, is unbiased estimators with minimal covariance matrices whatever the variance components. Lastly, see ([Pereira et al. (2014)]), we study the algebraic structure of orthogonal models, mixed models whose variance covariance matrices are all positive semi definite, linear combinations of known orthogonal pairwise orthogonal projection matrices, OPOPM, and whose least square estimators, LSE, of estimable vectors are best linear unbiased estimator, BLUE, whatever the variance components, so they are uniformly BLUE, UBLUE. From the results of the algebraic structure we will get explicit expressions for the LSE of these models.

Cultural journalism in a digital environment : new models, practices and possibilities

Both culture coverage and digital journalism are contemporary phenomena that have undergone several transformations within a short period of time. Whenever the media enters a period of uncertainty such as the present one, there is an attempt to innovate in order to seek sustainability, skip the crisis or find a new public. This indicates that there are new trends to be understood and explored, i.e., how are media innovating in a digital environment? Not only does the professional debate about the future of journalism justify the need to explore the issue, but so do the academic approaches to cultural journalism. However, none of the studies so far have considered innovation as a motto or driver and tried to explain how the media are covering culture, achieving sustainability and engaging with the readers in a digital environment. This research examines how European media which specialize in culture or have an important cultural section are innovating in a digital environment. Specifically, we see how these innovation strategies are being taken in relation to the approach to culture and dominant cultural areas, editorial models, the use of digital tools for telling stories, overall brand positioning and extensions, engagement with the public and business models. We conducted a mixed methods study combining case studies of four media projects, which integrates qualitative web features and content analysis, with quantitative web content analysis. Two major general-interest journalistic brands which started as physical newspapers – The Guardian (London, UK) and Público (Lisbon, Portugal) – a magazine specialized in international affairs, culture and design – Monocle (London, UK) – and a native digital media project that was launched by a cultural organization – Notodo, by La Fábrica – were the four case studies chosen. Findings suggest, on one hand, that we are witnessing a paradigm shift in culture coverage in a digital environment, challenging traditional boundaries related to cultural themes and scope, angles, genres, content format and delivery, engagement and business models. Innovation in the four case studies lies especially along the product dimensions (format and content), brand positioning and process (business model and ways to engage with users). On the other hand, there are still perennial values that are crucial to innovation and sustainability, such as commitment to journalism, consistency (to the reader, to brand extensions and to the advertiser), intelligent differentiation and the capability of knowing what innovation means and how it can be applied, since this thesis also confirms that one formula doesn´t suit all. Changing minds, exceeding cultural inertia and optimizing the memory of the websites, looking at them as living, organic bodies, which continuously interact with the readers in many different ways, and not as a closed collection of articles, are still the main challenges for some media.

Development of human central nervous system 3D in vitro models for preclinical research

Neurological disorders are a major concern in modern societies, with increasing prevalence mainly related with the higher life expectancy. Most of the current available therapeutic options can only control and ameliorate the patients’ symptoms, often be-coming refractory over time. Therapeutic breakthroughs and advances have been hampered by the lack of accurate central nervous system (CNS) models. The develop-ment of these models allows the study of the disease onset/progression mechanisms and the preclinical evaluation of novel therapeutics. This has traditionally relied on genetically engineered animal models that often diverge considerably from the human phenotype (developmentally, anatomically and physiologically) and 2D in vitro cell models, which fail to recapitulate the characteristics of the target tissue (cell-cell and cell-matrix interactions, cell polarity). The in vitro recapitulation of CNS phenotypic and functional features requires the implementation of advanced culture strategies that enable to mimic the in vivo struc-tural and molecular complexity. Models based on differentiation of human neural stem cells (hNSC) in 3D cultures have great potential as complementary tools in preclinical research, bridging the gap between human clinical studies and animal models. This thesis aimed at the development of novel human 3D in vitro CNS models by integrat-ing agitation-based culture systems and a wide array of characterization tools. Neural differentiation of hNSC as 3D neurospheres was explored in Chapter 2. Here, it was demonstrated that human midbrain-derived neural progenitor cells from fetal origin (hmNPC) can generate complex tissue-like structures containing functional dopaminergic neurons, as well as astrocytes and oligodendrocytes. Chapter 3 focused on the development of cellular characterization assays for cell aggregates based on light-sheet fluorescence imaging systems, which resulted in increased spatial resolu-tion both for fixed samples or live imaging. The applicability of the developed human 3D cell model for preclinical research was explored in Chapter 4, evaluating the poten-tial of a viral vector candidate for gene therapy. The efficacy and safety of helper-dependent CAV-2 (hd-CAV-2) for gene delivery in human neurons was evaluated, demonstrating increased neuronal tropism, efficient transgene expression and minimal toxicity. The potential of human 3D in vitro CNS models to mimic brain functions was further addressed in Chapter 5. Exploring the use of 13C-labeled substrates and Nucle-ar Magnetic Resonance (NMR) spectroscopy tools, neural metabolic signatures were evaluated showing lineage-specific metabolic specialization and establishment of neu-ron-astrocytic shuttles upon differentiation. Chapter 6 focused on transferring the knowledge and strategies described in the previous chapters for the implementation of a scalable and robust process for the 3D differentiation of hNSC derived from human induced pluripotent stem cells (hiPSC). Here, software-controlled perfusion stirred-tank bioreactors were used as technological system to sustain cell aggregation and dif-ferentiation. The work developed in this thesis provides practical and versatile new in vitro ap-proaches to model the human brain. Furthermore, the culture strategies described herein can be further extended to other sources of neural phenotypes, including pa-tient-derived hiPSC. The combination of this 3D culture strategy with the implemented characterization methods represents a powerful complementary tool applicable in the drug discovery, toxicology and disease modeling.

The characteristics of social entrepreneurship business models in Portugal

This work project is based on the MIES (Map of Innovation and Social Entrepreneurship in Portugal) database and it aims to understand the characteristics of social business models in the context of the portuguese market, by determining whether they follow the proposed characteristics by John Elkington and Pamela Hartigan, and then adding to their matrix. Furthermore, it tries to determine success patterns by comparing a group of successful social ventures with a group of less successful ones, with the objective of increasing the knowledge of social entrepreneurship as it applies to Portugal and provide a framework for future study.

Integration of geometric consistency contributory factors in three-leg junctions collision prediction models of Portuguese two-lane national highways

This paper aims at developing a collision prediction model for three-leg junctions located in national roads (NR) in Northern Portugal. The focus is to identify factors that contribute for collision type crashes in those locations, mainly factors related to road geometric consistency, since literature is scarce on those, and to research the impact of three modeling methods: generalized estimating equations, random-effects negative binomial models and random-parameters negative binomial models, on the factors of those models. The database used included data published between 2008 and 2010 of 177 three-leg junctions. It was split in three groups of contributing factors which were tested sequentially for each of the adopted models: at first only traffic, then, traffic and the geometric characteristics of the junctions within their area of influence; and, lastly, factors which show the difference between the geometric characteristics of the segments boarding the junctionsâ area of influence and the segment included in that area were added. The choice of the best modeling technique was supported by the result of a cross validation made to ascertain the best model for the three sets of researched contributing factors. The models fitted with random-parameters negative binomial models had the best performance in the process. In the best models obtained for every modeling technique, the characteristics of the road environment, including proxy measures for the geometric consistency, along with traffic volume, contribute significantly to the number of collisions. Both the variables concerning junctions and the various national highway segments in their area of influence, as well as variations from those characteristics concerning roadway segments which border the already mentioned area of influence have proven their relevance and, therefore, there is a rightful need to incorporate the effect of geometric consistency in the three-leg junctions safety studies.

Assessment of the efficiency of prefabricated hybrid composite plates (HCPs) for retrofitting of damaged interior RC beam–column joints

The effectiveness of prefabricated hybrid composite plates (HCPs) as a seismic retrofitting solution for damaged interior RC beam-column joints is experimentally studied. HCP is composed of a thin plate made of strain hardening cementitious composite (SHCC) reinforced with CFRP sheets/laminates. Two full-scale severely damaged interior beam-column joints are retrofitted using two different configurations of HCPs. The effectiveness of these retrofitting solutions mainly in terms of hysteretic response, dissipated energy, degradation of secant stiffness, displacement ductility and failure modes are compared to their virgin states. According to these criteria, both solutions resulted in superior responses regarding the ones registered in their virgin states.

Flexural strengthening of RC beams using hybrid composite plate (HCP): experimental and analytical study

Hybrid Composite Plate (HCP) is a reliable recently proposed retrofitting solution for concrete structures, which is composed of a strain hardening cementitious composite (SHCC) plate reinforced with Carbon Fibre Reinforced Polymer (CFRP). This system benefits from the synergetic advantages of these two composites, namely the high ductility of SHCC and the high tensile strength of CFRPs. In the materialstructural of HCP, the ultra-ductile SHCC plate acts as a suitable medium for stress transfer between CFRP laminates (bonded into the pre-sawn grooves executed on the SHCC plate) and the concrete substrate by means of a connection system made by either chemical anchors, adhesive, or a combination thereof. In comparison with traditional applications of FRP systems, HCP is a retrofitting solution that (i) is less susceptible to the detrimental effect of the lack of strength and soundness of the concrete cover in the strengthening effectiveness; (ii) assures higher durability for the strengthened elements and higher protection to the FRP component in terms of high temperatures and vandalism; and (iii) delays, or even, prevents detachment of concrete substrate. This paper describes the experimental program carried out, and presents and discusses the relevant results obtained on the assessment of the performance of HCP strengthened reinforced concrete (RC) beams subjected to flexural loading. Moreover, an analytical approach to estimate the ultimate flexural capacity of these beams is presented, which was complemented with a numerical strategy for predicting their load-deflection behaviour. By attaching HCP to the beams’ soffit, a significant increase in the flexural capacity at service, at yield initiation of the tension steel bars and at failure of the beams can be achieved, while satisfactory deflection ductility is assured and a high tensile capacity of the CFRP laminates is mobilized. Both analytical and numerical approaches have predicted with satisfactory agreement, the load-deflection response of the reference beam and the strengthened ones tested experimentally.

Shear strengthening of damaged reinforced concrete beams with hybrid composite plates

This paper aims to evaluate experimentally the potentialities of Hybrid Composite Plates (HCPs) technique for the shear strengthening of reinforced concrete (RC) beams that were previously subjected to intense damage in shear. HCP is a thin plate of Strain Hardening Cementitious Composite (SHCC) reinforced with Carbon Fiber Reinforced Polymer (CFRP) laminates. For this purpose, an experimental program composed of two series of beams (rectangular and T cross section) was executed to assess the strengthening efficiency of this technique. In the first step of this experimental program, the control beams, without steel stirrups, were loaded up to their shear failure, and fully unloaded. Then, these pre-damaged beams were shear strengthened by applying HCPs to their lateral faces by using a combination of epoxy adhesive and mechanical anchors. The bolts were applied with a certain torque in order to increase the concrete confinement. The obtained results showed that the increase of load carrying capacity of the damaged strengthened beams when HCPs were applied with epoxy adhesive and mechanical anchors was 2 and 2.5 times of the load carrying capacity of the corresponding reference beams (without HCPs) for the rectangular and T cross section beam series, respectively. To further explore the potentialities of the HCPs technique for the shear strengthening, the experimental tests were simulated using an advanced numerical model by a FEM-based computer program. After demonstration the good predictive performance of the numerical model, a parametric study was executed to highlight the influence of SHCC as an alternative for mortar, as well as the influence of torque level applied to the mechanical anchors, on the load carrying capacity of beams strengthened with the proposed technique.

Evaluation of the performance of recycled textile fibres in the mechanical behaviour of a gypsum and cork composite material

Given the need for using more sustainable constructive solutions, an innovative composite material based on a combination of distinct industrial by-products is proposed aiming to reduce waste and energy consumption in the production of construction materials. The raw materials are thermal activated flue-gas desulphurization (FGD) gypsum, which acts as a binder, granulated cork as the aggregate and recycled textile fibres from used tyres intended to reinforce the material. This paper presents the results of the design of the composite mortar mixes, the characterization of the key physical properties (density, porosity and ultrasonic pulse velocity) and the mechanical validation based on uniaxial compressive tests and fracture energy tests. In the experimental campaign, the influence of the percentage of the raw materials in terms of gypsum mass, on the mechanical properties of the composite material was assessed. It was observed that the percentage of granulated cork decreases the compressive strength of the composite material but contributes to the increase in the compressive fracture energy. Besides, the recycled textile fibres play an important role in the mode I fracture process and in the fracture energy of the composite material, resulting in a considerable increase in the mode I fracture energy.

Conceptual-physical bridging – From BPMN models to physical implementations on kettle

Developing and implementing data-oriented workflows for data migration processes are complex tasks involving several problems related to the integration of data coming from different schemas. Usually, they involve very specific requirements - every process is almost unique. Having a way to abstract their representation will help us to better understand and validate them with business users, which is a crucial step for requirements validation. In this demo we present an approach that provides a way to enrich incrementally conceptual models in order to support an automatic way for producing their correspondent physical implementation. In this demo we will show how B2K (Business to Kettle) system works transforming BPMN 2.0 conceptual models into Kettle data-integration executable processes, approaching the most relevant aspects related to model design and enrichment, model to system transformation, and system execution.

Automatic generation of ETL physical systems from BPMN conceptual models

ETL conceptual modeling is a very important activity in any data warehousing system project implementation. Owning a high-level system representation allowing for a clear identification of the main parts of a data warehousing system is clearly a great advantage, especially in early stages of design and development. However, the effort to model conceptually an ETL system rarely is properly rewarded. Translating ETL conceptual models directly into something that saves work and time on the concrete implementation of the system process it would be, in fact, a great help. In this paper we present and discuss a hybrid approach to this problem, combining the simplicity of interpretation and power of expression of BPMN on ETL systems conceptualization with the use of ETL patterns to produce automatically an ETL skeleton, a first prototype system, which has the ability to be executed in a commercial ETL tool like Kettle.

Implementation of integral viscoelastic constitutive models in OpenFOAM® computational library

This work reports the implementation and verification of a new so lver in OpenFOAM® open source computational library, able to cope with integral viscoelastic models based on the integral upper-convected Maxwell model. The code is verified through the comparison of its predictions with analytical solutions and numerical results obtained with the differential upper-convected Maxwell model

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Producing LFT composite parts for large consumption markets from thermoplastic powder-coated towpregs

Thermoplastic matrix composites are receiving increasing interest in last years. This is due to several advantageous properties and speed of processing of these materials as compared to their thermoset counterparts. Among thermoplastic composites, Long Fibre Thermoplastics (LFTs) have seen the fastest growth, mainly due to developments in the automotive sector. LFTs combine the (semi-)structural material properties of long (>1 cm) fibres, with the ease and speed of thermoplastic processing. This paper reports a study of a novel low-cost LFT technology and resulting composites. A patented powder-coating machine able to produce continuously pre-impregnated materials directly from fibre rovings and polymer powders was used to process glass-fibre reinforced polypropylene (GF/PP) towpregs. Such pre-impregnated materials were then chopped and used to make LFTs in a patented low-cost piston-blender developed by the Centre of Lightweight Structures, TUD-TNO, the Netherlands. The work allowed studying the most relevant towpreg production parameters and establishing the processing window needed to obtain a good quality GF/PP powder coated material. Finally, the processing window that allows producing LFTs of good quality in the piston-blender and the mechanical properties of final stamped GF/PP composite parts were also determined.

Development of a new U 200 pultrusion die to produce GRP composite profiles using different thermosetting resins

In this work, a steel heated pultrusion die was designed, developed and manufactured to produce U200 glass fibre reinforced thermosetting matrix (GRP) profiles. The finite element analysis (FEA) was used to predict and optimise the developed die heating by using cylindrical electrical powered cartridges. To assess the new die performance it was mounted in the 120 kN pultrusion line of the Portuguese company Vidropol SA and used to produce continuously U200 profiles able to meet all requirements specified for the E23 grade accordingly to the European Standard EN 13706: 2002. After setting up the type, orientation and sequence of layers in laminate, orthophthalic, isophthalic and bisphenolic unsaturated polyester as well as vinylester resins were used to produce glass fibre reinforced U 200 composite profiles. An appropriated catalyst system was selected and the processing variables optimised for each case, namely, pultrusion pull-speed and die temperature. Finally, the produced U200 profiles were submitted to visual inspection, calcination and mechanical tests, namely, flexural, tensional and interlaminar shear strength (ILSS) tests, to assess their accomplishment with the EN 13706 requirements.