Viva@Matemática project: a different way to see math

Viva@Mat is a project developed by four Math teachers from the School of Industrial Studies and Management (ESEIG) that was born with the fundamental objective of engaging ESEIG students with different math backgrounds in Math challenging activities. Some of these activities were transformed into real palpable materials and others into small interactive ones, being the great majority of them proposed by ESEIG’ students themselves. This small project rapidly grew into something we didn’t expect – it did flow over the walls of our institution to the general involving community – specifically to pre-university schools through the Viva@Math Exhibits – Orange, Blue and Green (the fourth, the Purple one is still in development). Nowadays, Viva@Math Exhibits – the public face of the Project – are itinerant and have been travelling between several, and different institutions (pre-university schools, preparatory schools, libraries, among others), around ESEIG and IPP area of influence and having registered visitors/participants of all ages. In this article we will describe the Viva@Math Project, its different activities that are categorized in some “great groups” like Numerical Trivia, Logic Activities and Mental Calculation, Puzzles, Geometric Curiosities, Magic Tricks, among others, designed to challenge students to use the underlying logical-mathematical reasoning to any ordinary and everyday activity. We will give specific and concrete examples of some of the activities developed and, also, reproduce of the general stimulating feedback the Project receives from the enrolled “actors” (teachers, students and their relatives, institutions, among others). We feel that this Project has become a small “bridge” between the pre-university schools and Higher Education Institutions (HEI), in trying to shorten the “gap” between the institutions of different levels of education and bring them to work together.

A Novel Autosomal Recessive GJA1 Missense Mutation Linked to Craniometaphyseal Dysplasia

Craniometaphyseal dysplasia (CMD) is a rare sclerosing skeletal disorder with progressive hyperostosis of craniofacial bones. CMD can be inherited in an autosomal dominant (AD) trait or occur after de novo mutations in the pyrophosphate transporter ANKH. Although the autosomal recessive (AR)form of CMD had been mapped to 6q21-22 the mutation has been elusive. In this study, we performed whole-exome sequencing for one subject with AR CMD and identified a novel missense mutation (c.716G>A, p.Arg239Gln) in the C-terminus of the gap junction protein alpha-1 (GJA1) coding for connexin 43 (Cx43). We confirmed this mutation in 6 individuals from 3 additional families. The homozygous mutation cosegregated only with affected family members. Connexin 43 is a major component of gap junctions in osteoblasts, osteocytes, osteoclasts and chondrocytes. Gap junctions are responsible for the diffusion of low molecular weight molecules between cells. Mutations in Cx43 cause several dominant and recessive disorders involving developmental abnormalities of bone such as dominant and recessive oculodentodigital dysplasia (ODDD; MIM #164200, 257850) and isolated syndactyly type III (MIM #186100), the characteristic digital anomaly in ODDD. However, characteristic ocular and dental features of ODDD as well as syndactyly are absent in patients with the recessive Arg239Gln Cx43 mutation. Bone remodeling mechanisms disrupted by this novel Cx43 mutation remain to be elucidated.

Continente Choose&Drive

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

Needs assessment of people with severe mental illnesses and their families in Azerbaijan

RESUMO: Os indivíduos com doença mental grave, assim como os seus familiares, podem ser caracterizados como uma população em que ocorre uma combinação complexa de necessidades médicas e psicossociais, nomeadamente a nível do diagnóstico e do acesso aos serviços de saúde mental. A avaliação de necessidades pode fornecer informações importantes para o desenvolvimento de intervenções eficazes, tanto a nível da população como a nível individual. Este estudo teve como objetivo determinar as diferentes necessidades reportadas pelos pacientes com doença mental grave e seus familiares , assim como investigar as possíveis relações entre o estado de necessidades e as variáveis sócio-demográficas e clínicas. Simultaneamente, o estudo teve como objetivo avaliar a sobrecarga familiar e a satisfação dos utentes com os serviços de saúde mental. Foi elaborado um estudo transversal, realizado numa amostra de conveniência de cinquenta díades de paciente/membro da família, seguidos em regime de ambulatório no Centro Nacional de Saúde Mental. Foram utilizados como instrumentos de avaliação um questionário sociodemográfico, a Escala Breve de Avaliação Psiquiátrica (BPRS), o questionário de Avaliação de Necessidades de Camberwell (CAN), o Questionário de Avaliação do Envolvimento (IEQ) e a Escala de Verona de Satisfação com os Serviços (VSSS). As mais frequentes necessidades não-satisfeitas foram o ‘sofrimento psicológico’, as ‘atividades sociais’ e os ‘benefícios sociais’. O estudo mostrou uma sobrecarga significativa nas famílias que cuidam de pessoas com doença mental grave, que se correlacionou com as suas opiniões sobre as necessidades dos pacientes e teve um impacto negativo sobre o bem-estar psicológico. Os três mais importantes predictores de sofrimento psíquico em familiares foram o sexo, a situação laboral e a relação com o paciente. A avaliação da satisfação com os serviços revelou a existência de um hiato significativo entre os serviços prestados e os serviços desejados, reportados pelos pacientes e seus familiares. A maioria dos participantes do estudo desejavam ter um trabalho protegido, ou receber ajuda para encontrar emprego. Os resultados deste estudo poderão ser usados para fins de planeamento desenvolvimento e avaliação de serviços de saúde mental no Azerbeijão. Algumas recomendações sobre a melhoria dos serviços de saúde mental para pacientes com doença mental grave e suas famílias são feitas na secção final do trabalho.----------ABSTRACT: Patients suffering from severe mental illness, in addition to their family members, may be characterized as a population with a complex combination of medical and psychosocial needs, which are under-recognized and under-addressed by mental health services. At the same time, needs assessment provides important information necessary for developing effective interventions at both population and individual level. The study was aimed to determine various needs perceived by patients with SMI and their family members, as well as to find out possible relations between the needs and socio-demographic and clinical variables. Similarly the study was intended to evaluate family burden and users’ satisfaction with services. This was a cross-sectional study conducted on a convenience sample. Fifty dyads of a patient and family member applying for out-patient services to the National Mental Health Centre participated in the study. Sociodemographic questionnaire, Brief Psychiatric Rating Scale, Camberwell Assessment of Need, Involvement Evaluation Questionnaire, and Verona Service Satisfaction Scale were used as assessment tools. The most prominent unmet needs reported by people with SMI and their relatives were psychological distress, social activities and welfare benefits. The study showed significant burden in families caring for people with SMI, which correlated with their views about patients’ needs and had a negative impact on the psychological well-being. The three most important predictors of psychological distress in family members were gender, employment status and relationship to patient. Evaluation of satisfaction with services pointed out the gap between provided and desired services reported by patients and their relatives. Most of study participants wished to have sheltered work, or receive help in finding employment. The results of this study may be used for the purposes of mental health service planning, development and evaluation in our country. Some recommendations on improvement of mental health services for patients with SMI and their families have been made in the conclusion.

Analysis of temporal and spatial variations of forest. A case of study in notheastern Armenia

The forest has a crucial ecological role and the continuous forest loss can cause colossal effects on the environment. As Armenia is one of the low forest covered countries in the world, this problem is more critical. Continuous forest disturbances mainly caused by illegal logging started from the early 1990s had a huge damage on the forest ecosystem by decreasing the forest productivity and making more areas vulnerable to erosion. Another aspect of the Armenian forest is the lack of continuous monitoring and absence of accurate estimation of the level of cuts in some years. In order to have insight about the forest and the disturbances in the long period of time we used Landsat TM/ETM + images. Google Earth Engine JavaScript API was used, which is an online tool enabling the access and analysis of a great amount of satellite imagery. To overcome the data availability problem caused by the gap in the Landsat series in 1988- 1998, extensive cloud cover in the study area and the missing scan lines, we used pixel based compositing for the temporal window of leaf on vegetation (June-late September). Subsequently, pixel based linear regression analyses were performed. Vegetation indices derived from the 10 biannual composites for the years 1984-2014 were used for trend analysis. In order to derive the disturbances only in forests, forest cover layer was aggregated and the original composites were masked. It has been found, that around 23% of forests were disturbed during the study period.

Predicting market direction with hidden Markov models

This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models to predict market direction. The paper draws an analogy between financial markets and speech recognition, seeking inspiration from the latter to solve common issues in quantitative investing. Whereas previous works focus mostly on very complex modifications of the original hidden markov model algorithm, the current paper provides an innovative methodology by drawing inspiration from thoroughly tested, yet simple, speech recognition methodologies. By grouping returns into sequences, Hidden Markov Models can then predict market direction the same way they are used to identify phonemes in speech recognition. The model proves highly successful in identifying market direction but fails to consistently identify whether a trend is in place. All in all, the current paper seeks to bridge the gap between speech recognition and quantitative finance and, even though the model is not fully successful, several refinements are suggested and the room for improvement is significant.

Fostering e-participation sustainability through a BPM-driven semantic model

According to a recent Eurobarometer survey (2014), 68% of Europeans tend not to trust national governments. As the increasing alienation of citizens from politics endangers democracy and welfare, governments, practitioners and researchers look for innovative means to engage citizens in policy matters. One of the measures intended to overcome the so-called democratic deficit is the promotion of civic participation. Digital media proliferation offers a set of novel characteristics related to interactivity, ubiquitous connectivity, social networking and inclusiveness that enable new forms of societal-wide collaboration with a potential impact on leveraging participative democracy. Following this trend, e-Participation is an emerging research area that consists in the use of Information and Communication Technologies to mediate and transform the relations among citizens and governments towards increasing citizens’ participation in public decision-making. However, despite the widespread efforts to implement e-Participation through research programs, new technologies and projects, exhaustive studies on the achieved outcomes reveal that it has not yet been successfully incorporated in institutional politics. Given the problems underlying e-Participation implementation, the present research suggested that, rather than project-oriented efforts, the cornerstone for successfully implementing e-Participation in public institutions as a sustainable added-value activity is a systematic organisational planning, embodying the principles of open-governance and open-engagement. It further suggested that BPM, as a management discipline, can act as a catalyst to enable the desired transformations towards value creation throughout the policy-making cycle, including political, organisational and, ultimately, citizen value. Following these findings, the primary objective of this research was to provide an instrumental model to foster e-Participation sustainability across Government and Public Administration towards a participatory, inclusive, collaborative and deliberative democracy. The developed artefact, consisting in an e-Participation Organisational Semantic Model (ePOSM) underpinned by a BPM-steered approach, introduces this vision. This approach to e-Participation was modelled through a semi-formal lightweight ontology stack structured in four sub-ontologies, namely e-Participation Strategy, Organisational Units, Functions and Roles. The ePOSM facilitates e-Participation sustainability by: (1) Promoting a common and cross-functional understanding of the concepts underlying e-Participation implementation and of their articulation that bridges the gap between technical and non-technical users; (2) Providing an organisational model which allows a centralised and consistent roll-out of strategy-driven e-Participation initiatives, supported by operational units dedicated to the execution of transformation projects and participatory processes; (3) Providing a standardised organisational structure, goals, functions and roles related to e-Participation processes that enhances process-level interoperability among government agencies; (4) Providing a representation usable in software development for business processes’ automation, which allows advanced querying using a reasoner or inference engine to retrieve concrete and specific information about the e-Participation processes in place. An evaluation of the achieved outcomes, as well a comparative analysis with existent models, suggested that this innovative approach tackling the organisational planning dimension can constitute a stepping stone to harness e-Participation value.

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.

How different generations contact and search for brands on social media? Comparing gen X and Y

This research intends to examine if there were significant differences on the brand engagement and on the electronic word of mouth (e-WOM)1 referral intention through Facebook between Generation X and Generation Y (also called millennials). Also, this study intends to examine if there are differences in the motivations that drive these generations to interact with brands through Facebook. Results indicated that Generation Y members consumed more content on Facebook brands’ pages than Generation X. Also, they were more likely to have an e-WOM referral intention as well as being more driven by brand affiliation and opportunity seeking. Finally, currently employed individuals were found to contribute with more content than students. This study fills the gap in the literature by addressing how marketing professionals should market their brand and interact and engage with their customers, based on customers’ generational cohort.

Towards a knowledge society

Economies are moving towards competitive stadiums based on knowledge and innovation. The changing environment and the level of globalization demand important efforts in order to sustain competitive advantages. Portugal has experienced a remarkable evolution since its adhesion to the European Union in several fields: economic development, Research & Development (R&D) consolidation, health parameters and social cohesion. As other developed economies, Portugal started its journey towards a knowledge-based economy and has been consolidating an innovation system during the last 35 years. The following report aims to analyze the evolution of a system since its creation to its last transformation within a globalized context. Challenges such as the lack of maturity of the system, the economic crisis, the European paradox, and closing the gap with other European countries are addressed in the next chapters. Likewise, recommendations on these points are provided by the end of the report as potential solutions.

Industrial engineering and management curriculum profile: Developing a framework of competences

This paper presents a framework of competences developed for Industrial Engineering and Management that can be used as a tool for curriculum analysis and design, including the teaching and learning processes as well as the alignment of the curriculum with the professional profile. The framework was applied to the Industrial Engineering and Management program at University of Minho (UMinho), Portugal, and it provides an overview of the connection between IEM knowledge areas and the competences defined in its curriculum. The framework of competences was developed through a process of analysis using a combination of methods and sources for data collection. The framework was developed according to four main steps: 1) characterization of IEM knowledge areas; 2) definition of IEM competences; 3) survey; 4) application of the framework at the IEM curriculum. The findings showed that the framework is useful to build an integrated vision of the curriculum. The most visible aspect in the learning outcomes of IEM program is the lack of balance between technical and transversal competences. There was not almost any reference to the transversal competences and it is fundamentally concentrated on Project-Based Learning courses. The framework presented in this paper provides a contribution to the definition of IEM professional profile through a set of competences which need to be explored further. In addition, it may be a relevant tool for IEM curriculum analysis and a contribution for bridging the gap between universities and companies.

Task clustering on ETL systems – A pattern-oriented approach

Usually, data warehousing populating processes are data-oriented workflows composed by dozens of granular tasks that are responsible for the integration of data coming from different data sources. Specific subset of these tasks can be grouped on a collection together with their relationships in order to form higher- level constructs. Increasing task granularity allows for the generalization of processes, simplifying their views and providing methods to carry out expertise to new applications. Well-proven practices can be used to describe general solutions that use basic skeletons configured and instantiated according to a set of specific integration requirements. Patterns can be applied to ETL processes aiming to simplify not only a possible conceptual representation but also to reduce the gap that often exists between two design perspectives. In this paper, we demonstrate the feasibility and effectiveness of an ETL pattern-based approach using task clustering, analyzing a real world ETL scenario through the definitions of two commonly used clusters of tasks: a data lookup cluster and a data conciliation and integration cluster.

Gamification e game-based learning: uma abordagem lúdica à aprendizagem

Relatório de estágio de mestrado em Ensino de Informática