Epidemic store for massive scale systems

The MAP-i doctoral program of the Universities of Minho, Aveiro and Porto

Column-based databases: estudo exploratório no âmbito das bases de dados NoSQL

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Document-based databases: estudo comparativo no âmbito das bases de dados NoSql

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Concise server-wide causality management for eventually consistent data stores

Large scale distributed data stores rely on optimistic replication to scale and remain highly available in the face of net work partitions. Managing data without coordination results in eventually consistent data stores that allow for concurrent data updates. These systems often use anti-entropy mechanisms (like Merkle Trees) to detect and repair divergent data versions across nodes. However, in practice hash-based data structures are too expensive for large amounts of data and create too many false conflicts. Another aspect of eventual consistency is detecting write conflicts. Logical clocks are often used to track data causality, necessary to detect causally concurrent writes on the same key. However, there is a nonnegligible metadata overhead per key, which also keeps growing with time, proportional with the node churn rate. Another challenge is deleting keys while respecting causality: while the values can be deleted, perkey metadata cannot be permanently removed without coordination. Weintroduceanewcausalitymanagementframeworkforeventuallyconsistentdatastores,thatleveragesnodelogicalclocks(BitmappedVersion Vectors) and a new key logical clock (Dotted Causal Container) to provides advantages on multiple fronts: 1) a new efficient and lightweight anti-entropy mechanism; 2) greatly reduced per-key causality metadata size; 3) accurate key deletes without permanent metadata.

HOXA9 as a key regulator in glioma initiation, aggressiveness and response to therapy

Tese de Doutoramento em Ciências da Saúde

Using customer lifetime value to improve the prediction of bank deposit subscription in telemarketing campaigns

Customer lifetime value (LTV) enables using client characteristics, such as recency, frequency and monetary (RFM) value, to describe the value of a client through time in terms of profitability. We present the concept of LTV applied to telemarketing for improving the return-on-investment, using a recent (from 2008 to 2013) and real case study of bank campaigns to sell long- term deposits. The goal was to benefit from past contacts history to extract additional knowledge. A total of twelve LTV input variables were tested, un- der a forward selection method and using a realistic rolling windows scheme, highlighting the validity of five new LTV features. The results achieved by our LTV data-driven approach using neural networks allowed an improvement up to 4 pp in the Lift cumulative curve for targeting the deposit subscribers when compared with a baseline model (with no history data). Explanatory knowledge was also extracted from the proposed model, revealing two highly relevant LTV features, the last result of the previous campaign to sell the same product and the frequency of past client successes. The obtained results are particularly valuable for contact center companies, which can improve pre- dictive performance without even having to ask for more information to the companies they serve.

A relational algebra approach to ETL modeling

The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and Porto

Desenvolvimento de estruturas fibrosas com comportamento auxético

Tese de Doutoramento Engenharia Têxtil

Biochemical and physical surface functionalization of polycaprolactone as a key mediator of osteogenic differentiation and vascularized tissue morphogenesis

Tese de Doutoramento em Engenharia de Tecidos, Medicina Regenerativa e Células Estaminais.

Re-Design of ribbon for new applications

O conceito de qualidade de vida surge pela primeira vez em 1920, através do economista inglês Arthur Cecil Pigou, que utiliza este termo para descrever o impacto governamental sobre a vida das pessoas mais desfavorecidas. Com a instalação de uma era industrializada e com o fim da 2º Guerra Mundial, a sociedade mudou de paradigma e iniciou uma procura incessante de formas para melhorar a sua qualidade de vida. Este conceito desenvolve-se juntamente com o desenvolvimento do conceito de educação, saúde, habitação, transporte, trabalho e lazer, bem como indicadores do aumento da esperança de vida, a diminuição da mortalidade infantil e dos níveis de poluição. O avanço da tecnologia teve um papel fundamental para a evolução desses conceitos, bem como o Design na procura de soluções para aplicação dessas mesmas tecnologias. No caso concreto da indústria tèxtil, a tendência é o desenvolvimento de têxteis inteligentes envolvendo a engenharia electrónica no seu processo de conceptualização e de fabrico. A chamada tecnologia wearable abre novos horizontes para a criação de soluções inovadoras, abrindo novos nichos de mercado com elevado valor acrescentado. Existem atualmente vários produtos no mercado cuja funcionalidade e utilidade lhes conferiu um estatuto imutável ao longo dos anos, onde a evolução não avançou na tendência atual. Esse é o caso dos tecidos estreitos, cuja funcionalidade poderá adquirir novas capacidades e ser utilizada em diferentes componentes têxteis nas mais variadas áreas. Essas capacidades poderão ser acrescentadas pela incorporação de materiais com luminosidade (Led’s e L-Wire) nas suas estruturas. Neste estudo realizado o design de produtos com novas funcionalidades, adaptando as tecnologias até agora desenvolvidas em novas soluções e/ou novas recriações de produto.

Extreme value Birnbaum-Saunders regression models applied to environmental data

Extreme value models are widely used in different areas. The Birnbaum–Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum–Saunders regression models, which includes model formulation, estimation, inference and checking. We further conduct a simulation study for evaluating its performance. A statistical analysis with real-world extreme value environmental data using the methodology is provided as illustration.

A mensuração do Capital Humano nas organizações: estudo de caso da empresa Tuacar, SA

Relatório de estágio de mestrado em Contabilidade

Aplicação da metodologia WID numa indústria de calçado

Dissertação de mestrado em Engenharia Industrial

Sustentabilidade no Design: uma abordagem aos resíduos limpos das indústrias do calçado

Dissertação de mestrado em Design e Marketing

Exploring female mice interstrain differences relevant for models of depression

Depression is an extremely heterogeneous disorder. Diverse molecular mechanisms have been suggested to underlie its etiology. To understand the molecular mechanisms responsible for this complex disorder, researchers have been using animal models extensively, namely mice from various genetic backgrounds and harboring distinct genetic modifications. The use of numerous mouse models has contributed to enrich our knowledge on depression. However, accumulating data also revealed that the intrinsic characteristics of each mouse strain might influence the experimental outcomes, which may justify some conflicting evidence reported in the literature. To further understand the impact of the genetic background, we performed a multimodal comparative study encompassing the most relevant parameters commonly addressed in depression, in three of the most widely used mouse strains: Balb/c, C57BL/6, and CD-1. Moreover, female mice were selected for this study taken into account the higher prevalence of depression in women and the fewer animal studies using this gender. Our results show that Balb/c mice have a more pronounced anxious-like behavior than CD-1 and C57BL/6 mice, whereas C57BL/6 animals present the strongest depressive-like trait. Furthermore, C57BL/6 mice display the highest rate of proliferating cells and brain-derived neurotrophic factor (Bdnf) expression levels in the hippocampus, while hippocampal dentate granular neurons of Balb/c mice show smaller dendritic lengths and fewer ramifications. Of notice, the expression levels of inducible nitric oxide synthase (iNos) predict 39.5% of the depressive-like behavior index, which suggests a key role of hippocampal iNOS in depression. Overall, this study reveals important interstrain differences in several behavioral dimensions and molecular and cellular parameters that should be considered when preparing and analyzing experiments addressing depression using mouse models. It further contributes to the literature by revealing the predictive value of hippocampal iNos expression levels in depressive-like behavior, irrespectively of the mouse strain.