Simplified wind turbine models for wind energy integration into power systems

This paper analyses the boundaries of simplified wind turbine models used to represent the behavior of wind turbines in order to conduct power system stability studies. Based on experimental measurements, the response of recent simplified (also known as generic) wind turbine models that are currently being developed by the International Standard IEC 61400-27 is compared to complex detailed models elaborated by wind turbine manufacturers. This International Standard, whose Technical Committee was convened in October 2009, is focused on defining generic simulation models for both wind turbines (Part 1) and wind farms (Part 2). The results of this work provide an improved understanding of the usability of generic models for conducting power system simulations.

Indicadores de prognóstico em utentes com disfunção do ombro submetidos a uma intervenção terapêutica direcionada para a estabilidade dinâmica da escápulo-torácica

RESUMO: Introdução/ Objetivo: Segundo a revisão sistemática de Chester e colaboradores (2013b)apenas dois fatores de prognóstico demonstraram uma associação consistente com o resultado que foram a duração dos sintomas e a funcionalidade na avaliação inicial. O objetivo do estudo é identificar indicadores de bom e mau prognóstico em utentes com disfunção do complexo articular do ombro (DCAO), tendo por base, aspetos da avaliação inicial do utente e critérios de alta de abolição da dor, aumento da funcionalidade e da estabilidade dinâmica considerando uma intervenção terapêutica direcionada para o aumento da estabilidade dinâmica da escápulo-torácica. Metodologia: Efetuou-se um estudo de coorte clínico retrospetivo. Para tal, aplicou-se um protocolo de intervenção terapêutica e analisou-se os resultados. A amostra foi constituída por 82 indivíduos com DCAO [53 com síndrome do conflito subacromial (SCSA) e 29 com instabilidade da glenoumeral (IGU)], residentes nos distritos de Lisboa, Setúbal e Santarém com o intuito de iniciar tratamento de fisioterapia. A análise dos dados foi efetuada tendo em consideração dois procedimentos: análise univariada (através do método de Kaplan-Meier para cada CVP) e análise multifatorial (pela análise de regressão de Cox e regressão logística nos grupos de utentes com SCSA, IGU e DCAO). Resultados: O tempo mediano de continuação no tratamento em fisioterapia foi de 7 semanas para os utentes com SCSA e 6 semanas para utentes com IGU. Segundo o teste de Logrank, na análise univariada, existem sete e oito covariáveis preditoras (CVP) com associação estatisticamente significativa (p<0,05) para o subgrupo SCSA e IGU, respectivamente. De acordo com estes resultados, a primeira parte da DASH e a SPADI são as únicas CVP com associação comuns às duas disfunções. Pela análise multifatorial e, em congruência com o teste de Wald, nenhuma das CVP contribui estatisticamente para o modelo preditivo de continuidade do tratamento de fisioterapia em qualquer um dos três modelos estudados: subgrupo SCSA, subgrupo IGU e utentes com DCAO. Conclusão: Por uma análise univariada verificou-se que existem CVP associadas à alta dos tratamentos em fisioterapia e estas não são as mesmas em ambas as DCAO. Contudo, a magnitude do efeito de cada CVP nos modelos multifatoriais definidos para os grupos de utentes com SCSA, IGU e DCAO não demonstraram valor estatisticamente significativo pelo que não foi possível determinar modelos de prognóstico em utentes com DCAO.-------------ABSTRACT: Background/ Purpose: According with the systematic review from Chester and collaborators (2013b) just two prognostic factors demonstrated a consistent association with the outcome: the duration of symptoms and functionality in the initial assessment. The purpose of the study is to identify indicators of good and poor prognosis in patients with shoulder’s dysfunctions, based on aspects of the initial assessment and discharge criteria of absence of pain, increased functionality and dynamic stability considering a therapeutic intervention used to increase the dynamic stability of scapulo-thoracic. Methodology: It was conducted a retrospective study of clinical cohort. For this purpose it was applied a protocol with therapeutic intervention and the results were analyzed. The sample consisted of 82 individuals with shoulder’s dysfunction (53 with subacromial impingement (SIMP) and 29 with shoulder instability (SINS) residing in the districts of Lisbon, Setúbal and Santarém in order to start physiotherapy. Data analysis was performed taking into account two procedures: univariate analysis [using the Kaplan-Meier method for each co-variant predictor variable (CVP)] and multifactorial analysis [analysis by Cox regression and logistic regression on groups of patients with SIMP, SINS and shoulder’s dysfunction (SD)]. Results: The median time of follow-up treatment at physical therapy was 7 weeks for patients with SIMP and 6 weeks for patients with SINS. According to the Logrank test in the univariate analysis, there are seven and eight CVP with a statistically significant association (p<0.05) for the patients with SIMP and SINS, respectively. According to these results, the first part of the DASH and SPADI are the only CVP common to both disorders association. By multifatorial analyses, and in agreement with the Wald test, none of the CVP contributes statistically to the predictive model of continuity of physiotherapy treatment in any of the three studied models: patients with SIMP, patients with SINS and patients with SD. Conclusion: In an univariate analysis, it was verified that there are CVP associated with discharge from treatments of physical therapy and these are not the same in both SD. However, the magnitude of effect of each CVP in multifactorial models for defined patients groups with SIMP, SINS and SD showed no statistically significant. Therefore, it was not possible to determine prognostic models for patients with SD.

Development of 3D in vitro models for prediction of hepatic metabolism and toxicity

The development of human cell models that recapitulate hepatic functionality allows the study of metabolic pathways involved in toxicity and disease. The increased biological relevance, cost-effectiveness and high-throughput of cell models can contribute to increase the efficiency of drug development in the pharmaceutical industry. Recapitulation of liver functionality in vitro requires the development of advanced culture strategies to mimic in vivo complexity, such as 3D culture, co-cultures or biomaterials. However, complex 3D models are typically associated with poor robustness, limited scalability and compatibility with screening methods. In this work, several strategies were used to develop highly functional and reproducible spheroid-based in vitro models of human hepatocytes and HepaRG cells using stirred culture systems. In chapter 2, the isolation of human hepatocytes from resected liver tissue was implemented and a liver tissue perfusion method was optimized towards the improvement of hepatocyte isolation and aggregation efficiency, resulting in an isolation protocol compatible with 3D culture. In chapter 3, human hepatocytes were co-cultivated with mesenchymal stem cells (MSC) and the phenotype of both cell types was characterized, showing that MSC acquire a supportive stromal function and hepatocytes retain differentiated hepatic functions, stability of drug metabolism enzymes and higher viability in co-cultures. In chapter 4, a 3D alginate microencapsulation strategy for the differentiation of HepaRG cells was evaluated and compared with the standard 2D DMSO-dependent differentiation, yielding higher differentiation efficiency, comparable levels of drug metabolism activity and significantly improved biosynthetic activity. The work developed in this thesis provides novel strategies for 3D culture of human hepatic cell models, which are reproducible, scalable and compatible with screening platforms. The phenotypic and functional characterization of the in vitro systems performed contributes to the state of the art of human hepatic cell models and can be applied to the improvement of pre-clinical drug development efficiency of the process, model disease and ultimately, development of cell-based therapeutic strategies for liver failure.

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.

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.

Flood resilient housing recovery models: a theoretical case study in Maldives

Natural disasters are events that cause general and widespread destruction of the built environment and are becoming increasingly recurrent. They are a product of vulnerability and community exposure to natural hazards, generating a multitude of social, economic and cultural issues of which the loss of housing and the subsequent need for shelter is one of its major consequences. Nowadays, numerous factors contribute to increased vulnerability and exposure to natural disasters such as climate change with its impacts felt across the globe and which is currently seen as a worldwide threat to the built environment. The abandonment of disaster-affected areas can also push populations to regions where natural hazards are felt more severely. Although several actors in the post-disaster scenario provide for shelter needs and recovery programs, housing is often inadequate and unable to resist the effects of future natural hazards. Resilient housing is commonly not addressed due to the urgency in sheltering affected populations. However, by neglecting risks of exposure in construction, houses become vulnerable and are likely to be damaged or destroyed in future natural hazard events. That being said it becomes fundamental to include resilience criteria, when it comes to housing, which in turn will allow new houses to better withstand the passage of time and natural disasters, in the safest way possible. This master thesis is intended to provide guiding principles to take towards housing recovery after natural disasters, particularly in the form of flood resilient construction, considering floods are responsible for the largest number of natural disasters. To this purpose, the main structures that house affected populations were identified and analyzed in depth. After assessing the risks and damages that flood events can cause in housing, a methodology was proposed for flood resilient housing models, in which there were identified key criteria that housing should meet. The same methodology is based in the US Federal Emergency Management Agency requirements and recommendations in accordance to specific flood zones. Finally, a case study in Maldives – one of the most vulnerable countries to sea level rise resulting from climate change – has been analyzed in light of housing recovery in a post-disaster induced scenario. This analysis was carried out by using the proposed methodology with the intent of assessing the resilience of the newly built housing to floods in the aftermath of the 2004 Indian Ocean Tsunami.

Archaeological Remains Accounting for the Presence and Exploitation of the North Atlantic Right Whale Eubalaena glacialis on the Portuguese Coast (Peniche, West Iberia), 16th to 17th Century

The former occurrence of the North Atlantic right whale Eubalaena glacialis on the Portuguese coast may be inferred from the historical range of that species in Europe and in NW Africa. It is generally accepted that it was the main prey of coastal whaling in the Middle Ages and in the pre-modern period, but this assumption still needs firming up based on biological and archaeological evidence. We describe the skeletal remains of right whales excavated at Peniche in 2001-2002, in association with archaeological artefacts. The whale bones were covered by sandy sediments on the old seashore and they have been tentatively dated around the 16th to 17th centuries. This study contributes material evidence to the former occurrence of E. glacialis in Portugal (West Iberia). Some whale bones show unequivocal man-made scars. These are associated to wounds from instruments with a sharp-cutting blade. This evidence for past human interaction may suggest that whaling for that species was active at Peniche around the early 17th century.

Predictive factors of post-discharge surgical site infections among patients from a teaching hospital

Introduction Surgical site infections (SSIs) often manifest after patients are discharged and are missed by hospital-based surveillance. Methods We conducted a case-reference study nested in a prospective cohort of patients from six surgical specialties in a teaching hospital. The factors related to SSI were compared for cases identified during the hospital stay and after discharge. Results Among 3,427 patients, 222 (6.4%) acquired an SSI. In 138 of these patients, the onset of the SSI occurred after discharge. Neurological surgery and the use of steroids were independently associated with a greater likelihood of SSI diagnosis during the hospital stay. Conclusions Our results support the idea of a specialty-based strategy for post-discharge SSI surveillance.

The future of airline business models:

This research is titled “The Future of Airline Business Models: Which Will Win?” and it is part of the requirements for the award of a Masters in Management from NOVA BSE and another from Luiss Guido Carlo University. The purpose is to elaborate a complete market analysis of the European Air Transportation Industry in order to predict which Airlines, strategies and business models may be successful in the next years. First, an extensive literature review of the business model concept has been done. Then, a detailed overview of the main European Airlines and the strategies that they have been implementing so far has been developed. Finally, the research is illustrated with three case studies

Evaluation of the predictive indices for candidemia in an adult intensive care unit

INTRODUCTION: To evaluate predictive indices for candidemia in an adult intensive care unit (ICU) and to propose a new index. METHODS: A prospective cohort study was conducted between January 2011 and December 2012. This study was performed in an ICU in a tertiary care hospital at a public university and included 114 patients staying in the adult ICU for at least 48 hours. The association of patient variables with candidemia was analyzed. RESULTS: There were 18 (15.8%) proven cases of candidemia and 96 (84.2%) cases without candidemia. Univariate analysis revealed the following risk factors: parenteral nutrition, severe sepsis, surgical procedure, dialysis, pancreatitis, acute renal failure, and an APACHE II score higher than 20. For the Candida score index, the odds ratio was 8.50 (95% CI, 2.57 to 28.09); the sensitivity, specificity, positive predictive value, and negative predictive value were 0.78, 0.71, 0.33, and 0.94, respectively. With respect to the clinical predictor index, the odds ratio was 9.45 (95%CI, 2.06 to 43.39); the sensitivity, specificity, positive predictive value, and negative predictive value were 0.89, 0.54, 0.27, and 0.96, respectively. The proposed candidemia index cutoff was 8.5; the sensitivity, specificity, positive predictive value, and negative predictive value were 0.77, 0.70, 0.33, and 0.94, respectively. CONCLUSIONS: The Candida score and clinical predictor index excluded candidemia satisfactorily. The effectiveness of the candidemia index was comparable to that of the Candida score.

Predictive value of the ankle-brachial index in the evaluation of intermittent claudication

The purpose of this study was to determine whether the ankle-brachial index (ABI) could be used to predict the prognosis for a patient with intermittent claudication (IC). We studied 611 patients prospectively during 28 months of follow-up. We analyzed the predictive power of using various levels of ABI - 0.30 to 0.70 at 0.05 increments - in terms of the measure's specificity (association with a favorable outcome after exercise rehabilitation therapy) and sensitivity (association with a poor outcome after exercise rehabilitation therapy). We found that using an ABI of 0.30 as a cut-off value produced the lowest margin of error overall, but the predictive power was still low with respect to identifying the patients with a poor prognosis after non-aggressive therapeutic treatment. Further study is needed to perhaps identify a second factor that could increase the sensitivity of the test.

Building 3D City Models: Testing and Comparing Laser Scanning and Low-Cost UAV Data Using FOSS Technologies

Contém resumo

Damage propagation in composite Materials meso-mechanical models

Composite materials have a complex behavior, which is difficult to predict under different types of loads. In the course of this dissertation a methodology was developed to predict failure and damage propagation of composite material specimens. This methodology uses finite element numerical models created with Ansys and Matlab softwares. The methodology is able to perform an incremental-iterative analysis, which increases, gradually, the load applied to the specimen. Several structural failure phenomena are considered, such as fiber and/or matrix failure, delamination or shear plasticity. Failure criteria based on element stresses were implemented and a procedure to reduce the stiffness of the failed elements was prepared. The material used in this dissertation consist of a spread tow carbon fabric with a 0°/90° arrangement and the main numerical model analyzed is a 26-plies specimen under compression loads. Numerical results were compared with the results of specimens tested experimentally, whose mechanical properties are unknown, knowing only the geometry of the specimen. The material properties of the numerical model were adjusted in the course of this dissertation, in order to find the lowest difference between the numerical and experimental results with an error lower than 5% (it was performed the numerical model identification based on the experimental results).

Understanding multi-asset factor models: Factor exposure interpretation

Field lab: Business project

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.