Abstract
Measuring and forecasting changes in coastal and deep-water ecosystems and climates requires sustained long-term measurements from marine observation systems. One of the key considerations in analyzing data from marine observatories is quality assurance (QA). The data acquired by these infrastructures accumulates into Giga and Terabytes per year, necessitating an accurate automatic identification of false samples. A particular challenge in the QA of oceanographic datasets is the avoidance of disqualification of data samples that, while appearing as outliers, actually represent real short-term phenomena, that are of importance. In this paper, we present a novel cross-sensor QA approach that validates the disqualification decision of a data sample from an examined dataset by comparing it to samples from related datasets. This group of related datasets is chosen so as to reflect upon the same oceanographic phenomena that enable some prediction of the examined dataset. In our approach, a disqualification is validated if the detected anomaly is present only in the examined dataset, but not in its related datasets. Results for a surface water temperature dataset recorded by our Texas A&M-Haifa Eastern Mediterranean Marine Observatory (THEMO)-over a period of 7 months, show an improved trade-off between accurate and false disqualification rates when compared to two standard benchmark schemes.

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Abstract
Ocean exploration and monitoring with autonomous platforms can provide researchers and decision makers with valuable data, trends and insights into the largest ecosystem on Earth. Regardless of the recognition of the importance of such platforms in this scenario, their design and development remains an open challenge. In particular, energy efficiency, control and robustness are major concerns with implications in terms of autonomy and sustainability. Wingsails allow autonomous boats to navigate with increased autonomy, due to lower power consumption, and greater robustness, due to simpler control. Within the scope of a project that addresses the design, development and deployment of a rigid wing autonomous sailboat to perform long term missions in the ocean, this paper summarises the general principles for airfoil selection and wingsail design in robotic sailing, and are given some insights on how these aspects influence the autonomous sailboat being developed by the authors.

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AbstractIntroductionIrritable Bowel Syndrome (IBS) is a functional and multifactorial gastrointestinal disorder characterized by pain, abdominal distention and motility changes, currently diagnosed based on the Rome IV criteria. The efficacy of classic pharmacological, psychological and dietary treatments for this condition are generally low. The Fermentable Oligosaccharides, Disaccharides, Monosaccharides and Polyols (FODMAP) are short chain carbohydrates poorly absorbed at the intestinal level, fermentable by the microbiota and presumably involved in IBS-associated symptomatology.AimsTo evaluate the efficacy, feasibility and acceptability of a FODMAP-restricted feeding approach in the relief of symptomatology and in the improvement of the quality of life of patients with IBS, determining the reintroduction of the FODMAP food subgroup(s) involved in the symptom exacerbation.Materials and MethodsAfter assessing the existence of initial emotional disorders through the Hospital Anxiety and Depression Scale (HADS) and eating habits, through dietary history, patients diagnosed with IBS were put on a FODMAP-restricted diet for 6 weeks. During this period, the weekly evolution of symptom frequency was assessed. At the end, tests were undertaken to discover the global evolution of the symptoms through the Irritable Bowel Syndrome - Global Assessment Scale (IBS-GAI), the severity of symptomatology through the Irritable Bowel Syndrome - Severity Scoring System (IBS-SSS) and quality of life through Irritable Bowel Syndrome - Quality of Life (IBS-QoL).Subsequently, participants tested their tolerance to various FODMAP subtypes with weekly and isolated reintroduction of these in their diet.ResultsIn the 36 participants, with a mean age of 38.8 years, there was a reduction in the total consumption of FODMAP from 22.1 g to 2.1 g (p < 0.001). A moderate or substantial improvement in the IBS-GAI was observed in 88.9%. An average reduction of 235 points in the IBS-SSS (p < 0.001) and a mean increase of 28.7 in the IBS-QoL (p < 0.001) was achieved. The initial anxiety and depression levels were not associated with IBS-SSS and presented an inverse association with the IBS-QoL. There was significant improvement in all symptomatology during the 1st week of total FODMAP restriction, except for constipation with an amelioration observed at the 6st week. There was a frequency of intolerance ranging from 30.8% for fructans to 80.8% for lactose with the reintroduction of the FODMAP subtypes.ConclusionA FODMAP-restricted diet, implemented over a period of 6 weeks, is effective in reducing the severity and frequency of GI symptoms and improving the quality of life of portuguese patients with IBS.

Abstract
Diabetes type I is a chronic disease that requires strict supervision. MyDiabetes is a utility application for diabetic users. This application served as basis to develop a logical unit, composed of logical rules, translated from medical protocols and guidelines, to advise the user. The data in the application is a source of knowledge about the user's health state and diabetes intrinsic characteristics. An existing concern is the weak user adherence and consequential data absence. The implemented solutions were gamification and an interface rework. As later confirmed through a survey, users feel captivated by appealing interfaces, achievements and medals. In a near future, we will resume our work with the S. Joao's hospital, with a new trial and volunteers. User testing will be used to validate the gamification techniques.

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Purpose The purpose of this paper is to present the Moore-Penrose pseudoinverse (PI) modeling and compare with artificial neural network (ANN) modeling for switched reluctance machine (SRM) performance. Design/methodology/approach In a design of an SRM, there are a number of parameters that are chosen empirically inside a certain interval, therefore, to find an optimal geometry it is necessary to define a good model for SRM. The proposed modeling uses the Moore-Penrose PI for the resolution of linear systems and finite element simulation data. To attest to the quality of PI modeling, a model using ANN is established and the two models are compared with the values determined by simulations of finite elements. Findings The proposed PI model showed better accuracy, generalization capacity and lower computational cost than the ANN model. Originality/value The proposed approach can be applied to any problem as long as experimental/computational results can be obtained and will deliver the best approximation model to the available data set.