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Alzheimer's disease (AD) is one of the most prevalent neurodegenerative diseases and it is strongly associated with age. There are four AD stages: mild cognitive impairment (MCI), mild, moderate (ADM) and advanced (ADA). This work aims at developing a new tool capable of distinguishing the different stages of AD at scalp level. Features such as the conventional frequencies relative power of the power spectrum wavelet packet transform have been extracted from the electroencephalogram signals in order to feed four classifiers: random forest decision trees, linear and quadratic support-vector-machines and linear discriminant analysis. The obtained results were analyzed through topographic maps and enabled the distinguish between binary groups with the following overall accuracies: 85.5% (C-MCI); 88.2% (C-ADM); 91.4% (C-ADA); 89.7% (MCI-ADM); 82.4% (MCI-ADA) and 81.3% (ADM-ADA). The applied method was able to detect major differences in scalp areas above the frontal and temporal lobes of the brain as AD progresses.

Cold content (CC) is an internal energy state within a snowpack and is defined by the energy deficit required to attain isothermal snowmelt temperature (0 °C). For any snowpack, fulfilling the cold content deficit is a pre-requisite before the onset of the snowmelt. Cold content for a given snowpack thus plays a critical role because it affects both the timing and the rate of snowmelt. Estimating the cold content is a labour-intensive task as it requires extracting in-situ snow temperature and density. Hence, few studies have focused on characterizing this snowpack variable. This study describes the multilayer cold content of a snowpack and its variability across four sites with contrasting canopy structures within a coniferous boreal forest in southern Québec, Canada, throughout winter 2017–18. The analysis was divided into two steps. In the first step, the observed CC data from weekly snowpits for 60 % of the snow cover period were examined. During the second step, a reconstructed time series of CC was produced and analyzed to highlight the high-resolution temporal variability of CC for the full snow cover period. To accomplish this, the Canadian Land Surface Scheme (CLASS; featuring a single-layer snow model) was first implemented to obtain simulations of the average snow density at each of the four sites. Next, an empirical procedure was used to produce realistic density profiles, which, when combined with in situ continuous snow temperature measurements from an automatic profiling station, provides a time series of CC estimates at half-hour intervals for the entire winter. At the four sites, snow persisted on the ground for 218 days, with melt events occurring on 42 of those days. Based on snowpit observations, the largest mean CC (−2.62 MJ m−2) was observed at the site with the thickest snow cover. The maximum difference in mean CC between the four study sites was −0.47 MJ m−2, representing a site-to-site variability of 20 %. Before analyzing the reconstructed CC time series, a comparison with snowpit data confirmed that CLASS yielded reasonable estimates of the snow water equivalent (SWE) (R2 = 0.64 and percent bias (Pbias) = −17.1 %), bulk snow density (R2 = 0.71 and Pbias = 1.6 %), and bulk cold content (R2 = 0.90 and Pbias = −2.0 %). A snow density profile derived by utilizing an empirical formulation also provided reasonable estimates of cold content (R2 = 0.42 and Pbias = 5.17 %). Thanks to these encouraging results, the reconstructed and continuous CC series could be analyzed at the four sites, revealing the impact of rain-on-snow and cold air pooling episodes on the variation of CC. The continuous multilayer cold content time series also provided us with information about the effect of stand structure, local topography, and meteorological conditions on cold content variability. Additionally, a weak relationship between canopy structure and CC was identified.

Achieving a balanced healthcare workforce requires health planners to adjust the supply of health human resources (HHR). Mathematical programming models have been widely used to assist such planning, but the way uncertainty is usually considered in these models entails methodological and practical issues and often disregards radical yet plausible changes to the future. This study proposes a new socio-technical methodology to factor in uncertainty over the future within mathematical programming modelling. The methodological approach makes use of foresight and scenario planning concepts to build tailor-made scenarios and scenario fit input parameters, which are then used within mathematical programming models. Health stakeholders and experts are engaged in the scenario building process. Causal map modelling and morphological analysis are adopted to digest stakeholders and experts’ information about the future and give origin to contrasting and meaningful scenarios describing plausible future. These scenarios are then adjusted and validated by stakeholders and experts, who then elicit their best quantitative estimates for coherent combinations of input parameters for the mathematical programming model under each scenario. These sets of parameters for each scenario are then fed to the mathematical programming model to obtain optimal solutions that can be interpreted in light of the meaning of the scenario. The proposed methodology has been applied to a case study involving HHR planning in Portugal, but its scope far extends HHR planning, being especially suited for addressing strategic and policy planning problems that are sensitive to input parameters. info:eu-repo/semantics/acceptedVersion

Output-only methods are widely used to characterize the dynamic behavior of very diverse structures. However, their application to floating structures may be limited due to their strong nonlinear behavior. Therefore, since there is very little experience on the application of these experimental tools to these very peculiar structures, it is very important to develop studies, either based on numerical simulations or on real experimental data, to better understand their potential and limitations. In an initial phase, the use of numerical simulations permits a better control of all the involved variables. In this work, the Covariance-driven Stochastic Subspace Identification (SSI-COV) algorithm is applied to numerically simulated data of two different solutions to Floating Offshore Wind Turbines (FOWT) and for its capability of tracking the rigid body motion modal properties and susceptibility to different modeling restrictions and environmental conditions tested. The feasibility of applying the methods in an automated fashion in the processing of a large number of datasets is also evaluated. While the structure natural frequencies were consistently obtained from all the simulations, some difficulties were observed in the estimation of the mode shape components in the most changeling scenarios. The estimated modal damping coefficients were in good agreement with the expected results. From all the results, it can be concluded that output-only methods are capable of characterizing the dynamic behavior of a floating structure, even in the context of continuous dynamic monitoring using automated tracking of the modal properties, and should now be tested under uncontrolled environmental loads.

Objective: This study aims to distinguish, at early stages, patients with Alzheimer’s disease (AD), patients with Parkinson’s disease (PD) and healthy control (CTL) subjects using a nonlinear multiband electroencephalography (EEG)-based procedure. Method: An EEG nonlinear multiband analysis was performed in order to extract features for feeding several classifiers (such as decision trees, support vector machines, K-nearestneighbours, and logistic regression) within a leave-one-out cross-validation procedure. Results: The comparison between (a) PD versus AD groups reached classification accuracies of 100% on at least one channel of δ, θ, α, and β bands; (b) AD versus CTL groups provided accuracies of 100% on at least one channel in δ band; (c) PD versus CTL groups reached 100% of accuracy on at least one channel of γ and δ bands; and (d) the combination of PD and AD groups versus CTL group provided an accuracy of 90.6% in the θ band. Conclusions: Our findings suggest that patients may benefit from careful monitoring for early signs of change in the EEG pattern in both AD and PD.

International audience; The current requirements for composite cylinders are still based on an arbitrary approach derived from the behaviour of metal structures, that the designed burst pressure should be at least 2.5 times the maximum in-service pressure [1]. This could lead to an over-designed composite cylinder for which the weight saving would be less than optimum. Moreover, predicting the lifetime of composite cylinders is a challenging task due to their anisotropic characteristics. A federal research institute in Germany (BAM) has proposed a minimum load-cycle requirement that mitigates this issue by using a Monte-Carlo analysis of the burst test results [2-3]. To enrich this study, more experiments are required however they are normally limited by the necessity of long duration testing times (loading rate and number of cylinders) and the design (stacking sequence of the composite layer). A multi-scale model incorporating the micromechanical behaviour of composite structures has been developed at Mines ParisTech. The model has shown similar behaviour to that of composite cylinders under different loading rates [4]. This indicates that the model could assist the Monte-Carlo analysis study. An evaluation of the multi-scale model therefore has been carried out to determine its limitations in predicting lifetimes of composite cylinders. The evaluation starts with the comparison of burst pressures with type IV composite cylinders under different loading rates. A μCT-Scan of a type IV cylinder has been carried out at the University of Southampton. The produced images were analysed using the Fast-Fourier Transform (FFT) technique to determine the configuration of the composite layers, which is required by the model. Finally, the time dependent effect studied, by using the multi scale model, has been described. In the long-term, this study can be used to conduct a parametric study for creating more efficient design of type IV cylinders.

O procedimento tradicional de controlo da estabilidade microbiológica no vinho consiste na adição de dióxido de enxofre (SO2), que atua como agente antimicrobiano e também antioxidante. A procura de métodos alternativos de controlo microbiológico é importante e necessária, dado que o dióxido de enxofre é um potencial alérgeno e os consumidores procuram cada vez mais produtos saudáveis e livres de conservantes. A radiação ultravioleta tem sido estudada como uma tecnologia inovadora que pode auxiliar na redução do teor de dioxido de enxofre em enologia. O objectivo deste trabalho foi optimizar as condições do processo, face aos resultados já obtidos anteriormente, e avaliar a eficiência na estabilização microbiologica, e a sua influência nos parâmetros fisico-quimicos, na composição fenólica, e nas caracteristicas sensoriais. Assim, o vinho tinto com teor muito baixo em SO2 foi submetido a radiação UV-C com duas doses diferentes, 424J/L e 778J/L, e procedeu-se ainda à preparação de um controlo, a que foi adicionado 30 mg/L de dióxido de enxofre. Os vinhos (UV0, UV1 e UV2) foram analisados ao longo do tempo (de 0 a 4 meses). Os resultados mostram que o tratamento com menor dose é eficaz no controlo microbiológico do produto. A análise sensorial mostrou que o tratamento com radiação UV-C não afectou o aroma e o sabor dos vinhos, inclusivamente estes vinhos foram mais pontuados no descritor intensidade da cor. The traditional procedure for the control of the microbiological stability of wine consists of the addition of sulfur dioxide (SO2), which acts as an antimicrobial agent and also as an antioxidant. The search for alternative methods of microbiological control is important and necessary, since SO2 is a potential allergen and consumers are increasingly looking for healthier and preservative free products. Ultraviolet radiation was tested as an innovative technology that can help reduce the amount of sulphur dioxide used in winemaking. The object of this study was to optimize the process conditions compared to the results obtained previously, and to evaluate the efficiency of microbiological stabilization and its influence on the physico-chemical characteristics, the phenolic composition and sensory profile. Thus, red wine with very low content of sulphur dioxide was subjected to UV-C radiation in two different doses 424J/l e 778J/l, and the preparation of a control wine was carried out to which 30 mg/l sulfur dioxide was added. The wines (control=UV0, UV1 and UV2) were analyzed over time (from 0 to 4 months). The results show that treatment with a lower dosage is effective in the microbiological control of the product. The wines subjected to treatment with UV-C showed an increase in intensity of colour, and the treatment does not affect the flavour and taste of the wine. info:eu-repo/semantics/publishedVersion

A major unanswered question regarding the dispersal of modern humans around the world concerns the geographical site of the first human steps outside of Africa. The "southern coastal route" model predicts that the early stages of the dispersal took place when people crossed the Red Sea to southern Arabia, but genetic evidence has hitherto been tenuous. We have addressed this question by analyzing the three minor west-Eurasian haplogroups, N1, N2, and X. These lineages branch directly from the first non-African founder node, the root of haplogroup N, and coalesce to the time of the first successful movement of modern humans out of Africa, ∼60 thousand years (ka) ago. We sequenced complete mtDNA genomes from 85 Southwest Asian samples carrying these haplogroups and compared them with a database of 300 European examples. The results show that these minor haplogroups have a relict distribution that suggests an ancient ancestry within the Arabian Peninsula, and they most likely spread from the Gulf Oasis region toward the Near East and Europe during the pluvial period 55-24 ka ago. This pattern suggests that Arabia was indeed the first staging post in the spread of modern humans around the world. FCT, the Portuguese Foundation for Science and Technology, supported this work through the research project PTDC/CS-ANT/113832/2009 and the personal grants to V.F. (SFRH/BD/61342/2009), N.M.S. (SFRH/BD/69119/2010), J.B.P. (SFRH/BD/45657/2008), M.D.C. (SFRH/BD/48372/2008), and P.S. (SFRH/BPD/64233/2009). We also thank the Leverhulme Trust (research project grant 10 105/D) and the DeLaszlo Foundation for financial support to P.S. The Instituto de Patologia e Imunologia Molecular da Universidade do Porto is an Associate Laboratory of the Portuguese Ministry of Science, Technology, and Higher Education and is partially supported by FCT.

Currently, a number of wave energy converters are being analyzed by means of numerical models in order to predict the electrical power generation under given wave conditions. A common characteristic of this procedure is to integrate the loadings from the hydrodynamics, power take-off and mooring systems into a central wave to wire model. The power production then depends on the control strategy which is applied to the device. The objective of this paper is to develop numerical methods for motion analysis of marine structures with a special emphasis on wave energy converters. Two different time domain models are applied to a point absorber system working in pitch mode only. The device is similar to the well-known Wavestar prototype located in the Danish North Sea. A laboratory model has been set up in order to validate the numerical simulations of the dynamics. Wave Excitation force and the response of the device for regular and irregular waves were measured. Good correspondence is found between the numerical and the physical model for relatively mild wave conditions. For higher waves the numerical model seems to underestimate the response of the device due to its linear fluid-structure interaction assumption and linearized equation of motion. The region over which the numerical model is valid will be presented in terms of non-dimensional parameters describing the different wave states.Copyright © 2012 by ASME

Failure of fibre-reinforced composites is affected by fatigue, which increases the challenge in designing safe and reliable composite structures. This paper presents an analytical model to predict the fatigue life of unidirectional composites under longitudinal tension-tension. The matrix and fibre-matrix interface are represented through a cohesive constitutive law, and a Paris law is used to model fatigue due to interfacial cracks propagating from fibre-breaks. The strength of single-fibres is modelled by a Weibull distribution, which is scaled hierarchically though a stochastic failure analysis of composite fibre-bundles, computing stochastic S-N curves of lab-scaled specimens in less than one minute. Model predictions are successfully validated against experiments from the literature. This model can be used to reduce the need for fatigue testing, and also to evaluate the impact of constituent properties on the fatigue life of composites.

This paper presents experimental and numerical results for tensile strength of tow based discontinues composite (TBDC) plates manufactured using ultra-thin fibre tapes of high stiffness carbon fibres. Numerical models were used to explore the design space of these materials, in order to identify the optimal tow properties that maximise the strength of TBDCs. The experimental show good agreement with the numerical predictions and demonstrate a significant increase in the tensile strength by reducing the tow thickness and increasing the stiffness of the fibres. Strength increases of up to 100%, compared with a commercially available material system, are found, illustrating the highly promising potential of this type of material.

Conventional randomly-oriented Tow Based Discontinues Composites (TBDCs) are materials which combine good mechanical properties, lightweight and high manufacturability, and are therefore interesting for high-volume transport industries. This paper proposes, designs and successfully demonstrates a pathway to produce TBDCs with outstanding stiffness and tensile strength, by using ultra-thin tapes of (ultra-) high modulus carbon-fibres. Numerical models are used to explore the design space of discontinuous composite materials, in order to identify the optimal microstructural design to maximise stiffness and strength. Selected microstructures are manufactured and tested under tension; the experimental results show good agreement with the numerical predictions, and demonstrate a significant increase in the tensile strength and Young’s modulus of TBDCs by reducing the tow thickness and increasing the modulus of the fibres. Strength and stiffness increases of over 100% compared with the commercially available TBDC systems are achieved, resulting in mechanical properties that match the strength and overcome the stiffness of aerospace-graded continuous-fibre laminates.