The impact of ocean acidification and warming on the skeletal mechanical properties of the sea urchin Paracentrotus lividus from laboratory and field observations

Increased atmospheric CO2 concentration is leading to changes in the carbonate chemistry and the temperature of the ocean. The impact of these processes on marine organisms will depend on their ability to cope with those changes, particularly the maintenance of calcium carbonate structures. Both a laboratory experiment (long-term exposure to decreased pH and increased temperature) and collections of individuals from natural environments characterized by low pH levels (individuals from intertidal pools and around a CO2 seep) were here coupled to comprehensively study the impact of near-future conditions of pH and temperature on the mechanical properties of the skeleton of the euechinoid sea urchin Paracentrotus lividus. To assess skeletal mechanical properties, we characterized the fracture force, Young's modulus, second moment of area, material nanohardness, and specific Young's modulus of sea urchin test plates. None of these parameters were significantly affected by low pH and/or increased temperature in the laboratory experiment and by low pH only in the individuals chronically exposed to lowered pH from the CO2 seeps. In tidal pools, the fracture force was higher and the Young's modulus lower in ambital plates of individuals from the rock pool characterized by the largest pH variations but also a dominance of calcifying algae, which might explain some of the variation. Thus, decreases of pH to levels expected for 2100 did not directly alter the mechanical properties of the test of P. lividus. Since the maintenance of test integrity is a question of survival for sea urchins and since weakened tests would increase the sea urchins' risk of predation, our findings indicate that the decreasing seawater pH and increasing seawater temperature expected for the end of the century should not represent an immediate threat to sea urchins vulnerability.

Urban Living Room: Inclusive U District Station Plaza Design

Thesis (Master's)--University of Washington, 2015

Simulating SOC changes in 11 land use change chronosequences from the Brazilian Amazon with RothC and Century models

Land use and land cover changes in the Brazilian Amazon have major implications for regional and global carbon (C) cycling. Cattle pasture represents the largest single use (about 70%) of this once-forested land in most of the region. The main objective of this study was to evaluate the accuracy of the RothC and Century models at estimating soil organic C (SOC) changes under forest-to-pasture conditions in the Brazilian Amazon. We used data from 11 site-specific 'forest to pasture' chronosequences with the Century Ecosystem Model (Century 4.0) and the Rothamsted C Model (RothC 26.3). The models predicted that forest clearance and conversion to well managed pasture would cause an initial decline in soil C stocks (0-20 cm depth), followed in the majority of cases by a slow rise to levels exceeding those under native forest. One exception to this pattern was a chronosequence in Suia-Missu, which is under degraded pasture. In three other chronosequences the recovery of soil C under pasture appeared to be only to about the same level as under the previous forest. Statistical tests were applied to determine levels of agreement between simulated SOC stocks and observed stocks for all the sites within the 11 chronosequences. The models also provided reasonable estimates (coefficient of correlation = 0.8) of the microbial biomass C in the 0-10 cm soil layer for three chronosequences, when compared with available measured data. The Century model adequately predicted the magnitude and the overall trend in delta C-13 for the six chronosequences where measured 813 C data were available. This study gave independent tests of model performance, as no adjustments were made to the models to generate outputs. Our results suggest that modelling techniques can be successfully used for monitoring soil C stocks and changes, allowing both the identification of current patterns in the soil and the projection of future conditions. Results were used and discussed not only to evaluate soil C dynamics but also to indicate soil C sequestration opportunities for the Brazilian Amazon region. Moreover, modelling studies in these 'forest to pasture' systems have important applications, for example, the calculation of CO, emissions from land use change in national greenhouse gas inventories. (0 2007 Elsevier B.V. All rights reserved.

Simulated climate change impact on summer dissolved organic carbon release from peat and surface vegetation: implications for drinking water treatment

Uncertainty regarding changes in dissolved organic carbon (DOC) quantity and quality has created interest in managing peatlands for their ecosystem services such as drinking water provision. The evidence base for such interventions is, however, sometimes contradictory. We performed a laboratory climate manipulation using a factorial design on two dominant peatland vegetation types (Calluna vulgaris and Sphagnum Spp.) and a peat soil collected from a drinking water catchment in Exmoor National Park, UK. Temperature and rainfall were set to represent baseline and future conditions under the UKCP09 2080s high emissions scenario for July and August. DOC leachate then underwent standard water treatment of coagulation/flocculation before chlorination. C. vulgaris leached more DOC than Sphagnum Spp. (7.17 versus 3.00 mg g−1) with higher specific ultraviolet (SUVA) values and a greater sensitivity to climate, leaching more DOC under simulated future conditions. The peat soil leached less DOC (0.37 mg g−1) than the vegetation and was less sensitive to climate. Differences in coagulation removal efficiency between the DOC sources appears to be driven by relative solubilisation of protein-like DOC, observed through the fluorescence peak C/T. Post-coagulation only differences between vegetation types were detected for the regulated disinfection by-products (DBPs), suggesting climate change influence at this scale can be removed via coagulation. Our results suggest current biodiversity restoration programmes to encourage Sphagnum Spp. will result in lower DOC concentrations and SUVA values, particularly with warmer and drier summers.

Probabilistic skill in ensemble seasonal forecasts

Simulation models are widely employed to make probability forecasts of future conditions on seasonal to annual lead times. Added value in such forecasts is reflected in the information they add, either to purely empirical statistical models or to simpler simulation models. An evaluation of seasonal probability forecasts from the Development of a European Multimodel Ensemble system for seasonal to inTERannual prediction (DEMETER) and ENSEMBLES multi-model ensemble experiments is presented. Two particular regions are considered: Nino3.4 in the Pacific and the Main Development Region in the Atlantic; these regions were chosen before any spatial distribution of skill was examined. The ENSEMBLES models are found to have skill against the climatological distribution on seasonal time-scales. For models in ENSEMBLES that have a clearly defined predecessor model in DEMETER, the improvement from DEMETER to ENSEMBLES is discussed. Due to the long lead times of the forecasts and the evolution of observation technology, the forecast-outcome archive for seasonal forecast evaluation is small; arguably, evaluation data for seasonal forecasting will always be precious. Issues of information contamination from in-sample evaluation are discussed and impacts (both positive and negative) of variations in cross-validation protocol are demonstrated. Other difficulties due to the small forecast-outcome archive are identified. The claim that the multi-model ensemble provides a ‘better’ probability forecast than the best single model is examined and challenged. Significant forecast information beyond the climatological distribution is also demonstrated in a persistence probability forecast. The ENSEMBLES probability forecasts add significantly more information to empirical probability forecasts on seasonal time-scales than on decadal scales. Current operational forecasts might be enhanced by melding information from both simulation models and empirical models. Simulation models based on physical principles are sometimes expected, in principle, to outperform empirical models; direct comparison of their forecast skill provides information on progress toward that goal.

Análise do impacto de conversores de frequência na qualidade da energia do sistema de distribuição de uma indústria de petróleo

Apresenta-se neste trabalho uma análise da qualidade da energia do sistema de distribuição de uma indústria de petróleo, de modo a avaliar o impacto da instalação de conversores de frequência no que diz respeito ao fenômeno de distorção harmônica. Os dados de distorção harmônica de tensão foram coletados através de duas medições com duração de sete dias consecutivos, sendo uma realizada antes e outra depois da instalação dos conversores de frequência. Adicionalmente, um estudo computacional utilizando o PTW (Power Tools for Windows) é apresentado com o intuito de simular condições futuras de instalação de novos conversores de frequência e de avaliar a influência dos bancos de capacitores na amplificação da distorção harmônica no sistema de distribuição.

Regeneração natural em ecounidades maduras e em reorganização de fragmentos de Floresta Estacional Semidecídua

The Atlantic Rainforest biome has been going through fragmentation processes caused by agriculture and urbanization in green areas. Structural studies associated with the silvigenetic approach allow the understanding of what the past has caused in the present structure and predict future conditions of disturbed fragments. The objective of this study was to compare the composition and diversity of arboreous natural regeneration of steady-state and reorganization ecounits in two Seasonal Semideciduous Forest fragments. The hypothesis was that specific composition varies in these two different ecounits due to differential adaptation of species in canopy gaps and closed canopy. The survey was made in three areas with different perturbation backgrounds of 0,5 ha each. 60 permanent plots of 4m² each (2m x 2m) were stablished along the studied fragments following the proportion of ecounits presented in a previous mapping. Each plot was divided in 4 sub-plots of 1m² and arboreous individuals between 0,20m and 1,30m height were sampled and posteriorly separated in two height classes: I) individuals between 0,20m and 0,50m height (2m² sampling) and II) individuals between 0,51m and 1,30m height (4m² sampling). It was sampled 338 individuals from 53 families and 23 species. The Shannon index was 3,26 (Area A), 2,27 (Area B) and 2,42 (Area C) whereas Areas B and C values are considered low in our state Semidecidous Forests. Steady-state ecounits presented the highest values for abundance and species richness. Chi-square test pointed out species’ selection for determined ecounits in the studied community. Rarefaction method analysis showed diversity increase in steady-state ecounits and a stablishment in species richness curves for reorganization ecounits

The impact of ocean acidification and warming on the skeletal mechanical properties of the sea urchin Paracentrotus lividus from laboratory and field observations

Increased atmospheric CO2 concentration is leading to changes in the carbonate chemistry and the temperature of the ocean. The impact of these processes on marine organisms will depend on their ability to cope with those changes, particularly the maintenance of calcium carbonate structures. Both a laboratory experiment (long-term exposure to decreased pH and increased temperature) and collections of individuals from natural environments characterized by low pH levels (individuals from intertidal pools and around a CO2 seep) were here coupled to comprehensively study the impact of near-future conditions of pH and temperature on the mechanical properties of the skeleton of the euechinoid sea urchin Paracentrotus lividus. To assess skeletal mechanical properties, we characterized the fracture force, Young's modulus, second moment of area, material nanohardness, and specific Young's modulus of sea urchin test plates. None of these parameters were significantly affected by low pH and/or increased temperature in the laboratory experiment and by low pH only in the individuals chronically exposed to lowered pH from the CO2 seeps. In tidal pools, the fracture force was higher and the Young's modulus lower in ambital plates of individuals from the rock pool characterized by the largest pH variations but also a dominance of calcifying algae, which might explain some of the variation. Thus, decreases of pH to levels expected for 2100 did not directly alter the mechanical properties of the test of P. lividus. Since the maintenance of test integrity is a question of survival for sea urchins and since weakened tests would increase the sea urchins' risk of predation, our findings indicate that the decreasing seawater pH and increasing seawater temperature expected for the end of the century should not represent an immediate threat to sea urchins vulnerability

Short- versus long-term responses to changing CO2 in a coastal dinoflagellate bloom

Increasing pCO2 (partial pressure of CO2 ) in an "acidified" ocean will affect phytoplankton community structure, but manipulation experiments with assemblages briefly acclimated to simulated future conditions may not accurately predict the long-term evolutionary shifts that could affect inter-specific competitive success. We assessed community structure changes in a natural mixed dinoflagellate bloom incubated at three pCO2 levels (230, 433, and 765 ppm) in a short-term experiment (2 weeks). The four dominant species were then isolated from each treatment into clonal cultures, and maintained at all three pCO2 levels for approximately 1 year. Periodically (4, 8, and 12 months), these pCO2 -conditioned clones were recombined into artificial communities, and allowed to compete at their conditioning pCO2 level or at higher and lower levels. The dominant species in these artificial communities of CO2 -conditioned clones differed from those in the original short-term experiment, but individual species relative abundance trends across pCO2 treatments were often similar. Specific growth rates showed no strong evidence for fitness increases attributable to conditioning pCO2 level. Although pCO2 significantly structured our experimental communities, conditioning time and biotic interactions like mixotrophy also had major roles in determining competitive outcomes. New methods of carrying out extended mixed species experiments are needed to accurately predict future long-term phytoplankton community responses to changing pCO2 .

Comparative responses of two dominant Antarctic phytoplankton taxa to interactions between ocean acidification, warming, irradiance, and iron availability

We investigated the responses of the ecologically dominant Antarctic phytoplankton species Phaeocystis antarctica (a prymnesiophyte) and Fragilariopsis cylindrus (a diatom) to a clustered matrix of three global change variables (CO2, mixed-layer depth, and temperature) under both iron (Fe)-replete and Fe-limited conditions based roughly on the Intergovernmental Panel on Climate Change (IPCC) A2 scenario: (1) Current conditions, 39 Pa (380 ppmv) CO2, 50 µmol photons/m**2/s light, and 2°C; (2) Year 2060, 61 Pa (600 ppmv) CO2, 100 µmol photons/m**2/s light, and 4°C; (3) Year 2100, 81 Pa (800 ppmv) CO2, 150 µmol photons/m**2/s light, and 6°C. The combined interactive effects of these global change variables and changing Fe availability on growth, primary production, and cell morphology are species specific. A competition experiment suggested that future conditions could lead to a shift away from P. antarctica and toward diatoms such as F. cylindrus. Along with decreases in diatom cell size and shifts from prymnesiophyte colonies to single cells under the future scenario, this could potentially lead to decreased carbon export to the deep ocean. Fe : C uptake ratios of both species increased under future conditions, suggesting phytoplankton of the Southern Ocean will increase their Fe requirements relative to carbon fixation. The interactive effects of Fe, light, CO2, and temperature on Antarctic phytoplankton need to be considered when predicting the future responses of biology and biogeochemistry in this region.

Diseño y aplicación de una metodología prospectiva para la determinación de los condicionantes futuros del crecimiento de los grandes buques portacontenedores

Durante las últimas décadas se observa una tendencia sostenida al crecimiento en las dimensiones de los grandes buques portacontenedores, que produce, que las infraestructuras portuarias y otras destinadas al tráfico de contenedores deban adaptarse para poder brindar los servicios correspondientes y mantenerse competitivas con otras para no perder el mercado. Esta situación implica importantes inversiones y modificaciones en los sistemas de transporte de contenedores por el gran volumen de carga que se debe mover en un corto periodo de tiempo, lo que genera la necesidad de tomar previsiones relacionadas con la probable evolución a futuro de las dimensiones que alcanzarán los grandes buques portacontenedores. En relación a los aspectos citados surge la inquietud de determinar los condicionantes futuros del crecimiento de los grandes buques portacontenedores, con una visión totalizadora de todos los factores que incidirán en los próximos años, ya sea como un freno o un impulso a la tendencia que se verifica en el pasado y en el presente. En consideración a que el tema a tratar y resolver se encuentra en el futuro, con un horizonte de predicción de veinte años, se diseña y se aplica una metodología prospectiva, que permite alcanzar conclusiones con mayor grado de objetividad sobre probables escenarios futuros. La metodología prospectiva diseñada, conjuga distintas herramientas metodológicas, cualitativas, semi-cuantitativas y cuantitativas que se validan entre sí. Sobre la base del pasado y el presente, las herramientas cuantitativas permiten encontrar relaciones entre variables y hacer proyecciones, sin embargo, estas metodologías pierden validez más allá de los tres a cuatro años, por los vertiginosos y dinámicos cambios que se producen actualmente, en las áreas política, social y económica. Las metodologías semi-cuantitativas y cualitativas, empleadas en forma conjunta e integradas, permiten el análisis de circunstancias del pasado y del presente, obteniendo resultados cuantitativos que se pueden proyectar hacia un futuro cercano, los que integrados en estudios cualitativos proporcionan resultados a largo plazo, facilitando considerar variables cualitativas como la creciente preocupación por la preservación del medio ambiente y la piratería. La presente tesis, tiene como objetivo principal “identificar los condicionantes futuros del crecimiento de los grandes buques portacontenedores y determinar sus escenarios”. Para lo cual, la misma se estructura en fases consecutivas y que se retroalimentan continuamente. Las tres primeras fases son un enfoque sobre el pasado y el presente, que establece el problema a resolver. Se estudian los antecedentes y el estado del conocimiento en relación a los factores y circunstancias que motivaron y facilitaron la tendencia al crecimiento de los grandes buques. También se estudia el estado del conocimiento de las metodologías para predecir el futuro y se diseña de una metodología prospectiva. La cuarta fase, denominada Resultados, se desarrolla en distintas etapas, fundamentadas en las fases anteriores, con el fin de resolver el problema dando respuestas a las preguntas que se formularon para alcanzar el objetivo fijado. En el proceso de esta fase, con el objeto de predecir probables futuros, se aplica la metodología prospectiva diseñada, que contempla el análisis del pasado y el presente, que determina los factores cuya influencia provocó el crecimiento en dimensiones de los grandes buques hasta la actualidad, y que constituye la base para emplear los métodos prospectivos que permiten determinar qué factores condicionarán en el futuro la evolución de los grandes buques. El probable escenario futuro formado por los factores determinados por el criterio experto, es validado mediante un modelo cuantitativo dinámico, que además de obtener el probable escenario futuro basado en las tendencias de comportamiento hasta el presente de los factores determinantes considerados, permite estudiar distintos probables escenarios futuros en función de considerar un cambio en la tendencia futura de los factores determinantes. El análisis del pasado indica que la tendencia al crecimiento de los grandes buques portacontenedores hasta el presente, se ha motivado por un crecimiento económico mundial que se tradujo en un aumento del comercio internacional, particularmente entre los países de Asia, con Europa y Estados Unidos. Esta tendencia se ha visto favorecida por el factor globalización y la acelerada evolución tecnológica que ha permitido superar los obstáculos que se presentaron. Es de destacar que aún en periodos de crisis económicas, con pronósticos de contracciones en el comercio, en los últimos años continuó la tendencia al crecimiento en dimensiones, en busca de una economía de escala para el transporte marítimo de contenedores, en las rutas transoceánicas. La investigación de la evolución de los grandes buques portacontenedores en el futuro, se efectúa mediante el empleo de una metodología prospectiva en la que el criterio experto se valida con un método cuantitativo dinámico, y además se fundamenta en una solida base pre-prospectiva. La metodología diseñada permite evaluar con un alto grado de objetividad cuales serán los condicionantes que incidirán en el crecimiento en tamaño de los grandes buques portacontenedores en el escenario con mayor probabilidad de acontecer en los próximos veinte años (2032), y también en otros escenarios que podrían presentarse en el caso de que los factores modifiquen su tendencia o bien se produzcan hechos aleatorios. El resultado se sintetiza en que la tendencia al crecimiento de los grandes buques portacontenedores en los próximos 20 años se verá condicionada por factores en relación a los conceptos de oferta (los que facilitan u obstaculizan la tendencia), demanda (los que motivan o impulsan la tendencia) y factores externos (los que desestabilizan el equilibrio entre oferta y demanda). La tendencia al crecimiento de los grandes buques portacontenedores se verá obstaculizada / limitada principalmente por factores relacionados a las infraestructuras, resultando los pasos y/o canales vinculados a las rutas marítimas, los limitantes futuros al crecimiento en dimensiones de los grandes buques portacontenedores; y la interacción buque / infraestructura (grúas) un factor que tenderá a obstaculizar esta tendencia de los grandes portacontenedores. El desarrollo económico mundial que estimula el comercio internacional y los factores precio del petróleo y condicionantes medioambientales impulsarán la tendencia al crecimiento de los grandes buques portacontenedores. Recent years have seen a sustained tendency towards the growth in the dimensions of large container ships. This has meant that port and other infrastructure used for container traffic has had to be adapted in order to provide the required services and to maintain a competitive position, so as not to lose market share. This situation implies the need for major investments in modifications to the container transport system, on account of the large volume of traffic to be handled in a short period of time. This in turn has generated a need to make provision for the probable future evolution of the ultimate dimensions that will be reached by large container ships. Such considerations give rise to the question of what are the future determinants for the growth of large container ships, requiring an overall vision of all the factors that will apply in future years, whether as a brake on or an incentive to the growth tendency which has been seen in the past and present In view of the fact that the theme to be dealt with and resolved relates to the future, with a forecasting horizon of some 20 years, a foresight methodology has been designed and applied so as to enable conclusions about probable future scenarios to be reached with a greater degree of objectivity. The designed methodology contains different methodological tools, both qualitative, semi-quantitative and quantitative, which are internally consistent. On the basis of past and present observations, the quantitative elements enable relationships to be established and forecasts to be made. Nevertheless such an approach loses validity more than three or four years into the future, on account of the very rapid and dynamic changes which may be seen at present in political, social and economic spheres. The semi-quantitative and qualitative methodologies are used coherently together and allow the analysis of past and present conditions, thus obtaining quantitative results which for short-term projections, which when integrated with the qualitative studies provide results for the long-term, facilitating the consideration of qualitative variables such as the increasing importance of environmental protection and the impact of piracy. The principal objective of the present thesis is "to identify the future conditions affecting the growth of large container ships and to determine possible scenarios". The thesis is structured in consecutive and related phases. The first three phases focus on the past and present in order to determine the problem to be resolved. The background is studied in order to establish the state of knowledge about the factors and circumstances which have motivated and facilitated the growth tendency for large container ships and the methodologies that have been used. In this way a specific foresight methodology is designed. The fourth phase, Results, is developed in distinct stages based on the previous phases, so as to resolve the problem posed and responding to the questions that arise. In this way the determined objective is reached. The fourth phase sees the application of the methodology that has been designed in order to predict posible futures. This includes analysis of the past and present factors which have caused the growth in the dimensions of large container ships up to the present. These provide the basis on which to apply the foresight methods which enable the future factors which will condition the development of such large container ships. The probable future scenarios are made up of the factors identified by expert judgement (using the Delphi technique) and validated by means of a dynamic quantitative model. This model both identifies the probable future scenarios based on past and present factors and enables the different future scenarios to be analysed as a function of future changes in the conditioning factors. Analysis of the past shows that the growth tendency up to the present for large container ships has been motivated by the growth of the world economy and the consequent increased international trade, especially between the countries of Asia with Europe and the United States. This tendency has been favoured by the trend towards globalization and by the rapid technical evolution in ship design, which has allowed the obstacles encountered to be overcome. It should be noted that even in periods of economic crisis, with an expectation for reduced trade, as experienced in recent years, the tendency towards increased ship dimensions has continued in search of economies of scale for the maritime transport of containers on transoceanic routes. The present investigation of the future evolution of large container ships has been done using a foresight methodology in which the expert judgement is validated by a dynamic quantitative methodology, founded on a firm pre-foresight analysis. The methodology that has been designed permits the evaluation, with a high degree of objectivity, of the future factors that will affect the growth of large container ships for the most probable scenario expected in the next 20 years (up to 2032). The evaluation applies also to other scenarios which may arise, in the event that their component factors are modified or indeed in the light of random events. In summary, the conclusión is that the tendency for growth in large container ships in the future 20 years will be determined by: factors related to supply, which slow or halt the tendency; factors related to demand, which encourage the tendency and finally, external factors which interrupt the equilibrium between supply and demand. The tendency for increasing growth in large container ships will be limited or even halted by factors related to infrastructure, including the natural and man-made straits and canals used by maritime transport. In addition the infrastructure required to serve such vessels both in port (including cranes and other equipment) and related transport, will tend to slow the growth tendency. The factors which will continue to encourage the tendency towards the growth of large container ships include world economic development, which stimulates international trade, and an increasing emphasis on environmental aspects.

Extracción de conocimientos de la diabetes tipo 1 utilizando la metodología de "Data Mining"

La diabetes mellitus es un trastorno en la metabolización de los carbohidratos, caracterizado por la nula o insuficiente segregación de insulina (hormona producida por el páncreas), como resultado del mal funcionamiento de la parte endocrina del páncreas, o de una creciente resistencia del organismo a esta hormona. Esto implica, que tras el proceso digestivo, los alimentos que ingerimos se transforman en otros compuestos químicos más pequeños mediante los tejidos exocrinos. La ausencia o poca efectividad de esta hormona polipéptida, no permite metabolizar los carbohidratos ingeridos provocando dos consecuencias: Aumento de la concentración de glucosa en sangre, ya que las células no pueden metabolizarla; consumo de ácidos grasos mediante el hígado, liberando cuerpos cetónicos para aportar la energía a las células. Esta situación expone al enfermo crónico, a una concentración de glucosa en sangre muy elevada, denominado hiperglucemia, la cual puede producir a medio o largo múltiples problemas médicos: oftalmológicos, renales, cardiovasculares, cerebrovasculares, neurológicos… La diabetes representa un gran problema de salud pública y es la enfermedad más común en los países desarrollados por varios factores como la obesidad, la vida sedentaria, que facilitan la aparición de esta enfermedad. Mediante el presente proyecto trabajaremos con los datos de experimentación clínica de pacientes con diabetes de tipo 1, enfermedad autoinmune en la que son destruidas las células beta del páncreas (productoras de insulina) resultando necesaria la administración de insulina exógena. Dicho esto, el paciente con diabetes tipo 1 deberá seguir un tratamiento con insulina administrada por la vía subcutánea, adaptado a sus necesidades metabólicas y a sus hábitos de vida. Para abordar esta situación de regulación del control metabólico del enfermo, mediante una terapia de insulina, no serviremos del proyecto “Páncreas Endocrino Artificial” (PEA), el cual consta de una bomba de infusión de insulina, un sensor continuo de glucosa, y un algoritmo de control en lazo cerrado. El objetivo principal del PEA es aportar al paciente precisión, eficacia y seguridad en cuanto a la normalización del control glucémico y reducción del riesgo de hipoglucemias. El PEA se instala mediante vía subcutánea, por lo que, el retardo introducido por la acción de la insulina, el retardo de la medida de glucosa, así como los errores introducidos por los sensores continuos de glucosa cuando, se descalibran dificultando el empleo de un algoritmo de control. Llegados a este punto debemos modelar la glucosa del paciente mediante sistemas predictivos. Un modelo, es todo aquel elemento que nos permita predecir el comportamiento de un sistema mediante la introducción de variables de entrada. De este modo lo que conseguimos, es una predicción de los estados futuros en los que se puede encontrar la glucosa del paciente, sirviéndonos de variables de entrada de insulina, ingesta y glucosa ya conocidas, por ser las sucedidas con anterioridad en el tiempo. Cuando empleamos el predictor de glucosa, utilizando parámetros obtenidos en tiempo real, el controlador es capaz de indicar el nivel futuro de la glucosa para la toma de decisones del controlador CL. Los predictores que se están empleando actualmente en el PEA no están funcionando correctamente por la cantidad de información y variables que debe de manejar. Data Mining, también referenciado como Descubrimiento del Conocimiento en Bases de Datos (Knowledge Discovery in Databases o KDD), ha sido definida como el proceso de extracción no trivial de información implícita, previamente desconocida y potencialmente útil. Todo ello, sirviéndonos las siguientes fases del proceso de extracción del conocimiento: selección de datos, pre-procesado, transformación, minería de datos, interpretación de los resultados, evaluación y obtención del conocimiento. Con todo este proceso buscamos generar un único modelo insulina glucosa que se ajuste de forma individual a cada paciente y sea capaz, al mismo tiempo, de predecir los estados futuros glucosa con cálculos en tiempo real, a través de unos parámetros introducidos. Este trabajo busca extraer la información contenida en una base de datos de pacientes diabéticos tipo 1 obtenidos a partir de la experimentación clínica. Para ello emplearemos técnicas de Data Mining. Para la consecución del objetivo implícito a este proyecto hemos procedido a implementar una interfaz gráfica que nos guía a través del proceso del KDD (con información gráfica y estadística) de cada punto del proceso. En lo que respecta a la parte de la minería de datos, nos hemos servido de la denominada herramienta de WEKA, en la que a través de Java controlamos todas sus funciones, para implementarlas por medio del programa creado. Otorgando finalmente, una mayor potencialidad al proyecto con la posibilidad de implementar el servicio de los dispositivos Android por la potencial capacidad de portar el código. Mediante estos dispositivos y lo expuesto en el proyecto se podrían implementar o incluso crear nuevas aplicaciones novedosas y muy útiles para este campo. Como conclusión del proyecto, y tras un exhaustivo análisis de los resultados obtenidos, podemos apreciar como logramos obtener el modelo insulina-glucosa de cada paciente. ABSTRACT. The diabetes mellitus is a metabolic disorder, characterized by the low or none insulin production (a hormone produced by the pancreas), as a result of the malfunctioning of the endocrine pancreas part or by an increasing resistance of the organism to this hormone. This implies that, after the digestive process, the food we consume is transformed into smaller chemical compounds, through the exocrine tissues. The absence or limited effectiveness of this polypeptide hormone, does not allow to metabolize the ingested carbohydrates provoking two consequences: Increase of the glucose concentration in blood, as the cells are unable to metabolize it; fatty acid intake through the liver, releasing ketone bodies to provide energy to the cells. This situation exposes the chronic patient to high blood glucose levels, named hyperglycemia, which may cause in the medium or long term multiple medical problems: ophthalmological, renal, cardiovascular, cerebrum-vascular, neurological … The diabetes represents a great public health problem and is the most common disease in the developed countries, by several factors such as the obesity or sedentary life, which facilitate the appearance of this disease. Through this project we will work with clinical experimentation data of patients with diabetes of type 1, autoimmune disease in which beta cells of the pancreas (producers of insulin) are destroyed resulting necessary the exogenous insulin administration. That said, the patient with diabetes type 1 will have to follow a treatment with insulin, administered by the subcutaneous route, adapted to his metabolic needs and to his life habits. To deal with this situation of metabolic control regulation of the patient, through an insulin therapy, we shall be using the “Endocrine Artificial Pancreas " (PEA), which consists of a bomb of insulin infusion, a constant glucose sensor, and a control algorithm in closed bow. The principal aim of the PEA is providing the patient precision, efficiency and safety regarding the normalization of the glycemic control and hypoglycemia risk reduction". The PEA establishes through subcutaneous route, consequently, the delay introduced by the insulin action, the delay of the glucose measure, as well as the mistakes introduced by the constant glucose sensors when, decalibrate, impede the employment of an algorithm of control. At this stage we must shape the patient glucose levels through predictive systems. A model is all that element or set of elements which will allow us to predict the behavior of a system by introducing input variables. Thus what we obtain, is a prediction of the future stages in which it is possible to find the patient glucose level, being served of input insulin, ingestion and glucose variables already known, for being the ones happened previously in the time. When we use the glucose predictor, using obtained real time parameters, the controller is capable of indicating the future level of the glucose for the decision capture CL controller. The predictors that are being used nowadays in the PEA are not working correctly for the amount of information and variables that it need to handle. Data Mining, also indexed as Knowledge Discovery in Databases or KDD, has been defined as the not trivial extraction process of implicit information, previously unknown and potentially useful. All this, using the following phases of the knowledge extraction process: selection of information, pre- processing, transformation, data mining, results interpretation, evaluation and knowledge acquisition. With all this process we seek to generate the unique insulin glucose model that adjusts individually and in a personalized way for each patient form and being capable, at the same time, of predicting the future conditions with real time calculations, across few input parameters. This project of end of grade seeks to extract the information contained in a database of type 1 diabetics patients, obtained from clinical experimentation. For it, we will use technologies of Data Mining. For the attainment of the aim implicit to this project we have proceeded to implement a graphical interface that will guide us across the process of the KDD (with graphical and statistical information) of every point of the process. Regarding the data mining part, we have been served by a tool called WEKA's tool called, in which across Java, we control all of its functions to implement them by means of the created program. Finally granting a higher potential to the project with the possibility of implementing the service for Android devices, porting the code. Through these devices and what has been exposed in the project they might help or even create new and very useful applications for this field. As a conclusion of the project, and after an exhaustive analysis of the obtained results, we can show how we achieve to obtain the insulin–glucose model for each patient.

Effects of ocean warming and acidification on the early stages of marine fishes

Tese de doutoramento, Ciências do Mar, Universidade de Lisboa, Faculdade de Ciências, 2016

Effects of ocean acidification on growth and physiology of Ulva lactuca (Chlorophyta) in a rockpool-scenario, link to supplementary data

Rising atmospheric CO2-concentrations will have severe consequences for a variety of biological processes. We investigated the responses of the green alga Ulva lactuca (Linnaeus) to rising CO2-concentrations in a rockpool scenario. U. lactuca was cultured under aeraton with air containing either preindustrial pCO2 (280µatm) or for the end of the 21st century predicted (700µatm) pCO2 for 31 days. We addressed the following question: Will elevated CO2-concentrations affect photosynthesis (net photosynthesis, rETR(max), Fv/Fm, pigment composition) and growth of U. lactuca in rockpools with limited water exchange? Two phases of the experiment were distinguished: In the initial phase (day 1-4) the Seawater Carbonate System (SWCS) of the culture medium could be adjusted to the selected atmospheric pCO2 condition by continuous aeration with target pCO2 values. In the second phase (day 4-31) the SWCS was largely determined by the metabolism of the growing U. lactuca biomass. In the initial phase, Fv/Fm and rETR(max) were only slightly elevated at high CO2-concentrations whereas growth was significantly enhanced. After 31 days the Chl a content of the thalli was significantly lower under future conditions and the photosynthesis of thalli grown under preindustrial conditions was not dependent on external carbonic anhydrase. Biomass increased significantly at high CO2-concentrations. At low CO2-concentrations most adult thalli disintegrated between day 14 and 21, whereas at high CO2-concentrations most thalli remained integer until day 31. Thallus disintegration at low CO2-concentrations was mirrored in a drastic decline in seawater DIC and HCO3-. Accordingly, the SWCS differed significantly between the treatments. Our results indicated a slight enhancement of photosynthetic performance and significantly elevated growth of U. lactuca at future CO2-concentrations. The accelerated thallus disintegration at high CO2-concentrations under conditions of limited water exchange indicates additional CO2 effects on the life cycle of U. lactuca when living in rockpools.

Freeway travel time estimation and prediction using dynamic neural networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. ^ This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.^