Asymptotic solution for the two-body problem with constant tangencial acceleration

An analytical solution of the two body problem perturbed by a constant tangential acceleration is derived with the aid of perturbation theory. The solution, which is valid for circular and elliptic orbits with generic eccentricity, describes the instantaneous time variation of all orbital elements. A comparison with high-accuracy numerical results shows that the analytical method can be effectively applied to multiple-revolution low-thrust orbit transfer around planets and in interplanetary space with negligible error.

Ab initio Methodology for Calculating Elastic Constant and Sound Velocity for Hydrogen and Deuterium in Molecular Solid Phase

Hydrogen isotopes play a critical role both in inertial and magnetic confinement Nuclear Fusion. Since the preferent fuel needed for this technology is a mixture of deuterium and tritium. The study of these isotopes particularly at very low temperatures carries a technological interest in other applications. The present line promotes a deep study on the structural configuration that hydrogen and deuterium adopt at cryogenic temperatures and at high pressures. Typical conditions occurring in present Inertial Fusion target designs. Our approach is aims to determine the crystal structure characteristics, phase transitions and other parameters strongly correlated to variations of temperature and pressure. With this results is possible calculated the elastic constant and sound velocity for hydrogen and deuterium in molecular solid phase.

Architecture for text normalization using statistical machine translation techniques

This paper proposes an architecture, based on statistical machine translation, for developing the text normalization module of a text to speech conversion system. The main target is to generate a language independent text normalization module, based on data and flexible enough to deal with all situa-tions presented in this task. The proposed architecture is composed by three main modules: a tokenizer module for splitting the text input into a token graph (tokenization), a phrase-based translation module (token translation) and a post-processing module for removing some tokens. This paper presents initial exper-iments for numbers and abbreviations. The very good results obtained validate the proposed architecture.

A critical force constant of the structural phase transition in quartz

Long wavelength optical phonons of quartz were analyzed by a Born-Von Karman model not previously used. It was found that only one force constant associated with the turning of the Si-O bonds has a critical effect on the soft-mode frequency and the α-β transition in quartz. The square of the soft-mode frequency was found to depend linearly on this force constant which has the temperature dependence K(T)= -5.33+225.3x10-4(851-T)2/3 in units of 104 dyn/cm2.

Accurate analytical approximation of asteroid deflection with constant tangential thrust

We present analytical formulas to estimate the variation of achieved deflection for an Earth-impacting asteroid following a continuous tangential low-thrust deflection strategy. Relatively simple analytical expressions are obtained with the aid of asymptotic theory and the use of Peláez orbital elements set, an approach that is particularly suitable to the asteroid deflection problem and is not limited to small eccentricities. The accuracy of the proposed formulas is evaluated numerically showing negligible error for both early and late deflection campaigns. The results will be of aid in planning future low-thrust asteroid deflection missions

Jupiter power generation with electrodynamic tethers at constant orbital energy

An electrodynamic tether system for power generation at Jupiter is presented that allows extracting energy from Jupiter's corotating plasmasphere while leaving the system orbital energy unaltered to first order. The spacecraft is placed in a polar orbit with the tether spinning in the orbital plane so that the resulting Lorentz force, neglecting Jupiter's magnetic dipole tilt, is orthogonal to the instantaneous velocity vector and orbital radius, hence affecting orbital inclination rather than orbital energy. In addition, the electrodynamic tether subsystem, which consists of two radial tether arms deployed from the main central spacecraft, is designed in such a way as to extract maximum power while keeping the resulting Lorentz torque constantly null. The power-generation performance of the system and the effect on the orbit inclination is evaluated analytically for different orbital conditions and verified numerically. Finally, a thruster-based inclination-compensation maneuver at apoapsis is added, resulting in an efficient scheme to extract energy from the plasmasphere of the planet with minimum propellant consumption and no inclination change. A tradeoff analysis is conducted showing that, depending on tether size and orbit characteristics, the system performance can be considerably higher than conventional power-generation methods.

Validation of the burn-up code EVOLCODE 2.0 with PWR experimental data and with a Sensitivity/Uncertainty analysis

A validation of the burn-up simulation system EVOLCODE 2.0 is presented here, involving the experimental measurement of U and Pu isotopes and some fission fragments production ratios after a burn-up of around 30 GWd/tU in a Pressurized Light Water Reactor (PWR). This work provides an in-depth analysis of the validation results, including the possible sources of the uncertainties. An uncertainty analysis based on the sensitivity methodology has been also performed, providing the uncertainties in the isotopic content propagated from the cross sections uncertainties. An improvement of the classical Sensitivity/ Uncertainty (S/U) model has been developed to take into account the implicit dependence of the neutron flux normalization, that is, the effect of the constant power of the reactor. The improved S/U methodology, neglected in this kind of studies, has proven to be an important contribution to the explanation of some simulation-experiment discrepancies for which, in general, the cross section uncertainties are, for the most relevant actinides, an important contributor to the simulation uncertainties, of the same order of magnitude and sometimes even larger than the experimental uncertainties and the experiment- simulation differences. Additionally, some hints for the improvement of the JEFF3.1.1 fission yield library and for the correction of some errata in the experimental data are presented.

On a parabolic-elliptic chemotactic system with non-constant chemotactic sensitivity

We study a parabolic–elliptic chemotactic system describing the evolution of a population’s density “u” and a chemoattractant’s concentration “v”. The system considers a non-constant chemotactic sensitivity given by “χ(N−u)”, for N≥0, and a source term of logistic type “λu(1−u)”. The existence of global bounded classical solutions is proved for any χ>0, N≥0 and λ≥0. By using a comparison argument we analyze the stability of the constant steady state u=1, v=1, for a range of parameters. – For N>1 and Nλ>2χ, any positive and bounded solution converges to the steady state. – For N≤1 the steady state is locally asymptotically stable and for χN<λ, the steady state is globally asymptotically stable.

Measurement of the intrinsic damping constant in individual nanodisks of Y3Fe5O12 and Y3Fe5O12|Pt

We report on an experimental study on the spin-waves relaxation rate in two series of nanodisks of diameter ϕ=300 , 500, and 700 nm, patterned out of two systems: a 20 nm thick yttrium iron garnet (YIG) film grown by pulsed laser deposition either bare or covered by 13 nm of Pt. Using a magnetic resonance force microscope, we measure precisely the ferromagnetic resonance linewidth of each individual YIG and YIG|Pt nanodisks. We find that the linewidth in the nanostructure is sensibly smaller than the one measured in the extended film. Analysis of the frequency dependence of the spectral linewidth indicates that the improvement is principally due to the suppression of the inhomogeneous part of the broadening due to geometrical confinement, suggesting that only the homogeneous broadening contributes to the linewidth of the nanostructure. For the bare YIG nano-disks, the broadening is associated to a damping constant α=4 × 10−4 . A threefold increase of the linewidth is observed for the series with Pt cap layer, attributed to the spin pumping effect. The measured enhancement allows to extract the spin mixing conductance found to be G↑↓=1.55 × 1014 Ω−1 m−2 for our YIG(20nm)|Pt interface, thus opening large opportunities for the design of YIG based nanostructures with optimized magnetic losses.

The normalization of the "Active-Sedentary" lifestyle in spanish youth

Sedentarism has become one of the major concerns of our times. Nowadays people spend most of the time sitting down and moving by mechanical means instead of exercising themselves. Younger generations do only a little more sport today than their counterparts did a decade ago. In other words, sedentary habits have become common in our society, especially among the young. What cultural mechanisms have contributed to this? What are the consequences of a sedentary lifestyle for our health and well-being? These are the questions we have posed in this study. We conducted qualitative research among Spanish young people, and the results have provided important clues to help us understand better how ?active sedentarism? has become the norm among young people.

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.