Families of symmetric periodic orbits in the three body problem and the figure eight

Ejemplar dedicado a: Actas de las VI Jornadas de Mecánica CelesteIn this paper we show a technique for the continuation of symmetric periodic orbits in systems with time-reversal symmetries. The geometric idea of this technique allows us to generalize the “cylinder” theorem for this kind of systems. We state the main theoretical result without proof (to be published elsewhere). We focus on the application of this scheme to the three body problem (TBP), taking as starting point the figure eight orbit [3] to find families of symmetric periodic orbits.DGYCIT/ Junta de Andalucía DGES PB98-1152DGYCIT/ Junta de Andalucía BFM-2003-0033

Continuation of Gerver's supereight choreography

Ejemplar dedicado a: Actas de las IX Jornadas de Mecánica CelesteIn [6] we developed a continuation technique for periodic orbits in reversible systems having some first integrals and corresponding symmetries. One of the applications was the continuation of Gerver’s supereight choreography when one or several of the masses are varied. In this note we give a more complete description of the families of periodic orbits which can be obtained in this way.Spanish Ministry of Education BFM2003-00336Spanish Ministry of Education MTM2006-00847University of Seville SAB2005-018

Decision Tree for Early Detection of Cognitive Impairment by Community Pharmacists

Purpose: The early detection of Mild Cognitive Impairment (MCI) is essential in aging societies where dementia is becoming a common manifestation among the elderly. Thus our aim is to develop a decision tree to discriminate individuals at risk of MCI among non-institutionalized elderly users of community pharmacy. A more clinically and patient-oriented role of the community pharmacist in primary care makes the dispensation of medication an adequate situation for an effective, rapid, easy, and reproducible screening of MCI.Methods: A cross-sectional study was conducted with 728 non-institutionalized participants older than 65. A total of 167 variables were collected such as age, gender, educational attainment, daily sleep duration, reading frequency, subjective memory complaint, and medication. Two screening tests were used to detect possible MCI: Short Portable Mental State Questionnaire (SPMSQ) and the Mini-Mental State Examination (MMSE). Participants classified as positive were referred to clinical diagnosis. A decision tree and predictive models are presented as a result of applying techniques of machine learning for a more efficient enrollment.Results: One hundred and twenty-eight participants (17.4%) scored positive on MCI tests. A recursive partitioning algorithm with the most significant variables determined that the most relevant for the decision tree are: female sex, sleeping more than 9 h daily, age higher than 79 years as risk factors, and reading frequency. Moreover, psychoanaleptics, nootropics, and antidepressants, and anti-inflammatory drugs achieve a high score of importance according to the predictive algorithms. Furthermore, results obtained from these algorithms agree with the current research on MCI.Conclusion: Lifestyle-related factors such as sleep duration and the lack of reading habits are associated with the presence of positive in MCI test. Moreover, we have depicted how machine learning provides a sound methodology to produce tools for early detection of MCI in community pharmacy.Impact of findings on practice: The community of pharmacists provided with adequate tools could develop a crucial task in the early detection of MCI to redirect them immediately to the specialists in neurology or psychiatry. Pharmacists are one of the most accessible and regularly visited health care professionals and they can play a vital role in early detection of MCI

Evolución de Studium. Despliegue de la plataforma moodle 2.x

Memoria ID-2012.001. Ayudas de la Universidad de Salamanca para la innovación docente, curso 2012-2013

Cualificación en los Objetivos establecidos en la Agenda 2030 de estudiantes y profesores en el Máster Universitario en Profesor de Educación Secundaria Obligatoria y Bachillerato, Formación Profesional y Enseñanza de Idiomas (MUPES)

Memoria ID2022-157 Ayudas de la Universidad de Salamanca para la innovación docente, curso 2022-2023

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Continuation of symmetric invariant curves for the system with Lyapunov exponent zero. <br><br>x_n+1 = arctan (<i>a</i> x_n) + <i>b</i> sin θ_n,<br>θ_n+1 = θ_n + <i>ω</i>,<br><br

Supervised filters for EEG signal in naturally occurring epilepsy forecasting.

Nearly 1% of the global population has Epilepsy. Forecasting epileptic seizures with an acceptable confidence level, could improve the disease treatment and thus the lifestyle of the people who suffer it. To do that the electroencephalogram (EEG) signal is usually studied through spectral power band filtering, but this paper proposes an alternative novel method of preprocessing the EEG signal based on supervised filters. Such filters have been employed in a machine learning algorithm, such as the K-Nearest Neighbor (KNN), to improve the prediction of seizures. The proposed solution extends with this novel approach an algorithm that was submitted to win the third prize of an international Data Science challenge promoted by Kaggle contest platform and the American Epilepsy Society, the Epilepsy Foundation, National Institutes of Health (NIH) and Mayo Clinic. A formal description of these preprocessing methods is presented and a detailed analysis in terms of Receiver Operating Characteristics (ROC) curve and Area Under ROC curve is performed. The obtained results show statistical significant improvements when compared with the spectral power band filtering (PBF) typical baseline. A trend between performance and the dataset size is observed, suggesting that the supervised filters bring better information, compared to the conventional PBF filters, as the dataset grows in terms of monitored variables (sensors) and time length. The paper demonstrates a better accuracy in forecasting when new filters are employed and its main contribution is in the field of machine learning algorithms to develop more accurate predictive systems

Numerical explorations in a modified potential of the TBP

This is a working document distributed in 2005 among our group and other researchers interested about bifurcation for numerical continuation of modified potential of the three body problem (TBP) starting from the figure-8 Chenciner and Montgomery(2000). In 2018, Dr.~Toshiaki Fujiwara told us that he was going to cite our private communication about this topic. Therefore, this document is making publicly available that communication as well as the code for numerical continuation with AUTO. The body of this document consists in the working document of 2005, adding some remarks as footnotes and a bibliography with the papers where the algorithms are described

ROC curves for the preprocessing methods.

<p>Following the notation in the paper: PBF (dark green), DS (orange), VAR (blue), DM (pink), TVM (light blue), Sq.diff (yellow) for all the test set (public+private) given by the Kaggle contest.</p