Reflexiones acerca de la medicina popular

La primitiva medicina, empírica, toma desde la antigüedad dos direcciones dispares: la hechiceril y la de progresivo carácter científico que aboca en la medicina actual. Las prácticas de la llamada popular con sus componentes empírico y mágico derivan de la primera dirección. Tres elementos constituyen la trama del universal fenómeno del curanderismo: el curandero, el paciente y los métodos curatorios cuyas características esenciales se exponen y comentan en este trabajo. Así como también la creciente pérdida de sus peculiaridades clásicas y de su procedimiento en favor de nuevos recursos hoy en boga. Mas, en tanto existan enfermedades de difícil tratamiento o incurables, la curandería del tipo que sea pervivirá como puerta abierta a la esperanza.Hasierako medikuntza enpirikoak, Aintzinatetik bertatik bi norabide desberdin hartuko zituen: sorginkeriarena alde batetik eta, izaera gero eta zientifikoagoa beretuz, gaurko medikuntza emango duena bestetik. Herri-sendagintza deiturikoa bere alderdi enpiriki eta magikoarekin lehenbizikotik dator. Hiru osagaiok eratzen dute sendagintza-fenomeno unibertsal horren bilbadura: sendatzailea, eria eta sendatzeko metodoak, berauen funtsezko ezaugarriak lan honetan azaldu eta aipatzen direlarik. Aldi berean, haren berezitasun klasikoen galera gero eta nabarmenagoa da, egun harrera hobeagoa duten beste baliabide batzuk ordezkatuz doazelarik. Alabaina, tratamendu zaila duten edo sendaezinak diren eritasunak dauden bitartean, mota bateko zein besteko sasisendagintzak iraun egingo du esperantzari irekitako leiho baten antzera.Primitive medicine, empirical, takes from antiquity two different directions: the sorcery, and the rather scientific direction, which emerges into the present medicine. Practices of so called popular medicine, with its empirical and magic components, derive from the first direction. Three components represent the plot of the universal phenomenon of quackery: the quacker, the patien and the healing methods essential characteristics are explained and commented in this work. It also takes notes of the increasing loss of its traditional peculiarities, and of its position in favour of new resources which are in vogue. But, as long as there are diseases with a difficult treatment or incurable, quackery of any kind will survive, as an open door to hope

Letamendía, Ander. El dedo blanco del pelotari

Recensión bibliográfica de la obra del médico Ander Letamendia "El dedo blanco del pelotari" dedicada al estudio de la lesiones de los pelotaris

Quality assessment of composts officially registered as organic fertilisers in Spain

Composting of organic wastes is a management strategy linked to circular economy models through the transformation of these wastes into an organic product, compost, which can be used as fertiliser, soil amendment or growing media. However, the concept of ‘compost quality' is not enough defined to take a technical decision about which is its best use or application. In the last decade, different guidelines and regulations about organic fertilisers have been developed. For instance, in Spain the Fertilisers Regulation categorises compost under five kinds according to the raw materials used - organic amendment compost (OaC), manure compost (MaC), green compost (GrC), vermicompost (VC), ‘alperujo' compost (AlC) -, and under three quality levels (A, B or C) depending exclusively on the heavy metals content. This work analyses the national database of all composts (307) marketed in Spain, considering the analytical parameters declared, with the objective of proposing a methodology to define a global quality index. For this assessment, two indicators are employed: a fertility indicator, related to the nutrients content, and a clean indicator, related to the heavy metals content. Results show an average compost formulation 2.5:2.5:2.5 (N:P 2 O 5 :K 2 O). MaC and OaC present the highest fertility indicator, whereas VC the lowest. Regarding the clean indicator, GrC, MaC and VC are cleaner than OaC. In the future, this new quality assessment should be completed by including other indicators related to physical and biological characteristic (e.g. porosity, stability/maturity, phytotoxicity) that could determine the most proper use of compost.European Agricultural fund for Rural Development and Rural Development Program of Gobierno de Navarra 2014-2020 (project 'Pilot Project of circular bio-economy of organic wastes at local scale with social and training dimension')

Hydraulic Press Commissioning Cost Reductions via Machine Learning Solutions

Abstract publicado en EUROSIM 2019 Abstract Volume. ARGESIM Report 58, ISBN: 978-3-901608-92-6 (ebook), DOI: 10.11128/arep.58In industrial processes, PI controllers remain as the dominant control technique due to their applicability and performance reliability. However, there could be applications where the PI controller is not enough to fulfill certain specifications, such as in the force control loop of hydraulic presses, in which specific pressure profiles need to be ensured in order not to damage theworkpiece. An Iterative Learning Control scheme is presented as a Machine Learning control alternative to the PI controller, in order to track the pressure profiles required for any operational case. Iterative Learning Control is based on the notion that a system that realizes the same process repeatedly, e.g. hydraulic presses, can improve its performance by learning from previous iterations. The improvements are revealed in high-fidelity simulations of a hydraulic press model, in which the tracking performance of the PI controller is considerably improved in terms of overshoot and the settling time of pressure signal.UPV/EHU, Grupo de Investigación de Inteligencia Computaciona

Hydraulic Press Commissioning Cost Reductions via Machine Learning Solutions

Abstract publicado en EUROSIM 2019 Abstract Volume. ARGESIM Report 58, ISBN: 978-3-901608-92-6 (ebook), DOI: 10.11128/arep.58In industrial processes, PI controllers remain as the dominant control technique due to their applicability and performance reliability. However, there could be applications where the PI controller is not enough to fulfill certain specifications, such as in the force control loop of hydraulic presses, in which specific pressure profiles need to be ensured in order not to damage theworkpiece. An Iterative Learning Control scheme is presented as a Machine Learning control alternative to the PI controller, in order to track the pressure profiles required for any operational case. Iterative Learning Control is based on the notion that a system that realizes the same process repeatedly, e.g. hydraulic presses, can improve its performance by learning from previous iterations. The improvements are revealed in high-fidelity simulations of a hydraulic press model, in which the tracking performance of the PI controller is considerably improved in terms of overshoot and the settling time of pressure signal.UPV/EHU, Grupo de Investigación de Inteligencia Computaciona

la víctima menor de edad en el proceso penal

El objetivo del trabajo es examinar las especialidades y la protección que se le da a la víctima menor en el procedimiento penal, desde el punto de vista del Derecho español. <br /

An Innovative MIMO Iterative Learning Control Approach for the Position Control of a Hydraulic Press

To improve the performance of hydraulic press position control and eliminate the need to manually define control signals, this paper proposes a multi-input-multi-output (MIMO) Iterative Learning Control (ILC) algorithm. The MIMO ILC algorithm design is based on the inversion of the known low frequency dynamics of the hydraulic press, whereas the unknown and uncertain high frequency dynamics are discarded due to their low influence in the learning transient. Moreover, for the MIMO ILC convergence condition, a graphical method is proposed, in which the ILC learning filter eigenvalues are analyzed. This method allows studying the stability and convergence rate of the algorithm intuitively. Theoretical analysis and results prove that with the MIMO ILC algorithm the position control is automated and that high precision in the position tracking is gained. A comparison with other model inverse ILC approaches is carried out and it is shown that the proposed MIMO ILC algorithm outperforms the existing algorithms, reducing the number of iterations required to converge while guaranteeing system stability. Furthermore, experimental results in a hydraulic test rig are presented and compared to those obtained with a conventional PI controllerThis work was supported in part by the Department of Development and Infrastructures of the Government of the Basque Country via Industrial Doctorate Program BIKAINTEK under Grant 20-AF-W2-2018-00015

Iterative Learning Control and Gaussian Process Regression for Hydraulic Cushion Control

In this paper, we investigate on extending a feed-forward control scheme for the force control circuit of a hydraulic cushion with Gaussian Process nonlinear regression and Iterative Learning Control. Gaussian Processes allow the possibility of estimating the unknown proportional valve nonlinearities and provide uncertainty measurements of the predictions. However, the system must realize a high precision tracking control which is not achievable if any uncertainty remains in the estimation. Therefore, an extra feed-forward signal based on Iterative Learning Control is used to obtain a precise and fast force reference tracking performance. The design of the Iterative Learning Control is based on an inverted linearized model in which a fourth-order low-pass filter is included to attenuate the unknown valve dynamics. The low-pass filter is split up into two second-order low-pass filters, one of which is applied in the positive, the other in the negative, direction of time, resulting in zero-phase filtering. Simulation results show that Gaussian Process regression allows the possibility of using feed-forward control and that the force tracking performance is improved by introducing Iterative Learning Control.This work has been partially funded by the Department of Development and Infrastructures of the Government of the Basque Country, via Industrial Doctoral Program BIKAINTEK (Official Bulleting of the Basque Country no 67 on 09/04/1