Optimización de la predicción de demanda de agua mediante algoritmos neuro-genéticos para un conjunto de datos reducido

La predicción de la demanda de agua es uno de los factores principales en el diseño y gestión de sistemas de abastecimiento y distribución de agua. Recientemente, avanzadas técnicas en inteligencia computacional como las Redes Neuronales Artificiales (RNAs) han sido aplicadas para la predicción de series temporales con importantes resultados. En este trabajo se ha desarrollado una metodología híbrida que combina RNAs y Algoritmos Genéticos multiobjetivo para la predicción a corto plazo de la demanda de agua en una Comunidad de Regantes cuando la disponibilidad de datos es escasa. El modelo fue desarrollado utilizando datos de series temporales del Sector VII de la Zona Regable Bembézar M.D. Tras el proceso de optimización con un algoritmo genético multiobjetivo se obtuvo una RNA de tipo perceptrón multicapa entrenada mediante el algoritmo Regularización Bayesiana con 24 neuronas en la primera capa oculta y 21 en la segunda. El modelo desarrollado fue capaz de explicar el 95 % de la varianza total de los datos observados con un Error Estándar de Predicción del 9.38 % (periodo de test).Ministerio de Economía y Competitivida

New memory-based hybrid model for middle-term water demand forecasting in irrigated areas

The energy demand and their associated costs in pressurized irrigation networks together with water scarcity are currently causing serious challenges for irrigation district’s (ID) managers. Additionally, most of the new water distribution networks in IDs have been designed to be operated on-demand complexing ID managers the daily decision-making process. The knowledge of the water demand several days in advance would facilitate the management of the system and would help to optimize the water use and energy costs. For an efficient management and optimization of the water-energy nexus in IDs, longer term forecasting models are needed. In this work, a new hybrid model (called LSTMHybrid) combining Fuzzy Logic (FL), Genetic Algorithm (GA), LSTM encoder-decoder and dense or full connected neural networks (DNN) for the one-week forecasting of irrigation water demand at ID scale has been developed. LSTMHybrid was developed in Python and applied to a real ID. The optimal input variables for LSTMHydrid were mean temperature (°C), reference evapotranspiration (mm), solar radiation (MJ m−2) and irrigation water demand of the ID (m3) from 1 to 7 days prior to the first day of prediction. The optimal LSTMHybrid model selected consisted of 50 LSTM cells in the encoder submodel, 409 LSTM cells in the decoder submodel and three hidden layers in the DNN submodel with 31, 96 and 128 neurons in each hidden layer, respectively. Thus, LSTMHybrid had a total of 1.5 million parameters, obtaining a representativeness higher than 94 % and an accuracy around of 20 %

Decreased CX3CL1 Levels in the Cerebrospinal Fluid of Patients With Alzheimer’s Disease

Alzheimer’s disease (AD) is a neurodegenerative disease characterized by the presence of neurofibrillary tangles, constituted by tau protein, and plaques formed by amyloid-beta protein. The disease courses with high neural damage, which leads to memory loss and death. Here we analyzed the presence of CX3CL1, a chemokine expressed by neurons, in cerebrospinal fluid (CSF) samples from control subjects and patients with mild cognitive impairment and AD dementia. CX3CL1 was decreased in the CSF of AD dementia patients compared to control subjects. However, there was not difference in plasma samples from the same subjects

REUTIVAR: Model for Precision Fertigation Scheduling for Olive Orchards Using Reclaimed Water

Olive orchard is the most representative and iconic crop in Andalusia (Southern Spain). It is also considered one of the major economic activities of this region. However, due to its extensive growing area, olive orchard is also the most water-demanding crop in the Guadalquivir River Basin. In addition, its fertilization is commonly imprecise, which causes over-fertilization, especially nitrogen. This leads to pollution problems in both soil and water, threating the environment and the system sustainability. This concern is further exacerbated by the use of reclaimed water to irrigate since water is already a nutrient carrier. In this work, a model which determines the real-time irrigation and fertilization scheduling for olive orchard, applying treated wastewater, has been developed. The precision fertigation model considers weather information, both historical and forecast data, soil characteristics, hydraulic characteristics of the system, water allocation, tree nutrient status, and irrigation water quality. As a result, daily information about irrigation time and fertilizer quantity, considering the most susceptible crop stage, is provided. The proposed model showed that by using treated wastewater, additional fertilization was not required, leading to significant environmental benefits but also benefits in the total farm financial costs

Maturation dynamics of the axon initial segment (AIS) of newborn dentate granule cells in young adult C57BL/6J mice

This published version will be available under a Creative Commons Attribution 4.0 International License (CC-BY) after a 6 month periodNewborn dentate granule cells (DGCs) are generated in the hippocampal dentate gyrus (DG) of rodents through a process called adult hippocampal neurogenesis, which is subjected to tight intrinsic and extrinsic regulation. The use of retroviruses encoding fluorescent proteins has allowed the characterization of the maturation dynamics of newborn DGCs, including their morphological development and the establishment and maturation of their afferent and efferent synaptic connections. However, the study of a crucial cellular compartment of these cells, namely, the axon initial segment (AIS), has remained unexplored to date. The AIS is not only the site of action potential initiation, but it also has a unique molecular identity that makes it one of the master regulators of neural plasticity and excitability. Here we examined the dynamics of AIS formation in newborn DGCs of young female adult C57BL/6J mice in vivo. Our data reveal notable changes in AIS length and thickness throughout cell maturation under physiological conditions and show that the most remarkable structural changes coincide with periods of intense morphological and functional remodeling. Moreover, we demonstrate that AIS development can be modulated extrinsically by both neuroprotective (environmental enrichment) and detrimental (lipopolysaccharide from Escherichia coli) stimuliThis work was supported by the Spanish Ministry of Economy and Competitiveness SAF-2017-82185-R and RYC-2015-171899 to M.L.-M. and SAF-2014-53040-P to J.Á., Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas to J.Á., Alzheimer's Association 2015-NIRG-340709 and AARG-17-528125 to M.L.-M., Association for Frontotemporal Degeneration 2016 Basic Science Pilot Grant Award to M.L.-M., and Fundación Ramón Areces and Banco de Santander to the Centro de Biología Molecular Severo Ochoa Institutional Grant

Reducing the energy demand in irrigation water supply systems. Experiences from southern Europe

In recent years, many modernization processes have been undertaken in irrigation districts with a view to improving water use efficiency. In southern Spain, many irrigation districts have either been modernized or are currently being upgraded. However, as part of the modernization process some unexpected side effects have been observed. This paper analyzes the relative advantages and limitations of modernization based on field data collected in a typical Andalusian irrigation district. Although the amount of water diverted for irrigation to farms has been considerably reduced, consumptive use has increased. The costs for operation and system maintenance have dramatically risen (400%), as the energy for pumping water is much higher now compared to the gravity fed systems used previously. Then a regional analysis of the relationship between energy requirements and irrigation water applied in ten irrigation districts, in Southern Spain, has been carried out. Results show that 1000 kWh ha–1 is the energy required to apply an average depth of 2590 m3 ha-1. Finally, energy saving options are identified and discussed

EnjoyYourLAB: a mobile application that supports the lecturing in the Hydraulics laboratories (Phase II)

EnjoyYourLAB es una aplicación móvil (APP) de apoyo a la docencia de las prácticas de laboratorio de Ingeniería Hidráulica. En esta segunda fase se ha depurado la aplicación y se ha completado con la incorporación de la recreación virtual del laboratorio de la Escuela Politécnica Superior de Belmez y con la edición de los vídeos de las prácticas de laboratorio. Se han editado vídeos docentes de las prácticas de laboratorio referentes a medida de presiones y aforo de caudales, pérdidas de carga en tuberías y singularidades, determinación de la curva característica de una bomba y punto de funcionamiento, régimen uniforme y gradualmente variado en canales abiertos y determinación de las fuerzas de empuje sobre superficies planas sumergidas. A través de la App los alumnos tendrán acceso a la plataforma Moodle, a las memorias de prácticas, material audiovisual e información técnica de los distintos dispositivos empleados. A través de esta herramienta los estudiantes tendrán disponible un mayor nivel de información, que podrán consultar y visualizar tantas veces cómo deseen lo que contribuirá a la solidez del conocimiento adquirido.EnjoyYourLAB is a mobile application that supports the practical lessons in the hydraulics laboratory. In the second phase, the App has been updated with a virtual rendering of the Lab at the Advanced Polytechnic School of Belmez and with the edited videos of the practical sessions. The videos edited are about the pressure and flow measurements, head losses in pressurized pipes, characteristics curves of a pump, steady and variable flow in open channels, and the estimation of the hydrostatic forces in submerged surfaces Also students have access to the moodle platform, guidelines for the practical exercises, audios, and technical information. Through this tool the students have access to a higher level of data, which can check at any time, and the number of time required to improve the robustness of the acquired knowledge

Middleware to Operate Smart Photovoltaic Irrigation Systems in Real Time

Climate change, water scarcity and higher energy requirements and electric tariff compromises the continuity of the irrigated agriculture. Precision agriculture (PA) or renewable energy sources which are based on communication and information technologies and a large amount of data are key to ensuring this economic activity and guaranteeing food security at the global level. Several works which are based on the use of PA and renewable energy sources have been developed in order to optimize different variables of irrigated agriculture such as irrigation scheduling. However, the large amount of technologies and sensors that these models need to be implemented are still far from being easily accessible and usable by farmers. In this way, a middleware called Real time Smart Solar Irrigation Manager (RESSIM) has been developed in this work and implemented in MATLABTM with the aim to provide to farmers a user-friendly tool for the daily making decision process of irrigation scheduling using a smart photovoltaic irrigation management module. RESSIM middleware was successfully tested in a real field during a full irrigation season of olive trees using a real smart photovoltaic irrigation system

Optical constants of evaporation-deposited silicon monoxide films in the 7.1-800 eV photon energy range

8 págs.; 11 figs.The transmittance of silicon monoxide films prepared by thermal evaporation was measured from 7.1 to 800 eV and used to determine the optical constants of the material. SiO films deposited onto C-coated microgrids in ultrahigh vacuum conditions were measured in situ from 7.1 to 23.1 eV. Grid-supported SiO films deposited in high vacuum conditions were characterized ex situ from 28.5 to 800 eV. At each photon energy, transmittance, and thickness data were used to calculate the extinction coefficient k. The obtained k values combined with data from the literature, and with interpolations and extrapolations in the rest of the electromagnetic spectrum provided a complete set of k values that was used in a Kramers-Kronig analysis to obtain the real part of the index of refraction, n. Two different sum-rule tests were performed that indicated good consistency of the data. © 2009 American Institute of Physics.This work was supported by the National Programme for Space Research, Subdirección General de Proyectos de Investigación, Ministerio de Ciencia y Tecnología, Project Nos. ESP2002-01391 and ESP2005-02650. This work was also performed under the auspices of the U.S. Department of Energy by the University of California Lawrence Berkeley National Laboratory under Contract No. DE-AC03-76F00098 and by the University of California Lawrence Livermore National Laboratory under Contract No. DE-AC52- 07NA27344. M.F.-P. is thankful to Consejo Superior de Investigaciones Científicas Spain for funding under the Programa I3P Contract No. I3P-BPD2004, partially supported by the European Social Fund. M.V.-D. acknowledges financial support from a FPI Contract No. BES-2006-14047 fellowship.Peer Reviewe

EnjoyYourLAB: a mobile APP that supports the practical seasons in the Hydraulic Laboratories

EnjoyYourLAB es una aplicación móvil (APP)de apoyo a la docencia de las prácticas de laboratorio de Ingeniería Hidráulica La aplicación integra una recreación virtual de los laboratorios así como de los principales equipos que lo constituyen. A través de la App los alumnos tendrán acceso a la plataforma moodle, a las memorias de prácticas, material audiovisual e información técnica.EnjoyYourLAB is a mobile application that supports the practical seasons in the hydraulics laboratory. The App consists in a virtual rendering of the Lab and the main devices. Also, students have access to the moodle platform, guidelines for the practical exercises, audios, and technical information