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

Caracterización morfológica, textural y composicional de las partículas de oro reveladas en placeres marinos de las playas Mejías y Jiguaní (NE de Cuba Oriental)

En este trabajo se describen los principales rasgos morfológicos, texturales y composicionales de las partículas de oro presentes en los placeres marinos costeros de las playas Mejías y Jiguaní, Cuba. Las partículas de oro estudiadas en ambos depósitos, son muy finas, mostrando formas tabulares predominantes; en ocasiones aparecen muy aplastadas, formando especies de laminillas o hojuelas, observándose, a través de las imágenes de electrones etrodispersados,partículas con texturas internas muy complejas , así como cariado de los granos. Las partículas están compuestas por subgranos de composición diferente,correspondientes a aleaciones naturales de Electrum, oro nativo y oro mercurial en ambos placeres y aleaciones de Au-Cu (tetraauricuprido) en el Placer Jiguaní. Estos subgranos frecuentemente se encuentran alterados en sus bordes. Esta alteración consiste predominantemente en un enriquecimiento en oro con relación a la plata

Watershed level analysis of sediment filling in a Mexican highland reservoir

The Upper Lerma River Basin (ULRB) in Mexico, with a watershed area of 2118 km2, is strongly affected by urbanization and deforestation. More than 1.5 million people and more than 2000 industries are located within it (INEGI, 2000). Furthermore, the basin topography is abrupt with levels ranging from 2560 to 4570 m.a.s.l. and its precipitation varies from 700 mm in the lower basin to 1200 mm at higher levels. The erosion produced by climactic and anthropic effects is concentrated in the José Antonio Alzate Reservoir, which is located at the basin outlet and captures all the waters of the ULRB. The basin, which had an initial capacity of 45 hm3, has lost much of its capacity in only 42 years as is demonstrated here. Presented in this paper are the results from an erosion model using the RUSLE (Revised Universal Soil Loss Equation) methodology, which allows for the identification of critical areas. The resulting model is capable of explaining the high rate of sediment contribution. With the intention of validating the model, a bathymetric study of the reservoir was performed. .Actual bottom reservoir levels were compared with the levels before dam construction. This process was made with a GIS using a re-sampling process. The results show that reservoir storage capacity has been reduced by 21 hm3 which makes difficult the irrigation and flood control functions of the reservoir. Selective removal of sediments will lead to benefits in pollutant removal in the reservoir and improved capacity for downstream irrigation supply and flood control.La cuenca Alta del río Lerma (CARL) en el Estado de México con una extensión de 2118 km2, se encuentra fuertemente afectada por la urbanización y la deforestación. En efecto, allí se asientan más de 1.5 millones de habitantes y más de 2000 industrias (INEGI, 2000). Adicionalmente la topografía de la cuenca es bastante abrupta con elevaciones desde 4570 m.s.n.m. hasta 2560 m.s.n.m. y su régimen pluvial varía de promedios anuales en las zonas altas de 1200 mm a 700 mm en las zonas bajas. La erosión producida por efectos climáticos y antrópicos se refleja en el embalse José Antonio Alzate el primero sobre el río Lerma y que capta todas las aguas de la CARL. El embalse con un capacidad de almacenamiento al construirse de 45 hm3 ha perdido mucha capacidad en tan solo 42 años de vida como se demuestra en este trabajo. Se presentan los resultados de un modelo de erosión de la cuenca utilizando el método RUSLE, lo cual permitió identificar las áreas críticas. El modelo resultante es capaz de explicar la alta tasa de aporte de sedimentos. Con el fin de validar el modelo se efectuó un levantamiento batimétrico del embalse. La topografía actual se comparó con la existente antes de la construcción de la cortina. Este proceso de acoplamiento fue realizado en un SIG con base en un proceso de remuestreo. Los resultados muestran una reducción en la capacidad del embalse de 21 hm3 lo cual le impide cumplir adecuadamente con sus funciones de irrigación y control de inundaciones. Una remoción selectiva de sedimentos es propuesta en este artículo procurando incrementar la eficiencia de remoción de contaminantes del embalse y la capacidad para el control de inundaciones y suministro de agua para irrigación

A comparative study of supports for the synthesis of oligonucleotides without using ammonia

A comparative study of the cleavage efficiency of succinyl, phthaloyl, oxalyl, 2(2-nitrophenyl)ethyl, 9-fluorenylmethyl, and 2-nitrobenzyl supports in 0.5M DBU solutions is described. A decrease in cleavage efficiency is observed when small oligonucleotides containing thymidine are linked to the supports. In these conditions oxalyl supports gave the best yields followed by 2-(2-nitrophenyl)ethyl and 9-fluorenylmethyl supports.We are grateful to CICYT (PB92-0043) and E.E.C.C. Biomedicine and Health Programme (BMH1-CT93-1669) for financial support. We thank Drs. Matthias Mann, Gitte Neubauer, Matthias Wilm (EMBL) and Irene Fernández (University of Barcelona) for obtaining mass spectra.Peer reviewe

Relaxation properties in a lattice gas model with asymmetrical particles

We study the relaxation process in a two-dimensional lattice gas model, where the interactions come from the excluded volume. In this model particles have three arms with an asymmetrical shape, which results in geometrical frustration that inhibits full packing. A dynamical crossover is found at the arm percolation of the particles, from a dynamical behavior characterized by a single step relaxation above the transition, to a two-step decay below it. Relaxation functions of the self-part of density fluctuations are well fitted by a stretched exponential form, with a $\beta$ exponent decreasing when the temperature is lowered until the percolation transition is reached, and constant below it. The structural arrest of the model seems to happen only at the maximum density of the model, where both the inverse diffusivity and the relaxation time of density fluctuations diverge with a power law. The dynamical non linear susceptibility, defined as the fluctuations of the self-overlap autocorrelation, exhibits a peak at some characteristic time, which seems to diverge at the maximum density as well.Comment: 7 pages and 9 figure

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 %

Reflectarray antennas for dual polarization and broadband telecom satellite applications

A reflectarray antenna with improved performance is proposed to operate in dual-polarization and transmit-receive frequencies in Ku-band for broadcast satellite applications. The reflectarray element contains two orthogonal sets of four coplanar parallel dipoles printed on two surfaces, each set combining lateral and broadside coupling. A 40-cm prototype has been designed, manufactured, and tested. The lengths of the coupled dipoles in the reflectarray cells have been optimized to produce a collimated beam in dual polarization in the transmit and receive bands. The measured radiation patterns confirm the high performance of the antenna in terms of bandwidth (27%), low losses, and low levels of cross polarization. Some preliminary simulations at 11.95 GHz for a 1.2-m antenna with South American coverage are presented to show the potential of the proposed antenna for spaceborne antennas in Ku-band

New CMOS VLSI Linear Self-Timed Architectures

The implementation of digital signal processor circuits via self-timed techniques is currently a valid altemative to solve some problems encountered in synchronous VLSI circuits. However; a main difference between synchronous and asynchronous circuits is the hardware resources needed to implement asynchronous circuits. This communication presents four less-costly alternatives to a previously reported linear selftimed architecture, and their application in the design of FIFO memories. Furthermore, the integration and characterization in the laboratory of prototypes of these FIFOs are presented

MeSH indexing based on automatically generated summaries

BACKGROUND: MEDLINE citations are manually indexed at the U.S. National Library of Medicine (NLM) using as reference the Medical Subject Headings (MeSH) controlled vocabulary. For this task, the human indexers read the full text of the article. Due to the growth of MEDLINE, the NLM Indexing Initiative explores indexing methodologies that can support the task of the indexers. Medical Text Indexer (MTI) is a tool developed by the NLM Indexing Initiative to provide MeSH indexing recommendations to indexers. Currently, the input to MTI is MEDLINE citations, title and abstract only. Previous work has shown that using full text as input to MTI increases recall, but decreases precision sharply. We propose using summaries generated automatically from the full text for the input to MTI to use in the task of suggesting MeSH headings to indexers. Summaries distill the most salient information from the full text, which might increase the coverage of automatic indexing approaches based on MEDLINE. We hypothesize that if the results were good enough, manual indexers could possibly use automatic summaries instead of the full texts, along with the recommendations of MTI, to speed up the process while maintaining high quality of indexing results. RESULTS: We have generated summaries of different lengths using two different summarizers, and evaluated the MTI indexing on the summaries using different algorithms: MTI, individual MTI components, and machine learning. The results are compared to those of full text articles and MEDLINE citations. Our results show that automatically generated summaries achieve similar recall but higher precision compared to full text articles. Compared to MEDLINE citations, summaries achieve higher recall but lower precision. CONCLUSIONS: Our results show that automatic summaries produce better indexing than full text articles. Summaries produce similar recall to full text but much better precision, which seems to indicate that automatic summaries can efficiently capture the most important contents within the original articles. The combination of MEDLINE citations and automatically generated summaries could improve the recommendations suggested by MTI. On the other hand, indexing performance might be dependent on the MeSH heading being indexed. Summarization techniques could thus be considered as a feature selection algorithm that might have to be tuned individually for each MeSH heading