Early warning system for coffee rust disease based on error correcting output codes: a proposal

Colombian coffee producers have had to face the severe consequences of the coffee rust disease since it was first reported in the country in 1983. Recently, machine learning researchers have tried to predict infection through classifiers such as decision trees, regression Support Vector Ma­chines (SVM), non-deterministic classifiers and Bayesian Networks, but it has been theoretically and empirically demonstrated that combining multiple classifiers can substantially improve the classification perfor­mance of the constituent members. An Early Warning System (EWS) for coffee rust disease was therefore proposed based on Error Correcting Output Codes (ECOC) and SVM to compute the binary functions of Plant Density, Shadow Level, Soil Acidity, Last Nighttime Rainfall Intensity and Last Days Relative Humidity.Los productores de café colombianos han sufrido severas consecuencias por la Roya desde que fue reportada por primera vez en el país en el año 1983. Recientemente, investigadores de aprendizaje automático han intentado predecir la roya a través de clasificadores como: arboles de de­cisión, máquinas de vector de soporte, clasificadores no determinísticos y redes bayesianas, pero se ha demostrado teórica y empíricamente que la combinación de múltiples clasificadores puede mejorar sustancialmente el rendimiento en la clasificación. En este sentido es propuesto un sistema de alerta temprana para la roya en el café, basado en códigos de salida de corrección de error y máquinas de vector de soporte para calcular las funciones binarias de la densidad de planta, el nivel de sombra, la acidez del suelo, la intensidad de lluvia en la última noche, y en últimos días, con humedad relativa

Sistema de alerta temprana para la roya en el café basado en códigos de salida de corrección de error: una propuesta

Colombian coffee producers have had to face the severe consequences of the coffee rust disease since it was first reported in the country in 1983. Recently, machine learning researchers have tried to predict infection through classifiers such as decision trees, regression Support Vector Ma­chines (SVM), non-deterministic classifiers and Bayesian Networks, but it has been theoretically and empirically demonstrated that combining multiple classifiers can substantially improve the classification perfor­mance of the constituent members. An Early Warning System (EWS) for coffee rust disease was therefore proposed based on Error Correcting Output Codes (ECOC) and SVM to compute the binary functions of Plant Density, Shadow Level, Soil Acidity, Last Nighttime Rainfall Intensity and Last Days Relative Humidity.Los productores de café colombianos han sufrido severas consecuencias por la Roya desde que fue reportada por primera vez en el país en el año 1983. Recientemente, investigadores de aprendizaje automático han intentado predecir la roya a través de clasificadores como: arboles de de­cisión, máquinas de vector de soporte, clasificadores no determinísticos y redes bayesianas, pero se ha demostrado teórica y empíricamente que la combinación de múltiples clasificadores puede mejorar sustancialmente el rendimiento en la clasificación. En este sentido es propuesto un sistema de alerta temprana para la roya en el café, basado en códigos de salida de corrección de error y máquinas de vector de soporte para calcular las funciones binarias de la densidad de planta, el nivel de sombra, la acidez del suelo, la intensidad de lluvia en la última noche, y en últimos días, con humedad relativa

Parto y distocias en la perra y en la gata

El conocimiento de la fisiología normal del parto, eutocia, resulta indispensable para reconocer y, por lo tanto, establecer un adecuado plan de actuación clínica ante un parto patológico o distócico. En la primera parte de este artículo revisamos los mecanismos del parto en la perra y en la gata poniendo especial interés en aquellos aspectos de mayor trascendencia clínica; posteriormente estudiamos el parto patológico, su diagnóstico y las técnicas obstétricas que debemos emplear para resolver el problema que plantea un parto distócico en los animales de compañía.An adequate knowledge of the physiological parturition, eutocya, results essential in order to recognize and then establishing an accurate plan of clinicalperformance, to cope with the pathological whelping or dystocia. That's why in the first part of this article the mechanism of parturition in the bitch and the queen are reviewed, watching especiaUythose aspects of clinical significance; after this we study the pathological parturition, its identification and the obstetrical techniques to use in order to get successin the resolution of the trouble that a dystocia in companion animals represents

Neutrino Halos in Clusters of Galaxies and their Weak Lensing Signature

We study whether non-linear gravitational effects of relic neutrinos on the development of clustering and large-scale structure may be observable by weak gravitational lensing. We compute the density profile of relic massive neutrinos in a spherical model of a cluster of galaxies, for several neutrino mass schemes and cluster masses. Relic neutrinos add a small perturbation to the mass profile, making it more extended in the outer parts. In principle, this non-linear neutrino perturbation is detectable in an all-sky weak lensing survey such as EUCLID by averaging the shear profile of a large fraction of the visible massive clusters in the universe, or from its signature in the general weak lensing power spectrum or its cross-spectrum with galaxies. However, correctly modeling the distribution of mass in baryons and cold dark matter and suppressing any systematic errors to the accuracy required for detecting this neutrino perturbation is severely challenging.Comment: 13 pages, 11 figures. Submitted to JCA

Establishing Diagnostic Skills in Novice Bilingual Clinicians: A Scaffolded Approach

This study sought to scaffold administration performance of a standardized bilingual screener to sufficient levels of accuracy for data collection using principles of Cognitive Load Theory by managing task complexity when training pre-service clinicians. Before training administration skills, two students were given copies of the manual for the Bilingual English Spanish Oral Screener (BESOS) and asked to administer the protocol independently. During the intervention phase, students were scaffolded through administration tasks of increasing complexity and given explicit instruction, which included tailored goals, modeling and feedback. Performance for four skills was assessed using a fidelity rubric and analyzed using visual analysis. Performance varied per skill but overall scores were higher during the intervention phases than during the baseline phase for both students. In addition, accuracy of performance maintained across client participants showing patterns of generalization. Although the data are limited, scaffolding training skills for pre-service clinicians appears supportive in training administration skills for bilingual tasks. The level of support may vary per skill and per language. Future research may seek to investigate other clinical skills and tasks

Un nuevo conjunto de datos para la detección de roya en cultivos de café Colombianos basado en clasificadores

Coffee production is the main agricultural activity in Colombia. More than 350.000 Colombian families depend on coffee harvest. Since coffee rust disease was first reported in the country in 1983, these families have had to face severe consequences. Recently, machine learning approaches have built a dataset for monitoring coffee rust incidence that involves weather conditions and physic crop properties. This background encouraged us to build a dataset for coffee rust detection in Colombian crops through data mining process as Cross Industry Standard Process for Data Mining (CRISP-DM). In this paper we define a proper data to generate accurate models; once the dataset is built, this is tested using classifiers as: Support Vector Regression, Backpropagation Neural Networks and Regression Trees.La producción de café es la principal actividad agrícola en Colombia. Más de 350.000 familias colombianas dependen de la cosecha de café. En este sentido, la roya fue reportada por primera vez en el país en 1983, y desde entonces estas familias han tenido que enfrentar graves consecuencias. Recientemente, diversos enfoques basados en aprendizaje automático han construido un conjunto de datos para el monitoreo de la incidencia de la roya del café, teniendo en cuenta las condiciones climáticas y las propiedades físicas de los cultivos. Estas investigaciones motivaron la creación de un conjunto de datos para la detección de la roya en cultivos Colombianos a través del proceso de minería de datos CRISP-DM. En este trabajo se definió un conjunto de datos con el objetivo de generar clasificadores precisos; una vez construido el conjunto de datos, fue probado mediante tres clasificadores: Maquinas de vector de regresión, Redes neuronales con propagación hacia atrás y Árboles de regresión

Etiopathology of chronic tubular, glomerular and renovascular nephropathies: Clinical implications

Chronic kidney disease (CKD) comprises a group of pathologies in which the renal excretory function is chronically compromised. Most, but not all, forms of CKD are progressive and irreversible, pathological syndromes that start silently (i.e. no functional alterations are evident), continue through renal dysfunction and ends up in renal failure. At this point, kidney transplant or dialysis (renal replacement therapy, RRT) becomes necessary to prevent death derived from the inability of the kidneys to cleanse the blood and achieve hydroelectrolytic balance. Worldwide, nearly 1.5 million people need RRT, and the incidence of CKD has increased significantly over the last decades. Diabetes and hypertension are among the leading causes of end stage renal disease, although autoimmunity, renal atherosclerosis, certain infections, drugs and toxins, obstruction of the urinary tract, genetic alterations, and other insults may initiate the disease by damaging the glomerular, tubular, vascular or interstitial compartments of the kidneys. In all cases, CKD eventually compromises all these structures and gives rise to a similar phenotype regardless of etiology. This review describes with an integrative approach the pathophysiological process of tubulointerstitial, glomerular and renovascular diseases, and makes emphasis on the key cellular and molecular events involved. It further analyses the key mechanisms leading to a merging phenotype and pathophysiological scenario as etiologically distinct diseases progress. Finally clinical implications and future experimental and therapeutic perspectives are discussed

New Eruptive YSOs from SPICY and WISE

© Published under Creative Commons license CC BY-SA 4.0.This work presents four high-amplitude variable YSOs (≃3 mag at near-or mid-IR wavelengths) arising from the SPICY catalog. Three outbursts show a duration that is longer than 1 year, and are still ongoing. And additional YSO brightened over the last two epochs of NEOWISE observations and the duration of the outburst is thus unclear. Analysis of the spectra of the four sources confirms them as new members of the eruptive variable class. We find two YSOs that can be firmly classified as bona fide FUors and one object that falls in the V1647 Ori-like class. Given the uncertainty in the duration of its outburst, an additional YSO can only be classified as a candidate FUor. Continued monitoring and follow-up of these particular sources is important to better understand the accretion process of YSOs.Peer reviewe

Potencial Analítico de los Polímeros de Impronta Molecular (MIPs) como Elementos de Reconocimiento Biomimético

Los polímeros de impronta molecular (MIPs) son materiales sintéticos que presentan propiedades de reconocimiento molecular específico hacia determinados compuestos. Estos materiales con “memoria selectiva” presentan un elevado potencial analítico como sustitutos de elementos de reconocimiento de origen biológico para el desarrollo de sensores, como sorbentes en procesos de extracción en fase sólida (SPE) y como fases estacionarias para HPLC y CE. La síntesis de estos materiales se basa en la formación de una estructura polimérica, altamente entrecruzada, alrededor de una molécula que actúa como plantilla que se extrae después de la polimerización. De esta forma, el MIP contendrá sitios de unión que son complementarios a la molécula plantilla en forma, tamaño y distribución de grupos funcionales que permiten su reconocimiento posterior, de forma selectiva Los MIPs suelen presentar ventajas interesantes en comparación con los receptore