Aplicación de un modelo de aprendizaje supervisado para analizar el comportamiento de variables medioambientales en un cultivo de café

Context: The collection and storage of data on environmental variables in a coffee crop, through wireless sensor networks allow the transformation of said data and the application of a supervised learning model to establish its behavior. Method: For the present work, an architecture of 3 wireless sensor nodes was developed. Each node consists of a Lucy3 programmable card, to which the temperature, environmental humidity, and soil moisture sensors were connected. The measurement terrain is located in El Cortijo coffee farm. Measurements were made over a period of two weeks, three hours a day, sending the information from the nodes described above to a gateway that then transmitted the information to a base station. Finally, the data was loaded on an online platform for transformation and predictive analytics through a supervised learning model. Results: The tests allowed demonstrating the effectiveness of the design of the wireless network in the collection and transmission of data. It was later found that the application of the supervised learning model through the analysis of classification with decision trees allowed predicting the behavior of the variables, which were evaluated in specific time frames and conditions. Conclusions: By applying predictive models, the conditions of the crop can be improved, allowing the yield of the analyzed variables to be optimized, thus minimizing the loss of resources and improving the efficiency of processes such as sowing and harvesting the grain.Contexto: La recolección y almacenamiento de datos sobre variables medioambientales en un cultivo de café mediante el uso de redes inalámbricas de sensores permiten transformar dichos datos y aplicar un modelo de aprendizaje supervisado para establecer su comportamiento. Método: Para el presente trabajo, se desarrolló una arquitectura con 3 nodos sensores inalámbricos. Cada uno consistía en una tarjeta programable Lucy3, a la cual se conectaron sensores de temperatura, humedad ambiental y humedad del suelo. El terreno de medición se encuentra ubicado en la finca de café El Cortijo, y las mediciones se realizaron durante un período de dos semanas, tres horas al día, enviando la información de los nodos descritos anteriormente a un Gateway que luego transmitió la información a una estación base. Finalmente, los datos se cargaron en una plataforma en línea para transformación y análisis predictivo a través de un modelo de aprendizaje supervisado. Resultados: Las pruebas realizadas permitieron demostrar la efectividad del diseño de la red inalámbrica en la recolección y transmisión de datos. Además se encontró que la aplicación del modelo de aprendizaje supervisado a través del análisis de clasificación con árboles de decisión permitió predecir el comportamiento de las variables evaluadas en plazos y condiciones específicas. Conclusiones: Mediante la aplicación de modelos predictivos se pueden mejorar las condiciones del cultivo, lo que permite optimizar el rendimiento de las variables analizadas, minimizar la pérdida de recursos y mejorar la eficiencia de procesos como la siembra y la cosecha del grano

Application of the Internet of Things through a Network of Wireless Sensors in a Coffee Crop for Monitoring and Control its Environmental Variables

En este artículo se presenta la aplicación del Internet de las cosas (IoT), como herramienta tecnológica para el desarrollo de una red inalámbrica de sensores, con el objetivo de monitorear y controlar una serie de variables ambientales que inciden en el cultivo del café y su calidad final. Se procedió al diseño lógico y físico de la red y sus dispositivos, se configuró la red de sensores en un terreno determinado y se procedió a recolectar la información de ciertas variables ambientales, para ser comparadas con una serie de parámetros ya establecidos, que permitirán al caficultor observar el comportamiento de dichas variables a través del tiempo y establecer la generación de alertas o advertencias cuando estas medidas se encuentran por fuera de los rangos establecidos. Una vez desarrollado el estudio se pudo determinar que el manejo del cultivo del café es bastante complejo, debido a la gran cantidad de variedades que se encuentran, el terreno y las variables de tipo ambiental que afectan el proceso de producción y la calidad final del grano. Además, se determinó que el desarrollo e implementación de redes inalámbricas de sensores es posible hoy en día por factores como la reducción de los costos de los dispositivos y el uso de software de código abierto, evitándose valores de licenciamiento adicionales. Finalmente, con base en los parámetros analizados, se pudo establecer que uno de los principales problemas en los cultivos de café es la humedad intensa, que en la práctica puede llegar a afectar el rendimiento de los sensores y sus mediciones.This article presents the application of the Internet of things (IoT), as a technological tool for the development of a wireless sensor network with the aim of monitoring and controlling a series of environmental variables affecting the cultivation of coffee and its final quality. The logical and physical design of the network and its devices was carried out, the sensors network was configured in a given field and the information of certain environmental variables was collected to be compared with a series of parameters already established. This procedure will allow the coffee growers to observe the behavior of these variables over time and set the generation of alerts or warnings when these measures are outside the established ranges. The study determined that the management of coffee cultivation is quite complex due to the large number of varieties found, the terrain and environmental variables affecting the production process and the final quality of the grain. It was also determined that the development and implementation of wireless sensor networks is possible today due to factors such as the reduction of device costs and the use of open source software, avoiding additional licensing values. Finally, based on the parameters analyzed, it was possible to establish that one of the main problems in coffee crops is the intense humidity that, in practice, can affect the performance of the sensors and their measurements

Aortic calcification and femoral bone density are independently associated with left ventricular mass in patients with chronic kidney disease

Background Vascular calcification and reduced bone density are prevalent in chronic kidney disease and linked to increased cardiovascular risk. The mechanism is unknown. We assessed the relationship between vascular calcification, femoral bone density and left ventricular mass in patients with stage 3 non-diabetic chronic kidney disease in a cross-sectional observational study. Methodology and Principal Findings A total of 120 patients were recruited (54% male, mean age 55±14 years, mean glomerular filtration rate 50±13 ml/min/1.73 m2). Abdominal aortic calcification was assessed using lateral lumbar spine radiography and was present in 48%. Mean femoral Z-score measured using dual energy x-ray absorptiometry was 0.60±1.06. Cardiovascular magnetic resonance imaging was used to determine left ventricular mass. One patient had left ventricular hypertrophy. Subjects with aortic calcification had higher left ventricular mass compared to those without (56±16 vs. 48±12 g/m2, P = 0.002), as did patients with femoral Z-scores below zero (56±15 vs. 49±13 g/m2, P = 0.01). In univariate analysis presence of aortic calcification correlated with left ventricular mass (r = 0.32, P = 0.001); mean femoral Z-score inversely correlated with left ventricular mass (r = −0.28, P = 0.004). In a multivariate regression model that included presence of aortic calcification, mean femoral Z-score, gender and 24-hour systolic blood pressure, 46% of the variability in left ventricular mass was explained (P<0.001). Conclusions In patients with stage 3 non-diabetic chronic kidney disease, lower mean femoral Z-score and presence of aortic calcification are independently associated with increased left ventricular mass. Further research exploring the pathophysiology that underlies these relationships is warranted

Prevalence and trajectories of depressive symptoms in mothers of children with newly diagnosed epilepsy

Purpose: To examine the prevalence, trajectories, and predictors of depressive symptoms (DS) in mothers of children with new-onset epilepsy. Methods: A sample of 339 mothers was analyzed from the health-related quality of life in children with epilepsy study assessed four times during the first 24 months after diagnosis. Mothers\u27 DS were measured using the Center for Epidemiological Studies Depression Scale. Trajectories of DS were investigated using group-based trajectory modeling, and maternal, child, and family factors were compared across groups using analysis of variance (ANOVA) and chi square tests. Multinomial logistic regression identified predictors of DS trajectories. Key Findings: A total of 258 mothers completed the study. Prevalence of depression ranged from 30-38% across four times within the first 24 months after their child\u27s diagnosis. Four trajectories of DS were observed: low stable (59%), borderline (25%), moderate increasing (9%), and high decreasing (7%). Using the low stable group as the reference group, the borderline group was younger, had worse family functioning, and fewer family resources; the moderate increasing group was younger, had children with cognitive problems, worse family functioning, and more family demands; and the high decreasing group had less education and children with lower quality of life. Significance: Risk for clinical depression is common among mothers of children with new-onset epilepsy. These mothers are not homogenous, but consist of groups with different trajectories and predictors of DS. Child\u27s cognitive problems was the strongest predictor identified; epilepsy severity did not predict DS trajectory. Health care professionals should consider routinely assessing maternal depression during clinic visits for pediatric epilepsy. © 2010 International League Against Epilepsy

The impact of maternal depressive symptoms on health-related quality of life in children with epilepsy: A prospective study of family environment as mediators and moderators

Purpose: To examine the impact of maternal depressive symptoms (DS) on health-related quality of life (HRQL) in children with new-onset epilepsy and to identify family factors that moderate and mediate this relationship during the first 24 months after epilepsy diagnosis. Methods: A sample of 339 mother-child dyads recruited from pediatric neurologists across Canada in the Health-related Quality of Life in Children with Epilepsy Study. Mothers\u27 and neurologists\u27 reports were collected at four times during the 24-month follow-up. Mothers\u27 DS were measured using the Center for Epidemiological Studies Depression Scale (CES-D) and children\u27s HRQL using the Quality of Life in Childhood Epilepsy (QOLCE). Data were modeled using individual growth curve modeling. Key Findings: Maternal DS were observed to have a negative impact on QOLCE scores at 24 months (β = -0.47, p \u3c 0.0001) and the rate of change in QOLCE scores during follow-up (β = -0.04, p = 0.0250). This relationship was moderated by family resources (β = 0.25, p = 0.0243), and the magnitude of moderation varied over time (β = 0.09, p = 0.0212). Family functioning and demands partially mediated the impact of maternal DS on child HRQL (β = -0.07, p = 0.0007; β = -0.12, p = 0.0006). Significance: Maternal DS negatively impact child HRQL in new-onset epilepsy during the first 24 months after diagnosis. This relationship is moderated by family resources and mediated by family functioning and demands. By adopting family centered approaches, health care professionals may be able to intervene at the maternal or family level to promote more positive outcomes in children. © 2010 International League Against Epilepsy

Settlement response of fibre reinforced railway ballast

Ballasted track is the prevalent track form worldwide and with good design and maintenance can satisfy high performance demands including those of high speed lines. However, increasingly onerous loading is being placed on existing ballasted track networks in many parts of the world by more frequent, longer, faster and heavier trains. This leads to reduced windows of time for maintenance activities while simultaneously increasing maintenance needs. Therefore there are potential advantages if ballasted track could be modified to increase durability both in terms of intervals between maintenance interventions, e.g. tamping, and overall life cycle. This paper presents an assessment of the potential for randomly reinforced ballast, a mixture of ballast and fibres of selected dimensions and properties, to increase the durability of railway track. Compared with other types of reinforcement, fibres have potential advantages of: isotropy (avoiding the formation of weak planes); the possibility of using recycled plastic material; and expected compatibility with normal maintenance procedures. A series of full size tests has been conducted in the Southampton Railway Testing Facility (SRTF) to evaluate the resilient and plastic response of reinforced ballast to vertical cyclic loading. The testing apparatus represents a slice of single track extended to the shoulders and including one sleeper. A vertical load, representing a 20 tonne train axle, was applied by a hydraulic actuator with a frequency of 3Hz to 3 million cycles. Tests carried out thus far demonstrate the importance of selecting an appropriate fibre width as a function of the average particle size of the ballast to be reinforced. Appropriately selected fibres are shown to reduce ballast vertical permanent deformations by about 25%

Disponibilidad léxica en estudiantes bogotanos

This paper shows some results of the research Léxico disponible en estudiantes bogotanos carried out by the Universidad Pedagógica Nacional and the Instituto Caro y Cuervo. First, the methodological approach and some basic concepts (i.e. frequent vocabulary, available vocabulary and lexical availability index) of the research are developed. Then, the quantitative results are linked to the lexical productivity and lexical richness of the individuals. Finally, it is explained how lexical availability index determines the lexical cohesion of the interest focus.Este artículo presenta la investigación realizada por la Universidad Pedagógica Nacional y el Instituto Caro y Cuervo sobre el léxico disponible en estudiantes bogotanos. Primero se desarrollan el enfoque metodológico y algunos conceptos básicos (por ejemplo, léxico frecuente, léxico disponible e índice de disponibilidad léxica). En seguida se explica la relación entre los resultados cuantitativos y la productividad y la riqueza léxicas de los sujetos. Finalmente, se describe cómo la disponibilidad léxica determina la cohesión léxica de los centros de interés