New clues to organ size control in plants

A review of the mechanisms that control organ size in plants

Approx-SMOTE: Fast SMOTE for Big Data on Apache Spark

One of the main goals of Big Data research, is to find new data mining methods that are able to process large amounts of data in acceptable times. In Big Data classification, as in traditional classification, class imbalance is a common problem that must be addressed, in the case of Big Data also looking for a solution that can be applied in an acceptable execution time. In this paper we present Approx-SMOTE, a parallel implementation of the SMOTE algorithm for the Apache Spark framework. The key difference with the original SMOTE, besides parallelism, is that it uses an approximated version of k-Nearest Neighbor which makes it highly scalable. Although an implementation of SMOTE for Big Data already exists (SMOTE-BD), it uses an exact Nearest Neighbor search, which does not make it entirely scalable. Approx-SMOTE on the other hand is able to achieve up to 30 times faster run times without sacrificing the improved classification performance offered by the original SMOTE.“La Caixa” Foundation, under agreement LCF/PR/PR18/51130007. This work was supported by the Junta de Castilla y León under project BU055P20 and by the Ministry of Science and Innovation of Spain under project PID2020-119894 GB-I00, co-financed through European Union FEDER funds. It also was supported through Consejería de Educación of the Junta de Castilla y León and the European Social Fund through a pre-doctoral grant (EDU/1100/2017). This material is based upon work supported by Google Cloud

Monitorización de la actividad y rendimiento de los alumnos en Moodle para su análisis visual

La enseñanza en plataformas de aprendizaje en línea exige a los docentes analizar la actividad y rendimiento de los estudiantes sobre los objetos de aprendizaje del curso. Todos los entornos virtuales de aprendizaje implementan un módulo que permite recoger esta información. Pero estos datos en crudo necesitan ser procesados para facilitar el análisis del aprendizaje y ayudar al docente en la toma de decisiones en su proceso de enseñanza. En este trabajo se presenta una nueva aplicación de escritorio que accede a los registros y calificaciones de los estudiantes de una instancia de Moodle, permitiendo la monitorización de su actividad y rendimiento. La aplicación organiza y resume dichos datos, incluyendo su análisis visual desde distintas perspectivas. La aplicación, de código abierto y libre uso, ha sido validada institucionalmente a través del instituto de formación del profesorado, sobre un grupo de profesores con docencia reglada en modalidad en línea y presencial. Como resultado final, se describe su uso, analizando con casos de usos reales cómo ayudar a mejorar la enseñanza. Abordamos problemas como la detección de abandono, la comparación de la actividad entre estudiantes, la comprobación de calidad de las actividades o la secuencia de aprendizaje que siguen los estudiantes.Teaching on online learning platforms requires teachers to analyze student activity and performance on course learning objects. All virtual learning environments implement a module to collect this information. But this raw data needs to be processed to facilitate the analysis of learning and help the teacher in making decisions in his or her teaching process. In this paper we present a new desktop application that accesses the records and grades of students in a Moodle instance, allowing the monitoring of their activity and performance. The application organizes and summarizes this data, including its visual analysis from different perspectives. The application, which is open source and free to use, has been institutionally validated through the teacher training institute, on a group of teachers with formal online and face-to-face teaching. As a final result, its use is described, analyzing with real use cases how to help improve teaching. We address issues such as detecting dropouts, comparing activity among students, checking the quality of activities or the learning sequence that students follow.Este trabajo ha sido posible gracias a las ayudas concedidas por la Consejería de Educación de la Junta de Castilla y León a la Universidad de Burgos (OL-2018-01) para el apoyo al desarrollo de la formación on-line cofinanciadas por el Fondo Europeo de Desarrollo Regional

A domestication-associated gene, CsLH, encodes a phytochrome B protein that regulates hypocotyl elongation in cucumber

Plant height is an important agronomic trait; tall plants are prone to collapse (lodging) and are unsuitable for high-density planting (Li et al., 2020). During the Green Revolution, a multitude of genes acting as core or peripheral regulators of plant height were identified and used in breeding (Eshed and Lippman, 2019); however, most were reported in cereal crop plants (Eshed and Lippman, 2019) and few have been characterized in the Cucurbitaceae, which are economically important horticultural plants cultivated worldwide. Here, we describe LONG HYPOCOTYL (CsLH), encoding the photoreceptor phytochrome B (PHYB), which we show has been subjected to selection during cucumber (Cucumis sativus L.) domestication.info:eu-repo/semantics/publishedVersio

Missing data imputation of solar radiation data under different atmospheric conditions

[Abstract] Global solar broadband irradiance on a planar surface is measured at weather stations by pyranometers. In the case of the present research, solar radiation values from nine meteorological stations of the MeteoGalicia real-time observational network, captured and stored every ten minutes, are considered. In this kind of record, the lack of data and/or the presence of wrong values adversely affects any time series study. Consequently, when this occurs, a data imputation process must be performed in order to replace missing data with estimated values. This paper aims to evaluate the multivariate imputation of ten-minute scale data by means of the chained equations method (MICE). This method allows the network itself to impute the missing or wrong data of a solar radiation sensor, by using either all or just a group of the measurements of the remaining sensors. Very good results have been obtained with the MICE method in comparison with other methods employed in this field such as Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR). The average RMSE value of the predictions for the MICE algorithm was 13.37% while that for the MLR it was 28.19%, and 31.68% for the IDW.Ministerio de Economía y Competitividad; AYA2010-1851

Seguimiento de la actividad y abandono en Moodle mediante la aplicación UBUMonitor

Teaching with online learning platforms should simplify the monitoring of students’ activity, particularly when evaluating student dropout. Popular learning environments such as Moodle should implement visual analytic tools that facilitate such tasks, nevertheless, institutions are usually reluctant to incorporate them. This paper presents UBUMonitor, a desktop application that allows the visualization of student’s activity data, extended as a proof of concept with a module for dropout tracking. Therefore, by using UBUMonitor, teachers will be able to easily visualize their students’ engagement with their subject, which can facilitate early action to prevent students from dropping out more effectivel

Hemoglobinuria como signo de disfunción protésica

We report a case of 39 years old patient with rheumatic mitral valve disease and who had a prosthetic replacement that is being studied due to a suspicious hematuria. Finally the diagnosis of hemoglobinuria due to intravascu- lar hemolysis has been confirmed and collaboration with the Cardiology department has been requested. In the transthoracic echocardiography and transesophageal echocardiography a severe mitral periprosthetic leak has been noticed. It was decided valve replacement surgery. Hemolysis disappeared finally after the surgical correction of the valve disease. When there is hemolysis after a valve replacement we must suspect of the existence of a periprosthetic leak.Se describe el caso de una paciente de 39 años con antecedente de valvulopatía mitral reumática con recambio protésico, en estudio por supuesta hematuria durante más de un año. Finalmente se confirma que se trata de hemoglobinuria por hemólisis intravascular y se solicita colaboración con Cardiología. En ecocardiografía transtorácica y posteriormente transesofágica se observa fuga mitral perivalvular severa. Se decide recambio valvular mitral con desaparición de la hemólisis tras la corrección quirúrgica. Ante la presencia de hemólisis tras reemplazo valvular se debe sospechar fuga periprotésica

A PHABULOSA/cytokinin feedback loop controls root growth in arabidopsis

The hormone cytokinin (CK) controls root length in Arabidopsis thaliana by defining where dividing cells, derived from stem cells of the root meristem, start to differentiate [ [1], [2], [3], [4], [5] and [6]]. However, the regulatory inputs directing CK to promote differentiation remain poorly understood. Here, we show that the HD-ZIPIII transcription factor PHABULOSA (PHB) directly activates the CK biosynthesis gene ISOPENTENYL TRANSFERASE 7 (IPT7), thus promoting cell differentiation and regulating root length. We further demonstrate that CK feeds back to repress both PHB and microRNA165, a negative regulator of PHB. These interactions comprise an incoherent regulatory loop in which CK represses both its activator and a repressor of its activator. We propose that this regulatory circuit determines the balance of cell division and differentiation during root development and may provide robustness against CK fluctuations