The percentile residual life up to time t0: ordering and aging properties

Motivated by practical issues, a new stochastic order for random variables is introduced by comparing all their percentile residual life functions until a certain instant. Some interpretations of these stochastic orders are given, and various properties of them are derived. The relationships to other stochastic orders are studied, and also an application in Reliability Theory is described. Finally, we present some characterization results of the decreasing percentile residual life up to time t0 aging notion.Aging notion, Hazard rate, Mean residual life, Percentile residual life, Reliability, Stochastic ordering

Characterization of bathtub distributions via percentile residual life functions

In reliability theory and survival analysis, many set of data are generated by distributions with bathtub shaped hazard rate functions. Launer (1993) established several relations between the behaviour of the hazard rate function and the percentile residual life function. In particular, necessary conditions were given for a special type of bathtub distributions in terms of percentile residual life functions. The purpose of this paper is to complete the study initiated by Launer (1993) and to characterize (necessary and sufficient conditions) all types of bathtub distributions.Percentile residual life, Bathtub hazard rate, Aging notions,

Comparing quantile residual life functions by confidence bands

A quantile residual life function is the quantile of the remaining life of a surviving subject, as it varies with time. In this article we present a nonparametric method for constructing confidence bands for the difference of two quantile residual life functions. These bands provide evidence for two random variables ordering with respect to a quantile residual life order introduced in Franco-Pereira et al. (2010). A simulation study has been carried out in order to evaluate and illustrate the performance and the consistency of this new methodology. We also present applications to real data examples.Quantile residual life, Confidence bands

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Peer Reviewe

The percentile residual life up to time t(o): Ordering and aging properties

Motivated by practical issues, a new stochastic order for random variables is introduced by comparing all their percentile residual life functions until a certain instant. Some interpretations of these stochastic orders are given, and various properties of them are derived. The relationships to other stochastic orders are studied and also an application in reliability theory is described. Finally, we present some characterization results of the decreasing percentile residual life up to time to aging notion

Aprendizaje de imágenes histológicas utilizando un microscopio virtual: metodología y opinión de los alumnos

El concepto de tejido es un constructo teorético muy útil para aprender a conocer las estructuras microscópicas del organismo y para diagnosticar, de forma objetiva, la mayoría de las lesiones, a través de imágenes histológicas (IH). Tradicionalmente, aprender a interpretar IH se basa en su observación repetitiva y monótona. Esto y la consideración de la Histología como una disciplina meramente descriptiva, ha determinado su escasa relevancia y su alto nivel de olvido para los alumnos, como ha sido puesto de relieve en varias publicaciones. Los recursos digitales han facilitado, de forma sustancial, el aprendizaje de la Histología, aunque todavía sigue basándose en la observación iterativa y monótona de IH. Para facilitar y mejorar dicho aprendizaje hemos creando y publicado una clasificación y sistematización de las IH. En este trabajo presentamos la combinación de la sistematización de las IH con el uso de un microscopio virtual accesible a todos los alumnos en cualquier lugar y momento (tablets, smartphones, ordenadores de mesa, portátiles, etc.). La evaluación de esta metodología, mediante una encuesta, pone de manifiesto su alto grado de aceptación por los alumnos y sus enormes posibilidades para un aprendizaje, a la vez, autónomo y colaborativo

The role of web sharing, species recognition and host-plant defence in interspecific competition between two herbivorous mite species

When competing with indigenous species, invasive species face a problem, because they typically start with a few colonizers. Evidently, some species succeeded, begging an answer to the question how they invade. Here, we investigate how the invasive spider mite Tetranychus evansi interacts with the indigenous species T. urticae when sharing the solanaceous host plant tomato: do they choose to live together or to avoid each other’s colonies? Both species spin protective, silken webs on the leaf surfaces, under which they live in groups of con- and possibly heterospecifics. In Spain, T. evansi invaded the non-crop field where native Tetranychus species including T. urticae dominated. Moreover, T. evansi outcompetes T. urticae when released together on a tomato plant. However, molecular plant studies suggest that T. urticae benefits from the local down-regulation of tomato plant defences by T. evansi, whereas T. evansi suffers from the induction of these defences by T. urticae. Therefore, we hypothesize that T. evansi avoids leaves infested with T. urticae whereas T. urticae prefers leaves infested by T. evansi. Using wild-type tomato and a mutant lacking jasmonate-mediated anti-herbivore defences, we tested the hypothesis and found that T. evansi avoided sharing webs with T. urticae in favour of a web with conspecifics, whereas T. urticae more frequently chose to share webs with T. evansi than with conspecifics. Also, T. evansi shows higher aggregation on a tomato plant than T. urticae, irrespective of whether the mites occur on the plant together or not

Resistencia a Tuta absoluta en una entrada de la especie silvestre de tomate Solanum pimpinellifolium

2 páginas, 1 figura, 1 tabla.-- Artículo publicado en la revista profesional de sanidad vegetal.-- et al.[EN]: We previously found resistance to pests (twospotted spider mite and whitefly) based on type IV glandular trichomes and acylsucrose production in an accession of the wild tomato species S. pimpinellifolium from the germplasm collection at the Experimental Station La Mayora – CSIC. Resistance to the South American tomato pinworm of that accession and plant materials derived from it was investigated in greenhouse conditions at CNPH (Brasilia, Brazil) and, when Tuta absoluta was introduced into Spain, at Exp. Sta. La Mayora (Málaga, southern Spain). Genotypes carrying type IV glandular trichomes showed reduced pest damage, especially on young, apical leaves. Possibility for control of Tuta by the utilization of resistant tomato cultivars looks forward to future breeding programmes for the trait.[ES]: Una entrada de la especie silvestre de tomate S. pimpinellifolium del banco de germoplasma de la Estación Experimental La Mayora-CSIC presenta resistencia a plagas (araña roja y mosca blanca) merced a sus tricomas glandulares de tipo IV y producción de acilsacarosas. Con el fin de estudiar si esta entrada y otros genotipos de tomate de ella derivados eran también resistentes a T. absoluta, se realizaron experimentos en condiciones de invernadero en CNPH (Brasilia, Brasil) y, una vez que Tuta se introdujo en España, en la E.E. La Mayora (Algarrobo, Málaga). Los genotipos con tricomas de tipo IV sufrieron menores daños por la plaga, especialmente en las hojas apicales, más jóvenes. La posibilidad del control de Tuta mediante la utilización de variedades resistentes queda abierta a futuros programas de mejora genética del carácter.Trabajo financiado por MICINN-FEDER (Proyecto AGL2007-66760-C02-02/AGR).Peer reviewe

EHRtemporalVariability: delineating temporal data-set shifts in electronic health records

[EN] Background: Temporal variability in health-care processes or protocols is intrinsic to medicine. Such variability can potentially introduce dataset shifts, a data quality issue when reusing electronic health records (EHRs) for secondary purposes. Temporal data-set shifts can present as trends, as well as abrupt or seasonal changes in the statistical distributions of data over time. The latter are particularly complicated to address in multimodal and highly coded data. These changes, if not delineated, can harm population and data-driven research, such as machine learning. Given that biomedical research repositories are increasingly being populated with large sets of historical data from EHRs, there is a need for specific software methods to help delineate temporal data-set shifts to ensure reliable data reuse. Results: EHRtemporalVariability is an open-source R package and Shiny app designed to explore and identify temporal data-set shifts. EHRtemporalVariability estimates the statistical distributions of coded and numerical data over time; projects their temporal evolution through non-parametric information geometric temporal plots; and enables the exploration of changes in variables through data temporal heat maps. We demonstrate the capability of EHRtemporalVariability to delineate data-set shifts in three impact case studies, one of which is available for reproducibility. Conclusions: EHRtemporalVariability enables the exploration and identification of data-set shifts, contributing to the broad examination and repurposing of large, longitudinal data sets. Our goal is to help ensure reliable data reuse for a wide range of biomedical data users. EHRtemporalVariability is designed for technical users who are programmatically utilizing the R package, as well as users who are not familiar with programming via the Shiny user interface.This work was supported by Universitat Politecnica de Valencia grant PAID-00-17, Generalitat Valenciana grant BEST/2018, and projects H2020-SC1-2016-CNECT No. 727560 and H2020-SC1-BHC-2018-2020 No. 825750Sáez Silvestre, C.; Gutiérrez-Sacristán, A.; Kohane, I.; Garcia-Gomez, JM.; Avillach, P. (2020). EHRtemporalVariability: delineating temporal data-set shifts in electronic health records. GigaScience. 9(8):1-7. https://doi.org/10.1093/gigascience/giaa079S1798Gewin, V. (2016). Data sharing: An open mind on open data. Nature, 529(7584), 117-119. doi:10.1038/nj7584-117aKatzan, I. L., & Rudick, R. A. (2012). Time to Integrate Clinical and Research Informatics. Science Translational Medicine, 4(162). doi:10.1126/scitranslmed.3004583Zhu, L., & Zheng, W. J. (2018). 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