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El futuro de la investigación en emprendimiento estratégico: inducción y deducción a través del Machine Learning
Get PDFSobre la base de la nueva era big data, este artículo tiene por objetivo proporcionar orientación sobre las metodologías principales de Machine Learning y su impacto tanto en el proceso de construcción del conocimiento como en la práctica en el campo del emprendimiento estratégico. Tratará de proponer varias formas en que estas nuevas metodologías afectarán la construcción del conocimiento, tales como: (a) cerrar el círculo inducción-deduccción; (b) generar nuevas ideas; (c) analizar modelos más complejos, holísticos y dinámicos, (d) promover su reproducibilidad y replicabilidad; y (e) integrar la práctica y la investigación. También se tratará de identificar la relevancia de las nuevas metodologías de Machine Learning para las empresas que buscan una ventaja competitiva sostenible. Se proporcionana evidencia de apoyo en varias investigaciones y casos prácticos de éxito.Based on the new big data era, this article aims to provide guidance on the main Machine Learning methodologies and their impact on both the knowledge construction process and the practice in the field of strategic entrepreneurship. It will try to propose several ways in which these new methodologies will affect the construction of knowledge, such as: (a) closing the induction-deduction circle; (b) generate new ideas; (c) analyze more complex, holistic and dynamic models, (d) promote their reproducibility and replicability; and (e) integrate practice and research. It will also try to identify the relevance of new Machine Learning methodologies for companies seeking a sustainable competitive advantage. Supporting evidence is provided in various research and case studies of success
International education narratives. Transdisciplinary educative innovation experiences based on bilingual teaching
No full textEsta obra está formada por los trabajos científicos pertenecientes al Proyecto de innovación “Inter-disciplinary Lectures. A Possitive Rebound for English Teaching”La internacionalización en el mundo académico es un modo de transferir conocimiento enriqueciendo así las capacidades cognitivas y las competencias transversales de los alumnos. Esta fuente de conocimiento permite a los docentes compartir experiencias, aumentar los acuerdos de trabajo entre facultades y participar de otras visiones y modelos de aprendizaje.
Este libro resume varias experiencias académicas internacionales entre facultades, empresas e instituciones de 6 países (Alemania, Francia, Japón, Portugal, España y EE. UU.) y 15 organizaciones. En total, 21 participantes (académicos, estudiantes y expertos) de diversas disciplinas.
La obra presenta diversas narrativas sobre experiencias internacionales de profesores y estudiantes que a lo largo de los años han ido colaborando con la Universidad de Burgos en diferentes acciones y compromisos.
Todo esto descubre la internacionalización como un modo de evaluación tácita y mejora continua de los modelos educativos universitarios.Proyecto de innovación“Inter-disciplinary Lectures. A Possitive Rebound for English Teaching” de la convocatoria de ayudas a grupos de innovación docente reconocidos para la elaboración de materiales docentes para los años 2021 y 2022 (resolución de 23 de febrero de 2021 del Vicerrectorado de Personal Docente e Investigador de la Universidad de Burgos)
Spectral distribution of Solar Radiation under CIE standard sky conditions
No full textComunicación presentada en: XII Congreso Nacional y III Internacional de Ingeniería Termodinámica (12 CNIT), June 19- July 1, Madrid (Spain)Solar radiation (SR) is the main driver of the planetary energy balance and it is essential in various areas of human activity. In the energy context, particularly in renewable energies, the broadband solar radiation is converted into useful heat or electricity. The interaction of the wavelengths of the visible spectrum of SR (daylighting or illuminance, L, 400-780 nm) with the photoreceptors of the human eye, allows to perceive the world and its colors, and it has influence on mood and circadian rhythms. Daylight is also essential for the improvement in the energy efficiency of buildings and visual comfort. . In agriculture, Photosynthetically Active Radiation (PAR, 400-700 nm) is the energy source to trigger photosynthesis which makes possible the production of food and biomass. Finally, Ultraviolet UVR (UV-A, 315-400 nm; UV-B, 280-215 nm) is responsible for a wide variety of photochemical reactions, especially its shorter wavelengths have deleterious effects in many biological systems.The authors gratefully acknowledge the financial support provided by the Spanish Ministry of Science & Innovation under the I+D+i state program “Challenges Research Projects” (Ref. RTI2018-098900-B-I00). Elena Garrachón-Gómez thanks financial support provided by Junta de Castilla y León (Programa Operativo de Empleo Juvenil, Fondo Social Europeo e Iniciativa de Empleo Juvenil
Importancia ministerial: Modelo de análisis aplicado al caso hondureño
No full text¿Cuáles son los ministerios más importantes en Honduras? y ¿por qué son importantes los ministerios importantes? Para responder a estas preguntas este estudio ofrece un análisis de la impor tancia de las carteras ministeriales hondureñas desde 1982 hasta 2020. Para ello este estudio sigue la propuesta teórica de Camerlo y Martínez-Gallardo que sugiere distinguir cuatro dimen-siones claves (gestión de políticas públicas, asignación discrecional de recursos, capacidad política y capacidad organizacional). Los hallazgos de esta investigación pusieron de manifiesto que la rele-vancia ministerial en este país está vinculada a aquellas carteras que, además de contar con valor estratégico e impacto, tienen potencialmente la posibilidad de disponer de fondos discrecionales para desarrollar políticas clientelares que han permitido a los partidos tradicionales mantenerse en el poder a lo largo de todo el periodo analizado.What are the most important ministries in Honduras? And why are important ministries important? To answer these questions, this study offers an analysis of the importance of the Hon-duran ministerial portfolios from 1982 to 2020. For this, this study follows the theoretical proposal of Camerlo and Martínez-Gallardo that suggests distinguishing four key dimensions (policy man-agement public, discretionary allocation of resources, political capacity and organizational capacity). The findings of this research showed that the ministerial relevance in this country is linked to those portfolios that, in addition to having strategic value and impact, potentially have the possibility of having discretionary funds to develop clientelistic policies that have allowed tradi-tional parties stay in power throughout the period analyzed
Potential of functional analysis applied to Sentinel-2 time-series to assess relevant agronomic parameters at the within-field level in viticulture
No full textSentinel-2 satellite imagery offers a wealth of spectral information combined with a weekly temporal resolution. It is seen as a promising tool to extract spatial information about vineyards and link them to agronomic parameters. Usually, only one or a few images are commonly employed at specific stages like veraison in viticulture. Extracting further information from time-series images may be of interest; however, this remains an issue due to the noisy and complex nature of extracted time-series. The functional analysis proposes a robust continuous representation of these time-series, which can then be used with adapted statistical tools. This paper focuses on extracting relevant information at the within-field level on two vineyards in Spain, which can be jointly interpreted with field observations and measurements. More precisely, it discusses the use of popular linear dimensionality reduction techniques, namely Principal Component Analysis (PCA) and Partial Least Square (PLS), adapted to functional data in order to decompose NDVI time-series into a weighted sum of several functional components. The unsupervised methods, like PCA, decomposed the spatial structure within the vineyards using a few components, resulting in a better and more manageable dataset than the one obtained using simple non-constrained methods. The results show significant correlations with ground-truth data showing the added value of considering the whole NDVI temporal series compared to a single NDVI map at veraison. The proposed approach provided helpful information about each component's yearly trend. Moreover, the results are linked to grapevines' seasonal phenology and management practices, highlighting phenomena affecting the vineyard's development. This method is particularly suited for interactions with field experts, who may derive relevant agronomic information from the decomposition maps.This work has been possible thanks to the economic support of Junta de Castilla y León (Spain), Instituto Tecnológico Agrario de Castilla y León (ITACyL), the project INIA RTA2014-00077-C02, FPI-INIA2016-017, FEDER funds and the cooperation of ‘Bodega Martín Berdugo’ and ‘Bodega Cuatro Rayas”
A Comprehensive Review of Instruments Measuring Attitudes Toward Science
No full textThe development of attitudes toward science instruments has recently emerged in science education research. However, a comprehensive review of their psychometric properties, using currently accepted assessment standards, has not yet been completed. Consequently, this review discusses the validity and reliability of 18 measures published between 2005 and 2019 in leading science education journals. Findings showed that construct validity and internal consistency reliability was reported for all instruments; however, evidence for predictive validity and temporal stability reliability was rather scarce, which could limit their use in intervention and correlational type of studies. Similarly, content validity was found to be underreported. Consequently, the relevance, comprehensiveness, and comprehensibility of the items in some instruments are currently unknown and yet to be established in future studies. Finally, there is a gap in the literature regarding instruments that can be used across different countries and scientific disciplines, which could restrict accumulative and comparative results worldwide. Since the use of valid and reliable measurement instruments is a crucial aspect of educational research, the findings of this study could be useful in assisting researchers and practitioners in selecting the most appropriate measure for different research designs
Validation and calibration of models to estimate photosynthetically active radiation considering different time scales and sky conditions
Get PDFPhotosynthetically Active Radiation (PAR) is a fundamental parameter for developing plant productivity models. Nevertheless,
instrumentation for measuring PAR and to record it is scarce at conventional meteorological stations. Several procedures have therefore
been proposed for PAR estimation. In this work, 21 previously published analytical models that correlate PAR with easily available
meteorological parameters are collected. Although longer time scales were considered in the original publications, a minute range
was applied in this work to calibrate the PAR models. In total, more than 10 million input records were gathered from the SURFRAD
station network from a 10-year long time series with data frequencies recorded every 1 min. The models were calibrated both globally,
using data from all stations and locally, with data from each station. After calibration, the models were validated for minute, hourly and
daily data, obtaining low fitting errors at the different stations in all cases, both when using the globally calibrated models and with the
models calibrated for each location. Although the PAR results in general improved for locally calibrated models, the use of local models
is not justified, since the global models presented offered very satisfactory PAR results for the different climatic conditions where the
meteorological stations are located. Thus, PAR estimation model should then be selected, solely considering the meteorological variables
available at the specific location. When applying the globally calibrated models to input data classified according to sky conditions (from
clear to overcast), the PAR models continued to perform satisfactorily, although the error statistics of some models for overcast skies
worsened.The authors gratefully acknowledge the financial support provided by the Spanish Ministry of Science & Innovation under the I + D+i state program “Challenges Research Projects” (Ref. RTI2018-098900-B-I00)
Nonlinear physics opens a new paradigm for accurate transcription start site prediction
Get PDFThere is evidence that DNA breathing (spontaneous opening of the DNA strands)
plays a relevant role in the interactions of DNA with other molecules, and in particular
in the transcription process. Therefore, having physical models that can predict these
openings is of interest. However, this source of information has not been used before
either in transcription start sites (TSSs) or promoter prediction. In this article, one such
model is used as an additional information source that, when used by a machine learn‑
ing (ML) model, improves the results of current methods for the prediction of TSSs. In
addition, we provide evidence on the validity of the physical model, as it is able by itself
to predict TSSs with high accuracy. This opens an exciting avenue of research at the
intersection of statistical mechanics and ML, where ML models in bioinformatics can be
improved using physical models of DNA as feature extractors.This work has been supported by the Junta de Andalucia under project UCO1264182 and by the Ministry of Science, Innovation and Universities under project PID2019-109481GB-I00/AEI/q10.13039/501100011033, in both cases co-financed through European Union FEDER funds. José A. Barbero-Aparicio is founded through a predoctoral grant from the University of Burgos