Dataset.

Analysis of the effect of genotype on rE median, rE dispersion, and sFAi dispersion

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/365355
Digital.CSIC. Repositorio Institucional del CSIC
  • Navarro, Tomás
  • Iannini, Antonella
  • Neto, Marta
  • Campoy-López, Alejandro
  • Muñoz-García, Javier
  • Pereira, Paulo S.
  • Ares, Saúl
  • Casares, Fernando
First block shows each genotype’s effect on the rE median, their p.values, and the predicted median for each of them. The second and third blocks show the standard deviation of each group for rE and sFAi, respectively, and the result of the comparison of variances of each group against the optix>+ reference group., Peer reviewed
 
DOI: http://hdl.handle.net/10261/365355
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/365355

HANDLE: http://hdl.handle.net/10261/365355
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/365355
 
Ver en: http://hdl.handle.net/10261/365355
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/365355

r-INCLIVA. Repositorio Institucional de Producción Científica de INCLIVA
oai:incliva.fundanetsuite.com:p4321
Artículo científico (article). 2020

I'M NOT GOOD FOR ANYTHING AND THAT'S WHY I'M STRESSED: ANALYSIS OF THE EFFECT OF SELF-EFFICACY AND EMOTIONAL INTELLIGENCE ON STUDENT STRESS USING SEM AND QCA

r-INCLIVA. Repositorio Institucional de Producción Científica de INCLIVA
  • Navarro-Mateu D
  • Alonso-Larza L
  • Gomez-Dominguez M
  • Prado-Gasco V
  • Valero-Moreno S
Stress negatively affects the well-being and the quality of life of the society. Specifically in the academic context, it is relevant to analyze its levels due to its impact on performance and learning. There are factors that affect the said stress including, among others, self-efficacy, and emotional intelligence. The purpose of this study is to analyze how emotional intelligence and perceived self-efficacy affect student stress. In order to show this influence, two complementary methodologies are implemented: the structural equation models (SEMs) and the comparative qualitative analysis (QCA). A total of 477 students (85% of women) from a private University of Valencia participated in the study, with ages ranging from 18 to 53 years old (M = 21.57, SD = 3.68). The assessment instruments used were as follows: Emotional Intelligence Scale (TMMS-24) to measure emotional intelligence; General Self-Efficacy Scale (GSS) to measure self-efficacy; and Perceived Stress Scale (PSS) to measure stress. The results in the SEM endorse the hypotheses that emotional clarity and self-efficacy are negatively related to stress and positively related to emotional attention (EA), explaining 25% of the variance. The QCA results show that none of the variables is a necessary condition for inducing stress. Nevertheless, different combinations of these variables are sufficient conditions to explain 35% of the high stress levels. The most important combination over high stress levels seems to be the interaction between high levels of EA and low levels of self-efficacy. Regarding the low levels of perceived stress, there are sufficient conditions to explain 50% of them. Mainly, the most important interaction is between low levels of self-efficacy and low levels of EA. The comparison of both methodologies enables the broadening of new horizons at the methodological level applicable to different contexts.



RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/65508
Artículo científico (article). 2015

STATISTICAL ANALYSIS OF THE EFFECT OF THE TEMPERATURE AND INLET HUMIDITIES ON THE PARAMETERS OF A PEMFC MODEL

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
  • Giner Sanz, Juan José|||0000-0003-0441-6102
  • Ortega Navarro, Emma María|||0000-0001-6902-018X
  • Pérez-Herranz, Valentín|||0000-0002-4010-0888
An individual PEM fuel cell 6-parameter mechanistic model was developed. In parallel, experimental polarization curves were obtained at different temperature and inlet gas humidities conditions. The 6 model parameters were determined by fitting the semi empirical model to the experimental curve using a non linear regression method. Finally, a statistical analysis was carried out in order to determine which operating conditions (temperature and inlet humidities) have a significant effect on which model parameters. A black box model was built in order to relate the model parameter values to the significant operating conditions for each one of them. The obtained model was able to satisfactory reproduce the experimental behaviour of the system at low current densities., The authors are very grateful to the vice-chancellor for research of the Universitat Politecnica de Valencia for its financial support in form of excellence grant; and to the Generalitat Valenciana for its economic support in form of Vali+d grant (Ref: ACIF-2013-268).





RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/125085
Artículo científico (article). 2018

STATISTICAL ANALYSIS OF THE EFFECT OF TEMPERATURE AND INLET HUMIDITIES ON THE PARAMETERS OF A SEMIEMPIRICAL MODEL OF THE INTERNAL RESISTANCE OF A POLYMER ELECTROLYTE MEMBRANE FUEL CELL

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
  • Giner-Sanz, Juan José|||0000-0003-0441-6102
  • Ortega Navarro, Emma María|||0000-0001-6902-018X
  • Pérez-Herranz, Valentín|||0000-0002-4010-0888
[EN] he internal resistance of a PEM fuel cell depends on the operation conditions and on the current delivered by the cell. This work's goal is to obtain a semiempirical model able to reproduce the effect of the operation current on the internal resistance of an individual cell of a commercial PEM fuel cell stack; and to perform a statistical analysis in order to study the effect of the operation temperature and the inlet humidities on the parameters of the model. First, the internal resistance of the individual fuel cell operating in different operation conditions was experimentally measured for different DC currents, using the high frequency intercept of the impedance spectra. Then, a semiempirical model based on Springer and co-workers¿ model was proposed. This model is able to successfully reproduce the experimental trends. Subsequently, the curves of resistance versus DC current obtained for different operation conditions were fitted to the semiempirical model, and an analysis of variance (ANOVA) was performed in order to determine which factors have a statistically significant effect on each model parameter. Finally, a response surface method was applied in order to obtain a regression model., The authors are very grateful to the Generalitat Valenciana for its economic support in form of Valid grant (Ref:. ACIF-2013-268)





RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/196960
Proyecto fin de carrera. Trabajo final de grado (bachelorThesis). 2023

ANALYSIS OF THE EFFECT OF ACTION OBSERVATION AND MOTOR IMAGERY ON BRAIN CONNECTIVITY

ANÁLISIS DEL EFECTO DE LA OBSERVACIÓN DE LA ACCIÓN Y LA IMAGINACIÓN MOTORA EN LA CONECTIVIDAD CEREBRAL.

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
  • Navarro Piles, Hugo
[ES] El objetivo principal de este estudio es investigar la conectividad cerebral durante dos condiciones diferentes: Tarea de Observación de la Acción (TOA) e Imaginería Motora (IM), utilizando la electroencefalografía (EEG) como técnica de registro. Para obtener resultados fiables y de alta calidad, se aplicaron varias técnicas de preprocesamiento de datos. En primer lugar, se filtró la señal EEG en el rango de frecuencias de 1-45 Hz para eliminar las frecuencias no deseadas y mejorar la calidad de la señal. A continuación, los datos se segmentaron en épocas temporales específicas, que iban de -5 a 6,5 segundos, para analizar y comparar la actividad cerebral en puntos temporales clave. Durante el análisis, se tuvo en cuenta la calidad de los canales de EEG. Los canales con defectos o interferencias visuales se eliminaron del estudio para evitar distorsiones en los resultados. Además, se utilizó el análisis de componentes independientes (ICA) para identificar y eliminar fuentes de artefactos que pudieran afectar a la interpretación de la conectividad cerebral. Tras el preprocesamiento de los datos, se calcularon las matrices de conectividad cerebral utilizando el índice de retraso de fase (PLI). Esta medida proporciona información sobre la sincronización y la comunicación funcional entre diferentes regiones cerebrales. Se analizaron las conexiones funcionales en todo el cerebro durante las condiciones AOT y MI, con el objetivo de identificar patrones de conectividad específicos asociados a cada tarea. Un análisis adicional se centró en dos bandas específicas de frecuencias cerebrales: la banda mu (8-12 Hz) y la banda beta (14-20 Hz). Estas bandas están relacionadas con procesos motores y cognitivos, y su estudio permitió una exploración más detallada de la actividad cerebral durante AOT y MI. Además, se realizaron análisis específicos para identificar patrones de comportamiento comunes en la conectividad cerebral durante ambas condiciones. Se examinaron las similitudes y diferencias en la conectividad funcional entre diferentes regiones cerebrales, proporcionando valiosos conocimientos sobre los mecanismos neuronales subyacentes de la observación de la acción y la imaginería motora. Este estudio utiliza técnicas avanzadas de procesamiento de señales y análisis de la conectividad cerebral para investigar la actividad neuronal durante la AOT y la MI. Los resultados obtenidos no sólo mejorarán nuestra comprensión de los procesos cognitivos y motores implicados, sino que también pueden tener aplicaciones clínicas en áreas como la rehabilitación y el neurofeedback., [EN] The main objective of this study is to investigate brain connectivity during two different conditions: Action Observation Task (AOT) and Motor Imagery (MI), using electroencephalography (EEG) as the recording technique. To obtain reliable and high-quality results, various data preprocessing techniques were applied. Firstly, the EEG signal was filtered in the frequency range of 1-45 Hz to remove unwanted frequencies and improve signal quality. Next, the data was segmented into specific time epochs, ranging from -5 to 6.5 seconds, to analyze and compare brain activity at key time points. During the analysis, the quality of the EEG channels was taken into account. Channels with defects or visual interferences were eliminated from the study to avoid distortions in the results. Furthermore, independent component analysis (ICA) was used to identify and remove artifact sources that could impact the interpretation of brain connectivity. After preprocessing the data, brain connectivity matrices were calculated using the Phase Lag Index (PLI). This measure provides information about the synchronization and functional communication between different brain regions. Functional connections throughout the brain were analyzed during the AOT and MI conditions, aiming to identify specific connectivity patterns associated with each task. An additional analysis focused on two specific brain frequency bands: the mu band (8-12 Hz) and the beta band (14-20 Hz). These bands are related to motor and cognitive processes, and their study allowed for a more detailed exploration of brain activity during AOT and MI. Furthermore, specific analyses were conducted to identify common behavioral patterns in brain connectivity during both conditions. Similarities and differences in functional connectivity between different brain regions were examined, providing valuable insights into the underlying neural mechanisms of action observation and motor imagery. In summary, this study utilizes advanced signal processing techniques and analysis of brain connectivity to investigate neuronal activity during AOT and MI. The obtained results will not only enhance our understanding of the cognitive and motor processes involved but may also have clinical applications in areas such as rehabilitation and neurofeedback.




idUS. Depósito de Investigación de la Universidad de Sevilla
oai:idus.us.es:11441/58660
Artículo científico (article). 2016

A TRANSCRIPTOMIC ANALYSIS OF THE EFFECT OF GENISTEIN ON SINORHIZOBIUM FREDII HH103 REVEALS NOVEL RHIZOBIAL GENES PUTATIVELY INVOLVED IN SYMBIOSIS

idUS. Depósito de Investigación de la Universidad de Sevilla
  • Pérez Montaño, Francisco de Asís
  • Jiménez Guerrero, Irene
  • Acosta Jurado, Sebastián
  • Navarro Gómez, Pilar
  • Ollero Márquez, Francisco Javier
  • Ruiz Sainz, José Enrique
  • López Baena, Francisco Javier
  • Vinardell González, José María
Sinorhizobium fredii HH103 is a rhizobial soybean symbiont that exhibits an extremely broad host-range. Flavonoids exuded by legume roots induce the expression of rhizobial symbiotic genes and activate the bacterial protein NodD, which binds to regulatory DNA sequences called nod boxes (NB). NB drive the expression of genes involved in the production of molecular signals (Nod factors) as well as the transcription of ttsI, whose encoded product binds to tts boxes (TB), inducing the secretion of proteins (effectors) through the type 3 secretion system (T3SS). In this work, a S. fredii HH103 global gene expression analysis in the presence of the flavonoid genistein was carried out, revealing a complex regulatory network. Three groups of genes differentially expressed were identified: i) genes controlled by NB, ii) genes regulated by TB, and iii) genes not preceded by a NB or a TB. Interestingly, we have found differentially expressed genes not previously studied in rhizobia, being some of them not related to Nod factors or the T3SS. Future characterization of these putative symbiotic-related genes could shed light on the understanding of the complex molecular dialogue established between rhizobia and legumes., España, Ministerio de Economía y Competitividad BIO2011-30229-C01, España, Ministerio de Economía y Competitividad AGL2012-38831, Junta de Andalucía, P11-CVI-7050, Junta de Andalucía P11-CVI-7500




Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/365355
Dataset. 2024

ANALYSIS OF THE EFFECT OF GENOTYPE ON RE MEDIAN, RE DISPERSION, AND SFAI DISPERSION

Digital.CSIC. Repositorio Institucional del CSIC
  • Navarro, Tomás
  • Iannini, Antonella
  • Neto, Marta
  • Campoy-López, Alejandro
  • Muñoz-García, Javier
  • Pereira, Paulo S.
  • Ares, Saúl
  • Casares, Fernando
First block shows each genotype’s effect on the rE median, their p.values, and the predicted median for each of them. The second and third blocks show the standard deviation of each group for rE and sFAi, respectively, and the result of the comparison of variances of each group against the optix>+ reference group., Peer reviewed




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