Determinación de los coeficientes de convección de calor en el flujo radial a través de un lecho de empaque de polietileno

Se presenta una metodología teórico-experimental para determinar los coeficientes intersticiales de transferencia de calor pro-medio en el flujo radial de agua a través de un lecho de empaque de polietileno donde el fluido no está en equilibrio térmico con la fase sólida. Los coeficientes de transferencia de calor se obtienen a través del Single Blow Transient Method combinando los resultados experimentales en un banco de ensayo con las soluciones numéricas del modelo matemático. El sistema de ecua-ciones diferenciales parciales generado en el modelo matemático es resuelto a través de una metodología numérica basada en el método de volúmenes finitos. Las pruebas experimentales y las soluciones numéricas se realizaron para diferentes valores de velocidad superficial del fluido a la entrada del lecho y para diversos valores de porosidad del medio, obteniéndose que los números de Nusselt aumentan al incrementarse el número de Reynolds, y de igual manera, también aumentan al disminuir la porosidad del medio, observándose valores de Nusselt hasta de 2,8 para una porosidad de 0,375 y un número de Reynolds de 650.A numerical-experimental methodology was used for determining interstitial heat transfer coefficients in water flowing through po-rous media where it was not in heat balance with the solid phase. Heat transfer coefficients were obtained through the single blow transient test method, combining experimental test equipment results with a mathematical model’s numerical solution. The partial differential equation system produced by the mathematical model was resolved by a numerical finite volume method-ba-sed methodology. Experimental tests and numerical solutions were satisfactorily carried out for different values from the fluid’s surface speed from the entrance to the bed and for different porosity values, finding that Nusselt numbers increased when Reynolds numbers also increased and that Nusselt numbers increased when porosity decreased. A 650 Reynolds number and 0.375 porosity gave a Nusselt number of up to 2.8

Evolutionary system for prediction and optimization of hardware architecture performance

The design of computer architectures is a very complex problem. The multiple parameters make the number of possible combinations extremely high. Many researchers have used simulation, although it is a slow solution since evaluating a single point of the search space can take hours. In this work we propose using evolutionary multilayer perceptron (MLP) to compute the performance of an architecture parameter settings. Instead of exploring the search space, simulating many configurations, our method randomly selects some architecture configurations; those are simulated to obtain their performance, and then an artificial neural network is trained to predict the remaining configurations performance. Results obtained show a high accuracy of the estimations using a simple method to select the configurations we have to simulate to optimize the MLP. In order to explore the search space, we have designed a genetic algorithm that uses the MLP as fitness function to find the niche where the best architecture configurations (those with higher performance) are located. Our models need only a small fraction of the design space, obtaining small errors and reducing required simulation by two orders of magnitude.Peer ReviewedPostprint (published version

Añadiendo mecanismos de ayuda en un juez on-line automático para soporte a mentorías académicas

Todos los jueces en línea, incluído en sus inicios ¡Acepta el reto! (https://www.aceptaelreto.com) desarrollado por profesores de la UCM, adolecen de un problema de realimentación al usuario: cuando el visitante hace un envío incorrecto el sistema no es capaz de dar información específica del error. El documento es la memoria final de un Proyecto de Innovación y Mejora de la Calidad Docente (PIMCD) de 2017/2018 en el que se puso en marcha un sistema de pistas en el juez

Development and validation of combined symptom‐medication scores for allergic rhinitis*

Background: Validated combined symptom-medication scores (CSMSs) are needed to investigate the effects of allergic rhinitis treatments. This study aimed to use real-life data from the MASK-air® app to generate and validate hypothesis- and data-driven CSMSs. Methods: We used MASK-air® data to assess the concurrent validity, test-retest reliability and responsiveness of one hypothesis-driven CSMS (modified CSMS: mCSMS), one mixed hypothesis- and data-driven score (mixed score), and several data-driven CSMSs. The latter were generated with MASK-air® data following cluster analysis and regression models or factor analysis. These CSMSs were compared with scales measuring (i) the impact of rhinitis on work productivity (visual analogue scale [VAS] of work of MASK-air® , and Work Productivity and Activity Impairment: Allergy Specific [WPAI-AS]), (ii) quality-of-life (EQ-5D VAS) and (iii) control of allergic diseases (Control of Allergic Rhinitis and Asthma Test [CARAT]). Results: We assessed 317,176 days of MASK-air® use from 17,780 users aged 16-90 years, in 25 countries. The mCSMS and the factor analyses-based CSMSs displayed poorer validity and responsiveness compared to the remaining CSMSs. The latter displayed moderate-to-strong correlations with the tested comparators, high test-retest reliability and moderate-to-large responsiveness. Among data-driven CSMSs, a better performance was observed for cluster analyses-based CSMSs. High accuracy (capacity of discriminating different levels of rhinitis control) was observed for the latter (AUC-ROC = 0.904) and for the mixed CSMS (AUC-ROC = 0.820). Conclusion: The mixed CSMS and the cluster-based CSMSs presented medium-high validity, reliability and accuracy, rendering them as candidates for primary endpoints in future rhinitis trials

Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Funder: Funder: Fundación bancaria ‘La Caixa’ Number: LCF/PR/PR16/51110003 Funder: Grifols SA Number: LCF/PR/PR16/51110003 Funder: European Union/EFPIA Innovative Medicines Initiative Joint Number: 115975 Funder: JPco-fuND FP-829-029 Number: 733051061Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Multiancestry analysis of the HLA locus in Alzheimer’s and Parkinson’s diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues

Pathways towards democratization of hydro-environment observations and data

This White Paper grew out of the collaborative work conducted byseveral IAHR Technical Committees, with a focus on the TechnicalCommittee on Experimental Methods and Instrumentation.The outcome is a community vision on future pathways aimed atleveraging conventional and emerging (unconventional) methodsto facilitate access to hydro-environment observations in the nearfuture. It has been formulated in collaboration with a broad spectrumof experts from different backgrounds

Evolutionary system for prediction and optimization of hardware architecture performance

The design of computer architectures is a very complex problem. The multiple parameters make the number of possible combinations extremely high. Many researchers have used simulation, although it is a slow solution since evaluating a single point of the search space can take hours. In this work we propose using evolutionary multilayer perceptron (MLP) to compute the performance of an architecture parameter settings. Instead of exploring the search space, simulating many configurations, our method randomly selects some architecture configurations; those are simulated to obtain their performance, and then an artificial neural network is trained to predict the remaining configurations performance. Results obtained show a high accuracy of the estimations using a simple method to select the configurations we have to simulate to optimize the MLP. In order to explore the search space, we have designed a genetic algorithm that uses the MLP as fitness function to find the niche where the best architecture configurations (those with higher performance) are located. Our models need only a small fraction of the design space, obtaining small errors and reducing required simulation by two orders of magnitude.Peer Reviewe