Estudio térmico del edificio de la EPSEB (UPC) mediante certificación con Calener y estudio de eficiencia energética mediante Lider

La intención de este proyecto es realizar un estudio energético, para ello se ha elegido el edificio de la EPSEB. El edificio que pertenece a la UPC está situado en C/ Doctor Marañón de Barcelona. Fue construido a principio de los años 60 y tiene una planta semisótano, planta baja y cuatro plantas piso. En primer lugar, se ha realizado un trabajo experimental consistente en la determinación de las transmisiones de flujo de calor y las temperaturas superficiales en las diferentes fachadas, así como los registros de temperatura en las diferentes estancias del edificio. Estas mediciones nos han permitido conocer la variabilidad de flujo según influyen los factores ambientales. Gracias a los diversos ensayos realizados en las fachadas del edificio hemos podido ver la gran influencia que tienen tanto la radiación solar como la velocidad del viento. Cuando la radiación solar incide directamente sobre el vidrio hace que el flujo varíe, pudiendo incluso llegar a haber aportación de calor del exterior al interior. Se analizó también la diferencia de flujo entre una ventana con la persiana subida y otra con la persiana bajada, y se corroboró la importancia de hacer un buen uso de las protecciones solares para intentar reducir el gasto energético ya sea en calefactar o refrigerar las estancias. Durante el invierno se debería aprovechar la radiación solar dejando las persianas subidas durante las horas que incida el sol y después bajarlas para conservar el calor. En verano se recomienda tenerlas bajas para que no incida la radiación solar y aumente desproporcionadamente la temperatura interior de las aulas En cuanto a la velocidad del viento se han realizado ensayos que nos llevan a pensar que en las fachadas a barlovento la resistividad exterior del aire coincide con los datos que se indican en el CTE (Rse=0,04 m2K/W), mientras que para fachadas a sotavento la resistividad exterior es mayor, alcanzando los 0,08 m2K/W. El Código Técnico de la Edificación siempre se queda con el valor más desfavorable. Se debería tener en cuenta este dato a la hora de hacer medidas in situ con el fin de poder conocer los valores reales. Después se ha realizado un estudio del estado energético de la piel del edificio de la EPSEB (UPC). Para realizar este estudio se han utilizado una serie de programas informáticos especializados: LIDER y CALENER. Los registros de temperatura interior permiten evaluar el grado de confort en el interior del edificio y correlacionarlo con el coste energético. En general la temperatura interior media en invierno no alcanza los 20ºC y puesto que el coste energético es inferior al que demanda el LIDER podríamos pensar que en el edificio se pasa frío. Estos programas se utilizan actualmente para hacer la calificación energética de los edificios y para su adecuación al Código Técnico de la Edificación. Por último, aprovechando que durante el desarrollo de este proyecto se realizó el cambio de carpinterías del edificio, se aprovecho para comprobar la mejora que generaba en la certificación energética. Hemos visto que en cuanto a la perdida de flujo con las nuevas carpinterías hay una mejora considerable, ya que se pierden 20KWh/m2 menos. Aunque ésta es una buena intervención puede ser que no sea suficiente para mejorar el rendimiento energético del edificio. Según los datos extraídos del CALENER la instalación que mas CO2 emite es la iluminación, más del 60% del total. Por tanto, se debería plantear alguna mejora en dicha instalación como podría ser la sustitución de las luminarias por lámparas fluorescentes compactas de la clase A o por otros sistemas eficientes que permitan optimizar la instalación

Reflections on changeability versus stability of health-related quality of life: distinguishing between its environmental and genetic components

The field of health-related quality of life (HRQOL) could benefit from a broadening of perspectives to include recent advancements in research on adaptation, positive psychology, and genetics. These advances shed new light on the extent to which HRQOL is changeable or fixed. The objective of this paper is to integrate these insights and to discuss their implications for HRQOL research. We describe the Hedonic Treadmill theory, which asserts that positive events only temporarily affect happiness since people quickly return to hedonic neutrality. New empirical evidence suggests important revisions of this theory, providing a more optimistic picture of the possibility for change. Advances in positive psychology show that relatively simple interventions have the power to induce a sustainable increase in levels of happiness. Finally, a small but growing number of studies have found independent genetic influences in well-being, life satisfaction, perceived health, and even HRQOL. Given the increasing empirical evidence that HRQOL can be sustainably enhanced and is in part genetically determined, it may be useful to consider HRQOL as a concept that has state (environmental) and trait (genetic) components. This distinction will allow us to explore new pathways of improving theory, methods, and clinical practice. The overarching novel questions concern the extent to which HRQOL components are environmentally or genetically determined, and which factors lead to lasting improvement. This distinction begs for new research approaches, such as time-sampling techniques and interdisciplinary research investigating the genetic variants of HRQOL. Distinguishing between those aspects that are amenable to change from those that are relatively fixed and stable will help better target specific support interventions

The Establishment of the GENEQOL Consortium to Investigate the Genetic Disposition of Patient-Reported Quality-of-Life Outcomes

To our knowledge, no comprehensive, interdisciplinary initiatives have been taken to examine the role of genetic variants on patient-reported quality-of-life outcomes. The overall objective of this paper is to describe the establishment of an international and interdisciplinary consortium, the GENEQOL Consortium, which intends to investigate the genetic disposition of patient-reported quality-of-life outcomes. We have identified five primary patient-reported quality-of-life outcomes as initial targets: negative psychological affect, positive psychological affect, self-rated physical health, pain, and fatigue. The first tangible objective of the GENEQOL Consortium is to develop a list of potential biological pathways, genes and genetic variants involved in these quality-of-life outcomes, by reviewing current genetic knowledge. The second objective is to design a research agenda to investigate and validate those genes and genetic variants of patient-reported quality-of-life outcomes, by creating large datasets. During its first meeting, the Consortium has discussed draft summary documents addressing these questions for each patient-reported quality-of-life outcome. A summary of the primary pathways and robust findings of the genetic variants involved is presented here. The research agenda outlines possible research objectives and approaches to examine these and new quality-of-life domains. Intriguing questions arising from this endeavor are discussed. Insight into the genetic versus environmental components of patient-reported quality-of-life outcomes will ultimately allow us to explore new pathways for improving patient care. If we can identify patients who are susceptible to poor quality of life, we will be able to better target specific clinical interventions to enhance their quality of life and treatment outcomes.quality of life, self-rated health, pain, fatigue, genetic disposition, Patient-Reported Quality-of-Life Outcomes

Parameter Efficient Deep Probabilistic Forecasting

Probabilistic time series forecasting is crucial in many application domains, such as retail, ecommerce, finance, and biology. With the increasing availability of large volumes of data, a number of neural architectures have been proposed for this problem. In particular, Transformer-based methods achieve state-of-the-art performance on real-world benchmarks. However, these methods require a large number of parameters to be learned, which imposes high memory requirements on the computational resources for training such models. To address this problem, we introduce a novel bidirectional temporal convolutional network that requires an order of magnitude fewer parameters than a common Transformer-based approach. Our model combines two temporal convolutional networks: the first network encodes future covariates of the time series, whereas the second network encodes past observations and covariates. We jointly estimate the parameters of an output distribution via these two networks. Experiments on four real-world datasets show that our method performs on par with four state-of-the-art probabilistic forecasting methods, including a Transformer-based approach and WaveNet, on two point metrics (sMAPE and NRMSE) as well as on a set of range metrics (quantile loss percentiles) in the majority of cases. We also demonstrate that our method requires significantly fewer parameters than Transformer-based methods, which means that the model can be trained faster with significantly lower memory requirements, which as a consequence reduces the infrastructure cost for deploying these models

Responsiveness: a reinvention of the wheel?

BACKGROUND: Since the mid eighties, responsiveness is considered to be a separate property of health status questionnaires distinct from reliability and validity. The aim of the study was to assess the strength of the relationship between internal consistency reliability, referring to an instrument's sensitivity to differences in health status among subjects at one point in time, and responsiveness referring to sensitivity to health status changes over time. METHODS: We used three different datasets comprising the scores of patients on the Barthel, the SIP and the GO-QoL instruments at two points in time. The internal consistency was reduced stepwise by removing the item that contributed most to a scale's reliability. We calculated the responsiveness expressed by the Standardized Response Mean (SRM) on each set of remaining items. The strength of the relationship between the thus obtained internal consistency coefficients and SRMs was quantified by Spearman rank correlation coefficients. RESULTS: Strong to perfect correlations (0.90 – 1.00) was found between internal consistency coefficients and SRMs for all instruments indicating, that the two can be used interchangeably. CONCLUSION: The results contradict the conviction that responsiveness is a separate psychometric property. The internal consistency coefficient adequately reflects an instrument's potential sensitivity to changes over time

Explaining quality of life with crisis theory

Based on the premises of crisis theory. we expected cancer patients in-crisis to report a poorer quality of life (QL) and cancer patients post-crisis to report a similar level of overall QL in comparison to healthy individuals. To explain these hypothesized findings, we expected the coping resources and strategies of patients in-crisis to be equally effective and those of patients post-crisis to be more effective as compared to those of healthy individuals. The sample consisted of: (a) 217 consecutive cancer patients in the acute phases of their illness (patients in-crisis) (b) 192 disease-free cancer patients (patients post-crisis): and (c) 201 randomly selected healthy individuals. Established measures of QL, self-esteem and neuroticism (coping resources) and coping behavior (coping strategies) were mailed. As expected. patients in-crisis reported a poorer QL (p <0.001) and patients post-crisis a similar overall QL as compared to healthy individuals. There were no significant or systematic differences between the mean levels of coping resources and strategies between the respective groups, Two-way analysis of variance indicated a group X coping resource interaction effect on overall QL for self-esteem (p <0.01). As expected, the amount of variance of overall QL explained by self-esteem was largest for patients post-crisis (27%) and comparable for patients in-crisis and healthy individuals (10 and 11%). Patients in-crisis were not able to make their coping resources and strategies more effective, whereas patients post-crisis seemed to have enhanced the effectiveness of self-esteem in restoring their QL as compared to healthy persons. Copyright (C) 2002 John Wiley Sons, Ltd

Hierarchical Forecasting at Scale

Existing hierarchical forecasting techniques scale poorly when the number of time series increases. We propose to learn a coherent forecast for millions of time series with a single bottom-level forecast model by using a sparse loss function that directly optimizes the hierarchical product and/or temporal structure. The benefit of our sparse hierarchical loss function is that it provides practitioners a method of producing bottom-level forecasts that are coherent to any chosen cross-sectional or temporal hierarchy. In addition, removing the need for a post-processing step as required in traditional hierarchical forecasting techniques reduces the computational cost of the prediction phase in the forecasting pipeline. On the public M5 dataset, our sparse hierarchical loss function performs up to 10% (RMSE) better compared to the baseline loss function. We implement our sparse hierarchical loss function within an existing forecasting model at bol, a large European e-commerce platform, resulting in an improved forecasting performance of 2% at the product level. Finally, we found an increase in forecasting performance of about 5-10% when evaluating the forecasting performance across the cross-sectional hierarchies that we defined. These results demonstrate the usefulness of our sparse hierarchical loss applied to a production forecasting system at a major e-commerce platform