Probabilistic load forecasting for building energy models

In the current energy context of intelligent buildings and smart grids, the use of load forecasting to predict future building energy performance is becoming increasingly relevant. The prediction accuracy is directly influenced by input uncertainties such as the weather forecast, and its impact must be considered. Traditional load forecasting provides a single expected value for the predicted load and cannot properly incorporate the effect of these uncertainties. This research presents a methodology that calculates the probabilistic load forecast while accounting for the inherent uncertainty in forecast weather data. In the recent years, the probabilistic load forecasting approach has increased in importance in the literature but it is mostly focused on black-box models which do not allow performance evaluation of specific components of envelope, HVAC systems, etc. This research fills this gap using a white-box model, a building energy model (BEM) developed in EnergyPlus, to provide the probabilistic load forecast. Through a Gaussian kernel density estimation (KDE), the procedure converts the point load forecast provided by the BEM into a probabilistic load forecast based on historical data, which is provided by the building’s indoor and outdoor monitoring system. An hourly map of the uncertainty of the load forecast due to the weather forecast is generated with different prediction intervals. The map provides an overview of different prediction intervals for each hour, along with the probability that the load forecast error is less than a certain value. This map can then be applied to the forecast load that is provided by the BEM by applying the prediction intervals with their associated probabilities to its outputs. The methodology was implemented and evaluated in a real school building in Denmark. The results show that the percentage of the real values that are covered by the prediction intervals for the testing month is greater than the confidence level (80%), even when a small amount of data are used for the creation of the uncertainty map; therefore, the proposed method is appropriate for predicting the probabilistic expected error in load forecasting due to the use of weather forecast data

Characteristics of post-menopausal women with genitourinary syndrome of menopause: Implications for vulvovaginal atrophy diagnosis and treatment selection.

BACKGROUND: Vulvovaginal atrophy (VVA), also known as genitourinary syndrome of menopause, exerts a negative impact on the sexuality, health and quality of life of post-menopausal women. A better understanding of post-menopausal women's profiles as defined by their attitude and behaviours in relation to their VVA symptoms may improve public health policies and will allow appropriate targeting of public health campaigns. These improvements may help women of middle and advanced age recover and maintain their quality of life. In this study, we analysed the attitudes of post-menopausal women, aged 45-74 years, with VVA symptoms from five European countries, with the aim of identifying profile markers to improve healthcare strategies. METHODS: Two consecutive cross-sectional studies were conducted in five European countries (the UK, France, Spain, Germany and Italy). An initial exploratory study (n=69) was based on interviews and then an analytical study (n=749) was based on online surveys to validate women's profiles by means of a multi-level approach. RESULTS: We identified eight profiles: self-treater, pragmatic, vivacious, reserved, silent sufferer, expressive, stoic and sad. The percentage distribution varied among the countries. The 'pragmatic', 'vivacious' and 'expressive' women were the most proactive, talkative and open with their healthcare professional, whereas women with the 'reserved' and 'stoic' profiles showed less interest in searching for information about their VVA symptoms, either from their healthcare professional or from other sources. CONCLUSIONS: The attitudes and behaviours of post-menopausal women in relation to their VVA allow for the clear definition of a series of profiles with varying representation across countries. This study reveals the importance of identifying post-menopausal women's profiles to develop interventions to help them overcome barriers to the diagnosis, management and treatment of VVA

Effects of increasing the affinity of CarD for RNA polymerase on Mycobacterium tuberculosis growth, rRNA transcription, and virulence

CarD is an essential RNA polymerase (RNAP) interacting protein in Mycobacterium tuberculosis that stimulates formation of RNAP-promoter open complexes. CarD plays a complex role in M. tuberculosis growth and virulence that is not fully understood. Therefore, to gain further insight into the role of CarD in M. tuberculosis growth and virulence, we determined the effect of increasing the affinity of CarD for RNAP. Using site-directed mutagenesis guided by crystal structures of CarD bound to RNAP, we identified amino acid substitutions that increase the affinity of CarD for RNAP. Using these substitutions, we show that increasing the affinity of CarD for RNAP increases the stability of the CarD protein in M. tuberculosis. In addition, we show that increasing the affinity of CarD for RNAP increases the growth rate in M. tuberculosis without affecting 16S rRNA levels. We further show that increasing the affinity of CarD for RNAP reduces M. tuberculosis virulence in a mouse model of infection despite the improved growth rate in vitro. Our findings suggest that the CarD-RNAP interaction protects CarD from proteolytic degradation in M. tuberculosis, establish that growth rate and rRNA levels can be uncoupled in M. tuberculosis and demonstrate that the strength of the CarD-RNAP interaction has been finely tuned to optimize virulence. IMPORTANCE Mycobacterium tuberculosis, the causative agent of tuberculosis, remains a major global health problem. In order to develop new strategies to battle this pathogen, we must gain a better understanding of the molecular processes involved in its survival and pathogenesis. We have previously identified CarD as an essential transcriptional regulator in mycobacteria. In this study, we detail the effects of increasing the affinity of CarD for RNAP on transcriptional regulation, CarD protein stability, and virulence. These studies expand our understanding of the global transcription regulator CarD, provide insight into how CarD activity is regulated, and broaden our understanding of prokaryotic transcription

Reproducibility of the energy metabolism response to an oral glucose tolerance test: influence of a postcalorimetric correction procedure

Purpose Metabolic fexibility (MetF), which is a surrogate of metabolic health, can be assessed by the change in the respiratory exchange ratio (RER) in response to an oral glucose tolerance test (OGTT). We aimed to determine the day-to-day reproducibility of the energy expenditure (EE) and RER response to an OGTT, and whether a simulation-based postcalorimetric correction of metabolic cart readouts improves day-to-day reproducibility. Methods The EE was assessed (12 young adults, 6 women, 27±2 years old) using an Omnical metabolic cart (Maastricht Instruments, Maastricht, The Netherlands) after an overnight fast (12 h) and after a 75-g oral glucose dose on 2 separate days (48 h). On both days, we assessed EE in 7 periods (one 30-min baseline and six 15-min postprandial). The ICcE was performed immediately after each recording period, and capillary glucose concentration (using a digital glucometer) was determined. Results We observed a high day-to-day reproducibility for the assessed RER (coefcients of variation [CV]<4%) and EE (CVs<9%) in the 7 diferent periods. In contrast, the RER and EE areas under the curve showed a low day-to-day reproducibility (CV=22% and 56%, respectively). Contrary to our expectations, the postcalorimetric correction procedure did not infuence the day-to-day reproducibility of the energy metabolism response, possibly because the Omnical’s accuracy was~100%. Conclusion Our study demonstrates that the energy metabolism response to an OGTT is poorly reproducible (CVs>20%) even using a very accurate metabolic cart. Furthermore, the postcalorimetric correction procedure did not infuence the day-to-day reproducibility. Trial registration NCT04320433; March 25, 2020.Funding for open access charge: Universidad de Granada / CBUA. Supported by the Spanish Ministry of Economy and Competitiveness via Retos de la Sociedad grant DEP2016-79512-R (to JRR), and European Regional Development Funds (ERDF); Spanish Ministry of Education grant (FPU15/04059 to JMAA; and FPU19/01609 to LJ-F); the University of Granada Plan Propio de Investigación 2016-Excellence actions: Unit of Excellence on Exercise and Health (to JRR)—Plan Propio de Investigación 2018 and 2020 Programa Contratos-Puente and Programa Perfeccionamiento de Doctores (to GS-D, and to JMAA respectively); Junta de Andalucía, Consejería de Conocimiento, Investigación y Universidades grant SOMM17/6107/UGR (to JRR) via the ERDF; and the Fundación Alfonso Martín Escudero (to GS-D)

Modelo de gestión para un control de calidad eficiente en edificios de nueva planta

The management of the quality control of each building process is usually set up in Spain from different levels of demand. This work tries to obtain a model of reference, to compare the quality control of the building process of a specific product (building), and to be able to evaluate its warranty level. In the quest of this purpose, we take credit of specialized sources and 153 real cases of Quality Control were carefully revised using a multi-judgment method. Applying different techniques to get a specific valuation (impartial) of the input parameters through Delphi’s method (17 experts query), whose matrix treatment with the Fuzzy-QFD tool condenses numerical references through a weighted distribution of the selected functions and their corresponding conditioning factors. The model thus obtained (M153) is useful in order to have a quality control reference to meet the expectations of the quality.La gestión del control de calidad en cada proceso edificatorio se plantea habitualmente en España desde distintos niveles de exigencia. El presente trabajo tiene por objeto obtener un modelo de referencia para comparar el control del proceso edificatorio realizado sobre un producto concreto (edificio) y poder evaluar su nivel de garantía. Para ello recurrimos a fuentes especializadas así como al estudio de 153 casos reales de expedientes de control de calidad utilizando una metodología del tipo multicriterio. Se aplican técnicas conducentes a una valoración concreta (objetiva) de los parámetros de entrada mediante el método Delphi (consulta a 17 expertos), cuyo tratamiento matricial con la herramienta Fuzzy-QFD condensa referencias numéricas a través de un reparto de pesos entre las funciones seleccionadas y sus correspondientes factores intervinientes. El modelo así obtenido (M153) es útil como referente óptimo de las actuaciones de control que conllevan el cumplimiento de las expectativas de calidad

Epitaxial integration of CoFe₂O₄ thin films on Si (001) surfaces using TiN buffer layers

Epitaxial cobalt ferrite thin films with strong in-plane magnetic anisotropy have been grown on Si (001) substrates using a TiN buffer layer. The epitaxial films have been grown by ion beam sputtering using either metallic, CoFe₂, or ceramic, CoFe₂2O₄, targets. X-ray diffraction (XRD) and Rutherford spectrometry (RBS) in random and channeling configuration have been used to determine the epitaxial relationship CoFe₂O₄ [100]/TiN [100]/Si [100]. Mossbauer spectroscopy, in combination with XRD and RBS, has been used to determine the composition and structure of the cobalt ferrite thin films. The TiN buffer layer induces a compressive strain in the cobalt ferrite thin films giving rise to an in-plane magnetic anisotropy. The degree of in- plane anisotropy depends on the lattice mismatch between CoFe₂O₂ and TiN, which is larger for CoFe₂O₄ thin films grown on the reactive sputtering process with ceramic targets

Challenges in the COVID-19 vaccination era: Prioritization of vaccines among essential workers in Mexico

The coronavirus disease-2019 (COVID-19) pandemic gave rise to a massive global health concern that has placed an unprecedented strain on healthcare systems, education and economy. The recent vaccine roll-out gave humanity a glimpse of hope. However, more than 50% of the vaccine supply has been acquired by high-income countries, forcing low- and middle-income countries to prioritize who should be vaccinated. In Mexico, the first phase of the vaccination program prioritized healthcare personnel working in front-line COVID-19 public institutions. The second phase was planned for the remaining healthcare workers attending at both COVID and non-COVID areas. The government, however, aiming to reopen schools, decided to vaccinate teachers instead. This raised several concerns, since Mexico tops the ranking of deaths among healthcare workers due to COVID-19 worldwide. Furthermore, the possible framing of vaccines as a political tool has caused commotion among the Mexican people and media, especially since 2021 is the Midterm Election year in Mexico, and the Teachers’ Union has historically played an essential role in this matter. Therefore, it is relevant to share the vaccination experience in resource-constrained settings to provide help and advice to reach an optimal strategy and deflate this pandemic

Model predictive control optimization via genetic algorithm using a detailed building energy model

There is growing concern about how to mitigate climate change in which the reduction of CO2 emissions plays an important role. Buildings have gained attention in recent years since they are responsible for around 30% of greenhouse gases. In this context, advance control strategies to optimize HVAC systems are necessary because they can provide significant energy savings whilst maintaining indoor thermal comfort. Simulation-based model predictive control (MPC) procedures allow an increase in building energy performance through the smart control of HVAC systems. The paper presents a methodology that overcomes one of the critical issues in using detailed building energy models in MPC optimizations¿computational time. Through a case study, the methodology explains how to resolve this issue. Three main novel approaches are developed: a reduction in the search space for the genetic algorithm (NSGA-II) thanks to the use of the curve of free oscillation; a reduction in convergence time based on a process of two linked stages; and, finally, a methodology to measure, in a combined way, the temporal convergence of the algorithm and the precision of the obtained solution

Forest productivity in southwestern Europe controlled by coupled North Atlantic and Atlantic Multidecadal Oscillations

The North Atlantic Oscillation (NAO) depicts annual and decadal oscillatory modes ofvariability responsible for dry spells over the European continent. The NAO therefore holds agreat potential to evaluate the role, as carbon sinks, of water-limited forests under climatechange. However, uncertainties related to inconsistent responses of long-term forestproductivity to NAO have so far hampered firm conclusions on its impacts. We hypothesizethat, in part, such inconsistencies might have their origin in periodical sea surfacetemperature anomalies in the Atlantic Ocean (i.e., Atlantic Multidecadal Oscillation, AMO).Here we show strong empirical evidence in support of this hypothesis using 120 years ofperiodical inventory data from Iberian pine forests. Our results point to AMO+ NAO+ andAMO&#8722;NAO&#8722; phases as being critical for forest productivity, likely due to decreased winterwater balance and abnormally low winter temperatures, respectively. Our findings could beessential for the evaluation of ecosystem functioning vulnerabilities associated with increasedclimatic anomalies under unprecedented warming conditions in the Mediterranean

Methodology for the quantification of the impact of weather forecasts in predictive simulation models

The use of Building Energy Models (BEM) has become widespread to reduce building energy consumption. Projection of the model in the future to know how different consumption strategies can be evaluated is one of the main applications of BEM. Many energy management optimization strategies can be used and, among others, model predictive control (MPC) has become very popular nowadays. When using models for predicting the future, we have to assume certain errors that come from uncertainty parameters. One of these uncertainties is the weather forecast needed to predict the building behavior in the near future. This paper proposes a methodology for quantifying the impact of the error generated by the weather forecast in the building¿s indoor climate conditions and energy demand. The objective is to estimate the error introduced by the weather forecast in the load forecasting to have more precise predicted data. The methodology employed site-specific, near-future forecast weather data obtained through online open access Application Programming Interfaces (APIs). The weather forecast providers supply forecasts up to 10 days ahead of key weather parameters such as outdoor temperature, relative humidity, wind speed and wind direction. This approach uses calibrated EnergyPlus models to foresee the errors in the indoor thermal behavior and energy demand caused by the increasing day-ahead weather forecasts. A case study investigated the impact of using up to 7-day weather forecasts on..