Weather Files for the Calibration of Building Energy Models

In the fight against climate change, energy modeling is a key tool used to analyze the performance of proposed energy conservation measures for buildings. Studies on the integration of photovoltaic energy in buildings must use calibrated building energy models, as only with them is the demand curve real, and the savings obtained at the self-consumption level, energy storage in the building, or feed into the grid are accurate. The adjustment process of a calibrated model depends on aspects inherent to the building properties (envelope parameters, internal loads, use schedules) as well as external to them (weather, ground properties, etc.). Naturally, the uncertainty of each is essential to obtaining good results. As for the meteorological data, it is preferable to use data from a weather station located in the building or its surroundings, although this is not always possible due to the cost of the initial investment and its maintenance. As a result, weather stations with public access to their data, such as those located at airports or specific locations in cities, are largely used to perform calibrations of building energy models, making it challenging to converge the simulated model with measured data. This research sheds light on how this obstacle can be overcome by using weather data provided by a third-party company, bridging the gap between reality and energy models. For this purpose, calibrations of the two buildings proposed in Annex 58 were performed with different weather configurations, using the mean absolute error (MAE) uncertainty index and Spearman’s rank correlation coefficient (rho) as comparative measures. An optimal and cost-effective solution was found as an alternative to an on-site weather station, based on the use of a single outdoor temperature sensor in combination with third-party weather data, achieving a robust and reliable building energy model

GaAs nanoscale membranes: prospects for seamless integration of III–Vs on silicon

The growth of compound semiconductors on silicon has been widely sought after for decades, but reliable methods for defect-free combination of these materials have remained elusive. Recently, interconnected GaAs nanoscale membranes have been used as templates for the scalable integration of nanowire networks on III-V substrates. Here, we demonstrate how GaAs nanoscale membranes can be seamlessly integrated on silicon by controlling the density of nuclei in the initial stages of growth. We also correlate the absence or presence of defects with the existence of a single or multiple nucleation regime for the single membranes. Certain defects exhibit well-differentiated spectroscopic features that we identify with cathodoluminescence and micro-photoluminescence techniques. Overall, this work presents a new approach for the seamless integration of compound semiconductors on silicon

A pilot 1-year follow-up randomised controlled trial comparing metacognitive training to psychoeducation in schizophrenia: effects on insight

Poor insight in schizophrenia spectrum disorders (SSD) is linked with negative outcomes. This single-centre, assessor-blind, parallel-group 1-year follow-up randomised controlled trial (RCT) tested whether metacognitive training (MCT) (compared to psychoeducation) may improve insight and outcomes in outpatients with SSD assessed: at baseline (T0); after treatment (T1) and at 1-year follow-up (T2). Insight (primary outcome) was measured with (i) the Schedule for Assessment of Insight-Expanded version- (SAI-E), including illness recognition (IR), symptom relabelling (SR), treatment compliance (TC) and total insight scores (TIS); and (ii) the Beck Cognitive Insight Scale (BCIS). Between-group comparisons were nonsignificant, while within the MCT group (but not within controls) there was a significant medium effect size for improved TIS at T2 (d = 0.67, P = 0.02). Secondary outcomes included cognitive measures: Jumping to Conclusions (JTC), Theory of Mind (ToM), plus symptom severity and functioning. Compared to psychoeducation, MCT improved the PANSS excitement (d = 1.21, P = 0.01) and depressed (d = 0.76, P = 0.05) factors at T2; and a JTC task both at T1 (P = 0.016) and at T2 (P = 0.031). Participants in this RCT receiving MCT showed improved insight at 1-year follow-up, which was associated with better mood and reduced JTC cognitive bias. In this pilot study, no significant benefits on insight of MCT over psychoeducation were detected, which may have been due to insufficient power

Sit-to-Stand Analysis in the Wild using Silhouettes for Longitudinal Health Monitoring

We present the first fully automated Sit-to-Stand or Stand-to-Sit (StS) analysis framework for long-term monitoring of patients in free-living environments using video silhouettes. Our method adopts a coarse-to-fine time localisation approach, where a deep learning classifier identifies possible StS sequences from silhouettes, and a smart peak detection stage provides fine localisation based on 3D bounding boxes. We tested our method on data from real homes of participants and monitored patients undergoing total hip or knee replacement. Our results show 94.4% overall accuracy in the coarse localisation and an error of 0.026 m/s in the speed of ascent measurement, highlighting important trends in the recuperation of patients who underwent surgery

Can metacognitive interventions improve insight in schizophrenia spectrum disorders? A systematic review and meta-analysis

Background: Patients with schizophrenia spectrum disorders (SSD) tend to lack insight, which is linked to poor outcomes. The effect size of previous treatments on insight changes in SSD has been small. Metacognitive interventions may improve insight in SSD, although this remains unproved. Methods: We carried out a systematic review and meta-analysis of randomized controlled trials (RCTs) to examine the effects of metacognitive interventions designed for SSD, namely Metacognitive Training (MCT) and Metacognitive Reflection and Insight Therapy (MERIT), on changes in cognitive and clinical insight at post-treatment and at follow-up. Results: Twelve RCTs, including 10 MCT RCTs (n = 717 participants) and two MERIT trials (n = 90), were selected, totalling N = 807 participants. Regarding cognitive insight six RCTs (n = 443) highlighted a medium effect of MCT on self-reflectiveness at post-treatment, d = 0.46, p < 0.01, and at follow-up, d = 0.30, p < 0.01. There was a small effect of MCT on self-certainty at post-treatment, d = −0.23, p = 0.03, but not at follow-up. MCT was superior to controls on an overall Composite Index of cognitive insight at post-treatment, d = 1.11, p < 0.01, and at follow-up, d = 0.86, p = 0.03, although we found evidence of heterogeneity. Of five MCT trials on clinical insight (n = 244 participants), which could not be meta-analysed, four of them favoured MCT compared v. control. The two MERIT trials reported conflicting results. Conclusions: Metacognitive interventions, particularly Metacognitive Training, appear to improve insight in patients with SSD, especially cognitive insight shortly after treatment. Further long-term RCTs are needed to establish whether these metacognitive interventions-related insight changes are sustained over a longer time period and result in better outcomes

A Robust Statistical Method for Association-Based eQTL Analysis

Background: It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS) is statistical inference of linkage disequilibrium (LD) between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation. Methodology: We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations. Results/Conclusions: The analyses show that the new method confers an improved statistical power for detecting genuin

Fluctuations in measured radioactive decay rates inside a modified Faraday cage: Correlations with space weather

[EN] For several years, reports have been published about fluctuations in measured radioactive decay time-series and in some instances linked to astrophysical as well as classical environmental influences. Anomalous behaviors of radioactive decay measurement and measurement of capacitance inside and outside a modified Faraday cage were documented by our group in previous work. In the present report, we present an in-depth analysis of our measurement with regard to possible correlations with space weather, i.e. the geomagnetic activity (GMA) and cosmic-ray activity (CRA). Our analysis revealed that the decay and capacitance time-series are statistically significantly correlated with GMA and CRA when specific conditions are met. The conditions are explained in detail and an outlook is given on how to further investigate this important finding. Our discovery is relevant for all researchers investigating radioactive decay measurements since they point out that the space weather condition during the measurement is relevant for partially explaining the observed variability.This work has been partially financed by: grant no. 20170764 (Equipos de deteccion, regulacion e informacion en el sector de los sistemas inteligentes de transporte (ITS). Nuevos modelos y ensayos de compatibilidad y verificacion de funcionamiento) (Spain), by grant no. RTI2018-102256-B-I00 (Spain), by the Generalitat Valenciana (Spain) under project Bioingenieria de las Radiaciones Ionizantes. Biorad (PROMETEO/2018/035) and the project MEMO RADION (IDIFEDER/2018/038) co-financed by the Programa Operativo del Fondo Social Europeo 2014-2020", and by grant No.075-00845-20-01 (Russia).Milián-Sánchez, V.; Scholkmann, F.; Fernández De Córdoba, P.; Mocholí Salcedo, A.; Mocholí-Belenguer, F.; Iglesias-Martínez, ME.; Castro-Palacio, JC.... (2020). 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Pb(II) Induces Scramblase Activation and Ceramide-Domain Generation in Red Blood Cells

The mechanisms of Pb(II) toxicity have been studied in human red blood cells using confocal microscopy, immunolabeling, fluorescence-activated cell sorting and atomic force microscopy. The process follows a sequence of events, starting with calcium entry, followed by potassium release, morphological change, generation of ceramide, lipid flip-flop and finally cell lysis. Clotrimazole blocks potassium channels and the whole process is inhibited. Immunolabeling reveals the generation of ceramide-enriched domains linked to a cell morphological change, while the use of a neutral sphingomyelinase inhibitor greatly delays the process after the morphological change, and lipid flip-flop is significantly reduced. These facts point to three major checkpoints in the process: first the upstream exchange of calcium and potassium, then ceramide domain formation, and finally the downstream scramblase activation necessary for cell lysis. In addition, partial non-cytotoxic cholesterol depletion of red blood cells accelerates the process as the morphological change occurs faster. Cholesterol could have a role in modulating the properties of the ceramide-enriched domains. This work is relevant in the context of cell death, heavy metal toxicity and sphingolipid signaling.AGA was a predoctoral student supported by the Basque Government and later by the University of the Basque Country (UPV/EHU). This work was also supported in part by grants from the Spanish Government (FEDER/MINECO BFU 2015-66306-P to F.M.G. and A.A.) and the Basque Government (IT849-13 to F.M.G. and IT838-13 to A.A.), and by the Swiss National Science Foundation

Virus Adaptation by Manipulation of Host's Gene Expression

Viruses adapt to their hosts by evading defense mechanisms and taking over cellular metabolism for their own benefit. Alterations in cell metabolism as well as side-effects of antiviral responses contribute to symptoms development and virulence. Sometimes, a virus may spill over from its usual host species into a novel one, where usually will fail to successfully infect and further transmit to new host. However, in some cases, the virus transmits and persists after fixing beneficial mutations that allow for a better exploitation of the new host. This situation would represent a case for a new emerging virus. Here we report results from an evolution experiment in which a plant virus was allowed to infect and evolve on a naïve host. After 17 serial passages, the viral genome has accumulated only five changes, three of which were non-synonymous. An amino acid substitution in the viral VPg protein was responsible for the appearance of symptoms, whereas one substitution in the viral P3 protein the epistatically contributed to exacerbate severity. DNA microarray analyses show that the evolved and ancestral viruses affect the global patterns of host gene expression in radically different ways. A major difference is that genes involved in stress and pathogen response are not activated upon infection with the evolved virus, suggesting that selection has favored viral strategies to escape from host defenses