Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
3,764
result(s) for
"Vidal, R"
Sort by:
Energy Management Systems in Higher Education Institutions’ Buildings
This study reviews the methods used to implement energy management systems (EnMS) in higher education institutions (HEIs) and their impact on improving energy performance considering their relationship with the requirements for an EnMS according to ISO 50001. From 2310 articles, 136 articles and 5 technical reports related to EnMS and energy efficiency were selected and analyzed. A synthesis of the major actions taken by HEIs to enhance their energy performance is presented, including energy management strategies, methods for measuring and estimating consumption, occupant behavior models that influence energy use, barriers to energy efficiency in HEIs buildings, and future challenges. It was found that studies on building energy management systems often do not incorporate an analysis of CO2 emissions reduction. Funding for this research is driven by directives and policies related to energy performance. These results should assist HEIs seeking to implement an EnMS to improve their energy performance and reduce CO2 emissions, thereby contributing to energy security, climate change mitigation, and fostering a new culture of energy use and consumption. It was also found that, although most studies do not explicitly mention the ISO 50001 standard, all of them comply with at least one of its requirements. Additionally, 27% of energy management strategies focus on operational aspects, while 26% involve energy audits, primarily through measurement, estimation, forecasting, energy reviews, and the establishment of an energy baseline (EnBL).
Journal Article
B chromosome retrotransposed sequences persist through speciation, contributing to genomic and regulatory innovations in the fish genus Psalidodon (Characiformes, Acestrorhamphidae)
B chromosomes are supernumerary genetic elements rich in repetitive DNA. Many species within the fish genus Psalidodon possess a large metacentric B chromosome that exhibits signs of recent retrotransposon activity, resulting in truncated pseudogenic copies of standard A chromosomes genes, specifically sbno2 and simc1 . We aimed to characterize the structure of the B chromosome pseudogenes sbno2-B and simc1-B and their evolutionary history in four B chromosome variants of three Psalidodon species, as well as their expression patterns in Psalidodon paranae individuals with a single B chromosome (1B). Our findings suggest that the retrotransposition process of each gene occurred in an ancestral B chromosome, which later diverged into distinct trajectories within each species following speciation. In the high-copy B chromosomes, the sbno2-B pseudogene shows dozens of interspersed copies, while the simc1-B pseudogene usually shows three copies arranged in tandem. In Psalidodon paranae 1B individuals, underexpression of the sbno2 and simc1 genes in ovaries indicates that the pseudogenic B copies probably influence gene expression through non-coding RNA interference mechanisms. This shows that the retrotransposon activity on B chromosomes generates genomic diversity and neofunctionalization, impacting gene regulatory networks, and possibly contributing to the persistence of B chromosome in populations.
Journal Article
Nuclear structure advancements with multi-nucleon transfer reactions
Multi-Nucleon Transfer (MNT) reactions have been used for decades as a reaction mechanism, in order to populate excited states in nuclei far from stability and to perform nuclear structure studies. Nevertheless, the development of set-ups involving high acceptance tracking magnetic spectrometers (mainly existing in Europe), coupled with the Advanced GAmma Tracking Array (AGATA) opens new possibilities, especially if they are used in conjunction with high-intensity stable beams or ISOL RIBs. In this article, we will discuss the capabilities of such set-ups aiming at different goals, including complete information in high-resolution spectroscopy as well as lifetime measurements.
Journal Article
Simulation of the AGATA spectrometer and coupling with ancillary detectors
The design study of the AGATA array began with the development of the AGATA simulation code using GEANT4. The latter played a key part in the final design of the array and provided a cost effective solution for the early development of the tracking algorithm. The code has since been maintained and developed by the collaboration to provide more realistic simulations, with reaction chambers, ancillary detectors and surrounding mechanical structures completing the entire setup.
Journal Article
Improving deep learning performance with missing values via deletion and compensation
Missing values in a dataset is one of the most common difficulties in real applications. Many different techniques based on machine learning have been proposed in the literature to face this problem. In this work, the great representation capability of the stacked denoising auto-encoders is used to obtain a new method of imputating missing values based on two ideas: deletion and compensation. This method improves imputation performance by artificially deleting values in the input features and using them as targets in the training process. Nevertheless, although the deletion of samples is demonstrated to be really efficient, it may cause an imbalance between the distributions of the training and the test sets. In order to solve this issue, a compensation mechanism is proposed based on a slight modification of the error function to be optimized. Experiments over several datasets show that the deletion and compensation not only involve improvements in imputation but also in classification in comparison with other classical techniques.
Journal Article
Complete autoencoders for classification with missing values
It has been demonstrated that modified denoising stacking autoencoders (MSDAEs) serve to implement high-performance missing value imputation schemes. On the other hand, complete MSDAE (CMSDAE) classifiers, which extend their inputs with target estimates from an auxiliary classifier and are layer by layer trained to recover both the observation and the target estimates, offer classification results that are better than those provided by MSDAEs. As a consequence, investigating whether CMSDAEs can improve the MSDAEs imputation processes has an obvious practical importance. In this correspondence, two types of imputation mechanisms with CMSDAEs are considered. The first is a direct procedure in which the CMSDAE output is just the target. The second mechanism is suggested by the presence of the targets in the vectors to be autoencoded, and it uses the well-known multitask learning (MTL) ideas, including the observations as a secondary task. Experimental results show that these CMSDAE structures increase the quality of the missing value imputations, in particular the MTL versions. They give the best result in 5 out of 6 missing value problems.
Journal Article
Assessing Predictive Value of SARS-CoV-2 Epitope-Specific CD8+ T-Cell Response in Patients with Severe Symptoms
Specific T cell responses against SARS-CoV-2 provided an overview of acquired immunity during the pandemic. Anti-SARS-CoV-2 immunity determines the severity of acute illness, but also might be related to the possible persistence of symptoms (long COVID). We retrospectively analyzed ex vivo longitudinal CD8+ T cell responses in 26 COVID-19 patients diagnosed with severe disease, initially (1 month) and long-term (10 months), and in a cohort of 32 vaccinated healthcare workers without previous SARS-CoV-2 infection. We used peptide-human leukocyte antigen (pHLA) dextramers recognizing 26 SARS-CoV-2-derived epitopes of viral and other non-structural proteins. Most patients responded to at least one of the peptides studied, mainly derived from non-structural ORF1ab proteins. After 10 months follow-up, CD8+ T cell responses were maintained at long term and reaction against certain epitopes (A*01:01-ORF1ab1637) was still detected and functional, showing a memory-like phenotype (CD127+ PD-1+). The total number of SARS-CoV-2-specific CD8+ T cells was significantly associated with protection against long COVID in these patients. Compared with vaccination, infected patients showed a less effective immune response to spike protein-derived peptides restricted by HLA. So, the A*01:01-S865 and A*24:02-S1208 dextramers were only recognized in vaccinated individuals. We conclude that initial SARS-CoV-2-specific CD8+ T cell response could be used as a marker to understand the evolution of severe disease and post-acute sequelae after SARS-CoV-2 infection.
Journal Article
Economic Analysis of a Multi-Sided Platform for Sensor-Based Services in the Internet of Things
A business model for sensor-based services is proposed where a platform creates a multi-sided market. The business model comprises a platform that serves as an intermediary between human users, app developers, and sensor networks, so that the users use the apps and the apps process the data supplied by the sensor networks. The platform, acting as a monopolist, posts a fee for each of the three sides so as to maximize its profit. This business model intends to mimic the market-creating innovation that main mobile apps platforms have generated in the smartphone sector. We conduct an analysis of the profit maximization problem faced by the platform, show that optimum prices exist for any parameter value, and show that these prices always induce an equilibrium in the number of agents from each side that join the platform. We show that the relative strength of the value that advertisers attach to the users determines the platform price structure. Depending on the value of this relative strength, two alternative subsidizing strategies are feasible: to subsidize either the users’ subscription or the developers’ registration. Finally, all agents benefit from an increase in the population at any of the three sides. This result provides a rationale for incentivizing not only the user participation, but also the entry of developer undertakings and the deployment of wireless sensor network infrastructure.
Journal Article
Influenza A infections: predictors of disease severity
Influenza affects approximately 10% of the world’s population annually. It is associated with high morbidity and mortality rates due to its propensity to progress to severe acute respiratory infection, leading to 10–40% of hospitalized patients needing intensive care. Characterizing the multifactorial predictors of poor prognosis is essential for developing strategies against this disease. This study aimed to identify predictors of disease severity in influenza A-infected (IFA-infected) patients and to propose a prognostic score. A retrospective cross-sectional study was conducted with 142 IFA-infected out- and inpatients treated at a tertiary hospital between 2010 and 2018. The viral subtypes, hemagglutinin mutations, viral load, IL-28B SNPs, and clinical risk factors were evaluated according to the patient’s ICU admission. Multivariate analysis identified the following risk factors for disease severity: neuromuscular diseases (OR = 7.02; 95% CI = 1.18–41.75; p = 0.032), cardiovascular diseases (OR = 5.47; 95% CI = 1.96–15.27; p = 0.001), subtype (H1N1) pdm09 infection (OR = 2.29; 95% CI = 1.02–5.15; p = 0.046), and viral load (OR = 1.43; 95% CI = 1.09–1.88; p = 0.009). The prognosis score for ICU admission is based on these predictors of severity presented and ROC curve AUC = 0.812 (p < 0.0001). Our results identified viral and host predictors of disease severity in IFA-infected patients, yielding a prognostic score that had a high performance in predicting the IFA patients’ ICU admission and better results than a viral load value alone. However, its implementation in health services needs to be validated in a broader population.
Journal Article