Massive Database Generation for 2.5D Borehole Electromagnetic Measurements using Refined Isogeometric Analysis

Borehole resistivity measurements are routinely inverted in real-time during geosteering operations. The inversion process can be efficiently performed with the help of advanced artificial intelligence algorithms such as deep learning. These methods require a massive dataset that relates multiple Earth models with the corresponding borehole resistivity measurements. In here, we propose to use an advanced numerical method —refined isogeometric analysis (rIGA)— to perform rapid and accurate 2.5D simulations and generate databases when considering arbitrary 2D Earth models. Numerical results show that we can generate a meaningful synthetic database composed of 100,000 Earth models with the corresponding measurements in 56 hours using a workstation equipped with two CPUs.European POCTEFA 2014–2020 Project PIXIL (EFA362/19); The grant ‘‘Artificial Intelligence in BCAM number EXP. 2019/0043

Epithelial morphometric alterations and mucosecretory responses in the nasal cavity of mice chronically exposed to hydrothermal emissions

Air pollutants (either of natural or anthropogenic origin) represent a considerable environmental risk to human health by affecting the respiratory system and causing respiratory disorders. In this study, we investigate the effects of chronic exposure to hydrothermal emissions on the nasal cavity of mice since it is the first and the most exposed region of the respiratory system. This study, carried in S. Miguel Island, Azores—Portugal, used Mus musculus as a bioindicator species. Mice were captured in an area with non-eruptive active volcanism (Furnas Village) and another area without volcanism (Rabo de Peixe, reference site). The hydrothermal emissions present at Furnas Village are characterized by the continuous release of several gases (CO₂, H₂S, ²²²Rn) along with metals (e.g. Hg, Cd, Zn, Al) and particulate matter into the environment. We test the hypothesis whether chronic exposure to this specific type of pollution causes epithelial morphometric, mucosecretory and neuronal alterations on the nasal cavity. Thickness measurements were taken in the squamous, respiratory and olfactory epithelia. The relative density of cell types (basal, support and neurons) was also assessed in the olfactory epithelium and the mucosecretory activity was determined in the lateral nasal glands, Bowman’s gland and goblet cells. Mice chronically exposed to hydrothermal emissions presented thinner olfactory epithelia and lesser mucous production, which could result in loss of olfactory capabilities as well as a decrease in the protective function provided by the mucous to the lower respiratory tract. For the first time, it is demonstrated that, in mice, this specific type of non-eruptive active volcanism causes epithelial and mucosecretory alterations, leading to the loss of olfactory capabilities.Ricardo Camarinho is currently supported by a Ph.D. fellowship grant (M3.1.a/F/048/2015) from Fundo Regional da Ciencia (Regional Government of the Azores).info:eu-repo/semantics/publishedVersio

Resilience to the effects of social stress on vulnerability to developing drug addiction

We review the still scarce but growing literature on resilience to the effects of social stress on the rewarding properties of drugs of abuse. We define the concept of resilience and how it is applied to the field of drug addiction research. We also describe the internal and external protective factors associated with resilience, such as individual behavioral traits and social support. We then explain the physiological response to stress and how it is modulated by resilience factors. In the subsequent section, we describe the animal models commonly used in the study of resilience to social stress, and we focus on the effects of chronic social defeat (SD), a kind of stress induced by repeated experience of defeat in an agonistic encounter, on different animal behaviors (depression- and anxiety-like behavior, cognitive impairment and addiction-like symptoms). We then summarize the current knowledge on the neurobiological substrates of resilience derived from studies of resilience to the effects of chronic SD stress on depression- and anxiety-related behaviors in rodents. Finally, we focus on the limited studies carried out to explore resilience to the effects of SD stress on the rewarding properties of drugs of abuse, describing the current state of knowledge and suggesting future research directions

Physical activity level and lifestyle-related risk factors from Catalan physicians.

BACKGROUND: Physicians' own Physical Activity (PA) and other health-related habits influence PA promotion. The current study identifies the PA level, according to the current PA recommendations and other health-related habits of physicians from the Catalan Medical Council. METHODS: 2400 physicians (30-55 years) were randomly selected; each received a self-administered mailed questionnaire identifying medical specialization, work setting, health self-perception, body mass index (BMI), PA, and smoking habits. RESULTS: 762 physicians responded (52% female). Almost 1 in 2 (49.3%) exercised sufficiently, nearly all self-perceived good health, while 80.5% were nonsmokers. Almost 6 in 10 males reported overweight or obesity (56.9%) versus 18.2% of females. Active physicians dominated specific groups: (1) aged 45-55 years, (2) specializing either in primary care or surgery, (3) working in the private sector, (4) BMI < 25 kg/m2, (5) perceiving themselves in good health, or (6) having free leisure time. CONCLUSIONS: Only half of Catalan physicians met current PA recommendations; male physicians were particularly at risk for overweight/obesity. Overweight and under-exercise were associated with private workplaces and positive health perceptions, meaning that it is it is now possible to target inactive and/or overweight Catalan physicians in future interventions

Analysis of platelets from a diet-induced obesity rat model: elucidating platelet dysfunction in obesity

Obesity is one of the main health problems in industrialized countries. The contribution of multiple factors developed in obesity can hardly be modeled in vitro. In this context, the development of animal models mimicking human obesity could be essential. The aim of the present study was to compare platelets from a diet-induced obesity (DIO) rat model with their lean control group in order to elucidate platelet dysfunction mechanisms in obesity and correlate the results with previous data from morbid obese patients. In parallel, we also established a blood collection and platelet isolation methodology to study the DIO rat model at biochemical and functional level. Optimal blood collection was obtained from vena cava and platelet isolation was based on a serial of centrifugations avoiding platelet activation. Our results show that the DIO rat model simulate obesity pathologically since weight gain, fasting glucose and platelet counts are increased in obese rats. Interestingly, platelet levels of the active form of Src (pTyr(419)) showed a tendency to increase in DIO rats pointing towards a potential dysfunction in Src family kinases-related signalling pathways in obesity. Moreover, platelets from DIO rats adhere more to collagen compared with the control group, pointing towards Glycoprotein VI (GPVI) as one of the dysregulated receptors in obesity, in agreement with our recent studies in humans. These results confirm that obesity, in line with human studies, present a platelet dysregulation, and highlight the relevance of considering novel antithrombotic drug targets in these patients, such as GPVI

Aportación metodológica para determinar el índice de calidad del medio ambiente urbano y edificado del Área Metropolitana de Barcelona

El presente trabajo está orientado hacia la determinación de una metodología que evalúa características socio-residenciales, diagnostica el estado de bienestar del medio ambiente urbano del Área Metropolitana de Barcelona (AMB), responde al estado en que se encuentran las viviendas pre-existentes al 2001. La investigación incorpora una aportación al enfoque de valoración inmobiliaria sustentada en técnicas de valores sociales como parte de un contexto integral. La orientación al desarrollo sostenible constituye dar un enfoque de valoración inmobiliaria, es decir, retomando el valor de uso como una combinación de valores urbanos y de satisfacción residencial en la base del análisis. La hipótesis de la investigación nace a partir de desarrollar una metodología sustentada en indicadores parciales (simples) idóneos para la obtención del Índice de Calidad Edificada del AMB obtenido por el método del indicador sintético de distancia DP2. El objetivo de la investigación es demostrar la validación del método del indicador sintético de distancia.This work is oriented towards the determination of a methodology to assess socio-residential characteristics, diagnoses the welfare state of the urban environment in the metropolitan area of Barcelona (AMB), responds to the state that are pre-existing dwellings to 2001 . The research incorporates a contribution to real estate valuation approach supported by techniques of social values as part of a comprehensive context. The sustainable development orientation is an approach to property valuation, returning the value in use as a combination of urban values and residential satisfaction in the analysis. The hypothesis of the research stems from developing a methodology supported by partial indicators (simple) suitable for obtaining Built Quality Index of AMB obtained by the method of the synthetic indicator DP2 away. The objective of this research is to demonstrate the validation of the method of the synthetic indicator away.Peer Reviewe

Bridge damage identification under varying environmental and operational conditions combining Deep Learning and numerical simulations

This work proposes a novel supervised learning approach to identify damage in operating bridge structures. We propose a method to introduce the effect of environmental and operational conditions into the synthetic damage scenarios employed for training a Deep Neural Network, which is applicable to large-scale complex structures. We apply a clustering technique based on Gaussian Mixtures to effectively select Q representative measurements from a long-term monitoring dataset. We employ these measurements as the target response to solve various Finite Element Model Updating problems before generating different damage scenarios. The synthetic and experimental measurements feed two Deep Neural Networks that assess the structural health condition in terms of damage severity and location. We demonstrate the applicability of the proposed method with a real full-scale case study: the Infante Dom Henrique bridge in Porto. A comparative study reveals that neglecting different environmental and operational conditions during training detracts the damage identification task. By contrast, our method provides successful results during a synthetic validation

Deep learning enhanced principal component analysis for structural health monitoring

This paper proposes a Deep Learning Enhanced Principal Component Analysis (PCA) approach for outlier detection to assess the structural condition of bridges. We employ partially explainable autoencoder architecture to replicate and enhance the data compression and reconstruction ability of PCA. The particularity of the method lies in the addition of residual connections to account for nonlinearities. We apply the proposed method to monitoring data obtained from two bridges under real operation conditions and compare the results before and after adding the residual connections. Results show that the addition of residual connections enhances the outlier detection ability of the network, allowing to detect lighter damages