University of Oviedo
  • Oviedo, Asturias, Spain
Recent publications
First-episode psychosis (FEP) patients show structural brain abnormalities at the first episode. Whether the cortical changes that follow a FEP are progressive and whether age at onset modulates these changes remains unclear. This is a multicenter MRI study in a deeply phenotyped sample of 74 FEP patients with a wide age range at onset (15–35 years) and 64 neurotypical healthy controls (HC). All participants underwent two MRI scans with a 2-year follow-up interval. We computed the longitudinal percentage of change (PC) for cortical thickness (CT), surface area (CSA) and volume (CV) for frontal, temporal, parietal and occipital lobes. We used general linear models to assess group differences in PC as a function of age at FEP. We conducted post-hoc analyses for metrics where PC differed as a function of age at onset. We found a significant age-by-diagnosis interaction effect for PC of temporal lobe CT ( d = 0.54; p = 002). In a post-hoc-analysis, adolescent-onset (≤19 y) FEP showed more severe longitudinal cortical thinning in the temporal lobe than adolescent HC. We did not find this difference in adult-onset FEP compared to adult HC. Our study suggests that, in individuals with psychosis, CT changes that follow the FEP are dependent on the age at first episode, with those with an earlier onset showing more pronounced cortical thinning in the temporal lobe.
Industrial plants commonly generate gas emissions that are not caused intentionally. These emissions are known as fugitive emissions. Early detection of fugitive emissions helps to find points of failure in the different processes and avoid sources of pollution, helping to reduce danger to the environment and to respect legislation. Despite the importance of the problem, there are no published solutions in the specialized literature about the location and automated detection of fugitive emissions in industrial plants. Therefore, this article proposes an effective approach based on convolutional neural networks for semantic segmentation. The proposed solution takes advantage of existing surveillance cameras to apply state-of-the-art image segmentation methods, in particular, the semantic segmentation network DeeplabV3 + . This work explores aspects such as the ability to differentiate gases like water vapor and clouds from fugitive emissions, the possibility of reusing models in different industrial plants, the differences between multi-class and binary classification, the importance of proportions in the number of images in each class, the use of weights to balance classes, the comparison of a standard size test versus a real use case test, and the feasibility of an area-based alarm system to warn of emissions. This paper describes a methodology to configure the proposed solution for a specific industrial facility.
The correction of the phase variations induced by the atmospheric turbulence is one of the most complex problems that an Adaptive Optics (AO) System must deal with, as it must calculate the properties of all the atmosphere traversed by the light from several measures taken by ground-based telescopes. Traditional reconstructors systems used in AO are based on computational algorithms where its reconstruction quality improves with the number of measures made by the telescopes’ sensors. That means that sensors are getting greater and greater with their corresponding higher financial expense. Artificial Intelligence (IA) has become in recent years a real alternative to traditional computational methods as reconstructors for AO systems. Fully-convolutional neural networks (FCNs) specifically have shown great performances working in Solar AO, demonstrating their ability to obtain a lot of valuable information from the recorded images for the wavefront phase evaluation. Along this research, the influence of the properties of the telescope's sensors and of the observations in the reconstructions made by the FCNs’ is measured, to obtain the configuration that best suits the performance of artificial neural networks (ANN). The presented results determine the way forward for the future sensors for telescopes with reconstruction systems based on ANNs, to obtain higher quality reconstructions employing fewer economic resources.
The special characteristics of the cleaning industry have an important impact on the health and safety of its workforce. Making use of data from more than 79,000 occupational accidents, the aim of the present research is to use machine learning techniques to develop a model to predict incapacity for work (expressed in days of absence) due to work-related overexertion injuries among service sector cleaners in Spain. The severity of accidents caused by overexertion depends on several factors that can be classified into the following categories: injury typology, individual factors, employment conditions, accident circumstances and health and safety management and standards in the company.
The arrangement of the panels in Open Joint Ventilated Façades (OJVF) is a potential factor in improving the energy efficiency of this building system. The distribution of joints in the façade influences the behaviour of the air flow in the channel which in turn could affect the overall heat exchanges with the envelope and thus the internal conditions of the building. Tiling panels can be installed on ventilated façades with different arrangement patterns according to the layout of the joints: lined up, staggered, stepped, diagonal or random, although manufacturers recommend a façade layout with in-line gaps to avoid costly façade maintenance. Thus, landscape and portrait layout with continuous joints are the most frequent arrangement in ventilated façades. This research assesses the benefit of the installation of OJVF panels in both layouts in order to reduce the cooling loads. Two real OJVFs with different panel arrangements, landscape and portrait, are analysed. Also, they are compared with a conventional façade with a sealed air cavity. All solutions are modelled and simulated using the commercial computational fluid dynamics software ANSYS FLUENT to evaluate the fluid-dynamic and thermal behaviour of the façades in summer and winter conditions. The energy performance of these solutions is evaluated, analysing different parameters such as panel’s temperature, mean air velocity inside the cavity, fluid pathlines through the open joints and thermal flux in the air cavity and to the room. The airflow inside the cavity is mainly driven by thermal buoyancy in all façades but differs from bi-dimensional convective loops in conventional façades to three-dimensional complex and asymmetrical airflows in OJVFs. The results obtained show that both OJVF configurations perform much better than the conventional sealed façade, reducing the heat transfer into the room by 30% in the summer period. In any case, the landscape OJVF façade reduces the transfer in the same period to a minimum value of 7.3 W/m2, which is 3% less than the flux transferred through the vertical one. This small difference in the energy performance of OJVFs makes the choice of panel orientation more based on other criteria such as aesthetics.
The growth of the world merchant fleet in recent decades has caused an increase in congestion and complexity in maritime traffic, especially in coastal areas, straits and nearby channels. This fact, which acts negatively upon maritime safety, however, has meant a decrease in the number of accidents, rather, they have even been reduced by half in the last decade. This anomaly is explained by the implementation of Vessel Traffic Services (VTS) in these conflict areas and for this reason, in this review we will study, through the analysis of different relevant studies on the subject, the relationship between the human element and maritime safety, focusing on the figure of the vessel traffic service operator (VTSO) as a link between safety and efficiency, exploring their staffing, training, functions and factors affecting them within the maritime system. This review was conducted following the reporting guidelines for systematic reviews based on the PRISMA 2020 model (Preferred Reporting Items for Systematic Reviews and meta-Analyses). Also, a bibliometric analysis of the extensive academic literature pertaining to maritime safety in relation to the human factor was carried out, focusing especially on VTS and the operators that act in them, with a special focus on the period from 2000 to 2020. Based on 371 articles, the bibliometric analyses yield to us the information on the publication patterns related to the year of publication and the keywords by identifying the main thematic groups, finally extracting 11 representative articles that have been investigated in detail focusing on the influence of the human factor in maritime safety in the VTS environment.
Using novel US household survey data, we examine the role of financial socialization, meant as the exposure to financial concepts while growing up, and self-control in explaining saving behavior. We pay special attention to the potential existence of gender differences in the influence of parental teachings received early in life and self-control skills on saving habits. In addition, we analyze the relationship between financial socialization, self-control and the ownership of different financial products. Results indicate that financial socialization received early in life and self-control are positively associated with general saving habits. However, their contribution differs depending on the type of financial product being analyzed. Furthermore, the gender gap in saving propensity in the favor of males is mainly due to differences in characteristics rather than differences in coefficients.
The paper presents the results of a novel 3-D shared aperture 3×3 matrix antenna-array for 26 GHz band 5 G wireless networks. Radiation elements constituting the array are hexagonal-shaped patches that are elevated above the common dielectric substrate by 3.35 mm and excited through a metallic rod of 0.4 mm diameter. The rod protrudes through the substrate of 0.8 mm thickness. It is shown that by isolating each radiating element in the array with a wall suppresses unwanted electromagnetic (EM) wave interactions, resulting in improvement in the antenna’s impedance matching and radiation characteristics. Moreover, the results show that by embedding hexagonal-shaped slots in the patches improve the antenna's gain and radiation efficiency performance. The subwavelength length slots in the patches essentially transform the radiating elements to exhibit metasurface characteristics when the array is illuminated by EM-waves. The proposed array structure has an average gain and radiation efficiency of 20 dBi and 93%, respectively, across 24.0-28.4 GHz. The isolation between its radiation elements is greater than 22 dB. Compared to the unslotted array the improvement in isolation between radiating elements is greater than 11 dB, and the gain and efficiency are better than 10.5 dBi, and 25%, respectively. The compact array has a fractional bandwidth of 16% and a form factor of 20×20×3.35 mm³.
Energy awareness is one of the most relevant research directions in scheduling problems. In this paper we consider the minimization of both the makespan and the energy consumption in the classical job shop scheduling problem. The energy model considered allows several possible states for the machines: off, stand-by, idle, setup and processing. To solve this multi-objective problem we propose an NSGA-II based evolutionary algorithm combined with local search and a heuristic procedure to improve the energy consumption of a given schedule. We also propose an advanced constraint programming (CP) approach as well as a Mixed-Integer Linear Programming (MILP) model, to the aim of comparing their performances against those obtained with the NSGA-II. The experimental study is performed against a benchmark set that extends by 41 instances of increasing size, the set tackled in the previous literature against the same problem. The experiments demonstrate the superiority of the NSGA-II algorithm over all other methods, despite the utilization of CP and MILP allows to draw interesting conclusions on the overall solution optimality, revealing that there is still room for further optimization.
Ship collisions are some of the biggest risks in shipping, and Decision Support System/Collision Avoidance-Alert Systems (DSS/CAS) are being developed to prevent and avoid them. They must become an essential equipment for any vessel, especially for Maritime Autonomous Surface Ships (MASS). Assuming the Convention on the International Regulations for Preventing Collisions at Sea, 1972 (COLREG 72) as the basis for every DSS/CAS, there is growing concern in the maritime field about the lack of consistency of published studies, in particular those on the design of algorithms for the control of ship collision avoidance manoeuvres, with the requirements of the current COLREG. The methods applied for the assessment of scenarios and situations will be analyzed, since only a correct appraisal of the circumstances will bring about the adequate response for such critical situations. COLREG is conceived to always have the Officers Of the Navigational Watch (OONW) (more specific than the overly generic expression Officer On Watch -OOW), at the center of every decision. Therefore, in the design of a DSS/CAS, interpretations that approach collision situations from a different perspective than that of an OONW should be avoided. Safe communication with other vessels would reinforce and improve the information available to the OONW. This paper aims to offer an insight into ship collisions avoidance according to COLREG 72 that may prove useful to the OONWs either on board or remotely, or even to autonomous systems. It is illustrated by examples taken from some works which, despite their great influence in the current literature, do not have a correct standpoint.
We study the homogeneous Dirichlet problem for the degenerate parabolic equation of the Kirchhoff type u_t − a(||∇u||_2^2)Δu = b(||u||_2^2)|u|^{q(x,t)−2}u in Q_T = Ω×(0, T), where T >0, Ω ⊂ R^n, n≥2, is a smooth bounded domain. The exponent q(x, t) is a measurable function in QT with values in an interval [q−,q+]⊂(1,∞). The coefficients a(·), b(·) are continuous functions defined on R+. It is assumed that a(s)→0 or a(s)→∞ as s→0+; therefore, the equation degenerates or becomes singular as ||∇u(t)||2→0. We prove the local in time solvability of the problem and derive sufficient conditions of the finite time blow-up of the nonnegative solutions. The upper and lower estimates on the blow-up moment are found.
Although the installation of photovoltaic systems on roofs is a successful investment, rooftop space availability has been identified as a significant limiting factor in achieving zero-energy buildings, especially by building components such as chimneys, elevator machine rooms, fans, plumbing vents, etc. This study presents a general algorithm for the optimal deployment of photovoltaic module rows installed on irregular flat roof shapes. The presented algorithm takes into account the irregular rooftop shape, the self-shading of photovoltaic modules, the inclusion of building components, commercial photovoltaic modules with different sizes, mounting systems with different configurations, distances required for maintenance, and the technical reports to minimize shading effects. The proposed algorithm allowed to increase in the amount of solar energy received by the photovoltaic modules. The optimisation process takes into account the weather conditions at the specific location. The optimisation algorithm was implemented using a specific Mathematica™ code in which the commands used in the development of the code were introduced to facilitate its replication. The optimisation algorithm output provides the essential parameters for the optimal photovoltaic system design such as: the optimum number of mounting systems and their configuration, the optimum tilt angle of the mounting system and its dimensions, the photovoltaic module model, the maximum total area of the photovoltaic field and the maximum annual energy captured by the photovoltaic modules. We compared the mounting system layout obtained with the proposed algorithm with the tilt angle photovoltaic module layout recommended by three technical papers (IDAE Technical Report, Lorenzo’s equation and Jacobson’s equation) with respect to photovoltaic field area gain, energy gain and levelised cost of energy.The optimal photovoltaic module layout obtains the maximum photovoltaic field area gain of 35.52% with respect to the Jacobson’s equation and the minimum of 32.29% with respect to the IDAE Technical Report. The optimal photovoltaic module layout obtains the maximum energy gain of 27.83% with respect to the Jacobson’s equation and the minimum of 24.84% with respect to the IDAE Technical Report. The levelized cost of energy of the optimal PV module layout is lower than that of the other arrangements studied. The algorithm presented may be useful for decision-makers or policymakers in determining the optimal distribution of photovoltaic modules on irregular rooftop shapes.
Professional development (PD) of teachers working with students in the first years of learning to read is a privileged way of preventing initial reading difficulties and its effects in the long and short term. This research studies the effects of PD in student reading performance, although the results are not conclusive with regard to which PD format is more adequate. The objective of this study is to determine which modality (face-to-face with a coach vs. without a coach) and intensity (number of contact hours) of PD are more efficient in achieving fluency improvement in student performance in the code-focussed skills in the first years of learning to read. Both pre-schoolers and their teachers took part in the study with a quasi-experimental pre-test post-test design. The experimental group (n = 71) was provided literacy instruction from teachers (n = 8) who received 40 h of face-to-face training with a coach and the control group (n = 29) was provided literacy instruction from teachers (n = 8) who received only 8 h of initial training (without coaching). The results showed significant intra-group improvements with a large reduction in students at risk for reading difficulties. No significant differences were obtained between groups in reading performance. This suggests greater efficiency in a lower intensity format of PD without a coach in the development of code-focussed skills. The study considers the need to adequately assess reading ability in the light of attitude and motivation of teachers as variables which influence the efficiency of PD.
The remediation of legacy metal(loid) contaminated soils in-situ relies on the addition of [organic] amendments to reduce the mobility and bioavailability of metal(loid)s, improve soil geochemical parameters and restore vegetation growth. Two vermicomposts of food and animal manure waste origin (V1 and V2) were amended to an arsenic (As) and copper (Cu) contaminated mine soil (≤1500 mg kg⁻¹). Leaching columns and pot experiments evaluated copper and arsenic in soil pore waters, as well as pH, dissolved organic carbon (DOC) and phosphate (PO4³⁻) concentrations. The uptake of As and Cu to ryegrass was also measured via the pot experiment, whilst recovered biochars from the column leaching test were measured for metal sorption at the termination of leaching. Vermicompost amendment to soil facilitated ryegrass growth which was entirely absent from the untreated soil in the pot test. All amendment combinations raised pore water pH by ∼4 units. Copper concentrations in pore waters from columns and pots showed steep reductions (∼1 mg L⁻¹), as a result of V1 & V2 compared to untreated soil (∼500 mg L⁻¹). Combined with an increase in DOC and PO4³⁻, As was mobilised an order of magnitude by V1. Biochar furthest reduced Cu in pore waters from the columns to <0.1 mg L⁻¹, as a result of surface sorption. The results of this study indicate that biochar can restrict the mobility of Cu from a contaminated mine soil after other amendment interventions have been used to promote revegetation. However, the case of As, biochar cannot counter the profound impact of vermicompost on arsenic mobility.
Introduction During the COVID-19 pandemic various degrees of lockdown were applied by countries around the world. It is considered that such measures have an adverse effect on mental health but the relationship of measure intensity with the mental health effect has not been thoroughly studied. Here we report data from the larger COMET-G study pertaining to this question. Material and Methods During the COVID-19 pandemic, data were gathered with an online questionnaire from 55,589 participants from 40 countries (64.85% females aged 35.80 ±13.61; 34.05% males aged 34.90±13.29 and 1.10% other aged 31.64±13.15). Anxiety was measured with the STAI, depression with the CES-D and suicidality with the RASS. Distress and probable depression were identified with the use of a previously developed cut-off and algorithm respectively. Statistical Analysis It included the calculation of Relative Risk (RR), Factorial ANOVA and Multiple backwards stepwise linear regression analysis Results Approximately two-thirds were currently living under significant restrictions due to lockdown. For both males and females the risk to develop clinical depression correlated significantly with each and every level of increasing lockdown degree (RR 1.72 and 1.90 respectively). The combined lockdown and psychiatric history increased RR to 6.88 The overall relationship of lockdown with severity of depression, though significant was small. Conclusions The current study is the first which reports an almost linear relationship between lockdown degree and effect in mental health. Our findings, support previous suggestions concerning the need for a proactive targeted intervention to protect mental health more specifically in vulnerable groups
Reliable data on the availability of solar energy is needed, as solar energy is an essential resource for sustainable development worldwide. However, ground-based radiometric stations are scarce, at least in large areas far from population and in developing countries, so there are difficulties in validating methods for estimating solar radiation. Indirect models mitigate the problem by providing radiation data from other meteorological variables, which can be measured with low-cost equipment and calibrated with data from secondary station networks. However, models’ accuracy decreases if estimations are required far away from the calibration stations. It is hoped that modified models that include the influence of geographical and topographical variables can attenuate this drawback in data-scarce regions. This paper evaluates the accuracy and generality of 14 existing models of monthly global solar radiation based on temperature, which is a routinely measured variable. At first, models are locally calibrated at 105 stations in three large areas in Spain. Then, from the local coefficients of eight stations selected in each area, general equations are derived for the coefficients of each model as function of the ratio between elevation and distance to the sea. The predictions of these modified models, i.e., using coefficients derived from general equations, are compared both for the eight base stations and the remaining ones used for validation. In the comparisons, not only errors averaged in groups of stations are considered, but also local results. Several models perform well in some areas, but a simple homogeneous model is the only one whose indicators are good in all areas and hardly vary when using general coefficients derived from the data measured at all available stations.
Species Distribution Models (SDMs) are essential tools for predicting climate change impact on species' distributions and are commonly employed as an informative tool on which to base management and conservation actions. Focusing only on a part of the entire distribution of a species for fitting SDMs is a common approach. Yet, geographically restricting their range can result in considering only a subset of the species' ecological niche (i.e., niche truncation) which could lead to biased spatial predictions of future climate change effects, particularly if future conditions belong to those parts of the species ecological niche that have been excluded for model fitting. The integration of large-scale distribution data encompassing the whole species range with more regional data can improve future predictions but comes along with challenges owing to the broader scale and/or lower quality usually associated with these data. Here, we compare future predictions obtained from a traditional SDM fitted on a regional dataset (Switzerland) to predictions obtained from data integration methods that combine regional and European datasets for several bird species breeding in Switzerland. Three models were fitted: a traditional SDM based only on regional data and thus not accounting for niche truncation, a data pooling model where the two datasets are merged without considering differences in extent or resolution, and a downscaling hierarchical approach that accounts for differences in extent and resolution. Results show that the traditional model leads to much larger predicted range changes (either positively or negatively) under climate change than both data integration methods. The traditional model also identified different variables as main drivers of species' distribution compared to data-integration models. Differences between models regarding predicted range changes were larger for species where future conditions were outside the range of conditions existing in the regional dataset (i.e., when future conditions implied extrapolation). In conclusion, we showed that (i) models Frontiers in Ecology and Evolution 01 Chevalier et al. 10.3389/fevo.2022.944116 calibrated on a geographically restricted dataset provide markedly different predictions than data integration models and (ii) that these differences are at least partly explained by niche truncation. This suggests that using data integration methods could lead to more accurate predictions and more nuanced range changes than regional SDMs through a better characterization of species' entire realized niches.
This study deals with the Indigo Carmine (IC) dye removal using synthetic mesoporous Titanium dioxide (TiO2) nanoparticles. The surface charge investigation shows a pHzc equal to 4.25. The central composite design (CCD) model optimization of the adsorption process identified 57 min as the optimal contact time. For optimum IC contents of 30 and 58 mg/L, the recorded adsorption capacities were 123 and 261 mg/g in the dark reactor (DR) and sunlight reactor (SR), respectively. The thermodynamic investigation suggests an endothermic and spontaneous physisorption process, and the regeneration tests show higher stability of the mesoporous TiO2 in the SR. SEM and TEM analyses show a TiO2 agglomeration in DR and nanoparticles swelling in SR.
Children and adolescents in residential care often present with emotional and/or behavioral problems associated to previous adverse experiences such as abuse and neglect. Consequently, child welfare systems have developed therapeutic residential care (TRC) programs to address the most complex needs of this population. The aim of this study is to explore the characteristics of youths in TRC comparing them with those of youth in general residential care (GRC), and to detect the factors predicting referral to TRC programs. The sample consisted of 900 adolescents aged 12-17 years old (M = 15.57; SD = 1.33; 66.2% boys), from General Residential Care (n = 554) and Therapeutic Residential Care (n = 346). Profile information was collected through official files and an ad hoc questionnaire. Mental health problems were evaluated using the youth self-report (YSR). Significant sociodemographic differences were found between groups. Also, a higher frequency of emotional abuse and neglect, worse mental health, more breakdowns in child welfare measures and risk behaviors were found among adolescents in TRC. Sociodemographic and familial characteristics, features of the protective process and risk behaviors were associated to referral to TRC programs. Youths in GRC and TRC present with mental and behavioral problems that make it necessary to implement prevention programs and early detection procedures. Screening and evaluation of youth's mental health and establishment of concrete criteria are suggested to ensure appropriate referral to the most suitable resource according to the individual needs of adolescents.
Recent advances in cancer characterization have consistently revealed marked heterogeneity, impeding the completion of integrated molecular and clinical maps for each malignancy. Here, we focus on chronic lymphocytic leukemia (CLL), a B cell neoplasm with variable natural history that is conventionally categorized into two subtypes distinguished by extent of somatic mutations in the heavy-chain variable region of immunoglobulin genes (IGHV). To build the ‘CLL map,’ we integrated genomic, transcriptomic and epigenomic data from 1,148 patients. We identified 202 candidate genetic drivers of CLL (109 new) and refined the characterization of IGHV subtypes, which revealed distinct genomic landscapes and leukemogenic trajectories. Discovery of new gene expression subtypes further subcategorized this neoplasm and proved to be independent prognostic factors. Clinical outcomes were associated with a combination of genetic, epigenetic and gene expression features, further advancing our prognostic paradigm. Overall, this work reveals fresh insights into CLL oncogenesis and prognostication.
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Jorge Tolivia
  • Área de Biología Celular
Díaz García Marta Elena
  • Department of Physical and Analytical Chemistry
Daniel Gayo-Avello
  • Department of Information Technology
Pedro Álvarez-Álvarez
  • Department of Organisms and Systems Biology
Edificio Histórico, C/ San Francisco, 3, 33003, Oviedo, Asturias, Spain
Head of institution
Ignacio Villaverde Menéndez
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