Modelling the Leakage Current Behaviour of Polluted Ceramic Insulators by Using Acoustic Emissions and Relative Humidity

Understanding the behaviour of leakage current (LC) is not an easy task for engineers and new techniques are needed to identify the outage risk of some electrical circuits. Therefore, this paper presents a Generalized Linear Model (GLM) to characterise the LC variations in 230 kV ceramic insulators located in outdoor electrical substations subject to high pollution levels. The model uses data such as LC, acoustic emission (AE), and environmental variables (EVs). We found that the model represents the LC variation of electrical insulators of high voltage circuits. This model is useful for designing detection systems that represent the contamination levels and predict the behaviour of changes related to EV. With this model, we can determine the risk indicators for failure of electrical insulators in high-pollution areas

Regulación y bienestar económico: evaluación de la regulación de servicios públicos domiciliarios de acueducto y electricidad en Colombia en la década de los noventa. Caso empresas públicas de Medellín

Las reformas de mediados de los noventa, basadas en las leyes 142 y 143 de 1994, introdujeron cambios institucionales y metodológicos en la regulación tarifaria para los servicios de electricidad y acueducto en Colombia. Este artículo, además de reseñar dichos cambios, evalúa a través de un contrafactual cómo hubiese sido la evolución tarifaria si no se hubiese presentado la reforma de los 90’s. Así mismo, estima las elasticidades precio y gasto para dichos servicios mediante el Sistema Casi Ideal de Demanda (AIDS) y con el cálculo de la variación equivalente establece si la regulación generó una mejora en el bienestar de los consumidores

Efecto del hierro en el crecimiento y acumulación de lípidos en la microalga colombiana Chlorella Vulgaris LAUN 0019

En este trabajo se evalúa el efecto del ión ferroso (Fe2+) sobre el crecimiento y acumulación de lípidos totales de la microalga Chlorella vulgaris. Se empleó medio Bristol estándar para su cultivo; la cinética de crecimiento se midió por conteo directo y la determinación de lípidos totales se realizó mediante extracción con Soxhlet. Se estudiaron cinco diferentes concentraciones de este ión, entre 2,16 μM y 50,0 μM. El medio enriquecido con una concentración de 10,0 μM produjo la máxima velocidad específica de crecimiento celular (0,76 día-1), mientras que las máximas productividades de biomasa y de lípidos se presentaron a la concentración 5,00 μM con valores de 112,4 mg·L-1·día-1 y 6,52 mg·L-1·día-1 respectivamente. Para las concentraciones más altas de hierro (21,5 y 50,0 μM), la microalga presentó inhibición por sustrato. Finalmente, para concentraciones menores que 10,0 μM se encontró que para una significancia del 5% la concentración del hierro no afecta significativamente la productividad de biomasa y lípidos

El derecho del trabajo y la seguridad social en la encrucijada: retos para la disciplina laboral

Ministerio de Economía y Competitividad DER2012-32111Ministerio de Economía y Competitividad DER2015-6936

Characterization of cassava ORANGE proteins and their capability to increase provitamin A carotenoids accumulation

Cassava (Manihot esculenta Crantz) biofortification with provitamin A carotenoids is an ongoing process that aims to alleviate vitamin A deficiency. The moderate content of provitamin A carotenoids achieved so far limits the contribution to providing adequate dietary vitamin A levels. Strategies to increase carotenoid content focused on genes from the carotenoids biosynthesis pathway. In recent years, special emphasis was given to ORANGE protein (OR), which promotes the accumulation of carotenoids and their stability in several plants. The aim of this work was to identify, characterize and investigate the role of OR in the biosynthesis and stabilization of carotenoids in cassava and its relationship with phytoene synthase (PSY), the rate-limiting enzyme of the carotenoids biosynthesis pathway. Gene and protein characterization of OR, expression levels, protein amounts and carotenoids levels were evaluated in roots of one white (60444) and two yellow cassava cultivars (GM5309-57 and GM3736-37). Four OR variants were found in yellow cassava roots. Although comparable expression was found for three variants, significantly higher OR protein amounts were observed in the yellow varieties. In contrast, cassava PSY1 expression was significantly higher in the yellow cultivars, but PSY protein amount did not vary. Furthermore, we evaluated whether expression of one of the variants, MeOR_X1, affected carotenoid accumulation in cassava Friable Embryogenic Callus (FEC). Overexpression of maize PSY1 alone resulted in carotenoids accumulation and induced crystal formation. Co-expression with MeOR_X1 led to greatly increase of carotenoids although PSY1 expression was high in the co-expressed FEC. Our data suggest that posttranslational mechanisms controlling OR and PSY protein stability contribute to higher carotenoid levels in yellow cassava. Moreover, we showed that cassava FEC can be used to study the efficiency of single and combinatorial gene expression in increasing the carotenoid content prior to its application for the generation of biofortified cassava with enhanced carotenoids levels

Ingeniería Forestal y ambiental en medios insulares

Las Islas Canarias a pesar de su reducida extensión y del relativo poco peso específico a nivel mundial, no es ajena a los problemas globales detectados en la conservación de bosques y en la importancia que éstos tienen para obtener beneficios económicos, socioculturales y ambientales. La gestión forestal sostenible es en este sentido esencial para asegurar y compatibilizar los diversos beneficios del bosque. El papel específico de los bosques y su gestión son sin embargo temas aún por conocer en nuestras islas, por lo que el Año Internacional de los Bosques ha representado una oportunidad única para dar a conocer el mundo forestal y acercarlo a nuestra sociedad. El presente libro consta de 25 capítulos donde se ha contemplado la mayoría de los aspectos a tener en cuenta en la planificación y gestión del medio forestal y natural. Desde la historia forestal del archipiélago, hasta el uso y técnicas de manejo de los recursos naturales, incluyendo el agua, la energía en forma de biomasa y la selvicultura

Exposing and Overcoming Limitations of Clinical Laboratory Tests in COVID-19 by Adding Immunological Parameters; A Retrospective Cohort Analysis and Pilot Study

BackgroundTwo years since the onset of the COVID-19 pandemic no predictive algorithm has been generally adopted for clinical management and in most algorithms the contribution of laboratory variables is limited. ObjectivesTo measure the predictive performance of currently used clinical laboratory tests alone or combined with clinical variables and explore the predictive power of immunological tests adequate for clinical laboratories. Methods: Data from 2,600 COVID-19 patients of the first wave of the pandemic in the Barcelona area (exploratory cohort of 1,579, validation cohorts of 598 and 423 patients) including clinical parameters and laboratory tests were retrospectively collected. 28-day survival and maximal severity were the main outcomes considered in the multiparametric classical and machine learning statistical analysis. A pilot study was conducted in two subgroups (n=74 and n=41) measuring 17 cytokines and 27 lymphocyte phenotypes respectively. Findings1) Despite a strong association of clinical and laboratory variables with the outcomes in classical pairwise analysis, the contribution of laboratory tests to the combined prediction power was limited by redundancy. Laboratory variables reflected only two types of processes: inflammation and organ damage but none reflected the immune response, one major determinant of prognosis. 2) Eight of the thirty variables: age, comorbidity index, oxygen saturation to fraction of inspired oxygen ratio, neutrophil-lymphocyte ratio, C-reactive protein, aspartate aminotransferase/alanine aminotransferase ratio, fibrinogen, and glomerular filtration rate captured most of the combined statistical predictive power. 3) The interpretation of clinical and laboratory variables was moderately improved by grouping them in two categories i.e., inflammation related biomarkers and organ damage related biomarkers; Age and organ damage-related biomarker tests were the best predictors of survival, and inflammatory-related ones were the best predictors of severity. 4) The pilot study identified immunological tests (CXCL10, IL-6, IL-1RA and CCL2), that performed better than most currently used laboratory tests. ConclusionsLaboratory tests for clinical management of COVID 19 patients are valuable but limited predictors due to redundancy; this limitation could be overcome by adding immunological tests with independent predictive power. Understanding the limitations of tests in use would improve their interpretation and simplify clinical management but a systematic search for better immunological biomarkers is urgent and feasible

Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning

Quantitative or qualitative differences in immunity may drive clinical severity in COVID-19. Although longitudinal studies to record the course of immunological changes are ample, they do not necessarily predict clinical progression at the time of hospital admission. Here we show, by a machine learning approach using serum pro-inflammatory, anti-inflammatory and anti-viral cytokine and anti-SARS-CoV-2 antibody measurements as input data, that COVID-19 patients cluster into three distinct immune phenotype groups. These immune-types, determined by unsupervised hierarchical clustering that is agnostic to severity, predict clinical course. The identified immune-types do not associate with disease duration at hospital admittance, but rather reflect variations in the nature and kinetics of individual patient's immune response. Thus, our work provides an immune-type based scheme to stratify COVID-19 patients at hospital admittance into high and low risk clinical categories with distinct cytokine and antibody profiles that may guide personalized therapy. Developing predictive methods to identify patients with high risk of severe COVID-19 disease is of crucial importance. Authors show here that by measuring anti-SARS-CoV-2 antibody and cytokine levels at the time of hospital admission and integrating the data by unsupervised hierarchical clustering/machine learning, it is possible to predict unfavourable outcome

Impact of SARS-Cov-2 infection in patients with hypertrophic cardiomyopathy : results of an international multicentre registry

To describe the natural history of SARS-CoV-2 infection in patients with hypertrophic cardiomyopathy (HCM) compared with a control group and to identify predictors of adverse events. Three hundred and five patients [age 56.6 ± 16.9 years old, 191 (62.6%) male patients] with HCM and SARS-Cov-2 infection were enrolled. The control group consisted of 91 131 infected individuals. Endpoints were (i) SARS-CoV-2 related mortality and (ii) severe clinical course [death or intensive care unit (ICU) admission]. New onset of atrial fibrillation, ventricular arrhythmias, shock, stroke, and cardiac arrest were also recorded. Sixty-nine (22.9%) HCM patients were hospitalized for non-ICU level care, and 21 (7.0%) required ICU care. Seventeen (5.6%) died: eight (2.6%) of respiratory failure, four (1.3%) of heart failure, two (0.7%) suddenly, and three (1.0%) due to other SARS-CoV-2-related complications. Covariates associated with mortality in the multivariable were age {odds ratio (OR) per 10 year increase 2.25 [95% confidence interval (CI): 1.12-4.51], P = 0.0229}, baseline New York Heart Association class [OR per one-unit increase 4.01 (95%CI: 1.75-9.20), P = 0.0011], presence of left ventricular outflow tract obstruction [OR 5.59 (95%CI: 1.16-26.92), P = 0.0317], and left ventricular systolic impairment [OR 7.72 (95%CI: 1.20-49.79), P = 0.0316]. Controlling for age and sex and comparing HCM patients with a community-based SARS-CoV-2 cohort, the presence of HCM was associated with a borderline significant increased risk of mortality OR 1.70 (95%CI: 0.98-2.91, P = 0.0600). Over one-fourth of HCM patients infected with SARS-Cov-2 required hospitalization, including 6% in an ICU setting. Age and cardiac features related to HCM, including baseline functional class, left ventricular outflow tract obstruction, and systolic impairment, conveyed increased risk of mortality

The structure of N=2 supersymmetric nonlinear sigma models in AdS_4

We present a detailed study of the most general N=2 supersymmetric sigma models in four-dimensional anti-de Sitter space AdS_4 formulated in terms of N=1 chiral superfields. The target space is demonstrated to be a non-compact hyperkahler manifold restricted to possess a special Killing vector field which generates an SO(2) group of rotations on the two-sphere of complex structures and necessarily leaves one of them invariant. All hyperkahler cones, that is the target spaces of N=2 superconformal sigma models, prove to possess such a vector field that belongs to the Lie algebra of an isometry group SU(2) acting by rotations on the complex structures. A unique property of the N=2 sigma models constructed is that the algebra of OSp(2|4) transformations closes off the mass shell. We uncover the underlying N=2 superfield formulation for the N=2 sigma models constructed and compute the associated N=2 supercurrent. We give a special analysis of the most general systems of self-interacting N=2 tensor multiplets in AdS_4 and their dual sigma models realized in terms of N=1 chiral multiplets. We also briefly discuss the relationship between our results on N=2 supersymmetric sigma models formulated in the N=1 AdS superspace and the off-shell sigma models constructed in the N=2 AdS superspace in arXiv:0807.3368.Comment: 84 pages; v2: typos corrected, version published in JHE