Operation and control design of an input-series-input-parallel-output-series conversion scheme for offshore DC wind systems

High-power converters for high-voltage direct current transmission systems and collecting networks are attracting increasing interest for application in large offshore wind farms. Offshore wind farms are capable of generating more electric energy at lower cost when compared with onshore wind systems. In this study, DC/DC voltage conversion should be achieved with a power converter that uses readily available semiconductor devices. A modular DC/DC converter can achieve the required system currents and voltages without exceeding semiconductor ratings. In this study, the operation and control strategy for an input-series–input-parallel–output-series (ISIPOS) energy conversion system for wind systems are presented. The ISIPOS system allows the direct connection of wind turbines to the DC grid. In this research, the design process to control the input and output currents and voltages is explained. In addition, a new method to ensure voltage and current sharing between the different modules is presented and explained. The basic structure, control design, and system performance are tested using MATLAB/SIMULINK. Practical results validate the control design flexibility of the ISIPOS topology when controlled by a TMSF280335 DSP

Deciphering the impact of uncertainty on the accuracy of large wildfire spread simulations

Predicting wildfire spread is a challenging task fraught with uncertainties. ‘Perfect’ predictions are unfeasible since uncertainties will always be present. Improving fire spread predictions is important to reduce its negative environmental impacts. Here, we propose to understand, characterize, and quantify the impact of uncertainty in the accuracy of fire spread predictions for very large wildfires. We frame this work from the perspective of the major problems commonly faced by fire model users, namely the necessity of accounting for uncertainty in input data to produce reliable and useful fire spread predictions. Uncertainty in input variables was propagated throughout the modeling framework and its impact was evaluated by estimating the spatial discrepancy between simulated and satellite-observed fire progression data, for eight very large wildfires in Portugal. Results showed that uncertainties in wind speed and direction, fuel model assignment and typology, location and timing of ignitions, had a major impact on prediction accuracy.We argue that uncertainties in these variables should be integrated in future fire spread simulation approaches, and provide the necessary data for any firemodel user to do soinfo:eu-repo/semantics/publishedVersio

Atividade biológica de extratos acetato de etila, etanólico e aquoso de timbó (Lonchocarpus floribundus) sobre carrapato bovino

Os extratos acetato de etila, etanólico e aquoso de raízes de Lonchocarpus floribundus foram utilizados, a fim de avaliar a atividade biológica sobre carrapato bovino. Carrapatos adultos foram coletados em bovinos infestados artificialmente, separados em grupos de dez indivíduos, pesados e imersos, separadamente, nos extratos de raízes de L. Floribundus, nas concentrações de 5, 25, 50, 75 e 100 mg mL-1. Para a avaliação em larvas, foram utilizados indivíduos de 14 a 21 dias, os quais foram imersos nos extratos nas concentrações de 1, 5, 10, 15 e 20 mg mL-1. Após o tratamento, cada grupo foi colocado em placa de Petri e incubado a 27 ± 1 ºC e umidade relativa de 80 ± 5%. Os extratos avaliados não foram eficazes para induzir, acima de 50%, a mortalidade de fêmeas ingurgitadas. Os extratos acetato de etila e etanólico induziram 100% de mortalidade de larvas. Entretanto, quanto aos valores de concentração letal mediana (CL50), o extrato etanólico (CL50 = 2,1 mg mL-1) foi mais tóxico que o extrato acetato de etila (CL50 = 4,1 mg mL-1). O extrato etanólico estimou concentração inibitória mediana (CI50) de 3,0 mg mL-1 e foi mais tóxico que os demais extratos quanto a este parâmetro de avaliação. Entre os três extratos avaliados, os extratos acetato de etila e etanólico apresentaram os melhores resultados quanto ao controle de reprodução de R. (B.) microplus, atingindo 100% na concentração de 5 mg mL-1. Os extratos de raízes de L. Floribundus apresentaram atividade biológica sobre carrapato bovino

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Robustness of the shrinkage estimator for the relative potency in the combination of multivariate bioassays

This paper investigates the robustness of the shrinkage Bayesian estimator for the relative potency parameter in the combinations of multivariate bioassays proposed in Chen et al.(1999), which incorporated prior information on the model parame- ters based on Je reys' rules. This investigation is carried out for the families of t-distribution and Cauchy-distribution based on the characteristics of bioassay the- ory since the t-distribution approaches the normal distribution which is the most commonly used distribution in the applications of bioassay as the degrees of freedom increases and the t-distribution approaches the Cauchy-distribution as the degrees of freedom approaches 1 which is also an important distribution in bioassay. A real data is used to illustrate the application of this investigation. This analysis further supports the application of the shrinkage Bayesian estimator to the theory of bioassay along with the empirical Bayesian estimator.http://www.tandfonline.com/loi/lsta202017-09-30hb2016Statistic