Stratospheric Influence on the Tropospheric Circulation Revealed by Idealized Ensemble Forecasts

The coupling between the stratosphere and troposphere following Stratospheric Sudden Warming (SSW) events is investigated in an idealized atmospheric General Circulation Model, with focus on the influence of stratospheric memory on the troposphere. Ensemble forecasts are performed to confirm the role of the stratosphere in the observed equatorward shift of the tropospheric midlatitude jet following an SSW. It is demonstrated that the tropospheric response to the weakening of the lower stratospheric vortex is robust, but weak in amplitude and thus easily masked by tropospheric variability. The amplitude of the response in the troposphere is crucially sensitive to the depth of the SSW. The persistence of the response in the troposphere is attributed to both the increased predictability of the stratosphere following an SSW, and the dynamical coupling between the tropospheric jet and lower stratosphere. These results suggest value in resolving the stratosphere and assimilating upper atmospheric data in forecast models

Consideraciones respecto al desarrollo de la climatización en la arquitectura de la costa ecuatoriana

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Air-Mass Origin as a Diagnostic of Tropospheric Transport

We introduce rigorously defined air masses as a diagnostic of tropospheric transport. The fractional contribution from each air mass partitions air at any given point according to either where it was last in the planetary boundary layer or where it was last in contact with the stratosphere. The utility of these air-mass fractions is demonstrated for the climate of a dynamical core circulation model and its response to specified heating. For an idealized warming typical of end-of-century projections, changes in air-mass fractions are in the order of 10% and reveal the model's climate change in tropospheric transport: poleward-shifted jets and surface-intensified eddy kinetic energy lead to more efficient stirring of air out of the midlatitude boundary layer, suggesting that, in the future, there may be increased transport of black carbon and industrial pollutants to the Arctic upper troposphere. Correspondingly, air is less efficiently mixed away from the subtropical boundary layer. The air-mass fraction that had last stratosphere contact at midlatitudes increases all the way to the surface, in part due to increased isentropic eddy transport across the tropopause. Correspondingly, the air-mass fraction that had last stratosphere contact at high latitudes is reduced through decreased downwelling across the tropopause. A weakened Hadley circulation leads to decreased interhemispheric transport in the model's future climate

Nonparametric estimation of time varying parameters under shape restrictions

In this paper we propose a new method to estimate nonparametrically a time varying parameter model when some qualitative information from outside data (e.g. seasonality) is available. In this framework we make two main contributions. First, the resulting estimator is shown to belong to the class of generalized ridge estimators and under some conditions its rate of convergence is optimal within its smoothness class. Furthermore, if the outside data information is fullfilled by the underlying model, the estimator shows efficiency gains in small sample sizes. Second, for the implementation process, since the estimation procedure envolves the computation of the inverse of a high order matrix we provide an algorithm that avoids this computation and, also, a data-driven method is derived to select the control parameters. The practical performance of the method is demonstrated in a simulation study and in an application to the demand of soft drinks in Canada.This work was supported by Dirección General de Enseñanza Superior del Ministerio de Educación y Ciencia under research grant PB98-0149, and by the Universidad del País Vasco under research grant UPV 038.321-HA129/99

Nonparametric estimation of time varying parameters under shape restrictions

In this paper we propose a new method to estimate nonparametrically a time varying parameter model when some qualitative information from outside data (e.g. seasonality) is available. In this framework we make two main contributions. First, the resulting estimator is shown to belong to the class of generalized ridge estimators and under some conditions its rate of convergence is optimal within its smoothness class. Furthermore, if the outside data information is fullfilled by the underlying model, the estimator shows efficiency gains in small sample sizes. Second, for the implementation process, since the estimation procedure envolves the computation of the inverse of a high order matrix we provide an algorithm that avoids this computation and, also, a data-driven method is derived to select the control parameters. The practical performance of the method is demonstrated in a simulation study and in an application to the demand of soft drinks in Canada.nonparametric regression, Kernel estimators, time varying coefficients, bandwidth selection, estimation algorithm, seasonality

Excreção de amônia por tambaqui (Colossoma macropomum) de acordo com variações na temperatura da água e massa do peixe.

O objetivo deste trabalho foi quantificar taxas de excreção diária de amônia em tambaqui (Colossoma macropomum), principal espécie criada na Amazônia, que podem variar de acordo com a temperatura da água e a massa dos peixes

The 4G/5G PAI-1 polymorphism influences the endothelial response to IL-1 and the modulatory effect of pravastatin

BACKGROUND: Increased plasminogen activator inhibitor (PAI-1) levels lead to impaired fibrinolytic function associated with higher cardiovascular risk. PAI-1 expression may be regulated by different inflammatory cytokines such as interleukin-1alpha (IL-1). Several polymorphisms have been described in the PAI-1 gene. AIM: We examined the influence of the 4G/5G polymorphism in the promoter region on IL-1alpha-induced PAI-1 expression by human umbilical vein endothelial cells (HUVEC) in presence or absence of pravastatin. METHODS AND RESULTS: Genotyped HUVEC were incubated with IL-1alpha (500 U mL(-1)) in presence or absence of pravastatin (1-10 microm). PAI-1 expression was analyzed by real time polymerase chain reaction (PCR), and PAI-1 antigen measured in supernatants by ELISA. IL-1alpha increased PAI-1 secretion in a genotype-dependent manner, and higher values were observed for 4G/4G compared with both 4G/5G and 5G/5G cultures (P < 0.05). Preincubation of HUVEC with 10 microm pravastatin significantly reduced IL-1-induced PAI-1 expression in 4G/4G HUVEC compared with untreated cultures (177.5% +/- 24.5% vs. 257.9% +/- 39.0%, P < 0.05). Pravastatin also attenuated the amount of secreted PAI-1 by 4G/4G HUVEC after IL-1 stimulation (5020.6 +/- 165.7 ng mL(-1) vs. 4261.1 +/- 309.8 ng mL(-1), P < 0.05). This effect was prevented by coincubation with mevalonate, indicating a dependence on HMG-CoA reductase inhibition. CONCLUSIONS: The endothelial 4G/5G PAI-1 genotype influences the PAI-1 response to IL-1alpha and the modulatory effect of pravastatin. As increased PAI-1 levels have been linked to cardiovascular disease the observed endothelial modulation by pravastatin may have potential clinical implications

The Mediating Effect of Self-Efficacy on the Clinical Learning Environment and Critical Thinking

Newly graduated nursing students entering the work field are not meeting the standard levels of skills such as critical thinking. The clinical learning environment (CLE) is a crucial part of nursing education that allows nursing students to develop critical thinking skills while dealing with real-life patient scenarios. Moreover, present during clinical exposure is self-efficacy that is vaguely linked to the CLE and critical thinking. Hence, this study aims to identify the relationships between these three variables. This quantitative study purposively sampled 134 nursing students enrolled during the Academic Year 2019-2020. Respondents answered an online survey questionnaire composed of four parts: the demographic profile, CLE, perceived clinical self-efficacy, and critical thinking. The descriptive statistics using SPSS 24 revealed that the respondents perceived their CLE as good, they had a high level of perceived clinical self-efficacy, and they had a good level of perceived critical thinking. Moreover, Structural Equation Modeling (SEM) using AMOS 23 revealed that the model’s fit indices are excellent (CMIN = .985; CFI = 1; SRMR = 0.043; RMSEA = 0.00; and PClose = 0.895). Analysis showed that CLE has a positive direct effect on perceived clinical self-efficacy but no significant direct effect on perceived critical thinking. Further, perceived clinical self-efficacy has a positive direct effect on perceived critical thinking. Lastly, self-efficacy fully mediates the positive relationship between the CLE and perceived critical thinking. Evidence reveals that nursing educators could increase students’ perceived critical thinking in the clinical area by enhancing self-efficacy. The study recommends replication of the study with larger samples and that CLE instruments should be further validated and developed. Keywords: self-efficacy, hospital placement, structural equation modeling, critical thinkin