neuralnet: Training of neural networks

Artificial neural networks are applied in many situations. neuralnet is built to train multi-layer perceptrons in the context of regression analyses, i.e. to approximate functional relationships between covariates and response variables. Thus, neural networks are used as extensions of generalized linear models. neuralnet is a very flexible package. The backpropagation algorithm and three versions of resilient backpropagation are implemented and it provides a custom-choice of activation and error function. An arbitrary number of covariates and response variables as well as of hidden layers can theoretically be included

The impact of sulfur hexafluoride (SF₆) sinks on age of air climatologies and trends

Mean age of air (AoA) is a common diagnostic for the strength of the stratospheric overturning circulation in both climate models and observations. AoA climatologies and AoA trends over the recent decades of model simulations and proxies derived from observations of long-lived tracers do not agree. Satellite observations show much older air than climate models, and while most models compute a clear decrease in AoA over the last decades, a 30-year time series from measurements shows a statistically nonsignificant positive trend in the Northern Hemisphere extratropical middle stratosphere. Measurement-based AoA derivations are often founded on observations of the trace gas sulfur hexafluoride (SF$_{6}$), a fairly long-lived gas with a near-linear increase in emissions during recent decades. However, SF$_{6}$ has chemical sinks in the mesosphere that are not considered in most model studies. In this study, we explicitly compute the chemical SF$_{6}$ sinks based on chemical processes in the global chemistry climate model EMAC (ECHAM/MESSy Atmospheric Chemistry). We show that good agreement between stratospheric AoA in EMAC and MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) is reached through the inclusion of chemical SF$_{6}$ sinks, as these sinks lead to a strong increase in the stratospheric AoA and, therefore, to a better agreement with MIPAS satellite observations. Remaining larger differences at high latitudes are addressed, and possible reasons for these differences are discussed. Subsequently, we demonstrate that the AoA trends are also strongly influenced by the chemical SF6 sinks. Under consideration of the SF$_{6}$ sinks, the AoA trends over the recent decades reverse sign from negative to positive. We conduct sensitivity simulations which reveal that this sign reversal does not result from trends in the stratospheric circulation strength nor from changes in the strength of the SF$_{6}$ sinks. We illustrate that even a constant SF$_{6}$ destruction rate causes a positive trend in the derived AoA, as the amount of depleted SF$_{6}$ scales with increasing SF$_{6}$ abundance itself. In our simulations, this effect overcompensates for the impact of the accelerating stratospheric circulation which naturally decreases AoA. Although various sources of uncertainties cannot be quantified in detail in this study, our results suggest that the inclusion of SF$_{6}$ depletion in models has the potential to reconcile the AoA trends of models and observations. We conclude the study with a first approach towards a correction to account for SF$_{6}$ loss and deduce that a linear correction might be applicable to values of AoA of up to 4 years

Impact of Lagrangian transport on lower-stratospheric transport timescales in a climate model

We investigate the impact of model trace gas transport schemes on the representation of transport processes in the upper troposphere and lower stratosphere. Towards this end, the Chemical Lagrangian Model of the Stratosphere (CLaMS) was coupled to the ECHAM/MESSy Atmospheric Chemistry (EMAC) model and results from the two transport schemes (Lagrangian critical Lyapunov scheme and flux-form semi-Lagrangian, respectively) were compared. Advection in CLaMS was driven by the EMAC simulation winds, and thereby the only differences in transport between the two sets of results were caused by differences in the transport schemes. To analyze the timescales of large-scale transport, multiple tropical-surface-emitted tracer pulses were performed to calculate age of air spectra, while smaller-scale transport was analyzed via idealized, radioactively decaying tracers emitted in smaller regions (nine grid cells) within the stratosphere. The results show that stratospheric transport barriers are significantly stronger for Lagrangian EMAC-CLaMS transport due to reduced numerical diffusion. In particular, stronger tracer gradients emerge around the polar vortex, at the subtropical jets, and at the edge of the tropical pipe. Inside the polar vortex, the more diffusive EMAC flux-form semi-Lagrangian transport scheme results in a substantially higher amount of air with ages from 0 to 2 years (up to a factor of 5 higher). In the lowermost stratosphere, mean age of air is much smaller in EMAC, owing to stronger diffusive cross-tropopause transport. Conversely, EMAC-CLaMS shows a summertime lowermost stratosphere age inversion – a layer of older air residing below younger air (an “eave”). This pattern is caused by strong poleward transport above the subtropical jet and is entirely blurred by diffusive cross-tropopause transport in EMAC. Potential consequences from the choice of the transport scheme on chemistry–climate and geoengineering simulations are discussed

The impact of sulfur hexafluoride (SF6) sinks on age of air climatologies and trends

Mean age of air (AoA) is a common diagnostic for the strength of the stratospheric overturning circulation in both climate models and observations. AoA climatologies and AoA trends over the recent decades of model simulations and proxies derived from observations of long-lived tracers do not agree. Satellite observations show much older air than climate models, and while most models compute a clear decrease in AoA over the last decades, a 30-year time series from measurements shows a statistically nonsignificant positive trend in the Northern Hemisphere extratropical middle stratosphere. Measurement-based AoA derivations are often founded on observations of the trace gas sulfur hexafluoride (SF6), a fairly long-lived gas with a near-linear increase in emissions during recent decades. However, SF6 has chemical sinks in the mesosphere that are not considered in most model studies. In this study, we explicitly compute the chemical SF6 sinks based on chemical processes in the global chemistry climate model EMAC (ECHAM/MESSy Atmospheric Chemistry). We show that good agreement between stratospheric AoA in EMAC and MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) is reached through the inclusion of chemical SF6 sinks, as these sinks lead to a strong increase in the stratospheric AoA and, therefore, to a better agreement with MIPAS satellite observations. Remaining larger differences at high latitudes are addressed, and possible reasons for these differences are discussed. Subsequently, we demonstrate that the AoA trends are also strongly influenced by the chemical SF6 sinks. Under consideration of the SF6 sinks, the AoA trends over the recent decades reverse sign from negative to positive. We conduct sensitivity simulations which reveal that this sign reversal does not result from trends in the stratospheric circulation strength nor from changes in the strength of the SF6 sinks. We illustrate that even a constant SF6 destruction rate causes a positive trend in the derived AoA, as the amount of depleted SF6 scales with increasing SF6 abundance itself. In our simulations, this effect overcompensates for the impact of the accelerating stratospheric circulation which naturally decreases AoA. Although various sources of uncertainties cannot be quantified in detail in this study, our results suggest that the inclusion of SF6 depletion in models has the potential to reconcile the AoA trends of models and observations. We conclude the study with a first approach towards a correction to account for SF6 loss and deduce that a linear correction might be applicable to values of AoA of up to 4 years

Oxytocin Receptor Genotype Modulates Ventral Striatal Activity to Social Cues and Response to Stressful Life Events

Background Common variants in the oxytocin receptor gene (OXTR) have been shown to influence social and affective behavior and to moderate the effect of adverse experiences on risk for social-affective problems. However, the intermediate neurobiological mechanisms are not fully understood. Although human functional neuroimaging studies have reported that oxytocin effects on social behavior and emotional states are mediated by amygdala function, animal models indicate that oxytocin receptors in the ventral striatum (VS) modulate sensitivity to social reinforcers. This study aimed to comprehensively investigate OXTR-dependent brain mechanisms associated with social-affective problems. Methods In a sample of 1445 adolescents we tested the effect of 23-tagging single nucleotide polymorphisms across the OXTR region and stressful life events (SLEs) on functional magnetic resonance imaging blood oxygen level-dependent activity in the VS and amygdala to animated angry faces. Single nucleotide polymorphisms for which gene-wide significant effects on brain function were found were then carried forward to examine associations with social-affective problems. Results A gene-wide significant effect of rs237915 showed that adolescents with minor CC-genotype had significantly lower VS activity than CT/TT-carriers. Significant or nominally significant gene × environment effects on emotional problems (in girls) and peer problems (in boys) revealed a strong increase in clinical symptoms as a function of SLEs in CT/TT-carriers but not CC-homozygotes. However, in low-SLE environments, CC-homozygotes had more emotional problems (girls) and peer problems (boys). Moreover, among CC-homozygotes, reduced VS activity was related to more peer problems. Conclusions These findings suggest that a common OXTR-variant affects brain responsiveness to negative social cues and that in "risk- carriers" reduced sensitivity is simultaneously associated with more social-affective problems in "favorable environments" and greater resilience against stressful experiences. © 2014 Society of Biological Psychiatry

Neural networks for modeling gene-gene interactions in association studies

<p>Abstract</p> <p>Background</p> <p>Our aim is to investigate the ability of neural networks to model different two-locus disease models. We conduct a simulation study to compare neural networks with two standard methods, namely logistic regression models and multifactor dimensionality reduction. One hundred data sets are generated for each of six two-locus disease models, which are considered in a low and in a high risk scenario. Two models represent independence, one is a multiplicative model, and three models are epistatic. For each data set, six neural networks (with up to five hidden neurons) and five logistic regression models (the null model, three main effect models, and the full model) with two different codings for the genotype information are fitted. Additionally, the multifactor dimensionality reduction approach is applied.</p> <p>Results</p> <p>The results show that neural networks are more successful in modeling the structure of the underlying disease model than logistic regression models in most of the investigated situations. In our simulation study, neither logistic regression nor multifactor dimensionality reduction are able to correctly identify biological interaction.</p> <p>Conclusions</p> <p>Neural networks are a promising tool to handle complex data situations. However, further research is necessary concerning the interpretation of their parameters.</p

What causes the mid-winter cooling?

This thesis investigated the influence and conditions of vertical propagation of planetary waves on the mid-winter cooling in the southern hemispheric polar meso- sphere. MERRA zonal wind data was used to extract planetary waves with zonal wavenumber 1, 2 and 3 at 72°S in 2008 and 2009. The wave periods of 4, 5, 10 and 16 days were separated using Morlet wavelet analysis. A correlation between the wave amplitude and carbon monoxide as a tracer for vertical motion could be found from autumn until late winter (from March until late August/mid September). Between the wave amplitude and the mean zonal wind anticorrelation was shown from early winter until late winter (April until late Au- gust/mid September). Both correlations were found to stop when the mesospheric circulation restores in September. In addition agreement between calculations for the upper bound of the Charney-Drazin criterion for vertical propagation and the wave activity was found until late August/mid September