Arbeitsbericht Nr. 2015-02, August 2015

Entscheidungsbäume sind als Prognoseverfahren im Bereich des maschinellen Lernens verbreitet. Jedoch fehlt bisher eine Untersuchung, in wieweit sich die Algorithmen auch zur Imputation eignen. Dies ist insbesonders vor dem Hintergrund der verschiedenen Zielstellungen einer Imputation und einer Klassifikation relevant. So liegt bei einer Imputation häufig ein stärkerer Fokus auf der Struktur des Gesamtdatensatzes, wohingegen eine Klassifikation auf eine möglichst genaue Vorhersage einzelner Objekte abzielt. Neben den klassischen deterministischen Entscheidungsbäumen mit Majority Rule werden daher auch Entscheidungsbäume mit Class Probability Rule mit einer Zufallskomponente in die Untersuchung mit einbezogen. In einer Simulationsstudie, in der als Vergleichsverfahren zusätzlich eine Modus-Imputation und ein Random Hot Deck eingesetzt werden, zeigt sich, dass kein Verfahren in allen Fällen zum besten Ergebnis führt. So führt die Imputation mittels Entscheidungsbaum und Class Probability Rule meist zur geringsten Verzerrung der Häufigkeitsverteilung, jedoch stellt der Entscheidungsbaum mit Majority Rule meist die ursprünglichen Werte am besten wieder her. Welches Verfahren zur Imputation verwendet werden sollte, ist also abhängig vom Ziel der Imputation

Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

Acknowledgments We thank Reik V. Donner for inspiring suggestions that initialized the work presented herein. Jan H. Feldhoff is credited for providing us with the STARS simulation data and for his contributions to fruitful discussions. Comments by the anonymous reviewers are gratefully acknowledged as they led to substantial improvements of the manuscript.Peer reviewedPublisher PD

Nitric oxide sensing in plants is mediated by proteolytic control of group VII ERF transcription factors

Nitric oxide (NO) is an important signaling compound in prokaryotes and eukaryotes. In plants, NO regulates critical developmental transitions and stress responses. Here, we identify a mechanism for NO sensing that coordinates responses throughout development based on targeted degradation of plant-specific transcriptional regulators, the group VII ethylene response factors (ERFs). We show that the N-end rule pathway of targeted proteolysis targets these proteins for destruction in the presence of NO, and we establish them as critical regulators of diverse NO-regulated processes, including seed germination, stomatal closure, and hypocotyl elongation. Furthermore, we define the molecular mechanism for NO control of germination and crosstalk with abscisic acid (ABA) signaling through ERF-regulated expression of ABSCISIC ACID INSENSITIVE5 (ABI5). Our work demonstrates how NO sensing is integrated across multiple physiological processes by direct modulation of transcription factor stability and identifies group VII ERFs as central hubs for the perception of gaseous signals in plants

The RACE Project: Robustness by Autonomous Competence Enhancement

This paper reports on the aims, the approach, and the results of the European project RACE. The project aim was to enhance the behavior of an autonomous robot by having the robot learn from conceptualized experiences of previous performance, based on initial models of the domain and its own actions in it. This paper introduces the general system architecture; it then sketches some results in detail regarding hybrid reasoning and planning used in RACE, and instances of learning from the experiences of real robot task execution. Enhancement of robot competence is operationalized in terms of performance quality and description length of the robot instructions, and such enhancement is shown to result from the RACE system

Effects of external nutrient sources and extreme weather events on the nutrient budget of a Southern European coastal lagoon

The seasonal and annual nitrogen (N), phosphorus (P), and carbon (C) budgets of the mesotidal Ria Formosa lagoon, southern Portugal, were estimated to reveal the main inputs and outputs, the seasonal patterns, and how they may influence the ecological functioning of the system. The effects of extreme weather events such as long-lasting strong winds causing upwelling and strong rainfall were assessed. External nutrient inputs were quantified; ocean exchange was assessed in 24-h sampling campaigns, and final calculations were made using a hydrodynamic model of the lagoon. Rain and stream inputs were the main freshwater sources to the lagoon. However, wastewater treatment plant and groundwater discharges dominated nutrient input, together accounting for 98, 96, and 88 % of total C, N, and P input, respectively. Organic matter and nutrients were continuously exported to the ocean. This pattern was reversed following extreme events, such as strong winds in early summer that caused upwelling and after a period of heavy rainfall in late autumn. A principal component analysis (PCA) revealed that ammonium and organic N and C exchange were positively associated with temperature as opposed to pH and nitrate. These variables reflected mostly the benthic lagoon metabolism, whereas particulate P exchange was correlated to Chl a, indicating that this was more related to phytoplankton dynamics. The increase of stochastic events, as expected in climate change scenarios, may have strong effects on the ecological functioning of coastal lagoons, altering the C and nutrient budgets.Portuguese Science and Technology Foundation (FCT) [POCI/MAR/58427/2004, PPCDT/MAR/58427/2004]; Portuguese Science and Technology Foundation (FCT

ATM regulates proteasome-dependent subnuclear localization of TRF1, which is important for telomere maintenance

Ataxia telangiectasia mutated (ATM), a PI-3 kinase essential for maintaining genomic stability, has been shown to regulate TRF1, a negative mediator of telomerase-dependent telomere extension. However, little is known about ATM-mediated TRF1 phosphorylation site(s) in vivo. Here, we report that ATM phosphorylates S367 of TRF1 and that this phosphorylation renders TRF1 free of chromatin. We show that phosphorylated (pS367)TRF1 forms distinct non-telomeric subnuclear foci and that these foci occur predominantly in S and G2 phases, implying that their formation is cell cycle regulated. We show that phosphorylated (pS367)TRF1-containing foci are sensitive to proteasome inhibition. We find that a phosphomimic mutation of S367D abrogates TRF1 binding to telomeric DNA and renders TRF1 susceptible to protein degradation. In addition, we demonstrate that overexpressed TRF1-S367D accumulates in the subnuclear domains containing phosphorylated (pS367)TRF1 and that these subnuclear domains overlap with nuclear proteasome centers. Taken together, these results suggest that phosphorylated (pS367)TRF1-containing foci may represent nuclear sites for TRF1 proteolysis. Furthermore, we show that TRF1 carrying the S367D mutation is unable to inhibit telomerase-dependent telomere lengthening or to suppress the formation of telomere doublets and telomere loss in TRF1-depleted cells, suggesting that S367 phosphorylation by ATM is important for the regulation of telomere length and stability

Wind gust estimation for Mid-European winter storms: towards a probabilistic view

Three wind gust estimation (WGE) methods implemented in the numerical weather prediction (NWP) model COSMO-CLM are evaluated with respect to their forecast quality using skill scores. Two methods estimate gusts locally from mean wind speed and the turbulence state of the atmosphere, while the third one considers the mixing-down of high momentum within the planetary boundary layer (WGE Brasseur). One hundred and fifty-eight windstorms from the last four decades are simulated and results are compared with gust observations at 37 stations in Germany. Skill scores reveal that the local WGE methods show an overall better behaviour, whilst WGE Brasseur performs less well except for mountain regions. The here introduced WGE turbulent kinetic energy (TKE) permits a probabilistic interpretation using statistical characteristics of gusts at observational sites for an assessment of uncertainty. The WGE TKE formulation has the advantage of a ‘native’ interpretation of wind gusts as result of local appearance of TKE. The inclusion of a probabilistic WGE TKE approach in NWP models has, thus, several advantages over other methods, as it has the potential for an estimation of uncertainties of gusts at observational sites

Population Receptive Field Dynamics in Human Visual Cortex

Seminal work in the early nineties revealed that the visual receptive field of neurons in cat primary visual cortex can change in location and size when artificial scotomas are applied. Recent work now suggests that these single neuron receptive field dynamics also pertain to the neuronal population receptive field (pRF) that can be measured in humans with functional magnetic resonance imaging (fMRI). To examine this further, we estimated the pRF in twelve healthy participants while masking the central portion of the visual field. We found that the pRF changes in location and size for two differently sized artificial scotomas, and that these pRF dynamics are most likely due to a combination of the neuronal receptive field position and size scatter as well as modulatory feedback signals from extrastriate visual areas

Histological basis of laminar MRI patterns in high resolution images of fixed human auditory cortex

Functional magnetic resonance imaging (fMRI) studies of the auditory region of the temporal lobe would benefit from the availability of image contrast that allowed direct identification of the primary auditory cortex, as this region cannot be accurately located using gyral landmarks alone. Previous work has suggested that the primary area can be identified in magnetic resonance (MR) images because of its relatively high myelin content. However, MR images are also affected by the iron content of the tissue and in this study we sought to confirm that different MR image contrasts did correlate with the myelin content in the grey matter and were not primarily affected by iron content as is the case in the primary visual and somatosensory areas. By imaging blocks of fixed post-mortem cortex in a 7 Tesla scanner and then sectioning them for histological staining we sought to assess the relative contribution of myelin and iron to the grey matter contrast in the auditory region. Evaluating the image contrast in T2*-weighted images and quantitative R2* maps showed a reasonably high correlation between the myelin density of the grey matter and the intensity of the MR images. The correlation with T1-weighted phase sensitive inversion recovery (PSIR) images was better than with the previous two image types, and there were clearly differentiated borders between adjacent cortical areas in these images. A significant amount of iron was present in the auditory region, but did not seem to contribute to the laminar pattern of the cortical grey matter in MR images. Similar levels of iron were present in the grey and white matter and although iron was present in fibres within the grey matter, these fibres were fairly uniformly distributed across the cortex. Thus we conclude that T1- and T2*-weighted imaging sequences do demonstrate the relatively high myelin levels that are characteristic of the deep layers in primary auditory cortex and allow it and some of the surrounding areas to be reliably distinguished

Projections of global warming-induced impacts on winter storm losses in the German private household sector

We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971–2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6–35 % for 2011–2040, of 20–30 % for 2041–2070, and of 40–55 % for 2071–2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses