• Publicationsclose
• Other research productsclose
• Open Access close
• Research close
• DE close

Motivated by the current discussion on different separate banking systems, we provide an overview of the different systems, question them and outline their effect on systemic stability and the German banking sector. The results show that the various separate banking systems only play a minor role in reducing and limiting systemic risk. They only marginally contribute to solving conflicts of interest and can even be detrimental to banking business diversification. A separate banking system could, however, facilitate banking supervision by reducing the banking system’s complexity. Furthermore, credible threats to not support investment banks with federal resources in times of crisis could lead to a more adequate incentives structure of suppliers of equity and outside capital. More efficient measures to further reduce systemic risk in the financial sector should, however, use different levers, such as additional minimum regulatory capital requirements.

A search is performed for Higgs-boson-mediated flavor-changing neutral currents in the decays of top quarks. The search is based on proton-proton collision data corresponding to an integrated luminosity of 19.7 fb$^{-1}$ at a center-of-mass energy of 8 TeV collected with the CMS detector at the LHC. Events in which a top quark pair is produced with one top quark decaying into a charm or up quark and a Higgs boson (H), and the other top quark decaying into a bottom quark and a W boson are selected. The Higgs boson in these events is assumed to subsequently decay into either dibosons or difermions. No significant excess is observed above the expected standard model background, and an upper limit at the 95% confidence level is set on the branching fraction B(t $\to$ Hc) of 0.40% and B(t $\to$ Hu) of 0.55%, where the expected upper limits are 0.43% and 0.40%, respectively. These results correspond to upper limits on the square of the flavor-changing Higgs boson Yukawa couplings $|\lambda^{H}_{tc}|^2$ < 6.9 $\times$ 10$^{-3}$ and $|\lambda^{H}_{tu}|^2$ < 9.8 $\times$ 10$^{-3}$. Journal of high energy physics 1702(02), 079(2017). doi:10.1007/JHEP02(2017)079 Published by Springer, Berlin

Compact myelin forms the basis of nerve insulation essential for higher vertebrates. Dozens of myelin membrane bilayers undergo tight stacking, and in the peripheral nervous system, this is partially enabled by myelin protein zero (P0). Consisting of an immunoglobulin (Ig)-like extracellular domain, a single transmembrane helix, and a cytoplasmic extension (P0ct), P0 harbours an important task in ensuring the integrity of compact myelin in the extracellular compartment, referred to as the intraperiod line. Several disease mutations resulting in peripheral neuropathies have been identified for P0, reflecting its physiological importance, but the arrangement of P0 within the myelin ultrastructure remains obscure. We performed a biophysical characterization of recombinant P0ct. P0ct contributes to the binding affinity between apposed cytoplasmic myelin membrane leaflets, which not only results in changes of the bilayer properties, but also potentially involves the arrangement of the Ig-like domains in a manner that stabilizes the intraperiod line. Transmission electron cryomicroscopy of native full-length P0 showed that P0 stacks lipid membranes by forming antiparallel dimers between the extracellular Ig-like domains. The zipper-like arrangement of the P0 extracellular domains between two membranes explains the double structure of the myelin intraperiod line. Our results contribute to the understanding of PNS myelin, the role of P0 therein, and the underlying molecular foundation of compact myelin stability in health and disease. Scientific Reports, 9 ISSN:2045-2322

In digital history, uncertainty is generally regarded as an unavoidable evil. One generally aims to reduce—and ideally resolve—uncertainty in data as much as possible. However, information systems are not designed to handle the absence of information; we discuss how both SQL’s seemingly simple Null marker and the TEI Guideline’s elaborate facilities for recording “certainty” fail to address the challenges posed by uncertainty. Neither is big data and a “digital historical positivism” a satisfactory answer: the causal models that underpin historical narratives do not simply emerge from a collection of facts. Here, it is necessary to distinguish between two types of uncertainty: historical uncertainty, which concerns the facts of the past, and historiographical uncertainty, which concerns the causal models constructed by historians. The latter results from different interpretations of the causal relations between the facts; given our limited knowledge of the past, it is ultimately irreducible. But it is also this uncertainty that allows us to construct the narratives we need for sense-making. We argue that in this sense uncertainty may be regarded as an unavoidable good and that we should aim to design computational frameworks that treat it as an asset rather than an obstacle.

The life-cycle hypothesis implies that consumption would not decline at retirement. However, several studies found relevant declines in food consumption after retirement for the United States. Others concluded that this contradiction of the life-cycle hypothesis is solved by allowing for broader measures of consumption than food. Using repeated cross-section data for Germany, this paper analyzes the retirement consumption puzzle for the German case. For our broadest consumption measure, which includes the flow of durables' consumption, we find, on average, no significant consumption decline at retirement. This also holds if the potential endogeneity of individual retirement is controlled for in instrumental variable regressions. We also find heterogeneity in retirement effects among birth cohorts, the level of household wealth, and the level of consumption, but these effects do not support the hypothesis that retirement is associated with a strong reduction of consumption among poorer households.

This paper describes how feature extraction on ancient pottery can be combined with recent developments in artificial intelligence to draw up an automated, but still flexible classification system. These features include for instance several dimensions of the vessel's body, ratios thereof, an abstract representation of the overall shape, the shape of vessel segments and the number and type of attachments such as handles, lugs and feet. While most traditional approaches to classification are based on statistical analysis or the search for fuzzy clusters in high-dimensional spaces, we apply machine learning techniques, such as decision tree algorithms and neural networks. These methods allow for an objective and reproducible classification process. Conclusions about the "typability" of data, the evolution of types and the diagnostic attributes of the types themselves can be drawn as well.

Conditional yield skewness is an important summary statistic of the state of the economy. It exhibits pronounced variation over the business cycle and with the stance of monetary policy, and a tight relationship with the slope of the yield curve. Most importantly, variation in yield skewness has substantial forecasting power for future bond excess returns, high-frequency interest rate changes around FOMC announcements, and consensus survey forecast errors for the ten-year Treasury yield. The COVID pandemic did not disrupt these relations: historically high skewness correctly anticipated the run-up in long-term Treasury yields starting in late 2020. The connection between skewness, survey forecast errors, excess returns, and departures of yields from normality is consistent with a theoretical framework where one of the agents has biased beliefs.