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Detailed results of linear and logistic regression models for all dimensions. (DOCX 55 kb)

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.

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.

What are the societal and political consequences of the recognition of armed non-state actors (ANSAs) in the context of asymmetric conflicts? Based on a discussion of diverse contemporary examples the three authors present the state of research on recognition dynamics. They shed light on the ambivalences of recognition practises and "thick recognition" in asymmetric conflicts, revealing dilemmas and unintended consequences. They recommend further empirical research and knowledge transfer among practitioners, researchers, and policymakers to better understand the dynamics and draw benefits for international security and conflict management.

In this paper we study the finite sample and asymptotic properties of various weighting estimators of the local average treatment effect (LATE), several of which are based on Abadie (2003)'s kappa theorem. Our framework presumes a binary endogenous explanatory variable ("treatment") and a binary instrumental variable, which may only be valid after conditioning on additional covariates. We argue that one of the Abadie estimators, which we show is weight normalized, is likely to dominate the others in many contexts. A notable exception is in settings with one-sided noncompliance, where certain unnormalized estimators have the advantage of being based on a denominator that is bounded away from zero. We use a simulation study and three empirical applications to illustrate our findings. In applications to causal effects of college education using the college proximity instrument (Card, 1995) and causal effects of childbearing using the sibling sex composition instrument (Angrist and Evans, 1998), the unnormalized estimates are clearly unreasonable, with "incorrect" signs, magnitudes, or both. Overall, our results suggest that (i) the relative performance of different kappa weighting estimators varies with features of the data-generating process; and that (ii) the normalized version of Tan (2006)'s estimator may be an attractive alternative in many contexts. Applied researchers with access to a binary instrumental variable should also consider covariate balancing or doubly robust estimators of the LATE.