Local Multiplicative Bias Correction for Asymmetric Kernel Density Estimators

We consider semiparametric asymmetric kernel density estimators when the unknown density has support on [0, ¥). We provide a unifying framework which contains asymmetric kernel versions of several semiparametric density estimators considered previously in the literature. This framework allows us to use popular parametric models in a nonparametric fashion and yields estimators which are robust to misspecification. We further develop a specification test to determine if a density belongs to a particular parametric family. The proposed estimators outperform rival non- and semiparametric estimators in finite samples and are simple to implement. We provide applications to loss data from a large Swiss health insurer and Brazilian income data.semiparametric density estimation; asymmetric kernel; income distribution; loss distribution; health insurance; specification testing

Real Asset Returns and Components of Inflation: A Structural VAR Analysis

We shed new light on the negative relationship between real stock returns or real interest rates and (i) ex post inflation, (ii) expected inflation, (iii) unexpected inflation and (iv) changes in expected inflation. Using the structural vector autoregression methodology, we propose a decomposition of those series into economically interpretable components driven by aggregate supply, real demand and money market shocks. Our empirical results support Fama’s ’proxy hypothesis’ and the predictions of several general equilibrium models. Concerning the negative relation between the real rate of interest and inflation, we find that the Mundell-Tobin model and the explanation of Fama and Gibbons (1982) are not competitors: both add insight in their own way about the reasons for the negative correlation between those variables. However, the importance of the latter explanation has decreased since the 1980’s.real stock returns, real rate of interest, expected and unexpected inflation, ’Fisher hypothesis’, structural VAR.

Real Asset Returns and Components of Inflation: A Structural VAR Analysis

We shed new light on the negative relationship between real stock returns or real interest rates and (i) ex post inflation, (ii) expected inflation, (iii) unexpected inflation and (iv) changes in expected inflation. Using the structural vector autoregression methodology, we propose a decomposition of those series into economically interpretable components driven by aggregate supply, real demand and money market shocks. Our empirical results support Fama’s ’proxy hypothesis’ and the predictions of several general equilibrium models. Concerning the negative relation between the real rate of interest and inflation, we find that the Mundell-Tobin model and the explanation of Fama and Gibbons (1982) are not competitors: both add insight in their own way about the reasons for the negative correlation between those variables. However, the importance of the latter explanation has decreased since the 1980’s

Real Asset Returns and Components of Inflation: A Structural VAR Analysis

We shed new light on the negative relationship between real stock returns or real interest rates and (i) post inflation, (ii) expected inflation, (iii) unexpected inflation and (iv) changes in expected inflation. Using the structural vector autoregression methodology, we propose a decomposition of those series into economically interpretable components driven by aggregate supply, real demand and money market shocks. Our empirical results support Fama’s ‘proxy hypothesis’ and the predictions of several general equilibrium models. Concerning the negative relation between the real rate of interest and inflation, we find that the Mundell-Tobin model and the explanation of Fama and Gibbons (1982) are not competitors: both add insight in their own way about the reasons for the negative correlation between those variables. However, the importance of the latter explanation decreased since the 1980’s.Real stock returns; Real rate of interest; Expected and unexpected inflation; 'Fisher hypothesis'; Structural VAR

Efficient Semiparametric Estimation of the Fama–French Model and Extensions

This paper develops a new estimation procedure for characteristic-based factor models of stock returns. We treat the factor model as a weighted additive nonparametric regression model, with the factor returns serving as time-varying weights and a set of univariate nonparametric functions relating security characteristic to the associated factor betas. We use a time-series and cross-sectional pooled weighted additive nonparametric regression methodology to simultaneously estimate the factor returns and characteristic-beta functions. By avoiding the curse of dimensionality, our methodology allows for a larger number of factors than existing semiparametric methods. We apply the technique to the three-factor Fama–French model, Carhart’s four-factor extension of it that adds a momentum factor, and a five-factor extension that adds an own-volatility factor. We find that momentum and own-volatility factors are at least as important, if not more important, than size and value in explaining equity return comovements. We test the multifactor beta pricing theory against a general alternative using a new nonparametric tes

Human TRIM5α mediated restriction of different HIV-1 subtypes and Lv2 sensitive and insensitive HIV-2 variants

In order to characterize the antiviral activity of human TRIM5α in more detail human derived indicator cell lines over expressing wild type human TRIM5α were generated and challenged with HIV-1 and HIV-2 viruses pseudotyped with HIV envelope proteins in comparison to VSV-G pseudotyped particles. HIV envelope protein pseudotyped particles (HIV-1[NL4.3], HIV-1[BaL]) showed a similar restriction to infection (12 fold inhibition) compared to VSV-G pseudotyped viruses after challenging TZM-huTRIM5α cells. For HIV-2 a stronger restriction to infection was observed when the homologous envelope protein Env42S was pseudotyped onto these particles compared to VSV-G pseudotyped HIV-2 particles (8.6 fold inhibition versus 3.4 fold inhibition). It has been shown that HIV-2 is restricted by the restriction factor Lv2, acting on capsid like TRIM5α. A mutation of amino acid 73 (I73V) of HIV-2 capsid renders this virus Lv2-insensitive. Lv2-insensitive VSV-G pseudotyped HIV-2/I73V particles showed a similar restriction to infection as did HIV-2[VSV-G] particles (4 fold inhibition). HIV-2 envelope protein (Env42S)-pseudotyped HIV-2/I73V particles revealed a 9.3 fold increase in infection in TZM cells but remained restricted in TZM-huTRIM5α cells (80.6 fold inhibition) clearly indicating that at least two restriction factors, TRIM5α and Lv2, act on incoming HIV-2 particles. Further challenge experiments using primary isolates from different HIV-1 subtypes and from HIV-1 group O showed that wild type human TRIM5α restricted infection independent of coreceptor use of the infecting particle but to variable degrees (between 1.2 and 19.6 fold restriction)

A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN)

Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool to investigate equivocal neurological patterns during fetal development. However, the number of acquisitions of satisfactory quality available in this cohort of sensitive subjects remains scarce, thus hindering the validation of advanced image processing techniques. Numerical phantoms can mitigate these limitations by providing a controlled environment with a known ground truth. In this work, we present FaBiAN, an open-source Fetal Brain magnetic resonance Acquisition Numerical phantom that simulates clinical T2-weighted fast spin echo sequences of the fetal brain. This unique tool is based on a general, flexible and realistic setup that includes stochastic fetal movements, thus providing images of the fetal brain throughout maturation comparable to clinical acquisitions. We demonstrate its value to evaluate the robustness and optimize the accuracy of an algorithm for super-resolution fetal brain magnetic resonance imaging from simulated motion-corrupted 2D low-resolution series compared to a synthetic high-resolution reference volume. We also show that the images generated can complement clinical datasets to support data-intensive deep learning methods for fetal brain tissue segmentation

Genetic Exchange of Multidrug Efflux Pumps among Two Enterobacterial Species with Distinctive Ecological Niches

AcrAB-TolC is the major multidrug efflux system in Enterobacteriaceae recognizing structurally unrelated molecules including antibiotics, dyes, and detergents. Additionally, in Escherichia coli it mediates resistance to bile salts. In the plant pathogen Erwinia amylovora AcrAB-TolC is required for virulence and phytoalexin resistance. Exchange analysis of AcrAB-TolC was conducted by complementing mutants of both species defective in acrB or tolC with alleles from either species. The acrB and tolC mutants exhibited increased susceptibility profiles for 24 different antibiotics. All mutants were complemented with acrAB or tolC, respectively, regardless of the taxonomic origin of the alleles. Importantly, complementation of E. amylovora mutants with respective E. coli genes restored virulence on apple plants. It was concluded that AcrAB and TolC of both species could interact and that these interactions did not yield in altered functions despite the divergent ecological niches, to which E. coli and E. amylovora have adopted