On trend extraction models: Interpretation,empirical evidence and forecasting performance

This paper deals with the economic interpretation of the unobserved components model in the light of the apparent problem posed by previous work in that several practiced methodologies seem to lead to very different models of certain economic variables. A detailed empirical analysis is carried out to show how the failure in obtaining quasi-orthogonal components can seriously bias the interpretation of some decomposition procedures. Finally, the forecasting performance (in both the short and long run) of these decomposition models is analyzed in comparison with other alternatives.     

Range Extension and Channel Capacity Increase in Impulse-Radio Ultra-Wideband Communications

We theoretically analyze the channel capacity of a 5th-order Gaussian pulse-based ultra-wideband (UWB) system and experimentally demonstrate 2 Gbit/s UWB-over-fiber transmission systems incorporating wireless transmission. Both electrical and photonic UWB pulse generation methods are employed and its performance is compared. By utilizing optimum UWB pulse design and employing a digital signal processing (DSP) receiver, a bit-error-rate above the forward error correction (FEC) limit for 8 meters of wireless ...     

Pathogen-induced human TH17 cells produce IFN-γ or IL-10 and are regulated by IL-1β

IL-17-producing CD4+ T helper cells (TH17) have been extensively investigated in mouse models of autoimmunity. However, the requirements for differentiation and the properties of pathogen-induced human TH17 cells remain poorly defined. Using an approach that combines the in vitro priming of naive T cells with the ex vivo analysis of memory T cells, we describe here two types of human TH17 cells with distinct effector function and differentiation requirements. Candida albicans-specific TH17 cells produced IL-17 and IFN-γ, but no IL-10, whereas Staphylococcus aureus-specific TH17 cells produced IL-17 and could produce IL-10 upon restimulation. IL-6, IL-23 and IL-1β contributed to TH17 differentiation induced by both pathogens, but IL-1β was essential in C. albicans-induced TH17 differentiation to counteract the inhibitory activity of IL-12 and to prime IL-17/IFN-γ double-producing cells. In addition, IL-1β inhibited IL-10 production in differentiating and in memory TH17 cells, whereas blockade of IL-1β in vivo led to increased IL-10 production by memory TH17 cells. We also show that, after restimulation, TH17 cells transiently downregulated IL-17 production through a mechanism that involved IL-2-induced activation of STAT5 and decreased expression of ROR-γt. Taken together these findings demonstrate that by eliciting different cytokines C. albicans and S. aureus prime TH17 cells that produce either IFN-γ or IL-10, and identify IL-1β and IL-2 as pro- and anti-inflammatory regulators of TH17 cells both at priming and in the effector phase.     

The Drosophila melanogaster Genetic Reference Panel

A major challenge of biology is understanding the relationship between molecular genetic variation and variation in quantitative traits, including fitness. This relationship determines our ability to predict phenotypes from genotypes and to understand how evolutionary forces shape variation within and between species. Previous efforts to dissect the genotype-phenotype map were based on incomplete genotypic information. Here, we describe the Drosophila melanogaster Genetic Reference Panel (DGRP), a community resource for analysis of population genomics and quantitative traits. The DGRP consists of fully sequenced inbred lines derived from a natural population. Population genomic analyses reveal reduced polymorphism in centromeric autosomal regions and the X chromosome, evidence for positive and negative selection, and rapid evolution of the X chromosome. Many variants in novel genes, most at low frequency, are associated with quantitative traits and explain a large fraction of the phenotypic variance. The DGRP facilitates genotype-phenotype mapping using the power of Drosophila genetics.