Gauge dilution and leptogenesis

In this paper, we examine how gauge interactions can dilute the lepton asymmetry in lepton induced baryogenesis. Constraints imposed on Majorana masses keep this dilution at an acceptable level.Comment: 5 page

Comparative genomics of Burkholderia multivorans, a ubiquitous pathogen with a highly conserved genomic structure

The natural environment serves as a reservoir of opportunistic pathogens. A well-established method for studying the epidemiology of such opportunists is multilocus sequence typing, which in many cases has defined strains predisposed to causing infection. Burkholderia multivorans is an important pathogen in people with cystic fibrosis (CF) and its epidemiology suggests that strains are acquired from non-human sources such as the natural environment. This raises the central question of whether the isolation source (CF or environment) or the multilocus sequence type (ST) of B. multivorans better predicts their genomic content and functionality. We identified four pairs of B. multivorans isolates, representing distinct STs and consisting of one CF and one environmental isolate each. All genomes were sequenced using the PacBio SMRT sequencing technology, which resulted in eight high-quality B. multivorans genome assemblies. The present study demonstrated that the genomic structure of the examined B. multivorans STs is highly conserved and that the B. multivorans genomic lineages are defined by their ST. Orthologous protein families were not uniformly distributed among chromosomes, with core orthologs being enriched on the primary chromosome and ST-specific orthologs being enriched on the second and third chromosome. The ST-specific orthologs were enriched in genes involved in defense mechanisms and secondary metabolism, corroborating the strain-specificity of these virulence characteristics. Finally, the same B. multivorans genomic lineages occur in both CF and environmental samples and on different continents, demonstrating their ubiquity and evolutionary persistence

How mineralogy and geochemistry can improve the significance of Pb isotopes in metal provenance studies

Lead isotopes combined with trace element data represent a powerful tool for non-ferrous metal provenance studies. Nevertheless, unconsidered geological factors and archaeological data, as well as ignored analytical procedures, may substantially modify the interpretation of the isotopic and trace element signature obtained as a potential ore candidate. Three archaeological examples, accompanied by high-resolution lead isotopic measurements (MC–ICP–MS), are presented here to discuss the above-mentioned criticisms and to propose some solutions. The first example deals with prehistoric/historical gold/silver-mining activity from Romania (the Baia Borşa and Roşia Montană ore deposits). The second one regards the lead/silver metallurgical activity from the Mont-Lozère massif (France) during medieval times. The third example focuses on the comparison between two batches of lead isotope data gathered on Roman lead ingots from Saintes-Maries-de-la-Mer, using different SRM 981 Pb values

Force generation of curved actin gels characterized by combined AFM-epifluorescence measurements

Polymerization of actin into branched filaments is the driving force behind active migration of eukaryotic cells and motility of intracellular organelles. The site-directed assembly of a polarized branched array forms an expanding gel that generates the force that pushes the membrane. Here, we use atomic force microscopy to understand the relation between actin polymerization and the produced force. Functionalized spherical colloidal probes of varying size and curvature are attached to the atomic force microscopy cantilever and initiate the formation of a polarized actin gel in a solution mimicking the in vivo context. The gel growth is recorded by epifluorescence microscopy both against the cantilever and in the perpendicular (lateral) nonconstrained direction. In this configuration, the gel growth stops simultaneously in both directions at the stall force, which corresponds to a pressure of 0.15 nN/μm(2). The results show that the growth of the gel is limited laterally, in the absence of external force, by internal mechanical stresses resulting from a combination of the curved geometry and the molecular mechanism of site-directed assembly of a cohesive branched filament array

Long-Distance Wind-Dispersal of Spores in a Fungal Plant Pathogen: Estimation of Anisotropic Dispersal Kernels from an Extensive Field Experiment

Given its biological significance, determining the dispersal kernel (i.e., the distribution of dispersal distances) of spore-producing pathogens is essential. Here, we report two field experiments designed to measure disease gradients caused by sexually- and asexually-produced spores of the wind-dispersed banana plant fungus Mycosphaerella fijiensis. Gradients were measured during a single generation and over 272 traps installed up to 1000 m along eight directions radiating from a traceable source of inoculum composed of fungicide-resistant strains. We adjusted several kernels differing in the shape of their tail and tested for two types of anisotropy. Contrasting dispersal kernels were observed between the two types of spores. For sexual spores (ascospores), we characterized both a steep gradient in the first few metres in all directions and rare long-distance dispersal (LDD) events up to 1000 m from the source in two directions. A heavy-tailed kernel best fitted the disease gradient. Although ascospores distributed evenly in all directions, average dispersal distance was greater in two different directions without obvious correlation with wind patterns. For asexual spores (conidia), few dispersal events occurred outside of the source plot. A gradient up to 12.5 m from the source was observed in one direction only. Accordingly, a thin-tailed kernel best fitted the disease gradient, and anisotropy in both density and distance was correlated with averaged daily wind gust. We discuss the validity of our results as well as their implications in terms of disease diffusion and management strategy

Non-local interactions in hydrodynamic turbulence at high Reynolds numbers: the slow emergence of scaling laws

We analyze the data stemming from a forced incompressible hydrodynamic simulation on a grid of 2048^3 regularly spaced points, with a Taylor Reynolds number of Re~1300. The forcing is given by the Taylor-Green flow, which shares similarities with the flow in several laboratory experiments, and the computation is run for ten turnover times in the turbulent steady state. At this Reynolds number the anisotropic large scale flow pattern, the inertial range, the bottleneck, and the dissipative range are clearly visible, thus providing a good test case for the study of turbulence as it appears in nature. Triadic interactions, the locality of energy fluxes, and structure functions of the velocity increments are computed. A comparison with runs at lower Reynolds numbers is performed, and shows the emergence of scaling laws for the relative amplitude of local and non-local interactions in spectral space. The scalings of the Kolmogorov constant, and of skewness and flatness of velocity increments, performed as well and are consistent with previous experimental results. Furthermore, the accumulation of energy in the small-scales associated with the bottleneck seems to occur on a span of wavenumbers that is independent of the Reynolds number, possibly ruling out an inertial range explanation for it. Finally, intermittency exponents seem to depart from standard models at high Re, leaving the interpretation of intermittency an open problem.Comment: 8 pages, 8 figure

Leptogenesis, neutrino masses and gauge unification

Leptogenesis is considered in its natural context where Majorana neutrinos fit in a gauge unification scheme and therefore couple to some extra gauge bosons. The masses of some of these gauge bosons are expected to be similar to those of the heavy Majorana particles, and this can have important consequences for leptogenesis. In fact, the effect can go both ways. Stricter bounds are obtained on one hand due to the dilution of the CP-violating effect by new decay and scattering channels, while, in a re-heating scheme, the presence of gauge couplings facilitates the re-population of the Majorana states. The latter effect allows in particular for smaller Dirac couplings.Comment: 11pages, 7 figures. v2: definition of the lepton asymmetry corrected, small numerical changes for the baryon number, conclusion does not change; typos corrected and references adde

The opportunities of two-phase hybrid stepping motor back EMF sampling

By counting the step command pulses, stepping motors can be straightforwardly used for open loop positioning. However, open-loop control is often insufficient to guarantee accurate and energy efficient movements. More intelligent stepping motor algorithms can meet these concerns, however, this requires position information. The back EMF signal contains useful information on the rotor position. This information can be used to monitor the motor condition and to implement a more advanced position control algorithm. A theoretical analysis gives insight into the back EMF generated in a two-phase hybrid stepping motor. In this paper a, by the authors, patented sampling method is considered to measure the back EMF signal. The opportunities of this method are considered theoretically. Moreover this paper presents extensive measurement results proving the opportunities of the method, to develop more intelligent stepping motor algorithms

How Not To Drown in Data:A Guide for Biomaterial Engineers

High-throughput assays that produce hundreds of measurements per sample are powerful tools for quantifying cell–material interactions. With advances in automation and miniaturization in material fabrication, hundreds of biomaterial samples can be rapidly produced, which can then be characterized using these assays. However, the resulting deluge of data can be overwhelming. To the rescue are computational methods that are well suited to these problems. Machine learning techniques provide a vast array of tools to make predictions about cell–material interactions and to find patterns in cellular responses. Computational simulations allow researchers to pose and test hypotheses and perform experiments in silico. This review describes approaches from these two domains that can be brought to bear on the problem of analyzing biomaterial screening data