τ−→π−π0ντ\tau^{-} \to \pi^{-} \pi^{0} \nu_\tau decay in the extended NJL model

The width of the decay $\tau^{-} \to \pi^{-} \pi^{0} \nu_\tau$ was calculated in the extended NJL model. Contact interaction of $W$ boson with pion pair as well as the contribution of the $\rho$ mesons in ground and first radial-exited states are taken into account. The sum of the contact diagram and diagram with intermediate $\rho$ meson in the ground state leads to the result which coincides with the result of the vector-dominance model. Our results are in satisfactory agreement with experimental data.Comment: 5 pages, 3 figures, 1 tabl

Net ecosystem fluxes of isoprene over tropical South America inferred from Global Ozone Monitoring Experiment (GOME) observations of HCHO columns

We estimate isoprene emissions over tropical South America during 1997-2001 using column measurements of formaldehyde (HCHO) from the Global Ozone Monitoring Experiment (GOME) satellite instrument, the GEOS-Chem chemistry transport model, and the MEGAN (Model of Emissions of Gases and Aerosols from Nature) bottom-up isoprene inventory. GEOS-Chem is qualitatively consistent with in situ ground-based and aircraft concentration profiles of isoprene and HCHO, and GOME HCHO column data (r = 0.41; bias = +35%), but has less skill in reproducing wet season observations. Observed variability of GOME HCHO columns over South America is determined largely by isoprene and biomass burning. We find that the column contributions from other biogenic volatile organic compounds (VOC) are typically smaller than the column fitting uncertainty. HCHO columns influenced by biomass burning are removed using Along Track Scanning Radiometer (ATSR) firecounts and GOME NO2 columns. We find that South America can be split into eastern and western regions, with fires concentrated over the eastern region. A monthly mean linear transfer function, determined by GEOS-Chem, is used to infer isoprene emissions from observed HCHO columns. The seasonal variation of GOME isoprene emissions over the western region is broadly consistent with MEGAN (r = 0.41; bias = -256%), with largest isoprene emissions during the dry season when the observed variability is consistent with knowledge of temperature dependence. During the wet season other unknown factors play a significant role in determining observed variability. Copyright 2008 by the American Geophysical Union

Fast Distributed Approximation for Max-Cut

Finding a maximum cut is a fundamental task in many computational settings. Surprisingly, it has been insufficiently studied in the classic distributed settings, where vertices communicate by synchronously sending messages to their neighbors according to the underlying graph, known as the $\mathcal{LOCAL}$ or $\mathcal{CONGEST}$ models. We amend this by obtaining almost optimal algorithms for Max-Cut on a wide class of graphs in these models. In particular, for any $\epsilon > 0$, we develop randomized approximation algorithms achieving a ratio of $(1-\epsilon)$ to the optimum for Max-Cut on bipartite graphs in the $\mathcal{CONGEST}$ model, and on general graphs in the $\mathcal{LOCAL}$ model. We further present efficient deterministic algorithms, including a $1/3$-approximation for Max-Dicut in our models, thus improving the best known (randomized) ratio of $1/4$. Our algorithms make non-trivial use of the greedy approach of Buchbinder et al. (SIAM Journal on Computing, 2015) for maximizing an unconstrained (non-monotone) submodular function, which may be of independent interest

High-spectral-resolution Fabry-Perot interferometers overcome fundamental limitations of present volcanic gas remote sensing techniques

Remote sensing (RS) of volcanic gases has become a central tool for studying volcanic activity. For instance, ultraviolet (UV) skylight spectroscopy with grating spectrographs (GS) enables SO2 (and, under favourable conditions, BrO) quantification in volcanic plumes from autonomous platforms at safe distances. These measurements can serve volcanic monitoring and they cover all stages of volcanic activity in long measurement time series, which substantially contributes to the refinement of theories on volcanic degassing. Infrared (IR) remote sensing techniques are able to measure further volcanic gases (e.g., HF, HCl, CO2, CO). However, the employed Fourier transform spectrometers (FTSs) are intrinsically intricate and, due to limited resolving power or light throughput, mostly rely on either lamps, direct sun, or hot lava as light source, usually limiting measurements to individual field campaigns. We show that many limitations of grating spectrographs and Fourier transform spectrometer measurements can be overcome by Fabry-Perot interferometer (FPI) based spectrograph implementations. Compared to grating spectrographs and Fourier transform spectrometers, Fabry-Perot interferometer spectrographs reach a 1-3 orders of magnitude higher spectral resolution and superior light throughput with compact and stable set-ups. This leads to 1) enhanced sensitivity and selectivity of the spectral trace gas detection, 2) enables the measurement of so far undetected volcanic plume constituents [e.g., hydroxyl (OH) or sulfanyl (SH)], and 3) extends the range of gases that can be measured continuously using the sky as light source. Here, we present measurements with a shoe-box-size Fabry-Perot interferometer spectrograph (resolving power of ca. 150000), performed in the crater of Nyiragongo volcano. By analysing the light of a ultraviolet light emitting diode that is sent through the hot gas emission of an active lava flow, we reach an OH detection limit of about 20 ppb, which is orders of magnitude lower than the mixing ratios predicted by high-temperature chemical models. Furthermore, we introduce example calculations that demonstrate the feasibility of skylight-based remote sensing of HF and HCl in the short-wave infrared with Fabry-Perot interferometer spectrographs, which opens the path to continuous monitoring and data acquisition during all stages of volcanic activity. This is only one among many further potential applications of remote sensing of volcanic gases with high spectral resolution

Report of the QCD Working Group

The activities of the QCD working group concentrated on improving the understanding and Monte Carlo simulation of multi-jet final states due to hard QCD processes at LEP, i.e. quark-antiquark plus multi-gluon and/or secondary quark production, with particular emphasis on four-jet final states and b-quark mass effects. Specific topics covered are: relevant developments in the main event generators PYTHIA, HERWIG and ARIADNE; the new multi-jet generator APACIC++; description and tuning of inclusive (all-flavour) jet rates; quark mass effects in the three- and four-jet rates; mass, higher-order and hadronization effects in four-jet angular and shape distributions; b-quark fragmentation and gluon splitting into b-quarks.Comment: 95 pages, 48 figures, contribution to Proceedings of the LEP2 Monte Carlo Workshop. References for NLO 4-jet matrix elements adde

Excited Leptons at the CERN Large Hadron Collider

We analyze the potential of the CERN Large Hadron Collider (LHC) to search for excited spin-1/2 electrons and neutrinos. Assuming a SU(2)_L X U(1)_Y invariant model, we study in detail the single production of excited electrons and neutrinos and respective backgrounds through the reactions p p -> e+ e- V and e+- \nu V with V=photon, W, or Z. We show that the LHC will be able to tighten considerably the direct constraints on these possible new states, probing excited lepton masses up to 1-2 TeV depending on their couplings to fermions and gauge bosons.Comment: 15 pages, 7 figure

converging evidence from an intermediate phenotype approach

Representing a phylogenetically old and very basic mechanism of inhibitory neurotransmission, glycine receptors have been implicated in the modulation of behavioral components underlying defensive responding toward threat. As one of the first findings being confirmed by genome-wide association studies for the phenotype of panic disorder and agoraphobia, allelic variation in a gene coding for the glycine receptor beta subunit (GLRB) has recently been associated with increased neural fear network activation and enhanced acoustic startle reflexes. On the basis of two independent healthy control samples, we here aimed to further explore the functional significance of the GLRB genotype (rs7688285) by employing an intermediate phenotype approach. We focused on the phenotype of defensive system reactivity across the levels of brain function, structure, and physiology. Converging evidence across both samples was found for increased neurofunctional activation in the (anterior) insular cortex in GLRB risk allele carriers and altered fear conditioning as a function of genotype. The robustness of GLRB effects is demonstrated by consistent findings across different experimental fear conditioning paradigms and recording sites. Altogether, findings provide translational evidence for glycine neurotransmission as a modulator of the brain’s evolutionary old dynamic defensive system and provide further support for a strong, biologically plausible candidate intermediate phenotype of defensive reactivity. As such, glycine-dependent neurotransmission may open up new avenues for mechanistic research on the etiopathogenesis of fear and anxiety disorders

Estimations of isoprenoid emission capacity from enclosure studies: measurements, data processing, quality and standardized measurement protocols

The capacity for volatile isoprenoid production under standardized environmental conditions at a certain time (ES, the emission factor) is a key characteristic in constructing isoprenoid emission inventories. However, there is large variation in published ES estimates for any given species partly driven by dynamic modifications in ES due to acclimation and stress responses. Here we review additional sources of variation in ES estimates that are due to measurement and analytical techniques and calculation and averaging procedures, and demonstrate that estimations of ES critically depend on applied experimental protocols and on data processing and reporting. A great variety of experimental setups has been used in the past, contributing to study-to-study variations in ES estimates. We suggest that past experimental data should be distributed into broad quality classes depending on whether the data can or cannot be considered quantitative based on rigorous experimental standards. Apart from analytical issues, the accuracy of ES values is strongly driven by extrapolation and integration errors introduced during data processing. Additional sources of error, especially in meta-database construction, can further arise from inconsistent use of units and expression bases of ES. We propose a standardized experimental protocol for BVOC estimations and highlight basic meta-information that we strongly recommend to report with any ES measurement. We conclude that standardization of experimental and calculation protocols and critical examination of past reports is essential for development of accurate emission factor databases.JRC.H.7-Climate Risk Managemen