A Renormalization Group Improved Calculation of Top Quark Production near Threshold

The top quark cross section close to threshold in $e^+e^-$ annihilation is computed including the summation of logarithms of the velocity at next-to-next-to-leading-logarithmic order in QCD. The remaining theoretical uncertainty in the normalization of the total cross section is at the few percent level, an order of magnitude smaller than in previous next-to-next-to-leading order calculations. This uncertainty is smaller than the effects of a light standard model Higgs boson.Comment: changed figures, added reference

Relativistic Doppler effect: universal spectra and zeptosecond pulses

We report on a numerical observation of the train of zeptosecond pulses produced by reflection of a relativistically intense femtosecond laser pulse from the oscillating boundary of an overdense plasma because of the Doppler effect. These pulses promise to become a unique experimental and technological tool since their length is of the order of the Bohr radius and the intensity is extremely high $\propto 10^{19}$ W/cm$^2$. We present the physical mechanism, analytical theory, and direct particle-in-cell simulations. We show that the harmonic spectrum is universal: the intensity of $n$th harmonic scales as $1/n^{p}$ for $n < 4\gamma^2$, where $\gamma$ is the largest $\gamma$--factor of the electron fluid boundary, $p=3$ and $p=5/2$ for the broadband and quasimonochromatic laser pulses respectively.Comment: 4 figure

Evaluation of the ESBL-coding plasmids transmissibility in E. coli isolated from ambulatory patient's urina

Representatives of the Enterobacteriaceae family are the main causative agents of urinary tract infections. Escherichia coli can exhibit resistance to [beta] -lactam antibiotics by synthesizing ESBL (extended spectrum [beta]-lactamases). CTX-M [beta] -lactamases are the dominant group of ESBL. In this paper, we investigated the ability of E. coli urinary isolates to transmit resistance genes within the plasmid. An analysis of the effectiveness of conjugation has shown that E. coli strains producing ESBL are capable of transferring resistance genes to a recipient bacterium at a high frequency

Hadronic light-by-light scattering contribution to the muon g-2

We review recent developments concerning the hadronic light-by-light scattering contribution to the anomalous magnetic moment of the muon. We first discuss why fully off-shell hadronic form factors should be used for the evaluation of this contribution to the g-2. We then reevaluate the numerically dominant pion-exchange contribution in the framework of large-N_C QCD, using an off-shell pion-photon-photon form factor which fulfills all QCD short-distance constraints, in particular, a new short-distance constraint on the off-shell form factor at the external vertex in g-2, which relates the form factor to the quark condensate magnetic susceptibility in QCD. Combined with available evaluations of the other contributions to hadronic light-by-light scattering this leads to the new result a_{\mu}(LbyL; had) = (116 \pm 40) x 10^{-11}, with a conservative error estimate in view of the many still unsolved problems. Some potential ways for further improvements are briefly discussed as well. For the electron we obtain the new estimate a_{e}(LbyL; had) = (3.9 \pm 1.3) x 10^{-14}.Comment: 6 pages, 1 figure, to be published in the proceedings of the PhiPsi09 workshop, Oct. 13-16, 2009, Beijing, Chin

Light dark forces at flavor factories

SuperB experiment could represent an ideal environment to test a new U (1) symmetry related to light dark forces candidates. A promising discovery channel is represented by the resonant production of a boson U, followed by its decay into lepton pairs. Beyond approximations adopted in the literature, an exact tree level calculation of the radiative processes $e+ e- \rightarrow \gamma, U \rightarrow \mu^+ \mu^- \gamma, e^+ e^- \gamma$ and corresponding QED backgrounds is performed, including also the most important higher-order corrections. The calculation is implemented in a release of the generator BabaYaga@NLO useful for data analysis and interpretation. The distinct features of U boson production are shown and the statistical significance is analysed

Recent global and regional trends in burned area and their compensating environmental controls

The apparent decline in the global incidence of fire between 1996 and 2015, as measured by satellite- observations of burned area, has been related to socioeconomic and land use changes. However, recent decades have also seen changes in climate and vegetation that influence fire and fire-enabled vegetation models do not reproduce the apparent decline. Given that the satellite-derived burned area datasets are still relatively short (<20 years), this raises questions both about the robustness of the apparent decline and what causes it. We use two global satellite-derived burned area datasets and a data-driven fire model to (1) assess the spatio-temporal robustness of the burned area trends and (2) to relate the trends to underlying changes in temperature, precipitation, human population density and vegetation conditions. Although the satellite datasets and simulation all show a decline in global burned area over ~20 years, the trend is not significant and is strongly affected by the start and end year chosen for trend analysis and the year-to-year variability in burned area. The global and regional trends shown by the two satellite datasets are poorly correlated for the common overlapping period (2001–2015) and the fire model simulates changes in global and regional burned area that lie within the uncertainties of the satellite datasets. The model simulations show that recent increases in temperature would lead to increased burned area but this effect is compensated by increasing wetness or increases in population, both of which lead to declining burned area. Increases in vegetation cover and density associated with recent greening trends lead to increased burned area in fuel-limited regions. Our analyses show that global and regional burned area trends result from the interaction of compensating trends in controls of wildfire at regional scales

Molecular diet analysis in mussels and other metazoan filter feeders and an assessment of their utility as natural eDNA samplers

Molecular gut content analysis is a popular tool to study food web interactions and has recently been suggested as an alternative source for DNA-based biomonitoring. However, the overabundant consumer's DNA often outcompetes that of its diet during PCR. Lineage-specific primers are an efficient means to reduce consumer amplification while retaining broad specificity for dietary taxa. Here, we designed an amplicon sequencing assay to monitor the eukaryotic diet of mussels and other metazoan filter feeders and explore the utility of mussels as natural eDNA samplers to monitor planktonic communities. We designed several lineage-specific rDNA primers with broad taxonomic suitability for eukaryotes. The primers were tested using DNA extracts of different limnic and marine mussel species and the results compared to eDNA water samples collected next to the mussel colonies. In addition, we analysed several 25-year time series samples of mussels from German rivers. Our primer sets efficiently prevent the amplification of mussels and other metazoans. The recovered DNA reflects a broad dietary preference across the eukaryotic tree of life and considerable taxonomic overlap with filtered water samples. We also show the utility of a reversed version of our primers, which prevents amplification of nonmetazoan taxa from complex eukaryote community samples, by enriching fauna associated with the marine brown algae Fucus vesiculosus. Our protocol will enable large-scale dietary analysis in metazoan filter feeders, facilitate aquatic food web analysis and allow surveying of aquacultures for pathogens. Moreover, we show that mussels and other aquatic filter feeders can serve as complementary DNA source for biomonitoring

Transport properties of heterogeneous materials derived from Gaussian random fields: Bounds and Simulation

We investigate the effective conductivity ($\sigma_e$) of a class of amorphous media defined by the level-cut of a Gaussian random field. The three point solid-solid correlation function is derived and utilised in the evaluation of the Beran-Milton bounds. Simulations are used to calculate $\sigma_e$ for a variety of fields and volume fractions at several different conductivity contrasts. Relatively large differences in $\sigma_e$ are observed between the Gaussian media and the identical overlapping sphere model used previously as a `model' amorphous medium. In contrast $\sigma_e$ shows little variability between different Gaussian media.Comment: 15 pages, 14 figure

A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)

Vegetation fires affect human infrastructures, ecosystems, global vegetation distribution, and atmospheric composition. However, the climatic, environmental, and socioeconomic factors that control global fire activity in vegetation are only poorly understood, and in various complexities and formulations are represented in global process-oriented vegetation-fire models. Data-driven model approaches such as machine learning algorithms have successfully been used to identify and better understand controlling factors for fire activity. However, such machine learning models cannot be easily adapted or even implemented within process-oriented global vegetation-fire models. To overcome this gap between machine learning-based approaches and process-oriented global fire models, we introduce a new flexible data-driven fire modelling approach here (Satellite Observations to predict FIre Activity, SOFIA approach version 1). SOFIA models can use several predictor variables and functional relationships to estimate burned area that can be easily adapted with more complex process-oriented vegetation-fire models. We created an ensemble of SOFIA models to test the importance of several predictor variables. SOFIA models result in the highest performance in predicting burned area if they account for a direct restriction of fire activity under wet conditions and if they include a land cover-dependent restriction or allowance of fire activity by vegetation density and biomass. The use of vegetation optical depth data from microwave satellite observations, a proxy for vegetation biomass and water content, reaches higher model performance than commonly used vegetation variables from optical sensors. We further analyse spatial patterns of the sensitivity between anthropogenic, climate, and vegetation predictor variables and burned area. We finally discuss how multiple observational datasets on climate, hydrological, vegetation, and socioeconomic variables together with data-driven modelling and model–data integration approaches can guide the future development of global process-oriented vegetation-fire models