On The Origin Of The Gamma Rays From The Galactic Center

The region surrounding the center of the Milky Way is both astrophysically rich and complex, and is predicted to contain very high densities of dark matter. Utilizing three years of data from the Fermi Gamma Ray Space Telescope (and the recently available Pass 7 ultraclean event class), we study the morphology and spectrum of the gamma ray emission from this region and find evidence of a spatially extended component which peaks at energies between 300 MeV and 10 GeV. We compare our results to those reported by other groups and find good agreement. The extended emission could potentially originate from either the annihilations of dark matter particles in the inner galaxy, or from the collisions of high energy protons that are accelerated by the Milky Way's supermassive black hole with gas. If interpreted as dark matter annihilation products, the emission spectrum favors dark matter particles with a mass in the range of 7-12 GeV (if annihilating dominantly to leptons) or 25-45 GeV (if annihilating dominantly to hadronic final states). The intensity of the emission corresponds to a dark matter annihilation cross section consistent with that required to generate the observed cosmological abundance in the early universe (sigma v ~ 3 x 10^-26 cm^3/s). We also present conservative limits on the dark matter annihilation cross section which are at least as stringent as those derived from other observations.Comment: 13 pages, 11 figure

Frame-dragging effects on magnetic fields near a rotating black hole

We discuss the role of general relativity frame dragging acting on magnetic field lines near a rotating (Kerr) black hole. Near ergosphere the magnetic structure becomes strongly influenced and magnetic null points can develop. We consider aligned magnetic fields as well as fields inclined with respect to the rotation axis, and the two cases are shown to behave in profoundly different ways. Further, we construct surfaces of equal values of local electric and magnetic intensities, which have not yet been discussed in the full generality of a boosted rotating black hole.Comment: to appear in the proceedings of "The Central Kiloparsec in Galactic Nuclei (AHAR 2011)", Journal of Physics: Conference Series (JPCS), IOP Publishin

Comparative evaluation of synergy of combinations of \u3b2-lactams with fluoroquinolones or macrolides in Streptococcus pneumoniae

OBJECTIVES: Streptococcus pneumoniae has shown a great ability to develop efficacious mechanisms of resistance to the main drugs for the treatment of pneumonia, such as \u3b2-lactams, macrolides and fluoroquinolones. The present study aimed to compare the antipneumococcal activity of combinations of respiratory fluoroquinolones with cephalosporins (either parenteral or oral) or protected penicillin versus the standard combinations (i.e. a macrolide with a protected penicillin or cephalosporin) against 100 isolates with different susceptibilities to macrolides and/or penicillin. METHODS: Chequerboard assays for all isolates and time-kill curves for nine isolates with different patterns of susceptibility were performed. Synergy between antibiotics at serum peak concentrations was also determined. RESULTS: The combination of levofloxacin with ceftriaxone produced the highest rate of synergy (54/100), mainly against macrolide-resistant strains (22/30). Antagonism was not observed for any tested combination apart from clarithromycin with amoxicillin/clavulanic acid (22/100 isolates). Although the killing activities of all antibiotics improved when they were tested in combination, synergy was observed only for some combinations after 12 and/or 24 h. Serum concentrations were effective in inhibiting the growth of the tested strains. CONCLUSIONS: Combinations of levofloxacin with parenteral cephalosporins were the most active among all the tested combinations, while antagonism occurred when clarithromycin and amoxicillin/clavulanic acid were tested

Smart Climate Hydropower Tool: A Machine-Learning Seasonal Forecasting Climate Service to Support Cost–Benefit Analysis of Reservoir Management

This study proposes a climate service named Smart Climate Hydropower Tool (SCHT) and designed as a hybrid forecast system for supporting decision-making in a context of hydropower production. SCHT is technically designed to make use of information from state-of-art seasonal forecasts provided by the Copernicus Climate Data Store (CDS) combined with a range of different machine learning algorithms to perform the seasonal forecast of the accumulated inflow discharges to the reservoir of hydropower plants. The machine learning algorithms considered include support vector regression, Gaussian processes, long short-term memory, non-linear autoregressive neural networks with exogenous inputs, and a deep-learning neural networks model. Each machine learning model is trained over past decades datasets of recorded data, and forecast performances are validated and evaluated using separate test sets with reference to the historical average of discharge values and simpler multiparametric regressions. Final results are presented to the users through a user-friendly web interface developed from a tied connection with end-users in an effective co-design process. Methods are tested for forecasting the accumulated seasonal river discharges up to six months in advance for two catchments in Colombia, South America. Results indicate that the machine learning algorithms that make use of a complex and/or recurrent architecture can better simulate the temporal dynamic behaviour of the accumulated river discharge inflow to both case study reservoirs, thus rendering SCHT a useful tool in providing information for water resource managers in better planning the allocation of water resources for different users and for hydropower plant managers when negotiating power purchase contracts in competitive energy markets

Smart climate hydropower tool: A machine-learning seasonal forecasting climate service to support cost–benefit analysis of reservoir management

This study proposes a climate service named Smart Climate Hydropower Tool (SCHT) and designed as a hybrid forecast system for supporting decision-making in a context of hydropower production. SCHT is technically designed to make use of information from state-of-art seasonal forecasts provided by the Copernicus Climate Data Store (CDS) combined with a range of different machine learning algorithms to perform the seasonal forecast of the accumulated inflow discharges to the reservoir of hydropower plants. The machine learning algorithms considered include support vector regression, Gaussian processes, long short-term memory, non-linear autoregressive neural networks with exogenous inputs, and a deep-learning neural networks model. Each machine learning model is trained over past decades datasets of recorded data, and forecast performances are validated and evaluated using separate test sets with reference to the historical average of discharge values and simpler multiparametric regressions. Final results are presented to the users through a user-friendly web interface developed from a tied connection with end-users in an effective co-design process. Methods are tested for forecasting the accumulated seasonal river discharges up to six months in advance for two catchments in Colombia, South America. Results indicate that the machine learning algorithms that make use of a complex and/or recurrent architecture can better simulate the temporal dynamic behaviour of the accumulated river discharge inflow to both case study reservoirs, thus rendering SCHT a useful tool in providing information for water resource managers in better planning the allocation of water resources for different users and for hydropower plant managers when negotiating power purchase contracts in competitive energy markets

Similar glycaemic control and risk of hypoglycaemia with patient- versus physician-managed titration of insulin glargine 300 U/mL across subgroups of patients with T2DM: a post hoc analysis of ITAS

Aims: The Italian Titration Approach Study (ITAS) demonstrated comparable HbA1c reductions and similarly low hypoglycaemia risk at 6 months in poorly controlled, insulin-naïve adults with T2DM who initiated self- or physician-titrated insulin glargine 300 U/mL (Gla-300) in the absence of sulphonylurea/glinide. The association of patient characteristics with glycaemic and hypoglycaemic outcomes was assessed. Methods: This post hoc analysis investigated whether baseline patient characteristics and previous antihyperglycaemic drugs were associated with HbA1c change and hypoglycaemia risk in patient- versus physician-managed Gla-300 titration. Results: HbA1c change, incidence of hypoglycaemia (any type) and nocturnal rates were comparable between patient- and physician-managed arms in all subgroups. Hypoglycaemia rates across subgroups (0.03 to 3.52 events per patient-year) were generally as low as observed in the full ITAS population. Small increases in rates of 00:00–pre-breakfast and anytime hypoglycaemia were observed in the ≤ 10-year diabetes duration subgroup in the patient- versus physician-managed arm (heterogeneity of effect; p < 0.05). Conclusions: Comparably fair glycaemic control and similarly low hypoglycaemia risk were achieved in almost all patient subgroups with patient- versus physician-led Gla-300 titration. These results reinforce efficacy and safety of Gla-300 self-titration across a range of phenotypes of insulin-naïve people with T2DM. Clinical trial registration: EudraCT 2015-001167-3

Single Hole Green's Functions in Insulating Copper Oxides at Nonzero Temperature

We consider the single hole dynamics in a modified $t-J$ model at finite temperature. The modified model includes a next nearest ($t'$) and next-next nearest ($t''$) hopping. The model has been considered before in the zero temperature limit to explain angle resolved photo-emission measurements. We extend this consideration to the case of finite temperature where long-range anti-ferromagnetic order is destroyed, using the self-consistent Born approximation. The Dyson equation which relates the single hole Green's functions for a fixed pseudo-spin and for fixed spin is derived. The Green's function with fixed pseudo-spin is infrared stable but the Green's function with fixed spin is close to an infrared divergency. We demonstrate how to renormalize this Green's function in order to assure numerical convergence. At non-zero temperature the quasi-particle peaks are found to shift down in energy and to be broadened.Comment: 7 pages, RevTex, 5 Postscript figure

Whistler waves generated inside magnetic dips in the young solar wind: observations of the Search-Coil Magnetometer on board Parker Solar Probe

Context. Whistler waves are electromagnetic waves produced by electron-driven instabilities, that in turn can reshape the electron distributions via wave-particle interactions. In the solar wind, they are one of the main candidates for explaining the scattering of the strahl electron population into the halo at increasing radial distances from the Sun and for subsequently regulating the solar wind heat flux. However, it is unclear what type of instability dominates to drive whistlers in the solar wind. Aims. Our goal is to study whistler wave parameters in the young solar wind sampled by Parker Solar Probe (PSP). The wave normal angle (WNA) in particular is a key parameter to discriminate between the generation mechanisms of these waves. Methods. We analyze the cross-spectral matrices of magnetic fieldfluctuations measured by the Search-Coil Magnetometer (SCM) and processed by the Digital Fields Board (DFB) from the FIELDS suite during PSP's first perihelion. Results. Among the 2701 wave packets detected in the cross spectra, namely individual bins in time and frequency, most were quasi-parallel to the background magnetic field but a significant part (3%) of observed waves had oblique (> 45{\deg}) WNA. The validation analysis conducted with the time-series waveforms reveal that this percentage is a lower limit. Moreover, we find that about 64% of the whistler waves detected in the spectra are associated with at least one magnetic dip. Conclusions. We conclude that magnetic dips provides favorable conditions for the generation of whistler waves. We hypothesize that the whistlers detected in magnetic dips are locally generated by the thermal anisotropy as quasi-parallel and can gain obliqueness during their propagation. We finally discuss the implication of our results for the scattering of the strahl in the solar wind.Comment: 15 pages, 14 figures, recommended for publication in A&