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Galactic cosmic rays reach energies of at least a few petaelectronvolts (of the order of 1015 electronvolts). This implies that our Galaxy contains petaelectronvolt accelerators (‘PeVatrons’), but all proposed models of Galactic cosmic-ray accelerators encounter difficulties at exactly these energies. Dozens of Galactic accelerators capable of accelerating particles to energies of tens of teraelectronvolts (of the order of 1013 electronvolts) were inferred from recent γ-ray observations3. However, none of the currently known accelerators—not even the handful of shell-type supernova remnants commonly believed to supply most Galactic cosmic rays—has shown the characteristic tracers of petaelectronvolt particles, namely, power-law spectra of γ-rays extending without a cut-off or a spectral break to tens of teraelectronvolts4. Here we report deep γ-ray observations with arcminute angular resolution of the region surrounding the Galactic Centre, which show the expected tracer of the presence of petaelectronvolt protons within the central 10 parsecs of the Galaxy. We propose that the supermassive black hole Sagittarius A* is linked to this PeVatron. Sagittarius A* went through active phases in the past, as demonstrated by X-ray outbursts5and an outflow from the Galactic Centre6. Although its current rate of particle acceleration is not sufficient to provide a substantial contribution to Galactic cosmic rays, Sagittarius A* could have plausibly been more active over the last 106–107 years, and therefore should be considered as a viable alternative to supernova remnants as a source of petaelectronvolt Galactic cosmic rays.
A search for dark matter linelike signals iss performed in the vicinity of the Galactic Center by the H.E.S.S. experiment on observational data taken in 2014. An unbinned likelihood analysis iss developed to improve the sensitivity to linelike signals. The upgraded analysis along with newer data extend the energy coverage of the previous measurement down to 100 GeV. The 18 h of data collected with the H.E.S.S. array allow one to rule out at 95% C.L. the presence of a 130 GeV line (at l = -1.5 degrees, b = 0 degrees and for a dark matter profile centered at this location) previously reported in Fermi-LAT data. This new analysis overlaps significantly in energy with previous Fermi-LAT and H.E.S.S. results. No significant excess associated with dark matter annihilations was found in the energy range of 100 GeV to 2 TeV and upper limits on the gamma-ray flux and the velocity weighted annihilation cross section are derived adopting an Einasto dark matter halo profile. Expected limits for present and future large statistics H.E.S.S. observations are also given.
The inner region of the Milky Way halo harbors a large amount of dark matter (DM). Given its proximity, it is one of the most promising targets to look for DM. We report on a search for the annihilations of DM particles using gamma-ray observations towards the inner 300 pc of the Milky Way, with the H.E.S.S. array of ground-based Cherenkov telescopes. The analysis is based on a 2D maximum likelihood method using Galactic Center (GC) data accumulated by H.E.S.S. over the last 10 years (2004-2014), and does not show any significant gamma-ray signal above background. Assuming Einasto and Navarro-Frenk-White DM density profiles at the GC, we derive upper limits on the annihilation cross section <sigma nu >. These constraints are the strongest obtained so far in the TeV DM mass range and improve upon previous limits by a factor 5. For the Einasto profile, the constraints reach <sigma nu > values of 6 x 10(-26) cm(3) s(-1) in the W+W- channel for a DM particle mass of 1.5 TeV, and 2 x 10(-26) cm(3) s(-1) in the tau(+)tau(-) channel for a 1 TeV mass. For the first time, ground-based gamma-ray observations have reached sufficient sensitivity to probe <sigma nu > values expected from the thermal relic density for TeV DM particles.
Mental disorders are among the greatest medical and social challenges facing us. They can occur at all stages of life and are among the most important commonly occurring diseases. In Germany 28 % of the population suffer from a mental disorder every year, while the lifetime risk of suffering from a mental disorder is almost 50 %. Mental disorders cause great suffering for those affected and their social network. Quantitatively speaking, they can be considered to be among those diseases creating the greatest burden for society due to reduced productivity, absence from work and premature retirement. The Federal Ministry of Education and Research is funding a new research network from 2015 to 2019 with up to 35 million euros to investigate mental disorders in order to devise and develop better therapeutic measures and strategies for this population by means of basic and translational clinical research. This is the result of a competitive call for research proposals entitled research network for mental diseases. It is a nationwide network of nine consortia with up to ten psychiatric and clinical psychology partner institutions from largely university-based research facilities for adults and/or children and adolescents. Furthermore, three cross-consortia platform projects will seek to identify shared causes of diseases and new diagnostic modalities for anxiety disorders, attention deficit hyperactivity disorders (ADHS), autism, bipolar disorders, depression, schizophrenia and psychotic disorders as well as substance-related and addictive disorders. The spectrum of therapeutic approaches to be examined ranges from innovative pharmacological and psychotherapeutic treatment to novel brain stimulation procedures. In light of the enormous burden such diseases represent for society as a whole, a sustainable improvement in the financial support for those researching mental disorders seems essential. This network aims to become a nucleus for long overdue and sustained support for a German center for mental disorders.
Teacher judgments in terms of grades, proficiency assessments, and recommending placement in ability groups can have important consequences for a child’s future educational path. Whether or not students’ sociodemographic background characteristics are systematically related to teacher judgments has been a controversial topic of discussion. Using data from the TIMSS-Transition Study (N = 3285 fourth graders) administered across 13 German federal states in the 2006–2007 school year and survey data from parents and teachers, we investigated whether or not the average classroom socioeconomic status is reflected in teacher judgments and also examined possible underlying processes. We also probed the role of teachers’ own socioeconomic backgrounds (at the age of 16) in their later susceptibility to differentially judge students from different socioeconomic backgrounds and in differentially composed classrooms. Multilevel regression analyses revealed that, after controlling for differences in achievement (as indicated by standardized tests), teachers’ judgments were associated with the classrooms’ socioeconomic composition, and this finding could not be attributed to the average levels of motivation or behavior in the classroom. Teachers were similarly likely to exhibit such differential judgments regardless of their own socioeconomic background. These findings are discussed in the context of their implications for educational policy.