The average GeV-band Emission from Gamma-Ray Bursts

We analyze the emission in the 0.3-30 GeV energy range of Gamma-Ray Bursts detected with the Fermi Gamma-ray Space Telescope. We concentrate on bursts that were previously only detected with the Gamma-Ray Burst Monitor in the keV energy range. These bursts will then be compared to the bursts that were individually detected with the Large Area Telescope at higher energies. To estimate the emission of faint GRBs we use non-standard analysis methods and sum over many GRBs to find an average signal which is significantly above background level. We use a subsample of 99 GRBs listed in the Burst Catalog from the first two years of observation. Although mostly not individually detectable, the bursts not detected by the Large Area Telescope on average emit a significant flux in the energy range from 0.3 GeV to 30 GeV, but their cumulative energy fluence is only 8% of that of all GRBs. Likewise, the GeV-to-MeV flux ratio is less and the GeV-band spectra are softer. We confirm that the GeV-band emission lasts much longer than the emission found in the keV energy range. The average allsky energy flux from GRBs in the GeV band is 6.4*10^-4 erg cm^-2 yr^-1 or only 4% of the energy flux of cosmic rays above the ankle at 10^18.6 eV.Comment: Astronomy and Astrophysics, version accepted for publicatio

Large bi-diagonal matrices and random perturbations

This is a first paper by the authors dedicated to the distribution of eigenvalues for random perturbations of large bidiagonal Toeplitz matrices.Comment: 34 pages, 4 figure

Determinants of Further Training: Evidence for Germany

Based on a German representative sample of employees we explore the relevance and development of further training in private sector firms. We focus on formal training and explore possible individual and job-based determinants of its incidence. We also show changes over time during a 20 year observation period from 1989 to 2008. Most hypotheses are supported by the empirical evidence. Job status and firm size are the most relevant characteristics for training participation. Furthermore, our analyses reveal a general trend of rising training rates from 1989 to 2008 indicating an increased importance in the German labor market.further training, GSOEP, human capital, panel data

The Economics of Pending Patents

We provide a treatment of a number of questions pertaining to pending patents – a subject that has so-far mainly been discussed en-passant in the existing literature. We present the underlying institutional and legal framework that governs pending patents and some basic facts related to them. Then, we focus on the strategic considerations of firms in the earliest stage of the patenting process and the interplay with the patent office. This is followed by considering the perspective of the patent and trademark offices (PTOs), in particular, acknowledging the limited resources that are available to PTOs. Finally, we investigate the potential abuse of pending patents and the role of reputation of patenting firms.patenting, pending patents, innovation, patent office overload, patent inspection, grant delays

Scaling Properties of Parallelized Multicanonical Simulations

We implemented a parallel version of the multicanonical algorithm and applied it to a variety of systems with phase transitions of first and second order. The parallelization relies on independent equilibrium simulations that only communicate when the multicanonical weight function is updated. That way, the Markov chains efficiently sample the temporary distributions allowing for good estimations of consecutive weight functions. The systems investigated range from the well known Ising and Potts spin systems to bead-spring polymers. We estimate the speedup with increasing number of parallel processes. Overall, the parallelization is shown to scale quite well. In the case of multicanonical simulations of the $q$-state Potts model ($q\ge6$) and multimagnetic simulations of the Ising model, the optimal performance is limited due to emerging barriers.Comment: Contribution to the Proceedings of "Recent Developments in Computer Simulational Studies in Condensed Matter Physics 2013

Lewis acid catalyzed transfer hydromethallylation for the construction of quaternary carbon centers

The design and gram‐scale synthesis of a cyclohexa‐1,4‐diene‐based surrogate of isobutene gas is reported. Using the highly electron‐deficient Lewis acid B(C6F5)3, application of this surrogate in the hydromethallylation of electron‐rich styrene derivatives provided sterically congested quaternary carbon centers. The reaction proceeds by C(sp3)−C(sp3) bond formation at a tertiary carbenium ion that is generated by alkene protonation. The possibility of two concurrent mechanisms is proposed on the basis of mechanistic experiments using a deuterated surrogate.TU Berlin, Open-Access-Mittel - 201

Onset of anomalous diffusion in colloids confined to quasi-monolayers

It has been recently shown that a colloidal monolayer, e.g., formed at a fluid interface or by means of a suitable confining potential, exhibits anomalous collective diffusion. This is a consequence of the hydrodynamic interactions mediated by the three-dimensional (3D) ambient fluid when the particles are confined to reside on a two-dimensional (2D) manifold. We study theoretically and with numerical simulations the crossover from normal to anomalous diffusion as the particles are, in real systems, confined by a 3D external potential and thus have the possibility to fluctuate out of the 2D manifold, thus forming actually a quasi-monolayer.Comment: 13 pages, 9 figure

Jamming-Resistant Learning in Wireless Networks

We consider capacity maximization in wireless networks under adversarial interference conditions. There are n links, each consisting of a sender and a receiver, which repeatedly try to perform a successful transmission. In each time step, the success of attempted transmissions depends on interference conditions, which are captured by an interference model (e.g. the SINR model). Additionally, an adversarial jammer can render a (1-delta)-fraction of time steps unsuccessful. For this scenario, we analyze a framework for distributed learning algorithms to maximize the number of successful transmissions. Our main result is an algorithm based on no-regret learning converging to an O(1/delta)-approximation. It provides even a constant-factor approximation when the jammer exactly blocks a (1-delta)-fraction of time steps. In addition, we consider a stochastic jammer, for which we obtain a constant-factor approximation after a polynomial number of time steps. We also consider more general settings, in which links arrive and depart dynamically, and where each sender tries to reach multiple receivers. Our algorithms perform favorably in simulations.Comment: 22 pages, 2 figures, typos remove