Quantum Parabolic Sombrero

We have discussed the energy levels and probability distribution density for a quantum particle placed in the two-dimensional sombrero-shaped potential $V(\rho,\rho_0)=\mu\omega^2|\rho^2-\rho_0^2|/2$.Comment: 10 pages, LaTex, 6 figures (eps). accepted in Phys. Lett.

Rational matrix solutions to the Leech equation: The Ball-Trent approach revisited

Using spectral factorization techniques, a method is given by which rational matrix solutions to the Leech equation with rational matrix data can be computed explicitly. This method is based on an approach by J.A. Ball and T.T. Trent, and generalizes techniques from recent work of T.T. Trent for the case of polynomial matrix data.Comment: 15 page

Incidental catches of pelagic megafauna by the EU pelagic fleet in the Mauritanian exclusive economic zone during the year 2001 : results extracted from the scientific observer program

The joint project between the Netherlands Institute for Fisheries Research (RIVO) and the Mauritanian Institute for Oceanography and Fisheries Research (IMROP) has been initiated in 1998 in order to strengthen Mauritania’s capacity for research on stocks of small pelagic fish. Part of this project is the 'Scientific Observer Program' that monitors the catches (conserved and discarded) of the EU fishery for small pelagics in Mauritania. The EU pelagic fleet in Mauritania focuses their fisheries mainly on the group of sardinella, additional target species are horse mackerel, chub mackerel and pilchard. Still, the unwanted bycatches of non-commercial large animals such as sharks and dolphins is inevitable so far. This report describes the total bycatches of the pelagic megafauna by the EU pelagic fleet in the Mauritanian Exclusive Economic Zone during the year 2001. The current sampling of large bycatches appears to be full of shortcomings and the collected data are inadequate to apply for the evaluation of the impact of the EU pelagic fishery in Mauritania. Therefore it is concluded that the program needs to undergo a thorough renewal. Essential recommendations are given

Network of Steel: Neural Font Style Transfer from Heavy Metal to Corporate Logos

We introduce a method for transferring style from the logos of heavy metal bands onto corporate logos using a VGG16 network. We establish the contribution of different layers and loss coefficients to the learning of style, minimization of artefacts and maintenance of readability of corporate logos. We find layers and loss coefficients that produce a good tradeoff between heavy metal style and corporate logo readability. This is the first step both towards sparse font style transfer and corporate logo decoration using generative networks. Heavy metal and corporate logos are very different artistically, in the way they emphasize emotions and readability, therefore training a model to fuse the two is an interesting problem