Circularly polarized waves in a plasma with vacuum polarization effects

The theory for large amplitude circularly polarized waves propagating along an external magnetic field is extended in order to include also vacuum polarization effects. A general dispersion relation, which unites previous results, is derived.Comment: 5 pages (To appear in Physics of Plasmas

Short wavelength quantum electrodynamical correction to cold plasma-wave propagation

The effect of short wavelength quantum electrodynamic (QED) correction on plasma-wave propagation is investigated. The effect on plasma oscillations and on electromagnetic waves in an unmagnetized as well as a magnetized plasma is investigated. The effects of the short wavelength QED corrections are most significant for plasma oscillations and for extraordinary modes. In particular, the QED correction allow plasma oscillations to propagate, and the extra-ordinary mode looses its stop band. The significance of our results is discussed.Comment: 12 pages, 5 figure

A linearized kinetic theory of spin-1/2 particles in magnetized plasmas

We have considered linear kinetic theory including the electron spin properties in a magnetized plasma. The starting point is a mean field Vlasov-like equation, derived from a fully quantum mechanical treatment, where effects from the electron spin precession and the magnetic dipole force is taken into account. The general conductivity tensor is derived, including both the free current contribution, as well as the magnetization current associated with the spin contribution. We conclude the paper with an extensive discussion of the quantum-mechanical boundary where we list parameter conditions that must be satisfied for various quantum effects to be influential.Comment: 11 page

Analytic continuation by averaging Pad\'e approximants

The ill-posed analytic continuation problem for Green's functions and self-energies is investigated by revisiting the Pad\'{e} approximants technique. We propose to remedy the well-known problems of the Pad\'{e} approximants by performing an average of several continuations, obtained by varying the number of fitted input points and Pad\'{e} coefficients independently. The suggested approach is then applied to several test cases, including Sm and Pr atomic self-energies, the Green's functions of the Hubbard model for a Bethe lattice and of the Haldane model for a nano-ribbon, as well as two special test functions. The sensitivity to numerical noise and the dependence on the precision of the numerical libraries are analysed in detail. The present approach is compared to a number of other techniques, i.e. the non-negative least-square method, the non-negative Tikhonov method and the maximum entropy method, and is shown to perform well for the chosen test cases. This conclusion holds even when the noise on the input data is increased to reach values typical for quantum Monte Carlo simulations. The ability of the algorithm to resolve fine structures is finally illustrated for two relevant test functions.Comment: 10 figure

Development and evaluation of deep learning algorithms for assessment of acute burns and the need for surgery

Assessment of burn extent and depth are critical and require very specialized diagnosis. Automated image-based algorithms could assist in performing wound detection and classification. We aimed to develop two deep-learning algorithms that respectively identify burns, and classify whether they require surgery. An additional aim assessed the performances in different Fitzpatrick skin types. Annotated burn (n = 1105) and background (n = 536) images were collected. Using a commercially available platform for deep learning algorithms, two models were trained and validated on 70% of the images and tested on the remaining 30%. Accuracy was measured for each image using the percentage of wound area correctly identified and F1 scores for the wound identifier; and area under the receiver operating characteristic (AUC) curve, sensitivity, and specificity for the wound classifier. The wound identifier algorithm detected an average of 87.2% of the wound areas accurately in the test set. For the wound classifier algorithm, the AUC was 0.885. The wound identifier algorithm was more accurate in patients with darker skin types; the wound classifier was more accurate in patients with lighter skin types. To conclude, image-based algorithms can support the assessment of acute burns with relatively good accuracy although larger and different datasets are needed.Peer reviewe

Restoration of peatlands and greenhouse gas balances

In this chapter the impact of peatland restoration on greenhouse gas fluxes is discussed based on a literature review. Casestudies are presented covering different peatland types, different regions and different starting conditions

Nonlinear wave interaction and spin models in the MHD regime

Here we consider the influence on the electron spin in the MHD regime. Recently developed models which include spin-velocity correlations are taken as a starting point. A theoretical argument is presented, suggesting that in the MHD regime a single fluid electron model with spin correlations is equivalent to a model with spin-up and spin-down electrons constituting different fluids, but where the spin-velocity correlations are omitted. Three wave interaction of 2 shear Alfven waves and a compressional Alfven wave is then taken as a model problem to evaluate the asserted equivalence. The theoretical argument turns out to be supported, as the predictions of the two models agree completely. Furthermore, the three wave coupling coefficients obey the Manley-Rowe relations, which give further support to the soundness of the models and the validity of the assumptions made in the derivation. Finally we point out that the proposed two-fluid model can be incorporated in standard Particle-In-Cell schemes with only minor modifications.Comment: 8 page