Modeling the impact of gold mining on ecosystem servicesin Ghana´S Southern water basins

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesAll natural resources are more or less limited and they can be overused and destroyed. While nature degradation occurs, political decisions are often short-sighted and profit-oriented, the importance of ecosystems is often unknown or less important than other interests for the decisionmaker. In this work, we apply GIS technics and InVEST models within a gold mining area in the southern water basins in Ghana. The aim was to identify the impact of mining activities on ecosystem services. The research was done with freely available datasets. It was possible to model and map water and soil pollution and to identify differences between regions were gold mining is taking place and regions without it. Gold mining was identified as a threat to the quality of the habitat and the water and soil quality regulation ecosystem services. This work may contribute to mitigate the negative effects of gold mining activities

Nucleon average quark momentum fraction with Nf=2+1N_\mathrm{f}=2+1 Wilson fermions

We report on an analysis of the average quark momentum fraction of the nucleon and related quantities using $N_\mathrm{f}=2+1$ Wilson fermions. Computations are performed on four CLS ensembles covering three values of the lattice spacing at pion masses down to $M_\pi \approx 200\,\mathrm{MeV}$. Several source-sink separations ($\sim 1.0\,\mathrm{fm}$ to $\sim 1.4\,\mathrm{fm}$) are used to assess the excited-state contamination. To gain further insight, the generalized pencil-of-functions approach has been implemented to reduce the excited-state contamination in the relevant two- and three-point functions. Preliminary results are shown for the isovector nucleon charges from vector, axial vector and tensor derivative (twist-2) operators.Comment: 8 pages, 3 figures, 2 tables. Talk presented at the 35th International Symposium on Lattice Field Theory, 18-24 June 2017, Granada, Spai

Revisiting the no-boundary proposal with a scalar field

Recent works have suggested that the no-boundary proposal should be defined as a sum over regular, not necessarily compact, metrics. We show that such a prescription can be implemented in the presence of a scalar field. For concreteness, we consider the model of Garay et al., in which the potential is a sum of exponentials, and which lends itself to an analytical treatment. Compared to the earlier implementation, we find that saddle points with unstable fluctuations can be eliminated by imposition of an appropriate regularity condition. This leads to the appearance of additional saddle points, corresponding to unclosed geometries. We argue that such saddles will occur generically, though we also find in our example that they are subdominant to the closed, Hartle-Hawking, saddle points. When the potential is positive, classical spacetime is only predicted for inflationary histories. When the potential is negative, we recover the AdS gravitational path integral, with a stable scalar field included. One puzzle that we find is that in general the path integral must be restricted to sum only over specific, discrete and late time dependent initial values of the scalar field. Only when the scalar is required to take real values is this puzzle eliminated, a situation that moreover leads to advantageous phenomenological characteristics

Towards Fleet-wide Sharing of Wind Turbine Condition Information through Privacy-preserving Federated Learning

Terabytes of data are collected every day by wind turbine manufacturers from their fleets. The data contain valuable real-time information for turbine health diagnostics and performance monitoring, for predicting rare failures and the remaining service life of critical parts. And yet, this wealth of data from wind turbine fleets remains inaccessible to operators, utility companies, and researchers as manufacturing companies prefer the privacy of their fleets' turbine data for business strategic reasons. The lack of data access impedes the exploitation of opportunities, such as improving data-driven turbine operation and maintenance strategies and reducing downtimes. We present a distributed federated machine learning approach that leaves the data on the wind turbines to preserve the data privacy, as desired by manufacturers, while still enabling fleet-wide learning on those local data. We demonstrate in two case studies that wind turbines which are scarce in representative training data benefit from more accurate fault detection models with federated learning, while no turbine experiences a loss in model performance by participating in the federated learning process. When comparing conventional and federated training processes, the average model training time rises significantly by a factor of up to 14 in the federated training due to increased communication and overhead operations. Thus, model training times might constitute an impediment that needs to be further explored and alleviated in federated learning applications, especially for large wind turbine fleets

Cross-Modal Multivariate Pattern Analysis

Multivariate pattern analysis (MVPA) is an increasingly popular method of analyzing functional magnetic resonance imaging (fMRI) data1-4. Typically, the method is used to identify a subject's perceptual experience from neural activity in certain regions of the brain. For instance, it has been employed to predict the orientation of visual gratings a subject perceives from activity in early visual cortices5 or, analogously, the content of speech from activity in early auditory cortices6

Magnetic Switching of Phase-Slip Dissipation in NbSe2 Nanobelts

The stability of the superconducting dissipationless and resistive states in single-crystalline NbSe2 nanobelts is characterized by transport measurements in an external magnetic field (H). Current-driven electrical measurements show voltage steps, indicating the nucleation of phase-slip structures. Well below the critical temperature, the position of the voltage steps exhibits a sharp, periodic dependence as a function of H. This phenomenon is discussed in the context of two possible mechanisms: the interference of the order parameter and the periodic rearrangement of the vortex lattice within the nanobelt.Comment: 4 figure