Africa: SDP and Sports Academies

Within mainstream migration studies, there is a voluminous literature on migration development interactions and outcomes (cf. De Haas, 2010). As this Handbook reveals, there is also a significant and growing body of research on the relationships between sport and development. Falling between these two canons of academic work is a smaller literature which has explored the intersections between sports migration and development in the global South (Bale, 2004; Darby, 2000; Esson, 2015a; Klein, 2014). Much of this work has focused on football migration from the African continent, particularly West Africa, and has acknowledged that football academies, defined as facilities or coaching programs designed to produce talent predominantly for export, are pivotal in this process (Darby, Akindes and Kirwin, 2007). Recent scholarship has shown how aspirations to migrate and the academies that seek to facilitate this articulate with varying forms of social and economic development in complex ways, and produce more heterogeneous outcomes than were previously observed (Darby, 2013a; Dubinsky and Schler, 2017). This chapter explores these articulations in relation to football in Africa, predominantly Ghana where academies have become increasingly visible. While African football is the focus of this chapter, this discussion speaks to wider debates on the migration development nexus in the context of sport, namely the tension between sport development, the commodification of sporting talent, and aspirations to develop an individual through sport and thereby enact

The influence of flow discharge variations on the morphodynamics of a diffluence-confluence unit on a large river: Impacts of discharge variation on a diffluence-confluence unit

© 2017 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd. Bifurcations are key geomorphological nodes in anabranching and braided fluvial channels, controlling local bed morphology, the routing of sediment and water, and ultimately defining the stability of their associated diffluence–confluence unit. Recently, numerical modelling of bifurcations has focused on the relationship between flow conditions and the partitioning of sediment between the bifurcate channels. Herein, we report on field observations spanning September 2013 to July 2014 of the three-dimensional flow structure, bed morphological change and partitioning of both flow discharge and suspended sediment through a large diffluence–confluence unit on the Mekong River, Cambodia, across a range of flow stages (from 13 500 to 27 000 m 3 s −1 ). Analysis of discharge and sediment load throughout the diffluence–confluence unit reveals that during the highest flows (Q = 27 000 m 3 s −1 ), the downstream island complex is a net sink of sediment (losing 2600 ± 2000 kg s −1 between the diffluence and confluence), whereas during the rising limb (Q = 19 500 m 3 s −1 ) and falling limb flows (Q = 13 500 m 3 s −1 ) the sediment balance is in quasi-equilibrium. We show that the discharge asymmetry of the bifurcation varies with discharge and highlight that the influence of upstream curvature-induced water surface slope and bed morphological change may be first-order controls on bifurcation configuration. Comparison of our field data to existing bifurcation stability diagrams reveals that during lower (rising and falling limb) flow the bifurcation may be classified as unstable, yet transitions to a stable condition at high flows. However, over the long term (1959–2013) aerial imagery reveals the diffluence–confluence unit to be fairly stable. We propose, therefore, that the long-term stability of the bifurcation, as well as the larger channel planform and morphology of the diffluence–confluence unit, may be controlled by the dominant sediment transport regime of the system. © 2017 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd

Gaussian Approximation Potentials: theory, software implementation and application examples

Gaussian Approximation Potentials are a class of Machine Learned Interatomic Potentials routinely used to model materials and molecular systems on the atomic scale. The software implementation provides the means for both fitting models using ab initio data and using the resulting potentials in atomic simulations. Details of the GAP theory, algorithms and software are presented, together with detailed usage examples to help new and existing users. We review some recent developments to the GAP framework, including MPI parallelisation of the fitting code enabling its use on thousands of CPU cores and compression of descriptors to eliminate the poor scaling with the number of different chemical elements

Extreme flood-driven fluvial bank erosion and sediment loads: direct process measurements using integrated Mobile Laser Scanning (MLS) and hydro-acoustic techniques: Direct measurement of flood-driven erosion using MLS and MBES

Copyright © 2016 John Wiley & Sons, Ltd. This methods paper details the first attempt at monitoring bank erosion, flow and suspended sediment at a site during flooding on the Mekong River induced by the passage of tropical cyclones. We deployed integrated mobile laser scanning (MLS) and multibeam echo sounding (MBES), alongside acoustic Doppler current profiling (aDcp), to directly measure changes in river bank and bed at high (~0.05 m) spatial resolution, in conjunction with measurements of flow and suspended sediment dynamics. We outline the methodological steps used to collect and process this complex point cloud data, and detail the procedures used to process and calibrate the aDcp flow and sediment flux data. A comparison with conventional remote sensing methods of estimating bank erosion, using aerial images and Landsat imagery, reveals that traditional techniques are error prone at the high temporal resolutions required to quantify the patterns and volumes of bank erosion induced by the passage of individual flood events. Our analysis reveals the importance of cyclone-driven flood events in causing high rates of erosion and suspended sediment transport, with a c. twofold increase in bank erosion volumes and a fourfold increase in suspended sediment volumes in the cyclone-affected wet season. Copyright © 2016 John Wiley & Sons, Ltd

Structure prediction of stable sodium germanides at 0 and 10 GPa

In this work we used ab-initio random structure searching (AIRSS) to carry out a systematic search for crystalline Na-Ge materials at both 0 and 10 GPa. The high-throughput structural relaxations were accelerated using a machine-learned interatomic potential (MLIP) fit to density-functional theory (DFT) reference data, allowing ∼1.5 million structures to be relaxed. At ambient conditions we predict three new Zintl phases, Na3Ge2, Na2Ge and Na9Ge4, to be stable and a number of Ge-rich layered structures to lie in close proximity to the convex hull. The known NaδGe34 clathrate and Na4Ge13 host-guest structures are found to be relatively stabilized at higher temperature by vibrational contributions to the free energy. Overall, the low energy phases exhibit exceptional structural diversity, with the expected mixture of covalent and ionic bonding confirmed using the electron-localisation function (ELF). The local Ge structural motifs present at each composition were determined using Smooth Overlap of Atomic Positions (SOAP) descriptors and the Ge-K edge was simulated for representatives of each motif, providing a direct link to experimental x-ray absorption spectroscopy (XAS). Two Ge-rich phases are predicted to be stable at 10 GPa; NaGe3 and NaGe2 have simple kagome and simple hexagonal Ge lattices respectively with Na contained in the pores. NaGe3 is isostructural with the MgB3 and MgSi3 family of kagome superconductors and remains dynamically stable at 0 GPa. Removing the Na from NaGe2 results in the hexagonal lonsdalite Ge allotrope, which has a direct band gap

Tensor-reduced atomic density representations

Density based representations of atomic environments that are invariant under Euclidean symmetries have become a widely used tool in the machine learning of interatomic potentials, broader data-driven atomistic modelling and the visualisation and analysis of materials datasets.The standard mechanism used to incorporate chemical element information is to create separate densities for each element and form tensor products between them. This leads to a steep scaling in the size of the representation as the number of elements increases. Graph neural networks, which do not explicitly use density representations, escape this scaling by mapping the chemical element information into a fixed dimensional space in a learnable way. We recast this approach as tensor factorisation by exploiting the tensor structure of standard neighbour density based descriptors. In doing so, we form compact tensor-reduced representations whose size does not depend on the number of chemical elements, but remain systematically convergeable and are therefore applicable to a wide range of data analysis and regression tasks.Comment: 8 pages, 4 figure

Sustainable Human Presence on the Moon using In Situ Resources

New capabilities, technologies and infrastructure must be developed to enable a sustained human presence on the moon and beyond. The key to having this permanent presence is the utilization of in situ resources. To this end, NASA is investigating how in situ resources can be utilized to improve mission success by reducing up-mass, improving safety, reducing risk, and bringing down costs for the overall mission. To ensure that this capability is available when needed, technology development is required now. NASA/Marshall Space Flight Center (MSFC) is supporting this endeavor, along with other NASA centers, by exploring how lunar regolith can be mined for uses such as construction, life support, propulsion, power, and fabrication. Efforts at MSFC include development of lunar regolith simulant for hardware testing and development, extraction of oxygen and other materials from the lunar regolith, production of parts and tools on the moon from local materials or from provisioned feedstocks, and capabilities to show that produced parts are "ready for use". This paper discusses the lunar regolith, how the regolith is being replicated in the development of simulants and possible uses of the regolith

ACEpotentials.jl : a Julia implementation of the atomic cluster expansion

We introduce ACEpotentials.jl, a Julia-language software package that constructs interatomic potentials from quantum mechanical reference data using the Atomic Cluster Expansion [R. Drautz, Phys. Rev. B 99, 014104 (2019)]. As the latter provides a complete description of atomic environments, including invariance to overall translation and rotation as well as permutation of like atoms, the resulting potentials are systematically improvable and data efficient. Furthermore, the descriptor’s expressiveness enables use of a linear model, facilitating rapid evaluation and straightforward application of Bayesian techniques for active learning. We summarize the capabilities of ACEpotentials.jl and demonstrate its strengths (simplicity, interpretability, robustness, performance) on a selection of prototypical atomistic modelling workflows