Exchange Interactions in Paramagnetic Amorphous and Disordered Crystalline CrN-based Systems

We present a first principles supercell methodology for the calculation of exchange interactions of magnetic materials with arbitrary degrees of structural and chemical disorder in their high temperature paramagnetic state. It is based on a projection of the total magnetic energy of the system onto local pair clusters, allowing the interactions to vary independently as a response to their local environments. We demonstrate our method by deriving the distance dependent exchange interactions in vibrating crystalline CrN, a Ti$_{0.5}$Cr$_{0.5}$N solid solution as well as in amorphous CrN. Our method reveals strong local environment effects in all three systems. In the amorphous case we use the full set of exchange interactions in a search for the non-collinear magnetic ground state.Comment: 5 pages, 3 figure

Dynamics of solar wind protons reflected by the Moon

Solar system bodies that lack a significant atmosphere and significant internal magnetic fields, such as the Moon and asteroids, have been considered as passive absorbers of the solar wind. However, ion observations near the Moon by the SELENE spacecraft show that a fraction of the impacting solar wind protons are reflected by the surface of the Moon. Using new observations of the velocity spectrum of these reflected protons by the SARA experiment on-board the Chandrayaan-1 spacecraft at the Moon, we show by modeling that the reflection of solar wind protons will affect the global plasma environment. These global perturbations of the ion fluxes and the magnetic fields will depend on microscopic properties of the object's reflecting surface. This solar wind reflection process could explain past ion observations at the Moon, and the process should occur universally at all atmosphereless non-magnetized objects.Comment: 12 pages, 8 figure

Building Data-Driven Pathways From Routinely Collected Hospital Data:A Case Study on Prostate Cancer

Background: Routinely collected data in hospitals is complex, typically heterogeneous, and scattered across multiple Hospital Information Systems (HIS). This big data, created as a byproduct of health care activities, has the potential to provide a better understanding of diseases, unearth hidden patterns, and improve services and cost. The extent and uses of such data rely on its quality, which is not consistently checked, nor fully understood. Nevertheless, using routine data for the construction of data-driven clinical pathways, describing processes and trends, is a key topic receiving increasing attention in the literature. Traditional algorithms do not cope well with unstructured processes or data, and do not produce clinically meaningful visualizations. Supporting systems that provide additional information, context, and quality assurance inspection are needed. Objective: The objective of the study is to explore how routine hospital data can be used to develop data-driven pathways that describe the journeys that patients take through care, and their potential uses in biomedical research; it proposes a framework for the construction, quality assessment, and visualization of patient pathways for clinical studies and decision support using a case study on prostate cancer. Methods: Data pertaining to prostate cancer patients were extracted from a large UK hospital from eight different HIS, validated, and complemented with information from the local cancer registry. Data-driven pathways were built for each of the 1904 patients and an expert knowledge base, containing rules on the prostate cancer biomarker, was used to assess the completeness and utility of the pathways for a specific clinical study. Software components were built to provide meaningful visualizations for the constructed pathways. Results: The proposed framework and pathway formalism enable the summarization, visualization, and querying of complex patient-centric clinical information, as well as the computation of quality indicators and dimensions. A novel graphical representation of the pathways allows the synthesis of such information. Conclusions: Clinical pathways built from routinely collected hospital data can unearth information about patients and diseases that may otherwise be unavailable or overlooked in hospitals. Data-driven clinical pathways allow for heterogeneous data (ie, semistructured and unstructured data) to be collated over a unified data model and for data quality dimensions to be assessed. This work has enabled further research on prostate cancer and its biomarkers, and on the development and application of methods to mine, compare, analyze, and visualize pathways constructed from routine data. This is an important development for the reuse of big data in hospitals

Protons in the near-lunar wake observed by the Sub-keV Atom Reflection Analyzer on board Chandrayaan-1

Significant proton fluxes were detected in the near wake region of the Moon by an ion mass spectrometer on board Chandrayaan-1. The energy of these nightside protons is slightly higher than the energy of the solar wind protons. The protons are detected close to the lunar equatorial plane at a $140^{\circ}$ solar zenith angle, i.e., ~50$^{\circ}$ behind the terminator at a height of 100 km. The protons come from just above the local horizon, and move along the magnetic field in the solar wind reference frame. We compared the observed proton flux with the predictions from analytical models of an electrostatic plasma expansion into a vacuum. The observed velocity was higher than the velocity predicted by analytical models by a factor of 2 to 3. The simple analytical models cannot explain the observed ion dynamics along the magnetic field in the vicinity of the Moon.Comment: 28 pages, 7 figure

The Fermi Surface Effect on Magnetic Interlayer Coupling

The oscillating magnetic interlayer coupling of Fe over spacer layers consisting of Cu$_{x}$Pd$_{1-x}$ alloys is investigated by first principles density functional theory. The amplitude, period and phase of the coupling, as well as the disorder-induced decay, are analyzed in detail and the consistency to the Ruderman-Kittel-Kasuya-Yoshida (RKKY) theory is discussed. For the first time an effect of the Fermi surface nesting strength on the amplitude is established from first principles calculations. An unexpected variation of the phase and disorder-induced decay is obtained and the results are discussed in terms of asymptotics

Dopamine protects neurons against glutamate-induced excitotoxicity

Glutamate excitotoxicity is responsible for neuronal death in acute neurological disorders including stroke, trauma and neurodegenerative disease. Loss of calcium homeostasis is a key mediator of glutamate-induced cell death. The neurotransmitter dopamine (DA) is known to modulate calcium signalling, and here we show that it can do so in response to physiological concentrations of glutamate. Furthermore, DA is able to protect neurons from glutamate-induced cell death at pathological concentrations of glutamate. We demonstrate that DA has a novel role in preventing delayed calcium deregulation in cortical, hippocampal and midbrain neurons. The effect of DA in abolishing glutamate excitotoxicity can be induced by DA receptor agonists, and is abolished by DA receptor antagonists. Our data indicate that the modulation of glutamate excitotoxicity by DA is receptor-mediated. We postulate that DA has a major physiological function as a safety catch to restrict the glutamate-induced calcium signal, and thereby prevent glutamate-induced cell death in the brain

An open and parallel multiresolution framework using block-based adaptive grids

A numerical approach for solving evolutionary partial differential equations in two and three space dimensions on block-based adaptive grids is presented. The numerical discretization is based on high-order, central finite-differences and explicit time integration. Grid refinement and coarsening are triggered by multiresolution analysis, i.e. thresholding of wavelet coefficients, which allow controlling the precision of the adaptive approximation of the solution with respect to uniform grid computations. The implementation of the scheme is fully parallel using MPI with a hybrid data structure. Load balancing relies on space filling curves techniques. Validation tests for 2D advection equations allow to assess the precision and performance of the developed code. Computations of the compressible Navier-Stokes equations for a temporally developing 2D mixing layer illustrate the properties of the code for nonlinear multi-scale problems. The code is open source

Energetic Hydrogen and Oxygen Atoms Observed on the Nightside of Mars

We present measurements of energetic hydrogen and oxygen atoms (ENAs) on the nightside of Mars detected by the neutral particle detector (NPD) of ASPERA-3 on Mars Express. We focus on the observations for which the field-of-view of NPD was directed at the nightside of Mars or at the region around the limb, thus monitoring the flow of ENAs towards the nightside of the planet. We derive energy spectra and total fluxes, and have compiled maps of hydrogen ENA outflow. The hydrogen ENA intensities reach 105 cm−2 sr−1 s−1, but no oxygen ENA signals above the detection threshold of 104 cm−2 sr−1 s−1 are observed. These intensities are considerably lower than most theoretical predictions. We explain the discrepancy as due to an overestimation of the charge-exchange processes in the models for which too high an exospheric density was assumed. Recent UV limb emission measurements (Galli et al., this issue) point to a hydrogen exobase density of 1010 m−3 and a very hot hydrogen component, whereas the models were based on a hydrogen exobase density of 1012 m−3 and a temperature of 200 K predicted by Krasnopolsky and Gladstone (1996). Finally, we estimate the global atmospheric loss rate of hydrogen and oxygen due to the production of ENA