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

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

An \emph{ab initio} method for locating characteristic potential energy minima of liquids

It is possible in principle to probe the many--atom potential surface using density functional theory (DFT). This will allow us to apply DFT to the Hamiltonian formulation of atomic motion in monatomic liquids [\textit{Phys. Rev. E} {\bf 56}, 4179 (1997)]. For a monatomic system, analysis of the potential surface is facilitated by the random and symmetric classification of potential energy valleys. Since the random valleys are numerically dominant and uniform in their macroscopic potential properties, only a few quenches are necessary to establish these properties. Here we describe an efficient technique for doing this. Quenches are done from easily generated "stochastic" configurations, in which the nuclei are distributed uniformly within a constraint limiting the closeness of approach. For metallic Na with atomic pair potential interactions, it is shown that quenches from stochastic configurations and quenches from equilibrium liquid Molecular Dynamics (MD) configurations produce statistically identical distributions of the structural potential energy. Again for metallic Na, it is shown that DFT quenches from stochastic configurations provide the parameters which calibrate the Hamiltonian. A statistical mechanical analysis shows how the underlying potential properties can be extracted from the distributions found in quenches from stochastic configurations

Unveiling teachers' beliefs on visual cognition and learning styles of deaf and hard of hearing students: a Portuguese-Swedish study

Vision is considered a privileged sensory channel for deaf and hard of hearing (DHH) students to learn, and, naturally, they recognize themselves as visual learners. This assumption also seems widespread among schoolteachers, which led us to analyse the intersection between teachers’ beliefs on deaf and hard of hearing students’ academic achievement, visual skills, attentional difficulties, and the perceived importance of image display in class. An online survey was designed to analyse the beliefs of the schoolteachers about the deaf and hard of hearing students learning in educational settings from Portugal and Sweden. Participated 133 teachers, 70 Portuguese and 63 Swedish, from the preschool to the end of mandatory education (ages 3–18) with several years of experience. The content analysis and the computed SPSS statistical significance tests reveal that surveyed teachers believe that deaf and hard of hearing students have better visual skills when compared with their hearing peers yet show divergent beliefs about visual attentional processes. Within the teachers’ perceptions on learning barriers to DHH students, the distractibility and cognitive effort factors were highlighted, among communicational difficulties in class. Conclusions about the prevalence of learning misconceptions in teachers from both countries analysed, corroborate previous studies on neuromyths in education, and bring novelty to Deaf Education field. The work of translation of scientific knowledge, teacher training updating, and partnership between researchers and educators are also urgently needed in special education.info:eu-repo/semantics/publishedVersio

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

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

Gain-of-function R225Q mutation in AMP-activated protein kinase gamma3 subunit increases mitochondrial biogenesis in glycolytic skeletal muscle

AMP-activated protein kinase (AMPK) is a heterotrimeric complex, composed of a catalytic subunit (alpha) and two regulatory subunits (beta and gamma), that works as a cellular energy sensor. The existence of multiple heterotrimeric complexes provides a molecular basis for the multiple roles of this highly conserved signaling system. The AMPK gamma3 subunit is predominantly expressed in skeletal muscle, mostly in type II glycolytic fiber types. We determined whether the AMPK gamma3 subunit has a role in signaling pathways that mediate mitochondrial biogenesis in skeletal muscle. We provide evidence that overexpression or ablation of the AMPK gamma3 subunit does not appear to play a critical role in defining mitochondrial content in resting skeletal muscle. However, overexpression of a mutant form (R225Q) of the AMPK gamma3 subunit (Tg-AMPKgamma3(225Q)) increases mitochondrial biogenesis in glycolytic skeletal muscle. These adaptations are associated with an increase in expression of the co-activator PGC-1alpha and several transcription factors that regulate mitochondrial biogenesis, including NRF-1, NRF-2, and TFAM. Succinate dehydrogenase staining, a marker of the oxidative profile of individual fibers, was also increased in transversal skeletal muscle sections of white gastrocnemius muscle from Tg-AMPKgamma3(225Q) mice, independent of changes in fiber type composition. In conclusion, a single nucleotide mutation (R225Q) in the AMPK gamma3 subunit is associated with mitochondrial biogenesis in glycolytic skeletal muscle, concomitant with increased expression of the co-activator PGC-1alpha and several transcription factors that regulate mitochondrial proteins, without altering fiber type composition

Label-Free Proteomics Approach Characterizes Plasma Protein Signature of Donor Brain Death

Purpose Despite recent advances in donation after circulatory death, transplants from brain-dead donors remain the sole source in heart transplantation (HTx) worldwide. Due to organ shortage, marginal donors are increasingly used and the utilization of transplants becomes markedly more challenging. They undergo invariably brain death that induces a systemic cytokine and catecholamine storm that lead to systemic inflammation, labile hemodynamics, and organ hypoperfusion. Together, these can damage the heart and aggravate later occurring graft injury, and ultimately, compromise graft function. However, the effect of donor brain death on allografts is not well understood. Methods In a separate prospective, blinded single-center trial, we collected donor plasma samples and relevant clinical patient data from 50 HTx brain-dead donors and as controls plasma samples from age- and gender-matched 23 healthy volunteers. Quantitative label-free proteomics in high definition MSE mode (HDMSE) was carried out on the samples. Various statistical analyses were performed on quantitative proteomics data to obtain the most reliably distinguishing proteins, which classify the donors vs controls. Results With two or more unique proteins per identification, 463 proteins were quantified in our pilot study. A complete separation between donors and controls based on a set of 278 proteins (p-valuePeer reviewe