2,552 research outputs found
Improving the Efficiency of FP-LAPW Calculations
The full-potential linearized augmented-plane wave (FP-LAPW) method is well
known to enable most accurate calculations of the electronic structure and
magnetic properties of crystals and surfaces. The implementation of atomic
forces has greatly increased it's applicability, but it is still generally
believed that FP-LAPW calculations require substantial higher computational
effort compared to the pseudopotential plane wave (PPW) based methods.
In the present paper we analyse the FP-LAPW method from a computational point
of view. Starting from an existing implementation (WIEN95 code), we identified
the time consuming parts and show how some of them can be formulated more
efficiently. In this context also the hardware architecture plays a crucial
role. The remaining computational effort is mainly determined by the setup and
diagonalization of the Hamiltonian matrix. For the latter, two different
iterative schemes are compared. The speed-up gained by these optimizations is
compared to the runtime of the ``original'' version of the code, and the PPW
approach. We expect that the strategies described here, can also be used to
speed up other computer codes, where similar tasks must be performed.Comment: 20 pages, 3 figures. Appears in Comp. Phys. Com. Other related
publications can be found at http://www.rz-berlin.mpg.de/th/paper.htm
Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks
Graph refinement, or the task of obtaining subgraphs of interest from
over-complete graphs, can have many varied applications. In this work, we
extract trees or collection of sub-trees from image data by, first deriving a
graph-based representation of the volumetric data and then, posing the tree
extraction as a graph refinement task. We present two methods to perform graph
refinement. First, we use mean-field approximation (MFA) to approximate the
posterior density over the subgraphs from which the optimal subgraph of
interest can be estimated. Mean field networks (MFNs) are used for inference
based on the interpretation that iterations of MFA can be seen as feed-forward
operations in a neural network. This allows us to learn the model parameters
using gradient descent. Second, we present a supervised learning approach using
graph neural networks (GNNs) which can be seen as generalisations of MFNs.
Subgraphs are obtained by training a GNN-based graph refinement model to
directly predict edge probabilities. We discuss connections between the two
classes of methods and compare them for the task of extracting airways from 3D,
low-dose, chest CT data. We show that both the MFN and GNN models show
significant improvement when compared to one baseline method, that is similar
to a top performing method in the EXACT'09 Challenge, and a 3D U-Net based
airway segmentation model, in detecting more branches with fewer false
positives.Comment: Accepted for publication at Medical Image Analysis. 14 page
Massive gene loss in mistletoe (<em>Viscum</em>, Viscaceae) mitochondria
Parasitism is a successful survival strategy across all kingdoms and has evolved repeatedly in angiosperms. Parasitic plants obtain nutrients from other plants and some are agricultural pests. Obligate parasites, which cannot complete their lifecycle without a host, may lack functional photosystems (holoparasites), or have retained photosynthesis (hemiparasites). Plastid genomes are often reduced in parasites, but complete mitochondrial genomes have not been sequenced and their mitochondrial respiratory capacities are largely unknown. The hemiparasitic European mistletoe (Viscum album), known from folklore and postulated therapeutic properties, is a pest in plantations and forestry. We compare the mitochondrial genomes of three Viscum species based on the complete mitochondrial genome of V. album, the first from a parasitic plant. We show that mitochondrial genes encoding proteins of all respiratory complexes are lacking or pseudogenized raising several questions relevant to all parasitic plants: Are any mitochondrial gene functions essential? Do any genes need to be located in the mitochondrial genome or can they all be transferred to the nucleus? Can parasitic plants survive without oxidative phosphorylation by using alternative respiratory pathways? More generally, our study is a step towards understanding how host- and self-perception, host integration and nucleic acid transfer has modified ancestral mitochondrial genomes
Mitochondria in parasitic plants
Plant mitochondrial genomes are renowned for their structural complexity, extreme variation in size and mutation rates, and ability to incorporate foreign DNA. Parasitic flowering plants are no exception, and the close association between parasite and host may even enhance the likelihood of horizontal gene transfer (HGT) between them. Recent studies on mistletoes (Viscum) have revealed that these parasites have lost an exceptional number of mitochondrial genes, including all complex I genes of the respiratory chain. At the same time, an altered respiratory pathway has been demonstrated. Here we review the current understanding of mitochondrial evolution in parasitic plants with a special emphasis on HGT to and from parasite mitochondrial genomes, as well as the uniquely altered mitochondria in Viscum and related plants. © 2020 The Author
Extraction of Airways using Graph Neural Networks
We present extraction of tree structures, such as airways, from image data as
a graph refinement task. To this end, we propose a graph auto-encoder model
that uses an encoder based on graph neural networks (GNNs) to learn embeddings
from input node features and a decoder to predict connections between nodes.
Performance of the GNN model is compared with mean-field networks in their
ability to extract airways from 3D chest CT scans.Comment: Extended Abstract submitted to MIDL, 2018. 3 page
Comorbidities between tuberculosis and common mental disorders: A scoping review of epidemiological patterns and person-centred care interventions from low-to-middle income and BRICS countries
Background : There is increasing evidence that the substantial global burden of disease for tuberculosis unfolds in concert with dimensions of common mental disorders. Person-centred care holds much promise to ameliorate these comorbidities in low-tomiddle income countries and emerging economies. Towards this end, this paper aimed to review 1) the nature and extent of tuberculosis and common mental disorder comorbidity and 2) person-centred tuberculosis care in low-to-middle income countries and emerging economies. Main text : A scoping review was conducted of English-language studies published from 2000-2019 in peer-reviewed and grey literature, using established guidelines, for each of the study objectives. Four broad tuberculosis/mental disorder comorbidities were described in the literature, namely alcohol use and tuberculosis, depression and tuberculosis, anxiety and tuberculosis, and general mental health and tuberculosis. Rates of comorbidity varied widely across countries for depression, anxiety, alcohol use and general mental health. Alcohol use and tuberculosis were significantly related, especially in the context of poverty. The initial tuberculosis diagnostic episode had substantial socio-psychological effects on service users. While men tended to report higher rates of alcohol use and treatment default, women in general had worse mental health outcomes. Older age and a history of mental illness were also associated with pronounced tuberculosis and mental disorder comorbidity. Person-centred tuberculosis care interventions were almost absent, with only one study from Nepal identified. Conclusions : There is an emerging body of evidence describing the nature and extent of tuberculosis and mental disorders comorbidity in low-to-middle income countries. Despite the potential of person-centred interventions, evidence is limited. This review highlights a pronounced need to address psychosocial comorbidities with TB in LMICs, where models of person-centred TB care in routine care platforms may yield promising outcomes
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