Analyzing and Modeling the Performance of the HemeLB Lattice-Boltzmann Simulation Environment

We investigate the performance of the HemeLB lattice-Boltzmann simulator for cerebrovascular blood flow, aimed at providing timely and clinically relevant assistance to neurosurgeons. HemeLB is optimised for sparse geometries, supports interactive use, and scales well to 32,768 cores for problems with ~81 million lattice sites. We obtain a maximum performance of 29.5 billion site updates per second, with only an 11% slowdown for highly sparse problems (5% fluid fraction). We present steering and visualisation performance measurements and provide a model which allows users to predict the performance, thereby determining how to run simulations with maximum accuracy within time constraints.Comment: Accepted by the Journal of Computational Science. 33 pages, 16 figures, 7 table

Right ventricular infarction complicated by right to left shunt

A case of right ventricular infarction complicated by a right to left shunt through a patent foramen ovale is presented. The diagnosis was confirmed by two-dimensional echocardiography with contrast injection and indicator dye-dilution curve and oximetry at cardiac catheterization

Modelling Individual Evacuation Decisions during Natural Disasters: A Case Study of Volcanic Crisis in Merapi, Indonesia

As the size of human populations increases, so does the severity of the impacts of natural disasters. This is partly because more people are now occupying areas which are susceptible to hazardous natural events, hence, evacuation is needed when such events occur. Evacuation can be the most important action to minimise the impact of any disaster, but in many cases there are always people who are reluctant to leave. This paper describes an agent-based model (ABM) of evacuation decisions, focusing on the emergence of reluctant people in times of crisis and using Merapi, Indonesia as a case study. The individual evacuation decision model is influenced by several factors formulated from a literature review and survey. We categorised the factors influencing evacuation decisions into two opposing forces, namely, the driving factors to leave (evacuate) versus those to stay, to formulate the model. The evacuation decision (to stay/leave) of an agent is based on an evaluation of the strength of these driving factors using threshold-based rules. This ABM was utilised with a synthetic population from census microdata, in which everyone is characterised by the decision rule. Three scenarios with varying parameters are examined to calibrate the model. Validations were conducted using a retrodictive approach by performing spatial and temporal comparisons between the outputs of simulation and the real data. We present the results of the simulations and discuss the outcomes to conclude with the most plausible scenario

Development and exploratory cluster-randomised opportunistic trial of a theory-based intervention to enhance physical activity among adolescents

Peer reviewedPostprin

Voltage control of nuclear spin in ferromagnetic Schottky diodes

We employ optical pump-probe spectroscopy to investigate the voltage dependence of spontaneous electron and nuclear spin polarizations in hybrid MnAs/n-GaAs and Fe/n-GaAs Schottky diodes. Through the hyperfine interaction, nuclear spin polarization that is imprinted by the ferromagnet acts on conduction electron spins as an effective magnetic field. We demonstrate tuning of this nuclear field from <0.05 to 2.4 kG by varying a small bias voltage across the MnAs device. In addition, a connection is observed between the diode turn-on and the onset of imprinted nuclear polarization, while traditional dynamic nuclear polarization exhibits relatively little voltage dependence.Comment: Submitted to Physical Review B Rapid Communications. 15 pages, 3 figure

Segmentation of the Prostatic Gland and the Intraprostatic Lesions on Multiparametic Magnetic Resonance Imaging Using Mask Region-Based Convolutional Neural Networks

Purpose: Accurate delineation of the prostate gland and intraprostatic lesions (ILs) is essential for prostate cancer dose-escalated radiation therapy. The aim of this study was to develop a sophisticated deep neural network approach to magnetic resonance image analysis that will help IL detection and delineation for clinicians. Methods and Materials: We trained and evaluated mask region-based convolutional neural networks to perform the prostate gland and IL segmentation. There were 2 cohorts in this study: 78 public patients (cohort 1) and 42 private patients from our institution (cohort 2). Prostate gland segmentation was performed using T2-weighted images (T2WIs), although IL segmentation was performed using T2WIs and coregistered apparent diffusion coefficient maps with prostate patches cropped out. The IL segmentation model was extended to select 5 highly suspicious volumetric lesions within the entire prostate. Results: The mask region-based convolutional neural networks model was able to segment the prostate with dice similarity coefficient (DSC) of 0.88 ± 0.04, 0.86 ± 0.04, and 0.82 ± 0.05; sensitivity (Sens.) of 0.93, 0.95, and 0.95; and specificity (Spec.) of 0.98, 0.85, and 0.90. However, ILs were segmented with DSC of 0.62 ± 0.17, 0.59 ± 0.14, and 0.38 ± 0.19; Sens. of 0.55 ± 0.30, 0.63 ± 0.28, and 0.22 ± 0.24; and Spec. of 0.974 ± 0.010, 0.964 ± 0.015, and 0.972 ± 0.015 in public validation/public testing/private testing patients when trained with patients from cohort 1 only. When trained with patients from both cohorts, the values were as follows: DSC of 0.64 ± 0.11, 0.56 ± 0.15, and 0.46 ± 0.15; Sens. of 0.57 ± 0.23, 0.50 ± 0.28, and 0.33 ± 0.17; and Spec. of 0.980 ± 0.009, 0.969 ± 0.016, and 0.977 ± 0.013. Conclusions: Our research framework is able to perform as an end-to-end system that automatically segmented the prostate gland and identified and delineated highly suspicious ILs within the entire prostate. Therefore, this system demonstrated the potential for assisting the clinicians in tumor delineation

Using the ECMWF OpenIFS model and state-of-the-art training techniques in meteorological education

The OpenIFS programme of the European Centre for Medium-Range Weather Forecasts (ECMWF) maintains a version of the ECMWF forecast model (IFS; Integrated Forecasting System) for use in education and research at universities, national meteorological services and other institutes. The OpenIFS model can be run on high-performance computing systems, desktop or laptop computers to produce weather forecasts in a similar way to the operational forecasts at ECMWF. Application of OpenIFS as a training tool is wide ranging. At several universities, masters students are taught modelling aspects via sensitivity studies, such as numerical stability, impact of spatial resolution and physical parameterisation settings on the forecast quality. The OpenIFS single column model is used to study a subset of physical processes in the atmosphere. Participants of the OpenIFS user workshops are trained through selected weather events on interpretation of different forecasts, for example ensemble forecasts, probabilistic information, seasonal forecasts. The OpenIFS user meetings and training events demonstrate advanced and easy-to-use graphical tools and training technologies. Metview is developed to analyse, visualise and evaluate the forecast outputs. OpenIFS and Metview “virtual machines” relieve the tutors from the difficulties often found in installing this software on the local computing environment. They provide data, applications and documents in a package tested in-house and deployed easily to another site. A further step on virtualisation is utilising cloud servers, ensuring the computational resources demanded by model runs are available in the cloud space. This paper shows the education activity in the OpenIFS programme with some examples.</p

Annotation of two large contiguous regions from the Haemonchus contortus genome using RNA-seq and comparative analysis with Caenorhabditis elegans

The genomes of numerous parasitic nematodes are currently being sequenced, but their complexity and size, together with high levels of intra-specific sequence variation and a lack of reference genomes, makes their assembly and annotation a challenging task. Haemonchus contortus is an economically significant parasite of livestock that is widely used for basic research as well as for vaccine development and drug discovery. It is one of many medically and economically important parasites within the strongylid nematode group. This group of parasites has the closest phylogenetic relationship with the model organism Caenorhabditis elegans, making comparative analysis a potentially powerful tool for genome annotation and functional studies. To investigate this hypothesis, we sequenced two contiguous fragments from the H. contortus genome and undertook detailed annotation and comparative analysis with C. elegans. The adult H. contortus transcriptome was sequenced using an Illumina platform and RNA-seq was used to annotate a 409 kb overlapping BAC tiling path relating to the X chromosome and a 181 kb BAC insert relating to chromosome I. In total, 40 genes and 12 putative transposable elements were identified. 97.5% of the annotated genes had detectable homologues in C. elegans of which 60% had putative orthologues, significantly higher than previous analyses based on EST analysis. Gene density appears to be less in H. contortus than in C. elegans, with annotated H. contortus genes being an average of two-to-three times larger than their putative C. elegans orthologues due to a greater intron number and size. Synteny appears high but gene order is generally poorly conserved, although areas of conserved microsynteny are apparent. C. elegans operons appear to be partially conserved in H. contortus. Our findings suggest that a combination of RNA-seq and comparative analysis with C. elegans is a powerful approach for the annotation and analysis of strongylid nematode genomes

Podoplanin drives dedifferentiation and amoeboid invasion of melanoma

Melanoma is an aggressive skin cancer developing from melanocytes, frequently resulting in metastatic disease. Melanoma cells utilize amoeboid migration as mode of local invasion. Amoeboid invasion is characterized by rounded cell morphology and high actomyosin contractility driven by Rho GTPase signalling. Migrastatic drugs targeting actin polymerization and contractility are therefore a promising treatment option for metastatic melanoma. To predict amoeboid invasion and metastatic potential, biomarkers functionally linked to contractility pathways are needed. The glycoprotein podoplanin drives actomyosin contractility in lymphoid fibroblasts and is overexpressed in many cancers. We show that podoplanin enhances amoeboid invasion in melanoma. Podoplanin expression in murine melanoma drives rounded cell morphology, increasing motility, and invasion in vivo. Podoplanin expression is increased in a subset of dedifferentiated human melanoma, and in vitro is sufficient to upregulate melanoma-associated marker Pou3f2/Brn2. Together, our data define podoplanin as a functional biomarker for dedifferentiated invasive melanoma and a promising migrastatic therapeutic target