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Modeling of Nanodusty Plasmas

Abstract: 

Modeling of Nanodusty Plasmas

These researchers are developing computational models of gas plasmas in which nanoparticles nucleate and grow. Their main interest is in the types of plasmas used for industrial applications such as semiconductor processing and materials synthesis. The group's primary focus is on the development of numerical models to simulate the spatiotemporal evolution of such plasmas, including the nucleation, growth, charging and transport of nanoparticles, and the effect of the nanoparticle aerosol on the plasma behavior. They are improving a 1D model of a two-parallel plates capacitively-coupled RF plasma that has been developed in the group. The main goal is to tailor nanoparticle size and flux to the substrate located at the bottom electrode. Experiments are done at the LPICM group in Paris, France. In addition, this group collaborates with the Kushner group from the University of Michigan to develop a 2D model of a capacitively-coupled RF plasma used for the synthesis of silicon nanocrystals in which a mixture of Ar:SiH4 flows through a narrow quartz tube. 

A Research Spotlight about this group's work appeared on the MSI website in March 2014.

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Group name: 
girshick

Pediatric Hemiplegia: Synergistic Treatment Using RTMS and CIT

Abstract: 

Pediatric Hemiplegia: Synergistic Treatment Using RTMS and CIT

Paralysis following stroke stems not only from the loss of neurons killed by the stroke but also from the loss of neurons lying dormant in the stroke hemisphere. One of the reasons viable neurons become dormant (down-regulated) is because of excessive interhemispheric inhibition imposed on them from the nonstroke hemisphere. Suppression of the source of this excessive interhemispheric inhibition can be achieved with the noninvasive method called repetitive transcranial magnetic stimulation (rTMS).

The specific aims of this study are to determine the efficacy, mechanism, and safety of a series of five treatments of 6-Hz primed low-frequency rTMS applied to nonstroke hemisphere and combined with motor learning training to promote recovery of the paretic hand. Forty subjects with stroke will be randomly assigned to one of four treatment groups; rTMS-only, Track-only, rTMS-sham, and rTMS-combined. The hypotheses are: the rTMS/combined group will show the greatest improvements in hand function; and the rTMS/combined group will show the greatest improvements in cortical excitability using paired-pulse TMS testing and in brain reorganization measured with resting state functional MRI (rfMRI) and diffusion tensor imaging (DTI). Computationally intensive tasks, including pre- and post-processing of these imaging data, require the supercomputers in order to progress the work in a reasonable time frame. 

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Group name: 
careyj

Genomics, Metagenomics, and Transcriptomics of Fungal Pathogens of Invertebrates

Abstract: 

Genomics, Metagenomics, and Transcriptomics of Fungal Pathogens of Invertebrates

Using a combination of next generation sequencing, phylogenomics, genetics, and natural products chemistry, the Bushley lab examines the evolution, diversity, and functions of fungal secondary metabolites. Current research projects utilizing MSI resources include: 

  • A comparative population genomic study of the evolution of NRPS secondary metabolites among strains of the beetle pathogen and cyclosporin producing fungus Tolypocladium inflatum using PacBio sequencing
  • A comparative genomic and transcriptomic analysis of interactions of insect pathogenic and endophytic fungi with both plant and insect hosts
  • A metagenomics study of fungal pathogens of the  soybean cyst nematodes to elucidate patterns of distribution in natural and agricultural ecosystems and potential roles in mediating resistance to nematodes
  • Metagenomics analyses of tropical endophytic fungi of Papua New Guinea and potential anti-herbivore and anti-cancer activity.

These research projects utilize HPC computing for de-novo genome sequencing and assembly, RNA-Seq, network analysis, large-scale phylogenomic analyses, and population genotyping.

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Group name: 
bushleyk

Discover Evidence of Personalized Health Management to Improve Healthcare Outcomes

Abstract: 

Discover Evidence of Personalized Health Management to Improve Healthcare Outcomes

For most medical problems, clinical (patient) heterogeneity influences treatment efficacy and results in variations in outcome in one-treatment-fits-all settings. However, an opportunity exists to improve outcomes while reducing costs using currently existing treatments when we understand how clinical heterogeneity influences treatment efficacy and how much of a difference exists among treatment options. Knowledge of how to personalize treatment to account for this clinical heterogeneity is the key to optimizing outcome and improving treatment efficiency.

Projects by this research group use this opportunity to improve healthcare outcomes, whose evidence is extracted from electronic health records. These projects are:

  • Mining personalized Alzheimer's Disease treatment from data
  • Predicting a cognitive decline curve for Alzheimer disease
  • Using a data-mining approach to facilitate efficient use of nursing resources

In general, each project derives evidence of improved-outcome evidence associated with treatment options, patient characteristics, and interactions. They benefit largely from MSI computing resources.

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Group name: 
chic

Enhancing Scalability and Energy Efficiency in Extreme-Scale Parallel Systems Through Application-Aware Communication Reduction

Abstract: 

Enhancing Scalability and Energy Efficiency in Extreme-Scale Parallel Systems Through Application-Aware Communication Reduction

Accesses to shared data should be synchronized to guarantee correct execution of parallel programs. Synchronization dictates a total or partial order on parallel tasks of execution. Since each synchronization point represents a point of serialization, synchronization can easily hurt scalability of parallel programs. To improve scalability in the face of inevitable synchronization, these researchers propose to relax synchronization. The idea is to eliminate a subset of the synchronization points, and to exploit the implicit noise tolerance of an important class of the future parallel applications – (R)ecognition, (M)ining, and (S)ynthesis, in mitigating relaxation-induced atomicity violations or data races. This project explores how relaxation can improve the scalability of parallel programs. Relaxation can enhance scalability as long as the relaxation-induced degradation in the accuracy of computing remains at acceptable levels. Accordingly, the researchers start with exploration of the trade-off space of accuracy degradation vs. speed-up.

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Group name: 
karpuzcu

Electronic Structure Calculations of Organic Reaction Mechanisms

Abstract: 

Electronic Structure Calculations of Organic Reaction Mechanisms

The hydroxyl radical (OH) is the most important oxidant in the lower atmosphere, or troposphere. Computational research in the past decade, conducted in part by this lab, has begun to elucidate pathways for OH formation that do not require the direct participation of photons. Many of these pathways involve the generation and decomposition of hydroperoxides, and can account for current deficiencies in regional atmospheric chemistry models. In 2015, the Kuwata lab used MSI resources to address the reactivity of an atmospherically relevant hydroperoxide, the vinyl hydroperoxide formed in alkene ozonolysis. In 2016, MSI resources will be used to treat a wider set of possible vinyl hydroperoxide reactions. The researchers are especially interested in the molecules derived from the ozonolysis of isoprene because isoprene is the most abundant unsaturated hydrocarbon in the lower atmosphere. Their predictions for these reactions could therefore have a huge impact on the understanding of atmospheric chemistry. In particular, if researchers predict significant yields of stable alcohols, this would lower the predicted OH yield of isoprene ozonolysis. The resulting deficit in the OH atmospheric “budget” would drive a search for additional OH sources.

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Group name: 
kuwatak0

Solar Torsional Oscillation in the Presence of Convection

Abstract: 

Solar Torsional Oscillation in the Presence of Convection

The torsional oscillation is a perturbation to the differential rotation in the convection zone of the sun that is spatially correlated with sunspot activity. Previous work has examined conditions necessary for the torsional oscillation to propagate through the convection zone using mean-field models with parameterized convection. This project examines the propagation behavior using an axisymmetric magnetohydrodynamic model utilizing explicit convection. Specifically, stationary perturbations will be generated at three different latitudes to provide a direct comparison to previous work. Further, perturbations traveling from a latitude of 45° both poleward and equatorward will be used to assess the effect of motion on the propagation. The resources at MSI are necessary because the simulations are very large. The grid contains 1,500 nodes, and three variables must be computed at each node. Each simulation will last for several million time steps. The code requires the use of an Intel Fortran compiler and MPI.

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Group name: 
moskowit

Magnetoencephalographic Studies of Motor Uncertainty in Health and Disease

Abstract: 

Magnetoencephalographic Studies of Motor Uncertainty in Health and Disease

These researchers have designed and carried out experiments with human participants that focus on reaching (using a joystick) to targets situated at diverse spatial locations while systematically varying the amount of information available about the possible location of the target's appearance during a cueing period. The brain activity of participants was recorded during these tasks using magnetoencephalography (MEG) - a technique that records magnetic activity in the brain with millisecond resolution at femtotesla intensities.

The researchers are currently using statistical methods that include discriminant analysis and multiple linear regression as well as signal processing metrics such as a variety of Phase Locking Indexes to optimally correlate the MEG signal as it relates to the direction of the upcoming target and the amount of uncertainty about its location. They thus hope to be able to better understand the process by which alternative motor plans are represented in the brain and how ultimately one of them is selected. They use MATLAB to carry out their analyses. Given the computationally intensive nature of these analyses (e.g. discriminant analyses run over sliding windows across hundreds of channels per subject, PLIs calculated across thousand of voxels per subject), the use of MSI resources should help shorten the considerable amount of time required, while also allowing the researchers to rapidly interrogate the data in a variety of different ways.

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Group name: 
pellizze

Analysis of Colonic Bacterial Populations; MicroRNA Pathway Analysis

Abstract: 

Analysis of Colonic Bacterial Populations; MicroRNA Pathway Analysis

Examining bacteria populations within the large intestine of mammals (the microbiome) has become of tremendous interest. These researchers focus on how different dietary treatments affect such populations. They are currently examining the effect of amount of dietary fat and of types of dietary fiber influence such populations, and will soon begin another project examining how polylactose, a potential new prebiotic, may affect the microbiome. MSI's computing resources are extremely important in analyzing the bacterial DNA sequence data obtained from the University of Minnesota Genomics Center that are used to identify the genus and species of bacteria present in the microbiome.

A second area of interest is understanding what changes occur in different species of microRNA (miRNA) in the colonic mucosa of carcinogen-treated animals exposed to different dietary interventions, and how these changes may influence different metabolic pathways related to colon cancer. This project uses Integrated Pathway Analysis software available through MSI.

Both of these activities will help further our understanding how diet can reduce colon cancer risk, and by what mechanism this may occur.

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Group name: 
gallaher

Antimicrobial Peptides and Autoimmune Disease

Abstract: 

Antimicrobial Peptides and Autoimmune Disease

The Sjögren’s Syndrome Knowledge Base (SSKB) is a resource for Sjögren’s syndrome research. The foundation for SSKB is a database of genes and proteins associated with Sjögren’s syndrome extracted from PubMed. The foundational database was established using the text-mining program EBIMed to query the Pubmed database, using the search term "Sjogren's Syndrome" restricted to "MeshHeadingsList."

The initial search in 2007 resulted in a selection of 7,733 abstracts and 1,293 potential genes/proteins. The abstracts were manually evaluated to remove duplicates and false-positives, resulting in a preliminary database of about 900 protein names and associated genes. In the case of older publications, where gene names were not readily identifiable, gene names were assigned based on in depth evaluation of the protein name context and available gene data in public databases, including Entrez and Uniprot. The data is continually updated and manually annotated to include new publications and data relating to the genes in the SSKB.

In a second project, microbiome data are collected by 16S rRNA sequencing of microbial samples from mouse and human anatomical sites. Data storage is requested for large data sets. Analysis is conducted in collaboration with the laboratory of Dan Knights (Computer Science and Engineering).

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Group name: 
gorrsu

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