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  1. Mass spectrometry imaging (MSI) has primarily been applied in localizing biomolecules within biological matrices. Although well-suited, the application of MSI for comparing thousands of spatially defined spotted samples has been limited. One reason for this is a lack of suitable and accessible data processing tools for the analysis of large arrayed MSI sample sets. In this paper, the OpenMSI Arrayed Analysis Toolkit (OMAAT) is a software package that addresses the challenges of analyzing spatially defined samples in MSI data sets. OMAAT is written in Python and is integrated with OpenMSI (, a platform for storing, sharing, and analyzing MSI data.more » By using a web-based python notebook (Jupyter), OMAAT is accessible to anyone without programming experience yet allows experienced users to leverage all features. OMAAT was evaluated by analyzing an MSI data set of a high-throughput glycoside hydrolase activity screen comprising 384 samples arrayed onto a NIMS surface at a 450 μm spacing, decreasing analysis time >100-fold while maintaining robust spot-finding. The utility of OMAAT was demonstrated for screening metabolic activities of different sized soil particles, including hydrolysis of sugars, revealing a pattern of size dependent activities. Finally, these results introduce OMAAT as an effective toolkit for analyzing spatially defined samples in MSI. OMAAT runs on all major operating systems, and the source code can be obtained from the following GitHub repository:« less
  2. This article is a U.S. Government work and is in the public domain in the USA. Numerous studies have shown that atmospheric models with high horizontal resolution better represent the physics and statistics of precipitation in climate models. While it is abundantly clear from these studies that high-resolution increases the rate of extreme precipitation, it is not clear whether these added extreme events are “realistic”; whether they occur in simulations in response to the same forcings that drive similar events in reality. In order to understand whether increasing horizontal resolution results in improved model fidelity, a hindcast-based, multiresolution experimental designmore » has been conceived and implemented: the InitiaLIzed-ensemble, Analyze, and Develop (ILIAD) framework. The ILIAD framework allows direct comparison between observed and simulated weather events across multiple resolutions and assessment of the degree to which increased resolution improves the fidelity of extremes. Analysis of 5 years of daily 5 day hindcasts with the Community Earth System Model at horizontal resolutions of 220, 110, and 28 km shows that: (1) these hindcasts reproduce the resolution-dependent increase of extreme precipitation that has been identified in longer-duration simulations, (2) the correspondence between simulated and observed extreme precipitation improves as resolution increases; and (3) this increase in extremes and precipitation fidelity comes entirely from resolved-scale precipitation. Evidence is presented that this resolution-dependent increase in precipitation intensity can be explained by the theory of Rauscher et al. (), which states that precipitation intensifies at high resolution due to an interaction between the emergent scaling (spectral) properties of the wind field and the constraint of fluid continuity.« less
  3. We have developed a high-throughput graphics processing units (GPU) code that can characterize a large database of crystalline porous materials. In our algorithm, the GPU is utilized to accelerate energy grid calculations where the grid values represent interactions (i.e., Lennard-Jones + Coulomb potentials) between gas molecules (i.e., CHmore » $$_{4}$$ and CO$$_{2}$$) and material's framework atoms. Using a parallel flood fill CPU algorithm, inaccessible regions inside the framework structures are identified and blocked based on their energy profiles. Finally, we compute the Henry coefficients and heats of adsorption through statistical Widom insertion Monte Carlo moves in the domain restricted to the accessible space. The code offers significant speedup over a single core CPU code and allows us to characterize a set of porous materials at least an order of magnitude larger than ones considered in earlier studies. For structures selected from such a prescreening algorithm, full adsorption isotherms can be calculated by conducting multiple grand canonical Monte Carlo simulations concurrently within the GPU.« less
  4. The additional computing power offered by the planned exascale facilities could be transformational across the spectrum of plasma and fusion research — provided that the new architectures can be efficiently applied to our problem space. The collaboration that will be required to succeed should be viewed as an opportunity to identify and exploit cross-disciplinary synergies. To assess the opportunities and requirements as part of the development of an overall strategy for computing in the exascale era, the Exascale Requirements Review meeting of the Fusion Energy Sciences (FES) community was convened January 27–29, 2016, with participation from a broad range ofmore » fusion and plasma scientists, specialists in applied mathematics and computer science, and representatives from the U.S. Department of Energy (DOE) and its major computing facilities. This report is a summary of that meeting and the preparatory activities for it and includes a wealth of detail to support the findings. Technical opportunities, requirements, and challenges are detailed in this report (and in the recent report on the Workshop on Integrated Simulation). Science applications are described, along with mathematical and computational enabling technologies. Also see for more information.« less
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"Rübel, Oliver"

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