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At least 595 records · Page 33

University of Oklahoma - High Energy Physics (Final Report)

The High Energy Physics program at the University of Oklahoma, Pat Skubic, Principal Investigator, is attempting to understand nature at the deepest level using the most advanced experimental and theoretical tools. The four experimental faculty, Brad Abbott, Phil Gutierrez, Pat Skubic, and Mike Strauss, together with post-doctoral associates and graduate students, are finishing their work as part of the DØ collaboration at Fermilab, and increasingly focusing their investigations at the Large Hadron Collidor (LHC) as part of the ATLAS Collaboration. Work at the LHC has become even more exciting with the recent discovery by ATLAS and the other collaboration, CMS, of the long-sought Higgs boson, which plays a key role in generating masses for the elementary constituents of matter. Work of the OUHEP group has been in the three areas of hardware, software, and analysis. Now that the Higgs boson has been discovered, completing the Standard Model of fundamental physics, new efforts will focus on finding hints of physics beyond the standard model, such as supersymmetry. The OUHEP theory group (Kim Milton, PI) also consists of four faculty members, Howie Baer, Chung Kao, Kim Milton, and Yun Wang, and associated students and postdocs. They are involved in understanding fundamental issues in formulating theories of the microworld, and in proposing models that carry us past the Standard Model, which is an incomplete description of nature. They therefore work in close concert with their experimental colleagues. One also can study fundamental physics by looking at the large scale structure of the universe; in particular the "dark energy" that seems to be causing the universe to expand at an accelerating rate, effectively makes up about 3/4 of the energy in the universe, and yet is totally unidentified. Dark energy and dark matter, which together account for nearly all of the energy in the universe, are an important probe of fundamental physics at the very shortest distances, or at the very highest energies. The outcomes of the group's combined experimental and theoretical research will be an improved understanding of nature, at the highest energies reachable, from which applications to technological innovation will surely result, as they always have from such studies in the past.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The 2019 Nonlinear Mechanics and Dynamics Research Institute

The 2019 Nonlinear Mechanics and Dynamics (NOMAD) Research Institute was successfully held from June 17 to August 1, 2019. NOMAD brings together participants with diverse technical backgrounds to work in small teams to cultivate new ideas and approaches in engineering mechanics and dynamics research. NOMAD provides an opportunity for researchers especially early career researchers - to develop lasting collaborations that go beyond what can be established from the limited interactions at their institutions or at annual conferences. A total of 20 students came to Albuquerque, New Mexico to participate in the seven-week long program held at the Mechanical Engineering building on the University of New Mexico campus. The students collaborated on one of seven research projects that were developed by various mentors from Sandia National Laboratories, the University of New Mexico, and academic institutions. In addition to the research activities, the students attended weekly technical seminars, various tours, and socialized at various off-hour events including an Albuquerque Isotopes baseball game. At the end of the summer, the students gave a final technical presentation on their research findings. Many of the research discoveries made at NOMAD are published as proceedings at technical conferences and have direct alignment with the critical mission work performed at Sandia.

42 ENGINEERING↗

P-Mart: Interactive Analysis of Ion Abundance Global Proteomics Data

The use of mass-spectrometry-based techniques for global protein profiling of biomedical or environmental experiments has become a major focus in research centered on biomarker discovery; however, one of the most important issues recently highlighted in the new era of omics data generation is the ability to perform analyses in a robust and reproducible manner. This has been hypothesized to be one of the issues hindering the ability of clinical proteomics to successfully identify clinical diagnostic and prognostic biomarkers of disease. P-Mart (https://pmart.labworks.org) is an interactive web-based software environment that enables domain scientists to perform quality-control processing, statistics, and exploration of large-complex proteomics data sets without requiring statistical programming. P-Mart is developed in a manner that allows researchers to perform analyses via a series of modules, explore the results using interactive visualization, and finalize the analyses with a collection of output files documenting all stages of the analysis and a report to allow reproduction of the analysis.

59 BASIC BIOLOGICAL SCIENCES↗

MtrA modulates Mycobacterium tuberculosis cell division in host microenvironments to mediate intrinsic resistance and drug tolerance

The success of Mycobacterium tuberculosis (Mtb) is largely attributed to its ability to physiologically adapt and withstand diverse localized stresses within host microenvironments. Here, we present a data-driven model (EGRIN 2.0) that captures the dynamic interplay of environmental cues and genome-encoded regulatory programs in Mtb. Analysis of EGRIN 2.0 shows how modulation of the MtrAB two-component signaling system tunes Mtb growth in response to related host microenvironmental cues. Disruption of MtrAB by tunable CRISPR interference confirms that the signaling system regulates multiple peptidoglycan hydrolases, among other targets, that are important for cell division. Further, MtrA decreases the effectiveness of antibiotics by mechanisms of both intrinsic resistance and drug tolerance. Together, the model-enabled dissection of complex MtrA regulation highlights its importance as a drug target and illustrates how EGRIN 2.0 facilitates discovery and mechanistic characterization of Mtb adaptation to specific host microenvironments within the host.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly

Like all higher organisms, plants have evolved in the context of a microbial world, shaping both their evolution and their contemporary ecology. Interactions between plant roots and soil microorganisms are critical for plant fitness in natural environments. Given this co-evolution and the pivotal importance of plant–microbial interactions, it has been hypothesized, and a growing body of literature suggests, that plants may regulate the composition of their rhizosphere to promote the growth of microorganisms that improve plant fitness in a given ecosystem. In this paper, using a combination of comparative genomics and exometabolomics, we show that pre-programmed developmental processes in plants (Avena barbata) result in consistent patterns in the chemical composition of root exudates. This chemical succession in the rhizosphere interacts with microbial metabolite substrate preferences that are predictable from genome sequences. Specifically, we observed a preference by rhizosphere bacteria for consumption of aromatic organic acids exuded by plants (nicotinic, shikimic, salicylic, cinnamic and indole-3-acetic). The combination of these plant exudation traits and microbial substrate uptake traits interact to yield the patterns of microbial community assembly observed in the rhizosphere of an annual grass. Finally, this discovery provides a mechanistic underpinning for the process of rhizosphere microbial community assembly and provides an attractive direction for the manipulation of the rhizosphere microbiome for beneficial outcomes.

54 ENVIRONMENTAL SCIENCES↗

Parallel processing of filtered queries in attributed semantic graphs

Execution of complex analytic queries on massive semantic graphs is a challenging problem in big-data analytics that requires high-performance parallel computing. In a semantic graph, vertices and edges carry attributes of various types and the analytic queries typically depend on the values of these attributes. Thus, the computation must view the graph through a filter that passes only those individual vertices and edges of interest. Previous investigations have developed Knowledge Discovery Toolbox (KDT), a sophisticated Python library for parallel graph computations. In KDT, the user can write custom graph algorithms by specifying operations between edges and vertices ( semiring operations ). The user can also customize existing graph algorithms by writing filters. While the high-level language for this customization enables domain scientists to productively express their graph analytics requirements, the customized queries perform poorly due to the overhead of having to call into the Python virtual machine for each vertex and edge. In this work, we use the Selective Embedded Just-In-Time Specialization (SEJITS) approach to automatically translate semiring operations and filters defined by programmers into a lower-level efficiency language, bypassing the upcall into Python. We evaluate our approach by comparing it with the high-performance Combinatorial BLAS engine and show that our approach combines the benefits of programming in a high-level language with executing in a low-level parallel environment. We increase the system's flexibility by developing techniques that provide users with the ability to define new vertex and edge types from Python. We also present a new Roofline model for graph traversals and show that we achieve performance that is significantly closer to the bounds suggested by the Roofline. Finally, to further understand the complex interaction with the underlying architecture, we present an analysis using performance counters that quantifies the improvement in hardware behavior in the context our SEJITS methodology. Comprehensively, we demonstrate the first known solution to the problem of obtaining high performance from a productivity language when applying graph algorithms selectively on semantic graphs with hundreds of millions of edges and scaling to thousands of processors for graphs.

97 MATHEMATICS AND COMPUTING↗

Column-by-column observation of dislocation motion in CdTe: Dynamic scanning transmission electron microscopy

The dynamics of partial dislocations in CdTe have been observed at the atomic scale using aberration-corrected scanning transmission electron microscopy (STEM), allowing the mobility of different dislocations to be directly compared: Cd-core Shockley partial dislocations are more mobile than Te-core partials, and dislocation cores with unpaired columns have higher mobility than those without unpaired columns. The dynamic imaging also provides insight into the process by which the dislocations glide. Dislocations with dangling bonds on unpaired columns are found to be more mobile because the dangling bonds mediate the bond exchanges required for the dislocations to move. Furthermore, a screw dislocation has been resolved to dissociate into a Shockley partial-dislocation pair along two different directions, revealing a way for the screw dislocation to glide in the material. The results show that dynamic STEM imaging has the potential to uncover the details of dislocation motion not easily accessible by other means. This research was sponsored by the U.S. DOE, Office of Energy Efficiency and Renewable Energy, Foundational Program to Advance Cell Efficiency (F-PACE, DE-FOA-0000492), (CL, YLW, NP, YFY, SJP), the Office of DOE-BES, Materials Science and Engineering Division (ARL), DOE Grant No. DE-FG02-09ER46554 (YYZ, STP), and a user project supported by ORNL's Center for Nanophase Materials Sciences (CNMS), which is also sponsored by DOE-BES. Supercomputer time was provided by the National Center for Supercomputing Applications which is supported by the DOE Office of Science under Contract No. DE-AC02-05CH11231, and the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant No. ACI-1053575. Chen Li [No. 656378] and Timothy Pennycook [No.655760] are currently funded by the European Union's Marie Sklodowska-Curie Grants.

36 MATERIALS SCIENCE↗

The 2017 Nonlinear Mechanics and Dynamics Research Institute.

The 2017 Nonlinear Mechanics and Dynamics (NOMAD) Research Institute was successfully held from June 19 to July 28, 2017. NOMAD seeks to bring together participants with diverse technical backgrounds to work in small teams to utilize an interactive approach to cultivate new ideas and approaches in engineering . NOMAD provides an opportunity for researchers - especially early career researchers - to develop lasting collaborations that go beyond what can be established from the limited interactions at their institutions or at annual conferences. A total of 17 students from around the world came to Albuquerque, New Mexico to participate in the six - week long program held at the University of New Mexico campus. The students collaborated on one of six research projects that were developed by various mentors from Sandia National Laboratories, academia, and other government laboratories. In addition to the research activities, the students attended weekly technical seminars, toured the National Museum of Nuclear Science & History, and socialized at various off - hour events including an Albuquerque Isotopes baseball game. At the end of the summer, the students gave a final technical presentation o n their research findings that was broadcast via Skype. Many of the research discoveries made at NOMAD are published as proceedings at technical conference s and have direct alignment with the critical mission work performed at Sandia.

42 ENGINEERING↗

Peptide programming of supramolecular vinylidene fluoride ferroelectric phases

Ferroelectric structures have spontaneous macroscopic polarization that can be inverted using external electric fields and have potential applications including information storage, energy transduction, ultralow-power nanoelectronics and biomedical devices. These functions would benefit from nanoscale control of ferroelectric structure, the ability to switch polarization with lower applied fields (low coercive field) and biocompatibility. Soft ferroelectrics based on poly(vinylidene fluoride) (PVDF) have a thermodynamically unstable ferroelectric phase in the homopolymer, complex semi-crystalline structures, and high coercive fields. Here, in this work, we report on ferroelectric materials formed by water-soluble molecules containing only six VDF repeating units covalently conjugated to a tetrapeptide, with the propensity to assemble into the β-sheet structures that are ubiquitous in proteins. This led to the discovery of ribbon-shaped ferroelectric supramolecular assemblies that are thermodynamically stable with their long axes parallel to both the preferred hydrogen-bonding direction of β-sheets and the bistable polar axes of VDF hexamers. Relative to a commonly used ferroelectric copolymer, the biomolecular assemblies exhibit a coercive field that is two orders of magnitude lower, as the result of supramolecular dynamics, and a similar level of remnant polarization, despite having a peptide content of 49 wt%. Furthermore, the Curie temperature of the assemblies is about 40 °C higher than that of a copolymer containing a similar amount of VDF. This supramolecular system was created using a biologically inspired strategy that is attractive in terms of sustainability and that could lead to new functions for soft ferroelectrics.

36 MATERIALS SCIENCE↗

Serendipitous discovery connects grandfather and granddaughter at the Lab 60 years apart A third-generation employee learns about Los Alamos family history

The Lab’s enduring mission work means staff like Cameron Townsend are one of many family members who have careers at LANL. Cameron is her family’s third generation to work at the Lab, starting with her great grandparents, followed by her grandparents (skipping her parents), and now including her and her husband. She didn’t know about her family history at the Lab until she started working here three years ago when a typical day on the job became a serendipitous window into her family’s long history with the Lab. Cameron, who is an architect in EPC-ES: Environmental Stewardship and helps manage the Lab’s historic buildings program, was given a drawing from 1960 to aid in an assessment. The drafter’s name on the sketch: Ron Turner, her grandfather.

99 GENERAL AND MISCELLANEOUS↗

Normality of I-V Measurements Using ML

There is an increased interest in instrument-computing ecosystems (ICEs) that support science workflows empowered by AI-automated experiments and computations in diverse areas. In particular, electrochemistry ICEs are promising for accelerating the design and discovery of electrochemical systems for energy storage and conversion, by automating significant parts of workflows that combine synthesis and characterization experiments with computations. They require the integration of flow controllers, solvent containers, pumps, fraction collectors, and potentiostats, all connected to an electrochemical cell, as illustrated in Fig. 1. These are specialized instruments with custom software that is not originally designed for network integration. We developed network and software solutions for electrochemical workflows that adapt system and instrument settings in real-time for multiple rounds of experiments. In particular, we developed Python wrappers for Application Programming Interfaces (APIs) of instrument commands and Pyro client-server modules that enable them to be executed from remote computers. The entire workflow is orchestrated by a Jupyter notebook running on a remote computer.

Al Najjar, Anees↗

My Green Car: The Adventure Begins (Ep. 1) – DOE Lab-Corps Video Series

One key difference between a great technology that stays in the lab and one that reaches the marketplace is customer interest. In Episode 1, the Lab’s MyGreenCar team gets ready to step outside the lab and test their technology’s value to consumers in a scientific way. What makes a new technology compelling enough to transition out of the lab and become a consumer product? That’s the question Berkeley Lab researchers Samveg Saxena, Nihar Shah, and Dana Hansen plus industry mentor Russell Carrington set out to answer for MyGreenCar, an app providing personalized fuel economy or electric vehicle range estimates for consumers researching new cars. DOE’s Lab-Corps program offered the technology team some answers. The EERE-funded program, based on the National Science Foundation’s I-Corps™ model for entrepreneurial training, provides tools and training to move energy-related inventions to the marketplace. During Lab-Corp’s intensive six-week session, technology teams interview 100 customer and value chain members to discover which potential products based on their technologies will have significant market pull. A six video series follows the MyGreenCar team’s Lab-Corps experience, from pre-training preparation with the Lab’s Innovation and Partnerships Office through the ups and downs of the customer discovery process. Will the app make it to the marketplace? You’ll just have to watch.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

My Green Car: Taking it to the Streets (Ep. 3) – DOE Lab-Corps Video Series

The researcher team finds enthusiastic consumers at familiar Berkeley hangouts. Then Industry Mentor Russell Carrington pushes the group to consider who will pay for the information the fuel economy app provides. What makes a new technology compelling enough to transition out of the lab and become a consumer product? That’s the question Berkeley Lab researchers Samveg Saxena, Nihar Shah, and Dana Hansen plus industry mentor Russell Carrington set out to answer for MyGreenCar, an app providing personalized fuel economy or electric vehicle range estimates for consumers researching new cars. DOE’s Lab-Corps program offered the technology team some answers. The EERE-funded program, based on the National Science Foundation’s I-Corps™ model for entrepreneurial training, provides tools and training to move energy-related inventions to the marketplace. During Lab-Corp’s intensive six-week session, technology teams interview 100 customer and value chain members to discover which potential products based on their technologies will have significant market pull. A six video series follows the MyGreenCar team’s Lab-Corps experience, from pre-training preparation with the Lab’s Innovation and Partnerships Office through the ups and downs of the customer discovery process. Will the app make it to the marketplace? You’ll just have to watch.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Computation Annual Report (2013)

Computation provides the intellectual electricity that helps make Lawrence Livermore National Laboratory (LLNL) a thriving and innovative research and development (R&D) institution. Our hardware, software, and discipline experts are integrated into almost every field of research at LLNL. Our in-house programs, software applications, and support initiatives help achieve mission-critical national-security objectives for the U.S. Departments of Energy, Homeland Security, and Defense, as well as other federal and state agencies. We deliver comprehensive support to a wide set of scientific disciplines that include physical sciences (materials modeling, fluid dynamics), biology (genomic sequencing), mathematics (scalable algorithms), and computer sciences (parallel processing, real-time control systems). This year, we have expanded our outreach with high performance computing (HPC) collaborations and made great strides in our capabilities related to mathematical computation, control systems, and computation infrastructure, many of them in concert with partners in industry and academia. The Computation workforce remains highly motivated and passionate about melding computational expertise with cutting-edge science and technology to enable breakthroughs. 2013 has once again proven that Computation provides the foundation and support that are essential for productivity at LLNL. Every scientific discipline and program leverages the tools and expertise provided by our staff. We remain at the forefront of HPC moving towards exascale and have developed the infrastructure and proficiency to make this an achievable goal. Our researchers repeatedly deliver outstanding research, attracting collaborations with the biggest names in academia and industry, while joining forces with other national laboratories to further push the bounds of what is scientifically possible. Computation’s mission is echoed by the President of the United States in his assertion that “our future depends on reaffirming America’s role as the world’s engine of scientific discovery and technological innovation.” Driven by this lofty goal, we employ our state-of-the-art computational capabilities to ensure LLNL’s position as a global science and technology leader.

97 MATHEMATICS AND COMPUTING↗

Two Luminous Post-AGB Stars in the Galactic Globular Cluster M19

We report the discovery of a luminous “yellow” post–asymptotic giant branch (PAGB) star in the globular cluster (GC) M19 (NGC 6273), identified during our uBVI survey of Galactic GCs. The uBVI photometric system is optimized to detect stars with large Balmer discontinuities, indicating very low surface gravities and high luminosities. The spectral energy distribution (SED) of the star is consistent with an effective temperature of about 6250 K and a surface gravity of logg=0.5. We use Gaia data to show that the star’s proper motion and radial velocity are consistent with cluster membership. One aim of our program is to test yellow PAGB stars as candidate Population II standard candles for determining extragalactic distances. We derive a visual absolute magnitude of M {sub V} = − 3.39 ± 0.09 for the M19 star. This is in close agreement with the M {sub V} values found for yellow PAGB stars in the GCs ω Cen, NGC 5986, and M79, indicating a very narrow luminosity function. These objects are 4 mag brighter than RR Lyrae variables, and they can largely avoid the issues of interstellar extinction that are a problem for Population I distance indicators. We also identified a second luminous PAGB object in M19, this one a hotter “UV-bright” star. Its SED is consistent with an effective temperature of about 11,750 K and logg=2.0. The two objects have nearly identical bolometric luminosities, logL/L{sub ⊙}=3.24 and 3.22, respectively.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Recent Results from CLEO

The CLEO Experiment, utilizing symmetric e{sup +}e{sup -} collisions provided by the Cornell Electron Storage Ring (CESR) in the charmonium and bottomonium regions, has a wide-reaching program in the study of hadrons and the strong force. This review briefly summarizes recent contributions the CLEO Collaboration has made in the study of: (1) light quark systems (rare decays of the {eta}'); (2) charmonium radiative decays to light quarks (J/{psi} and {psi}(2S) radiative decays to the {eta} and {eta}'); (3) mesons with open charm (the D and D{sub s} decay constants); (4) charmonium transitions (a multipole analysis of {psi}(2S) {yields} {gamma}{chi}{sub c1,2} and {chi}{sub c1,2} {yields} {gamma}J/{psi}); and (5) bottomonium spectroscopy (confirming evidence for the discovery of the {eta}{sub b}(1S)).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Atacama Cosmology Telescope: A Catalog of >4000 Sunyaev–Zel’dovich Galaxy Clusters

Here, we present a catalog of 4195 optically confirmed Sunyaev–Zel’dovich (SZ) selected galaxy clusters detected with signal-to-noise ratio >4 in 13,211 deg 2 of sky surveyed by the Atacama Cosmology Telescope (ACT). Cluster candidates were selected by applying a multifrequency matched filter to 98 and 150 GHz maps constructed from ACT observations obtained from 2008 to 2018 and confirmed using deep, wide-area optical surveys. The clusters span the redshift range 0.04 < z < 1.91 (median z = 0.52). The catalog contains 222 z > 1 clusters, and a total of 868 systems are new discoveries. Assuming an SZ signal versus mass-scaling relation calibrated from X-ray observations, the sample has a 90% completeness mass limit of M 500 c > 3.8 × 10 14 M ⊙ , evaluated at z = 0.5, for clusters detected at signal-to-noise ratio >5 in maps filtered at an angular scale of 2.'4. The survey has a large overlap with deep optical weak-lensing surveys that are being used to calibrate the SZ signal mass-scaling relation, such as the Dark Energy Survey (4566 deg 2 ), the Hyper Suprime-Cam Subaru Strategic Program (469 deg 2 ), and the Kilo Degree Survey (825 deg 2 ). We highlight some noteworthy objects in the sample, including potentially projected systems, clusters with strong lensing features, clusters with active central galaxies or star formation, and systems of multiple clusters that may be physically associated. The cluster catalog will be a useful resource for future cosmological analyses and studying the evolution of the intracluster medium and galaxies in massive clusters over the past 10 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗

Proteomics of ovarian cancer: functional insights and clinical applications

In the past decade, there has been an increasing interest in applying proteomics to assist in understanding the pathogenesis of ovarian cancer, elucidating the mechanism of drug resistance, and in the development of biomarkers for early detection of ovarian cancer. Although ovarian cancer is a spectrum of different diseases, the strategies for diagnosis and treatment with surgery and adjuvant therapy are similar across ovarian cancer types, increasing the general applicability of discoveries made through proteomics research. While proteomic experiments face many difficulties which slow the pace of clinical applications, recent advances in proteomic technology contribute significantly to the identification of aberrant proteins and networks which can serve as targets for biomarker development and individualized therapies. This review provides a summary of the literature on proteomics’ contributions to ovarian cancer research and highlights the current issues, future directions, and challenges. In conclusion, we propose that protein-level characterization of primary lesion in ovarian cancer can decipher the mystery of this disease, improve diagnostic tools, and lead to more effective screening programs.

59 BASIC BIOLOGICAL SCIENCES↗