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We report on complete genome sequences of five Pseudomonas soil isolates that are capable of metabolizing pentose sugars and aromatic monomers. These complete genome sequence data provide insight into possible alternative hosts for the production of biofuels and bio-based chemicals from lignocellulosic feedstock.
Neuromorphic computing is a non-von Neumann computing paradigm that performs computation by emulating the human brain. Neuromorphic systems are extremely energy-efficient and known to consume thousands of times less power than CPUs and GPUs. They have the potential to drive critical use cases such as autonomous vehicles, edge computing and internet of things in the future. For this reason, they are sought to be an indispensable part of the future computing landscape. Neuromorphic systems are mainly used for spike-based machine learning applications, although there are some non-machine learning applications in graph theory, differential equations, and spike-based simulations. These applications suggest that neuromorphic computing might be capable of general-purpose computing. However, general-purpose computability of neuromorphic computing has not been established yet. In this work, we prove that neuromorphic computing is Turing-complete and therefore capable of general-purpose computing. Specifically, we present a model of neuromorphic computing, with just two neuron parameters (threshold and leak), and two synaptic parameters (weight and delay). We devise neuromorphic circuits for computing all the μ-recursive functions (i.e., constant, successor and projection functions) and all the μ-recursive operators (i.e., composition, primitive recursion and minimization operators). Given that the μ-recursive functions and operators are precisely the ones that can be computed using a Turing machine, this work establishes the Turing-completeness of neuromorphic computing.
The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here) from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.
The design of photonic crystals with complete bandgaps has recently received considerable research focus for numerous reasons. This work leverages well-known nonlinear programming techniques to alleviate the non-smoothness caused by degenerate eigenvalues such that topology optimization problems can be solved with the open-source IPOPT software. A fully-vectorial plane wave expansion technique is used with an iterative eigensolver to efficiently predict dispersion properties of candidate structures. Nonlinear programming is employed to solve the inverse problem of designing three-dimensional periodic structures that exhibit complete two-dimensional (2D) and three-dimensional (3D) photonic bandgaps. Mesh refinement is performed to alleviate the large computational burden of designing and analyzing photonic crystals, and a periodic density filter is implemented to impose a minimum feature size for manufacturability considerations.
Large amounts of metagenomically-derived data are submitted to PATRIC for analysis. In the future, we expect even more jobs submitted to PATRIC will use metagenomic data. One in-demand use case is the extraction of near-complete draft genomes from assembled contigs of metagenomic origin. The PATRIC metagenome binning service utilizes the PATRIC database to furnish a large, diverse set of reference genomes. We provide a new service for supervised extraction and annotation of high-quality, near-complete genomes from metagenomically-derived contigs. Reference genomes are assigned to putative draft genome bins based on the presence of single-copy universal marker roles in the sample, and contigs are sorted into these bins by their similarity to reference genomes in PATRIC. Each set of binned contigs represents a draft genome that will be annotated by RASTtk in PATRIC. A structured-language binning report is provided containing quality measurements and taxonomic information about the contig bins. The PATRIC metagenome binning service emphasizes extraction of high-quality genomes for downstream analysis using other PATRIC tools and services. Due to its supervised nature, the binning service is not appropriate for mining novel or extremely low-coverage genomes from metagenomic samples.
In FY-12, the glass sample chips were filled by capillary action when they were dipped into the solutions being sampled either by hand or by the robotic sampling system. Issues were noted at the end of FY-12 that many of the channels were not completely filling (10-15% of the 10 μl channels and up to 40% of the 2 μl channels). Therefore, testing was conducted in FY-13 on filling the glass sample chips by use of a flow-through header (Table 1). Results indicate flow through filling is better at completely filling the chip channels, although some amount of solution can be lost when the chip is removed from the filling header.
Silver-exchanged mordenite (AgZ) has been identified as a potential sorbent for iodine present in the off-gas streams of a used nuclear fuel reprocessing facility. In such a facility, both elemental and organic forms of iodine are released from the dissolver in gaseous form. These species of iodine must be captured with high efficiency for a facility to avoid radioactive iodine release above regulatory limits in the gaseous effluent of the plant. Studies completed at Idaho National Laboratory (INL) examined the adsorption of organic iodine in the form of CH3I by AgZ. Upon breakthrough of the feed gas through the sorbent bed, elemental iodine was observed in the effluent stream, despite the fact that the only source of iodine in the system was the CH3I in the feed gas.1 This behavior does not appear to have been reported previously nor has it been independently confirmed. Thus, as a result of these prior studies, multiple knowledge gaps relating to the adsorption of CH3I by AgZ were identified, and a multi-lab test plan, including Oak Ridge National Laboratory (ORNL), INL, Pacific Northwest National Laboratory (PNNL), and Sandia National Laboratories, was formulated to address each in a systematic way.2 For this report, the scope of work for ORNL was further narrowed to three thin-bed experiments that would characterize CH3I adsorption onto AgZ in the presence of water, NO, and NO2. Completion of these three-thin bed experiments demonstrated that organic iodine in the form of CH3I was adsorbed by reduced silver mordenite (Ag0Z) to a 50% higher loading than that of I2 when adsorbed from a dry air stream. Adsorption curves suggest different adsorption mechanisms for I2 and CH3I. In the presence of NO and NO2 gas, the loading of CH3I onto Ag0Z is suppressed and may be reversible. Further, the presence of NO and NO2 gas appears to oxidize CH3I to I2; this is indicated by an adsorption curve similar to that of I2 on Ag0Z. Finally, the loss of organic iodine loading capacity by Ag0Z in the presence of NOx is unaffected by the addition of water vapor to the gas stream; no marked additional loss in capacity or retention was observed.
This report describes work on the successful completion of Milestone M2FT-14OR03100115 (8/20/2014) entitled, “Complete new adsorbent materials for marine testing to demonstrate 4.5 g-U/kg adsorbent”. This effort is part of the Seawater Uranium Recovery Program, sponsored by the U.S. Department of Energy, Office of Nuclear Energy, and involved the development of new adsorbent materials at the Oak Ridge National Laboratory (ORNL) and marine testing at the Pacific Northwest National Laboratory (PNNL). ORNL has recently developed two new families of fiber adsorbents that have demonstrated uranium adsorption capacities greater than 4.5 g-U/kg adsorbent after marine testing at PNNL. One adsorbent was synthesized by radiation-induced graft polymerization of itaconic acid and acrylonitrile onto high surface area polyethylene fibers followed by amidoximation and base conditioning. This fiber showed a capacity of 4.6 g-U/kg adsorbent in marine testing at PNNL. The second adsorbent was prepared by atom-transfer radical polymerization of t-butyl acrylate and acrylonitrile onto halide-functionalized round fibers followed by amidoximation and base hydrolysis. This fiber demonstrated uranium adsorption capacity of 5.4 g-U/kg adsorbent in marine testing at PNNL.
This report details the initial fabrication and delivery of two Fuel Cycle Research and Development (FCRD) irradiation capsules (ATFSC01 and ATFSC02), with associated quality assurance documentation, to the High Flux Isotope Reactor (HFIR). The capsules and documentation were delivered by September 30, 2015, thus meeting the deadline for milestone M3FT-15OR0202268. These irradiation experiments are testing silicon carbide composite tubes in order to obtain experimental validation of thermo-mechanical models of stress states in SiC cladding irradiated under a prototypic high heat flux. This document contains a copy of the completed capsule fabrication request sheets, which detail all constituent components, pertinent drawings, etc., along with a detailed summary of the capsule assembly process performed by the Thermal Hydraulics and Irradiation Engineering Group (THIEG) in the Reactor and Nuclear Systems Division (RNSD). A complete fabrication package record is maintained by the THIEG and is available upon request.
The Mie-Gruneisen equation of state (EOS) is frequently used in hydro simulations to model solids at high pressure (up to a few Mb). It is an incomplete EOS characterized by a Gr¨uneisen coefficient, = -V (@eP)V , that is a function of only V . Expressions are derived for isentropes and isotherms. This enables the extension to a complete EOS. Thermodynamic consistency requires that the specific heat is a function of a single scaled-temperature. A complete extension is uniquely determined by the temperature dependence of the specific heat at a fixed reference density. In addition we show that if the domain of the EOS extends to T = 0 and the specific heat vanishes on the zero isotherm then a function of only V is equivalent to a specific heat with a single temperature scale. If the EOS domain does not include the zero isotherm, then a specific heat with a single temperature scale leads to a generalization of the Mie-Gr¨uneisen EOS in which the pressure is linear in both the specific energy and the temperature. This corresponds to the limiting case of two temperature scales with one of the scales in the high temperature limit. Such an EOS has previously been used to model liquid nitromethane.
In this paper, we expand on previous validation work by Dixon and Hughes. That is, we present a more complete suite of validation results with respect to to the well-known Lockwood energy deposition experiment. Lockwood et al. measured energy deposition in materials including beryllium, carbon, aluminum, iron, copper, molybdenum, tantalum, and uranium, for both single- and multi-layer 1-D geometries. Source configurations included mono-energetic, mono-directional electron beams with energies of 0.05-MeV, 0.1-MeV, 0.3- MeV, 0.5-MeV, and 1-MeV, in both normal and off-normal angles of incidence. These experiments are particularly valuable for validating electron transport codes, because they are closely represented by simulating pencil beams incident on 1-D semi-infinite slabs with and without material interfaces. Herein, we include total energy deposition and energy deposition profiles for the single-layer experiments reported by Lockwood et al. (a more complete multi-layer validation will follow in another report).
The FY17Q2 milestone of the ECP/VTK-m project, which is the first milestone, includes the completion of design documents for the introduction of virtual methods into the VTK-m framework. Specifically, the ability from within the code of a device (e.g. GPU or Xeon Phi) to jump to a virtual method specified at run time. This change will enable us to drastically reduce the compile time and the executable code size for the VTK-m library. Our first design introduced the idea of adding virtual functions to classes that are used during algorithm execution. (Virtual methods were previously banned from the so called execution environment.) The design was straightforward. VTK-m already has the generic concepts of an “array handle” that provides a uniform interface to memory of different structures and an “array portal” that provides generic access to said memory. These array handles and portals use C++ templating to adjust them to different memory structures. This composition provides a powerful ability to adapt to data sources, but requires knowing static types. The proposed design creates a template specialization of an array portal that decorates another array handle while hiding its type. In this way we can wrap any type of static array handle and then feed it to a single compiled instance of a function. The second design focused on the mechanics of implementing virtual methods on parallel devices with a focus on CUDA. Our initial experiments on CUDA showed a very large overhead for using virtual C++ classes with virtual methods, the standard approach. Instead, we are using an alternate method provided by C that uses function pointers. With the completion of this milestone, we are able to move to the implementation of objects with virtual (like) methods. The upshot will be much faster compile times and much smaller library/executable sizes.
The FY17Q3 milestone of the ECP/VTK-m project includes the completion of a VTK-m filter that computes normal vectors for surfaces. Normal vectors are those that point perpendicular to the surface and are an important direction when rendering the surface. The implementation includes the parallel algorithm itself, a filter module to simplify integrating it into other software, and documentation in the VTK-m Users’ Guide. With the completion of this milestone, we are able to necessary information to rendering systems to provide appropriate shading of surfaces. This milestone also feeds into subsequent milestones that progressively improve the approximation of surface direction.
The FY17Q4 milestone of the ECP/VTK-m project includes the completion of a key-reduce scheduling mechanism, a spatial division algorithm, an algorithm for basic particle advection, and the computation of smoothed surface normals. With the completion of this milestone, we are able to, respectively, more easily group like elements (a common visualization algorithm operation), provide the fundamentals for geometric search structures, provide the fundamentals for many flow visualization algorithms, and provide more realistic rendering of surfaces approximated with facets.
This report provides an update on the completion of long-lead components procurement of new sodium materials test loop. The loop, designated as SMT-3, is a forced-convection sodium loop to be used for the evaluation of sodium compatibility of advanced Alloy 709 with emphasis on long term exposures of tensile, creep, fatigue, creep fatigue, and fracture toughness ASTM-size specimens in support of ASME Code qualification and NRC licensing. The report is a deliverable (Level 4) in FY18 (M4NT-18AN050503013), under the Work Package NT-18AN05050301, “A709 Sodium Compatibility” performed by Argonne National Laboratory (ANL), as part of the Advanced Materials Program for the Advanced Reactor Technology. This work package enables the development of advanced structural materials by providing corrosion, microstructure, and mechanical property data from the standpoint of sodium compatibility of advanced structural alloys. The first sodium loop (SMT-1) with a single tank was constructed in 2011 at ANL and has been in operation for exposure of subsize sheet specimens of advanced alloys at a single temperature. The second sodium loop with dual tanks (SMT-2) was constructed in 2013 and has been in operation for the exposure of subsize sheet specimens of advanced alloys at two different temperatures. The current loop (SMT-3) has been designed to incorporate sufficient chamber capacity to expose a large number of ASTM-size specimens to evaluate the sodium effects on tensile, creep, fatigue, creep-fatigue, and fracture toughness properties, in support of ASME Code Qualification and USNRC Licensing. Three major long lead items were identified: 1) Selection and approval of location for the new loop and installation of the necessary infrastructure, such as transformer, power supply panels, and wiring, that is adequate for the long term operation of the loop, 2) Perform a detailed piping analysis that meets the ANL QA and Safety guidelines as well as complying with ASME Code requirements, and 3) Design and fabrication of the specimen exposure vessels that are capable of at least 42 tensile, creep, and fatigue specimens in each vessel and is compliant and compatible with ASME Code and the piping design analysis. The SMT-3 loop will be located in Building 206 adjacent to the currently operating SMT-2 loop. In addition, we have removed the aged power supply system in Building 206 and installed a new transformer, wiring, and power panels for the new loop. The preliminary loop design was sent to an outside vendor for a detailed piping analysis, to ensure compliance with the ASME Code guidelines. The piping design was completed in FY2017. The construction of components such as cold trap, economizers, piping arrangement etc. will be performed in the central shops at ANL. About 150 liters of sodium for the loop will be procured in early FY2018. The loop system is designed to circulate sodium through the sample tanks and he associated loop without an operator for an extended period of time. With the three sodium loops (i.e., single-tank, dual-tank and four–tank), materials can be tested at different sodium temperatures, and large tensile, creep, fatigue, creep-fatigue, and fracture toughness specimens can be exposed to sodium for extended periods of time and generate data on mechanical properties in support of ASME Code Qualification and USNRC Licensing of advanced Alloy 709 for use as a structural material in SFRs.
This work examines how we may cast machine learning within a complete Bayesian framework to quantify and suppress explanatory complexity from first principles. Our investigation into both the philosophy and mathematics of rational belief leads us to emphasize the critical role of Bayesian inference in learning well-justified predictions within a rigorous and complete extended logic. The Bayesian framework allows us to coherently account for evidence in the learned plausibility of potential explanations. As an extended logic, the Bayesian paradigm regards probability as a notion of degrees of truth. In order to satisfy critical properties of probability as a coherent measure, as well as maintain consistency with binary propositional logic, we arrive at Bayes' Theorem as the only justifiable mechanism to update our beliefs to account for empiracle evidence. Yet, in the machine learning paradigm, where explanations are unconstrained algorithmic abstractions, we arrive at a critical challenge: Bayesian inference requires prior belief. Conventional approaches fail to yield a consistent framework in which we could compare prior plausibility among the infinities of potential choices in learning architectures. The difficulty of articulating well-justified prior belief over abstract models is the provinence of memorization in traditional machine learning training practices. This becomes exceptionally problematic in the context of limited datasets, when we wish to learn justifiable predictions from only a small amount of data.
Department 00635, Performance Assurance, assessments reveal risks and opportunities for improvement Labs-wide. This assessment was conducted to identify opportunities for improving the Department 00635 Assessment Program. This evaluation was conducted to identify opportunities for improving the Center 00600 assessment process by reviewing the quality of assessments completed by Environment Safety and Health (ES&H) personnel in fiscal year (FY) 2018. Approximately 20 percent of the Center 00600 assessments completed in FY18 were reviewed. One assessment was selected from each Center 00600 department contingent on availability in the Assurance Information System (AIS).
The following report contains details on the drilling and completion of the new wells D-9-8#2 and D-9-9#2, as well as the recompletion work for the previously temporarily abandoned D-4-13 and D-4-14 wells. Each of the four wells will be used for observation activities for the SECARB Phase III Anthropogenic Test. A drilling and completion narrative and an as built description of the well including drawings and material specifications for the D-9- 8#2 and D-9-9#2 are outlined in this report. An outline of the recompletion procedure for the D-4-13 and D-4-14 wells is also included.