Supporting Documentation for "An Exploratory Data Mining Study of Re-entry Events: Foundations for Multi-Modality Sensing and Data Fusion"
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The field of microbiome research has evolved rapidly over the past few decades, and has become a topic of great scientific and public interest. As a result of this rapid growth in interest covering different fields, we are lacking a clear commonly agreed definition of the term ‘microbiome’. Moreover, a consensus on best practices in microbiome research is missing. Recently, a panel of international experts discussed the current gaps in the frame of the European-funded MicrobiomeSupport project. The meeting brought together about 40 leaders from diverse microbiome areas, while more than a hundred experts from all over the world took part in an online survey accompanying the workshop. This article excerpts the outcomes of the workshop and the corresponding online survey embedded in a short historical introduction and uture outlook. We propose a definition of microbiome based on the compact, clear and comprehensive description of the term provided by Whipps et al. in 1988, amended with a set of novel recommendations considering the latest technological developments and research findings. We clearly separate the terms microbiome and microbiota, and provide a comprehensive discussion considering the composition of microbiota, the heterogeneity and dynamics of microbiomes in time and space, the stability and resilience of microbial networks, the definition of core microbiomes and functionally relevant keystone species as well as co-evolutionary principles of microbe-host and inter-species interactions within the microbiome. These broad definitions together with the suggested unifying concepts will help to improve standardization of microbiome studies in the future, and could be the starting point for an integrated assessment of data resulting in a more rapid transfer of knowledge from basic science into practice.
This dataset contains 636,246 profile images of vehicles representing 13,963 unique vehicles. The data was collected by a set of roadside sensors over the course of three years. Each time a vehicle passed by one of the sensors, a series of images was collected. The images were processed to detect and localize each vehicle, and a license plate reader collocated with the sensor was used to provide a unique ID for the vehicle. Actual license plate numbers have been obfuscated by replacing with an arbitrary numerical ID for each vehicle. After localizing the vehicle in each image, the original RGB image was rotated, scaled, and shifted to produce a new RGB image of size 234x234 pixels such that the outermost two wheels are located at predetermined pixel locations in the image. In this way, all vehicle images are aligned to one another. This registration process occasionally results in a portion of certain vehicles being cutoff at the edges of the image. The dataset has been partitioned into two sets called training and validation. The two partitions no common vehicles, i.e., a vehicle present in one partition is guaranteed not to be present in the other. In this way, an algorithm can be validated against a set of new vehicles that were not seen during the training process. The training set contains 543,926 images from 64,440 vehicle passes representing 11,918 unique vehicles, while the validation set contains 92,320 images from 10,991 vehicle passes representing 2,045 unique vehicles. Vehicle images are organized by directories corresponding to unique vehicles. The file naming scheme is as follows: veh_{vehID}_tr_{passID}_{frameID}_{elevation}_{timeofday}.jpg where {vehID} is the vehicle ID (unique across the entire dataset), {passID} is an identifier for each tracked vehicle pass (unique across the entire dataset), {frameID} is the index of the frame within the given vehicle pass starting at 0, {elevation} is a two-letter string indicating whether the sensor was elevated (el) or at ground-level (gl), and {timeofday} is a two-letter string indicating whether the image was captured during daytime (dt) or nighttime (nt).
Model developed for Type-3 Wind Turbine Generators in EMT Simulator REINTEGRATE
AC Grid source for testing standalone components in REINTEGRATE
Modern quantum key distribution (QKD) network designs are based on sending photons from one node to another and require free-space or dedicated fiber optic cables between nodes. The purpose of this is to co-generate secret key material on both sides of the quantum channel. In addition to this quantum link, there are several insecure classical channels that allow QKD algorithms to exchange book-keeping information and send symmetrically encrypted data. The attenuation of photons transmitted through fiber becomes too high to practically generate key material over fiber at distances of more than 100 km. Free-space transmission through the atmosphere or the vacuum of space can reduce attenuation, but at the cost of system complexity and sensitivity to other impairments, such as weather. To extend the effective range of QKD networks, we present a method that combines QKD algorithms with post-quantum, homomorphic key-switching to allow multiple parties to effectively share secret key material over longer distances through semi-trusted relay nodes. We define how such a system should work for arbitrary network topologies and provide proofs that our scheme is both correct and secure. We assess the feasibility of this solution by building and evaluating two implementations based on lattice-based cryptography: learning with errors.
Most existing buildings have sub-optimal heating, ventilation, and air conditioning (HVAC) controls, resulting in wasted energy and occupant discomfort. Retro-commissioning (RCx) addresses many of these issues, but it is a lengthy and highly customized process. Limited capabilities of existing building automation system hardware restricts the scope of most RCx projects. Incentive programs consider building automation system (BAS) hardware retrofits to be high-capital investments and do not allow them in typical RCx programs. This paper describes work that the authors are leading to facilitate technical and market innovation in the BAS industry to unlock large savings in existing commercial buildings through deep retrofits of BAS hardware and software. California and New York research projects are demonstrating BAS retrofits leveraging the American Society of Heating, Refrigeration, and Air Conditioning Engineers’ (ASHRAE) new Guideline 36 high performance sequences of operation to achieve greater than 20 percent whole building energy savings, while saving costs and reducing risk through streamlined processes and standardization across BAS manufacturer product lines and across implementation practices. This paper describes market barriers that impede achieving deep savings from BAS retrofits in custom incentive and traditional RCx programs and presents a new maximum potential BAS retrofit model that addresses these barriers. The new model leverages the authors’ efforts in market enablement through open standards, BAS industry partnerships, and tools for cost-effective scaling that includes tools for project screening, savings calculations, and measurement and verification (M&V). This approach is widely applicable and will be ready for at-scale implementation within two years.
Since their introduction in 1929, Pauling’s five rules have been used by scientists from many disciplines to rationalize and predict stable arrangements of atoms and coordination polyhedra in crystalline solids; amorphous materials such as silicate glasses and melts; nanomaterials, poorly crystalline solids; aqueous cation and anion complexes; and sorption complexes at mineral-aqueous solution interfaces. The predictive power of these simple yet powerful rules was challenged recently by George et al. (2020), who performed a statistical analysis of the performance of Pauling’s five rules for about 5000 oxide crystal structures. They concluded that only 13% of the oxides satisfy the last four rules simultaneously and that the second rule has the most exceptions. They also found that Pauling’s first rule is satisfied for only 66% of the coordination environments tested and concluded that no simple rule linking ionic radius to coordination environment will be predictive due to the variable quality of univalent radii. We address these concerns and discuss quantum mechanical calculations that complement Pauling’s rules, particularly his first (radius sum and radius ratio rule) and second (electrostatic valence rule) rules. We also present a more realistic view of the bonded radii of atoms, derived by determining the local minimum in the electron density distribution measured along trajectories between bonded atoms known as bond paths, i.e., the bond critical point (rc). Electron density at the bond critical point is a quantum mechanical observable that correlates well with Pauling bond strength. Moreover, a metal atom in a polyhedron has as many bonded radii as it has bonded interactions, resulting in metal and O atoms that may not be spherical. O atoms, for example, are not spherical in many oxide-based crystal structures. Instead, the electron density of a bonded oxygen is often highly distorted or polarized, with its bonded radius decreasing systematically from ~1.38 Å when bonded to highly electropositive atoms like sodium to 0.64 Å when bonded to highly electronegative atoms like nitrogen. Bonded radii determined for metal atoms match the Shannon (1976) radii for more electropositive atoms, but the match decreases systematically as the electronegativities of the M atoms increase. As a result, significant departures from the radius ratio rule in the analysis by George et al. (2020) is not surprising. We offer a modified, more fundamental version of Pauling’s first rule and demonstrate that the second rule has a one-to-one connection between the electron density accumulated between the bonded atoms at the bond critical point and the Pauling bond strength of the bonded interaction. Pauling’s second rule implicitly assumes that bond strength is invariant with bond length for a given pair of bonded atoms. Many studies have since shown that this is not the case, and Brown and Shannon (1973) developed an equation and a set of parameters to describe the relation between bond length and bond strength, now redefined as bond valence to avoid confusion with Pauling bond-strength. Brown (1980) used the valence-sum rule, together with the path rule and the valence-matching principle, as the three axioms of bond-valence theory (BVT), a powerful method for understanding many otherwise elusive aspects of crystals and also their participation in dynamic processes. We show how a priori bond-valence calculations can predict unstrained bond-lengths and how bond-valence mapping can locate low-Z atoms in a crystal structure (e.g., Li) or examine possible diffusion pathways for atoms through crystal structures. In addition, we briefly discuss Pauling’s third, fourth, and fifth rules, the first two of which concern the sharing of polyhedron elements (edges and faces) and the common instability associated with structures in which a polyhedron shares an edge or face with another polyhedron and contains high-valence cations. The olivine [α-(MgxFe1–x)2SiO4] crystal structure is used to illustrate the distortions from hexagonal close-packing of O atoms caused by metal-metal repulsion across shared polyhedron edges. We conclude by discussing several applications of BVT to Earth materials, including the use of BVT to: (1) locate H+ ions in crystal structures, including the location of protons in the crystal structures of nominally anhydrous minerals in Earth’s mantle; (2) determine how strongly bonded (usually anionic) structural units interact with weakly bonded (usually cationic) interstitial complexes in complex uranyl-oxide and uranyl-oxysalt minerals using the valence-matching principle; (3) calculate Lewis acid strengths of cations and Lewis base strengths of anions; (4) determine how (H2O) groups can function as bond-valence transformers by dividing one bond into two bonds of half the bond valence; (5) help characterize products of sorption reactions of aqueous cations (e.g., Co2+ and Pb2+) and oxyanions [e.g., selenate (Se6+O4)2- and selenite (Se4+O3)2-] at mineral-aqueous solution interfaces and the important role of protons in these reactions; and (6) help characterize the local coordination environments of highly charged cations (e.g., Zr4+, Ti4+, U4+, U5+, and U6+) in silicate glasses and melts.
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This project sought to address the technical and economic barriers to carbon dioxide (CO 2 ) capture and utilization using microalgae. Specifically, a dual photobioreactor (PBR)/open raceway pond (ORP) cultivation system was evaluated with respect to capital and operational costs, productivity, and culture health, and compared to an ORP-only cultivation system. In the dual (or “hybrid”) system, a cyclic flow PBR was used to provide inoculum for two open raceway ponds after each harvest, with the hypothesis that this PBR + pond system should result in improved performance compared to traditional raceway ponds. Two other raceway ponds were operated conventionally as a control, the experiments being performed at Duke Energy’s East Bend Station in northern KY using coal-derived flue gas as the CO 2 source. Although algae productivity achieved was mediocre due to the fact that the experiments had to be performed late in the growing season when climatic conditions were not optimal for high growth, the hybrid cultivation system showed a higher level of algae productivity (statistically significant) compared to the traditional ponds. In order to realize the maximum value of the algal biomass produced, fractionation of the biomass was examined. Bioplastic compounding and material characterization was subsequently performed using three feed stocks: whole biomass, lipid-extracted biomass and the proteinaceous residue from full fractionation. In general, the whole and lipid-extracted biomass gave similar results in terms of the properties of the resulting bioplastics, while the proteinaceous residue showed promise for the production of a polybutylene adipate terephthalate (PBAT) blend. Finally, sustainability assessment of a putative biorefinery system was conducted, including techno-economic and life cycle impact assessment. Nine different production scenarios were considered, comprising combinations of the three different biomass growth architectures (ORP, PBR and dual PBR-ORP systems) coupled with three different algae biomass processing pathways (drying only, lipid extraction and fractionation). Results show that the minimum selling price of the bioplastic feed stock (BPFS) is within the realm of economic competition with prices as low as $970 USD tonne -1 . Additionally, life cycle impact assessment results indicate drastic improvements in performance of the produced BPFS, with reductions in greenhouse gas emissions ranging between 67 and 116% compared to a petroleum based plastic feedstock.
Non-Destructive Assay (NDA) instruments are a large component of nuclear material (NM) measurement at LANL. Nuclear Material Control and Accountability Group (SAFE-NMCA) personnel in the Safeguards Division are responsible for oversight of the instruments used for material accountability measurements. It is the responsibility of SAFE-NMCA to ensure that all instruments are operating as expected and can produce quality measurements to provide assurance that requirements of the DOE approved NMCA Plan are being met.
BEE will give ECP a tool that great simplifies the deployment of containerized workflows on the next generation of pre-exascale and exascale systems, as well as public and private clouds. BEE allows scientists to describe their workflow using the Common Workflow Language and then deploy that workflow across the entire spectrum of systems without having to learn the specifics of each container runtime, HPC resource manager, or cloud API. BEE also streamlines the curation and sharing of common workflows among the scientific community.
The direct numerical simulation (DNS) of the canonical wall-mounted unit cube subjected to two distinct incident velocity profiles is performed at a Reynolds number where the bulk flow characteristics are known to become relatively Reynolds number insensitive. The aim of this work is to highlight the sensitivity of such bluff-body flows to mean shear and to provide a representative set of data for such flow scenarios where common turbulence modeling techniques often fail. Simple boundary conditions and a small domain are selected to allow for cost-effective and easy comparisons for model development purposes. In addition to mean velocity profiles, select turbulence statistics are presented in detail. Further, the basic efficacy of eddy viscosity models is evaluated and found to be adequate only for the shear stress components for the bluff-body flows examined here. Other failure mechanisms for RANS are proposed.
PBX 9501 is a plastic bonded explosive composed of 95 wt % HMX and a binder; see [Gibbs and Popolato, 1980, pp. 109–119]. SURF is a reactive burn model for shock initiation and propagation of detonation waves. It has previously been calibrated for PBX 9501. Here the SURF model is recalibrated for PBX 9501; specifically, lot 730-010 at ρ = 1.837 g/cc 3 . The new calibration uses the Davis reactants and products EOS calibrated for the AWSD model [Aslam et al., 2020]. The burn rate in the shock initiation regime is fit to the Pop plot from 5 embedded gauge shock-to-detonation transition (SDT) experiments from [Gustavsen et al., 1999, see fig 12 and table 5]. In the propagation regime, the burn rate is fit to curvature effect data (detonation speed as function of front curvature); see [Aslam, 2007]. Also the burn parameters are adjusted to fit the gap-stick experiment [Hill et al., 2018]. Simulating the detonation wave speed in this experiment requires a model that is accurate for initiation with complex shock loading; in particular, a pressure decreasing gradient behind a curved lead shock. This is more difficult than calibrating to the standard SDT experiments which are 1-D and driven by a sustained shock. Simulations of the gap-stick experiment for PBX 9501 with the SURF model will be discussed in a subsequent report.
Modern manufacturing requires the use of many Commercial Off-The Shelf (COTS) tools and systems on the production floor. Wireless communications is prevalent in modern COTS devices. COTS equipment come with little information regarding what EXACTLY is in the equipment. Many vendors do not even have data for what is in their equipment – built to spec. Our industry has unique requirements and very few vendors design to meet our needs.
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Abstract not provided.