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At least 235 records · Page 13

Revisiting Five Years of CASMI Contests with EPA Identification Tools

Software applications for high resolution mass spectrometry (HRMS)-based non-targeted analysis (NTA) continue to enhance chemical identification capabilities. Given the variety of available applications, determining the most fit-for-purpose tools and workflows can be difficult. The Critical Assessment of Small Molecule Identification (CASMI) contests were initiated in 2012 to provide a means to evaluate compound identification tools on a standardized set of blinded tandem mass spectrometry (MS/MS) data. Five CASMI contests have resulted in recommendations, publications, and invaluable datasets for practitioners of HRMS-based screening studies. The US Environmental Protection Agency’s (EPA) CompTox Chemicals Dashboard is now recognized as a valuable resource for compound identification in NTA studies. However, this application was too new and immature in functionality to participate in the five previous CASMI contests. In this work, we performed compound identification on all five CASMI contest datasets using Dashboard tools and data in order to critically evaluate Dashboard performance relative to that of other applications. CASMI data was accessed via the CASMI webpage and processed for use in our spectral matching and identification workflow. Relative to applications used by former contest participants, our tools, data, and workflow performed well, placing more challenge compounds in the top five of ranked candidates than did the winners of three contest years and tying in a fourth. In addition, we conducted an in-depth review of the CASMI structure sets and made these reviewed sets available via the Dashboard. Our results suggest that Dashboard data and tools would enhance chemical identification capabilities for practitioners of HRMS-based NTA.

97 MATHEMATICS AND COMPUTING↗

Minimally Mutated HIV-1 Broadly Neutralizing Antibodies to Guide Reductionist Vaccine Design

An optimal HIV vaccine should induce broadly neutralizing antibodies (bnAbs) that neutralize diverse viral strains and subtypes. However, potent bnAbs develop in only a small fraction of HIV-infected individuals, all contain rare features such as extensive mutation, insertions, deletions, and/or long complementarity-determining regions, and some are polyreactive, casting doubt on whether bnAbs to HIV can be reliably induced by vaccination. We engineered two potent VRC01-class bnAbs that minimized rare features. According to a quantitative features frequency analysis, the set of features for one of these minimally mutated bnAbs compared favorably with all 68 HIV bnAbs analyzed and was similar to antibodies elicited by common vaccines. This same minimally mutated bnAb lacked polyreactivity in four different assays. We then divided the minimal mutations into spatial clusters and dissected the epitope components interacting with those clusters, by mutational and crystallographic analyses coupled with neutralization assays. Finally, by synthesizing available data, we developed a working-concept boosting strategy to select the mutation clusters in a logical order following a germline-targeting prime. We have thus developed potent HIV bnAbs that may be more tractable vaccine goals compared to existing bnAbs, and we have proposed a strategy to elicit them. This reductionist approach to vaccine design, guided by antibody and antigen structure, could be applied to design candidate vaccines for other HIV bnAbs or protective Abs against other pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

Fast Magnetic Reconnection: “Ideal” Tearing and the Hall Effect

One of the main questions in magnetic reconnection is the origin of triggering behavior with on/off properties that, once it is activated, accounts for the fast magnetic energy conversion to kinetic and thermal energies at the heart of explosive events in astrophysical and laboratory plasmas. Over the past decade, progress has been made on the initiation of fast reconnection via the plasmoid instability and what has been called “ideal” tearing, which sets in once current sheets thin to a critical inverse aspect ratio (a/L){sub c}. As shown by Pucci and Velli, at (a/L){sub c}∼S{sup −1/3}, the timescale for the instability to develop becomes of the order of the Alfvén time and independent of the Lundquist number (here defined in terms of current sheet length L). However, given the large values of S in natural plasmas, this transition might occur for thicknesses of the inner resistive singular layer that are comparable to the ion inertial length d {sub i}. When this occurs, Hall currents produce a three-dimensional quadrupole structure of the magnetic field, and the dispersive waves introduced by the Hall effect accelerate the instability. Here we present a linear study showing how the “ideal” tearing mode critical aspect ratio is modified when Hall effects are taken into account, including more general scaling laws of the growth rates in terms of sheet inverse aspect ratio: the critical inverse aspect ratio is amended to a/L≃(di/L){sup 0.29}(1/S){sup 0.19}, at which point the instability growth rate becomes Alfvénic and does not depend on either of the (small) parameters d{sub i}/L,1/S. We discuss the implications of this generalized triggering aspect ratio for recently developed phase diagrams of magnetic reconnection.

79 ASTRONOMY AND ASTROPHYSICS↗

Influence of Containment on Defects in GeSi Crystals

Crystals grown without being in contact with a container have superior quality to otherwise similar crystals grown in direct contact with a container, especially with respect to impurity incorporation, formation of dislocations, and residual stress in crystals. "Detached" or "dewetted" Bridgman growth is similar to regular Bridgman growth in that most of the melt is in contact with the crucible wall, but the crystal is separated from the wall by a small gap, typically of the order of 10(exp -5) m. A small meniscus bridges the gap between the top of the crystal and the wall. Key parameters involved in achieving detached growth are the contact angle between the melt and crucible and the pressure differential across the meniscus. Sessile drop measurements were used to determine the wetting angles of Ge(sub 1-x)Si(sub x) melts on a variety of substrates and found that the highest wetting angles were achieved with pyrolitic boron nitride (pBN). GeSi crystals have been repeatedly grown detached in pBN crucibles but only occasionally in crucibles with lower wetting angles. Experiments have been conducted to assess the effect of pressure differential across the meniscus in sealed crucibles. This was done by adjusting the temperature profile after partial melting of the starting material. In a separate set of experiments, the pressure was controlled by connecting the volume below the meniscus to a regulated gas supply. The experiments were in agreement with calculations which predicted that stable detachment will only occur in crucibles with a low wetting angle over a relatively narrow range of pressure differential. Detached-grown crystals exhibited superior structural quality as evidenced by measurements of etch pit density, synchrotron white beam X-ray topography and double axis X-ray diffraction.

Volz, M. P.↗

Introducing Tropical Geometric Approaches to Delay Tolerant Networking Optimization

Delay Tolerant Networking (DTN) is the standard approach to the networking of space systems with the goal of supporting the Solar System Internet (SSI). Current space networks have a small scale and often depend on rigorously scheduled (pre-determined) contact opportunities; this manual approach inhibits scalability. The goal of this paper is to recast these scheduling problems in order to apply the optimization machinery of tropical geometry. Contact opportunities in space are dependent on such factors as orbital mechanics and asset availability, which induce time-varying connectivity; indeed, end-to-end connectivity might never occur. Routing optimization within this structure is classically difficult and typically utilizes Dijkstra's algorithm as applied to contact graphs. Alternatively, we follow the successes of tropical geometry in train schedule optimization, job assignments, and even traditional networking, by extending this approach to this more general (i.e. disconnected) problem space. These successes imply tropical geometry provides a useful framework in the context of DTNs, starting with applications to queuing theory and long-haul links. Recently, tropical geometry has been applied to parametric path optimization on graphs with variable edge weights. In this work, we extend these advances to account for the problem of routing in a space network, and find that tropical geometry is well-suited to the challenges offered by this new setting, including contact schedules featuring probabilities. Our approach leverages the combinatorial nature of the problem to give feasible shortest path trees in the presence of variable channel conditions and latency, evolving topologies, and uncertainty inherent in space routing. We discuss our tropical approach to DTN for two Python implementations, a Verilog Tropical ALU implementation, tropical frameworks for other parametric graph problems, and solution stability. Lastly, a program for future work is included to illuminate the path ahead.

Delay Tolerant Networking↗

Conceptual Framework to Enable Early Warning of Relevant Phenomena (Emerging Phenomena and Big Data)

Graphs are commonly used to represent natural and man-made dynamic systems such as food webs, economic and social networks, gene regulation, and the internet. We describe a conceptual framework to enable early warning of relevant phenomena that is based on an artificial time-based, evolving network graph that can give rise to one or more recognizable structures. We propose to quantify the dynamics using the method of delays through Takens Theorem to produce another graph we call the Phase Graph. The Phase Graph enables us to quantify changes of the system that form a topology in phase space. Our proposed method is unique because it is based on dynamic system analysis that incorporates Takens Theorem, Graph Theory, and Franzosi-Pettini (F-P) theorem about topology and phase transitions. The F-P Theorem states that the necessary condition for phase transition is a change in the topology. By detecting a change in the topology that we represent as a set of M-order Phase Graphs, we conclude a corresponding change in the phase of the system. The onset of this phase change enables early warning of emerging relevant phenomena.

complexity↗

Parametric Flutter Analysis of the TCA Configuration and Recommendation for FFM Design and Scaling

The current HSR Aeroelasticity plan to design, build, and test a full span, free flying transonic flutter model in the TDT has many technical obstacles that must be overcome for a successful program. One technical obstacle is the determination of a suitable configuration and point in the sky to use in setting the scaling point for the ASE models program. Determining this configuration and point in the sky requires balancing several conflicting requirements, including model buildability, tunnel test safety, and the ability of the model to represent the flutter mechanisms of interest. As will be discussed in detail in subsequent sections, the current TCA design exhibits several flutter mechanisms of interest. It has been decided that the ASE models program will focus on the low frequency symmetric flutter mechanism, and will make no attempt to investigate high frequency flutter mechanisms. There are several reasons for this choice. First, it is believed that the high frequency flutter mechanisms are similar in nature to classical wing bending/torsion flutter, and therefore there is more confidence that this mechanism can be predicted using current techniques. The low frequency mode, on the other hand, is a highly coupled mechanism involving wing, body, tail, and engine motion which may be very difficult to predict. Second, the high frequency flutter modes result in very small weight penalties (several hundred pounds), while suppression of the low frequency mechanism inside the flight envelope causes thousands of pounds to be added to the structure. In order to successfully test the low frequency flutter mode of interest, a suitable starting configuration and point in the sky must be identified. The configuration and point in the sky must result in a wind tunnel model that (1) represents the low-frequency wing/body/engine/empennage flutter mechanisms that are unique to HSCT configurations, (2) flutters at an acceptably low frequency in the tunnel, (3) flutters at an acceptably low dynamic pressure in the tunnel, (4) allows sufficient weight for model buildability without inordinately high cost, and (5) has significant separation between the target flutter mechanism and other, potentially catastrophic, flutter mechanisms.

Baker, Myles↗

CoLoRe-2LPT: Lyman-$α$ mock catalogues for the validation of DESI cosmological analyses

The Lyman-$α$ (Ly$α$) forest has become a crucial probe for studying the large-scale structure of the universe at high redshift ($z > 2$), providing powerful constraints on Baryon Acoustic Oscillations (BAO) and the full-shape (FS) clustering of matter. As a key ingredient for upcoming BAO and FS analyses, we present a new generation of fast cosmological Ly$α$ mocks based on second-order Lagrangian perturbation theory (2LPT). These new mocks significantly improve upon previous log-normal approaches, both at accurately capturing small scale clustering and at recovering the non-linear broadening of the BAO peak. They are able to reproduce Ly$α$ statistics within $10\%$ of the latest DESI measurement; including the Ly$α$ bias and the redshift-space distortion $β$ parameter, mean transmitted flux, and 1D power spectrum. The corresponding quasar (QSO) clustering is also improved with respect to previous approaches, calibrated against high-resolution Abacus simulations, recovering the observational QSO linear bias to less than $5\%$ and improving redshift-space distortions via 2LPT velocities and the addition of Fingers-of-God effects. Furthermore, these mocks incorporate high column density systems and metal lines, allowing us to explore the effects and systematics induced by these astrophysical contaminants. This new set of mocks has been key for enhancing the modeling and validation of the DESI DR2 Ly$α$ full shape cosmological analysis. This work provides a physically motivated and computationally efficient tool for simulating current and next-generation Ly$α$ surveys and validating FS and BAO analysis.

Bernal, M.F. Ruiz-Herrera [Madrid, CIEMAT] (ORCID:↗

IMPACT OF GRAIN EVOLUTION ON THE CHEMICAL STRUCTURE OF PROTOPLANETARY DISKS

We study the impact of dust evolution in a protoplanetary disk (PPD) around a T Tauri star on the disk's chemical composition. For the first time, we utilize a comprehensive model of dust evolution, which includes growth, fragmentation, and sedimentation. Specific attention is paid to the influence of grain evolution on the penetration of the UV field in the disk. A chemical model that includes a comprehensive set of gas-phase and grain-surface chemical reactions is used to simulate the chemical structure of the disk. The main effect of grain evolution on the disk's chemical composition comes from sedimentation and, to a lesser degree, from reduction of the total grain-surface area. The net effect of grain growth is suppressed by the fragmentation process which maintains a population of small grains, dominating the total grain surface area. We consider three models of dust properties. In model GS, both growth and sedimentation are taken into account. In models A5 and A4, all grains are assumed to be the same size (10{sup -5} cm and 10{sup -4} cm, respectively) with a constant gas-to-dust mass ratio of 100. As in previous studies, the 'three-layer' pattern (cold midplane, warm molecular layer, and hot atmosphere) in the disk-chemical structure is preserved in all models, but shifted closer to the midplane in models with increased grain size (GS and A4). Unlike other similar studies, we find that in models GS and A4, the column densities of most gas-phase species are enhanced by 1-3 orders of magnitude relative to those in a model with pristine dust (A5), while column densities of their surface counterparts are decreased. We show that column densities of certain species, such as C{sub 2}H, HC{sub 2n+1}N (n = 0-3), H{sub 2}O, and some other molecules, as well as the C{sub 2}H{sub 2}/HCN abundance ratio, all of which are accessible with Herschel and ALMA, can be used as observational tracers of early stages of the grain evolution process in PPDs.

79 ASTRONOMY AND ASTROPHYSICS↗

Preliminary Work for Examining the Scalability of Reinforcement Learning

Researchers began studying automated agents that learn to perform multiple-step tasks early in the history of artificial intelligence (Samuel, 1963; Samuel, 1967; Waterman, 1970; Fikes, Hart & Nilsonn, 1972). Multiple-step tasks are tasks that can only be solved via a sequence of decisions, such as control problems, robotics problems, classic problem-solving, and game-playing. The objective of agents attempting to learn such tasks is to use the resources they have available in order to become more proficient at the tasks. In particular, each agent attempts to develop a good policy, a mapping from states to actions, that allows it to select actions that optimize a measure of its performance on the task; for example, reducing the number of steps necessary to complete the task successfully. Our study focuses on reinforcement learning, a set of learning techniques where the learner performs trial-and-error experiments in the task and adapts its policy based on the outcome of those experiments. Much of the work in reinforcement learning has focused on a particular, simple representation, where every problem state is represented explicitly in a table, and associated with each state are the actions that can be chosen in that state. A major advantage of this table lookup representation is that one can prove that certain reinforcement learning techniques will develop an optimal policy for the current task. The drawback is that the representation limits the application of reinforcement learning to multiple-step tasks with relatively small state-spaces. There has been a little theoretical work that proves that convergence to optimal solutions can be obtained when using generalization structures, but the structures are quite simple. The theory says little about complex structures, such as multi-layer, feedforward artificial neural networks (Rumelhart & McClelland, 1986), but empirical results indicate that the use of reinforcement learning with such structures is promising. These empirical results make no theoretical claims, nor compare the policies produced to optimal policies. A goal of our work is to be able to make the comparison between an optimal policy and one stored in an artificial neural network. A difficulty of performing such a study is finding a multiple-step task that is small enough that one can find an optimal policy using table lookup, yet large enough that, for practical purposes, an artificial neural network is really required. We have identified a limited form of the game OTHELLO as satisfying these requirements. The work we report here is in the very preliminary stages of research, but this paper provides background for the problem being studied and a description of our initial approach to examining the problem. In the remainder of this paper, we first describe reinforcement learning in more detail. Next, we present the game OTHELLO. Finally we argue that a restricted form of the game meets the requirements of our study, and describe our preliminary approach to finding an optimal solution to the problem.

Clouse, Jeff↗

Process-oriented stochastic perturbations applied to the parametrization of turbulence and shallow convection for ensemble prediction

Weather forecasting nowadays often requires some estimation of uncertainties associated with the output of meteorological models, in order to better inform decision making, especially in the context of intense weather events. Ensemble prediction systems provide such information through sets of possible scenarios which are designed to represent various uncertainty sources, including model uncertainties. A wide variety of methods have been proposed to estimate model uncertainties, among which perturbation methods targeting uncertain processes are a promising research field. Here, we focus on the representation of small-scale variability by process-oriented perturbation schemes applied to two key physical processes, namely turbulence and shallow convection. The perturbations are applied to a single-column version of the convection-permitting AROME model, in three idealized boundary-layer cases. Large-eddy simulations (LESs) of the same cases serve as a reference for the subgrid variability that has to be represented, and the results are also compared to those given by the Stochastically Perturbed Parametrization Tendencies (SPPT) method, which is a method commonly used by weather forecast centres to represent model uncertainty. The spread produced by our process-oriented perturbations of turbulence and shallow convection does not represent all the small-scale variability implied by the LESs for temperature and humidity. However, it is of a similar order of magnitude for the wind, thanks to perturbations generated by the stochastic turbulence scheme. The dispersion is structurally different from what is obtained with SPPT. It is non-negligible in the lower levels, where SPPT perturbations are usually suppressed because of numerical instabilities, indicating a possible complementarity between the schemes.

54 ENVIRONMENTAL SCIENCES↗

Study of Fluid Flow Control in Protein Crystallization using Strong Magnetic Fields

An important component in biotechnology, particularly in the area of protein engineering and rational drug design is the knowledge of the precise three-dimensional molecular structure of proteins. The quality of structural information obtained from X-ray diffraction methods is directly dependent on the degree of perfection of the protein crystals. As a consequence, the growth of high quality macromolecular crystals for diffraction analyses has been the central focus for biochemists, biologists, and bioengineers. Macromolecular crystals are obtained from solutions that contain the crystallizing species in equilibrium with higher aggregates, ions, precipitants, other possible phases of the protein, foreign particles, the walls of the container, and a likely host of other impurities. By changing transport modes in general, i.e., reduction of convection and sedimentation, as is achieved in "microgravity", researchers have been able to dramatically affect the movement and distribution of macromolecules in the fluid, and thus their transport, formation of crystal nuclei, and adsorption to the crystal surface. While a limited number of high quality crystals from space flights have been obtained, as the recent National Research Council (NRC) review of the NASA microgravity crystallization program pointed out, the scientific approach and research in crystallization of proteins has been mainly empirical yielding inconclusive results. We postulate that we can reduce convection in ground-based experiments and we can understand the different aspects of convection control through the use of strong magnetic fields and field gradients. Whether this limited convection in a magnetic field will provide the environment for the growth of high quality crystals is still a matter of conjecture that our research will address. The approach exploits the variation of fluid magnetic susceptibility with concentration for this purpose and the convective damping is realized by appropriately positioning the crystal growth cell so that the magnetic susceptibility force counteracts terrestrial gravity. The general objective is to test the hypothesis of convective control using a strong magnetic field and magnetic field gradient and to understand the nature of the various forces that come into play. Specifically we aim to delineate causative factors and to quantify them through experiments, analysis and numerical modeling. Once the basic understanding is obtained, the study will focus on testing the hypothesis on proteins of pyruvate dehydrogenase complex (PDC), proteins E1 and E3. Obtaining high crystal quality of these proteins is of great importance to structural biologists since their structures need to be determined. Specific goals for the investigation are: 1. To develop an understanding of convection control in diamagnetic fluids with concentration gradients through experimentation and numerical modeling. Specifically solutal buoyancy driven convection due to crystal growth will be considered. 2. To develop predictive measures for successful crystallization in a magnetic field using analyses and numerical modeling for use in future protein crystal growth experiments. This will establish criteria that can be used to estimate the efficacy of magnetic field flow damping on crystallization of candidate proteins. 3. To demonstrate the understanding of convection damping by high magnetic fields to a class of proteins that is of interest and whose structure is as yet not determined. 4. To compare quantitatively, the quality of the grown crystals with and without a magnetic field. X-ray diffraction techniques will be used for the comparative studies. In a preliminary set of experiments, we studied crystal dissolution effects in a 5 Tesla magnet available at NASA Marshall Space Flight Center (MSFC). Using a Schlieren setup, a 1mm crystal of Alum (Aluminum-Potassium Sulfate) was introduced in a 75% saturated solution and the resulting dissolution plume was observed. The experiment was conducted both in the presence and absence of a magnetic field gradient. The magnet produces a gradient field of approx. 1 Tesla2/cm. Image analysis of the recorded images indicated an enhanced plume velocity that was of the order of the measurement limit. For this experiment, both the gradient and gravity fields are in the same direction resulting in an enhanced effective gravity that tends to accelerate the observed plume velocity. While the results are not conclusive, pending further tests, it clearly points out the inadequacy of the MSFC magnet for conducting protein crystallization experiments and the need for a stronger magnet. In spacebased experiments, however, where the gravitational effects are small, only a weak magnetic field will be required to control or mitigate the effects of convective contamination.

Ramachandran, Narayanan↗

A new concept for searching for time-reversal symmetry violation using Pa-229 ions trapped in optical crystals

Certain pear-shaped nuclei are expected to have enhanced sensitivity to time-reversal and parity-violating interactions originating within the nuclear medium. In particular, Protactinium-229 is thought to be about 100,000 times more sensitive than Mercury-199 which currently sets some of the most stringent limits for these types of interactions. Several challenges would first have to be addressed in order to take advantage of this discovery potential. First, there is not currently a significant source of Pa-229 (1.5 day half-life); however, there are plans to harvest Pa-229 at the Facility for Rare Isotope Beams at Michigan State University. Second, the spin-5/2 nucleus of Pa-229 limits its coherence time while also making it sensitive to systematic effects related to local electric field gradients. On the other hand, this also give Pa-229 an additional source of signal in the form of a magnetic quadrupole moment (MQM) which violates the same symmetries as an EDM but is not observable in spin-1/2 systems. Third, in order to compensate for the small atom numbers and short coherence times, the Pa-229 atoms would have to be probed with exceptionally large electric and magnetic fields that may be possible if Pa-229 ions are embedded inside an optical crystal. We will describe some aspects of this concept using the stable Praseodymium-141 isotope as a surrogate which has the same nuclear spin and similar atomic structure of Pa-229.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Super-swelled lyotropic single crystals

Lipids self-assemble into diverse supramolecular structures that exhibit thermotropic and/or lyotropic behavior. Lyotropic mesophases, where membranes conform to periodic minimal surfaces dividing two nonpenetrating aqueous subspaces, are arguably one of the most intriguing phases of lipid materials. Traditional 3D bicontinuous cubic lipid materials appear as a polycrystal of varying degrees of order. When exposed to water, the properties of the molecular building blocks of the membrane determine specific swelling limits setting the lattice dimensions at about 15 nm. This limited swelling severely impairs their application as delivery vehicles of large drugs or as matrices for guiding protein crystallization. We report the discovery of self-assembly strategies leading to the emergence of lipid bicontinuous single crystals with unprecedented swelling capacity. Here, the conventional strategy to increase unit cell size is tweaking membrane composition to include charged building blocks, a process to achieve electrostatic-driven swelling. In this paper, we demonstrate that controlling self-assembly external conditions when coupled to membrane composition yields 3D bicontinuous cubic phases that swell up to lattice dimensions of 68 nm. Importantly, and contrary to what is perceived for soft lyotropic materials in general, the self-assembly methodology enables the development of large super-swelled monocrystals. Utilizing small-angle X-ray scattering and cryoelectron microscopy, we underpin three crucial factors dictating the stabilization of super-swelled lipid bicontinuous cubic single crystals: (i) organic solvent drying speed, (ii) membrane charge density, and (iii) polyethylene glycol-conjugated lipids amount.

36 MATERIALS SCIENCE↗

Prediction of vacancy defect diffusion paths in high entropy alloys via machine learning on molecular dynamics data

Identifying the diffusion path of point defects is a critical step in understanding their evolution and the mechanisms of related phenomena. Defect diffusion occurs at small length and time scales, with impacts on material properties that may continue to evolve over ns to μs, ms, and the continuum scale (s, min, etc., and cm, m, etc.). The time scale accessible to molecular dynamics (MD) simulations is limited by small step sizes, typically in the fs range. Thus, surrogate models of MD simulations through machine learning (ML)-based algorithms are of great interest, especially for complex systems such as high entropy alloys (HEAs). In this work, dynamics governing vacancy migration in HEA were approximated with graph convolutional network (GCN) models as ansatzes for kinetic Monte Carlo (KMC) rate catalogs. Network design considered that diffusion in crystalline solids generally depends on interactions between defects and their immediate neighbor atoms. Graphs represented the vacancy surroundings, MD-generated trajectories provided training and comparison datasets, and unsupervised GCN models approximated interatomic dynamics governing vacancy migration in HEAs as ansatzes for KMC. A proof-of-concept model trained on MD data for the Fe, Ni, Cr, Co, and Cu HEA environment was used with two different neighbor interactions to assess the feasibility of training a GCN to predict vacancy defect transition rates in the HEA environment. The resulting setup rapidly generated MD-formatted synthetic trajectories based on dynamics learned from the MD training set, with a time acceleration of roughly two orders of magnitude and a similar diffusion coefficient to MD observations. Additionally, Nudged Elastic Band (NEB) calculations were performed on randomly generated FeNiCrCoCu HEA structures to determine vacancy migration barriers across nearest-neighbor sites. Transition probabilities for each jump, categorized by atomic type, were extracted from these calculations. NEB-based and GCN-based approaches led to similar outcomes.

Reimer, C↗

Exotic Molecules in Space: A Coordinated Astronomical Laboratory and Theoretical Study

The past three years have been a period of great progress in our laboratory investigation of molecules of astrophysical interest-the most productive by far in the 20-year history of a research program which has led to the discovery of over 20% of the 123 known interstellar and circumstellar molecules. Most of the discoveries made during this period have been the result of the construction in late 1995 and early 1996 of a Fourier transform microwave spectrometer working in the centimeter-wave band. The sensitivity of this instrument from the moment that it was turned on has exceeded our expectations by an order of magnitude. The Table below shows the 46 new molecules which have been discovered. Most are carbon chains, the dominant type of molecule which has been found in space. Several comments with respect to these molecules should be made: 1. There are probably no mistakes in any of the identifications, since these have been confirmed by the standard, powerful assays and tests used to check spectroscopic identifications: isotopic substitution, quantum calculations of the expected molecular structures, detection of hyperfine structure, Zeeman effect, etc. 2. The radio laboratory astrophysics of the entire set is complete for the time being, in the sense that essentially all the astronomically interesting radio transitions (including hfs when present) are either directly measured or can now be calculated from the derived spectroscopic constants to better than 1 part per million (or 0.3 km s-1 in radial velocity, and often much better than that). 3. Six of the forty six new molecules have already been identified in space, in every case but one on the basis of our laboratory measurements. 4. Sensitive as they are, our laboratory techniques are far from fundamental limits on sensitivity, and 5. One of the principal motivations of our research is to close the fairly small mass and size gap, now only a factor of a few, between the smallest postulated interstellar grains and the largest identified interstellar molecules.

Thaddeus, Patrick↗

Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring the feasibility of crack detection in plate weldments through an interposed layer of viscoelastic material.

Development of new approaches in the nondestructive evaluation of welded steel plates for large naval structures continues to be an area of interest for the DoD and the military complex. In this report we will evaluate an elastic-microwave based detection and imaging method using both numerical finite element (3D FEM) and experimental methods. The evaluation was performed on two test articles that were designed to represent critical structural components with flaws of interest. Details of the materials and the mechanical drawings were provided with the test articles. Flaws, cracks and weld defects have been included in the test articles to determine detection sensitivity and accuracy of the proposed method. Our approach uses a microwave interferometer (MI) to record the scattered response of flaws in the steel plated as it is driven by an incident elastic field. The MI can “see” (penetrate) through the viscoelastic coating to the upper surface of the plate. Out-of-plane displacement amplitudes of 10nm in the frequency range (1kHz to 25kHz) are readily observable, with the key feature being, that the surface bond between the coating and the steel plate are undisturbed. The non-contact aspect of the interferometer allows for large surface regions to be accurately and efficiently scanned in space and time. Spatiotemporal data sets of this kind and specialized wavefield processing provide powerful detection and imaging modalities. From these wavefield data sets, a plate thickness mapping capability has been demonstrated that can detect thickness changes on the order of 0.79 mm (1/32”) with spatial resolution on the order of the spatial sampling rate, 15mm (~5/8”). We have also shown that a topological energy analysis of the wavefield data can detect and locate small flaws, on the order of 5-10 mm (0.025-0.40”) in the welded joint of a 1.5” thick T-plate. As before, these results are obtained through a 2” thick viscoelastic coating without altering the integrity of coating or the coating bond. These results show that we are detecting and locating damage (flaws) in the plate that are much smaller than the wavelength of the propagating guided modes. Classical scattering theory places a (λ/2) resolution limit on the detectability of flaws in terms of the incident field [22], however, since the spatial resolution of the scanned region is much smaller, (Δx=Δy=15mm) and the inherent natural focusing of the time reversal operation, we are able to detect smaller flaws on the order of (λ/10). It is important to realize that we are not imaging the flaw but detecting and localizing a difference between a reference (pristine) sample and the measured (damaged) sample, relative to a spatial grid on the surface. The current scan resolution is 15mm x 15mm. At present we cannot expect to resolve individual flaws within a grid space only their cumulative effect. Even with the current limitations, this imaging approach appears to be a promising alternative to current methods where the coating layer is removed.

36 MATERIALS SCIENCE↗