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At least 19 records

Retrofitting Word Embeddings with the UMLS Metathesaurus for Clinical Information Extraction

Deep learning has surged in popularity and proven to be effective for various artificial intelligence applications including information extraction from cancer pathology reports. Since word representation is a core unit that enables deep learning algorithms to understand words and be able to perform NLP, this representation must include as much information as possible to help these algorithms achieve high classification performance. Therefore, in this work in addition to the distributional information of words in large sized corpora, we use UMLS vocabulary resources to enrich the vector space representation of words with the semantic relations between words. These resources provide many terminologies pertaining to cancer. The refined word embeddings are used with a convolutional neural (CNN) model to extract four data elements from cancer pathology reports; ICD-O-3 tumor topography codes, tumor laterality, behavior, and histological grade. We observed that using UMLS vocabulary resources to enrich word embeddings of CNN models consistently outperformed CNN models without pre-training word embeddings and even with pre-trained word embeddings on a domain specific corpus across all four tasks. The results show marginal improvement on the laterality task, but a significant improvement on the other tasks, especially for the macro-f score. Specifically, the improvements are 3%, 13%, and 15% for tumor site, histological grade, and behavior tasks, respectively. This approach is encouraging to enrich word embeddings with more clinical data resources to be used for information abstraction tasks from clinical pathology reports.

Alawad, Mohammed↗

Embedded Web Technology: Applying World Wide Web Standards to Embedded Systems

Embedded Systems have traditionally been developed in a highly customized manner. The user interface hardware and software along with the interface to the embedded system are typically unique to the system for which they are built, resulting in extra cost to the system in terms of development time and maintenance effort. World Wide Web standards have been developed in the passed ten years with the goal of allowing servers and clients to intemperate seamlessly. The client and server systems can consist of differing hardware and software platforms but the World Wide Web standards allow them to interface without knowing about the details of system at the other end of the interface. Embedded Web Technology is the merging of Embedded Systems with the World Wide Web. Embedded Web Technology decreases the cost of developing and maintaining the user interface by allowing the user to interface to the embedded system through a web browser running on a standard personal computer. Embedded Web Technology can also be used to simplify an Embedded System's internal network.

Ponyik, Joseph G.↗

Integrating subsystem embedding subalgebras and coupled cluster Green’s function: a theoretical foundation for quantum embedding in excitation manifold

Here, in this study, we introduce a novel approach to coupled-cluster Green's function (CCGF) embedding by seamlessly integrating conventional CCGF theory with the state-of-the-art sub-system embedding sub-algebras coupled cluster (SES-CC) formalism. This integration focuses primarily on delineating the characteristics of the sub-system and the corresponding segments of the Green's function, defined explicitly by active orbitals. Crucially, our work involves the adaptation of the SES-CC paradigm, addressing the left eigenvalue problem through a distinct form of Hamiltonian similarity transformation. This advancement not only facilitates a comprehensive representation of the interaction between the embedded sub-system and its surrounding environment but also paves the way for the quantum mechanical description of multiple embedded domains, particularly by employing the emergent quantum flow algorithms. Our theoretical underpinnings further set the stage for a generalization to multiple embedded sub-systems. This expansion holds significant promise for the exploration and application of non-equilibrium quantum systems, enhancing the understanding of system–environment interactions. In doing so, the research underscores the potential of SES-CC embedding within the realm of quantum computations and multi-scale simulations, promising a good balance between accuracy and computational efficiency.

97 MATHEMATICS AND COMPUTING↗

A Moving Embedded Boundary Approach for the Compressible Navier-Stokes Equations in a Block-Structured Adaptive Refinement Framework

A computational technique has been developed to perform compressible flow simulations involving moving boundaries using an embedded boundary approach within the block-structured adaptive mesh refinement (SAMR) framework of AMReX [1], [91], [92]. We leverage the SAMR capability to obtain quantitatively accurate results whilst using robust, second-order finite volume schemes. A conservative, unsplit, cut-cell approach is utilized and a ghost-cell approach is developed for computing the flux on the moving, embedded boundary faces. A third-order least-squares formulation has been developed to compute the wall velocity gradients, and was found to significantly improve the performance of the solver in terms of the quantitative comparison of surface quantities such as the skin friction coefficient. Various test cases are performed to validate the method, and compared with analytical, experimental, and other numerical results in literature. Inviscid and viscous test cases are performed that span a wide regime of flow speeds - acoustic (harmonically pulsating sphere), smooth flows (expansion fan created by a receding piston) and flows with shocks (shock-cylinder interaction, shock-wedge interaction, pitching NACA 0012 airfoil and shock-cone interaction). A closed system with moving boundaries - an oscillating piston in a cylinder, showed that the percentage error in mass within the system decreases with refinement, demonstrating that the numerical scheme is conservative with grid refinement, but is not discretely conservative. Viscous test cases involve that of a horizontally moving cylinder at Re = 40, an inline oscillating cylinder at Re = 100, and a transversely oscillating cylinder at Re = 185. The judicious use of adaptive mesh refinement with appropriate refinement criteria to capture the regions of interest leads to well-resolved flow features, and good quantitative comparison is observed with the results available in literature.

adaptive refinement↗

Design and Analysis of Embedded I&C for a Fully Submerged Magnetically Suspended Impeller Pump

Improving nuclear reactor power system designs and fuel-processing technologies for safer and more efficient operation requires the development of new component designs. In particular, many of the advanced reactor designs such as the molten salt reactors and high-temperature gas-cooled reactors have operating environments beyond the capability of most currently available commercial components. To address this gap, new cross-cutting technologies need to be developed that will enable design, fabrication, and reliable operation of new classes of reactor components. The Advanced Sensor Initiative of the Nuclear Energy Enabling Technologies initiative is investigating advanced sensor and control designs that are capable of operating in these extreme environments. Under this initiative, Oak Ridge National Laboratory (ORNL) has been developing embedded instrumentation and control (I&C) for extreme environments. To develop, test, and validate these new sensing and control techniques, ORNL is building a pump test bed that utilizes submerged magnetic bearings to levitate the shaft. The eventual goal is to apply these techniques to a high-temperature (700°C) canned rotor pump that utilizes active magnetic bearings to eliminate the need for mechanical bearings and seals. The technologies will benefit the Next Generation Power Plant, Advanced Reactor Concepts, and Small Modular Reactor programs. In this paper, we will detail the design and analysis of the embedded I&C test bed with submerged magnetic bearings, focusing on the interplay between the different major systems. Then we will analyze the forces on the shaft and their role in the magnetic bearing design. Next, we will develop the radial and thrust bearing geometries needed to meet the operational requirements of the test bed. In conclusion, we will present some initial system identification results to validate the theoretical models of the test bed dynamics.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Application of the locally self-consistent embedding approach to the Anderson model with non-uniform random distributions

Highlights: • Typical Medium Theory (TMT) for the Anderson Localization. • Locally Self-Consistent Multiple Scattering Method (LSMS) for Random Disordered Systems. • Linear Scaling Computational Method for Random Disordered Systems. We apply the recently developed embedding scheme for the locally self-consistent method to random disorder electrons systems. The method is based on the locally self-consistent multiple scattering theory and the typical medium theory. The locally self-consistent multiple scattering theory divides a system into many small designated local interaction zones. The subsystem within each local interaction zone is embedded in a self-consistent field from the typical medium theory. This approximation allows the study of random systems with large numbers of sites. We present results for the three dimensional Anderson model with different random disorder potential distributions. Using the typical density of states as an indicator of Anderson localization, we find that the method can capture the localization for commonly studied disorder potentials. These include the uniform distribution, the Gaussian distribution, and even the unbounded Cauchy distribution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Propagation of positive discharges in an air bubble having an embedded water droplet

Low temperature plasmas generated inside gas bubbles immersed in water is an effective method of rapidly transferring plasma generated reactive species to the water for applications in biomedicine, agriculture and environment. Reactive species are generally produced in the gas phase plasma and then solvate into the liquid. The large surface-to-volume ratio (SVR) of the bubble accelerates this process. In generating bubbles in water, aerosols and droplets are also contained within the bubble. These droplets also have a large SVR and so can be rapidly plasma activated. However, the presence of the droplets can also impact the propagation of the plasma in the bubble. In this paper, results are discussed from computational and experimental investigations of the formation and evolution of discharges in an air bubble immersed in water with an embedded water droplet. The computations were performed with a two-dimensional plasma hydrodynamics model. Experiments were performed with a quasi-2D bubble apparatus. In bubbles having a droplet, a plasma filament typically bridges from the powered electrode to the droplet, and then from the droplet to the bubble surface. A surface-hugging streamer also occurs on the inner bubble surface and on the surface of the droplet. Both surface streamers result in part from surface charge accumulation and can dominate the formation of reactive species that transport into the droplet. Increasing droplet conductivity suppresses propagation of the surface discharge and leads to a lower density of aqueous reactive species. Increasing conductivity of the surrounding water does not change the overall structure of the discharge but does slightly elevate the discharge intensity. Finally, the size and shape of the embedded droplet can significantly affect the formation and propagation of the streamer.

2D fluid modelling↗

Nonequilibrium Environment Dynamics in a Frequency-Dependent Polarizable Embedding Model

Hybrid quantum mechanical/molecular mechanical (QM/MM) models are some of the most powerful and computationally feasible approaches to account for solvent effects or more general environmental perturbations on quantum chemical systems. In their more recent formulations (known as polarizable embedding) they can account for electrostatic and mutual polarization effects between the QM and the MM subsystems. In this paper, a polarizable embedding scheme based on induced dipoles that is both able to describe electron evolution of the embedded QM system in an efficient manner as well as to capture the frequency dependent behavior of the solvent, is proposed. The effects of this frequency dependent solvent on a time- dependent model system - the Rabi oscillations of H+2 in a resonant - field are considered. The solvent is shown to introduce only mild perturbations when the excitation frequencies of the solvent and the solute are off-resonant. However, the dynamics of the H+2 are fundamentally changed in the presence of a near-resonant excitation solvent.

Wildman, Andrew↗

A weighted state redistribution algorithm for embedded boundary grids

State redistribution is an algorithm that stabilizes cut cells for embedded boundary grid methods. This work extends the earlier algorithm in several important ways. First, state redistribution is extended to three spatial dimensions. Second, we discuss several algorithmic changes and improvements motivated by the more complicated cut cell geometries that can occur in higher dimensions. In particular, we introduce a weighted version with less dissipation in an easily generalizable framework. Third, we demonstrate that state redistribution can also stabilize a solution update that includes both advective and diffusive contributions. Notably, the stabilization algorithm is shown to be effective for incompressible as well as compressible reacting flows. Finally, we discuss the implementation of the algorithm for several exascale-ready simulation codes based on AMReX, demonstrating ease of use in combination with domain decomposition, hybrid parallelism and complex physics.

97 MATHEMATICS AND COMPUTING↗

Neural embedding: learning the embedding of the manifold of physics data

In this paper, we present a method of embedding physics data manifolds with metric structure into lower dimensional spaces with simpler metrics, such as Euclidean and Hyperbolic spaces. We then demonstrate that it can be a powerful step in the data analysis pipeline for many applications. Using progressively more realistic simulated collisions at the Large Hadron Collider, we show that this embedding approach learns the underlying latent structure. With the notion of volume in Euclidean spaces, we provide for the first time a viable solution to quantifying the true search capability of model agnostic search algorithms in collider physics (i.e. anomaly detection). Finally, we discuss how the ideas presented in this paper can be employed to solve many practical challenges that require the extraction of physically meaningful representations from information in complex high dimensional datasets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Time-Dependent Complete Active Space Embedded in Polarizable Force Field

Electron correlation and environmental effects play important roles in electron dynamics and spectroscopic observables of chemical systems in condensed phase. In this paper, we present a time-dependent complete active space configuration interaction (TD-CASCI) approach embedded in a polaraizable force filed, MMPol. The present implementation of TD-CASCI/MMPol utilizes a direct matrix-vector contraction, allowing studies of large systems. This scheme is used to study the solvatochromic shift of coumarin 153 in methanol. The TD-CASCI/MMPol approach captures the double excitation character in the excited state wave function and accurately predicts the solvatochromic red-shift of coumarin 153 dye within the experimental range, outperforming linear response time-dependent density functional theory. The effect of using different reference orbitals for the TD-CASCI/MMPol simulation is also investigated, highlighting the need for an unbiased treatment of all electronic states in the energy range of interest.

Liu, Hongbin↗

Functionalized Embedded Monometallic Nickel Catalysts for Enhanced Hydrogen Evolution: Performance and Stability

Viable anionic exchange membrane (AEM) electrolysis for H 2 production requires highly active hydrogen evolution reaction (HER) catalysts that are also robust and cost-effective. Traditionally juxtaposition of two transition metals with one being more oxophilic is necessary for easier access to water in the inner Helmholtz plane as a source of protons in the crucial Volmer step for enhanced HER activity. However, they are prone to passivation at anodic potentials or deactivation via the formation of sub-surface metal hydrides at high cathodic overpotentials. Here we report a method of enabling close juxtaposition of Ni-Ni-oxide surfaces by functionalizing Ni-based catalysts via the careful thermal treatment of carbon-supported Ni nano-particles chelated with a select organic chelating compound referred to as cupferron. This functionalization results in an embedded Ni surface with a clear graphitic coating engendering long-term stability for passivation and subsurface hydride formation. The stability and activity of the functionalized Ni catalyst are demonstrated in half-cell RDE and full-cell AEM membrane-based hydrogen pump experiments. In the case of the latter, the functionalized Ni outperforms carbon-supported Pt.

25 ENERGY STORAGE↗

Natural Charge-Transfer Analysis: Eliminating Spurious Charge-Transfer States in Time-Dependent Density Functional Theory via Diabatization, with Application to Projection-Based Embedding

For many types of vertical excitation energies, linear-response time-dependent density functional theory (LR-TDDFT) offers a useful degree of accuracy combined with unrivaled computational efficiency, although charge-transfer excitation energies are often systematically and dramatically underestimated, especially for large systems and those that contain explicit solvent. As a result, low energy electronic spectra of solution-phase chromophores often contain tens to hundreds of spurious charge-transfer states, making LR-TDDFT needlessly expensive in bulk solution. More nefariously, intensity borrowing by the low-energy charge-transfer states can affect intensities of the valence excitations even if those excitation energies are accurate. At higher excitation energies, it is difficult to distinguish spurious CT states from genuine charge-transfer-to-solvent (CTTS) excitations. In this work, we introduce an automated diabatization scheme that enables fast and effective screening of the CTTS acceptor space in bulk solution. Our procedure introduces the concept of “natural charge-transfer orbitals”, which provide a means to isolate characteristic pairs of orbitals that are most likely to participate in a CTTS excitation. The projection of these orbitals onto solvent-centered virtual orbitals provides a criterion for defining the most important solvent molecules in a given excitation. We apply this method to analyze an ab initio molecular dynamics (MD) trajectory of I-(aq) and report the lowest-energy CTTS band in the absorption spectrum. Our results are in excellent agreement with experimental measurements for bulk I-(aq), and only one-third of the water molecules in the I-(H2O)96 simulation cell need to be described with LR-TDDFT in order to obtain excitation energies that are converged to < 0.1 eV. The tools introduced herein will improve the accuracy, efficiency, and usability of LR-TDDFT in solution-phase environments

Carter-Fenk, Kevin D.↗

An Fe-Ni-Cr embedded atom method potential for austenitic and ferritic systems: An Fe-Ni-Cr embedded atom method potential for austenitic and ferritic systems

Fe-Ni-Cr stainless-steels are important structural materials because of their superior strength and corrosion resistance. Atomistic studies of mechanical properties of stainless-steels, however, have been limited by the lack of high-fidelity interatomic potentials. Here in this paper, using density functional theory as a guide, we have developed a new Fe-Ni-Cr embedded atom method potential. We demonstrate that our potential enables stable molecular dynamics simulations of stainless-steel alloys at high temperatures, accurately reproduces the stacking fault energy—known to strongly influence the mode of plastic deformation (e.g., twinning vs. dislocation glide vs. cross-slip)—of these alloys over a range of compositions, and gives reasonable elastic constants, energies, and volumes for various compositions. The latter are pertinent for determining short-range order and solute strengthening effects. Our results suggest that our potential is suitable for studying mechanical properties of austenitic and ferritic stainless-steels which have vast implementation in the scientific and industrial communities.

36 MATERIALS SCIENCE↗

Rotationally invariant slave-boson and density matrix embedding theory: Unified framework and comparative study on the one-dimensional and two-dimensional Hubbard model [Rotationally invariant slave-boson and density matrix embedding theory: A unified framework and a comparative study on the 1D and 2D Hubbard Model]

We present detailed benchmark ground-state calculations of the one- and two-dimensional Hubbard model utilizing the cluster extensions of the rotationally invariant slave-boson mean-field theory and the density matrix embedding theory. Our analysis shows that the overall accuracy and the performance of these two methods are very similar. Furthermore, we propose a unified computational framework that allows us to implement both of these techniques on the same footing. In conclusion, this provides us with a different line of interpretation and paves the ways for developing systematically distinct generalizations of these complementary approaches.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗