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At least 343 records · Page 19

High-fidelity model-driven deception platform for cyber-physical systems

A system is described for protecting a cyber-physical system against a potential attacker of the cyber-physical system. The system includes at least one processor configured to: collect historical information about the cyber-physical system, and train, based on the historical information, a machine-learned model to predict future conditions of at least a portion of the cyber-physical system. Responsive to detecting an input signal to the cyber-physical system, the system is configured to output an alert to the cyber-physical system indicative of a potential attacker, and respond to the input signal by simulating, based on the future conditions predicted by the machine-learned model, functionality and communications of the at least a portion of the cyber-physical system.

Edgar, Thomas W.↗

Power control system modification and simulation of CPR1000 - 181

Due to development of electric power system, the proportion of nuclear power and its needs for load follow operation have become large. Then there would be higher requirements to the power control ability of the nuclear power system. The axial power distribution may change a lot in the operation process and be affected by many factors. In particular, as the power change is performed within a load follow maneuver, several modifications occur in the core from a neutronic view point: the fuel and moderator temperature change, the xenon concentration and distribution are modified, the power distribution skewed axially, etc. These changes need to be adequately counterbalanced to keep both the core critical and the power distribution acceptable. The traditional approach in pressurized water reactors (PWRs) is compensating for the reactivity change due to the power variation by adjusting the soluble boron concentration and moving a limited number of control banks. However, dilution/boronation strategy becomes expensive for short time changes and leads to large volume of liquid effluent, so it is eager about a capability to perform load follow operation without changing soluble boron concentration. CPR1000, one of the main reactor types in China national development, is taken an example in this paper. It adopts a control method called Mode G, using G banks, N banks, R bank and soluble boron to perform the load follow control. According to the analysis of the physics and thermal principle, a two-node dynamic function model was built, putting the coupling coefficient and mutual influence into consideration. By the calculation of these transient parameter values which are acquired by the steady-state calculation of single channel, the core system model of CPR1000 is established. In order to carry out the load follow operation without the boron adjustment, named as BTP mode, the control banks were regrouped to control the average temperature by M banks and axial offset by AO bank. After that, the average temperature control system (M banks control system) and the axial offset control system (AO bank control system) are built. When the optimal control system is connected to the core model simulation platform, the BTP mode load follow operation of the modified CPR1000 is simulated in the end of the paper. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A Generic and Multi-Functional Electromagnetic Transient Model for Grid-Following Inverter: Preprint

This article presents a generic and multi-functional electromagnetic transient (EMT) dynamic model of grid following (GFL) inverter-based resource (IBR) using the PSCAD TM software platform. The features of the developed model includes the flexibility in selecting various types and combinations of DC sources covering PV modules, battery modules, ideal DC source module, as well as flexibility in selecting either switched or averaged model of inverter. This model also covers exhaustive lists of controller logic covering open-loop/closed-loop PQ dispatch control, DC voltage and AC terminal voltage control along with the conventional current control designed in dq-domain, aB- domain and positive-negative sequence domain. Moreover, this model is equipped with the flexibility in selecting various types of current limiting schemes that includes saturation-based as well as latching-based current limiter, anti-windup protection. Moreover, the EMT model is agnostic to the MVA rating and is suitable for interfacing transmission systems by being complaint with the IEEE Std. 2800. The generality in the power circuits and the multi-functional options in operation and control of the developed EMT model makes it suitable for both academia and industry to study various power system aspects not limited to but such as fault behavior of GFL IBR and impacts on protection system, transient stability of a system interfaced with large number of GFL IBRs etc.

grid following inverter↗

Modeling the Transfer Function for the Dark Energy Survey

We present a forward-modeling simulation framework designed to model the data products from the Dark Energy Survey (DES). This forward-model process can be thought of as a transfer function—a mapping from cosmological/astronomical signals to the final data products used by the scientists. Using output from the cosmological simulations (the Blind Cosmology Challenge), we generate simulated images (the Ultra Fast Image Simulator) and catalogs representative of the DES data. In this work we demonstrate the framework by simulating the 244 deg 2 coadd images and catalogs in five bands for the DES Science Verification data. The simulation output is compared with the corresponding data to show that major characteristics of the images and catalogs can be captured. We also point out several directions of future improvements. Two practical examples—star-galaxy classification and proximity effects on object detection—are then used to illustrate how one can use the simulations to address systematics issues in data analysis. With clear understanding of the simplifications in our model, we show that one can use the simulations side-by-side with data products to interpret the measurements. This forward modeling approach is generally applicable for other upcoming and future surveys. It provides a powerful tool for systematics studies that is sufficiently realistic and highly controllable.

79 ASTRONOMY AND ASTROPHYSICS↗

Exchange-correlation functional challenges in modeling quaternary chalcogenides

The development of next-generation quaternary chalcogenides, such as Cu2ZnSnS4 (CZTS) and Cu2ZnGeS4 (CZGS), for solar energy and thermoelectric applications hinges upon both careful experimentation and accurate quantum mechanical modeling. To address the latter, many have turned to density functional theory (DFT), which offers several choices for the approximate treatment of electron exchange and correlation (XC). Popular XC functionals include the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA) and the recently developed strongly constrained and appropriately normed (SCAN) meta-GGA. Extensions of DFT functionals, such as adding a Hubbard U correction and introducing a fraction of the Fock exchange (hybrid functionals), have been used widely to model systems containing 3d metal ions. However, no studies yet have compared comprehensively PBE(+U) and SCAN(+U) in the quality of their predictions of the bulk and defect thermodynamics of quaternary chalcogenides, which play a critical role in device fabrication and performance. Hence, here we calculate the (i) 0 K formation energies of bulk Ge compounds and (ii) neutral defect formation energies including charge-balanced (e.g., CuZn + ZnCu) and charge-imbalanced (e.g., CuSn) combinations of antisites and vacancies in CZTS and CZGS using the PBE, PBE +U, SCAN, SCAN +U, and the hybrid Heyd-Scuseria-Ernzerhof XC frameworks. We find that the formation energies of charge-imbalanced defects are more sensitive to the choice of the XC functional than those of charge-balanced defects, which can be explained by the differences in the extent of penalization of defect-generated delocalized electrons/holes by PBE, PBE +U, SCAN, and SCAN +U. Additionally, our results show that SCAN systematically underbinds Ge-containing compounds, thus highlighting the need for even further improvement of XC functionals. Based on our findings, we recommend the use of SCAN for modeling quaternary chalcogenides because its errors are systematic, and it has the firmest theoretical underpinning. Our work provides guidance for future modeling of quaternary chalcogenides.

14 SOLAR ENERGY↗

Predictive Models for Pulmonary Function Changes After Radiotherapy for Breast Cancer and Lymphoma

Purpose: To propose multivariate predictive models for changes in pulmonary function tests ({Delta}PFTs) with respect to preradiotherapy (pre-RT) values in patients undergoing RT for breast cancer and lymphoma. Methods and Materials: A prospective study was designed to measure {Delta}PFTs of patients undergoing RT. Sixty-six patients were included. Spirometry, lung capacity (measured by helium dilution), and diffusing capacity of carbon monoxide tests were used to measure lung function. Two lung definitions were considered: paired lung vs. irradiated lung (IL). Correlation analysis of dosimetric parameters (mean lung dose and the percentage of lung volume receiving more than a threshold dose) and {Delta}PFTs was carried out to find the best dosimetric predictor. Chemotherapy, age, smoking, and the selected dose-volume parameter were considered as single and interaction terms in a multivariate analysis. Stability of results was checked by bootstrapping. Results: Both lung definitions proved to be similar. Modeling was carried out for IL. Acute and late damage showed the highest correlations with volumes irradiated above {approx}20 Gy (maximum R{sup 2} = 0.28) and {approx}40 Gy (maximum R{sup 2} = 0.21), respectively. RT alone induced a minor and transitory restrictive defect (p = 0.013). Doxorubicin-cyclophosphamide-paclitaxel (Taxol), when administered pre-RT, induced a late, large restrictive effect, independent of RT (p = 0.031). Bootstrap values confirmed the results. Conclusions: None of the dose-volume parameters was a perfect predictor of outcome. Thus, different predictor models for {Delta}PFTs were derived for the IL, which incorporated other nondosimetric parameters mainly through interaction terms. Late {Delta}PFTs seem to behave more serially than early ones. Large restrictive defects were demonstrated in patients pretreated with doxorubicin-cyclophosphamide-paclitaxel.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Status of genome function annotation in model organisms and crops

Abstract Since the entry into genome‐enabled biology several decades ago, much progress has been made in determining, describing, and disseminating the functions of genes and their products. Yet, this information is still difficult to access for many scientists and for most genomes. To provide easy access and a graphical summary of the status of genome function annotation for model organisms and bioenergy and food crop species, we created a web application ( https://genomeannotation.rheelab.org ) to visualize, search, and download genome annotation data for 28 species. The summary graphics and data tables will be updated semi‐annually, and snapshots will be archived to provide a historical record of the progress of genome function annotation efforts. Clear and simple visualization of up‐to‐date genome function annotation status, including the extent of what is unknown, will help address the grand challenge of elucidating the functions of all genes in organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Gauges, loops, and polynomials for partition functions of graphical models

Graphical models represent multivariate and generally not normalized probability distributions. Computing the normalization factor, called the partition function, is the main inference challenge relevant to multiple statistical and optimization applications. The problem is #P-hard that is of an exponential complexity with respect to the number of variables. Here, aimed at approximating the partition function, we consider multi-graph models where binary variables and multivariable factors are associated with edges and nodes, respectively, of an undirected multi-graph. We suggest a new methodology for analysis and computations that combines the Gauge function technique from Chertkov and Chernyak with the technique developed in Anari and Oveis Gharan 2017 arXiv:1702.02937; Gurvits 2011 arXiv:1106.2844; Straszak and Vishnoi 2017 55th Annual Allerton Conf. on Communication, Control, and Computing, based on the recent progress in the field of real stable polynomials. We show that the Gauge function, representing a single-out term in a finite sum expression for the partition function which achieves extremum at the so-called belief-propagation gauge, has a natural polynomial representation in terms of gauges/variables associated with edges of the multi-graph. Moreover, Gauge function can be used to recover the partition function through a sequence of transformations allowing appealing algebraic and graphical interpretations. Algebraically, one step in the sequence consists of the application of a differential operator over gauges associated with an edge. Graphically, the sequence is interpreted as a repetitive elimination/contraction of edges resulting in multi-graph models on decreasing in size (number of edges) graphs with the same partition function as in the original multi-graph model. Even though the complexity of computing factors in the sequence of the derived multi-graph models and respective Gauge functions grow exponentially with the number of eliminated edges, polynomials associated with the new factors remain bi-stable if the original factors have this property. Moreover, we show that BP estimations in the sequence do not decrease, each low-bounding the partition function.

97 MATHEMATICS AND COMPUTING↗

Improved Models for Metallic Nanoparticle Cores from Atomic Pair Distribution Function (PDF) Analysis

X-ray atomic pair distribution functions (PDFs) were collected from a range of canonical metallic nanomaterials, both elemental and alloyed, prepared using different synthesis methods and exhibiting drastically different morphological properties. Widely applied shape-tuned attenuated crystal (AC) fcc models proved inadequate, yielding structured, coherent, and correlated fit residuals. However, equally simple discrete cluster models could account for the largest amplitude features in these difference signals. A hypothesis testing based approach to nanoparticle structure modeling systematically ruled out effects from crystallite size, composition, shape, and surface faceting as primary factors contributing to the AC misfit. On the other hand, decahedrally twinned cluster cores were found to be the origin of the AC structure misfits for a majority of the nanomaterials reported here. It is further motivated that the PDF can readily differentiate between the arrangement of domains in these multiply twinned motifs. Most of the nanomaterials surveyed also fall within the sub-5 nm size regime where traditional electron microscopy cannot easily detect and quantify domain structures, with sampling representative of the average nanocrystal synthesized. Here, the results demonstrate that PDF analysis is a powerful method for understanding internal atomic interfaces in small noble metallic nanomaterials. Such core cluster models, easily built algorithmically, should serve as starting structures for more advanced models able to capture atomic positional disorder, ligand induced or otherwise, near nanocrystal surfaces.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Density Functional Tight Binding Model with an Extended Basis Set and Three-Body Repulsion for Hydrogen under Extreme Thermodynamic Conditions

Here, we present a new DFTB-p3b density functional tight binding model for hydrogen at extremely high pressures and temperatures, which includes a polarizable basis set ( p ) and a three-body environmentally dependent repulsive potential ( 3b ). We find that use of an extended basis set is necessary under dissociated liquid conditions to account for the substantial p-orbital character of the electronic states around the Fermi energy. The repulsive energy is determined through comparison to cold curve pressures computed from density functional theory (DFT) for the hexagonal close-packed solid, as well as pressures from thermally equilibrated DFT-MD simulations of the liquid phase. In particular, we observe improved agreement in our DFTB-p3b model with previous theoretical and experimental results for the shock Hugoniot of hydrogen up to 100 GPa and 25000 K, compared to a standard DFTB model using pairwise interactions and an s-orbital basis set, only. In conclusion, the DFTB-p3b approach discussed here provides a general method to extend the DFTB method for a wide variety of materials over a significantly larger range of thermodynamic conditions than previously possible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonlocal Polyakov-Nambu-Jona-Lasinio model with wave function renormalization at finite temperature and chemical potential

We study the phase diagram of strongly interacting matter in the framework of a nonlocal SU(2) chiral quark model which includes wave function renormalization and coupling to the Polyakov loop. Both nonlocal interactions based on the frequently used exponential form factor, and on fits to the quark mass and renormalization functions obtained in lattice calculations are considered. Special attention is paid to the determination of the critical points, both in the chiral limit and at finite quark mass. In particular, we study the position of the critical end point as well as the value of the associated critical exponents for different model parametrizations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Numerical Optimization of Density Functional Tight Binding Models: Application to Molecules Containing Carbon, Hydrogen, Nitrogen, and Oxygen

New parametrizations for semiempirical density functional tight binding (DFTB) theory have been developed by the numerical optimization of adjustable parameters to minimize errors in the atomization energy and interatomic forces with respect to ab initio calculated data. Initial guesses for the radial dependences of the Slater- Koster bond integrals and overlap integrals were obtained from minimum basis density functional theory calculations. The radial dependences of the pair potentials and the bond and overlap integrals were represented by simple analytic functions. The adjustable parameters in these functions were optimized by simulated annealing and steepest descent algorithms to minimize the value of an objective function that quantifies the error between the DFTB model and ab initio calculated data. The accuracy and transferability of the resulting DFTB models for the C, H, N, and O system were assessed by comparing the predicted atomization energies and equilibrium molecular geometries of small molecules that were not included in the training data from DFTB to ab initio data. The DFTB models provide accurate predictions of the properties of hydrocarbons and more complex molecules containing C, H, N, and O.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling mixtures of thyroid gland function disruptors in a vertebrate alternative model, the zebrafish eleutheroembryo

Maternal thyroxine (T4) plays an essential role in fetal brain development, and even mild and transitory deficits in free-T4 in pregnant women can produce irreversible neurological effects in their offspring. Women of childbearing age are daily exposed to mixtures of chemicals disrupting the thyroid gland function (TGFDs) through the diet, drinking water, air and pharmaceuticals, which has raised the highest concern for the potential additive or synergic effects on the development of mild hypothyroxinemia during early pregnancy. Recently we demonstrated that zebrafish eleutheroembryos provide a suitable alternative model for screening chemicals impairing the thyroid hormone synthesis. The present study used the intrafollicular T4-content (IT4C) of zebrafish eleutheroembryos as integrative endpoint for testing the hypotheses that the effect of mixtures of TGFDs with a similar mode of action [inhibition of thyroid peroxidase (TPO)] was well predicted by a concentration addition concept (CA) model, whereas the response addition concept (RA) model predicted better the effect of dissimilarly acting binary mixtures of TGFDs [TPO-inhibitors and sodium-iodide symporter (NIS)-inhibitors]. However, CA model provided better prediction of joint effects than RA in five out of the six tested mixtures. The exception being the mixture MMI (TPO-inhibitor)-KClO{sub 4} (NIS-inhibitor) dosed at a fixed ratio of EC{sub 10} that provided similar CA and RA predictions and hence it was difficult to get any conclusive result. There results support the phenomenological similarity criterion stating that the concept of concentration addition could be extended to mixture constituents having common apical endpoints or common adverse outcomes. - Highlights: • Potential synergic or additive effect of mixtures of chemicals on thyroid function. • Zebrafish as alternative model for testing the effect of mixtures of goitrogens. • Concentration addition seems to predict better the effect of mixtures of goitrogens.

60 APPLIED LIFE SCIENCES↗

Optimization of global model composed of radial basis functions using the term-ranking approach

A term-ranking method is put forward to optimize the global model composed of radial basis functions to improve the predictability of the model. The effectiveness of the proposed method is examined by numerical simulation and experimental data. Numerical simulations indicate that this method can significantly lengthen the prediction time and decrease the Bayesian information criterion of the model. The application to real voice signal shows that the optimized global model can capture more predictable component in chaos-like voice data and simultaneously reduce the predictable component (periodic pitch) in the residual signal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A MULTIVARIATE FIT LUMINOSITY FUNCTION AND WORLD MODEL FOR LONG GAMMA-RAY BURSTS

It is proposed that the luminosity function, the rest-frame spectral correlations, and distributions of cosmological long-duration (Type-II) gamma-ray bursts (LGRBs) may be very well described as a multivariate log-normal distribution. This result is based on careful selection, analysis, and modeling of LGRBs' temporal and spectral variables in the largest catalog of GRBs available to date: 2130 BATSE GRBs, while taking into account the detection threshold and possible selection effects. Constraints on the joint rest-frame distribution of the isotropic peak luminosity (L{sub iso}), total isotropic emission (E{sub iso}), the time-integrated spectral peak energy (E{sub p,z}), and duration (T{sub 90,z}) of LGRBs are derived. The presented analysis provides evidence for a relatively large fraction of LGRBs that have been missed by the BATSE detector with E{sub iso} extending down to {approx}10{sup 49} erg and observed spectral peak energies (E{sub p} ) as low as {approx}5 keV. LGRBs with rest-frame duration T{sub 90,z} {approx}< 1 s or observer-frame duration T{sub 90} {approx}< 2 s appear to be rare events ({approx}< 0.1% chance of occurrence). The model predicts a fairly strong but highly significant correlation ({rho} = 0.58 {+-} 0.04) between E{sub iso} and E{sub p,z} of LGRBs. Also predicted are strong correlations of L{sub iso} and E{sub iso} with T{sub 90,z} and moderate correlation between L{sub iso} and E{sub p,z}. The strength and significance of the correlations found encourage the search for underlying mechanisms, though undermine their capabilities as probes of dark energy's equation of state at high redshifts. The presented analysis favors-but does not necessitate-a cosmic rate for BATSE LGRBs tracing metallicity evolution consistent with a cutoff Z/Z{sub Sun} {approx} 0.2-0.5, assuming no luminosity-redshift evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)

Tropical forest dynamics play a crucial role in the global carbon, water, and energy cycles. However, realistically simulating the dynamics of competition and coexistence between different plant functional types (PFTs) in tropical forests remains a significant challenge. This study aims to improve the modeling of PFT coexistence in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a vegetation demography model implemented in the Energy Exascale Earth System Model (E3SM) land model (ELM), ELM-FATES. Specifically, we explore (1) whether plant trait relationships established from field measurements can constrain ELM-FATES simulations and (2) whether machine learning (ML)-based surrogate models can emulate the complex ELM-FATES model and optimize parameter selections to improve PFT coexistence modeling. We conducted three ensembles of ELM-FATES experiments at a tropical forest site near Manaus, Brazil. By comparing the ensemble experiments without (Exp-CTR) and with (Exp-OBS) consideration of observed trait relationships, we found that accounting for these relationships slightly improves the simulations of water, energy, and carbon variables when compared to observations but degrades the simulation of PFT coexistence. Using ML-based surrogate models trained on Exp-CTR, we optimized the trait parameters in ELM-FATES and conducted another ensemble of experiments (Exp-ML) with these optimized parameters. The proportion of PFT coexistence experiments significantly increased from 21 % in Exp-CTR to 73 % in Exp-ML. After filtering the experiments that allow for PFT coexistence to agree with observations (within 15 % tolerance), 33 % of the Exp-ML experiments were retained, which is a significant improvement compared to the 1.4 % in Exp-CTR. Exp-ML also accurately reproduces the annual means and seasonal variations in water, energy, and carbon fluxes and the field inventory of aboveground biomass. This study represents a reproducible method that utilizes machine learning to identify parameter values that improve model fidelity against observations and PFT coexistence in vegetation demography models for diverse ecosystems. Our study also suggests the need for new mechanisms to enhance the robust simulation of coexisting plants in ELM-FATES and has significant implications for modeling the response and feedbacks of ecosystem dynamics to climate change.

54 ENVIRONMENTAL SCIENCES↗

Accuracy of the microcanonical Lanczos method to compute real-frequency dynamical spectral functions of quantum models at finite temperatures

We examine the accuracy of the microcanonical Lanczos method (MCLM) developed by Long et al. [Phys. Rev. B 68, 235106 (2003)] to compute dynamical spectral functions of interacting quantum models at finite temperatures. The MCLM is based on the microcanonical ensemble, which becomes exact in the thermodynamic limit. To apply the microcanonical ensemble at a fixed temperature, one has to find energy eigenstates with the energy eigenvalue corresponding to the internal energy in the canonical ensemble. Here in this paper, we propose to use thermal pure quantum state methods by Sugiura and Shimizu [Phys. Rev. Lett. 111, 010401 (2013)] to obtain the internal energy. After obtaining the energy eigenstates using the Lanczos diagonalization method, dynamical quantities are computed via a continued fraction expansion, a standard procedure for Lanczos-based numerical methods. Using one-dimensional antiferromagnetic Heisenberg chains with S = 1/2, we demonstrate that the proposed procedure is reasonably accurate, even for relatively small systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗