Phase stability of TiO 2 polymorphs from diffusion Quantum Monte Carlo

DOE PAGES

Luo, Ye; Benali, Anouar; Shulenburger, Luke; ...

2016-11-24

Titanium dioxide, TiO 2, has multiple applications in catalysis, energy conversion and memristive devices because of its electronic structure. Most of applications utilize the naturally existing phases: rutile, anatase and brookite. In spite of the simple form of TiO 2 and its wide uses, there is long- standing disagreement between theory and experiment on the energetic ordering of these phases that has never been resolved. We present the first analysis of phase stability at zero temperature using the highly accurate many-body fixed node diffusion Quantum Monte Carlo (QMC) method. We include temperature effects by calculating the Helmholtz free energy includingmore » both internal energy corrected by QMC and vibrational contributions from phonon calculations within the quasi harmonic approximation via density functional perturbation theory. Our QMC calculations find that anatase is the most stable phase at zero temperature, consistent with many previous mean- field calculations. Furthermore, at elevated temperatures, rutile becomes the most stable phase. For all finite temperatures, brookite is always the least stable phase.« less

Generalizing the self-healing diffusion Monte Carlo approach to finite temperature: A path for the optimization of low-energy many-body bases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reboredo, Fernando A.; Kim, Jeongnim

A statistical method is derived for the calculation of thermodynamic properties of many-body systems at low temperatures. This method is based on the self-healing diffusion Monte Carlo method for complex functions [F. A. Reboredo, J. Chem. Phys. 136, 204101 (2012)] and some ideas of the correlation function Monte Carlo approach [D. M. Ceperley and B. Bernu, J. Chem. Phys. 89, 6316 (1988)]. In order to allow the evolution in imaginary time to describe the density matrix, we remove the fixed-node restriction using complex antisymmetric guiding wave functions. In the process we obtain a parallel algorithm that optimizes a small subspacemore » of the many-body Hilbert space to provide maximum overlap with the subspace spanned by the lowest-energy eigenstates of a many-body Hamiltonian. We show in a model system that the partition function is progressively maximized within this subspace. We show that the subspace spanned by the small basis systematically converges towards the subspace spanned by the lowest energy eigenstates. Possible applications of this method for calculating the thermodynamic properties of many-body systems near the ground state are discussed. The resulting basis can also be used to accelerate the calculation of the ground or excited states with quantum Monte Carlo.« less

An efficient Monte Carlo-based algorithm for scatter correction in keV cone-beam CT

NASA Astrophysics Data System (ADS)

Poludniowski, G.; Evans, P. M.; Hansen, V. N.; Webb, S.

2009-06-01

A new method is proposed for scatter-correction of cone-beam CT images. A coarse reconstruction is used in initial iteration steps. Modelling of the x-ray tube spectra and detector response are included in the algorithm. Photon diffusion inside the imaging subject is calculated using the Monte Carlo method. Photon scoring at the detector is calculated using forced detection to a fixed set of node points. The scatter profiles are then obtained by linear interpolation. The algorithm is referred to as the coarse reconstruction and fixed detection (CRFD) technique. Scatter predictions are quantitatively validated against a widely used general-purpose Monte Carlo code: BEAMnrc/EGSnrc (NRCC, Canada). Agreement is excellent. The CRFD algorithm was applied to projection data acquired with a Synergy XVI CBCT unit (Elekta Limited, Crawley, UK), using RANDO and Catphan phantoms (The Phantom Laboratory, Salem NY, USA). The algorithm was shown to be effective in removing scatter-induced artefacts from CBCT images, and took as little as 2 min on a desktop PC. Image uniformity was greatly improved as was CT-number accuracy in reconstructions. This latter improvement was less marked where the expected CT-number of a material was very different to the background material in which it was embedded.

How large are nonadiabatic effects in atomic and diatomic systems?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Yubo, E-mail: yyang173@illinois.edu, E-mail: normantubman2015@u.northwestern.edu; Tubman, Norm M., E-mail: yyang173@illinois.edu, E-mail: normantubman2015@u.northwestern.edu; Ceperley, David M.

2015-09-28

With recent developments in simulating nonadiabatic systems to high accuracy, it has become possible to determine how much energy is attributed to nuclear quantum effects beyond zero-point energy. In this work, we calculate the non-relativistic ground-state energies of atomic and molecular systems without the Born-Oppenheimer approximation. For this purpose, we utilize the fixed-node diffusion Monte Carlo method, in which the nodes depend on both the electronic and ionic positions. We report ground-state energies for all systems studied, ionization energies for the first-row atoms and atomization energies for the first-row hydrides. We find the ionization energies of the atoms to bemore » nearly independent of the Born-Oppenheimer approximation, within the accuracy of our results. The atomization energies of molecular systems, however, show small effects of the nonadiabatic coupling between electrons and nuclei.« less

How large are nonadiabatic effects in atomic and diatomic systems?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Yubo; Kylänpää, Ilkka; Tubman, Norm M.

2015-09-29

With recent developments in simulating nonadiabatic systems to high accuracy, it has become possible to determine how much energy is attributed to nuclear quantum effects beyond zero-point energy. Here, we calculate the non-relativistic ground-state energies of atomic and molecular systems without the Born-Oppenheimer approximation. For this purpose, we utilize the fixed-node diffusion Monte Carlo method, in which the nodes depend on both the electronic and ionic positions. Our report shows the ground-state energies for all systems studied, ionization energies for the first-row atoms and atomization energies for the first-row hydrides. We find the ionization energies of the atoms to bemore » nearly independent of the Born-Oppenheimer approximation, within the accuracy of our results. The atomization energies of molecular systems, however, show small effects of the nonadiabatic coupling between electrons and nuclei.« less

Generalizing the self-healing diffusion Monte Carlo approach to finite temperature: a path for the optimization of low-energy many-body basis expansions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jeongnim; Reboredo, Fernando A.

The self-healing diffusion Monte Carlo method for complex functions [F. A. Reboredo J. Chem. Phys. {\\bf 136}, 204101 (2012)] and some ideas of the correlation function Monte Carlo approach [D. M. Ceperley and B. Bernu, J. Chem. Phys. {\\bf 89}, 6316 (1988)] are blended to obtain a method for the calculation of thermodynamic properties of many-body systems at low temperatures. In order to allow the evolution in imaginary time to describe the density matrix, we remove the fixed-node restriction using complex antisymmetric trial wave functions. A statistical method is derived for the calculation of finite temperature properties of many-body systemsmore » near the ground state. In the process we also obtain a parallel algorithm that optimizes the many-body basis of a small subspace of the many-body Hilbert space. This small subspace is optimized to have maximum overlap with the one expanded by the lower energy eigenstates of a many-body Hamiltonian. We show in a model system that the Helmholtz free energy is minimized within this subspace as the iteration number increases. We show that the subspace expanded by the small basis systematically converges towards the subspace expanded by the lowest energy eigenstates. Possible applications of this method to calculate the thermodynamic properties of many-body systems near the ground state are discussed. The resulting basis can be also used to accelerate the calculation of the ground or excited states with Quantum Monte Carlo.« less

Optimizing diffusion in multiplexes by maximizing layer dissimilarity

NASA Astrophysics Data System (ADS)

Serrano, Alfredo B.; Gómez-Gardeñes, Jesús; Andrade, Roberto F. S.

2017-05-01

Diffusion in a multiplex depends on the specific link distribution between the nodes in each layer, but also on the set of the intralayer and interlayer diffusion coefficients. In this work we investigate, in a quantitative way, the efficiency of multiplex diffusion as a function of the topological similarity among multiplex layers. This similarity is measured by the distance between layers, taken among the pairs of layers. Results are presented for a simple two-layer multiplex, where one of the layers is held fixed, while the other one can be rewired in a controlled way in order to increase or decrease the interlayer distance. The results indicate that, for fixed values of all intra- and interlayer diffusion coefficients, a large interlayer distance generally enhances the global multiplex diffusion, providing a topological mechanism to control the global diffusive process. For some sets of networks, we develop an algorithm to identify the most sensitive nodes in the rewirable layer, so that changes in a small set of connections produce a drastic enhancement of the global diffusion of the whole multiplex system.

Diffusion of a Concentrated Lattice Gas in a Regular Comb Structure

NASA Astrophysics Data System (ADS)

Garcia, Paul; Wentworth, Christopher

2008-10-01

Understanding diffusion in constrained geometries is of interest in a variety of contexts as varied as mass transport in disordered solids, such as a percolation cluster, or intercellular transport of water molecules in biological tissue. In this investigation we explore diffusion in a very simple constrained geometry: a comb-like structure involving a one-dimensional backbone of lattice sites with regularly spaced teeth of fixed length. The model considered assumes a fixed concentration of diffusing particles can hop to nearest-neighbor sites only, and they do not interact with each other except that double occupancy is not allowed. The system is simulated using a Monte Carlo simulation procedure. The mean-square displacement of a tagged particle is calculated from the simulation as a function of time. The simulation shows normal diffusive behavior after a period of anomalous diffusion that increases as the tooth size increases.

Density functional theory versus quantum Monte Carlo simulations of Fermi gases in the optical-lattice arena★

NASA Astrophysics Data System (ADS)

Pilati, Sebastiano; Zintchenko, Ilia; Troyer, Matthias; Ancilotto, Francesco

2018-04-01

We benchmark the ground state energies and the density profiles of atomic repulsive Fermi gases in optical lattices (OLs) computed via density functional theory (DFT) against the results of diffusion Monte Carlo (DMC) simulations. The main focus is on a half-filled one-dimensional OLs, for which the DMC simulations performed within the fixed-node approach provide unbiased results. This allows us to demonstrate that the local spin-density approximation (LSDA) to the exchange-correlation functional of DFT is very accurate in the weak and intermediate interactions regime, and also to underline its limitations close to the strongly-interacting Tonks-Girardeau limit and in very deep OLs. We also consider a three-dimensional OL at quarter filling, showing also in this case the high accuracy of the LSDA in the moderate interaction regime. The one-dimensional data provided in this study may represent a useful benchmark to further develop DFT methods beyond the LSDA and they will hopefully motivate experimental studies to accurately measure the equation of state of Fermi gases in higher-dimensional geometries. Supplementary material in the form of one pdf file available from the Journal web page at http://https://doi.org/10.1140/epjb/e2018-90021-1.

Importance of σ Bonding Electrons for the Accurate Description of Electron Correlation in Graphene.

PubMed

Zheng, Huihuo; Gan, Yu; Abbamonte, Peter; Wagner, Lucas K

2017-10-20

Electron correlation in graphene is unique because of the interplay between the Dirac cone dispersion of π electrons and long-range Coulomb interaction. Because of the zero density of states at Fermi level, the random phase approximation predicts no metallic screening at long distance and low energy, so one might expect that graphene should be a poorly screened system. However, empirically graphene is a weakly interacting semimetal, which leads to the question of how electron correlations take place in graphene at different length scales. We address this question by computing the equal time and dynamic structure factor S(q) and S(q,ω) of freestanding graphene using ab initio fixed-node diffusion Monte Carlo simulations and the random phase approximation. We find that the σ electrons contribute strongly to S(q,ω) for relevant experimental values of ω even at distances up to around 80 Å. These findings illustrate how the emergent physics from underlying Coulomb interactions results in the observed weakly correlated semimetal.

WARP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bergmann, Ryan M.; Rowland, Kelly L.

2017-04-12

WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed at UC Berkeley to efficiently execute on NVIDIA graphics processing unit (GPU) platforms. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo method, namely, that very few physical and geometrical simplifications are applied. WARP is able to calculate multiplication factors, neutron flux distributions (in both space and energy), and fission source distributions for time-independent neutron transport problems. It can run in both criticality or fixed source modes, but fixed source mode is currentlymore » not robust, optimized, or maintained in the newest version. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. The goal of developing WARP is to investigate algorithms that can grow into a full-featured, continuous energy, Monte Carlo neutron transport code that is accelerated by running on GPUs. The crux of the effort is to make Monte Carlo calculations faster while producing accurate results. Modern supercomputers are commonly being built with GPU coprocessor cards in their nodes to increase their computational efficiency and performance. GPUs execute efficiently on data-parallel problems, but most CPU codes, including those for Monte Carlo neutral particle transport, are predominantly task-parallel. WARP uses a data-parallel neutron transport algorithm to take advantage of the computing power GPUs offer.« less

Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema

PubMed Central

Chiang, Chia-Wen; Wang, Yong; Sun, Peng; Lin, Tsen-Hsuan; Trinkaus, Kathryn; Cross, Anne H.; Song, Sheng-Kwei

2014-01-01

The effect of extra-fiber structural and pathological components confounding diffusion tensor imaging (DTI) computation was quantitatively investigated using data generated by both Monte-Carlo simulations and tissue phantoms. Increased extent of vasogenic edema, by addition of various amount of gel to fixed normal mouse trigeminal nerves or by increasing non-restricted isotropic diffusion tensor components in Monte-Carlo simulations, significantly decreased fractional anisotropy (FA), increased radial diffusivity, while less significantly increased axial diffusivity derived by DTI. Increased cellularity, mimicked by graded increase of the restricted isotropic diffusion tensor component in Monte-Carlo simulations, significantly decreased FA and axial diffusivity with limited impact on radial diffusivity derived by DTI. The MC simulation and tissue phantom data were also analyzed by the recently developed diffusion basis spectrum imaging (DBSI) to simultaneously distinguish and quantify the axon/myelin integrity and extra-fiber diffusion components. Results showed that increased cellularity or vasogenic edema did not affect the DBSI-derived fiber FA, axial or radial diffusivity. Importantly, the extent of extra-fiber cellularity and edema estimated by DBSI correlated with experimentally added gel and Monte-Carlo simulations. We also examined the feasibility of applying 25-direction diffusion encoding scheme for DBSI analysis on coherent white matter tracts. Results from both phantom experiments and simulations suggested that the 25-direction diffusion scheme provided comparable DBSI estimation of both fiber diffusion parameters and extra-fiber cellularity/edema extent as those by 99-direction scheme. An in vivo 25-direction DBSI analysis was performed on experimental autoimmune encephalomyelitis (EAE, an animal model of human multiple sclerosis) optic nerve as an example to examine the validity of derived DBSI parameters with post-imaging immunohistochemistry verification. Results support that in vivo DBSI using 25-direction diffusion scheme correctly reflect the underlying axonal injury, demyelination, and inflammation of optic nerves in EAE mice. PMID:25017446

Optimal resource diffusion for suppressing disease spreading in multiplex networks

NASA Astrophysics Data System (ADS)

Chen, Xiaolong; Wang, Wei; Cai, Shimin; Stanley, H. Eugene; Braunstein, Lidia A.

2018-05-01

Resource diffusion is a ubiquitous phenomenon, but how it impacts epidemic spreading has received little study. We propose a model that couples epidemic spreading and resource diffusion in multiplex networks. The spread of disease in a physical contact layer and the recovery of the infected nodes are both strongly dependent upon resources supplied by their counterparts in the social layer. The generation and diffusion of resources in the social layer are in turn strongly dependent upon the state of the nodes in the physical contact layer. Resources diffuse preferentially or randomly in this model. To quantify the degree of preferential diffusion, a bias parameter that controls the resource diffusion is proposed. We conduct extensive simulations and find that the preferential resource diffusion can change phase transition type of the fraction of infected nodes. When the degree of interlayer correlation is below a critical value, increasing the bias parameter changes the phase transition from double continuous to single continuous. When the degree of interlayer correlation is above a critical value, the phase transition changes from multiple continuous to first discontinuous and then to hybrid. We find hysteresis loops in the phase transition. We also find that there is an optimal resource strategy at each fixed degree of interlayer correlation under which the threshold reaches a maximum and the disease can be maximally suppressed. In addition, the optimal controlling parameter increases as the degree of inter-layer correlation increases.

Quantum Monte Carlo with very large multideterminant wavefunctions.

PubMed

Scemama, Anthony; Applencourt, Thomas; Giner, Emmanuel; Caffarel, Michel

2016-07-01

An algorithm to compute efficiently the first two derivatives of (very) large multideterminant wavefunctions for quantum Monte Carlo calculations is presented. The calculation of determinants and their derivatives is performed using the Sherman-Morrison formula for updating the inverse Slater matrix. An improved implementation based on the reduction of the number of column substitutions and on a very efficient implementation of the calculation of the scalar products involved is presented. It is emphasized that multideterminant expansions contain in general a large number of identical spin-specific determinants: for typical configuration interaction-type wavefunctions the number of unique spin-specific determinants Ndetσ ( σ=↑,↓) with a non-negligible weight in the expansion is of order O(Ndet). We show that a careful implementation of the calculation of the Ndet -dependent contributions can make this step negligible enough so that in practice the algorithm scales as the total number of unique spin-specific determinants,  Ndet↑+Ndet↓, over a wide range of total number of determinants (here, Ndet up to about one million), thus greatly reducing the total computational cost. Finally, a new truncation scheme for the multideterminant expansion is proposed so that larger expansions can be considered without increasing the computational time. The algorithm is illustrated with all-electron fixed-node diffusion Monte Carlo calculations of the total energy of the chlorine atom. Calculations using a trial wavefunction including about 750,000 determinants with a computational increase of ∼400 compared to a single-determinant calculation are shown to be feasible. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Structure of LiPs ground and excited states

NASA Astrophysics Data System (ADS)

Bressanini, Dario

2018-01-01

The lithium atom in its ground state can bind positronium (Ps) forming LiPs, an electronically stable system. In this study we use the fixed node diffusion Monte Carlo method to perform a detailed investigation of the internal structure of LiPs, establishing to what extent it could be described by smaller interacting subsystems. To study the internal structure of positronic systems we propose a way to analyze the particle distribution functions: We first order the particle-nucleus distances, from the closest to the farthest. We then bin the ordered distances obtaining, for LiPs, five distribution functions that we call sorted distribution functions. We used them to show that Ps is a quite well-defined entity inside LiPs: The positron is forming positronium not only when it is far away from the nucleus, but also when it is in the same region of space occupied by the 2 s electrons. Hence, it is not correct to describe LiPs as positronium "orbiting" around a lithium atom, as sometimes has been done, since the positron penetrates the electronic distribution and can be found close to the nucleus.

Semi-stochastic full configuration interaction quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Holmes, Adam; Petruzielo, Frank; Khadilkar, Mihir; Changlani, Hitesh; Nightingale, M. P.; Umrigar, C. J.

2012-02-01

In the recently proposed full configuration interaction quantum Monte Carlo (FCIQMC) [1,2], the ground state is projected out stochastically, using a population of walkers each of which represents a basis state in the Hilbert space spanned by Slater determinants. The infamous fermion sign problem manifests itself in the fact that walkers of either sign can be spawned on a given determinant. We propose an improvement on this method in the form of a hybrid stochastic/deterministic technique, which we expect will improve the efficiency of the algorithm by ameliorating the sign problem. We test the method on atoms and molecules, e.g., carbon, carbon dimer, N2 molecule, and stretched N2. [4pt] [1] Fermion Monte Carlo without fixed nodes: a Game of Life, death and annihilation in Slater Determinant space. George Booth, Alex Thom, Ali Alavi. J Chem Phys 131, 050106, (2009).[0pt] [2] Survival of the fittest: Accelerating convergence in full configuration-interaction quantum Monte Carlo. Deidre Cleland, George Booth, and Ali Alavi. J Chem Phys 132, 041103 (2010).

The finite element model for the propagation of light in scattering media: a direct method for domains with nonscattering regions.

PubMed

Arridge, S R; Dehghani, H; Schweiger, M; Okada, E

2000-01-01

We present a method for handling nonscattering regions within diffusing domains. The method develops from an iterative radiosity-diffusion approach using Green's functions that was computationally slow. Here we present an improved implementation using a finite element method (FEM) that is direct. The fundamental idea is to introduce extra equations into the standard diffusion FEM to represent nondiffusive light propagation across a nonscattering region. By appropriate mesh node ordering the computational time is not much greater than for diffusion alone. We compare results from this method with those from a discrete ordinate transport code, and with Monte Carlo calculations. The agreement is very good, and, in addition, our scheme allows us to easily model time-dependent and frequency domain problems.

A Monte Carlo Simulation of Vesicle Exocytosis in the Buffered Diffusion of Calcium Channel Currents

NASA Astrophysics Data System (ADS)

Dimcovic, Z.; Eagan, T. P.; Brown, R. W.; Petschek, R. G.; Eppell, S. J.; Yunker, A. M. R.; Sharp, A. H.; McEnery, M. W.

2001-04-01

The voltage-dependent opening of calcium channels results in an influx of calcium ions that leads to the fusion of synaptic vesicles with the cell membrane, resulting in the release of neurotransmitters. This allows nerve impulses to be transmitted from one neuron to another. A Monte Carlo model of the three-dimensional diffusion of calcium following a channel opening is employed to estimate the space and time dependence of the calcium density. The effects of fixed and mobile calcium buffers are included, and a tethered nearby vesicle is considered. The importance of the size and location of the vesicle is studied. When the vesicle is ignored, these results are compared with the analytical calculations of Naraghi and Neher and the Monte Carlo calculations of Bennett et al. The finite-vesicle-size analysis offers new insights into the process of neurosecretion. Support: NIH MH55747, AHA 96001250, NSF 0086643, and CWRU Presidential Research Initiative grants.

Applications of flow-networks to opinion-dynamics

NASA Astrophysics Data System (ADS)

Tupikina, Liubov; Kurths, Jürgen

2015-04-01

Networks were successfully applied to describe complex systems, such as brain, climate, processes in society. Recently a socio-physical problem of opinion-dynamics was studied using network techniques. We present the toy-model of opinion-formation based on the physical model of advection-diffusion. We consider spreading of the opinion on the fixed subject, assuming that opinion on society is binary: if person has opinion then the state of the node in the society-network equals 1, if the person doesn't have opinion state of the node equals 0. Opinion can be spread from one person to another if they know each other, or in the network-terminology, if the nodes are connected. We include into the system governed by advection-diffusion equation the external field to model such effects as for instance influence from media. The assumptions for our model can be formulated as the following: 1.the node-states are influenced by the network structure in such a way, that opinion can be spread only between adjacent nodes (the advective term of the opinion-dynamics), 2.the network evolution can have two scenarios: -network topology is not changing with time; -additional links can appear or disappear each time-step with fixed probability which requires adaptive networks properties. Considering these assumptions for our system we obtain the system of equations describing our model-dynamics which corresponds well to other socio-physics models, for instance, the model of the social cohesion and the famous voter-model. We investigate the behavior of the suggested model studying "waiting time" of the system, time to get to the stable state, stability of the model regimes for different values of model parameters and network topology.

The Fluctuation-Dissipation Theorem of Colloidal Particle's energy on 2D Periodic Substrates: A Monte Carlo Study of thermal noise-like fluctuation and diffusion like Brownian motion

NASA Astrophysics Data System (ADS)

Najafi, Amin

2014-05-01

Using the Monte Carlo simulations, we have calculated mean-square fluctuations in statistical mechanics, such as those for colloids energy configuration are set on square 2D periodic substrates interacting via a long range screened Coulomb potential on any specific and fixed substrate. Random fluctuations with small deviations from the state of thermodynamic equilibrium arise from the granular structure of them and appear as thermal diffusion with Gaussian distribution structure as well. The variations are showing linear form of the Fluctuation-Dissipation Theorem on the energy of particles constitutive a canonical ensemble with continuous diffusion process of colloidal particle systems. The noise-like variation of the energy per particle and the order parameter versus the Brownian displacement of sum of large number of random steps of particles at low temperatures phase are presenting a markovian process on colloidal particles configuration, too.

"An estimate of the probability of vesicle exocytosis in a Monte Carlo model of buffered diffusion of calcium channel currents"

NASA Astrophysics Data System (ADS)

Dimcovic, Z. M.; Eagan, T. P.; Kidane, T. K.; Brown, R. W.; Petschek, R. G.; McEnery, M. W.

2001-10-01

The opening of voltage-dependent calcium channels results in an influx of calcium ions promoting the fusion of synaptic vesicles. The fusion leads to release of neurotransmitters, which in turn allow the propagation of nerve impulses. A Monte Carlo model of the diffusion of calcium following its surge into the cell is used to estimate the probability for exocytosis. Besides the calcium absorption by fixed and mobile buffers, key ingredients are the physical size and position of the tethered vesicle and a sensing model for the interaction of the vesicle and calcium. The release probability is compared to previously published studies where the finite vesicle size was not considered. (Supported by NIH MH55747, AHA 96001250, NSF0086643, and a CWRU Presidential Research Initiative grant.)

Path integral Monte Carlo and the electron gas

NASA Astrophysics Data System (ADS)

Brown, Ethan W.

Path integral Monte Carlo is a proven method for accurately simulating quantum mechanical systems at finite-temperature. By stochastically sampling Feynman's path integral representation of the quantum many-body density matrix, path integral Monte Carlo includes non-perturbative effects like thermal fluctuations and particle correlations in a natural way. Over the past 30 years, path integral Monte Carlo has been successfully employed to study the low density electron gas, high-pressure hydrogen, and superfluid helium. For systems where the role of Fermi statistics is important, however, traditional path integral Monte Carlo simulations have an exponentially decreasing efficiency with decreased temperature and increased system size. In this thesis, we work towards improving this efficiency, both through approximate and exact methods, as specifically applied to the homogeneous electron gas. We begin with a brief overview of the current state of atomic simulations at finite-temperature before we delve into a pedagogical review of the path integral Monte Carlo method. We then spend some time discussing the one major issue preventing exact simulation of Fermi systems, the sign problem. Afterwards, we introduce a way to circumvent the sign problem in PIMC simulations through a fixed-node constraint. We then apply this method to the homogeneous electron gas at a large swatch of densities and temperatures in order to map out the warm-dense matter regime. The electron gas can be a representative model for a host of real systems, from simple medals to stellar interiors. However, its most common use is as input into density functional theory. To this end, we aim to build an accurate representation of the electron gas from the ground state to the classical limit and examine its use in finite-temperature density functional formulations. The latter half of this thesis focuses on possible routes beyond the fixed-node approximation. As a first step, we utilize the variational principle inherent in the path integral Monte Carlo method to optimize the nodal surface. By using a ansatz resembling a free particle density matrix, we make a unique connection between a nodal effective mass and the traditional effective mass of many-body quantum theory. We then propose and test several alternate nodal ansatzes and apply them to single atomic systems. Finally, we propose a method to tackle the sign problem head on, by leveraging the relatively simple structure of permutation space. Using this method, we find we can perform exact simulations this of the electron gas and 3He that were previously impossible.

Information loss and reconstruction in diffuse fluorescence tomography

PubMed Central

Bonfert-Taylor, Petra; Leblond, Frederic; Holt, Robert W.; Tichauer, Kenneth; Pogue, Brian W.; Taylor, Edward C.

2012-01-01

This paper is a theoretical exploration of spatial resolution in diffuse fluorescence tomography. It is demonstrated that, given a fixed imaging geometry, one cannot—relative to standard techniques such as Tikhonov regularization and truncated singular value decomposition—improve the spatial resolution of the optical reconstructions via increasing the node density of the mesh considered for modeling light transport. Using techniques from linear algebra, it is shown that, as one increases the number of nodes beyond the number of measurements, information is lost by the forward model. It is demonstrated that this information cannot be recovered using various common reconstruction techniques. Evidence is provided showing that this phenomenon is related to the smoothing properties of the elliptic forward model that is used in the diffusion approximation to light transport in tissue. This argues for reconstruction techniques that are sensitive to boundaries, such as L1-reconstruction and the use of priors, as well as the natural approach of building a measurement geometry that reflects the desired image resolution. PMID:22472763

Understanding quantum tunneling using diffusion Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Inack, E. M.; Giudici, G.; Parolini, T.; Santoro, G.; Pilati, S.

2018-03-01

In simple ferromagnetic quantum Ising models characterized by an effective double-well energy landscape the characteristic tunneling time of path-integral Monte Carlo (PIMC) simulations has been shown to scale as the incoherent quantum-tunneling time, i.e., as 1 /Δ2 , where Δ is the tunneling gap. Since incoherent quantum tunneling is employed by quantum annealers (QAs) to solve optimization problems, this result suggests that there is no quantum advantage in using QAs with respect to quantum Monte Carlo (QMC) simulations. A counterexample is the recently introduced shamrock model (Andriyash and Amin, arXiv:1703.09277), where topological obstructions cause an exponential slowdown of the PIMC tunneling dynamics with respect to incoherent quantum tunneling, leaving open the possibility for potential quantum speedup, even for stoquastic models. In this work we investigate the tunneling time of projective QMC simulations based on the diffusion Monte Carlo (DMC) algorithm without guiding functions, showing that it scales as 1 /Δ , i.e., even more favorably than the incoherent quantum-tunneling time, both in a simple ferromagnetic system and in the more challenging shamrock model. However, a careful comparison between the DMC ground-state energies and the exact solution available for the transverse-field Ising chain indicates an exponential scaling of the computational cost required to keep a fixed relative error as the system size increases.

SU-E-T-222: Computational Optimization of Monte Carlo Simulation On 4D Treatment Planning Using the Cloud Computing Technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chow, J

Purpose: This study evaluated the efficiency of 4D lung radiation treatment planning using Monte Carlo simulation on the cloud. The EGSnrc Monte Carlo code was used in dose calculation on the 4D-CT image set. Methods: 4D lung radiation treatment plan was created by the DOSCTP linked to the cloud, based on the Amazon elastic compute cloud platform. Dose calculation was carried out by Monte Carlo simulation on the 4D-CT image set on the cloud, and results were sent to the FFD4D image deformation program for dose reconstruction. The dependence of computing time for treatment plan on the number of computemore » node was optimized with variations of the number of CT image set in the breathing cycle and dose reconstruction time of the FFD4D. Results: It is found that the dependence of computing time on the number of compute node was affected by the diminishing return of the number of node used in Monte Carlo simulation. Moreover, the performance of the 4D treatment planning could be optimized by using smaller than 10 compute nodes on the cloud. The effects of the number of image set and dose reconstruction time on the dependence of computing time on the number of node were not significant, as more than 15 compute nodes were used in Monte Carlo simulations. Conclusion: The issue of long computing time in 4D treatment plan, requiring Monte Carlo dose calculations in all CT image sets in the breathing cycle, can be solved using the cloud computing technology. It is concluded that the optimized number of compute node selected in simulation should be between 5 and 15, as the dependence of computing time on the number of node is significant.« less

Comparison of flat cleaved and cylindrical diffusing fibers as treatment sources for interstitial photodynamic therapy.

PubMed

Baran, Timothy M; Foster, Thomas H

2014-02-01

For interstitial photodynamic therapy (iPDT) of bulky tumors, careful treatment planning is required in order to ensure that a therapeutic dose is delivered to the tumor, while minimizing damage to surrounding normal tissue. In clinical contexts, iPDT has typically been performed with either flat cleaved or cylindrical diffusing optical fibers as light sources. Here, the authors directly compare these two source geometries in terms of the number of fibers and duration of treatment required to deliver a prescribed light dose to a tumor volume. Treatment planning software for iPDT was developed based on graphics processing unit enhanced Monte Carlo simulations. This software was used to optimize the number of fibers, total energy delivered by each fiber, and the position of individual fibers in order to deliver a target light dose (D90) to 90% of the tumor volume. Treatment plans were developed using both flat cleaved and cylindrical diffusing fibers, based on tissue volumes derived from CT data from a head and neck cancer patient. Plans were created for four cases: fixed energy per fiber, fixed number of fibers, and in cases where both or neither of these factors were fixed. When the number of source fibers was fixed at eight, treatment plans based on flat cleaved fibers required each to deliver 7180-8080 J in order to deposit 90 J/cm(2) in 90% of the tumor volume. For diffusers, each fiber was required to deliver 2270-2350 J (333-1178 J/cm) in order to achieve this same result. For the case of fibers delivering a fixed 900 J, 13 diffusers or 19 flat cleaved fibers at a spacing of 1 cm were required to deliver the desired dose. With energy per fiber fixed at 2400 J and the number of fibers fixed at eight, diffuser fibers delivered the desired dose to 93% of the tumor volume, while flat cleaved fibers delivered this dose to 79%. With both energy and number of fibers allowed to vary, six diffusers delivering 3485-3600 J were required, compared to ten flat cleaved fibers delivering 2780-3600 J. For the same number of fibers, cylindrical diffusers allow for a shorter treatment duration compared to flat cleaved fibers. For the same energy delivered per fiber, diffusers allow for the insertion of fewer fibers in order to deliver the same light dose to a target volume.

Dielectric response of periodic systems from quantum Monte Carlo calculations.

PubMed

Umari, P; Willamson, A J; Galli, Giulia; Marzari, Nicola

2005-11-11

We present a novel approach that allows us to calculate the dielectric response of periodic systems in the quantum Monte Carlo formalism. We employ a many-body generalization for the electric-enthalpy functional, where the coupling with the field is expressed via the Berry-phase formulation for the macroscopic polarization. A self-consistent local Hamiltonian then determines the ground-state wave function, allowing for accurate diffusion quantum Monte Carlo calculations where the polarization's fixed point is estimated from the average on an iterative sequence, sampled via forward walking. This approach has been validated for the case of an isolated hydrogen atom and then applied to a periodic system, to calculate the dielectric susceptibility of molecular-hydrogen chains. The results found are in excellent agreement with the best estimates obtained from the extrapolation of quantum-chemistry calculations.

Multigroup Monte Carlo on GPUs: Comparison of history- and event-based algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamilton, Steven P.; Slattery, Stuart R.; Evans, Thomas M.

This article presents an investigation of the performance of different multigroup Monte Carlo transport algorithms on GPUs with a discussion of both history-based and event-based approaches. Several algorithmic improvements are introduced for both approaches. By modifying the history-based algorithm that is traditionally favored in CPU-based MC codes to occasionally filter out dead particles to reduce thread divergence, performance exceeds that of either the pure history-based or event-based approaches. The impacts of several algorithmic choices are discussed, including performance studies on Kepler and Pascal generation NVIDIA GPUs for fixed source and eigenvalue calculations. Single-device performance equivalent to 20–40 CPU cores onmore » the K40 GPU and 60–80 CPU cores on the P100 GPU is achieved. Last, in addition, nearly perfect multi-device parallel weak scaling is demonstrated on more than 16,000 nodes of the Titan supercomputer.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tokár, K.; Derian, R.; Mitas, L.

Using explicitly correlated fixed-node quantum Monte Carlo and density functional theory (DFT) methods, we study electronic properties, ground-state multiplets, ionization potentials, electron affinities, and low-energy fragmentation channels of charged half-sandwich and multidecker vanadium-benzene systems with up to 3 vanadium atoms, including both anions and cations. It is shown that, particularly in anions, electronic correlations play a crucial role; these effects are not systematically captured with any commonly used DFT functionals such as gradient corrected, hybrids, and range-separated hybrids. On the other hand, tightly bound cations can be described qualitatively by DFT. A comparison of DFT and quantum Monte Carlo providesmore » an in-depth understanding of the electronic structure and properties of these correlated systems. The calculations also serve as a benchmark study of 3d molecular anions that require a balanced many-body description of correlations at both short- and long-range distances.« less

Multigroup Monte Carlo on GPUs: Comparison of history- and event-based algorithms

DOE PAGES

Hamilton, Steven P.; Slattery, Stuart R.; Evans, Thomas M.

2017-12-22

This article presents an investigation of the performance of different multigroup Monte Carlo transport algorithms on GPUs with a discussion of both history-based and event-based approaches. Several algorithmic improvements are introduced for both approaches. By modifying the history-based algorithm that is traditionally favored in CPU-based MC codes to occasionally filter out dead particles to reduce thread divergence, performance exceeds that of either the pure history-based or event-based approaches. The impacts of several algorithmic choices are discussed, including performance studies on Kepler and Pascal generation NVIDIA GPUs for fixed source and eigenvalue calculations. Single-device performance equivalent to 20–40 CPU cores onmore » the K40 GPU and 60–80 CPU cores on the P100 GPU is achieved. Last, in addition, nearly perfect multi-device parallel weak scaling is demonstrated on more than 16,000 nodes of the Titan supercomputer.« less

Information transmission on hybrid networks

NASA Astrophysics Data System (ADS)

Chen, Rongbin; Cui, Wei; Pu, Cunlai; Li, Jie; Ji, Bo; Gakis, Konstantinos; Pardalos, Panos M.

2018-01-01

Many real-world communication networks often have hybrid nature with both fixed nodes and moving modes, such as the mobile phone networks mainly composed of fixed base stations and mobile phones. In this paper, we discuss the information transmission process on the hybrid networks with both fixed and mobile nodes. The fixed nodes (base stations) are connected as a spatial lattice on the plane forming the information-carrying backbone, while the mobile nodes (users), which are the sources and destinations of information packets, connect to their current nearest fixed nodes respectively to deliver and receive information packets. We observe the phase transition of traffic load in the hybrid network when the packet generation rate goes from below and then above a critical value, which measures the network capacity of packets delivery. We obtain the optimal speed of moving nodes leading to the maximum network capacity. We further improve the network capacity by rewiring the fixed nodes and by considering the current load of fixed nodes during packets transmission. Our purpose is to optimize the network capacity of hybrid networks from the perspective of network science, and provide some insights for the construction of future communication infrastructures.

Diffusion Monte Carlo approach versus adiabatic computation for local Hamiltonians

NASA Astrophysics Data System (ADS)

Bringewatt, Jacob; Dorland, William; Jordan, Stephen P.; Mink, Alan

2018-02-01

Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real non-negative amplitudes and thus for whom destructive interference is not manifest. This raises the question of whether classical Monte Carlo algorithms can efficiently simulate quantum adiabatic optimization with stoquastic Hamiltonians. Recent results have given counterexamples in which path-integral and diffusion Monte Carlo fail to do so. However, most adiabatic optimization algorithms, such as for solving MAX-k -SAT problems, use k -local Hamiltonians, whereas our previous counterexample for diffusion Monte Carlo involved n -body interactions. Here we present a 6-local counterexample which demonstrates that even for these local Hamiltonians there are cases where diffusion Monte Carlo cannot efficiently simulate quantum adiabatic optimization. Furthermore, we perform empirical testing of diffusion Monte Carlo on a standard well-studied class of permutation-symmetric tunneling problems and similarly find large advantages for quantum optimization over diffusion Monte Carlo.

Secure Multicast Tree Structure Generation Method for Directed Diffusion Using A* Algorithms

NASA Astrophysics Data System (ADS)

Kim, Jin Myoung; Lee, Hae Young; Cho, Tae Ho

The application of wireless sensor networks to areas such as combat field surveillance, terrorist tracking, and highway traffic monitoring requires secure communication among the sensor nodes within the networks. Logical key hierarchy (LKH) is a tree based key management model which provides secure group communication. When a sensor node is added or evicted from the communication group, LKH updates the group key in order to ensure the security of the communications. In order to efficiently update the group key in directed diffusion, we propose a method for secure multicast tree structure generation, an extension to LKH that reduces the number of re-keying messages by considering the addition and eviction ratios of the history data. For the generation of the proposed key tree structure the A* algorithm is applied, in which the branching factor at each level can take on different value. The experiment results demonstrate the efficiency of the proposed key tree structure against the existing key tree structures of fixed branching factors.

Efficiency analysis of diffusion on T-fractals in the sense of random walks.

PubMed

Peng, Junhao; Xu, Guoai

2014-04-07

Efficiently controlling the diffusion process is crucial in the study of diffusion problem in complex systems. In the sense of random walks with a single trap, mean trapping time (MTT) and mean diffusing time (MDT) are good measures of trapping efficiency and diffusion efficiency, respectively. They both vary with the location of the node. In this paper, we analyze the effects of node's location on trapping efficiency and diffusion efficiency of T-fractals measured by MTT and MDT. First, we provide methods to calculate the MTT for any target node and the MDT for any source node of T-fractals. The methods can also be used to calculate the mean first-passage time between any pair of nodes. Then, using the MTT and the MDT as the measure of trapping efficiency and diffusion efficiency, respectively, we compare the trapping efficiency and diffusion efficiency among all nodes of T-fractal and find the best (or worst) trapping sites and the best (or worst) diffusing sites. Our results show that the hub node of T-fractal is the best trapping site, but it is also the worst diffusing site; and that the three boundary nodes are the worst trapping sites, but they are also the best diffusing sites. Comparing the maximum of MTT and MDT with their minimums, we find that the maximum of MTT is almost 6 times of the minimum of MTT and the maximum of MDT is almost equal to the minimum for MDT. Thus, the location of target node has large effect on the trapping efficiency, but the location of source node almost has no effect on diffusion efficiency. We also simulate random walks on T-fractals, whose results are consistent with the derived results.

Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce

PubMed Central

Pratx, Guillem; Xing, Lei

2011-01-01

Monte Carlo simulation is considered the most reliable method for modeling photon migration in heterogeneous media. However, its widespread use is hindered by the high computational cost. The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. We ported the MC321 Monte Carlo package to Hadoop, an open-source MapReduce framework. In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. The simulation time was found to be linearly dependent on the number of photons and inversely proportional to the number of nodes. For a cluster size of 240 nodes, the simulation of 100 billion photon histories took 22 min, a 1258 × speed-up compared to the single-threaded Monte Carlo program. The overall computational throughput was 85,178 photon histories per node per second, with a latency of 100 s. The distributed simulation produced the same output as the original implementation and was resilient to hardware failure: the correctness of the simulation was unaffected by the shutdown of 50% of the nodes. PMID:22191916

Determination of fluence rate and temperature distributions in the rat brain; implications for photodynamic therapy.

PubMed

Angell-Petersen, Even; Hirschberg, Henry; Madsen, Steen J

2007-01-01

Light and heat distributions are measured in a rat glioma model used in photodynamic therapy. A fiber delivering 632-nm light is fixed in the brain of anesthetized BDIX rats. Fluence rates are measured using calibrated isotropic probes that are positioned stereotactically. Mathematical models are then used to derive tissue optical properties, enabling calculation of fluence rate distributions for general tumor and light application geometries. The fluence rates in tumor-free brains agree well with the models based on diffusion theory and Monte Carlo simulation. In both cases, the best fit is found for absorption and reduced scattering coefficients of 0.57 and 28 cm(-1), respectively. In brains with implanted BT(4)C tumors, a discrepancy between diffusion and Monte Carlo-derived two-layer models is noted. Both models suggest that tumor tissue has higher absorption and less scattering than normal brain. Temperatures are measured by inserting thermocouples directly into tumor-free brains. A model based on diffusion theory and the bioheat equation is found to be in good agreement with the experimental data and predict a thermal penetration depth of 0.60 cm in normal rat brain. The predicted parameters can be used to estimate the fluences, fluence rates, and temperatures achieved during photodynamic therapy.

Puzzle of magnetic moments of Ni clusters revisited using quantum Monte Carlo method.

PubMed

Lee, Hung-Wen; Chang, Chun-Ming; Hsing, Cheng-Rong

2017-02-28

The puzzle of the magnetic moments of small nickel clusters arises from the discrepancy between values predicted using density functional theory (DFT) and experimental measurements. Traditional DFT approaches underestimate the magnetic moments of nickel clusters. Two fundamental problems are associated with this puzzle, namely, calculating the exchange-correlation interaction accurately and determining the global minimum structures of the clusters. Theoretically, the two problems can be solved using quantum Monte Carlo (QMC) calculations and the ab initio random structure searching (AIRSS) method correspondingly. Therefore, we combined the fixed-moment AIRSS and QMC methods to investigate the magnetic properties of Ni n (n = 5-9) clusters. The spin moments of the diffusion Monte Carlo (DMC) ground states are higher than those of the Perdew-Burke-Ernzerhof ground states and, in the case of Ni 8-9 , two new ground-state structures have been discovered using the DMC calculations. The predicted results are closer to the experimental findings, unlike the results predicted in previous standard DFT studies.

Improved knowledge diffusion model based on the collaboration hypernetwork

NASA Astrophysics Data System (ADS)

Wang, Jiang-Pan; Guo, Qiang; Yang, Guang-Yong; Liu, Jian-Guo

2015-06-01

The process for absorbing knowledge becomes an essential element for innovation in firms and in adapting to changes in the competitive environment. In this paper, we present an improved knowledge diffusion hypernetwork (IKDH) model based on the idea that knowledge will spread from the target node to all its neighbors in terms of the hyperedge and knowledge stock. We apply the average knowledge stock V(t) , the variable σ2(t) , and the variance coefficient c(t) to evaluate the performance of knowledge diffusion. By analyzing different knowledge diffusion ways, selection ways of the highly knowledgeable nodes, hypernetwork sizes and hypernetwork structures for the performance of knowledge diffusion, results show that the diffusion speed of IKDH model is 3.64 times faster than that of traditional knowledge diffusion (TKDH) model. Besides, it is three times faster to diffuse knowledge by randomly selecting "expert" nodes than that by selecting large-hyperdegree nodes as "expert" nodes. Furthermore, either the closer network structure or smaller network size results in the faster knowledge diffusion.

Ferromagnetic transition in a simple variant of the Ising model on multiplex networks

NASA Astrophysics Data System (ADS)

Krawiecki, A.

2018-02-01

Multiplex networks consist of a fixed set of nodes connected by several sets of edges which are generated separately and correspond to different networks ("layers"). Here, a simple variant of the Ising model on multiplex networks with two layers is considered, with spins located in the nodes and edges corresponding to ferromagnetic interactions between them. Critical temperatures for the ferromagnetic transition are evaluated for the layers in the form of random Erdös-Rényi graphs or heterogeneous scale-free networks using the mean-field approximation and the replica method, from the replica symmetric solution. Both methods require the use of different "partial" magnetizations, associated with different layers of the multiplex network, and yield qualitatively similar results. If the layers are strongly heterogeneous the critical temperature differs noticeably from that for the Ising model on a network being a superposition of the two layers, evaluated in the mean-field approximation neglecting the effect of the underlying multiplex structure on the correlations between the degrees of nodes. The critical temperature evaluated from the replica symmetric solution depends sensitively on the correlations between the degrees of nodes in different layers and shows satisfactory quantitative agreement with that obtained from Monte Carlo simulations. The critical behavior of the magnetization for the model with strongly heterogeneous layers can depend on the distributions of the degrees of nodes and is then determined by the properties of the most heterogeneous layer.

A Hierarchical Bayesian Model for Calibrating Estimates of Species Divergence Times

PubMed Central

Heath, Tracy A.

2012-01-01

In Bayesian divergence time estimation methods, incorporating calibrating information from the fossil record is commonly done by assigning prior densities to ancestral nodes in the tree. Calibration prior densities are typically parametric distributions offset by minimum age estimates provided by the fossil record. Specification of the parameters of calibration densities requires the user to quantify his or her prior knowledge of the age of the ancestral node relative to the age of its calibrating fossil. The values of these parameters can, potentially, result in biased estimates of node ages if they lead to overly informative prior distributions. Accordingly, determining parameter values that lead to adequate prior densities is not straightforward. In this study, I present a hierarchical Bayesian model for calibrating divergence time analyses with multiple fossil age constraints. This approach applies a Dirichlet process prior as a hyperprior on the parameters of calibration prior densities. Specifically, this model assumes that the rate parameters of exponential prior distributions on calibrated nodes are distributed according to a Dirichlet process, whereby the rate parameters are clustered into distinct parameter categories. Both simulated and biological data are analyzed to evaluate the performance of the Dirichlet process hyperprior. Compared with fixed exponential prior densities, the hierarchical Bayesian approach results in more accurate and precise estimates of internal node ages. When this hyperprior is applied using Markov chain Monte Carlo methods, the ages of calibrated nodes are sampled from mixtures of exponential distributions and uncertainty in the values of calibration density parameters is taken into account. PMID:22334343

Influence maximization in complex networks through optimal percolation

NASA Astrophysics Data System (ADS)

Morone, Flaviano; Makse, Hernan; CUNY Collaboration; CUNY Collaboration

The whole frame of interconnections in complex networks hinges on a specific set of structural nodes, much smaller than the total size, which, if activated, would cause the spread of information to the whole network, or, if immunized, would prevent the diffusion of a large scale epidemic. Localizing this optimal, that is, minimal, set of structural nodes, called influencers, is one of the most important problems in network science. Here we map the problem onto optimal percolation in random networks to identify the minimal set of influencers, which arises by minimizing the energy of a many-body system, where the form of the interactions is fixed by the non-backtracking matrix of the network. Big data analyses reveal that the set of optimal influencers is much smaller than the one predicted by previous heuristic centralities. Remarkably, a large number of previously neglected weakly connected nodes emerges among the optimal influencers. Reference: F. Morone, H. A. Makse, Nature 524,65-68 (2015)

THEORY OF SOLAR MERIDIONAL CIRCULATION AT HIGH LATITUDES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dikpati, Mausumi; Gilman, Peter A., E-mail: dikpati@ucar.edu, E-mail: gilman@ucar.edu

2012-02-10

We build a hydrodynamic model for computing and understanding the Sun's large-scale high-latitude flows, including Coriolis forces, turbulent diffusion of momentum, and gyroscopic pumping. Side boundaries of the spherical 'polar cap', our computational domain, are located at latitudes {>=} 60 Degree-Sign . Implementing observed low-latitude flows as side boundary conditions, we solve the flow equations for a Cartesian analog of the polar cap. The key parameter that determines whether there are nodes in the high-latitude meridional flow is {epsilon} = 2{Omega}n{pi}H{sup 2}/{nu}, where {Omega} is the interior rotation rate, n is the radial wavenumber of the meridional flow, H ismore » the depth of the convection zone, and {nu} is the turbulent viscosity. The smaller the {epsilon} (larger turbulent viscosity), the fewer the number of nodes in high latitudes. For all latitudes within the polar cap, we find three nodes for {nu} = 10{sup 12} cm{sup 2} s{sup -1}, two for 10{sup 13}, and one or none for 10{sup 15} or higher. For {nu} near 10{sup 14} our model exhibits 'node merging': as the meridional flow speed is increased, two nodes cancel each other, leaving no nodes. On the other hand, for fixed flow speed at the boundary, as {nu} is increased the poleward-most node migrates to the pole and disappears, ultimately for high enough {nu} leaving no nodes. These results suggest that primary poleward surface meridional flow can extend from 60 Degree-Sign to the pole either by node merging or by node migration and disappearance.« less

Monte Carlo simulation of the mixed alkali effect with cooperative jumps

NASA Astrophysics Data System (ADS)

Habasaki, Junko; Hiwatari, Yasuaki

2000-12-01

In our previous works on molecular dynamics (MD) simulations of lithium metasilicate (Li2SiO3), it has been shown that the long time behavior of the lithium ions in Li2SiO3 has been characterized by the component showing the enhanced diffusion (Lévy flight) due to cooperative jumps. It has also been confirmed that the contribution of such component decreases by interception of the paths in the mixed alkali silicate (LiKSiO3). Namely, cooperative jumps of like ions are much decreased in number owing to the interception of the path for unlike alkali-metal ions. In the present work, we have performed a Monte Carlo simulation using a cubic lattice in order to establish the role of the cooperative jumps in the transport properties in a mixed alkali glass. Fixed particles (blockage) were introduced instead of the interception of the jump paths for unlike alkali-metal ions. Two types of cooperative motions (a pull type and a push type) were taken into account. Low-dimensionality of the jump path caused by blockage resulted in a decrease of a diffusion coefficient of the particles. The effect of blockage is enhanced when the cooperative motions were introduced.

Multiple Factors-Aware Diffusion in Social Networks

DTIC Science & Technology

2015-05-22

Multiple Factors-Aware Diffusion in Social Networks Chung-Kuang Chou(B) and Ming-Syan Chen Department of Electrical Engineering, National Taiwan...propagates from nodes to nodes over a social network . The behavior that a node adopts an information piece in a social network can be affected by...Twitter dataset. Keywords: Social networks · Diffusion models 1 Introduction Information diffusion in social networks has been an active research field

Using hybrid implicit Monte Carlo diffusion to simulate gray radiation hydrodynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cleveland, Mathew A., E-mail: cleveland7@llnl.gov; Gentile, Nick

This work describes how to couple a hybrid Implicit Monte Carlo Diffusion (HIMCD) method with a Lagrangian hydrodynamics code to evaluate the coupled radiation hydrodynamics equations. This HIMCD method dynamically applies Implicit Monte Carlo Diffusion (IMD) [1] to regions of a problem that are opaque and diffusive while applying standard Implicit Monte Carlo (IMC) [2] to regions where the diffusion approximation is invalid. We show that this method significantly improves the computational efficiency as compared to a standard IMC/Hydrodynamics solver, when optically thick diffusive material is present, while maintaining accuracy. Two test cases are used to demonstrate the accuracy andmore » performance of HIMCD as compared to IMC and IMD. The first is the Lowrie semi-analytic diffusive shock [3]. The second is a simple test case where the source radiation streams through optically thin material and heats a thick diffusive region of material causing it to rapidly expand. We found that HIMCD proves to be accurate, robust, and computationally efficient for these test problems.« less

Linear and Non-Linear Dielectric Response of Periodic Systems from Quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Umari, Paolo

2006-03-01

We present a novel approach that allows to calculate the dielectric response of periodic systems in the quantum Monte Carlo formalism. We employ a many-body generalization for the electric enthalpy functional, where the coupling with the field is expressed via the Berry-phase formulation for the macroscopic polarization. A self-consistent local Hamiltonian then determines the ground-state wavefunction, allowing for accurate diffusion quantum Monte Carlo calculations where the polarization's fixed point is estimated from the average on an iterative sequence. The polarization is sampled through forward-walking. This approach has been validated for the case of the polarizability of an isolated hydrogen atom, and then applied to a periodic system. We then calculate the linear susceptibility and second-order hyper-susceptibility of molecular-hydrogen chains whith different bond-length alternations, and assess the quality of nodal surfaces derived from density-functional theory or from Hartree-Fock. The results found are in excellent agreement with the best estimates obtained from the extrapolation of quantum-chemistry calculations.P. Umari, A.J. Williamson, G. Galli, and N. MarzariPhys. Rev. Lett. 95, 207602 (2005).

GE781: a Monte Carlo package for fixed target experiments

NASA Astrophysics Data System (ADS)

Davidenko, G.; Funk, M. A.; Kim, V.; Kuropatkin, N.; Kurshetsov, V.; Molchanov, V.; Rud, S.; Stutte, L.; Verebryusov, V.; Zukanovich Funchal, R.

The Monte Carlo package for the fixed target experiment B781 at Fermilab, a third generation charmed baryon experiment, is described. This package is based on GEANT 3.21, ADAMO database and DAFT input/output routines.

Knowledge diffusion in the collaboration hypernetwork

NASA Astrophysics Data System (ADS)

Yang, Guang-Yong; Hu, Zhao-Long; Liu, Jian-Guo

2015-02-01

As knowledge constitutes a primary productive force, it is important to understand the performance of knowledge diffusion. In this paper, we present a knowledge diffusion model based on the local-world non-uniform hypernetwork, which introduces the preferential diffusion mechanism and the knowledge absorptive capability αj, where αj is correlated with the hyperdegree dH(j) of node j. At each time step, we randomly select a node i as the sender; a receiver node is selected from the set of nodes that the sender i has published with previously, with probability proportional to the number of papers they have published together. Applying the average knowledge stock V bar(t) , the variance σ2(t) and the variance coefficient c(t) of knowledge stock to measure the growth and diffusion of knowledge and the adequacy of knowledge diffusion, we have made 3 groups of comparative experiments to investigate how different network structures, hypernetwork sizes and knowledge evolution mechanisms affect the knowledge diffusion, respectively. As the diffusion mechanisms based on the hypernetwork combine with the hyperdegree of node, the hypernetwork is more suitable for investigating the performance of knowledge diffusion. Therefore, the proposed model could be helpful for deeply understanding the process of the knowledge diffusion in the collaboration hypernetwork.

A model of partial differential equations for HIV propagation in lymph nodes

NASA Astrophysics Data System (ADS)

Marinho, E. B. S.; Bacelar, F. S.; Andrade, R. F. S.

2012-01-01

A system of partial differential equations is used to model the dissemination of the Human Immunodeficiency Virus (HIV) in CD4+T cells within lymph nodes. Besides diffusion terms, the model also includes a time-delay dependence to describe the time lag required by the immunologic system to provide defenses to new virus strains. The resulting dynamics strongly depends on the properties of the invariant sets of the model, consisting of three fixed points related to the time independent and spatial homogeneous tissue configurations in healthy and infected states. A region in the parameter space is considered, for which the time dependence of the space averaged model variables follows the clinical pattern reported for infected patients: a short scale primary infection, followed by a long latency period of almost complete recovery and third phase characterized by damped oscillations around a value with large HIV counting. Depending on the value of the diffusion coefficient, the latency time increases with respect to that one obtained for the space homogeneous version of the model. It is found that same initial conditions lead to quite different spatial patterns, which depend strongly on the latency interval.

Diffusion of chains in a periodic potential

NASA Astrophysics Data System (ADS)

Terranova, G. R.; Mártin, H. O.; Aldao, C. M.

2017-09-01

We studied the diffusion of 1D rigid chains in a square wave potential of period T. We considered chains of type A (composed of N particles A) and chains of type A-B (composed of N/2 particles A and N/2 particles B). The square wave potential represents domains, a lamellar structure observed for block copolymers, in which the repulsive δ energy between each A particle (B particle) of the chain and B particles (A particles) of the medium where the chains diffuse. From Monte Carlo simulations and analytical results it is found that the normalized diffusivity D, for N\\ll T , presents a universal behavior as a function of X  =  Nδ for chains of type A and X  =  (Nδ  -  lnT 2) for chains of type A-B, with and exponential decay for large values of X. For fixed values of δ and T, D is a periodic function of N with period T and 2T for chains of type A and type A-B, respectively.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kent, Paul R.; Krogel, Jaron T.

Growth in computational resources has lead to the application of real space diffusion quantum Monte Carlo to increasingly heavy elements. Although generally assumed to be small, we find that when using standard techniques, the pseudopotential localization error can be large, on the order of an electron volt for an isolated cerium atom. We formally show that the localization error can be reduced to zero with improvements to the Jastrow factor alone, and we define a metric of Jastrow sensitivity that may be useful in the design of pseudopotentials. We employ an extrapolation scheme to extract the bare fixed node energymore » and estimate the localization error in both the locality approximation and the T-moves schemes for the Ce atom in charge states 3+/4+. The locality approximation exhibits the lowest Jastrow sensitivity and generally smaller localization errors than T-moves although the locality approximation energy approaches the localization free limit from above/below for the 3+/4+ charge state. We find that energy minimized Jastrow factors including three-body electron-electron-ion terms are the most effective at reducing the localization error for both the locality approximation and T-moves for the case of the Ce atom. Less complex or variance minimized Jastrows are generally less effective. Finally, our results suggest that further improvements to Jastrow factors and trial wavefunction forms may be needed to reduce localization errors to chemical accuracy when medium core pseudopotentials are applied to heavy elements such as Ce.« less

Discrete Diffusion Monte Carlo for Electron Thermal Transport

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Cao, Duc; Wollaeger, Ryan; Moses, Gregory

2014-10-01

The iSNB (implicit Schurtz Nicolai Busquet electron thermal transport method of Cao et al. is adapted to a Discrete Diffusion Monte Carlo (DDMC) solution method for eventual inclusion in a hybrid IMC-DDMC (Implicit Monte Carlo) method. The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the iSNB-DDMC method will be presented. This work was supported by Sandia National Laboratory - Albuquerque.

Locating multiple diffusion sources in time varying networks from sparse observations.

PubMed

Hu, Zhao-Long; Shen, Zhesi; Cao, Shinan; Podobnik, Boris; Yang, Huijie; Wang, Wen-Xu; Lai, Ying-Cheng

2018-02-08

Data based source localization in complex networks has a broad range of applications. Despite recent progress, locating multiple diffusion sources in time varying networks remains to be an outstanding problem. Bridging structural observability and sparse signal reconstruction theories, we develop a general framework to locate diffusion sources in time varying networks based solely on sparse data from a small set of messenger nodes. A general finding is that large degree nodes produce more valuable information than small degree nodes, a result that contrasts that for static networks. Choosing large degree nodes as the messengers, we find that sparse observations from a few such nodes are often sufficient for any number of diffusion sources to be located for a variety of model and empirical networks. Counterintuitively, sources in more rapidly varying networks can be identified more readily with fewer required messenger nodes.

Monte Carlo Transport for Electron Thermal Transport

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

2015-11-01

The iSNB (implicit Schurtz Nicolai Busquet multigroup electron thermal transport method of Cao et al. is adapted into a Monte Carlo transport method in order to better model the effects of non-local behavior. The end goal is a hybrid transport-diffusion method that combines Monte Carlo Transport with a discrete diffusion Monte Carlo (DDMC). The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the method will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.

Swollen lymph nodes

MedlinePlus

... lymph nodes, including: Seizure medicines such as phenytoin Typhoid immunization Which lymph nodes are swollen depends on ... hard, irregular, or fixed in place. You have fever, night sweats, or unexplained weight loss. Any node ...

Key node selection in minimum-cost control of complex networks

NASA Astrophysics Data System (ADS)

Ding, Jie; Wen, Changyun; Li, Guoqi

2017-11-01

Finding the key node set that is connected with a given number of external control sources for driving complex networks from initial state to any predefined state with minimum cost, known as minimum-cost control problem, is critically important but remains largely open. By defining an importance index for each node, we propose revisited projected gradient method extension (R-PGME) in Monte-Carlo scenario to determine key node set. It is found that the importance index of a node is strongly correlated to occurrence rate of that node to be selected as a key node in Monte-Carlo realizations for three elementary topologies, Erdős-Rényi and scale-free networks. We also discover the distribution patterns of key nodes when the control cost reaches its minimum. Specifically, the importance indices of all nodes in an elementary stem show a quasi-periodic distribution with high peak values in the beginning and end of a quasi-period while they approach to a uniform distribution in an elementary cycle. We further point out that an elementary dilation can be regarded as two elementary stems whose lengths are the closest, and the importance indices in each stem present similar distribution as in an elementary stem. Our results provide a better understanding and deep insight of locating the key nodes in different topologies with minimum control cost.

Directed Diffusion Modelling for Tesso Nilo National Parks Case Study

NASA Astrophysics Data System (ADS)

Yasri, Indra; Safrianti, Ery

2018-01-01

— Directed Diffusion (DD has ability to achieve energy efficiency in Wireless Sensor Network (WSN). This paper proposes Directed Diffusion (DD) modelling for Tesso Nilo National Parks (TNNP) case study. There are 4 stages of scenarios involved in this modelling. It’s started by appointing of sampling area through GPS coordinate. The sampling area is determined by optimization processes from 500m x 500m up to 1000m x 1000m with 100m increment in between. The next stage is sensor node placement. Sensor node is distributed in sampling area with three different quantities i.e. 20 nodes, 30 nodes and 40 nodes. One of those quantities is choose as an optimized sensor node placement. The third stage is to implement all scenarios in stages 1 and stages 2 on DD modelling. In the last stage, the evaluation process to achieve most energy efficient in the combination of optimized sampling area and optimized sensor node placement on Direct Diffusion (DD) routing protocol. The result shows combination between sampling area 500m x 500m and 20 nodes able to achieve energy efficient to support a forest preventive fire system at Tesso Nilo National Parks.

Hybrid Monte Carlo-Diffusion Method For Light Propagation in Tissue With a Low-Scattering Region

NASA Astrophysics Data System (ADS)

Hayashi, Toshiyuki; Kashio, Yoshihiko; Okada, Eiji

2003-06-01

The heterogeneity of the tissues in a head, especially the low-scattering cerebrospinal fluid (CSF) layer surrounding the brain has previously been shown to strongly affect light propagation in the brain. The radiosity-diffusion method, in which the light propagation in the CSF layer is assumed to obey the radiosity theory, has been employed to predict the light propagation in head models. Although the CSF layer is assumed to be a nonscattering region in the radiosity-diffusion method, fine arachnoid trabeculae cause faint scattering in the CSF layer in real heads. A novel approach, the hybrid Monte Carlo-diffusion method, is proposed to calculate the head models, including the low-scattering region in which the light propagation does not obey neither the diffusion approximation nor the radiosity theory. The light propagation in the high-scattering region is calculated by means of the diffusion approximation solved by the finite-element method and that in the low-scattering region is predicted by the Monte Carlo method. The intensity and mean time of flight of the detected light for the head model with a low-scattering CSF layer calculated by the hybrid method agreed well with those by the Monte Carlo method, whereas the results calculated by means of the diffusion approximation included considerable error caused by the effect of the CSF layer. In the hybrid method, the time-consuming Monte Carlo calculation is employed only for the thin CSF layer, and hence, the computation time of the hybrid method is dramatically shorter than that of the Monte Carlo method.

Hybrid Monte Carlo-diffusion method for light propagation in tissue with a low-scattering region.

PubMed

Hayashi, Toshiyuki; Kashio, Yoshihiko; Okada, Eiji

2003-06-01

The heterogeneity of the tissues in a head, especially the low-scattering cerebrospinal fluid (CSF) layer surrounding the brain has previously been shown to strongly affect light propagation in the brain. The radiosity-diffusion method, in which the light propagation in the CSF layer is assumed to obey the radiosity theory, has been employed to predict the light propagation in head models. Although the CSF layer is assumed to be a nonscattering region in the radiosity-diffusion method, fine arachnoid trabeculae cause faint scattering in the CSF layer in real heads. A novel approach, the hybrid Monte Carlo-diffusion method, is proposed to calculate the head models, including the low-scattering region in which the light propagation does not obey neither the diffusion approximation nor the radiosity theory. The light propagation in the high-scattering region is calculated by means of the diffusion approximation solved by the finite-element method and that in the low-scattering region is predicted by the Monte Carlo method. The intensity and mean time of flight of the detected light for the head model with a low-scattering CSF layer calculated by the hybrid method agreed well with those by the Monte Carlo method, whereas the results calculated by means of the diffusion approximation included considerable error caused by the effect of the CSF layer. In the hybrid method, the time-consuming Monte Carlo calculation is employed only for the thin CSF layer, and hence, the computation time of the hybrid method is dramatically shorter than that of the Monte Carlo method.

Portable multi-node LQCD Monte Carlo simulations using OpenACC

NASA Astrophysics Data System (ADS)

Bonati, Claudio; Calore, Enrico; D'Elia, Massimo; Mesiti, Michele; Negro, Francesco; Sanfilippo, Francesco; Schifano, Sebastiano Fabio; Silvi, Giorgio; Tripiccione, Raffaele

This paper describes a state-of-the-art parallel Lattice QCD Monte Carlo code for staggered fermions, purposely designed to be portable across different computer architectures, including GPUs and commodity CPUs. Portability is achieved using the OpenACC parallel programming model, used to develop a code that can be compiled for several processor architectures. The paper focuses on parallelization on multiple computing nodes using OpenACC to manage parallelism within the node, and OpenMPI to manage parallelism among the nodes. We first discuss the available strategies to be adopted to maximize performances, we then describe selected relevant details of the code, and finally measure the level of performance and scaling-performance that we are able to achieve. The work focuses mainly on GPUs, which offer a significantly high level of performances for this application, but also compares with results measured on other processors.

Influence maximization in complex networks through optimal percolation

NASA Astrophysics Data System (ADS)

Morone, Flaviano; Makse, Hernán A.

2015-08-01

The whole frame of interconnections in complex networks hinges on a specific set of structural nodes, much smaller than the total size, which, if activated, would cause the spread of information to the whole network, or, if immunized, would prevent the diffusion of a large scale epidemic. Localizing this optimal, that is, minimal, set of structural nodes, called influencers, is one of the most important problems in network science. Despite the vast use of heuristic strategies to identify influential spreaders, the problem remains unsolved. Here we map the problem onto optimal percolation in random networks to identify the minimal set of influencers, which arises by minimizing the energy of a many-body system, where the form of the interactions is fixed by the non-backtracking matrix of the network. Big data analyses reveal that the set of optimal influencers is much smaller than the one predicted by previous heuristic centralities. Remarkably, a large number of previously neglected weakly connected nodes emerges among the optimal influencers. These are topologically tagged as low-degree nodes surrounded by hierarchical coronas of hubs, and are uncovered only through the optimal collective interplay of all the influencers in the network. The present theoretical framework may hold a larger degree of universality, being applicable to other hard optimization problems exhibiting a continuous transition from a known phase.

Influence maximization in complex networks through optimal percolation.

PubMed

Morone, Flaviano; Makse, Hernán A

2015-08-06

The whole frame of interconnections in complex networks hinges on a specific set of structural nodes, much smaller than the total size, which, if activated, would cause the spread of information to the whole network, or, if immunized, would prevent the diffusion of a large scale epidemic. Localizing this optimal, that is, minimal, set of structural nodes, called influencers, is one of the most important problems in network science. Despite the vast use of heuristic strategies to identify influential spreaders, the problem remains unsolved. Here we map the problem onto optimal percolation in random networks to identify the minimal set of influencers, which arises by minimizing the energy of a many-body system, where the form of the interactions is fixed by the non-backtracking matrix of the network. Big data analyses reveal that the set of optimal influencers is much smaller than the one predicted by previous heuristic centralities. Remarkably, a large number of previously neglected weakly connected nodes emerges among the optimal influencers. These are topologically tagged as low-degree nodes surrounded by hierarchical coronas of hubs, and are uncovered only through the optimal collective interplay of all the influencers in the network. The present theoretical framework may hold a larger degree of universality, being applicable to other hard optimization problems exhibiting a continuous transition from a known phase.

Queues on a Dynamically Evolving Graph

NASA Astrophysics Data System (ADS)

Mandjes, Michel; Starreveld, Nicos J.; Bekker, René

2018-04-01

This paper considers a population process on a dynamically evolving graph, which can be alternatively interpreted as a queueing network. The queues are of infinite-server type, entailing that at each node all customers present are served in parallel. The links that connect the queues have the special feature that they are unreliable, in the sense that their status alternates between `up' and `down'. If a link between two nodes is down, with a fixed probability each of the clients attempting to use that link is lost; otherwise the client remains at the origin node and reattempts using the link (and jumps to the destination node when it finds the link restored). For these networks we present the following results: (a) a system of coupled partial differential equations that describes the joint probability generating function corresponding to the queues' time-dependent behavior (and a system of ordinary differential equations for its stationary counterpart), (b) an algorithm to evaluate the (time-dependent and stationary) moments, and procedures to compute user-perceived performance measures which facilitate the quantification of the impact of the links' outages, (c) a diffusion limit for the joint queue length process. We include explicit results for a series relevant special cases, such as tandem networks and symmetric fully connected networks.

Dynamic node immunization for restraint of harmful information diffusion in social networks

NASA Astrophysics Data System (ADS)

Yang, Dingda; Liao, Xiangwen; Shen, Huawei; Cheng, Xueqi; Chen, Guolong

2018-08-01

To restrain the spread of harmful information is crucial for the healthy and sustainable development of social networks. We address the problem of restraining the spread of harmful information by immunizing nodes in the networks. Previous works have developed methods based on the network topology or studied how to immunize nodes in the presence of initial infected nodes. These static methods, in which nodes are immunized at once, may have poor performance in the certain situation due to the dynamics of diffusion. To tackle this problem, we introduce a new dynamic immunization problem of immunizing nodes during the process of the diffusion in this paper. We formulate the problem and propose a novel heuristic algorithm by dealing with two sub-problems: (1) how to select a node to achieve the best immunization effect at the present time? (2) whether the selected node should be immunized right now? Finally, we demonstrate the effectiveness of our algorithm through extensive experiments on various real datasets.

How thin barrier metal can be used to prevent Co diffusion in the modern integrated circuits?

NASA Astrophysics Data System (ADS)

Dixit, Hemant; Konar, Aniruddha; Pandey, Rajan; Ethirajan, Tamilmani

2017-11-01

In modern integrated circuits (ICs), billions of transistors are connected to each other via thin metal layers (e.g. copper, cobalt, etc) known as interconnects. At elevated process temperatures, inter-diffusion of atomic species can occur among these metal layers, causing sub-optimal performance of interconnects, which may lead to the failure of an IC. Thus, typically a thin barrier metal layer is used to prevent the inter-diffusion of atomic species within interconnects. For ICs with sub-10 nm transistors (10 nm technology node), the design rule (thickness scaling) demands the thinnest possible barrier layer. Therefore, here we investigate the critical thickness of a titanium-nitride (TiN) barrier that can prevent the cobalt diffusion using multi-scale modeling and simulations. First, we compute the Co diffusion barrier in crystalline and amorphous TiN with the nudged elastic band method within first-principles density functional theory simulations. Later, using the calculated activation energy barriers, we quantify the Co diffusion length in the TiN metal layer with the help of kinetic Monte Carlo simulations. Such a multi-scale modelling approach yields an exact critical thickness of the metal layer sufficient to prevent the Co diffusion in IC interconnects. We obtain a diffusion length of a maximum of 2 nm for a typical process of thermal annealing at 400 °C for 30 min. Our study thus provides useful physical insights for the Co diffusion in the TiN layer and further quantifies the critical thickness (~2 nm) to which the metal barrier layer can be thinned down for sub-10 nm ICs.

Analytical model of diffuse reflectance spectrum of skin tissue

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.; Firago, V. A.; Sobchuk, A. N.

2014-01-01

We have derived simple analytical expressions that enable highly accurate calculation of diffusely reflected light signals of skin in the spectral range from 450 to 800 nm at a distance from the region of delivery of exciting radiation. The expressions, taking into account the dependence of the detected signals on the refractive index, transport scattering coefficient, absorption coefficient and anisotropy factor of the medium, have been obtained in the approximation of a two-layer medium model (epidermis and dermis) for the same parameters of light scattering but different absorption coefficients of layers. Numerical experiments on the retrieval of the skin biophysical parameters from the diffuse reflectance spectra simulated by the Monte Carlo method show that commercially available fibre-optic spectrophotometers with a fixed distance between the radiation source and detector can reliably determine the concentration of bilirubin, oxy- and deoxyhaemoglobin in the dermis tissues and the tissue structure parameter characterising the size of its effective scatterers. We present the examples of quantitative analysis of the experimental data, confirming the correctness of estimates of biophysical parameters of skin using the obtained analytical expressions.

Diffuse large B-cell lymphoma presenting as a unilateral solitary round pulmonary hilar node infarction.

PubMed

Yonemori, Kan; Kusumoto, Masahiko; Matsuno, Yoshihiro; Tateishi, Ukihide; Watanabe, Shun-Ichi; Watanabe, Takashi; Moriyama, Noriyuki

2006-03-01

Unilateral solitary pulmonary hilar node adenopathy is a rare presentation of diffuse large B-cell lymphoma. In this report, the authors present a case with a solitary pulmonary hilar lymph node infarction caused by diffuse large B-cell lymphoma. Enhanced CT examinations revealed a well-defined round mass with homogenous low attenuation in the left pulmonary hilum. Both radiological imaging and pathological examination can provide useful information for the interpretation of abnormalities and may enable the diagnosis of rare aetiologies.

Analysis and Assessment of Operation Risk for Hybrid AC/DC Power System based on the Monte Carlo Method

NASA Astrophysics Data System (ADS)

Hu, Xiaojing; Li, Qiang; Zhang, Hao; Guo, Ziming; Zhao, Kun; Li, Xinpeng

2018-06-01

Based on the Monte Carlo method, an improved risk assessment method for hybrid AC/DC power system with VSC station considering the operation status of generators, converter stations, AC lines and DC lines is proposed. According to the sequential AC/DC power flow algorithm, node voltage and line active power are solved, and then the operation risk indices of node voltage over-limit and line active power over-limit are calculated. Finally, an improved two-area IEEE RTS-96 system is taken as a case to analyze and assessment its operation risk. The results show that the proposed model and method can intuitively and directly reflect the weak nodes and weak lines of the system, which can provide some reference for the dispatching department.

Modeling 2D and 3D diffusion.

PubMed

Saxton, Michael J

2007-01-01

Modeling obstructed diffusion is essential to the understanding of diffusion-mediated processes in the crowded cellular environment. Simple Monte Carlo techniques for modeling obstructed random walks are explained and related to Brownian dynamics and more complicated Monte Carlo methods. Random number generation is reviewed in the context of random walk simulations. Programming techniques and event-driven algorithms are discussed as ways to speed simulations.

Correlation of human papilloma virus status with quantitative perfusion/diffusion/metabolic imaging parameters in the oral cavity and oropharyngeal squamous cell carcinoma: comparison of primary tumour sites and metastatic lymph nodes.

PubMed

Han, M; Lee, S J; Lee, D; Kim, S Y; Choi, J W

2018-05-17

To investigate the differences in perfusion/diffusion/metabolic imaging parameters according to human papilloma virus (HPV) status in the oral cavity and oropharyngeal squamous cell carcinoma (OC-OPSCC), separately in primary tumour sites and metastatic lymph nodes. This retrospective study comprised 41 patients with primary OC-OPSCCs and 29 patients with metastatic lymph nodes. The perfusion/diffusion/metabolic imaging parameters were measured at the primary tumour and the largest ipsilateral metastatic lymph node. The quantitative parameters were compared between the HPV-positive and -negative groups. The HPV-positivity was 39% (16 patients) for the primary tumours and 51.7% (15 patients) for the metastatic lymph nodes. Patients with HPV-positive tumours had a lower T stage (p=0.034). The metastatic lymph nodes for the HPV-positive patients were bulkier (p=0.016) and more frequently had cystic morphology (p=0.005). The perfusion parameters were not different, regardless of HPV status. The diffusion parameter (ADC min , p=0.011) of the metastatic lymph nodes in the HPV-positive groups was lower and metabolic parameter (metabolic tumour volume p=0.035 and total lesion glycolysis p=0.037) were higher than those in HPV-negative groups. The diffusion and metabolic parameters of metastatic lymph nodes from OC-OPSCC were different according to HPV status. The perfusion parameters did not clearly represent HPV status. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Data decomposition of Monte Carlo particle transport simulations via tally servers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romano, Paul K.; Siegel, Andrew R.; Forget, Benoit

An algorithm for decomposing large tally data in Monte Carlo particle transport simulations is developed, analyzed, and implemented in a continuous-energy Monte Carlo code, OpenMC. The algorithm is based on a non-overlapping decomposition of compute nodes into tracking processors and tally servers. The former are used to simulate the movement of particles through the domain while the latter continuously receive and update tally data. A performance model for this approach is developed, suggesting that, for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead on contemporary supercomputers. An implementation of the algorithmmore » in OpenMC is then tested on the Intrepid and Titan supercomputers, supporting the key predictions of the model over a wide range of parameters. We thus conclude that the tally server algorithm is a successful approach to circumventing classical on-node memory constraints en route to unprecedentedly detailed Monte Carlo reactor simulations.« less

GATE Monte Carlo simulation of dose distribution using MapReduce in a cloud computing environment.

PubMed

Liu, Yangchuan; Tang, Yuguo; Gao, Xin

2017-12-01

The GATE Monte Carlo simulation platform has good application prospects of treatment planning and quality assurance. However, accurate dose calculation using GATE is time consuming. The purpose of this study is to implement a novel cloud computing method for accurate GATE Monte Carlo simulation of dose distribution using MapReduce. An Amazon Machine Image installed with Hadoop and GATE is created to set up Hadoop clusters on Amazon Elastic Compute Cloud (EC2). Macros, the input files for GATE, are split into a number of self-contained sub-macros. Through Hadoop Streaming, the sub-macros are executed by GATE in Map tasks and the sub-results are aggregated into final outputs in Reduce tasks. As an evaluation, GATE simulations were performed in a cubical water phantom for X-ray photons of 6 and 18 MeV. The parallel simulation on the cloud computing platform is as accurate as the single-threaded simulation on a local server and the simulation correctness is not affected by the failure of some worker nodes. The cloud-based simulation time is approximately inversely proportional to the number of worker nodes. For the simulation of 10 million photons on a cluster with 64 worker nodes, time decreases of 41× and 32× were achieved compared to the single worker node case and the single-threaded case, respectively. The test of Hadoop's fault tolerance showed that the simulation correctness was not affected by the failure of some worker nodes. The results verify that the proposed method provides a feasible cloud computing solution for GATE.

Monte Carlo-based fluorescence molecular tomography reconstruction method accelerated by a cluster of graphic processing units.

PubMed

Quan, Guotao; Gong, Hui; Deng, Yong; Fu, Jianwei; Luo, Qingming

2011-02-01

High-speed fluorescence molecular tomography (FMT) reconstruction for 3-D heterogeneous media is still one of the most challenging problems in diffusive optical fluorescence imaging. In this paper, we propose a fast FMT reconstruction method that is based on Monte Carlo (MC) simulation and accelerated by a cluster of graphics processing units (GPUs). Based on the Message Passing Interface standard, we modified the MC code for fast FMT reconstruction, and different Green's functions representing the flux distribution in media are calculated simultaneously by different GPUs in the cluster. A load-balancing method was also developed to increase the computational efficiency. By applying the Fréchet derivative, a Jacobian matrix is formed to reconstruct the distribution of the fluorochromes using the calculated Green's functions. Phantom experiments have shown that only 10 min are required to get reconstruction results with a cluster of 6 GPUs, rather than 6 h with a cluster of multiple dual opteron CPU nodes. Because of the advantages of high accuracy and suitability for 3-D heterogeneity media with refractive-index-unmatched boundaries from the MC simulation, the GPU cluster-accelerated method provides a reliable approach to high-speed reconstruction for FMT imaging.

Social relevance: toward understanding the impact of the individual in an information cascade

NASA Astrophysics Data System (ADS)

Hall, Robert T.; White, Joshua S.; Fields, Jeremy

2016-05-01

Information Cascades (IC) through a social network occur due to the decision of users to disseminate content. We define this decision process as User Diffusion (UD). IC models typically describe an information cascade by treating a user as a node within a social graph, where a node's reception of an idea is represented by some activation state. The probability of activation then becomes a function of a node's connectedness to other activated nodes as well as, potentially, the history of activation attempts. We enrich this Coarse-Grained User Diffusion (CGUD) model by applying actor type logics to the nodes of the graph. The resulting Fine-Grained User Diffusion (FGUD) model utilizes prior research in actor typing to generate a predictive model regarding the future influence a user will have on an Information Cascade. Furthermore, we introduce a measure of Information Resonance that is used to aid in predictions regarding user behavior.

Analysis of complex network performance and heuristic node removal strategies

NASA Astrophysics Data System (ADS)

Jahanpour, Ehsan; Chen, Xin

2013-12-01

Removing important nodes from complex networks is a great challenge in fighting against criminal organizations and preventing disease outbreaks. Six network performance metrics, including four new metrics, are applied to quantify networks' diffusion speed, diffusion scale, homogeneity, and diameter. In order to efficiently identify nodes whose removal maximally destroys a network, i.e., minimizes network performance, ten structured heuristic node removal strategies are designed using different node centrality metrics including degree, betweenness, reciprocal closeness, complement-derived closeness, and eigenvector centrality. These strategies are applied to remove nodes from the September 11, 2001 hijackers' network, and their performance are compared to that of a random strategy, which removes randomly selected nodes, and the locally optimal solution (LOS), which removes nodes to minimize network performance at each step. The computational complexity of the 11 strategies and LOS is also analyzed. Results show that the node removal strategies using degree and betweenness centralities are more efficient than other strategies.

Optimising probe holder design for sentinel lymph node imaging using clinical photoacoustic system with Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Sivasubramanian, Kathyayini; Periyasamy, Vijitha; Wen, Kew Kok; Pramanik, Manojit

2017-03-01

Photoacoustic tomography is a hybrid imaging modality that combines optical and ultrasound imaging. It is rapidly gaining attention in the field of medical imaging. The challenge is to translate it into a clinical setup. In this work, we report the development of a handheld clinical photoacoustic imaging system. A clinical ultrasound imaging system is modified to integrate photoacoustic imaging with the ultrasound imaging. Hence, light delivery has been integrated with the ultrasound probe. The angle of light delivery is optimized in this work with respect to the depth of imaging. Optimization was performed based on Monte Carlo simulation for light transport in tissues. Based on the simulation results, the probe holders were fabricated using 3D printing. Similar results were obtained experimentally using phantoms. Phantoms were developed to mimic sentinel lymph node imaging scenario. Also, in vivo sentinel lymph node imaging was done using the same system with contrast agent methylene blue up to a depth of 1.5 cm. The results validate that one can use Monte Carlo simulation as a tool to optimize the probe holder design depending on the imaging needs. This eliminates a trial and error approach generally used for designing a probe holder.

Thermally induced gas flows in ratchet channels with diffuse and specular boundaries

PubMed Central

Shahabi, Vahid; Baier, Tobias; Roohi, Ehsan; Hardt, Steffen

2017-01-01

A net gas flow can be induced in the gap between periodically structured surfaces held at fixed but different temperatures when the reflection symmetry along the channel axis is broken. Such a situation arises when one surface features a ratchet structure and can be augmented by altering the boundary conditions on different parts of this surface, with some regions reflecting specularly and others diffusely. In order to investigate the physical mechanisms inducing the flow in this configuration at various Knudsen numbers and geometric configurations, direct simulation Monte Carlo (DSMC) simulations are employed using transient adaptive subcells for collision partner selection. At large Knudsen numbers the results compare favorably with analytical expressions, while for small Knudsen numbers a qualitative explanation for the flow in the strong temperature inhomogeneity at the tips of the ratchet is provided. A detailed investigation of the performance for various ratchet geometries suggests optimum working conditions for a Knudsen pump based on this mechanism. PMID:28128309

Kinetic Monte Carlo Simulation of Cation Diffusion in Low-K Ceramics

NASA Technical Reports Server (NTRS)

Good, Brian

2013-01-01

Low thermal conductivity (low-K) ceramic materials are of interest to the aerospace community for use as the thermal barrier component of coating systems for turbine engine components. In particular, zirconia-based materials exhibit both low thermal conductivity and structural stability at high temperature, making them suitable for such applications. Because creep is one of the potential failure modes, and because diffusion is a mechanism by which creep takes place, we have performed computer simulations of cation diffusion in a variety of zirconia-based low-K materials. The kinetic Monte Carlo simulation method is an alternative to the more widely known molecular dynamics (MD) method. It is designed to study "infrequent-event" processes, such as diffusion, for which MD simulation can be highly inefficient. We describe the results of kinetic Monte Carlo computer simulations of cation diffusion in several zirconia-based materials, specifically, zirconia doped with Y, Gd, Nb and Yb. Diffusion paths are identified, and migration energy barriers are obtained from density functional calculations and from the literature. We present results on the temperature dependence of the diffusivity, and on the effects of the presence of oxygen vacancies in cation diffusion barrier complexes as well.

HMB-45, S-100, NK1/C3, and MART-1 in metastatic melanoma.

PubMed

Zubovits, Judit; Buzney, Elizabeth; Yu, Lawrence; Duncan, Lyn M

2004-02-01

The diagnosis of melanoma metastatic to lymph node remains a difficult problem given its histological diversity. We examined the staining patterns of S-100, NK1/C3, HMB-45, and MART-1 (DC10) in melanoma metastases to lymph nodes. Immunohistochemical stains were performed on tissue sections of 126 formalin-fixed lymph nodes from 126 patients with an established diagnosis of metastatic melanoma. A total of 98% of cases (123 of 126) stained positive for S-100, 93% (117 of 125) stained positive for NK1/C3, 82% (103 of 126) stained positive for MART-1, and 76% (95 of 125) stained positive for HMB-45. The distribution and intensity of staining varied among these markers. A diffuse staining pattern, defined as >50% of tumor cells stained, was observed in 83% of MART-1-positive cases but in only 56% of S-100-positive cases, 48% of NK1/C3-positive cases, and 34% of HMB-45-positive cases. A maximally intense signal was almost always observed for MART-1 (83% of positive cases) but was rarely observed for NK1/C3 (20%). S-100 and HMB-45 showed maximally intense staining in 50% and 54% of cases, respectively. S-100 and NK1/C3 stained both histiocytes and melanocytes, whereas MART-1 and HMB-45 stained only melanocytes. Seventy-eight cases (63%) stained positive for all 4 markers, 17 cases (14%) stained for all markers except HMB-45, 13 cases (10%) stained for all markers except MART-1, 6 cases (5%) stained only with S-100 and NK1/C3, 4 cases (3%) stained only with S-100 and HMB-45, and 2 cases stained for all markers except S-100. One case each stained for the following: only S-100, only S-100 and HMB-45, and all markers except NK1/C3. One case exhibited absence of staining for any of these markers. We demonstrate that lymph node metastases of melanoma are heterogeneous with regard to tumor marker expression. S-100 and NK1/C3 were the most sensitive stains for detecting metastatic melanoma; however, they both also stain other nontumor cells in lymph nodes. MART-1 did not stain histiocytes and exhibited a more frequently intense and diffuse staining pattern than NK1/C3. HMB-45 was less sensitive and demonstrated less diffuse staining than MART-1.

FAST TRACK COMMUNICATION: The origin of Bohm diffusion, investigated by a comparison of different modelling methods

NASA Astrophysics Data System (ADS)

Bultinck, E.; Mahieu, S.; Depla, D.; Bogaerts, A.

2010-07-01

'Bohm diffusion' causes the electrons to diffuse perpendicularly to the magnetic field lines. However, its origin is not yet completely understood: low and high frequency electric field fluctuations are both named to cause Bohm diffusion. The importance of including this process in a Monte Carlo (MC) model is demonstrated by comparing calculated ionization rates with particle-in-cell/Monte Carlo collisions (PIC/MCC) simulations. A good agreement is found with a Bohm diffusion parameter of 0.05, which corresponds well to experiments. Since the PIC/MCC method accounts for fast electric field fluctuations, we conclude that Bohm diffusion is caused by fast electric field phenomena.

Fixed forced detection for fast SPECT Monte-Carlo simulation

NASA Astrophysics Data System (ADS)

Cajgfinger, T.; Rit, S.; Létang, J. M.; Halty, A.; Sarrut, D.

2018-03-01

Monte-Carlo simulations of SPECT images are notoriously slow to converge due to the large ratio between the number of photons emitted and detected in the collimator. This work proposes a method to accelerate the simulations based on fixed forced detection (FFD) combined with an analytical response of the detector. FFD is based on a Monte-Carlo simulation but forces the detection of a photon in each detector pixel weighted by the probability of emission (or scattering) and transmission to this pixel. The method was evaluated with numerical phantoms and on patient images. We obtained differences with analog Monte Carlo lower than the statistical uncertainty. The overall computing time gain can reach up to five orders of magnitude. Source code and examples are available in the Gate V8.0 release.

Fixed forced detection for fast SPECT Monte-Carlo simulation.

PubMed

Cajgfinger, T; Rit, S; Létang, J M; Halty, A; Sarrut, D

2018-03-02

Monte-Carlo simulations of SPECT images are notoriously slow to converge due to the large ratio between the number of photons emitted and detected in the collimator. This work proposes a method to accelerate the simulations based on fixed forced detection (FFD) combined with an analytical response of the detector. FFD is based on a Monte-Carlo simulation but forces the detection of a photon in each detector pixel weighted by the probability of emission (or scattering) and transmission to this pixel. The method was evaluated with numerical phantoms and on patient images. We obtained differences with analog Monte Carlo lower than the statistical uncertainty. The overall computing time gain can reach up to five orders of magnitude. Source code and examples are available in the Gate V8.0 release.

Kinetic Monte Carlo Simulation of Oxygen and Cation Diffusion in Yttria-Stabilized Zirconia

NASA Technical Reports Server (NTRS)

Good, Brian

2011-01-01

Yttria-stabilized zirconia (YSZ) is of interest to the aerospace community, notably for its application as a thermal barrier coating for turbine engine components. In such an application, diffusion of both oxygen ions and cations is of concern. Oxygen diffusion can lead to deterioration of a coated part, and often necessitates an environmental barrier coating. Cation diffusion in YSZ is much slower than oxygen diffusion. However, such diffusion is a mechanism by which creep takes place, potentially affecting the mechanical integrity and phase stability of the coating. In other applications, the high oxygen diffusivity of YSZ is useful, and makes the material of interest for use as a solid-state electrolyte in fuel cells. The kinetic Monte Carlo (kMC) method offers a number of advantages compared with the more widely known molecular dynamics simulation method. In particular, kMC is much more efficient for the study of processes, such as diffusion, that involve infrequent events. We describe the results of kinetic Monte Carlo computer simulations of oxygen and cation diffusion in YSZ. Using diffusive energy barriers from ab initio calculations and from the literature, we present results on the temperature dependence of oxygen and cation diffusivity, and on the dependence of the diffusivities on yttria concentration and oxygen sublattice vacancy concentration. We also present results of the effect on diffusivity of oxygen vacancies in the vicinity of the barrier cations that determine the oxygen diffusion energy barriers.

Full-dimensional quantum calculations of ground-state tunneling splitting of malonaldehyde using an accurate ab initio potential energy surface

NASA Astrophysics Data System (ADS)

Wang, Yimin; Braams, Bastiaan J.; Bowman, Joel M.; Carter, Stuart; Tew, David P.

2008-06-01

Quantum calculations of the ground vibrational state tunneling splitting of H-atom and D-atom transfer in malonaldehyde are performed on a full-dimensional ab initio potential energy surface (PES). The PES is a fit to 11 147 near basis-set-limit frozen-core CCSD(T) electronic energies. This surface properly describes the invariance of the potential with respect to all permutations of identical atoms. The saddle-point barrier for the H-atom transfer on the PES is 4.1 kcal/mol, in excellent agreement with the reported ab initio value. Model one-dimensional and ``exact'' full-dimensional calculations of the splitting for H- and D-atom transfer are done using this PES. The tunneling splittings in full dimensionality are calculated using the unbiased ``fixed-node'' diffusion Monte Carlo (DMC) method in Cartesian and saddle-point normal coordinates. The ground-state tunneling splitting is found to be 21.6 cm-1 in Cartesian coordinates and 22.6 cm-1 in normal coordinates, with an uncertainty of 2-3 cm-1. This splitting is also calculated based on a model which makes use of the exact single-well zero-point energy (ZPE) obtained with the MULTIMODE code and DMC ZPE and this calculation gives a tunneling splitting of 21-22 cm-1. The corresponding computed splittings for the D-atom transfer are 3.0, 3.1, and 2-3 cm-1. These calculated tunneling splittings agree with each other to within less than the standard uncertainties obtained with the DMC method used, which are between 2 and 3 cm-1, and agree well with the experimental values of 21.6 and 2.9 cm-1 for the H and D transfer, respectively.

Full-dimensional quantum calculations of ground-state tunneling splitting of malonaldehyde using an accurate ab initio potential energy surface.

PubMed

Wang, Yimin; Braams, Bastiaan J; Bowman, Joel M; Carter, Stuart; Tew, David P

2008-06-14

Quantum calculations of the ground vibrational state tunneling splitting of H-atom and D-atom transfer in malonaldehyde are performed on a full-dimensional ab initio potential energy surface (PES). The PES is a fit to 11 147 near basis-set-limit frozen-core CCSD(T) electronic energies. This surface properly describes the invariance of the potential with respect to all permutations of identical atoms. The saddle-point barrier for the H-atom transfer on the PES is 4.1 kcalmol, in excellent agreement with the reported ab initio value. Model one-dimensional and "exact" full-dimensional calculations of the splitting for H- and D-atom transfer are done using this PES. The tunneling splittings in full dimensionality are calculated using the unbiased "fixed-node" diffusion Monte Carlo (DMC) method in Cartesian and saddle-point normal coordinates. The ground-state tunneling splitting is found to be 21.6 cm(-1) in Cartesian coordinates and 22.6 cm(-1) in normal coordinates, with an uncertainty of 2-3 cm(-1). This splitting is also calculated based on a model which makes use of the exact single-well zero-point energy (ZPE) obtained with the MULTIMODE code and DMC ZPE and this calculation gives a tunneling splitting of 21-22 cm(-1). The corresponding computed splittings for the D-atom transfer are 3.0, 3.1, and 2-3 cm(-1). These calculated tunneling splittings agree with each other to within less than the standard uncertainties obtained with the DMC method used, which are between 2 and 3 cm(-1), and agree well with the experimental values of 21.6 and 2.9 cm(-1) for the H and D transfer, respectively.

Propagation Modeling and Analysis of Molecular Motors in Molecular Communication.

PubMed

Chahibi, Youssef; Akyildiz, Ian F; Balasingham, Ilangko

2016-12-01

Molecular motor networks (MMNs) are networks constructed from molecular motors to enable nanomachines to perform coordinated tasks of sensing, computing, and actuation at the nano- and micro- scales. Living cells are naturally enabled with this same mechanism to establish point-to-point communication between different locations inside the cell. Similar to a railway system, the cytoplasm contains an intricate infrastructure of tracks, named microtubules, interconnecting different internal components of the cell. Motor proteins, such as kinesin and dynein, are able to travel along these tracks directionally, carrying with them large molecules that would otherwise be unreliably transported across the cytoplasm using free diffusion. Molecular communication has been previously proposed for the design and study of MMNs. However, the topological aspects of MMNs, including the effects of branches, have been ignored in the existing studies. In this paper, a physical end-to-end model for MMNs is developed, considering the location of the transmitter node, the network topology, and the receiver nodes. The end-to-end gain and group delay are considered as the performance measures, and analytical expressions for them are derived. The analytical model is validated by Monte-Carlo simulations and the performance of MMNs is analyzed numerically. It is shown that, depending on their nature and position, MMN nodes create impedance effects that are critical for the overall performance. This model could be applied to assist the design of artificial MMNs and to study cargo transport in neurofilaments to elucidate brain diseases related to microtubule jamming.

Application of Monte Carlo Method for Evaluation of Uncertainties of ITS-90 by Standard Platinum Resistance Thermometer

NASA Astrophysics Data System (ADS)

Palenčár, Rudolf; Sopkuliak, Peter; Palenčár, Jakub; Ďuriš, Stanislav; Suroviak, Emil; Halaj, Martin

2017-06-01

Evaluation of uncertainties of the temperature measurement by standard platinum resistance thermometer calibrated at the defining fixed points according to ITS-90 is a problem that can be solved in different ways. The paper presents a procedure based on the propagation of distributions using the Monte Carlo method. The procedure employs generation of pseudo-random numbers for the input variables of resistances at the defining fixed points, supposing the multivariate Gaussian distribution for input quantities. This allows taking into account the correlations among resistances at the defining fixed points. Assumption of Gaussian probability density function is acceptable, with respect to the several sources of uncertainties of resistances. In the case of uncorrelated resistances at the defining fixed points, the method is applicable to any probability density function. Validation of the law of propagation of uncertainty using the Monte Carlo method is presented on the example of specific data for 25 Ω standard platinum resistance thermometer in the temperature range from 0 to 660 °C. Using this example, we demonstrate suitability of the method by validation of its results.

Long non-coding RNA CCAT1 as a diagnostic and prognostic molecular marker in various cancers: a meta-analysis.

PubMed

Zhang, Zhihui; Xie, Haibiao; Liang, Daqiang; Huang, Lanbing; Liang, Feiguo; Qi, Qiang; Yang, Xinjian

2018-05-04

Long non-coding RNA colon cancer-associated transcript-1 (CCAT1) is newly found to be related with diagnoses and prognosis of cancer. This meta-analysis was performed to investigate the relationship between CCAT1 expression and clinical parameters, including survival condition, lymph node metastasis and tumor node metastasis grade. The primary literatures were collected through initial search criteria from electronic databases, including PubMed, OVID Evidence-based medicine Reviews and others (up to May 12, 2017). Eligible studies were identified and selected by the inclusion and exclusion criteria. Data was extracted and computed into Hazard ratio (HR) for the assessment of overall survival, subgroup analyses were prespecified based on the digestive tract cancer or others. Analysis of different CCAT1 expression related with lymph node metastasis or tumor node metastasis grade was conducted. Risk of bias was assessed by the Newcastle-Ottawa Scale. 9 studies were included. This meta-analysis showed that high CCAT1 expression level was related to poor overall survival, the pooled HR was 2.42 (95% confidence interval, CI: 1.86-3.16; P < 0.001; fix- effects model), similarly in the cancer type subgroups: digestive tract cancer (HR, 2.42; 95% CI, 1.79-3.29; P < 0.001; fix- effects model) and others (HR, 2.42; 95% CI, 1.42-4.13; P = 0.001; fix- effects model). The analysis showed that high CCAT1 was strongly related to positive lymph node metastasis (Odds ratio, OR: 3.24; 95% CI, 2.04-5.16; P < 0.001; fix- effects model), high tumor node metastasis stage (OR, 3.87; 95% CI, 2.53-5.92; P < 0.001; fix- effects model). In conclusion, this meta-analysis revealed that CCAT1 had potential as a diagnostic and prognostic biomarker in various cancers.

Study on formation of step bunching on 6H-SiC (0001) surface by kinetic Monte Carlo method

NASA Astrophysics Data System (ADS)

Li, Yuan; Chen, Xuejiang; Su, Juan

2016-05-01

The formation and evolution of step bunching during step-flow growth of 6H-SiC (0001) surfaces were studied by three-dimensional kinetic Monte Carlo (KMC) method and compared with the analytic model based on the theory of Burton-Cabera-Frank (BCF). In the KMC model the crystal lattice was represented by a structured mesh which fixed the position of atoms and interatomic bonding. The events considered in the model were adatoms adsorption and diffusion on the terrace, and adatoms attachment, detachment and interlayer transport at the step edges. In addition, effects of Ehrlich-Schwoebel (ES) barriers at downward step edges and incorporation barriers at upwards step edges were also considered. In order to obtain more elaborate information for the behavior of atoms in the crystal surface, silicon and carbon atoms were treated as the minimal diffusing species. KMC simulation results showed that multiple-height steps were formed on the vicinal surface oriented toward [ 1 1 bar 00 ] or [ 11 2 bar 0 ] directions. And then the formation mechanism of the step bunching was analyzed. Finally, to further analyze the formation processes of step bunching, a one-dimensional BCF analytic model with ES and incorporation barriers was used, and then it was solved numerically. In the BCF model, the periodic boundary conditions (PBC) were applied, and the parameters were corresponded to those used in the KMC model. The evolution character of step bunching was consistent with the results obtained by KMC simulation.

Monte Carlo simulation of the back-diffusion of electrons in nitrogen

NASA Astrophysics Data System (ADS)

Radmilović-Radjenović, M.; Nina, A.; Nikitović, Ž.

2009-01-01

In this paper, the process of back-diffusion in nitrogen is studied by means of Monte Carlo simulations. In particular we analyze the influence of different aspects of back-diffusion in order to simplify the models of plasma displays, low pressure gas breakdown and detectors of high energy particles. The obtained simulation results show that the escape coefficient depends strongly on the reflection coefficient and the initial energy of electrons. It was also found that the back-diffusion range and number of collisions before returning to the cathode in nitrogen are smaller than those in argon for similar conditions.

Kinetic Monte Carlo (kMC) simulation of carbon co-implant on pre-amorphization process.

PubMed

Park, Soonyeol; Cho, Bumgoo; Yang, Seungsu; Won, Taeyoung

2010-05-01

We report our kinetic Monte Carlo (kMC) study of the effect of carbon co-implant on the pre-amorphization implant (PAL) process. We employed BCA (Binary Collision Approximation) approach for the acquisition of the initial as-implant dopant profile and kMC method for the simulation of diffusion process during the annealing process. The simulation results implied that carbon co-implant suppresses the boron diffusion due to the recombination with interstitials. Also, we could compare the boron diffusion with carbon diffusion by calculating carbon reaction with interstitial. And we can find that boron diffusion is affected from the carbon co-implant energy by enhancing the trapping of interstitial between boron and interstitial.

Adaptive form-finding method for form-fixed spatial network structures

NASA Astrophysics Data System (ADS)

Lan, Cheng; Tu, Xi; Xue, Junqing; Briseghella, Bruno; Zordan, Tobia

2018-02-01

An effective form-finding method for form-fixed spatial network structures is presented in this paper. The adaptive form-finding method is introduced along with the example of designing an ellipsoidal network dome with bar length variations being as small as possible. A typical spherical geodesic network is selected as an initial state, having bar lengths in a limit group number. Next, this network is transformed into the ellipsoidal shape as desired by applying compressions on bars according to the bar length variations caused by transformation. Afterwards, the dynamic relaxation method is employed to explicitly integrate the node positions by applying residual forces. During the form-finding process, the boundary condition of constraining nodes on the ellipsoid surface is innovatively considered as reactions on the normal direction of the surface at node positions, which are balanced with the components of the nodal forces in a reverse direction induced by compressions on bars. The node positions are also corrected according to the fixed-form condition in each explicit iteration step. In the serial results of time history, the optimal solution is found from a time history of states by properly choosing convergence criteria, and the presented form-finding procedure is proved to be applicable for form-fixed problems.

Global-view coefficients: a data management solution for parallel quantum Monte Carlo applications: A DATA MANAGEMENT SOLUTION FOR QMC APPLICATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niu, Qingpeng; Dinan, James; Tirukkovalur, Sravya

2016-01-28

Quantum Monte Carlo (QMC) applications perform simulation with respect to an initial state of the quantum mechanical system, which is often captured by using a cubic B-spline basis. This representation is stored as a read-only table of coefficients and accesses to the table are generated at random as part of the Monte Carlo simulation. Current QMC applications, such as QWalk and QMCPACK, replicate this table at every process or node, which limits scalability because increasing the number of processors does not enable larger systems to be run. We present a partitioned global address space approach to transparently managing this datamore » using Global Arrays in a manner that allows the memory of multiple nodes to be aggregated. We develop an automated data management system that significantly reduces communication overheads, enabling new capabilities for QMC codes. Experimental results with QWalk and QMCPACK demonstrate the effectiveness of the data management system.« less

A Component-Based Diffusion Model With Structural Diversity for Social Networks.

PubMed

Qing Bao; Cheung, William K; Yu Zhang; Jiming Liu

2017-04-01

Diffusion on social networks refers to the process where opinions are spread via the connected nodes. Given a set of observed information cascades, one can infer the underlying diffusion process for social network analysis. The independent cascade model (IC model) is a widely adopted diffusion model where a node is assumed to be activated independently by any one of its neighbors. In reality, how a node will be activated also depends on how its neighbors are connected and activated. For instance, the opinions from the neighbors of the same social group are often similar and thus redundant. In this paper, we extend the IC model by considering that: 1) the information coming from the connected neighbors are similar and 2) the underlying redundancy can be modeled using a dynamic structural diversity measure of the neighbors. Our proposed model assumes each node to be activated independently by different communities (or components) of its parent nodes, each weighted by its effective size. An expectation maximization algorithm is derived to infer the model parameters. We compare the performance of the proposed model with the basic IC model and its variants using both synthetic data sets and a real-world data set containing news stories and Web blogs. Our empirical results show that incorporating the community structure of neighbors and the structural diversity measure into the diffusion model significantly improves the accuracy of the model, at the expense of only a reasonable increase in run-time.

Transmission versus reflectance spectroscopy for quantitation

NASA Astrophysics Data System (ADS)

Gardner, Craig M.

2018-01-01

The objective of this work was to compare the accuracy of analyte concentration estimation when using transmission versus diffuse reflectance spectroscopy of a scattering medium. Monte Carlo ray tracing of light through the medium was used in conjunction with pure component absorption spectra and Beer-Lambert absorption along each ray's pathlength to generate matched sets of pseudoabsorbance spectra, containing water and six analytes present in skin. PLS regression models revealed an improvement in accuracy when using transmission compared to reflectance for a range of medium thicknesses and instrument noise levels. An analytical expression revealed the source of the accuracy degradation with reflectance was due both to the reduced collection efficiency for a fixed instrument etendue and to the broad pathlength distribution that detected light travels in the medium before exiting from the incident side.

Effects of sorption competition on caesium diffusion through compacted argillaceous rock

NASA Astrophysics Data System (ADS)

Jakob, Andreas; Pfingsten, Wilfried; Van Loon, Luc

2009-05-01

We carried out a small-scale laboratory diffusion experiment on a disk-like sample of Opalinus clay from the Mont Terri underground laboratory (Switzerland) using 134Cs as tracer. A through-diffusion phase was followed by an out-diffusion phase where the tracer taken up by the sample was released again. Since the tracer concentration at both boundaries was monitored, careful mass-balance considerations were feasible. A first analysis of the experimental data was done in the frame of a single-species model accounting only for transport and non-linear sorption of caesium. The model could match the data of the through-diffusion phase, however only, when strongly reducing the sorption data based on batch sorption experiments. Yet, such a procedure was in strong contradiction with sorption measurements performed on dispersed and compacted systems. In addition, predictions concerning tracer out-diffusion and mass-balance considerations clearly revealed the shortcomings of this type of model. In a second attempt we applied a multi-species transport model where now the whole water chemistry and a sorption model for caesium were considered. First, the value for the diffusion coefficient was fixed to the best-fit value of the single-species model. But again, the sorption site densities had to be reduced strongly albeit the reduction factor was smaller. Only when fixing the sorption site densities to those values of the sorption model and letting the effective diffusion coefficient D e free for the adjustment, could through-diffusion data be reasonably well fitted and out-diffusion as well as mass-balances be predicted in a satisfying manner. The main results are: (1) The best-fit could be achieved with a value for D e of 1.8 × 10 -10 m 2 s -1 which is rather high but corroborated by results of a molecular modelling study. (2) If caesium arrives in the Opalinus clay sample potassium and sodium (calcium etc.) ions are released and caesium ions are sorbed. The released cations diffuse to lower concentration regions according to their individual concentration gradients. Since locally the cation concentration for potassium, (sodium and calcium) is increased, sorption of these cations is also locally enhanced, affecting in return the sorption behaviour of migrating caesium. Consequently, the sorption process of caesium in such diffusion experiments cannot be addressed by a non-linear isotherm formalism any longer. (3) A reasonable analysis of such single tracer diffusion experiments therefore requires the combined description of transport (diffusion) and sorption of many cations and the whole complex water chemistry of the system. Thus, single-species models can only be applied with care in the considered concentration ranges.

Accelerated rescaling of single Monte Carlo simulation runs with the Graphics Processing Unit (GPU).

PubMed

Yang, Owen; Choi, Bernard

2013-01-01

To interpret fiber-based and camera-based measurements of remitted light from biological tissues, researchers typically use analytical models, such as the diffusion approximation to light transport theory, or stochastic models, such as Monte Carlo modeling. To achieve rapid (ideally real-time) measurement of tissue optical properties, especially in clinical situations, there is a critical need to accelerate Monte Carlo simulation runs. In this manuscript, we report on our approach using the Graphics Processing Unit (GPU) to accelerate rescaling of single Monte Carlo runs to calculate rapidly diffuse reflectance values for different sets of tissue optical properties. We selected MATLAB to enable non-specialists in C and CUDA-based programming to use the generated open-source code. We developed a software package with four abstraction layers. To calculate a set of diffuse reflectance values from a simulated tissue with homogeneous optical properties, our rescaling GPU-based approach achieves a reduction in computation time of several orders of magnitude as compared to other GPU-based approaches. Specifically, our GPU-based approach generated a diffuse reflectance value in 0.08ms. The transfer time from CPU to GPU memory currently is a limiting factor with GPU-based calculations. However, for calculation of multiple diffuse reflectance values, our GPU-based approach still can lead to processing that is ~3400 times faster than other GPU-based approaches.

A Machine-Checked Proof of A State-Space Construction Algorithm

NASA Technical Reports Server (NTRS)

Catano, Nestor; Siminiceanu, Radu I.

2010-01-01

This paper presents the correctness proof of Saturation, an algorithm for generating state spaces of concurrent systems, implemented in the SMART tool. Unlike the Breadth First Search exploration algorithm, which is easy to understand and formalise, Saturation is a complex algorithm, employing a mutually-recursive pair of procedures that compute a series of non-trivial, nested local fixed points, corresponding to a chaotic fixed point strategy. A pencil-and-paper proof of Saturation exists, but a machine checked proof had never been attempted. The key element of the proof is the characterisation theorem of saturated nodes in decision diagrams, stating that a saturated node represents a set of states encoding a local fixed-point with respect to firing all events affecting only the node s level and levels below. For our purpose, we have employed the Prototype Verification System (PVS) for formalising the Saturation algorithm, its data structures, and for conducting the proofs.

Simulation of atomic diffusion in the Fcc NiAl system: A kinetic Monte Carlo study

DOE PAGES

Alfonso, Dominic R.; Tafen, De Nyago

2015-04-28

The atomic diffusion in fcc NiAl binary alloys was studied by kinetic Monte Carlo simulation. The environment dependent hopping barriers were computed using a pair interaction model whose parameters were fitted to relevant data derived from electronic structure calculations. Long time diffusivities were calculated and the effect of composition change on the tracer diffusion coefficients was analyzed. These results indicate that this variation has noticeable impact on the atomic diffusivities. A reduction in the mobility of both Ni and Al is demonstrated with increasing Al content. As a result, examination of the pair interaction between atoms was carried out formore » the purpose of understanding the predicted trends.« less

Longitudinal 3.0T MRI analysis of changes in lymph node volume and apparent diffusion coefficient in an experimental animal model of metastatic and hyperplastic lymph nodes.

PubMed

Klerkx, Wenche M; Geldof, Albert A; Heintz, A Peter; van Diest, Paul J; Visser, Fredy; Mali, Willem P; Veldhuis, Wouter B

2011-05-01

To perform a longitudinal analysis of changes in lymph node volume and apparent diffusion coefficient (ADC) in healthy, metastatic, and hyperplastic lymph nodes. Three groups of four female Copenhagen rats were studied. Metastasis was induced by injecting cells with a high metastatic potential in their left hind footpad. Reactive nodes were induced by injecting Complete Freund Adjuvant (CFA). Imaging was performed at baseline and at 2, 5, 8, 11, and 14 days after tumor cell injection. Finally, lymph nodes were examined histopathologically. The model was highly efficient in inducing lymphadenopathy: subcutaneous cell or CFA inoculation resulted in ipsilateral metastatic or reactive popliteal lymph nodes in all rats. Metastatic nodal volumes increased exponentially from 5-7 mm(3) at baseline to 25 mm(3) at day 14, while the control node remained 5 mm(3). The hyperplastic nodes showed a rapid volume increase reaching a plateau at day 6. The ADC of metastatic nodes significantly decreased (range 13%-32%), but this decrease was also seen in reactive nodes. Metastatic and hyperplastic lymph nodes differed in terms of enlargement patterns and ADC changes. Enlarged reactive or malignant nodes could not be differentiated based on their ADC values. Copyright © 2011 Wiley-Liss, Inc.

Brownian dynamics and dynamic Monte Carlo simulations of isotropic and liquid crystal phases of anisotropic colloidal particles: a comparative study.

PubMed

Patti, Alessandro; Cuetos, Alejandro

2012-07-01

We report on the diffusion of purely repulsive and freely rotating colloidal rods in the isotropic, nematic, and smectic liquid crystal phases to probe the agreement between Brownian and Monte Carlo dynamics under the most general conditions. By properly rescaling the Monte Carlo time step, being related to any elementary move via the corresponding self-diffusion coefficient, with the acceptance rate of simultaneous trial displacements and rotations, we demonstrate the existence of a unique Monte Carlo time scale that allows for a direct comparison between Monte Carlo and Brownian dynamics simulations. To estimate the validity of our theoretical approach, we compare the mean square displacement of rods, their orientational autocorrelation function, and the self-intermediate scattering function, as obtained from Brownian dynamics and Monte Carlo simulations. The agreement between the results of these two approaches, even under the condition of heterogeneous dynamics generally observed in liquid crystalline phases, is excellent.

Choice of reference measurements affects quantification of long diffusion time behaviour using stimulated echoes.

PubMed

Kleinnijenhuis, Michiel; Mollink, Jeroen; Lam, Wilfred W; Kinchesh, Paul; Khrapitchev, Alexandre A; Smart, Sean C; Jbabdi, Saad; Miller, Karla L

2018-02-01

To demonstrate how reference data affect the quantification of the apparent diffusion coefficient (ADC) in long diffusion time measurements with diffusion-weighted stimulated echo acquisition mode (DW-STEAM) measurements, and to present a modification to avoid contribution from crusher gradients in DW-STEAM. For DW-STEAM, reference measurements at long diffusion times have significant b 0 value, because b = 0 cannot be achieved in practice as a result of the need for signal spoiling. Two strategies for acquiring reference data over a range of diffusion times were considered: constant diffusion weighting (fixed-b 0 ) and constant gradient area (fixed-q 0 ). Fixed-b 0 and fixed-q 0 were compared using signal calculations for systems with one and two diffusion coefficients, and experimentally using data from postmortem human corpus callosum samples. Calculations of biexponential diffusion decay show that the ADC is underestimated for reference images with b > 0, which can induce an apparent time-dependence for fixed-q 0 . Restricted systems were also found to be affected. Experimentally, the exaggeration of the diffusion time-dependent effect under fixed-q 0 versus fixed-b 0 was in a range predicted theoretically, accounting for 62% (longitudinal) and 35% (radial) of the time dependence observed in white matter. Variation in the b-value of reference measurements in DW-STEAM can induce artificial diffusion time dependence in ADC, even in the absence of restriction. Magn Reson Med 79:952-959, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Fate of the open-shell singlet ground state in the experimentally accessible acenes: A quantum Monte Carlo study

NASA Astrophysics Data System (ADS)

Dupuy, Nicolas; Casula, Michele

2018-04-01

By means of the Jastrow correlated antisymmetrized geminal power (JAGP) wave function and quantum Monte Carlo (QMC) methods, we study the ground state properties of the oligoacene series, up to the nonacene. The JAGP is the accurate variational realization of the resonating-valence-bond (RVB) ansatz proposed by Pauling and Wheland to describe aromatic compounds. We show that the long-ranged RVB correlations built in the acenes' ground state are detrimental for the occurrence of open-shell diradical or polyradical instabilities, previously found by lower-level theories. We substantiate our outcome by a direct comparison with another wave function, tailored to be an open-shell singlet (OSS) for long-enough acenes. By comparing on the same footing the RVB and OSS wave functions, both optimized at a variational QMC level and further projected by the lattice regularized diffusion Monte Carlo method, we prove that the RVB wave function has always a lower variational energy and better nodes than the OSS, for all molecular species considered in this work. The entangled multi-reference RVB state acts against the electron edge localization implied by the OSS wave function and weakens the diradical tendency for higher oligoacenes. These properties are reflected by several descriptors, including wave function parameters, bond length alternation, aromatic indices, and spin-spin correlation functions. In this context, we propose a new aromatic index estimator suitable for geminal wave functions. For the largest acenes taken into account, the long-range decay of the charge-charge correlation functions is compatible with a quasi-metallic behavior.

Diffusion of Zonal Variables Using Node-Centered Diffusion Solver

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, T B

2007-08-06

Tom Kaiser [1] has done some preliminary work to use the node-centered diffusion solver (originally developed by T. Palmer [2]) in Kull for diffusion of zonal variables such as electron temperature. To avoid numerical diffusion, Tom used a scheme developed by Shestakov et al. [3] and found their scheme could, in the vicinity of steep gradients, decouple nearest-neighbor zonal sub-meshes leading to 'alternating-zone' (red-black mode) errors. Tom extended their scheme to couple the sub-meshes with appropriate chosen artificial diffusion and thereby solved the 'alternating-zone' problem. Because the choice of the artificial diffusion coefficient could be very delicate, it is desirablemore » to use a scheme that does not require the artificial diffusion but still able to avoid both numerical diffusion and the 'alternating-zone' problem. In this document we present such a scheme.« less

Kinetic Monte Carlo Simulation of Oxygen Diffusion in Ytterbium Disilicate

NASA Astrophysics Data System (ADS)

Good, Brian

2015-03-01

Ytterbium disilicate is of interest as a potential environmental barrier coating for aerospace applications, notably for use in next generation jet turbine engines. In such applications, the diffusion of oxygen and water vapor through these coatings is undesirable if high temperature corrosion is to be avoided. In an effort to understand the diffusion process in these materials, we have performed kinetic Monte Carlo simulations of vacancy-mediated oxygen diffusion in Ytterbium Disilicate. Oxygen vacancy site energies and diffusion barrier energies are computed using Density Functional Theory. We find that many potential diffusion paths involve large barrier energies, but some paths have barrier energies smaller than one electron volt. However, computed vacancy formation energies suggest that the intrinsic vacancy concentration is small in the pure material, with the result that the material is unlikely to exhibit significant oxygen permeability.

Nonlinear Network Description for Many-Body Quantum Systems in Continuous Space

NASA Astrophysics Data System (ADS)

Ruggeri, Michele; Moroni, Saverio; Holzmann, Markus

2018-05-01

We show that the recently introduced iterative backflow wave function can be interpreted as a general neural network in continuum space with nonlinear functions in the hidden units. Using this wave function in variational Monte Carlo simulations of liquid 4He in two and three dimensions, we typically find a tenfold increase in accuracy over currently used wave functions. Furthermore, subsequent stages of the iteration procedure define a set of increasingly good wave functions, each with its own variational energy and variance of the local energy: extrapolation to zero variance gives energies in close agreement with the exact values. For two dimensional 4He, we also show that the iterative backflow wave function can describe both the liquid and the solid phase with the same functional form—a feature shared with the shadow wave function, but now joined by much higher accuracy. We also achieve significant progress for liquid 3He in three dimensions, improving previous variational and fixed-node energies.

Collaborative localization in wireless sensor networks via pattern recognition in radio irregularity using omnidirectional antennas.

PubMed

Jiang, Joe-Air; Chuang, Cheng-Long; Lin, Tzu-Shiang; Chen, Chia-Pang; Hung, Chih-Hung; Wang, Jiing-Yi; Liu, Chang-Wang; Lai, Tzu-Yun

2010-01-01

In recent years, various received signal strength (RSS)-based localization estimation approaches for wireless sensor networks (WSNs) have been proposed. RSS-based localization is regarded as a low-cost solution for many location-aware applications in WSNs. In previous studies, the radiation patterns of all sensor nodes are assumed to be spherical, which is an oversimplification of the radio propagation model in practical applications. In this study, we present an RSS-based cooperative localization method that estimates unknown coordinates of sensor nodes in a network. Arrangement of two external low-cost omnidirectional dipole antennas is developed by using the distance-power gradient model. A modified robust regression is also proposed to determine the relative azimuth and distance between a sensor node and a fixed reference node. In addition, a cooperative localization scheme that incorporates estimations from multiple fixed reference nodes is presented to improve the accuracy of the localization. The proposed method is tested via computer-based analysis and field test. Experimental results demonstrate that the proposed low-cost method is a useful solution for localizing sensor nodes in unknown or changing environments.

Growth dominates choice in network percolation

NASA Astrophysics Data System (ADS)

Vijayaraghavan, Vikram S.; Noël, Pierre-André; Waagen, Alex; D'Souza, Raissa M.

2013-09-01

The onset of large-scale connectivity in a network (i.e., percolation) often has a major impact on the function of the system. Traditionally, graph percolation is analyzed by adding edges to a fixed set of initially isolated nodes. Several years ago, it was shown that adding nodes as well as edges to the graph can yield an infinite order transition, which is much smoother than the traditional second-order transition. More recently, it was shown that adding edges via a competitive process to a fixed set of initially isolated nodes can lead to a delayed, extremely abrupt percolation transition with a significant jump in large but finite systems. Here we analyze a process that combines both node arrival and edge competition. If started from a small collection of seed nodes, we show that the impact of node arrival dominates: although we can significantly delay percolation, the transition is of infinite order. Thus, node arrival can mitigate the trade-off between delay and abruptness that is characteristic of explosive percolation transitions. This realization may inspire new design rules where network growth can temper the effects of delay, creating opportunities for network intervention and control.

Dynamical Response of Networks Under External Perturbations: Exact Results

NASA Astrophysics Data System (ADS)

Chinellato, David D.; Epstein, Irving R.; Braha, Dan; Bar-Yam, Yaneer; de Aguiar, Marcus A. M.

2015-04-01

We give exact statistical distributions for the dynamic response of influence networks subjected to external perturbations. We consider networks whose nodes have two internal states labeled 0 and 1. We let nodes be frozen in state 0, in state 1, and the remaining nodes change by adopting the state of a connected node with a fixed probability per time step. The frozen nodes can be interpreted as external perturbations to the subnetwork of free nodes. Analytically extending and to be smaller than 1 enables modeling the case of weak coupling. We solve the dynamical equations exactly for fully connected networks, obtaining the equilibrium distribution, transition probabilities between any two states and the characteristic time to equilibration. Our exact results are excellent approximations for other topologies, including random, regular lattice, scale-free and small world networks, when the numbers of fixed nodes are adjusted to take account of the effect of topology on coupling to the environment. This model can describe a variety of complex systems, from magnetic spins to social networks to population genetics, and was recently applied as a framework for early warning signals for real-world self-organized economic market crises.

A Massively Parallel Code for Polarization Calculations

NASA Astrophysics Data System (ADS)

Akiyama, Shizuka; Höflich, Peter

2001-03-01

We present an implementation of our Monte-Carlo radiation transport method for rapidly expanding, NLTE atmospheres for massively parallel computers which utilizes both the distributed and shared memory models. This allows us to take full advantage of the fast communication and low latency inherent to nodes with multiple CPUs, and to stretch the limits of scalability with the number of nodes compared to a version which is based on the shared memory model. Test calculations on a local 20-node Beowulf cluster with dual CPUs showed an improved scalability by about 40%.

Efficient kinetic Monte Carlo method for reaction-diffusion problems with spatially varying annihilation rates

NASA Astrophysics Data System (ADS)

Schwarz, Karsten; Rieger, Heiko

2013-03-01

We present an efficient Monte Carlo method to simulate reaction-diffusion processes with spatially varying particle annihilation or transformation rates as it occurs for instance in the context of motor-driven intracellular transport. Like Green's function reaction dynamics and first-passage time methods, our algorithm avoids small diffusive hops by propagating sufficiently distant particles in large hops to the boundaries of protective domains. Since for spatially varying annihilation or transformation rates the single particle diffusion propagator is not known analytically, we present an algorithm that generates efficiently either particle displacements or annihilations with the correct statistics, as we prove rigorously. The numerical efficiency of the algorithm is demonstrated with an illustrative example.

Application of Diffusion Monte Carlo to Materials Dominated by van der Waals Interactions

DOE PAGES

Benali, Anouar; Shulenburger, Luke; Romero, Nichols A.; ...

2014-06-12

Van der Waals forces are notoriously difficult to account for from first principles. We perform extensive calculation to assess the usefulness and validity of diffusion quantum Monte Carlo when applied to van der Waals forces. We present results for noble gas solids and clusters - archetypical van der Waals dominated assemblies, as well as a relevant pi-pi stacking supramolecular complex: DNA + intercalating anti-cancer drug Ellipticine.

Fixed-time synchronization of complex networks with nonidentical nodes and stochastic noise perturbations

NASA Astrophysics Data System (ADS)

Zhang, Wanli; Li, Chuandong; Huang, Tingwen; Huang, Junjian

2018-02-01

This paper investigates the fixed-time synchronization of complex networks (CNs) with nonidentical nodes and stochastic noise perturbations. By designing new controllers, constructing Lyapunov functions and using the properties of Weiner process, different synchronization criteria are derived according to whether the node systems in the CNs or the goal system satisfies the corresponding conditions. Moreover, the role of the designed controllers is analyzed in great detail by constructing a suitable comparison system and a new method is presented to estimate the settling time by utilizing the comparison system. Results of this paper can be applied to both directed and undirected weighted networks. Numerical simulations are offered to verify the effectiveness of our new results.

Distributed estimation of sensors position in underwater wireless sensor network

NASA Astrophysics Data System (ADS)

Zandi, Rahman; Kamarei, Mahmoud; Amiri, Hadi

2016-05-01

In this paper, a localisation method for determining the position of fixed sensor nodes in an underwater wireless sensor network (UWSN) is introduced. In this simple and range-free scheme, the node localisation is achieved by utilising an autonomous underwater vehicle (AUV) that transverses through the network deployment area, and that periodically emits a message block via four directional acoustic beams. A message block contains the actual known AUV position as well as a directional dependent marker that allows a node to identify the respective transmit beam. The beams form a fixed angle with the AUV body. If a node passively receives message blocks, it could calculate the arithmetic mean of the coordinates existing in each messages sequence, to find coordinates at two different time instants via two different successive beams. The node position can be derived from the two computed positions of the AUV. The major advantage of the proposed localisation algorithm is that it is silent, which leads to energy efficiency for sensor nodes. The proposed method does not require any synchronisation among the nodes owing to being silent. Simulation results, using MATLAB, demonstrated that the proposed method had better performance than other similar AUV-based localisation methods in terms of the rates of well-localised sensor nodes and positional root mean square error.

Knowledge diffusion of dynamical network in terms of interaction frequency.

PubMed

Liu, Jian-Guo; Zhou, Qing; Guo, Qiang; Yang, Zhen-Hua; Xie, Fei; Han, Jing-Ti

2017-09-07

In this paper, we present a knowledge diffusion (SKD) model for dynamic networks by taking into account the interaction frequency which always used to measure the social closeness. A set of agents, which are initially interconnected to form a random network, either exchange knowledge with their neighbors or move toward a new location through an edge-rewiring procedure. The activity of knowledge exchange between agents is determined by a knowledge transfer rule that the target node would preferentially select one neighbor node to transfer knowledge with probability p according to their interaction frequency instead of the knowledge distance, otherwise, the target node would build a new link with its second-order neighbor preferentially or select one node in the system randomly with probability 1 - p. The simulation results show that, comparing with the Null model defined by the random selection mechanism and the traditional knowledge diffusion (TKD) model driven by knowledge distance, the knowledge would spread more fast based on SKD driven by interaction frequency. In particular, the network structure of SKD would evolve as an assortative one, which is a fundamental feature of social networks. This work would be helpful for deeply understanding the coevolution of the knowledge diffusion and network structure.

Binding energies and spatial structures of small carrier complexes in monolayer transition-metal dichalcogenides via diffusion Monte Carlo

DOE PAGES

Mayers, Matthew Z.; Berkelbach, Timothy C.; Hybertsen, Mark S.; ...

2015-10-09

Ground-state diffusion Monte Carlo is used to investigate the binding energies and intercarrier radial probability distributions of excitons, trions, and biexcitons in a variety of two-dimensional transition-metal dichalcogenide materials. We compare these results to approximate variational calculations, as well as to analogous Monte Carlo calculations performed with simplified carrier interaction potentials. Our results highlight the successes and failures of approximate approaches as well as the physical features that determine the stability of small carrier complexes in monolayer transition-metal dichalcogenide materials. In conclusion, we discuss points of agreement and disagreement with recent experiments.

GATE Monte Carlo simulation in a cloud computing environment

NASA Astrophysics Data System (ADS)

Rowedder, Blake Austin

The GEANT4-based GATE is a unique and powerful Monte Carlo (MC) platform, which provides a single code library allowing the simulation of specific medical physics applications, e.g. PET, SPECT, CT, radiotherapy, and hadron therapy. However, this rigorous yet flexible platform is used only sparingly in the clinic due to its lengthy calculation time. By accessing the powerful computational resources of a cloud computing environment, GATE's runtime can be significantly reduced to clinically feasible levels without the sizable investment of a local high performance cluster. This study investigated a reliable and efficient execution of GATE MC simulations using a commercial cloud computing services. Amazon's Elastic Compute Cloud was used to launch several nodes equipped with GATE. Job data was initially broken up on the local computer, then uploaded to the worker nodes on the cloud. The results were automatically downloaded and aggregated on the local computer for display and analysis. Five simulations were repeated for every cluster size between 1 and 20 nodes. Ultimately, increasing cluster size resulted in a decrease in calculation time that could be expressed with an inverse power model. Comparing the benchmark results to the published values and error margins indicated that the simulation results were not affected by the cluster size and thus that integrity of a calculation is preserved in a cloud computing environment. The runtime of a 53 minute long simulation was decreased to 3.11 minutes when run on a 20-node cluster. The ability to improve the speed of simulation suggests that fast MC simulations are viable for imaging and radiotherapy applications. With high power computing continuing to lower in price and accessibility, implementing Monte Carlo techniques with cloud computing for clinical applications will continue to become more attractive.

Oxygen self-diffusion mechanisms in monoclinic Zr O2 revealed and quantified by density functional theory, random walk analysis, and kinetic Monte Carlo calculations

NASA Astrophysics Data System (ADS)

Yang, Jing; Youssef, Mostafa; Yildiz, Bilge

2018-01-01

In this work, we quantify oxygen self-diffusion in monoclinic-phase zirconium oxide as a function of temperature and oxygen partial pressure. A migration barrier of each type of oxygen defect was obtained by first-principles calculations. Random walk theory was used to quantify the diffusivities of oxygen interstitials by using the calculated migration barriers. Kinetic Monte Carlo simulations were used to calculate diffusivities of oxygen vacancies by distinguishing the threefold- and fourfold-coordinated lattice oxygen. By combining the equilibrium defect concentrations obtained in our previous work together with the herein calculated diffusivity of each defect species, we present the resulting oxygen self-diffusion coefficients and the corresponding atomistically resolved transport mechanisms. The predicted effective migration barriers and diffusion prefactors are in reasonable agreement with the experimentally reported values. This work provides insights into oxygen diffusion engineering in Zr O2 -related devices and parametrization for continuum transport modeling.

Hopping in the Crowd to Unveil Network Topology.

PubMed

Asllani, Malbor; Carletti, Timoteo; Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco

2018-04-13

We introduce a nonlinear operator to model diffusion on a complex undirected network under crowded conditions. We show that the asymptotic distribution of diffusing agents is a nonlinear function of the nodes' degree and saturates to a constant value for sufficiently large connectivities, at variance with standard diffusion in the absence of excluded-volume effects. Building on this observation, we define and solve an inverse problem, aimed at reconstructing the a priori unknown connectivity distribution. The method gathers all the necessary information by repeating a limited number of independent measurements of the asymptotic density at a single node, which can be chosen randomly. The technique is successfully tested against both synthetic and real data and is also shown to estimate with great accuracy the total number of nodes.

Hopping in the Crowd to Unveil Network Topology

NASA Astrophysics Data System (ADS)

Asllani, Malbor; Carletti, Timoteo; Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco

2018-04-01

We introduce a nonlinear operator to model diffusion on a complex undirected network under crowded conditions. We show that the asymptotic distribution of diffusing agents is a nonlinear function of the nodes' degree and saturates to a constant value for sufficiently large connectivities, at variance with standard diffusion in the absence of excluded-volume effects. Building on this observation, we define and solve an inverse problem, aimed at reconstructing the a priori unknown connectivity distribution. The method gathers all the necessary information by repeating a limited number of independent measurements of the asymptotic density at a single node, which can be chosen randomly. The technique is successfully tested against both synthetic and real data and is also shown to estimate with great accuracy the total number of nodes.

The diffusion of a Ga atom on GaAs(001)β2(2 × 4): Local superbasin kinetic Monte Carlo

NASA Astrophysics Data System (ADS)

Lin, Yangzheng; Fichthorn, Kristen A.

2017-10-01

We use first-principles density-functional theory to characterize the binding sites and diffusion mechanisms for a Ga adatom on the GaAs(001)β 2(2 × 4) surface. Diffusion in this system is a complex process involving eleven unique binding sites and sixteen different hops between neighboring binding sites. Among the binding sites, we can identify four different superbasins such that the motion between binding sites within a superbasin is much faster than hops exiting the superbasin. To describe diffusion, we use a recently developed local superbasin kinetic Monte Carlo (LSKMC) method, which accelerates a conventional kinetic Monte Carlo (KMC) simulation by describing the superbasins as absorbing Markov chains. We find that LSKMC is up to 4300 times faster than KMC for the conditions probed in this study. We characterize the distribution of exit times from the superbasins and find that these are sometimes, but not always, exponential and we characterize the conditions under which the superbasin exit-time distribution should be exponential. We demonstrate that LSKMC simulations assuming an exponential superbasin exit-time distribution yield the same diffusion coefficients as conventional KMC.

First-principles-based kinetic Monte Carlo studies of diffusion of hydrogen in Ni–Al and Ni–Fe binary alloys

DOE PAGES

Tafen, De Nyago

2015-02-14

The diffusion of dilute hydrogen in fcc Ni–Al and Ni–Fe binary alloys was examined using kinetic Monte Carlo method with input kinetic parameters obtained from first-principles density functional theory. The simulation involves the implementation of computationally efficient energy barrier model that describes the configuration dependence of the hydrogen hopping. The predicted hydrogen diffusion coefficients in Ni and Ni 89.4Fe 10.6 are compared well with the available experimental data. In Ni–Al, the model predicts lower hydrogen diffusivity compared to that in Ni. Overall, diffusion prefactors and the effective activation energies of H in Ni–Fe and Ni–Al are concentration dependent of themore » alloying element. Furthermore, the changes in their values are the results of the short-range order (nearest-neighbor) effect on the interstitial diffusion of hydrogen in fcc Ni-based alloys.« less

Transmission versus reflectance spectroscopy for quantitation.

PubMed

Gardner, Craig M

2018-01-01

The objective of this work was to compare the accuracy of analyte concentration estimation when using transmission versus diffuse reflectance spectroscopy of a scattering medium. Monte Carlo ray tracing of light through the medium was used in conjunction with pure component absorption spectra and Beer-Lambert absorption along each ray's pathlength to generate matched sets of pseudoabsorbance spectra, containing water and six analytes present in skin. PLS regression models revealed an improvement in accuracy when using transmission compared to reflectance for a range of medium thicknesses and instrument noise levels. An analytical expression revealed the source of the accuracy degradation with reflectance was due both to the reduced collection efficiency for a fixed instrument etendue and to the broad pathlength distribution that detected light travels in the medium before exiting from the incident side. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Monte Carlo charged-particle tracking and energy deposition on a Lagrangian mesh.

PubMed

Yuan, J; Moses, G A; McKenty, P W

2005-10-01

A Monte Carlo algorithm for alpha particle tracking and energy deposition on a cylindrical computational mesh in a Lagrangian hydrodynamics code used for inertial confinement fusion (ICF) simulations is presented. The straight line approximation is used to follow propagation of "Monte Carlo particles" which represent collections of alpha particles generated from thermonuclear deuterium-tritium (DT) reactions. Energy deposition in the plasma is modeled by the continuous slowing down approximation. The scheme addresses various aspects arising in the coupling of Monte Carlo tracking with Lagrangian hydrodynamics; such as non-orthogonal severely distorted mesh cells, particle relocation on the moving mesh and particle relocation after rezoning. A comparison with the flux-limited multi-group diffusion transport method is presented for a polar direct drive target design for the National Ignition Facility. Simulations show the Monte Carlo transport method predicts about earlier ignition than predicted by the diffusion method, and generates higher hot spot temperature. Nearly linear speed-up is achieved for multi-processor parallel simulations.

Atomistic models of vacancy-mediated diffusion in silicon

NASA Astrophysics Data System (ADS)

Dunham, Scott T.; Wu, Can Dong

1995-08-01

Vacancy-mediated diffusion of dopants in silicon is investigated using Monte Carlo simulations of hopping diffusion, as well as analytic approximations based on atomistic considerations. Dopant/vacancy interaction potentials are assumed to extend out to third-nearest neighbor distances, as required for pair diffusion theories. Analysis focusing on the third-nearest neighbor sites as bridging configurations for uncorrelated hops leads to an improved analytic model for vacancy-mediated dopant diffusion. The Monte Carlo simulations of vacancy motion on a doped silicon lattice verify the analytic results for moderate doping levels. For very high doping (≳2×1020 cm-3) the simulations show a very rapid increase in pair diffusivity due to interactions of vacancies with more than one dopant atom. This behavior has previously been observed experimentally for group IV and V atoms in silicon [Nylandsted Larsen et al., J. Appl. Phys. 73, 691 (1993)], and the simulations predict both the point of onset and doping dependence of the experimentally observed diffusivity enhancement.

Methods and systems for detecting abnormal digital traffic

DOEpatents

Goranson, Craig A [Kennewick, WA; Burnette, John R [Kennewick, WA

2011-03-22

Aspects of the present invention encompass methods and systems for detecting abnormal digital traffic by assigning characterizations of network behaviors according to knowledge nodes and calculating a confidence value based on the characterizations from at least one knowledge node and on weighting factors associated with the knowledge nodes. The knowledge nodes include a characterization model based on prior network information. At least one of the knowledge nodes should not be based on fixed thresholds or signatures. The confidence value includes a quantification of the degree of confidence that the network behaviors constitute abnormal network traffic.

A Simple Dissection Method for the Conduction System of the Human Heart

ERIC Educational Resources Information Center

Yanagawa, Nariaki; Nakajima, Yuji

2009-01-01

A simple dissection guide for the conduction system of the human heart is shown. The atrioventricular (AV) node, AV bundle, and right bundle branch were identified in a formaldehyde-fixed human heart. The sinu-atrial (SA) node could not be found, but the region in which SA node was contained was identified using the SA nodal artery. Gross…

A Stirling engine analysis method based upon moving gas nodes

NASA Technical Reports Server (NTRS)

Martini, W. R.

1986-01-01

A Lagrangian nodal analysis method for Stirling engines (SEs) is described, validated, and applied to a conventional SE and an isothermalized SE (with fins in the hot and cold spaces). The analysis employs a constant-mass gas node (which moves with respect to the solid nodes during each time step) instead of the fixed gas nodes of Eulerian analysis. The isothermalized SE is found to have efficiency only slightly greater than that of a conventional SE.

T-Opt: A 3D Monte Carlo simulation for light delivery design in photodynamic therapy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Honda, Norihiro; Hazama, Hisanao; Awazu, Kunio

2017-02-01

The interstitial photodynamic therapy (iPDT) with 5-aminolevulinic acid (5-ALA) is a safe and feasible treatment modality of malignant glioblastoma. In order to cover the tumour volume, the exact position of the light diffusers within the lesion is needed to decide precisely. The aim of this study is the development of evaluation method of treatment volume with 3D Monte Carlo simulation for iPDT using 5-ALA. Monte Carlo simulations of fluence rate were performed using the optical properties of the brain tissue infiltrated by tumor cells and normal tissue. 3-D Monte Carlo simulation was used to calculate the position of the light diffusers within the lesion and light transport. The fluence rate near the diffuser was maximum and decreased exponentially with distance. The simulation can calculate the amount of singlet oxygen generated by PDT. In order to increase the accuracy of simulation results, the parameter for simulation includes the quantum yield of singlet oxygen generation, the accumulated concentration of photosensitizer within tissue, fluence rate, molar extinction coefficient at the wavelength of excitation light. The simulation is useful for evaluation of treatment region of iPDT with 5-ALA.

SU-D-210-04: Using Radiotherapy Biomaterials to Brand and Track Deadly Cancer Cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Altundal, Y; Sajo, E; Ngwa, W

Purpose: Metastasis accounts for over 90% of all cancer associated suffering and death and arguably presents the most formidable challenges in cancer management. The detection of metastatic or rare circulating tumor cells (CTCs) in blood or lymph nodes remains a formidable technological challenge. In this study, we investigated the time needed to label each cancer cell in-situ (right at the source tumor) with sufficient number of GNPs that will allow enhanced non-invasive detection via photoacoustic imaging in the lymph nodes. Such in-situ labeling can be achieved via sustained release of the GNPs from Radiotherapy (RT) biomaterials (e.g. fiducials, spacers) coated/loadedmore » with the GNP. Methods: The minimum concentration (1000 GNPs/cell for 50nm GNPs) to detect GNPs with photoacoustic imaging method was experimentally measured by Mallidi et al. and fixed at the tumor sub-volume periphery. In this work, the GNPs were assumed to diffuse from a point source, placed in the middle of a 2–3cm tumor, with an initial concentration of 7–30 mg/g. The time required to label the cells with GNPs was calculated by solving the three dimensional diffusion-reaction equation analytically. The diffusion coefficient of 10nm GNPs was experimentally determined previously. Stokes-Einstein equation was used to calculate the diffusion coefficients for other sizes (2–50nm) of GNPs. The cellular uptake rate constants for several sizes of GNPs were experimentally measured by Jin et al. Results: The time required to label the cells was found 0.635–15.91 days for 2–50nm GNPs with an initial concentration of 7 mg/g GNPs in a 2 cm tumor; 1.379–34.633 days for 2–50nm GNPs with an initial concentration of 30 mg/g GNPs in a 3cm tumor. Conclusion: Our results highlight new potential for labeling CTCs with GNPs released from smart RT biomaterials (i.e. fiducials or spacers loaded with the GNP) towards enhanced non-invasive imaging/detection via photoacoustic imaging.« less

NMR diffusion simulation based on conditional random walk.

PubMed

Gudbjartsson, H; Patz, S

1995-01-01

The authors introduce here a new, very fast, simulation method for free diffusion in a linear magnetic field gradient, which is an extension of the conventional Monte Carlo (MC) method or the convolution method described by Wong et al. (in 12th SMRM, New York, 1993, p.10). In earlier NMR-diffusion simulation methods, such as the finite difference method (FD), the Monte Carlo method, and the deterministic convolution method, the outcome of the calculations depends on the simulation time step. In the authors' method, however, the results are independent of the time step, although, in the convolution method the step size has to be adequate for spins to diffuse to adjacent grid points. By always selecting the largest possible time step the computation time can therefore be reduced. Finally the authors point out that in simple geometric configurations their simulation algorithm can be used to reduce computation time in the simulation of restricted diffusion.

Multi-scale dynamics and relaxation of a tethered membrane in a solvent by Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Pandey, Ras; Anderson, Kelly; Farmer, Barry

2006-03-01

A tethered membrane modeled by a flexible sheet dissipates entropy as it wrinkles and crumples. Nodes of a coarse grained membrane are connected via multiple pathways for dynamical modes to propagate. We consider a sheet with nodes connected by fluctuating bonds on a cubic lattice. The empty lattice sites constitute an effective solvent medium via node-solvent interaction. Each node execute its stochastic motion with the Metropolis algorithm subject to bond fluctuations, excluded volume constraints, and interaction energy. Dynamics and conformation of the sheet are examined at a low and a high temperature with attractive and repulsive node-node interactions for the contrast in an attractive solvent medium. Variations of the mean square displacement of the center node of the sheet and that of its center of mass with the time steps are examined in detail which show different power-law motion from short to long time regimes. Relaxation of the gyration radius and scaling of its asymptotic value with the molecular weight are examined.

Hybrid diffusion-P3 equation in N-layered turbid media: steady-state domain.

PubMed

Shi, Zhenzhi; Zhao, Huijuan; Xu, Kexin

2011-10-01

This paper discusses light propagation in N-layered turbid media. The hybrid diffusion-P3 equation is solved for an N-layered finite or infinite turbid medium in the steady-state domain for one point source using the extrapolated boundary condition. The Fourier transform formalism is applied to derive the analytical solutions of the fluence rate in Fourier space. Two inverse Fourier transform methods are developed to calculate the fluence rate in real space. In addition, the solutions of the hybrid diffusion-P3 equation are compared to the solutions of the diffusion equation and the Monte Carlo simulation. For the case of small absorption coefficients, the solutions of the N-layered diffusion equation and hybrid diffusion-P3 equation are almost equivalent and are in agreement with the Monte Carlo simulation. For the case of large absorption coefficients, the model of the hybrid diffusion-P3 equation is more precise than that of the diffusion equation. In conclusion, the model of the hybrid diffusion-P3 equation can replace the diffusion equation for modeling light propagation in the N-layered turbid media for a wide range of absorption coefficients.

Accurate anharmonic zero-point energies for some combustion-related species from diffusion Monte Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harding, Lawrence B.; Georgievskii, Yuri; Klippenstein, Stephen J.

Full dimensional analytic potential energy surfaces based on CCSD(T)/cc-pVTZ calculations have been determined for 48 small combustion related molecules. The analytic surfaces have been used in Diffusion Monte Carlo calculations of the anharmonic, zero point energies. Here, the resulting anharmonicity corrections are compared to vibrational perturbation theory results based both on the same level of electronic structure theory and on lower level electronic structure methods (B3LYP and MP2).

Accurate Anharmonic Zero-Point Energies for Some Combustion-Related Species from Diffusion Monte Carlo.

PubMed

Harding, Lawrence B; Georgievskii, Yuri; Klippenstein, Stephen J

2017-06-08

Full-dimensional analytic potential energy surfaces based on CCSD(T)/cc-pVTZ calculations have been determined for 48 small combustion-related molecules. The analytic surfaces have been used in Diffusion Monte Carlo calculations of the anharmonic zero-point energies. The resulting anharmonicity corrections are compared to vibrational perturbation theory results based both on the same level of electronic structure theory and on lower-level electronic structure methods (B3LYP and MP2).

Accurate anharmonic zero-point energies for some combustion-related species from diffusion Monte Carlo

DOE PAGES

Harding, Lawrence B.; Georgievskii, Yuri; Klippenstein, Stephen J.

2017-05-17

Full dimensional analytic potential energy surfaces based on CCSD(T)/cc-pVTZ calculations have been determined for 48 small combustion related molecules. The analytic surfaces have been used in Diffusion Monte Carlo calculations of the anharmonic, zero point energies. Here, the resulting anharmonicity corrections are compared to vibrational perturbation theory results based both on the same level of electronic structure theory and on lower level electronic structure methods (B3LYP and MP2).

Monte Carlo Study of Cosmic-Ray Propagation in the Galaxy and Diffuse Gamma-Ray Production

NASA Astrophysics Data System (ADS)

Huang, C.-Y.; Pohl, M.

This talk present preliminary results for the time-dependent cosmic-ray propagation in the Galaxy by a fully 3-dimensional Monte Carlo simulation. The distribution of cosmic-rays (both protons and helium nuclei) in the Galaxy is studied on various spatial scales for both constant and variable cosmic-ray sources. The continuous diffuse gamma-ray emission produced by cosmic-rays during the propagation is evaluated. The results will be compared with calculations made with other propagation models.

Hyperswitch Network For Hypercube Computer

NASA Technical Reports Server (NTRS)

Chow, Edward; Madan, Herbert; Peterson, John

1989-01-01

Data-driven dynamic switching enables high speed data transfer. Proposed hyperswitch network based on mixed static and dynamic topologies. Routing header modified in response to congestion or faults encountered as path established. Static topology meets requirement if nodes have switching elements that perform necessary routing header revisions dynamically. Hypercube topology now being implemented with switching element in each computer node aimed at designing very-richly-interconnected multicomputer system. Interconnection network connects great number of small computer nodes, using fixed hypercube topology, characterized by point-to-point links between nodes.

Trapping in scale-free networks with hierarchical organization of modularity.

PubMed

Zhang, Zhongzhi; Lin, Yuan; Gao, Shuyang; Zhou, Shuigeng; Guan, Jihong; Li, Mo

2009-11-01

A wide variety of real-life networks share two remarkable generic topological properties: scale-free behavior and modular organization, and it is natural and important to study how these two features affect the dynamical processes taking place on such networks. In this paper, we investigate a simple stochastic process--trapping problem, a random walk with a perfect trap fixed at a given location, performed on a family of hierarchical networks that exhibit simultaneously striking scale-free and modular structure. We focus on a particular case with the immobile trap positioned at the hub node having the largest degree. Using a method based on generating functions, we determine explicitly the mean first-passage time (MFPT) for the trapping problem, which is the mean of the node-to-trap first-passage time over the entire network. The exact expression for the MFPT is calculated through the recurrence relations derived from the special construction of the hierarchical networks. The obtained rigorous formula corroborated by extensive direct numerical calculations exhibits that the MFPT grows algebraically with the network order. Concretely, the MFPT increases as a power-law function of the number of nodes with the exponent much less than 1. We demonstrate that the hierarchical networks under consideration have more efficient structure for transport by diffusion in contrast with other analytically soluble media including some previously studied scale-free networks. We argue that the scale-free and modular topologies are responsible for the high efficiency of the trapping process on the hierarchical networks.

Elastic scattering spectroscopy findings in formalin-fixed oral squamous cell carcinoma specimens

NASA Astrophysics Data System (ADS)

Swinson, B.; Elmaaytah, M.; Jerjes, W.; Hopper, C.

2005-11-01

Oral squamous cell carcinoma (OSCC) has been shown to spread locally and infiltrate adjacent bone or via the lymphatic system to the cervical lymph nodes. This usually necessitates a surgical neck dissection and either a local or segmental resection for bone clearance. While histopathology remains the gold standard for tissue diagnosis, several new diagnostic techniques are being developed that rely on physical and biochemical changes that mirror or precede malignant changes within tissue. The aim of this study was to compare findings of Elastic Scattering Spectroscopy (ESS) with histopathology on formalin-fixed specimens of both neck lymph node dissections and de-calcified archival bone from patients with OSCC. We wished to see if this technique could be used as an adjunct or alternative to histopathology in defining cervical nodal involvement and if it could be used to identify bone resection margins positive for tumour. 130 lymph nodes were examined from 13 patients. The nodes were formalin-fixed, bivalved and examined by ESS. The intensity of the spectrum at 4 points was considered for comparison; at 360nm, 450nm, 630nm and 690nm. 341 spectra were taken from the mandibular specimens of 21 patients, of which 231 spectra were taken from histologically positive sites and the rest were normal. The nodes and bone specimens were then routinely processed with haematoxylin and eosin-stained sections, examined histopathologically, and the results compared. Using Linear Discriminant Analysis (LDA) as a statistical method, a sensitivity of 98% and a specificity of 68% was obtained for the neck nodes and a sensitivity of 87% and a specificity of 80% for the bone margins.

The role of tissue microstructure and water exchange in biophysical modelling of diffusion in white matter.

PubMed

Nilsson, Markus; van Westen, Danielle; Ståhlberg, Freddy; Sundgren, Pia C; Lätt, Jimmy

2013-08-01

Biophysical models that describe the outcome of white matter diffusion MRI experiments have various degrees of complexity. While the simplest models assume equal-sized and parallel axons, more elaborate ones may include distributions of axon diameters and axonal orientation dispersions. These microstructural features can be inferred from diffusion-weighted signal attenuation curves by solving an inverse problem, validated in several Monte Carlo simulation studies. Model development has been paralleled by microscopy studies of the microstructure of excised and fixed nerves, confirming that axon diameter estimates from diffusion measurements agree with those from microscopy. However, results obtained in vivo are less conclusive. For example, the amount of slowly diffusing water is lower than expected, and the diffusion-encoded signal is apparently insensitive to diffusion time variations, contrary to what may be expected. Recent understandings of the resolution limit in diffusion MRI, the rate of water exchange, and the presence of microscopic axonal undulation and axonal orientation dispersions may, however, explain such apparent contradictions. Knowledge of the effects of biophysical mechanisms on water diffusion in tissue can be used to predict the outcome of diffusion tensor imaging (DTI) and of diffusion kurtosis imaging (DKI) studies. Alterations of DTI or DKI parameters found in studies of pathologies such as ischemic stroke can thus be compared with those predicted by modelling. Observations in agreement with the predictions strengthen the credibility of biophysical models; those in disagreement could provide clues of how to improve them. DKI is particularly suited for this purpose; it is performed using higher b-values than DTI, and thus carries more information about the tissue microstructure. The purpose of this review is to provide an update on the current understanding of how various properties of the tissue microstructure and the rate of water exchange between microenvironments are reflected in diffusion MRI measurements. We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single PGSE sequences on clinical MRI scanners, but results obtained with animal MRI scanners are also considered. While modelling of white matter is the central theme, experiments on model systems that highlight important aspects of the biophysical models are also reviewed.

Online sequential Monte Carlo smoother for partially observed diffusion processes

NASA Astrophysics Data System (ADS)

Gloaguen, Pierre; Étienne, Marie-Pierre; Le Corff, Sylvain

2018-12-01

This paper introduces a new algorithm to approximate smoothed additive functionals of partially observed diffusion processes. This method relies on a new sequential Monte Carlo method which allows to compute such approximations online, i.e., as the observations are received, and with a computational complexity growing linearly with the number of Monte Carlo samples. The original algorithm cannot be used in the case of partially observed stochastic differential equations since the transition density of the latent data is usually unknown. We prove that it may be extended to partially observed continuous processes by replacing this unknown quantity by an unbiased estimator obtained for instance using general Poisson estimators. This estimator is proved to be consistent and its performance are illustrated using data from two models.

Lambda network having 2.sup.m-1 nodes in each of m stages with each node coupled to four other nodes for bidirectional routing of data packets between nodes

DOEpatents

Napolitano, Jr., Leonard M.

1995-01-01

The Lambda network is a single stage, packet-switched interprocessor communication network for a distributed memory, parallel processor computer. Its design arises from the desired network characteristics of minimizing mean and maximum packet transfer time, local routing, expandability, deadlock avoidance, and fault tolerance. The network is based on fixed degree nodes and has mean and maximum packet transfer distances where n is the number of processors. The routing method is detailed, as are methods for expandability, deadlock avoidance, and fault tolerance.

Fungible Correlation Matrices: A Method for Generating Nonsingular, Singular, and Improper Correlation Matrices for Monte Carlo Research.

PubMed

Waller, Niels G

2016-01-01

For a fixed set of standardized regression coefficients and a fixed coefficient of determination (R-squared), an infinite number of predictor correlation matrices will satisfy the implied quadratic form. I call such matrices fungible correlation matrices. In this article, I describe an algorithm for generating positive definite (PD), positive semidefinite (PSD), or indefinite (ID) fungible correlation matrices that have a random or fixed smallest eigenvalue. The underlying equations of this algorithm are reviewed from both algebraic and geometric perspectives. Two simulation studies illustrate that fungible correlation matrices can be profitably used in Monte Carlo research. The first study uses PD fungible correlation matrices to compare penalized regression algorithms. The second study uses ID fungible correlation matrices to compare matrix-smoothing algorithms. R code for generating fungible correlation matrices is presented in the supplemental materials.

Limitations of the commonly used simplified laterally uniform optical fiber probe-tissue interface in Monte Carlo simulations of diffuse reflectance

PubMed Central

Naglič, Peter; Pernuš, Franjo; Likar, Boštjan; Bürmen, Miran

2015-01-01

Light propagation models often simplify the interface between the optical fiber probe tip and tissue to a laterally uniform boundary with mismatched refractive indices. Such simplification neglects the precise optical properties of the commonly used probe tip materials, e.g. stainless steel or black epoxy. In this paper, we investigate the limitations of the laterally uniform probe-tissue interface in Monte Carlo simulations of diffuse reflectance. In comparison to a realistic probe-tissue interface that accounts for the layout and properties of the probe tip materials, the simplified laterally uniform interface is shown to introduce significant errors into the simulated diffuse reflectance. PMID:26504647

Modeling the migration of platinum nanoparticles on surfaces using a kinetic Monte Carlo approach

DOE PAGES

Li, Lin; Plessow, Philipp N.; Rieger, Michael; ...

2017-02-15

We propose a kinetic Monte Carlo (kMC) model for simulating the movement of platinum particles on supports, based on atom-by-atom diffusion on the surface of the particle. The proposed model was able to reproduce equilibrium cluster shapes predicted using Wulff-construction. The diffusivity of platinum particles was simulated both purely based on random motion and assisted using an external field that causes a drift velocity. The overall particle diffusivity increases with temperature; however, the extracted activation barrier appears to be temperature independent. Additionally, this barrier was found to increase with particle size, as well as, with the adhesion between the particlemore » and the support.« less

Self-assembly of the yeast actomyosin contractile ring as an aggregation process: kinetics of formation and instability regimes

NASA Astrophysics Data System (ADS)

Ojkic, Nikola; Vavylonis, Dimitrios

2009-03-01

Fission yeast cells assemble an equatorial contractile ring for cytokinesis, the last step of mitosis. The ring assembles from ˜ 65 membrane-bound ``nodes''' containing myosin motors and other proteins. Actin filaments that grow out from the nodes establish transient connections among the nodes and aid in pulling them together in a process that appears as pair-wise attraction (Vavylonis et al. Science 97:319, 2008). We used scaling arguments, coarse grained stability analysis of homogeneous states, and Monte Carlo simulations of simple models, to explore the conditions that yield fast and efficient ring formation, as opposed to formation of isolated clumps. We described our results as a function of: number of nodes, rate of establishing connections, range of node interaction, distance traveled per node interaction and broad band width, w. Uniform cortical 2d distributions of nodes are stable over short times due to randomness of connections among nodes, but become unstable over long times due to fluctuations in the initial node distribution. Successful condensation of nodes into a ring requires sufficiently small w such that lateral contraction occurs faster then clump formation.

Anisotropic hydrogen diffusion in α-Zr and Zircaloy predicted by accelerated kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Zhang, Yongfeng; Jiang, Chao; Bai, Xianming

2017-01-01

This report presents an accelerated kinetic Monte Carlo (KMC) method to compute the diffusivity of hydrogen in hcp metals and alloys, considering both thermally activated hopping and quantum tunneling. The acceleration is achieved by replacing regular KMC jumps in trapping energy basins formed by neighboring tetrahedral interstitial sites, with analytical solutions for basin exiting time and probability. Parameterized by density functional theory (DFT) calculations, the accelerated KMC method is shown to be capable of efficiently calculating hydrogen diffusivity in α-Zr and Zircaloy, without altering the kinetics of long-range diffusion. Above room temperature, hydrogen diffusion in α-Zr and Zircaloy is dominated by thermal hopping, with negligible contribution from quantum tunneling. The diffusivity predicted by this DFT + KMC approach agrees well with that from previous independent experiments and theories, without using any data fitting. The diffusivity along is found to be slightly higher than that along , with the anisotropy saturated at about 1.20 at high temperatures, resolving contradictory results in previous experiments. Demonstrated using hydrogen diffusion in α-Zr, the same method can be extended for on-lattice diffusion in hcp metals, or systems with similar trapping basins.

Anisotropic hydrogen diffusion in α-Zr and Zircaloy predicted by accelerated kinetic Monte Carlo simulations

PubMed Central

Zhang, Yongfeng; Jiang, Chao; Bai, Xianming

2017-01-01

This report presents an accelerated kinetic Monte Carlo (KMC) method to compute the diffusivity of hydrogen in hcp metals and alloys, considering both thermally activated hopping and quantum tunneling. The acceleration is achieved by replacing regular KMC jumps in trapping energy basins formed by neighboring tetrahedral interstitial sites, with analytical solutions for basin exiting time and probability. Parameterized by density functional theory (DFT) calculations, the accelerated KMC method is shown to be capable of efficiently calculating hydrogen diffusivity in α-Zr and Zircaloy, without altering the kinetics of long-range diffusion. Above room temperature, hydrogen diffusion in α-Zr and Zircaloy is dominated by thermal hopping, with negligible contribution from quantum tunneling. The diffusivity predicted by this DFT + KMC approach agrees well with that from previous independent experiments and theories, without using any data fitting. The diffusivity along is found to be slightly higher than that along , with the anisotropy saturated at about 1.20 at high temperatures, resolving contradictory results in previous experiments. Demonstrated using hydrogen diffusion in α-Zr, the same method can be extended for on-lattice diffusion in hcp metals, or systems with similar trapping basins. PMID:28106154

Anisotropic hydrogen diffusion in α-Zr and Zircaloy predicted by accelerated kinetic Monte Carlo simulations

DOE PAGES

Zhang, Yongfeng; Jiang, Chao; Bai, Xianming

2017-01-20

Here, this report presents an accelerated kinetic Monte Carlo (KMC) method to compute the diffusivity of hydrogen in hcp metals and alloys, considering both thermally activated hopping and quantum tunneling. The acceleration is achieved by replacing regular KMC jumps in trapping energy basins formed by neighboring tetrahedral interstitial sites, with analytical solutions for basin exiting time and probability. Parameterized by density functional theory (DFT) calculations, the accelerated KMC method is shown to be capable of efficiently calculating hydrogen diffusivity in α-Zr and Zircaloy, without altering the kinetics of long-range diffusion. Above room temperature, hydrogen diffusion in α-Zr and Zircaloy ismore » dominated by thermal hopping, with negligible contribution from quantum tunneling. The diffusivity predicted by this DFT + KMC approach agrees well with that from previous independent experiments and theories, without using any data fitting. The diffusivity along < c > is found to be slightly higher than that along < a >, with the anisotropy saturated at about 1.20 at high temperatures, resolving contradictory results in previous experiments. Demonstrated using hydrogen diffusion in α-Zr, the same method can be extended for on-lattice diffusion in hcp metals, or systems with similar trapping basins.« less

Identification of influential spreaders in online social networks using interaction weighted K-core decomposition method

NASA Astrophysics Data System (ADS)

Al-garadi, Mohammed Ali; Varathan, Kasturi Dewi; Ravana, Sri Devi

2017-02-01

Online social networks (OSNs) have become a vital part of everyday living. OSNs provide researchers and scientists with unique prospects to comprehend individuals on a scale and to analyze human behavioral patterns. Influential spreaders identification is an important subject in understanding the dynamics of information diffusion in OSNs. Targeting these influential spreaders is significant in planning the techniques for accelerating the propagation of information that is useful for various applications, such as viral marketing applications or blocking the diffusion of annoying information (spreading of viruses, rumors, online negative behaviors, and cyberbullying). Existing K-core decomposition methods consider links equally when calculating the influential spreaders for unweighted networks. Alternatively, the proposed link weights are based only on the degree of nodes. Thus, if a node is linked to high-degree nodes, then this node will receive high weight and is treated as an important node. Conversely, the degree of nodes in OSN context does not always provide accurate influence of users. In the present study, we improve the K-core method for OSNs by proposing a novel link-weighting method based on the interaction among users. The proposed method is based on the observation that the interaction of users is a significant factor in quantifying the spreading capability of user in OSNs. The tracking of diffusion links in the real spreading dynamics of information verifies the effectiveness of our proposed method for identifying influential spreaders in OSNs as compared with degree centrality, PageRank, and original K-core.

Complex mammary carcinoma with metastases to lymph nodes, subcutaneous tissue, and multiple joints in a dog.

PubMed

McCourt, Maggie R; Dieterly, Alexandra M; Mackey, Paige E; Lyon, Shane D; Rizzi, Theresa E; Ritchey, Jerry W

2018-05-07

An 8-year-old, intact female, mixed-breed dog presented to the Oklahoma State University Boren Veterinary Medical Teaching Hospital for evaluation of progressive lameness and joint effusion of multiple joints. Physical examination revealed joint effusion of the elbow, hock, and stifle joints bilaterally, enlarged left axillary and right popliteal lymph nodes, a subcutaneous mass over the left elbow, and a subcutaneous mass involving the left second and third mammary glands. Cytologic examination of the mammary mass, enlarged lymph nodes, and joint fluid from most affected joints revealed a monomorphic population of loosely cohesive neoplastic epithelial cells. The patient was humanely euthanized, and subsequent necropsy with histopathologic examination revealed a complex mammary carcinoma with metastases to enlarged lymph nodes, subcutaneous tissue over the left elbow, and the synovium of multiple joints. Immunohistochemical stains were performed and showed diffusely positive pan cytokeratin, CK8/18, and CK19 staining in the neoplastic luminal epithelial cells of the mammary carcinoma, synovium, and lymph nodes, and showed diffusely positive vimentin staining of the myoepithelial cells. Myoepithelial calponin positivity was diffuse in the mammary mass and lymph nodes but minimal in the synovium. Only the mammary mass showed p63 positivity. Metastatic mammary neoplasia is relatively common in dogs; however, metastasis to the synovium has only been reported once previously in the literature. This is the first case utilizing immunohistochemistry for confirmation and characterization of metastases. © 2018 American Society for Veterinary Clinical Pathology.

A network model of successive partitioning-limited solute diffusion through the stratum corneum.

PubMed

Schumm, Phillip; Scoglio, Caterina M; van der Merwe, Deon

2010-02-07

As the most exposed point of contact with the external environment, the skin is an important barrier to many chemical exposures, including medications, potentially toxic chemicals and cosmetics. Traditional dermal absorption models treat the stratum corneum lipids as a homogenous medium through which solutes diffuse according to Fick's first law of diffusion. This approach does not explain non-linear absorption and irregular distribution patterns within the stratum corneum lipids as observed in experimental data. A network model, based on successive partitioning-limited solute diffusion through the stratum corneum, where the lipid structure is represented by a large, sparse, and regular network where nodes have variable characteristics, offers an alternative, efficient, and flexible approach to dermal absorption modeling that simulates non-linear absorption data patterns. Four model versions are presented: two linear models, which have unlimited node capacities, and two non-linear models, which have limited node capacities. The non-linear model outputs produce absorption to dose relationships that can be best characterized quantitatively by using power equations, similar to the equations used to describe non-linear experimental data.

A framework for analyzing contagion in assortative banking networks

PubMed Central

Hurd, Thomas R.; Gleeson, James P.; Melnik, Sergey

2017-01-01

We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis)assortative edge probabilities (i.e., a tendency for small banks to link to large banks). We analyze default cascades triggered by shocking the network and find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point. We derive a cascade condition, analogous to the basic reproduction number R0 in epidemic modelling, that characterizes whether or not a single initially defaulted bank can trigger a cascade that extends to a finite fraction of the infinite network. This cascade condition is an easily computed measure of the systemic risk inherent in a given banking network topology. We use percolation theory for random networks to derive a formula for the frequency of global cascades. These analytical results are shown to provide limited quantitative agreement with Monte Carlo simulation studies of finite-sized networks. We show that edge-assortativity, the propensity of nodes to connect to similar nodes, can have a strong effect on the level of systemic risk as measured by the cascade condition. However, the effect of assortativity on systemic risk is subtle, and we propose a simple graph theoretic quantity, which we call the graph-assortativity coefficient, that can be used to assess systemic risk. PMID:28231324

A framework for analyzing contagion in assortative banking networks.

PubMed

Hurd, Thomas R; Gleeson, James P; Melnik, Sergey

2017-01-01

We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis)assortative edge probabilities (i.e., a tendency for small banks to link to large banks). We analyze default cascades triggered by shocking the network and find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point. We derive a cascade condition, analogous to the basic reproduction number R0 in epidemic modelling, that characterizes whether or not a single initially defaulted bank can trigger a cascade that extends to a finite fraction of the infinite network. This cascade condition is an easily computed measure of the systemic risk inherent in a given banking network topology. We use percolation theory for random networks to derive a formula for the frequency of global cascades. These analytical results are shown to provide limited quantitative agreement with Monte Carlo simulation studies of finite-sized networks. We show that edge-assortativity, the propensity of nodes to connect to similar nodes, can have a strong effect on the level of systemic risk as measured by the cascade condition. However, the effect of assortativity on systemic risk is subtle, and we propose a simple graph theoretic quantity, which we call the graph-assortativity coefficient, that can be used to assess systemic risk.

Cell-veto Monte Carlo algorithm for long-range systems.

PubMed

Kapfer, Sebastian C; Krauth, Werner

2016-09-01

We present a rigorous efficient event-chain Monte Carlo algorithm for long-range interacting particle systems. Using a cell-veto scheme within the factorized Metropolis algorithm, we compute each single-particle move with a fixed number of operations. For slowly decaying potentials such as Coulomb interactions, screening line charges allow us to take into account periodic boundary conditions. We discuss the performance of the cell-veto Monte Carlo algorithm for general inverse-power-law potentials, and illustrate how it provides a new outlook on one of the prominent bottlenecks in large-scale atomistic Monte Carlo simulations.

Optimizing Resource Utilization in Grid Batch Systems

NASA Astrophysics Data System (ADS)

Gellrich, Andreas

2012-12-01

On Grid sites, the requirements of the computing tasks (jobs) to computing, storage, and network resources differ widely. For instance Monte Carlo production jobs are almost purely CPU-bound, whereas physics analysis jobs demand high data rates. In order to optimize the utilization of the compute node resources, jobs must be distributed intelligently over the nodes. Although the job resource requirements cannot be deduced directly, jobs are mapped to POSIX UID/GID according to the VO, VOMS group and role information contained in the VOMS proxy. The UID/GID then allows to distinguish jobs, if users are using VOMS proxies as planned by the VO management, e.g. ‘role=production’ for Monte Carlo jobs. It is possible to setup and configure batch systems (queuing system and scheduler) at Grid sites based on these considerations although scaling limits were observed with the scheduler MAUI. In tests these limitations could be overcome with a home-made scheduler.

A monte carlo study of restricted diffusion: Implications for diffusion MRI of prostate cancer.

PubMed

Gilani, Nima; Malcolm, Paul; Johnson, Glyn

2017-04-01

Diffusion MRI is used frequently to assess prostate cancer. The prostate consists of cellular tissue surrounding fluid filled ducts. Here, the diffusion properties of the ductal fluid alone were studied. Monte Carlo simulations were used to investigate ductal residence times to determine whether ducts can be regarded as forming a separate compartment and whether ductal radius could determine the Apparent Diffusion Coefficient (ADC) of the ductal fluid. Random walks were simulated in cavities. Average residence times were estimated for permeable cavities. Signal reductions resulting from application of a Stejskal-Tanner pulse sequence were calculated in impermeable cavities. Simulations were repeated for cavities of different radii and different diffusion times. Residence times are at least comparable with diffusion times even in relatively high grade tumors. ADCs asymptotically approach theoretical limiting values. At large radii and short diffusion times, ADCs are similar to free diffusion. At small radii and long diffusion times, ADCs are reduced toward zero, and kurtosis approaches a value of -1.2. Restricted diffusion in cavities of similar sizes to prostate ducts may reduce ductal ADCs. This may contribute to reductions in total ADC seen in prostate cancer. Magn Reson Med 77:1671-1677, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Multimodal imaging of lymph nodes and tumors using glycol-chitosan-coated gold nanoparticles (Conference Presentation)

NASA Astrophysics Data System (ADS)

Sun, In-Cheol; Dumani, Diego S.; Emelianov, Stanislav Y.

2017-03-01

A key step in staging cancer is the diagnosis of metastasis that spreads through lymphatic system. For this reason, researchers develop various methods of sentinel lymph node mapping that often use a radioactive tracer. This study introduces a safe, cost-effective, high-resolution, high-sensitivity, and real-time method of visualizing the sentinel lymph node: ultrasound-guided photoacoustic (US/PA) imaging augmented by a contrast agent. In this work, we use clearable gold nanoparticles covered by a biocompatible polymer (glycol chitosan) to enhance cellular uptake by macrophages abundant in lymph nodes. We incubate macrophages with glycol-chitosan-coated gold nanoparticles (0.05 mg Au/ml), and then fix them with paraformaldehyde solution for an analysis of in vitro dark-field microscopy and cell phantom. The analysis shows enhanced cellular uptake of nanoparticles by macrophages and strong photoacoustic signal from labeled cells in tissue-mimicking cell phantoms consisting gelatin solution (6 %) with silica gel (25 μm, 0.3%) and fixed macrophages. The in-vivo US/PA imaging of cervical lymph nodes in healthy mice (nu/nu, female, 5 weeks) indicates a strong photoacoustic signal from a lymph node 10 minutes post-injection (2.5 mg Au/ml, 80 μl). The signal intensity and the nanoparticle-labeled volume of tissue within the lymph node continues to increase until 4 h post-injection. Histological analysis further confirms the accumulation of gold nanoparticles within the lymph nodes. This work suggests the feasibility of molecular/cellular US/PA imaging with biocompatible gold nanoparticles as a photoacoustic contrast agent in the diagnosis of lymph-node-related diseases.

Combining Heterogeneous Correlation Matrices: Simulation Analysis of Fixed-Effects Methods

ERIC Educational Resources Information Center

Hafdahl, Adam R.

2008-01-01

Monte Carlo studies of several fixed-effects methods for combining and comparing correlation matrices have shown that two refinements improve estimation and inference substantially. With rare exception, however, these simulations have involved homogeneous data analyzed using conditional meta-analytic procedures. The present study builds on…

Travelling to the south: Phylogeographic spatial diffusion model in Monttea aphylla (Plantaginaceae), an endemic plant of the Monte Desert

PubMed Central

Cosacov, Andrea; Ferreiro, Gabriela; Johnson, Leigh A.; Sérsic, Alicia N.

2017-01-01

Effects of Pleistocene climatic oscillations on plant phylogeographic patterns are relatively well studied in forest, savanna and grassland biomes, but such impacts remain less explored on desert regions of the world, especially in South America. Here, we performed a phylogeographical study of Monttea aphylla, an endemic species of the Monte Desert, to understand the evolutionary history of vegetation communities inhabiting the South American Arid Diagonal. We obtained sequences of three chloroplast (trnS–trnfM, trnH–psbA and trnQ–rps16) and one nuclear (ITS) intergenic spacers from 272 individuals of 34 localities throughout the range of the species. Population genetic and Bayesian coalescent analyses were performed to infer genealogical relationships among haplotypes, population genetic structure, and demographic history of the study species. Timing of demographic events was inferred using Bayesian Skyline Plot and the spatio-temporal patterns of lineage diversification was reconstructed using Bayesian relaxed diffusion models. Palaeo-distribution models (PDM) were performed through three different timescales to validate phylogeographical patterns. Twenty-five and 22 haplotypes were identified in the cpDNA and nDNA data, respectively. that clustered into two main genealogical lineages following a latitudinal pattern, the northern and the southern Monte (south of 35° S). The northern Monte showed two lineages of high genetic structure, and more relative stable demography than the southern Monte that retrieved three groups with little phylogenetic structure and a strong signal of demographic expansion that would have started during the Last Interglacial period (ca. 120 Ka). The PDM and diffusion models analyses agreed in the southeast direction of the range expansion. Differential effect of climatic oscillations across the Monte phytogeographic province was observed in Monttea aphylla lineages. In northern Monte, greater genetic structure and more relative stable demography resulted from a more stable climate than in the southern Monte. Pleistocene glaciations drastically decreased the species area in the southern Monte, which expanded in a southeastern direction to the new available areas during the interglacial periods. PMID:28582433

Convective diffusion of nanoparticles from the epithelial barrier toward regional lymph nodes.

PubMed

Dukhin, Stanislav S; Labib, Mohamed E

2013-11-01

Drug delivery using nanoparticles as drug carriers has recently attracted the attention of many investigators. Targeted delivery of nanoparticles to the lymph nodes is especially important to prevent cancer metastasis or infection, and to diagnose disease stage. However, systemic injection of nanoparticles often results in organ toxicity because they reach and accumulate in all the lymph nodes in the body. An attractive strategy would be to deliver the drug-loaded nanoparticles to a subset of draining lymph nodes corresponding to a specific site or organ to minimize systemic toxicity. In this respect, mucosal delivery of nanoparticles to regional draining lymph nodes of a selected site creates a new opportunity to accomplish this task with minimal toxicity. One example is the delivery of nanoparticles from the vaginal lumen to draining lymph nodes to prevent the transmission of HIV in women. Other known examples include mucosal delivery of vaccines to induce immunity. In all cases, molecular and particle transport by means of diffusion and convective diffusion play a major role. The corresponding transport processes have common inherent regularities and are addressed in this review. Here we use nanoparticle delivery from the vaginal lumen to the lymph nodes as an example to address the many aspects of associated transport processes. In this case, nanoparticles penetrate the epithelial barrier and move through the interstitium (tissue) to the initial lymphatics until they finally reach the lymph nodes. Since the movement of interstitial liquid near the epithelial barrier is retarded, nanoparticle transport was found to take place through special foci present in the epithelium. Immediately after nanoparticles emerge from the foci, they move through the interstitium due to diffusion affected by convection (convective diffusion). Specifically, the convective transport of nanoparticles occurs due to their convection together with interstitial fluid through the interstitium toward the initial lymph capillaries. Afterwards, nanoparticles move together with the lymph flow along the initial lymph capillaries and then enter the afferent lymphatics and ultimately reach the lymph node. As the liquid moves through the interstitium toward the initial lymph capillaries due to the axial movement of lymph along the lymphatics, the theory for coupling between lymph flow and concomitant flow through the interstitium is developed to describe this general case. The developed theory is applied to interpret the large uptake of Qdots by lymph nodes during inflammation, which is induced by pre-treating mouse vagina with the surfactant Nonoxynol-9 prior to instilling the Qdots. Inflammation is viewed here to cause broadening of the pores within the interstitium with the concomitant formation of transport channels which function as conduits to transport the nanoparticles to the initial lymph capillaries. We introduced the term "effective channels" to denote those channels which interconnect with foci present in the epithelial barrier and which function to transport nanoparticles to initial lymph capillaries. The time of transport toward the lymph node, predicated by the theory, increases rapidly with increasing the distance y0 between the epithelial barrier and the initial lymph capillaries. Transport time is only a few hours, when y0 is small, about some R (where R is the initial lymph capillary radius), due to the predomination of a rather rapid convection in this case. This transport time to the lymph nodes may be tens of hours (or longer) when y0 is essentially larger and the slow diffusion controls the transport rate in a zone not far from the epithelial barrier, where convection is weak at large y0. Accounting for transport by diffusion only, which is mainly considered in many relevant publications, is not sufficient to explain our nanoparticle uptake kinetics because the possibility of fast transport due to convection is overlooked. Our systematic investigations have revealed that the information about the main transport conditions, namely, y0 and the pore broadening up to the dimension of the interstitial transport channels, is necessary to create the quantitative model of enhanced transport during inflammation with the use of the proposed model as a prerequisite. The modeling for convective diffusion of nanoparticles from the epithelial barrier to the lymph node has been mainly accomplished here, while the diffusion only scenario is accounted for in other studies. This first modeling is a semi-quantitative one. A more rigorous mathematical approach is almost impossible at this stage because the transport properties of the model are introduced here for the first time. These properties include: discovery of foci in the epithelium, formation of transport channels, definition of channels interconnecting with foci (effective foci and channels), generation of flow in the interstitium toward the initial lymph capillaries due to axial flow within afferent lymphatics, deformation of this flow due to hydrodynamic impermeability of the squamous layer with the formation of the hydrodynamic stagnation zone near the epithelial barrier, predomination of slow diffusion transport within the above zone, and predomination of fast convection of nanoparticles near the initial lymph capillaries. Copyright © 2013 Elsevier B.V. All rights reserved.

Convective diffusion of nanoparticles from the epithelial barrier towards regional lymph nodes

PubMed Central

Dukhin, Stanislav S; Labib, Mohamed E.

2013-01-01

Drug delivery using nanoparticles as drug carriers has recently attracted the attention of many investigators. Targeted delivery of nanoparticles to lymph nodes is especially important to prevent cancer metastasis or infection, and to diagnose disease stage. However, systemic injection of nanoparticles often results in organ toxicity because they reach and accumulate in all the lymph nodes in the body. An attractive strategy would be to deliver the drug-loaded nanoparticles to a subset of draining lymph nodes corresponding to a specific site or organ to minimize systemic toxicity. In this respect, mucosal delivery of nanoparticles to regional draining lymph nodes of a selected site creates a new opportunity to accomplish this task with minimal toxicity. One example is the delivery of nanoparticles from the vaginal lumen to draining lymph nodes to prevent the transmission of HIV in women. Other known examples include mucosal delivery of vaccines to induce immunity. In all cases, molecular and particle transport by means of diffusion and convective diffusion play a major role. The corresponding transport processes have common inherent regularities and are addressed in this review. Here we use nanoparticles delivery from the vaginal lumen to lymph nodes as an example to address the many aspects of associated transport processes. In this case, nanoparticles penetrate the epithelial barrier and move through the interstitium (tissue) to the initial lymphatics until they finally reach the lymph nodes. Since the movement of interstitial liquid near the epithelial barrier is retarded, nanoparticles transport was found to take place through special foci present in the epithelium. Immediately after nanoparticles emerge from the foci, they move through the interstitium due to diffusion affected by convection (convective diffusion). Specifically, the convective transport of nanoparticles occurs due to their convection together with interstitial fluid through the interstitium towards the initial lymph capillaries. Afterwards, nanoparticles move together with the lymph flow along the initial lymph capillaries and then enter the afferent lymphatics and ultimately reach the lymph node. As the liquid moves through the interstitium towards the initial lymph capillaries due to the axial movement of lymph along the lymphatics, the theory for coupling between lymph flow and concomitant flow through the interstitium is developed to describe this general case. The developed theory is applied to interpret the large uptake of Qdots by lymph nodes during inflammation, which is induced by pre-treating mouse vagina with the surfactant Nonoxynol-9 prior to instilling the Qdots. Inflammation is viewed here to cause broadening of the pores within the interstitium with the concomitant formation of transport channels which function as conduits to transport the nanoparticles to the initial lymph capillaries. We introduced the term “effective channels” to denote those channels which interconnect with foci present in the epithelial barrier and which function to transport nanoparticles to initial lymph capillaries. The time of transport towards the lymph node, predicated by the theory, increases rapidly with increasing the distance y0 between the epithelial barrier and the initial lymph capillaries. Transport time is only a few hours, when y0 is small, about some R (where R is the initial lymph capillary radius), due to the predomination of a rather rapid convection in this case. This transport time to lymph nodes may be tens of hours (or longer) when y0 is essentially larger and the slow diffusion controls the transport rate in a zone not far from the epithelial barrier, where convection is weak at large y0. Accounting for transport by diffusion only, which is mainly considered in many relevant publications, is not sufficient to explain our nanoparticles uptake kinetics because the possibility of fast transport due to convection is overlooked. Our systematic investigations have revealed that the information about the main transport conditions, namely, y0 and the pore broadening up to the dimension of the interstitial transport channels, is necessary to create the quantitative model of enhanced transport during inflammation with the use of the proposed model as a prerequisite. The modeling for convective diffusion of nanoparticles from the epithelial barrier to the lymph node has been mainly accomplished here, while the diffusion only scenario is accounted for in other studies. This first modeling is a semi-quantitative one. A more rigorous mathematical approach is almost impossible at this stage because the transport properties of the model are introduced here for the first time. These properties include: discovery of foci in the epithelium, formation of transport channels, definition of channels interconnecting with foci (effective foci and channels), generation of flow in the interstitium towards the initial lymph capillaries due to axial flow within afferent lymphatics, deformation of this flow due to hydrodynamic impermeability of the squamous layer with the formation of the hydrodynamic stagnation zone near the epithelial barrier, predomination of slow diffusion transport within the above zone, and predomination of fast convection of nanoparticles near the initial lymph capillaries. PMID:23859221

Multi-target Detection, Tracking, and Data Association on Road Networks Using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Barkley, Brett E.

A cooperative detection and tracking algorithm for multiple targets constrained to a road network is presented for fixed-wing Unmanned Air Vehicles (UAVs) with a finite field of view. Road networks of interest are formed into graphs with nodes that indicate the target likelihood ratio (before detection) and position probability (after detection). A Bayesian likelihood ratio tracker recursively assimilates target observations until the cumulative observations at a particular location pass a detection criterion. At this point, a target is considered detected and a position probability is generated for the target on the graph. Data association is subsequently used to route future measurements to update the likelihood ratio tracker (for undetected target) or to update a position probability (a previously detected target). Three strategies for motion planning of UAVs are proposed to balance searching for new targets with tracking known targets for a variety of scenarios. Performance was tested in Monte Carlo simulations for a variety of mission parameters, including tracking on road networks with varying complexity and using UAVs at various altitudes.

Finite-Time and Fixed-Time Cluster Synchronization With or Without Pinning Control.

PubMed

Liu, Xiwei; Chen, Tianping

2018-01-01

In this paper, the finite-time and fixed-time cluster synchronization problem for complex networks with or without pinning control are discussed. Finite-time (or fixed-time) synchronization has been a hot topic in recent years, which means that the network can achieve synchronization in finite-time, and the settling time depends on the initial values for finite-time synchronization (or the settling time is bounded by a constant for any initial values for fixed-time synchronization). To realize the finite-time and fixed-time cluster synchronization, some simple distributed protocols with or without pinning control are designed and the effectiveness is rigorously proved. Several sufficient criteria are also obtained to clarify the effects of coupling terms for finite-time and fixed-time cluster synchronization. Especially, when the cluster number is one, the cluster synchronization becomes the complete synchronization problem; when the network has only one node, the coupling term between nodes will disappear, and the synchronization problem becomes the simplest master-slave case, which also includes the stability problem for nonlinear systems like neural networks. All these cases are also discussed. Finally, numerical simulations are presented to demonstrate the correctness of obtained theoretical results.

A Distributed Data-Gathering Protocol Using AUV in Underwater Sensor Networks.

PubMed

Khan, Jawaad Ullah; Cho, Ho-Shin

2015-08-06

In this paper, we propose a distributed data-gathering scheme using an autonomous underwater vehicle (AUV) working as a mobile sink to gather data from a randomly distributed underwater sensor network where sensor nodes are clustered around several cluster headers. Unlike conventional data-gathering schemes where the AUV visits either every node or every cluster header, the proposed scheme allows the AUV to visit some selected nodes named path-nodes in a way that reduces the overall transmission power of the sensor nodes. Monte Carlo simulations are performed to investigate the performance of the proposed scheme compared with several preexisting techniques employing the AUV in terms of total amount of energy consumption, standard deviation of each node's energy consumption, latency to gather data at a sink, and controlling overhead. Simulation results show that the proposed scheme not only reduces the total energy consumption but also distributes the energy consumption more uniformly over the network, thereby increasing the lifetime of the network.

Effect of node attributes on the temporal dynamics of network structure

NASA Astrophysics Data System (ADS)

Momeni, Naghmeh; Fotouhi, Babak

2017-03-01

Many natural and social networks evolve in time and their structures are dynamic. In most networks, nodes are heterogeneous, and their roles in the evolution of structure differ. This paper focuses on the role of individual attributes on the temporal dynamics of network structure. We focus on a basic model for growing networks that incorporates node attributes (which we call "quality"), and we focus on the problem of forecasting the structural properties of the network in arbitrary times for an arbitrary initial network. That is, we address the following question: If we are given a certain initial network with given arbitrary structure and known node attributes, then how does the structure change in time as new nodes with given distribution of attributes join the network? We solve the model analytically and obtain the quality-degree joint distribution and degree correlations. We characterize the role of individual attributes in the position of individual nodes in the hierarchy of connections. We confirm the theoretical findings with Monte Carlo simulations.

Radon detection in conical diffusion chambers: Monte Carlo calculations and experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rickards, J.; Golzarri, J. I.; Espinosa, G., E-mail: espinosa@fisica.unam.mx

2015-07-23

The operation of radon detection diffusion chambers of truncated conical shape was studied using Monte Carlo calculations. The efficiency was studied for alpha particles generated randomly in the volume of the chamber, and progeny generated randomly on the interior surface, which reach track detectors placed in different positions within the chamber. Incidence angular distributions, incidence energy spectra and path length distributions are calculated. Cases studied include different positions of the detector within the chamber, varying atmospheric pressure, and introducing a cutoff incidence angle and energy.

Topological Weyl superconductor to diffusive thermal Hall metal crossover in the B phase of UPt3

NASA Astrophysics Data System (ADS)

Goswami, Pallab; Nevidomskyy, Andriy H.

2015-12-01

The recent phase-sensitive measurements in the superconducting B phase of UPt3 provide strong evidence for the triplet, chiral kz(kx±i ky) 2 pairing symmetries, which endow the Cooper pairs with orbital angular momentum projections Lz=±2 along the c axis. In the absence of disorder such pairing can support both line and point nodes, and both types of nodal quasiparticles exhibit nontrivial topology in the momentum space. The point nodes, located at the intersections of the closed Fermi surfaces with the c axis, act as the double monopoles and the antimonopoles of the Berry curvature, and generalize the notion of Weyl quasiparticles. Consequently, the B phase should support an anomalous thermal Hall effect, the polar Kerr effect, in addition to the protected Fermi arcs on the (1 ,0 ,0 ) and the (0 ,1 ,0 ) surfaces. The line node at the Fermi surface equator acts as a vortex loop in the momentum space and gives rise to the zero-energy, dispersionless Andreev bound states on the (0 ,0 ,1 ) surface. At the transition from the B phase to the A phase, the time-reversal symmetry is restored, and only the line node survives inside the A phase. As both line and double-Weyl point nodes possess linearly vanishing density of states, we show that weak disorder acts as a marginally relevant perturbation. Consequently, an infinitesimal amount of disorder destroys the ballistic quasiparticle pole, while giving rise to a diffusive phase with a finite density of states at the zero energy. The resulting diffusive phase exhibits T -linear specific heat, and an anomalous thermal Hall effect. We predict that the low-temperature thermodynamic and transport properties display a crossover between a ballistic thermal Hall semimetal and a diffusive thermal Hall metal. By contrast, the diffusive phase obtained from a time-reversal-invariant pairing exhibits only the T -linear specific heat without any anomalous thermal Hall effect.

Recent advances and future prospects for Monte Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Forrest B

2010-01-01

The history of Monte Carlo methods is closely linked to that of computers: The first known Monte Carlo program was written in 1947 for the ENIAC; a pre-release of the first Fortran compiler was used for Monte Carlo In 1957; Monte Carlo codes were adapted to vector computers in the 1980s, clusters and parallel computers in the 1990s, and teraflop systems in the 2000s. Recent advances include hierarchical parallelism, combining threaded calculations on multicore processors with message-passing among different nodes. With the advances In computmg, Monte Carlo codes have evolved with new capabilities and new ways of use. Production codesmore » such as MCNP, MVP, MONK, TRIPOLI and SCALE are now 20-30 years old (or more) and are very rich in advanced featUres. The former 'method of last resort' has now become the first choice for many applications. Calculations are now routinely performed on office computers, not just on supercomputers. Current research and development efforts are investigating the use of Monte Carlo methods on FPGAs. GPUs, and many-core processors. Other far-reaching research is exploring ways to adapt Monte Carlo methods to future exaflop systems that may have 1M or more concurrent computational processes.« less

Parameters Free Computational Characterization of Defects in Transition Metal Oxides with Diffusion Quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Santana, Juan A.; Krogel, Jaron T.; Kent, Paul R.; Reboredo, Fernando

Materials based on transition metal oxides (TMO's) are among the most challenging systems for computational characterization. Reliable and practical computations are possible by directly solving the many-body problem for TMO's with quantum Monte Carlo (QMC) methods. These methods are very computationally intensive, but recent developments in algorithms and computational infrastructures have enabled their application to real materials. We will show our efforts on the application of the diffusion quantum Monte Carlo (DMC) method to study the formation of defects in binary and ternary TMO and heterostructures of TMO. We will also outline current limitations in hardware and algorithms. This work is supported by the Materials Sciences & Engineering Division of the Office of Basic Energy Sciences, U.S. Department of Energy (DOE).

Lambda network having 2{sup m{minus}1} nodes in each of m stages with each node coupled to four other nodes for bidirectional routing of data packets between nodes

DOEpatents

Napolitano, L.M. Jr.

1995-11-28

The Lambda network is a single stage, packet-switched interprocessor communication network for a distributed memory, parallel processor computer. Its design arises from the desired network characteristics of minimizing mean and maximum packet transfer time, local routing, expandability, deadlock avoidance, and fault tolerance. The network is based on fixed degree nodes and has mean and maximum packet transfer distances where n is the number of processors. The routing method is detailed, as are methods for expandability, deadlock avoidance, and fault tolerance. 14 figs.

Dynamic Monte Carlo description of thermal desorption processes

NASA Astrophysics Data System (ADS)

Weinketz, Sieghard

1994-07-01

The applicability of the dynamic Monte Carlo method of Fichthorn and Weinberg, in which the time evolution of a system is described in terms of the absolute number of different microscopic possible events and their associated transition rates, is discussed for the case of thermal desorption simulations. It is shown that the definition of the time increment at each successful event leads naturally to the macroscopic differential equation of desorption, in the case of simple first- and second-order processes in which the only possible events are desorption and diffusion. This equivalence is numerically demonstrated for a second-order case. In the sequence, the equivalence of this method with the Monte Carlo method of Sales and Zgrablich for more complex desorption processes, allowing for lateral interactions between adsorbates, is shown, even though the dynamic Monte Carlo method does not bear their limitation of a rapid surface diffusion condition, thus being able to describe a more complex ``kinetics'' of surface reactive processes, and therefore be applied to a wider class of phenomena, such as surface catalysis.

Competing contact processes in the Watts-Strogatz network

NASA Astrophysics Data System (ADS)

Rybak, Marcin; Malarz, Krzysztof; Kułakowski, Krzysztof

2016-06-01

We investigate two competing contact processes on a set of Watts-Strogatz networks with the clustering coefficient tuned by rewiring. The base for network construction is one-dimensional chain of N sites, where each site i is directly linked to nodes labelled as i ± 1 and i ± 2. So initially, each node has the same degree k i = 4. The periodic boundary conditions are assumed as well. For each node i the links to sites i + 1 and i + 2 are rewired to two randomly selected nodes so far not-connected to node i. An increase of the rewiring probability q influences the nodes degree distribution and the network clusterization coefficient 𝓒. For given values of rewiring probability q the set 𝓝(q)={𝓝1,𝓝2,...,𝓝 M } of M networks is generated. The network's nodes are decorated with spin-like variables s i ∈ { S,D }. During simulation each S node having a D-site in its neighbourhood converts this neighbour from D to S state. Conversely, a node in D state having at least one neighbour also in state D-state converts all nearest-neighbours of this pair into D-state. The latter is realized with probability p. We plot the dependence of the nodes S final density n S T on initial nodes S fraction n S 0. Then, we construct the surface of the unstable fixed points in (𝓒, p, n S 0) space. The system evolves more often toward n S T for (𝓒, p, n S 0) points situated above this surface while starting simulation with (𝓒, p, n S 0) parameters situated below this surface leads system to n S T =0. The points on this surface correspond to such value of initial fraction n S * of S nodes (for fixed values 𝓒 and p) for which their final density is n S T=1/2.

Kinetic Monte Carlo Simulations of Oxygen Diffusion in Environmental Barrier Coating Materials

NASA Technical Reports Server (NTRS)

Good, Brian S.

2017-01-01

Ceramic Matrix Composite (CMC) materials are of interest for use in next-generation turbine engine components, offering a number of significant advantages, including reduced weight and high operating temperatures. However, in the hot environment in which such components operate, the presence of water vapor can lead to corrosion and recession, limiting the useful life of the components. Such degradation can be reduced through the use of Environmental Barrier Coatings (EBCs) that limit the amount of oxygen and water vapor reaching the component. Candidate EBC materials include Yttrium and Ytterbium silicates. In this work we present results of kinetic Monte Carlo (kMC) simulations of oxygen diffusion, via the vacancy mechanism, in Yttrium and Ytterbium disilicates, along with a brief discussion of interstitial diffusion.

Monte-Carlo simulation of a stochastic differential equation

NASA Astrophysics Data System (ADS)

Arif, ULLAH; Majid, KHAN; M, KAMRAN; R, KHAN; Zhengmao, SHENG

2017-12-01

For solving higher dimensional diffusion equations with an inhomogeneous diffusion coefficient, Monte Carlo (MC) techniques are considered to be more effective than other algorithms, such as finite element method or finite difference method. The inhomogeneity of diffusion coefficient strongly limits the use of different numerical techniques. For better convergence, methods with higher orders have been kept forward to allow MC codes with large step size. The main focus of this work is to look for operators that can produce converging results for large step sizes. As a first step, our comparative analysis has been applied to a general stochastic problem. Subsequently, our formulization is applied to the problem of pitch angle scattering resulting from Coulomb collisions of charge particles in the toroidal devices.

Tune the topology to create or destroy patterns

NASA Astrophysics Data System (ADS)

Asllani, Malbor; Carletti, Timoteo; Fanelli, Duccio

2016-12-01

We consider the dynamics of a reaction-diffusion system on a multigraph. The species share the same set of nodes but can access different links to explore the embedding spatial support. By acting on the topology of the networks we can control the ability of the system to self-organise in macroscopic patterns, emerging as a symmetry breaking instability of an homogeneous fixed point. Two different cases study are considered: on the one side, we produce a global modification of the networks, starting from the limiting setting where species are hosted on the same graph. On the other, we consider the effect of inserting just one additional single link to differentiate the two graphs. In both cases, patterns can be generated or destroyed, as follows the imposed, small, topological perturbation. Approximate analytical formulae allow to grasp the essence of the phenomenon and can potentially inspire innovative control strategies to shape the macroscopic dynamics on multigraph networks.

Giant Steps in Cefalù

NASA Astrophysics Data System (ADS)

Jeffery, David J.; Mazzali, Paolo A.

2007-08-01

Giant steps is a technique to accelerate Monte Carlo radiative transfer in optically-thick cells (which are isotropic and homogeneous in matter properties and into which astrophysical atmospheres are divided) by greatly reducing the number of Monte Carlo steps needed to propagate photon packets through such cells. In an optically-thick cell, packets starting from any point (which can be regarded a point source) well away from the cell wall act essentially as packets diffusing from the point source in an infinite, isotropic, homogeneous atmosphere. One can replace many ordinary Monte Carlo steps that a packet diffusing from the point source takes by a randomly directed giant step whose length is slightly less than the distance to the nearest cell wall point from the point source. The giant step is assigned a time duration equal to the time for the RMS radius for a burst of packets diffusing from the point source to have reached the giant step length. We call assigning giant-step time durations this way RMS-radius (RMSR) synchronization. Propagating packets by series of giant steps in giant-steps random walks in the interiors of optically-thick cells constitutes the technique of giant steps. Giant steps effectively replaces the exact diffusion treatment of ordinary Monte Carlo radiative transfer in optically-thick cells by an approximate diffusion treatment. In this paper, we describe the basic idea of giant steps and report demonstration giant-steps flux calculations for the grey atmosphere. Speed-up factors of order 100 are obtained relative to ordinary Monte Carlo radiative transfer. In practical applications, speed-up factors of order ten and perhaps more are possible. The speed-up factor is likely to be significantly application-dependent and there is a trade-off between speed-up and accuracy. This paper and past work suggest that giant-steps error can probably be kept to a few percent by using sufficiently large boundary-layer optical depths while still maintaining large speed-up factors. Thus, giant steps can be characterized as a moderate accuracy radiative transfer technique. For many applications, the loss of some accuracy may be a tolerable price to pay for the speed-ups gained by using giant steps.

Use of Monte Carlo simulation for the interpretation and analysis of diffuse scattering

NASA Astrophysics Data System (ADS)

Welberry, T. R.; Chan, E. J.; Goossens, D. J.; Heerdegen, A. P.

2010-02-01

With the development of computer simulation methods there is, for the first time, the possibility of having a single general method that can be used for any diffuse scattering problem in any type of system. As computers get ever faster it is expected that current methods will become increasingly powerful and applicable to a wider and wider range of problems and materials and provide results in increasingly fine detail. In this article we discuss two contrasting recent examples. The first is concerned with the two polymorphic forms of the pharmaceutical compound benzocaine. The strong and highly structured diffuse scattering in these is shown to be symptomatic of the presence of highly correlated molecular motions. The second concerns Ag+ fast ion conduction in the pearceite/polybasite family of mineral solid electrolytes. Here Monte-Carlo simulation is used to model the diffuse scattering and gain insight into how the ionic conduction arises.

The effect of catastrophic collisional fragmentation and diffuse medium accretion on a computational interstellar dust system

NASA Technical Reports Server (NTRS)

Liffman, Kurt

1990-01-01

The effects of catastrophic collisional fragmentation and diffuse medium accretion on a the interstellar dust system are computed using a Monte Carlo computer model. The Monte Carlo code has as its basis an analytic solution of the bulk chemical evolution of a two-phase interstellar medium, described by Liffman and Clayton (1989). The model is subjected to numerous different interstellar processes as it transfers from one interstellar phase to another. Collisional fragmentation was found to be the dominant physical process that shapes the size spectrum of interstellar dust. It was found that, in the diffuse cloud phase, 90 percent of the refractory material is locked up in the dust grains, primarily due to accretion in the molecular medium. This result is consistent with the observed depletions of silicon. Depletions were found to be affected only slightly by diffuse cloud accretion.

Monte Carlo simulations of particle acceleration at oblique shocks: Including cross-field diffusion

NASA Technical Reports Server (NTRS)

Baring, M. G.; Ellison, D. C.; Jones, F. C.

1995-01-01

The Monte Carlo technique of simulating diffusive particle acceleration at shocks has made spectral predictions that compare extremely well with particle distributions observed at the quasi-parallel region of the earth's bow shock. The current extension of this work to compare simulation predictions with particle spectra at oblique interplanetary shocks has required the inclusion of significant cross-field diffusion (strong scattering) in the simulation technique, since oblique shocks are intrinsically inefficient in the limit of weak scattering. In this paper, we present results from the method we have developed for the inclusion of cross-field diffusion in our simulations, namely model predictions of particle spectra downstream of oblique subluminal shocks. While the high-energy spectral index is independent of the shock obliquity and the strength of the scattering, the latter is observed to profoundly influence the efficiency of injection of cosmic rays into the acceleration process.

Kinetic Monte Carlo Simulation of Oxygen Diffusion in Ytterbium Disilicate

NASA Technical Reports Server (NTRS)

Good, Brian S.

2015-01-01

Ytterbium disilicate is of interest as a potential environmental barrier coating for aerospace applications, notably for use in next generation jet turbine engines. In such applications, the transport of oxygen and water vapor through these coatings to the ceramic substrate is undesirable if high temperature oxidation is to be avoided. In an effort to understand the diffusion process in these materials, we have performed kinetic Monte Carlo simulations of vacancy-mediated and interstitial oxygen diffusion in Ytterbium disilicate. Oxygen vacancy and interstitial site energies, vacancy and interstitial formation energies, and migration barrier energies were computed using Density Functional Theory. We have found that, in the case of vacancy-mediated diffusion, many potential diffusion paths involve large barrier energies, but some paths have barrier energies smaller than one electron volt. However, computed vacancy formation energies suggest that the intrinsic vacancy concentration is small. In the case of interstitial diffusion, migration barrier energies are typically around one electron volt, but the interstitial defect formation energies are positive, with the result that the disilicate is unlikely to exhibit experience significant oxygen permeability except at very high temperature.

Ultrasound-guided photoacoustic imaging of lymph nodes with biocompatible gold nanoparticles as a novel contrast agent (Conference Presentation)

NASA Astrophysics Data System (ADS)

Sun, In-Cheol; Dumani, Diego; Emelianov, Stanislav Y.

2017-02-01

A key step in staging cancer is the diagnosis of metastasis that spreads through lymphatic system. For this reason, researchers develop various methods of sentinel lymph node mapping that often use a radioactive tracer. This study introduces a safe, cost-effective, high-resolution, high-sensitivity, and real-time method of visualizing the sentinel lymph node: ultrasound-guided photoacoustic (US/PA) imaging augmented by a contrast agent. In this work, we use clearable gold nanoparticles covered by a biocompatible polymer (glycol chitosan) to enhance cellular uptake by macrophages abundant in lymph nodes. We incubate macrophages with glycol-chitosan-coated gold nanoparticles (0.05 mg Au/ml), and then fix them with paraformaldehyde solution for an analysis of in vitro dark-field microscopy and cell phantom. The analysis shows enhanced cellular uptake of nanoparticles by macrophages and strong photoacoustic signal from labeled cells in tissue-mimicking cell phantoms consisting gelatin solution (6 %) with silica gel (25 μm, 0.3%) and fixed macrophages (13 X 105 cells). The in-vivo US/PA imaging of cervical lymph nodes in healthy mice (nu/nu, female, 5 weeks) indicates a strong photoacoustic signal from a lymph node 10 minutes post-injection (2.5 mg Au/ml, 80 μl). The signal intensity and the nanoparticle-labeled volume of tissue within the lymph node continues to increase until 4 h post-injection. Histological analysis further confirms the accumulation of gold nanoparticles within the lymph nodes. This work suggests the feasibility of molecular/cellular US/PA imaging with biocompatible gold nanoparticles as a photoacoustic contrast agent in the diagnosis of lymph-node-related diseases.

An Ab Initio and Kinetic Monte Carlo Simulation Study of Lithium Ion Diffusion on Graphene

PubMed Central

Zhong, Kehua; Yang, Yanmin; Xu, Guigui; Zhang, Jian-Min; Huang, Zhigao

2017-01-01

The Li+ diffusion coefficients in Li+-adsorbed graphene systems were determined by combining first-principle calculations based on density functional theory with Kinetic Monte Carlo simulations. The calculated results indicate that the interactions between Li ions have a very important influence on lithium diffusion. Based on energy barriers directly obtained from first-principle calculations for single-Li+ and two-Li+ adsorbed systems, a new equation predicting energy barriers with more than two Li ions was deduced. Furthermore, it is found that the temperature dependence of Li+ diffusion coefficients fits well to the Arrhenius equation, rather than meeting the equation from electrochemical impedance spectroscopy applied to estimate experimental diffusion coefficients. Moreover, the calculated results also reveal that Li+ concentration dependence of diffusion coefficients roughly fits to the equation from electrochemical impedance spectroscopy in a low concentration region; however, it seriously deviates from the equation in a high concentration region. So, the equation from electrochemical impedance spectroscopy technique could not be simply used to estimate the Li+ diffusion coefficient for all Li+-adsorbed graphene systems with various Li+ concentrations. Our work suggests that interactions between Li ions, and among Li ion and host atoms will influence the Li+ diffusion, which determines that the Li+ intercalation dependence of Li+ diffusion coefficient should be changed and complex. PMID:28773122

How the contagion at links influences epidemic spreading

NASA Astrophysics Data System (ADS)

Ruan, Zhongyuan; Tang, Ming; Liu, Zonghua

2013-04-01

The reaction-diffusion (RD) model of epidemic spreading generally assume that contagion occurs only at the nodes of network, i.e., the links are used only for migration/diffusion of agents. However, in reality, we observe that contagion occurs also among the travelers staying in the same car, train or plane etc., which consist of the links of network. To reflect the contagious effect of links, we here present a traveling-contagion model where contagion occurs not only at nodes but also at links. Considering that the population density in transportation is generally much larger than that in districts, we introduce different infection rates for the nodes and links, respectively, whose two extreme cases correspond to the type-I and type-II reactions in the RD model [V. Colizza, R. Pastor-Satorras, A. Vespignani, Nat. Phys. 3, 276 (2007)]. Through studying three typical diffusion processes, we reveal both numerically and theoretically that the contagion at links can accelerate significantly the epidemic spreading. This finding is helpful in designing the controlling strategies of epidemic spreading.

Very Efficient High-order Hyperbolic Schemes for Time-dependent Advection Diffusion Problems: Third-, Fourth-, and Sixth-order

DTIC Science & Technology

2014-07-07

boundary condition (x ¼ 7p =2; j ¼ 2p; U ¼ 1; m ¼ 1) on N ¼ 10 uniform nodes (Dt ¼ 0:01.) Table 10 Unsteady linear advection–diffusion problem with periodic...500 3rd 55 2 4th 55 2 6th 55 2 1000 3rd 116 2 4th 116 2 6th 116 2 Table 11 Unsteady linear advection–diffusion problem with oscillatory BC (x ¼ 7p =2; a...dependent problem with oscillatory BC (x ¼ 7p =2; a ¼ 1.) using the third-order RD-GT scheme with the BDF3 time discretization. Number of nodes Dt (BDF3

Timescales of magmatic processes prior to the ˜4.7 ka Agnano-Monte Spina eruption (Campi Flegrei caldera, Southern Italy) based on diffusion chronometry from sanidine phenocrysts

NASA Astrophysics Data System (ADS)

Iovine, Raffaella Silvia; Fedele, Lorenzo; Mazzeo, Fabio Carmine; Arienzo, Ilenia; Cavallo, Andrea; Wörner, Gerhard; Orsi, Giovanni; Civetta, Lucia; D'Antonio, Massimo

2017-02-01

Barium diffusion chronometry applied to sanidine phenocrysts from the trachytic Agnano-Monte Spina eruption (˜4.7 ka) constrains the time between reactivation and eruption of magma batches in the Campi Flegrei caldera. Backscattered electron imaging and quantitative electron microprobe measurements on 50 sanidine phenocrysts from representative pumice samples document core-to-rim compositional zoning. We focus on compositional breaks near the crystal rims that record magma mixing processes just prior to eruption. Diffusion times were modeled at a magmatic temperature of 930 °C using profiles based on quantitative BaO point analyses, X-ray scans, and grayscale swath profiles, yielding times ≤60 years between mixing and eruption. Such short timescales are consistent with volcanological and geochronological data that indicate that at least six eruptions occurred in the Agnano-San Vito area during few centuries before the Agnano-Monte Spina eruption. Thus, the short diffusion timescales are similar to time intervals between eruptions. Therefore, the rejuvenation time of magma residing in a shallow reservoir after influx of a new magma batch that triggered the eruption, and thus pre-eruption warning times, may be as short as years to a few decades at Campi Flegrei caldera.

Smart darting diffusion Monte Carlo: Applications to lithium ion-Stockmayer clusters

NASA Astrophysics Data System (ADS)

Christensen, H. M.; Jake, L. C.; Curotto, E.

2016-05-01

In a recent investigation [K. Roberts et al., J. Chem. Phys. 136, 074104 (2012)], we have shown that, for a sufficiently complex potential, the Diffusion Monte Carlo (DMC) random walk can become quasiergodic, and we have introduced smart darting-like moves to improve the sampling. In this article, we systematically characterize the bias that smart darting moves introduce in the estimate of the ground state energy of a bosonic system. We then test a simple approach to eliminate completely such bias from the results. The approach is applied for the determination of the ground state of lithium ion-n-dipoles clusters in the n = 8-20 range. For these, the smart darting diffusion Monte Carlo simulations find the same ground state energy and mixed-distribution as the traditional approach for n < 14. In larger systems we find that while the ground state energies agree quantitatively with or without smart darting moves, the mixed-distributions can be significantly different. Some evidence is offered to conclude that introducing smart darting-like moves in traditional DMC simulations may produce a more reliable ground state mixed-distribution.

A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies

DOE PAGES

Hoffmann, Max J.; Bligaard, Thomas

2018-01-22

Here, mean-field microkinetic models in combination with Brønsted–Evans–Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the “fruit fly” example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants.more » As a result, we show that for the case of infinitely fast diffusion and absence of adsorbate-adsorbate interaction it is, in fact, possible to match the prediction of the mean-field-theory method and the lattice kinetic Monte Carlo method. As a corollary, we conclude that lattice kinetic Monte Carlo simulations of surface chemical reactions are most likely to provide additional insight over mean-field simulations if diffusion limitations or adsorbate–adsorbate interactions have a significant influence on the mixing of the adsorbates.« less

A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoffmann, Max J.; Bligaard, Thomas

Here, mean-field microkinetic models in combination with Brønsted–Evans–Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the “fruit fly” example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants.more » As a result, we show that for the case of infinitely fast diffusion and absence of adsorbate-adsorbate interaction it is, in fact, possible to match the prediction of the mean-field-theory method and the lattice kinetic Monte Carlo method. As a corollary, we conclude that lattice kinetic Monte Carlo simulations of surface chemical reactions are most likely to provide additional insight over mean-field simulations if diffusion limitations or adsorbate–adsorbate interactions have a significant influence on the mixing of the adsorbates.« less

Criticality Calculations with MCNP6 - Practical Lectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Forrest B.; Rising, Michael Evan; Alwin, Jennifer Louise

2016-11-29

These slides are used to teach MCNP (Monte Carlo N-Particle) usage to nuclear criticality safety analysts. The following are the lecture topics: course information, introduction, MCNP basics, criticality calculations, advanced geometry, tallies, adjoint-weighted tallies and sensitivities, physics and nuclear data, parameter studies, NCS validation I, NCS validation II, NCS validation III, case study 1 - solution tanks, case study 2 - fuel vault, case study 3 - B&W core, case study 4 - simple TRIGA, case study 5 - fissile mat. vault, criticality accident alarm systems. After completion of this course, you should be able to: Develop an input modelmore » for MCNP; Describe how cross section data impact Monte Carlo and deterministic codes; Describe the importance of validation of computer codes and how it is accomplished; Describe the methodology supporting Monte Carlo codes and deterministic codes; Describe pitfalls of Monte Carlo calculations; Discuss the strengths and weaknesses of Monte Carlo and Discrete Ordinants codes; The diffusion theory model is not strictly valid for treating fissile systems in which neutron absorption, voids, and/or material boundaries are present. In the context of these limitations, identify a fissile system for which a diffusion theory solution would be adequate.« less

Linear Transceiver Design for Interference Alignment: Complexity and Computation

DTIC Science & Technology

2010-07-01

restriction on the choice of beamforming vector of node b. Thus, for any fixed transmit node b in H , there are multiple restriction sets, each...signal space can be chosen. The receive nodes in H can achieve interference alignment if and only if these restricted sets of one-dimensional signal...total number of restriction sets is at most linear in the number of edges in H and each restriction set contains at most two one-dimensional

Simple Random Sampling-Based Probe Station Selection for Fault Detection in Wireless Sensor Networks

PubMed Central

Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

2011-01-01

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate. PMID:22163789

Simple random sampling-based probe station selection for fault detection in wireless sensor networks.

PubMed

Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

2011-01-01

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate.

Decentralised fixed modes of networked MIMO systems

NASA Astrophysics Data System (ADS)

Hao, Yuqing; Duan, Zhisheng; Chen, Guanrong

2018-04-01

In this paper, decentralised fixed modes (DFMs) of a networked system are studied. The network topology is directed and weighted and the nodes are higher-dimensional linear time-invariant (LTI) dynamical systems. The effects of the network topology, the node-system dynamics, the external control inputs, and the inner interactions on the existence of DFMs for the whole networked system are investigated. A necessary and sufficient condition for networked multi-input/multi-output (MIMO) systems in a general topology to possess no DFMs is derived. For networked single-input/single-output (SISO) LTI systems in general as well as some typical topologies, some specific conditions for having no DFMs are established. It is shown that the existence of DFMs is an integrated result of the aforementioned relevant factors which cannot be decoupled into individual DFMs of the node-systems and the properties solely determined by the network topology.

Anomaly Detection Techniques for Ad Hoc Networks

ERIC Educational Resources Information Center

Cai, Chaoli

2009-01-01

Anomaly detection is an important and indispensable aspect of any computer security mechanism. Ad hoc and mobile networks consist of a number of peer mobile nodes that are capable of communicating with each other absent a fixed infrastructure. Arbitrary node movements and lack of centralized control make them vulnerable to a wide variety of…

A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging.

PubMed

Nair, Shalini Rajandran; Tan, Li Kuo; Mohd Ramli, Norlisah; Lim, Shen Yang; Rahmat, Kartini; Mohd Nor, Hazman

2013-06-01

To develop a decision tree based on standard magnetic resonance imaging (MRI) and diffusion tensor imaging to differentiate multiple system atrophy (MSA) from Parkinson's disease (PD). 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3. Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta-rostral) showed statistically significant (P < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 % sensitivity, 96 % specificity, 92 % PPV and 96 % NPV. Twelve out of 13 MSA patients were accurately classified. Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD. • Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. • Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. • A decision tree is descriptive and predictive in differentiating between clinical entities. • A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.

Structure-correlated diffusion anisotropy in nanoporous channel networks by Monte Carlo simulations and percolation theory

NASA Astrophysics Data System (ADS)

Kondrashova, Daria; Valiullin, Rustem; Kärger, Jörg; Bunde, Armin

2017-07-01

Nanoporous silicon consisting of tubular pores imbedded in a silicon matrix has found many technological applications and provides a useful model system for studying phase transitions under confinement. Recently, a model for mass transfer in these materials has been elaborated [Kondrashova et al., Sci. Rep. 7, 40207 (2017)], which assumes that adjacent channels can be connected by "bridges" (with probability pbridge) which allows diffusion perpendicular to the channels. Along the channels, diffusion can be slowed down by "necks" which occur with probability pneck. In this paper we use Monte-Carlo simulations to study diffusion along the channels and perpendicular to them, as a function of pbridge and pneck, and find remarkable correlations between the diffusivities in longitudinal and radial directions. For clarifying the diffusivity in radial direction, which is governed by the concentration of bridges, we applied percolation theory. We determine analytically how the critical concentration of bridges depends on the size of the system and show that it approaches zero in the thermodynamic limit. Our analysis suggests that the critical properties of the model, including the diffusivity in radial direction, are in the universality class of two-dimensional lattice percolation, which is confirmed by our numerical study.

A transformed path integral approach for solution of the Fokker-Planck equation

NASA Astrophysics Data System (ADS)

Subramaniam, Gnana M.; Vedula, Prakash

2017-10-01

A novel path integral (PI) based method for solution of the Fokker-Planck equation is presented. The proposed method, termed the transformed path integral (TPI) method, utilizes a new formulation for the underlying short-time propagator to perform the evolution of the probability density function (PDF) in a transformed computational domain where a more accurate representation of the PDF can be ensured. The new formulation, based on a dynamic transformation of the original state space with the statistics of the PDF as parameters, preserves the non-negativity of the PDF and incorporates short-time properties of the underlying stochastic process. New update equations for the state PDF in a transformed space and the parameters of the transformation (including mean and covariance) that better accommodate nonlinearities in drift and non-Gaussian behavior in distributions are proposed (based on properties of the SDE). Owing to the choice of transformation considered, the proposed method maps a fixed grid in transformed space to a dynamically adaptive grid in the original state space. The TPI method, in contrast to conventional methods such as Monte Carlo simulations and fixed grid approaches, is able to better represent the distributions (especially the tail information) and better address challenges in processes with large diffusion, large drift and large concentration of PDF. Additionally, in the proposed TPI method, error bounds on the probability in the computational domain can be obtained using the Chebyshev's inequality. The benefits of the TPI method over conventional methods are illustrated through simulations of linear and nonlinear drift processes in one-dimensional and multidimensional state spaces. The effects of spatial and temporal grid resolutions as well as that of the diffusion coefficient on the error in the PDF are also characterized.

Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure.

PubMed

Wang, Henry; Ma, Yunzhi; Pratx, Guillem; Xing, Lei

2011-09-07

Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

Epidemic spreading in metapopulation networks with heterogeneous infection rates

NASA Astrophysics Data System (ADS)

Gong, Yong-Wang; Song, Yu-Rong; Jiang, Guo-Ping

2014-12-01

In this paper, we study epidemic spreading in metapopulation networks wherein each node represents a subpopulation symbolizing a city or an urban area and links connecting nodes correspond to the human traveling routes among cities. Differently from previous studies, we introduce a heterogeneous infection rate to characterize the effect of nodes' local properties, such as population density, individual health habits, and social conditions, on epidemic infectivity. By means of a mean-field approach and Monte Carlo simulations, we explore how the heterogeneity of the infection rate affects the epidemic dynamics, and find that large fluctuations of the infection rate have a profound impact on the epidemic threshold as well as the temporal behavior of the prevalence above the epidemic threshold. This work can refine our understanding of epidemic spreading in metapopulation networks with the effect of nodes' local properties.

Boundary-induced pattern formation from uniform temporal oscillation

NASA Astrophysics Data System (ADS)

Kohsokabe, Takahiro; Kaneko, Kunihiko

2018-04-01

Pattern dynamics triggered by fixing a boundary is investigated. By considering a reaction-diffusion equation that has a unique spatially uniform and limit cycle attractor under a periodic or Neumann boundary condition, and then by choosing a fixed boundary condition, we found three novel phases depending on the ratio of diffusion constants of activator to inhibitor: transformation of temporally periodic oscillation into a spatially periodic fixed pattern, travelling wave emitted from the boundary, and aperiodic spatiotemporal dynamics. The transformation into a fixed, periodic pattern is analyzed by crossing of local nullclines at each spatial point, shifted by diffusion terms, as is analyzed by using recursive equations, to obtain the spatial pattern as an attractor. The generality of the boundary-induced pattern formation as well as its relevance to biological morphogenesis is discussed.

Minimum spanning tree analysis of the human connectome.

PubMed

van Dellen, Edwin; Sommer, Iris E; Bohlken, Marc M; Tewarie, Prejaas; Draaisma, Laurijn; Zalesky, Andrew; Di Biase, Maria; Brown, Jesse A; Douw, Linda; Otte, Willem M; Mandl, René C W; Stam, Cornelis J

2018-06-01

One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion-weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null-model. The MST of individual subjects matched this reference MST for a mean 58%-88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so-called rich club nodes (a subset of high-degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical-subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Surface entropy of liquids via a direct Monte Carlo approach - Application to liquid Si

NASA Technical Reports Server (NTRS)

Wang, Z. Q.; Stroud, D.

1990-01-01

Two methods are presented for a direct Monte Carlo evaluation of the surface entropy S(s) of a liquid interacting by specified, volume-independent potentials. The first method is based on an application of the approach of Ferrenberg and Swendsen (1988, 1989) to Monte Carlo simulations at two different temperatures; it gives much more reliable results for S(s) in liquid Si than previous calculations based on numerical differentiation. The second method expresses the surface entropy directly as a canonical average at fixed temperature.

Monte Carlo sampling in diffusive dynamical systems

NASA Astrophysics Data System (ADS)

Tapias, Diego; Sanders, David P.; Altmann, Eduardo G.

2018-05-01

We introduce a Monte Carlo algorithm to efficiently compute transport properties of chaotic dynamical systems. Our method exploits the importance sampling technique that favors trajectories in the tail of the distribution of displacements, where deviations from a diffusive process are most prominent. We search for initial conditions using a proposal that correlates states in the Markov chain constructed via a Metropolis-Hastings algorithm. We show that our method outperforms the direct sampling method and also Metropolis-Hastings methods with alternative proposals. We test our general method through numerical simulations in 1D (box-map) and 2D (Lorentz gas) systems.

LMC: Logarithmantic Monte Carlo

NASA Astrophysics Data System (ADS)

Mantz, Adam B.

2017-06-01

LMC is a Markov Chain Monte Carlo engine in Python that implements adaptive Metropolis-Hastings and slice sampling, as well as the affine-invariant method of Goodman & Weare, in a flexible framework. It can be used for simple problems, but the main use case is problems where expensive likelihood evaluations are provided by less flexible third-party software, which benefit from parallelization across many nodes at the sampling level. The parallel/adaptive methods use communication through MPI, or alternatively by writing/reading files, and mostly follow the approaches pioneered by CosmoMC (ascl:1106.025).

Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution.

PubMed

Mukhopadhyay, Nitai D; Sampson, Andrew J; Deniz, Daniel; Alm Carlsson, Gudrun; Williamson, Jeffrey; Malusek, Alexandr

2012-01-01

Correlated sampling Monte Carlo methods can shorten computing times in brachytherapy treatment planning. Monte Carlo efficiency is typically estimated via efficiency gain, defined as the reduction in computing time by correlated sampling relative to conventional Monte Carlo methods when equal statistical uncertainties have been achieved. The determination of the efficiency gain uncertainty arising from random effects, however, is not a straightforward task specially when the error distribution is non-normal. The purpose of this study is to evaluate the applicability of the F distribution and standardized uncertainty propagation methods (widely used in metrology to estimate uncertainty of physical measurements) for predicting confidence intervals about efficiency gain estimates derived from single Monte Carlo runs using fixed-collision correlated sampling in a simplified brachytherapy geometry. A bootstrap based algorithm was used to simulate the probability distribution of the efficiency gain estimates and the shortest 95% confidence interval was estimated from this distribution. It was found that the corresponding relative uncertainty was as large as 37% for this particular problem. The uncertainty propagation framework predicted confidence intervals reasonably well; however its main disadvantage was that uncertainties of input quantities had to be calculated in a separate run via a Monte Carlo method. The F distribution noticeably underestimated the confidence interval. These discrepancies were influenced by several photons with large statistical weights which made extremely large contributions to the scored absorbed dose difference. The mechanism of acquiring high statistical weights in the fixed-collision correlated sampling method was explained and a mitigation strategy was proposed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Method for designing gas tag compositions

DOEpatents

Gross, Kenny C.

1995-01-01

For use in the manufacture of gas tags such as employed in a nuclear reactor gas tagging failure detection system, a method for designing gas tagging compositions utilizes an analytical approach wherein the final composition of a first canister of tag gas as measured by a mass spectrometer is designated as node #1. Lattice locations of tag nodes in multi-dimensional space are then used in calculating the compositions of a node #2 and each subsequent node so as to maximize the distance of each node from any combination of tag components which might be indistinguishable from another tag composition in a reactor fuel assembly. Alternatively, the measured compositions of tag gas numbers 1 and 2 may be used to fix the locations of nodes 1 and 2, with the locations of nodes 3-N then calculated for optimum tag gas composition. A single sphere defining the lattice locations of the tag nodes may be used to define approximately 20 tag nodes, while concentric spheres can extend the number of tag nodes to several hundred.

Direct Simulation of Extinction in a Slab of Spherical Particles

NASA Technical Reports Server (NTRS)

Mackowski, D.W.; Mishchenko, Michael I.

2013-01-01

The exact multiple sphere superposition method is used to calculate the coherent and incoherent contributions to the ensemble-averaged electric field amplitude and Poynting vector in systems of randomly positioned nonabsorbing spherical particles. The target systems consist of cylindrical volumes, with radius several times larger than length, containing spheres with positional configurations generated by a Monte Carlo sampling method. Spatially dependent values for coherent electric field amplitude, coherent energy flux, and diffuse energy flux, are calculated by averaging of exact local field and flux values over multiple configurations and over spatially independent directions for fixed target geometry, sphere properties, and sphere volume fraction. Our results reveal exponential attenuation of the coherent field and the coherent energy flux inside the particulate layer and thereby further corroborate the general methodology of the microphysical radiative transfer theory. An effective medium model based on plane wave transmission and reflection by a plane layer is used to model the dependence of the coherent electric field on particle packing density. The effective attenuation coefficient of the random medium, computed from the direct simulations, is found to agree closely with effective medium theories and with measurements. In addition, the simulation results reveal the presence of a counter-propagating component to the coherent field, which arises due to the internal reflection of the main coherent field component by the target boundary. The characteristics of the diffuse flux are compared to, and found to be consistent with, a model based on the diffusion approximation of the radiative transfer theory.

A Smart Collaborative Routing Protocol for Reliable Data Diffusion in IoT Scenarios.

PubMed

Ai, Zheng-Yang; Zhou, Yu-Tong; Song, Fei

2018-06-13

It is knotty for current routing protocols to meet the needs of reliable data diffusion during the Internet of Things (IoT) deployments. Due to the random placement, limited resources and unattended features of existing sensor nodes, the wireless transmissions are easily exposed to unauthorized users, which becomes a vulnerable area for various malicious attacks, such as wormhole and Sybil attacks. However, the scheme based on geographic location is a suitable candidate to defend against them. This paper is inspired to propose a smart collaborative routing protocol, Geographic energy aware routing and Inspecting Node (GIN), for guaranteeing the reliability of data exchanging. The proposed protocol integrates the directed diffusion routing, Greedy Perimeter Stateless Routing (GPSR), and the inspecting node mechanism. We first discuss current wireless routing protocols from three diverse perspectives (improving transmission rate, shortening transmission range and reducing transmission consumption). Then, the details of GIN, including the model establishment and implementation processes, are presented by means of the theoretical analysis. Through leveraging the game theory, the inspecting node is elected to monitor the network behaviors. Thirdly, we evaluate the network performances, in terms of transmission delay, packet loss ratio, and throughput, between GIN and three traditional schemes (i.e., Flooding, GPSR, and GEAR). The simulation results illustrate that the proposed protocol is able to outperform the others.

An accurate, compact and computationally efficient representation of orbitals for quantum Monte Carlo calculations

NASA Astrophysics Data System (ADS)

Luo, Ye; Esler, Kenneth; Kent, Paul; Shulenburger, Luke

Quantum Monte Carlo (QMC) calculations of giant molecules, surface and defect properties of solids have been feasible recently due to drastically expanding computational resources. However, with the most computationally efficient basis set, B-splines, these calculations are severely restricted by the memory capacity of compute nodes. The B-spline coefficients are shared on a node but not distributed among nodes, to ensure fast evaluation. A hybrid representation which incorporates atomic orbitals near the ions and B-spline ones in the interstitial regions offers a more accurate and less memory demanding description of the orbitals because they are naturally more atomic like near ions and much smoother in between, thus allowing coarser B-spline grids. We will demonstrate the advantage of hybrid representation over pure B-spline and Gaussian basis sets and also show significant speed-up like computing the non-local pseudopotentials with our new scheme. Moreover, we discuss a new algorithm for atomic orbital initialization which used to require an extra workflow step taking a few days. With this work, the highly efficient hybrid representation paves the way to simulate large size even in-homogeneous systems using QMC. This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Computational Materials Sciences Program.

[Therapeutic outcomes in patients with cervical cancer FIGO stage IB1].

PubMed

Kornovski, Y; Ismail, E; Kaneva, M

2012-01-01

To establish overall and disease-free survival (OS and DFS) for patients with FIGO IB1 stage cervical cancer for median period of follow-up of 41 months. Between 11.2002-11.2011 110 women with histologically confirmed cervical cancer IB1 stage were operated on by the author. Surgery was radical hysterectomy class III (Piver) and pelvic lymphonodulectomy (ovariectomy was optionally). 76 patients were submitted to adjuvant RT (TGT- 52 - 54 Gy). The period of follow-up ranges from 2 to 104 monts, median 41 monts. The acturial OS and DFS in patients with cervical cancer IB1 stage were estimated as 90% and 90.9%, respectively. Eleven patients had died for the period of follow-up and in 10 occurred local or distant recurrences. The time to develop recurrences was estimated as 16.81 months. Four patients developed local recurrences and six--distant metastases. Surgical and combined therapy of cervical cancer patients IB1 stage leads to high rate OS and DFS--90% and 90.9%, respectively. The incidence rate of distant metastases (5.5%)--in six patients in this stage makes pelvic lymph node dissection crucial and the presence of LM in gluteal and presacral lymph nodes requires paraaortic lymph node dissection.

Analytic continuation of quantum Monte Carlo data by stochastic analytical inference.

PubMed

Fuchs, Sebastian; Pruschke, Thomas; Jarrell, Mark

2010-05-01

We present an algorithm for the analytic continuation of imaginary-time quantum Monte Carlo data which is strictly based on principles of Bayesian statistical inference. Within this framework we are able to obtain an explicit expression for the calculation of a weighted average over possible energy spectra, which can be evaluated by standard Monte Carlo simulations, yielding as by-product also the distribution function as function of the regularization parameter. Our algorithm thus avoids the usual ad hoc assumptions introduced in similar algorithms to fix the regularization parameter. We apply the algorithm to imaginary-time quantum Monte Carlo data and compare the resulting energy spectra with those from a standard maximum-entropy calculation.

Probabilistic generation of random networks taking into account information on motifs occurrence.

PubMed

Bois, Frederic Y; Gayraud, Ghislaine

2015-01-01

Because of the huge number of graphs possible even with a small number of nodes, inference on network structure is known to be a challenging problem. Generating large random directed graphs with prescribed probabilities of occurrences of some meaningful patterns (motifs) is also difficult. We show how to generate such random graphs according to a formal probabilistic representation, using fast Markov chain Monte Carlo methods to sample them. As an illustration, we generate realistic graphs with several hundred nodes mimicking a gene transcription interaction network in Escherichia coli.

Probabilistic Generation of Random Networks Taking into Account Information on Motifs Occurrence

PubMed Central

Bois, Frederic Y.

2015-01-01

Abstract Because of the huge number of graphs possible even with a small number of nodes, inference on network structure is known to be a challenging problem. Generating large random directed graphs with prescribed probabilities of occurrences of some meaningful patterns (motifs) is also difficult. We show how to generate such random graphs according to a formal probabilistic representation, using fast Markov chain Monte Carlo methods to sample them. As an illustration, we generate realistic graphs with several hundred nodes mimicking a gene transcription interaction network in Escherichia coli. PMID:25493547

An Efficient MCMC Algorithm to Sample Binary Matrices with Fixed Marginals

ERIC Educational Resources Information Center

Verhelst, Norman D.

2008-01-01

Uniform sampling of binary matrices with fixed margins is known as a difficult problem. Two classes of algorithms to sample from a distribution not too different from the uniform are studied in the literature: importance sampling and Markov chain Monte Carlo (MCMC). Existing MCMC algorithms converge slowly, require a long burn-in period and yield…

Hybrid-optimization strategy for the communication of large-scale Kinetic Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Wu, Baodong; Li, Shigang; Zhang, Yunquan; Nie, Ningming

2017-02-01

The parallel Kinetic Monte Carlo (KMC) algorithm based on domain decomposition has been widely used in large-scale physical simulations. However, the communication overhead of the parallel KMC algorithm is critical, and severely degrades the overall performance and scalability. In this paper, we present a hybrid optimization strategy to reduce the communication overhead for the parallel KMC simulations. We first propose a communication aggregation algorithm to reduce the total number of messages and eliminate the communication redundancy. Then, we utilize the shared memory to reduce the memory copy overhead of the intra-node communication. Finally, we optimize the communication scheduling using the neighborhood collective operations. We demonstrate the scalability and high performance of our hybrid optimization strategy by both theoretical and experimental analysis. Results show that the optimized KMC algorithm exhibits better performance and scalability than the well-known open-source library-SPPARKS. On 32-node Xeon E5-2680 cluster (total 640 cores), the optimized algorithm reduces the communication time by 24.8% compared with SPPARKS.

A Distributed Data-Gathering Protocol Using AUV in Underwater Sensor Networks

PubMed Central

Khan, Jawaad Ullah; Cho, Ho-Shin

2015-01-01

In this paper, we propose a distributed data-gathering scheme using an autonomous underwater vehicle (AUV) working as a mobile sink to gather data from a randomly distributed underwater sensor network where sensor nodes are clustered around several cluster headers. Unlike conventional data-gathering schemes where the AUV visits either every node or every cluster header, the proposed scheme allows the AUV to visit some selected nodes named path-nodes in a way that reduces the overall transmission power of the sensor nodes. Monte Carlo simulations are performed to investigate the performance of the proposed scheme compared with several preexisting techniques employing the AUV in terms of total amount of energy consumption, standard deviation of each node’s energy consumption, latency to gather data at a sink, and controlling overhead. Simulation results show that the proposed scheme not only reduces the total energy consumption but also distributes the energy consumption more uniformly over the network, thereby increasing the lifetime of the network. PMID:26287189

Effect of rich-club on diffusion in complex networks

NASA Astrophysics Data System (ADS)

Berahmand, Kamal; Samadi, Negin; Sheikholeslami, Seyed Mahmood

2018-05-01

One of the main issues in complex networks is the phenomenon of diffusion in which the goal is to find the nodes with the highest diffusing power. In diffusion, there is always a conflict between accuracy and efficiency time complexity; therefore, most of the recent studies have focused on finding new centralities to solve this problem and have offered new ones, but our approach is different. Using one of the complex networks’ features, namely the “rich-club”, its effect on diffusion in complex networks has been analyzed and it is demonstrated that in datasets which have a high rich-club, it is better to use the degree centrality for finding influential nodes because it has a linear time complexity and uses the local information; however, this rule does not apply to datasets which have a low rich-club. Next, real and artificial datasets with the high rich-club have been used in which degree centrality has been compared to famous centrality using the SIR standard.

On common noise-induced synchronization in complex networks with state-dependent noise diffusion processes

NASA Astrophysics Data System (ADS)

Russo, Giovanni; Shorten, Robert

2018-04-01

This paper is concerned with the study of common noise-induced synchronization phenomena in complex networks of diffusively coupled nonlinear systems. We consider the case where common noise propagation depends on the network state and, as a result, the noise diffusion process at the nodes depends on the state of the network. For such networks, we present an algebraic sufficient condition for the onset of synchronization, which depends on the network topology, the dynamics at the nodes, the coupling strength and the noise diffusion. Our result explicitly shows that certain noise diffusion processes can drive an unsynchronized network towards synchronization. In order to illustrate the effectiveness of our result, we consider two applications: collective decision processes and synchronization of chaotic systems. We explicitly show that, in the former application, a sufficiently large noise can drive a population towards a common decision, while, in the latter, we show how common noise can synchronize a network of Lorentz chaotic systems.

Comparison of flat cleaved and cylindrical diffusing fibers as treatment sources for interstitial photodynamic therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baran, Timothy M., E-mail: timothy.baran@rochester.edu; Foster, Thomas H.

Purpose: For interstitial photodynamic therapy (iPDT) of bulky tumors, careful treatment planning is required in order to ensure that a therapeutic dose is delivered to the tumor, while minimizing damage to surrounding normal tissue. In clinical contexts, iPDT has typically been performed with either flat cleaved or cylindrical diffusing optical fibers as light sources. Here, the authors directly compare these two source geometries in terms of the number of fibers and duration of treatment required to deliver a prescribed light dose to a tumor volume. Methods: Treatment planning software for iPDT was developed based on graphics processing unit enhanced Montemore » Carlo simulations. This software was used to optimize the number of fibers, total energy delivered by each fiber, and the position of individual fibers in order to deliver a target light dose (D{sub 90}) to 90% of the tumor volume. Treatment plans were developed using both flat cleaved and cylindrical diffusing fibers, based on tissue volumes derived from CT data from a head and neck cancer patient. Plans were created for four cases: fixed energy per fiber, fixed number of fibers, and in cases where both or neither of these factors were fixed. Results: When the number of source fibers was fixed at eight, treatment plans based on flat cleaved fibers required each to deliver 7180–8080 J in order to deposit 90 J/cm{sup 2} in 90% of the tumor volume. For diffusers, each fiber was required to deliver 2270–2350 J (333–1178 J/cm) in order to achieve this same result. For the case of fibers delivering a fixed 900 J, 13 diffusers or 19 flat cleaved fibers at a spacing of 1 cm were required to deliver the desired dose. With energy per fiber fixed at 2400 J and the number of fibers fixed at eight, diffuser fibers delivered the desired dose to 93% of the tumor volume, while flat cleaved fibers delivered this dose to 79%. With both energy and number of fibers allowed to vary, six diffusers delivering 3485–3600 J were required, compared to ten flat cleaved fibers delivering 2780–3600 J. Conclusions: For the same number of fibers, cylindrical diffusers allow for a shorter treatment duration compared to flat cleaved fibers. For the same energy delivered per fiber, diffusers allow for the insertion of fewer fibers in order to deliver the same light dose to a target volume.« less

Mobile agent location in distributed environments

NASA Astrophysics Data System (ADS)

Fountoukis, S. G.; Argyropoulos, I. P.

2012-12-01

An agent is a small program acting on behalf of a user or an application which plays the role of a user. Artificial intelligence can be encapsulated in agents so that they can be capable of both behaving autonomously and showing an elementary decision ability regarding movement and some specific actions. Therefore they are often called autonomous mobile agents. In a distributed system, they can move themselves from one processing node to another through the interconnecting network infrastructure. Their purpose is to collect useful information and to carry it back to their user. Also, agents are used to start, monitor and stop processes running on the individual interconnected processing nodes of computer cluster systems. An agent has a unique id to discriminate itself from other agents and a current position. The position can be expressed as the address of the processing node which currently hosts the agent. Very often, it is necessary for a user, a processing node or another agent to know the current position of an agent in a distributed system. Several procedures and algorithms have been proposed for the purpose of position location of mobile agents. The most basic of all employs a fixed computing node, which acts as agent position repository, receiving messages from all the moving agents and keeping records of their current positions. The fixed node, responds to position queries and informs users, other nodes and other agents about the position of an agent. Herein, a model is proposed that considers pairs and triples of agents instead of single ones. A location method, which is investigated in this paper, attempts to exploit this model.

Nuclear reactor transient analysis via a quasi-static kinetics Monte Carlo method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jo, YuGwon; Cho, Bumhee; Cho, Nam Zin, E-mail: nzcho@kaist.ac.kr

2015-12-31

The predictor-corrector quasi-static (PCQS) method is applied to the Monte Carlo (MC) calculation for reactor transient analysis. To solve the transient fixed-source problem of the PCQS method, fission source iteration is used and a linear approximation of fission source distributions during a macro-time step is introduced to provide delayed neutron source. The conventional particle-tracking procedure is modified to solve the transient fixed-source problem via MC calculation. The PCQS method with MC calculation is compared with the direct time-dependent method of characteristics (MOC) on a TWIGL two-group problem for verification of the computer code. Then, the results on a continuous-energy problemmore » are presented.« less

A novel Kinetic Monte Carlo algorithm for Non-Equilibrium Simulations

NASA Astrophysics Data System (ADS)

Jha, Prateek; Kuzovkov, Vladimir; Grzybowski, Bartosz; Olvera de La Cruz, Monica

2012-02-01

We have developed an off-lattice kinetic Monte Carlo simulation scheme for reaction-diffusion problems in soft matter systems. The definition of transition probabilities in the Monte Carlo scheme are taken identical to the transition rates in a renormalized master equation of the diffusion process and match that of the Glauber dynamics of Ising model. Our scheme provides several advantages over the Brownian dynamics technique for non-equilibrium simulations. Since particle displacements are accepted/rejected in a Monte Carlo fashion as opposed to moving particles following a stochastic equation of motion, nonphysical movements (e.g., violation of a hard core assumption) are not possible (these moves have zero acceptance). Further, the absence of a stochastic ``noise'' term resolves the computational difficulties associated with generating statistically independent trajectories with definitive mean properties. Finally, since the timestep is independent of the magnitude of the interaction forces, much longer time-steps can be employed than Brownian dynamics. We discuss the applications of this scheme for dynamic self-assembly of photo-switchable nanoparticles and dynamical problems in polymeric systems.

Data Access Based on a Guide Map of the Underwater Wireless Sensor Network

PubMed Central

Wei, Zhengxian; Song, Min; Yin, Guisheng; Wang, Hongbin; Cheng, Albert M. K.

2017-01-01

Underwater wireless sensor networks (UWSNs) represent an area of increasing research interest, as data storage, discovery, and query of UWSNs are always challenging issues. In this paper, a data access based on a guide map (DAGM) method is proposed for UWSNs. In DAGM, the metadata describes the abstracts of data content and the storage location. The center ring is composed of nodes according to the shortest average data query path in the network in order to store the metadata, and the data guide map organizes, diffuses and synchronizes the metadata in the center ring, providing the most time-saving and energy-efficient data query service for the user. For this method, firstly the data is stored in the UWSN. The storage node is determined, the data is transmitted from the sensor node (data generation source) to the storage node, and the metadata is generated for it. Then, the metadata is sent to the center ring node that is the nearest to the storage node and the data guide map organizes the metadata, diffusing and synchronizing it to the other center ring nodes. Finally, when there is query data in any user node, the data guide map will select a center ring node nearest to the user to process the query sentence, and based on the shortest transmission delay and lowest energy consumption, data transmission routing is generated according to the storage location abstract in the metadata. Hence, specific application data transmission from the storage node to the user is completed. The simulation results demonstrate that DAGM has advantages with respect to data access time and network energy consumption. PMID:29039757

Data Access Based on a Guide Map of the Underwater Wireless Sensor Network.

PubMed

Wei, Zhengxian; Song, Min; Yin, Guisheng; Song, Houbing; Wang, Hongbin; Ma, Xuefei; Cheng, Albert M K

2017-10-17

Underwater wireless sensor networks (UWSNs) represent an area of increasing research interest, as data storage, discovery, and query of UWSNs are always challenging issues. In this paper, a data access based on a guide map (DAGM) method is proposed for UWSNs. In DAGM, the metadata describes the abstracts of data content and the storage location. The center ring is composed of nodes according to the shortest average data query path in the network in order to store the metadata, and the data guide map organizes, diffuses and synchronizes the metadata in the center ring, providing the most time-saving and energy-efficient data query service for the user. For this method, firstly the data is stored in the UWSN. The storage node is determined, the data is transmitted from the sensor node (data generation source) to the storage node, and the metadata is generated for it. Then, the metadata is sent to the center ring node that is the nearest to the storage node and the data guide map organizes the metadata, diffusing and synchronizing it to the other center ring nodes. Finally, when there is query data in any user node, the data guide map will select a center ring node nearest to the user to process the query sentence, and based on the shortest transmission delay and lowest energy consumption, data transmission routing is generated according to the storage location abstract in the metadata. Hence, specific application data transmission from the storage node to the user is completed. The simulation results demonstrate that DAGM has advantages with respect to data access time and network energy consumption.

Kinetic Monte Carlo Investigation of the Effects of Vacancy Pairing on Oxygen Diffusivity in Yttria-Stabilized Zirconia

NASA Technical Reports Server (NTRS)

Good, Brian S.

2011-01-01

Yttria-stabilized zirconia s high oxygen diffusivity and corresponding high ionic conductivity, and its structural stability over a broad range of temperatures, have made the material of interest for use in a number of applications, for example, as solid electrolytes in fuel cells. At low concentrations, the stabilizing yttria also serves to increase the oxygen diffusivity through the presence of corresponding oxygen vacancies, needed to maintain charge neutrality. At higher yttria concentration, however, diffusivity is impeded by the larger number of relatively high energy migration barriers associated with yttrium cations. In addition, there is evidence that oxygen vacancies preferentially occupy nearest-neighbor sites around either dopant or Zr cations, further affecting vacancy diffusion. We present the results of ab initio calculations that indicate that it is energetically favorable for oxygen vacancies to occupy nearest-neighbor sites adjacent to Y ions, and that the presence of vacancies near either species of cation lowers the migration barriers. Kinetic Monte Carlo results from simulations incorporating this effect are presented and compared with results from simulations in which the effect is not present.

Molecular dynamics and Monte Carlo simulations resolve apparent diffusion rate differences for proteins confined in nanochannels

DOE PAGES

Tringe, J. W.; Ileri, N.; Levie, H. W.; ...

2015-08-01

We use Molecular Dynamics and Monte Carlo simulations to examine molecular transport phenomena in nanochannels, explaining four orders of magnitude difference in wheat germ agglutinin (WGA) protein diffusion rates observed by fluorescence correlation spectroscopy (FCS) and by direct imaging of fluorescently-labeled proteins. We first use the ESPResSo Molecular Dynamics code to estimate the surface transport distance for neutral and charged proteins. We then employ a Monte Carlo model to calculate the paths of protein molecules on surfaces and in the bulk liquid transport medium. Our results show that the transport characteristics depend strongly on the degree of molecular surface coverage.more » Atomic force microscope characterization of surfaces exposed to WGA proteins for 1000 s show large protein aggregates consistent with the predicted coverage. These calculations and experiments provide useful insight into the details of molecular motion in confined geometries.« less

Auxiliary field diffusion Monte Carlo calculations of light and medium-mass nuclei with local chiral interactions

NASA Astrophysics Data System (ADS)

Lonardoni, D.; Gandolfi, S.; Lynn, J. E.; Petrie, C.; Carlson, J.; Schmidt, K. E.; Schwenk, A.

2018-04-01

Quantum Monte Carlo methods have recently been employed to study properties of nuclei and infinite matter using local chiral effective-field-theory interactions. In this work, we present a detailed description of the auxiliary field diffusion Monte Carlo algorithm for nuclei in combination with local chiral two- and three-nucleon interactions up to next-to-next-to-leading order. We show results for the binding energy, charge radius, charge form factor, and Coulomb sum rule in nuclei with 3 ≤A ≤16 . Particular attention is devoted to the effect of different operator structures in the three-body force for different cutoffs. The outcomes suggest that local chiral interactions fit to few-body observables give a very good description of the ground-state properties of nuclei up to 16O, with the exception of one fit for the softer cutoff which predicts overbinding in larger nuclei.

Application of the three-component bidirectional reflectance distribution function model to Monte Carlo calculation of spectral effective emissivities of nonisothermal blackbody cavities.

PubMed

Prokhorov, Alexander; Prokhorova, Nina I

2012-11-20

We applied the bidirectional reflectance distribution function (BRDF) model consisting of diffuse, quasi-specular, and glossy components to the Monte Carlo modeling of spectral effective emissivities for nonisothermal cavities. A method for extension of a monochromatic three-component (3C) BRDF model to a continuous spectral range is proposed. The initial data for this method are the BRDFs measured in the plane of incidence at a single wavelength and several incidence angles and directional-hemispherical reflectance measured at one incidence angle within a finite spectral range. We proposed the Monte Carlo algorithm for calculation of spectral effective emissivities for nonisothermal cavities whose internal surface is described by the wavelength-dependent 3C BRDF model. The results obtained for a cylindroconical nonisothermal cavity are discussed and compared with results obtained using the conventional specular-diffuse model.

An empirical approach to estimate near-infra-red photon propagation and optically induced drug release in brain tissues

NASA Astrophysics Data System (ADS)

Prabhu Verleker, Akshay; Fang, Qianqian; Choi, Mi-Ran; Clare, Susan; Stantz, Keith M.

2015-03-01

The purpose of this study is to develop an alternate empirical approach to estimate near-infra-red (NIR) photon propagation and quantify optically induced drug release in brain metastasis, without relying on computationally expensive Monte Carlo techniques (gold standard). Targeted drug delivery with optically induced drug release is a noninvasive means to treat cancers and metastasis. This study is part of a larger project to treat brain metastasis by delivering lapatinib-drug-nanocomplexes and activating NIR-induced drug release. The empirical model was developed using a weighted approach to estimate photon scattering in tissues and calibrated using a GPU based 3D Monte Carlo. The empirical model was developed and tested against Monte Carlo in optical brain phantoms for pencil beams (width 1mm) and broad beams (width 10mm). The empirical algorithm was tested against the Monte Carlo for different albedos along with diffusion equation and in simulated brain phantoms resembling white-matter (μs'=8.25mm-1, μa=0.005mm-1) and gray-matter (μs'=2.45mm-1, μa=0.035mm-1) at wavelength 800nm. The goodness of fit between the two models was determined using coefficient of determination (R-squared analysis). Preliminary results show the Empirical algorithm matches Monte Carlo simulated fluence over a wide range of albedo (0.7 to 0.99), while the diffusion equation fails for lower albedo. The photon fluence generated by empirical code matched the Monte Carlo in homogeneous phantoms (R2=0.99). While GPU based Monte Carlo achieved 300X acceleration compared to earlier CPU based models, the empirical code is 700X faster than the Monte Carlo for a typical super-Gaussian laser beam.

DMA engine for repeating communication patterns

DOEpatents

Chen, Dong; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Steinmacher-Burow, Burkhard; Vranas, Pavlos

2010-09-21

A parallel computer system is constructed as a network of interconnected compute nodes to operate a global message-passing application for performing communications across the network. Each of the compute nodes includes one or more individual processors with memories which run local instances of the global message-passing application operating at each compute node to carry out local processing operations independent of processing operations carried out at other compute nodes. Each compute node also includes a DMA engine constructed to interact with the application via Injection FIFO Metadata describing multiple Injection FIFOs where each Injection FIFO may containing an arbitrary number of message descriptors in order to process messages with a fixed processing overhead irrespective of the number of message descriptors included in the Injection FIFO.

Spreading dynamics in complex networks

NASA Astrophysics Data System (ADS)

Pei, Sen; Makse, Hernán A.

2013-12-01

Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from epidemic control, innovation diffusion, viral marketing, and social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community—LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in the LiveJournal social network, only a small fraction of them are involved in spreading. For the spreading processes in LiveJournal, while degree can locate nodes participating in information diffusion with higher probability, k-shell is more effective in finding nodes with a large influence. Our results should provide useful information for designing efficient spreading strategies in reality.

New Monte Carlo model of cylindrical diffusing fibers illustrates axially heterogeneous fluorescence detection: simulation and experimental validation

PubMed Central

Baran, Timothy M.; Foster, Thomas H.

2011-01-01

We present a new Monte Carlo model of cylindrical diffusing fibers that is implemented with a graphics processing unit. Unlike previously published models that approximate the diffuser as a linear array of point sources, this model is based on the construction of these fibers. This allows for accurate determination of fluence distributions and modeling of fluorescence generation and collection. We demonstrate that our model generates fluence profiles similar to a linear array of point sources, but reveals axially heterogeneous fluorescence detection. With axially homogeneous excitation fluence, approximately 90% of detected fluorescence is collected by the proximal third of the diffuser for μs'/μa = 8 in the tissue and 70 to 88% is collected in this region for μs'/μa = 80. Increased fluorescence detection by the distal end of the diffuser relative to the center section is also demonstrated. Validation of these results was performed by creating phantoms consisting of layered fluorescent regions. Diffusers were inserted into these layered phantoms and fluorescence spectra were collected. Fits to these spectra show quantitative agreement between simulated fluorescence collection sensitivities and experimental results. These results will be applicable to the use of diffusers as detectors for dosimetry in interstitial photodynamic therapy. PMID:21895311

Binding and Diffusion of Lithium in Graphite: Quantum Monte Carlo Benchmarks and Validation of van der Waals Density Functional Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ganesh, P.; Kim, Jeongnim; Park, Changwon

2014-11-03

In highly accurate diffusion quantum Monte Carlo (QMC) studies of the adsorption and diffusion of atomic lithium in AA-stacked graphite are compared with van der Waals-including density functional theory (DFT) calculations. Predicted QMC lattice constants for pure AA graphite agree with experiment. Pure AA-stacked graphite is shown to challenge many van der Waals methods even when they are accurate for conventional AB graphite. Moreover, the highest overall DFT accuracy, considering pure AA-stacked graphite as well as lithium binding and diffusion, is obtained by the self-consistent van der Waals functional vdW-DF2, although errors in binding energies remain. Empirical approaches based onmore » point charges such as DFT-D are inaccurate unless the local charge transfer is assessed. Our results demonstrate that the lithium carbon system requires a simultaneous highly accurate description of both charge transfer and van der Waals interactions, favoring self-consistent approaches.« less

Hybrid transport and diffusion modeling using electron thermal transport Monte Carlo SNB in DRACO

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Moses, Gregory

2017-10-01

The iSNB (implicit Schurtz Nicolai Busquet) multigroup diffusion electron thermal transport method is adapted into an Electron Thermal Transport Monte Carlo (ETTMC) transport method to better model angular and long mean free path non-local effects. Previously, the ETTMC model had been implemented in the 2D DRACO multiphysics code and found to produce consistent results with the iSNB method. Current work is focused on a hybridization of the computationally slower but higher fidelity ETTMC transport method with the computationally faster iSNB diffusion method in order to maximize computational efficiency. Furthermore, effects on the energy distribution of the heat flux divergence are studied. Work to date on the hybrid method will be presented. This work was supported by Sandia National Laboratories and the Univ. of Rochester Laboratory for Laser Energetics.

A coarse-grained Monte Carlo approach to diffusion processes in metallic nanoparticles

NASA Astrophysics Data System (ADS)

Hauser, Andreas W.; Schnedlitz, Martin; Ernst, Wolfgang E.

2017-06-01

A kinetic Monte Carlo approach on a coarse-grained lattice is developed for the simulation of surface diffusion processes of Ni, Pd and Au structures with diameters in the range of a few nanometers. Intensity information obtained via standard two-dimensional transmission electron microscopy imaging techniques is used to create three-dimensional structure models as input for a cellular automaton. A series of update rules based on reaction kinetics is defined to allow for a stepwise evolution in time with the aim to simulate surface diffusion phenomena such as Rayleigh breakup and surface wetting. The material flow, in our case represented by the hopping of discrete portions of metal on a given grid, is driven by the attempt to minimize the surface energy, which can be achieved by maximizing the number of filled neighbor cells.

Effective emissivities of isothermal blackbody cavities calculated by the Monte Carlo method using the three-component bidirectional reflectance distribution function model.

PubMed

Prokhorov, Alexander

2012-05-01

This paper proposes a three-component bidirectional reflectance distribution function (3C BRDF) model consisting of diffuse, quasi-specular, and glossy components for calculation of effective emissivities of blackbody cavities and then investigates the properties of the new reflection model. The particle swarm optimization method is applied for fitting a 3C BRDF model to measured BRDFs. The model is incorporated into the Monte Carlo ray-tracing algorithm for isothermal cavities. Finally, the paper compares the results obtained using the 3C model and the conventional specular-diffuse model of reflection.

A variational Monte Carlo study of different spin configurations of electron-hole bilayer

NASA Astrophysics Data System (ADS)

Sharma, Rajesh O.; Saini, L. K.; Bahuguna, Bhagwati Prasad

2018-05-01

We report quantum Monte Carlo results for mass-asymmetric electron-hole bilayer (EHBL) system with different-different spin configurations. Particularly, we apply a variational Monte Carlo method to estimate the ground-state energy, condensate fraction and pair-correlations function at fixed density rs = 5 and interlayer distance d = 1 a.u. We find that spin-configuration of EHBL system, which consists of only up-electrons in one layer and down-holes in other i.e. ferromagnetic arrangement within layers and anti-ferromagnetic across the layers, is more stable than the other spin-configurations considered in this study.

MC3: Multi-core Markov-chain Monte Carlo code

NASA Astrophysics Data System (ADS)

Cubillos, Patricio; Harrington, Joseph; Lust, Nate; Foster, AJ; Stemm, Madison; Loredo, Tom; Stevenson, Kevin; Campo, Chris; Hardin, Matt; Hardy, Ryan

2016-10-01

MC3 (Multi-core Markov-chain Monte Carlo) is a Bayesian statistics tool that can be executed from the shell prompt or interactively through the Python interpreter with single- or multiple-CPU parallel computing. It offers Markov-chain Monte Carlo (MCMC) posterior-distribution sampling for several algorithms, Levenberg-Marquardt least-squares optimization, and uniform non-informative, Jeffreys non-informative, or Gaussian-informative priors. MC3 can share the same value among multiple parameters and fix the value of parameters to constant values, and offers Gelman-Rubin convergence testing and correlated-noise estimation with time-averaging or wavelet-based likelihood estimation methods.

An investigation of light transport through scattering bodies with non-scattering regions.

PubMed

Firbank, M; Arridge, S R; Schweiger, M; Delpy, D T

1996-04-01

Near-infra-red (NIR) spectroscopy is increasingly being used for monitoring cerebral oxygenation and haemodynamics. One current concern is the effect of the clear cerebrospinal fluid upon the distribution of light in the head. There are difficulties in modelling clear layers in scattering systems. The Monte Carlo model should handle clear regions accurately, but is too slow to be used for realistic geometries. The diffusion equation can be solved quickly for realistic geometries, but is only valid in scattering regions. In this paper we describe experiments carried out on a solid slab phantom to investigate the effect of clear regions. The experimental results were compared with the different models of light propagation. We found that the presence of a clear layer had a significant effect upon the light distribution, which was modelled correctly by Monte Carlo techniques, but not by diffusion theory. A novel approach to calculating the light transport was developed, using diffusion theory to analyze the scattering regions combined with a radiosity approach to analyze the propagation through the clear region. Results from this approach were found to agree with both the Monte Carlo and experimental data.

Smart darting diffusion Monte Carlo: Applications to lithium ion-Stockmayer clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Christensen, H. M.; Jake, L. C.; Curotto, E., E-mail: curotto@arcadia.edu

2016-05-07

In a recent investigation [K. Roberts et al., J. Chem. Phys. 136, 074104 (2012)], we have shown that, for a sufficiently complex potential, the Diffusion Monte Carlo (DMC) random walk can become quasiergodic, and we have introduced smart darting-like moves to improve the sampling. In this article, we systematically characterize the bias that smart darting moves introduce in the estimate of the ground state energy of a bosonic system. We then test a simple approach to eliminate completely such bias from the results. The approach is applied for the determination of the ground state of lithium ion-n–dipoles clusters in themore » n = 8–20 range. For these, the smart darting diffusion Monte Carlo simulations find the same ground state energy and mixed-distribution as the traditional approach for n < 14. In larger systems we find that while the ground state energies agree quantitatively with or without smart darting moves, the mixed-distributions can be significantly different. Some evidence is offered to conclude that introducing smart darting-like moves in traditional DMC simulations may produce a more reliable ground state mixed-distribution.« less

Inhibiting diffusion of complex contagions in social networks: theoretical and experimental results

PubMed Central

Anil Kumar, V.S.; Marathe, Madhav V.; Ravi, S.S.; Rosenkrantz, Daniel J.

2014-01-01

We consider the problem of inhibiting undesirable contagions (e.g. rumors, spread of mob behavior) in social networks. Much of the work in this context has been carried out under the 1-threshold model, where diffusion occurs when a node has just one neighbor with the contagion. We study the problem of inhibiting more complex contagions in social networks where nodes may have thresholds larger than 1. The goal is to minimize the propagation of the contagion by removing a small number of nodes (called critical nodes) from the network. We study several versions of this problem and prove that, in general, they cannot even be efficiently approximated to within any factor ρ ≥ 1, unless P = NP. We develop efficient and practical heuristics for these problems and carry out an experimental study of their performance on three well known social networks, namely epinions, wikipedia and slashdot. Our results show that these heuristics perform significantly better than five other known methods. We also establish an efficiently computable upper bound on the number of nodes to which a contagion can spread and evaluate this bound on many real and synthetic networks. PMID:25750583

The Fixed Target Experiment for Studies of Baryonic Matter at the Nuclotron (BM@N)

NASA Astrophysics Data System (ADS)

Kapishin, M. N.

2017-12-01

BM@N (Baryonic Matter at Nuclotron) is the first experiment to be realized at the NICA-Nuclotron accelerator complex. The aim of the BM@N experiment is to study relativistic heavy ion beam interactions with fixed targets. The BM@N setup, results of Monte Carlo simulations, and the BM@N experimental program are presented.

Monte Carlo simulations of coupled diffusion and surface reactions during the aqueous corrosion of borosilicate glasses

DOE PAGES

Kerisit, Sebastien; Pierce, Eric M.; Ryan, Joseph V.

2014-09-19

Borosilicate nuclear waste glasses develop complex altered layers as a result of coupled processes such as hydrolysis of network species, condensation of Si species, and diffusion. However, diffusion has often been overlooked in Monte Carlo models of the aqueous corrosion of borosilicate glasses. Therefore, in this paper three different models for dissolved Si diffusion in the altered layer were implemented in a Monte Carlo model and evaluated for glasses in the compositional range (75 - x) mol% SiO 2 (12.5 + x/2) mol% B 2O 3 and (12.5 + x/2) mol% Na 2O, where 0 ≤ x ≤ 20%, andmore » corroded in static conditions at a surface-area-to-volume ratio of 1000 m -1. The three models considered instantaneous homogenization (M1), linear concentration gradients (M2), and concentration profiles determined by solving Fick's 2nd law using a finite difference method (M3). Model M3 revealed that concentration profiles in the altered layer are not linear and show changes in shape and magnitude as corrosion progresses, unlike those assumed in model M2. Furthermore, model M3 showed that, for borosilicate glasses with a high forward dissolution rate compared to the diffusion rate, the gradual polymerization and densification of the altered layer is significantly delayed compared to models M1 and M2. Finally, models M1 and M2 were found to be appropriate models only for glasses with high release rates such as simple borosilicate glasses with low ZrO 2 content.« less

Blob-Spring Model for the Dynamics of Ring Polymer in Obstacle Environment

NASA Astrophysics Data System (ADS)

Lele, Ashish K.; Iyer, Balaji V. S.; Juvekar, Vinay A.

2008-07-01

The dynamical behavior of cyclic macromolecules in a fixed obstacle (FO) environment is very different than the behavior of linear chains in the same topological environment; while the latter relax by a snake-like reptational motion from their chain ends the former can relax only by contour length fluctuations since they are endless. Duke, Obukhov and Rubinstein proposed a scaling model (the DOR model) to interpret the dynamical scaling exponents shown by Monte Carlo simulations of rings in a FO environment. We present a model (blob-spring model) to describe the dynamics of flexible and non-concatenated ring polymer in FO environment based on a theoretical formulation developed for the dynamics of an unentangled fractal polymer. We argue that the perpetual evolution of ring perimeter by the motion of contour segments results in an extra frictional load. Our model predicts self-similar dynamics with scaling exponents for the molecular weight dependence of diffusion coefficient and relaxation times that are in agreement with the scaling model proposed by Obukhov et al.

[A morphometric analysis of the nuclei and nucleoli in tumor cells in lymphogranulomatosis, diffuse large B-cell lymphoma and anaplastic large cell lymphoma].

PubMed

Gorgidze, L A; Vorob'ev, I A

2009-01-01

To make a comparative morphometric analysis of the nuclei and nucleoli of tumor cells in lymphogranulomatosis (LGM), diffuse large B-cell lymphoma (DLBCL) and anaplastic large cell lymphoma (ALCL) for differential diagnosis of these lymphomas. Biopsy material (lymph node biopsies) was frozen in hexane, fixed and stained, then microscopic pictures were made. Mean area of tumor cell nuclei in LGM was 97.25 +/- 68.77 mcm2, in DLBCL and ALCL--55.89 +/- 20.13 mcm2 and 70.31 +/- 34.64 mcm2, respectively. The area differences were significant (p < 0.001). Hodgkin's and Berezovsky-Rid-Sternberg cell bucleoli area was the largest (11.44 +/- 7.83 mcm2). The nucleoli of the former are larger than those of the latter. Mean area of the nucleoli in DLBCL was 3.05 +/- 1.58, in ALCL--5.53 +/- 4.94 mcm2. The differences are significant (p < 0.001). Nucleoli in Hodgkin 's cells are significantly larger than those in the tumor cells in ALCL and DLBCL and the nucleoli with the area more than 12 mcm2 can be used in differential diagnosis between LGM and DLBCL but not between LGM and ALCL.

Method for designing gas tag compositions

DOEpatents

Gross, K.C.

1995-04-11

For use in the manufacture of gas tags such as employed in a nuclear reactor gas tagging failure detection system, a method for designing gas tagging compositions utilizes an analytical approach wherein the final composition of a first canister of tag gas as measured by a mass spectrometer is designated as node No. 1. Lattice locations of tag nodes in multi-dimensional space are then used in calculating the compositions of a node No. 2 and each subsequent node so as to maximize the distance of each node from any combination of tag components which might be indistinguishable from another tag composition in a reactor fuel assembly. Alternatively, the measured compositions of tag gas numbers 1 and 2 may be used to fix the locations of nodes 1 and 2, with the locations of nodes 3-N then calculated for optimum tag gas composition. A single sphere defining the lattice locations of the tag nodes may be used to define approximately 20 tag nodes, while concentric spheres can extend the number of tag nodes to several hundred. 5 figures.

Patterns of a spatial exploration under time evolution of the attractiveness: Persistent nodes, degree distribution, and spectral properties

NASA Astrophysics Data System (ADS)

da Silva, Roberto

2018-06-01

This work explores the features of a graph generated by agents that hop from one node to another node, where the nodes have evolutionary attractiveness. The jumps are governed by Boltzmann-like transition probabilities that depend both on the euclidean distance between the nodes and on the ratio (β) of the attractiveness between them. It is shown that persistent nodes, i.e., nodes that never been reached by this special random walk are possible in the stationary limit differently from the case where the attractiveness is fixed and equal to one for all nodes (β = 1). Simultaneously, one also investigates the spectral properties and statistics related to the attractiveness and degree distribution of the evolutionary network. Finally, a study of the crossover between persistent phase and no persistent phase was performed and it was also observed the existence of a special type of transition probability which leads to a power law behaviour for the time evolution of the persistence.

Increasing the Lifetime of Mobile WSNs via Dynamic Optimization of Sensor Node Communication Activity

PubMed Central

Guimarães, Dayan Adionel; Sakai, Lucas Jun; Alberti, Antonio Marcos; de Souza, Rausley Adriano Amaral

2016-01-01

In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node dynamically optimizes the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors’ batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the optimization problem an even more dynamic character. We report large increased lifetimes over the non-optimized network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information. PMID:27657075

Increasing the Lifetime of Mobile WSNs via Dynamic Optimization of Sensor Node Communication Activity.

PubMed

Guimarães, Dayan Adionel; Sakai, Lucas Jun; Alberti, Antonio Marcos; de Souza, Rausley Adriano Amaral

2016-09-20

In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node dynamically optimizes the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors' batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the optimization problem an even more dynamic character. We report large increased lifetimes over the non-optimized network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information.

Lymph node pick up by separate stations: Option or necessity.

PubMed

Morgagni, Paolo; Nanni, Oriana; Carretta, Elisa; Altini, Mattia; Saragoni, Luca; Falcini, Fabio; Garcea, Domenico

2015-05-27

To evaluate whether lymph node pick up by separate stations could be an indicator of patients submitted to appropriate surgical treatment. One thousand two hundred and three consecutive gastric cancer patients submitted to radical resection in 7 general hospitals and for whom no information was available on the extension of lymphatic dissection were included in this retrospective study. Patients were divided into 2 groups: group A, where the stomach specimen was directly formalin-fixed and sent to the pathologist, and group B, where lymph nodes were picked up after surgery and fixed for separate stations. Sixty-two point three percent of group A patients showed < 16 retrieved lymph nodes compared to 19.4% of group B (P < 0.0001). Group B (separate stations) patients had significantly higher survival rates than those in group A [46.1 mo (95%CI: 36.5-56.0) vs 27.7 mo (95%CI: 21.3-31.9); P = 0.0001], independently of T or N stage. In multivariate analysis, group A also showed a higher risk of death than group B (HR = 1.24; 95%CI: 1.05-1.46). Separate lymphatic station dissection increases the number of retrieved nodes, leads to better tumor staging, and permits verification of the surgical dissection. The number of dissected stations could potentially be used as an index to evaluate the quality of treatment received.

Performance evaluation of an importance sampling technique in a Jackson network

NASA Astrophysics Data System (ADS)

brahim Mahdipour, E.; Masoud Rahmani, Amir; Setayeshi, Saeed

2014-03-01

Importance sampling is a technique that is commonly used to speed up Monte Carlo simulation of rare events. However, little is known regarding the design of efficient importance sampling algorithms in the context of queueing networks. The standard approach, which simulates the system using an a priori fixed change of measure suggested by large deviation analysis, has been shown to fail in even the simplest network settings. Estimating probabilities associated with rare events has been a topic of great importance in queueing theory, and in applied probability at large. In this article, we analyse the performance of an importance sampling estimator for a rare event probability in a Jackson network. This article carries out strict deadlines to a two-node Jackson network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We have estimated the probability of network blocking for various sets of parameters, and also the probability of missing the deadline of customers for different loads and deadlines. We have finally shown that the probability of total population overflow may be affected by various deadline values, service rates and arrival rates.

Sparse and Adaptive Diffusion Dictionary (SADD) for recovering intra-voxel white matter structure.

PubMed

Aranda, Ramon; Ramirez-Manzanares, Alonso; Rivera, Mariano

2015-12-01

On the analysis of the Diffusion-Weighted Magnetic Resonance Images, multi-compartment models overcome the limitations of the well-known Diffusion Tensor model for fitting in vivo brain axonal orientations at voxels with fiber crossings, branching, kissing or bifurcations. Some successful multi-compartment methods are based on diffusion dictionaries. The diffusion dictionary-based methods assume that the observed Magnetic Resonance signal at each voxel is a linear combination of the fixed dictionary elements (dictionary atoms). The atoms are fixed along different orientations and diffusivity profiles. In this work, we present a sparse and adaptive diffusion dictionary method based on the Diffusion Basis Functions Model to estimate in vivo brain axonal fiber populations. Our proposal overcomes the following limitations of the diffusion dictionary-based methods: the limited angular resolution and the fixed shapes for the atom set. We propose to iteratively re-estimate the orientations and the diffusivity profile of the atoms independently at each voxel by using a simplified and easier-to-solve mathematical approach. As a result, we improve the fitting of the Diffusion-Weighted Magnetic Resonance signal. The advantages with respect to the former Diffusion Basis Functions method are demonstrated on the synthetic data-set used on the 2012 HARDI Reconstruction Challenge and in vivo human data. We demonstrate that improvements obtained in the intra-voxel fiber structure estimations benefit brain research allowing to obtain better tractography estimations. Hence, these improvements result in an accurate computation of the brain connectivity patterns. Copyright © 2015 Elsevier B.V. All rights reserved.

Diffusion in Deterministic Interacting Lattice Systems

NASA Astrophysics Data System (ADS)

Medenjak, Marko; Klobas, Katja; Prosen, Tomaž

2017-09-01

We study reversible deterministic dynamics of classical charged particles on a lattice with hard-core interaction. It is rigorously shown that the system exhibits three types of transport phenomena, ranging from ballistic, through diffusive to insulating. By obtaining an exact expressions for the current time-autocorrelation function we are able to calculate the linear response transport coefficients, such as the diffusion constant and the Drude weight. Additionally, we calculate the long-time charge profile after an inhomogeneous quench and obtain diffusive profilewith the Green-Kubo diffusion constant. Exact analytical results are corroborated by Monte Carlo simulations.

Improved algorithm for estimating optical properties of food and biological materials using spatially-resolved diffuse reflectance

USDA-ARS?s Scientific Manuscript database

In this research, the inverse algorithm for estimating optical properties of food and biological materials from spatially-resolved diffuse reflectance was optimized in terms of data smoothing, normalization and spatial region of reflectance profile for curve fitting. Monte Carlo simulation was used ...

O the Derivation of the Schroedinger Equation from Stochastic Mechanics.

NASA Astrophysics Data System (ADS)

Wallstrom, Timothy Clarke

The thesis is divided into four largely independent chapters. The first three chapters treat mathematical problems in the theory of stochastic mechanics. The fourth chapter deals with stochastic mechanisms as a physical theory and shows that the Schrodinger equation cannot be derived from existing formulations of stochastic mechanics, as had previously been believed. Since the drift coefficients of stochastic mechanical diffusions are undefined on the nodes, or zeros of the density, an important problem has been to show that the sample paths stay away from the nodes. In Chapter 1, it is shown that for a smooth wavefunction, the closest approach to the nodes can be bounded solely in terms of the time -integrated energy. The ergodic properties of stochastic mechanical diffusions are greatly complicated by the tendency of the particles to avoid the nodes. In Chapter 2, it is shown that a sufficient condition for a stationary process to be ergodic is that there exist positive t and c such that for all x and y, p^{t} (x,y) > cp(y), and this result is applied to show that the set of spin-1over2 diffusions is uniformly ergodic. In stochastic mechanics, the Bopp-Haag-Dankel diffusions on IR^3times SO(3) are used to represent particles with spin. Nelson has conjectured that in the limit as the particle's moment of inertia I goes to zero, the projections of the Bopp -Haag-Dankel diffusions onto IR^3 converge to a Markovian limit process. This conjecture is proved for the spin-1over2 case in Chapter 3, and the limit process identified as the diffusion naturally associated with the solution to the regular Pauli equation. In Chapter 4 it is shown that the general solution of the stochastic Newton equation does not correspond to a solution of the Schrodinger equation, and that there are solutions to the Schrodinger equation which do not satisfy the Guerra-Morato Lagrangian variational principle. These observations are shown to apply equally to other existing formulations of stochastic mechanics, and it is argued that these difficulties represent fundamental inadequacies in the physical foundation of stochastic mechanics.

Sequential Monte Carlo for Maximum Weight Subgraphs with Application to Solving Image Jigsaw Puzzles.

PubMed

Adluru, Nagesh; Yang, Xingwei; Latecki, Longin Jan

2015-05-01

We consider a problem of finding maximum weight subgraphs (MWS) that satisfy hard constraints in a weighted graph. The constraints specify the graph nodes that must belong to the solution as well as mutual exclusions of graph nodes, i.e., pairs of nodes that cannot belong to the same solution. Our main contribution is a novel inference approach for solving this problem in a sequential monte carlo (SMC) sampling framework. Usually in an SMC framework there is a natural ordering of the states of the samples. The order typically depends on observations about the states or on the annealing setup used. In many applications (e.g., image jigsaw puzzle problems), all observations (e.g., puzzle pieces) are given at once and it is hard to define a natural ordering. Therefore, we relax the assumption of having ordered observations about states and propose a novel SMC algorithm for obtaining maximum a posteriori estimate of a high-dimensional posterior distribution. This is achieved by exploring different orders of states and selecting the most informative permutations in each step of the sampling. Our experimental results demonstrate that the proposed inference framework significantly outperforms loopy belief propagation in solving the image jigsaw puzzle problem. In particular, our inference quadruples the accuracy of the puzzle assembly compared to that of loopy belief propagation.

Sequential Monte Carlo for Maximum Weight Subgraphs with Application to Solving Image Jigsaw Puzzles

PubMed Central

Adluru, Nagesh; Yang, Xingwei; Latecki, Longin Jan

2015-01-01

We consider a problem of finding maximum weight subgraphs (MWS) that satisfy hard constraints in a weighted graph. The constraints specify the graph nodes that must belong to the solution as well as mutual exclusions of graph nodes, i.e., pairs of nodes that cannot belong to the same solution. Our main contribution is a novel inference approach for solving this problem in a sequential monte carlo (SMC) sampling framework. Usually in an SMC framework there is a natural ordering of the states of the samples. The order typically depends on observations about the states or on the annealing setup used. In many applications (e.g., image jigsaw puzzle problems), all observations (e.g., puzzle pieces) are given at once and it is hard to define a natural ordering. Therefore, we relax the assumption of having ordered observations about states and propose a novel SMC algorithm for obtaining maximum a posteriori estimate of a high-dimensional posterior distribution. This is achieved by exploring different orders of states and selecting the most informative permutations in each step of the sampling. Our experimental results demonstrate that the proposed inference framework significantly outperforms loopy belief propagation in solving the image jigsaw puzzle problem. In particular, our inference quadruples the accuracy of the puzzle assembly compared to that of loopy belief propagation. PMID:26052182

The Thinnest Path Problem

DTIC Science & Technology

2016-07-22

their corresponding transmission powers . At first glance, one may wonder whether the thinnest path problem is simply a shortest path problem with the...nature of the shortest path problem. Another aspect that complicates the problem is the choice of the transmission power at each node (within a maximum...fixed transmission power at each node (in this case, the resulting hypergraph degenerates to a standard graph), the thinnest path problem is NP

A network of discrete events for the representation and analysis of diffusion dynamics.

PubMed

Pintus, Alberto M; Pazzona, Federico G; Demontis, Pierfranco; Suffritti, Giuseppe B

2015-11-14

We developed a coarse-grained description of the phenomenology of diffusive processes, in terms of a space of discrete events and its representation as a network. Once a proper classification of the discrete events underlying the diffusive process is carried out, their transition matrix is calculated on the basis of molecular dynamics data. This matrix can be represented as a directed, weighted network where nodes represent discrete events, and the weight of edges is given by the probability that one follows the other. The structure of this network reflects dynamical properties of the process of interest in such features as its modularity and the entropy rate of nodes. As an example of the applicability of this conceptual framework, we discuss here the physics of diffusion of small non-polar molecules in a microporous material, in terms of the structure of the corresponding network of events, and explain on this basis the diffusivity trends observed. A quantitative account of these trends is obtained by considering the contribution of the various events to the displacement autocorrelation function.

Atomistic models of Cu diffusion in CuInSe2 under variations in composition

NASA Astrophysics Data System (ADS)

Sommer, David E.; Dunham, Scott T.

2018-03-01

We construct an analytic model for the composition dependence of the vacancy-mediated Cu diffusion coefficient in undoped CuInSe2 using parameters from density functional theory. The applicability of this model is supported numerically with kinetic lattice Monte Carlo and Onsager transport tensors. We discuss how this model relates to experimental measurements of Cu diffusion, arguing that our results can account for significant contributions to the bulk diffusion of Cu tracers in non-stoichiometric CuInSe2.

Diffuse sclerosing variant of thyroid carcinoma presenting as Hashimoto thyroiditis: a case report.

PubMed

Vukasović, Anamarija; Kuna, Sanja Kusacić; Ostović, Karmen Trutin; Prgomet, Drago; Banek, Tomislav

2012-11-01

The aim of report is to present a case of a rare diffuse sclerosing variant of a papillary thyroid carcinoma. A 15-year old girl referred for ultrasound examination because of painless thyroid swelling lasting 10 days before. An ultrasound of the neck showed diffusely changed thyroid parenchyma, without nodes, looking as lymphocytic thyroiditis Hashimoto at first, but with snow-storm appearance, predominantly in the right lobe. Positive thyroid peroxidase antibodies (TPO-AT) also suggested Hashimoto thyroiditis. Repeated US-FNAB (fine needle-aspiration biopsy) of the right lobe revealed diffuse sclerosing variant of papillary thyroid carcinoma and patient underwent total thyreoidectomy. Patohistologic finding confirmed diffuse sclerosing variant of a papillary thyroid carcinoma in the both thyroid lobes and several metastatic lymph nodes. Two months later patient recived radioablative therapy with 3700 MBq (100 mCi) of 1-131 followed by levothyroxine replacement. At the moment, patient is without evidence of local or distant metastases and next regular control is scheduled in 6 months. In conclusion, a diffuse sclerosing variant is rare form of papillary thyroid carcinoma that echographically looks similar to Hashimoto thyroiditis and sometimes could be easily overlooked.

Node Self-Deployment Algorithm Based on an Uneven Cluster with Radius Adjusting for Underwater Sensor Networks

PubMed Central

Jiang, Peng; Xu, Yiming; Wu, Feng

2016-01-01

Existing move-restricted node self-deployment algorithms are based on a fixed node communication radius, evaluate the performance based on network coverage or the connectivity rate and do not consider the number of nodes near the sink node and the energy consumption distribution of the network topology, thereby degrading network reliability and the energy consumption balance. Therefore, we propose a distributed underwater node self-deployment algorithm. First, each node begins the uneven clustering based on the distance on the water surface. Each cluster head node selects its next-hop node to synchronously construct a connected path to the sink node. Second, the cluster head node adjusts its depth while maintaining the layout formed by the uneven clustering and then adjusts the positions of in-cluster nodes. The algorithm originally considers the network reliability and energy consumption balance during node deployment and considers the coverage redundancy rate of all positions that a node may reach during the node position adjustment. Simulation results show, compared to the connected dominating set (CDS) based depth computation algorithm, that the proposed algorithm can increase the number of the nodes near the sink node and improve network reliability while guaranteeing the network connectivity rate. Moreover, it can balance energy consumption during network operation, further improve network coverage rate and reduce energy consumption. PMID:26784193

Scientific Impact Recognition Award. Sentinel node staging for breast cancer: intraoperative molecular pathology overcomes conventional histologic sampling errors.

PubMed

Blumencranz, Peter; Whitworth, Pat W; Deck, Kenneth; Rosenberg, Anne; Reintgen, Douglas; Beitsch, Peter; Chagpar, Anees; Julian, Thomas; Saha, Sukamal; Mamounas, Eleftherios; Giuliano, Armando; Simmons, Rache

2007-10-01

When sentinel node dissection reveals breast cancer metastasis, completion axillary lymph node dissection is ideally performed during the same operation. Intraoperative histologic techniques have low and variable sensitivity. A new intraoperative molecular assay (GeneSearch BLN Assay; Veridex, LLC, Warren, NJ) was evaluated to determine its efficiency in identifying significant sentinel lymph node metastases (>.2 mm). Positive or negative BLN Assay results generated from fresh 2-mm node slabs were compared with results from conventional histologic evaluation of adjacent fixed tissue slabs. In a prospective study of 416 patients at 11 clinical sites, the assay detected 98% of metastases >2 mm and 88% of metastasis greater >.2 mm, results superior to frozen section. Micrometastases were less frequently detected (57%) and assay positive results in nodes found negative by histology were rare (4%). The BLN Assay is properly calibrated for use as a stand alone intraoperative molecular test.

Towards the development of tamper-resistant, ground-based mobile sensor nodes

NASA Astrophysics Data System (ADS)

Mascarenas, David; Stull, Christopher; Farrar, Charles

2011-11-01

Mobile sensor nodes hold great potential for collecting field data using fewer resources than human operators would require and potentially requiring fewer sensors than a fixed-position sensor array. It would be very beneficial to allow these mobile sensor nodes to operate unattended with a minimum of human intervention. In order to allow mobile sensor nodes to operate unattended in a field environment, it is imperative that they be capable of identifying and responding to external agents that may attempt to tamper with, damage or steal the mobile sensor nodes, while still performing their data collection mission. Potentially hostile external agents could include animals, other mobile sensor nodes, or humans. This work will focus on developing control policies to help enable a mobile sensor node to identify and avoid capture by a hostile un-mounted human. The work is developed in a simulation environment, and demonstrated using a non-holonomic, ground-based mobile sensor node. This work will be a preliminary step toward ensuring the cyber-physical security of ground-based mobile sensor nodes that operate unattended in potentially unfriendly environments.

Simulation of Changes in Diffusion Related to Different Pathologies at Cellular Level After Traumatic Brain Injury

PubMed Central

Lin, Mu; He, Hongjian; Schifitto, Giovanni; Zhong, Jianhui

2016-01-01

Purpose The goal of the current study was to investigate tissue pathology at the cellular level in traumatic brain injury (TBI) as revealed by Monte Carlo simulation of diffusion tensor imaging (DTI)-derived parameters and elucidate the possible sources of conflicting findings of DTI abnormalities as reported in the TBI literature. Methods A model with three compartments separated by permeable membranes was employed to represent the diffusion environment of water molecules in brain white matter. The dynamic diffusion process was simulated with a Monte Carlo method using adjustable parameters of intra-axonal diffusivity, axon separation, glial cell volume fraction, and myelin sheath permeability. The effects of tissue pathology on DTI parameters were investigated by adjusting the parameters of the model corresponding to different stages of brain injury. Results The results suggest that the model is appropriate and the DTI-derived parameters simulate the predominant cellular pathology after TBI. Our results further indicate that when edema is not prevalent, axial and radial diffusivity have better sensitivity to axonal injury and demyelination than other DTI parameters. Conclusion DTI is a promising biomarker to detect and stage tissue injury after TBI. The observed inconsistencies among previous studies are likely due to scanning at different stages of tissue injury after TBI. PMID:26256558

Kinetic Monte Carlo Simulations of Oxygen Diffusion in Environmental Barrier Coating Materials

NASA Technical Reports Server (NTRS)

Good, Brian S.

2017-01-01

Ceramic Matrix Composite (CMC) materials are of interest for use in next-generation turbine engine components, offering a number of significant advantages, including reduced weight and high operating temperatures. However, in the hot environment in which such components operate, the presence of water vapor can lead to corrosion and recession, limiting the useful life of the components. Such degradation can be reduced through the use of Environmental Barrier Coatings (EBCs) that limit the amount of oxygen and water vapor reaching the component. Candidate EBC materials include Yttrium and Ytterbium silicates. In this work we present results of kinetic Monte Carlo (kMC) simulations of oxygen diffusion, via the vacancy mechanism, in Yttrium and Ytterbium disilicates, along with a brief discussion of interstitial diffusion. An EBC system typically includes a bond coat located between the EBC and the component surface. Bond coat materials are generally chosen for properties other than low oxygen diffusivity, but low oxygen diffusivity is nevertheless a desirable characteristic, as the bond coat could provide some additional component protection, particularly in the case where cracks in the coating system provide a direct path from the environment to the bond coat interface. We have therefore performed similar kMC simulations of oxygen diffusion in this material.

Self-Diffusion of small Ag and Ni islands on Ag(111) and Ni(111) using the self-learning kinetic Monte Carlo method

NASA Astrophysics Data System (ADS)

Islamuddin Shah, Syed; Nandipati, Giridhar; Kara, Abdelkader; Rahman, Talat S.

2012-02-01

We have applied a modified Self-Learning Kinetic Monte Carlo (SLKMC) method [1] to examine the self-diffusion of small Ag and Ni islands, containing up to 10 atom, on the (111) surface of the respective metal. The pattern recognition scheme in this new SLKMC method allows occupancy of the fcc, hcp and top sites on the fcc(111) surface and employs them to identify the local neighborhood around a central atom. Molecular static calculations with semi empirical interatomic potential and reliable techniques for saddle point search revealed several new diffusion mechanisms that contribute to the diffusion of small islands. For comparison we have also evaluated the diffusion characteristics of Cu clusters on Cu(111) and compared results with previous findings [2]. Our results show a linear increase in effective energy barriers scaling almost as 0.043, 0.051 and 0.064 eV/atom for the Cu/Cu(111), Ag/Ag(111), and Ni/Ni(111) systems, respectively. For all three systems, diffusion of small islands proceeds mainly through concerted motion, although several multiple and single atom processes also contribute. [1] Oleg Trushin et al. Phys. Rev. B 72, 115401 (2005) [2] Altaf Karim et al. Phys. Rev. B 73, 165411 (2006)

New Quantum Diffusion Monte Carlo Method for strong field time dependent problems

NASA Astrophysics Data System (ADS)

Kalinski, Matt

2017-04-01

We have recently formulated the Quantum Diffusion Quantum Monte Carlo (QDMC) method for the solution of the time-dependent Schrödinger equation when it is equivalent to the reaction-diffusion system coupled by the highly nonlinear potentials of the type of Shay. Here we formulate a new Time Dependent QDMC method free of the nonlinearities described by the constant stochastic process of the coupled diffusion with transmutation. As before two kinds of diffusing particles (color walkers) are considered but which can further also transmute one into the other. Each of the species undergoes the hypothetical Einstein random walk progression with transmutation. The progressed particles transmute into the particles of the other kind before contributing to or annihilating the other particles density. This fully emulates the Time Dependent Schrödinger equation for any number of quantum particles. The negative sign of the real and the imaginary parts of the wave function is handled by the ``spinor'' densities carrying the sign as the degree of freedom. We apply the method for the exact time-dependent observation of our discovered two-electron Langmuir configurations in the magnetic and circularly polarized fields.

Self-learning kinetic Monte Carlo simulations of Al diffusion in Mg

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nandipati, Giridhar; Govind, Niranjan; Andersen, Amity

2016-03-16

Atomistic on-lattice self-learning kinetic Monte Carlo (SLKMC) method was used to examine the vacancy-mediated diffusion of an Al atom in pure hcp Mg. Local atomic environment dependent activation barriers for vacancy-atom exchange processes were calculated on-the-fly using climbing image nudged-elastic band method (CI-NEB) and using a Mg-Al binary modified embedded-atom method (MEAM) interatomic potential. Diffusivities of vacancy and Al atom in pure Mg were obtained from SLKMC simulations and are compared with values available in the literature that are obtained from experiments and first-principle calculations. Al Diffusivities obtained from SLKMC simulations are lower, due to larger activation barriers and lowermore » diffusivity prefactors, than those available in the literature but have same order of magnitude. We present all vacancy-Mg and vacancy-Al atom exchange processes and their activation barriers that were identified in SLKMC simulations. We will describe a simple mapping scheme to map a hcp lattice on to a simple cubic lattice that would enable hcp lattices to be simulated in an on-lattice KMC framework. We also present the pattern recognition scheme used in SLKMC simulations.« less

Self-Learning Off-Lattice Kinetic Monte Carlo method as applied to growth on metal surfaces

NASA Astrophysics Data System (ADS)

Trushin, Oleg; Kara, Abdelkader; Rahman, Talat

2007-03-01

We propose a new development in the Self-Learning Kinetic Monte Carlo (SLKMC) method with the goal of improving the accuracy with which atomic mechanisms controlling diffusive processes on metal surfaces may be identified. This is important for diffusion of small clusters (2 - 20 atoms) in which atoms may occupy Off-Lattice positions. Such a procedure is also necessary for consideration of heteroepitaxial growth. The new technique combines an earlier version of SLKMC [1] with the inclusion of off-lattice occupancy. This allows us to include arbitrary positions of adatoms in the modeling and makes the simulations more realistic and reliable. We have tested this new approach for the case of the diffusion of small 2D Cu clusters diffusion on Cu(111) and found good performance and satisfactory agreement with results obtained from previous version of SLKMC. The new method also helped reveal a novel atomic mechanism contributing to cluster migration. We have also applied this method to study the diffusion of Cu clusters on Ag(111), and find that Cu atoms generally prefer to occupy off-lattice sites. [1] O. Trushin, A. Kara, A. Karim, T.S. Rahman Phys. Rev B 2005

Solar Wind Implantation into Lunar Regolith II: Monte Carlo Simulations of Hydrogen Retention in a Surface with Defects and the Hydrogen (H, H2) Exosphere

NASA Technical Reports Server (NTRS)

Tucker, O. J.; Farrell, W. M.; Killen, R. M.; Hurley, D. M.

2018-01-01

Recently, the near-infrared observations of the OH veneer on the lunar surface by the Moon Mineralogy Mapper (M3) have been refined to constrain the OH content to 500-750 parts per million (ppm). The observations indicate diurnal variations in OH up to 200 ppm possibly linked to warmer surface temperatures at low latitude. We examine the M3 observations using a statistical mechanics approach to model the diffusion of implanted H in the lunar regolith. We present results from Monte Carlo simulations of the diffusion of implanted solar wind H atoms and the subsequently derived H and H2 exospheres.

Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure

NASA Astrophysics Data System (ADS)

Wang, Henry; Ma, Yunzhi; Pratx, Guillem; Xing, Lei

2011-09-01

Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed. This work was presented in part at the 2010 Annual Meeting of the American Association of Physicists in Medicine (AAPM), Philadelphia, PA.

Dynamical processes and epidemic threshold on nonlinear coupled multiplex networks

NASA Astrophysics Data System (ADS)

Gao, Chao; Tang, Shaoting; Li, Weihua; Yang, Yaqian; Zheng, Zhiming

2018-04-01

Recently, the interplay between epidemic spreading and awareness diffusion has aroused the interest of many researchers, who have studied models mainly based on linear coupling relations between information and epidemic layers. However, in real-world networks the relation between two layers may be closely correlated with the property of individual nodes and exhibits nonlinear dynamical features. Here we propose a nonlinear coupled information-epidemic model (I-E model) and present a comprehensive analysis in a more generalized scenario where the upload rate differs from node to node, deletion rate varies between susceptible and infected states, and infection rate changes between unaware and aware states. In particular, we develop a theoretical framework of the intra- and inter-layer dynamical processes with a microscopic Markov chain approach (MMCA), and derive an analytic epidemic threshold. Our results suggest that the change of upload and deletion rate has little effect on the diffusion dynamics in the epidemic layer.

Shear wave elastography diagnosis of the diffuse sclerosing variant of papillary thyroid carcinoma: A case report.

PubMed

Xue, Nianyu; Xu, Youfeng; Huang, Pintong; Zhang, Shengmin; Wang, Hongwei; Yu, Fei

2016-08-01

The present study aimed to report the shear wave elastography (SWE) findings in a patient with the diffuse sclerosing variant of papillary thyroid carcinoma (DSVPTC). Since patients with DSVPTC may present with typical clinicopathological features and initially appear to have Hashimoto's thyroiditis, a thorough clinical evaluation and an early diagnosis are important. A 20-year-old female patient presented with a 1-month history of a neck mass and sore throat. Conventional ultrasound and SWE were performed using an AIXPLORER system with 14-5 MHz linear transducer. The patient had undergone total thyroidectomy and bilateral neck lymph node dissection, and an intraoperative pathology consultation to confirm the malignancy of lymph node metastasis. Pathological diagnosis was DSVPTC in both lobes, with lymph node metastases in the bilateral neck. The clinical presentation and serological findings were all indicative of Hashimoto's thyroiditis. Thyroid ultrasonography revealed diffuse enlargement of the both lobes, heterogenous echogenicity without mass formation, diffuse scattered microcalcifications and poor vascularization. SWE revealed stiff values of the thyroid: The mean stiffness was 99.7 kpa, the minimum stiffness was 59.1 kpa and the maximum stiffness was 180.1 kpa. The maximum stiffness of the DSVPTC (180.1 kpa) was higher compared with the diagnostic criteria of malignant thyroid nodules (65 kPa). SWE may be considered as a novel and valuable method to diagnose DSVPC.

Shear wave elastography diagnosis of the diffuse sclerosing variant of papillary thyroid carcinoma: A case report

PubMed Central

Xue, Nianyu; Xu, Youfeng; Huang, Pintong; Zhang, Shengmin; Wang, Hongwei; Yu, Fei

2016-01-01

The present study aimed to report the shear wave elastography (SWE) findings in a patient with the diffuse sclerosing variant of papillary thyroid carcinoma (DSVPTC). Since patients with DSVPTC may present with typical clinicopathological features and initially appear to have Hashimoto's thyroiditis, a thorough clinical evaluation and an early diagnosis are important. A 20-year-old female patient presented with a 1-month history of a neck mass and sore throat. Conventional ultrasound and SWE were performed using an AIXPLORER system with 14-5 MHz linear transducer. The patient had undergone total thyroidectomy and bilateral neck lymph node dissection, and an intraoperative pathology consultation to confirm the malignancy of lymph node metastasis. Pathological diagnosis was DSVPTC in both lobes, with lymph node metastases in the bilateral neck. The clinical presentation and serological findings were all indicative of Hashimoto's thyroiditis. Thyroid ultrasonography revealed diffuse enlargement of the both lobes, heterogenous echogenicity without mass formation, diffuse scattered microcalcifications and poor vascularization. SWE revealed stiff values of the thyroid: The mean stiffness was 99.7 kpa, the minimum stiffness was 59.1 kpa and the maximum stiffness was 180.1 kpa. The maximum stiffness of the DSVPTC (180.1 kpa) was higher compared with the diagnostic criteria of malignant thyroid nodules (65 kPa). SWE may be considered as a novel and valuable method to diagnose DSVPC. PMID:27446574

Diffusion of oxygen interstitials in UO2+x using kinetic Monte Carlo simulations: Role of O/M ratio and sensitivity analysis

NASA Astrophysics Data System (ADS)

Behera, Rakesh K.; Watanabe, Taku; Andersson, David A.; Uberuaga, Blas P.; Deo, Chaitanya S.

2016-04-01

Oxygen interstitials in UO2+x significantly affect the thermophysical properties and microstructural evolution of the oxide nuclear fuel. In hyperstoichiometric Urania (UO2+x), these oxygen interstitials form different types of defect clusters, which have different migration behavior. In this study we have used kinetic Monte Carlo (kMC) to evaluate diffusivities of oxygen interstitials accounting for mono- and di-interstitial clusters. Our results indicate that the predicted diffusivities increase significantly at higher non-stoichiometry (x > 0.01) for di-interstitial clusters compared to a mono-interstitial only model. The diffusivities calculated at higher temperatures compare better with experimental values than at lower temperatures (< 973 K). We have discussed the resulting activation energies achieved for diffusion with all the mono- and di-interstitial models. We have carefully performed sensitivity analysis to estimate the effect of input di-interstitial binding energies on the predicted diffusivities and activation energies. While this article only discusses mono- and di-interstitials in evaluating oxygen diffusion response in UO2+x, future improvements to the model will primarily focus on including energetic definitions of larger stable interstitial clusters reported in the literature. The addition of larger clusters to the kMC model is expected to improve the comparison of oxygen transport in UO2+x with experiment.

Full Configuration Interaction Quantum Monte Carlo and Diffusion Monte Carlo: A Comparative Study of the 3D Homogeneous Electron Gas

NASA Astrophysics Data System (ADS)

Shepherd, James J.; López Ríos, Pablo; Needs, Richard J.; Drummond, Neil D.; Mohr, Jennifer A.-F.; Booth, George H.; Grüneis, Andreas; Kresse, Georg; Alavi, Ali

2013-03-01

Full configuration interaction quantum Monte Carlo1 (FCIQMC) and its initiator adaptation2 allow for exact solutions to the Schrödinger equation to be obtained within a finite-basis wavefunction ansatz. In this talk, we explore an application of FCIQMC to the homogeneous electron gas (HEG). In particular we use these exact finite-basis energies to compare with approximate quantum chemical calculations from the VASP code3. After removing the basis set incompleteness error by extrapolation4,5, we compare our energies with state-of-the-art diffusion Monte Carlo calculations from the CASINO package6. Using a combined approach of the two quantum Monte Carlo methods, we present the highest-accuracy thermodynamic (infinite-particle) limit energies for the HEG achieved to date. 1 G. H. Booth, A. Thom, and A. Alavi, J. Chem. Phys. 131, 054106 (2009). 2 D. Cleland, G. H. Booth, and A. Alavi, J. Chem. Phys. 132, 041103 (2010). 3 www.vasp.at (2012). 4 J. J. Shepherd, A. Grüneis, G. H. Booth, G. Kresse, and A. Alavi, Phys. Rev. B. 86, 035111 (2012). 5 J. J. Shepherd, G. H. Booth, and A. Alavi, J. Chem. Phys. 136, 244101 (2012). 6 R. Needs, M. Towler, N. Drummond, and P. L. Ríos, J. Phys.: Condensed Matter 22, 023201 (2010).

Interplay of network dynamics and heterogeneity of ties on spreading dynamics.

PubMed

Ferreri, Luca; Bajardi, Paolo; Giacobini, Mario; Perazzo, Silvia; Venturino, Ezio

2014-07-01

The structure of a network dramatically affects the spreading phenomena unfolding upon it. The contact distribution of the nodes has long been recognized as the key ingredient in influencing the outbreak events. However, limited knowledge is currently available on the role of the weight of the edges on the persistence of a pathogen. At the same time, recent works showed a strong influence of temporal network dynamics on disease spreading. In this work we provide an analytical understanding, corroborated by numerical simulations, about the conditions for infected stable state in weighted networks. In particular, we reveal the role of heterogeneity of edge weights and of the dynamic assignment of weights on the ties in the network in driving the spread of the epidemic. In this context we show that when weights are dynamically assigned to ties in the network, a heterogeneous distribution is able to hamper the diffusion of the disease, contrary to what happens when weights are fixed in time.

Nonlocal birth-death competitive dynamics with volume exclusion

NASA Astrophysics Data System (ADS)

Khalil, Nagi; López, Cristóbal; Hernández-García, Emilio

2017-06-01

A stochastic birth-death competition model for particles with excluded volume is proposed. The particles move, reproduce, and die on a regular lattice. While the death rate is constant, the birth rate is spatially nonlocal and implements inter-particle competition by a dependence on the number of particles within a finite distance. The finite volume of particles is accounted for by fixing an upper value to the number of particles that can occupy a lattice node, compromising births and movements. We derive closed macroscopic equations for the density of particles and spatial correlation at two adjacent sites. Under different conditions, the description is further reduced to a single equation for the particle density that contains three terms: diffusion, a linear death, and a highly nonlinear and nonlocal birth term. Steady-state homogeneous solutions, their stability which reveals spatial pattern formation, and the dynamics of time-dependent homogeneous solutions are discussed and compared, in the one-dimensional case, with numerical simulations of the particle system.

Epidemic Reconstruction in a Phylogenetics Framework: Transmission Trees as Partitions of the Node Set

PubMed Central

Hall, Matthew; Woolhouse, Mark; Rambaut, Andrew

2015-01-01

The use of genetic data to reconstruct the transmission tree of infectious disease epidemics and outbreaks has been the subject of an increasing number of studies, but previous approaches have usually either made assumptions that are not fully compatible with phylogenetic inference, or, where they have based inference on a phylogeny, have employed a procedure that requires this tree to be fixed. At the same time, the coalescent-based models of the pathogen population that are employed in the methods usually used for time-resolved phylogeny reconstruction are a considerable simplification of epidemic process, as they assume that pathogen lineages mix freely. Here, we contribute a new method that is simultaneously a phylogeny reconstruction method for isolates taken from an epidemic, and a procedure for transmission tree reconstruction. We observe that, if one or more samples is taken from each host in an epidemic or outbreak and these are used to build a phylogeny, a transmission tree is equivalent to a partition of the set of nodes of this phylogeny, such that each partition element is a set of nodes that is connected in the full tree and contains all the tips corresponding to samples taken from one and only one host. We then implement a Monte Carlo Markov Chain (MCMC) procedure for simultaneous sampling from the spaces of both trees, utilising a newly-designed set of phylogenetic tree proposals that also respect node partitions. We calculate the posterior probability of these partitioned trees based on a model that acknowledges the population structure of an epidemic by employing an individual-based disease transmission model and a coalescent process taking place within each host. We demonstrate our method, first using simulated data, and then with sequences taken from the H7N7 avian influenza outbreak that occurred in the Netherlands in 2003. We show that it is superior to established coalescent methods for reconstructing the topology and node heights of the phylogeny and performs well for transmission tree reconstruction when the phylogeny is well-resolved by the genetic data, but caution that this will often not be the case in practice and that existing genetic and epidemiological data should be used to configure such analyses whenever possible. This method is available for use by the research community as part of BEAST, one of the most widely-used packages for reconstruction of dated phylogenies. PMID:26717515

Roles of Formin Nodes and Myosin Motor Activity in Mid1p-dependent Contractile-Ring Assembly during Fission Yeast Cytokinesis

PubMed Central

Coffman, Valerie C.; Nile, Aaron H.; Lee, I-Ju; Liu, Huayang

2009-01-01

Two prevailing models have emerged to explain the mechanism of contractile-ring assembly during cytokinesis in the fission yeast Schizosaccharomyces pombe: the spot/leading cable model and the search, capture, pull, and release (SCPR) model. We tested some of the basic assumptions of the two models. Monte Carlo simulations of the SCPR model require that the formin Cdc12p is present in >30 nodes from which actin filaments are nucleated and captured by myosin-II in neighboring nodes. The force produced by myosin motors pulls the nodes together to form a compact contractile ring. Live microscopy of cells expressing Cdc12p fluorescent fusion proteins shows for the first time that Cdc12p localizes to a broad band of 30–50 dynamic nodes, where actin filaments are nucleated in random directions. The proposed progenitor spot, essential for the spot/leading cable model, usually disappears without nucleating actin filaments. α-Actinin ain1 deletion cells form a normal contractile ring through nodes in the absence of the spot. Myosin motor activity is required to condense the nodes into a contractile ring, based on slower or absent node condensation in myo2-E1 and UCS rng3-65 mutants. Taken together, these data provide strong support for the SCPR model of contractile-ring formation in cytokinesis. PMID:19864459

Development of fast wireless detection system for fixed offshore platform

NASA Astrophysics Data System (ADS)

Li, Zhigang; Yu, Yan; Jiao, Dong; Wang, Jie; Li, Zhirui; Ou, Jinping

2011-04-01

Offshore platforms' security is concerned since in 1950s and 1960s, and in the early 1980s some important specifications and standards are built, and all these provide technical basis of fixed platform design, construction, installation and evaluation. With the condition that more and more platforms are in serving over age, the research about the evaluation and detection technology of offshore platform has been a hotspot, especially underwater detection, and assessment method based on the finite element calculation. For fixed platform structure detection, conventional NDT methods, such as eddy current, magnetic powder, permeate, X-ray and ultrasonic, etc, are generally used. These techniques are more mature, intuitive, but underwater detection needs underwater robot, the necessary supporting tools of auxiliary equipment, and trained professional team, thus resources and cost used are considerable, installation time of test equipment is long. This project presents a new kind of fast wireless detection and damage diagnosis system for fixed offshore platform using wireless sensor networks, that is, wireless sensor nodes can be put quickly on the offshore platform, detect offshore platform structure global status by wireless communication, and then make diagnosis. This system is operated simply, suitable for offshore platform integrity states rapid assessment. The designed system consists in intelligence acquisition equipment and 8 wireless collection nodes, the whole system has 64 collection channels, namely every wireless collection node has eight 16-bit accuracy of A/D channels. Wireless collection node, integrated with vibration sensing unit, embedded low-power micro-processing unit, wireless transceiver unit, large-capacity power unit, and GPS time synchronization unit, can finish the functions such as vibration data collection, initial analysis, data storage, data wireless transmission. Intelligence acquisition equipment, integrated with high-performance computation unit, wireless transceiver unit, mobile power unit and embedded data analysis software, can totally control multi-wireless collection nodes, receive and analyze data, parameter identification. Data is transmitted at the 2.4GHz wireless communication channel, every sensing data channel in charge of data transmission is in a stable frequency band, control channel responsible for the control of power parameters is in a public frequency band. The test is initially conducted for the designed system, experimental results show that the system has good application prospects and practical value with fast arrangement, high sampling rate, high resolution, capacity of low frequency detection.

Learnable Models for Information Diffusion and its Associated User Behavior in Micro-blogosphere

DTIC Science & Technology

2012-08-30

According to the work of Even-Dar and Shapira (2007), we recall the definition of the ba- sic voter model on network G. In the model, each node of G...reason as follows. We started with the K distinct initial nodes and all the other nodes were neutral in the beginning. Recall that we set the average time... memory , running under Linux. Learning to predict opinion share and detect anti-majority opinionists in social networks 29 7 Conclusion Unlike the popular

Monte Carlo based method for fluorescence tomographic imaging with lifetime multiplexing using time gates

PubMed Central

Chen, Jin; Venugopal, Vivek; Intes, Xavier

2011-01-01

Time-resolved fluorescence optical tomography allows 3-dimensional localization of multiple fluorophores based on lifetime contrast while providing a unique data set for improved resolution. However, to employ the full fluorescence time measurements, a light propagation model that accurately simulates weakly diffused and multiple scattered photons is required. In this article, we derive a computationally efficient Monte Carlo based method to compute time-gated fluorescence Jacobians for the simultaneous imaging of two fluorophores with lifetime contrast. The Monte Carlo based formulation is validated on a synthetic murine model simulating the uptake in the kidneys of two distinct fluorophores with lifetime contrast. Experimentally, the method is validated using capillaries filled with 2.5nmol of ICG and IRDye™800CW respectively embedded in a diffuse media mimicking the average optical properties of mice. Combining multiple time gates in one inverse problem allows the simultaneous reconstruction of multiple fluorophores with increased resolution and minimal crosstalk using the proposed formulation. PMID:21483610

Auxiliary field diffusion Monte Carlo calculations of light and medium-mass nuclei with local chiral interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lonardoni, D.; Gandolfi, S.; Lynn, J. E.

Quantum Monte Carlo methods have recently been employed to study properties of nuclei and infinite matter using local chiral effective-field-theory interactions. In this paper, we present a detailed description of the auxiliary field diffusion Monte Carlo algorithm for nuclei in combination with local chiral two- and three-nucleon interactions up to next-to-next-to-leading order. We show results for the binding energy, charge radius, charge form factor, and Coulomb sum rule in nuclei withmore » $$3{\\le}A{\\le}16$$. Particular attention is devoted to the effect of different operator structures in the three-body force for different cutoffs. Finally, the outcomes suggest that local chiral interactions fit to few-body observables give a very good description of the ground-state properties of nuclei up to $$^{16}\\mathrm{O}$$, with the exception of one fit for the softer cutoff which predicts overbinding in larger nuclei.« less

Auxiliary field diffusion Monte Carlo calculations of light and medium-mass nuclei with local chiral interactions

DOE PAGES

Lonardoni, D.; Gandolfi, S.; Lynn, J. E.; ...

2018-04-24

Quantum Monte Carlo methods have recently been employed to study properties of nuclei and infinite matter using local chiral effective-field-theory interactions. In this paper, we present a detailed description of the auxiliary field diffusion Monte Carlo algorithm for nuclei in combination with local chiral two- and three-nucleon interactions up to next-to-next-to-leading order. We show results for the binding energy, charge radius, charge form factor, and Coulomb sum rule in nuclei withmore » $$3{\\le}A{\\le}16$$. Particular attention is devoted to the effect of different operator structures in the three-body force for different cutoffs. Finally, the outcomes suggest that local chiral interactions fit to few-body observables give a very good description of the ground-state properties of nuclei up to $$^{16}\\mathrm{O}$$, with the exception of one fit for the softer cutoff which predicts overbinding in larger nuclei.« less

Kinetic Monte Carlo Simulation of Oxygen Diffusion in Ytterbium Disilicate

NASA Technical Reports Server (NTRS)

Good, Brian S.

2015-01-01

Silicon-based ceramic components for next-generation jet turbine engines offer potential weight savings, as well as higher operating temperatures, both of which lead to increased efficiency and lower fuel costs. Silicon carbide (SiC), in particular, offers low density, good strength at high temperatures, and good oxidation resistance in dry air. However, reaction of SiC with high-temperature water vapor, as found in the hot section of jet turbine engines in operation, can cause rapid surface recession, which limits the lifetime of such components. Environmental Barrier Coatings (EBCs) are therefore needed if long component lifetime is to be achieved. Rare earth silicates such as Yb2Si2O7 and Yb2SiO5 have been proposed for such applications; in an effort to better understand diffusion in such materials, we have performed kinetic Monte Carlo (kMC) simulations of oxygen diffusion in Ytterbium disilicate, Yb2- Si2O7. The diffusive process is assumed to take place via the thermally activated hopping of oxygen atoms among oxygen vacancy sites or among interstitial sites. Migration barrier energies are computed using density functional theory (DFT).

Monte Carlo random walk simulation of electron transport in confined porous TiO{sub 2} as a promising candidate for photo-electrode of nano-crystalline solar cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Javadi, M.; Abdi, Y., E-mail: y.abdi@ut.ac.ir

2015-08-14

Monte Carlo continuous time random walk simulation is used to study the effects of confinement on electron transport, in porous TiO{sub 2}. In this work, we have introduced a columnar structure instead of the thick layer of porous TiO{sub 2} used as anode in conventional dye solar cells. Our simulation results show that electron diffusion coefficient in the proposed columnar structure is significantly higher than the diffusion coefficient in the conventional structure. It is shown that electron diffusion in the columnar structure depends both on the cross section area of the columns and the porosity of the structure. Also, wemore » demonstrate that such enhanced electron diffusion can be realized in the columnar photo-electrodes with a cross sectional area of ∼1 μm{sup 2} and porosity of 55%, by a simple and low cost fabrication process. Our results open up a promising approach to achieve solar cells with higher efficiencies by engineering the photo-electrode structure.« less

Monte Carlo random walk simulation of electron transport in confined porous TiO2 as a promising candidate for photo-electrode of nano-crystalline solar cells

NASA Astrophysics Data System (ADS)

Javadi, M.; Abdi, Y.

2015-08-01

Monte Carlo continuous time random walk simulation is used to study the effects of confinement on electron transport, in porous TiO2. In this work, we have introduced a columnar structure instead of the thick layer of porous TiO2 used as anode in conventional dye solar cells. Our simulation results show that electron diffusion coefficient in the proposed columnar structure is significantly higher than the diffusion coefficient in the conventional structure. It is shown that electron diffusion in the columnar structure depends both on the cross section area of the columns and the porosity of the structure. Also, we demonstrate that such enhanced electron diffusion can be realized in the columnar photo-electrodes with a cross sectional area of ˜1 μm2 and porosity of 55%, by a simple and low cost fabrication process. Our results open up a promising approach to achieve solar cells with higher efficiencies by engineering the photo-electrode structure.

Estimation of the Thermal Process in the Honeycomb Panel by a Monte Carlo Method

NASA Astrophysics Data System (ADS)

Gusev, S. A.; Nikolaev, V. N.

2018-01-01

A new Monte Carlo method for estimating the thermal state of the heat insulation containing honeycomb panels is proposed in the paper. The heat transfer in the honeycomb panel is described by a boundary value problem for a parabolic equation with discontinuous diffusion coefficient and boundary conditions of the third kind. To obtain an approximate solution, it is proposed to use the smoothing of the diffusion coefficient. After that, the obtained problem is solved on the basis of the probability representation. The probability representation is the expectation of the functional of the diffusion process corresponding to the boundary value problem. The process of solving the problem is reduced to numerical statistical modelling of a large number of trajectories of the diffusion process corresponding to the parabolic problem. It was used earlier the Euler method for this object, but that requires a large computational effort. In this paper the method is modified by using combination of the Euler and the random walk on moving spheres methods. The new approach allows us to significantly reduce the computation costs.

A theoretical framework to predict the most likely ion path in particle imaging.

PubMed

Collins-Fekete, Charles-Antoine; Volz, Lennart; Portillo, Stephen K N; Beaulieu, Luc; Seco, Joao

2017-03-07

In this work, a generic rigorous Bayesian formalism is introduced to predict the most likely path of any ion crossing a medium between two detection points. The path is predicted based on a combination of the particle scattering in the material and measurements of its initial and final position, direction and energy. The path estimate's precision is compared to the Monte Carlo simulated path. Every ion from hydrogen to carbon is simulated in two scenarios, (1) where the range is fixed and (2) where the initial velocity is fixed. In the scenario where the range is kept constant, the maximal root-mean-square error between the estimated path and the Monte Carlo path drops significantly between the proton path estimate (0.50 mm) and the helium path estimate (0.18 mm), but less so up to the carbon path estimate (0.09 mm). However, this scenario is identified as the configuration that maximizes the dose while minimizing the path resolution. In the scenario where the initial velocity is fixed, the maximal root-mean-square error between the estimated path and the Monte Carlo path drops significantly between the proton path estimate (0.29 mm) and the helium path estimate (0.09 mm) but increases for heavier ions up to carbon (0.12 mm). As a result, helium is found to be the particle with the most accurate path estimate for the lowest dose, potentially leading to tomographic images of higher spatial resolution.

CT of chronic infiltrative lung disease: Prevalence of mediastinal lymphadenopathy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niimi, Hiroshi; Kang, Eun-Young; Kwong, S.

1996-03-01

Our goal was to determine the prevalence of mediastinal lymph node enlargement at CT in patients with diffuse infiltrative lung disease. The study was retrospective and included 175 consecutive patients with diffuse infiltrative lung diseases. Diagnoses included idiopathic pulmonary fibrosis (IPF) (n = 61), usual interstitial pneumonia associated with collagen vascular disease (CVD) (n = 20), idiopathic bronchiolitis obliterans organizing pneumonia (BOOP) (n = 22), extrinsic allergic alveolitis (EAA) (n = 17), and sarcoidosis (n = 55). Fifty-eight age-matched patients with CT of the chest performed for unrelated conditions served as controls. The presence, number, and sites of enlarged nodesmore » (short axis {ge}10 mm in diameter) were recorded. Enlarged mediastinal nodes were present in 118 of 175 patients (67%) with infiltrative lung disease and 3 of 58 controls (5%) (p < 0.001). The prevalence of enlarged nodes was 84% (46 of 55) in sarcoidosis, 67% (41 of 61) in IPF, 70% (14 of 20) in CVD, 53% (9 of 17) in EAA, and 36% (8 of 22) in BOOP. The mean number of enlarged nodes was higher in sarcoidosis (mean 3.2) than in the other infiltrative diseases (mean 1.2) (p < 0.001). Enlarged nodes were most commonly present in station 10R, followed by 7, 4R, and 5. Patients with infiltrative lung disease frequently have enlarged mediastinal lymph nodes. However, in diseases other than sarcoid, usually only one or two nodes are enlarged and their maximal short axis diameter is <15 mm. 11 refs., 2 figs., 1 tab.« less

Liquid Water from First Principles: Validation of Different Sampling Approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mundy, C J; Kuo, W; Siepmann, J

2004-05-20

A series of first principles molecular dynamics and Monte Carlo simulations were carried out for liquid water to assess the validity and reproducibility of different sampling approaches. These simulations include Car-Parrinello molecular dynamics simulations using the program CPMD with different values of the fictitious electron mass in the microcanonical and canonical ensembles, Born-Oppenheimer molecular dynamics using the programs CPMD and CP2K in the microcanonical ensemble, and Metropolis Monte Carlo using CP2K in the canonical ensemble. With the exception of one simulation for 128 water molecules, all other simulations were carried out for systems consisting of 64 molecules. It is foundmore » that the structural and thermodynamic properties of these simulations are in excellent agreement with each other as long as adiabatic sampling is maintained in the Car-Parrinello molecular dynamics simulations either by choosing a sufficiently small fictitious mass in the microcanonical ensemble or by Nos{acute e}-Hoover thermostats in the canonical ensemble. Using the Becke-Lee-Yang-Parr exchange and correlation energy functionals and norm-conserving Troullier-Martins or Goedecker-Teter-Hutter pseudopotentials, simulations at a fixed density of 1.0 g/cm{sup 3} and a temperature close to 315 K yield a height of the first peak in the oxygen-oxygen radial distribution function of about 3.0, a classical constant-volume heat capacity of about 70 J K{sup -1} mol{sup -1}, and a self-diffusion constant of about 0.1 Angstroms{sup 2}/ps.« less

Multilevel Sequential2 Monte Carlo for Bayesian inverse problems

NASA Astrophysics Data System (ADS)

Latz, Jonas; Papaioannou, Iason; Ullmann, Elisabeth

2018-09-01

The identification of parameters in mathematical models using noisy observations is a common task in uncertainty quantification. We employ the framework of Bayesian inversion: we combine monitoring and observational data with prior information to estimate the posterior distribution of a parameter. Specifically, we are interested in the distribution of a diffusion coefficient of an elliptic PDE. In this setting, the sample space is high-dimensional, and each sample of the PDE solution is expensive. To address these issues we propose and analyse a novel Sequential Monte Carlo (SMC) sampler for the approximation of the posterior distribution. Classical, single-level SMC constructs a sequence of measures, starting with the prior distribution, and finishing with the posterior distribution. The intermediate measures arise from a tempering of the likelihood, or, equivalently, a rescaling of the noise. The resolution of the PDE discretisation is fixed. In contrast, our estimator employs a hierarchy of PDE discretisations to decrease the computational cost. We construct a sequence of intermediate measures by decreasing the temperature or by increasing the discretisation level at the same time. This idea builds on and generalises the multi-resolution sampler proposed in P.S. Koutsourelakis (2009) [33] where a bridging scheme is used to transfer samples from coarse to fine discretisation levels. Importantly, our choice between tempering and bridging is fully adaptive. We present numerical experiments in 2D space, comparing our estimator to single-level SMC and the multi-resolution sampler.

Distributed Dynamic Host Configuration Protocol (D2HCP)

PubMed Central

Villalba, Luis Javier García; Matesanz, Julián García; Orozco, Ana Lucila Sandoval; Díaz, José Duván Márquez

2011-01-01

Mobile Ad Hoc Networks (MANETs) are multihop wireless networks of mobile nodes without any fixed or preexisting infrastructure. The topology of these networks can change randomly due to the unpredictable mobility of nodes and their propagation characteristics. In most networks, including MANETs, each node needs a unique identifier to communicate. This work presents a distributed protocol for dynamic node IP address assignment in MANETs. Nodes of a MANET synchronize from time to time to maintain a record of IP address assignments in the entire network and detect any IP address leaks. The proposed stateful autoconfiguration scheme uses the OLSR proactive routing protocol for synchronization and guarantees unique IP addresses under a variety of network conditions, including message losses and network partitioning. Simulation results show that the protocol incurs low latency and communication overhead for IP address assignment. PMID:22163856

Distributed Dynamic Host Configuration Protocol (D2HCP).

PubMed

Villalba, Luis Javier García; Matesanz, Julián García; Orozco, Ana Lucila Sandoval; Díaz, José Duván Márquez

2011-01-01

Mobile Ad Hoc Networks (MANETs) are multihop wireless networks of mobile nodes without any fixed or preexisting infrastructure. The topology of these networks can change randomly due to the unpredictable mobility of nodes and their propagation characteristics. In most networks, including MANETs, each node needs a unique identifier to communicate. This work presents a distributed protocol for dynamic node IP address assignment in MANETs. Nodes of a MANET synchronize from time to time to maintain a record of IP address assignments in the entire network and detect any IP address leaks. The proposed stateful autoconfiguration scheme uses the OLSR proactive routing protocol for synchronization and guarantees unique IP addresses under a variety of network conditions, including message losses and network partitioning. Simulation results show that the protocol incurs low latency and communication overhead for IP address assignment.

Pressure recovery performance of conical diffusers at high subsonic Mach numbers

NASA Technical Reports Server (NTRS)

Dolan, F. X.; Runstadler, P. W., Jr.

1973-01-01

The pressure recovery performance of conical diffusers has been measured for a wide range of geometries and inlet flow conditions. The approximate level and location (in terms of diffuser geometry of optimum performance were determined. Throat Mach numbers from low subsonic (m sub t equals 0.2) through choking (m sub t equals 1.0) were investigated in combination with throat blockage from 0.03 to 0.12. For fixed Mach number, performance was measured over a fourfold range of inlet Reynolds number. Maps of pressure recovery are presented as a function of diffuser geometry for fixed sets of inlet conditions. The influence of inlet blockage, throat Mach number, and inlet Reynolds number is discussed.

Dynamics of influence on hierarchical structures

NASA Astrophysics Data System (ADS)

Fotouhi, Babak; Rabbat, Michael G.

2013-08-01

Dichotomous spin dynamics on a pyramidal hierarchical structure (the Bethe lattice) are studied. The system embodies a number of classes, where a class comprises nodes that are equidistant from the root (head node). Weighted links exist between nodes from the same and different classes. The spin (hereafter state) of the head node is fixed. We solve for the dynamics of the system for different boundary conditions. We find necessary conditions so that the classes eventually repudiate or acquiesce in the state imposed by the head node. The results indicate that to reach unanimity across the hierarchy, it suffices that the bottommost class adopts the same state as the head node. Then the rest of the hierarchy will inevitably comply. This also sheds light on the importance of mass media as a means of synchronization between the topmost and bottommost classes. Surprisingly, in the case of discord between the head node and the bottommost classes, the average state over all nodes inclines towards that of the bottommost class regardless of the link weights and intraclass configurations. Hence the role of the bottommost class is signified.

Characterization of metal adsorption kinetic properties in batch and fixed-bed reactors.

PubMed

Chen, J Paul; Wang, Lin

2004-01-01

Copper adsorption kinetic properties in batch and fixed-bed reactors were studied in this paper. The isothermal adsorption experiments showed that the copper adsorption capacity of a granular activated carbon (Filtrasorb 200) increased when ionic strength was higher. The presence of EDTA diminished the adsorption. An intraparticle diffusion model and a fixed-bed model were successfully used to describe the batch kinetic and fixed-bed operation behaviors. The kinetics became faster when the solution pH was not controlled, implying that the surface precipitation caused some metal uptake. The external mass transfer coefficient, the diffusivity and the dispersion coefficient were obtained from the modeling. It was found that both external mass transfer and dispersion coefficients increased when the flow rate was higher. Finally effects of kinetic parameters on simulation of fixed-bed operation were conducted.

Monte Carlo Modeling of VLWIR HgCdTe Interdigitated Pixel Response

NASA Astrophysics Data System (ADS)

D'Souza, A. I.; Stapelbroek, M. G.; Wijewarnasuriya, P. S.

2010-07-01

Increasing very long-wave infrared (VLWIR, λ c ≈ 15 μm) pixel operability was approached by subdividing each pixel into four interdigitated subpixels. High response is maintained across the pixel, even if one or two interdigitated subpixels are deselected (turned off), because interdigitation provides that the preponderance of minority carriers photogenerated in the pixel are collected by the selected subpixels. Monte Carlo modeling of the photoresponse of the interdigitated subpixel simulates minority-carrier diffusion from carrier creation to recombination. Each carrier generated at an appropriately weighted random location is assigned an exponentially distributed random lifetime τ i, where < τ i> is the bulk minority-carrier lifetime. The minority carrier is allowed to diffuse for a short time d τ, and the fate of the carrier is decided from its present position and the boundary conditions, i.e., whether the carrier is absorbed in a junction, recombined at a surface, reflected from a surface, or recombined in the bulk because it lived for its designated lifetime. If nothing happens, the process is then repeated until one of the boundary conditions is attained. The next step is to go on to the next carrier and repeat the procedure for all the launches of minority carriers. For each minority carrier launched, the original location and boundary condition at fatality are recorded. An example of the results from Monte Carlo modeling is that, for a 20- μm diffusion length, the calculated quantum efficiency (QE) changed from 85% with no subpixels deselected, to 78% with one subpixel deselected, 67% with two subpixels deselected, and 48% with three subpixels deselected. Demonstration of the interdigitated pixel concept and verification of the Monte Carlo modeling utilized λ c(60 K) ≈ 15 μm HgCdTe pixels in a 96 × 96 array format. The measured collection efficiency for one, two, and three subelements selected, divided by the collection efficiency for all four subelements selected, matched that calculated using Monte Carlo modeling.

Competitive adsorption of furfural and phenolic compounds onto activated carbon in fixed bed column.

PubMed

Sulaymon, Abbas H; Ahmed, Kawther W

2008-01-15

For a multicomponent competitive adsorption of furfural and phenolic compounds, a mathematical model was builtto describe the mass transfer kinetics in a fixed bed column with activated carbon. The effects of competitive adsorption equilibrium constant, axial dispersion, external mass transfer, and intraparticle diffusion resistance on the breakthrough curve were studied for weakly adsorbed compound (furfural) and strongly adsorbed compounds (parachlorophenol and phenol). Experiments were carried out to remove the furfural and phenolic compound from aqueous solution. The equilibrium data and intraparticle diffusion coefficients obtained from separate experiments in a batch adsorber, by fitting the experimental data with theoretical model. The results show that the mathematical model includes external mass transfer and pore diffusion using nonlinear isotherms and provides a good description of the adsorption process for furfural and phenolic compounds in a fixed bed adsorber.

Adaptive fixed-time control for cluster synchronisation of coupled complex networks with uncertain disturbances

NASA Astrophysics Data System (ADS)

Jiang, Shengqin; Lu, Xiaobo; Cai, Guoliang; Cai, Shuiming

2017-12-01

This paper focuses on the cluster synchronisation problem of coupled complex networks with uncertain disturbances under an adaptive fixed-time control strategy. To begin with, complex dynamical networks with community structure which are subject to uncertain disturbances are taken into account. Then, a novel adaptive control strategy combined with fixed-time techniques is proposed to guarantee the nodes in the communities to desired states in a settling time. In addition, the stability of complex error systems is theoretically proved based on Lyapunov stability theorem. At last, two examples are presented to verify the effectiveness of the proposed adaptive fixed-time control.

Teaching the Growth, Ripening, and Agglomeration of Nanostructures in Computer Experiments

ERIC Educational Resources Information Center

Meyburg, Jan Philipp; Diesing, Detlef

2017-01-01

This article describes the implementation and application of a metal deposition and surface diffusion Monte Carlo simulation in a physical chemistry lab course. Here the self-diffusion of Ag atoms on a Ag(111) surface is modeled and compared to published experimental results. Both the thin-film homoepitaxial growth during adatom deposition onto a…

Electron and ion acceleration in relativistic shocks with applications to GRB afterglows

NASA Astrophysics Data System (ADS)

Warren, Donald C.; Ellison, Donald C.; Bykov, Andrei M.; Lee, Shiu-Hang

2015-09-01

We have modelled the simultaneous first-order Fermi shock acceleration of protons, electrons, and helium nuclei by relativistic shocks. By parametrizing the particle diffusion, our steady-state Monte Carlo simulation allows us to follow particles from particle injection at non-relativistic thermal energies to above PeV energies, including the non-linear smoothing of the shock structure due to cosmic ray (CR) backpressure. We observe the mass-to-charge (A/Z) enhancement effect believed to occur in efficient Fermi acceleration in non-relativistic shocks and we parametrize the transfer of ion energy to electrons seen in particle-in-cell (PIC) simulations. For a given set of environmental and model parameters, the Monte Carlo simulation determines the absolute normalization of the particle distributions and the resulting synchrotron, inverse Compton, and pion-decay emission in a largely self-consistent manner. The simulation is flexible and can be readily used with a wide range of parameters typical of γ-ray burst (GRB) afterglows. We describe some preliminary results for photon emission from shocks of different Lorentz factors and outline how the Monte Carlo simulation can be generalized and coupled to hydrodynamic simulations of GRB blast waves. We assume Bohm diffusion for simplicity but emphasize that the non-linear effects we describe stem mainly from an extended shock precursor where higher energy particles diffuse further upstream. Quantitative differences will occur with different diffusion models, particularly for the maximum CR energy and photon emission, but these non-linear effects should be qualitatively similar as long as the scattering mean-free path is an increasing function of momentum.

Kinetic Monte Carlo simulations of electrodeposition: Crossover from continuous to instantaneous homogeneous nucleation within Avrami’s law

NASA Astrophysics Data System (ADS)

Frank, Stefan; Rikvold, Per Arne

2006-06-01

The influence of lateral adsorbate diffusion on the dynamics of the first-order phase transition in a two-dimensional Ising lattice gas with attractive nearest-neighbor interactions is investigated by means of kinetic Monte Carlo simulations. For example, electrochemical underpotential deposition proceeds by this mechanism. One major difference from adsorption in vacuum surface science is that under control of the electrode potential and in the absence of mass-transport limitations, local adsorption equilibrium is approximately established. We analyze our results using the theory of Kolmogorov, Johnson and Mehl, and Avrami (KJMA), which we extend to an exponentially decaying nucleation rate. Such a decay may occur due to a suppression of nucleation around existing clusters in the presence of lateral adsorbate diffusion. Correlation functions prove the existence of such exclusion zones. By comparison with microscopic results for the nucleation rate I and the interface velocity of the growing clusters v, we can show that the KJMA theory yields the correct order of magnitude for Iv2. This is true even though the spatial correlations mediated by diffusion are neglected. The decaying nucleation rate causes a gradual crossover from continuous to instantaneous nucleation, which is complete when the decay of the nucleation rate is very fast on the time scale of the phase transformation. Hence, instantaneous nucleation can be homogeneous, producing negative minima in the two-point correlation functions. We also present in this paper an n-fold way Monte Carlo algorithm for a square lattice gas with adsorption/desorption and lateral diffusion.

Diffusion in confinement: kinetic simulations of self- and collective diffusion behavior of adsorbed gases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abouelnasr, MKF; Smit, B

2012-01-01

The self- and collective-diffusion behaviors of adsorbed methane, helium, and isobutane in zeolite frameworks LTA, MFI, AFI, and SAS were examined at various concentrations using a range of molecular simulation techniques including Molecular Dynamics (MD), Monte Carlo (MC), Bennett-Chandler (BC), and kinetic Monte Carlo (kMC). This paper has three main results. (1) A novel model for the process of adsorbate movement between two large cages was created, allowing the formulation of a mixing rule for the re-crossing coefficient between two cages of unequal loading. The predictions from this mixing rule were found to agree quantitatively with explicit simulations. (2) Amore » new approach to the dynamically corrected Transition State Theory method to analytically calculate self-diffusion properties was developed, explicitly accounting for nanoscale fluctuations in concentration. This approach was demonstrated to quantitatively agree with previous methods, but is uniquely suited to be adapted to a kMC simulation that can simulate the collective-diffusion behavior. (3) While at low and moderate loadings the self- and collective-diffusion behaviors in LTA are observed to coincide, at higher concentrations they diverge. A change in the adsorbate packing scheme was shown to cause this divergence, a trait which is replicated in a kMC simulation that explicitly models this behavior. These phenomena were further investigated for isobutane in zeolite MFI, where MD results showed a separation in self- and collective-diffusion behavior that was reproduced with kMC simulations.« less

Diffusion in confinement: kinetic simulations of self- and collective diffusion behavior of adsorbed gases.

PubMed

Abouelnasr, Mahmoud K F; Smit, Berend

2012-09-07

The self- and collective-diffusion behaviors of adsorbed methane, helium, and isobutane in zeolite frameworks LTA, MFI, AFI, and SAS were examined at various concentrations using a range of molecular simulation techniques including Molecular Dynamics (MD), Monte Carlo (MC), Bennett-Chandler (BC), and kinetic Monte Carlo (kMC). This paper has three main results. (1) A novel model for the process of adsorbate movement between two large cages was created, allowing the formulation of a mixing rule for the re-crossing coefficient between two cages of unequal loading. The predictions from this mixing rule were found to agree quantitatively with explicit simulations. (2) A new approach to the dynamically corrected Transition State Theory method to analytically calculate self-diffusion properties was developed, explicitly accounting for nanoscale fluctuations in concentration. This approach was demonstrated to quantitatively agree with previous methods, but is uniquely suited to be adapted to a kMC simulation that can simulate the collective-diffusion behavior. (3) While at low and moderate loadings the self- and collective-diffusion behaviors in LTA are observed to coincide, at higher concentrations they diverge. A change in the adsorbate packing scheme was shown to cause this divergence, a trait which is replicated in a kMC simulation that explicitly models this behavior. These phenomena were further investigated for isobutane in zeolite MFI, where MD results showed a separation in self- and collective- diffusion behavior that was reproduced with kMC simulations.

A long-term stable power supply μDMFC stack for wireless sensor node applications

NASA Astrophysics Data System (ADS)

Wu, Z. L.; Wang, X. H.; Teng, F.; Li, X. Z.; Wu, X. M.; Liu, L. T.

2013-12-01

A passive, air-breathing 4-cell micro direct methanol fuel cell (μDMFC) stack is presented featured by a fuel delivery structure for a long-term & stable power supply. The fuel is reserved in a T shape tank and diffuses through the porous diffusion layer to the catalyst at anode. The stack has a maximum power output of 110mW with 3M methanol at room temperature and output a stable power even thought 5% fuel is the remained in reservoir. Its performance decreases less than 3% for 100 hours continuous work. As such, it is believed to be more applicable for powering the wireless sensor nodes.

Conformation and Dynamics of a Flexible Sheet in Solvent Media by Monte Carlo Simulations

NASA Astrophysics Data System (ADS)

Pandey, Ras; Anderson, Kelly; Heinz, Hendrik; Farmer, Barry

2005-03-01

Flexibility of the clay sheet is limited even in the ex-foliated state in some solvent media. A coarse grained model is used to investigate dynamics and conformation of a flexible sheet to model such a clay platelet in an effective solvent medium on a cubic lattice of size L^3 with lattice constant a. The undeformed sheet is described by a square lattice of size Ls^2, where, each node of the sheet is represented by the unit cube of the cubic lattice and 2a is the minimum distance between the nearest neighbor nodes to incorporate the excluded volume constraints. Additionally, each node interacts with neighboring nodes and solvent (empty) sites within a range ri. Each node execute their stochastic motion with the Metropolis algorithm subject to bond length fluctuation and excluded volume constraints. Mean square displacements of the center node and that of its center of mass are investigated as a function of time step for a set of these parameters. The radius of gyration (Rg) is also examined concurrently to understand its relaxation. Multi-scale segmental dynamics of the sheet is studied by identifying the power-law dependence in various time regimes. Relaxation of Rg and its dependence of temperature are planned to be discussed.

Inverse Monte Carlo method in a multilayered tissue model for diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Fredriksson, Ingemar; Larsson, Marcus; Strömberg, Tomas

2012-04-01

Model based data analysis of diffuse reflectance spectroscopy data enables the estimation of optical and structural tissue parameters. The aim of this study was to present an inverse Monte Carlo method based on spectra from two source-detector distances (0.4 and 1.2 mm), using a multilayered tissue model. The tissue model variables include geometrical properties, light scattering properties, tissue chromophores such as melanin and hemoglobin, oxygen saturation and average vessel diameter. The method utilizes a small set of presimulated Monte Carlo data for combinations of different levels of epidermal thickness and tissue scattering. The path length distributions in the different layers are stored and the effect of the other parameters is added in the post-processing. The accuracy of the method was evaluated using Monte Carlo simulations of tissue-like models containing discrete blood vessels, evaluating blood tissue fraction and oxygenation. It was also compared to a homogeneous model. The multilayer model performed better than the homogeneous model and all tissue parameters significantly improved spectral fitting. Recorded in vivo spectra were fitted well at both distances, which we previously found was not possible with a homogeneous model. No absolute intensity calibration is needed and the algorithm is fast enough for real-time processing.

AIDS: Secretions and Implications for Nursing Care-Givers.

DTIC Science & Technology

1992-05-06

addition, infected cells may be found in many different organs, often at the same time: the brain, lymph nodes , thymus gland, bone marrow, lungs, skin...symptomatic disease with diffuse non-malignant lymph node hypertrophy. Aside from these symptoms of lymphadenopathy, patients are typically healthy...a person physically and mentally crippled. AIDS dementia complex (ADC) or subacute HIV encephalopathy, primary lymphomas, toxoplasmosis , cryptococcal

Mapping to Irregular Torus Topologies and Other Techniques for Petascale Biomolecular Simulation

PubMed Central

Phillips, James C.; Sun, Yanhua; Jain, Nikhil; Bohm, Eric J.; Kalé, Laxmikant V.

2014-01-01

Currently deployed petascale supercomputers typically use toroidal network topologies in three or more dimensions. While these networks perform well for topology-agnostic codes on a few thousand nodes, leadership machines with 20,000 nodes require topology awareness to avoid network contention for communication-intensive codes. Topology adaptation is complicated by irregular node allocation shapes and holes due to dedicated input/output nodes or hardware failure. In the context of the popular molecular dynamics program NAMD, we present methods for mapping a periodic 3-D grid of fixed-size spatial decomposition domains to 3-D Cray Gemini and 5-D IBM Blue Gene/Q toroidal networks to enable hundred-million atom full machine simulations, and to similarly partition node allocations into compact domains for smaller simulations using multiple-copy algorithms. Additional enabling techniques are discussed and performance is reported for NCSA Blue Waters, ORNL Titan, ANL Mira, TACC Stampede, and NERSC Edison. PMID:25594075

Diffuse X-ray scattering from benzil, C(14)H(10)O(2): analysis via automatic refinement of a Monte Carlo model.

PubMed

Welberry, T R; Goossens, D J; Edwards, A J; David, W I

2001-01-01

A recently developed method for fitting a Monte Carlo computer-simulation model to observed single-crystal diffuse X-ray scattering has been used to study the diffuse scattering in benzil, diphenylethanedione, C(6)H(5)-CO-CO-C(6)H(5). A model involving 13 parameters consisting of 11 intermolecular force constants, a single intramolecular torsional force constant and a local Debye-Waller factor was refined to give an agreement factor, R = [summation operator omega(Delta I)(2)/summation operator omega I(obs)(2)](1/2), of 14.5% for 101,324 data points. The model was purely thermal in nature. The analysis has shown that the diffuse lines, which feature so prominently in the observed diffraction patterns, are due to strong longitudinal displacement correlations. These are transmitted from molecule to molecule via a network of contacts involving hydrogen bonding of an O atom on one molecule and the para H atom of the phenyl ring of a neighbouring molecule. The analysis also allowed the determination of a torsional force constant for rotations about the single bonds in the molecule. This is the first diffuse scattering study in which measurement of such internal molecular torsion forces has been attempted.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Dr. Li; Cui, Xiaohui; Cemerlic, Alma

Ad hoc networks are very helpful in situations when no fixed network infrastructure is available, such as natural disasters and military conflicts. In such a network, all wireless nodes are equal peers simultaneously serving as both senders and routers for other nodes. Therefore, how to route packets through reliable paths becomes a fundamental problems when behaviors of certain nodes deviate from wireless ad hoc routing protocols. We proposed a novel Dirichlet reputation model based on Bayesian inference theory which evaluates reliability of each node in terms of packet delivery. Our system offers a way to predict and select a reliablemore » path through combination of first-hand observation and second-hand reputation reports. We also proposed moving window mechanism which helps to adjust ours responsiveness of our system to changes of node behaviors. We integrated the Dirichlet reputation into routing protocol of wireless ad hoc networks. Our extensive simulation indicates that our proposed reputation system can improve good throughput of the network and reduce negative impacts caused by misbehaving nodes.« less

Monte Carlo Simulations of the Photospheric Emission in Gamma-Ray Bursts

NASA Astrophysics Data System (ADS)

Bégué, D.; Siutsou, I. A.; Vereshchagin, G. V.

2013-04-01

We studied the decoupling of photons from ultra-relativistic spherically symmetric outflows expanding with constant velocity by means of Monte Carlo simulations. For outflows with finite widths we confirm the existence of two regimes: photon-thick and photon-thin, introduced recently by Ruffini et al. (RSV). The probability density function of the last scattering of photons is shown to be very different in these two cases. We also obtained spectra as well as light curves. In the photon-thick case, the time-integrated spectrum is much broader than the Planck function and its shape is well described by the fuzzy photosphere approximation introduced by RSV. In the photon-thin case, we confirm the crucial role of photon diffusion, hence the probability density of decoupling has a maximum near the diffusion radius well below the photosphere. The time-integrated spectrum of the photon-thin case has a Band shape that is produced when the outflow is optically thick and its peak is formed at the diffusion radius.

MONTE CARLO SIMULATIONS OF THE PHOTOSPHERIC EMISSION IN GAMMA-RAY BURSTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Begue, D.; Siutsou, I. A.; Vereshchagin, G. V.

2013-04-20

We studied the decoupling of photons from ultra-relativistic spherically symmetric outflows expanding with constant velocity by means of Monte Carlo simulations. For outflows with finite widths we confirm the existence of two regimes: photon-thick and photon-thin, introduced recently by Ruffini et al. (RSV). The probability density function of the last scattering of photons is shown to be very different in these two cases. We also obtained spectra as well as light curves. In the photon-thick case, the time-integrated spectrum is much broader than the Planck function and its shape is well described by the fuzzy photosphere approximation introduced by RSV.more » In the photon-thin case, we confirm the crucial role of photon diffusion, hence the probability density of decoupling has a maximum near the diffusion radius well below the photosphere. The time-integrated spectrum of the photon-thin case has a Band shape that is produced when the outflow is optically thick and its peak is formed at the diffusion radius.« less

Application of Monte Carlo techniques to transient thermal modeling of cavity radiometers having diffuse-specular surfaces

NASA Technical Reports Server (NTRS)

Mahan, J. R.; Eskin, L. D.

1981-01-01

A viable alternative to the net exchange method of radiative analysis which is equally applicable to diffuse and diffuse-specular enclosures is presented. It is particularly more advantageous to use than the net exchange method in the case of a transient thermal analysis involving conduction and storage of energy as well as radiative exchange. A new quantity, called the distribution factor is defined which replaces the angle factor and the configuration factor. Once obtained, the array of distribution factors for an ensemble of surface elements which define an enclosure permits the instantaneous net radiative heat fluxes to all of the surfaces to be computed directly in terms of the known surface temperatures at that instant. The formulation of the thermal model is described, as is the determination of distribution factors by application of a Monte Carlo analysis. The results show that when fewer than 10,000 packets are emitted, an unsatisfactory approximation for the distribution factors is obtained, but that 10,000 packets is sufficient.

Kinetic Monte Carlo simulation of nanoparticle film formation via nanocolloid drying

NASA Astrophysics Data System (ADS)

Kameya, Yuki

2017-06-01

A kinetic Monte Carlo simulation of nanoparticle film formation via nanocolloid drying is presented. The proposed two-dimensional model addresses the dynamics of nanoparticles in the vertical plane of a drying nanocolloid film. The gas-liquid interface movement due to solvent evaporation was controlled by a time-dependent chemical potential, and the resultant particle dynamics including Brownian diffusion and aggregate growth were calculated. Simulations were performed at various Peclet numbers defined based on the rate ratio of solvent evaporation and nanoparticle diffusion. At high Peclet numbers, nanoparticles accumulated at the top layer of the liquid film and eventually formed a skin layer, causing the formation of a particulate film with a densely packed structure. At low Peclet numbers, enhanced particle diffusion led to significant particle aggregation in the bulk colloid, and the resulting film structure became highly porous. The simulated results showed some typical characteristics of a drying nanocolloid that had been reported experimentally. Finally, the potential of the model as well as the remaining challenges are discussed.

Staging of pelvic lymph nodes in patients with prostate cancer: Usefulness of multiple b value SE-EPI diffusion-weighted imaging on a 3.0 T MR system.

PubMed

Vallini, Valentina; Ortori, Simona; Boraschi, Piero; Manassero, Francesca; Gabelloni, Michela; Faggioni, Lorenzo; Selli, Cesare; Bartolozzi, Carlo

2016-01-01

To evaluate the usefulness of diffusion-weighted imaging (DWI) with a multiple b value SE-EPI sequence on a 3.0 T MR scanner for staging of pelvic lymph nodes in patients with prostate cancer candidate to radical prostatectomy and extended pelvic lymph node dissection (PLND). Institutional review board approval was obtained and written informed consent was taken from all enrolled subjects. A series of 26 patients with pathologically proven prostate cancer (high or intermediate risk according to D'Amico risk groups) scheduled for radical prostatectomy and PLND underwent 3 T MRI before surgery. DWI was performed using an axial respiratory-triggered spin-echo echo-planar sequence with multiple b values (500, 800, 1000, 1500 s/mm(2)) in all diffusion directions. ADC values were calculated by means of dedicated software fitting the curve obtained from the corresponding ADC for each b value. Fitted ADC measurements were performed at the level of proximal and distal external iliac, internal iliac, and obturator nodal stations bilaterally. Lymph node appearance was also assessed in terms of short axis, long-to-short axis ratio, node contour and intranodal heterogeneity of signal intensity. A total of 173 lymph nodes and 104 nodal stations were evaluated on DWI and pathologically analysed. Mean fitted ADC values were 0.79 ± 0.14 × 10(-3) mm(2)/s for metastatic lymph nodes and 1.13 ± 0.29 × 10(-3) mm(2)/s in non-metastatic ones (P < 0.0001). The cut-off for fitted ADC obtained by ROC curve analysis was 0.91 × 10(-3) mm(2)/s. A two-point-level score was assigned for each qualitative parameter, and the mean grading score was 6.09 ± 0.61 for metastastic lymph nodes and 5.42 ± 0.79 for non-metastatic ones, respectively (P = 0.001). Using a score threshold of 4 for morphological, structural, and dimensional MRI analysis and a cut--off value of 0.91 × 10(-3) mm(2)/s for fitted ADC measurements of pelvic lymph nodes, per--station sensitivity, specificity, PPV, NPV and diagnostic accuracy were 100%, 7.9%, 15.6%, 100% and 21.3%, and 84.6%, 89.5%, 57.9%, 97.1% and 88.8%, respectively. 3.0T DWI with a multiple b value SE-EPI sequence may help distinguish benign from malignant pelvic lymph nodes in patients with prostate cancer.

Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle.

PubMed

Gibbs, David L; Shmulevich, Ilya

2017-06-01

The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf.

Shoot atmospheric contact is of little importance to aeration of deeper portions of the wetland plant Meionectes brownii; submerged organs mainly acquire O2 from the water column or produce it endogenously in underwater photosynthesis.

PubMed

Rich, Sarah Meghan; Pedersen, Ole; Ludwig, Martha; Colmer, Timothy David

2013-01-01

Partial shoot submergence is considered less stressful than complete submergence of plants, as aerial contact allows gas exchange with the atmosphere. In situ microelectrode studies of the wetland plant Meionectes brownii showed that O(2) dynamics in the submerged stems and aquatic roots of partially submerged plants were similar to those of completely submerged plants, with internal O(2) concentrations in both organs dropping to less than 5 kPa by dawn regardless of submergence level. The anatomy at the nodes and the relationship between tissue porosity and rates of O(2) diffusion through stems were studied. Stem internodes contained aerenchyma and had mean gas space area of 17.7% per cross section, whereas nodes had 8.2%, but nodal porosity was highly variable, some nodes had very low porosity or were completely occluded (ca. 23% of nodes sampled). The cumulative effect of these low porosity nodes would have impeded internal O(2) movement down stems. Therefore, regardless of the presence of an aerial connection, the deeper portions of submerged organs sourced most of their O(2) via inwards diffusion from the water column during the night, and endogenous production in underwater photosynthesis during the daytime. © 2012 Blackwell Publishing Ltd.

Epidemic dynamics on a risk-based evolving social network

NASA Astrophysics Data System (ADS)

Antwi, Shadrack; Shaw, Leah

2013-03-01

Social network models have been used to study how behavior affects the dynamics of an infection in a population. Motivated by HIV, we consider how a trade-off between benefits and risks of sexual connections determine network structure and disease prevalence. We define a stochastic network model with formation and breaking of links as changes in sexual contacts. Each node has an intrinsic benefit its neighbors derive from connecting to it. Nodes' infection status is not apparent to others, but nodes with more connections (higher degree) are assumed more likely to be infected. The probability to form and break links is determined by a payoff computed from the benefit and degree-dependent risk. The disease is represented by a SI (susceptible-infected) model. We study network and epidemic evolution via Monte Carlo simulation and analytically predict the behavior with a heterogeneous mean field approach. The dependence of network connectivity and infection threshold on parameters is determined, and steady state degree distribution and epidemic levels are obtained. We also study a situation where system-wide infection levels alter perception of risk and cause nodes to adjust their behavior. This is a case of an adaptive network, where node status feeds back to change network geometry.

Information spreading in complex networks with participation of independent spreaders

NASA Astrophysics Data System (ADS)

Ma, Kun; Li, Weihua; Guo, Quantong; Zheng, Xiaoqi; Zheng, Zhiming; Gao, Chao; Tang, Shaoting

2018-02-01

Information diffusion dynamics in complex networks is often modeled as a contagion process among neighbors which is analogous to epidemic diffusion. The attention of previous literature is mainly focused on epidemic diffusion within one network, which, however neglects the possible interactions between nodes beyond the underlying network. The disease can be transmitted to other nodes by other means without following the links in the focal network. Here we account for this phenomenon by introducing the independent spreaders in a susceptible-infectious-recovered contagion process. We derive the critical epidemic thresholds on Erdős-Rényi and scale-free networks as a function of infectious rate, recovery rate and the activeness of independent spreaders. We also present simulation results on ER and SF networks, as well as on a real-world email network. The result shows that the extent to which a disease can infect might be more far-reaching, than we can explain in terms of link contagion only. Besides, these results also help to explain how activeness of independent spreaders can affect the diffusion process, which can be used to explore many other dynamical processes.

Dynamic Communicability Predicts Infectiousness

NASA Astrophysics Data System (ADS)

Mantzaris, Alexander V.; Higham, Desmond J.

Using real, time-dependent social interaction data, we look at correlations between some recently proposed dynamic centrality measures and summaries from large-scale epidemic simulations. The evolving network arises from email exchanges. The centrality measures, which are relatively inexpensive to compute, assign rankings to individual nodes based on their ability to broadcast information over the dynamic topology. We compare these with node rankings based on infectiousness that arise when a full stochastic SI simulation is performed over the dynamic network. More precisely, we look at the proportion of the network that a node is able to infect over a fixed time period, and the length of time that it takes for a node to infect half the network. We find that the dynamic centrality measures are an excellent, and inexpensive, proxy for the full simulation-based measures.

Parallel scalability of Hartree-Fock calculations

NASA Astrophysics Data System (ADS)

Chow, Edmond; Liu, Xing; Smelyanskiy, Mikhail; Hammond, Jeff R.

2015-03-01

Quantum chemistry is increasingly performed using large cluster computers consisting of multiple interconnected nodes. For a fixed molecular problem, the efficiency of a calculation usually decreases as more nodes are used, due to the cost of communication between the nodes. This paper empirically investigates the parallel scalability of Hartree-Fock calculations. The construction of the Fock matrix and the density matrix calculation are analyzed separately. For the former, we use a parallelization of Fock matrix construction based on a static partitioning of work followed by a work stealing phase. For the latter, we use density matrix purification from the linear scaling methods literature, but without using sparsity. When using large numbers of nodes for moderately sized problems, density matrix computations are network-bandwidth bound, making purification methods potentially faster than eigendecomposition methods.

A Data-Gathering Scheme with Joint Routing and Compressive Sensing Based on Modified Diffusion Wavelets in Wireless Sensor Networks.

PubMed

Gu, Xiangping; Zhou, Xiaofeng; Sun, Yanjing

2018-02-28

Compressive sensing (CS)-based data gathering is a promising method to reduce energy consumption in wireless sensor networks (WSNs). Traditional CS-based data-gathering approaches require a large number of sensor nodes to participate in each CS measurement task, resulting in high energy consumption, and do not guarantee load balance. In this paper, we propose a sparser analysis that depends on modified diffusion wavelets, which exploit sensor readings' spatial correlation in WSNs. In particular, a novel data-gathering scheme with joint routing and CS is presented. A modified ant colony algorithm is adopted, where next hop node selection takes a node's residual energy and path length into consideration simultaneously. Moreover, in order to speed up the coverage rate and avoid the local optimal of the algorithm, an improved pheromone impact factor is put forward. More importantly, theoretical proof is given that the equivalent sensing matrix generated can satisfy the restricted isometric property (RIP). The simulation results demonstrate that the modified diffusion wavelets' sparsity affects the sensor signal and has better reconstruction performance than DFT. Furthermore, our data gathering with joint routing and CS can dramatically reduce the energy consumption of WSNs, balance the load, and prolong the network lifetime in comparison to state-of-the-art CS-based methods.

QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

NASA Astrophysics Data System (ADS)

Kim, Jeongnim; Baczewski, Andrew D.; Beaudet, Todd D.; Benali, Anouar; Chandler Bennett, M.; Berrill, Mark A.; Blunt, Nick S.; Josué Landinez Borda, Edgar; Casula, Michele; Ceperley, David M.; Chiesa, Simone; Clark, Bryan K.; Clay, Raymond C., III; Delaney, Kris T.; Dewing, Mark; Esler, Kenneth P.; Hao, Hongxia; Heinonen, Olle; Kent, Paul R. C.; Krogel, Jaron T.; Kylänpää, Ilkka; Li, Ying Wai; Lopez, M. Graham; Luo, Ye; Malone, Fionn D.; Martin, Richard M.; Mathuriya, Amrita; McMinis, Jeremy; Melton, Cody A.; Mitas, Lubos; Morales, Miguel A.; Neuscamman, Eric; Parker, William D.; Pineda Flores, Sergio D.; Romero, Nichols A.; Rubenstein, Brenda M.; Shea, Jacqueline A. R.; Shin, Hyeondeok; Shulenburger, Luke; Tillack, Andreas F.; Townsend, Joshua P.; Tubman, Norm M.; Van Der Goetz, Brett; Vincent, Jordan E.; ChangMo Yang, D.; Yang, Yubo; Zhang, Shuai; Zhao, Luning

2018-05-01

QMCPACK is an open source quantum Monte Carlo package for ab initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater–Jastrow type trial wavefunctions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary-field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit and graphical processing unit systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://qmcpack.org.

QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids.

PubMed

Kim, Jeongnim; Baczewski, Andrew T; Beaudet, Todd D; Benali, Anouar; Bennett, M Chandler; Berrill, Mark A; Blunt, Nick S; Borda, Edgar Josué Landinez; Casula, Michele; Ceperley, David M; Chiesa, Simone; Clark, Bryan K; Clay, Raymond C; Delaney, Kris T; Dewing, Mark; Esler, Kenneth P; Hao, Hongxia; Heinonen, Olle; Kent, Paul R C; Krogel, Jaron T; Kylänpää, Ilkka; Li, Ying Wai; Lopez, M Graham; Luo, Ye; Malone, Fionn D; Martin, Richard M; Mathuriya, Amrita; McMinis, Jeremy; Melton, Cody A; Mitas, Lubos; Morales, Miguel A; Neuscamman, Eric; Parker, William D; Pineda Flores, Sergio D; Romero, Nichols A; Rubenstein, Brenda M; Shea, Jacqueline A R; Shin, Hyeondeok; Shulenburger, Luke; Tillack, Andreas F; Townsend, Joshua P; Tubman, Norm M; Van Der Goetz, Brett; Vincent, Jordan E; Yang, D ChangMo; Yang, Yubo; Zhang, Shuai; Zhao, Luning

2018-05-16

QMCPACK is an open source quantum Monte Carlo package for ab initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wavefunctions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary-field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit and graphical processing unit systems. We detail the program's capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://qmcpack.org.

Opinion formation models in static and dynamic social networks

NASA Astrophysics Data System (ADS)

Singh, Pramesh

We study models of opinion formation on static as well as dynamic networks where interaction among individuals is governed by widely accepted social theories. In particular, three models of competing opinions based on distinct interaction mechanisms are studied. A common feature in all of these models is the existence of a tipping point in terms of a model parameter beyond which a rapid consensus is reached. In the first model that we study on a static network, a node adopts a particular state (opinion) if a threshold fraction of its neighbors are already in that state. We introduce a few initiator nodes which are in state '1' in a population where every node is in state '0'. Thus, opinion '1' spreads through the population until no further influence is possible. Size of the spread is greatly affected by how these initiator nodes are selected. We find that there exists a critical fraction of initiators pc that is needed to trigger global cascades for a given threshold phi. We also study heuristic strategies for selecting a set of initiator nodes in order to maximize the cascade size. The structural properties of networks also play an important role in the spreading process. We study how the dynamics is affected by changing the clustering in a network. It turns out that local clustering is helpful in spreading. Next, we studied a model where the network is dynamic and interactions are homophilic. We find that homophily-driven rewiring impedes the reaching of consensus and in the absence of committed nodes (nodes that are not influenceable on their opinion), consensus time Tc diverges exponentially with network size N . As we introduce a fraction of committed nodes, beyond a critical value, the scaling of Tc becomes logarithmic in N. We also find that slight change in the interaction rule can produce strikingly different scaling behaviors of T c . However, introducing committed agents in the system drastically improves the scaling of the consensus time regardless of the interaction rules considered. Finally, a three-state (leftist, rightist, centrist) model that couples the dynamics of social balance with an external deradicalizing field is studied. The mean-field analysis shows that for a weak external field, the system exhibits a metastable fixed point and a saddle point in addition to a stable fixed point. However, if the strength of the external field is sufficiently large (larger than a critical value), there is only one (stable) fixed point which corresponds to an all-centrist consensus state (absorbing state). In the weak-field regime, the convergence time to the absorbing state is evaluated using the quasi-stationary(QS) distribution and is found to be in good agreement with the results obtained by numerical simulations.

Targeted PET imaging strategy to differentiate malignant from inflamed lymph nodes in diffuse large B-cell lymphoma

PubMed Central

Salloum, Darin; Carney, Brandon; Brand, Christian; Kossatz, Susanne; Sadique, Ahmad; Lewis, Jason S.; Weber, Wolfgang A.; Wendel, Hans-Guido; Reiner, Thomas

2017-01-01

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma in adults. DLBCL exhibits highly aggressive and systemic progression into multiple tissues in patients, particularly in lymph nodes. Whole-body 18F-fluodeoxyglucose positron emission tomography ([18F]FDG-PET) imaging has an essential role in diagnosing DLBCL in the clinic; however, [18F]FDG-PET often faces difficulty in differentiating malignant tissues from certain nonmalignant tissues with high glucose uptake. We have developed a PET imaging strategy for DLBCL that targets poly[ADP ribose] polymerase 1 (PARP1), the expression of which has been found to be much higher in DLBCL than in healthy tissues. In a syngeneic DLBCL mouse model, this PARP1-targeted PET imaging approach allowed us to discriminate between malignant and inflamed lymph nodes, whereas [18F]FDG-PET failed to do so. Our PARP1-targeted PET imaging approach may be an attractive addition to the current PET imaging strategy to differentiate inflammation from malignancy in DLBCL. PMID:28827325

Comparing Vibrationally Averaged Nuclear Shielding Constants by Quantum Diffusion Monte Carlo and Second-Order Perturbation Theory.

PubMed

Ng, Yee-Hong; Bettens, Ryan P A

2016-03-03

Using the method of modified Shepard's interpolation to construct potential energy surfaces of the H2O, O3, and HCOOH molecules, we compute vibrationally averaged isotropic nuclear shielding constants ⟨σ⟩ of the three molecules via quantum diffusion Monte Carlo (QDMC). The QDMC results are compared to that of second-order perturbation theory (PT), to see if second-order PT is adequate for obtaining accurate values of nuclear shielding constants of molecules with large amplitude motions. ⟨σ⟩ computed by the two approaches differ for the hydrogens and carbonyl oxygen of HCOOH, suggesting that for certain molecules such as HCOOH where big displacements away from equilibrium happen (internal OH rotation), ⟨σ⟩ of experimental quality may only be obtainable with the use of more sophisticated and accurate methods, such as quantum diffusion Monte Carlo. The approach of modified Shepard's interpolation is also extended to construct shielding constants σ surfaces of the three molecules. By using a σ surface with the equilibrium geometry as a single data point to compute isotropic nuclear shielding constants for each descendant in the QDMC ensemble representing the ground state wave function, we reproduce the results obtained through ab initio computed σ to within statistical noise. Development of such an approach could thereby alleviate the need for any future costly ab initio σ calculations.

The Role of Node Restriction on Cadmium Accumulation in the Brown Rice of 12 Chinese Rice (Oryza sativa L.) Cultivars.

PubMed

Huang, Gaoxiang; Ding, Changfeng; Guo, Fuyu; Li, Xiaogang; Zhou, Zhigao; Zhang, Taolin; Wang, Xingxiang

2017-11-29

For selection or breeding of rice (Oryza sativa L.) cultivars with low Cd affinity, the role of node Cd restriction on Cd accumulation in brown rice was studied. A pot experiment was conducted to investigate the concentration of Cd in different sections of 12 Chinese rice cultivars. The results indicated that the Cd accumulation in the brown rice was mainly dependent on the root or shoot Cd concentration. Among the cultivars with nearly equal shoot Cd concentrations, Cd accumulation in brown rice was mainly dependent on the transport of Cd in the shoot. However, the Cd transport in the shoot was significantly restricted by the nodes, especially by the first node. Furthermore, the area of the diffuse vascular bundle in the junctional region of the flag leaf and the first node was a key contributor to the variations in Cd restriction by the nodes.

Locating influential nodes in complex networks

PubMed Central

Malliaros, Fragkiskos D.; Rossi, Maria-Evgenia G.; Vazirgiannis, Michalis

2016-01-01

Understanding and controlling spreading processes in networks is an important topic with many diverse applications, including information dissemination, disease propagation and viral marketing. It is of crucial importance to identify which entities act as influential spreaders that can propagate information to a large portion of the network, in order to ensure efficient information diffusion, optimize available resources or even control the spreading. In this work, we capitalize on the properties of the K-truss decomposition, a triangle-based extension of the core decomposition of graphs, to locate individual influential nodes. Our analysis on real networks indicates that the nodes belonging to the maximal K-truss subgraph show better spreading behavior compared to previously used importance criteria, including node degree and k-core index, leading to faster and wider epidemic spreading. We further show that nodes belonging to such dense subgraphs, dominate the small set of nodes that achieve the optimal spreading in the network. PMID:26776455

A slotted access control protocol for metropolitan WDM ring networks

NASA Astrophysics Data System (ADS)

Baziana, P. A.; Pountourakis, I. E.

2009-03-01

In this study we focus on the serious scalability problems that many access protocols for WDM ring networks introduce due to the use of a dedicated wavelength per access node for either transmission or reception. We propose an efficient slotted MAC protocol suitable for WDM ring metropolitan area networks. The proposed network architecture employs a separate wavelength for control information exchange prior to the data packet transmission. Each access node is equipped with a pair of tunable transceivers for data communication and a pair of fixed tuned transceivers for control information exchange. Also, each access node includes a set of fixed delay lines for synchronization reasons; to keep the data packets, while the control information is processed. An efficient access algorithm is applied to avoid both the data wavelengths and the receiver collisions. In our protocol, each access node is capable of transmitting and receiving over any of the data wavelengths, facing the scalability issues. Two different slot reuse schemes are assumed: the source and the destination stripping schemes. For both schemes, performance measures evaluation is provided via an analytic model. The analytical results are validated by a discrete event simulation model that uses Poisson traffic sources. Simulation results show that the proposed protocol manages efficient bandwidth utilization, especially under high load. Also, comparative simulation results prove that our protocol achieves significant performance improvement as compared with other WDMA protocols which restrict transmission over a dedicated data wavelength. Finally, performance measures evaluation is explored for diverse numbers of buffer size, access nodes and data wavelengths.

Statistical error in simulations of Poisson processes: Example of diffusion in solids

NASA Astrophysics Data System (ADS)

Nilsson, Johan O.; Leetmaa, Mikael; Vekilova, Olga Yu.; Simak, Sergei I.; Skorodumova, Natalia V.

2016-08-01

Simulations of diffusion in solids often produce poor statistics of diffusion events. We present an analytical expression for the statistical error in ion conductivity obtained in such simulations. The error expression is not restricted to any computational method in particular, but valid in the context of simulation of Poisson processes in general. This analytical error expression is verified numerically for the case of Gd-doped ceria by running a large number of kinetic Monte Carlo calculations.

Transfer matrix method for four-flux radiative transfer.

PubMed

Slovick, Brian; Flom, Zachary; Zipp, Lucas; Krishnamurthy, Srini

2017-07-20

We develop a transfer matrix method for four-flux radiative transfer, which is ideally suited for studying transport through multiple scattering layers. The model predicts the specular and diffuse reflection and transmission of multilayer composite films, including interface reflections, for diffuse or collimated incidence. For spherical particles in the diffusion approximation, we derive closed-form expressions for the matrix coefficients and show remarkable agreement with numerical Monte Carlo simulations for a range of absorption values and film thicknesses, and for an example multilayer slab.

Additional Value of Diffusion-Weighted Imaging to Evaluate Prognostic Factors of Breast Cancer: Correlation with the Apparent Diffusion Coefficient.

PubMed

Park, Eun Kyung; Cho, Kyu Ran; Seo, Bo Kyoung; Woo, Ok Hee; Cho, Sung Bum; Bae, Jeoung Won

2016-01-01

Breast cancer is a heterogeneous disease with diverse prognoses. The main prognostic determinants are lymph node status, tumor size, histological grade, and biological factors, such as hormone receptors, human epidermal growth factor receptor 2 (HER2), Ki-67 protein levels, and p53 expression. Diffusion-weighted imaging (DWI) can be used to measure the apparent diffusion coefficient (ADC) that provides information related to tumor cellularity and the integrity of the cell membranes. The goal of this study was to evaluate whether ADC measurements could provide information on the prognostic factors of breast cancer. A total of 71 women with invasive breast cancer, treated consecutively, who underwent preoperative breast MRIs with DWI at 3.0 Tesla and subsequent surgery, were prospectively included in this study. Each DWI was acquired with b values of 0 and 1000 s/mm(2). The mean ADC values of the lesions were measured, including the entire lesion on the three largest sections. We performed histopathological analyses for the tumor size, lymph node status, histological grade, hormone receptors, human epidermal growth factor receptor 2 (HER2), Ki-67, p53, and molecular subtypes. The associations with the ADC values and prognostic factors of breast cancer were evaluated using the independent-samples t test and the one-way analysis of variance (ANOVA). A low ADC value was associated with lymph node metastasis (P < 0.01) and with high Ki-67 protein levels (P = 0.03). There were no significant differences in the ADC values among the histological grade (P = 0.48), molecular subtype (P = 0.51), tumor size (P = 0.46), and p53 protein level (P = 0.62). The pre-operative use of the 3.0 Tesla DWI could provide information about the lymph node status and tumor proliferation for breast cancer patients, and could help determine the optimal treatment plan.

Diffuse characteristics study of laser target board using Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Yang, Pengling; Wu, Yong; Wang, Zhenbao; Tao, Mengmeng; Wu, Junjie; Wang, Ping; Yan, Yan; Zhang, Lei; Feng, Gang; Zhu, Jinghui; Feng, Guobin

2013-05-01

In this paper, Torrance-Sparrow and Oren-Nayar model is adopt to study diffuse characteristics of laser target board. The model which based on geometric optics, assumes that rough surfaces are made up of a series of symmetric V-groove cavities with different slopes at microscopic level. The distribution of the slopes of the V-grooves are modeled as beckman distribution function, and every microfacet of the V-groove cavity is assumed to behave like a perfect mirror, which means the reflected ray follows Fresnel law at the microfacet. The masking and shadowing effects of rough surface are also taken into account through geometric attenuation factor. Monte Carlo method is used to simulate the diffuse reflectance distribution of the laser target board with different materials and processing technology, and all the calculated results are verified by experiment. It is shown that the profile of bidirectional reflectance distribution curve is lobe-shaped with the maximum lies along the mirror reflection direction. The width of the profile is narrower for a lower roughness value, and broader for a higher roughness value. The refractive index of target material will also influence the intensity and distribution of diffuse reflectance of laser target surface.

Use of Monte-Carlo Simulations in Polyurethane Polymerization Processes

DTIC Science & Technology

1995-11-01

situations, the mechanisms of molecular species diffusion must be considered. Gupta et al (Ref. 10) have demonstrated the use of Monte-Carlo simulations in...many thoughtful discussions. P154742.PDF [Page: 41 of 78] UNCLASSIFIED 29 9. 0 REFERENCES 1. Muthiah, R. M.; Krishnamurthy, V. N.; Gupta , B. R...Time Evolution of Coupled Chemical Reactions", Journal of Computational Physics, Vol. 22, 1976, pg. 403 7. Pandit,Shubhangi S.; Juvekar, Vinay A

Computer simulation of stochastic processes through model-sampling (Monte Carlo) techniques.

PubMed

Sheppard, C W.

1969-03-01

A simple Monte Carlo simulation program is outlined which can be used for the investigation of random-walk problems, for example in diffusion, or the movement of tracers in the blood circulation. The results given by the simulation are compared with those predicted by well-established theory, and it is shown how the model can be expanded to deal with drift, and with reflexion from or adsorption at a boundary.

A Smoluchowski model of crystallization dynamics of small colloidal clusters

NASA Astrophysics Data System (ADS)

Beltran-Villegas, Daniel J.; Sehgal, Ray M.; Maroudas, Dimitrios; Ford, David M.; Bevan, Michael A.

2011-10-01

We investigate the dynamics of colloidal crystallization in a 32-particle system at a fixed value of interparticle depletion attraction that produces coexisting fluid and solid phases. Free energy landscapes (FELs) and diffusivity landscapes (DLs) are obtained as coefficients of 1D Smoluchowski equations using as order parameters either the radius of gyration or the average crystallinity. FELs and DLs are estimated by fitting the Smoluchowski equations to Brownian dynamics (BD) simulations using either linear fits to locally initiated trajectories or global fits to unbiased trajectories using Bayesian inference. The resulting FELs are compared to Monte Carlo Umbrella Sampling results. The accuracy of the FELs and DLs for modeling colloidal crystallization dynamics is evaluated by comparing mean first-passage times from BD simulations with analytical predictions using the FEL and DL models. While the 1D models accurately capture dynamics near the free energy minimum fluid and crystal configurations, predictions near the transition region are not quantitatively accurate. A preliminary investigation of ensemble averaged 2D order parameter trajectories suggests that 2D models are required to capture crystallization dynamics in the transition region.

Influence of a fat layer on the near infrared spectra of human muscle: quantitative analysis based on two-layered Monte Carlo simulations and phantom experiments

NASA Technical Reports Server (NTRS)

Yang, Ye; Soyemi, Olusola O.; Landry, Michelle R.; Soller, Babs R.

2005-01-01

The influence of fat thickness on the diffuse reflectance spectra of muscle in the near infrared (NIR) region is studied by Monte Carlo simulations of a two-layer structure and with phantom experiments. A polynomial relationship was established between the fat thickness and the detected diffuse reflectance. The influence of a range of optical coefficients (absorption and reduced scattering) for fat and muscle over the known range of human physiological values was also investigated. Subject-to-subject variation in the fat optical coefficients and thickness can be ignored if the fat thickness is less than 5 mm. A method was proposed to correct the fat thickness influence. c2005 Optical Society of America.

Effective diffusion coefficient including the Marangoni effect

NASA Astrophysics Data System (ADS)

Kitahata, Hiroyuki; Yoshinaga, Natsuhiko

2018-04-01

Surface-active molecules supplied from a particle fixed at the water surface create a spatial gradient of the molecule concentration, resulting in Marangoni convection. Convective flow transports the molecules far from the particle, enhancing diffusion. We analytically derive the effective diffusion coefficient associated with the Marangoni convection rolls. The resulting estimated effective diffusion coefficient is consistent with our numerical results and the apparent diffusion coefficient measured in experiments.

Geodesic Monte Carlo on Embedded Manifolds

PubMed Central

Byrne, Simon; Girolami, Mark

2013-01-01

Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows in the Hamilton–Jacobi representation. This paper takes the differential geometric basis of Markov chain Monte Carlo further by considering methods to simulate from probability distributions that themselves are defined on a manifold, with common examples being classes of distributions describing directional statistics. Proposal mechanisms are developed based on the geodesic flows over the manifolds of support for the distributions, and illustrative examples are provided for the hypersphere and Stiefel manifold of orthonormal matrices. PMID:25309024

Accurate quantification of fluorescent targets within turbid media based on a decoupled fluorescence Monte Carlo model.

PubMed

Deng, Yong; Luo, Zhaoyang; Jiang, Xu; Xie, Wenhao; Luo, Qingming

2015-07-01

We propose a method based on a decoupled fluorescence Monte Carlo model for constructing fluorescence Jacobians to enable accurate quantification of fluorescence targets within turbid media. The effectiveness of the proposed method is validated using two cylindrical phantoms enclosing fluorescent targets within homogeneous and heterogeneous background media. The results demonstrate that our method can recover relative concentrations of the fluorescent targets with higher accuracy than the perturbation fluorescence Monte Carlo method. This suggests that our method is suitable for quantitative fluorescence diffuse optical tomography, especially for in vivo imaging of fluorophore targets for diagnosis of different diseases and abnormalities.

Computational lymphatic node models in pediatric and adult hybrid phantoms for radiation dosimetry

NASA Astrophysics Data System (ADS)

Lee, Choonsik; Lamart, Stephanie; Moroz, Brian E.

2013-03-01

We developed models of lymphatic nodes for six pediatric and two adult hybrid computational phantoms to calculate the lymphatic node dose estimates from external and internal radiation exposures. We derived the number of lymphatic nodes from the recommendations in International Commission on Radiological Protection (ICRP) Publications 23 and 89 at 16 cluster locations for the lymphatic nodes: extrathoracic, cervical, thoracic (upper and lower), breast (left and right), mesentery (left and right), axillary (left and right), cubital (left and right), inguinal (left and right) and popliteal (left and right), for different ages (newborn, 1-, 5-, 10-, 15-year-old and adult). We modeled each lymphatic node within the voxel format of the hybrid phantoms by assuming that all nodes have identical size derived from published data except narrow cluster sites. The lymph nodes were generated by the following algorithm: (1) selection of the lymph node site among the 16 cluster sites; (2) random sampling of the location of the lymph node within a spherical space centered at the chosen cluster site; (3) creation of the sphere or ovoid of tissue representing the node based on lymphatic node characteristics defined in ICRP Publications 23 and 89. We created lymph nodes until the pre-defined number of lymphatic nodes at the selected cluster site was reached. This algorithm was applied to pediatric (newborn, 1-, 5-and 10-year-old male, and 15-year-old males) and adult male and female ICRP-compliant hybrid phantoms after voxelization. To assess the performance of our models for internal dosimetry, we calculated dose conversion coefficients, called S values, for selected organs and tissues with Iodine-131 distributed in six lymphatic node cluster sites using MCNPX2.6, a well validated Monte Carlo radiation transport code. Our analysis of the calculations indicates that the S values were significantly affected by the location of the lymph node clusters and that the values increased for smaller phantoms due to the shorter inter-organ distances compared to the bigger phantoms. By testing sensitivity of S values to random sampling and voxel resolution, we confirmed that the lymph node model is reasonably stable and consistent for different random samplings and voxel resolutions.

Endometrial cancer: correlation of apparent diffusion coefficient with tumor grade, depth of myometrial invasion, and presence of lymph node metastases.

PubMed

Rechichi, Gilda; Galimberti, Stefania; Signorelli, Mauro; Franzesi, Cammillo Talei; Perego, Patrizia; Valsecchi, Maria Grazia; Sironi, Sandro

2011-07-01

The objective of our study was to investigate whether apparent diffusion coefficient (ADC) values of endometrial cancer differ from those of normal endometrium and myometrium and whether they vary according to histologic tumor grade, the depth of myometrial invasion, or lymph node status. Seventy patients with histologically proved endometrial cancer and 36 control subjects with normal endometrium were enrolled in this prospective study. T2-weighted, dynamic T1-weighted, and diffusion-weighted images with b values of 0 and 1000 s/mm(2) were obtained of all patients. The ADC values of endometrial cancer, normal endometrium, and normal myometrium were recorded. Tumor grade, the depth of myometrial invasion, and lymph node status were assessed at postoperative histopathologic analysis. The mean (± SD) ADC value (10(-3) mm(2)/s) of endometrial cancer (0.77 ± 0.12) was significantly lower than that of normal endometrium (1.31 ± 0.11, p < 0.0001) and normal myometrium (1.52 ± 0.21, p < 0.0001), with no overlap between the two former distributions. There was no significant difference between ADC values of endometrial cancer tissue in patients with tumor grade 1 (0.79 ± 0.08, n = 14), grade 2 (0.76 ± 0.14, n = 40), or grade 3 (0.75 ± 0.12, n = 16) (p = 0.67); in patients with deep (0.77 ± 0.13, n = 18) and those with superficial (0.76 ± 0.12, n = 52) myometrial invasion (p = 0.87); and in patients with (0.78 ± 0.10, n = 6) and those without (0.75 ± 0.14, n = 39) lymph node metastases (p = 0.64). ADC values allow normal endometrium to be differentiated from endometrial carcinoma; however, they do not correlate with histologic tumor grade, the depth of myometrial invasion, or whether lymph node metastases are present.

Wireless Sensor Networks - Node Localization for Various Industry Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Derr, Kurt; Manic, Milos

Fast, effective monitoring following airborne releases of toxic substances is critical to mitigate risks to threatened population areas. Wireless sensor nodes at fixed predetermined locations may monitor such airborne releases and provide early warnings to the public. A challenging algorithmic problem is determining the locations to place these sensor nodes while meeting several criteria: 1) provide complete coverage of the domain, and 2) create a topology with problem dependent node densities, while 3) minimizing the number of sensor nodes. This manuscript presents a novel approach to determining optimal sensor placement, Advancing Front mEsh generation with Constrained dElaunay Triangulation and Smoothingmore » (AFECETS) that addresses these criteria. A unique aspect of AFECETS is the ability to determine wireless sensor node locations for areas of high interest (hospitals, schools, high population density areas) that require higher density of nodes for monitoring environmental conditions, a feature that is difficult to find in other research work. The AFECETS algorithm was tested on several arbitrary shaped domains. AFECETS simulation results show that the algorithm 1) provides significant reduction in the number of nodes, in some cases over 40%, compared to an advancing front mesh generation algorithm, 2) maintains and improves optimal spacing between nodes, and 3) produces simulation run times suitable for real-time applications.« less

Wireless Sensor Networks - Node Localization for Various Industry Problems

DOE PAGES

Derr, Kurt; Manic, Milos

2015-06-01

Fast, effective monitoring following airborne releases of toxic substances is critical to mitigate risks to threatened population areas. Wireless sensor nodes at fixed predetermined locations may monitor such airborne releases and provide early warnings to the public. A challenging algorithmic problem is determining the locations to place these sensor nodes while meeting several criteria: 1) provide complete coverage of the domain, and 2) create a topology with problem dependent node densities, while 3) minimizing the number of sensor nodes. This manuscript presents a novel approach to determining optimal sensor placement, Advancing Front mEsh generation with Constrained dElaunay Triangulation and Smoothingmore » (AFECETS) that addresses these criteria. A unique aspect of AFECETS is the ability to determine wireless sensor node locations for areas of high interest (hospitals, schools, high population density areas) that require higher density of nodes for monitoring environmental conditions, a feature that is difficult to find in other research work. The AFECETS algorithm was tested on several arbitrary shaped domains. AFECETS simulation results show that the algorithm 1) provides significant reduction in the number of nodes, in some cases over 40%, compared to an advancing front mesh generation algorithm, 2) maintains and improves optimal spacing between nodes, and 3) produces simulation run times suitable for real-time applications.« less

SU-E-T-314: The Application of Cloud Computing in Pencil Beam Scanning Proton Therapy Monte Carlo Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Z; Gao, M

Purpose: Monte Carlo simulation plays an important role for proton Pencil Beam Scanning (PBS) technique. However, MC simulation demands high computing power and is limited to few large proton centers that can afford a computer cluster. We study the feasibility of utilizing cloud computing in the MC simulation of PBS beams. Methods: A GATE/GEANT4 based MC simulation software was installed on a commercial cloud computing virtual machine (Linux 64-bits, Amazon EC2). Single spot Integral Depth Dose (IDD) curves and in-air transverse profiles were used to tune the source parameters to simulate an IBA machine. With the use of StarCluster softwaremore » developed at MIT, a Linux cluster with 2–100 nodes can be conveniently launched in the cloud. A proton PBS plan was then exported to the cloud where the MC simulation was run. Results: The simulated PBS plan has a field size of 10×10cm{sup 2}, 20cm range, 10cm modulation, and contains over 10,000 beam spots. EC2 instance type m1.medium was selected considering the CPU/memory requirement and 40 instances were used to form a Linux cluster. To minimize cost, master node was created with on-demand instance and worker nodes were created with spot-instance. The hourly cost for the 40-node cluster was $0.63 and the projected cost for a 100-node cluster was $1.41. Ten million events were simulated to plot PDD and profile, with each job containing 500k events. The simulation completed within 1 hour and an overall statistical uncertainty of < 2% was achieved. Good agreement between MC simulation and measurement was observed. Conclusion: Cloud computing is a cost-effective and easy to maintain platform to run proton PBS MC simulation. When proton MC packages such as GATE and TOPAS are combined with cloud computing, it will greatly facilitate the pursuing of PBS MC studies, especially for newly established proton centers or individual researchers.« less

Heterogeneous delays making parents synchronized: A coupled maps on Cayley tree model

NASA Astrophysics Data System (ADS)

Singh, Aradhana; Jalan, Sarika

2014-06-01

We study the phase synchronized clusters in the diffusively coupled maps on the Cayley tree networks for heterogeneous delay values. Cayley tree networks comprise of two parts: the inner nodes and the boundary nodes. We find that heterogeneous delays lead to various cluster states, such as; (a) cluster state consisting of inner nodes and boundary nodes, and (b) cluster state consisting of only boundary nodes. The former state may comprise of nodes from all the generations forming self-organized cluster or nodes from few generations yielding driven clusters depending upon on the parity of heterogeneous delay values. Furthermore, heterogeneity in delays leads to the lag synchronization between the siblings lying on the boundary by destroying the exact synchronization among them. The time lag being equal to the difference in the delay values. The Lyapunov function analysis sheds light on the destruction of the exact synchrony among the last generation nodes. To the end we discuss the relevance of our results with respect to their applications in the family business as well as in understanding the occurrence of genetic diseases.

First Monte Carlo analysis of fragmentation functions from single-inclusive e + e - annihilation

DOE PAGES

Sato, Nobuo; Ethier, J. J.; Melnitchouk, W.; ...

2016-12-02

Here, we perform the first iterative Monte Carlo (IMC) analysis of fragmentation functions constrained by all available data from single-inclusive $e^+ e^-$ annihilation into pions and kaons. The IMC method eliminates potential bias in traditional analyses based on single fits introduced by fixing parameters not well contrained by the data, and provides a statistically rigorous determination of uncertainties. Our analysis reveals specific features of fragmentation functions using the new IMC methodology and those obtained from previous analyses, especially for light quarks and for strange quark fragmentation to kaons.

Extramammary Paget's disease of the vulva.

PubMed

Gavriilidis, Paschalis; Chrysanthopoulos, Konstantinos; Gerasimidou, Domniki

2013-11-21

Vulvar Paget's disease is an extremely rare neoplasm that accounts for less than 1% of the vulvar malignancies. We present a case of a 75-year-old woman, who had an eczematoid lesion involving the labia majora and minora bilaterally, with infiltration to the clitoris. Enlarged non-fixed lymph nodes were palpable in the inguinal region bilaterally. A biopsy of the vulva showed Paget's disease. She underwent radical vulvectomy with bilateral inguinal lymph node dissection. The patient remained disease free at 6-month follow-up.

Simulations of singlet exciton diffusion in organic semiconductors: a review

DOE PAGES

Bjorgaard, Josiah A.; Kose, Muhammet Erkan

2014-12-22

Our review describes the various aspects of simulation strategies for exciton diffusion in condensed phase thin films of organic semiconductors. Several methods for calculating energy transfer rate constants are discussed along with procedures for how to account for energetic disorder. Exciton diffusion can be modelled by using kinetic Monte-Carlo methods or master equations. Recent literature on simulation efforts for estimating exciton diffusion lengths of various conjugated polymers and small molecules are introduced. Moreover, these studies are discussed in the context of the effects of morphology on exciton diffusion and the necessity of accurate treatment of disorder for comparison of simulationmore » results with those of experiment.« less

Transport diffusion in deformed carbon nanotubes

NASA Astrophysics Data System (ADS)

Feng, Jiamei; Chen, Peirong; Zheng, Dongqin; Zhong, Weirong

2018-03-01

Using non-equilibrium molecular dynamics and Monte Carlo methods, we have studied the transport diffusion of gas in deformed carbon nanotubes. Perfect carbon nanotube and various deformed carbon nanotubes are modeled as transport channels. It is found that the transport diffusion coefficient of gas does not change in twisted carbon nanotubes, but changes in XY-distortion, Z-distortion and local defect carbon nanotubes comparing with that of the perfect carbon nanotube. Furthermore, the change of transport diffusion coefficient is found to be associated with the deformation factor. The relationship between transport diffusion coefficient and temperature is also discussed in this paper. Our results may contribute to understanding the mechanism of molecular transport in nano-channel.

Towards understanding the behavior of physical systems using information theory

NASA Astrophysics Data System (ADS)

Quax, Rick; Apolloni, Andrea; Sloot, Peter M. A.

2013-09-01

One of the goals of complex network analysis is to identify the most influential nodes, i.e., the nodes that dictate the dynamics of other nodes. In the case of autonomous systems or transportation networks, highly connected hubs play a preeminent role in diffusing the flow of information and viruses; in contrast, in language evolution most linguistic norms come from the peripheral nodes who have only few contacts. Clearly a topological analysis of the interactions alone is not sufficient to identify the nodes that drive the state of the network. Here we show how information theory can be used to quantify how the dynamics of individual nodes propagate through a system. We interpret the state of a node as a storage of information about the state of other nodes, which is quantified in terms of Shannon information. This information is transferred through interactions and lost due to noise, and we calculate how far it can travel through a network. We apply this concept to a model of opinion formation in a complex social network to calculate the impact of each node by measuring how long its opinion is remembered by the network. Counter-intuitively we find that the dynamics of opinions are not determined by the hubs or peripheral nodes, but rather by nodes with an intermediate connectivity.

Inhomogeneous Monte Carlo simulations of dermoscopic spectroscopy

NASA Astrophysics Data System (ADS)

Gareau, Daniel S.; Li, Ting; Jacques, Steven; Krueger, James

2012-03-01

Clinical skin-lesion diagnosis uses dermoscopy: 10X epiluminescence microscopy. Skin appearance ranges from black to white with shades of blue, red, gray and orange. Color is an important diagnostic criteria for diseases including melanoma. Melanin and blood content and distribution impact the diffuse spectral remittance (300-1000nm). Skin layers: immersion medium, stratum corneum, spinous epidermis, basal epidermis and dermis as well as laterally asymmetric features (eg. melanocytic invasion) were modeled in an inhomogeneous Monte Carlo model.

Kinetic Monte Carlo Simulations of Diffusion in Environmental Barrier Coating Materials

NASA Technical Reports Server (NTRS)

Good, Brian

2017-01-01

Ceramic Matrix Components (CMC) components for use in turbine engines offer a number of advantages compared with current practice. However, such components are subject to degradation through a variety of mechanisms. In particular, in the hot environment inside a turbine in operation a considerable amount of water vapor is present, and this can lead to corrosion and recession. Environmental Barrier Coating (EBC) systems that limit the amount of oxygen and water reaching the component are required to reduce this degradation and extend component life. A number of silicate-based materials are under consideration for use in such coating systems, including Yttterbium and Yttrium di- and monosilicates. In this work, we present results of kinetic Monte Carlo computer simulations of oxygen diffusion in Yttrium disilicate, and compare with previous work on Yttterbium disilicate. Coatings may also exhibit cracking, and the cracks can provide a direct path for oxygen to reach the component. There is typically a bond coat between the coating and component surface, but the bond coat material is generally chosen for properties other than low oxygen diffusivity. Nevertheless, the degree to which the bond coat can inhibit oxygen diffusion is of interest, as it may form the final defense against oxygen impingement on the component. We have therefore performed similar simulations of oxygen diffusion through HfSiO4, a proposed bond coat material.

From epidemics to information propagation: Striking differences in structurally similar adaptive network models

NASA Astrophysics Data System (ADS)

Trajanovski, Stojan; Guo, Dongchao; Van Mieghem, Piet

2015-09-01

The continuous-time adaptive susceptible-infected-susceptible (ASIS) epidemic model and the adaptive information diffusion (AID) model are two adaptive spreading processes on networks, in which a link in the network changes depending on the infectious state of its end nodes, but in opposite ways: (i) In the ASIS model a link is removed between two nodes if exactly one of the nodes is infected to suppress the epidemic, while a link is created in the AID model to speed up the information diffusion; (ii) a link is created between two susceptible nodes in the ASIS model to strengthen the healthy part of the network, while a link is broken in the AID model due to the lack of interest in informationless nodes. The ASIS and AID models may be considered as first-order models for cascades in real-world networks. While the ASIS model has been exploited in the literature, we show that the AID model is realistic by obtaining a good fit with Facebook data. Contrary to the common belief and intuition for such similar models, we show that the ASIS and AID models exhibit different but not opposite properties. Most remarkably, a unique metastable state always exists in the ASIS model, while there an hourglass-shaped region of instability in the AID model. Moreover, the epidemic threshold is a linear function in the effective link-breaking rate in the AID model, while it is almost constant but noisy in the AID model.

Identification of genomic aberrations associated with lymph node metastasis in diffuse-type gastric cancer.

PubMed

Choi, Ji-Hye; Kim, Young-Bae; Ahn, Ji Mi; Kim, Min Jae; Bae, Won Jung; Han, Sang-Uk; Woo, Hyun Goo; Lee, Dakeun

2018-04-06

Diffuse-type gastric cancer (DGC) is a GC subtype with heterogeneous clinical outcomes. Lymph node metastasis of DGC heralds a dismal progression, which hampers the curative treatment of patients. However, the genomic heterogeneity of DGC remains unknown. To identify genomic variations associated with lymph node metastasis in DGC, we performed whole exome sequencing on 23 cases of DGC and paired non-tumor tissues and compared the mutation profiles according to the presence (N3, n = 13) or absence (N0, n = 10) of regional lymph node metastasis. Overall, we identified 185 recurrently mutated genes in DGC, which included a significant novel mutation at CMTM2, as well as previously known mutations at CDH1, RHOA, and TP53. Noticeably, CMTM2 expression could predict the prognostic outcomes of DGC but not intestinal-type GC (IGC), indicating pivotal roles of CMTM2 in DGC progression. In addition, we identified a recurrent loss of heterozygosity (LOH) of DNA copy numbers at the 3p12-pcen locus in DGC. A comparison of N0 and N3 tumors showed that N3 tumors exhibited more frequent DNA copy number aberrations, including copy-neutral LOH and mutations of CpTpT trinucleotides, than N0 tumors (P = 0.2 × 10 -3 ). In conclusion, DGCs have distinct profiles of somatic mutations and DNA copy numbers according to the status of lymph node metastasis, and this might be helpful in delineating the pathobiology of DGC.

Spectrum efficient distance-adaptive paths for fixed and fixed-alternate routing in elastic optical networks

NASA Astrophysics Data System (ADS)

Agrawal, Anuj; Bhatia, Vimal; Prakash, Shashi

2018-01-01

Efficient utilization of spectrum is a key concern in the soon to be deployed elastic optical networks (EONs). To perform routing in EONs, various fixed routing (FR), and fixed-alternate routing (FAR) schemes are ubiquitously used. FR, and FAR schemes calculate a fixed route, and a prioritized list of a number of alternate routes, respectively, between different pairs of origin o and target t nodes in the network. The route calculation performed using FR and FAR schemes is predominantly based on either the physical distance, known as k -shortest paths (KSP), or on the hop count (HC). For survivable optical networks, FAR usually calculates link-disjoint (LD) paths. These conventional routing schemes have been efficiently used for decades in communication networks. However, in this paper, it has been demonstrated that these commonly used routing schemes cannot utilize the network spectral resources optimally in the newly introduced EONs. Thus, we propose a new routing scheme for EON, namely, k -distance adaptive paths (KDAP) that efficiently utilizes the benefit of distance-adaptive modulation, and bit rate-adaptive superchannel capability inherited by EON to improve spectrum utilization. In the proposed KDAP, routes are found and prioritized on the basis of bit rate, distance, spectrum granularity, and the number of links used for a particular route. To evaluate the performance of KSP, HC, LD, and the proposed KDAP, simulations have been performed for three different sized networks, namely, 7-node test network (TEST7), NSFNET, and 24-node US backbone network (UBN24). We comprehensively assess the performance of various conventional, and the proposed routing schemes by solving both the RSA and the dual RSA problems under homogeneous and heterogeneous traffic requirements. Simulation results demonstrate that there is a variation amongst the performance of KSP, HC, and LD, depending on the o - t pair, and the network topology and its connectivity. However, the proposed KDAP always performs better for all the considered networks and traffic scenarios, as compared to the conventional routing schemes, namely, KSP, HC, and LD. The proposed KDAP achieves up to 60 % , and 10.46 % improvement in terms of spectrum utilization, and resource utilization ratio, respectively, over the conventional routing schemes.

Monte Carlo tree search -based non-coplanar trajectory design for station parameter optimized radiation therapy (SPORT).

PubMed

Dong, Peng; Liu, Hongcheng; Xing, Lei

2018-06-04

An important yet challenging problem in LINAC-based rotational arc radiation therapy is the design of beam trajectory, which requires simultaneous consideration of delivery efficiency and final dose distribution. In this work, we propose a novel trajectory selection strategy by developing a Monte Carlo tree search (MCTS) algorithm during the beam trajectory selection process. Methods: To search through the vast number of possible trajectories, MCTS algorithm was implemented. In this approach, a candidate trajectory is explored by starting from a leaf node and sequentially examining the next level of linked nodes with consideration of geometric and physical constraints. The maximum Upper Confidence Bounds for Trees, which is a function of average objective function value and the number of times the node under testing has been visited, was employed to intelligently select the trajectory. For each candidate trajectory, we run an inverse fluence map optimization with an infinity norm regularization. The ranking of the plan as measured by the corresponding objective function value was then fed back to update the statistics of the nodes on the trajectory. The method was evaluated with a chest wall and a brain case, and the results were compared with the coplanar and noncoplanar 4pi beam configurations. Results: For both clinical cases, the MCTS method found effective and easy-to-deliver trajectories within an hour. As compared with the coplanar plans, it offers much better sparing of the OARs while maintaining the PTV coverage. The quality of the MCTS-generated plan is found to be comparable to the 4pi plans. Conclusion: AI based on MCTS is valuable to facilitate the design of beam trajectory and paves the way for future clinical use of non-coplanar treatment delivery. . © 2018 Institute of Physics and Engineering in Medicine.

An energy-efficient and compact clustering scheme with temporary support nodes for cognitive radio sensor networks.

PubMed

Salim, Shelly; Moh, Sangman; Choi, Dongmin; Chung, Ilyong

2014-08-11

A cognitive radio sensor network (CRSN) is a wireless sensor network whose sensor nodes are equipped with cognitive radio capability. Clustering is one of the most challenging issues in CRSNs, as all sensor nodes, including the cluster head, have to use the same frequency band in order to form a cluster. However, due to the nature of heterogeneous channels in cognitive radio, it is difficult for sensor nodes to find a cluster head. This paper proposes a novel energy-efficient and compact clustering scheme named clustering with temporary support nodes (CENTRE). CENTRE efficiently achieves a compact cluster formation by adopting two-phase cluster formation with fixed duration. By introducing a novel concept of temporary support nodes to improve the cluster formation, the proposed scheme enables sensor nodes in a network to find a cluster head efficiently. The performance study shows that not only is the clustering process efficient and compact but it also results in remarkable energy savings that prolong the overall network lifetime. In addition, the proposed scheme decreases both the clustering overhead and the average distance between cluster heads and their members.

An Energy-Efficient and Compact Clustering Scheme with Temporary Support Nodes for Cognitive Radio Sensor Networks

PubMed Central

Salim, Shelly; Moh, Sangman; Choi, Dongmin; Chung, Ilyong

2014-01-01

A cognitive radio sensor network (CRSN) is a wireless sensor network whose sensor nodes are equipped with cognitive radio capability. Clustering is one of the most challenging issues in CRSNs, as all sensor nodes, including the cluster head, have to use the same frequency band in order to form a cluster. However, due to the nature of heterogeneous channels in cognitive radio, it is difficult for sensor nodes to find a cluster head. This paper proposes a novel energy-efficient and compact clustering scheme named clustering with temporary support nodes (CENTRE). CENTRE efficiently achieves a compact cluster formation by adopting two-phase cluster formation with fixed duration. By introducing a novel concept of temporary support nodes to improve the cluster formation, the proposed scheme enables sensor nodes in a network to find a cluster head efficiently. The performance study shows that not only is the clustering process efficient and compact but it also results in remarkable energy savings that prolong the overall network lifetime. In addition, the proposed scheme decreases both the clustering overhead and the average distance between cluster heads and their members. PMID:25116905

Adaptive intensity modulated radiotherapy for advanced prostate cancer

NASA Astrophysics Data System (ADS)

Ludlum, Erica Marie

The purpose of this research is to develop and evaluate improvements in intensity modulated radiotherapy (IMRT) for concurrent treatment of prostate and pelvic lymph nodes. The first objective is to decrease delivery time while maintaining treatment quality, and evaluate the effectiveness and efficiency of novel one-step optimization compared to conventional two-step optimization. Both planning methods are examined at multiple levels of complexity by comparing the number of beam apertures, or segments, the amount of radiation delivered as measured by monitor units (MUs), and delivery time. One-step optimization is demonstrated to simplify IMRT planning and reduce segments (from 160 to 40), MUs (from 911 to 746), and delivery time (from 22 to 7 min) with comparable plan quality. The second objective is to examine the capability of three commercial dose calculation engines employing different levels of accuracy and efficiency to handle high--Z materials, such as metallic hip prostheses, included in the treatment field. Pencil beam, convolution superposition, and Monte Carlo dose calculation engines are compared by examining the dose differences for patient plans with unilateral and bilateral hip prostheses, and for phantom plans with a metal insert for comparison with film measurements. Convolution superposition and Monte Carlo methods calculate doses that are 1.3% and 34.5% less than the pencil beam method, respectively. Film results demonstrate that Monte Carlo most closely represents actual radiation delivery, but none of the three engines accurately predict the dose distribution when high-Z heterogeneities exist in the treatment fields. The final objective is to improve the accuracy of IMRT delivery by accounting for independent organ motion during concurrent treatment of the prostate and pelvic lymph nodes. A leaf-shifting algorithm is developed to track daily prostate position without requiring online dose calculation. Compared to conventional methods of adjusting patient position, adjusting the multileaf collimator (MLC) leaves associated with the prostate in each segment significantly improves lymph node dose coverage (maintains 45 Gy compared to 42.7, 38.3, and 34.0 Gy for iso-shifts of 0.5, 1 and 1.5 cm). Altering the MLC portal shape is demonstrated as a new and effective solution to independent prostate movement during concurrent treatment.

NRMC - A GPU code for N-Reverse Monte Carlo modeling of fluids in confined media

NASA Astrophysics Data System (ADS)

Sánchez-Gil, Vicente; Noya, Eva G.; Lomba, Enrique

2017-08-01

NRMC is a parallel code for performing N-Reverse Monte Carlo modeling of fluids in confined media [V. Sánchez-Gil, E.G. Noya, E. Lomba, J. Chem. Phys. 140 (2014) 024504]. This method is an extension of the usual Reverse Monte Carlo method to obtain structural models of confined fluids compatible with experimental diffraction patterns, specifically designed to overcome the problem of slow diffusion that can appear under conditions of tight confinement. Most of the computational time in N-Reverse Monte Carlo modeling is spent in the evaluation of the structure factor for each trial configuration, a calculation that can be easily parallelized. Implementation of the structure factor evaluation in NVIDIA® CUDA so that the code can be run on GPUs leads to a speed up of up to two orders of magnitude.

A High-Order Low-Order Algorithm with Exponentially Convergent Monte Carlo for Thermal Radiative Transfer

DOE PAGES

Bolding, Simon R.; Cleveland, Mathew Allen; Morel, Jim E.

2016-10-21

In this paper, we have implemented a new high-order low-order (HOLO) algorithm for solving thermal radiative transfer problems. The low-order (LO) system is based on the spatial and angular moments of the transport equation and a linear-discontinuous finite-element spatial representation, producing equations similar to the standard S 2 equations. The LO solver is fully implicit in time and efficiently resolves the nonlinear temperature dependence at each time step. The high-order (HO) solver utilizes exponentially convergent Monte Carlo (ECMC) to give a globally accurate solution for the angular intensity to a fixed-source pure-absorber transport problem. This global solution is used tomore » compute consistency terms, which require the HO and LO solutions to converge toward the same solution. The use of ECMC allows for the efficient reduction of statistical noise in the Monte Carlo solution, reducing inaccuracies introduced through the LO consistency terms. Finally, we compare results with an implicit Monte Carlo code for one-dimensional gray test problems and demonstrate the efficiency of ECMC over standard Monte Carlo in this HOLO algorithm.« less

Distributed ESO based cooperative tracking control for high-order nonlinear multiagent systems with lumped disturbance and application in multi flight simulators systems.

PubMed

Cong, Zhang

2018-03-01

Based on extended state observer, a novel and practical design method is developed to solve the distributed cooperative tracking problem of higher-order nonlinear multiagent systems with lumped disturbance in a fixed communication topology directed graph. The proposed method is designed to guarantee all the follower nodes ultimately and uniformly converge to the leader node with bounded residual errors. The leader node, modeled as a higher-order non-autonomous nonlinear system, acts as a command generator giving commands only to a small portion of the networked follower nodes. Extended state observer is used to estimate the local states and lumped disturbance of each follower node. Moreover, each distributed controller can work independently only requiring the relative states and/or the estimated relative states information between itself and its neighbors. Finally an engineering application of multi flight simulators systems is demonstrated to test and verify the effectiveness of the proposed algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

The Reduction of TED in Ion Implanted Silicon

NASA Astrophysics Data System (ADS)

Jain, Amitabh

2008-11-01

The leading challenge in the continued scaling of junctions made by ion implantation and annealing is the control of the undesired transient enhanced diffusion (TED) effect. Spike annealing has been used as a means to reduce this effect and has proven successful in previous nodes. The peak temperature in this process is typically 1050 °C and the time spent within 50 °C of the peak is of the order of 1.5 seconds. As technology advances along the future scaling roadmap, further reduction or elimination of the enhanced diffusion effect is necessary. We have shown that raising the peak temperature to 1175 °C or more and reduction of the anneal time at peak temperature to less than a millisecond is effective in eliminating enhanced diffusion. We show that it is possible to employ a sequence of millisecond anneal followed by spike anneal to obtain profiles that do not exhibit gradient degradation at the junction and have junction depth and sheet resistance appropriate to the needs of future technology nodes. We have implemented millisecond annealing using a carbon dioxide laser to support high-volume manufacturing of 65 nm microprocessors and system-on-chip products. We further show how the use of molecular ion implantation to produce amorphousness followed by laser annealing to produce solid phase epitaxial regrowth results in junctions that meet the shallow depth and abruptness requirements of the 32 nm node.

Diffuse reflectance imaging for non-melanoma skin cancer detection using laser feedback interferometry

NASA Astrophysics Data System (ADS)

Mowla, Alireza; Taimre, Thomas; Lim, Yah L.; Bertling, Karl; Wilson, Stephen J.; Prow, Tarl W.; Soyer, H. P.; Rakić, Aleksandar D.

2016-04-01

We propose a compact, self-aligned, low-cost, and versatile infrared diffuse-reflectance laser imaging system using a laser feedback interferometry technique with possible applications in in vivo biological tissue imaging and skin cancer detection. We examine the proposed technique experimentally using a three-layer agar skin phantom. A cylindrical region with a scattering rate lower than that of the surrounding normal tissue was used as a model for a non-melanoma skin tumour. The same structure was implemented in a Monte Carlo computational model. The experimental results agree well with the Monte Carlo simulations validating the theoretical basis of the technique. Results prove the applicability of the proposed technique for biological tissue imaging, with the capability of depth sectioning and a penetration depth of well over 1.2 mm into the skin phantom.

High-pressure hydrogen sulfide by diffusion quantum Monte Carlo.

PubMed

Azadi, Sam; Kühne, Thomas D

2017-02-28

We revisit the enthalpy-pressure phase diagram of the various products from the different proposed decompositions of H 2 S at pressures above 150 GPa by means of accurate diffusion Monte Carlo simulations. Our results entail a revision of the ground-state enthalpy-pressure phase diagram. Specifically, we find that the C2/c HS 2 structure is persistent up to 440 GPa before undergoing a phase transition into the C2/m phase. Contrary to density functional theory, our calculations suggest that the C2/m phase of HS is more stable than the I4 1 /amd HS structure over the whole pressure range from 150 to 400 GPa. More importantly, we predict that the Im-3m phase is the most likely candidate for H 3 S, which is consistent with recent experimental x-ray diffraction measurements.

Quantitative, depth-resolved determination of particle motion using multi-exposure, spatial frequency domain laser speckle imaging.

PubMed

Rice, Tyler B; Kwan, Elliott; Hayakawa, Carole K; Durkin, Anthony J; Choi, Bernard; Tromberg, Bruce J

2013-01-01

Laser Speckle Imaging (LSI) is a simple, noninvasive technique for rapid imaging of particle motion in scattering media such as biological tissue. LSI is generally used to derive a qualitative index of relative blood flow due to unknown impact from several variables that affect speckle contrast. These variables may include optical absorption and scattering coefficients, multi-layer dynamics including static, non-ergodic regions, and systematic effects such as laser coherence length. In order to account for these effects and move toward quantitative, depth-resolved LSI, we have developed a method that combines Monte Carlo modeling, multi-exposure speckle imaging (MESI), spatial frequency domain imaging (SFDI), and careful instrument calibration. Monte Carlo models were used to generate total and layer-specific fractional momentum transfer distributions. This information was used to predict speckle contrast as a function of exposure time, spatial frequency, layer thickness, and layer dynamics. To verify with experimental data, controlled phantom experiments with characteristic tissue optical properties were performed using a structured light speckle imaging system. Three main geometries were explored: 1) diffusive dynamic layer beneath a static layer, 2) static layer beneath a diffuse dynamic layer, and 3) directed flow (tube) submerged in a dynamic scattering layer. Data fits were performed using the Monte Carlo model, which accurately reconstructed the type of particle flow (diffusive or directed) in each layer, the layer thickness, and absolute flow speeds to within 15% or better.

Nonequilibrium diffusive gas dynamics: Poiseuille microflow

NASA Astrophysics Data System (ADS)

Abramov, Rafail V.; Otto, Jasmine T.

2018-05-01

We test the recently developed hierarchy of diffusive moment closures for gas dynamics together with the near-wall viscosity scaling on the Poiseuille flow of argon and nitrogen in a one micrometer wide channel, and compare it against the corresponding Direct Simulation Monte Carlo computations. We find that the diffusive regularized Grad equations with viscosity scaling provide the most accurate approximation to the benchmark DSMC results. At the same time, the conventional Navier-Stokes equations without the near-wall viscosity scaling are found to be the least accurate among the tested closures.

Diffuse interstellar bands in reflection nebulae

NASA Technical Reports Server (NTRS)

Fischer, O.; Henning, Thomas; Pfau, Werner; Stognienko, R.

1994-01-01

A Monte Carlo code for radiation transport calculations is used to compare the profiles of the lambda lambda 5780 and 6613 Angstrom diffuse interstellar bands in the transmitted and the reflected light of a star embedded within an optically thin dust cloud. In addition, the behavior of polarization across the bands were calculated. The wavelength dependent complex indices of refraction across the bands were derived from the embedded cavity model. In view of the existence of different families of diffuse interstellar bands the question of other parameters of influence is addressed in short.

A Hardware-Accelerated Quantum Monte Carlo framework (HAQMC) for N-body systems

NASA Astrophysics Data System (ADS)

Gothandaraman, Akila; Peterson, Gregory D.; Warren, G. Lee; Hinde, Robert J.; Harrison, Robert J.

2009-12-01

Interest in the study of structural and energetic properties of highly quantum clusters, such as inert gas clusters has motivated the development of a hardware-accelerated framework for Quantum Monte Carlo simulations. In the Quantum Monte Carlo method, the properties of a system of atoms, such as the ground-state energies, are averaged over a number of iterations. Our framework is aimed at accelerating the computations in each iteration of the QMC application by offloading the calculation of properties, namely energy and trial wave function, onto reconfigurable hardware. This gives a user the capability to run simulations for a large number of iterations, thereby reducing the statistical uncertainty in the properties, and for larger clusters. This framework is designed to run on the Cray XD1 high performance reconfigurable computing platform, which exploits the coarse-grained parallelism of the processor along with the fine-grained parallelism of the reconfigurable computing devices available in the form of field-programmable gate arrays. In this paper, we illustrate the functioning of the framework, which can be used to calculate the energies for a model cluster of helium atoms. In addition, we present the capabilities of the framework that allow the user to vary the chemical identities of the simulated atoms. Program summaryProgram title: Hardware Accelerated Quantum Monte Carlo (HAQMC) Catalogue identifier: AEEP_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEP_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 691 537 No. of bytes in distributed program, including test data, etc.: 5 031 226 Distribution format: tar.gz Programming language: C/C++ for the QMC application, VHDL and Xilinx 8.1 ISE/EDK tools for FPGA design and development Computer: Cray XD1 consisting of a dual-core, dualprocessor AMD Opteron 2.2 GHz with a Xilinx Virtex-4 (V4LX160) or Xilinx Virtex-II Pro (XC2VP50) FPGA per node. We use the compute node with the Xilinx Virtex-4 FPGA Operating system: Red Hat Enterprise Linux OS Has the code been vectorised or parallelized?: Yes Classification: 6.1 Nature of problem: Quantum Monte Carlo is a practical method to solve the Schrödinger equation for large many-body systems and obtain the ground-state properties of such systems. This method involves the sampling of a number of configurations of atoms and averaging the properties of the configurations over a number of iterations. We are interested in applying the QMC method to obtain the energy and other properties of highly quantum clusters, such as inert gas clusters. Solution method: The proposed framework provides a combined hardware-software approach, in which the QMC simulation is performed on the host processor, with the computationally intensive functions such as energy and trial wave function computations mapped onto the field-programmable gate array (FPGA) logic device attached as a co-processor to the host processor. We perform the QMC simulation for a number of iterations as in the case of our original software QMC approach, to reduce the statistical uncertainty of the results. However, our proposed HAQMC framework accelerates each iteration of the simulation, by significantly reducing the time taken to calculate the ground-state properties of the configurations of atoms, thereby accelerating the overall QMC simulation. We provide a generic interpolation framework that can be extended to study a variety of pure and doped atomic clusters, irrespective of the chemical identities of the atoms. For the FPGA implementation of the properties, we use a two-region approach for accurately computing the properties over the entire domain, employ deep pipelines and fixed-point for all our calculations guaranteeing the accuracy required for our simulation.

Molecular simulations of a CO2/CO mixture in MIL-127

NASA Astrophysics Data System (ADS)

Chokbunpiam, Tatiya; Fritzsche, Siegfried; Parasuk, Vudhichai; Caro, Jürgen; Assabumrungrat, Suttichai

2018-03-01

Adsorption and diffusion of an equimolar feed mixture of CO2 and CO in MIL-127 at three different temperatures and pressures up to 12 bar were investigated by molecular simulations. The adsorption was simulated using Gibbs-Ensemble Monte Carlo (GEMC). The structure of the adsorbed phase and the diffusion in the MIL were investigated using Molecular Dynamics (MD) simulations. The adsorption selectivity of MIL-127 for CO2 over CO at 233 K was about 15. When combining adsorption and diffusion selectivities, a membrane selectivity of about 12 is predicted. For higher temperatures, both adsorption and diffusion selectivity are found to be smaller.

Diagnostic performance of magnetic resonance imaging and 3D endoanal ultrasound in detection, staging and assessment post treatment, in anal cancer.

PubMed

Reginelli, Alfonso; Granata, Vincenza; Fusco, Roberta; Granata, Francesco; Rega, Daniela; Roberto, Luca; Pellino, Gianluca; Rotondo, Antonio; Selvaggi, Francesco; Izzo, Francesco; Petrillo, Antonella; Grassi, Roberto

2017-04-04

We compared Magnetic Resonance Imaging (MRI) and 3D Endoanal Ultrasound (EAUS) imaging performance to confirm anal carcinoma and to monitor treatment response.58 patients with anal cancer were retrospectively enrolled. All patients underwent clinical examination, anoscopic examination; EAUS and contrast-enhanced MRI study before and after treatment. Four radiologists evaluated the presence of lesions, using a 4-point confidence scale, features of the lesion and nodes on EAUS images, T1-weighted (T1-W), T2-weighted (T2-W) and diffusion-weighted images (DWI) signal intensity (SI), the apparent diffusion coefficient (ADC) map for nodes and lesion, as well as enhancement pattern during dynamic MRI were assessed.All lesions were detected by EAUS while MRI detected 93.1% of anal cancer. MRI showed a good correlation with EAUS, anoscopy and clinical examination. The residual tissue not showed significant difference in EAUS assessment and T2-W SI in pre and post treatment. We found significant difference in dynamic study, in SI of DWI, in ADC map and values among responder's patients in pre and post treatment. The neoplastic nodes were hypoecoic on EAUS, with hyperintense signal on T2-W sequences and hypointense signal on T1-W. The neoplastic nodes showed SI on DWI sequences and ADC value similar to anal cancer. We found significant difference in nodes status in pre and post therapy on DWI data.3D EAUS and MRI are accurate techniques in anal cancer staging, although EAUS is more accurate than MRI for T1 stage. MRI allows correct detection of neoplastic nodes and can properly stratify patients into responders or non responders.

ICF target 2D modeling using Monte Carlo SNB electron thermal transport in DRACO

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

2016-10-01

The iSNB (implicit Schurtz Nicolai Busquet multigroup diffusion electron thermal transport method is adapted into a Monte Carlo (MC) transport method to better model angular and long mean free path non-local effects. The MC model was first implemented in the 1D LILAC code to verify consistency with the iSNB model. Implementation of the MC SNB model in the 2D DRACO code enables higher fidelity non-local thermal transport modeling in 2D implosions such as polar drive experiments on NIF. The final step is to optimize the MC model by hybridizing it with a MC version of the iSNB diffusion method. The hybrid method will combine the efficiency of a diffusion method in intermediate mean free path regions with the accuracy of a transport method in long mean free path regions allowing for improved computational efficiency while maintaining accuracy. Work to date on the method will be presented. This work was supported by Sandia National Laboratories and the Univ. of Rochester Laboratory for Laser Energetics.

The limitation of the proposed collection efficiency for fiber probes on the visible and near-infrared diffuse spectroscopy

NASA Astrophysics Data System (ADS)

Zhang, Linna; Ding, Hongyan; Lin, Ling; Wang, Yimin; Guo, Xin

2017-12-01

A fiber is usually used as a probe in visible and near-infrared diffuse spectra measurement. However, the use of different fiber probes in the same measurement may cause data mismatch problems. Our group has researched the influence of the parameters of fiber probe, including the aperture angle, on the diffuse spectrum by a modified Monte Carlo model. To eliminate the influence of the aperture angle, we proposed a fitted equation of correction coefficient to correct its difference in practical range. However, we did not discuss the limitation of this method. In this work, we explored the collection efficiency in different optical environment with Monte Carlo simulation method, and find the suitable conditions-weak absorbing and strong scattering media, for the proposed collection efficiency. Furthermore, we tried to explain the stability of the collection efficiency in this condition. This work gives suitable conditions for the collection efficiency. The use of collection efficiency can help reduce the influence of different measurement systems and is also helpful to the model translation.

Distribution in energies and acceleration times in DSA, and their effect on the cut-off

NASA Astrophysics Data System (ADS)

Brooks, A.; Protheroe, R. J.

2001-08-01

We have conducted Monte Carlo simulations of diffusive shock acceleration (DSA) to determine the distribution of times since injection taken to reach energy E > E0. This distribution of acceleration times for the case of momentum dependent diffusion is compared with that given by Drury and Forman (1983) based on extrapolation of the exact result (Toptygin 1980) for the case of the diffusion coefficient being independent of momentum. As a result of this distribution we find, as suggested by Drury et al. (1999), that Monte Carlo simulations result in smoother cut-offs and pile-ups in spectra of accelerated particles than expected from simple "box model" treatments of shock acceleration (e.g., Protheroe and Stanev 1999, Drury et al. 1999). This is particularly so for the case synchrotron pile-ups, which we find are replaced by a small bump at an energy about a factor of 2 below the expected cut-off, followed by a smooth cut-off with particles extending to energies well beyond the expected cut-off energy.

Monte Carlo analysis of neutron diffuse scattering data

NASA Astrophysics Data System (ADS)

Goossens, D. J.; Heerdegen, A. P.; Welberry, T. R.; Gutmann, M. J.

2006-11-01

This paper presents a discussion of a technique developed for the analysis of neutron diffuse scattering data. The technique involves processing the data into reciprocal space sections and modelling the diffuse scattering in these sections. A Monte Carlo modelling approach is used in which the crystal energy is a function of interatomic distances between molecules and torsional rotations within molecules. The parameters of the model are the spring constants governing the interactions, as they determine the correlations which evolve when the model crystal structure is relaxed at finite temperature. When the model crystal has reached equilibrium its diffraction pattern is calculated and a χ2 goodness-of-fit test between observed and calculated data slices is performed. This allows a least-squares refinement of the fit parameters and so automated refinement can proceed. The first application of this methodology to neutron, rather than X-ray, data is outlined. The sample studied was deuterated benzil, d-benzil, C14D10O2, for which data was collected using time-of-flight Laue diffraction on SXD at ISIS.

Photon migration through a turbid slab described by a model based on diffusion approximation. II. Comparison with Monte Carlo results.

PubMed

Martelli, F; Contini, D; Taddeucci, A; Zaccanti, G

1997-07-01

In our companion paper we presented a model to describe photon migration through a diffusing slab. The model, developed for a homogeneous slab, is based on the diffusion approximation and is able to take into account reflection at the boundaries resulting from the refractive index mismatch. In this paper the predictions of the model are compared with solutions of the radiative transfer equation obtained by Monte Carlo simulations in order to determine the applicability limits of the approximated theory in different physical conditions. A fitting procedure, carried out with the optical properties as fitting parameters, is used to check the application of the model to the inverse problem. The results show that significant errors can be made if the effect of the refractive index mismatch is not properly taken into account. Errors are more important when measurements of transmittance are used. The effects of using a receiver with a limited angular field of view and the angular distribution of the radiation that emerges from the slab have also been investigated.

Monolayers of hard rods on planar substrates. II. Growth

NASA Astrophysics Data System (ADS)

Klopotek, M.; Hansen-Goos, H.; Dixit, M.; Schilling, T.; Schreiber, F.; Oettel, M.

2017-02-01

Growth of hard-rod monolayers via deposition is studied in a lattice model using rods with discrete orientations and in a continuum model with hard spherocylinders. The lattice model is treated with kinetic Monte Carlo simulations and dynamic density functional theory while the continuum model is studied by dynamic Monte Carlo simulations equivalent to diffusive dynamics. The evolution of nematic order (excess of upright particles, "standing-up" transition) is an entropic effect and is mainly governed by the equilibrium solution, rendering a continuous transition [Paper I, M. Oettel et al., J. Chem. Phys. 145, 074902 (2016)]. Strong non-equilibrium effects (e.g., a noticeable dependence on the ratio of rates for translational and rotational moves) are found for attractive substrate potentials favoring lying rods. Results from the lattice and the continuum models agree qualitatively if the relevant characteristic times for diffusion, relaxation of nematic order, and deposition are matched properly. Applicability of these monolayer results to multilayer growth is discussed for a continuum-model realization in three dimensions where spherocylinders are deposited continuously onto a substrate via diffusion.

QMCPACK : an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

DOE PAGES

Kim, Jeongnim; Baczewski, Andrew T.; Beaudet, Todd D.; ...

2018-04-19

QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wave functions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performancemore » computing architectures, including multicore central processing unit (CPU) and graphical processing unit (GPU) systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://www.qmcpack.org.« less

QMCPACK : an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jeongnim; Baczewski, Andrew T.; Beaudet, Todd D.

QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wave functions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performancemore » computing architectures, including multicore central processing unit (CPU) and graphical processing unit (GPU) systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://www.qmcpack.org.« less

Raman Monte Carlo simulation for light propagation for tissue with embedded objects

NASA Astrophysics Data System (ADS)

Periyasamy, Vijitha; Jaafar, Humaira Bte; Pramanik, Manojit

2018-02-01

Monte Carlo (MC) stimulation is one of the prominent simulation technique and is rapidly becoming the model of choice to study light-tissue interaction. Monte Carlo simulation for light transport in multi-layered tissue (MCML) is adapted and modelled with different geometry by integrating embedded objects of various shapes (i.e., sphere, cylinder, cuboid and ellipsoid) into the multi-layered structure. These geometries would be useful in providing a realistic tissue structure such as modelling for lymph nodes, tumors, blood vessels, head and other simulation medium. MC simulations were performed on various geometric medium. Simulation of MCML with embedded object (MCML-EO) was improvised for propagation of the photon in the defined medium with Raman scattering. The location of Raman photon generation is recorded. Simulations were experimented on a modelled breast tissue with tumor (spherical and ellipsoidal) and blood vessels (cylindrical). Results were presented in both A-line and B-line scans for embedded objects to determine spatial location where Raman photons were generated. Studies were done for different Raman probabilities.

Convergence analysis of two-node CMFD method for two-group neutron diffusion eigenvalue problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeong, Yongjin; Park, Jinsu; Lee, Hyun Chul

2015-12-01

In this paper, the nonlinear coarse-mesh finite difference method with two-node local problem (CMFD2N) is proven to be unconditionally stable for neutron diffusion eigenvalue problems. The explicit current correction factor (CCF) is derived based on the two-node analytic nodal method (ANM2N), and a Fourier stability analysis is applied to the linearized algorithm. It is shown that the analytic convergence rate obtained by the Fourier analysis compares very well with the numerically measured convergence rate. It is also shown that the theoretical convergence rate is only governed by the converged second harmonic buckling and the mesh size. It is also notedmore » that the convergence rate of the CCF of the CMFD2N algorithm is dependent on the mesh size, but not on the total problem size. This is contrary to expectation for eigenvalue problem. The novel points of this paper are the analytical derivation of the convergence rate of the CMFD2N algorithm for eigenvalue problem, and the convergence analysis based on the analytic derivations.« less

A long-term stable power supply µDMFC stack for wireless sensor node applications

NASA Astrophysics Data System (ADS)

Wu, Zonglin; Wang, Xiaohong; Li, Xiaozhao; Xu, Manqi; Liu, Litian

2014-10-01

In this paper, a passive, air-breathing four-cell micro direct methanol fuel cell (µDMFC) stack featuring a fuel delivery structure for long-term and stable power supply is designed, fabricated and tested. The fuel is reserved in a T-shaped tank and diffuses through the porous diffusion layer to the catalyst at the anode. A peak power density of 25.7 mW cm-2 and a maximum power output of 113 mW are achieved with 3 M methanol at room temperature, and the stack can produce 60 mW of power, even though only 5% fuel remains in the reservoir. Combined with a low-input dc-dc convertor, the stack can realize a stable and optional constant voltage output from 1 V-6 V. The stack successfully powered a heavy metal sensor node for water environment monitoring 12 d continuously, with consumption of 10 mL 5 M methanol solution. As such, it is believed to be applicable for powering wireless sensor nodes.

New approach to effective diffusion coefficient evaluation in the nanostructured two-phase media

NASA Astrophysics Data System (ADS)

Lyashenko, Yu. O.; Liashenko, O. Y.; Morozovich, V. V.

2018-03-01

Most widely used basic and combined models for evaluation of the effective diffusion parameters of inhomogeneous two-phase zone are reviewed. A new combined model of effective medium is analyzed for the description of diffusion processes in the two-phase zones. In this model the effective diffusivity depends on the growth kinetic coefficients of each phase, the volume fractions of phases and on the additional parameter that generally characterizes the structure type of the two-phase zone. Our combined model describes two-phase zone evolution in the binary systems based on consideration of the diffusion fluxes through both phases. The Lattice Monte Carlo method was used to test the validity of different phenomenological models for evaluation of the effective diffusivity in nanostructured two-phase zones with different structural morphology.

Versatile Analysis of Single-Molecule Tracking Data by Comprehensive Testing against Monte Carlo Simulations

PubMed Central

Wieser, Stefan; Axmann, Markus; Schütz, Gerhard J.

2008-01-01

We propose here an approach for the analysis of single-molecule trajectories which is based on a comprehensive comparison of an experimental data set with multiple Monte Carlo simulations of the diffusion process. It allows quantitative data analysis, particularly whenever analytical treatment of a model is infeasible. Simulations are performed on a discrete parameter space and compared with the experimental results by a nonparametric statistical test. The method provides a matrix of p-values that assess the probability for having observed the experimental data at each setting of the model parameters. We show the testing approach for three typical situations observed in the cellular plasma membrane: i), free Brownian motion of the tracer, ii), hop diffusion of the tracer in a periodic meshwork of squares, and iii), transient binding of the tracer to slowly diffusing structures. By plotting the p-value as a function of the model parameters, one can easily identify the most consistent parameter settings but also recover mutual dependencies and ambiguities which are difficult to determine by standard fitting routines. Finally, we used the test to reanalyze previous data obtained on the diffusion of the glycosylphosphatidylinositol-protein CD59 in the plasma membrane of the human T24 cell line. PMID:18805933

A discussion on validity of the diffusion theory by Monte Carlo method

NASA Astrophysics Data System (ADS)

Peng, Dong-qing; Li, Hui; Xie, Shusen

2008-12-01

Diffusion theory was widely used as a basis of the experiments and methods in determining the optical properties of biological tissues. A simple analytical solution could be obtained easily from the diffusion equation after a series of approximations. Thus, a misinterpret of analytical solution would be made: while the effective attenuation coefficient of several semi-infinite bio-tissues were the same, the distribution of light fluence in the tissues would be the same. In order to assess the validity of knowledge above, depth resolved internal fluence of several semi-infinite biological tissues which have the same effective attenuation coefficient were simulated with wide collimated beam in the paper by using Monte Carlo method in different condition. Also, the influence of bio-tissue refractive index on the distribution of light fluence was discussed in detail. Our results showed that, when the refractive index of several bio-tissues which had the same effective attenuation coefficient were the same, the depth resolved internal fluence would be the same; otherwise, the depth resolved internal fluence would be not the same. The change of refractive index of tissue would have affection on the light depth distribution in tissue. Therefore, the refractive index is an important optical property of tissue, and should be taken in account while using the diffusion approximation theory.

A new Monte Carlo code for light transport in biological tissue.

PubMed

Torres-García, Eugenio; Oros-Pantoja, Rigoberto; Aranda-Lara, Liliana; Vieyra-Reyes, Patricia

2018-04-01

The aim of this work was to develop an event-by-event Monte Carlo code for light transport (called MCLTmx) to identify and quantify ballistic, diffuse, and absorbed photons, as well as their interaction coordinates inside the biological tissue. The mean free path length was computed between two interactions for scattering or absorption processes, and if necessary scatter angles were calculated, until the photon disappeared or went out of region of interest. A three-layer array (air-tissue-air) was used, forming a semi-infinite sandwich. The light source was placed at (0,0,0), emitting towards (0,0,1). The input data were: refractive indices, target thickness (0.02, 0.05, 0.1, 0.5, and 1 cm), number of particle histories, and λ from which the code calculated: anisotropy, scattering, and absorption coefficients. Validation presents differences less than 0.1% compared with that reported in the literature. The MCLTmx code discriminates between ballistic and diffuse photons, and inside of biological tissue, it calculates: specular reflection, diffuse reflection, ballistics transmission, diffuse transmission and absorption, and all parameters dependent on wavelength and thickness. The MCLTmx code can be useful for light transport inside any medium by changing the parameters that describe the new medium: anisotropy, dispersion and attenuation coefficients, and refractive indices for specific wavelength.

Complex Geometric Models of Diffusion and Relaxation in Healthy and Damaged White Matter

PubMed Central

Farrell, Jonathan A.D.; Smith, Seth A.; Reich, Daniel S.; Calabresi, Peter A.; van Zijl, Peter C.M.

2010-01-01

Which aspects of tissue microstructure affect diffusion weighted MRI signals? Prior models, many of which use Monte-Carlo simulations, have focused on relatively simple models of the cellular microenvironment and have not considered important anatomic details. With the advent of higher-order analysis models for diffusion imaging, such as high-angular-resolution diffusion imaging (HARDI), more realistic models are necessary. This paper presents and evaluates the reproducibility of simulations of diffusion in complex geometries. Our framework is quantitative, does not require specialized hardware, is easily implemented with little programming experience, and is freely available as open-source software. Models may include compartments with different diffusivities, permeabilities, and T2 time constants using both parametric (e.g., spheres and cylinders) and arbitrary (e.g., mesh-based) geometries. Three-dimensional diffusion displacement-probability functions are mapped with high reproducibility, and thus can be readily used to assess reproducibility of diffusion-derived contrasts. PMID:19739233

Knot probability of polygons subjected to a force: a Monte Carlo study

NASA Astrophysics Data System (ADS)

Janse van Rensburg, E. J.; Orlandini, E.; Tesi, M. C.; Whittington, S. G.

2008-01-01

We use Monte Carlo methods to study the knot probability of lattice polygons on the cubic lattice in the presence of an external force f. The force is coupled to the span of the polygons along a lattice direction, say the z-direction. If the force is negative polygons are squeezed (the compressive regime), while positive forces tend to stretch the polygons along the z-direction (the tensile regime). For sufficiently large positive forces we verify that the Pincus scaling law in the force-extension curve holds. At a fixed number of edges n the knot probability is a decreasing function of the force. For a fixed force the knot probability approaches unity as 1 - exp(-α0(f)n + o(n)), where α0(f) is positive and a decreasing function of f. We also examine the average of the absolute value of the writhe and we verify the square root growth law (known for f = 0) for all values of f.

Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows.

PubMed

Moussawi, A; Derzsy, N; Lin, X; Szymanski, B K; Korniss, G

2017-09-15

Cascading failures are a critical vulnerability of complex information or infrastructure networks. Here we investigate the properties of load-based cascading failures in real and synthetic spatially-embedded network structures, and propose mitigation strategies to reduce the severity of damages caused by such failures. We introduce a stochastic method for optimal heterogeneous distribution of resources (node capacities) subject to a fixed total cost. Additionally, we design and compare the performance of networks with N-stable and (N-1)-stable network-capacity allocations by triggering cascades using various real-world node-attack and node-failure scenarios. We show that failure mitigation through increased node protection can be effectively achieved against single-node failures. However, mitigating against multiple node failures is much more difficult due to the combinatorial increase in possible sets of initially failing nodes. We analyze the robustness of the system with increasing protection, and find that a critical tolerance exists at which the system undergoes a phase transition, and above which the network almost completely survives an attack. Moreover, we show that cascade-size distributions measured in this region exhibit a power-law decay. Finally, we find a strong correlation between cascade sizes induced by individual nodes and sets of nodes. We also show that network topology alone is a weak predictor in determining the progression of cascading failures.

Simple, efficient allocation of modelling runs on heterogeneous clusters with MPI

USGS Publications Warehouse

Donato, David I.

2017-01-01

In scientific modelling and computation, the choice of an appropriate method for allocating tasks for parallel processing depends on the computational setting and on the nature of the computation. The allocation of independent but similar computational tasks, such as modelling runs or Monte Carlo trials, among the nodes of a heterogeneous computational cluster is a special case that has not been specifically evaluated previously. A simulation study shows that a method of on-demand (that is, worker-initiated) pulling from a bag of tasks in this case leads to reliably short makespans for computational jobs despite heterogeneity both within and between cluster nodes. A simple reference implementation in the C programming language with the Message Passing Interface (MPI) is provided.

Monte Carlo simulation of near-infrared light propagation in realistic adult head models with hair follicles

NASA Astrophysics Data System (ADS)

Pan, Boan; Fang, Xiang; Liu, Weichao; Li, Nanxi; Zhao, Ke; Li, Ting

2018-02-01

Near infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) has been used to measure brain activation, which are clinically important. Monte Carlo simulation has been applied to the near infrared light propagation model in biological tissue, and has the function of predicting diffusion and brain activation. However, previous studies have rarely considered hair and hair follicles as a contributing factor. Here, we attempt to use MCVM (Monte Carlo simulation based on 3D voxelized media) to examine light transmission, absorption, fluence, spatial sensitivity distribution (SSD) and brain activation judgement in the presence or absence of the hair follicles. The data in this study is a series of high-resolution cryosectional color photograph of a standing Chinse male adult. We found that the number of photons transmitted under the scalp decreases dramatically and the photons exported to detector is also decreasing, as the density of hair follicles increases. If there is no hair follicle, the above data increase and has the maximum value. Meanwhile, the light distribution and brain activation have a stable change along with the change of hair follicles density. The findings indicated hair follicles make influence of NIRS in light distribution and brain activation judgement.

A kinetic Monte Carlo approach to diffusion-controlled thermal desorption spectroscopy

NASA Astrophysics Data System (ADS)

Schablitzki, T.; Rogal, J.; Drautz, R.

2017-06-01

Atomistic simulations of thermal desorption spectra for effusion from bulk materials to characterize binding or trapping sites are a challenging task as large system sizes as well as extended time scales are required. Here, we introduce an approach where we combine kinetic Monte Carlo with an analytic approximation of the superbasins within the framework of absorbing Markov chains. We apply our approach to the effusion of hydrogen from BCC iron, where the diffusion within bulk grains is coarse grained using absorbing Markov chains, which provide an exact solution of the dynamics within a superbasin. Our analytic approximation to the superbasin is transferable with respect to grain size and elliptical shapes and can be applied in simulations with constant temperature as well as constant heating rate. The resulting thermal desorption spectra are in close agreement with direct kinetic Monte Carlo simulations, but the calculations are computationally much more efficient. Our approach is thus applicable to much larger system sizes and provides a first step towards an atomistic understanding of the influence of structural features on the position and shape of peaks in thermal desorption spectra. This article is part of the themed issue 'The challenges of hydrogen and metals'.

Consistent second-order boundary implementations for convection-diffusion lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Zhang, Liangqi; Yang, Shiliang; Zeng, Zhong; Chew, Jia Wei

2018-02-01

In this study, an alternative second-order boundary scheme is proposed under the framework of the convection-diffusion lattice Boltzmann (LB) method for both straight and curved geometries. With the proposed scheme, boundary implementations are developed for the Dirichlet, Neumann and linear Robin conditions in a consistent way. The Chapman-Enskog analysis and the Hermite polynomial expansion technique are first applied to derive the explicit expression for the general distribution function with second-order accuracy. Then, the macroscopic variables involved in the expression for the distribution function is determined by the prescribed macroscopic constraints and the known distribution functions after streaming [see the paragraph after Eq. (29) for the discussions of the "streaming step" in LB method]. After that, the unknown distribution functions are obtained from the derived macroscopic information at the boundary nodes. For straight boundaries, boundary nodes are directly placed at the physical boundary surface, and the present scheme is applied directly. When extending the present scheme to curved geometries, a local curvilinear coordinate system and first-order Taylor expansion are introduced to relate the macroscopic variables at the boundary nodes to the physical constraints at the curved boundary surface. In essence, the unknown distribution functions at the boundary node are derived from the known distribution functions at the same node in accordance with the macroscopic boundary conditions at the surface. Therefore, the advantages of the present boundary implementations are (i) the locality, i.e., no information from neighboring fluid nodes is required; (ii) the consistency, i.e., the physical boundary constraints are directly applied when determining the macroscopic variables at the boundary nodes, thus the three kinds of conditions are realized in a consistent way. It should be noted that the present focus is on two-dimensional cases, and theoretical derivations as well as the numerical validations are performed in the framework of the two-dimensional five-velocity lattice model.

Collective diffusion in carbon nanotubes: Crossover between one dimension and three dimensions

NASA Astrophysics Data System (ADS)

Chen, Pei-Rong; Xu, Zhi-Cheng; Gu, Yu; Zhong, Wei-Rong

2016-08-01

Using non-equilibrium molecular dynamics and Monte Carlo methods, we study the collective diffusion of helium in carbon nanotubes. The results show that the collective diffusion coefficient (CDC) increases with the dimension of the channel. The collective diffusion coefficient has a linear relationship with the temperature and the concentration. There exist a ballistic transport in short carbon nanotubes and a diffusive transport in long carbon nanotubes. Fick’s law has an invalid region in the nanoscale channel. Project supported by the National Natural Science Foundation of China (Grant Nos. 11004082 and 11291240477), the Natural Science Foundation of Guangdong Province, China (Grant No. 2014A030313367), and the Fundamental Research Funds for the Central Universities, Jinan University (Grant No. 11614341).

A numerical solution for the diffusion equation in hydrogeologic systems

USGS Publications Warehouse

Ishii, A.L.; Healy, R.W.; Striegl, Robert G.

1989-01-01

The documentation of a computer code for the numerical solution of the linear diffusion equation in one or two dimensions in Cartesian or cylindrical coordinates is presented. Applications of the program include molecular diffusion, heat conduction, and fluid flow in confined systems. The flow media may be anisotropic and heterogeneous. The model is formulated by replacing the continuous linear diffusion equation by discrete finite-difference approximations at each node in a block-centered grid. The resulting matrix equation is solved by the method of preconditioned conjugate gradients. The conjugate gradient method does not require the estimation of iteration parameters and is guaranteed convergent in the absence of rounding error. The matrixes are preconditioned to decrease the steps to convergence. The model allows the specification of any number of boundary conditions for any number of stress periods, and the output of a summary table for selected nodes showing flux and the concentration of the flux quantity for each time step. The model is written in a modular format for ease of modification. The model was verified by comparison of numerical and analytical solutions for cases of molecular diffusion, two-dimensional heat transfer, and axisymmetric radial saturated fluid flow. Application of the model to a hypothetical two-dimensional field situation of gas diffusion in the unsaturated zone is demonstrated. The input and output files are included as a check on program installation. The definition of variables, input requirements, flow chart, and program listing are included in the attachments. (USGS)

Slow-down or speed-up of inter- and intra-cluster diffusion of controversial knowledge in stubborn communities based on a small world network

NASA Astrophysics Data System (ADS)

Ausloos, Marcel

2015-06-01

Diffusion of knowledge is expected to be huge when agents are open minded. The report concerns a more difficult diffusion case when communities are made of stubborn agents. Communities having markedly different opinions are for example the Neocreationist and Intelligent Design Proponents (IDP), on one hand, and the Darwinian Evolution Defenders (DED), on the other hand. The case of knowledge diffusion within such communities is studied here on a network based on an adjacency matrix built from time ordered selected quotations of agents, whence for inter- and intra-communities. The network is intrinsically directed and not necessarily reciprocal. Thus, the adjacency matrices have complex eigenvalues; the eigenvectors present complex components. A quantification of the slow-down or speed-up effects of information diffusion in such temporal networks, with non-Markovian contact sequences, can be made by comparing the real time dependent (directed) network to its counterpart, the time aggregated (undirected) network, - which has real eigenvalues. In order to do so, small world networks which both contain an odd number of nodes are studied and compared to similar networks with an even number of nodes. It is found that (i) the diffusion of knowledge is more difficult on the largest networks; (ii) the network size influences the slowing-down or speeding-up diffusion process. Interestingly, it is observed that (iii) the diffusion of knowledge is slower in IDP and faster in DED communities. It is suggested that the finding can be "rationalized", if some "scientific quality" and "publication habit" is attributed to the agents, as common sense would guess. This finding offers some opening discussion toward tying scientific knowledge to belief.

Unusual metastasis of left colon cancer: considerations on two cases.

PubMed

Gubitosi, Adelmo; Moccia, Giancarlo; Malinconico, Francesca Antonella; Gilio, Francesco; Iside, Giovanni; Califano, Umberto G A; Foroni, Fabrizio; Ruggiero, Roberto; Docimo, Giovanni; Parmeggiani, Domenico; Agresti, Massimo

2009-04-01

Usually, left colon cancer metastasis concerns liver, abdominal lymph nodes and lungs. Other localizations are quite rare occurrences. In spite of this, some uncommon metastasis sites are reported in literature, such as: peritoneum, ovaries, uterus, kidney testis, bones, thyroid, oral cavity and central nervous system. We report two cases of unusual localizations of left colon cancer metastasis localization, one into the retroperitoneal space and the other at the left axillary lynphnodes and between liver and pancreas. In the first reported case the diffusion pathway may have been the lymphatic mesocolic vessels, partially left in place from the previous surgery. In the second case the alleged metastatic lane may have been through the periumbilical lymph nodes to the parasternal lymph nodes and then to the internal mammary ones, finally reaching the axillary limph nodes.

Enhanced diffusion with abnormal temperature dependence in underdamped space-periodic systems subject to time-periodic driving

NASA Astrophysics Data System (ADS)

Marchenko, I. G.; Marchenko, I. I.; Zhiglo, A. V.

2018-01-01

We present a study of the diffusion enhancement of underdamped Brownian particles in a one-dimensional symmetric space-periodic potential due to external symmetric time-periodic driving with zero mean. We show that the diffusivity can be enhanced by many orders of magnitude at an appropriate choice of the driving amplitude and frequency. The diffusivity demonstrates abnormal (decreasing) temperature dependence at the driving amplitudes exceeding a certain value. At any fixed driving frequency Ω normal temperature dependence of the diffusivity is restored at low enough temperatures, T

Matching pursuit parallel decomposition of seismic data

NASA Astrophysics Data System (ADS)

Li, Chuanhui; Zhang, Fanchang

2017-07-01

In order to improve the computation speed of matching pursuit decomposition of seismic data, a matching pursuit parallel algorithm is designed in this paper. We pick a fixed number of envelope peaks from the current signal in every iteration according to the number of compute nodes and assign them to the compute nodes on average to search the optimal Morlet wavelets in parallel. With the help of parallel computer systems and Message Passing Interface, the parallel algorithm gives full play to the advantages of parallel computing to significantly improve the computation speed of the matching pursuit decomposition and also has good expandability. Besides, searching only one optimal Morlet wavelet by every compute node in every iteration is the most efficient implementation.

Cooperation in scale-free networks with limited associative capacities

NASA Astrophysics Data System (ADS)

Poncela, Julia; Gómez-Gardeñes, Jesús; Moreno, Yamir

2011-05-01

In this work we study the effect of limiting the number of interactions (the associative capacity) that a node can establish per round of a prisoner’s dilemma game. We focus on the way this limitation influences the level of cooperation sustained by scale-free networks. We show that when the game includes cooperation costs, limiting the associative capacity of nodes to a fixed quantity renders in some cases larger values of cooperation than in the unrestricted scenario. This allows one to define an optimum capacity for which cooperation is maximally enhanced. Finally, for the case without cooperation costs, we find that even a tight limitation of the associative capacity of nodes yields the same levels of cooperation as in the original network.

Digital micromirror device as amplitude diffuser for multiple-plane phase retrieval

NASA Astrophysics Data System (ADS)

Abregana, Timothy Joseph T.; Hermosa, Nathaniel P.; Almoro, Percival F.

2017-06-01

Previous implementations of the phase diffuser used in the multiple-plane phase retrieval method included a diffuser glass plate with fixed optical properties or a programmable yet expensive spatial light modulator. Here a model for phase retrieval based on a digital micromirror device as amplitude diffuser is presented. The technique offers programmable, convenient and low-cost amplitude diffuser for a non-stagnating iterative phase retrieval. The technique is demonstrated in the reconstructions of smooth object wavefronts.

Towards Standardization of X-ray Beam Filters in Digital Mammography and Digital Breast Tomosynthesis: Monte Carlo simulations and analytical modelling

PubMed Central

Shrestha, Suman; Vedantham, Srinivasan; Karellas, Andrew

2017-01-01

In digital breast tomosynthesis and digital mammography, the x-ray beam filter material and thickness vary between systems. Replacing K-edge filters with Al was investigated with the intent to reduce exposure duration and to simplify system design. Tungsten target x-ray spectra were simulated with K-edge filters (50μm Rh; 50μm Ag) and Al filters of varying thickness. Monte Carlo simulations were conducted to quantify the x-ray scatter from various filters alone, scatter-to-primary ratio (SPR) with compressed breasts, and to determine the radiation dose to the breast. These data were used to analytically compute the signal-difference-to-noise ratio (SDNR) at unit (1 mGy) mean glandular dose (MGD) for W/Rh and W/Ag spectra. At SDNR matched between K-edge and Al filtered spectra, the reductions in exposure duration and MGD were quantified for three strategies: (i) fixed Al thickness and matched tube potential in kilovolts (kV); (ii) fixed Al thickness and varying the kV to match the half-value layer (HVL) between Al and K-edge filtered spectra; and, (iii) matched kV and varying the Al thickness to match the HVL between Al and K-edge filtered spectra. Monte Carlo simulations indicate that the SPR with and without the breast were not different between Al and K-edge filters. Modelling for fixed Al thickness (700μm) and kV matched to K-edge filtered spectra, identical SDNR was achieved with 37–57% reduction in exposure duration and with 2–20% reduction in MGD, depending on breast thickness. Modelling for fixed Al thickness (700μm) and HVL matched by increasing the kV over [0,4] range, identical SDNR was achieved with 62–65% decrease in exposure duration and with 2–24% reduction in MGD, depending on breast thickness. For kV and HVL matched to K-edge filtered spectra by varying Al filter thickness over [700,880]μm range, identical SDNR was achieved with 23–56% reduction in exposure duration and 2–20% reduction in MGD, depending on breast thickness. These simulations indicate that increased fluence with Al filter of fixed or variable thickness substantially decreases exposure duration while providing for similar image quality with moderate reduction in MGD. PMID:28075335

A Handbook of Sound and Vibration Parameters

DTIC Science & Technology

1978-09-18

fixed in space. (Reference 1.) no motion atay node Static Divergence: (See Divergence.) Statistical Energy Analysis (SEA): Statistical energy analysis is...parameters of the circuits come from statistics of the vibrational characteristics of the structure. Statistical energy analysis is uniquely successful

Protograph LDPC Codes with Node Degrees at Least 3

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher

2006-01-01

In this paper we present protograph codes with a small number of degree-3 nodes and one high degree node. The iterative decoding threshold for proposed rate 1/2 codes are lower, by about 0.2 dB, than the best known irregular LDPC codes with degree at least 3. The main motivation is to gain linear minimum distance to achieve low error floor. Also to construct rate-compatible protograph-based LDPC codes for fixed block length that simultaneously achieves low iterative decoding threshold and linear minimum distance. We start with a rate 1/2 protograph LDPC code with degree-3 nodes and one high degree node. Higher rate codes are obtained by connecting check nodes with degree-2 non-transmitted nodes. This is equivalent to constraint combining in the protograph. The condition where all constraints are combined corresponds to the highest rate code. This constraint must be connected to nodes of degree at least three for the graph to have linear minimum distance. Thus having node degree at least 3 for rate 1/2 guarantees linear minimum distance property to be preserved for higher rates. Through examples we show that the iterative decoding threshold as low as 0.544 dB can be achieved for small protographs with node degrees at least three. A family of low- to high-rate codes with minimum distance linearly increasing in block size and with capacity-approaching performance thresholds is presented. FPGA simulation results for a few example codes show that the proposed codes perform as predicted.

Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks

PubMed Central

Clune, Jeff

2017-01-01

A long-term goal of AI is to produce agents that can learn a diversity of skills throughout their lifetimes and continuously improve those skills via experience. A longstanding obstacle towards that goal is catastrophic forgetting, which is when learning new information erases previously learned information. Catastrophic forgetting occurs in artificial neural networks (ANNs), which have fueled most recent advances in AI. A recent paper proposed that catastrophic forgetting in ANNs can be reduced by promoting modularity, which can limit forgetting by isolating task information to specific clusters of nodes and connections (functional modules). While the prior work did show that modular ANNs suffered less from catastrophic forgetting, it was not able to produce ANNs that possessed task-specific functional modules, thereby leaving the main theory regarding modularity and forgetting untested. We introduce diffusion-based neuromodulation, which simulates the release of diffusing, neuromodulatory chemicals within an ANN that can modulate (i.e. up or down regulate) learning in a spatial region. On the simple diagnostic problem from the prior work, diffusion-based neuromodulation 1) induces task-specific learning in groups of nodes and connections (task-specific localized learning), which 2) produces functional modules for each subtask, and 3) yields higher performance by eliminating catastrophic forgetting. Overall, our results suggest that diffusion-based neuromodulation promotes task-specific localized learning and functional modularity, which can help solve the challenging, but important problem of catastrophic forgetting. PMID:29145413

Gas levitator having fixed levitation node for containerless processing

NASA Technical Reports Server (NTRS)

Berge, L. H.; Oran, W. A.; Theiss, M. (Inventor)

1981-01-01

A method and apparatus is disclosed for levitating a specimen of material in a containerless environment at a stable nodal position independent of gravity. An elongated levitation tube has a contoured interior in the form of convergent section, constriction, and a divergent section in which the levitation node is created. A gas flow control means prevents separation of flow from the interior walls in the region of a specimen. The apparatus provides for levitating and heating the specimen simultaneously by combustion of a suitable gas mixture combined with an inert gas.

Virtual Network Embedding via Monte Carlo Tree Search.

PubMed

Haeri, Soroush; Trajkovic, Ljiljana

2018-02-01

Network virtualization helps overcome shortcomings of the current Internet architecture. The virtualized network architecture enables coexistence of multiple virtual networks (VNs) on an existing physical infrastructure. VN embedding (VNE) problem, which deals with the embedding of VN components onto a physical network, is known to be -hard. In this paper, we propose two VNE algorithms: MaVEn-M and MaVEn-S. MaVEn-M employs the multicommodity flow algorithm for virtual link mapping while MaVEn-S uses the shortest-path algorithm. They formalize the virtual node mapping problem by using the Markov decision process (MDP) framework and devise action policies (node mappings) for the proposed MDP using the Monte Carlo tree search algorithm. Service providers may adjust the execution time of the MaVEn algorithms based on the traffic load of VN requests. The objective of the algorithms is to maximize the profit of infrastructure providers. We develop a discrete event VNE simulator to implement and evaluate performance of MaVEn-M, MaVEn-S, and several recently proposed VNE algorithms. We introduce profitability as a new performance metric that captures both acceptance and revenue to cost ratios. Simulation results show that the proposed algorithms find more profitable solutions than the existing algorithms. Given additional computation time, they further improve embedding solutions.

Light propagation along the pericardium meridian at human wrist as evidenced by the optical experiment and Monte Carlo method.

PubMed

Jiang, Yi-fan; Chen, Chang-shui; Liu, Xiao-mei; Liu, Rong-ting; Liu, Song-hao

2015-04-01

To explore the characteristics of light propagation along the Pericardium Meridian and its surrounding areas at human wrist by using optical experiment and Monte Carlo method. An experiment was carried out to obtain the distribution of diffuse light on Pericardium Meridian line and its surrounding areas at the wrist, and then a simplified model based on the anatomical structure was proposed to simulate the light transportation within the same area by using Monte Carlo method. The experimental results showed strong accordance with the Monte Carlo simulation that the light propagation along the Pericardium Meridian had an advantage over its surrounding areas at the wrist. The advantage of light transport along Pericardium Merdian line was related to components and structure of tissue, also the anatomical structure of the area that the Pericardium Meridian line runs.

Stochastic many-body perturbation theory for anharmonic molecular vibrations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hermes, Matthew R.; Hirata, So, E-mail: sohirata@illinois.edu; CREST, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012

2014-08-28

A new quantum Monte Carlo (QMC) method for anharmonic vibrational zero-point energies and transition frequencies is developed, which combines the diagrammatic vibrational many-body perturbation theory based on the Dyson equation with Monte Carlo integration. The infinite sums of the diagrammatic and thus size-consistent first- and second-order anharmonic corrections to the energy and self-energy are expressed as sums of a few m- or 2m-dimensional integrals of wave functions and a potential energy surface (PES) (m is the vibrational degrees of freedom). Each of these integrals is computed as the integrand (including the value of the PES) divided by the value ofmore » a judiciously chosen weight function evaluated on demand at geometries distributed randomly but according to the weight function via the Metropolis algorithm. In this way, the method completely avoids cumbersome evaluation and storage of high-order force constants necessary in the original formulation of the vibrational perturbation theory; it furthermore allows even higher-order force constants essentially up to an infinite order to be taken into account in a scalable, memory-efficient algorithm. The diagrammatic contributions to the frequency-dependent self-energies that are stochastically evaluated at discrete frequencies can be reliably interpolated, allowing the self-consistent solutions to the Dyson equation to be obtained. This method, therefore, can compute directly and stochastically the transition frequencies of fundamentals and overtones as well as their relative intensities as pole strengths, without fixed-node errors that plague some QMC. It is shown that, for an identical PES, the new method reproduces the correct deterministic values of the energies and frequencies within a few cm{sup −1} and pole strengths within a few thousandths. With the values of a PES evaluated on the fly at random geometries, the new method captures a noticeably greater proportion of anharmonic effects.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haugen, Carl C.; Forget, Benoit; Smith, Kord S.

Most high performance computing systems being deployed currently and envisioned for the future are based on making use of heavy parallelism across many computational nodes and many concurrent cores. These types of heavily parallel systems often have relatively little memory per core but large amounts of computing capability. This places a significant constraint on how data storage is handled in many Monte Carlo codes. This is made even more significant in fully coupled multiphysics simulations, which requires simulations of many physical phenomena be carried out concurrently on individual processing nodes, which further reduces the amount of memory available for storagemore » of Monte Carlo data. As such, there has been a move towards on-the-fly nuclear data generation to reduce memory requirements associated with interpolation between pre-generated large nuclear data tables for a selection of system temperatures. Methods have been previously developed and implemented in MIT’s OpenMC Monte Carlo code for both the resolved resonance regime and the unresolved resonance regime, but are currently absent for the thermal energy regime. While there are many components involved in generating a thermal neutron scattering cross section on-the-fly, this work will focus on a proposed method for determining the energy and direction of a neutron after a thermal incoherent inelastic scattering event. This work proposes a rejection sampling based method using the thermal scattering kernel to determine the correct outgoing energy and angle. The goal of this project is to be able to treat the full S (a, ß) kernel for graphite, to assist in high fidelity simulations of the TREAT reactor at Idaho National Laboratory. The method is, however, sufficiently general to be applicable in other thermal scattering materials, and can be initially validated with the continuous analytic free gas model.« less

A first principles kinetic Monte Carlo investigation of the adsorption and mobility of gadolinium on the (100) surface of tungsten

NASA Astrophysics Data System (ADS)

Samin, Adib J.; Zhang, Jinsuo

2017-05-01

An accurate characterization of lanthanide adsorption and mobility on tungsten surfaces is important for pyroprocessing. In the present study, the adsorption and diffusion of gadolinium on the (100) surface of tungsten was investigated. It was found that the hollow sites were the most energetically favorable for the adsorption. It was further observed that a magnetic moment was induced following the adsorption of gadolinium on the tungsten surface and that the system with adsorbed hollow sites had the largest magnetization. A pathway for the surface diffusion of gadolinium was determined to occur by hopping between the nearest neighbor hollow sites via the bridge site and the activation energy for the hop was calculated to be 0.75 eV. The surface diffusion process was further assessed using two distinct kinetic Monte Carlo models; one that accounted for lateral adsorbate interactions up to the second nearest neighbor and one that did not account for such interatomic interactions in the adlayer. When the lateral interactions were included in the simulations, the diffusivity was observed to have a strong dependence on coverage (for the coverage values being studied). The effects of lateral interactions were further observed in a one-dimensional simulation of the diffusion equation where the asymmetry in the surface coverage profile upon its approach to a steady state distribution was clear in comparison with the simulations which did not account for those interactions.

Epithelial cancers and photon migration: Monte Carlo simulations and diffuse reflectance measurements

NASA Astrophysics Data System (ADS)

Tubiana, Jerome; Kass, Alex J.; Newman, Maya Y.; Levitz, David

2015-07-01

Detecting pre-cancer in epithelial tissues such as the cervix is a challenging task in low-resources settings. In an effort to achieve low cost cervical cancer screening and diagnostic method for use in low resource settings, mobile colposcopes that use a smartphone as their engine have been developed. Designing image analysis software suited for this task requires proper modeling of light propagation from the abnormalities inside tissues to the camera of the smartphones. Different simulation methods have been developed in the past, by solving light diffusion equations, or running Monte Carlo simulations. Several algorithms exist for the latter, including MCML and the recently developed MCX. For imaging purpose, the observable parameter of interest is the reflectance profile of a tissue under some specific pattern of illumination and optical setup. Extensions of the MCX algorithm to simulate this observable under these conditions were developed. These extensions were validated against MCML and diffusion theory for the simple case of contact measurements, and reflectance profiles under colposcopy imaging geometry were also simulated. To validate this model, the diffuse reflectance profiles of tissue phantoms were measured with a spectrometer under several illumination and optical settings for various homogeneous tissues phantoms. The measured reflectance profiles showed a non-trivial deviation across the spectrum. Measurements of an added absorber experiment on a series of phantoms showed that absorption of dye scales linearly when fit to both MCX and diffusion models. More work is needed to integrate a pupil into the experiment.

Reconstructing in-vivo reflectance spectrum of pigmented skin lesion by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Wang, Shuang; He, Qingli; Zhao, Jianhua; Lui, Harvey; Zeng, Haishan

2012-03-01

In dermatology applications, diffuse reflectance spectroscopy has been extensively investigated as a promising tool for the noninvasive method to distinguish melanoma from benign pigmented skin lesion (nevus), which is concentrated with the skin chromophores like melanin and hemoglobin. We carried out a theoretical study to examine melanin distribution in human skin tissue and establish a practical optical model for further pigmented skin investigation. The theoretical simulation was using junctional nevus as an example. A multiple layer skin optical model was developed on established anatomy structures of skin, the published optical parameters of different skin layers, blood and melanin. Monte Carlo simulation was used to model the interaction between excitation light and skin tissue and rebuild the diffuse reflectance process from skin tissue. A testified methodology was adopted to determine melanin contents in human skin based on in vivo diffuse reflectance spectra. The rebuild diffuse reflectance spectra were investigated by adding melanin into different layers of the theoretical model. One of in vivo reflectance spectra from Junctional nevi and their surrounding normal skin was studied by compare the ratio between nevus and normal skin tissue in both the experimental and simulated diffuse reflectance spectra. The simulation result showed a good agreement with our clinical measurements, which indicated that our research method, including the spectral ratio method, skin optical model and modifying the melanin content in the model, could be applied in further theoretical simulation of pigmented skin lesions.

Mobility of large clusters on a semiconductor surface: Kinetic Monte Carlo simulation results

NASA Astrophysics Data System (ADS)

M, Esen; A, T. Tüzemen; M, Ozdemir

2016-01-01

The mobility of clusters on a semiconductor surface for various values of cluster size is studied as a function of temperature by kinetic Monte Carlo method. The cluster resides on the surface of a square grid. Kinetic processes such as the diffusion of single particles on the surface, their attachment and detachment to/from clusters, diffusion of particles along cluster edges are considered. The clusters considered in this study consist of 150-6000 atoms per cluster on average. A statistical probability of motion to each direction is assigned to each particle where a particle with four nearest neighbors is assumed to be immobile. The mobility of a cluster is found from the root mean square displacement of the center of mass of the cluster as a function of time. It is found that the diffusion coefficient of clusters goes as D = A(T)Nα where N is the average number of particles in the cluster, A(T) is a temperature-dependent constant and α is a parameter with a value of about -0.64 < α < -0.75. The value of α is found to be independent of cluster sizes and temperature values (170-220 K) considered in this study. As the diffusion along the perimeter of the cluster becomes prohibitive, the exponent approaches a value of -0.5. The diffusion coefficient is found to change by one order of magnitude as a function of cluster size.

Linear and nonlinear susceptibilities from diffusion quantum Monte Carlo: application to periodic hydrogen chains.

PubMed

Umari, P; Marzari, Nicola

2009-09-07

We calculate the linear and nonlinear susceptibilities of periodic longitudinal chains of hydrogen dimers with different bond-length alternations using a diffusion quantum Monte Carlo approach. These quantities are derived from the changes in electronic polarization as a function of applied finite electric field--an approach we recently introduced and made possible by the use of a Berry-phase, many-body electric-enthalpy functional. Calculated susceptibilities and hypersusceptibilities are found to be in excellent agreement with the best estimates available from quantum chemistry--usually extrapolations to the infinite-chain limit of calculations for chains of finite length. It is found that while exchange effects dominate the proper description of the susceptibilities, second hypersusceptibilities are greatly affected by electronic correlations. We also assess how different approximations to the nodal surface of the many-body wave function affect the accuracy of the calculated susceptibilities.

Binding energies from diffusion Monte Carlo for the MB-pol H{sub 2}O and D{sub 2}O dimer: A comparison to experimental values

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mallory, Joel D.; Mandelshtam, Vladimir A.

2015-10-14

The diffusion Monte Carlo (DMC) method is applied to compute the ground state energies of the water monomer and dimer and their D{sub 2}O isotopomers using MB-pol; the most recent and most accurate ab inito-based potential energy surface (PES). MB-pol has already demonstrated excellent agreement with high level electronic structure data, as well as agreement with some experimental, spectroscopic, and thermodynamic data. Here, the DMC binding energies of (H{sub 2}O){sub 2} and (D{sub 2}O){sub 2} agree with the corresponding values obtained from velocity map imaging within, respectively, 0.01 and 0.02 kcal/mol. This work adds two more valuable data points thatmore » highlight the accuracy of the MB-pol PES.« less

ANALYSIS OF THE MOMENTS METHOD EXPERIMENT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kloster, R.L.

1959-09-01

Monte Cario calculations show the effects of a plane water-air boundary on both fast neutron and gamma dose rates. Multigroup diffusion theory calculation for a reactor source shows the effects of a plane water-air boundary on thermal neutron dose rate. The results of Monte Cario and multigroup calculations are compared with experimental values. The predicted boundary effect for fast neutrons of 7.3% agrees within 16% with the measured effect of 6.3%. The gamma detector did not measure a boundary effect because it lacked sensitivity at low energies. However, the effect predicted for gamma rays of 5 to 10% is asmore » large as that for neutrons. An estimate of the boundary effect for thermal neutrons from a PoBe source is obtained from the results of muitigroup diffusion theory calcuiations for a reactor source. The calculated boundary effect agrees within 13% with the measured values. (auth)« less

Fixed-Time Outer Synchronization of Complex Networks with Noise Coupling

NASA Astrophysics Data System (ADS)

Shi, Hong-Jun; Miao, Lian-Ying; Sun, Yong-Zheng; Liu, Mao-Xing

2018-03-01

In this paper, the fixed-time outer synchronization of complex networks with noise coupling is investigated. Based on the theory of fixed-time stability and matrix inequalities, sufficient conditions for fixed-time outer synchronization are established and the estimation of the upper bound of the setting time is obtained. The result shows that the setting time can be adjusted to a desired value regardless of the initial states. Numerical simulations are performed to verify the effectiveness of the theoretical results. The effects of control parameters and the density of controlled nodes on the converging time are studied. Supported by the National Natural Science Foundation of China under Grant Nos. 11711530203 and 11771443, and the Fundamental Research Funds for the Central Universities under Grant No. 2015XKMS076

Wideband, mobile networking technologies

NASA Astrophysics Data System (ADS)

Hyer, Kevin L.; Bowen, Douglas G.; Pulsipher, Dennis C.

2005-05-01

Ubiquitous communications will be the next era in the evolving communications revolution. From the human perspective, access to information will be instantaneous and provide a revolution in services available to both the consumer and the warfighter. Services will be from the mundane - anytime, anywhere access to any movie ever made - to the vital - reliable and immediate access to the analyzed real-time video from the multi-spectral sensors scanning for snipers in the next block. In the former example, the services rely on a fixed infrastructure of networking devices housed in controlled environments and coupled to fixed terrestrial fiber backbones - in the latter, the services are derived from an agile and highly mobile ad-hoc backbone established in a matter of minutes by size, weight, and power-constrained platforms. This network must mitigate significant changes in the transmission media caused by millisecond-scale atmospheric temperature variations, the deployment of smoke, or the drifting of a cloud. It must mitigate against structural obscurations, jet wash, or incapacitation of a node. To maintain vital connectivity, the mobile backbone must be predictive and self-healing on both near-real-time and real-time time scales. The nodes of this network must be reconfigurable to mitigate intentional and environmental jammers, block attackers, and alleviate interoperability concerns caused by changing standards. The nodes must support multi-access of disparate waveform and protocols.

MROrchestrator: A Fine-Grained Resource Orchestration Framework for MapReduce Clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharma, Bikash; Prabhakar, Ramya; Kandemir, Mahmut

2012-01-01

Efficient resource management in data centers and clouds running large distributed data processing frameworks like MapReduce is crucial for enhancing the performance of hosted applications and boosting resource utilization. However, existing resource scheduling schemes in Hadoop MapReduce allocate resources at the granularity of fixed-size, static portions of nodes, called slots. In this work, we show that MapReduce jobs have widely varying demands for multiple resources, making the static and fixed-size slot-level resource allocation a poor choice both from the performance and resource utilization standpoints. Furthermore, lack of co-ordination in the management of mul- tiple resources across nodes prevents dynamic slotmore » reconfigura- tion, and leads to resource contention. Motivated by this, we propose MROrchestrator, a MapReduce resource Orchestrator framework, which can dynamically identify resource bottlenecks, and resolve them through fine-grained, co-ordinated, and on- demand resource allocations. We have implemented MROrches- trator on two 24-node native and virtualized Hadoop clusters. Experimental results with a suite of representative MapReduce benchmarks demonstrate up to 38% reduction in job completion times, and up to 25% increase in resource utilization. We further show how popular resource managers like NGM and Mesos when augmented with MROrchestrator can hike up their performance.« less

Approximating high angular resolution apparent diffusion coefficient profiles using spherical harmonics under BiGaussian assumption

NASA Astrophysics Data System (ADS)

Cao, Ning; Liang, Xuwei; Zhuang, Qi; Zhang, Jun

2009-02-01

Magnetic Resonance Imaging (MRI) techniques have achieved much importance in providing visual and quantitative information of human body. Diffusion MRI is the only non-invasive tool to obtain information of the neural fiber networks of the human brain. The traditional Diffusion Tensor Imaging (DTI) is only capable of characterizing Gaussian diffusion. High Angular Resolution Diffusion Imaging (HARDI) extends its ability to model more complex diffusion processes. Spherical harmonic series truncated to a certain degree is used in recent studies to describe the measured non-Gaussian Apparent Diffusion Coefficient (ADC) profile. In this study, we use the sampling theorem on band-limited spherical harmonics to choose a suitable degree to truncate the spherical harmonic series in the sense of Signal-to-Noise Ratio (SNR), and use Monte Carlo integration to compute the spherical harmonic transform of human brain data obtained from icosahedral schema.

Relativistic collective diffusion in one-dimensional systems

NASA Astrophysics Data System (ADS)

Lin, Gui-Wu; Lam, Yu-Yiu; Zheng, Dong-Qin; Zhong, Wei-Rong

2018-05-01

The relativistic collective diffusion in one-dimensional molecular system is investigated through nonequilibrium molecular dynamics with Monte Carlo methods. We have proposed the relationship among the speed, the temperature, the density distribution and the collective diffusion coefficient of particles in a relativistic moving system. It is found that the relativistic speed of the system has no effect on the temperature, but the collective diffusion coefficient decreases to zero as the velocity of the system approaches to the speed of light. The collective diffusion coefficient is modified as D‧ = D(1 ‑w2 c2 )3 2 for satisfying the relativistic circumstances. The present results may contribute to the understanding of the behavior of the particles transport diffusion in a high speed system, as well as enlighten the study of biological metabolism at relativistic high speed situation.

RNA folding kinetics using Monte Carlo and Gillespie algorithms.

PubMed

Clote, Peter; Bayegan, Amir H

2018-04-01

RNA secondary structure folding kinetics is known to be important for the biological function of certain processes, such as the hok/sok system in E. coli. Although linear algebra provides an exact computational solution of secondary structure folding kinetics with respect to the Turner energy model for tiny ([Formula: see text]20 nt) RNA sequences, the folding kinetics for larger sequences can only be approximated by binning structures into macrostates in a coarse-grained model, or by repeatedly simulating secondary structure folding with either the Monte Carlo algorithm or the Gillespie algorithm. Here we investigate the relation between the Monte Carlo algorithm and the Gillespie algorithm. We prove that asymptotically, the expected time for a K-step trajectory of the Monte Carlo algorithm is equal to [Formula: see text] times that of the Gillespie algorithm, where [Formula: see text] denotes the Boltzmann expected network degree. If the network is regular (i.e. every node has the same degree), then the mean first passage time (MFPT) computed by the Monte Carlo algorithm is equal to MFPT computed by the Gillespie algorithm multiplied by [Formula: see text]; however, this is not true for non-regular networks. In particular, RNA secondary structure folding kinetics, as computed by the Monte Carlo algorithm, is not equal to the folding kinetics, as computed by the Gillespie algorithm, although the mean first passage times are roughly correlated. Simulation software for RNA secondary structure folding according to the Monte Carlo and Gillespie algorithms is publicly available, as is our software to compute the expected degree of the network of secondary structures of a given RNA sequence-see http://bioinformatics.bc.edu/clote/RNAexpNumNbors .

Monte Carlo model of light transport in multi-layered tubular organs

NASA Astrophysics Data System (ADS)

Zhang, Yunyao; Zhu, Jingping; Zhang, Ning

2017-02-01

We present a Monte Carlo static light migration model (Endo-MCML) to simulate endoscopic optical spectroscopy for tubular organs such as esophagus and colon. The model employs multi-layered hollow cylinder which emitting and receiving light both from the inner boundary to meet the conditions of endoscopy. Inhomogeneous sphere can be added in tissue layers to model cancer or other abnormal changes. The 3D light distribution and exit angle would be recorded as results. The accuracy of the model has been verified by Multi-layered Monte Carlo(MCML) method and NIRFAST. This model can be used for the forward modeling of light transport during endoscopically diffuse optical spectroscopy, light scattering spectroscopy, reflectance spectroscopy and other static optical detection or imaging technologies.

Diffusing-wave polarimetry for tissue diagnostics

NASA Astrophysics Data System (ADS)

Macdonald, Callum; Doronin, Alexander; Peña, Adrian F.; Eccles, Michael; Meglinski, Igor

2014-03-01

We exploit the directional awareness of circularly and/or elliptically polarized light propagating within media which exhibit high numbers of scattering events. By tracking the Stokes vector of the detected light on the Poincaŕe sphere, we demonstrate its applicability for characterization of anisotropy of scattering. A phenomenological model is shown to have an excellent agreement with the experimental data and with the results obtained by the polarization tracking Monte Carlo model, developed in house. By analogy to diffusing-wave spectroscopy we call this approach diffusing-wave polarimetry, and illustrate its utility in probing cancerous and non-cancerous tissue samplesin vitro for diagnostic purposes.

Sign problem and Monte Carlo calculations beyond Lefschetz thimbles

DOE PAGES

Alexandru, Andrei; Basar, Gokce; Bedaque, Paulo F.; ...

2016-05-10

We point out that Monte Carlo simulations of theories with severe sign problems can be profitably performed over manifolds in complex space different from the one with fixed imaginary part of the action (“Lefschetz thimble”). We describe a family of such manifolds that interpolate between the tangent space at one critical point (where the sign problem is milder compared to the real plane but in some cases still severe) and the union of relevant thimbles (where the sign problem is mild but a multimodal distribution function complicates the Monte Carlo sampling). As a result, we exemplify this approach using amore » simple 0+1 dimensional fermion model previously used on sign problem studies and show that it can solve the model for some parameter values where a solution using Lefschetz thimbles was elusive.« less

Stabilizing canonical-ensemble calculations in the auxiliary-field Monte Carlo method

NASA Astrophysics Data System (ADS)

Gilbreth, C. N.; Alhassid, Y.

2015-03-01

Quantum Monte Carlo methods are powerful techniques for studying strongly interacting Fermi systems. However, implementing these methods on computers with finite-precision arithmetic requires careful attention to numerical stability. In the auxiliary-field Monte Carlo (AFMC) method, low-temperature or large-model-space calculations require numerically stabilized matrix multiplication. When adapting methods used in the grand-canonical ensemble to the canonical ensemble of fixed particle number, the numerical stabilization increases the number of required floating-point operations for computing observables by a factor of the size of the single-particle model space, and thus can greatly limit the systems that can be studied. We describe an improved method for stabilizing canonical-ensemble calculations in AFMC that exhibits better scaling, and present numerical tests that demonstrate the accuracy and improved performance of the method.

Maximum Likelihood and Minimum Distance Applied to Univariate Mixture Distributions.

ERIC Educational Resources Information Center

Wang, Yuh-Yin Wu; Schafer, William D.

This Monte-Carlo study compared modified Newton (NW), expectation-maximization algorithm (EM), and minimum Cramer-von Mises distance (MD), used to estimate parameters of univariate mixtures of two components. Data sets were fixed at size 160 and manipulated by mean separation, variance ratio, component proportion, and non-normality. Results…

Teaching Classical Statistical Mechanics: A Simulation Approach.

ERIC Educational Resources Information Center

Sauer, G.

1981-01-01

Describes a one-dimensional model for an ideal gas to study development of disordered motion in Newtonian mechanics. A Monte Carlo procedure for simulation of the statistical ensemble of an ideal gas with fixed total energy is developed. Compares both approaches for a pseudoexperimental foundation of statistical mechanics. (Author/JN)

Progress in lattice gauge theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Creutz, M.

1983-01-01

These lectures first provide an overview of the current status of lattice gauge theory calculations. They then review some technical points on group integration, gauge fixing, and order parameters. Various Monte Carlo algorithms are discussed. Finally, alternatives to the Wilson action are considered in the context of universality for the continuum limit. 41 references.

Wavelength converter placement for different RWA algorithms in wavelength-routed all-optical networks

NASA Astrophysics Data System (ADS)

Chu, Xiaowen; Li, Bo; Chlamtac, Imrich

2002-07-01

Sparse wavelength conversion and appropriate routing and wavelength assignment (RWA) algorithms are the two key factors in improving the blocking performance in wavelength-routed all-optical networks. It has been shown that the optimal placement of a limited number of wavelength converters in an arbitrary mesh network is an NP complete problem. There have been various heuristic algorithms proposed in the literature, in which most of them assume that a static routing and random wavelength assignment RWA algorithm is employed. However, the existing work shows that fixed-alternate routing and dynamic routing RWA algorithms can achieve much better blocking performance. Our study in this paper further demonstrates that the wavelength converter placement and RWA algorithms are closely related in the sense that a well designed wavelength converter placement mechanism for a particular RWA algorithm might not work well with a different RWA algorithm. Therefore, the wavelength converter placement and the RWA have to be considered jointly. The objective of this paper is to investigate the wavelength converter placement problem under fixed-alternate routing algorithm and least-loaded routing algorithm. Under the fixed-alternate routing algorithm, we propose a heuristic algorithm called Minimum Blocking Probability First (MBPF) algorithm for wavelength converter placement. Under the least-loaded routing algorithm, we propose a heuristic converter placement algorithm called Weighted Maximum Segment Length (WMSL) algorithm. The objective of the converter placement algorithm is to minimize the overall blocking probability. Extensive simulation studies have been carried out over three typical mesh networks, including the 14-node NSFNET, 19-node EON and 38-node CTNET. We observe that the proposed algorithms not only outperform existing wavelength converter placement algorithms by a large margin, but they also can achieve almost the same performance comparing with full wavelength conversion under the same RWA algorithm.

High-efficiency wavefunction updates for large scale Quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Kent, Paul; McDaniel, Tyler; Li, Ying Wai; D'Azevedo, Ed

Within ab intio Quantum Monte Carlo (QMC) simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunctions. The evaluation of each Monte Carlo move requires finding the determinant of a dense matrix, which is traditionally iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. For calculations with thousands of electrons, this operation dominates the execution profile. We propose a novel rank- k delayed update scheme. This strategy enables probability evaluation for multiple successive Monte Carlo moves, with application of accepted moves to the matrices delayed until after a predetermined number of moves, k. Accepted events grouped in this manner are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency. This procedure does not change the underlying Monte Carlo sampling or the sampling efficiency. For large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude speedups can be obtained on both multi-core CPU and on GPUs, making this algorithm highly advantageous for current petascale and future exascale computations.

Learning to Predict Social Influence in Complex Networks

DTIC Science & Technology

2012-03-29

03/2010 – 17/03/2012 Abstract: First, we addressed the problem of analyzing information diffusion process in a social network using two kinds...algorithm which avoids the inner loop optimization during the search. We tested the performance using the structures of four real world networks, and...result of information diffusion that starts from the node. 2 We use “infected” and “activated” interchangeably. Efficient Discovery of Influential

Mobility based key management technique for multicast security in mobile ad hoc networks.

PubMed

Madhusudhanan, B; Chitra, S; Rajan, C

2015-01-01

In MANET multicasting, forward and backward secrecy result in increased packet drop rate owing to mobility. Frequent rekeying causes large message overhead which increases energy consumption and end-to-end delay. Particularly, the prevailing group key management techniques cause frequent mobility and disconnections. So there is a need to design a multicast key management technique to overcome these problems. In this paper, we propose the mobility based key management technique for multicast security in MANET. Initially, the nodes are categorized according to their stability index which is estimated based on the link availability and mobility. A multicast tree is constructed such that for every weak node, there is a strong parent node. A session key-based encryption technique is utilized to transmit a multicast data. The rekeying process is performed periodically by the initiator node. The rekeying interval is fixed depending on the node category so that this technique greatly minimizes the rekeying overhead. By simulation results, we show that our proposed approach reduces the packet drop rate and improves the data confidentiality.

BridgeRank: A novel fast centrality measure based on local structure of the network

NASA Astrophysics Data System (ADS)

Salavati, Chiman; Abdollahpouri, Alireza; Manbari, Zhaleh

2018-04-01

Ranking nodes in complex networks have become an important task in many application domains. In a complex network, influential nodes are those that have the most spreading ability. Thus, identifying influential nodes based on their spreading ability is a fundamental task in different applications such as viral marketing. One of the most important centrality measures to ranking nodes is closeness centrality which is efficient but suffers from high computational complexity O(n3) . This paper tries to improve closeness centrality by utilizing the local structure of nodes and presents a new ranking algorithm, called BridgeRank centrality. The proposed method computes local centrality value for each node. For this purpose, at first, communities are detected and the relationship between communities is completely ignored. Then, by applying a centrality in each community, only one best critical node from each community is extracted. Finally, the nodes are ranked based on computing the sum of the shortest path length of nodes to obtained critical nodes. We have also modified the proposed method by weighting the original BridgeRank and selecting several nodes from each community based on the density of that community. Our method can find the best nodes with high spread ability and low time complexity, which make it applicable to large-scale networks. To evaluate the performance of the proposed method, we use the SIR diffusion model. Finally, experiments on real and artificial networks show that our method is able to identify influential nodes so efficiently, and achieves better performance compared to other recent methods.

Development of response models for the Earth Radiation Budget Experiment (ERBE) sensors. Part 1: Dynamic models and computer simulations for the ERBE nonscanner, scanner and solar monitor sensors

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Choi, Sang H.; Chrisman, Dan A., Jr.; Samms, Richard W.

1987-01-01

Dynamic models and computer simulations were developed for the radiometric sensors utilized in the Earth Radiation Budget Experiment (ERBE). The models were developed to understand performance, improve measurement accuracy by updating model parameters and provide the constants needed for the count conversion algorithms. Model simulations were compared with the sensor's actual responses demonstrated in the ground and inflight calibrations. The models consider thermal and radiative exchange effects, surface specularity, spectral dependence of a filter, radiative interactions among an enclosure's nodes, partial specular and diffuse enclosure surface characteristics and steady-state and transient sensor responses. Relatively few sensor nodes were chosen for the models since there is an accuracy tradeoff between increasing the number of nodes and approximating parameters such as the sensor's size, material properties, geometry, and enclosure surface characteristics. Given that the temperature gradients within a node and between nodes are small enough, approximating with only a few nodes does not jeopardize the accuracy required to perform the parameter estimates and error analyses.

Dynamic heterogeneity in crossover spin facilitated model of supercooled liquid and fractional Stokes-Einstein relation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, Seo-Woo; Kim, Soree; Jung, YounJoon, E-mail: yjjung@snu.ac.kr

Kinetically constrained models have gained much interest as models that assign the origins of interesting dynamic properties of supercooled liquids to dynamical facilitation mechanisms that have been revealed in many experiments and numerical simulations. In this work, we investigate the dynamic heterogeneity in the fragile-to-strong liquid via Monte Carlo method using the model that linearly interpolates between the strong liquid-like behavior and the fragile liquid-like behavior by an asymmetry parameter b. When the asymmetry parameter is sufficiently small, smooth fragile-to-strong transition is observed both in the relaxation time and the diffusion constant. Using these physical quantities, we investigate fractional Stokes-Einsteinmore » relations observed in this model. When b is fixed, the system shows constant power law exponent under the temperature change, and the exponent has the value between that of the Frederickson-Andersen model and the East model. Furthermore, we investigate the dynamic length scale of our systems and also find the crossover relation between the relaxation time. We ascribe the competition between energetically favored symmetric relaxation mechanism and entropically favored asymmetric relaxation mechanism to the fragile-to-strong crossover behavior.« less

Temporal behaviour of a corner separation in a radial vaned diffuser of a centrifugal compressor operating near surge

NASA Astrophysics Data System (ADS)

Marsan, A.; Trébinjac, I.; Coste, S.; Leroy, G.

2013-12-01

The temporal behaviour of a flow separation in the hub-suction side corner of a transonic diffuser is studied thanks to unsteady numerical simulations based on the phase-lagged approach. The validity of the numerical results is confirmed by comparison with experimental unsteady pressure measurements. An analysis of the instantaneous skin-friction pattern and particles trajectories is presented. It highlights the topology of the separation and its temporal behaviour. The major result is that, despite of a highly time-dependent core flow, the separation is found to be a "fixed unsteady separation" characterized by a fixed location of the main saddle of the separation but an extent of the stall region modulated by the pressure waves induced by the impeller-diffuser interaction.

3D Model of Cytokinetic Contractile Ring Assembly: Node-Mediated and Backup Pathways

NASA Astrophysics Data System (ADS)

Bidone, Tamara; Vavylonis, Dimitrios

Cytokinetic ring assembly in model organism fission yeast is a dynamic process, involving condensation of a network of actin filaments and myosin motors bound to the cell membrane through cortical nodes. A 3D computational model of ring assembly illustrates how the combined activities of myosin motors, filament crosslinkers and actin turnover lead to robust ring formation [Bidone et al. Biophys. J, 2014]. We modeled the importance of the physical properties of node movement along the cell membrane and of myosin recruitment to nodes. Experiments by D. Zhang (Temasek Life Sciences) show that tethering of the cortical endoplasmic reticulum (ER) to the plasma membrane modulates the speed of node condensation and the degree of node clumping. We captured the trend observed in these experiments by changes in the node drag coefficient and initial node distribution in simulations PM. The model predicted that reducing crosslinking activities in ER tethering mutants with faster node speed enhances actomyosin clumping. We developed a model of how tilted and/or misplaced rings assemble in cells that lack the node structural component anillin-like Mid1 and thus fail to recruit myosin II to nodes independently of actin. If actin-dependent binding of diffusive myosin to the cortex is incorporated into the model, it generates progressively elongating cortical actomyosin strands with fluctuating actin bundles at the tails. These stands often close into a ring, similar to observations by the group of J.Q. Wu (The Ohio State University). NIH R01GM098430.

Monte Carlo Simulation of Visible Light Diffuse Reflection in Neonatal Skin

NASA Astrophysics Data System (ADS)

Atencio, J. A. Delgado; Rodríguez, E. E.; Rodríguez, A. Cornejo; Rivas-Silva, J. F.

2008-04-01

Neonatal jaundice is a medical condition that happens commonly in newborns as result of desbalance between the production and the elimination of the bilirubin. Around 50% of newborns in term and something more of 60% of the near-term becomes jaundiced in the first week of life. This excess of bilirubin in the blood is exhibited in the skin, the sclera of the eyes and the mucous of mouth like a characteristic yellow coloration. In this work we make several numerical simulations of the spectral diffuse reflection for the skin of newborns that present different values of the biological parameters (bilirubin content, grade of pigmentation and content of blood) that characterize it. These simulations will allow us to evaluate the influence of these parameters on the experimental determination of bilirubin by noninvasive optical methods. The simulations are made in the spectral range of 400-700 nm using the Monte Carlo code MCML and two programs developed in LabVIEW by the authors. We simulated the diffuse reflection spectrum of neonatal skin for concentrations of bilirubin in skin that covers an ample range: from physiological to harmful numbers. We considered the influence of factors such as grade of pigmentation and content of blood.

Diffusion-Based Model for Synaptic Molecular Communication Channel.

PubMed

Khan, Tooba; Bilgin, Bilgesu A; Akan, Ozgur B

2017-06-01

Computational methods have been extensively used to understand the underlying dynamics of molecular communication methods employed by nature. One very effective and popular approach is to utilize a Monte Carlo simulation. Although it is very reliable, this method can have a very high computational cost, which in some cases renders the simulation impractical. Therefore, in this paper, for the special case of an excitatory synaptic molecular communication channel, we present a novel mathematical model for the diffusion and binding of neurotransmitters that takes into account the effects of synaptic geometry in 3-D space and re-absorption of neurotransmitters by the transmitting neuron. Based on this model we develop a fast deterministic algorithm, which calculates expected value of the output of this channel, namely, the amplitude of excitatory postsynaptic potential (EPSP), for given synaptic parameters. We validate our algorithm by a Monte Carlo simulation, which shows total agreement between the results of the two methods. Finally, we utilize our model to quantify the effects of variation in synaptic parameters, such as position of release site, receptor density, size of postsynaptic density, diffusion coefficient, uptake probability, and number of neurotransmitters in a vesicle, on maximum number of bound receptors that directly affect the peak amplitude of EPSP.

Modeling active capping efficacy. 1. Metal and organometal contaminated sediment remediation.

PubMed

Viana, Priscilla Z; Yin, Ke; Rockne, Karl J

2008-12-01

Cd, Cr, Pb, Ag, As, Ba, Hg, CH3Hg, and CN transport through sand, granular activated carbon (GAC), organoclay, shredded tires, and apatite caps was modeled by deterministic and Monte Carlo methods. Time to 10% breakthrough, 30 and 100 yr cumulative release were metrics of effectiveness. Effective caps prevented above-cap concentrations from exceeding USEPA acute criteria at 100 yr assuming below-cap concentrations at solubility. Sand caps performed best under diffusion due to the greater diffusive path length. Apatite had the best advective performance for Cd, Cr, and Pb. Organoclay performed best for Ag, As, Ba, CH3Hg, and CN. Organoclay and apatite were equally effective for Hg. Monte Carlo analysis was used to determine output sensitivity. Sand was effective under diffusion for Cr within the 50% confidence interval (CI), for Cd and Pb (75% CI), and for As, Hg, and CH3Hg (95% CI). Under diffusion and advection, apatite was effective for Cd, Pb, and Hg (75% CI) and organoclay was effective for Hg and CH3Hg (50% CI). GAC and shredded tires performed relatively poorly. Although no single cap is a panacea, apatite and organoclay have the broadest range of effectiveness. Cap performance is most sensitive to the partitioning coefficient and hydraulic conductivity, indicating the importance of accurate site-specific measurement for these parameters.

The Harrison Diffusion Kinetics Regimes in Solute Grain Boundary Diffusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belova, Irina; Fiedler, T; Kulkarni, Nagraj S

2012-01-01

Knowledge of the limits of the principal Harrison kinetics regimes (Type-A, B and C) for grain boundary diffusion is very important for the correct analysis of the depth profiles in a tracer diffusion experiment. These regimes for self-diffusion have been extensively studied in the past by making use of the phenomenological Lattice Monte Carlo (LMC) method with the result that the limits are now well established. The relationship of those self-diffusion limits to the corresponding ones for solute diffusion in the presence of solute segregation to the grain boundaries remains unclear. In the present study, the influence of solute segregationmore » on the limits is investigated with the LMC method for the well-known parallel grain boundary slab model by showing the equivalence of two diffusion models. It is shown which diffusion parameters are useful for identifying the limits of the Harrison kinetics regimes for solute grain boundary diffusion. It is also shown how the measured segregation factor from the diffusion experiment in the Harrison Type-B kinetics regime may differ from the global segregation factor.« less

Diffusion in Colocation Contact Networks: The Impact of Nodal Spatiotemporal Dynamics.

PubMed

Thomas, Bryce; Jurdak, Raja; Zhao, Kun; Atkinson, Ian

2016-01-01

Temporal contact networks are studied to understand dynamic spreading phenomena such as communicable diseases or information dissemination. To establish how spatiotemporal dynamics of nodes impact spreading potential in colocation contact networks, we propose "inducement-shuffling" null models which break one or more correlations between times, locations and nodes. By reconfiguring the time and/or location of each node's presence in the network, these models induce alternative sets of colocation events giving rise to contact networks with varying spreading potential. This enables second-order causal reasoning about how correlations in nodes' spatiotemporal preferences not only lead to a given contact network but ultimately influence the network's spreading potential. We find the correlation between nodes and times to be the greatest impediment to spreading, while the correlation between times and locations slightly catalyzes spreading. Under each of the presented null models we measure both the number of contacts and infection prevalence as a function of time, with the surprising finding that the two have no direct causality.

Modified free volume theory of self-diffusion and molecular theory of shear viscosity of liquid carbon dioxide.

PubMed

Nasrabad, Afshin Eskandari; Laghaei, Rozita; Eu, Byung Chan

2005-04-28

In previous work on the density fluctuation theory of transport coefficients of liquids, it was necessary to use empirical self-diffusion coefficients to calculate the transport coefficients (e.g., shear viscosity of carbon dioxide). In this work, the necessity of empirical input of the self-diffusion coefficients in the calculation of shear viscosity is removed, and the theory is thus made a self-contained molecular theory of transport coefficients of liquids, albeit it contains an empirical parameter in the subcritical regime. The required self-diffusion coefficients of liquid carbon dioxide are calculated by using the modified free volume theory for which the generic van der Waals equation of state and Monte Carlo simulations are combined to accurately compute the mean free volume by means of statistical mechanics. They have been computed as a function of density along four different isotherms and isobars. A Lennard-Jones site-site interaction potential was used to model the molecular carbon dioxide interaction. The density and temperature dependence of the theoretical self-diffusion coefficients are shown to be in excellent agreement with experimental data when the minimum critical free volume is identified with the molecular volume. The self-diffusion coefficients thus computed are then used to compute the density and temperature dependence of the shear viscosity of liquid carbon dioxide by employing the density fluctuation theory formula for shear viscosity as reported in an earlier paper (J. Chem. Phys. 2000, 112, 7118). The theoretical shear viscosity is shown to be robust and yields excellent density and temperature dependence for carbon dioxide. The pair correlation function appearing in the theory has been computed by Monte Carlo simulations.

Timing considerations for preclinical MRgRT: effects of ion diffusion, SNR and imaging times on FXG gel calibration

NASA Astrophysics Data System (ADS)

Welch, M.; Foltz, W. D.; Jaffray, D. A.

2015-01-01

Sub-millimeter resolution images are required for gel dosimeters to be used in preclinical research, which is challenging for MR probed ferrous xylenol-orange (FXG) dosimeters due to ion diffusion and inadequate SNR. A preclinical 7 T MR, small animal irradiator and FXG dosimeters were used in all experiments. Ion diffusion was analyzed using high resolution (0.2 mm/pixel) T1 MR images collected every 5 minutes, post-irradiation, for an hour. Using Fick's second law, ion diffusion was approximated for the first hour post-irradiation. SNR, T1 map precision and calibration fit were determined for two MR protocols: (1) 10 minute acquisition, 0.35mm/pixel and 3mm slices, (2) 45 minute acquisition, 0. 25 mm/pixel and 2 mm slices. SNR and T1 map precision were calculated using a Monte Carlo simulation. Calibration curves were determined by plotting R1 relaxation rates versus depth dose data, and fitting a linear trend line. Ion diffusion was estimated as 0.003mm2 in the first hour post-irradiation. For protocols (1) and (2) respectively, Monte Carlo simulation predicted T1 precisions of 3% and 5% within individual voxels using experimental SNRs; the corresponding measured T1 precisions were 8% and 12%. The linear trend lines reported slopes of 27 ± 3 Gy*s (R2: 0.80 ± 0.04) and 27 ± 4 Gy*s (R2: 0.90 ± 0.04). Ion diffusion is negligible within the first hour post-irradiation, and an accurate and reproducible calibration can be achieved in a preclinical setting with sub-millimeter resolution.

A novel information cascade model in online social networks

NASA Astrophysics Data System (ADS)

Tong, Chao; He, Wenbo; Niu, Jianwei; Xie, Zhongyu

2016-02-01

The spread and diffusion of information has become one of the hot issues in today's social network analysis. To analyze the spread of online social network information and the attribute of cascade, in this paper, we discuss the spread of two kinds of users' decisions for city-wide activities, namely the "want to take part in the activity" and "be interested in the activity", based on the users' attention in "DouBan" and the data of the city-wide activities. We analyze the characteristics of the activity-decision's spread in these aspects: the scale and scope of the cascade subgraph, the structure characteristic of the cascade subgraph, the topological attribute of spread tree, and the occurrence frequency of cascade subgraph. On this basis, we propose a new information spread model. Based on the classical independent diffusion model, we introduce three mechanisms, equal probability, similarity of nodes, and popularity of nodes, which can generate and affect the spread of information. Besides, by conducting the experiments in six different kinds of network data set, we compare the effects of three mechanisms above mentioned, totally six specific factors, on the spread of information, and put forward that the node's popularity plays an important role in the information spread.

Pattern Formation on Networks: from Localised Activity to Turing Patterns

PubMed Central

McCullen, Nick; Wagenknecht, Thomas

2016-01-01

Networks of interactions between competing species are used to model many complex systems, such as in genetics, evolutionary biology or sociology and knowledge of the patterns of activity they can exhibit is important for understanding their behaviour. The emergence of patterns on complex networks with reaction-diffusion dynamics is studied here, where node dynamics interact via diffusion via the network edges. Through the application of a generalisation of dynamical systems analysis this work reveals a fundamental connection between small-scale modes of activity on networks and localised pattern formation seen throughout science, such as solitons, breathers and localised buckling. The connection between solutions with a single and small numbers of activated nodes and the fully developed system-scale patterns are investigated computationally using numerical continuation methods. These techniques are also used to help reveal a much larger portion of of the full number of solutions that exist in the system at different parameter values. The importance of network structure is also highlighted, with a key role being played by nodes with a certain so-called optimal degree, on which the interaction between the reaction kinetics and the network structure organise the behaviour of the system. PMID:27273339

Monte Carlo simulations of magnetic properties of Kekulene structure bilayers separate by a nonmagnetic with RKKY interactions

NASA Astrophysics Data System (ADS)

Jabar, A.; Masrour, R.

2018-05-01

The magnetic properties of magnetic bilayers of Kekulene structure separate by a nonmagnetic layer with Ruderman-Kittel-Kasuya-Yosida (RKKY) exchange interactions with Ising spin model have been studied using Monte Carlo simulations. The RKKY interaction between the bilayers of Kekulene is considered for different distances. The transition temperature has been deduced from the magnetizations and magnetic susceptibilities partial for a fixed value of nonmagnetic layer. The reduced transition temperatures are also deduced from the total magnetization and total magnetic susceptibilities with different values of L. The magnetic hysteresis cycles of systems have been determined.

The probability of quantal secretion near a single calcium channel of an active zone.

PubMed Central

Bennett, M R; Farnell, L; Gibson, W G

2000-01-01

A Monte Carlo analysis has been made of calcium dynamics and quantal secretion at microdomains in which the calcium reaches very high concentrations over distances of <50 nm from a channel and for which calcium dynamics are dominated by diffusion. The kinetics of calcium ions in microdomains due to either the spontaneous or evoked opening of a calcium channel, both of which are stochastic events, are described in the presence of endogenous fixed and mobile buffers. Fluctuations in the number of calcium ions within 50 nm of a channel are considerable, with the standard deviation about half the mean. Within 10 nm of a channel these numbers of ions can give rise to calcium concentrations of the order of 100 microM. The temporal changes in free calcium and calcium bound to different affinity indicators in the volume of an entire varicosity or bouton following the opening of a single channel are also determined. A Monte Carlo analysis is also presented of how the dynamics of calcium ions at active zones, after the arrival of an action potential and the stochastic opening of a calcium channel, determine the probability of exocytosis from docked vesicles near the channel. The synaptic vesicles in active zones are found docked in a complex with their calcium-sensor associated proteins and a voltage-sensitive calcium channel, forming a secretory unit. The probability of quantal secretion from an isolated secretory unit has been determined for different distances of an open calcium channel from the calcium sensor within an individual unit: a threefold decrease in the probability of secretion of a quantum occurs with a doubling of the distance from 25 to 50 nm. The Monte Carlo analysis also shows that the probability of secretion of a quantum is most sensitive to the size of the single-channel current compared with its sensitivity to either the binding rates of the sites on the calcium-sensor protein or to the number of these sites that must bind a calcium ion to trigger exocytosis of a vesicle. PMID:10777721

Paired-agent fluorescent imaging to detect micrometastases in breast sentinel lymph node biopsy: experiment design and protocol development

NASA Astrophysics Data System (ADS)

Li, Chengyue; Xu, Xiaochun; Basheer, Yusairah; He, Yusheng; Sattar, Husain A.; Brankov, Jovan G.; Tichauer, Kenneth M.

2018-02-01

Sentinel lymph node status is a critical prognostic factor in breast cancer treatment and is essential to guide future adjuvant treatment. The estimation that 20-60% of micrometastases are missed by conventional pathology has created a demand for the development of more accurate approaches. Here, a paired-agent imaging approach is presented that employs a control imaging agent to allow rapid, quantitative mapping of microscopic populations of tumor cells in lymph nodes to guide pathology sectioning. To test the feasibility of this approach to identify micrometastases, healthy pig lymph nodes were stained with targeted and control imaging agent solution to evaluate the potential for the agents to diffuse into and out of intact nodes. Aby-029, an anti-EGFR affibody was labeled with IRDye 800CW (LICOR) as targeted agent and IRDye 700DX was hydrolyzed as a control agent. Lymph nodes were stained and rinsed by directly injecting the agents into the lymph nodes after immobilization in agarose gel. Subsequently, lymph nodes were frozen-sectioned and imaged under an 80-um resolution fluorescence imaging system (Pearl, LICOR) to confirm equivalence of spatial distribution of both agents in the entire node. The binding potentials were acquired by a pixel-by-pixel calculation and was found to be 0.02 +/- 0.06 along the lymph node in the absence of binding. The results demonstrate this approach's potential to enhance the sensitivity of lymph node pathology by detecting fewer than 1000 cell in a whole human lymph node.

Consequences of switching from a fixed 2 : 1 ratio of amoxicillin/clavulanate (CLSI) to a fixed concentration of clavulanate (EUCAST) for susceptibility testing of Escherichia coli.

PubMed

Leverstein-van Hall, Maurine A; Waar, Karola; Muilwijk, Jan; Cohen Stuart, James

2013-11-01

The CLSI recommends a fixed 2 : 1 ratio of co-amoxiclav for broth microdilution susceptibility testing of Enterobacteriaceae, while EUCAST recommends a fixed 2 mg/L clavulanate concentration. The aims of this study were: (i) to determine the influence of a switch from CLSI to EUCAST methodology on Escherichia coli susceptibility rates; (ii) to compare susceptibility results obtained using EUCAST-compliant microdilution with those from disc diffusion and the Etest; and (iii) to evaluate the clinical outcome of patients with E. coli sepsis treated with co-amoxiclav in relation to the susceptibility results obtained using either method. Resistance rates were determined in three laboratories that switched from CLSI to EUCAST cards with the Phoenix system (Becton Dickinson) as well as in 17 laboratories that continued to use CLSI cards with the VITEK 2 system (bioMérieux). In one laboratory, isolates were simultaneously tested by both the Phoenix system and either disc diffusion (n = 471) or the Etest (n = 113). Medical and laboratory records were reviewed for E. coli sepsis patients treated with co-amoxiclav monotherapy. Only laboratories that switched methodology showed an increase in resistance rates - from 19% in 2010 to 31% in 2011 (P < 0.0001). All isolates that tested susceptible by microdilution were also susceptible by disc diffusion or the Etest, but of 326 isolates that tested resistant by microdilution, 43% and 59% tested susceptible by disc diffusion and the Etest, respectively. Among the 89 patients included there was a better correlation between clinical response and measured MICs using the Phoenix system than the Etest. EUCAST methodology resulted in higher co-amoxiclav E. coli resistance rates than CLSI methodology, but correlated better with clinical outcome. EUCAST-compliant microdilution and disc diffusion provided discrepant results.

Multiple relaxations of the cluster surface diffusion in a homoepitaxial SrTiO3 layer

NASA Astrophysics Data System (ADS)

Woo, Chang-Su; Chu, Kanghyun; Song, Jong-Hyun; Yang, Chan-Ho

2018-03-01

We examine the surface diffusion process of adatomic clusters on a (001)-oriented SrTiO3 single crystal using reflection high energy electron diffraction (RHEED). We find that the recovery curve of the RHEED intensity acquired after a homoepitaxial half-layer growth can be accurately fit into a double exponential function, indicating the existence of two dominant relaxation mechanisms. The characteristic relaxation times at selected growth temperatures are investigated to determine the diffusion activation barriers of 0.67 eV and 0.91 eV, respectively. The Monte Carlo simulation of the cluster hopping model suggests that the decrease in the number of dimeric and trimeric clusters during surface diffusion is the origin of the observed relaxation phenomena.

Scalable Domain Decomposed Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

O'Brien, Matthew Joseph

In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation. The main algorithms we consider are: • Domain decomposition of constructive solid geometry: enables extremely large calculations in which the background geometry is too large to fit in the memory of a single computational node. • Load Balancing: keeps the workload per processor as even as possible so the calculation runs efficiently. • Global Particle Find: if particles are on the wrong processor, globally resolve their locations to the correct processor based on particle coordinate and background domain. • Visualizing constructive solid geometry, sourcing particles, deciding that particle streaming communication is completed and spatial redecomposition. These algorithms are some of the most important parallel algorithms required for domain decomposed Monte Carlo particle transport. We demonstrate that our previous algorithms were not scalable, prove that our new algorithms are scalable, and run some of the algorithms up to 2 million MPI processes on the Sequoia supercomputer.

Threshold-based epidemic dynamics in systems with memory

NASA Astrophysics Data System (ADS)

Bodych, Marcin; Ganguly, Niloy; Krueger, Tyll; Mukherjee, Animesh; Siegmund-Schultze, Rainer; Sikdar, Sandipan

2016-11-01

In this article we analyze an epidemic dynamics model (SI) where we assume that there are k susceptible states, that is a node would require multiple (k) contacts before it gets infected. In specific, we provide a theoretical framework for studying diffusion rate in complete graphs and d-regular trees with extensions to dense random graphs. We observe that irrespective of the topology, the diffusion process could be divided into two distinct phases: i) the initial phase, where the diffusion process is slow, followed by ii) the residual phase where the diffusion rate increases manifold. In fact, the initial phase acts as an indicator for the total diffusion time in dense graphs. The most remarkable lesson from this investigation is that such a diffusion process could be controlled and even contained if acted upon within its initial phase.

Clustering model for transmission of the SARS virus: application to epidemic control and risk assessment

NASA Astrophysics Data System (ADS)

Small, Michael; Tse, C. K.

2005-06-01

We propose a new four state model for disease transmission and illustrate the model with data from the 2003 SARS epidemic in Hong Kong. The critical feature of this model is that the community is modelled as a small-world network of interconnected nodes. Each node is linked to a fixed number of immediate neighbors and a random number of geographically remote nodes. Transmission can only propagate between linked nodes. This model exhibits two features typical of SARS transmission: geographically localized outbreaks and “super-spreaders”. Neither of these features are evident in standard susceptible-infected-removed models of disease transmission. Our analysis indicates that “super-spreaders” may occur even if the infectiousness of all infected individuals is constant. Moreover, we find that nosocomial transmission in Hong Kong directly contributed to the severity of the outbreak and that by limiting individual exposure time to 3-5 days the extent of the SARS epidemic would have been minimal.

Joint Resource Optimization for Cognitive Sensor Networks with SWIPT-Enabled Relay.

PubMed

Lu, Weidang; Lin, Yuanrong; Peng, Hong; Nan, Tian; Liu, Xin

2017-09-13

Energy-constrained wireless networks, such as wireless sensor networks (WSNs), are usually powered by fixed energy supplies (e.g., batteries), which limits the operation time of networks. Simultaneous wireless information and power transfer (SWIPT) is a promising technique to prolong the lifetime of energy-constrained wireless networks. This paper investigates the performance of an underlay cognitive sensor network (CSN) with SWIPT-enabled relay node. In the CSN, the amplify-and-forward (AF) relay sensor node harvests energy from the ambient radio-frequency (RF) signals using power splitting-based relaying (PSR) protocol. Then, it helps forward the signal of source sensor node (SSN) to the destination sensor node (DSN) by using the harvested energy. We study the joint resource optimization including the transmit power and power splitting ratio to maximize CSN's achievable rate with the constraint that the interference caused by the CSN to the primary users (PUs) is within the permissible threshold. Simulation results show that the performance of our proposed joint resource optimization can be significantly improved.

I-MAC: an incorporation MAC for wireless sensor networks

NASA Astrophysics Data System (ADS)

Zhao, Jumin; Li, Yikun; Li, Dengao; Lin, Xiaojie

2017-11-01

This paper proposes an innovative MAC protocol called I-MAC. Protocol for wireless sensor networks, which combines the advantages of collision tolerance and collision cancellation. The protocol increases the number of antenna in wireless sensor nodes. The purpose is to monitor the occurrence of packet collisions by increasing the number of antenna in real time. The built-in identity structure is used in the frame structure in order to help the sending node to identify the location of the receiving node after a data packet collision is detected. Packets can be recovered from where the conflict occurred. In this way, we can monitor the conflict for a fixed period of time. It can improve the channel utilisation through changing the transmission probability of collision nodes and solve the problem of hidden terminal through collision feedback mechanism. We have evaluated our protocol. Our results show that the throughput of I-MAC is 5 percentage points higher than that of carrier sense multiple access/collision notification. The network utilisation of I-MAC is more than 92%.

Steady-State Electrodiffusion from the Nernst-Planck Equation Coupled to Local Equilibrium Monte Carlo Simulations.

PubMed

Boda, Dezső; Gillespie, Dirk

2012-03-13

We propose a procedure to compute the steady-state transport of charged particles based on the Nernst-Planck (NP) equation of electrodiffusion. To close the NP equation and to establish a relation between the concentration and electrochemical potential profiles, we introduce the Local Equilibrium Monte Carlo (LEMC) method. In this method, Grand Canonical Monte Carlo simulations are performed using the electrochemical potential specified for the distinct volume elements. An iteration procedure that self-consistently solves the NP and flux continuity equations with LEMC is shown to converge quickly. This NP+LEMC technique can be used in systems with diffusion of charged or uncharged particles in complex three-dimensional geometries, including systems with low concentrations and small applied voltages that are difficult for other particle simulation techniques.

Multilevel Sequential Monte Carlo Samplers for Normalizing Constants

DOE PAGES

Moral, Pierre Del; Jasra, Ajay; Law, Kody J. H.; ...

2017-08-24

This article considers the sequential Monte Carlo (SMC) approximation of ratios of normalizing constants associated to posterior distributions which in principle rely on continuum models. Therefore, the Monte Carlo estimation error and the discrete approximation error must be balanced. A multilevel strategy is utilized to substantially reduce the cost to obtain a given error level in the approximation as compared to standard estimators. Two estimators are considered and relative variance bounds are given. The theoretical results are numerically illustrated for two Bayesian inverse problems arising from elliptic partial differential equations (PDEs). The examples involve the inversion of observations of themore » solution of (i) a 1-dimensional Poisson equation to infer the diffusion coefficient, and (ii) a 2-dimensional Poisson equation to infer the external forcing.« less

Position, Orientation and Velocity Detection of Unmanned Underwater Vehicles (UUVs) Using an Optical Detector Array

PubMed Central

Pe’eri, Shachak; Thein, May-Win; Rzhanov, Yuri; Celikkol, Barbaros; Swift, M. Robinson

2017-01-01

This paper presents a proof-of-concept optical detector array sensor system to be used in Unmanned Underwater Vehicle (UUV) navigation. The performance of the developed optical detector array was evaluated for its capability to estimate the position, orientation and forward velocity of UUVs with respect to a light source fixed in underwater. The evaluations were conducted through Monte Carlo simulations and empirical tests under a variety of motion configurations. Monte Carlo simulations also evaluated the system total propagated uncertainty (TPU) by taking into account variations in the water column turbidity, temperature and hardware noise that may degrade the system performance. Empirical tests were conducted to estimate UUV position and velocity during its navigation to a light beacon. Monte Carlo simulation and empirical results support the use of the detector array system for optics based position feedback for UUV positioning applications. PMID:28758936

Monte Carlo Simulation of THz Multipliers

NASA Technical Reports Server (NTRS)

East, J.; Blakey, P.

1997-01-01

Schottky Barrier diode frequency multipliers are critical components in submillimeter and Thz space based earth observation systems. As the operating frequency of these multipliers has increased, the agreement between design predictions and experimental results has become poorer. The multiplier design is usually based on a nonlinear model using a form of harmonic balance and a model for the Schottky barrier diode. Conventional voltage dependent lumped element models do a poor job of predicting THz frequency performance. This paper will describe a large signal Monte Carlo simulation of Schottky barrier multipliers. The simulation is a time dependent particle field Monte Carlo simulation with ohmic and Schottky barrier boundary conditions included that has been combined with a fixed point solution for the nonlinear circuit interaction. The results in the paper will point out some important time constants in varactor operation and will describe the effects of current saturation and nonlinear resistances on multiplier operation.

Simulation studies of phase inversion in agitated vessels using a Monte Carlo technique.

PubMed

Yeo, Leslie Y; Matar, Omar K; Perez de Ortiz, E Susana; Hewitt, Geoffrey F

2002-04-15

A speculative study on the conditions under which phase inversion occurs in agitated liquid-liquid dispersions is conducted using a Monte Carlo technique. The simulation is based on a stochastic model, which accounts for fundamental physical processes such as drop deformation, breakup, and coalescence, and utilizes the minimization of interfacial energy as a criterion for phase inversion. Profiles of the interfacial energy indicate that a steady-state equilibrium is reached after a sufficiently large number of random moves and that predictions are insensitive to initial drop conditions. The calculated phase inversion holdup is observed to increase with increasing density and viscosity ratio, and to decrease with increasing agitation speed for a fixed viscosity ratio. It is also observed that, for a fixed viscosity ratio, the phase inversion holdup remains constant for large enough agitation speeds. The proposed model is therefore capable of achieving reasonable qualitative agreement with general experimental trends and of reproducing key features observed experimentally. The results of this investigation indicate that this simple stochastic method could be the basis upon which more advanced models for predicting phase inversion behavior can be developed.

MCNP Version 6.2 Release Notes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Werner, Christopher John; Bull, Jeffrey S.; Solomon, C. J.

Monte Carlo N-Particle or MCNP ® is a general-purpose Monte Carlo radiation-transport code designed to track many particle types over broad ranges of energies. This MCNP Version 6.2 follows the MCNP6.1.1 beta version and has been released in order to provide the radiation transport community with the latest feature developments and bug fixes for MCNP. Since the last release of MCNP major work has been conducted to improve the code base, add features, and provide tools to facilitate ease of use of MCNP version 6.2 as well as the analysis of results. These release notes serve as a general guidemore » for the new/improved physics, source, data, tallies, unstructured mesh, code enhancements and tools. For more detailed information on each of the topics, please refer to the appropriate references or the user manual which can be found at http://mcnp.lanl.gov. This release of MCNP version 6.2 contains 39 new features in addition to 172 bug fixes and code enhancements. There are still some 33 known issues the user should familiarize themselves with (see Appendix).« less

Present Status and Extensions of the Monte Carlo Performance Benchmark

NASA Astrophysics Data System (ADS)

Hoogenboom, J. Eduard; Petrovic, Bojan; Martin, William R.

2014-06-01

The NEA Monte Carlo Performance benchmark started in 2011 aiming to monitor over the years the abilities to perform a full-size Monte Carlo reactor core calculation with a detailed power production for each fuel pin with axial distribution. This paper gives an overview of the contributed results thus far. It shows that reaching a statistical accuracy of 1 % for most of the small fuel zones requires about 100 billion neutron histories. The efficiency of parallel execution of Monte Carlo codes on a large number of processor cores shows clear limitations for computer clusters with common type computer nodes. However, using true supercomputers the speedup of parallel calculations is increasing up to large numbers of processor cores. More experience is needed from calculations on true supercomputers using large numbers of processors in order to predict if the requested calculations can be done in a short time. As the specifications of the reactor geometry for this benchmark test are well suited for further investigations of full-core Monte Carlo calculations and a need is felt for testing other issues than its computational performance, proposals are presented for extending the benchmark to a suite of benchmark problems for evaluating fission source convergence for a system with a high dominance ratio, for coupling with thermal-hydraulics calculations to evaluate the use of different temperatures and coolant densities and to study the correctness and effectiveness of burnup calculations. Moreover, other contemporary proposals for a full-core calculation with realistic geometry and material composition will be discussed.

Monte Carlo algorithms for Brownian phylogenetic models.

PubMed

Horvilleur, Benjamin; Lartillot, Nicolas

2014-11-01

Brownian models have been introduced in phylogenetics for describing variation in substitution rates through time, with applications to molecular dating or to the comparative analysis of variation in substitution patterns among lineages. Thus far, however, the Monte Carlo implementations of these models have relied on crude approximations, in which the Brownian process is sampled only at the internal nodes of the phylogeny or at the midpoints along each branch, and the unknown trajectory between these sampled points is summarized by simple branchwise average substitution rates. A more accurate Monte Carlo approach is introduced, explicitly sampling a fine-grained discretization of the trajectory of the (potentially multivariate) Brownian process along the phylogeny. Generic Monte Carlo resampling algorithms are proposed for updating the Brownian paths along and across branches. Specific computational strategies are developed for efficient integration of the finite-time substitution probabilities across branches induced by the Brownian trajectory. The mixing properties and the computational complexity of the resulting Markov chain Monte Carlo sampler scale reasonably with the discretization level, allowing practical applications with up to a few hundred discretization points along the entire depth of the tree. The method can be generalized to other Markovian stochastic processes, making it possible to implement a wide range of time-dependent substitution models with well-controlled computational precision. The program is freely available at www.phylobayes.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Real-time topic-aware influence maximization using preprocessing.

PubMed

Chen, Wei; Lin, Tian; Yang, Cheng

2016-01-01

Influence maximization is the task of finding a set of seed nodes in a social network such that the influence spread of these seed nodes based on certain influence diffusion model is maximized. Topic-aware influence diffusion models have been recently proposed to address the issue that influence between a pair of users are often topic-dependent and information, ideas, innovations etc. being propagated in networks are typically mixtures of topics. In this paper, we focus on the topic-aware influence maximization task. In particular, we study preprocessing methods to avoid redoing influence maximization for each mixture from scratch. We explore two preprocessing algorithms with theoretical justifications. Our empirical results on data obtained in a couple of existing studies demonstrate that one of our algorithms stands out as a strong candidate providing microsecond online response time and competitive influence spread, with reasonable preprocessing effort.

Self-attracting walk on heterogeneous networks

NASA Astrophysics Data System (ADS)

Kim, Kanghun; Kyoung, Jaegu; Lee, D.-S.

2016-05-01

Understanding human mobility in cyberspace becomes increasingly important in this information era. While human mobility, memory-dependent and subdiffusive, is well understood in Euclidean space, it remains elusive in random heterogeneous networks like the World Wide Web. Here we study the diffusion characteristics of self-attracting walks, in which a walker is more likely to move to the locations visited previously than to unvisited ones, on scale-free networks. Under strong attraction, the number of distinct visited nodes grows linearly in time with larger coefficients in more heterogeneous networks. More interestingly, crossovers to sublinear growths occur in strongly heterogeneous networks. To understand these phenomena, we investigate the characteristic volumes and topology of the cluster of visited nodes and find that the reinforced attraction to hubs results in expediting exploration first but delaying later, as characterized by the scaling exponents that we derive. Our findings and analysis method can be useful for understanding various diffusion processes mediated by human.

White matter structure in loneliness: preliminary findings from diffusion tensor imaging.

PubMed

Tian, Yin; Liang, Shanshan; Yuan, Zhen; Chen, Sifan; Xu, Peng; Yao, Dezhong

2014-08-06

A pilot study was carried out to determine individual differences in perceived loneliness using diffusion tensor imaging. To the best of our knowledge, this is the first preliminary diffusion tensor imaging evidence that the ventral attention network, generally activated by attentional reorienting, was also related to loneliness. Image reconstruction results indicated significantly decreased fractional anisotropy of white matter fibers and that associated nodes of the ventral attention network are highly correlated with increased loneliness ratings. By providing evidence on the structural level, our findings suggested that attention-reorienting capabilities play an important role in shaping an individual's loneliness.

Conformal Dimensions via Large Charge Expansion

NASA Astrophysics Data System (ADS)

Banerjee, Debasish; Chandrasekharan, Shailesh; Orlando, Domenico

2018-02-01

We construct an efficient Monte Carlo algorithm that overcomes the severe signal-to-noise ratio problems and helps us to accurately compute the conformal dimensions of large-Q fields at the Wilson-Fisher fixed point in the O (2 ) universality class. Using it, we verify a recent proposal that conformal dimensions of strongly coupled conformal field theories with a global U (1 ) charge can be obtained via a series expansion in the inverse charge 1 /Q . We find that the conformal dimensions of the lowest operator with a fixed charge Q are almost entirely determined by the first few terms in the series.

Conformal Dimensions via Large Charge Expansion.

PubMed

Banerjee, Debasish; Chandrasekharan, Shailesh; Orlando, Domenico

2018-02-09

We construct an efficient Monte Carlo algorithm that overcomes the severe signal-to-noise ratio problems and helps us to accurately compute the conformal dimensions of large-Q fields at the Wilson-Fisher fixed point in the O(2) universality class. Using it, we verify a recent proposal that conformal dimensions of strongly coupled conformal field theories with a global U(1) charge can be obtained via a series expansion in the inverse charge 1/Q. We find that the conformal dimensions of the lowest operator with a fixed charge Q are almost entirely determined by the first few terms in the series.

Cs diffusion in SiC high-energy grain boundaries

NASA Astrophysics Data System (ADS)

Ko, Hyunseok; Szlufarska, Izabela; Morgan, Dane

2017-09-01

Cesium (Cs) is a radioactive fission product whose release is of concern for Tristructural-Isotropic fuel particles. In this work, Cs diffusion through high energy grain boundaries (HEGBs) of cubic-SiC is studied using an ab-initio based kinetic Monte Carlo (kMC) model. The HEGB environment was modeled as an amorphous SiC, and Cs defect energies were calculated using the density functional theory (DFT). From defect energies, it was suggested that the fastest diffusion mechanism is the diffusion of Cs interstitial in an amorphous SiC. The diffusion of Cs interstitial was simulated using a kMC model, based on the site and transition state energies sampled from the DFT. The Cs HEGB diffusion exhibited an Arrhenius type diffusion in the range of 1200-1600 °C. The comparison between HEGB results and the other studies suggests not only that the GB diffusion dominates the bulk diffusion but also that the HEGB is one of the fastest grain boundary paths for the Cs diffusion. The diffusion coefficients in HEGB are clearly a few orders of magnitude lower than the reported diffusion coefficients from in- and out-of-pile samples, suggesting that other contributions are responsible, such as radiation enhanced diffusion.